WorldWideScience

Sample records for addressing cancer clusters

  1. School‐based brief psycho‐educational intervention to raise adolescent cancer awareness and address barriers to medical help‐seeking about cancer: a cluster randomised controlled trial

    Science.gov (United States)

    Stoddart, Iona; Forbat, Liz; Neal, Richard D.; O'Carroll, Ronan E.; Haw, Sally; Rauchhaus, Petra; Kyle, Richard G.

    2015-01-01

    Abstract Objectives Raising cancer awareness and addressing barriers to help‐seeking may improve early diagnosis. The aim was to assess whether a psycho‐educational intervention increased adolescents' cancer awareness and addressed help‐seeking barriers. Methods This was a cluster randomised controlled trial involving 2173 adolescents in 20 schools. The intervention was a 50‐min presentation delivered by a member of Teenage Cancer Trust's (UK charity) education team. Schools were stratified by deprivation and roll size and randomly allocated to intervention/control conditions within these strata. Outcome measures were the number of cancer warning signs and cancer risk factors recognised, help‐seeking barriers endorsed and cancer communication. Communication self‐efficacy and intervention fidelity were also assessed. Results Regression models showed significant differences in the number of cancer warning signs and risk factors recognised between intervention and control groups. In intervention schools, the greatest increases in recognition of cancer warning signs at 6‐month follow‐up were for unexplained weight loss (from 44.2% to 62.0%) and change in the appearance of a mole (from 46.3% to 70.7%), up by 17.8% and 24.4%, respectively. Greatest increases in recognition of cancer risk factors were for getting sunburnt more than once as a child (from 41.0% to 57.6%) and being overweight (from 42.7% to 55.5%), up by 16.6% and 12.8%, respectively. Regression models showed that adolescents in intervention schools were 2.7 times more likely to discuss cancer at 2‐week follow‐up compared with the control group. No differences in endorsement of barriers to help‐seeking were observed. Conclusions School‐based brief psycho‐educational interventions are easy to deliver, require little resource and improve cancer awareness. © 2015 The Authors. Psycho‐Oncology published by John Wiley & Sons Ltd. PMID:26502987

  2. School-based brief psycho-educational intervention to raise adolescent cancer awareness and address barriers to medical help-seeking about cancer: a cluster randomised controlled trial.

    Science.gov (United States)

    Hubbard, Gill; Stoddart, Iona; Forbat, Liz; Neal, Richard D; O'Carroll, Ronan E; Haw, Sally; Rauchhaus, Petra; Kyle, Richard G

    2016-07-01

    Raising cancer awareness and addressing barriers to help-seeking may improve early diagnosis. The aim was to assess whether a psycho-educational intervention increased adolescents' cancer awareness and addressed help-seeking barriers. This was a cluster randomised controlled trial involving 2173 adolescents in 20 schools. The intervention was a 50-min presentation delivered by a member of Teenage Cancer Trust's (UK charity) education team. Schools were stratified by deprivation and roll size and randomly allocated to intervention/control conditions within these strata. Outcome measures were the number of cancer warning signs and cancer risk factors recognised, help-seeking barriers endorsed and cancer communication. Communication self-efficacy and intervention fidelity were also assessed. Regression models showed significant differences in the number of cancer warning signs and risk factors recognised between intervention and control groups. In intervention schools, the greatest increases in recognition of cancer warning signs at 6-month follow-up were for unexplained weight loss (from 44.2% to 62.0%) and change in the appearance of a mole (from 46.3% to 70.7%), up by 17.8% and 24.4%, respectively. Greatest increases in recognition of cancer risk factors were for getting sunburnt more than once as a child (from 41.0% to 57.6%) and being overweight (from 42.7% to 55.5%), up by 16.6% and 12.8%, respectively. Regression models showed that adolescents in intervention schools were 2.7 times more likely to discuss cancer at 2-week follow-up compared with the control group. No differences in endorsement of barriers to help-seeking were observed. School-based brief psycho-educational interventions are easy to deliver, require little resource and improve cancer awareness. © 2015 The Authors. Psycho-Oncology published by John Wiley & Sons Ltd. © 2015 The Authors. Psycho-Oncology published by John Wiley & Sons Ltd.

  3. Detecting space-time cancer clusters using residential histories

    Science.gov (United States)

    Jacquez, Geoffrey M.; Meliker, Jaymie R.

    2007-04-01

    Methods for analyzing geographic clusters of disease typically ignore the space-time variability inherent in epidemiologic datasets, do not adequately account for known risk factors (e.g., smoking and education) or covariates (e.g., age, gender, and race), and do not permit investigation of the latency window between exposure and disease. Our research group recently developed Q-statistics for evaluating space-time clustering in cancer case-control studies with residential histories. This technique relies on time-dependent nearest neighbor relationships to examine clustering at any moment in the life-course of the residential histories of cases relative to that of controls. In addition, in place of the widely used null hypothesis of spatial randomness, each individual's probability of being a case is instead based on his/her risk factors and covariates. Case-control clusters will be presented using residential histories of 220 bladder cancer cases and 440 controls in Michigan. In preliminary analyses of this dataset, smoking, age, gender, race and education were sufficient to explain the majority of the clustering of residential histories of the cases. Clusters of unexplained risk, however, were identified surrounding the business address histories of 10 industries that emit known or suspected bladder cancer carcinogens. The clustering of 5 of these industries began in the 1970's and persisted through the 1990's. This systematic approach for evaluating space-time clustering has the potential to generate novel hypotheses about environmental risk factors. These methods may be extended to detect differences in space-time patterns of any two groups of people, making them valuable for security intelligence and surveillance operations.

  4. Adaptation of a Counseling Intervention to Address Multiple Cancer Risk Factors among Overweight/Obese Latino Smokers

    Science.gov (United States)

    Castro, Yessenia; Fernández, Maria E.; Strong, Larkin L.; Stewart, Diana W.; Krasny, Sarah; Hernandez Robles, Eden; Heredia, Natalia; Spears, Claire A.; Correa-Fernández, Virmarie; Eakin, Elizabeth; Resnicow, Ken; Basen-Engquist, Karen; Wetter, David W.

    2015-01-01

    More than 60% of cancer-related deaths in the United States are attributable to tobacco use, poor nutrition, and physical inactivity, and these risk factors tend to cluster together. Thus, strategies for cancer risk reduction would benefit from addressing multiple health risk behaviors. We adapted an evidence-based intervention grounded in social…

  5. Breast Cancer Symptom Clusters Derived from Social Media and Research Study Data Using Improved K-Medoid Clustering

    Science.gov (United States)

    Ping, Qing; Yang, Christopher C.; Marshall, Sarah A.; Avis, Nancy E.; Ip, Edward H.

    2017-01-01

    Most cancer patients, including patients with breast cancer, experience multiple symptoms simultaneously while receiving active treatment. Some symptoms tend to occur together and may be related, such as hot flashes and night sweats. Co-occurring symptoms may have a multiplicative effect on patients’ functioning, mental health, and quality of life. Symptom clusters in the context of oncology were originally described as groups of three or more related symptoms. Some authors have suggested symptom clusters may have practical applications, such as the formulation of more effective therapeutic interventions that address the combined effects of symptoms rather than treating each symptom separately. Most studies that have sought to identify clusters in breast cancer survivors have relied on traditional research studies. Social media, such as online health-related forums, contain a bevy of user-generated content in the form of threads and posts, and could be used as a data source to identify and characterize symptom clusters among cancer patients. The present study seeks to determine patterns of symptom clusters in breast cancer survivors derived from both social media and research study data using improved K-Medoid clustering. A total of 50,426 publicly available messages were collected from Medhelp.com and 653 questionnaires were collected as part of a research study. The network of symptoms built from social media was sparse compared to that of the research study data, making the social media data easier to partition. The proposed revised K-Medoid clustering helps to improve the clustering performance by re-assigning some of the negative-ASW (average silhouette width) symptoms to other clusters after initial K-Medoid clustering. This retains an overall non-decreasing ASW and avoids the problem of trapping in local optima. The overall ASW, individual ASW, and improved interpretation of the final clustering solution suggest improvement. The clustering results suggest

  6. Breast Cancer Symptom Clusters Derived from Social Media and Research Study Data Using Improved K-Medoid Clustering.

    Science.gov (United States)

    Ping, Qing; Yang, Christopher C; Marshall, Sarah A; Avis, Nancy E; Ip, Edward H

    2016-06-01

    Most cancer patients, including patients with breast cancer, experience multiple symptoms simultaneously while receiving active treatment. Some symptoms tend to occur together and may be related, such as hot flashes and night sweats. Co-occurring symptoms may have a multiplicative effect on patients' functioning, mental health, and quality of life. Symptom clusters in the context of oncology were originally described as groups of three or more related symptoms. Some authors have suggested symptom clusters may have practical applications, such as the formulation of more effective therapeutic interventions that address the combined effects of symptoms rather than treating each symptom separately. Most studies that have sought to identify clusters in breast cancer survivors have relied on traditional research studies. Social media, such as online health-related forums, contain a bevy of user-generated content in the form of threads and posts, and could be used as a data source to identify and characterize symptom clusters among cancer patients. The present study seeks to determine patterns of symptom clusters in breast cancer survivors derived from both social media and research study data using improved K-Medoid clustering. A total of 50,426 publicly available messages were collected from Medhelp.com and 653 questionnaires were collected as part of a research study. The network of symptoms built from social media was sparse compared to that of the research study data, making the social media data easier to partition. The proposed revised K-Medoid clustering helps to improve the clustering performance by re-assigning some of the negative-ASW (average silhouette width) symptoms to other clusters after initial K-Medoid clustering. This retains an overall non-decreasing ASW and avoids the problem of trapping in local optima. The overall ASW, individual ASW, and improved interpretation of the final clustering solution suggest improvement. The clustering results suggest

  7. *K-means and cluster models for cancer signatures.

    Science.gov (United States)

    Kakushadze, Zura; Yu, Willie

    2017-09-01

    We present *K-means clustering algorithm and source code by expanding statistical clustering methods applied in https://ssrn.com/abstract=2802753 to quantitative finance. *K-means is statistically deterministic without specifying initial centers, etc. We apply *K-means to extracting cancer signatures from genome data without using nonnegative matrix factorization (NMF). *K-means' computational cost is a fraction of NMF's. Using 1389 published samples for 14 cancer types, we find that 3 cancers (liver cancer, lung cancer and renal cell carcinoma) stand out and do not have cluster-like structures. Two clusters have especially high within-cluster correlations with 11 other cancers indicating common underlying structures. Our approach opens a novel avenue for studying such structures. *K-means is universal and can be applied in other fields. We discuss some potential applications in quantitative finance.

  8. Mutation Clusters from Cancer Exome.

    Science.gov (United States)

    Kakushadze, Zura; Yu, Willie

    2017-08-15

    We apply our statistically deterministic machine learning/clustering algorithm *K-means (recently developed in https://ssrn.com/abstract=2908286) to 10,656 published exome samples for 32 cancer types. A majority of cancer types exhibit a mutation clustering structure. Our results are in-sample stable. They are also out-of-sample stable when applied to 1389 published genome samples across 14 cancer types. In contrast, we find in- and out-of-sample instabilities in cancer signatures extracted from exome samples via nonnegative matrix factorization (NMF), a computationally-costly and non-deterministic method. Extracting stable mutation structures from exome data could have important implications for speed and cost, which are critical for early-stage cancer diagnostics, such as novel blood-test methods currently in development.

  9. Tumor-derived circulating endothelial cell clusters in colorectal cancer.

    KAUST Repository

    Cima, Igor; Kong, Say Li; Sengupta, Debarka; Tan, Iain B; Phyo, Wai Min; Lee, Daniel; Hu, Min; Iliescu, Ciprian; Alexander, Irina; Goh, Wei Lin; Rahmani, Mehran; Suhaimi, Nur-Afidah Mohamed; Vo, Jess H; Tai, Joyce A; Tan, Joanna H; Chua, Clarinda; Ten, Rachel; Lim, Wan Jun; Chew, Min Hoe; Hauser, Charlotte; van Dam, Rob M; Lim, Wei-Yen; Prabhakar, Shyam; Lim, Bing; Koh, Poh Koon; Robson, Paul; Ying, Jackie Y; Hillmer, Axel M; Tan, Min-Han

    2016-01-01

    Clusters of tumor cells are often observed in the blood of cancer patients. These structures have been described as malignant entities for more than 50 years, although their comprehensive characterization is lacking. Contrary to current consensus, we demonstrate that a discrete population of circulating cell clusters isolated from the blood of colorectal cancer patients are not cancerous but consist of tumor-derived endothelial cells. These clusters express both epithelial and mesenchymal markers, consistent with previous reports on circulating tumor cell (CTC) phenotyping. However, unlike CTCs, they do not mirror the genetic variations of matched tumors. Transcriptomic analysis of single clusters revealed that these structures exhibit an endothelial phenotype and can be traced back to the tumor endothelium. Further results show that tumor-derived endothelial clusters do not form by coagulation or by outgrowth of single circulating endothelial cells, supporting a direct release of clusters from the tumor vasculature. The isolation and enumeration of these benign clusters distinguished healthy volunteers from treatment-naïve as well as pathological early-stage (≤IIA) colorectal cancer patients with high accuracy, suggesting that tumor-derived circulating endothelial cell clusters could be used as a means of noninvasive screening for colorectal cancer. In contrast to CTCs, tumor-derived endothelial cell clusters may also provide important information about the underlying tumor vasculature at the time of diagnosis, during treatment, and throughout the course of the disease.

  10. Tumor-derived circulating endothelial cell clusters in colorectal cancer.

    KAUST Repository

    Cima, Igor

    2016-06-29

    Clusters of tumor cells are often observed in the blood of cancer patients. These structures have been described as malignant entities for more than 50 years, although their comprehensive characterization is lacking. Contrary to current consensus, we demonstrate that a discrete population of circulating cell clusters isolated from the blood of colorectal cancer patients are not cancerous but consist of tumor-derived endothelial cells. These clusters express both epithelial and mesenchymal markers, consistent with previous reports on circulating tumor cell (CTC) phenotyping. However, unlike CTCs, they do not mirror the genetic variations of matched tumors. Transcriptomic analysis of single clusters revealed that these structures exhibit an endothelial phenotype and can be traced back to the tumor endothelium. Further results show that tumor-derived endothelial clusters do not form by coagulation or by outgrowth of single circulating endothelial cells, supporting a direct release of clusters from the tumor vasculature. The isolation and enumeration of these benign clusters distinguished healthy volunteers from treatment-naïve as well as pathological early-stage (≤IIA) colorectal cancer patients with high accuracy, suggesting that tumor-derived circulating endothelial cell clusters could be used as a means of noninvasive screening for colorectal cancer. In contrast to CTCs, tumor-derived endothelial cell clusters may also provide important information about the underlying tumor vasculature at the time of diagnosis, during treatment, and throughout the course of the disease.

  11. Clusters of Adolescent and Young Adult Thyroid Cancer in Florida Counties

    Directory of Open Access Journals (Sweden)

    Raid Amin

    2014-01-01

    Full Text Available Background. Thyroid cancer is a common cancer in adolescents and young adults ranking 4th in frequency. Thyroid cancer has captured the interest of epidemiologists because of its strong association to environmental factors. The goal of this study is to identify thyroid cancer clusters in Florida for the period 2000–2008. This will guide further discovery of potential risk factors within areas of the cluster compared to areas not in cluster. Methods. Thyroid cancer cases for ages 15–39 were obtained from the Florida Cancer Data System. Next, using the purely spatial Poisson analysis function in SaTScan, the geographic distribution of thyroid cancer cases by county was assessed for clusters. The reference population was obtained from the Census Bureau 2010, which enabled controlling for population age, sex, and race. Results. Two statistically significant clusters of thyroid cancer clusters were found in Florida: one in southern Florida (SF (relative risk of 1.26; P value of <0.001 and the other in northwestern Florida (NWF (relative risk of 1.71; P value of 0.012. These clusters persisted after controlling for demographics including sex, age, race. Conclusion. In summary, we found evidence of thyroid cancer clustering in South Florida and North West Florida for adolescents and young adult.

  12. Symptom Cluster Trajectories During Chemotherapy in Breast Cancer Outpatients.

    Science.gov (United States)

    Hsu, Hsin-Tien; Lin, Kuan-Chia; Wu, Li-Min; Juan, Chiung-Hui; Hou, Ming-Feng; Hwang, Shiow-Li; Liu, Yi; Dodd, Marylin J

    2017-06-01

    Breast cancer patients often experience multiple symptoms and substantial discomfort. Some symptoms may occur simultaneously and throughout the duration of chemotherapy treatment. The aim of this study was to investigate symptom severity and symptom cluster trajectories during chemotherapy in outpatients with breast cancer in Taiwan. This prospective, longitudinal, repeated measures study administered a standardized questionnaire (M. D. Anderson Symptom Inventory Taiwan version) to 103 breast cancer patients during each day of the third 21-day cycle of chemotherapy. Latent class growth analysis was performed to examine symptom cluster trajectories. Three symptom clusters were identified within the first 14 days of the 21-day chemotherapy cycle: the neurocognition cluster (pain, shortness of breath, vomiting, memory problems, and numbness/tingling) with a trajectory of Y = 2.09 - 0.11 (days), the emotion-nausea cluster (nausea, disturbed sleep, distress/upset, drowsiness, and sadness) with a trajectory ofY = 3.57 - 0.20 (days), and the fatigue-anorexia cluster (fatigue, lack of appetite, and dry mouth) with a trajectory of Y = 4.22 - 0.21 (days). The "fatigue-anorexia cluster" and "emotion-nausea cluster" peaked at moderate levels on chemotherapy days 3-5, and then gradually decreased to mild levels within the first 14 days of the 21-day chemotherapy cycle. Distinct symptom clusters were observed during the third cycle of chemotherapy. Systematic and ongoing evaluation of symptom cluster trajectories during cancer treatment is essential. Healthcare providers can use these findings to enhance communication with their breast cancer patients and to prioritize symptoms that require attention and intervention. Copyright © 2017 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

  13. *K-means and Cluster Models for Cancer Signatures

    OpenAIRE

    Kakushadze, Zura; Yu, Willie

    2017-01-01

    We present *K-means clustering algorithm and source code by expanding statistical clustering methods applied in https://ssrn.com/abstract=2802753 to quantitative finance. *K-means is statistically deterministic without specifying initial centers, etc. We apply *K-means to extracting cancer signatures from genome data without using nonnegative matrix factorization (NMF). *K-means’ computational cost is a fraction of NMF’s. Using 1389 published samples for 14 cancer types, we find that 3 cancer...

  14. Addressing the Global Burden of Breast Cancer

    Science.gov (United States)

    The US National Cancer Institute’s Center for Global Health (CGH) has been a key partner in a multi-institutional expert team that has developed a set of publications to address foundational concerns in breast cancer care across the cancer care continuum and within limited resource settings.

  15. Clustering of health behaviours in adult survivors of childhood cancer and the general population.

    Science.gov (United States)

    Rebholz, C E; Rueegg, C S; Michel, G; Ammann, R A; von der Weid, N X; Kuehni, C E; Spycher, B D

    2012-07-10

    Little is known about engagement in multiple health behaviours in childhood cancer survivors. Using latent class analysis, we identified health behaviour patterns in 835 adult survivors of childhood cancer (age 20-35 years) and 1670 age- and sex-matched controls from the general population. Behaviour groups were determined from replies to questions on smoking, drinking, cannabis use, sporting activities, diet, sun protection and skin examination. The model identified four health behaviour patterns: 'risk-avoidance', with a generally healthy behaviour; 'moderate drinking', with higher levels of sporting activities, but moderate alcohol-consumption; 'risk-taking', engaging in several risk behaviours; and 'smoking', smoking but not drinking. Similar proportions of survivors and controls fell into the 'risk-avoiding' (42% vs 44%) and the 'risk-taking' cluster (14% vs 12%), but more survivors were in the 'moderate drinking' (39% vs 28%) and fewer in the 'smoking' cluster (5% vs 16%). Determinants of health behaviour clusters were gender, migration background, income and therapy. A comparable proportion of childhood cancer survivors as in the general population engage in multiple health-compromising behaviours. Because of increased vulnerability of survivors, multiple risk behaviours should be addressed in targeted health interventions.

  16. Symptom clustering and quality of life in patients with ovarian cancer undergoing chemotherapy.

    Science.gov (United States)

    Nho, Ju-Hee; Reul Kim, Sung; Nam, Joo-Hyun

    2017-10-01

    The symptom clusters in patients with ovarian cancer undergoing chemotherapy have not been well evaluated. We investigated the symptom clusters and effects of symptom clusters on the quality of life of patients with ovarian cancer. We recruited 210 ovarian cancer patients being treated with chemotherapy and used a descriptive cross-sectional study design to collect information on their symptoms. To determine inter-relationships among symptoms, a principal component analysis with varimax rotation was performed based on the patient's symptoms (fatigue, pain, sleep disturbance, chemotherapy-induced peripheral neuropathy, anxiety, depression, and sexual dysfunction). All patients had experienced at least two domains of concurrent symptoms, and there were two types of symptom clusters. The first symptom cluster consisted of anxiety, depression, fatigue, and sleep disturbance symptoms, while the second symptom cluster consisted of pain and chemotherapy-induced peripheral neuropathy symptoms. Our subgroup cluster analysis showed that ovarian cancer patients with higher-scoring symptoms had significantly poorer quality of life in both symptom cluster 1 and 2 subgroups, with subgroup-specific patterns. The symptom clusters were different depending on age, age at disease onset, disease duration, recurrence, and performance status of patients with ovarian cancer. In addition, ovarian cancer patients experienced different symptom clusters according to cancer stage. The current study demonstrated that there is a specific pattern of symptom clusters, and symptom clusters negatively influence the quality of life in patients with ovarian cancer. Identifying symptom clusters of ovarian cancer patients may have clinical implications in improving symptom management. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Clinicians' Perspectives on Managing Symptom Clusters in Advanced Cancer: A Semistructured Interview Study.

    Science.gov (United States)

    Dong, Skye T; Butow, Phyllis N; Agar, Meera; Lovell, Melanie R; Boyle, Frances; Stockler, Martin; Forster, Benjamin C; Tong, Allison

    2016-04-01

    Managing symptom clusters or multiple concurrent symptoms in patients with advanced cancer remains a clinical challenge. The optimal processes constituting effective management of symptom clusters remain uncertain. To describe the attitudes and strategies of clinicians in managing multiple co-occurring symptoms in patients with advanced cancer. Semistructured interviews were conducted with 48 clinicians (palliative care physicians [n = 10], oncologists [n = 6], general practitioners [n = 6], nurses [n = 12], and allied health providers [n = 14]), purposively recruited from two acute hospitals, two palliative care centers, and four community general practices in Sydney, Australia. Transcripts were analyzed using thematic analysis and adapted grounded theory. Six themes were identified: uncertainty in decision making (inadequacy of scientific evidence, relying on experiential knowledge, and pressure to optimize care); attunement to patient and family (sensitivity to multiple cues, prioritizing individual preferences, addressing psychosocial and physical interactions, and opening Pandora's box); deciphering cause to guide intervention (disaggregating symptoms and interactions, flexibility in assessment, and curtailing investigative intrusiveness); balancing complexities in medical management (trading off side effects, minimizing mismatched goals, and urgency in resolving severe symptoms); fostering hope and empowerment (allaying fear of the unknown, encouraging meaning making, championing patient empowerment, and truth telling); and depending on multidisciplinary expertise (maximizing knowledge exchange, sharing management responsibility, contending with hierarchical tensions, and isolation and discontinuity of care). Management of symptom clusters, as both an art and a science, is currently fraught with uncertainty in decision making. Strengthening multidisciplinary collaboration, continuity of care, more pragmatic planning of clinical trials to address more than one

  18. Spatial clustering of childhood cancer in Great Britain during the period 1969-1993.

    Science.gov (United States)

    McNally, Richard J Q; Alexander, Freda E; Vincent, Tim J; Murphy, Michael F G

    2009-02-15

    The aetiology of childhood cancer is poorly understood. Both genetic and environmental factors are likely to be involved. The presence of spatial clustering is indicative of a very localized environmental component to aetiology. Spatial clustering is present when there are a small number of areas with greatly increased incidence or a large number of areas with moderately increased incidence. To determine whether localized environmental factors may play a part in childhood cancer aetiology, we analyzed for spatial clustering using a large set of national population-based data from Great Britain diagnosed 1969-1993. The Potthoff-Whittinghill method was used to test for extra-Poisson variation (EPV). Thirty-two thousand three hundred and twenty-three cases were allocated to 10,444 wards using diagnosis addresses. Analyses showed statistically significant evidence of clustering for acute lymphoblastic leukaemia (ALL) over the whole age range (estimate of EPV = 0.05, p = 0.002) and for ages 1-4 years (estimate of EPV = 0.03, p = 0.015). Soft-tissue sarcoma (estimate of EPV = 0.03, p = 0.04) and Wilms tumours (estimate of EPV = 0.04, p = 0.007) also showed significant clustering. Clustering tended to persist across different time periods for cases of ALL (estimate of between-time period EPV = 0.04, p =0.003). In conclusion, we observed low level spatial clustering that is attributable to a limited number of cases. This suggests that environmental factors, which in some locations display localized clustering, may be important aetiological agents in these diseases. For ALL and soft tissue sarcoma, but not Wilms tumour, common infectious agents may be likely candidates.

  19. Space-time clusters of breast cancer using residential histories

    DEFF Research Database (Denmark)

    Nordsborg, Rikke Baastrup; Meliker, Jaymie R; Ersbøll, Annette Kjær

    2014-01-01

    BACKGROUND: A large proportion of breast cancer cases are thought related to environmental factors. Identification of specific geographical areas with high risk (clusters) may give clues to potential environmental risk factors. The aim of this study was to investigate whether clusters of breast...... cancer existed in space and time in Denmark, using 33 years of residential histories. METHODS: We conducted a population-based case-control study of 3138 female cases from the Danish Cancer Registry, diagnosed with breast cancer in 2003 and two independent control groups of 3138 women each, randomly...

  20. Symptom Clusters and Work Limitations in Employed Breast Cancer Survivors

    Science.gov (United States)

    2011-11-16

    gliomas (Fox, Lyon, & Farace , 2007). Across studies of breast cancer patients, similar symptom clusters have emerged: researchers have identified...Symptom clusters and quality of life in survivors of lung cancer. Oncology Nursing Forum, 33(5), 931-936. Fox, S., Lyon, D., & Farace , E. (2007

  1. Dynamic Change in p63 Protein Expression during Implantation of Urothelial Cancer Clusters

    Directory of Open Access Journals (Sweden)

    Takahiro Yoshida

    2015-07-01

    Full Text Available Although the dissemination of urothelial cancer cells is supposed to be a major cause of the multicentricity of urothelial tumors, the mechanism of implantation has not been well investigated. Here, we found that cancer cell clusters from the urine of patients with urothelial cancer retain the ability to survive, grow, and adhere. By using cell lines and primary cells collected from multiple patients, we demonstrate that △Np63α protein in cancer cell clusters was rapidly decreased through proteasomal degradation when clusters were attached to the matrix, leading to downregulation of E-cadherin and upregulation of N-cadherin. Decreased △Np63α protein level in urothelial cancer cell clusters was involved in the clearance of the urothelium. Our data provide the first evidence that clusters of urothelial cancer cells exhibit dynamic changes in △Np63α expression during attachment to the matrix, and decreased △Np63α protein plays a critical role in the interaction between cancer cell clusters and the urothelium. Thus, because △Np63α might be involved in the process of intraluminal dissemination of urothelial cancer cells, blocking the degradation of △Np63α could be a target of therapy to prevent the dissemination of urothelial cancer.

  2. A Multidisciplinary Investigation of a Polycythemia Vera Cancer Cluster of Unknown Origin

    Science.gov (United States)

    Seaman, Vincent; Dearwent, Steve M; Gable, Debra; Lewis, Brian; Metcalf, Susan; Orloff, Ken; Tierney, Bruce; Zhu, Jane; Logue, James; Marchetto, David; Ostroff, Stephen; Hoffman, Ronald; Xu, Mingjiang; Carey, David; Erlich, Porat; Gerhard, Glenn; Roda, Paul; Iannuzzo, Joseph; Lewis, Robert; Mellow, John; Mulvihill, Linda; Myles, Zachary; Wu, Manxia; Frank, Arthur; Gross-Davis, Carol Ann; Klotz, Judith; Lynch, Adam; Weissfeld, Joel; Weinberg, Rona; Cole, Henry

    2010-01-01

    Cancer cluster investigations rarely receive significant public health resource allocations due to numerous inherent challenges and the limited success of past efforts. In 2008, a cluster of polycythemia vera, a rare blood cancer with unknown etiology, was identified in northeast Pennsylvania. A multidisciplinary group of federal and state agencies, academic institutions, and local healthcare providers subsequently developed a multifaceted research portfolio designed to better understand the cause of the cluster. This research agenda represents a unique and important opportunity to demonstrate that cancer cluster investigations can produce desirable public health and scientific outcomes when necessary resources are available. PMID:20617023

  3. miR-206/133b Cluster: A Weapon against Lung Cancer?

    Directory of Open Access Journals (Sweden)

    Jing-Yu Pan

    2017-09-01

    Full Text Available Lung cancer is a deadly disease that ends numerous lives around the world. MicroRNAs (miRNAs are a group of non-coding RNAs involved in a variety of biological processes, such as cell growth, organ development, and tumorigenesis. The miR-206/133b cluster is located on the human chromosome 6p12.2, which is essential for growth and rebuilding of skeletal muscle. The miR-206/133b cluster has been verified to be dysregulated and plays a crucial role in lung cancer. miR-206 and miR-133b participate in lung tumor cell apoptosis, proliferation, migration, invasion, angiogenesis, drug resistance, and cancer treatment. The mechanisms are sophisticated, involving various target genes and molecular pathways, such as MET, EGFR, and the STAT3/HIF-1α/VEGF signal pathway. Hence, in this review, we summarize the role and potential mechanisms of the miR-206/133b cluster in lung cancer. Keywords: lung cancer, miR-206/133b cluster, miR-206, miR-133b

  4. Symptom Clusters and Quality of Life in Hospice Patients with Cancer

    Science.gov (United States)

    Omran, Suha; Khader, Yousef; McMillan, Susan

    2017-09-27

    Background: Symptom control is an important part of palliative care and important to achieve optimal quality of life (QOL). Studies have shown that patients with advanced cancer suffer from diverse and often severe physical and psychological symptoms. The aim is to explore the influence of symptom clusters on QOL among patients with advanced cancer. Materials and Methods: 709 patients with advanced cancer were recruited to participate in a clinical trial focusing on symptom management and QOL. Patients were adults newly admitted to hospice home care in one of two hospices in southwest Florida, who could pass mental status screening. The instruments used for data collection were the Demographic Data Form, Memorial Symptom Assessment Scale (MSAS), and the Hospice Quality of Life Index-14. Results: Exploratory factor analysis and multiple regression were used to identify symptom clusters and their influence on QOL. The results revealed that the participants experienced multiple concurrent symptoms. There were four symptom clusters found among these cancer patients. Individual symptom distress scores that were the strongest predictors of QOL were: feeling pain; dry mouth; feeling drowsy; nausea; difficulty swallowing; worrying and feeling nervous. Conclusions: Patients with advanced cancer reported various concurrent symptoms, and these form symptom clusters of four main categories. The four symptoms clusters have a negative influence on patients’ QOL and required specific care from different members of the hospice healthcare team. The results of this study should be used to guide health care providers’ symptom management. Proper attention to symptom clusters should be the basis for accurate planning of effective interventions to manage the symptom clusters experienced by advanced cancer patients. The health care provider needs to plan ahead for these symptoms and manage any concurrent symptoms for successful promotion of their patient’s QOL. Creative Commons

  5. MO-FG-BRB-03: Addressing the Cancer Challenge: International Cancer Experts Corps

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    Coleman, N. [Center for Cancer Research, National Cancer Institute (United States)

    2015-06-15

    corresponding potential benefits of addressing this challenge. To describe what radiation therapy infrastructure, in terms of facilities, equipment and personnel, will be required to address this challenge. To describe models of addressing personnel and infrastructure mobilization and capacity building within regions where significant cancer treatment disparities exist.

  6. MO-FG-BRB-03: Addressing the Cancer Challenge: International Cancer Experts Corps

    International Nuclear Information System (INIS)

    Coleman, N.

    2015-01-01

    corresponding potential benefits of addressing this challenge. To describe what radiation therapy infrastructure, in terms of facilities, equipment and personnel, will be required to address this challenge. To describe models of addressing personnel and infrastructure mobilization and capacity building within regions where significant cancer treatment disparities exist

  7. Identification of symptom clusters in cancer patients at palliative care clinic

    Directory of Open Access Journals (Sweden)

    Gülçin Senel Özalp

    2017-01-01

    Full Text Available Objective: Cancer patients often experience a large number of symptoms together. The aim of this study is to determine the symptom clusters in cancer patients at palliative care clinic. Methods: Hundred and seventy consecutive patients were enrolled in the study. Memorial Symptom Assessment Scale was used for symptom assessment of the patients. Results: The most experienced symptoms by the patients during the past week before hospitalization in palliative care clinic were lack of energy (95.4%, weight loss (91.2%, lack of appetite (89.4%, pain (88.2%, dry mouth (87.6%, feeling sad (87.6%, feeling nervous (82.9%, worrying (81.2%, and feeling irritable (80.6%. Five symptom clusters were defined. First cluster: pain, feeling nervous, dry mouth, worrying, feeling irritable, weight loss; second cluster: feeling drowsy, numbness/tingling in hands/feet, difficulty in sleeping, dizziness, constipation, I do not look like myself; third cluster: nausea, vomiting; fourth cluster: shortness of breath, difficulty in swallowing, cough, change in the way food tastes; and fifth cluster: feeling bloated, problems with urination, diarrhea, itching, mouth sores, hair loss, swelling of arm or legs, change in the skin. Conclusions: We encountered various symptom clusters in advanced cancer patients. Identification of symptom clusters and knowledge of cluster composition in oncological population may particularly contribute individualization of the treatment.

  8. Determining the number of clusters for nuclei segmentation in breast cancer image

    Science.gov (United States)

    Fatichah, Chastine; Navastara, Dini Adni; Suciati, Nanik; Nuraini, Lubna

    2017-02-01

    Clustering is commonly technique for image segmentation, however determining an appropriate number of clusters is still challenging. Due to nuclei variation of size and shape in breast cancer image, an automatic determining number of clusters for segmenting the nuclei breast cancer is proposed. The phase of nuclei segmentation in breast cancer image are nuclei detection, touched nuclei detection, and touched nuclei separation. We use the Gram-Schmidt for nuclei cell detection, the geometry feature for touched nuclei detection, and combining of watershed and spatial k-Means clustering for separating the touched nuclei in breast cancer image. The spatial k-Means clustering is employed for separating the touched nuclei, however automatically determine the number of clusters is difficult due to the variation of size and shape of single cell breast cancer. To overcome this problem, first we apply watershed algorithm to separate the touched nuclei and then we calculate the distance among centroids in order to solve the over-segmentation. We merge two centroids that have the distance below threshold. And the new of number centroid as input to segment the nuclei cell using spatial k- Means algorithm. Experiment show that, the proposed scheme can improve the accuracy of nuclei cell counting.

  9. Statistical Significance for Hierarchical Clustering

    Science.gov (United States)

    Kimes, Patrick K.; Liu, Yufeng; Hayes, D. Neil; Marron, J. S.

    2017-01-01

    Summary Cluster analysis has proved to be an invaluable tool for the exploratory and unsupervised analysis of high dimensional datasets. Among methods for clustering, hierarchical approaches have enjoyed substantial popularity in genomics and other fields for their ability to simultaneously uncover multiple layers of clustering structure. A critical and challenging question in cluster analysis is whether the identified clusters represent important underlying structure or are artifacts of natural sampling variation. Few approaches have been proposed for addressing this problem in the context of hierarchical clustering, for which the problem is further complicated by the natural tree structure of the partition, and the multiplicity of tests required to parse the layers of nested clusters. In this paper, we propose a Monte Carlo based approach for testing statistical significance in hierarchical clustering which addresses these issues. The approach is implemented as a sequential testing procedure guaranteeing control of the family-wise error rate. Theoretical justification is provided for our approach, and its power to detect true clustering structure is illustrated through several simulation studies and applications to two cancer gene expression datasets. PMID:28099990

  10. Taxonomical analysis of the Cancer cluster of galaxies

    International Nuclear Information System (INIS)

    Perea, J.; Olmo, A. del; Moles, M.

    1986-01-01

    A description is presented of the Cancer cluster of galaxies, based on a taxonomical analysis in (α,delta, Vsub(r)) space. Earlier results by previous authors on the lack of dynamical entity of the cluster are confirmed. The present analysis points out the existence of a binary structure in the most populated region of the complex. (author)

  11. Time-dependent risks of cancer clustering among couples: a nationwide population-based cohort study in Taiwan.

    Science.gov (United States)

    Wang, Jong-Yi; Liang, Yia-Wen; Yeh, Chun-Chen; Liu, Chiu-Shong; Wang, Chen-Yu

    2018-02-21

    Spousal clustering of cancer warrants attention. Whether the common environment or high-age vulnerability determines cancer clustering is unclear. The risk of clustering in couples versus non-couples is undetermined. The time to cancer clustering after the first cancer diagnosis is yet to be reported. This study investigated cancer clustering over time among couples by using nationwide data. A cohort of 5643 married couples in the 2002-2013 Taiwan National Health Insurance Research Database was identified and randomly matched with 5643 non-couple pairs through dual propensity score matching. Factors associated with clustering (both spouses with tumours) were analysed by using the Cox proportional hazard model. Propensity-matched analysis revealed that the risk of clustering of all tumours among couples (13.70%) was significantly higher than that among non-couples (11.84%) (OR=1.182, 95% CI 1.058 to 1.321, P=0.0031). The median time to clustering of all tumours and of malignant tumours was 2.92 and 2.32 years, respectively. Risk characteristics associated with clustering included high age and comorbidity. Shared environmental factors among spouses might be linked to a high incidence of cancer clustering. Cancer incidence in one spouse may signal cancer vulnerability in the other spouse. Promoting family-oriented cancer care in vulnerable families and preventing shared lifestyle risk factors for cancer are suggested. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  12. Modeling familial clustered breast cancer using published data

    NARCIS (Netherlands)

    Jonker, MA; Jacobi, CE; Hoogendoorn, WE; Nagelkerke, NJD; de Bock, GH; van Houwelingen, JC

    2003-01-01

    The purpose of this research was to model the familial clustering of breast cancer and to provide an accurate risk estimate for individuals from the general population, based on their family history of breast and ovarian cancer. We constructed a genetic model as an extension of a model by Claus et

  13. Non-negative matrix factorization by maximizing correntropy for cancer clustering

    KAUST Repository

    Wang, Jim Jing-Yan; Wang, Xiaolei; Gao, Xin

    2013-01-01

    Background: Non-negative matrix factorization (NMF) has been shown to be a powerful tool for clustering gene expression data, which are widely used to classify cancers. NMF aims to find two non-negative matrices whose product closely approximates the original matrix. Traditional NMF methods minimize either the l2 norm or the Kullback-Leibler distance between the product of the two matrices and the original matrix. Correntropy was recently shown to be an effective similarity measurement due to its stability to outliers or noise.Results: We propose a maximum correntropy criterion (MCC)-based NMF method (NMF-MCC) for gene expression data-based cancer clustering. Instead of minimizing the l2 norm or the Kullback-Leibler distance, NMF-MCC maximizes the correntropy between the product of the two matrices and the original matrix. The optimization problem can be solved by an expectation conditional maximization algorithm.Conclusions: Extensive experiments on six cancer benchmark sets demonstrate that the proposed method is significantly more accurate than the state-of-the-art methods in cancer clustering. 2013 Wang et al.; licensee BioMed Central Ltd.

  14. Non-negative matrix factorization by maximizing correntropy for cancer clustering

    KAUST Repository

    Wang, Jim Jing-Yan

    2013-03-24

    Background: Non-negative matrix factorization (NMF) has been shown to be a powerful tool for clustering gene expression data, which are widely used to classify cancers. NMF aims to find two non-negative matrices whose product closely approximates the original matrix. Traditional NMF methods minimize either the l2 norm or the Kullback-Leibler distance between the product of the two matrices and the original matrix. Correntropy was recently shown to be an effective similarity measurement due to its stability to outliers or noise.Results: We propose a maximum correntropy criterion (MCC)-based NMF method (NMF-MCC) for gene expression data-based cancer clustering. Instead of minimizing the l2 norm or the Kullback-Leibler distance, NMF-MCC maximizes the correntropy between the product of the two matrices and the original matrix. The optimization problem can be solved by an expectation conditional maximization algorithm.Conclusions: Extensive experiments on six cancer benchmark sets demonstrate that the proposed method is significantly more accurate than the state-of-the-art methods in cancer clustering. 2013 Wang et al.; licensee BioMed Central Ltd.

  15. Hierarchical clustering of breast cancer methylomes revealed differentially methylated and expressed breast cancer genes.

    Directory of Open Access Journals (Sweden)

    I-Hsuan Lin

    Full Text Available Oncogenic transformation of normal cells often involves epigenetic alterations, including histone modification and DNA methylation. We conducted whole-genome bisulfite sequencing to determine the DNA methylomes of normal breast, fibroadenoma, invasive ductal carcinomas and MCF7. The emergence, disappearance, expansion and contraction of kilobase-sized hypomethylated regions (HMRs and the hypomethylation of the megabase-sized partially methylated domains (PMDs are the major forms of methylation changes observed in breast tumor samples. Hierarchical clustering of HMR revealed tumor-specific hypermethylated clusters and differential methylated enhancers specific to normal or breast cancer cell lines. Joint analysis of gene expression and DNA methylation data of normal breast and breast cancer cells identified differentially methylated and expressed genes associated with breast and/or ovarian cancers in cancer-specific HMR clusters. Furthermore, aberrant patterns of X-chromosome inactivation (XCI was found in breast cancer cell lines as well as breast tumor samples in the TCGA BRCA (breast invasive carcinoma dataset. They were characterized with differentially hypermethylated XIST promoter, reduced expression of XIST, and over-expression of hypomethylated X-linked genes. High expressions of these genes were significantly associated with lower survival rates in breast cancer patients. Comprehensive analysis of the normal and breast tumor methylomes suggests selective targeting of DNA methylation changes during breast cancer progression. The weak causal relationship between DNA methylation and gene expression observed in this study is evident of more complex role of DNA methylation in the regulation of gene expression in human epigenetics that deserves further investigation.

  16. Statistical method on nonrandom clustering with application to somatic mutations in cancer

    Directory of Open Access Journals (Sweden)

    Rejto Paul A

    2010-01-01

    Full Text Available Abstract Background Human cancer is caused by the accumulation of tumor-specific mutations in oncogenes and tumor suppressors that confer a selective growth advantage to cells. As a consequence of genomic instability and high levels of proliferation, many passenger mutations that do not contribute to the cancer phenotype arise alongside mutations that drive oncogenesis. While several approaches have been developed to separate driver mutations from passengers, few approaches can specifically identify activating driver mutations in oncogenes, which are more amenable for pharmacological intervention. Results We propose a new statistical method for detecting activating mutations in cancer by identifying nonrandom clusters of amino acid mutations in protein sequences. A probability model is derived using order statistics assuming that the location of amino acid mutations on a protein follows a uniform distribution. Our statistical measure is the differences between pair-wise order statistics, which is equivalent to the size of an amino acid mutation cluster, and the probabilities are derived from exact and approximate distributions of the statistical measure. Using data in the Catalog of Somatic Mutations in Cancer (COSMIC database, we have demonstrated that our method detects well-known clusters of activating mutations in KRAS, BRAF, PI3K, and β-catenin. The method can also identify new cancer targets as well as gain-of-function mutations in tumor suppressors. Conclusions Our proposed method is useful to discover activating driver mutations in cancer by identifying nonrandom clusters of somatic amino acid mutations in protein sequences.

  17. Interventions to address sexual problems in people with cancer.

    Science.gov (United States)

    Barbera, L; Zwaal, C; Elterman, D; McPherson, K; Wolfman, W; Katz, A; Matthew, A

    2017-06-01

    Sexual dysfunction in people with cancer is a significant problem. The present clinical practice guideline makes recommendations to improve sexual function in people with cancer. This guideline was undertaken by the Interventions to Address Sexual Problems in People with Cancer Expert Panel, a group organized by the Program in Evidence-Based Care (pebc). Consistent with the pebc standardized approach, a systematic search was conducted for existing guidelines, and the literature in medline and embase for the years 2003-2015 was systematically searched for both systematic reviews and primary literature. Evidence found for men and for women was evaluated separately, and no restrictions were placed on cancer type or study design. Content and methodology experts performed an internal review of the resulting draft recommendations, which was followed by an external review by targeted experts and intended users. The search identified 4 existing guidelines, 13 systematic reviews, and 103 studies with relevance to the topic. The present guideline provides one overarching recommendation concerning the discussion of sexual health and dysfunction, which is aimed at all people with cancer. Eleven additional recommendations made separately for men and women deal with issues such as sexual response, body image, intimacy and relationships, overall sexual functioning and satisfaction, and vasomotor and genital symptoms. To our knowledge this clinical practice guideline is the first to comprehensively evaluate interventions for the improvement of sexual problems in people with cancer. The guideline will be a valuable resource to support practitioners and clinics in addressing sexuality in cancer survivors.

  18. Symptom Clusters in Advanced Cancer Patients: An Empirical Comparison of Statistical Methods and the Impact on Quality of Life.

    Science.gov (United States)

    Dong, Skye T; Costa, Daniel S J; Butow, Phyllis N; Lovell, Melanie R; Agar, Meera; Velikova, Galina; Teckle, Paulos; Tong, Allison; Tebbutt, Niall C; Clarke, Stephen J; van der Hoek, Kim; King, Madeleine T; Fayers, Peter M

    2016-01-01

    Symptom clusters in advanced cancer can influence patient outcomes. There is large heterogeneity in the methods used to identify symptom clusters. To investigate the consistency of symptom cluster composition in advanced cancer patients using different statistical methodologies for all patients across five primary cancer sites, and to examine which clusters predict functional status, a global assessment of health and global quality of life. Principal component analysis and exploratory factor analysis (with different rotation and factor selection methods) and hierarchical cluster analysis (with different linkage and similarity measures) were used on a data set of 1562 advanced cancer patients who completed the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire-Core 30. Four clusters consistently formed for many of the methods and cancer sites: tense-worry-irritable-depressed (emotional cluster), fatigue-pain, nausea-vomiting, and concentration-memory (cognitive cluster). The emotional cluster was a stronger predictor of overall quality of life than the other clusters. Fatigue-pain was a stronger predictor of overall health than the other clusters. The cognitive cluster and fatigue-pain predicted physical functioning, role functioning, and social functioning. The four identified symptom clusters were consistent across statistical methods and cancer types, although there were some noteworthy differences. Statistical derivation of symptom clusters is in need of greater methodological guidance. A psychosocial pathway in the management of symptom clusters may improve quality of life. Biological mechanisms underpinning symptom clusters need to be delineated by future research. A framework for evidence-based screening, assessment, treatment, and follow-up of symptom clusters in advanced cancer is essential. Copyright © 2016 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

  19. Residential cancer cluster investigation nearby a Superfund Study Area with trichloroethylene contamination.

    Science.gov (United States)

    Press, David J; McKinley, Meg; Deapen, Dennis; Clarke, Christina A; Gomez, Scarlett Lin

    2016-05-01

    Trichloroethylene (TCE) is an industrial solvent associated with liver cancer, kidney cancer, and non-Hodgkin's lymphoma (NHL). It is unclear whether an excess of TCE-associated cancers have occurred surrounding the Middlefield-Ellis-Whisman Superfund site in Mountain View, California. We conducted a population-based cancer cluster investigation comparing the incidence of NHL, liver, and kidney cancers in the neighborhood of interest to the incidence among residents in the surrounding four-county region. Case counts and address information were obtained using routinely collected data from the Greater Bay Area Cancer Registry, part of the Surveillance, Epidemiology, and End Results program. Population denominators were obtained from the 1990, 2000, and 2010 US censuses. Standardized incidence ratios (SIRs) with two-sided 99 % confidence intervals (CIs) were calculated for time intervals surrounding the US Censuses. There were no statistically significant differences between the neighborhood of interest and the larger region for cancers of the liver or kidney. A statistically significant elevation was observed for NHL during one of the three time periods evaluated (1996-2005: SIR = 1.8, 99 % CI 1.1-2.8). No statistically significant NHL elevation existed in the earlier 1988-1995 (SIR = 1.3, 99 % CI 0.5-2.6) or later 2006-2011 (SIR = 1.3, 99 % CI 0.6-2.4) periods. There is no evidence of an increased incidence of liver or kidney cancer, and there is a lack of evidence of a consistent, sustained, or more recent elevation in NHL occurrence in this neighborhood. This evaluation included existing cancer registry data, which cannot speak to specific exposures incurred by past or current residents of this neighborhood.

  20. Cluster symptoms in cancer patients: A systematic Review

    OpenAIRE

    Anastasios Tzenalis; Ioanna Vekili

    2013-01-01

    Clinical studies have shown that patients with cancer experience multiple and simultaneously occurring symptoms, both during the illness and the therapeutic interventions. Aim: The aim of the present systematic review study was to investigate the symptom complex (cluster symptoms) occurring in patients suffering from cancer and their effect on the outcome of the disease. Methods: Data collection was based on electronic databases «MEDLINE / PubMed», «CINAHL», «PsycINFO», «Science Direct», «Spr...

  1. Effects of symptom clusters and depression on the quality of life in patients with advanced lung cancer.

    Science.gov (United States)

    Choi, S; Ryu, E

    2018-01-01

    People with advanced lung cancer experience later symptoms after treatment that is related to poorer psychosocial and quality of life (QOL) outcomes. The purpose of this study was to identify the effect of symptom clusters and depression on the QOL of patients with advanced lung cancer. A sample of 178 patients with advanced lung cancer at the National Cancer Center in Korea completed a demographic questionnaire, the M.D. Anderson Symptom Inventory-Lung Cancer, the Center for Epidemiological Studies Depression Scale, and the Functional Assessment of Cancer Therapy-General scale. The most frequently experienced symptom was fatigue, anguish was the most severe symptom-associated distress, and 28.9% of participants were clinically depressed. Factor analysis was used to identify symptom clusters based on the severity of patients' symptom experiences. Three symptom clusters were identified: treatment-associated, lung cancer and psychological symptom clusters. The regression model found a significant negative impact on QOL for depression and lung cancer symptom cluster. Age as the control variable was found to be significant impact on QOL. Therefore, psychological screening and appropriate intervention is an essential part of advanced cancer care. Both pharmacological and non-pharmacological approaches for alleviating depression may help to improve the QOL of lung cancer patients. © 2016 John Wiley & Sons Ltd.

  2. Battling with breast cancer - addressing the issues

    Energy Technology Data Exchange (ETDEWEB)

    Amin, S; Wahid, N; Wasim, B; Tabassum, S [Patel Hospital Gulshan-e-Iqbal, Karachi (Pakistan)

    2011-06-15

    In the background of the current situation of breast cancer in Pakistan, with its rising incidence and mortality, non afford ability and inaccessibility to screening, diagnosis and treatment, Patel Hospital took up the task of addressing these issues at a local level, by initiating an annual free breast camp in the year 2006. In 2008 an inclusion criteria was defined to focus on high risk women for breast cancer. A comparative analysis over a period of three years was done. In the focused camps, in which 28% patients were found to have a positive family history. Most women were symptomatic. Total 11 patients were diagnosed to have cancer after evaluation. Six patients underwent definitive treatment. A problem with lack of awareness, regarding screening and treatment protocols was identified. Family history seems to be an important risk factor in our set up signifying the need to introduce extensive screening programmes. (author)

  3. Battling with breast cancer - addressing the issues

    International Nuclear Information System (INIS)

    Amin, S.; Wahid, N.; Wasim, B.; Tabassum, S.

    2011-01-01

    In the background of the current situation of breast cancer in Pakistan, with its rising incidence and mortality, non afford ability and inaccessibility to screening, diagnosis and treatment, Patel Hospital took up the task of addressing these issues at a local level, by initiating an annual free breast camp in the year 2006. In 2008 an inclusion criteria was defined to focus on high risk women for breast cancer. A comparative analysis over a period of three years was done. In the focused camps, in which 28% patients were found to have a positive family history. Most women were symptomatic. Total 11 patients were diagnosed to have cancer after evaluation. Six patients underwent definitive treatment. A problem with lack of awareness, regarding screening and treatment protocols was identified. Family history seems to be an important risk factor in our set up signifying the need to introduce extensive screening programmes. (author)

  4. MO-FG-BRB-01: Investing to Address the Global Cancer Challenge

    International Nuclear Information System (INIS)

    Atun, R.

    2015-01-01

    corresponding potential benefits of addressing this challenge. To describe what radiation therapy infrastructure, in terms of facilities, equipment and personnel, will be required to address this challenge. To describe models of addressing personnel and infrastructure mobilization and capacity building within regions where significant cancer treatment disparities exist

  5. MO-FG-BRB-01: Investing to Address the Global Cancer Challenge

    Energy Technology Data Exchange (ETDEWEB)

    Atun, R. [Harvard University (United States)

    2015-06-15

    corresponding potential benefits of addressing this challenge. To describe what radiation therapy infrastructure, in terms of facilities, equipment and personnel, will be required to address this challenge. To describe models of addressing personnel and infrastructure mobilization and capacity building within regions where significant cancer treatment disparities exist.

  6. Message passing vs. shared address space on a cluster of SMPs

    International Nuclear Information System (INIS)

    Shan, Hongzhang; Singh, Jaswinder Pal; Oliker, Leonid; Biswas, Rupak

    2001-01-01

    The emergence of scalable computer architectures using clusters of PCs or PC-SMPs with commodity networking has made them attractive platforms for high-end scientific computing. Currently, message passing (MP) and shared address space (SAS) are the two leading programming paradigms for these systems. MP has been standardized with MPI, and is the most common and mature parallel programming approach. However, MP code development can be extremely difficult, especially for irregularly structured computations. SAS offers substantial ease of programming, but may suffer from performance limitations due to poor spatial locality and high protocol overhead. In this paper, they compare the performance of and programming effort required for six applications under both programming models on a 32-CPU PC-SMP cluster. Our application suite consists of codes that typically do not exhibit scalable performance under shared-memory programming due to their high communication-to-computation ratios and complex communication patterns. Results indicate that SAS can achieve about half the parallel efficiency of MPI for most of the applications; however, on certain classes of problems, SAS performance is competitive with MPI

  7. Symptom clusters and related factors in bladder cancer patients three months after radical cystectomy.

    Science.gov (United States)

    Ren, Hongyan; Tang, Ping; Zhao, Qinghua; Ren, Guosheng

    2017-08-23

    To identify symptom distress and clusters in patients 3 months after radical cystectomy and to explore their potential predictors. A cross-sectional design was used to investigate 99 bladder cancer patients 3 months after radical cystectomy. Data were collected by demographic and disease characteristic questionnaires, the symptom experience scale of the M.D. Anderson symptom inventory, two additional symptoms specific to radical cystectomy, and the functional assessment of cancer therapy questionnaire. A factor analysis, stepwise regression, and correlation analysis were applied. Three symptom clusters were identified: fatigue-malaise, gastrointestinal, and psycho-urinary. Age, complication severity, albumin post-surgery (negative), orthotropic neobladder reconstruction, adjuvant chemotherapy and American Society of Anesthesiologists (ASA) scores were significant predictors of fatigue-malaise. Adjuvant chemotherapy, orthotropic neobladder reconstruction, female gender, ASA scores and albumin (negative) were significant predictors of gastrointestinal symptoms. Being unmarried, having a higher educational level and complication severity were significant predictors of psycho-urinary symptoms. The correlations between clusters and for each cluster with quality of life were significant, with the highest correlation observed between the psycho-urinary cluster and quality of life. Bladder cancer patients experience concurrent symptoms that appear to cluster and are significantly correlated with quality of life. Moreover, symptom clusters may be predicted by certain demographic and clinical characteristics.

  8. DEMARCATE: Density-based magnetic resonance image clustering for assessing tumor heterogeneity in cancer.

    Science.gov (United States)

    Saha, Abhijoy; Banerjee, Sayantan; Kurtek, Sebastian; Narang, Shivali; Lee, Joonsang; Rao, Ganesh; Martinez, Juan; Bharath, Karthik; Rao, Arvind U K; Baladandayuthapani, Veerabhadran

    2016-01-01

    Tumor heterogeneity is a crucial area of cancer research wherein inter- and intra-tumor differences are investigated to assess and monitor disease development and progression, especially in cancer. The proliferation of imaging and linked genomic data has enabled us to evaluate tumor heterogeneity on multiple levels. In this work, we examine magnetic resonance imaging (MRI) in patients with brain cancer to assess image-based tumor heterogeneity. Standard approaches to this problem use scalar summary measures (e.g., intensity-based histogram statistics) that do not adequately capture the complete and finer scale information in the voxel-level data. In this paper, we introduce a novel technique, DEMARCATE (DEnsity-based MAgnetic Resonance image Clustering for Assessing Tumor hEterogeneity) to explore the entire tumor heterogeneity density profiles (THDPs) obtained from the full tumor voxel space. THDPs are smoothed representations of the probability density function of the tumor images. We develop tools for analyzing such objects under the Fisher-Rao Riemannian framework that allows us to construct metrics for THDP comparisons across patients, which can be used in conjunction with standard clustering approaches. Our analyses of The Cancer Genome Atlas (TCGA) based Glioblastoma dataset reveal two significant clusters of patients with marked differences in tumor morphology, genomic characteristics and prognostic clinical outcomes. In addition, we see enrichment of image-based clusters with known molecular subtypes of glioblastoma multiforme, which further validates our representation of tumor heterogeneity and subsequent clustering techniques.

  9. Synthesis and Structure-Activity Relationship of Griseofulvin Analogues as Inhibitors of Centrosomal Clustering in Cancer Cells

    DEFF Research Database (Denmark)

    Rønnest, Mads Holger; Rebacz, Blanka; Markworth, Lene

    2009-01-01

    Griseofulvin was identified as an inhibitor of centrosomal clustering in a recently developed assay. Centrosomal clustering is an important cellular event that enables bipolar mitosis for cancer cell lines harboring supernumerary centrosomes. We report herein the synthesis and SAR of 34 griseoful......Griseofulvin was identified as an inhibitor of centrosomal clustering in a recently developed assay. Centrosomal clustering is an important cellular event that enables bipolar mitosis for cancer cell lines harboring supernumerary centrosomes. We report herein the synthesis and SAR of 34...

  10. Trajectories of Symptom Clusters, Performance Status, and Quality of Life During Concurrent Chemoradiotherapy in Patients With High-Grade Brain Cancers.

    Science.gov (United States)

    Kim, Sang-Hee; Byun, Youngsoon

    Symptom clusters must be identified in patients with high-grade brain cancers for effective symptom management during cancer-related therapy. The aims of this study were to identify symptom clusters in patients with high-grade brain cancers and to determine the relationship of each cluster with the performance status and quality of life (QOL) during concurrent chemoradiotherapy (CCRT). Symptoms were assessed using the Memorial Symptom Assessment Scale, and the performance status was evaluated using the Karnofsky Performance Scale. Quality of life was assessed using the Functional Assessment of Cancer Therapy-General. This prospective longitudinal survey was conducted before CCRT and at 2 to 3 weeks and 4 to 6 weeks after the initiation of CCRT. A total of 51 patients with newly diagnosed primary malignant brain cancer were included. Six symptom clusters were identified, and 2 symptom clusters were present at each time point (ie, "negative emotion" and "neurocognitive" clusters before CCRT, "negative emotion and decreased vitality" and "gastrointestinal and decreased sensory" clusters at 2-3 weeks, and "body image and decreased vitality" and "gastrointestinal" clusters at 4-6 weeks). The symptom clusters at each time point demonstrated a significant relationship with the performance status or QOL. Differences were observed in symptom clusters in patients with high-grade brain cancers during CCRT. In addition, the symptom clusters were correlated with the performance status and QOL of patients, and these effects could change during CCRT. The results of this study will provide suggestions for interventions to treat or prevent symptom clusters in patients with high-grade brain cancer during CCRT.

  11. Multilevel Opportunities to Address Lung Cancer Stigma across the Cancer Control Continuum.

    Science.gov (United States)

    Hamann, Heidi A; Ver Hoeve, Elizabeth S; Carter-Harris, Lisa; Studts, Jamie L; Ostroff, Jamie S

    2018-05-22

    The public health imperative to reduce the burden of lung cancer has seen unprecedented progress in recent years. Realizing fully the advances in lung cancer treatment and control requires attention to potential barriers in their momentum and implementation. In this analysis, we present and evaluate the argument that stigma is a highly significant barrier to fulfilling the clinical promise of advanced care and reduced lung cancer burden. This evaluation of lung cancer stigma is based on a multilevel perspective that incorporates the individual, persons in their immediate environment, the healthcare system, and the larger societal structure which shapes perceptions and decisions. We also consider current interventions and interventional needs within and across aspects of the lung cancer continuum, including prevention, screening, diagnosis, treatment, and survivorship. Current evidence suggests that stigma detrimentally impacts psychosocial, communication, and behavioral outcomes over the entire lung cancer control continuum and across multiple levels. Interventional efforts to alleviate stigma in the context of lung cancer show promise, yet more work is needed to evaluate their impact. Understanding and addressing the multi-level role of stigma is a crucial area for future study in order to realize the full benefits offered by lung cancer prevention, control, and treatment. Coordinated, interdisciplinary, and well-conceptualized efforts have the potential to reduce the barrier of stigma in the context of lung cancer and facilitate demonstrable improvements in clinical care and quality of life. Copyright © 2018. Published by Elsevier Inc.

  12. Designing a community-based lay health advisor training curriculum to address cancer health disparities.

    Science.gov (United States)

    Gwede, Clement K; Ashley, Atalie A; McGinnis, Kara; Montiel-Ishino, F Alejandro; Standifer, Maisha; Baldwin, Julie; Williams, Coni; Sneed, Kevin B; Wathington, Deanna; Dash-Pitts, Lolita; Green, B Lee

    2013-05-01

    Racial and ethnic minorities have disproportionately higher cancer incidence and mortality than their White counterparts. In response to this inequity in cancer prevention and care, community-based lay health advisors (LHAs) may be suited to deliver effective, culturally relevant, quality cancer education, prevention/screening, and early detection services for underserved populations. APPROACH AND STRATEGIES: Consistent with key tenets of community-based participatory research (CBPR), this project engaged community partners to develop and implement a unique LHA training curriculum to address cancer health disparities among medically underserved communities in a tricounty area. Seven phases of curriculum development went into designing a final seven-module LHA curriculum. In keeping with principles of CBPR and community engagement, academic-community partners and LHAs themselves were involved at all phases to ensure the needs of academic and community partners were mutually addressed in development and implementation of the LHA program. Community-based LHA programs for outreach, education, and promotion of cancer screening and early detection, are ideal for addressing cancer health disparities in access and quality care. When community-based LHAs are appropriately recruited, trained, and located in communities, they provide unique opportunities to link, bridge, and facilitate quality cancer education, services, and research.

  13. Local bladder cancer clusters in southeastern Michigan accounting for risk factors, covariates and residential mobility.

    Directory of Open Access Journals (Sweden)

    Geoffrey M Jacquez

    Full Text Available In case control studies disease risk not explained by the significant risk factors is the unexplained risk. Considering unexplained risk for specific populations, places and times can reveal the signature of unidentified risk factors and risk factors not fully accounted for in the case-control study. This potentially can lead to new hypotheses regarding disease causation.Global, local and focused Q-statistics are applied to data from a population-based case-control study of 11 southeast Michigan counties. Analyses were conducted using both year- and age-based measures of time. The analyses were adjusted for arsenic exposure, education, smoking, family history of bladder cancer, occupational exposure to bladder cancer carcinogens, age, gender, and race.Significant global clustering of cases was not found. Such a finding would indicate large-scale clustering of cases relative to controls through time. However, highly significant local clusters were found in Ingham County near Lansing, in Oakland County, and in the City of Jackson, Michigan. The Jackson City cluster was observed in working-ages and is thus consistent with occupational causes. The Ingham County cluster persists over time, suggesting a broad-based geographically defined exposure. Focused clusters were found for 20 industrial sites engaged in manufacturing activities associated with known or suspected bladder cancer carcinogens. Set-based tests that adjusted for multiple testing were not significant, although local clusters persisted through time and temporal trends in probability of local tests were observed.Q analyses provide a powerful tool for unpacking unexplained disease risk from case-control studies. This is particularly useful when the effect of risk factors varies spatially, through time, or through both space and time. For bladder cancer in Michigan, the next step is to investigate causal hypotheses that may explain the excess bladder cancer risk localized to areas of

  14. Space-Time Analysis of Testicular Cancer Clusters Using Residential Histories: A Case-Control Study in Denmark

    Science.gov (United States)

    Sloan, Chantel D.; Nordsborg, Rikke B.; Jacquez, Geoffrey M.; Raaschou-Nielsen, Ole; Meliker, Jaymie R.

    2015-01-01

    Though the etiology is largely unknown, testicular cancer incidence has seen recent significant increases in northern Europe and throughout many Western regions. The most common cancer in males under age 40, age period cohort models have posited exposures in the in utero environment or in early childhood as possible causes of increased risk of testicular cancer. Some of these factors may be tied to geography through being associated with behavioral, cultural, sociodemographic or built environment characteristics. If so, this could result in detectable geographic clusters of cases that could lead to hypotheses regarding environmental targets for intervention. Given a latency period between exposure to an environmental carcinogen and testicular cancer diagnosis, mobility histories are beneficial for spatial cluster analyses. Nearest-neighbor based Q-statistics allow for the incorporation of changes in residency in spatial disease cluster detection. Using these methods, a space-time cluster analysis was conducted on a population-wide case-control population selected from the Danish Cancer Registry with mobility histories since 1971 extracted from the Danish Civil Registration System. Cases (N=3297) were diagnosed between 1991 and 2003, and two sets of controls (N=3297 for each set) matched on sex and date of birth were included in the study. We also examined spatial patterns in maternal residential history for those cases and controls born in 1971 or later (N= 589 case-control pairs). Several small clusters were detected when aligning individuals by year prior to diagnosis, age at diagnosis and calendar year of diagnosis. However, the largest of these clusters contained only 2 statistically significant individuals at their center, and were not replicated in SaTScan spatial-only analyses which are less susceptible to multiple testing bias. We found little evidence of local clusters in residential histories of testicular cancer cases in this Danish population. PMID

  15. Space-time analysis of testicular cancer clusters using residential histories: a case-control study in Denmark.

    Directory of Open Access Journals (Sweden)

    Chantel D Sloan

    Full Text Available Though the etiology is largely unknown, testicular cancer incidence has seen recent significant increases in northern Europe and throughout many Western regions. The most common cancer in males under age 40, age period cohort models have posited exposures in the in utero environment or in early childhood as possible causes of increased risk of testicular cancer. Some of these factors may be tied to geography through being associated with behavioral, cultural, sociodemographic or built environment characteristics. If so, this could result in detectable geographic clusters of cases that could lead to hypotheses regarding environmental targets for intervention. Given a latency period between exposure to an environmental carcinogen and testicular cancer diagnosis, mobility histories are beneficial for spatial cluster analyses. Nearest-neighbor based Q-statistics allow for the incorporation of changes in residency in spatial disease cluster detection. Using these methods, a space-time cluster analysis was conducted on a population-wide case-control population selected from the Danish Cancer Registry with mobility histories since 1971 extracted from the Danish Civil Registration System. Cases (N=3297 were diagnosed between 1991 and 2003, and two sets of controls (N=3297 for each set matched on sex and date of birth were included in the study. We also examined spatial patterns in maternal residential history for those cases and controls born in 1971 or later (N= 589 case-control pairs. Several small clusters were detected when aligning individuals by year prior to diagnosis, age at diagnosis and calendar year of diagnosis. However, the largest of these clusters contained only 2 statistically significant individuals at their center, and were not replicated in SaTScan spatial-only analyses which are less susceptible to multiple testing bias. We found little evidence of local clusters in residential histories of testicular cancer cases in this Danish

  16. Space-time analysis of testicular cancer clusters using residential histories: a case-control study in Denmark.

    Science.gov (United States)

    Sloan, Chantel D; Nordsborg, Rikke B; Jacquez, Geoffrey M; Raaschou-Nielsen, Ole; Meliker, Jaymie R

    2015-01-01

    Though the etiology is largely unknown, testicular cancer incidence has seen recent significant increases in northern Europe and throughout many Western regions. The most common cancer in males under age 40, age period cohort models have posited exposures in the in utero environment or in early childhood as possible causes of increased risk of testicular cancer. Some of these factors may be tied to geography through being associated with behavioral, cultural, sociodemographic or built environment characteristics. If so, this could result in detectable geographic clusters of cases that could lead to hypotheses regarding environmental targets for intervention. Given a latency period between exposure to an environmental carcinogen and testicular cancer diagnosis, mobility histories are beneficial for spatial cluster analyses. Nearest-neighbor based Q-statistics allow for the incorporation of changes in residency in spatial disease cluster detection. Using these methods, a space-time cluster analysis was conducted on a population-wide case-control population selected from the Danish Cancer Registry with mobility histories since 1971 extracted from the Danish Civil Registration System. Cases (N=3297) were diagnosed between 1991 and 2003, and two sets of controls (N=3297 for each set) matched on sex and date of birth were included in the study. We also examined spatial patterns in maternal residential history for those cases and controls born in 1971 or later (N= 589 case-control pairs). Several small clusters were detected when aligning individuals by year prior to diagnosis, age at diagnosis and calendar year of diagnosis. However, the largest of these clusters contained only 2 statistically significant individuals at their center, and were not replicated in SaTScan spatial-only analyses which are less susceptible to multiple testing bias. We found little evidence of local clusters in residential histories of testicular cancer cases in this Danish population.

  17. Breast-related stereotype threat contributes to a symptom cluster in women with breast cancer.

    Science.gov (United States)

    Li, Jie; Gao, Wei; Yu, Li-Xiang; Zhu, Song-Ying; Cao, Feng-Lin

    2017-05-01

    To investigate the prevalence of breast-related stereotype threat and its effects on a symptom cluster consisting of anxiety, depression and fatigue and on each symptom. The stereotype that breasts are a sign of women's femininity results in patients with breast cancer fearing diminished femininity and rejection, which may induce psychological problems that co-occur as a symptom cluster. Cross-sectional study. A total of 131 patients with breast cancer postmastectomy completed the study. A question measuring breast-related stereotype threat, the Hospital Anxiety and Depression Scale and the Functional Assessment of Chronic Illness Therapy-Fatigue Scale were used to assess their breast-related stereotype threat and symptoms of anxiety, depression and fatigue. Of the 131 patients who answered the breast-related stereotype threat question, 86 (65·6%) reported breast-related stereotype threat. They did not differ significantly in social and clinical characteristics compared with those without the stereotype, but did report significantly higher levels of the symptom cluster and each symptom (anxiety, depression and fatigue). The odds ratios of the stereotype were significant for the symptom cluster, depression and fatigue (odds ratios = 2·52-3·98, p stereotype threat was common in patients with breast cancer. There was about a twofold increase in their risk of experiencing the symptom cluster and symptoms of depression and fatigue. In clinical practice, breast-related stereotype threat should be measured together with prevalent symptoms (e.g. anxiety, depression and fatigue) in patients with breast cancer. Our findings will aid the development of interventions for improving the mental health of women with breast cancer. © 2016 John Wiley & Sons Ltd.

  18. Adoptive T cell therapy: Addressing challenges in cancer immunotherapy

    Directory of Open Access Journals (Sweden)

    Yee Cassian

    2005-04-01

    Full Text Available Abstract Adoptive T cell therapy involves the ex vivo selection and expansion of effector cells for the treatment of patients with cancer. In this review, the advantages and limitations of using antigen-specific T cells are discussed in counterpoint to vaccine strategies. Although vaccination strategies represent more readily available reagents, adoptive T cell therapy provides highly selected T cells of defined phenotype, specificity and function that may influence their biological behavior in vivo. Adoptive T cell therapy offers not only translational opportunities but also a means to address fundamental issues in the evolving field of cancer immunotherapy.

  19. Poor Prognosis Indicated by Venous Circulating Tumor Cell Clusters in Early-Stage Lung Cancers.

    Science.gov (United States)

    Murlidhar, Vasudha; Reddy, Rishindra M; Fouladdel, Shamileh; Zhao, Lili; Ishikawa, Martin K; Grabauskiene, Svetlana; Zhang, Zhuo; Lin, Jules; Chang, Andrew C; Carrott, Philip; Lynch, William R; Orringer, Mark B; Kumar-Sinha, Chandan; Palanisamy, Nallasivam; Beer, David G; Wicha, Max S; Ramnath, Nithya; Azizi, Ebrahim; Nagrath, Sunitha

    2017-09-15

    Early detection of metastasis can be aided by circulating tumor cells (CTC), which also show potential to predict early relapse. Because of the limited CTC numbers in peripheral blood in early stages, we investigated CTCs in pulmonary vein blood accessed during surgical resection of tumors. Pulmonary vein (PV) and peripheral vein (Pe) blood specimens from patients with lung cancer were drawn during the perioperative period and assessed for CTC burden using a microfluidic device. From 108 blood samples analyzed from 36 patients, PV had significantly higher number of CTCs compared with preoperative Pe ( P ontology analysis revealed enrichment of cell migration and immune-related pathways in CTC clusters, suggesting survival advantage of clusters in circulation. Clusters display characteristics of therapeutic resistance, indicating the aggressive nature of these cells. Thus, CTCs isolated from early stages of lung cancer are predictive of poor prognosis and can be interrogated to determine biomarkers predictive of recurrence. Cancer Res; 77(18); 5194-206. ©2017 AACR . ©2017 American Association for Cancer Research.

  20. The Role of Inflammation in the Pain, Fatigue, and Sleep Disturbance Symptom Cluster in Advanced Cancer.

    Science.gov (United States)

    Kwekkeboom, Kristine L; Tostrud, Lauren; Costanzo, Erin; Coe, Christopher L; Serlin, Ronald C; Ward, Sandra E; Zhang, Yingzi

    2018-05-01

    Symptom researchers have proposed a model of inflammatory cytokine activity and dysregulation in cancer to explain co-occurring symptoms including pain, fatigue, and sleep disturbance. We tested the hypothesis that psychological stress accentuates inflammation and that stress and inflammation contribute to one's experience of the pain, fatigue, and sleep disturbance symptom cluster (symptom cluster severity, symptom cluster distress) and its impact (symptom cluster interference with daily life, quality of life). We used baseline data from a symptom cluster management trial. Adult participants (N = 158) receiving chemotherapy for advanced cancer reported pain, fatigue, and sleep disturbance on enrollment. Before intervention, participants completed measures of demographics, perceived stress, symptom cluster severity, symptom cluster distress, symptom cluster interference with daily life, and quality of life and provided a blood sample for four inflammatory biomarkers (interleukin-1β, interleukin-6, tumor necrosis factor-α, and C-reactive protein). Stress was not directly related to any inflammatory biomarker. Stress and tumor necrosis factor-α were positively related to symptom cluster distress, although not symptom cluster severity. Tumor necrosis factor-α was indirectly related to symptom cluster interference with daily life, through its effect on symptom cluster distress. Stress was positively associated with symptom cluster interference with daily life and inversely with quality of life. Stress also had indirect effects on symptom cluster interference with daily life, through its effect on symptom cluster distress. The proposed inflammatory model of symptoms was partially supported. Investigators should test interventions that target stress as a contributing factor in co-occurring pain, fatigue, and sleep disturbance and explore other factors that may influence inflammatory biomarker levels within the context of an advanced cancer diagnosis and treatment

  1. A phenanthrene derived PARP inhibitor is an extra-centrosomes de-clustering agent exclusively eradicating human cancer cells

    Directory of Open Access Journals (Sweden)

    Izraeli Shai

    2011-09-01

    Full Text Available Abstract Background Cells of most human cancers have supernumerary centrosomes. To enable an accurate chromosome segregation and cell division, these cells developed a yet unresolved molecular mechanism, clustering their extra centrosomes at two poles, thereby mimicking mitosis in normal cells. Failure of this bipolar centrosome clustering causes multipolar spindle structures and aberrant chromosomes segregation that prevent normal cell division and lead to 'mitotic catastrophe cell death'. Methods We used cell biology and biochemical methods, including flow cytometry, immunocytochemistry and live confocal imaging. Results We identified a phenanthrene derived PARP inhibitor, known for its activity in neuroprotection under stress conditions, which exclusively eradicated multi-centrosomal human cancer cells (mammary, colon, lung, pancreas, ovarian while acting as extra-centrosomes de-clustering agent in mitosis. Normal human proliferating cells (endothelial, epithelial and mesenchymal cells were not impaired. Despite acting as PARP inhibitor, the cytotoxic activity of this molecule in cancer cells was not attributed to PARP inhibition alone. Conclusion We identified a water soluble phenanthridine that exclusively targets the unique dependence of most human cancer cells on their supernumerary centrosomes bi-polar clustering for their survival. This paves the way for a new selective cancer-targeting therapy, efficient in a wide range of human cancers.

  2. An enhanced deterministic K-Means clustering algorithm for cancer subtype prediction from gene expression data.

    Science.gov (United States)

    Nidheesh, N; Abdul Nazeer, K A; Ameer, P M

    2017-12-01

    Clustering algorithms with steps involving randomness usually give different results on different executions for the same dataset. This non-deterministic nature of algorithms such as the K-Means clustering algorithm limits their applicability in areas such as cancer subtype prediction using gene expression data. It is hard to sensibly compare the results of such algorithms with those of other algorithms. The non-deterministic nature of K-Means is due to its random selection of data points as initial centroids. We propose an improved, density based version of K-Means, which involves a novel and systematic method for selecting initial centroids. The key idea of the algorithm is to select data points which belong to dense regions and which are adequately separated in feature space as the initial centroids. We compared the proposed algorithm to a set of eleven widely used single clustering algorithms and a prominent ensemble clustering algorithm which is being used for cancer data classification, based on the performances on a set of datasets comprising ten cancer gene expression datasets. The proposed algorithm has shown better overall performance than the others. There is a pressing need in the Biomedical domain for simple, easy-to-use and more accurate Machine Learning tools for cancer subtype prediction. The proposed algorithm is simple, easy-to-use and gives stable results. Moreover, it provides comparatively better predictions of cancer subtypes from gene expression data. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Analysis of k-means clustering approach on the breast cancer Wisconsin dataset.

    Science.gov (United States)

    Dubey, Ashutosh Kumar; Gupta, Umesh; Jain, Sonal

    2016-11-01

    Breast cancer is one of the most common cancers found worldwide and most frequently found in women. An early detection of breast cancer provides the possibility of its cure; therefore, a large number of studies are currently going on to identify methods that can detect breast cancer in its early stages. This study was aimed to find the effects of k-means clustering algorithm with different computation measures like centroid, distance, split method, epoch, attribute, and iteration and to carefully consider and identify the combination of measures that has potential of highly accurate clustering accuracy. K-means algorithm was used to evaluate the impact of clustering using centroid initialization, distance measures, and split methods. The experiments were performed using breast cancer Wisconsin (BCW) diagnostic dataset. Foggy and random centroids were used for the centroid initialization. In foggy centroid, based on random values, the first centroid was calculated. For random centroid, the initial centroid was considered as (0, 0). The results were obtained by employing k-means algorithm and are discussed with different cases considering variable parameters. The calculations were based on the centroid (foggy/random), distance (Euclidean/Manhattan/Pearson), split (simple/variance), threshold (constant epoch/same centroid), attribute (2-9), and iteration (4-10). Approximately, 92 % average positive prediction accuracy was obtained with this approach. Better results were found for the same centroid and the highest variance. The results achieved using Euclidean and Manhattan were better than the Pearson correlation. The findings of this work provided extensive understanding of the computational parameters that can be used with k-means. The results indicated that k-means has a potential to classify BCW dataset.

  4. Lung Cancer Signature Biomarkers: tissue specific semantic similarity based clustering of Digital Differential Display (DDD data

    Directory of Open Access Journals (Sweden)

    Srivastava Mousami

    2012-11-01

    Full Text Available Abstract Background The tissue-specific Unigene Sets derived from more than one million expressed sequence tags (ESTs in the NCBI, GenBank database offers a platform for identifying significantly and differentially expressed tissue-specific genes by in-silico methods. Digital differential display (DDD rapidly creates transcription profiles based on EST comparisons and numerically calculates, as a fraction of the pool of ESTs, the relative sequence abundance of known and novel genes. However, the process of identifying the most likely tissue for a specific disease in which to search for candidate genes from the pool of differentially expressed genes remains difficult. Therefore, we have used ‘Gene Ontology semantic similarity score’ to measure the GO similarity between gene products of lung tissue-specific candidate genes from control (normal and disease (cancer sets. This semantic similarity score matrix based on hierarchical clustering represents in the form of a dendrogram. The dendrogram cluster stability was assessed by multiple bootstrapping. Multiple bootstrapping also computes a p-value for each cluster and corrects the bias of the bootstrap probability. Results Subsequent hierarchical clustering by the multiple bootstrapping method (α = 0.95 identified seven clusters. The comparative, as well as subtractive, approach revealed a set of 38 biomarkers comprising four distinct lung cancer signature biomarker clusters (panel 1–4. Further gene enrichment analysis of the four panels revealed that each panel represents a set of lung cancer linked metastasis diagnostic biomarkers (panel 1, chemotherapy/drug resistance biomarkers (panel 2, hypoxia regulated biomarkers (panel 3 and lung extra cellular matrix biomarkers (panel 4. Conclusions Expression analysis reveals that hypoxia induced lung cancer related biomarkers (panel 3, HIF and its modulating proteins (TGM2, CSNK1A1, CTNNA1, NAMPT/Visfatin, TNFRSF1A, ETS1, SRC-1, FN1, APLP2, DMBT1

  5. Molybdenum cluster loaded PLGA nanoparticles: An innovative theranostic approach for the treatment of ovarian cancer.

    Science.gov (United States)

    Brandhonneur, N; Hatahet, T; Amela-Cortes, M; Molard, Y; Cordier, S; Dollo, G

    2018-04-01

    We evaluate poly (d,l-lactide-co-glycolide) (PLGA) nanoparticles embedding inorganic molybdenum octahedral cluster for photodynamic therapy of cancer (PDT). Tetrabutyl ammonium salt of Mo 6 Br 14 cluster unit, (TBA) 2 Mo 6 Br 14 , presents promising photosensitization activity in the destruction of targeted cancer cells. Stable cluster loaded nanoparticles (CNPs) were prepared by solvent displacement method showing spherical shapes, zeta potential values around -30 mV, polydispersity index lower than 0.2 and sizes around 100 nm. FT-IR and DSC analysis revealed the lack of strong chemical interaction between the cluster and the polymer within the nanoparticles. In vitro release study showed that (TBA) 2 Mo 6 Br 14 was totally dissolved in 20 min, while CNPs were able to control the release of encapsulated cluster. In vitro cellular viability studies conducted on A2780 ovarian cancer cell line treated up to 72 h with cluster or CNPs did not show any sign of toxicity in concentrations up to 20 µg/ml. This concentration was selected for photo-activation test on A2780 cells and CNPs were able to generate oxygen singlet resulting in a decrease of the cellular viability up to 50%, respectively compared to non-activated conditions. This work presents (TBA) 2 Mo 6 Br 14 as a novel photosensitizer for PDT and suggests PLGA nanoparticles as an efficient delivery system intended for tumor targeting. Copyright © 2018 Elsevier B.V. All rights reserved.

  6. Exploring the individual patterns of spiritual well-being in people newly diagnosed with advanced cancer: a cluster analysis.

    Science.gov (United States)

    Bai, Mei; Dixon, Jane; Williams, Anna-Leila; Jeon, Sangchoon; Lazenby, Mark; McCorkle, Ruth

    2016-11-01

    Research shows that spiritual well-being correlates positively with quality of life (QOL) for people with cancer, whereas contradictory findings are frequently reported with respect to the differentiated associations between dimensions of spiritual well-being, namely peace, meaning and faith, and QOL. This study aimed to examine individual patterns of spiritual well-being among patients newly diagnosed with advanced cancer. Cluster analysis was based on the twelve items of the 12-item Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being Scale at Time 1. A combination of hierarchical and k-means (non-hierarchical) clustering methods was employed to jointly determine the number of clusters. Self-rated health, depressive symptoms, peace, meaning and faith, and overall QOL were compared at Time 1 and Time 2. Hierarchical and k-means clustering methods both suggested four clusters. Comparison of the four clusters supported statistically significant and clinically meaningful differences in QOL outcomes among clusters while revealing contrasting relations of faith with QOL. Cluster 1, Cluster 3, and Cluster 4 represented high, medium, and low levels of overall QOL, respectively, with correspondingly high, medium, and low levels of peace, meaning, and faith. Cluster 2 was distinguished from other clusters by its medium levels of overall QOL, peace, and meaning and low level of faith. This study provides empirical support for individual difference in response to a newly diagnosed cancer and brings into focus conceptual and methodological challenges associated with the measure of spiritual well-being, which may partly contribute to the attenuated relation between faith and QOL.

  7. Unraveling the hidden heterogeneities of breast cancer based on functional miRNA cluster.

    Directory of Open Access Journals (Sweden)

    Li Li

    Full Text Available It has become increasingly clear that the current taxonomy of clinical phenotypes is mixed with molecular heterogeneity, which potentially affects the treatment effect for involved patients. Defining the hidden molecular-distinct diseases using modern large-scale genomic approaches is therefore useful for refining clinical practice and improving intervention strategies. Given that microRNA expression profiling has provided a powerful way to dissect hidden genetic heterogeneity for complex diseases, the aim of the study was to develop a bioinformatics approach that identifies microRNA features leading to the hidden subtyping of complex clinical phenotypes. The basic strategy of the proposed method was to identify optimal miRNA clusters by iteratively partitioning the sample and feature space using the two-ways super-paramagnetic clustering technique. We evaluated the obtained optimal miRNA cluster by determining the consistency of co-expression and the chromosome location among the within-cluster microRNAs, and concluded that the optimal miRNA cluster could lead to a natural partition of disease samples. We applied the proposed method to a publicly available microarray dataset of breast cancer patients that have notoriously heterogeneous phenotypes. We obtained a feature subset of 13 microRNAs that could classify the 71 breast cancer patients into five subtypes with significantly different five-year overall survival rates (45%, 82.4%, 70.6%, 100% and 60% respectively; p = 0.008. By building a multivariate Cox proportional-hazards prediction model for the feature subset, we identified has-miR-146b as one of the most significant predictor (p = 0.045; hazard ratios = 0.39. The proposed algorithm is a promising computational strategy for dissecting hidden genetic heterogeneity for complex diseases, and will be of value for improving cancer diagnosis and treatment.

  8. Symptom clusters in women with breast cancer: an analysis of data from social media and a research study.

    Science.gov (United States)

    Marshall, Sarah A; Yang, Christopher C; Ping, Qing; Zhao, Mengnan; Avis, Nancy E; Ip, Edward H

    2016-03-01

    User-generated content on social media sites, such as health-related online forums, offers researchers a tantalizing amount of information, but concerns regarding scientific application of such data remain. This paper compares and contrasts symptom cluster patterns derived from messages on a breast cancer forum with those from a symptom checklist completed by breast cancer survivors participating in a research study. Over 50,000 messages generated by 12,991 users of the breast cancer forum on MedHelp.org were transformed into a standard form and examined for the co-occurrence of 25 symptoms. The k-medoid clustering method was used to determine appropriate placement of symptoms within clusters. Findings were compared with a similar analysis of a symptom checklist administered to 653 breast cancer survivors participating in a research study. The following clusters were identified using forum data: menopausal/psychological, pain/fatigue, gastrointestinal, and miscellaneous. Study data generated the clusters: menopausal, pain, fatigue/sleep/gastrointestinal, psychological, and increased weight/appetite. Although the clusters are somewhat different, many symptoms that clustered together in the social media analysis remained together in the analysis of the study participants. Density of connections between symptoms, as reflected by rates of co-occurrence and similarity, was higher in the study data. The copious amount of data generated by social media outlets can augment findings from traditional data sources. When different sources of information are combined, areas of overlap and discrepancy can be detected, perhaps giving researchers a more accurate picture of reality. However, data derived from social media must be used carefully and with understanding of its limitations.

  9. Evaluation of secular trend and the existence of cases of clusters of bladder cancer in Goiania: descriptive study population-based; Avaliacao da tendencia temporal e da existencia de casos de clusters de cancer de bexiga em Goiania: estudo descritivo de base populacional

    Energy Technology Data Exchange (ETDEWEB)

    Antonio, Gisele Guimaraes Daflon

    2008-07-01

    More than 20 years after the radiological accident with cesium-137 in the city of Goiania, there is still a feeling in local population that the number of cases of cancer in the city is growing up due to the past radiation exposure and that the number of people contaminated or exposed was higher than the number reported. The present study aims to evaluate the temporal trend and the space-time distribution of bladder cancer cases in Goiania from 1988 and 2003, taking into account that bladder cancer presents the highest risk coefficients per unit of radiation dose among solid cancers. The study population was composed of all incident cases of bladder cancer registered in the Population-Based Cancer Registry of Goiania, between 1988 and 2003.Temporal trend of bladder cancer incidence was analyzed by sex and age groups ( < 60 and {>=} 60 years of age) through polynomial regression using age standardized incidence rates of bladder cancer (world population). SaTscan was used to determine whether statistical significant geographic clusters of high incidence of bladder cancer cases can be located in the city. The results showed a significant increase of bladder cancer incidence rates in males of all ages (p= 0.025) and for age group higher or equal to 60 years old (p=O.022), and a stability in trends for female sex. In the space-time analysis, a cluster was identified, however without statistical significance (p=0.278) and its location has no relationship with the main focuses of contamination of the radiological accident in 1987. We concluded that, despite of the increase of incidence rates in males, this can be explained by the improvement in diagnostic procedures throughout time, being this increase still not perceived in females considering the small number of cases. As chance can not be ruled out as the explanation of the identified cluster, we do not suggest any further detailed investigation in this cluster, as the occurrence of cluster diseases in space can occur

  10. Epidemiologic studies of radioactively contaminated environments and cancer clusters

    International Nuclear Information System (INIS)

    Boice, J.D. Jr.

    1991-01-01

    This paper reports on epidemiologic studies which address the distribution and determinants of disease in human populations. Investigations of the possible adverse effects of living in radioactively contaminated environments are difficult to conduct, however, because human populations tend to be fairly mobile, cumulative exposures to individuals from environmental conditions are difficult to estimate, and the risks associated with such exposures tend to be small relative to background levels of disease. Such studies can be arbitrarily classified as geographic correlation surveys, analytic studies, and cluster evaluations. Geographic correlation studies (ecological surveys) relate disease in populations to area characteristics. Although exposure to individuals is unknown, these exploratory or hypothesis-generating studies can identify areas to target for further in-depth evaluation. Analytic investigations relate individual exposure information to disease occurrence. Unusual occurrences of disease in time and place (clusters) occasionally point to a common environmental factor; cluster evaluations have been most successful in identifying the source of infectious disease outbreaks

  11. Clustering self-organizing maps (SOM) method for human papillomavirus (HPV) DNA as the main cause of cervical cancer disease

    Science.gov (United States)

    Bustamam, A.; Aldila, D.; Fatimah, Arimbi, M. D.

    2017-07-01

    One of the most widely used clustering method, since it has advantage on its robustness, is Self-Organizing Maps (SOM) method. This paper discusses the application of SOM method on Human Papillomavirus (HPV) DNA which is the main cause of cervical cancer disease, the most dangerous cancer in developing countries. We use 18 types of HPV DNA-based on the newest complete genome. By using open-source-based program R, clustering process can separate 18 types of HPV into two different clusters. There are two types of HPV in the first cluster while 16 others in the second cluster. The analyzing result of 18 types HPV based on the malignancy of the virus (the difficultness to cure). Two of HPV types the first cluster can be classified as tame HPV, while 16 others in the second cluster are classified as vicious HPV.

  12. Symptoms and Symptom Clusters Identified by Adolescents and Young Adults With Cancer Using a Symptom Heuristics App.

    Science.gov (United States)

    Ameringer, Suzanne; Erickson, Jeanne M; Macpherson, Catherine Fiona; Stegenga, Kristin; Linder, Lauri A

    2015-12-01

    Adolescents and young adults (AYAs) with cancer experience multiple distressing symptoms during treatment. Because the typical approach to symptom assessment does not easily reflect the symptom experience of individuals, alternative approaches to enhancing communication between the patient and provider are needed. We developed an iPad-based application that uses a heuristic approach to explore AYAs' cancer symptom experiences. In this mixed-methods descriptive study, 72 AYAs (13-29 years old) with cancer receiving myelosuppressive chemotherapy used the Computerized Symptom Capture Tool (C-SCAT) to create images of the symptoms and symptom clusters they experienced from a list of 30 symptoms. They answered open-ended questions within the C-SCAT about the causes of their symptoms and symptom clusters. The images generated through the C-SCAT and accompanying free-text data were analyzed using descriptive, content, and visual analyses. Most participants (n = 70) reported multiple symptoms (M = 8.14). The most frequently reported symptoms were nausea (65.3%), feeling drowsy (55.6%), lack of appetite (55.6%), and lack of energy (55.6%). Forty-six grouped their symptoms into one or more clusters. The most common symptom cluster was nausea/eating problems/appetite problems. Nausea was most frequently named as the priority symptom in a cluster and as a cause of other symptoms. Although common threads were present in the symptoms experienced by AYAs, the graphic images revealed unique perspectives and a range of complexity of symptom relationships, clusters, and causes. Results highlight the need for a tailored approach to symptom management based on how the AYA with cancer perceives his or her symptom experience. © 2015 Wiley Periodicals, Inc.

  13. Commentary: Utilizing Community-Engaged Approaches to Investigate and Address Hmong Women’s Cancer Disparities

    Directory of Open Access Journals (Sweden)

    Shannon M.A. Sparks

    2014-12-01

    Full Text Available Cancer is a growing concern for women in the Hmong community. Hmong women experience poor health outcomes for both cervical and breast cancer, largely due to low rates of screening and resultant late-stage at diagnosis. Both breast and cervical cancer screening are complicated by a multitude of social, cultural and environmental factors which influence health care decision-making and can otherwise serve to restrict access. We argue that community-engaged research, an orientation which prioritizes collaborative, equitable partnerships and community voice in identifying both problems and solutions, can be a valuable approach to helping address cancer health disparities for Hmong women. Using the Milwaukee-based “Healthy Hmong Women” project as a case example, we detail how the community-engaged approach implemented by the project partners was critical in identifying factors contributing to Hmong cancer disparities and appropriate interventions, as well as the overall acceptance and success of the project. Specifically, we discuss how this approach: (1 promoted community investment and ownership in the project; (2 facilitated the integration of local perspectives and experiences; (3 built capacity to address cancer screening disparities; (4 facilitated the creation of interventions targeting multiple ecological levels; and (5 framed the community as the foundation and driver of positive change.

  14. NOVEL CONTEXT-AWARE CLUSTERING WITH HIERARCHICAL ADDRESSING (CCHA) FOR THE INTERNET OF THINGS (IoT)

    DEFF Research Database (Denmark)

    Mahalle, Parikshit N.; Prasad, Neeli R.; Prasad, Ramjee

    2013-01-01

    As computing technology becomes more tightly coupled into dynamic and mobile world of the Internet of Things (IoT), security mechanism becomes more stringent, less flexible and intrusive. Scalability issue in the IoT makes Identity Management (IdM) of ubiquitous things more challenging. Forming ad......-hoc network, interaction between these nomadic devices to provide seamless service extend the need of new identi-ties to the things, addressing and IdM in the IoT. New identities and identifier format to alleviate the perfor-mance issue is introduced in this paper. This paper pre-sents novel Context......-aware Clustering with Hierarchical Addressing (CCHA) scheme for the things with new identifier format. Simulation results shows that CCHA achieves better performance with less energy expendi-ture, less end-to-end delay and more throughput. Results also show that CCHA significantly reduces the failure probability...

  15. Association of Inflammatory Cytokines With the Symptom Cluster of Pain, Fatigue, Depression, and Sleep Disturbance in Chinese Patients With Cancer.

    Science.gov (United States)

    Ji, Yan-Bo; Bo, Chun-Lu; Xue, Xiu-Juan; Weng, En-Ming; Gao, Guang-Chao; Dai, Bei-Bei; Ding, Kai-Wen; Xu, Cui-Ping

    2017-12-01

    Pain, fatigue, depression, and sleep disturbance are common in patients with cancer and usually co-occur as a symptom cluster. However, the mechanism underlying this symptom cluster is unclear. This study aimed to identify subgroups of cluster symptoms, compare demographic and clinical characteristics between subgroups, and examine the associations between inflammatory cytokines and cluster symptoms. Participants were 170 Chinese inpatients with cancer from two tertiary hospitals. Inflammatory markers including interleukin-6 (IL-6), interleukin-1 receptor antagonist, and tumor necrosis factor alpha were measured. Intergroup differences and associations of inflammatory cytokines with the cluster symptoms were examined with one-way analyses of variance and logistic regression. Based on cluster analysis, participants were categorized into Subgroup 1 (all low symptoms), Subgroup 2 (low pain and moderate fatigue), or Subgroup 3 (moderate-to-high on all symptoms). The three subgroups differed significantly in Eastern Cooperative Oncology Group (ECOG) performance status, sex, residence, current treatment, education, economic status, and inflammatory cytokines levels (all P cluster symptoms in cancer patients. Clinicians should identify patients at risk for more severe symptoms and formulate novel target interventions to improve symptom management. Copyright © 2017. Published by Elsevier Inc.

  16. Case-control geographic clustering for residential histories accounting for risk factors and covariates

    Science.gov (United States)

    2006-01-01

    Background Methods for analyzing space-time variation in risk in case-control studies typically ignore residential mobility. We develop an approach for analyzing case-control data for mobile individuals and apply it to study bladder cancer in 11 counties in southeastern Michigan. At this time data collection is incomplete and no inferences should be drawn – we analyze these data to demonstrate the novel methods. Global, local and focused clustering of residential histories for 219 cases and 437 controls is quantified using time-dependent nearest neighbor relationships. Business address histories for 268 industries that release known or suspected bladder cancer carcinogens are analyzed. A logistic model accounting for smoking, gender, age, race and education specifies the probability of being a case, and is incorporated into the cluster randomization procedures. Sensitivity of clustering to definition of the proximity metric is assessed for 1 to 75 k nearest neighbors. Results Global clustering is partly explained by the covariates but remains statistically significant at 12 of the 14 levels of k considered. After accounting for the covariates 26 Local clusters are found in Lapeer, Ingham, Oakland and Jackson counties, with the clusters in Ingham and Oakland counties appearing in 1950 and persisting to the present. Statistically significant focused clusters are found about the business address histories of 22 industries located in Oakland (19 clusters), Ingham (2) and Jackson (1) counties. Clusters in central and southeastern Oakland County appear in the 1930's and persist to the present day. Conclusion These methods provide a systematic approach for evaluating a series of increasingly realistic alternative hypotheses regarding the sources of excess risk. So long as selection of cases and controls is population-based and not geographically biased, these tools can provide insights into geographic risk factors that were not specifically assessed in the case

  17. Case-control geographic clustering for residential histories accounting for risk factors and covariates

    Directory of Open Access Journals (Sweden)

    Goovaerts Pierre

    2006-08-01

    Full Text Available Abstract Background Methods for analyzing space-time variation in risk in case-control studies typically ignore residential mobility. We develop an approach for analyzing case-control data for mobile individuals and apply it to study bladder cancer in 11 counties in southeastern Michigan. At this time data collection is incomplete and no inferences should be drawn – we analyze these data to demonstrate the novel methods. Global, local and focused clustering of residential histories for 219 cases and 437 controls is quantified using time-dependent nearest neighbor relationships. Business address histories for 268 industries that release known or suspected bladder cancer carcinogens are analyzed. A logistic model accounting for smoking, gender, age, race and education specifies the probability of being a case, and is incorporated into the cluster randomization procedures. Sensitivity of clustering to definition of the proximity metric is assessed for 1 to 75 k nearest neighbors. Results Global clustering is partly explained by the covariates but remains statistically significant at 12 of the 14 levels of k considered. After accounting for the covariates 26 Local clusters are found in Lapeer, Ingham, Oakland and Jackson counties, with the clusters in Ingham and Oakland counties appearing in 1950 and persisting to the present. Statistically significant focused clusters are found about the business address histories of 22 industries located in Oakland (19 clusters, Ingham (2 and Jackson (1 counties. Clusters in central and southeastern Oakland County appear in the 1930's and persist to the present day. Conclusion These methods provide a systematic approach for evaluating a series of increasingly realistic alternative hypotheses regarding the sources of excess risk. So long as selection of cases and controls is population-based and not geographically biased, these tools can provide insights into geographic risk factors that were not specifically

  18. Symptom clusters of ovarian cancer patients undergoing chemotherapy, and their emotional status and quality of life.

    Science.gov (United States)

    Hwang, Kyung-Hye; Cho, Ok-Hee; Yoo, Yang-Sook

    2016-04-01

    We conducted a descriptive study to identify the symptoms, emotional status, and quality of life experienced by hospitalized ovarian cancer patients undergoing chemotherapy, and influencing the factors of symptom clusters on their quality of life. A total of 192 patients who had been diagnosed with ovarian cancer and received adjuvant chemotherapy after surgery more than once from 2 university hospitals with over 800 beds located in the Seoul and Gyeonggi areas of South Korea were included in this study. Using a structured questionnaire, the symptoms, emotional status, and quality of life by these patients were investigated from May 2012 to June 2013. We identified the following 7 symptom clusters among ovarian cancer patients undergoing chemotherapy: psychological distress, fatigue-pain, abdominal discomfort, flu-like symptoms, fluid accumulation, and peripheral neuropathy. Patients with a high level of anxiety or depression experienced all symptoms at a higher level, and the 7 symptom clusters influenced all aspects of the patients' quality of life. This study provides to need interventions for the quality of life of ovarian cancer patients need to include the management of not only the physical symptoms and treatment-related side effects, but also the changes in their emotional status and daily lives. Copyright © 2015 Elsevier Ltd. All rights reserved.

  19. Providing palliative care to patients with cancer: Addressing the needs in Kenya

    Directory of Open Access Journals (Sweden)

    Pam Malloy

    2017-01-01

    Full Text Available Cancer is the third highest cause of death in Kenya, preceded by infectious and cardiovascular diseases, and in most cases, diagnosed in later stages. Nurses are the primary caregivers, assessing and managing these patients in the clinic, in inpatient settings, and in rural and remote communities. While cancer rates remain high, the burden to the patient, the caregiver, and society as a whole continues to rise. Kenya's poverty complicates cancer even further. Many Kenyans are unaware of cancer's signs and symptoms, and limited diagnostic and treatment centers are available. Despite these barriers, there is still hope and help for those in Kenya, who suffer from cancer. The World Health Organization has stated that palliative care is a basic human right and nurses providing this care in Kenya are making efforts to support cancer patients' ongoing needs, in order to promote compassionate palliative care and prevent suffering. The purpose of this paper is to address the palliative care needs of patients with cancer in Kenya by providing education to nurses and influencing health-care policy and education at micro and macro levels. A case study weaved throughout will highlight these issues.

  20. Spatial analyses identify the geographic source of patients at a National Cancer Institute Comprehensive Cancer Center.

    Science.gov (United States)

    Su, Shu-Chih; Kanarek, Norma; Fox, Michael G; Guseynova, Alla; Crow, Shirley; Piantadosi, Steven

    2010-02-01

    We examined the geographic distribution of patients to better understand the service area of the Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, a designated National Cancer Institute (NCI) comprehensive cancer center located in an urban center. Like most NCI cancer centers, the Sidney Kimmel Comprehensive Cancer Center serves a population beyond city limits. Urban cancer centers are expected to serve their immediate neighborhoods and to address disparities in access to specialty care. Our purpose was to learn the extent and nature of the cancer center service area. Statistical clustering of patient residence in the continental United States was assessed for all patients and by gender, cancer site, and race using SaTScan. Primary clusters detected for all cases and demographically and tumor-defined subpopulations were centered at Baltimore City and consisted of adjacent counties in Delaware, Pennsylvania, Virginia, West Virginia, New Jersey and New York, and the District of Columbia. Primary clusters varied in size by race, gender, and cancer site. Spatial analysis can provide insights into the populations served by urban cancer centers, assess centers' performance relative to their communities, and aid in developing a cancer center business plan that recognizes strengths, regional utility, and referral patterns. Today, 62 NCI cancer centers serve a quarter of the U.S. population in their immediate communities. From the Baltimore experience, we might project that the population served by these centers is actually more extensive and varies by patient characteristics, cancer site, and probably cancer center services offered.

  1. Prediction of chemotherapeutic response in bladder cancer using K-means clustering of dynamic contrast-enhanced (DCE)-MRI pharmacokinetic parameters.

    Science.gov (United States)

    Nguyen, Huyen T; Jia, Guang; Shah, Zarine K; Pohar, Kamal; Mortazavi, Amir; Zynger, Debra L; Wei, Lai; Yang, Xiangyu; Clark, Daniel; Knopp, Michael V

    2015-05-01

    To apply k-means clustering of two pharmacokinetic parameters derived from 3T dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to predict the chemotherapeutic response in bladder cancer at the mid-cycle timepoint. With the predetermined number of three clusters, k-means clustering was performed on nondimensionalized Amp and kep estimates of each bladder tumor. Three cluster volume fractions (VFs) were calculated for each tumor at baseline and mid-cycle. The changes of three cluster VFs from baseline to mid-cycle were correlated with the tumor's chemotherapeutic response. Receiver-operating-characteristics curve analysis was used to evaluate the performance of each cluster VF change as a biomarker of chemotherapeutic response in bladder cancer. The k-means clustering partitioned each bladder tumor into cluster 1 (low kep and low Amp), cluster 2 (low kep and high Amp), cluster 3 (high kep and low Amp). The changes of all three cluster VFs were found to be associated with bladder tumor response to chemotherapy. The VF change of cluster 2 presented with the highest area-under-the-curve value (0.96) and the highest sensitivity/specificity/accuracy (96%/100%/97%) with a selected cutoff value. The k-means clustering of the two DCE-MRI pharmacokinetic parameters can characterize the complex microcirculatory changes within a bladder tumor to enable early prediction of the tumor's chemotherapeutic response. © 2014 Wiley Periodicals, Inc.

  2. 18F-FDG PET radiomics approaches: comparing and clustering features in cervical cancer.

    Science.gov (United States)

    Tsujikawa, Tetsuya; Rahman, Tasmiah; Yamamoto, Makoto; Yamada, Shizuka; Tsuyoshi, Hideaki; Kiyono, Yasushi; Kimura, Hirohiko; Yoshida, Yoshio; Okazawa, Hidehiko

    2017-11-01

    The aims of our study were to find the textural features on 18 F-FDG PET/CT which reflect the different histological architectures between cervical cancer subtypes and to make a visual assessment of the association between 18 F-FDG PET textural features in cervical cancer. Eighty-three cervical cancer patients [62 squamous cell carcinomas (SCCs) and 21 non-SCCs (NSCCs)] who had undergone pretreatment 18 F-FDG PET/CT were enrolled. A texture analysis was performed on PET/CT images, from which 18 PET radiomics features were extracted including first-order features such as standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG), second- and high-order textural features using SUV histogram, normalized gray-level co-occurrence matrix (NGLCM), and neighborhood gray-tone difference matrix, respectively. These features were compared between SCC and NSCC using a Bonferroni adjusted P value threshold of 0.0028 (0.05/18). To assess the association between PET features, a heat map analysis with hierarchical clustering, one of the radiomics approaches, was performed. Among 18 PET features, correlation, a second-order textural feature derived from NGLCM, was a stable parameter and it was the only feature which showed a robust trend toward significant difference between SCC and NSCC. Cervical SCC showed a higher correlation (0.70 ± 0.07) than NSCC (0.64 ± 0.07, P = 0.0030). The other PET features did not show any significant differences between SCC and NSCC. A higher correlation in SCC might reflect higher structural integrity and stronger spatial/linear relationship of cancer cells compared with NSCC. A heat map with a PET feature dendrogram clearly showed 5 distinct clusters, where correlation belonged to a cluster including MTV and TLG. However, the association between correlation and MTV/TLG was not strong. Correlation was a relatively independent PET feature in cervical cancer. 18 F-FDG PET textural features might reflect the

  3. Cancer Clusters

    Science.gov (United States)

    ... and number of cases of each type, the age of the people with cancer, and the area and time period over which the cancers were diagnosed. They also ask about specific environmental hazards or concerns in the affected area. If the review of ...

  4. Pharmacokinetic analysis and k-means clustering of DCEMR images for radiotherapy outcome prediction of advanced cervical cancers.

    Science.gov (United States)

    Andersen, Erlend K F; Kristensen, Gunnar B; Lyng, Heidi; Malinen, Eirik

    2011-08-01

    Pharmacokinetic analysis of dynamic contrast enhanced magnetic resonance images (DCEMRI) allows for quantitative characterization of vascular properties of tumors. The aim of this study is twofold, first to determine if tumor regions with similar vascularization could be labeled by clustering methods, second to determine if the identified regions can be associated with local cancer relapse. Eighty-one patients with locally advanced cervical cancer treated with chemoradiotherapy underwent DCEMRI with Gd-DTPA prior to external beam radiotherapy. The median follow-up time after treatment was four years, in which nine patients had primary tumor relapse. By fitting a pharmacokinetic two-compartment model function to the temporal contrast enhancement in the tumor, two pharmacokinetic parameters, K(trans) and ύ(e), were estimated voxel by voxel from the DCEMR-images. Intratumoral regions with similar vascularization were identified by k-means clustering of the two pharmacokinetic parameter estimates over all patients. The volume fraction of each cluster was used to evaluate the prognostic value of the clusters. Three clusters provided a sufficient reduction of the cluster variance to label different vascular properties within the tumors. The corresponding median volume fraction of each cluster was 38%, 46% and 10%. The second cluster was significantly associated with primary tumor control in a log-rank survival test (p-value: 0.042), showing a decreased risk of treatment failure for patients with high volume fraction of voxels. Intratumoral regions showing similar vascular properties could successfully be labeled in three distinct clusters and the volume fraction of one cluster region was associated with primary tumor control.

  5. Pharmacokinetic analysis and k-means clustering of DCEMR images for radiotherapy outcome prediction of advanced cervical cancers

    International Nuclear Information System (INIS)

    Andersen, Erlend K. F.; Kristensen, Gunnar B.; Lyng, Heidi; Malinen, Eirik

    2011-01-01

    Introduction. Pharmacokinetic analysis of dynamic contrast enhanced magnetic resonance images (DCEMRI) allows for quantitative characterization of vascular properties of tumors. The aim of this study is twofold, first to determine if tumor regions with similar vascularization could be labeled by clustering methods, second to determine if the identified regions can be associated with local cancer relapse. Materials and methods. Eighty-one patients with locally advanced cervical cancer treated with chemoradiotherapy underwent DCEMRI with Gd-DTPA prior to external beam radiotherapy. The median follow-up time after treatment was four years, in which nine patients had primary tumor relapse. By fitting a pharmacokinetic two-compartment model function to the temporal contrast enhancement in the tumor, two pharmacokinetic parameters, K trans and u e , were estimated voxel by voxel from the DCEMR-images. Intratumoral regions with similar vascularization were identified by k-means clustering of the two pharmacokinetic parameter estimates over all patients. The volume fraction of each cluster was used to evaluate the prognostic value of the clusters. Results. Three clusters provided a sufficient reduction of the cluster variance to label different vascular properties within the tumors. The corresponding median volume fraction of each cluster was 38%, 46% and 10%. The second cluster was significantly associated with primary tumor control in a log-rank survival test (p-value: 0.042), showing a decreased risk of treatment failure for patients with high volume fraction of voxels. Conclusions. Intratumoral regions showing similar vascular properties could successfully be labeled in three distinct clusters and the volume fraction of one cluster region was associated with primary tumor control

  6. Pharmacokinetic analysis and k-means clustering of DCEMR images for radiotherapy outcome prediction of advanced cervical cancers

    Energy Technology Data Exchange (ETDEWEB)

    Andersen, Erlend K. F. (Dept. of Medical Physics, The Norwegian Radium Hospital, Oslo Univ. Hospital, Oslo (Norway)), e-mail: eirik.malinen@fys.uio.no; Kristensen, Gunnar B. (Section for Gynaecological Oncology, The Norwegian Radium Hospital, Oslo Univ. Hospital, Oslo (Norway)); Lyng, Heidi (Dept. of Radiation Biology, The Norwegian Radium Hospital, Oslo Univ. Hospital, Oslo (Norway)); Malinen, Eirik (Dept. of Medical Physics, The Norwegian Radium Hospital, Oslo Univ. Hospital, Oslo (Norway); Dept. of Physics, Univ. of Oslo, Oslo (Norway))

    2011-08-15

    Introduction. Pharmacokinetic analysis of dynamic contrast enhanced magnetic resonance images (DCEMRI) allows for quantitative characterization of vascular properties of tumors. The aim of this study is twofold, first to determine if tumor regions with similar vascularization could be labeled by clustering methods, second to determine if the identified regions can be associated with local cancer relapse. Materials and methods. Eighty-one patients with locally advanced cervical cancer treated with chemoradiotherapy underwent DCEMRI with Gd-DTPA prior to external beam radiotherapy. The median follow-up time after treatment was four years, in which nine patients had primary tumor relapse. By fitting a pharmacokinetic two-compartment model function to the temporal contrast enhancement in the tumor, two pharmacokinetic parameters, Ktrans and u{sub e}, were estimated voxel by voxel from the DCEMR-images. Intratumoral regions with similar vascularization were identified by k-means clustering of the two pharmacokinetic parameter estimates over all patients. The volume fraction of each cluster was used to evaluate the prognostic value of the clusters. Results. Three clusters provided a sufficient reduction of the cluster variance to label different vascular properties within the tumors. The corresponding median volume fraction of each cluster was 38%, 46% and 10%. The second cluster was significantly associated with primary tumor control in a log-rank survival test (p-value: 0.042), showing a decreased risk of treatment failure for patients with high volume fraction of voxels. Conclusions. Intratumoral regions showing similar vascular properties could successfully be labeled in three distinct clusters and the volume fraction of one cluster region was associated with primary tumor control

  7. The spatial evaluation of neighborhood clusters of birth defects

    Energy Technology Data Exchange (ETDEWEB)

    Frisch, J.D.

    1990-04-16

    Spatial statistics have recently been applied in epidemiology to evaluate clusters of cancer and birth defects. Their use requires a comparison population, drawn from the population at risk for disease, that may not always be readily available. In this dissertation the plausibility of using data on all birth defects, available from birth defects registries, as a surrogate for the spatial distribution of all live births in the analysis of clusters is assessed. Three spatial statistics that have been applied in epidemiologic investigations of clusters, nearest neighbor distance, average interpoint distance, and average distance to a fixed point, were evaluated by computer simulation for their properties in a unit square, and in a zip code region. Comparison of spatial distributions of live births and birth defects was performed by drawing samples of live births and birth defects from Santa Clara County, determining the street address at birth, geocoding this address and evaluating the resultant maps using various statistical techniques. The proposed method was then demonstrated on a previously confirmed cluster of oral cleft cases. All live births for the neighborhood were geocoded, as were all birth defects. Evaluation of this cluster using the nearest neighbor and average interpoint distance statistics was performed using randomization techniques with both the live births population and the birth defect population as comparison groups. 113 refs., 36 figs., 16 tabs.

  8. An analysis of content in comprehensive cancer control plans that address chronic hepatitis B and C virus infections as major risk factors for liver cancer.

    Science.gov (United States)

    Momin, Behnoosh; Richardson, Lisa

    2012-08-01

    Chronic hepatitis B and hepatitis C virus (HBV and HCV) infections are among the leading causes of preventable death worldwide. Chronic viral hepatitis is the cause of most primary liver cancer, which is the third leading cause of cancer deaths globally and the ninth leading cause of cancer deaths in the United States. The extent to which comprehensive cancer control (CCC) programs in states, tribal governments and organizations, territories, and Pacific Island jurisdictions address chronic hepatitis B and/or hepatitis C infections as risk factors for liver cancer or recommend interventions for liver cancer prevention in their CCC plans remains unknown. We searched CCC plans for this information using the search tool at http://www.cdc.gov/cancer/ncccp/ to access the content of plans for this information. A combination of key search terms including "liver cancer", "hepatitis", "chronic alcohol", and "alcohol abuse" were used to identify potential content regarding liver cancer risk factors and prevention. Relevant content was abstracted for further review and classification. Of 66 (Although CDC funds 65 programs, one of the Pacific Island Jurisdiction grantees is the Federated States of Micronesia (FSM). This national program supports four FSM states, each of which submits a cancer plan to CDC for a total of 69 plans. During this time period, 66 plans were available on the website.) CCC plans, 27% (n = 18) addressed liver cancer using the above-mentioned search terms. In the 23 plans that addressed HBV and/or HCV, there were 25 goals, objectives, strategies, and outcomes aimed at reducing the incidence or prevalence of HBV and/or HCV infection. While nearly a third of CCC programs identify at least one goal, objective, strategy, outcome, or prevention program to reduce cancer burden in their CCC plans, few plans discuss specific actions needed to reduce the burden of liver cancer.

  9. Distinct profile of vascular progenitor attachment to extracellular matrix proteins in cancer patients.

    Science.gov (United States)

    Labonté, Laura; Li, Yuhua; Addison, Christina L; Brand, Marjorie; Javidnia, Hedyeh; Corsten, Martin; Burns, Kevin; Allan, David S

    2012-04-01

    Vascular progenitor cells (VPCs) facilitate angiogenesis and initiate vascular repair by homing in on sites of damage and adhering to extracellular matrix (ECM) proteins. VPCs also contribute to tumor angiogenesis and induce angiogenic switching in sites of metastatic cancer. In this study, the binding of attaching cells in VPC clusters that form in vitro on specific ECM proteins was investigated. VPC cluster assays were performed in vitro on ECM proteins enriched in cancer cells and in remodelling tissue. Profiles of VPC clusters from patients with cancer were compared to healthy controls. The role of VEGF and integrin-specific binding of angiogenic attaching cells was addressed. VPC clusters from cancer patients were markedly increased on fibronectin relative to other ECM proteins tested, in contrast to VPC clusters from control subjects, which formed preferentially on laminin. Specific integrin-mediated binding of attaching cells in VPC clusters was matrix protein-dependent. Furthermore, cancer patients had elevated plasma VEGF levels compared to healthy controls and VEGF facilitated preferential VPC cluster formation on fibronectin. Incubating cells from healthy controls with VEGF induced a switch from the 'healthy' VPC binding profile to the profile observed in cancer patients with a marked increase in VPC cluster formation on fibronectin. The ECM proteins laminin and fibronectin support VPC cluster formation via specific integrins on attaching cells and can facilitate patterns of VPC cluster formation that are distinct in cancer patients. Larger studies, however, are needed to gain insight on how tumor angiogenesis may differ from normal repair processes.

  10. Multifunctional fluorescent iron quantum clusters for non-invasive radiofrequency ablationof cancer cells.

    Science.gov (United States)

    Jose, Akhila; Surendran, Mrudula; Fazal, Sajid; Prasanth, Bindhu-Paul; Menon, Deepthy

    2018-05-01

    This work reports the potential of iron quantum clusters (FeQCs) as a hyperthermia agent for cancer, by testing its in-vitro response to shortwave (MHz range), radiofrequency (RF) waves non-invasively. Stable, fluorescent FeQCs of size ∼1 nm prepared by facile aqueous chemistry from endogenous protein haemoglobin were found to give a high thermal response, with a ΔT ∼50 °C at concentrationsas low as165 μg/mL. The as-prepared nanoclusters purified by lyophilization as well as dialysis showed a concentration, power and time-dependent RF response, with the lyophilized FeQCs exhibiting pronounced heating effects. FeQCs were found to be cytocompatible to NIH-3T3 fibroblast and 4T1 cancer cells treated at concentrations upto 1000 μg/mL for 24 h. Upon incubation with FeQCs and exposure to RF waves, significant cancer cell death was observed which proves its therapeutic ability. The fluorescent ability of the clusters could additionally be utilized for imaging cancer cells upon excitation at ∼450 nm. Further, to demonstrate the feasibility of imparting additional functionality such as drug/biomolecule/dye loading to FeQCs, they were self assembled with cationic polymers to form nanoparticles. Self assembly did not alter the RF heating potential of FeQCs and additionally enhanced its fluorescence. The multifunctional fluorescent FeQCs therefore show good promise as a novel therapeutic agent for RF hyperthermia and drug loading. Copyright © 2018 Elsevier B.V. All rights reserved.

  11. Role of DNA methylation in miR-200c/141 cluster silencing in invasive breast cancer cells

    Directory of Open Access Journals (Sweden)

    Wernet Peter

    2010-08-01

    Full Text Available Abstract Background The miR-200c/141 cluster has recently been implicated in the epithelial to mesenchymal transition (EMT process. The expression of these two miRNAs is inversely correlated with tumorigenicity and invasiveness in several human cancers. The role of these miRNAs in cancer progression is based in part on their capacity to target the EMT activators ZEB1 and ZEB2, two transcription factors, which in turn repress expression of E-cadherin. Little is known about the regulation of the mir200c/141 cluster, whose targeting has been proposed as a promising new therapy for the most aggressive tumors. Findings We show that the miR-200c/141 cluster is repressed by DNA methylation of a CpG island located in the promoter region of these miRNAs. Whereas in vitro methylation of the miR-200c/141 promoter led to shutdown of promoter activity, treatment with a demethylating agent caused transcriptional reactivation in breast cancer cells formerly lacking expression of miR-200c and miR-141. More importantly, we observed that DNA methylation of the identified miR-200c/141 promoter was tightly correlated with phenotype and the invasive capacity in a panel of 8 human breast cancer cell lines. In line with this, in vitro induction of EMT by ectopic expression of the EMT transcription factor Twist in human immortalized mammary epithelial cells (HMLE was accompanied by increased DNA methylation and concomitant repression of the miR-200c/141 locus. Conclusions The present study demonstrates that expression of the miR-200c/141 cluster is regulated by DNA methylation, suggesting epigenetic regulation of this miRNA locus in aggressive breast cancer cell lines as well as untransformed mammary epithelial cells. This epigenetic silencing mechanism might represent a novel component of the regulatory circuit for the maintenance of EMT programs in cancer and normal cells.

  12. Role of DNA methylation in miR-200c/141 cluster silencing in invasive breast cancer cells.

    Science.gov (United States)

    Neves, Rui; Scheel, Christina; Weinhold, Sandra; Honisch, Ellen; Iwaniuk, Katharina M; Trompeter, Hans-Ingo; Niederacher, Dieter; Wernet, Peter; Santourlidis, Simeon; Uhrberg, Markus

    2010-08-03

    The miR-200c/141 cluster has recently been implicated in the epithelial to mesenchymal transition (EMT) process. The expression of these two miRNAs is inversely correlated with tumorigenicity and invasiveness in several human cancers. The role of these miRNAs in cancer progression is based in part on their capacity to target the EMT activators ZEB1 and ZEB2, two transcription factors, which in turn repress expression of E-cadherin. Little is known about the regulation of the mir200c/141 cluster, whose targeting has been proposed as a promising new therapy for the most aggressive tumors. We show that the miR-200c/141 cluster is repressed by DNA methylation of a CpG island located in the promoter region of these miRNAs. Whereas in vitro methylation of the miR-200c/141 promoter led to shutdown of promoter activity, treatment with a demethylating agent caused transcriptional reactivation in breast cancer cells formerly lacking expression of miR-200c and miR-141. More importantly, we observed that DNA methylation of the identified miR-200c/141 promoter was tightly correlated with phenotype and the invasive capacity in a panel of 8 human breast cancer cell lines. In line with this, in vitro induction of EMT by ectopic expression of the EMT transcription factor Twist in human immortalized mammary epithelial cells (HMLE) was accompanied by increased DNA methylation and concomitant repression of the miR-200c/141 locus. The present study demonstrates that expression of the miR-200c/141 cluster is regulated by DNA methylation, suggesting epigenetic regulation of this miRNA locus in aggressive breast cancer cell lines as well as untransformed mammary epithelial cells. This epigenetic silencing mechanism might represent a novel component of the regulatory circuit for the maintenance of EMT programs in cancer and normal cells.

  13. 1842676957299765Latent class cluster analysis to understand heterogeneity in prostate cancer treatment utilities

    Directory of Open Access Journals (Sweden)

    Meghani Salimah

    2009-01-01

    Full Text Available Abstract Background Men with prostate cancer are often challenged to choose between conservative management and a range of available treatment options each carrying varying risks and benefits. The trade-offs are between an improved life-expectancy with treatment accompanied by important risks such as urinary incontinence and erectile dysfunction. Previous studies of preference elicitation for prostate cancer treatment have found considerable heterogeneity in individuals' preferences for health states given similar treatments and clinical risks. Methods Using latent class mixture model (LCA, we first sought to understand if there are unique patterns of heterogeneity or subgroups of individuals based on their prostate cancer treatment utilities (calculated time trade-off utilities for various health states and if such unique subgroups exist, what demographic and urological variables may predict membership in these subgroups. Results The sample (N = 244 included men with prostate cancer (n = 188 and men at-risk for disease (n = 56. The sample was predominantly white (77%, with mean age of 60 years (SD ± 9.5. Most (85.9% were married or living with a significant other. Using LCA, a three class solution yielded the best model evidenced by the smallest Bayesian Information Criterion (BIC, substantial reduction in BIC from a 2-class solution, and Lo-Mendell-Rubin significance of < .001. The three identified clusters were named high-traders (n = 31, low-traders (n = 116, and no-traders (n = 97. High-traders were more likely to trade survival time associated with treatment to avoid potential risks of treatment. Low-traders were less likely to trade survival time and accepted risks of treatment. The no-traders were likely to make no trade-offs in any direction favouring the status quo. There was significant difference among the clusters in the importance of sexual activity (Pearson's χ2 = 16.55, P = 0.002; Goodman and Kruskal tau = 0.039, P < 0.001. In

  14. Barriers to mental health service use and preferences for addressing emotional concerns among lung cancer patients.

    Science.gov (United States)

    Mosher, Catherine E; Winger, Joseph G; Hanna, Nasser; Jalal, Shadia I; Fakiris, Achilles J; Einhorn, Lawrence H; Birdas, Thomas J; Kesler, Kenneth A; Champion, Victoria L

    2014-07-01

    This study examined barriers to mental health service use and preferences for addressing emotional concerns among lung cancer patients (N=165) at two medical centers in the Midwestern United States. Lung cancer patients completed an assessment of anxiety and depressive symptoms, mental health service use, barriers to using these services, and preferences for addressing emotional concerns. Only 45% of distressed patients received mental health care since their lung cancer diagnosis. The most prevalent patient-reported barriers to mental health service use among non-users of these services (n=110) included the desire to independently manage emotional concerns (58%) and inadequate knowledge of services (19%). In addition, 57% of distressed patients who did not access mental health services did not perceive the need for help. Seventy-five percent of respondents (123/164) preferred to talk to a primary care physician if they were to have an emotional concern. Preferences for counseling, psychiatric medication, peer support, spiritual care, or independently managing emotional concerns also were endorsed by many patients (range=40-50%). Older age was associated with a lower likelihood of preferring to see a counselor. Findings suggest that many distressed lung cancer patients underuse mental health services and do not perceive the need for such services. Efforts to increase appropriate use of services should address patients' desire for autonomy and lack of awareness of services. Copyright © 2014 John Wiley & Sons, Ltd.

  15. Comprehensive cluster analysis with Transitivity Clustering.

    Science.gov (United States)

    Wittkop, Tobias; Emig, Dorothea; Truss, Anke; Albrecht, Mario; Böcker, Sebastian; Baumbach, Jan

    2011-03-01

    Transitivity Clustering is a method for the partitioning of biological data into groups of similar objects, such as genes, for instance. It provides integrated access to various functions addressing each step of a typical cluster analysis. To facilitate this, Transitivity Clustering is accessible online and offers three user-friendly interfaces: a powerful stand-alone version, a web interface, and a collection of Cytoscape plug-ins. In this paper, we describe three major workflows: (i) protein (super)family detection with Cytoscape, (ii) protein homology detection with incomplete gold standards and (iii) clustering of gene expression data. This protocol guides the user through the most important features of Transitivity Clustering and takes ∼1 h to complete.

  16. Cluster detection methods applied to the Upper Cape Cod cancer data

    Directory of Open Access Journals (Sweden)

    Ozonoff David

    2005-09-01

    Full Text Available Abstract Background A variety of statistical methods have been suggested to assess the degree and/or the location of spatial clustering of disease cases. However, there is relatively little in the literature devoted to comparison and critique of different methods. Most of the available comparative studies rely on simulated data rather than real data sets. Methods We have chosen three methods currently used for examining spatial disease patterns: the M-statistic of Bonetti and Pagano; the Generalized Additive Model (GAM method as applied by Webster; and Kulldorff's spatial scan statistic. We apply these statistics to analyze breast cancer data from the Upper Cape Cancer Incidence Study using three different latency assumptions. Results The three different latency assumptions produced three different spatial patterns of cases and controls. For 20 year latency, all three methods generally concur. However, for 15 year latency and no latency assumptions, the methods produce different results when testing for global clustering. Conclusion The comparative analyses of real data sets by different statistical methods provides insight into directions for further research. We suggest a research program designed around examining real data sets to guide focused investigation of relevant features using simulated data, for the purpose of understanding how to interpret statistical methods applied to epidemiological data with a spatial component.

  17. Addressing Cancer Drug Costs and Value

    Science.gov (United States)

    The President’s Cancer Panel has released its latest report, Promoting Value, Affordability, and Innovation in Cancer Drug Treatment. The report recommends six actions to maximize the value and affordability of cancer drug treatment.

  18. Adolescent Cancer Education (ACE) to increase adolescent and parent cancer awareness and communication: study protocol for a cluster randomised controlled trial.

    Science.gov (United States)

    Kyle, Richard G; Macmillan, Iona; Rauchhaus, Petra; O'Carroll, Ronan; Neal, Richard D; Forbat, Liz; Haw, Sally; Hubbard, Gill

    2013-09-08

    Raising cancer awareness among adolescents has potential to increase their knowledge and confidence in identifying cancer symptoms and seeking timely medical help in adolescence and adulthood. Detecting cancer at an early stage is important because it reduces the risk of dying of some cancers and thereby contributes to improved cancer survival. Adolescents may also play an important role in increasing cancer communication within families. However, there are no randomised controlled trials (RCT) of the effectiveness of school-based educational interventions to increase adolescents' cancer awareness, and little is known about the role of adolescents in the upward diffusion of cancer knowledge to parents/carers. The aim of this study is to determine the effectiveness of a school-based educational intervention to raise adolescent and parent cancer awareness and adolescent-parent cancer communication. The Adolescent Cancer Education (ACE) study is a school-based, cluster RCT. Twenty secondary schools in the area covered by Glasgow City Council will be recruited. Special schools for adolescents whose additional needs cannot be met in mainstream education are excluded. Schools are randomised to receive a presentation delivered by a Teenage Cancer Trust educator in Autumn 2013 (intervention group) or Spring 2014 following completion of six-month follow-up measures (control group). Participants will be students recruited at the end of their first year of secondary education (S1) (age 12 to 13 years) and one parent/carer for each student, of the student's choice. The primary outcome is recognition of cancer symptoms two weeks post-intervention. Secondary outcomes are parents' cancer awareness and adolescent-parent cancer communication. Outcomes will be assessed at baseline (when adolescents are in the final term of S1), two-week, and six-month follow-up (when adolescents are in S2, age 13 to 14 years). Differences in outcomes between trial arms will be tested using

  19. Addressing cancer disparities via community network mobilization and intersectoral partnerships: a social network analysis.

    Directory of Open Access Journals (Sweden)

    Shoba Ramanadhan

    Full Text Available Community mobilization and collaboration among diverse partners are vital components of the effort to reduce and eliminate cancer disparities in the United States. We studied the development and impact of intersectoral connections among the members of the Massachusetts Community Network for Cancer Education, Research, and Training (MassCONECT. As one of the Community Network Program sites funded by the National Cancer Institute, this infrastructure-building initiative utilized principles of Community-based Participatory Research (CBPR to unite community coalitions, researchers, policymakers, and other important stakeholders to address cancer disparities in three Massachusetts communities: Boston, Lawrence, and Worcester. We conducted a cross-sectional, sociometric network analysis four years after the network was formed. A total of 38 of 55 members participated in the study (69% response rate. Over four years of collaboration, the number of intersectoral connections reported by members (intersectoral out-degree increased, as did the extent to which such connections were reported reciprocally (intersectoral reciprocity. We assessed relationships between these markers of intersectoral collaboration and three intermediate outcomes in the effort to reduce and eliminate cancer disparities: delivery of community activities, policy engagement, and grants/publications. We found a positive and statistically significant relationship between intersectoral out-degree and community activities and policy engagement (the relationship was borderline significant for grants/publications. We found a positive and statistically significant relationship between intersectoral reciprocity and community activities and grants/publications (the relationship was borderline significant for policy engagement. The study suggests that intersectoral connections may be important drivers of diverse intermediate outcomes in the effort to reduce and eliminate cancer disparities

  20. Symptom clusters in cancer patients and their relation to EGFR ligand modulation of the circadian axis.

    Science.gov (United States)

    Rich, Tyvin A

    2007-04-01

    Recent studies in chronobiology and the neurosciences have led to rapid growth in our understanding of the molecular biology of the human timekeeping apparatus and the neuroanatomic sites involved in signaling between the "master clock" in the hypothalamus and other parts of the brain. The circadian axis comprises a central clock mechanism and a downstream network of hypothalamic relay stations that modulate arousal, feeding, and sleeping behavior. Communication between the clock and these hypothalamic signaling centers is mediated, in part, by diffusible substances that include ligands of the epidermal growth factor receptor (EGFR). Preclinical studies reveal that EGFR ligands such as transforming growth factor-alpha (TGF-alpha) inhibit hypothalamic signaling of rhythmic behavior; clinical observations show that elevated levels of TGF-alpha are associated with fatigue, flattened circadian rhythms, and loss of appetite in patients with metastatic colorectal cancer. These data support the hypothesis that a symptom cluster of fatigue, appetite loss, and sleep disruption commonly seen in cancer patients may be related to EGFR ligands, released either by the cancer itself or by the host in response to the stress of cancer, and suggest that further examination of their role in the production of symptom clustering is warranted.

  1. Addressing Cancer Disparities Among American Indians through Innovative Technologies and Patient Navigation: The Walking Forward Experience

    Energy Technology Data Exchange (ETDEWEB)

    Petereit, Daniel G. [Department of Oncology, John T. Vucurevich Cancer Care Institute, Rapid City, SD (United States); Department of Human Oncology, University of Wisconsin School of Medicine and Public Health, Madison, WI (United States); Guadagnolo, B. Ashleigh [Department of Radiation Oncology, The University of Texas M.D. Anderson Cancer Center, Houston, TX (United States); Wong, Rosemary; Coleman, C. Norman, E-mail: dpetereit@regionalhealth.com [Radiation Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD (United States)

    2011-06-22

    Purpose/Objective(s): American Indians (AIs) present with more advanced stages of cancer and, therefore, suffer from higher cancer mortality rates compared to non-AIs. Under the National Cancer Institute (NCI) Cancer Disparities Research Partnership (CDRP) Program, we have been researching methods of improving cancer treatment and outcomes since 2002, for AIs in Western South Dakota, through the Walking Forward (WF) Program. Materials/Methods: This program consists of (a) a culturally tailored patient navigation program that facilitated access to innovative clinical trials in conjunction with a comprehensive educational program encouraging screening and early detection, (b), surveys to evaluate barriers to access, (c) clinical trials focusing on reducing treatment length to facilitate enhanced participation using brachytherapy and intensity modulated radiotherapy (IMRT) for breast and prostate cancer, as AIs live a median of 140 miles from the cancer center, and (d) a molecular study (ataxia telangiectasia mutated) to address whether there is a specific profile that increases toxicity risks. Results: We describe the design and implementation of this program, summary of previously published results, and ongoing research to influence stage at presentation. Some of the critical outcomes include the successful implementation of a community-based research program, development of trust within tribal communities, identification of barriers, analysis of nearly 400 navigated cancer patients, clinical trial accrual rate of 10%, and total enrollment of nearly 2,500 AIs on WF research studies. Conclusion: This NCI funded pilot program has achieved some initial measures of success. A research infrastructure has been created in a community setting to address new research questions and interventions. Efforts underway to promote cancer education and screening are presented, as well as applications of the lessons learned to other health disparity populations – both nationally and

  2. Addressing Cancer Disparities Among American Indians through Innovative Technologies and Patient Navigation: The Walking Forward Experience

    International Nuclear Information System (INIS)

    Petereit, Daniel G.; Guadagnolo, B. Ashleigh; Wong, Rosemary; Coleman, C. Norman

    2011-01-01

    Purpose/Objective(s): American Indians (AIs) present with more advanced stages of cancer and, therefore, suffer from higher cancer mortality rates compared to non-AIs. Under the National Cancer Institute (NCI) Cancer Disparities Research Partnership (CDRP) Program, we have been researching methods of improving cancer treatment and outcomes since 2002, for AIs in Western South Dakota, through the Walking Forward (WF) Program. Materials/Methods: This program consists of (a) a culturally tailored patient navigation program that facilitated access to innovative clinical trials in conjunction with a comprehensive educational program encouraging screening and early detection, (b), surveys to evaluate barriers to access, (c) clinical trials focusing on reducing treatment length to facilitate enhanced participation using brachytherapy and intensity modulated radiotherapy (IMRT) for breast and prostate cancer, as AIs live a median of 140 miles from the cancer center, and (d) a molecular study (ataxia telangiectasia mutated) to address whether there is a specific profile that increases toxicity risks. Results: We describe the design and implementation of this program, summary of previously published results, and ongoing research to influence stage at presentation. Some of the critical outcomes include the successful implementation of a community-based research program, development of trust within tribal communities, identification of barriers, analysis of nearly 400 navigated cancer patients, clinical trial accrual rate of 10%, and total enrollment of nearly 2,500 AIs on WF research studies. Conclusion: This NCI funded pilot program has achieved some initial measures of success. A research infrastructure has been created in a community setting to address new research questions and interventions. Efforts underway to promote cancer education and screening are presented, as well as applications of the lessons learned to other health disparity populations – both nationally and

  3. Testicular cancer: addressing the psychosexual issues.

    LENUS (Irish Health Repository)

    Moore, Annamarie

    2012-01-31

    Testicular cancer is the most common malignancy in men aged 15-35 years and predominantly occurs at a time in a man\\'s life when important decisions about marriage, starting a family and a professional career are being made. While treatments for testicular cancer are very successful, they can have a major impact on the person\\'s sexuality and sense of self. The focus of this article is on exploring the impact of cancer treatments for testicular cancer on men\\'s sexuality and how nurses can respond to their concerns in a sensitive and informed manner.

  4. Bayesian versus frequentist statistical inference for investigating a one-off cancer cluster reported to a health department

    Directory of Open Access Journals (Sweden)

    Wills Rachael A

    2009-05-01

    Full Text Available Abstract Background The problem of silent multiple comparisons is one of the most difficult statistical problems faced by scientists. It is a particular problem for investigating a one-off cancer cluster reported to a health department because any one of hundreds, or possibly thousands, of neighbourhoods, schools, or workplaces could have reported a cluster, which could have been for any one of several types of cancer or any one of several time periods. Methods This paper contrasts the frequentist approach with a Bayesian approach for dealing with silent multiple comparisons in the context of a one-off cluster reported to a health department. Two published cluster investigations were re-analysed using the Dunn-Sidak method to adjust frequentist p-values and confidence intervals for silent multiple comparisons. Bayesian methods were based on the Gamma distribution. Results Bayesian analysis with non-informative priors produced results similar to the frequentist analysis, and suggested that both clusters represented a statistical excess. In the frequentist framework, the statistical significance of both clusters was extremely sensitive to the number of silent multiple comparisons, which can only ever be a subjective "guesstimate". The Bayesian approach is also subjective: whether there is an apparent statistical excess depends on the specified prior. Conclusion In cluster investigations, the frequentist approach is just as subjective as the Bayesian approach, but the Bayesian approach is less ambitious in that it treats the analysis as a synthesis of data and personal judgements (possibly poor ones, rather than objective reality. Bayesian analysis is (arguably a useful tool to support complicated decision-making, because it makes the uncertainty associated with silent multiple comparisons explicit.

  5. Myeloid clusters are associated with a pro-metastatic environment and poor prognosis in smoking-related early stage non-small cell lung cancer.

    Directory of Open Access Journals (Sweden)

    Wang Zhang

    Full Text Available This study aimed to understand the role of myeloid cell clusters in uninvolved regional lymph nodes from early stage non-small cell lung cancer patients.Uninvolved regional lymph node sections from 67 patients with stage I-III resected non-small cell lung cancer were immunostained to detect myeloid clusters, STAT3 activity and occult metastasis. Anthracosis intensity, myeloid cluster infiltration associated with anthracosis and pSTAT3 level were scored and correlated with patient survival. Multivariate Cox regression analysis was performed with prognostic variables. Human macrophages were used for in vitro nicotine treatment.CD68+ myeloid clusters associated with anthracosis and with an immunosuppressive and metastasis-promoting phenotype and elevated overall STAT3 activity were observed in uninvolved lymph nodes. In patients with a smoking history, myeloid cluster score significantly correlated with anthracosis intensity and pSTAT3 level (P<0.01. Nicotine activated STAT3 in macrophages in long-term culture. CD68+ myeloid clusters correlated and colocalized with occult metastasis. Myeloid cluster score was an independent prognostic factor (P = 0.049 and was associated with survival by Kaplan-Maier estimate in patients with a history of smoking (P = 0.055. The combination of myeloid cluster score with either lymph node stage or pSTAT3 level defined two populations with a significant difference in survival (P = 0.024 and P = 0.004, respectively.Myeloid clusters facilitate a pro-metastatic microenvironment in uninvolved regional lymph nodes and associate with occult metastasis in early stage non-small cell lung cancer. Myeloid cluster score is an independent prognostic factor for survival in patients with a history of smoking, and may present a novel method to inform therapy choices in the adjuvant setting. Further validation studies are warranted.

  6. Opening Address

    Science.gov (United States)

    Yamada, T.

    2014-12-01

    Ladies and Gentlemen, it is my great honor and pleasure to present an opening address of the 3rd International Workshop on "State of the Art in Nuclear Cluster Physics"(SOTANCP3). On the behalf of the organizing committee, I certainly welcome all your visits to KGU Kannai Media Center belonging to Kanto Gakuin University, and stay in Yokohama. In particular, to whom come from abroad more than 17 countries, I would appreciate your participations after long long trips from your homeland to Yokohama. The first international workshop on "State of the Art in Nuclear Cluster Physics", called SOTANCP, was held in Strasbourg, France, in 2008, and the second one was held in Brussels, Belgium, in 2010. Then the third workshop is now held in Yokohama. In this period, we had the traditional 10th cluster conference in Debrecen, Hungary, in 2012. Thus we have the traditional cluster conference and SOTANCP, one after another, every two years. This obviously shows our field of nuclear cluster physics is very active and flourishing. It is for the first time in about 10 years to hold the international workshop on nuclear cluster physics in Japan, because the last cluster conference held in Japan was in Nara in 2003, about 10 years ago. The president in Nara conference was Prof. K. Ikeda, and the chairpersons were Prof. H. Horiuchi and Prof. I. Tanihata. I think, quite a lot of persons in this room had participated at the Nara conference. Since then, about ten years passed. So, this workshop has profound significance for our Japanese colleagues. The subjects of this workshop are to discuss "the state of the art in nuclear cluster physics" and also discuss the prospect of this field. In a couple of years, we saw significant progresses of this field both in theory and in experiment, which have brought better and new understandings on the clustering aspects in stable and unstable nuclei. I think, the concept of clustering has been more important than ever. This is true also in the

  7. Adenomatous polyposis coli (APC) regulates miR17-92 cluster through β-catenin pathway in colorectal cancer.

    Science.gov (United States)

    Li, Yajuan; Lauriola, Mattia; Kim, Donghwa; Francesconi, Mirko; D'Uva, Gabriele; Shibata, Dave; Malafa, Mokenge P; Yeatman, Timothy J; Coppola, Domenico; Solmi, Rossella; Cheng, Jin Q

    2016-09-01

    Adenomatous polyposis coli (APC) mutation is the most common genetic change in sporadic colorectal cancer (CRC). Although deregulations of miRNAs have been frequently reported in this malignancy, APC-regulated miRNAs have not been extensively documented. Here, by using an APC-inducible cell line and array analysis, we identified a total of 26 deregulated miRNAs. Among them, members of miR-17-92 cluster were dramatically inhibited by APC and induced by enforced expression of β-catenin. Furthermore, we demonstrate that activated β-catenin resulted from APC loss binds to and activates the miR-17-92 promoter. Notably, enforced expression of miR-19a overrides APC tumor suppressor activity, and knockdown of miR-19a in cancer cells with compromised APC function reduced their aggressive features in vitro. Finally, we observed that expression of miR-19a significantly correlates with β-catenin levels in colorectal cancer specimens, and it is associated to the aggressive stage of tumor progression. Thus, our study reveals that miR-17-92 cluster is directly regulated by APC/β-catenin pathway and could be a potential therapeutic target in colon cancers with aberrant APC/β-catenin signaling.

  8. Progress on clustered DNA damage in radiation research

    International Nuclear Information System (INIS)

    Yang Li'na; Zhang Hong; Di Cuixia; Zhang Qiuning; Wang Xiaohu

    2012-01-01

    Clustered DNA damage which caused by high LET heavy ion radiation can lead to mutation, tumorigenesis and apoptosis. Promoting apoptosis of cancer cells is always the basis of cancer treatment. Clustered DNA damage has been the hot topic in radiobiology. The detect method is diversity, but there is not a detail and complete protocol to analyze clustered DNA damage. In order to provide reference for clustered DNA damage in the radiotherapy study, the clustered DNA damage characteristics, the latest progresses on clustered DNA damage and the detecting methods are reviewed and discussed in detail in this paper. (authors)

  9. Substructure in clusters of galaxies

    International Nuclear Information System (INIS)

    Fitchett, M.J.

    1988-01-01

    Optical observations suggesting the existence of substructure in clusters of galaxies are examined. Models of cluster formation and methods used to detect substructure in clusters are reviewed. Consideration is given to classification schemes based on a departure of bright cluster galaxies from a spherically symmetric distribution, evidence for statistically significant substructure, and various types of substructure, including velocity, spatial, and spatial-velocity substructure. The substructure observed in the galaxy distribution in clusters is discussed, focusing on observations from general cluster samples, the Virgo cluster, the Hydra cluster, Centaurus, the Coma cluster, and the Cancer cluster. 88 refs

  10. Evaluation of Modified Categorical Data Fuzzy Clustering Algorithm on the Wisconsin Breast Cancer Dataset

    Directory of Open Access Journals (Sweden)

    Amir Ahmad

    2016-01-01

    Full Text Available The early diagnosis of breast cancer is an important step in a fight against the disease. Machine learning techniques have shown promise in improving our understanding of the disease. As medical datasets consist of data points which cannot be precisely assigned to a class, fuzzy methods have been useful for studying of these datasets. Sometimes breast cancer datasets are described by categorical features. Many fuzzy clustering algorithms have been developed for categorical datasets. However, in most of these methods Hamming distance is used to define the distance between the two categorical feature values. In this paper, we use a probabilistic distance measure for the distance computation among a pair of categorical feature values. Experiments demonstrate that the distance measure performs better than Hamming distance for Wisconsin breast cancer data.

  11. Impact of a cancer clinical trials web site on discussions about trial participation: a cluster randomized trial.

    Science.gov (United States)

    Dear, R F; Barratt, A L; Askie, L M; Butow, P N; McGeechan, K; Crossing, S; Currow, D C; Tattersall, M H N

    2012-07-01

    Cancer patients want access to reliable information about currently recruiting clinical trials. Oncologists and their patients were randomly assigned to access a consumer-friendly cancer clinical trials web site [Australian Cancer Trials (ACT), www.australiancancertrials.gov.au] or to usual care in a cluster randomized controlled trial. The primary outcome, measured from audio recordings of oncologist-patient consultations, was the proportion of patients with whom participation in any clinical trial was discussed. Analysis was by intention-to-treat accounting for clustering and stratification. Thirty medical oncologists and 493 patients were recruited. Overall, 46% of consultations in the intervention group compared with 34% in the control group contained a discussion about clinical trials (P=0.08). The mean consultation length in both groups was 29 min (P=0.69). The proportion consenting to a trial was 10% in both groups (P=0.65). Patients' knowledge about randomized trials was lower in the intervention than the control group (mean score 3.0 versus 3.3, P=0.03) but decisional conflict scores were similar (mean score 42 versus 43, P=0.83). Good communication between patients and physicians is essential. Within this context, a web site such as Australian Cancer Trials may be an important tool to encourage discussion about clinical trial participation.

  12. Addressing Risk and Reluctance at the Nexus of HIV and Anal Cancer Screening

    Science.gov (United States)

    Ka‘opua, Lana Sue I.; Cassel, Kevin; Shiramizu, Bruce; Stotzer, Rebecca L.; Robles, Andrew; Kapua, Cathy; Orton, Malulani; Milne, Cris; Sesepasara, Maddalynn

    2015-01-01

    Anal cancer disproportionately burdens persons living with human immunodeficiency virus (PLHIV) regardless of natal sex, sexual orientation, gender expression, and ethnic identity. Culturally competent communications are recommended to address health disparities, with sociocultural relevance ensured through constituent dialogic processes. Results are presented from six provider focus groups conducted to inform the promotion/education component of a Hawai‘i-based project on anal cancer screening tools. Krueger’s focus group methodology guided discussion queries. Verbatim transcripts of digitally recorded discussions were analyzed using grounded theory and PEN-3 procedures. Adherence to an audit trail ensured analytic rigor. Grounded theory analysis detected the overall theme of risk and reluctance to anal cancer screening, characterized by anal cancer not being “on the radar” of PLHIV, conflicting attributions of the anus and anal sex, fear of sex-shaming/-blaming, and other interrelated conceptual categories. PEN-3 analysis revealed strategies for destigmatizing anal cancer, through “real talk” (proactive, candid, nonjudgmental discussion) nested in a framework of sexual health and overall well-being, with additional tailoring for relevance to Native Hawaiians/Pacific Islanders, transgender persons, and other marginalized groups. Application of strategies for health practice are specific to the Hawai‘i context, yet may offer considerations for developing strengths-based, culturally relevant screening promotion/education with diverse PLHIV in other locales. PMID:26630979

  13. Addressing Risk and Reluctance at the Nexus of HIV and Anal Cancer Screening.

    Science.gov (United States)

    Ka'opua, Lana Sue I; Cassel, Kevin; Shiramizu, Bruce; Stotzer, Rebecca L; Robles, Andrew; Kapua, Cathy; Orton, Malulani; Milne, Cris; Sesepasara, Maddalynn

    2016-01-01

    Anal cancer disproportionately burdens persons living with human immunodeficiency virus (PLHIV) regardless of natal sex, sexual orientation, gender expression, and ethnic identity. Culturally competent communications are recommended to address health disparities, with sociocultural relevance ensured through constituent dialogic processes. Results are presented from six provider focus groups conducted to inform the promotion/education component of a Hawai'i-based project on anal cancer screening tools. Krueger's focus group methodology guided discussion queries. Verbatim transcripts of digitally recorded discussions were analyzed using grounded theory and PEN-3 procedures. Adherence to an audit trail ensured analytic rigor. Grounded theory analysis detected the overall theme of risk and reluctance to anal cancer screening, characterized by anal cancer not being "on the radar" of PLHIV, conflicting attributions of the anus and anal sex, fear of sex-shaming/-blaming, and other interrelated conceptual categories. PEN-3 analysis revealed strategies for destigmatizing anal cancer, through "real talk" (proactive, candid, nonjudgmental discussion) nested in a framework of sexual health and overall well-being, with additional tailoring for relevance to Native Hawaiians/Pacific Islanders, transgender persons, and other marginalized groups. Application of strategies for health practice are specific to the Hawai'i context, yet may offer considerations for developing strengths-based, culturally relevant screening promotion/education with diverse PLHIV in other locales. © 2015 Society for Public Health Education.

  14. Fluorescence Imaging Assisted Photodynamic Therapy Using Photosensitizer-Linked Gold Quantum Clusters.

    Science.gov (United States)

    Nair, Lakshmi V; Nazeer, Shaiju S; Jayasree, Ramapurath S; Ajayaghosh, Ayyappanpillai

    2015-06-23

    Fluorescence imaging assisted photodynamic therapy (PDT) is a viable two-in-one clinical tool for cancer treatment and follow-up. While the surface plasmon effect of gold nanorods and nanoparticles has been effective for cancer therapy, their emission properties when compared to gold nanoclusters are weak for fluorescence imaging guided PDT. In order to address the above issues, we have synthesized a near-infrared-emitting gold quantum cluster capped with lipoic acid (L-AuC with (Au)18(L)14) based nanoplatform with excellent tumor reduction property by incorporating a tumor-targeting agent (folic acid) and a photosensitizer (protoporphyrin IX), for selective PDT. The synthesized quantum cluster based photosensitizer PFL-AuC showed 80% triplet quantum yield when compared to that of the photosensitizer alone (63%). PFL-AuC having 60 μg (0.136 mM) of protoporphyrin IX was sufficient to kill 50% of the tumor cell population. Effective destruction of tumor cells was evident from the histopathology and fluorescence imaging, which confirm the in vivo PDT efficacy of PFL-AuC.

  15. Themes addressed by couples with advanced cancer during a communication skills training intervention.

    Science.gov (United States)

    Porter, Laura S; Fish, Laura; Steinhauser, Karen

    2018-04-25

    Couple-based communication interventions have beneficial effects for patients with cancer and their partners. However, few studies have targeted patients with advanced stages of disease and little is known about how best to assist couples in discussing issues related to life-limiting illness. The purpose of the present study was to identify themes couples addressed during a couple communication skills intervention, and the frequency with which they discussed issues related to end-of-life. Content analyses were conducted on recordings of 72 sessions from 12 couples facing advanced gastrointestinal (GI) cancer. Coding was based six themes identified a priori from the framework for understanding what patients and family value at end of life. The percent of couples addressing each theme was calculated to gauge level of importance and acceptability of these topics. The majority of couples addressed topics previously identified as salient at end-of-life, including clear decision making, affirmation of the whole person, pain and symptom management, contributing to others, and preparation for death. In addition, novel aspects to these themes emerged in the context of couples' conversations, illustrating the importance of the couple relationship in adjusting to life with a life-limiting illness and anticipating the transition to end-of-life. Findings suggest that couples likely would be receptive to an intervention that combines training in communication skills with guidance in focusing on issues related to life completion to assist with transitions at end of life. Such interventions might enhance both individuals' abilities to cope with illness-related symptoms and demands, enjoy the time they have together, and derive meaning from the experience. Copyright © 2018. Published by Elsevier Inc.

  16. Mismatch of Posttraumatic Stress Disorder (PTSD) Symptoms and DSM-IV Symptom Clusters in a Cancer Sample: Exploratory Factor Analysis of the PTSD Checklist-Civilian Version

    Science.gov (United States)

    Shelby, Rebecca A.; Golden-Kreutz, Deanna M.; Andersen, Barbara L.

    2007-01-01

    The Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV; American Psychiatric Association, 1994a) conceptualization of posttraumatic stress disorder (PTSD) includes three symptom clusters: reexperiencing, avoidance/numbing, and arousal. The PTSD Checklist-Civilian Version (PCL-C) corresponds to the DSM-IV PTSD symptoms. In the current study, we conducted exploratory factor analysis (EFA) of the PCL-C with two aims: (a) to examine whether the PCL-C evidenced the three-factor solution implied by the DSM-IV symptom clusters, and (b) to identify a factor solution for the PCL-C in a cancer sample. Women (N = 148) with Stage II or III breast cancer completed the PCL-C after completion of cancer treatment. We extracted two-, three-, four-, and five-factor solutions using EFA. Our data did not support the DSM-IV PTSD symptom clusters. Instead, EFA identified a four-factor solution including reexperiencing, avoidance, numbing, and arousal factors. Four symptom items, which may be confounded with illness and cancer treatment-related symptoms, exhibited poor factor loadings. Using these symptom items in cancer samples may lead to overdiagnosis of PTSD and inflated rates of PTSD symptoms. PMID:16281232

  17. A critical assessment of geographic clusters of breast and lung cancer incidences among residents living near the Tittabawassee and Saginaw Rivers, Michigan, USA.

    Science.gov (United States)

    Guajardo, Olga A; Oyana, Tonny J

    2009-01-01

    To assess previously determined geographic clusters of breast and lung cancer incidences among residents living near the Tittabawassee and Saginaw Rivers, Michigan, using a new set of environmental factors. Breast and lung cancer data were acquired from the Michigan Department of Community Health, along with point source pollution data from the U.S. Environmental Protection Agency. The datasets were used to determine whether there is a spatial association between disease risk and environmental contamination. GIS and spatial techniques were combined with statistical analysis to investigate local risk of breast and lung cancer. The study suggests that neighborhoods in close proximity to the river were associated with a high risk of breast cancer, while increased risk of lung cancer was detected among neighborhoods in close proximity to point source pollution and major highways. Statistically significant (P clusters of cancer incidences were observed among residents living near the rivers. These findings are useful to researchers and governmental agencies for risk assessment, regulation, and control of environmental contamination in the floodplains.

  18. A Critical Assessment of Geographic Clusters of Breast and Lung Cancer Incidences among Residents Living near the Tittabawassee and Saginaw Rivers, Michigan, USA

    Directory of Open Access Journals (Sweden)

    Olga A. Guajardo

    2009-01-01

    Full Text Available Objectives. To assess previously determined geographic clusters of breast and lung cancer incidences among residents living near the Tittabawassee and Saginaw Rivers, Michigan, using a new set of environmental factors. Materials and Methods. Breast and lung cancer data were acquired from the Michigan Department of Community Health, along with point source pollution data from the U.S. Environmental Protection Agency. The datasets were used to determine whether there is a spatial association between disease risk and environmental contamination. GIS and spatial techniques were combined with statistical analysis to investigate local risk of breast and lung cancer. Results and Conclusion. The study suggests that neighborhoods in close proximity to the river were associated with a high risk of breast cancer, while increased risk of lung cancer was detected among neighborhoods in close proximity to point source pollution and major highways. Statistically significant (P≤.001 clusters of cancer incidences were observed among residents living near the rivers. These findings are useful to researchers and governmental agencies for risk assessment, regulation, and control of environmental contamination in the floodplains.

  19. A Critical Assessment of Geographic Clusters of Breast and Lung Cancer Incidences among Residents Living near the Tittabawassee and Saginaw Rivers, Michigan, USA

    International Nuclear Information System (INIS)

    Guajardo, O.A.; Oyana, T.J.

    2010-01-01

    Objectives. To assess previously determined geographic clusters of breast and lung cancer incidences among residents living near the Tittabawassee and Saginaw Rivers, Michigan, using a new set of environmental factors. Materials and Methods. Breast and lung cancer data were acquired from the Michigan Department of Community Health, along with point source pollution data from the U.S. Environmental Protection Agency. The datasets were used to determine whether there is a spatial association between disease risk and environmental contamination. GIS and spatial techniques were combined with statistical analysis to investigate local risk of breast and lung cancer. Results and Conclusion. The study suggests that neighborhoods in close proximity to the river were associated with a high risk of breast cancer, while increased risk of lung cancer was detected among neighborhoods in close proximity to point source pollution and major highways. Statistically significant (P=.001) clusters of cancer incidences were observed among residents living near the rivers. These findings are useful to researchers and governmental agencies for risk assessment, regulation, and control of environmental contamination in the flood plains.

  20. Clusters in simple fluids

    International Nuclear Information System (INIS)

    Sator, N.

    2003-01-01

    This article concerns the correspondence between thermodynamics and the morphology of simple fluids in terms of clusters. Definitions of clusters providing a geometric interpretation of the liquid-gas phase transition are reviewed with an eye to establishing their physical relevance. The author emphasizes their main features and basic hypotheses, and shows how these definitions lead to a recent approach based on self-bound clusters. Although theoretical, this tutorial review is also addressed to readers interested in experimental aspects of clustering in simple fluids

  1. Clustering Millions of Faces by Identity.

    Science.gov (United States)

    Otto, Charles; Wang, Dayong; Jain, Anil K

    2018-02-01

    Given a large collection of unlabeled face images, we address the problem of clustering faces into an unknown number of identities. This problem is of interest in social media, law enforcement, and other applications, where the number of faces can be of the order of hundreds of million, while the number of identities (clusters) can range from a few thousand to millions. To address the challenges of run-time complexity and cluster quality, we present an approximate Rank-Order clustering algorithm that performs better than popular clustering algorithms (k-Means and Spectral). Our experiments include clustering up to 123 million face images into over 10 million clusters. Clustering results are analyzed in terms of external (known face labels) and internal (unknown face labels) quality measures, and run-time. Our algorithm achieves an F-measure of 0.87 on the LFW benchmark (13 K faces of 5,749 individuals), which drops to 0.27 on the largest dataset considered (13 K faces in LFW + 123M distractor images). Additionally, we show that frames in the YouTube benchmark can be clustered with an F-measure of 0.71. An internal per-cluster quality measure is developed to rank individual clusters for manual exploration of high quality clusters that are compact and isolated.

  2. Metabolic Study of Cancer Cells Using a pH Sensitive Hydrogel Nanofiber Light Addressable Potentiometric Sensor.

    Science.gov (United States)

    Shaibani, Parmiss Mojir; Etayash, Hashem; Naicker, Selvaraj; Kaur, Kamaljit; Thundat, Thomas

    2017-01-27

    We report a simple, fast, and cost-effective approach that measures cancer cell metabolism and their response to anticancer drugs in real time. Using a Light Addressable Potentiometric Sensor integrated with pH sensitive hydrogel nanofibers (NF-LAPS), we detect localized changes in pH of the media as cancer cells consume glucose and release lactate. NF-LAPS shows a sensitivity response of 74 mV/pH for cancer cells. Cancer cells (MDA MB231) showed a response of ∼0.4 unit change in pH compared to virtually no change observed for normal cells (MCF10A). We also observed a drop in pH for the multidrug-resistant cancer cells (MDA-MB-435MDR) in the presence of doxorubicin. However, inhibition of the metabolic enzymes such as hexokinase and lactate dehydrogenase-A suggested an improvement in the efficacy of doxorubicin by decreasing the level of acidification. This approach, based on extracellular acidification, enhances our understanding of cancer cell metabolic modes and their response to chemotherapies, which will help in the development of better treatments, including choice of drugs and dosages.

  3. Role of DNA methylation in miR-200c/141 cluster silencing in invasive breast cancer cells

    OpenAIRE

    Neves, Rui; Scheel, Christina; Weinhold, Sandra; Honisch, Ellen; Iwaniuk, Katharina M; Trompeter, Hans-Ingo; Niederacher, Dieter; Wernet, Peter; Santourlidis, Simeon; Uhrberg, Markus

    2010-01-01

    Abstract Background The miR-200c/141 cluster has recently been implicated in the epithelial to mesenchymal transition (EMT) process. The expression of these two miRNAs is inversely correlated with tumorigenicity and invasiveness in several human cancers. The role of these miRNAs in cancer progression is based in part on their capacity to target the EMT activators ZEB1 and ZEB2, two transcription factors, which in turn repress expression of E-cadherin. Little is known about the regulation of t...

  4. The Quality Initiative in Rectal Cancer (QIRC trial: study protocol of a cluster randomized controlled trial in surgery

    Directory of Open Access Journals (Sweden)

    Thabane Lehana

    2008-02-01

    Full Text Available Abstract Background Two unfortunate outcomes for patients treated surgically for rectal cancer are placement of a permanent colostomy and local tumor recurrence. Total mesorectal excision is a new technique for rectal cancer surgery that can lead to improved patient outcomes. We describe a cluster randomized controlled trial that is testing if the above patient outcomes can be improved through a knowledge translation strategy called the Quality Initiative in Rectal Cancer (QIRC strategy. The strategy is designed to optimize the use of total mesorectal excision techniques. Methods and Design Hospitals were randomized to the QIRC strategy (experimental group versus normal practice environment (control group. Participating hospitals, and the respective surgeon group operating in them, are from Ontario, Canada and have an annual procedure volume for major rectal cancer resections of 15 or greater. Patients were eligible if they underwent major rectal surgery for a diagnosis of primary rectal cancer. The surgeon-directed QIRC interventions included a workshop, use of opinion leaders, operative demonstrations, a post-operative questionnaire, and, audit and feedback. For an operative demonstration participating surgeons invited a study team surgeon to assist them with a case of rectal cancer surgery. The intent was to demonstrate total mesorectal excision techniques. Control arm surgeons received no intervention. Sample size calculations were two-sided, considered the clustering of data at the hospital level, and were driven by requirements for the outcome local recurrence. To detect an improvement in local recurrence from 20% to 8% with confidence we required 16 hospitals and 672 patients – 8 hospitals and 336 patients in each arm. Outcomes data are collected via chart review for at least 30 months after surgery. Analyses will use an intention-to-treat principle and will consider the clustering of data. Data collection will be complete by the end of

  5. Data clustering algorithms and applications

    CERN Document Server

    Aggarwal, Charu C

    2013-01-01

    Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, from basic methods to more refined and complex data clustering approaches. It pays special attention to recent issues in graphs, social networks, and other domains.The book focuses on three primary aspects of data clustering: Methods, describing key techniques commonly used for clustering, such as fea

  6. Development of Automatic Cluster Algorithm for Microcalcification in Digital Mammography

    International Nuclear Information System (INIS)

    Choi, Seok Yoon; Kim, Chang Soo

    2009-01-01

    Digital Mammography is an efficient imaging technique for the detection and diagnosis of breast pathological disorders. Six mammographic criteria such as number of cluster, number, size, extent and morphologic shape of microcalcification, and presence of mass, were reviewed and correlation with pathologic diagnosis were evaluated. It is very important to find breast cancer early when treatment can reduce deaths from breast cancer and breast incision. In screening breast cancer, mammography is typically used to view the internal organization. Clusterig microcalcifications on mammography represent an important feature of breast mass, especially that of intraductal carcinoma. Because microcalcification has high correlation with breast cancer, a cluster of a microcalcification can be very helpful for the clinical doctor to predict breast cancer. For this study, three steps of quantitative evaluation are proposed : DoG filter, adaptive thresholding, Expectation maximization. Through the proposed algorithm, each cluster in the distribution of microcalcification was able to measure the number calcification and length of cluster also can be used to automatically diagnose breast cancer as indicators of the primary diagnosis.

  7. An integrative analysis of cellular contexts, miRNAs and mRNAs reveals network clusters associated with antiestrogen-resistant breast cancer cells

    Directory of Open Access Journals (Sweden)

    Nam Seungyoon

    2012-12-01

    Full Text Available Abstract Background A major goal of the field of systems biology is to translate genome-wide profiling data (e.g., mRNAs, miRNAs into interpretable functional networks. However, employing a systems biology approach to better understand the complexities underlying drug resistance phenotypes in cancer continues to represent a significant challenge to the field. Previously, we derived two drug-resistant breast cancer sublines (tamoxifen- and fulvestrant-resistant cell lines from the MCF7 breast cancer cell line and performed genome-wide mRNA and microRNA profiling to identify differential molecular pathways underlying acquired resistance to these important antiestrogens. In the current study, to further define molecular characteristics of acquired antiestrogen resistance we constructed an “integrative network”. We combined joint miRNA-mRNA expression profiles, cancer contexts, miRNA-target mRNA relationships, and miRNA upstream regulators. In particular, to reduce the probability of false positive connections in the network, experimentally validated, rather than prediction-oriented, databases were utilized to obtain connectivity. Also, to improve biological interpretation, cancer contexts were incorporated into the network connectivity. Results Based on the integrative network, we extracted “substructures” (network clusters representing the drug resistant states (tamoxifen- or fulvestrant-resistance cells compared to drug sensitive state (parental MCF7 cells. We identified un-described network clusters that contribute to antiestrogen resistance consisting of miR-146a, -27a, -145, -21, -155, -15a, -125b, and let-7s, in addition to the previously described miR-221/222. Conclusions By integrating miRNA-related network, gene/miRNA expression and text-mining, the current study provides a computational-based systems biology approach for further investigating the molecular mechanism underlying antiestrogen resistance in breast cancer cells. In

  8. DETECTION OF CANCEROUS LESION BY UTERINE CERVIX IMAGE SEGMENTATION

    Directory of Open Access Journals (Sweden)

    P. Priya

    2014-02-01

    Full Text Available This paper works at segmentation of lesion observed in cervical cancer, which is the second most common cancer among women worldwide. The purpose of segmentation is to determine the location for a biopsy to be taken for diagnosis. Cervix cancer is a disease in which cancer cells are found in the tissues of the cervix. The acetowhite region is a major indicator of abnormality in the cervix image. This project addresses the problem of segmenting uterine cervix image into different regions. We analyze two algorithms namely Watershed, K-means clustering algorithm, Expectation Maximization (EM Image Segmentation algorithm. These segmentations methods are carried over for the colposcopic uterine cervix image.

  9. Nuclear cluster states

    International Nuclear Information System (INIS)

    Rae, W.D.M.; Merchant, A.C.

    1993-01-01

    We review clustering in light nuclei including molecular resonances in heavy ion reactions. In particular we study the systematics, paying special attention to the relationships between cluster states and superdeformed configurations. We emphasise the selection rules which govern the formation and decay of cluster states. We review some recent experimental results from Daresbury and elsewhere. In particular we report on the evidence for a 7-α chain state in 28 Si in experiments recently performed at the NSF, Daresbury. Finally we begin to address theoretically the important question of the lifetimes of cluster states as deduced from the experimental energy widths of the resonances. (Author)

  10. Convex Clustering: An Attractive Alternative to Hierarchical Clustering

    Science.gov (United States)

    Chen, Gary K.; Chi, Eric C.; Ranola, John Michael O.; Lange, Kenneth

    2015-01-01

    The primary goal in cluster analysis is to discover natural groupings of objects. The field of cluster analysis is crowded with diverse methods that make special assumptions about data and address different scientific aims. Despite its shortcomings in accuracy, hierarchical clustering is the dominant clustering method in bioinformatics. Biologists find the trees constructed by hierarchical clustering visually appealing and in tune with their evolutionary perspective. Hierarchical clustering operates on multiple scales simultaneously. This is essential, for instance, in transcriptome data, where one may be interested in making qualitative inferences about how lower-order relationships like gene modules lead to higher-order relationships like pathways or biological processes. The recently developed method of convex clustering preserves the visual appeal of hierarchical clustering while ameliorating its propensity to make false inferences in the presence of outliers and noise. The solution paths generated by convex clustering reveal relationships between clusters that are hidden by static methods such as k-means clustering. The current paper derives and tests a novel proximal distance algorithm for minimizing the objective function of convex clustering. The algorithm separates parameters, accommodates missing data, and supports prior information on relationships. Our program CONVEXCLUSTER incorporating the algorithm is implemented on ATI and nVidia graphics processing units (GPUs) for maximal speed. Several biological examples illustrate the strengths of convex clustering and the ability of the proximal distance algorithm to handle high-dimensional problems. CONVEXCLUSTER can be freely downloaded from the UCLA Human Genetics web site at http://www.genetics.ucla.edu/software/ PMID:25965340

  11. MicroRNA-210 regulates mitochondrial free radical response to hypoxia and krebs cycle in cancer cells by targeting iron sulfur cluster protein ISCU.

    Directory of Open Access Journals (Sweden)

    Elena Favaro

    2010-04-01

    Full Text Available Hypoxia in cancers results in the upregulation of hypoxia inducible factor 1 (HIF-1 and a microRNA, hsa-miR-210 (miR-210 which is associated with a poor prognosis.In human cancer cell lines and tumours, we found that miR-210 targets the mitochondrial iron sulfur scaffold protein ISCU, required for assembly of iron-sulfur clusters, cofactors for key enzymes involved in the Krebs cycle, electron transport, and iron metabolism. Down regulation of ISCU was the major cause of induction of reactive oxygen species (ROS in hypoxia. ISCU suppression reduced mitochondrial complex 1 activity and aconitase activity, caused a shift to glycolysis in normoxia and enhanced cell survival. Cancers with low ISCU had a worse prognosis.Induction of these major hallmarks of cancer show that a single microRNA, miR-210, mediates a new mechanism of adaptation to hypoxia, by regulating mitochondrial function via iron-sulfur cluster metabolism and free radical generation.

  12. Mobile telecommunications and health: report of an investigation into an alleged cancer cluster in Sandwell, West Midlands.

    Science.gov (United States)

    Stewart, Antony; Rao, Jammi N; Middleton, John D; Pearmain, Philippa; Evans, Tim

    2012-11-01

    Residents of one street expressed concern about the number of incident cancers, following the installation of a nearby mobile phone base station. The investigation explored whether the base station could be responsible for the cancers. Data were collected from residents' medical records. GPs and oncologists provided further information. Ward-level cancer incidence and mortality data were also obtained, over four three-year time periods. A total of 19 residents had developed cancer. The collection of cancers did not fulfil the criteria for a cancer cluster. Standardized mortality ratios (SMRs) for all malignant neoplasms (excluding non-melanoma skin cancers) in females (1.38 (95% CI, 1.08-1.74)) and all persons (1.27 (CI, 1.06-1.51)) were significantly higher than in the West Midlands during 2001-3. There were no significant differences for colorectal, female breast and prostate cancers, for any time period. Standardized incidence ratios (SIRs) for non-melanoma skin cancers in males and all persons was significantly lower than in the West Midlands during 1999-2001, and significantly lower in males, females and all persons during 2002-4. We cannot conclude that the base station was responsible for the cancers. It is unlikely that information around a single base station can either demonstrate or exclude causality.

  13. The Yo me cuido® Program: Addressing Breast Cancer Screening and Prevention Among Hispanic Women.

    Science.gov (United States)

    Davis, Jenna L; Ramos, Roberto; Rivera-Colón, Venessa; Escobar, Myriam; Palencia, Jeannette; Grant, Cathy G; Green, B Lee

    2015-09-01

    Breast cancer is less likely to be diagnosed at the earliest stage in Hispanic/Latino (Hispanic) women compared to non-Hispanic White women, even after accounting for differences in age, socioeconomic status, and method of detection. Moffitt Cancer Center created a comprehensive health education program called Yo me cuido (®) (YMC) to address and reduce breast cancer disparities among Spanish- and English-speaking Hispanic women by providing breast cancer and healthy lifestyles awareness and education, and promoting breast cancer screenings, reminders, and referrals for women 40 years and older. The purpose of this paper is to showcase the innovative approaches and methods to cancer prevention and early detection of the YMC program, and to promote it as an effective tool for improving outcomes in community health education, outreach, and engagement activities with Hispanic populations. Key components of the program include educational workshops, mammogram referrals, and a multimedia campaign. The YMC program is unique because of its approaches in reaching the Hispanic population, such as delivering the program with compassionate services to empower participants to live a healthier lifestyle. Additionally, direct follow-up for mammography screenings is provided by program staff. From 2011 to 2013, YMC has educated 2,226 women and 165 men through 93 workshops. About 684 (52 %) women ages 40 and older have had a screening mammogram within their first year of participating in the program. The YMC program is an innovative cancer education and outreach program that has demonstrated a positive impact on the lives of the Hispanic community in the Tampa Bay region.

  14. miR-15a/miR-16 cluster inhibits invasion of prostate cancer cells by suppressing TGF-β signaling pathway.

    Science.gov (United States)

    Jin, Wei; Chen, Fangjie; Wang, Kefeng; Song, Yan; Fei, Xiang; Wu, Bin

    2018-05-23

    To determine whether and how miR15a/16 regulate TGF-β signaling pathways during the progression of prostate cancer. We used bioinformatics prediction, reporter gene assay, real-time PCR, Matrigel invasion assay and Western blot to dissect the molecular mechanism of how miR-15a/miR-16 may cause metastasis in prostate tumor. MiR-15a/16 targeted and inhibited the expression of endogenous Smad3 and ACVR2A proteins. The overexpression of miR15a/16 down-regulated p-smad3 expression, affected the expression of both MMP2 and E-cadherin, and down-regulated the expression of the EMT-mediated factors Snail and Twist in LNCaP prostate cancer cells. The overexpression of miR15a/16 decreased the invasion of LNCaP cells. MiR-15a/miR-16 cluster could reverse the invasion of activin A-mediated prostate cancer cells. After the inhibition of the activin/smad signaling pathway, the inhibitory effect of invasion in prostate cancer cells by miR-15a/miR-16 cluster disappeared. Our data indicated that miR15a/16 inhibited the components of TGF-β signaling pathways in LNCaP cell line, which might relate to the progression and metastasis of prostate cancer. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

  15. Residential Mobility and Breast Cancer in Marin County, California, USA

    Directory of Open Access Journals (Sweden)

    Geoffrey M. Jacquez

    2013-12-01

    Full Text Available Marin County (California, USA has among the highest incidences of breast cancer in the U.S. A previously conducted case-control study found eight significant risk factors in participants enrolled from 1997–1999. These included being premenopausal, never using birth control pills, lower highest lifetime body mass index, having four or more mammograms from 1990–1994, beginning drinking alcohol after age 21, drinking an average two or more alcoholic drinks per day, being in the highest quartile of pack-years of cigarette smoking, and being raised in an organized religion. Previously conducted surveys provided residential histories; while  statistic accounted for participants’ residential mobility, and assessed clustering of breast cancer cases relative to controls based on the known risk factors. These identified specific cases, places, and times of excess breast cancer risk. Analysis found significant global clustering of cases localized to specific residential histories and times. Much of the observed clustering occurred among participants who immigrated to Marin County. However, persistent case-clustering of greater than fifteen years duration was also detected. Significant case-clustering among long-term residents may indicate geographically localized risk factors not accounted for in the study design, as well as uncertainty and incompleteness in the acquired addresses. Other plausible explanations include environmental risk factors and cases tending to settle in specific areas. A biologically plausible exposure or risk factor has yet to be identified.

  16. Spatial analysis of lung, colorectal, and breast cancer on Cape Cod: An application of generalized additive models to case-control data

    Directory of Open Access Journals (Sweden)

    Aschengrau Ann

    2005-06-01

    Full Text Available Abstract Background The availability of geographic information from cancer and birth defect registries has increased public demands for investigation of perceived disease clusters. Many neighborhood-level cluster investigations are methodologically problematic, while maps made from registry data often ignore latency and many known risk factors. Population-based case-control and cohort studies provide a stronger foundation for spatial epidemiology because potential confounders and disease latency can be addressed. Methods We investigated the association between residence and colorectal, lung, and breast cancer on upper Cape Cod, Massachusetts (USA using extensive data on covariates and residential history from two case-control studies for 1983–1993. We generated maps using generalized additive models, smoothing on longitude and latitude while adjusting for covariates. The resulting continuous surface estimates disease rates relative to the whole study area. We used permutation tests to examine the overall importance of location in the model and identify areas of increased and decreased risk. Results Maps of colorectal cancer were relatively flat. Assuming 15 years of latency, lung cancer was significantly elevated just northeast of the Massachusetts Military Reservation, although the result did not hold when we restricted to residences of longest duration. Earlier non-spatial epidemiology had found a weak association between lung cancer and proximity to gun and mortar positions on the reservation. Breast cancer hot spots tended to increase in magnitude as we increased latency and adjusted for covariates, indicating that confounders were partly hiding these areas. Significant breast cancer hot spots were located near known groundwater plumes and the Massachusetts Military Reservation. Discussion Spatial epidemiology of population-based case-control studies addresses many methodological criticisms of cluster studies and generates new exposure

  17. Addressing changed sexual functioning in cancer patients: A cross-sectional survey among Dutch oncology nurses.

    Science.gov (United States)

    Krouwel, E M; Nicolai, M P J; van Steijn-van Tol, A Q M J; Putter, H; Osanto, S; Pelger, R C M; Elzevier, H W

    2015-12-01

    In most types of cancer, the disease and its treatment can result in altered sexual function (SF). Oncology nurses are strategically placed to address SF since they have frequent patient interaction. Our aim was to establish their knowledge about and attitudes to SF in oncology care and identify their perceived barriers to addressing the subject. A 37-item questionnaire was administered during the 2012 Dutch Oncology Nursing Congress and mailed to 241 Dutch oncology nursing departments. The majority of 477 nurses (87.6%) agreed that discussing SF is their responsibility. Discussing SF routinely is performed by 33.4% of these nurses, consultations mainly consisted of mentioning treatment side-effects affecting SF (71.3%). There were significant differences depending on experience, knowledge, age, academic degree and department policy. Nurses ≤44 years old (p oncology experience (p = 0.001), insufficient knowledge (p oncology nurses consider counselling on sexual issues to be an important responsibility, in line with discussing other side-effects caused by the disease or its treatment. Nevertheless, cancer patients may not routinely be receiving a sexual health evaluation by oncology nurses. Results emphasize the potential benefit of providing knowledge, including practical training and a complete department protocol. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. Data Clustering on Breast Cancer Data Using Firefly Algorithm with Golden Ratio Method

    Directory of Open Access Journals (Sweden)

    DEMIR, M.

    2015-05-01

    Full Text Available Heuristic methods are problem solving methods. In general, they obtain near-optimal solutions, and they do not take the care of provability of this case. The heuristic methods do not guarantee to obtain the optimal results; however, they guarantee to obtain near-optimal solutions in considerable time. In this paper, an application was performed by using firefly algorithm - one of the heuristic methods. The golden ratio was applied to different steps of firefly algorithm and different parameters of firefly algorithm to develop a new algorithm - called Firefly Algorithm with Golden Ratio (FAGR. It was shown that the golden ratio made firefly algorithm be superior to the firefly algorithm without golden ratio. At this aim, the developed algorithm was applied to WBCD database (breast cancer database to cluster data obtained from breast cancer patients. The highest obtained success rate among all executions is 96% and the highest obtained average success rate in all executions is 94.5%.

  19. How Clusters Work

    Science.gov (United States)

    Technology innovation clusters are geographic concentrations of interconnected companies, universities, and other organizations with a focus on environmental technology. They play a key role in addressing the nation’s pressing environmental problems.

  20. Clustering of Mobile Ad Hoc Networks: An Adaptive Broadcast Period Approach

    OpenAIRE

    Gavalas, Damianos; Pantziou, Grammati; Konstantopoulos, Charalampos; Mamalis, Basilis

    2011-01-01

    Organization, scalability and routing have been identified as key problems hindering viability and commercial success of mobile ad hoc networks. Clustering of mobile nodes among separate domains has been proposed as an efficient approach to address those issues. In this work, we introduce an efficient distributed clustering algorithm that uses both location and energy metrics for cluster formation. Our proposed solution mainly addresses cluster stability, manageability and energy efficiency i...

  1. Symptom clusters and quality of life in China patients with lung ...

    African Journals Online (AJOL)

    Identifying symptom clusters helped clarify possible inter-relationships which may lead to the establishment of more effective symptom management interventions for patients with lung cancer in order to improve the quality of life. Keywords: symptom clusters, lung cancer, factor analysis, symptom management, quality of life

  2. cluML: A markup language for clustering and cluster validity assessment of microarray data.

    Science.gov (United States)

    Bolshakova, Nadia; Cunningham, Pádraig

    2005-01-01

    cluML is a new markup language for microarray data clustering and cluster validity assessment. The XML-based format has been designed to address some of the limitations observed in traditional formats, such as inability to store multiple clustering (including biclustering) and validation results within a dataset. cluML is an effective tool to support biomedical knowledge representation in gene expression data analysis. Although cluML was developed for DNA microarray analysis applications, it can be effectively used for the representation of clustering and for the validation of other biomedical and physical data that has no limitations.

  3. Downregulation of miR-130b~301b cluster is mediated by aberrant promoter methylation and impairs cellular senescence in prostate cancer

    Directory of Open Access Journals (Sweden)

    João Ramalho-Carvalho

    2017-02-01

    Full Text Available Abstract Background Numerous DNA-damaging cellular stresses, including oncogene activation and DNA-damage response (DDR, may lead to cellular senescence. Previous observations linked microRNA deregulation with altered senescent patterns, prompting us to investigate whether epigenetic repression of microRNAs expression might disrupt senescence in prostate cancer (PCa cells. Methods Differential methylation mapping in prostate tissues was carried using Infinium HumanMethylation450 BeadChip. After validation of methylation and expression analyses in a larger series of prostate tissues, the functional role of the cluster miR-130b~301b was explored using in vitro studies testing cell viability, apoptosis, invasion and DNA damage in prostate cancer cell lines. Western blot and RT-qPCR were performed to support those observations. Results We found that the miR-130b~301b cluster directs epigenetic activation of cell cycle inhibitors required for DDR activation, thus stimulating the senescence-associated secretory phenotype (SASP. Furthermore, overexpression of miR-130b~301b cluster markedly reduced the malignant phenotype of PCa cells. Conclusions Altogether, these data demonstrate that miR-130b~301b cluster overexpression might effectively induce PCa cell growth arrest through epigenetic regulation of proliferation-blocking genes and activation of cellular senescence.

  4. Collagen attachment to the substrate controls cell clustering through migration

    International Nuclear Information System (INIS)

    Hou, Yue; Rodriguez, Laura Lara; Wang, Juan; Schneider, Ian C

    2014-01-01

    Cell clustering and scattering play important roles in cancer progression and tissue engineering. While the extracellular matrix (ECM) is known to control cell clustering, much of the quantitative work has focused on the analysis of clustering between cells with strong cell–cell junctions. Much less is known about how the ECM regulates cells with weak cell–cell contact. Clustering characteristics were quantified in rat adenocarcinoma cells, which form clusters on physically adsorbed collagen substrates, but not on covalently attached collagen substrates. Covalently attaching collagen inhibited desorption of collagen from the surface. While changes in proliferation rate could not explain differences seen in the clustering, changes in cell motility could. Cells plated under conditions that resulted in more clustering had a lower persistence time and slower migration rate than those under conditions that resulted in less clustering. Understanding how the ECM regulates clustering will not only impact the fundamental understanding of cancer progression, but also will guide the design of tissue engineered constructs that allow for the clustering or dissemination of cells throughout the construct. (paper)

  5. External Evaluation Measures for Subspace Clustering

    DEFF Research Database (Denmark)

    Günnemann, Stephan; Färber, Ines; Müller, Emmanuel

    2011-01-01

    research area of subspace clustering. We formalize general quality criteria for subspace clustering measures not yet addressed in the literature. We compare the existing external evaluation methods based on these criteria and pinpoint limitations. We propose a novel external evaluation measure which meets...

  6. Identification of new candidate drugs for lung cancer using chemical-chemical interactions, chemical-protein interactions and a K-means clustering algorithm.

    Science.gov (United States)

    Lu, Jing; Chen, Lei; Yin, Jun; Huang, Tao; Bi, Yi; Kong, Xiangyin; Zheng, Mingyue; Cai, Yu-Dong

    2016-01-01

    Lung cancer, characterized by uncontrolled cell growth in the lung tissue, is the leading cause of global cancer deaths. Until now, effective treatment of this disease is limited. Many synthetic compounds have emerged with the advancement of combinatorial chemistry. Identification of effective lung cancer candidate drug compounds among them is a great challenge. Thus, it is necessary to build effective computational methods that can assist us in selecting for potential lung cancer drug compounds. In this study, a computational method was proposed to tackle this problem. The chemical-chemical interactions and chemical-protein interactions were utilized to select candidate drug compounds that have close associations with approved lung cancer drugs and lung cancer-related genes. A permutation test and K-means clustering algorithm were employed to exclude candidate drugs with low possibilities to treat lung cancer. The final analysis suggests that the remaining drug compounds have potential anti-lung cancer activities and most of them have structural dissimilarity with approved drugs for lung cancer.

  7. Comparing 3 dietary pattern methods--cluster analysis, factor analysis, and index analysis--With colorectal cancer risk: The NIH-AARP Diet and Health Study.

    Science.gov (United States)

    Reedy, Jill; Wirfält, Elisabet; Flood, Andrew; Mitrou, Panagiota N; Krebs-Smith, Susan M; Kipnis, Victor; Midthune, Douglas; Leitzmann, Michael; Hollenbeck, Albert; Schatzkin, Arthur; Subar, Amy F

    2010-02-15

    The authors compared dietary pattern methods-cluster analysis, factor analysis, and index analysis-with colorectal cancer risk in the National Institutes of Health (NIH)-AARP Diet and Health Study (n = 492,306). Data from a 124-item food frequency questionnaire (1995-1996) were used to identify 4 clusters for men (3 clusters for women), 3 factors, and 4 indexes. Comparisons were made with adjusted relative risks and 95% confidence intervals, distributions of individuals in clusters by quintile of factor and index scores, and health behavior characteristics. During 5 years of follow-up through 2000, 3,110 colorectal cancer cases were ascertained. In men, the vegetables and fruits cluster, the fruits and vegetables factor, the fat-reduced/diet foods factor, and all indexes were associated with reduced risk; the meat and potatoes factor was associated with increased risk. In women, reduced risk was found with the Healthy Eating Index-2005 and increased risk with the meat and potatoes factor. For men, beneficial health characteristics were seen with all fruit/vegetable patterns, diet foods patterns, and indexes, while poorer health characteristics were found with meat patterns. For women, findings were similar except that poorer health characteristics were seen with diet foods patterns. Similarities were found across methods, suggesting basic qualities of healthy diets. Nonetheless, findings vary because each method answers a different question.

  8. Strategies used by breast cancer survivors to address work-related limitations during and after treatment.

    Science.gov (United States)

    Sandberg, Joanne C; Strom, Carla; Arcury, Thomas A

    2014-01-01

    The primary objective of this exploratory study was to delineate the broad range of adjustments women breast cancer survivors draw upon to minimize cancer-related limitations at the workplace. The study also analyzed whether survivors used strategies to address work-related limitations in isolation or in combination with other strategies, and whether they used formal or informal strategies. Semi-structured, in-depth interviews were conducted with 14 women who were employed at the time of diagnosis of breast cancer and who continued to work during treatment or returned to work. Interviews were conducted 3 to 24 months after diagnosis. An iterative process was used to systematically analyze the data (the transcripts) using qualitative methods. Participants who worked during or after treatment adjusted their work schedule, performed fewer or other tasks, modified or changed their work environment, reduced non-work activities at the workplace, used cognitive prompts, and acted preemptively to make work tasks manageable after their return to work. Survivors used multiple adjustments and drew upon both formal and informal tactics to minimize or prevent cancer- or treatment-related effects from negatively affecting job performance. Knowledge about the broad range of both formal and informal strategies identified in this study may enable health care and social services providers, as well as cancer survivors and employers, to identify a wide range of specific strategies that may reduce the negative effects of work-related limitations in specific work settings. Insights gained from this analysis should inform future research on work and cancer survivorship. Copyright © 2014 Jacobs Institute of Women's Health. Published by Elsevier Inc. All rights reserved.

  9. Clustering multilayer omics data using MuNCut.

    Science.gov (United States)

    Teran Hidalgo, Sebastian J; Ma, Shuangge

    2018-03-14

    Omics profiling is now a routine component of biomedical studies. In the analysis of omics data, clustering is an essential step and serves multiple purposes including for example revealing the unknown functionalities of omics units, assisting dimension reduction in outcome model building, and others. In the most recent omics studies, a prominent trend is to conduct multilayer profiling, which collects multiple types of genetic, genomic, epigenetic and other measurements on the same subjects. In the literature, clustering methods tailored to multilayer omics data are still limited. Directly applying the existing clustering methods to multilayer omics data and clustering each layer first and then combing across layers are both "suboptimal" in that they do not accommodate the interconnections within layers and across layers in an informative way. In this study, we develop the MuNCut (Multilayer NCut) clustering approach. It is tailored to multilayer omics data and sufficiently accounts for both across- and within-layer connections. It is based on the novel NCut technique and also takes advantages of regularized sparse estimation. It has an intuitive formulation and is computationally very feasible. To facilitate implementation, we develop the function muncut in the R package NcutYX. Under a wide spectrum of simulation settings, it outperforms competitors. The analysis of TCGA (The Cancer Genome Atlas) data on breast cancer and cervical cancer shows that MuNCut generates biologically meaningful results which differ from those using the alternatives. We propose a more effective clustering analysis of multiple omics data. It provides a new venue for jointly analyzing genetic, genomic, epigenetic and other measurements.

  10. Quantitative proteomics and transcriptomics addressing the estrogen receptor subtype-mediated effects in T47D breast cancer cells exposed to the phytoestrogen genistein

    NARCIS (Netherlands)

    Sotoca Covaleda, A.M.; Sollewijn Gelpke, M.D.; Boeren, S.; Ström, A.; Gustafsson, J.A.; Murk, A.J.; Rietjens, I.M.C.M.; Vervoort, J.J.M.

    2011-01-01

    The present study addresses, by transcriptomics and quantitative SILAC-based proteomics, the estrogen receptor alpha (ER) and beta (ERß)-mediated effects on gene and protein expression in T47D breast cancer cells exposed to the phytoestrogen genistein. Using the T47D human breast cancer cell line

  11. Hierarchical clustering of HPV genotype patterns in the ASCUS-LSIL triage study

    Science.gov (United States)

    Wentzensen, Nicolas; Wilson, Lauren E.; Wheeler, Cosette M.; Carreon, Joseph D.; Gravitt, Patti E.; Schiffman, Mark; Castle, Philip E.

    2010-01-01

    Anogenital cancers are associated with about 13 carcinogenic HPV types in a broader group that cause cervical intraepithelial neoplasia (CIN). Multiple concurrent cervical HPV infections are common which complicate the attribution of HPV types to different grades of CIN. Here we report the analysis of HPV genotype patterns in the ASCUS-LSIL triage study using unsupervised hierarchical clustering. Women who underwent colposcopy at baseline (n = 2780) were grouped into 20 disease categories based on histology and cytology. Disease groups and HPV genotypes were clustered using complete linkage. Risk of 2-year cumulative CIN3+, viral load, colposcopic impression, and age were compared between disease groups and major clusters. Hierarchical clustering yielded four major disease clusters: Cluster 1 included all CIN3 histology with abnormal cytology; Cluster 2 included CIN3 histology with normal cytology and combinations with either CIN2 or high-grade squamous intraepithelial lesion (HSIL) cytology; Cluster 3 included older women with normal or low grade histology/cytology and low viral load; Cluster 4 included younger women with low grade histology/cytology, multiple infections, and the highest viral load. Three major groups of HPV genotypes were identified: Group 1 included only HPV16; Group 2 included nine carcinogenic types plus non-carcinogenic HPV53 and HPV66; and Group 3 included non-carcinogenic types plus carcinogenic HPV33 and HPV45. Clustering results suggested that colposcopy missed a prevalent precancer in many women with no biopsy/normal histology and HSIL. This result was confirmed by an elevated 2-year risk of CIN3+ in these groups. Our novel approach to study multiple genotype infections in cervical disease using unsupervised hierarchical clustering can address complex genotype distributions on a population level. PMID:20959485

  12. Chemical exposure and leukemia clusters

    International Nuclear Information System (INIS)

    Cartwright, R.A.

    1992-01-01

    This paper draws attention to the heterogeneous distribution of leukemia in childhood and in adults. The topic of cluster reports and generalized clustering is addressed. These issues are applied to what is known of the risk factor for both adult and childhood leukemia. Finally, the significance of parental occupational exposure and childhood leukemia is covered. (author). 23 refs

  13. Doxorubicin-loaded magnetic nanoparticle clusters for chemo-photothermal treatment of the prostate cancer cell line PC3

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Weibing; Zheng, Xinmin [Department of Urology, Zhongnan Hospital, Wuhan University, Wuhan, 430071 (China); Shen, Shun [School of Pharmacy, Fudan University, No. 826 Zhangheng Road, Shanghai, 201203 (China); Wang, Xinghuan, E-mail: xinghuanwang9@gmail.com [Department of Urology, Zhongnan Hospital, Wuhan University, Wuhan, 430071 (China)

    2015-10-16

    In addition to the conventional cancer treatment such as radiotherapy, chemotherapy and surgical management, nanomedicine-based approaches have attracted widespread attention in recent years. In this paper, a promising nanocarrier, magnetic nanoparticle clusters (MNCs) as porous materials which provided enough room on the surface, was developed for loading chemotherapeutic agent of doxorubicin (DOX). Moreover, MNCs are a good near-infrared (NIR) photothermal mediator. Thus, MNCs have great potential both in photothermal therapy (PTT) and drug delivery for chemo-photothermal therapy of cancer. We firstly explored the destruction of prostate cancer in vitro by the combination of PTT and chemotherapy using DOX@MNCs. Upon NIR irradiation at 808 nm, more cancer cells were killed when PC3 cells incubated with DOX@MNCs, owing to both MNCs-mediated photothermal ablation and cytotoxicity of light-triggered DOX release. Compared with PTT or chemotherapy alone, the chemo-photothermal therapy by DOX@MNCs showed a synergistically higher therapeutic efficacy. - Highlights: • MNCs have great potential both in photothermal therapy and drug delivery. • DOX@MNCs were used for chemo-photothermal therapy of prostate cancer cells. • DOX@MNCs showed a synergistically higher therapeutic efficacy.

  14. Which benefits and harms of preoperative radiotherapy should be addressed? A Delphi consensus study among rectal cancer patients and radiation oncologists

    International Nuclear Information System (INIS)

    Kunneman, Marleen; Pieterse, Arwen H.; Stiggelbout, Anne M.; Marijnen, Corrie A.M.

    2015-01-01

    Background and purpose: We previously found considerable variation in information provision on preoperative radiotherapy (PRT) in rectal cancer. Our aims were to reach consensus among patients and oncologists on which benefits/harms of PRT should be addressed during the consultation, and to assess congruence with daily clinical practice. Materials and methods: A four-round Delphi-study was conducted with two expert panels: (1) 31 treated rectal cancer patients and (2) 35 radiation oncologists. Thirty-seven possible benefits/harms were shown. Participants indicated whether addressing the benefit/harm was (1) essential, (2) desired, (3) not necessary, or (4) to be avoided. Consensus was assumed when ⩾80% of the panel agreed. Results were compared to 81 audio-taped consultations. Results: The panels reached consensus that six topics should be addressed in all patients (local control, survival, long term altered defecation pattern and faecal incontinence, perineal wound healing problems, advice to avoid pregnancy), three in male patients (erectile dysfunction, ejaculation disorder, infertility), and four in female patients (vaginal dryness, pain during intercourse, menopause, infertility). On average, less than half of these topics were addressed in daily clinical practice. Conclusions: This study showed substantial overlap between benefits/harms that patients and oncologists consider important to address during the consultation, and at the same time poor congruence with daily clinical practice

  15. The concept of cluster

    DEFF Research Database (Denmark)

    Laursen, Lea Louise Holst; Møller, Jørgen

    2013-01-01

    villages in order to secure their future. This paper will address the concept of cluster-villages as a possible approach to strengthen the conditions of contemporary Danish villages. Cluster-villages is a concept that gather a number of villages in a network-structure where the villages both work together...... to forskellige positioner ser vi en ny mulighed for landsbyudvikling, som vi kalder Clustervillages. In order to investigate the potentials and possibilities of the cluster-village concept the paper will seek to unfold the concept strategically; looking into the benefits of such concept. Further, the paper seeks...

  16. Evaluation of a Bladder Cancer Cluster in a Population of Criminal Investigators with the Bureau of Alcohol, Tobacco, Firearms and Explosives—Part 1: The Cancer Incidence

    Directory of Open Access Journals (Sweden)

    Susan R. Davis

    2012-01-01

    Full Text Available This study investigated a bladder cancer cluster in a cohort of employees, predominately criminal investigators, participating in a medical surveillance program with the United States Bureau of Alcohol, Tobacco, Firearms and Explosives (ATF between 1995 and 2007. Standardized incidence ratios (SIRs were used to compare cancer incidences in the ATF population and the US reference population. Seven cases of bladder cancer (five cases verified by pathology report at time of analysis were identified among a total employee population of 3,768 individuals. All cases were white males and criminal investigators. Six of seven cases were in the 30 to 49 age range at the time of diagnosis. The SIRs for white male criminal investigators undergoing examinations were 7.63 (95% confidence interval = 3.70–15.75 for reported cases and 5.45 (2.33–12.76 for verified cases. White male criminal investigators in the ATF population are at statistically significant increased risk for bladder cancer.

  17. Comparison of tests for spatial heterogeneity on data with global clustering patterns and outliers

    Directory of Open Access Journals (Sweden)

    Hachey Mark

    2009-10-01

    Full Text Available Abstract Background The ability to evaluate geographic heterogeneity of cancer incidence and mortality is important in cancer surveillance. Many statistical methods for evaluating global clustering and local cluster patterns are developed and have been examined by many simulation studies. However, the performance of these methods on two extreme cases (global clustering evaluation and local anomaly (outlier detection has not been thoroughly investigated. Methods We compare methods for global clustering evaluation including Tango's Index, Moran's I, and Oden's I*pop; and cluster detection methods such as local Moran's I and SaTScan elliptic version on simulated count data that mimic global clustering patterns and outliers for cancer cases in the continental United States. We examine the power and precision of the selected methods in the purely spatial analysis. We illustrate Tango's MEET and SaTScan elliptic version on a 1987-2004 HIV and a 1950-1969 lung cancer mortality data in the United States. Results For simulated data with outlier patterns, Tango's MEET, Moran's I and I*pop had powers less than 0.2, and SaTScan had powers around 0.97. For simulated data with global clustering patterns, Tango's MEET and I*pop (with 50% of total population as the maximum search window had powers close to 1. SaTScan had powers around 0.7-0.8 and Moran's I has powers around 0.2-0.3. In the real data example, Tango's MEET indicated the existence of global clustering patterns in both the HIV and lung cancer mortality data. SaTScan found a large cluster for HIV mortality rates, which is consistent with the finding from Tango's MEET. SaTScan also found clusters and outliers in the lung cancer mortality data. Conclusion SaTScan elliptic version is more efficient for outlier detection compared with the other methods evaluated in this article. Tango's MEET and Oden's I*pop perform best in global clustering scenarios among the selected methods. The use of SaTScan for

  18. Space-time clustering of non-hodgkin lymphoma using residential histories in a Danish case-control study.

    Directory of Open Access Journals (Sweden)

    Rikke Baastrup Nordsborg

    Full Text Available Non-Hodgkin lymphoma (NHL is a frequent cancer and incidence rates have increased markedly during the second half of the 20(th century; however, the few established risk factors cannot explain this rise and still little is known about the aetiology of NHL. Spatial analyses have been applied in an attempt to identify environmental risk factors, but most studies do not take human mobility into account. The aim of this study was to identify clustering of NHL in space and time in Denmark, using 33 years of residential addresses. We utilised the nation-wide Danish registers and unique personal identification number that all Danish citizens have to conduct a register-based case-control study of 3210 NHL cases and two independent control groups of 3210 each. Cases were identified in the Danish Cancer Registry and controls were matched by age and sex and randomly selected from the Civil Registration System. Residential addresses of cases and controls from 1971 to 2003 were collected from the Civil Registration System and geocoded. Data on pervious hospital diagnoses and operations were obtained from the National Patient Register. We applied the methods of the newly developed Q-statistics to identify space-time clustering of NHL. All analyses were conducted with each of the two control groups, and we adjusted for previous history of autoimmune disease, HIV/AIDS or organ transplantation. Some areas with statistically significant clustering were identified; however, results were not consistent across the two control groups; thus we interpret the results as chance findings. We found no evidence for clustering of NHL in space and time using 33 years of residential histories, suggesting that if the rise in incidence of NHL is a result of risk factors that vary across space and time, the spatio-temporal variation of such factors in Denmark is too small to be detected with the applied method.

  19. Vacancy-indium clusters in implanted germanium

    KAUST Repository

    Chroneos, Alexander I.

    2010-04-01

    Secondary ion mass spectroscopy measurements of heavily indium doped germanium samples revealed that a significant proportion of the indium dose is immobile. Using electronic structure calculations we address the possibility of indium clustering with point defects by predicting the stability of indium-vacancy clusters, InnVm. We find that the formation of large clusters is energetically favorable, which can explain the immobility of the indium ions. © 2010 Elsevier B.V. All rights reserved.

  20. Vacancy-indium clusters in implanted germanium

    KAUST Repository

    Chroneos, Alexander I.; Kube, R.; Bracht, Hartmut A.; Grimes, Robin W.; Schwingenschlö gl, Udo

    2010-01-01

    Secondary ion mass spectroscopy measurements of heavily indium doped germanium samples revealed that a significant proportion of the indium dose is immobile. Using electronic structure calculations we address the possibility of indium clustering with point defects by predicting the stability of indium-vacancy clusters, InnVm. We find that the formation of large clusters is energetically favorable, which can explain the immobility of the indium ions. © 2010 Elsevier B.V. All rights reserved.

  1. Redefining the Breast Cancer Exosome Proteome by Tandem Mass Tag Quantitative Proteomics and Multivariate Cluster Analysis.

    Science.gov (United States)

    Clark, David J; Fondrie, William E; Liao, Zhongping; Hanson, Phyllis I; Fulton, Amy; Mao, Li; Yang, Austin J

    2015-10-20

    Exosomes are microvesicles of endocytic origin constitutively released by multiple cell types into the extracellular environment. With evidence that exosomes can be detected in the blood of patients with various malignancies, the development of a platform that uses exosomes as a diagnostic tool has been proposed. However, it has been difficult to truly define the exosome proteome due to the challenge of discerning contaminant proteins that may be identified via mass spectrometry using various exosome enrichment strategies. To better define the exosome proteome in breast cancer, we incorporated a combination of Tandem-Mass-Tag (TMT) quantitative proteomics approach and Support Vector Machine (SVM) cluster analysis of three conditioned media derived fractions corresponding to a 10 000g cellular debris pellet, a 100 000g crude exosome pellet, and an Optiprep enriched exosome pellet. The quantitative analysis identified 2 179 proteins in all three fractions, with known exosomal cargo proteins displaying at least a 2-fold enrichment in the exosome fraction based on the TMT protein ratios. Employing SVM cluster analysis allowed for the classification 251 proteins as "true" exosomal cargo proteins. This study provides a robust and vigorous framework for the future development of using exosomes as a potential multiprotein marker phenotyping tool that could be useful in breast cancer diagnosis and monitoring disease progression.

  2. CADx of mammographic masses and clustered microcalcifications: A review

    International Nuclear Information System (INIS)

    Elter, Matthias; Horsch, Alexander

    2009-01-01

    Breast cancer is the most common type of cancer among women in the western world. While mammography is regarded as the most effective tool for the detection and diagnosis of breast cancer, the interpretation of mammograms is a difficult and error-prone task. Hence, computer aids have been developed that assist the radiologist in the interpretation of mammograms. Computer-aided detection (CADe) systems address the problem that radiologists often miss signs of cancers that are retrospectively visible in mammograms. Furthermore, computer-aided diagnosis (CADx) systems have been proposed that assist the radiologist in the classification of mammographic lesions as benign or malignant. While a broad variety of approaches to both CADe and CADx systems have been published in the past two decades, an extensive survey of the state of the art is only available for CADe approaches. Therefore, a comprehensive review of the state of the art of CADx approaches is presented in this work. Besides providing a summary, the goals for this article are to identify relations, contradictions, and gaps in literature, and to suggest directions for future research. Because of the vast amount of publications on the topic, this survey is restricted to the two most important types of mammographic lesions: masses and clustered microcalcifications. Furthermore, it focuses on articles published in international journals.

  3. CADx of mammographic masses and clustered microcalcifications: A review

    Energy Technology Data Exchange (ETDEWEB)

    Elter, Matthias; Horsch, Alexander [Fraunhofer Institute for Integrated Circuits (IIS), Am Wolfsmantel 33, 91058 Erlangen (Germany); Institute for Medical Statistics and Epidemiology, TU Muenchen, Ismaninger Strasse 22, 81675 Muenchen (Germany) and Department of Computer Science, University of Tromsoe Breivika, N-9037 Tromsoe (Norway)

    2009-06-15

    Breast cancer is the most common type of cancer among women in the western world. While mammography is regarded as the most effective tool for the detection and diagnosis of breast cancer, the interpretation of mammograms is a difficult and error-prone task. Hence, computer aids have been developed that assist the radiologist in the interpretation of mammograms. Computer-aided detection (CADe) systems address the problem that radiologists often miss signs of cancers that are retrospectively visible in mammograms. Furthermore, computer-aided diagnosis (CADx) systems have been proposed that assist the radiologist in the classification of mammographic lesions as benign or malignant. While a broad variety of approaches to both CADe and CADx systems have been published in the past two decades, an extensive survey of the state of the art is only available for CADe approaches. Therefore, a comprehensive review of the state of the art of CADx approaches is presented in this work. Besides providing a summary, the goals for this article are to identify relations, contradictions, and gaps in literature, and to suggest directions for future research. Because of the vast amount of publications on the topic, this survey is restricted to the two most important types of mammographic lesions: masses and clustered microcalcifications. Furthermore, it focuses on articles published in international journals.

  4. Clustering of Sun Exposure Measurements

    OpenAIRE

    Have, Anna Szynkowiak; Larsen, Jan; Hansen, Lars Kai; Philipsen, Peter Alshede; Thieden, Elisabeth; Wulf, Hans Christian

    2002-01-01

    In a medically motivated Sun-exposure study, questionnaires concerning Sun-habits were collected from a number of subjects together with UV radiation measurements. This paper focuses on identifying clusters in the heterogeneous set of data for the purpose of understanding possible relations between Sun-habits exposure and eventually assessing the risk of skin cancer. A general probabilistic framework originally developed for text and Web mining is demonstrated to be useful for clustering of b...

  5. Functional Principal Component Analysis and Randomized Sparse Clustering Algorithm for Medical Image Analysis

    Science.gov (United States)

    Lin, Nan; Jiang, Junhai; Guo, Shicheng; Xiong, Momiao

    2015-01-01

    Due to the advancement in sensor technology, the growing large medical image data have the ability to visualize the anatomical changes in biological tissues. As a consequence, the medical images have the potential to enhance the diagnosis of disease, the prediction of clinical outcomes and the characterization of disease progression. But in the meantime, the growing data dimensions pose great methodological and computational challenges for the representation and selection of features in image cluster analysis. To address these challenges, we first extend the functional principal component analysis (FPCA) from one dimension to two dimensions to fully capture the space variation of image the signals. The image signals contain a large number of redundant features which provide no additional information for clustering analysis. The widely used methods for removing the irrelevant features are sparse clustering algorithms using a lasso-type penalty to select the features. However, the accuracy of clustering using a lasso-type penalty depends on the selection of the penalty parameters and the threshold value. In practice, they are difficult to determine. Recently, randomized algorithms have received a great deal of attentions in big data analysis. This paper presents a randomized algorithm for accurate feature selection in image clustering analysis. The proposed method is applied to both the liver and kidney cancer histology image data from the TCGA database. The results demonstrate that the randomized feature selection method coupled with functional principal component analysis substantially outperforms the current sparse clustering algorithms in image cluster analysis. PMID:26196383

  6. Carbon stars in lmc clusters revisited

    OpenAIRE

    Marigo, Paola; Girardi, Leo Alberto; Chiosi, Cesare

    1996-01-01

    Examining the available data for AGB stars in the Large Magellanic Cloud (LMC) clusters, we address the question about the mass interval of low- and intermediate-mass stars which eventually evolve into carbon stars (C stars) during the TP-AGB phase. We combine the data compiled by Frogel, Mould & Blanco (1990) - near infrared photometry and spectral classification for luminous AGB stars in clusters - with the ages for individual clusters derived from independent methods. The resulting distrib...

  7. Up-regulation of HOXB cluster genes are epigenetically regulated in tamoxifen-resistant MCF7 breast cancer cells.

    Science.gov (United States)

    Yang, Seoyeon; Lee, Ji-Yeon; Hur, Ho; Oh, Ji Hoon; Kim, Myoung Hee

    2018-05-28

    Tamoxifen (TAM) is commonly used to treat estrogen receptor (ER)-positive breast cancer. Despite the remarkable benefits, resistance to TAM presents a serious therapeutic challenge. Since several HOX transcription factors have been proposed as strong candidates in the development of resistance to TAM therapy in breast cancer, we generated an in vitro model of acquired TAM resistance using ER-positive MCF7 breast cancer cells (MCF7-TAMR), and analyzed the expression pattern and epigenetic states of HOX genes. HOXB cluster genes were uniquely up-regulated in MCF7-TAMR cells. Survival analysis of in slico data showed the correlation of high expression of HOXB genes with poor response to TAM in ER-positive breast cancer patients treated with TAM. Gain- and loss-of-function experiments showed that the overexpression of multi HOXB genes in MCF7 renders cancer cells more resistant to TAM, whereas the knockdown restores TAM sensitivity. Furthermore, activation of HOXB genes in MCF7-TAMR was associated with histone modifications, particularly the gain of H3K9ac. These findings imply that the activation of HOXB genes mediate the development of TAM resistance, and represent a target for development of new strategies to prevent or reverse TAM resistance.

  8. Breast Cancer and Modifiable Lifestyle Factors in Argentinean Women: Addressing Missing Data in a Case-Control Study

    Science.gov (United States)

    Coquet, Julia Becaria; Tumas, Natalia; Osella, Alberto Ruben; Tanzi, Matteo; Franco, Isabella; Diaz, Maria Del Pilar

    2016-01-01

    A number of studies have evidenced the effect of modifiable lifestyle factors such as diet, breastfeeding and nutritional status on breast cancer risk. However, none have addressed the missing data problem in nutritional epidemiologic research in South America. Missing data is a frequent problem in breast cancer studies and epidemiological settings in general. Estimates of effect obtained from these studies may be biased, if no appropriate method for handling missing data is applied. We performed Multiple Imputation for missing values on covariates in a breast cancer case-control study of Córdoba (Argentina) to optimize risk estimates. Data was obtained from a breast cancer case control study from 2008 to 2015 (318 cases, 526 controls). Complete case analysis and multiple imputation using chained equations were the methods applied to estimate the effects of a Traditional dietary pattern and other recognized factors associated with breast cancer. Physical activity and socioeconomic status were imputed. Logistic regression models were performed. When complete case analysis was performed only 31% of women were considered. Although a positive association of Traditional dietary pattern and breast cancer was observed from both approaches (complete case analysis OR=1.3, 95%CI=1.0-1.7; multiple imputation OR=1.4, 95%CI=1.2-1.7), effects of other covariates, like BMI and breastfeeding, were only identified when multiple imputation was considered. A Traditional dietary pattern, BMI and breastfeeding are associated with the occurrence of breast cancer in this Argentinean population when multiple imputation is appropriately performed. Multiple Imputation is suggested in Latin America’s epidemiologic studies to optimize effect estimates in the future. PMID:27892664

  9. Exploring the Support Needs of Family Caregivers of Patients with Brain Cancer Using the CSNAT: A Comparative Study with Other Cancer Groups.

    Science.gov (United States)

    Aoun, Samar M; Deas, Kathleen; Howting, Denise; Lee, Gabriel

    2015-01-01

    A substantial burden is placed on family caregivers of patients diagnosed with brain cancers. Despite this, the support needs of the caregivers are often under-recognised and not addressed adequately in current routine and patient centred clinical care. The Carer Support Needs Assessment Tool (CSNAT) is a validated instrument designed to systematically identify and address caregiver needs [corrected]. It has been trialled in an Australian palliative care community setting using a stepped wedge cluster design involving 322 family carers of terminally ill patients. The current article reports on a subset from this trial, 29 caregivers of patients with primary brain cancer, and compares their profile and outcomes to those of other cancer groups. Caregiver strain was assessed using the Family Appraisal of Caregiving Questionnaire, caregiver physical and mental wellbeing using SF12 and caregiver workload using a questionnaire on support with activities of daily living (ADL). In comparison to caregivers of patients with all other cancers, the primary brain cancer group had significantly higher levels of caregiver strain, lower levels of mental wellbeing and a higher level of ADL workload. Their physical wellness also deteriorated significantly over time. An action plan approach led to practical solutions for addressing highlighted concerns. Four themes evolved from the family caregivers' feedback interviews: The extremely challenging caregiver experience with brain cancer; the systematic and practical approach of the CSNAT during rapid changes; connection with health professionals, feeling acknowledged and empowered; and timely advice and assurance of support during the caregiving journey. This preliminary study has demonstrated that the CSNAT provides a practical and useful tool for assessing the support needs of family caregivers of patients with brain cancer and has provided the basis for a larger scale, longitudinal study that allows a more detailed characterisation

  10. Automated detection of microcalcification clusters in mammograms

    Science.gov (United States)

    Karale, Vikrant A.; Mukhopadhyay, Sudipta; Singh, Tulika; Khandelwal, Niranjan; Sadhu, Anup

    2017-03-01

    Mammography is the most efficient modality for detection of breast cancer at early stage. Microcalcifications are tiny bright spots in mammograms and can often get missed by the radiologist during diagnosis. The presence of microcalcification clusters in mammograms can act as an early sign of breast cancer. This paper presents a completely automated computer-aided detection (CAD) system for detection of microcalcification clusters in mammograms. Unsharp masking is used as a preprocessing step which enhances the contrast between microcalcifications and the background. The preprocessed image is thresholded and various shape and intensity based features are extracted. Support vector machine (SVM) classifier is used to reduce the false positives while preserving the true microcalcification clusters. The proposed technique is applied on two different databases i.e DDSM and private database. The proposed technique shows good sensitivity with moderate false positives (FPs) per image on both databases.

  11. Scientific Cluster Deployment and Recovery - Using puppet to simplify cluster management

    Science.gov (United States)

    Hendrix, Val; Benjamin, Doug; Yao, Yushu

    2012-12-01

    Deployment, maintenance and recovery of a scientific cluster, which has complex, specialized services, can be a time consuming task requiring the assistance of Linux system administrators, network engineers as well as domain experts. Universities and small institutions that have a part-time FTE with limited time for and knowledge of the administration of such clusters can be strained by such maintenance tasks. This current work is the result of an effort to maintain a data analysis cluster (DAC) with minimal effort by a local system administrator. The realized benefit is the scientist, who is the local system administrator, is able to focus on the data analysis instead of the intricacies of managing a cluster. Our work provides a cluster deployment and recovery process (CDRP) based on the puppet configuration engine allowing a part-time FTE to easily deploy and recover entire clusters with minimal effort. Puppet is a configuration management system (CMS) used widely in computing centers for the automatic management of resources. Domain experts use Puppet's declarative language to define reusable modules for service configuration and deployment. Our CDRP has three actors: domain experts, a cluster designer and a cluster manager. The domain experts first write the puppet modules for the cluster services. A cluster designer would then define a cluster. This includes the creation of cluster roles, mapping the services to those roles and determining the relationships between the services. Finally, a cluster manager would acquire the resources (machines, networking), enter the cluster input parameters (hostnames, IP addresses) and automatically generate deployment scripts used by puppet to configure it to act as a designated role. In the event of a machine failure, the originally generated deployment scripts along with puppet can be used to easily reconfigure a new machine. The cluster definition produced in our CDRP is an integral part of automating cluster deployment

  12. Clustering Game Behavior Data

    DEFF Research Database (Denmark)

    Bauckhage, C.; Drachen, Anders; Sifa, Rafet

    2015-01-01

    of the causes, the proliferation of behavioral data poses the problem of how to derive insights therefrom. Behavioral data sets can be large, time-dependent and high-dimensional. Clustering offers a way to explore such data and to discover patterns that can reduce the overall complexity of the data. Clustering...... and other techniques for player profiling and play style analysis have, therefore, become popular in the nascent field of game analytics. However, the proper use of clustering techniques requires expertise and an understanding of games is essential to evaluate results. With this paper, we address game data...... scientists and present a review and tutorial focusing on the application of clustering techniques to mine behavioral game data. Several algorithms are reviewed and examples of their application shown. Key topics such as feature normalization are discussed and open problems in the context of game analytics...

  13. Cluster temperature. Methods for its measurement and stabilization

    International Nuclear Information System (INIS)

    Makarov, G N

    2008-01-01

    Cluster temperature is an important material parameter essential to many physical and chemical processes involving clusters and cluster beams. Because of the diverse methods by which clusters can be produced, excited, and stabilized, and also because of the widely ranging values of atomic and molecular binding energies (approximately from 10 -5 to 10 eV) and numerous energy relaxation channels in clusters, cluster temperature (internal energy) ranges from 10 -3 to about 10 8 K. This paper reviews research on cluster temperature and describes methods for its measurement and stabilization. The role of cluster temperature in and its influence on physical and chemical processes is discussed. Results on the temperature dependence of cluster properties are presented. The way in which cluster temperature relates to cluster structure and to atomic and molecular interaction potentials in clusters is addressed. Methods for strong excitation of clusters and channels for their energy relaxation are discussed. Some applications of clusters and cluster beams are considered. (reviews of topical problems)

  14. Glycogen synthase kinase 3 beta inhibits microRNA-183-96-182 cluster via the β-Catenin/TCF/LEF-1 pathway in gastric cancer cells.

    Science.gov (United States)

    Tang, Xiaoli; Zheng, Dong; Hu, Ping; Zeng, Zongyue; Li, Ming; Tucker, Lynne; Monahan, Renee; Resnick, Murray B; Liu, Manran; Ramratnam, Bharat

    2014-03-01

    Glycogen synthase kinase 3 beta (GSK3β) is a critical protein kinase that phosphorylates numerous proteins in cells and thereby impacts multiple pathways including the β-Catenin/TCF/LEF-1 pathway. MicroRNAs (miRs) are a class of noncoding small RNAs of ∼22 nucleotides in length. Both GSK3β and miR play myriad roles in cell functions including stem cell development, apoptosis, embryogenesis and tumorigenesis. Here we show that GSK3β inhibits the expression of miR-96, miR-182 and miR-183 through the β-Catenin/TCF/LEF-1 pathway. Knockout of GSK3β in mouse embryonic fibroblast cells increases expression of miR-96, miR-182 and miR-183, coinciding with increases in the protein level and nuclear translocation of β-Catenin. In addition, overexpression of β-Catenin enhances the expression of miR-96, miR-182 and miR-183 in human gastric cancer AGS cells. GSK3β protein levels are decreased in human gastric cancer tissue compared with surrounding normal gastric tissue, coinciding with increases of β-Catenin protein, miR-96, miR-182, miR-183 and primary miR-183-96-182 cluster (pri-miR-183). Furthermore, suppression of miR-183-96-182 cluster with miRCURY LNA miR inhibitors decreases the proliferation and migration of AGS cells. Knockdown of GSK3β with siRNA increases the proliferation of AGS cells. Mechanistically, we show that β-Catenin/TCF/LEF-1 binds to the promoter of miR-183-96-182 cluster gene and thereby activates the transcription of the cluster. In summary, our findings identify a novel role for GSK3β in the regulation of miR-183-96-182 biogenesis through β-Catenin/TCF/LEF-1 pathway in gastric cancer cells.

  15. Korean women: breast cancer knowledge, attitudes and behaviors

    Directory of Open Access Journals (Sweden)

    Ryujin Lisa T

    2001-08-01

    Full Text Available Abstract Introduction Clustered within the nomenclature of Asian American are numerous subgroups, each with their own ethnic heritage, cultural, and linguistic characteristics. An understanding of the prevailing health knowledge, attitudes, and screening behaviors of these subgroups is essential for creating population-specific health promotion programs. Methods Korean American women (123 completed baseline surveys of breast cancer knowledge, attitudes, and screening behaviors as part of an Asian grocery store-based breast cancer education program evaluation. Follow-up telephone surveys, initiated two weeks later, were completed by 93 women. Results Low adherence to the American Cancer Society's breast cancer screening guidelines and insufficient breast cancer knowledge were reported. Participants' receptiveness to the grocery store-based breast cancer education program underscores the importance of finding ways to reach Korean women with breast cancer early detection information and repeated cues for screening. The data also suggest that the Asian grocery store-based cancer education program being tested may have been effective in motivating a proportion of the women to schedule a breast cancer screening between the baseline and follow-up surveys. Conclusion The program offers a viable strategy to reach Korean women that addresses the language, cultural, transportation, and time barriers they face in accessing breast cancer early detection information.

  16. Socioeconomic and clinical factors are key to uncovering disparity in accrual onto therapeutic trials for breast cancer.

    Science.gov (United States)

    Behrendt, Carolyn E; Hurria, Arti; Tumyan, Lusine; Niland, Joyce C; Mortimer, Joanne E

    2014-11-01

    To monitor and address disparity in accrual, patient participation in cancer clinical trials is routinely summarized by race/ethnicity. To investigate whether confounding obscures racial/ethnic disparity in participation, all women with breast cancer treated by medical oncologists at City of Hope Comprehensive Cancer Center from 2004 through 2009 were classified by birthplace and self-reported race/ethnicity, and followed for accrual onto therapeutic trials through 2010. Undetectable on univariate analysis, significantly reduced participation by subjects of African, Asian, Eastern European, Latin American, and Middle Eastern ancestries was revealed after accounting for age, socioeconomic factors, tumor and oncologist characteristics, and intrapractice clustering of patients. Copyright © 2014 by the National Comprehensive Cancer Network.

  17. Clustering of Sun Exposure Measurements

    DEFF Research Database (Denmark)

    Have, Anna Szynkowiak; Larsen, Jan; Hansen, Lars Kai

    2002-01-01

    In a medically motivated Sun-exposure study, questionnaires concerning Sun-habits were collected from a number of subjects together with UV radiation measurements. This paper focuses on identifying clusters in the heterogeneous set of data for the purpose of understanding possible relations between...... Sun-habits exposure and eventually assessing the risk of skin cancer. A general probabilistic framework originally developed for text and Web mining is demonstrated to be useful for clustering of behavioral data. The framework combines principal component subspace projection with probabilistic...

  18. Testing feedback message framing and comparators to address prescribing of high-risk medications in nursing homes: protocol for a pragmatic, factorial, cluster-randomized trial.

    Science.gov (United States)

    Ivers, Noah M; Desveaux, Laura; Presseau, Justin; Reis, Catherine; Witteman, Holly O; Taljaard, Monica K; McCleary, Nicola; Thavorn, Kednapa; Grimshaw, Jeremy M

    2017-07-14

    Audit and feedback (AF) interventions that leverage routine administrative data offer a scalable and relatively low-cost method to improve processes of care. AF interventions are usually designed to highlight discrepancies between desired and actual performance and to encourage recipients to act to address such discrepancies. Comparing to a regional average is a common approach, but more recipients would have a discrepancy if compared to a higher-than-average level of performance. In addition, how recipients perceive and respond to discrepancies may depend on how the feedback itself is framed. We aim to evaluate the effectiveness of different comparators and framing in feedback on high-risk prescribing in nursing homes. This is a pragmatic, 2 × 2 factorial, cluster-randomized controlled trial testing variations in the comparator and framing on the effectiveness of quarterly AF in changing high-risk prescribing in nursing homes in Ontario, Canada. We grouped homes that share physicians into clusters and randomized these clusters into the four experimental conditions. Outcomes will be assessed after 6 months; all primary analyses will be by intention-to-treat. The primary outcome (monthly number of high-risk medications received by each patient) will be analysed using a general linear mixed effects regression model. We will present both four-arm and factorial analyses. With 160 clusters and an average of 350 beds per cluster, assuming no interaction and similar effects for each intervention, we anticipate 90% power to detect an absolute mean difference of 0.3 high-risk medications prescribed. A mixed-methods process evaluation will explore potential mechanisms underlying the observed effects, exploring targeted constructs including intention, self-efficacy, outcome expectations, descriptive norms, and goal prioritization. An economic analysis will examine cost-effectiveness analysis from the perspective of the publicly funded health care system. This protocol

  19. Detection of spatial aggregation of cases of cancer from data on patients and health centres contained in the Minimum Basic Data Set

    Directory of Open Access Journals (Sweden)

    Pablo Fernández-Navarro

    2018-05-01

    Full Text Available The feasibility of the Minimum Basic Data Set (MBDS as a tool in cancer research was explored monitoring its incidence through the detection of spatial clusters. Case-control studies based on MBDS and marked point process were carried out with the focus on the residence of patients from the Prince of Asturias University Hospital in Alcalá de Henares (Madrid, Spain. Patients older than 39 years with diagnoses of stomach, colorectal, lung, breast, prostate, bladder and kidney cancer, melanoma and haematological tumours were selected. Geocoding of the residence address of the cases was done by locating them in the continuous population roll provided by the Madrid Statistical Institute and extracting the coordinates. The geocoded control group was a random sample of 10 controls per case matched by frequency of age and sex. To assess case clusters, differences in Ripley K functions between cases and controls were calculated. The spatial location of clusters was explored by investigating spatial intensity and its ratio between cases and controls. Results suggest the existence of an aggregation of cancers with a common risk factor such as tobacco smoking (lung, bladder and kidney cancers. These clusters were located in an urban area with high socioeconomic deprivation. The feasibility of designing and carrying out case-control studies from the MBDS is shown and we conclude that MBDS can be a useful epidemiological tool for cancer surveillance and identification of risk factors through case-control spatial point process studies.

  20. Pain management in cancer center inpatients: a cluster randomized trial to evaluate a systematic integrated approach—The Edinburgh Pain Assessment and Management Tool

    OpenAIRE

    Fallon, M; Walker, J; Colvin, L; Rodriguez, A; Murray, G; Sharpe, M

    2018-01-01

    Purpose Pain is suboptimally managed in patients with cancer. We aimed to compare the effect of a policy of adding a clinician-delivered bedside pain assessment and management tool (Edinburgh Pain Assessment and management Tool [EPAT]) to usual care (UC) versus UC alone on pain outcomes. Patients and Methods In a two-arm, parallel group, cluster randomized (1:1) trial, we observed pain outcomes in 19 cancer centers in the United Kingdom and then randomly assigned the centers to eithe...

  1. Scientific Cluster Deployment and Recovery – Using puppet to simplify cluster management

    International Nuclear Information System (INIS)

    Hendrix, Val; Yao Yushu; Benjamin, Doug

    2012-01-01

    Deployment, maintenance and recovery of a scientific cluster, which has complex, specialized services, can be a time consuming task requiring the assistance of Linux system administrators, network engineers as well as domain experts. Universities and small institutions that have a part-time FTE with limited time for and knowledge of the administration of such clusters can be strained by such maintenance tasks. This current work is the result of an effort to maintain a data analysis cluster (DAC) with minimal effort by a local system administrator. The realized benefit is the scientist, who is the local system administrator, is able to focus on the data analysis instead of the intricacies of managing a cluster. Our work provides a cluster deployment and recovery process (CDRP) based on the puppet configuration engine allowing a part-time FTE to easily deploy and recover entire clusters with minimal effort. Puppet is a configuration management system (CMS) used widely in computing centers for the automatic management of resources. Domain experts use Puppet's declarative language to define reusable modules for service configuration and deployment. Our CDRP has three actors: domain experts, a cluster designer and a cluster manager. The domain experts first write the puppet modules for the cluster services. A cluster designer would then define a cluster. This includes the creation of cluster roles, mapping the services to those roles and determining the relationships between the services. Finally, a cluster manager would acquire the resources (machines, networking), enter the cluster input parameters (hostnames, IP addresses) and automatically generate deployment scripts used by puppet to configure it to act as a designated role. In the event of a machine failure, the originally generated deployment scripts along with puppet can be used to easily reconfigure a new machine. The cluster definition produced in our CDRP is an integral part of automating cluster deployment

  2. Magnetic resonance imaging with k-means clustering objectively measures whole muscle volume compartments in sarcopenia/cancer cachexia.

    Science.gov (United States)

    Gray, Calum; MacGillivray, Thomas J; Eeley, Clare; Stephens, Nathan A; Beggs, Ian; Fearon, Kenneth C; Greig, Carolyn A

    2011-02-01

    Sarcopenia and cachexia are characterized by infiltration of non-contractile tissue within muscle which influences area and volume measurements. We applied a statistical clustering (k-means) technique to magnetic resonance (MR) images of the quadriceps of young and elderly healthy women and women with cancer to objectively separate the contractile and non-contractile tissue compartments. MR scans of the thigh were obtained for 34 women (n = 16 young, (median) age 26 y; n = 9 older, age 80 y; n = 9 upper gastrointestinal cancer patients, age 65 y). Segmented regions of consecutive axial images were used to calculate cross-sectional area and (gross) volume. The k-means unsupervised algorithm was subsequently applied to the MR binary mask image array data with resultant volumes compared between groups. Older women and women with cancer had 37% and 48% less quadriceps muscle respectively than young women (p k-means subtracted a significant 9%, 14% and 20% non-contractile tissue from the quadriceps of young, older and patient groups respectively (p K-means objectively separates contractile and non-contractile tissue components. Women with upper GI cancer have significant fatty infiltration throughout whole muscle groups which is maintained when controlling for age. Copyright © 2010 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

  3. A nonparametric Bayesian approach for clustering bisulfate-based DNA methylation profiles.

    Science.gov (United States)

    Zhang, Lin; Meng, Jia; Liu, Hui; Huang, Yufei

    2012-01-01

    DNA methylation occurs in the context of a CpG dinucleotide. It is an important epigenetic modification, which can be inherited through cell division. The two major types of methylation include hypomethylation and hypermethylation. Unique methylation patterns have been shown to exist in diseases including various types of cancer. DNA methylation analysis promises to become a powerful tool in cancer diagnosis, treatment and prognostication. Large-scale methylation arrays are now available for studying methylation genome-wide. The Illumina methylation platform simultaneously measures cytosine methylation at more than 1500 CpG sites associated with over 800 cancer-related genes. Cluster analysis is often used to identify DNA methylation subgroups for prognosis and diagnosis. However, due to the unique non-Gaussian characteristics, traditional clustering methods may not be appropriate for DNA and methylation data, and the determination of optimal cluster number is still problematic. A Dirichlet process beta mixture model (DPBMM) is proposed that models the DNA methylation expressions as an infinite number of beta mixture distribution. The model allows automatic learning of the relevant parameters such as the cluster mixing proportion, the parameters of beta distribution for each cluster, and especially the number of potential clusters. Since the model is high dimensional and analytically intractable, we proposed a Gibbs sampling "no-gaps" solution for computing the posterior distributions, hence the estimates of the parameters. The proposed algorithm was tested on simulated data as well as methylation data from 55 Glioblastoma multiform (GBM) brain tissue samples. To reduce the computational burden due to the high data dimensionality, a dimension reduction method is adopted. The two GBM clusters yielded by DPBMM are based on data of different number of loci (P-value < 0.1), while hierarchical clustering cannot yield statistically significant clusters.

  4. Detecting space-time disease clusters with arbitrary shapes and sizes using a co-clustering approach

    Directory of Open Access Journals (Sweden)

    Sami Ullah

    2017-11-01

    Full Text Available Ability to detect potential space-time clusters in spatio-temporal data on disease occurrences is necessary for conducting surveillance and implementing disease prevention policies. Most existing techniques use geometrically shaped (circular, elliptical or square scanning windows to discover disease clusters. In certain situations, where the disease occurrences tend to cluster in very irregularly shaped areas, these algorithms are not feasible in practise for the detection of space-time clusters. To address this problem, a new algorithm is proposed, which uses a co-clustering strategy to detect prospective and retrospective space-time disease clusters with no restriction on shape and size. The proposed method detects space-time disease clusters by tracking the changes in space–time occurrence structure instead of an in-depth search over space. This method was utilised to detect potential clusters in the annual and monthly malaria data in Khyber Pakhtunkhwa Province, Pakistan from 2012 to 2016 visualising the results on a heat map. The results of the annual data analysis showed that the most likely hotspot emerged in three sub-regions in the years 2013-2014. The most likely hotspots in monthly data appeared in the month of July to October in each year and showed a strong periodic trend.

  5. Cluster analysis by optimal decomposition of induced fuzzy sets

    Energy Technology Data Exchange (ETDEWEB)

    Backer, E

    1978-01-01

    Nonsupervised pattern recognition is addressed and the concept of fuzzy sets is explored in order to provide the investigator (data analyst) additional information supplied by the pattern class membership values apart from the classical pattern class assignments. The basic ideas behind the pattern recognition problem, the clustering problem, and the concept of fuzzy sets in cluster analysis are discussed, and a brief review of the literature of the fuzzy cluster analysis is given. Some mathematical aspects of fuzzy set theory are briefly discussed; in particular, a measure of fuzziness is suggested. The optimization-clustering problem is characterized. Then the fundamental idea behind affinity decomposition is considered. Next, further analysis takes place with respect to the partitioning-characterization functions. The iterative optimization procedure is then addressed. The reclassification function is investigated and convergence properties are examined. Finally, several experiments in support of the method suggested are described. Four object data sets serve as appropriate test cases. 120 references, 70 figures, 11 tables. (RWR)

  6. CPTAC Collaborates with Molecular & Cellular Proteomics to Address Reproducibility in Targeted Assay Development | Office of Cancer Clinical Proteomics Research

    Science.gov (United States)

    The journal Molecular & Cellular Proteomics (MCP), in collaboration with the Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI), part of the National Institutes of Health, announce new guidelines and requirements for papers describing the development and application of targeted mass spectrometry measurements of peptides, modified peptides and proteins (Mol Cell Proteomics 2017; PMID: 28183812).  NCI’s participation is part of NIH’s overall effort to address the r

  7. Cancer survivorship: a new challenge in comprehensive cancer control.

    Science.gov (United States)

    Pollack, Lori A; Greer, Greta E; Rowland, Julia H; Miller, Andy; Doneski, Donna; Coughlin, Steven S; Stovall, Ellen; Ulman, Doug

    2005-10-01

    Cancer survivors are a growing population in the United States because of earlier cancer diagnosis, the aging of society, and more effective risk reduction and treatment. Concerns about the long-term physical, psychosocial, and economic effects of cancer treatment on cancer survivors and their families are increasingly being recognized and addressed by public, private, and non-profit organizations. The purpose of this paper is to discuss how survivorship fits within the framework of comprehensive cancer control. We summarize three national reports on cancer survivorship and highlight how various organizations and programs are striving to address the needs of cancer survivors through public health planning, including the challenges these groups face and the gaps in knowledge and available services. As cancer survivorship issues are being recognized, many organizations have objectives and programs to address concerns of those diagnosed with cancer. However, better coordination and dissemination may decrease overlap and increase the reach of efforts and there is limited evidence for the effectiveness and impact of these efforts.

  8. Toward the identification of communities with increased tobacco-associated cancer burden: Application of spatial modeling techniques

    Directory of Open Access Journals (Sweden)

    Noella A Dietz

    2011-01-01

    Full Text Available Introduction: Smoking-attributable risks for lung, esophageal, and head and neck (H/N cancers range from 54% to 90%. Identifying areas with higher than average cancer risk and smoking rates, then targeting those areas for intervention, is one approach to more rapidly lower the overall tobacco disease burden in a given state. Our research team used spatial modeling techniques to identify areas in Florida with higher than expected tobacco-associated cancer incidence clusters. Materials and Methods: Geocoded tobacco-associated incident cancer data from 1998 to 2002 from the Florida Cancer Data System were used. Tobacco-associated cancers included lung, esophageal, and H/N cancers. SaTScan was used to identify geographic areas that had statistically significant (P<0.10 excess age-adjusted rates of tobacco-associated cancers. The Poisson-based spatial scan statistic was used. Phi correlation coefficients were computed to examine associations among block groups with/without overlapping cancer clusters. The logistic regression was used to assess associations between county-level smoking prevalence rates and being diagnosed within versus outside a cancer cluster. Community-level smoking rates were obtained from the 2002 Florida Behavioral Risk Factor Surveillance System (BRFSS. Analyses were repeated using 2007 BRFSS to examine the consistency of associations. Results: Lung cancer clusters were geographically larger for both squamous cell and adenocarcinoma cases in Florida from 1998 to 2002, than esophageal or H/N clusters. There were very few squamous cell and adenocarcinoma esophageal cancer clusters. H/N cancer mapping showed some squamous cell and a very small amount of adenocarcinoma cancer clusters. Phi correlations were generally weak to moderate in strength. The odds of having an invasive lung cancer cluster increased by 12% per increase in the county-level smoking rate. Results were inconsistent for esophageal and H/N cancers, with some

  9. Swarm: robust and fast clustering method for amplicon-based studies

    Science.gov (United States)

    Rognes, Torbjørn; Quince, Christopher; de Vargas, Colomban; Dunthorn, Micah

    2014-01-01

    Popular de novo amplicon clustering methods suffer from two fundamental flaws: arbitrary global clustering thresholds, and input-order dependency induced by centroid selection. Swarm was developed to address these issues by first clustering nearly identical amplicons iteratively using a local threshold, and then by using clusters’ internal structure and amplicon abundances to refine its results. This fast, scalable, and input-order independent approach reduces the influence of clustering parameters and produces robust operational taxonomic units. PMID:25276506

  10. Swarm: robust and fast clustering method for amplicon-based studies

    Directory of Open Access Journals (Sweden)

    Frédéric Mahé

    2014-09-01

    Full Text Available Popular de novo amplicon clustering methods suffer from two fundamental flaws: arbitrary global clustering thresholds, and input-order dependency induced by centroid selection. Swarm was developed to address these issues by first clustering nearly identical amplicons iteratively using a local threshold, and then by using clusters’ internal structure and amplicon abundances to refine its results. This fast, scalable, and input-order independent approach reduces the influence of clustering parameters and produces robust operational taxonomic units.

  11. Clustering of near clusters versus cluster compactness

    International Nuclear Information System (INIS)

    Yu Gao; Yipeng Jing

    1989-01-01

    The clustering properties of near Zwicky clusters are studied by using the two-point angular correlation function. The angular correlation functions for compact and medium compact clusters, for open clusters, and for all near Zwicky clusters are estimated. The results show much stronger clustering for compact and medium compact clusters than for open clusters, and that open clusters have nearly the same clustering strength as galaxies. A detailed study of the compactness-dependence of correlation function strength is worth investigating. (author)

  12. Global methylation silencing of clustered proto-cadherin genes in cervical cancer: serving as diagnostic markers comparable to HPV

    International Nuclear Information System (INIS)

    Wang, Kai-Hung; Lin, Cuei-Jyuan; Liu, Chou-Jen; Liu, Dai-Wei; Huang, Rui-Lan; Ding, Dah-Ching; Weng, Ching-Feng; Chu, Tang-Yuan

    2015-01-01

    Epigenetic remodeling of cell adhesion genes is a common phenomenon in cancer invasion. This study aims to investigate global methylation of cell adhesion genes in cervical carcinogenesis and to apply them in early detection of cancer from cervical scraping. Genome-wide methylation array was performed on an investigation cohort, including 16 cervical intraepithelial neoplasia 3 (CIN3) and 20 cervical cancers (CA) versus 12 each of normal, inflammation and CIN1 as controls. Twelve members of clustered proto-cadherin (PCDH) genes were collectively methylated and silenced, which were validated in cancer cells of the cervix, endometrium, liver, head and neck, breast, and lung. In an independent cohort including 107 controls, 66 CIN1, 85 CIN2/3, and 38 CA, methylated PCDHA4 and PCDHA13 were detected in 2.8%, 24.2%, 52.9%, and 84.2% (P < 10 −25 ), and 2.8%, 24.2%, 50.6%, and 94.7% (P < 10 −29 ), respectively. In diagnosis of CIN2 or more severe lesion of the cervix, a combination test of methylated PCDHA4 or PCDHA13 from cervical scraping had a sensitivity, specificity, positive predictive value, and negative predictive value of 74.8%, 80.3%, 73%, and 81.8%, respectively. Testing of this combination from cervical scraping is equally sensitive but more specific than human papillomavirus (HPV) test in diagnosis of CIN2 or more severe lesions. The study disclosed a collective methylation of PCDH genes in cancer of cervix and other sites. At least two of them can be promising diagnostic markers for cervical cancer noninferior to HPV

  13. Tumor-Promoting Circuits That Regulate a Cancer-Related Chemokine Cluster: Dominance of Inflammatory Mediators Over Oncogenic Alterations

    International Nuclear Information System (INIS)

    Leibovich-Rivkin, Tal; Buganim, Yosef; Solomon, Hilla; Meshel, Tsipi; Rotter, Varda; Ben-Baruch, Adit

    2012-01-01

    Here, we investigated the relative contribution of genetic/signaling components versus microenvironmental factors to the malignancy phenotype. In this system, we took advantage of non-transformed fibroblasts that carried defined oncogenic modifications in Ras and/or p53. These cells were exposed to microenvironmental pressures, and the expression of a cancer-related chemokine cluster was used as readout for the malignancy potential (CCL2, CCL5, CXCL8, CXCL10). In cells kept in-culture, synergism between Ras hyper-activation and p53 dysfunction was required to up-regulate the expression of the chemokine cluster. The in vivo passage of Ras High /p53 Low -modified cells has led to tumor formation, accompanied by potentiation of chemokine release, implicating a powerful role for the tumor microenvironment in up-regulating the chemokine cluster. Indeed, we found that inflammatory mediators which are prevalent in tumor sites, such as TNFα and IL-1β, had a predominant impact on the release of the chemokines, which was substantially higher than that obtained by the oncogenic modifications alone, possibly acting through the transcription factors AP-1 and NF-κB. Together, our results propose that in the unbiased model system that we were using, inflammatory mediators of the tumor milieu have dominating roles over oncogenic modifications in dictating the expression of a pro-malignancy chemokine readout

  14. Large scale cluster computing workshop

    International Nuclear Information System (INIS)

    Dane Skow; Alan Silverman

    2002-01-01

    Recent revolutions in computer hardware and software technologies have paved the way for the large-scale deployment of clusters of commodity computers to address problems heretofore the domain of tightly coupled SMP processors. Near term projects within High Energy Physics and other computing communities will deploy clusters of scale 1000s of processors and be used by 100s to 1000s of independent users. This will expand the reach in both dimensions by an order of magnitude from the current successful production facilities. The goals of this workshop were: (1) to determine what tools exist which can scale up to the cluster sizes foreseen for the next generation of HENP experiments (several thousand nodes) and by implication to identify areas where some investment of money or effort is likely to be needed. (2) To compare and record experimences gained with such tools. (3) To produce a practical guide to all stages of planning, installing, building and operating a large computing cluster in HENP. (4) To identify and connect groups with similar interest within HENP and the larger clustering community

  15. Cluster-cluster clustering

    International Nuclear Information System (INIS)

    Barnes, J.; Dekel, A.; Efstathiou, G.; Frenk, C.S.; Yale Univ., New Haven, CT; California Univ., Santa Barbara; Cambridge Univ., England; Sussex Univ., Brighton, England)

    1985-01-01

    The cluster correlation function xi sub c(r) is compared with the particle correlation function, xi(r) in cosmological N-body simulations with a wide range of initial conditions. The experiments include scale-free initial conditions, pancake models with a coherence length in the initial density field, and hybrid models. Three N-body techniques and two cluster-finding algorithms are used. In scale-free models with white noise initial conditions, xi sub c and xi are essentially identical. In scale-free models with more power on large scales, it is found that the amplitude of xi sub c increases with cluster richness; in this case the clusters give a biased estimate of the particle correlations. In the pancake and hybrid models (with n = 0 or 1), xi sub c is steeper than xi, but the cluster correlation length exceeds that of the points by less than a factor of 2, independent of cluster richness. Thus the high amplitude of xi sub c found in studies of rich clusters of galaxies is inconsistent with white noise and pancake models and may indicate a primordial fluctuation spectrum with substantial power on large scales. 30 references

  16. Electron scattering on metal clusters and fullerenes

    International Nuclear Information System (INIS)

    Solov'yov, A.V.

    2001-01-01

    This paper gives a survey of physical phenomena manifesting themselves in electron scattering on atomic clusters. The main emphasis is made on electron scattering on fullerenes and metal clusters, however some results are applicable to other types of clusters as well. This work is addressed to theoretical aspects of electron-cluster scattering, however some experimental results are also discussed. It is demonstrated that the electron diffraction plays important role in the formation of both elastic and inelastic electron scattering cross sections. It is elucidated the essential role of the multipole surface and volume plasmon excitations in the formation of electron energy loss spectra on clusters (differential and total, above and below ionization potential) as well as the total inelastic scattering cross sections. Particular attention is paid to the elucidation of the role of the polarization interaction in low energy electron-cluster collisions. This problem is considered for electron attachment to metallic clusters and the plasmon enhanced photon emission. Finally, mechanisms of electron excitation widths formation and relaxation of electron excitations in metal clusters and fullerenes are discussed. (authors)

  17. Combinations of elevated tissue miRNA-17-92 cluster expression and serum prostate-specific antigen as potential diagnostic biomarkers for prostate cancer.

    Science.gov (United States)

    Feng, Sujuan; Qian, Xiaosong; Li, Han; Zhang, Xiaodong

    2017-12-01

    The aim of the present study was to investigate the effectiveness of the miR-17-92 cluster as a disease progression marker in prostate cancer (PCa). Reverse transcription-quantitative polymerase chain reaction analysis was used to detect the microRNA (miR)-17-92 cluster expression levels in tissues from patients with PCa or benign prostatic hyperplasia (BPH), in addition to in PCa and BPH cell lines. Spearman correlation was used for comparison and estimation of correlations between miRNA expression levels and clinicopathological characteristics such as the Gleason score and prostate-specific antigen (PSA). Receiver operating curve (ROC) analysis was performed for evaluation of specificity and sensitivity of miR-17-92 cluster expression levels for discriminating patients with PCa from patients with BPH. Kaplan-Meier analysis was plotted to investigate the predictive potential of miR-17-92 cluster for PCa biochemical recurrence. Expression of the majority of miRNAs in the miR-17-92 cluster was identified to be significantly increased in PCa tissues and cell lines. Bivariate correlation analysis indicated that the high expression of unregulated miRNAs was positively correlated with Gleason grade, but had no significant association with PSA. ROC curves demonstrated that high expression of miR-17-92 cluster predicted a higher diagnostic accuracy compared with PSA. Improved discriminating quotients were observed when combinations of unregulated miRNAs with PSA were used. Survival analysis confirmed a high combined miRNA score of miR-17-92 cluster was associated with shorter biochemical recurrence interval. miR-17-92 cluster could be a potential diagnostic and prognostic biomarker for PCa, and the combination of the miR-17-92 cluster and serum PSA may enhance the accuracy for diagnosis of PCa.

  18. Relative Expression of Vitamin D Hydroxylases, CYP27B1 and CYP24A1, and of Cyclooxygenase-2 and Heterogeneity of Human Colorectal Cancer in Relation to Age, Gender, Tumor Location, and Malignancy: Results from Factor and Cluster Analysis

    International Nuclear Information System (INIS)

    Brozek, Wolfgang; Manhardt, Teresa; Kállay, Enikö; Peterlik, Meinrad; Cross, Heide S.

    2012-01-01

    Previous studies on the significance of vitamin D insufficiency and chronic inflammation in colorectal cancer development clearly indicated that maintenance of cellular homeostasis in the large intestinal epithelium requires balanced interaction of 1,25-(OH) 2 D 3 and prostaglandin cellular signaling networks. The present study addresses the question how colorectal cancer pathogenesis depends on alterations of activities of vitamin D hydroxylases, i.e., CYP27B1-encoded 25-hydroxyvitamin D-1α-hydroxylase and CYP24A1-encoded 25-hydroxyvitamin D-24-hydroxylase, and inflammation-induced cyclooxygenase-2 (COX-2). Data from 105 cancer patients on CYP27B1, VDR, CYP24A1, and COX-2 mRNA expression in relation to tumor grade, anatomical location, gender and age were fit into a multivariate model of exploratory factor analysis. Nearly identical results were obtained by the principal factor and the maximum likelihood method, and these were confirmed by hierarchical cluster analysis: Within the eight mutually dependent variables studied four independent constellations were found that identify different features of colorectal cancer pathogenesis: (i) Escape of COX-2 activity from restraints by the CYP27B1/VDR system can initiate cancer growth anywhere in the colorectum regardless of age and gender; (ii) variations in COX-2 expression are mainly responsible for differences in cancer incidence in relation to tumor location; (iii) advancing age has a strong gender-specific influence on cancer incidence; (iv) progression from well differentiated to undifferentiated cancer is solely associated with a rise in CYP24A1 expression

  19. Relative Expression of Vitamin D Hydroxylases, CYP27B1 and CYP24A1, and of Cyclooxygenase-2 and Heterogeneity of Human Colorectal Cancer in Relation to Age, Gender, Tumor Location, and Malignancy: Results from Factor and Cluster Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Brozek, Wolfgang, E-mail: wolfgang.brozek@gmx.at; Manhardt, Teresa; Kállay, Enikö; Peterlik, Meinrad; Cross, Heide S. [Department of Pathophysiology, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna (Austria)

    2012-07-26

    Previous studies on the significance of vitamin D insufficiency and chronic inflammation in colorectal cancer development clearly indicated that maintenance of cellular homeostasis in the large intestinal epithelium requires balanced interaction of 1,25-(OH){sub 2}D{sub 3} and prostaglandin cellular signaling networks. The present study addresses the question how colorectal cancer pathogenesis depends on alterations of activities of vitamin D hydroxylases, i.e., CYP27B1-encoded 25-hydroxyvitamin D-1α-hydroxylase and CYP24A1-encoded 25-hydroxyvitamin D-24-hydroxylase, and inflammation-induced cyclooxygenase-2 (COX-2). Data from 105 cancer patients on CYP27B1, VDR, CYP24A1, and COX-2 mRNA expression in relation to tumor grade, anatomical location, gender and age were fit into a multivariate model of exploratory factor analysis. Nearly identical results were obtained by the principal factor and the maximum likelihood method, and these were confirmed by hierarchical cluster analysis: Within the eight mutually dependent variables studied four independent constellations were found that identify different features of colorectal cancer pathogenesis: (i) Escape of COX-2 activity from restraints by the CYP27B1/VDR system can initiate cancer growth anywhere in the colorectum regardless of age and gender; (ii) variations in COX-2 expression are mainly responsible for differences in cancer incidence in relation to tumor location; (iii) advancing age has a strong gender-specific influence on cancer incidence; (iv) progression from well differentiated to undifferentiated cancer is solely associated with a rise in CYP24A1 expression.

  20. Algorithms of maximum likelihood data clustering with applications

    Science.gov (United States)

    Giada, Lorenzo; Marsili, Matteo

    2002-12-01

    We address the problem of data clustering by introducing an unsupervised, parameter-free approach based on maximum likelihood principle. Starting from the observation that data sets belonging to the same cluster share a common information, we construct an expression for the likelihood of any possible cluster structure. The likelihood in turn depends only on the Pearson's coefficient of the data. We discuss clustering algorithms that provide a fast and reliable approximation to maximum likelihood configurations. Compared to standard clustering methods, our approach has the advantages that (i) it is parameter free, (ii) the number of clusters need not be fixed in advance and (iii) the interpretation of the results is transparent. In order to test our approach and compare it with standard clustering algorithms, we analyze two very different data sets: time series of financial market returns and gene expression data. We find that different maximization algorithms produce similar cluster structures whereas the outcome of standard algorithms has a much wider variability.

  1. AR-V7 in circulating tumor cells cluster as a predictive biomarker of abiraterone acetate and enzalutamide treatment in castration-resistant prostate cancer patients.

    Science.gov (United States)

    Okegawa, Takatsugu; Ninomiya, Naoki; Masuda, Kazuki; Nakamura, Yu; Tambo, Mitsuhiro; Nutahara, Kikuo

    2018-06-01

    We examined whether androgen receptor splice variant 7 (AR-V7) in circulating tumor cell(CTC)clusters can be used to predict survival in patients with bone metastatic castration resistant-prostate cancer (mCRPC) treated with abiraterone or enzalutamide. We retrospectively enrolled 98 patients with CRPC on abiraterone or enzalutamide, and investigated the prognostic value of CTC cluster detection (+ v -) and AR-V7 detection (+ v -) using a CTC cluster detection - based AR-V7 mRNA assay. We examined ≤50% prostate-specific antigen (PSA) responses, PSA progression-free survival (PSA-PFS), clinical and radiological progression-free survival (radiologic PSF), and overall survival (OS). We then assessed whether AR-V7 expression in CTC clusters identified after On-chip multi-imaging flow cytometry was related to disease progression and survival after first-line systemic therapy. All abiraterone-treated or enzalutamide-treated patients received prior docetaxel. The median follow-up was 20.7 (range: 3.0-37.0) months in the abiraterone and enzalutamide cohorts, respectively. Forty-nine of the 98 men (50.0%) were CTC cluster (-), 23 of the 98 men (23.5%) were CTC cluster(+)/AR-V7(-), and 26 of the 98 men (26.5%) were CTC cluster(+)/AR-V7(+). CTC cluster(+)/AR-V7(+) patients were more likely to have EOD ≥3 at diagnosis (P = 0.003), pain (P = 0.023), higher alkaline phosphatase levels (P cluster(+), CTC cluster(+)/AR-V7(-), and ALP >UNL were independently associated with a poor PSA-PFS, radiographic PFS, and OS in abiraterone-treated patients and enzalutamide-treated patients. The CTC clusters and AR-V7-positive CTC clusters detected were important for assessing the response to abiraterone or enzalutamide therapy and for predicting disease outcome. © 2018 Wiley Periodicals, Inc.

  2. Geovisual analytics to enhance spatial scan statistic interpretation: an analysis of U.S. cervical cancer mortality.

    Science.gov (United States)

    Chen, Jin; Roth, Robert E; Naito, Adam T; Lengerich, Eugene J; Maceachren, Alan M

    2008-11-07

    Kulldorff's spatial scan statistic and its software implementation - SaTScan - are widely used for detecting and evaluating geographic clusters. However, two issues make using the method and interpreting its results non-trivial: (1) the method lacks cartographic support for understanding the clusters in geographic context and (2) results from the method are sensitive to parameter choices related to cluster scaling (abbreviated as scaling parameters), but the system provides no direct support for making these choices. We employ both established and novel geovisual analytics methods to address these issues and to enhance the interpretation of SaTScan results. We demonstrate our geovisual analytics approach in a case study analysis of cervical cancer mortality in the U.S. We address the first issue by providing an interactive visual interface to support the interpretation of SaTScan results. Our research to address the second issue prompted a broader discussion about the sensitivity of SaTScan results to parameter choices. Sensitivity has two components: (1) the method can identify clusters that, while being statistically significant, have heterogeneous contents comprised of both high-risk and low-risk locations and (2) the method can identify clusters that are unstable in location and size as the spatial scan scaling parameter is varied. To investigate cluster result stability, we conducted multiple SaTScan runs with systematically selected parameters. The results, when scanning a large spatial dataset (e.g., U.S. data aggregated by county), demonstrate that no single spatial scan scaling value is known to be optimal to identify clusters that exist at different scales; instead, multiple scans that vary the parameters are necessary. We introduce a novel method of measuring and visualizing reliability that facilitates identification of homogeneous clusters that are stable across analysis scales. Finally, we propose a logical approach to proceed through the analysis of

  3. INDICATORS FOR CLUSTER SURVIVABILITY IN A DISPERSING CLOUD

    International Nuclear Information System (INIS)

    Chen, H.-C.; Ko, C.-M.

    2009-01-01

    We use N-body simulations to survey the response of embedded star clusters to the dispersal of their parent molecular cloud. The final stages of the clusters can be divided into three classes: the cluster (1) is destroyed, (2) has a loose structure, and (3) has a compact core. We are interested in three of the governing parameters of the parent cloud: (1) the mass, (2) the size, and (3) the dispersing rate. It is known that the final stage of the cluster is well correlated with the star formation efficiency (SFE) for systems with the same cluster and cloud profile. We deem that the SFE alone is not enough to address systems with clouds of different sizes. Our result shows that the initial cluster-cloud mass ratio at a certain Lagrangian radius and the initial kinetic energy are better indicators for the survivability of embedded clusters.

  4. Clustering of financial time series

    Science.gov (United States)

    D'Urso, Pierpaolo; Cappelli, Carmela; Di Lallo, Dario; Massari, Riccardo

    2013-05-01

    This paper addresses the topic of classifying financial time series in a fuzzy framework proposing two fuzzy clustering models both based on GARCH models. In general clustering of financial time series, due to their peculiar features, needs the definition of suitable distance measures. At this aim, the first fuzzy clustering model exploits the autoregressive representation of GARCH models and employs, in the framework of a partitioning around medoids algorithm, the classical autoregressive metric. The second fuzzy clustering model, also based on partitioning around medoids algorithm, uses the Caiado distance, a Mahalanobis-like distance, based on estimated GARCH parameters and covariances that takes into account the information about the volatility structure of time series. In order to illustrate the merits of the proposed fuzzy approaches an application to the problem of classifying 29 time series of Euro exchange rates against international currencies is presented and discussed, also comparing the fuzzy models with their crisp version.

  5. Structural profiles of human miRNA families from pairwise clustering

    DEFF Research Database (Denmark)

    Kaczkowski, Bogumil; Þórarinsson, Elfar; Reiche, Kristin

    2009-01-01

    secondary structure already predicted, little is known about the patterns of structural conservation among pre-miRNAs. We address this issue by clustering the human pre-miRNA sequences based on pairwise, sequence and secondary structure alignment using FOLDALIGN, followed by global multiple alignment...... of obtained clusters by WAR. As a result, the common secondary structure was successfully determined for four FOLDALIGN clusters: the RF00027 structural family of the Rfam database and three clusters with previously undescribed consensus structures. Availability: http://genome.ku.dk/resources/mirclust...

  6. Triggered cluster formation in the RMC

    Science.gov (United States)

    Li, Jin Zeng; Smith, Michael D.

    An investigation based on data from the spatially complete 2MASS Survey reveals that a remarkable burst of clustered star formation is taking place throughout the south-east quadrant of the Rosette Molecular Cloud. Compact clusters are forming in a multi-seeded mode, in parallel and at various places. In addition, sparse aggregates of embedded young stars are extensively distributed. Here we present the primary results and implications for high-mass and clustered star formation in this giant molecular cloud. In particular, we incorporate for the first time the birth of medium to low-mass stars into the scenario of sequential formation of OB clusters. Following the emergence of the young OB cluster NGC 2244, a variety of manifestations of forming clusters of medium to high mass appear in the vicinity of the swept-up layer of the H II region as well as further into the molecular cloud. The embedded clusters appear to form in a structured manner, which suggests they follow tracks laid out by the decay of macroturbulence. We address the possible origins of the turbulence. This leads us to propose a tree model to interpret the neat spatial distribution of clusters within a large section of the Rosette complex. Prominent new generation OB clusters are identified at the root of the tree pattern.

  7. Topic modeling for cluster analysis of large biological and medical datasets.

    Science.gov (United States)

    Zhao, Weizhong; Zou, Wen; Chen, James J

    2014-01-01

    The big data moniker is nowhere better deserved than to describe the ever-increasing prodigiousness and complexity of biological and medical datasets. New methods are needed to generate and test hypotheses, foster biological interpretation, and build validated predictors. Although multivariate techniques such as cluster analysis may allow researchers to identify groups, or clusters, of related variables, the accuracies and effectiveness of traditional clustering methods diminish for large and hyper dimensional datasets. Topic modeling is an active research field in machine learning and has been mainly used as an analytical tool to structure large textual corpora for data mining. Its ability to reduce high dimensionality to a small number of latent variables makes it suitable as a means for clustering or overcoming clustering difficulties in large biological and medical datasets. In this study, three topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, are proposed and tested on the cluster analysis of three large datasets: Salmonella pulsed-field gel electrophoresis (PFGE) dataset, lung cancer dataset, and breast cancer dataset, which represent various types of large biological or medical datasets. All three various methods are shown to improve the efficacy/effectiveness of clustering results on the three datasets in comparison to traditional methods. A preferable cluster analysis method emerged for each of the three datasets on the basis of replicating known biological truths. Topic modeling could be advantageously applied to the large datasets of biological or medical research. The three proposed topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, yield clustering improvements for the three different data types. Clusters more efficaciously represent truthful groupings and subgroupings in the data than traditional methods, suggesting

  8. Microgrids Real-Time Pricing Based on Clustering Techniques

    Directory of Open Access Journals (Sweden)

    Hao Liu

    2018-05-01

    Full Text Available Microgrids are widely spreading in electricity markets worldwide. Besides the security and reliability concerns for these microgrids, their operators need to address consumers’ pricing. Considering the growth of smart grids and smart meter facilities, it is expected that microgrids will have some level of flexibility to determine real-time pricing for at least some consumers. As such, the key challenge is finding an optimal pricing model for consumers. This paper, accordingly, proposes a new pricing scheme in which microgrids are able to deploy clustering techniques in order to understand their consumers’ load profiles and then assign real-time prices based on their load profile patterns. An improved weighted fuzzy average k-means is proposed to cluster load curve of consumers in an optimal number of clusters, through which the load profile of each cluster is determined. Having obtained the load profile of each cluster, real-time prices are given to each cluster, which is the best price given to all consumers in that cluster.

  9. Community strategies to address cancer disparities in Appalachian Kentucky.

    Science.gov (United States)

    Schoenberg, Nancy E; Howell, Britteny M; Fields, Nell

    2012-01-01

    Central Appalachian residents suffer disproportionate health disparities, including an all-cancer mortality rate 17% higher than the general population. During 10 focus groups and 19 key informant interviews, 91 Appalachian residents identified cancer screening challenges and strategies. Challenges included (1) inadequate awareness of screening need, (2) insufficient access to screening, and (3) lack of privacy. Strategies included (1) witnessing/storytelling, (2) capitalizing on family history, (3) improving publicity about screening resources, (4) relying on lay health advisors, and (5) bundling preventive services. These insights shaped our community-based participatory research intervention and offered strategies to others working in Appalachia, rural locales, and other traditionally underserved communities.

  10. When Do SMEs Benefit from E-Commerce in an Industrial Cluster?

    DEFF Research Database (Denmark)

    Hugger, Ada Scupola

    2005-01-01

    The goal of this paper is to explore how ICT networks may be used in industrial clusters, especially by SMEs. The two primary research questions addressed are as follows: 1) How do firms embedded in a cluster use public ICT infrastructures such as broadband access to the Internet? 2) Under what c...... conditions do firms in a cluster, especially SMEs, benefit from Internet usage?...

  11. Cancer as a complex phenotype: pattern of cancer distribution within and beyond the nuclear family.

    Directory of Open Access Journals (Sweden)

    Laufey T Amundadottir

    2004-12-01

    Full Text Available BACKGROUND: The contribution of low-penetrant susceptibility variants to cancer is not clear. With the aim of searching for genetic factors that contribute to cancer at one or more sites in the body, we have analyzed familial aggregation of cancer in extended families based on all cancer cases diagnosed in Iceland over almost half a century. METHODS AND FINDINGS: We have estimated risk ratios (RRs of cancer for first- and up to fifth-degree relatives both within and between all types of cancers diagnosed in Iceland from 1955 to 2002 by linking patient information from the Icelandic Cancer Registry to an extensive genealogical database, containing all living Icelanders and most of their ancestors since the settlement of Iceland. We evaluated the significance of the familial clustering for each relationship separately, all relationships combined (first- to fifth-degree relatives and for close (first- and second-degree and distant (third- to fifth-degree relatives. Most cancer sites demonstrate a significantly increased RR for the same cancer, beyond the nuclear family. Significantly increased familial clustering between different cancer sites is also documented in both close and distant relatives. Some of these associations have been suggested previously but others not. CONCLUSION: We conclude that genetic factors are involved in the etiology of many cancers and that these factors are in some cases shared by different cancer sites. However, a significantly increased RR conferred upon mates of patients with cancer at some sites indicates that shared environment or nonrandom mating for certain risk factors also play a role in the familial clustering of cancer. Our results indicate that cancer is a complex, often non-site-specific disease for which increased risk extends beyond the nuclear family.

  12. Development of on-chip multi-imaging flow cytometry for identification of imaging biomarkers of clustered circulating tumor cells.

    Directory of Open Access Journals (Sweden)

    Hyonchol Kim

    Full Text Available An on-chip multi-imaging flow cytometry system has been developed to obtain morphometric parameters of cell clusters such as cell number, perimeter, total cross-sectional area, number of nuclei and size of clusters as "imaging biomarkers", with simultaneous acquisition and analysis of both bright-field (BF and fluorescent (FL images at 200 frames per second (fps; by using this system, we examined the effectiveness of using imaging biomarkers for the identification of clustered circulating tumor cells (CTCs. Sample blood of rats in which a prostate cancer cell line (MAT-LyLu had been pre-implanted was applied to a microchannel on a disposable microchip after staining the nuclei using fluorescent dye for their visualization, and the acquired images were measured and compared with those of healthy rats. In terms of the results, clustered cells having (1 cell area larger than 200 µm2 and (2 nucleus area larger than 90 µm2 were specifically observed in cancer cell-implanted blood, but were not observed in healthy rats. In addition, (3 clusters having more than 3 nuclei were specific for cancer-implanted blood and (4 a ratio between the actual perimeter and the perimeter calculated from the obtained area, which reflects a shape distorted from ideal roundness, of less than 0.90 was specific for all clusters having more than 3 nuclei and was also specific for cancer-implanted blood. The collected clusters larger than 300 µm2 were examined by quantitative gene copy number assay, and were identified as being CTCs. These results indicate the usefulness of the imaging biomarkers for characterizing clusters, and all of the four examined imaging biomarkers-cluster area, nuclei area, nuclei number, and ratio of perimeter-can identify clustered CTCs in blood with the same level of preciseness using multi-imaging cytometry.

  13. Cluster and SOHO - a joint endeavor by ESA and NASA to address problems in solar, heliospheric, and space plasma physics

    International Nuclear Information System (INIS)

    Schmidt, R.; Domingo, V.; Shawhan, S.D.; Bohlin, D.

    1988-01-01

    The NASA/ESA Solar-Terrestrial Science Program, which consists of the four-spacecraft cluster mission and the Solar and Heliospheric Observatory (SOHO), is examined. It is expected that the SOHO spacecraft will be launched in 1995 to study solar interior structure and the physical processes associated with the solar corona. The SOHO design, operation, data, and ground segment are discussed. The Cluster mission is designed to study small-scale structures in the earth's plasma environment. The Soviet Union is expected to contribute two additional spacecraft, which will be similar to Cluster in instrumentation and design. The capabilities, mission strategy, spacecraft design, payload, and ground segment of Cluster are discussed. 19 references

  14. Chemical graph-theoretic cluster expansions

    International Nuclear Information System (INIS)

    Klein, D.J.

    1986-01-01

    A general computationally amenable chemico-graph-theoretic cluster expansion method is suggested as a paradigm for incorporation of chemical structure concepts in a systematic manner. The cluster expansion approach is presented in a formalism general enough to cover a variety of empirical, semiempirical, and even ab initio applications. Formally such approaches for the utilization of chemical structure-related concepts may be viewed as discrete analogues of Taylor series expansions. The efficacy of the chemical structure concepts then is simply bound up in the rate of convergence of the cluster expansions. In many empirical applications, e.g., boiling points, chromatographic separation coefficients, and biological activities, this rate of convergence has been observed to be quite rapid. More note will be made here of quantum chemical applications. Relations to questions concerning size extensivity of energies and size consistency of wave functions are addressed

  15. Addressable droplet microarrays for single cell protein analysis.

    Science.gov (United States)

    Salehi-Reyhani, Ali; Burgin, Edward; Ces, Oscar; Willison, Keith R; Klug, David R

    2014-11-07

    Addressable droplet microarrays are potentially attractive as a way to achieve miniaturised, reduced volume, high sensitivity analyses without the need to fabricate microfluidic devices or small volume chambers. We report a practical method for producing oil-encapsulated addressable droplet microarrays which can be used for such analyses. To demonstrate their utility, we undertake a series of single cell analyses, to determine the variation in copy number of p53 proteins in cells of a human cancer cell line.

  16. Clustering-based approaches to SAGE data mining

    Directory of Open Access Journals (Sweden)

    Wang Haiying

    2008-07-01

    Full Text Available Abstract Serial analysis of gene expression (SAGE is one of the most powerful tools for global gene expression profiling. It has led to several biological discoveries and biomedical applications, such as the prediction of new gene functions and the identification of biomarkers in human cancer research. Clustering techniques have become fundamental approaches in these applications. This paper reviews relevant clustering techniques specifically designed for this type of data. It places an emphasis on current limitations and opportunities in this area for supporting biologically-meaningful data mining and visualisation.

  17. Managing distance and covariate information with point-based clustering

    Directory of Open Access Journals (Sweden)

    Peter A. Whigham

    2016-09-01

    Full Text Available Abstract Background Geographic perspectives of disease and the human condition often involve point-based observations and questions of clustering or dispersion within a spatial context. These problems involve a finite set of point observations and are constrained by a larger, but finite, set of locations where the observations could occur. Developing a rigorous method for pattern analysis in this context requires handling spatial covariates, a method for constrained finite spatial clustering, and addressing bias in geographic distance measures. An approach, based on Ripley’s K and applied to the problem of clustering with deliberate self-harm (DSH, is presented. Methods Point-based Monte-Carlo simulation of Ripley’s K, accounting for socio-economic deprivation and sources of distance measurement bias, was developed to estimate clustering of DSH at a range of spatial scales. A rotated Minkowski L1 distance metric allowed variation in physical distance and clustering to be assessed. Self-harm data was derived from an audit of 2 years’ emergency hospital presentations (n = 136 in a New Zealand town (population ~50,000. Study area was defined by residential (housing land parcels representing a finite set of possible point addresses. Results Area-based deprivation was spatially correlated. Accounting for deprivation and distance bias showed evidence for clustering of DSH for spatial scales up to 500 m with a one-sided 95 % CI, suggesting that social contagion may be present for this urban cohort. Conclusions Many problems involve finite locations in geographic space that require estimates of distance-based clustering at many scales. A Monte-Carlo approach to Ripley’s K, incorporating covariates and models for distance bias, are crucial when assessing health-related clustering. The case study showed that social network structure defined at the neighbourhood level may account for aspects of neighbourhood clustering of DSH. Accounting for

  18. A latent class analysis of cancer risk behaviors among U.S. college students.

    Science.gov (United States)

    Kang, Joseph; Ciecierski, Christina Czart; Malin, Emily L; Carroll, Allison J; Gidea, Marian; Craft, Lynette L; Spring, Bonnie; Hitsman, Brian

    2014-07-01

    The purpose of this study is to understand how cancer risk behaviors cluster in U.S. college students and vary by race and ethnicity. Using the fall 2010 wave of the National College Health Assessment (NCHA), we conducted a latent class analysis (LCA) to evaluate the clustering of cancer risk behaviors/conditions: tobacco use, physical inactivity, unhealthy diet, alcohol binge drinking, and overweight/obesity. The identified clusters were then examined separately by students' self-reported race and ethnicity. Among 30,093 college students surveyed, results show a high prevalence of unhealthy diet as defined by insufficient fruit and vegetable intake (>95%) and physical inactivity (>60%). The LCA identified behavioral clustering for the entire sample and distinct clustering among Black and American Indian students. Cancer risk behaviors/conditions appear to cluster among college students differentially by race. Understanding how risk behaviors cluster in young adults can lend insight to racial disparities in cancer through adulthood. Health behavior interventions focused on modifying multiple risk behaviors and tailored to students' racial group could potentially have a much larger effect on cancer prevention than those targeting any single behavior. Copyright © 2014 Elsevier Inc. All rights reserved.

  19. Nurse-led group consultation intervention reduces depressive symptoms in men with localised prostate cancer: a cluster randomised controlled trial

    International Nuclear Information System (INIS)

    Schofield, Penelope; Gough, Karla; Lotfi-Jam, Kerryann; Bergin, Rebecca; Ugalde, Anna; Dudgeon, Paul; Crellin, Wallace; Schubach, Kathryn; Foroudi, Farshard; Tai, Keen Hun; Duchesne, Gillian; Sanson-Fisher, Rob; Aranda, Sanchia

    2016-01-01

    Radiotherapy for localised prostate cancer has many known and distressing side effects. The efficacy of group interventions for reducing psychological morbidity is lacking. This study investigated the relative benefits of a group nurse-led intervention on psychological morbidity, unmet needs, treatment-related concerns and prostate cancer-specific quality of life in men receiving curative intent radiotherapy for prostate cancer. This phase III, two-arm cluster randomised controlled trial included 331 men (consent rate: 72 %; attrition: 5 %) randomised to the intervention (n = 166) or usual care (n = 165). The intervention comprised four group and one individual consultation all delivered by specialist uro-oncology nurses. Primary outcomes were anxious and depressive symptoms as assessed by the Hospital Anxiety and Depression Scale. Unmet needs were assessed with the Supportive Care Needs Survey-SF34 Revised, treatment-related concerns with the Cancer Treatment Scale and quality of life with the Expanded Prostate Cancer Index −26. Assessments occurred before, at the end of and 6 months post-radiotherapy. Primary outcome analysis was by intention-to-treat and performed by fitting a linear mixed model to each outcome separately using all observed data. Mixed models analysis indicated that group consultations had a significant beneficial effect on one of two primary endpoints, depressive symptoms (p = 0.009), and one of twelve secondary endpoints, procedural concerns related to cancer treatment (p = 0.049). Group consultations did not have a significant beneficial effect on generalised anxiety, unmet needs and prostate cancer-specific quality of life. Compared with individual consultations offered as part of usual care, the intervention provides a means of delivering patient education and is associated with modest reductions in depressive symptoms and procedural concerns. Future work should seek to confirm the clinical feasibility and cost-effectiveness of group

  20. Geographical clustering of lung cancer in the province of Lecce, Italy: 1992-2001.

    Science.gov (United States)

    Bilancia, Massimo; Fedespina, Alessandro

    2009-07-01

    The triennial mortality rates for lung cancer in the two decades 1981-2001 in the province of Lecce, Italy, are significantly higher than those for the entire region of Apulia (to which the Province of Lecce belongs) and the national reference rates. Moreover, analyzing the rates in the three-year periods 1993-95, 1996-98 and 1999-01, there is a dramatic increase in mortality for both males and females, which still remains essentially unexplained: to understand the extent of this phenomenon, it is worth noting that the standardized mortality rate for males in 1999-01 is equal to 13.92 per 10000 person-years, compared to a value of 6.96 for Italy in the 2000-2002 period.These data have generated a considerable concern in the press and public opinion, which with little scientific reasoning have sometimes identified suspected culprits of the risk excess (for example, the emission caused by a number of large industrial sites located in the provinces of Brindisi and Taranto, bordering the Province of Lecce). The objective of this paper is to study on a scientifically sound basis the spatial distribution of risk for lung cancer mortality in the province of Lecce. Our goal is to demonstrate that most of the previous explanations are not supported by data: to this end, we will follow a hybrid approach that combines both frequentist and Bayesian disease mapping methods. Furthermore, we define a new sequential algorithm based on a modified version of the Besag-York-Mollié (BYM) model, suitably modified to detect geographical clusters of disease. Standardized mortality ratios (SMRs) for lung cancer in the province of Lecce: For males, the relative risk (measured by means of SMR, i.e. the ratio between observed and expected cases in each area under internal standardization) was judged to be significantly greater than 1 in many municipal areas, the significance being evaluated under the null hypothesis of neutral risk on the ground of area-specific p-values (denoted by rhoi

  1. Plasma soluble cluster of differentiation 147 levels are increased in breast cancer patients and associated with lymph node metastasis and chemoresistance.

    Science.gov (United States)

    Kuang, Y H; Liu, Y J; Tang, L L; Wang, S M; Yan, G J; Liao, L Q

    2018-05-25

    Cluster of differentiation 147 (CD147) contributes to breast cancer invasion, metastasis, and multidrug resistance. Recent studies have shown that peripheral soluble CD147 (sCD147) is increased in hepatocellular tumour and multiple myeloma patients and correlated with disease severity. The primary aim of our study was to assess the level, as well as the biological and clinical significance of sCD147 in breast cancer. We tested plasma sCD147 levels in 308 breast cancer patients by enzyme-linked immunosorbent assay between February 2014 and February 2017. A subset of 165 cases of benign breast diseases was included as a control group at the same period. We analysed the clinical significance of plasma sCD147 with relevance to clinicopathological factors of breast cancer patients. Plasma sCD147 levels were significantly higher in patients with primary breast cancer than those with benign breast diseases (P=0.001), in patients with locally advanced breast cancer (T3-T4 tumour) than those in early breast cancer (T1-T2 tumour; P=0.001), in patients with lymph node metastasis than in those without (P<0.001), and in patients with high recurrence risk than those with medium recurrence risk (P<0.001). Plasma sCD147 levels were also significantly higher in the chemotherapy-resistant group than in the chemotherapy-sensitive group (P=0.040). Plasma sCD147 was an independent predictor for lymph node metastasis in breast cancer patients (P=0.001). This is the first study to demonstrate that plasma sCD147 levels are elevated in breast cancer patients. Soluble CD147 is also associated with tumour size, lymph node metastasis, high recurrent risk, and chemoresistance. Our findings support that plasma sCD147 is an independent predictive factor for lymph node metastasis.

  2. Dynamically allocated virtual clustering management system

    Science.gov (United States)

    Marcus, Kelvin; Cannata, Jess

    2013-05-01

    The U.S Army Research Laboratory (ARL) has built a "Wireless Emulation Lab" to support research in wireless mobile networks. In our current experimentation environment, our researchers need the capability to run clusters of heterogeneous nodes to model emulated wireless tactical networks where each node could contain a different operating system, application set, and physical hardware. To complicate matters, most experiments require the researcher to have root privileges. Our previous solution of using a single shared cluster of statically deployed virtual machines did not sufficiently separate each user's experiment due to undesirable network crosstalk, thus only one experiment could be run at a time. In addition, the cluster did not make efficient use of our servers and physical networks. To address these concerns, we created the Dynamically Allocated Virtual Clustering management system (DAVC). This system leverages existing open-source software to create private clusters of nodes that are either virtual or physical machines. These clusters can be utilized for software development, experimentation, and integration with existing hardware and software. The system uses the Grid Engine job scheduler to efficiently allocate virtual machines to idle systems and networks. The system deploys stateless nodes via network booting. The system uses 802.1Q Virtual LANs (VLANs) to prevent experimentation crosstalk and to allow for complex, private networks eliminating the need to map each virtual machine to a specific switch port. The system monitors the health of the clusters and the underlying physical servers and it maintains cluster usage statistics for historical trends. Users can start private clusters of heterogeneous nodes with root privileges for the duration of the experiment. Users also control when to shutdown their clusters.

  3. Protein-gold clusters-capped mesoporous silica nanoparticles for high drug loading, autonomous gemcitabine/doxorubicin co-delivery, and in-vivo tumor imaging

    KAUST Repository

    Croissant, Jonas G.; Zhang, Dingyuan; Alsaiari, Shahad K.; Lu, Jie; Deng, Lin; Tamanoi, Fuyuhiko; Zink, Jeffrey I.; Khashab, Niveen M.

    2016-01-01

    Functional nanocarriers capable of transporting high drug contents without premature leakage and to controllably deliver several drugs are needed for better cancer treatments. To address this clinical need, gold cluster bovine serum albumin (AuNC@BSA) nanogates were engineered on mesoporous silica nanoparticles (MSN) for high drug loadings and co-delivery of two different anticancer drugs. The first drug, gemcitabine (GEM, 40 wt%), was loaded in positively-charged ammonium-functionalized MSN (MSN-NH3+). The second drug, doxorubicin (DOX, 32 wt%), was bound with negatively-charged AuNC@BSA electrostatically-attached onto MSN-NH3+, affording highly loaded pH-responsive MSN-AuNC@BSA nanocarriers. The co-delivery of DOX and GEM was achieved for the first time via an inorganic nanocarrier, possessing a zero-premature leakage behavior as well as drug loading capacities seven times higher than polymersome NPs. Besides, unlike the majority of strategies used to cap the pores of MSN, AuNC@BSA nanogates are biotools and were applied for targeted red nuclear staining and in-vivo tumor imaging. The straightforward non-covalent combination of MSN and gold-protein cluster bioconjugates thus leads to a simple, yet multifunctional nanotheranostic for the next generation of cancer treatments.

  4. Protein-gold clusters-capped mesoporous silica nanoparticles for high drug loading, autonomous gemcitabine/doxorubicin co-delivery, and in-vivo tumor imaging

    KAUST Repository

    Croissant, Jonas G.

    2016-03-23

    Functional nanocarriers capable of transporting high drug contents without premature leakage and to controllably deliver several drugs are needed for better cancer treatments. To address this clinical need, gold cluster bovine serum albumin (AuNC@BSA) nanogates were engineered on mesoporous silica nanoparticles (MSN) for high drug loadings and co-delivery of two different anticancer drugs. The first drug, gemcitabine (GEM, 40 wt%), was loaded in positively-charged ammonium-functionalized MSN (MSN-NH3+). The second drug, doxorubicin (DOX, 32 wt%), was bound with negatively-charged AuNC@BSA electrostatically-attached onto MSN-NH3+, affording highly loaded pH-responsive MSN-AuNC@BSA nanocarriers. The co-delivery of DOX and GEM was achieved for the first time via an inorganic nanocarrier, possessing a zero-premature leakage behavior as well as drug loading capacities seven times higher than polymersome NPs. Besides, unlike the majority of strategies used to cap the pores of MSN, AuNC@BSA nanogates are biotools and were applied for targeted red nuclear staining and in-vivo tumor imaging. The straightforward non-covalent combination of MSN and gold-protein cluster bioconjugates thus leads to a simple, yet multifunctional nanotheranostic for the next generation of cancer treatments.

  5. Control of entanglement transitions in quantum spin clusters

    Science.gov (United States)

    Irons, Hannah R.; Quintanilla, Jorge; Perring, Toby G.; Amico, Luigi; Aeppli, Gabriel

    2017-12-01

    Quantum spin clusters provide a platform for the experimental study of many-body entanglement. Here we address a simple model of a single-molecule nanomagnet featuring N interacting spins in a transverse field. The field can control an entanglement transition (ET). We calculate the magnetization, low-energy gap, and neutron-scattering cross section and find that the ET has distinct signatures, detectable at temperatures as high as 5% of the interaction strength. The signatures are stronger for smaller clusters.

  6. Energy Aware Cluster-Based Routing in Flying Ad-Hoc Networks.

    Science.gov (United States)

    Aadil, Farhan; Raza, Ali; Khan, Muhammad Fahad; Maqsood, Muazzam; Mehmood, Irfan; Rho, Seungmin

    2018-05-03

    Flying ad-hoc networks (FANETs) are a very vibrant research area nowadays. They have many military and civil applications. Limited battery energy and the high mobility of micro unmanned aerial vehicles (UAVs) represent their two main problems, i.e., short flight time and inefficient routing. In this paper, we try to address both of these problems by means of efficient clustering. First, we adjust the transmission power of the UAVs by anticipating their operational requirements. Optimal transmission range will have minimum packet loss ratio (PLR) and better link quality, which ultimately save the energy consumed during communication. Second, we use a variant of the K-Means Density clustering algorithm for selection of cluster heads. Optimal cluster heads enhance the cluster lifetime and reduce the routing overhead. The proposed model outperforms the state of the art artificial intelligence techniques such as Ant Colony Optimization-based clustering algorithm and Grey Wolf Optimization-based clustering algorithm. The performance of the proposed algorithm is evaluated in term of number of clusters, cluster building time, cluster lifetime and energy consumption.

  7. Energy Aware Cluster-Based Routing in Flying Ad-Hoc Networks

    Directory of Open Access Journals (Sweden)

    Farhan Aadil

    2018-05-01

    Full Text Available Flying ad-hoc networks (FANETs are a very vibrant research area nowadays. They have many military and civil applications. Limited battery energy and the high mobility of micro unmanned aerial vehicles (UAVs represent their two main problems, i.e., short flight time and inefficient routing. In this paper, we try to address both of these problems by means of efficient clustering. First, we adjust the transmission power of the UAVs by anticipating their operational requirements. Optimal transmission range will have minimum packet loss ratio (PLR and better link quality, which ultimately save the energy consumed during communication. Second, we use a variant of the K-Means Density clustering algorithm for selection of cluster heads. Optimal cluster heads enhance the cluster lifetime and reduce the routing overhead. The proposed model outperforms the state of the art artificial intelligence techniques such as Ant Colony Optimization-based clustering algorithm and Grey Wolf Optimization-based clustering algorithm. The performance of the proposed algorithm is evaluated in term of number of clusters, cluster building time, cluster lifetime and energy consumption.

  8. Understanding drugs in breast cancer through drug sensitivity screening.

    Science.gov (United States)

    Uhr, Katharina; Prager-van der Smissen, Wendy J C; Heine, Anouk A J; Ozturk, Bahar; Smid, Marcel; Göhlmann, Hinrich W H; Jager, Agnes; Foekens, John A; Martens, John W M

    2015-01-01

    With substantial numbers of breast tumors showing or acquiring treatment resistance, it is of utmost importance to develop new agents for the treatment of the disease, to know their effectiveness against breast cancer and to understand their relationships with other drugs to best assign the right drug to the right patient. To achieve this goal drug screenings on breast cancer cell lines are a promising approach. In this study a large-scale drug screening of 37 compounds was performed on a panel of 42 breast cancer cell lines representing the main breast cancer subtypes. Clustering, correlation and pathway analyses were used for data analysis. We found that compounds with a related mechanism of action had correlated IC50 values and thus grouped together when the cell lines were hierarchically clustered based on IC50 values. In total we found six clusters of drugs of which five consisted of drugs with related mode of action and one cluster with two drugs not previously connected. In total, 25 correlated and four anti-correlated drug sensitivities were revealed of which only one drug, Sirolimus, showed significantly lower IC50 values in the luminal/ERBB2 breast cancer subtype. We found expected interactions but also discovered new relationships between drugs which might have implications for cancer treatment regimens.

  9. A robust approach based on Weibull distribution for clustering gene expression data

    Directory of Open Access Journals (Sweden)

    Gong Binsheng

    2011-05-01

    Full Text Available Abstract Background Clustering is a widely used technique for analysis of gene expression data. Most clustering methods group genes based on the distances, while few methods group genes according to the similarities of the distributions of the gene expression levels. Furthermore, as the biological annotation resources accumulated, an increasing number of genes have been annotated into functional categories. As a result, evaluating the performance of clustering methods in terms of the functional consistency of the resulting clusters is of great interest. Results In this paper, we proposed the WDCM (Weibull Distribution-based Clustering Method, a robust approach for clustering gene expression data, in which the gene expressions of individual genes are considered as the random variables following unique Weibull distributions. Our WDCM is based on the concept that the genes with similar expression profiles have similar distribution parameters, and thus the genes are clustered via the Weibull distribution parameters. We used the WDCM to cluster three cancer gene expression data sets from the lung cancer, B-cell follicular lymphoma and bladder carcinoma and obtained well-clustered results. We compared the performance of WDCM with k-means and Self Organizing Map (SOM using functional annotation information given by the Gene Ontology (GO. The results showed that the functional annotation ratios of WDCM are higher than those of the other methods. We also utilized the external measure Adjusted Rand Index to validate the performance of the WDCM. The comparative results demonstrate that the WDCM provides the better clustering performance compared to k-means and SOM algorithms. The merit of the proposed WDCM is that it can be applied to cluster incomplete gene expression data without imputing the missing values. Moreover, the robustness of WDCM is also evaluated on the incomplete data sets. Conclusions The results demonstrate that our WDCM produces clusters

  10. German-Catalan workshop on epigenetics and cancer.

    Science.gov (United States)

    Vizoso, Miguel; Esteller, Manel

    2013-09-01

    In the First German-Catalan Workshop on Epigenetics and Cancer held in Heidelberg, Germany (June 17-19, 2013), cutting-edge laboratories (PEBC, IMPPC, DKFZ, and the Collaborative Research Centre Medical Epigenetics of Freiburg) discussed the latest breakthroughs in the field. The importance of DNA demethylation, non-coding and imprinted genes, metabolic stress, and cell transdifferentiation processes in cancer and non-cancer diseases were addressed in several lectures in a very participative and dynamic atmosphere.   The meeting brought together leading figures in the field of cancer epigenetics to present their research work from the last five years. Experts in different areas of oncology described important advances in colorectal, lung, neuroblastoma, leukemia, and lymphoma cancers. The workshop also provided an interesting forum for pediatrics, and focused on the need to improve the treatment of childhood tumors in order to avoid, as far as possible, brain damage and disruption of activity in areas of high plasticity. From the beginning, the relevance of "omics" and the advances in genome-wide analysis platforms, which allow cancer to be studied in a more comprehensive and inclusive way, was very clear. Modern "omics" offer the possibility of identifying metastases of uncertain origin and establishing epigenetic signatures linked to a specific cluster of patients with a particular prognosis. In this context, invited speakers described novel tumor-associated histone variants and DNA-specific methylation, highlighting their close connection with other processes such as cell-lineage commitment and stemness.

  11. AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number

    Directory of Open Access Journals (Sweden)

    Cooper James B

    2010-03-01

    Full Text Available Abstract Background Clustering the information content of large high-dimensional gene expression datasets has widespread application in "omics" biology. Unfortunately, the underlying structure of these natural datasets is often fuzzy, and the computational identification of data clusters generally requires knowledge about cluster number and geometry. Results We integrated strategies from machine learning, cartography, and graph theory into a new informatics method for automatically clustering self-organizing map ensembles of high-dimensional data. Our new method, called AutoSOME, readily identifies discrete and fuzzy data clusters without prior knowledge of cluster number or structure in diverse datasets including whole genome microarray data. Visualization of AutoSOME output using network diagrams and differential heat maps reveals unexpected variation among well-characterized cancer cell lines. Co-expression analysis of data from human embryonic and induced pluripotent stem cells using AutoSOME identifies >3400 up-regulated genes associated with pluripotency, and indicates that a recently identified protein-protein interaction network characterizing pluripotency was underestimated by a factor of four. Conclusions By effectively extracting important information from high-dimensional microarray data without prior knowledge or the need for data filtration, AutoSOME can yield systems-level insights from whole genome microarray expression studies. Due to its generality, this new method should also have practical utility for a variety of data-intensive applications, including the results of deep sequencing experiments. AutoSOME is available for download at http://jimcooperlab.mcdb.ucsb.edu/autosome.

  12. The Cognitive Limits to Economic Cluster Formation

    Directory of Open Access Journals (Sweden)

    Michael C. Carrol

    2012-01-01

    Full Text Available There has been increasing interest in the social dimensions of economic clusters. The literature now includes select examples of social network analysis plus an extensive discussion of learning regions. Unfortunately, much of this work treats the network as the primary unit of analysis. It may be that network attributes such as density, centrality, and power are primarily dependent on human limitations and not instituted factors. In other words, a human’s limited ability to process information may be a better determinant of cluster success than economic or network theory. The purpose of this paper is to highlight human limits in cluster formation. To do this, we draw on recent developments in the cognitive psychology and communications literatures. We explain that many of the factors that lead to underperforming cluster policies are the result of a human’s inability to develop and sustain a large number of social interactions. Any cluster policy must be cognizant of such limitations and carefully address these limits in the formation of the initial strategy.

  13. Understanding 3D human torso shape via manifold clustering

    Science.gov (United States)

    Li, Sheng; Li, Peng; Fu, Yun

    2013-05-01

    Discovering the variations in human torso shape plays a key role in many design-oriented applications, such as suit designing. With recent advances in 3D surface imaging technologies, people can obtain 3D human torso data that provide more information than traditional measurements. However, how to find different human shapes from 3D torso data is still an open problem. In this paper, we propose to use spectral clustering approach on torso manifold to address this problem. We first represent high-dimensional torso data in a low-dimensional space using manifold learning algorithm. Then the spectral clustering method is performed to get several disjoint clusters. Experimental results show that the clusters discovered by our approach can describe the discrepancies in both genders and human shapes, and our approach achieves better performance than the compared clustering method.

  14. Perspective: Size selected clusters for catalysis and electrochemistry

    Science.gov (United States)

    Halder, Avik; Curtiss, Larry A.; Fortunelli, Alessandro; Vajda, Stefan

    2018-03-01

    Size-selected clusters containing a handful of atoms may possess noble catalytic properties different from nano-sized or bulk catalysts. Size- and composition-selected clusters can also serve as models of the catalytic active site, where an addition or removal of a single atom can have a dramatic effect on their activity and selectivity. In this perspective, we provide an overview of studies performed under both ultra-high vacuum and realistic reaction conditions aimed at the interrogation, characterization, and understanding of the performance of supported size-selected clusters in heterogeneous and electrochemical reactions, which address the effects of cluster size, cluster composition, cluster-support interactions, and reaction conditions, the key parameters for the understanding and control of catalyst functionality. Computational modeling based on density functional theory sampling of local minima and energy barriers or ab initio molecular dynamics simulations is an integral part of this research by providing fundamental understanding of the catalytic processes at the atomic level, as well as by predicting new materials compositions which can be validated in experiments. Finally, we discuss approaches which aim at the scale up of the production of well-defined clusters for use in real world applications.

  15. Geographic Clusters of Basal Cell Carcinoma in a Northern California Health Plan Population.

    Science.gov (United States)

    Ray, G Thomas; Kulldorff, Martin; Asgari, Maryam M

    2016-11-01

    Rates of skin cancer, including basal cell carcinoma (BCC), the most common cancer, have been increasing over the past 3 decades. A better understanding of geographic clustering of BCCs can help target screening and prevention efforts. Present a methodology to identify spatial clusters of BCC and identify such clusters in a northern California population. This retrospective study used a BCC registry to determine rates of BCC by census block group, and used spatial scan statistics to identify statistically significant geographic clusters of BCCs, adjusting for age, sex, and socioeconomic status. The study population consisted of white, non-Hispanic members of Kaiser Permanente Northern California during years 2011 and 2012. Statistically significant geographic clusters of BCC as determined by spatial scan statistics. Spatial analysis of 28 408 individuals who received a diagnosis of at least 1 BCC in 2011 or 2012 revealed distinct geographic areas with elevated BCC rates. Among the 14 counties studied, BCC incidence ranged from 661 to 1598 per 100 000 person-years. After adjustment for age, sex, and neighborhood socioeconomic status, a pattern of 5 discrete geographic clusters emerged, with a relative risk ranging from 1.12 (95% CI, 1.03-1.21; P = .006) for a cluster in eastern Sonoma and northern Napa Counties to 1.40 (95% CI, 1.15-1.71; P Costa and west San Joaquin Counties, compared with persons residing outside that cluster. In this study of a northern California population, we identified several geographic clusters with modestly elevated incidence of BCC. Knowledge of geographic clusters can help inform future research on the underlying etiology of the clustering including factors related to the environment, health care access, or other characteristics of the resident population, and can help target screening efforts to areas of highest yield.

  16. How Do Social Capital and HIV/AIDS Outcomes Geographically Cluster and Which Sociocontextual Mechanisms Predict Differences Across Clusters?

    Science.gov (United States)

    Ransome, Yusuf; Dean, Lorraine T; Crawford, Natalie D; Metzger, David S; Blank, Michael B; Nunn, Amy S

    2017-09-01

    Place of residence has been associated with HIV transmission risks. Social capital, defined as features of social organization that improve efficiency of society by facilitating coordinated actions, often varies by neighborhood, and hypothesized to have protective effects on HIV care continuum outcomes. We examined whether the association between social capital and 2 HIV care continuum outcomes clustered geographically and whether sociocontextual mechanisms predict differences across clusters. Bivariate Local Moran's I evaluated geographical clustering in the association between social capital (participation in civic and social organizations, 2006, 2008, 2010) and [5-year (2007-2011) prevalence of late HIV diagnosis and linkage to HIV care] across Philadelphia, PA, census tracts (N = 378). Maps documented the clusters and multinomial regression assessed which sociocontextual mechanisms (eg, racial composition) predict differences across clusters. We identified 4 significant clusters (high social capital-high HIV/AIDS, low social capital-low HIV/AIDS, low social capital-high HIV/AIDS, and high social capital-low HIV/AIDS). Moran's I between social capital and late HIV diagnosis was (I = 0.19, z = 9.54, P social capital was lowest and HIV burden the highest, compared with clusters with high social capital and lowest HIV burden. The association between social participation and HIV care continuum outcomes cluster geographically in Philadelphia, PA. HIV prevention interventions should account for this phenomenon. Reducing geographic disparities will require interventions tailored to each continuum step and that address socioeconomic factors such as neighborhood median income.

  17. Knowledge intensive entrepreneurship from firm exit in a high-tech cluster: the case of the wireless communications cluster in Aalborg, Denmark

    DEFF Research Database (Denmark)

    Østergaard, Christian Richter; Park, Eun Kyung

    2012-01-01

    This chapter addresses how the existence of a cluster of firms with a specific knowledge base in a region affects future knowledge intensive entrepreneurship (KIE) in that region. Focusing on spinoff activities, the case of the wireless communication cluster in North Jutland in Denmark demonstrates...... how entrepreneurs develop knowledge, skills, routines, social capital and networks while working in an industry and then go on to use these resources to create new business in the same or related industries in the same approximate location....

  18. Investigation of Three Approaches to Address Fear of Recurrence Among Breast Cancer Survivors

    Science.gov (United States)

    2017-08-16

    Breast Neoplasms; Breast Cancer; Breast Carcinoma; Malignant Neoplasm of Breast; Cancer of Breast; Mammary Neoplasm, Human; Human Mammary Carcinoma; Malignant Tumor of Breast; Mammary Cancer; Mammary Carcinoma; Anxiety; Fear; Neoplasm Remission, Spontaneous; Spontaneous Neoplasm Regression; Regression, Spontaneous Neoplasm; Remission, Spontaneous Neoplasm; Spontaneous Neoplasm Remission

  19. Breast cancer data analysis for survivability studies and prediction.

    Science.gov (United States)

    Shukla, Nagesh; Hagenbuchner, Markus; Win, Khin Than; Yang, Jack

    2018-03-01

    Breast cancer is the most common cancer affecting females worldwide. Breast cancer survivability prediction is challenging and a complex research task. Existing approaches engage statistical methods or supervised machine learning to assess/predict the survival prospects of patients. The main objectives of this paper is to develop a robust data analytical model which can assist in (i) a better understanding of breast cancer survivability in presence of missing data, (ii) providing better insights into factors associated with patient survivability, and (iii) establishing cohorts of patients that share similar properties. Unsupervised data mining methods viz. the self-organising map (SOM) and density-based spatial clustering of applications with noise (DBSCAN) is used to create patient cohort clusters. These clusters, with associated patterns, were used to train multilayer perceptron (MLP) model for improved patient survivability analysis. A large dataset available from SEER program is used in this study to identify patterns associated with the survivability of breast cancer patients. Information gain was computed for the purpose of variable selection. All of these methods are data-driven and require little (if any) input from users or experts. SOM consolidated patients into cohorts of patients with similar properties. From this, DBSCAN identified and extracted nine cohorts (clusters). It is found that patients in each of the nine clusters have different survivability time. The separation of patients into clusters improved the overall survival prediction accuracy based on MLP and revealed intricate conditions that affect the accuracy of a prediction. A new, entirely data driven approach based on unsupervised learning methods improves understanding and helps identify patterns associated with the survivability of patient. The results of the analysis can be used to segment the historical patient data into clusters or subsets, which share common variable values and

  20. Accurate confidence aware clustering of array CGH tumor profiles.

    NARCIS (Netherlands)

    van Houte, B.P.P.; Heringa, J.

    2010-01-01

    Motivation: Chromosomal aberrations tend to be characteristic for given (sub)types of cancer. Such aberrations can be detected with array comparative genomic hybridization (aCGH). Clustering aCGH tumor profiles aids in identifying chromosomal regions of interest and provides useful diagnostic

  1. Geographical clustering of lung cancer in the province of Lecce, Italy: 1992–2001

    Science.gov (United States)

    Bilancia, Massimo; Fedespina, Alessandro

    2009-01-01

    Background The triennial mortality rates for lung cancer in the two decades 1981–2001 in the province of Lecce, Italy, are significantly higher than those for the entire region of Apulia (to which the Province of Lecce belongs) and the national reference rates. Moreover, analyzing the rates in the three-year periods 1993–95, 1996–98 and 1999–01, there is a dramatic increase in mortality for both males and females, which still remains essentially unexplained: to understand the extent of this phenomenon, it is worth noting that the standardized mortality rate for males in 1999–01 is equal to 13.92 per 10000 person-years, compared to a value of 6.96 for Italy in the 2000–2002 period. These data have generated a considerable concern in the press and public opinion, which with little scientific reasoning have sometimes identified suspected culprits of the risk excess (for example, the emission caused by a number of large industrial sites located in the provinces of Brindisi and Taranto, bordering the Province of Lecce). The objective of this paper is to study on a scientifically sound basis the spatial distribution of risk for lung cancer mortality in the province of Lecce. Our goal is to demonstrate that most of the previous explanations are not supported by data: to this end, we will follow a hybrid approach that combines both frequentist and Bayesian disease mapping methods. Furthermore, we define a new sequential algorithm based on a modified version of the Besag-York-Mollié (BYM) model, suitably modified to detect geographical clusters of disease. Results Standardized mortality ratios (SMRs) for lung cancer in the province of Lecce: For males, the relative risk (measured by means of SMR, i.e. the ratio between observed and expected cases in each area under internal standardization) was judged to be significantly greater than 1 in many municipal areas, the significance being evaluated under the null hypothesis of neutral risk on the ground of area

  2. Geographical clustering of lung cancer in the province of Lecce, Italy: 1992–2001

    Directory of Open Access Journals (Sweden)

    Fedespina Alessandro

    2009-07-01

    Full Text Available Abstract Background The triennial mortality rates for lung cancer in the two decades 1981–2001 in the province of Lecce, Italy, are significantly higher than those for the entire region of Apulia (to which the Province of Lecce belongs and the national reference rates. Moreover, analyzing the rates in the three-year periods 1993–95, 1996–98 and 1999–01, there is a dramatic increase in mortality for both males and females, which still remains essentially unexplained: to understand the extent of this phenomenon, it is worth noting that the standardized mortality rate for males in 1999–01 is equal to 13.92 per 10000 person-years, compared to a value of 6.96 for Italy in the 2000–2002 period. These data have generated a considerable concern in the press and public opinion, which with little scientific reasoning have sometimes identified suspected culprits of the risk excess (for example, the emission caused by a number of large industrial sites located in the provinces of Brindisi and Taranto, bordering the Province of Lecce. The objective of this paper is to study on a scientifically sound basis the spatial distribution of risk for lung cancer mortality in the province of Lecce. Our goal is to demonstrate that most of the previous explanations are not supported by data: to this end, we will follow a hybrid approach that combines both frequentist and Bayesian disease mapping methods. Furthermore, we define a new sequential algorithm based on a modified version of the Besag-York-Mollié (BYM model, suitably modified to detect geographical clusters of disease. Results Standardized mortality ratios (SMRs for lung cancer in the province of Lecce: For males, the relative risk (measured by means of SMR, i.e. the ratio between observed and expected cases in each area under internal standardization was judged to be significantly greater than 1 in many municipal areas, the significance being evaluated under the null hypothesis of neutral risk on

  3. Breast Cancer: Treatment Options

    Science.gov (United States)

    ... Breast Cancer > Breast Cancer: Treatment Options Request Permissions Breast Cancer: Treatment Options Approved by the Cancer.Net Editorial ... can be addressed as quickly as possible. Recurrent breast cancer If the cancer does return after treatment for ...

  4. Cluster processing for 16Mb DRAM production

    International Nuclear Information System (INIS)

    Bergendahl, A.; Horak, D.

    1989-01-01

    Multichamber and in-situ technology are used to meet the challenge of manufacturing 16-Mb cost/performance DRAMs. The 16-Mb fabrication process is more complex than earlier 1-Mb and 4-Mb chips. Clustering of sequential process steps effectively compensates for both manufacturing complexity and foreign-material (FM) related defect densities. The development time of clusters combining new processes and equipment in multiple automated steps is nearly as long as the product development cycle. This necessitates codevelopment of manufacturing process cluster with technology integration while addressing the factors influencing FM defect generation, processing turnaround time (TAT), manufacturing costs, yield and array cell and support device designs. The advantages of multichamber and in situ processing have resulted in their application throughout the entire 16-Mb DRAM process as appropriate equipment becomes available

  5. Understanding and effectively addressing breast cancer in African American women: Unpacking the social context.

    Science.gov (United States)

    Williams, David R; Mohammed, Selina A; Shields, Alexandra E

    2016-07-15

    Black women have a higher incidence of breast cancer before the age of 40 years, more severe disease at all ages, and an elevated mortality risk in comparison with white women. There is limited understanding of the contribution of social factors to these patterns. Elucidating the role of the social determinants of health in breast cancer disparities requires greater attention to how risk factors for breast cancer unfold over the lifecourse and to the complex ways in which socioeconomic status and racism shape exposure to psychosocial, physical, chemical, and other individual and community-level assaults that increase the risk of breast cancer. Research that takes seriously the social context in which black women live is also needed to maximize the opportunities to prevent breast cancer in this underserved group. Cancer 2016;122:2138-49. © 2016 American Cancer Society. © 2016 American Cancer Society.

  6. Tuning Properties in Silver Clusters

    KAUST Repository

    Joshi, Chakra Prasad

    2015-07-09

    The properties of Ag nanoclusters are not as well understood as those of their more precious Au cousins. However, a recent surge in the exploration of strategies to tune the physicochemical characteristics of Ag clusters addresses this imbalance, leading to new insights into their optical, luminescence, crystal habit, metal-core, ligand-shell and environmental properties. In this Perspective, we provide an overview of the latest strategies along with a brief introduction of the theoretical framework necessary to understand the properties of silver nanoclusters and the basis for their tuning. The advances in cluster research and the future prospects presented in this Perspective will eventually guide the next large systematic study of nanoclusters, resulting in a single collection of data similar to the periodic table of elements.

  7. Tuning Properties in Silver Clusters

    KAUST Repository

    Joshi, Chakra Prasad; Bootharaju, Megalamane Siddaramappa; Bakr, Osman

    2015-01-01

    The properties of Ag nanoclusters are not as well understood as those of their more precious Au cousins. However, a recent surge in the exploration of strategies to tune the physicochemical characteristics of Ag clusters addresses this imbalance, leading to new insights into their optical, luminescence, crystal habit, metal-core, ligand-shell and environmental properties. In this Perspective, we provide an overview of the latest strategies along with a brief introduction of the theoretical framework necessary to understand the properties of silver nanoclusters and the basis for their tuning. The advances in cluster research and the future prospects presented in this Perspective will eventually guide the next large systematic study of nanoclusters, resulting in a single collection of data similar to the periodic table of elements.

  8. Semi-supervised Probabilistic Distance Clustering and the Uncertainty of Classification

    Science.gov (United States)

    Iyigun, Cem; Ben-Israel, Adi

    Semi-supervised clustering is an attempt to reconcile clustering (unsupervised learning) and classification (supervised learning, using prior information on the data). These two modes of data analysis are combined in a parameterized model, the parameter θ ∈ [0, 1] is the weight attributed to the prior information, θ = 0 corresponding to clustering, and θ = 1 to classification. The results (cluster centers, classification rule) depend on the parameter θ, an insensitivity to θ indicates that the prior information is in agreement with the intrinsic cluster structure, and is otherwise redundant. This explains why some data sets (such as the Wisconsin breast cancer data, Merz and Murphy, UCI repository of machine learning databases, University of California, Irvine, CA) give good results for all reasonable classification methods. The uncertainty of classification is represented here by the geometric mean of the membership probabilities, shown to be an entropic distance related to the Kullback-Leibler divergence.

  9. xSyn: A Software Tool for Identifying Sophisticated 3-Way Interactions From Cancer Expression Data

    Directory of Open Access Journals (Sweden)

    Baishali Bandyopadhyay

    2017-08-01

    Full Text Available Background: Constructing gene co-expression networks from cancer expression data is important for investigating the genetic mechanisms underlying cancer. However, correlation coefficients or linear regression models are not able to model sophisticated relationships among gene expression profiles. Here, we address the 3-way interaction that 2 genes’ expression levels are clustered in different space locations under the control of a third gene’s expression levels. Results: We present xSyn, a software tool for identifying such 3-way interactions from cancer gene expression data based on an optimization procedure involving the usage of UPGMA (Unweighted Pair Group Method with Arithmetic Mean and synergy. The effectiveness is demonstrated by application to 2 real gene expression data sets. Conclusions: xSyn is a useful tool for decoding the complex relationships among gene expression profiles. xSyn is available at http://www.bdxconsult.com/xSyn.html .

  10. Beyond Apprenticeship: Knowledge Brokers and Sustainability of Apprentice-Based Clusters

    Directory of Open Access Journals (Sweden)

    Huasheng Zhu

    2016-12-01

    Full Text Available Knowledge learning and diffusion have long been discussed in the literature on the dynamics of industrial clusters, but recent literature provides little evidence for how different actors serve as knowledge brokers in the upgrading process of apprentice-based clusters, and does not dynamically consider how to preserve the sustainability of these clusters. This paper uses empirical evidence from an antique furniture manufacturing cluster in Xianyou, Fujian Province, in southeastern China, to examine the growth trajectory of the knowledge learning system of an antique furniture manufacturing cluster. It appears that the apprentice-based learning system is crucial during early stages of the cluster evolution, but later becomes complemented and relatively substituted by the role of both local governments and focal outsiders. This finding addresses the context of economic transformation and provides empirical insights into knowledge acquisition in apprentice-based clusters to question the rationality based on European and North American cases, and to provide a broader perspective for policy makers to trigger and sustain the development of apprentice-based clusters.

  11. Addressing Quality of Life Issues in Long Term Survivors of Head & Neck Cancer treated with Radiation Therapy

    Directory of Open Access Journals (Sweden)

    Bishan Basu

    2015-04-01

    Full Text Available The rapid advancement of curative treatment modalities has resulted in improvement of cure rates of head neck cancer leaving us with a larger number of long term survivors from the disease. Unfortunately, long term complications of therapy continue to hurt patients even after cure, compromising their quality of life. This is particularly true for the patients treated with primary radiation/chemo-radiation therapy, where so called organ preservation does not necessarily translate into preservation of organ function. Long term sequelae of treatment, particularly xerostomia and swallowing difficulties compromise the survivors’ quality of life. More studies, particularly suited to our clinical scenario, are warranted to address the quality of life issues in these patients, so that better evidence-based guidelines may be developed for their benefit.

  12. A point mutation in the [2Fe–2S] cluster binding region of the NAF-1 protein (H114C) dramatically hinders the cluster donor properties

    Energy Technology Data Exchange (ETDEWEB)

    Tamir, Sagi; Eisenberg-Domovich, Yael [The Hebrew University of Jerusalem, Edmond J. Safra Campus at Givat Ram, Jerusalem 91904 (Israel); Conlan, Andrea R.; Stofleth, Jason T.; Lipper, Colin H.; Paddock, Mark L. [University of California at San Diego, La Jolla, CA 92093 (United States); Mittler, Ron [University of North Texas, Denton, TX 76203 (United States); Jennings, Patricia A. [University of California at San Diego, La Jolla, CA 92093 (United States); Livnah, Oded, E-mail: oded.livnah@huji.ac.il; Nechushtai, Rachel, E-mail: oded.livnah@huji.ac.il [The Hebrew University of Jerusalem, Edmond J. Safra Campus at Givat Ram, Jerusalem 91904 (Israel)

    2014-06-01

    NAF-1 has been shown to be related with human health and disease, is upregulated in epithelial breast cancer and suppression of its expression significantly suppresses tumor growth. It is shown that replacement of the single His ligand with Cys resulted in dramatic changes to the properties of its 2Fe-2S clusters without any global crystal structural changes. NAF-1 is an important [2Fe–2S] NEET protein associated with human health and disease. A mis-splicing mutation in NAF-1 results in Wolfram Syndrome type 2, a lethal childhood disease. Upregulation of NAF-1 is found in epithelial breast cancer cells, and suppression of NAF-1 expression by knockdown significantly suppresses tumor growth. Key to NAF-1 function is the NEET fold with its [2Fe–2S] cluster. In this work, the high-resolution structure of native NAF-1 was determined to 1.65 Å resolution (R factor = 13.5%) together with that of a mutant in which the single His ligand of its [2Fe–2S] cluster, His114, was replaced by Cys. The NAF-1 H114C mutant structure was determined to 1.58 Å resolution (R factor = 16.0%). All structural differences were localized to the cluster binding site. Compared with native NAF-1, the [2Fe–2S] clusters of the H114C mutant were found to (i) be 25-fold more stable, (ii) have a redox potential that is 300 mV more negative and (iii) have their cluster donation/transfer function abolished. Because no global structural differences were found between the mutant and the native (wild-type) NAF-1 proteins, yet significant functional differences exist between them, the NAF-1 H114C mutant is an excellent tool to decipher the underlying biological importance of the [2Fe–2S] cluster of NAF-1 in vivo.

  13. A point mutation in the [2Fe–2S] cluster binding region of the NAF-1 protein (H114C) dramatically hinders the cluster donor properties

    International Nuclear Information System (INIS)

    Tamir, Sagi; Eisenberg-Domovich, Yael; Conlan, Andrea R.; Stofleth, Jason T.; Lipper, Colin H.; Paddock, Mark L.; Mittler, Ron; Jennings, Patricia A.; Livnah, Oded; Nechushtai, Rachel

    2014-01-01

    NAF-1 has been shown to be related with human health and disease, is upregulated in epithelial breast cancer and suppression of its expression significantly suppresses tumor growth. It is shown that replacement of the single His ligand with Cys resulted in dramatic changes to the properties of its 2Fe-2S clusters without any global crystal structural changes. NAF-1 is an important [2Fe–2S] NEET protein associated with human health and disease. A mis-splicing mutation in NAF-1 results in Wolfram Syndrome type 2, a lethal childhood disease. Upregulation of NAF-1 is found in epithelial breast cancer cells, and suppression of NAF-1 expression by knockdown significantly suppresses tumor growth. Key to NAF-1 function is the NEET fold with its [2Fe–2S] cluster. In this work, the high-resolution structure of native NAF-1 was determined to 1.65 Å resolution (R factor = 13.5%) together with that of a mutant in which the single His ligand of its [2Fe–2S] cluster, His114, was replaced by Cys. The NAF-1 H114C mutant structure was determined to 1.58 Å resolution (R factor = 16.0%). All structural differences were localized to the cluster binding site. Compared with native NAF-1, the [2Fe–2S] clusters of the H114C mutant were found to (i) be 25-fold more stable, (ii) have a redox potential that is 300 mV more negative and (iii) have their cluster donation/transfer function abolished. Because no global structural differences were found between the mutant and the native (wild-type) NAF-1 proteins, yet significant functional differences exist between them, the NAF-1 H114C mutant is an excellent tool to decipher the underlying biological importance of the [2Fe–2S] cluster of NAF-1 in vivo

  14. The NIDS Cluster: Scalable, Stateful Network Intrusion Detection on Commodity Hardware

    Energy Technology Data Exchange (ETDEWEB)

    Tierney, Brian L; Vallentin, Matthias; Sommer, Robin; Lee, Jason; Leres, Craig; Paxson, Vern; Tierney, Brian

    2007-09-19

    In this work we present a NIDS cluster as a scalable solution for realizing high-performance, stateful network intrusion detection on commodity hardware. The design addresses three challenges: (i) distributing traffic evenly across an extensible set of analysis nodes in a fashion that minimizes the communication required for coordination, (ii) adapting the NIDS's operation to support coordinating its low-level analysis rather than just aggregating alerts; and (iii) validating that the cluster produces sound results. Prototypes of our NIDS cluster now operate at the Lawrence Berkeley National Laboratory and the University of California at Berkeley. In both environments the clusters greatly enhance the power of the network security monitoring.

  15. Fuzzy sets, rough sets, multisets and clustering

    CERN Document Server

    Dahlbom, Anders; Narukawa, Yasuo

    2017-01-01

    This book is dedicated to Prof. Sadaaki Miyamoto and presents cutting-edge papers in some of the areas in which he contributed. Bringing together contributions by leading researchers in the field, it concretely addresses clustering, multisets, rough sets and fuzzy sets, as well as their applications in areas such as decision-making. The book is divided in four parts, the first of which focuses on clustering and classification. The second part puts the spotlight on multisets, bags, fuzzy bags and other fuzzy extensions, while the third deals with rough sets. Rounding out the coverage, the last part explores fuzzy sets and decision-making.

  16. Classification of protein profiles using fuzzy clustering techniques

    DEFF Research Database (Denmark)

    Karemore, Gopal; Mullick, Jhinuk B.; Sujatha, R.

    2010-01-01

     Present  study  has  brought  out  a  comparison  of PCA  and  fuzzy  clustering  techniques  in  classifying  protein profiles  (chromatogram)  of  homogenates  of  different  tissue origins:  Ovarian,  Cervix,  Oral  cancers,  which  were  acquired using HPLC–LIF (High Performance Liquid...... Chromatography- Laser   Induced   Fluorescence)   method   developed   in   our laboratory. Study includes 11 chromatogram spectra each from oral,  cervical,  ovarian  cancers  as  well  as  healthy  volunteers. Generally  multivariate  analysis  like  PCA  demands  clear  data that   is   devoid   of   day......   PCA   mapping   in   classifying   various cancers from healthy spectra with classification rate up to 95 % from  60%.  Methods  are  validated  using  various  clustering indexes   and   shows   promising   improvement   in   developing optical pathology like HPLC-LIF for early detection of various...

  17. Homogeneous pancreatic cancer spheroids mimic growth pattern of circulating tumor cell clusters and macrometastases: displaying heterogeneity and crater-like structure on inner layer.

    Science.gov (United States)

    Feng, Hao; Ou, Bao-Chi; Zhao, Jing-Kun; Yin, Shuai; Lu, Ai-Guo; Oechsle, Eva; Thasler, Wolfgang E

    2017-09-01

    Pancreatic cancer 3D in vitro models including multicellular tumor spheroid (MCTS), single cell-derived tumor spheroid (SCTS), tissue-derived tumor spheroid, and organotypic models provided powerful platforms to mimic in vivo tumor. Recent work supports that circulating tumor cell (CTC) clusters are more efficient in metastasis seeding than single CTCs. The purpose of this study is to establish 3D culture models which can mimic single CTC, monoclonal CTC clusters, and the expansion of macrometastases. Seven pancreatic ductal adenocarcinoma cell lines were used to establish MCTS and SCTS using hanging drop and ultra-low attachment plates. Spheroid immunofluorescence staining, spheroid formation assay, immunoblotting, and literature review were performed to investigate molecular biomarkers and the morphological characteristics of pancreatic tumor spheroids. Single cells experienced different growth patterns to form SCTS, like signet ring-like cells, blastula-like structures, and solid core spheroids. However, golf ball-like hollow spheroids could also be detected, especially when DanG and Capan-1 cells were cultivated with fibroblast-conditioned medium (p cell lines could also establish tumor spheroid with hanging drop plates by adding methylated cellulose. Tumor spheroids derived from pancreatic cancer cell line DanG possessed asymmetrically distributed proliferation center, immune-checkpoint properties. ß-catenin, Ki-67, and F-actin were active surrounding the crater-like structure distributing on the inner layer of viable rim cover of the spheroids, which was relevant to well-differentiated tumor cells. It is possible to establish 3D CTC cluster models from homogenous PDA cell lines using hanging drop and ultra-low attachment plates. PDA cell line displays its own intrinsic properties or heterogeneity. The mechanism of formation of the crater-like structure as well as golf ball-like structure needs further exploration.

  18. CCS-DTN: clustering and network coding-based efficient routing in social DTNs.

    Science.gov (United States)

    Zhang, Zhenjing; Ma, Maode; Jin, Zhigang

    2014-12-25

    With the development of mobile Internet, wireless communication via mobile devices has become a hot research topic, which is typically in the form of Delay Tolerant Networks (DTNs). One critical issue in the development of DTNs is routing. Although there is a lot research work addressing routing issues in DTNs, they cannot produce an advanced solution to the comprehensive challenges since only one or two aspects (nodes' movements, clustering, centricity and so on) are considered when the routing problem is handled. In view of these defects in the existing works, we propose a novel solution to address the routing issue in social DTNs. By this solution, mobile nodes are divided into different clusters. The scheme, Spray and Wait, is used for the intra-cluster communication while a new forwarding mechanism is designed for the inter-cluster version. In our solution, the characteristics of nodes and the relation between nodes are fully considered. The simulation results show that our proposed scheme can significantly improve the performance of the routing scheme in social DTNs.

  19. Results of a lay health education intervention to increase colorectal cancer screening among Filipino Americans: A cluster randomized controlled trial.

    Science.gov (United States)

    Cuaresma, Charlene F; Sy, Angela U; Nguyen, Tung T; Ho, Reginald C S; Gildengorin, Ginny L; Tsoh, Janice Y; Jo, Angela M; Tong, Elisa K; Kagawa-Singer, Marjorie; Stewart, Susan L

    2018-04-01

    Filipino colorectal cancer (CRC) screening rates fall below Healthy People 2020 goals. In this study, the authors explore whether a lay health educator (LHE) approach can increase CRC screening among Filipino Americans ages 50 to 75 years in Hawai'i. A cluster randomized controlled trial from 2012 through 2015 compared an intervention, which consisted of LHEs delivering 2 education sessions and 2 telephone follow-up calls on CRC screening plus a CRC brochure versus an attention control, in which 2 lectures and 2 follow-up calls on nutrition and physical activity plus a CRC brochure were provided. The primary outcome was change in self-reported ever receipt of CRC screening at 6 months. Among 304 participants (77% women, 86% had > 10 years of residence in the United States), the proportion of participants who reported ever having received CRC screening increased significantly in the intervention group (from 80% to 89%; P = .0003), but not in the control group (from 73% to 74%; P = .60). After covariate adjustment, there was a significant intervention effect (odds ratio, 1.9; 95% confidence interval, 1.0-3.5). There was no intervention effect on up-to-date screening. This first randomized controlled trial for CRC screening among Hawai'i's Filipinos used an LHE intervention with mixed, but promising, results. Cancer 2018;124:1535-42. © 2018 American Cancer Society. © 2018 American Cancer Society.

  20. A 3-stage model of patient-centered communication for addressing cancer patients' emotional distress.

    Science.gov (United States)

    Dean, Marleah; Street, Richard L

    2014-02-01

    To describe pathways through which clinicians can more effectively respond to patients' emotions in ways that contribute to betterment of the patient's health and well-being. A representative review of literature on managing emotions in clinical consultations was conducted. A three-stage, conceptual model for assisting clinicians to more effectively address the challenges of recognizing, exploring, and managing cancer patients' emotional distress in the clinical encounter was developed. To enhance and enact recognition of patients' emotions, clinicians can engage in mindfulness, self-situational awareness, active listening, and facilitative communication. To enact exploration, clinicians can acknowledge and validate emotions and provide empathy. Finally, clinicians can provide information empathetically, identify therapeutic resources, and give referrals and interventions as needed to help lessen patients' emotional distress. This model serves as a framework for future research examining pathways that link clinicians' emotional cue recognition to patient-centered responses exploring a patient's emotional distress to therapeutic actions that contribute to improved psychological and emotional health. Specific communicative and cognitive strategies are presented that can help clinicians better recognize a patient's emotional distress and respond in ways that have therapeutic value. Published by Elsevier Ireland Ltd.

  1. INFRARED OBSERVATIONAL MANIFESTATIONS OF YOUNG DUSTY SUPER STAR CLUSTERS

    Energy Technology Data Exchange (ETDEWEB)

    Martínez-González, Sergio; Tenorio-Tagle, Guillermo; Silich, Sergiy, E-mail: sergiomtz@inaoep.mx [Instituto Nacional de Astrofísica Óptica y Electrónica, AP 51, 72000 Puebla (Mexico)

    2016-01-01

    The growing evidence pointing at core-collapse supernovae as large dust producers makes young massive stellar clusters ideal laboratories to study the evolution of dust immersed in a hot plasma. Here we address the stochastic injection of dust by supernovae, and follow its evolution due to thermal sputtering within the hot and dense plasma generated by young stellar clusters. Under these considerations, dust grains are heated by means of random collisions with gas particles which result in the appearance of  infrared spectral signatures. We present time-dependent infrared spectral energy distributions that are to be expected from young stellar clusters. Our results are based on hydrodynamic calculations that account for the stochastic injection of dust by supernovae. These also consider gas and dust radiative cooling, stochastic dust temperature fluctuations, the exit of dust grains out of the cluster volume due to the cluster wind, and a time-dependent grain size distribution.

  2. INFRARED OBSERVATIONAL MANIFESTATIONS OF YOUNG DUSTY SUPER STAR CLUSTERS

    International Nuclear Information System (INIS)

    Martínez-González, Sergio; Tenorio-Tagle, Guillermo; Silich, Sergiy

    2016-01-01

    The growing evidence pointing at core-collapse supernovae as large dust producers makes young massive stellar clusters ideal laboratories to study the evolution of dust immersed in a hot plasma. Here we address the stochastic injection of dust by supernovae, and follow its evolution due to thermal sputtering within the hot and dense plasma generated by young stellar clusters. Under these considerations, dust grains are heated by means of random collisions with gas particles which result in the appearance of  infrared spectral signatures. We present time-dependent infrared spectral energy distributions that are to be expected from young stellar clusters. Our results are based on hydrodynamic calculations that account for the stochastic injection of dust by supernovae. These also consider gas and dust radiative cooling, stochastic dust temperature fluctuations, the exit of dust grains out of the cluster volume due to the cluster wind, and a time-dependent grain size distribution

  3. Personalized Metaheuristic Clustering Onto Web Documents

    Institute of Scientific and Technical Information of China (English)

    Wookey Lee

    2004-01-01

    Optimal clustering for the web documents is known to complicated cornbinatorial Optimization problem and it is hard to develop a generally applicable oplimal algorithm. An accelerated simuIated arlneaIing aIgorithm is developed for automatic web document classification. The web document classification problem is addressed as the problem of best describing a match between a web query and a hypothesized web object. The normalized term frequency and inverse document frequency coefficient is used as a measure of the match. Test beds are generated on - line during the search by transforming model web sites. As a result, web sites can be clustered optimally in terms of keyword vectofs of corresponding web documents.

  4. Other cancers in lung cancer families are overwhelmingly smoking-related cancers

    Directory of Open Access Journals (Sweden)

    Hongyao Yu

    2017-06-01

    Full Text Available Familial risks of lung cancer are well-established, but whether lung cancer clusters with other discordant cancers is less certain, particularly beyond smoking-related sites, which may provide evidence on genetic contributions to lung cancer aetiology. We used a novel approach to search for familial associations in the Swedish Family-Cancer Database. This involved assessment of familial relative risk for cancer X in families with increasing numbers of lung cancer patients and, conversely, relative risks for lung cancer in families with increasing numbers of patients with cancers X. However, we lacked information on smoking. The total number of lung cancers in the database was 125 563. We applied stringent statistical criteria and found that seven discordant cancers were associated with lung cancer among family members, and six of these were known to be connected with smoking: oesophageal, upper aerodigestive tract, liver, cervical, kidney and urinary bladder cancers. A further novel finding was that cancer of unknown primary also associated with lung cancer. We also factored in histological evidence and found that anal and connective tissue cancers could be associated with lung cancer for reasons other than smoking. For endometrial and prostate cancers, suggestive negative associations with lung cancer were found. Although we lacked information on smoking it is prudent to conclude that practically all observed discordant associations of lung cancer were with cancers for which smoking is a risk factor.

  5. The cluster [Re6Se8I6]3- penetrates biological membranes: drug-like properties for CNS tumor treatment and diagnosis.

    Science.gov (United States)

    Estrada, Lisbell D; Duran, Elizabeth; Cisterna, Matias; Echeverria, Cesar; Zheng, Zhiping; Borgna, Vincenzo; Arancibia-Miranda, Nicolas; Ramírez-Tagle, Rodrigo

    2018-03-24

    Tumorigenic cell lines are more susceptible to [Re 6 Se 8 I 6 ] 3- cluster-induced death than normal cells, becoming a novel candidate for cancer treatment. Still, the feasibility of using this type of molecules in human patients remains unclear and further pharmacokinetics analysis is needed. Using coupled plasma optical emission spectroscopy, we determined the Re-cluster tissue content in injected mice, as a biodistribution measurement. Our results show that the Re-cluster successfully reaches different tissues, accumulating mainly in heart and liver. In order to dissect the mechanism underlying cluster biodistribution, we used three different experimental approaches. First, we evaluate the degree of lipophilicity by determining the octanol/water partition coefficient. The cluster mostly remained in the octanol fraction, with a coefficient of 1.86 ± 0.02, which indicates it could potentially cross cell membranes. Then, we measured the biological membrane penetration through a parallel artificial membrane permeability assays (PAMPA) assay. The Re-cluster crosses the artificial membrane, with a coefficient of 122 nm/s that is considered highly permeable. To evaluate a potential application of the Re-cluster in central nervous system (CNS) tumors, we analyzed the cluster's brain penetration by exposing cultured blood-brain-barrier (BBB) cells to increasing concentrations of the cluster. The Re-cluster effectively penetrates the BBB, reaching nearly 30% of the brain side after 24 h. Thus, our results indicate that the Re-cluster penetrates biological membranes reaching different target organs-most probably due to its lipophilic properties-becoming a promising anti-cancer drug with high potential for CNS cancer's diagnosis and treatment.

  6. Identifying molecular subtypes in human colon cancer using gene expression and DNA methylation microarray data.

    Science.gov (United States)

    Ren, Zhonglu; Wang, Wenhui; Li, Jinming

    2016-02-01

    Identifying colon cancer subtypes based on molecular signatures may allow for a more rational, patient-specific approach to therapy in the future. Classifications using gene expression data have been attempted before with little concordance between the different studies carried out. In this study we aimed to uncover subtypes of colon cancer that have distinct biological characteristics and identify a set of novel biomarkers which could best reflect the clinical and/or biological characteristics of each subtype. Clustering analysis and discriminant analysis were utilized to discover the subtypes in two different molecular levels on 153 colon cancer samples from The Cancer Genome Atlas (TCGA) Data Portal. At gene expression level, we identified two major subtypes, ECL1 (expression cluster 1) and ECL2 (expression cluster 2) and a list of signature genes. Due to the heterogeneity of colon cancer, the subtype ECL1 can be further subdivided into three nested subclasses, and HOTAIR were found upregulated in subclass 2. At DNA methylation level, we uncovered three major subtypes, MCL1 (methylation cluster 1), MCL2 (methylation cluster 2) and MCL3 (methylation cluster 3). We found only three subtypes of CpG island methylator phenotype (CIMP) in colon cancer instead of the four subtypes in the previous reports, and we found no sufficient evidence to subdivide MCL3 into two distinct subgroups.

  7. Local breast cancer spatial patterning: a tool for community health resource allocation to address local disparities in breast cancer mortality.

    Directory of Open Access Journals (Sweden)

    Dana M Brantley-Sieders

    Full Text Available Despite available demographic data on the factors that contribute to breast cancer mortality in large population datasets, local patterns are often overlooked. Such local information could provide a valuable metric by which regional community health resources can be allocated to reduce breast cancer mortality. We used national and statewide datasets to assess geographical distribution of breast cancer mortality rates and known risk factors influencing breast cancer mortality in middle Tennessee. Each county in middle Tennessee, and each ZIP code within metropolitan Davidson County, was scored for risk factor prevalence and assigned quartile scores that were used as a metric to identify geographic areas of need. While breast cancer mortality often correlated with age and incidence, geographic areas were identified in which breast cancer mortality rates did not correlate with age and incidence, but correlated with additional risk factors, such as mammography screening and socioeconomic status. Geographical variability in specific risk factors was evident, demonstrating the utility of this approach to identify local areas of risk. This method revealed local patterns in breast cancer mortality that might otherwise be overlooked in a more broadly based analysis. Our data suggest that understanding the geographic distribution of breast cancer mortality, and the distribution of risk factors that contribute to breast cancer mortality, will not only identify communities with the greatest need of support, but will identify the types of resources that would provide the most benefit to reduce breast cancer mortality in the community.

  8. Content-addressable read/write memories for image analysis

    Science.gov (United States)

    Snyder, W. E.; Savage, C. D.

    1982-01-01

    The commonly encountered image analysis problems of region labeling and clustering are found to be cases of search-and-rename problem which can be solved in parallel by a system architecture that is inherently suitable for VLSI implementation. This architecture is a novel form of content-addressable memory (CAM) which provides parallel search and update functions, allowing speed reductions down to constant time per operation. It has been proposed in related investigations by Hall (1981) that, with VLSI, CAM-based structures with enhanced instruction sets for general purpose processing will be feasible.

  9. MSH2 mutation carriers are at higher risk of cancer than MLH1 mutation carriers : A study of hereditary nonpolyposis colorectal cancer families

    NARCIS (Netherlands)

    Vasen, HFA; Stormorken, A; Menko, FH; Nagengast, FM; Kleibeuker, JH; Griffioen, G; Taal, BG; Moller, P; Wijnen, JT

    2001-01-01

    Purpose: Hereditary nonpolyposis colorectal cancer (HNPCC) is an autosomal dominant disease characterized by the clustering of colorectal cancer, endometrial cancer, and various other cancers. The disease is caused by mutations in DNA-mismatch-repair (MMR) genes, most frequently in MLH1, MSH2, and

  10. MSH2 mutation carriers are at higher risk of cancer than MLH1 mutation carriers: a study of hereditary nonpolyposis colorectal cancer families.

    NARCIS (Netherlands)

    Vasen, H.F.; Stormorken, A.; Menko, F.H.; Nagengast, F.M.; Kleibeuker, J.H.; Griffioen, G.; Taal, B.G.; Moller, P.; Wijnen, J.T.

    2001-01-01

    PURPOSE: Hereditary nonpolyposis colorectal cancer (HNPCC) is an autosomal dominant disease characterized by the clustering of colorectal cancer, endometrial cancer, and various other cancers. The disease is caused by mutations in DNA-mismatch-repair (MMR) genes, most frequently in MLH1, MSH2, and

  11. Elucidating the underlying causes of oral cancer through spatial clustering in high-risk areas of Taiwan with a distinct gender ratio of incidence

    Directory of Open Access Journals (Sweden)

    Chi-Ting Chiang

    2010-05-01

    Full Text Available This study aimed to elucidate whether or not high-risk clusters of oral cancer (OC incidence spatially correlate with the prevalence rates of betel quid chewing (BQC and cigarette smoking (CS in Taiwan. The spatial autocorrelation and potential clusters of OC incidence among the 307 townships and heavy metal content of soil throughout Taiwan were identified using the Anselin’s local Moran test. Additionally, the spatial correlations among the incidence of OC, the prevalence of BQC and CS and heavy metal content of soil were determined based on a comparison of spatial clusters. High-risk OC (Moran’s I = 0.638, P <0.001 clusters were located in central and eastern Taiwan, while “hot spots” of BQC and CS prevalence were located mainly in eastern Taiwan. The distributions of BQC and CS lifestyle factors (P <0.001 were spatially autocorrelated. The “hot spots” of OC largely coincided with the “hot spots” of BQC, except for the Changhua and Yunlin counties, which are located in central Taiwan. However, high soil contents of nickel and chromium (P <0.001 in central Taiwan also coincided with the high-risk areas of OC incidence. In particular, Changhua county has incurred several decades of serious heavy-metal pollution, with inhabitants living in polluted areas having high-risk exposure to these metals. Results of this study suggest that, in addition to BQC and CS, anthropogenic pollution may profoundly impact the complexity of OC aetiology in central Taiwan.

  12. Creating a three level building classification using topographic and address-based data for Manchester

    Science.gov (United States)

    Hussain, M.; Chen, D.

    2014-11-01

    Buildings, the basic unit of an urban landscape, host most of its socio-economic activities and play an important role in the creation of urban land-use patterns. The spatial arrangement of different building types creates varied urban land-use clusters which can provide an insight to understand the relationships between social, economic, and living spaces. The classification of such urban clusters can help in policy-making and resource management. In many countries including the UK no national-level cadastral database containing information on individual building types exists in public domain. In this paper, we present a framework for inferring functional types of buildings based on the analysis of their form (e.g. geometrical properties, such as area and perimeter, layout) and spatial relationship from large topographic and address-based GIS database. Machine learning algorithms along with exploratory spatial analysis techniques are used to create the classification rules. The classification is extended to two further levels based on the functions (use) of buildings derived from address-based data. The developed methodology was applied to the Manchester metropolitan area using the Ordnance Survey's MasterMap®, a large-scale topographic and address-based data available for the UK.

  13. Childhood cancers in the UK and their relation to background radiation

    International Nuclear Information System (INIS)

    Kneale, G.W.; Stewart, A.M.

    1987-01-01

    This chapter shows the results of including two independent data sets in a study of several factors with cancer associations including background radiation. One data set came from the Oxford Survey of Childhood Cancers (OSCC); the other from the National Radiological Protection Board (NRPB) and findings are compatible with background radiation being the single most important cause of juvenile neoplasms. It also emerged that these neoplasms have a strongly clustered distribution. No obvious cause of clusters was found, but they had associations with prenatal and postnatal illnesses as well as background radiation. Therefore, since there is mounting sensitivity to infections during the latent phase of leukaemia, cancer clusters might be the result of competing causes of death having an epidemic distribution. The findings as a whole are compatible with all man-made additions to background (including leakages of radioactivity from a reprocessing plant) adding to risk of an early cancer death. Proof that certain leukaemia clusters in the vicinity of two reprocessing plants were caused in this way must await collection of data. (author)

  14. Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clustering

    Directory of Open Access Journals (Sweden)

    Sharma Animesh

    2007-01-01

    Full Text Available Abstract Background The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell tumor (SRBCT and thus often leads to misdiagnosis. Identification of biomarkers for distinguishing these cancers is a well studied problem. Existing methods typically evaluate each gene separately and do not take into account the nonlinear interaction between genes and the tools that are used to design the diagnostic prediction system. Consequently, more genes are usually identified as necessary for prediction. We propose a general scheme for finding a small set of biomarkers to design a diagnostic system for accurate classification of the cancer subgroups. We use multilayer networks with online gene selection ability and relational fuzzy clustering to identify a small set of biomarkers for accurate classification of the training and blind test cases of a well studied data set. Results Our method discerned just seven biomarkers that precisely categorized the four subgroups of cancer both in training and blind samples. For the same problem, others suggested 19–94 genes. These seven biomarkers include three novel genes (NAB2, LSP1 and EHD1 – not identified by others with distinct class-specific signatures and important role in cancer biology, including cellular proliferation, transendothelial migration and trafficking of MHC class antigens. Interestingly, NAB2 is downregulated in other tumors including Non-Hodgkin lymphoma and Neuroblastoma but we observed moderate to high upregulation in a few cases of Ewing sarcoma and Rabhdomyosarcoma, suggesting that NAB2 might be mutated in these tumors. These genes can discover the subgroups correctly with unsupervised learning, can differentiate non-SRBCT samples and they perform equally well with other machine learning tools including support vector machines. These biomarkers lead to four simple human interpretable

  15. Design Optimization of Multi-Cluster Embedded Systems for Real-Time Applications

    DEFF Research Database (Denmark)

    Pop, Paul; Eles, Petru; Peng, Zebo

    2004-01-01

    We present an approach to design optimization of multi-cluster embedded systems consisting of time-triggered and event-triggered clusters, interconnected via gateways. In this paper, we address design problems which are characteristic to multi-clusters: partitioning of the system functionality...... into time-triggered and event-triggered domains, process mapping, and the optimization of parameters corresponding to the communication protocol. We present several heuristics for solving these problems. Our heuristics are able to find schedulable implementations under limited resources, achieving...... an efficient utilization of the system. The developed algorithms are evaluated using extensive experiments and a real-life example....

  16. Design Optimization of Multi-Cluster Embedded Systems for Real-Time Applications

    DEFF Research Database (Denmark)

    Pop, Paul; Eles, Petru; Peng, Zebo

    2006-01-01

    We present an approach to design optimization of multi-cluster embedded systems consisting of time-triggered and event-triggered clusters, interconnected via gateways. In this paper, we address design problems which are characteristic to multi-clusters: partitioning of the system functionality...... into time-triggered and event-triggered domains, process mapping, and the optimization of parameters corresponding to the communication protocol. We present several heuristics for solving these problems. Our heuristics are able to find schedulable implementations under limited resources, achieving...... an efficient utilization of the system. The developed algorithms are evaluated using extensive experiments and a real-life example....

  17. The metabolic syndrome in cancer survivors

    NARCIS (Netherlands)

    de Haas, Esther C.; Oosting, Sjoukje F.; Lefrandt, Joop D.; Wolffenbuttel, Bruce H. R.; Sleijfer, Dirk Th; Gietema, Jourik A.

    The metabolic syndrome, as a cluster of cardiovascular risk factors, may represent an important connection between cancer treatment and its common late effect of cardiovascular disease. Insight into the aetiology of the metabolic syndrome after cancer treatment might help to identify and treat

  18. The effect of direct referral for fast CT scan in early lung cancer detection in general practice. A clinical, cluster-randomised trial.

    Science.gov (United States)

    Guldbrandt, Louise Mahncke

    2015-03-01

    This PhD thesis is based on the project "The effect of direct referral for fast CT scan in early lung cancer detection in general practice. A clinical, cluster-randomised trial", performed in Denmark in 2010-2013. The thesis includes four papers and focuses on early lung cancer diagnostics in general practice. A total of 4200 new cases of lung cancer are diagnosed in Denmark annually. The stage of the disease is an important prognostic factor; thus, the opportunity for curative treatment declines with more advanced tumour stage. Lung cancer patients in Denmark (like in the UK) have a poorer prognosis than lung cancer patients in other European countries. One explanation could be delayed diagnosis. A fast-track pathway was therefore introduced in an attempt to expedite the diagnosis of cancer. However, it seems that not all patients can be diagnosed through this pathway. In order to ensure fast and early lung cancer diagnosis, it is crucial to examine the initial diagnostic process in general and the role general practice plays in lung cancer diagnostics in particular. The specific areas of investigation include the pathways to diagnosis, the characteristics of patients who are at special risk of delayed diagnosis and the level of prediagnostic activity in general practice. A chest radiograph is often the first choice in the investigation of lung cancer. Unfortunately, radiographs are less suitable for central and small tumours. Low-dose computer tomography (LDCT), however, has a high sensitivity for lung cancer which implies that it can be used to detect patients with localised, potentially curable disease. The aim of this thesis was to increase our knowledge of the initial stages of lung cancer diagnostics in general practice. The thesis also examined the effect of a direct referral from general practice to an additional diagnostic test, the LDCT. The aims of this thesis were: 1) To describe Danish patients' pathways to the diagnosis of lung cancer in general and

  19. New Statistical Methodology for Determining Cancer Clusters

    Science.gov (United States)

    The development of an innovative statistical technique that shows that women living in a broad stretch of the metropolitan northeastern United States, which includes Long Island, are slightly more likely to die from breast cancer than women in other parts of the Northeast.

  20. Addressing current challenges in cancer immunotherapy with mathematical and computational modelling.

    Science.gov (United States)

    Konstorum, Anna; Vella, Anthony T; Adler, Adam J; Laubenbacher, Reinhard C

    2017-06-01

    The goal of cancer immunotherapy is to boost a patient's immune response to a tumour. Yet, the design of an effective immunotherapy is complicated by various factors, including a potentially immunosuppressive tumour microenvironment, immune-modulating effects of conventional treatments and therapy-related toxicities. These complexities can be incorporated into mathematical and computational models of cancer immunotherapy that can then be used to aid in rational therapy design. In this review, we survey modelling approaches under the umbrella of the major challenges facing immunotherapy development, which encompass tumour classification, optimal treatment scheduling and combination therapy design. Although overlapping, each challenge has presented unique opportunities for modellers to make contributions using analytical and numerical analysis of model outcomes, as well as optimization algorithms. We discuss several examples of models that have grown in complexity as more biological information has become available, showcasing how model development is a dynamic process interlinked with the rapid advances in tumour-immune biology. We conclude the review with recommendations for modellers both with respect to methodology and biological direction that might help keep modellers at the forefront of cancer immunotherapy development. © 2017 The Author(s).

  1. In vitro downregulated hypoxia transcriptome is associated with poor prognosis in breast cancer.

    Science.gov (United States)

    Abu-Jamous, Basel; Buffa, Francesca M; Harris, Adrian L; Nandi, Asoke K

    2017-06-15

    Hypoxia is a characteristic of breast tumours indicating poor prognosis. Based on the assumption that those genes which are up-regulated under hypoxia in cell-lines are expected to be predictors of poor prognosis in clinical data, many signatures of poor prognosis were identified. However, it was observed that cell line data do not always concur with clinical data, and therefore conclusions from cell line analysis should be considered with caution. As many transcriptomic cell-line datasets from hypoxia related contexts are available, integrative approaches which investigate these datasets collectively, while not ignoring clinical data, are required. We analyse sixteen heterogeneous breast cancer cell-line transcriptomic datasets in hypoxia-related conditions collectively by employing the unique capabilities of the method, UNCLES, which integrates clustering results from multiple datasets and can address questions that cannot be answered by existing methods. This has been demonstrated by comparison with the state-of-the-art iCluster method. From this collection of genome-wide datasets include 15,588 genes, UNCLES identified a relatively high number of genes (>1000 overall) which are consistently co-regulated over all of the datasets, and some of which are still poorly understood and represent new potential HIF targets, such as RSBN1 and KIAA0195. Two main, anti-correlated, clusters were identified; the first is enriched with MYC targets participating in growth and proliferation, while the other is enriched with HIF targets directly participating in the hypoxia response. Surprisingly, in six clinical datasets, some sub-clusters of growth genes are found consistently positively correlated with hypoxia response genes, unlike the observation in cell lines. Moreover, the ability to predict bad prognosis by a combined signature of one sub-cluster of growth genes and one sub-cluster of hypoxia-induced genes appears to be comparable and perhaps greater than that of known

  2. Classical plasma dynamics of Mie-oscillations in atomic clusters

    Science.gov (United States)

    Kull, H.-J.; El-Khawaldeh, A.

    2018-04-01

    Mie plasmons are of basic importance for the absorption of laser light by atomic clusters. In this work we first review the classical Rayleigh-theory of a dielectric sphere in an external electric field and Thomson’s plum-pudding model applied to atomic clusters. Both approaches allow for elementary discussions of Mie oscillations, however, they also indicate deficiencies in describing the damping mechanisms by electrons crossing the cluster surface. Nonlinear oscillator models have been widely studied to gain an understanding of damping and absorption by outer ionization of the cluster. In the present work, we attempt to address the issue of plasmon relaxation in atomic clusters in more detail based on classical particle simulations. In particular, we wish to study the role of thermal motion on plasmon relaxation, thereby extending nonlinear models of collective single-electron motion. Our simulations are particularly adopted to the regime of classical kinetics in weakly coupled plasmas and to cluster sizes extending the Debye-screening length. It will be illustrated how surface scattering leads to the relaxation of Mie oscillations in the presence of thermal motion and of electron spill-out at the cluster surface. This work is intended to give, from a classical perspective, further insight into recent work on plasmon relaxation in quantum plasmas [1].

  3. Symptom clusters in patients with nasopharyngeal carcinoma during radiotherapy.

    Science.gov (United States)

    Xiao, Wenli; Chan, Carmen W H; Fan, Yuying; Leung, Doris Y P; Xia, Weixiong; He, Yan; Tang, Linquan

    2017-06-01

    Despite the improvement in radiotherapy (RT) technology, patients with nasopharyngeal carcinoma (NPC) still suffer from numerous distressing symptoms simultaneously during RT. The purpose of the study was to investigate the symptom clusters experienced by NPC patients during RT. First-treated Chinese NPC patients (n = 130) undergoing late-period RT (from week 4 till the end) were recruited for this cross-sectional study. They completed a sociodemographic and clinical data questionnaire, the Chinese version of the M. D. Anderson Symptom Inventory - Head and Neck Module (MDASI-HN-C) and the Chinese version of the Functional Assessment of Cancer Therapy - Head and Neck Scale (FACT-H&N-C). Principal axis factor analysis with oblimin rotation, independent t-test, one-way analysis of variance (ANOVA) and Pearson product-moment correlation were used to analyze the data. Four symptom clusters were identified, and labelled general, gastrointestinal, nutrition impact and social interaction impact. Of these 4 types, the nutrition impact symptom cluster was the most severe. Statistically positive correlations were found between severity of all 4 symptom clusters and symptom interference, as well as weight loss. Statistically negative correlations were detected between the cluster severity and the QOL total score and 3 out of 5 subscale scores. The four clusters identified reveal the symptom patterns experienced by NPC patients during RT. Future intervention studies on managing these symptom clusters are warranted, especially for the nutrition impact symptom cluster. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. Low-Complexity Bayesian Estimation of Cluster-Sparse Channels

    KAUST Repository

    Ballal, Tarig

    2015-09-18

    This paper addresses the problem of channel impulse response estimation for cluster-sparse channels under the Bayesian estimation framework. We develop a novel low-complexity minimum mean squared error (MMSE) estimator by exploiting the sparsity of the received signal profile and the structure of the measurement matrix. It is shown that due to the banded Toeplitz/circulant structure of the measurement matrix, a channel impulse response, such as underwater acoustic channel impulse responses, can be partitioned into a number of orthogonal or approximately orthogonal clusters. The orthogonal clusters, the sparsity of the channel impulse response and the structure of the measurement matrix, all combined, result in a computationally superior realization of the MMSE channel estimator. The MMSE estimator calculations boil down to simpler in-cluster calculations that can be reused in different clusters. The reduction in computational complexity allows for a more accurate implementation of the MMSE estimator. The proposed approach is tested using synthetic Gaussian channels, as well as simulated underwater acoustic channels. Symbol-error-rate performance and computation time confirm the superiority of the proposed method compared to selected benchmark methods in systems with preamble-based training signals transmitted over clustersparse channels.

  5. Low-Complexity Bayesian Estimation of Cluster-Sparse Channels

    KAUST Repository

    Ballal, Tarig; Al-Naffouri, Tareq Y.; Ahmed, Syed

    2015-01-01

    This paper addresses the problem of channel impulse response estimation for cluster-sparse channels under the Bayesian estimation framework. We develop a novel low-complexity minimum mean squared error (MMSE) estimator by exploiting the sparsity of the received signal profile and the structure of the measurement matrix. It is shown that due to the banded Toeplitz/circulant structure of the measurement matrix, a channel impulse response, such as underwater acoustic channel impulse responses, can be partitioned into a number of orthogonal or approximately orthogonal clusters. The orthogonal clusters, the sparsity of the channel impulse response and the structure of the measurement matrix, all combined, result in a computationally superior realization of the MMSE channel estimator. The MMSE estimator calculations boil down to simpler in-cluster calculations that can be reused in different clusters. The reduction in computational complexity allows for a more accurate implementation of the MMSE estimator. The proposed approach is tested using synthetic Gaussian channels, as well as simulated underwater acoustic channels. Symbol-error-rate performance and computation time confirm the superiority of the proposed method compared to selected benchmark methods in systems with preamble-based training signals transmitted over clustersparse channels.

  6. Classification of human cancers based on DNA copy number amplification modeling

    Directory of Open Access Journals (Sweden)

    Knuutila Sakari

    2008-05-01

    Full Text Available Abstract Background DNA amplifications alter gene dosage in cancer genomes by multiplying the gene copy number. Amplifications are quintessential in a considerable number of advanced cancers of various anatomical locations. The aims of this study were to classify human cancers based on their amplification patterns, explore the biological and clinical fundamentals behind their amplification-pattern based classification, and understand the characteristics in human genomic architecture that associate with amplification mechanisms. Methods We applied a machine learning approach to model DNA copy number amplifications using a data set of binary amplification records at chromosome sub-band resolution from 4400 cases that represent 82 cancer types. Amplification data was fused with background data: clinical, histological and biological classifications, and cytogenetic annotations. Statistical hypothesis testing was used to mine associations between the data sets. Results Probabilistic clustering of each chromosome identified 111 amplification models and divided the cancer cases into clusters. The distribution of classification terms in the amplification-model based clustering of cancer cases revealed cancer classes that were associated with specific DNA copy number amplification models. Amplification patterns – finite or bounded descriptions of the ranges of the amplifications in the chromosome – were extracted from the clustered data and expressed according to the original cytogenetic nomenclature. This was achieved by maximal frequent itemset mining using the cluster-specific data sets. The boundaries of amplification patterns were shown to be enriched with fragile sites, telomeres, centromeres, and light chromosome bands. Conclusions Our results demonstrate that amplifications are non-random chromosomal changes and specifically selected in tumor tissue microenvironment. Furthermore, statistical evidence showed that specific chromosomal features

  7. Regions of micro-calcifications clusters detection based on new features from imbalance data in mammograms

    Science.gov (United States)

    Wang, Keju; Dong, Min; Yang, Zhen; Guo, Yanan; Ma, Yide

    2017-02-01

    Breast cancer is the most common cancer among women. Micro-calcification cluster on X-ray mammogram is one of the most important abnormalities, and it is effective for early cancer detection. Surrounding Region Dependence Method (SRDM), a statistical texture analysis method is applied for detecting Regions of Interest (ROIs) containing microcalcifications. Inspired by the SRDM, we present a method that extract gray and other features which are effective to predict the positive and negative regions of micro-calcifications clusters in mammogram. By constructing a set of artificial images only containing micro-calcifications, we locate the suspicious pixels of calcifications of a SRDM matrix in original image map. Features are extracted based on these pixels for imbalance date and then the repeated random subsampling method and Random Forest (RF) classifier are used for classification. True Positive (TP) rate and False Positive (FP) can reflect how the result will be. The TP rate is 90% and FP rate is 88.8% when the threshold q is 10. We draw the Receiver Operating Characteristic (ROC) curve and the Area Under the ROC Curve (AUC) value reaches 0.9224. The experiment indicates that our method is effective. A novel regions of micro-calcifications clusters detection method is developed, which is based on new features for imbalance data in mammography, and it can be considered to help improving the accuracy of computer aided diagnosis breast cancer.

  8. TH-E-BRF-08: Subpopulations of Similarly-Responding Lesions in Metastatic Prostate Cancer

    International Nuclear Information System (INIS)

    Lin, C; Harmon, S; Perk, T; Jeraj, R

    2014-01-01

    Purpose: In patients with multiple lesions, resistance to cancer treatments and subsequent disease recurrence may be due to heterogeneity of response across lesions. This study aims to identify subpopulations of similarly-responding metastatic prostate cancer lesions in bone using quantitative PET metrics. Methods: Seven metastatic prostate cancer patients treated with AR-directed therapy received pre-treatment and mid-treatment [F-18]NaF PET/CT scans. Images were registered using an articulated CT registration algorithm and transformations were applied to PET segmentations. Midtreatment response was calculated on PET-based texture features. Hierarchical agglomerative clustering was used to form groups of similarly-responding lesions, with the number of natural clusters (K) determined by the inconsistency coefficient. Lesion clustering was performed within each patient, and for the pooled population. The cophenetic coefficient (C) quantified how well the data was clustered. The Jaccard Index (JI) assessed similarity of cluster assignments from patient clustering and from population clustering. Results: 188 lesions in seven patients were identified for analysis (between 6 to 53 lesions per patient). Lesion response was defined as percent change relative to pre-treatment for 23 uncorrelated PET-based feature identifiers. . High response heterogeneity was found across all lesions (i.e. range ΔSUVmax =−95.98% to 775.00%). For intra-patient clustering, K ranged from 1–20. Population-based clustering resulted in 75 clusters, of 1-6 lesions each. Intra-patient clustering resulted in higher quality clusters than population clustering (mean C=0.95, range=0.89 to 1.00). For all patients, cluster assignments from population clustering showed good agreement to intra-patient clustering (mean JI=0.87, range=0.68 to 1.00). Conclusion: Subpopulations of similarly-responding lesions were identified in patients with multiple metastatic lesions. Good agreement was found between

  9. Novel density-based and hierarchical density-based clustering algorithms for uncertain data.

    Science.gov (United States)

    Zhang, Xianchao; Liu, Han; Zhang, Xiaotong

    2017-09-01

    Uncertain data has posed a great challenge to traditional clustering algorithms. Recently, several algorithms have been proposed for clustering uncertain data, and among them density-based techniques seem promising for handling data uncertainty. However, some issues like losing uncertain information, high time complexity and nonadaptive threshold have not been addressed well in the previous density-based algorithm FDBSCAN and hierarchical density-based algorithm FOPTICS. In this paper, we firstly propose a novel density-based algorithm PDBSCAN, which improves the previous FDBSCAN from the following aspects: (1) it employs a more accurate method to compute the probability that the distance between two uncertain objects is less than or equal to a boundary value, instead of the sampling-based method in FDBSCAN; (2) it introduces new definitions of probability neighborhood, support degree, core object probability, direct reachability probability, thus reducing the complexity and solving the issue of nonadaptive threshold (for core object judgement) in FDBSCAN. Then, we modify the algorithm PDBSCAN to an improved version (PDBSCANi), by using a better cluster assignment strategy to ensure that every object will be assigned to the most appropriate cluster, thus solving the issue of nonadaptive threshold (for direct density reachability judgement) in FDBSCAN. Furthermore, as PDBSCAN and PDBSCANi have difficulties for clustering uncertain data with non-uniform cluster density, we propose a novel hierarchical density-based algorithm POPTICS by extending the definitions of PDBSCAN, adding new definitions of fuzzy core distance and fuzzy reachability distance, and employing a new clustering framework. POPTICS can reveal the cluster structures of the datasets with different local densities in different regions better than PDBSCAN and PDBSCANi, and it addresses the issues in FOPTICS. Experimental results demonstrate the superiority of our proposed algorithms over the existing

  10. Oral toxicity management in head and neck cancer patients treated with chemotherapy and radiation: Dental pathologies and osteoradionecrosis (Part 1) literature review and consensus statement.

    Science.gov (United States)

    Buglione, Michela; Cavagnini, Roberta; Di Rosario, Federico; Sottocornola, Lara; Maddalo, Marta; Vassalli, Lucia; Grisanti, Salvatore; Salgarello, Stefano; Orlandi, Ester; Paganelli, Corrado; Majorana, Alessandra; Gastaldi, Giorgio; Bossi, Paolo; Berruti, Alfredo; Pavanato, Giovanni; Nicolai, Piero; Maroldi, Roberto; Barasch, Andrei; Russi, Elvio G; Raber-Durlacher, Judith; Murphy, Barbara; Magrini, Stefano M

    2016-01-01

    Radiotherapy alone or in combination with chemotherapy and/or surgery is the typical treatment for head and neck cancer patients. Acute side effects (such as oral mucositis, dermatitis, salivary changes, taste alterations, etc.), and late toxicities in particular (such as osteo-radionecrosis, hypo-salivation and xerostomia, trismus, radiation caries etc.), are often debilitating. These effects tend to be underestimated and insufficiently addressed in the medical community. A multidisciplinary group of head and neck cancer specialists met in Milan with the aim of reaching a consensus on clinical definitions and management of these toxicities. The Delphi Appropriateness method was used for developing the consensus, and external experts evaluated the conclusions. This paper contains 10 clusters of statements about the clinical definitions and management of head and neck cancer treatment sequels (dental pathologies and osteo-radionecroses) that reached consensus, and offers a review of the literature about these topics. The review was split into two parts: the first part dealt with dental pathologies and osteo-radionecroses (10 clusters of statements), whereas this second part deals with trismus and xerostomia. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  11. [Work-Related Medical Rehabilitation in Cancer Rehabilitation - Short-Term Results from a Cluster-Randomized Multicenter-Trial].

    Science.gov (United States)

    Wienert, Julian; Bethge, Matthias

    2018-05-25

    Rehabilitation programs that support return to work become increasingly relevant for cancer survivors. In Germany, such programs were established as work-related medical rehabilitation (WMR). The study investigated whether WMR leads to better results compared to medical rehabilitation (MR). We report effects on secondary outcomes when the rehabilitation program was completed. Clusters of participants were randomly assigned to WMR or MR. Patients of working age and an elevated risk of not returning to work were included. The grade of implementation was assessed by dose delivered and dose received. Study outcomes were assessed using scales measuring functioning and symptoms, coping with illness as well as self-reported work ability. Treatment effects were estimated using mixed linear models. From 232 planned randomized intervention groups, 165 (71%) were realized. In total, 476 patients were included. Mean age of participants was 50.7 years (SD=7.3). Most frequent primary diagnoses were malignant neoplasms of the breast. Participants in the WMR program reported significantly better outcomes regarding quality of life (SMD=0.17-0.25), fatigue (SMD=0.18-0.27), coping with illness (SMD=0.17-0.22), and self-reported work-ability (SMD=0.16) compared to participants in MR program (all p<0.05). The results indicate a positive effect in favor of WMR for cancer patients with an elevated risk of not returning to work at the end of their treatment. © Georg Thieme Verlag KG Stuttgart · New York.

  12. A taxonomy of epithelial human cancer and their metastases

    Directory of Open Access Journals (Sweden)

    De Moor Bart

    2009-12-01

    Full Text Available Abstract Background Microarray technology has allowed to molecularly characterize many different cancer sites. This technology has the potential to individualize therapy and to discover new drug targets. However, due to technological differences and issues in standardized sample collection no study has evaluated the molecular profile of epithelial human cancer in a large number of samples and tissues. Additionally, it has not yet been extensively investigated whether metastases resemble their tissue of origin or tissue of destination. Methods We studied the expression profiles of a series of 1566 primary and 178 metastases by unsupervised hierarchical clustering. The clustering profile was subsequently investigated and correlated with clinico-pathological data. Statistical enrichment of clinico-pathological annotations of groups of samples was investigated using Fisher exact test. Gene set enrichment analysis (GSEA and DAVID functional enrichment analysis were used to investigate the molecular pathways. Kaplan-Meier survival analysis and log-rank tests were used to investigate prognostic significance of gene signatures. Results Large clusters corresponding to breast, gastrointestinal, ovarian and kidney primary tissues emerged from the data. Chromophobe renal cell carcinoma clustered together with follicular differentiated thyroid carcinoma, which supports recent morphological descriptions of thyroid follicular carcinoma-like tumors in the kidney and suggests that they represent a subtype of chromophobe carcinoma. We also found an expression signature identifying primary tumors of squamous cell histology in multiple tissues. Next, a subset of ovarian tumors enriched with endometrioid histology clustered together with endometrium tumors, confirming that they share their etiopathogenesis, which strongly differs from serous ovarian tumors. In addition, the clustering of colon and breast tumors correlated with clinico-pathological characteristics

  13. Brightest Cluster Galaxies in REXCESS Clusters

    Science.gov (United States)

    Haarsma, Deborah B.; Leisman, L.; Bruch, S.; Donahue, M.

    2009-01-01

    Most galaxy clusters contain a Brightest Cluster Galaxy (BCG) which is larger than the other cluster ellipticals and has a more extended profile. In the hierarchical model, the BCG forms through many galaxy mergers in the crowded center of the cluster, and thus its properties give insight into the assembly of the cluster as a whole. In this project, we are working with the Representative XMM-Newton Cluster Structure Survey (REXCESS) team (Boehringer et al 2007) to study BCGs in 33 X-ray luminous galaxy clusters, 0.055 < z < 0.183. We are imaging the BCGs in R band at the Southern Observatory for Astrophysical Research (SOAR) in Chile. In this poster, we discuss our methods and give preliminary measurements of the BCG magnitudes, morphology, and stellar mass. We compare these BCG properties with the properties of their host clusters, particularly of the X-ray emitting gas.

  14. clues: An R Package for Nonparametric Clustering Based on Local Shrinking

    Directory of Open Access Journals (Sweden)

    Fang Chang

    2010-02-01

    Full Text Available Determining the optimal number of clusters appears to be a persistent and controversial issue in cluster analysis. Most existing R packages targeting clustering require the user to specify the number of clusters in advance. However, if this subjectively chosen number is far from optimal, clustering may produce seriously misleading results. In order to address this vexing problem, we develop the R package clues to automate and evaluate the selection of an optimal number of clusters, which is widely applicable in the field of clustering analysis. Package clues uses two main procedures, shrinking and partitioning, to estimate an optimal number of clusters by maximizing an index function, either the CH index or the Silhouette index, rather than relying on guessing a pre-specified number. Five agreement indices (Rand index, Hubert and Arabie’s adjusted Rand index, Morey and Agresti’s adjusted Rand index, Fowlkes and Mallows index and Jaccard index, which measure the degree of agreement between any two partitions, are also provided in clues. In addition to numerical evidence, clues also supplies a deeper insight into the partitioning process with trajectory plots.

  15. Space-time interactions in childhood cancers

    International Nuclear Information System (INIS)

    Morris, V.

    1990-01-01

    During the last twenty five years, there have been sporadic published reports of cases of childhood leukaemia occurring in clusters. Renewed interest in the topic, following suggests that clusters may occur in the vicinity of nuclear establishments, has prompted this report of an investigation into 418 childhood cancer cases which occurred in the Midlands between 1953 and 1960. There was evidence among some age groups and diagnoses of an unexpectedly high number of close pairs of onsets, and some indication of similar patterns among births of children who later developed cancer. Measles appeared to occur more often in the 2-3 years before the onset of leukaemia in children who were later involved in close pairs than in their matched controls. It is concluded that common infectious diseases of childhood may play a minor role in the development of some cancers. Epidemics of these diseases may then be reflected on a greatly reduced scale in the subsequent distribution of cancer cases. (author)

  16. Distributed controller clustering in software defined networks.

    Directory of Open Access Journals (Sweden)

    Ahmed Abdelaziz

    Full Text Available Software Defined Networking (SDN is an emerging promising paradigm for network management because of its centralized network intelligence. However, the centralized control architecture of the software-defined networks (SDNs brings novel challenges of reliability, scalability, fault tolerance and interoperability. In this paper, we proposed a novel clustered distributed controller architecture in the real setting of SDNs. The distributed cluster implementation comprises of multiple popular SDN controllers. The proposed mechanism is evaluated using a real world network topology running on top of an emulated SDN environment. The result shows that the proposed distributed controller clustering mechanism is able to significantly reduce the average latency from 8.1% to 1.6%, the packet loss from 5.22% to 4.15%, compared to distributed controller without clustering running on HP Virtual Application Network (VAN SDN and Open Network Operating System (ONOS controllers respectively. Moreover, proposed method also shows reasonable CPU utilization results. Furthermore, the proposed mechanism makes possible to handle unexpected load fluctuations while maintaining a continuous network operation, even when there is a controller failure. The paper is a potential contribution stepping towards addressing the issues of reliability, scalability, fault tolerance, and inter-operability.

  17. Distributed controller clustering in software defined networks.

    Science.gov (United States)

    Abdelaziz, Ahmed; Fong, Ang Tan; Gani, Abdullah; Garba, Usman; Khan, Suleman; Akhunzada, Adnan; Talebian, Hamid; Choo, Kim-Kwang Raymond

    2017-01-01

    Software Defined Networking (SDN) is an emerging promising paradigm for network management because of its centralized network intelligence. However, the centralized control architecture of the software-defined networks (SDNs) brings novel challenges of reliability, scalability, fault tolerance and interoperability. In this paper, we proposed a novel clustered distributed controller architecture in the real setting of SDNs. The distributed cluster implementation comprises of multiple popular SDN controllers. The proposed mechanism is evaluated using a real world network topology running on top of an emulated SDN environment. The result shows that the proposed distributed controller clustering mechanism is able to significantly reduce the average latency from 8.1% to 1.6%, the packet loss from 5.22% to 4.15%, compared to distributed controller without clustering running on HP Virtual Application Network (VAN) SDN and Open Network Operating System (ONOS) controllers respectively. Moreover, proposed method also shows reasonable CPU utilization results. Furthermore, the proposed mechanism makes possible to handle unexpected load fluctuations while maintaining a continuous network operation, even when there is a controller failure. The paper is a potential contribution stepping towards addressing the issues of reliability, scalability, fault tolerance, and inter-operability.

  18. [Electronic and structural properties of individual nanometer-size supported metallic clusters

    International Nuclear Information System (INIS)

    Reifenberger, R.

    1993-01-01

    This report summarizes the work performed under contract DOE-FCO2-84ER45162. During the past ten years, our study of electron emission from laser-illuminated field emission tips has taken on a broader scope by addressing problems of direct interest to those concerned with the unique physical and chemical properties of nanometer-size clusters. The work performed has demonstrated that much needed data can be obtained on individual nanometer-size clusters supported on a wide-variety of different substrates. The work was performed in collaboration with R.P. Andres in the School of Chemical Engineering at Purdue University. The Multiple Expansion Cluster Source developed by Andres and his students was essential for producing the nanometer-size clusters studied. The following report features a discussion of these results. This report provides a motivation for studying the properties of nanometer-size clusters and summarizes the results obtained

  19. An evolutionarily conserved three-dimensional structure in the vertebrate Irx clusters facilitates enhancer sharing and coregulation

    NARCIS (Netherlands)

    Tena, J.J.; Alonso, M.E.; de la Calle-Mustienes, E.; Splinter, E.; de Laat, W.; Manzanares, M.; Gomez-Skarmeta, J.L.

    2011-01-01

    Developmental gene clusters are paradigms for the study of gene regulation; however, the mechanisms that mediate phenomena such as coregulation and enhancer sharing remain largely elusive. Here we address this issue by analysing the vertebrate Irx clusters. We first present a deep enhancer screen of

  20. A heuristic approach to possibilistic clustering algorithms and applications

    CERN Document Server

    Viattchenin, Dmitri A

    2013-01-01

    The present book outlines a new approach to possibilistic clustering in which the sought clustering structure of the set of objects is based directly on the formal definition of fuzzy cluster and the possibilistic memberships are determined directly from the values of the pairwise similarity of objects.   The proposed approach can be used for solving different classification problems. Here, some techniques that might be useful at this purpose are outlined, including a methodology for constructing a set of labeled objects for a semi-supervised clustering algorithm, a methodology for reducing analyzed attribute space dimensionality and a methods for asymmetric data processing. Moreover,  a technique for constructing a subset of the most appropriate alternatives for a set of weak fuzzy preference relations, which are defined on a universe of alternatives, is described in detail, and a method for rapidly prototyping the Mamdani’s fuzzy inference systems is introduced. This book addresses engineers, scientist...

  1. Three-Dimensional Scaffold Chip with Thermosensitive Coating for Capture and Reversible Release of Individual and Cluster of Circulating Tumor Cells.

    Science.gov (United States)

    Cheng, Shi-Bo; Xie, Min; Chen, Yan; Xiong, Jun; Liu, Ya; Chen, Zhen; Guo, Shan; Shu, Ying; Wang, Ming; Yuan, Bi-Feng; Dong, Wei-Guo; Huang, Wei-Hua

    2017-08-01

    Tumor metastasis is attributed to circulating tumor cells (CTC) or CTC clusters. Many strategies have hitherto been designed to isolate CTCs, but there are few methods that can capture and gently release CTC clusters as efficient as single CTCs. Herein, we developed a three-dimensional (3D) scaffold chip with thermosensitive coating for high-efficiency capture and release of individual and cluster CTCs. The 3D scaffold chip successfully combines the specific recognition and physically obstructed effect of 3D scaffold structure to significantly improve cell clusters capture efficiency. Thermosensitive gelatin hydrogel uniformly coated on the scaffold dissolves at 37 °C quickly, and the captured cells are gently released from chip with high viability. Notably, this platform was applied to isolate CTCs from cancer patients' blood samples. This allows global DNA and RNA methylation analysis of collected single CTC and CTC clusters, indicating the great potential of this platform in cancer diagnosis and downstream analysis at the molecular level.

  2. Functional Interference Clusters in Cancer Patients With Bone Metastases: A Secondary Analysis of RTOG 9714

    International Nuclear Information System (INIS)

    Chow, Edward; James, Jennifer; Barsevick, Andrea; Hartsell, William; Ratcliffe, Sarah; Scarantino, Charles; Ivker, Robert; Roach, Mack; Suh, John; Petersen, Ivy; Konski, Andre; Demas, William; Bruner, Deborah

    2010-01-01

    Purpose: To explore the relationships (clusters) among the functional interference items in the Brief Pain Inventory (BPI) in patients with bone metastases. Methods: Patients enrolled in the Radiation Therapy Oncology Group (RTOG) 9714 bone metastases study were eligible. Patients were assessed at baseline and 4, 8, and 12 weeks after randomization for the palliative radiotherapy with the BPI, which consists of seven functional items: general activity, mood, walking ability, normal work, relations with others, sleep, and enjoyment of life. Principal component analysis with varimax rotation was used to determine the clusters between the functional items at baseline and the follow-up. Cronbach's alpha was used to determine the consistency and reliability of each cluster at baseline and follow-up. Results: There were 448 male and 461 female patients, with a median age of 67 years. There were two functional interference clusters at baseline, which accounted for 71% of the total variance. The first cluster (physical interference) included normal work and walking ability, which accounted for 58% of the total variance. The second cluster (psychosocial interference) included relations with others and sleep, which accounted for 13% of the total variance. The Cronbach's alpha statistics were 0.83 and 0.80, respectively. The functional clusters changed at week 12 in responders but persisted through week 12 in nonresponders. Conclusion: Palliative radiotherapy is effective in reducing bone pain. Functional interference component clusters exist in patients treated for bone metastases. These clusters changed over time in this study, possibly attributable to treatment. Further research is needed to examine these effects.

  3. DLTAP: A Network-efficient Scheduling Method for Distributed Deep Learning Workload in Containerized Cluster Environment

    OpenAIRE

    Qiao Wei; Li Ying; Wu Zhong-Hai

    2017-01-01

    Deep neural networks (DNNs) have recently yielded strong results on a range of applications. Training these DNNs using a cluster of commodity machines is a promising approach since training is time consuming and compute-intensive. Furthermore, putting DNN tasks into containers of clusters would enable broader and easier deployment of DNN-based algorithms. Toward this end, this paper addresses the problem of scheduling DNN tasks in the containerized cluster environment. Efficiently scheduling ...

  4. The role of economic clusters in improving urban planning support

    NARCIS (Netherlands)

    Yang, Zhenshan|info:eu-repo/dai/nl/251865274

    2010-01-01

    Improving the mechanism of integrating economic and spatial developments is an important issue in urban policy analysis and design. As Economic Clusters (ECs) become an important organisation in contemporary urban development in both economic and spatial practices, the research addresses the

  5. Metal cluster compounds - chemistry and importance; clusters containing isolated main group element atoms, large metal cluster compounds, cluster fluxionality

    International Nuclear Information System (INIS)

    Walther, B.

    1988-01-01

    This part of the review on metal cluster compounds deals with clusters containing isolated main group element atoms, with high nuclearity clusters and metal cluster fluxionality. It will be obvious that main group element atoms strongly influence the geometry, stability and reactivity of the clusters. High nuclearity clusters are of interest in there own due to the diversity of the structures adopted, but their intermediate position between molecules and the metallic state makes them a fascinating research object too. These both sites of the metal cluster chemistry as well as the frequently observed ligand and core fluxionality are related to the cluster metal and surface analogy. (author)

  6. Retrieval with Clustering in a Case-Based Reasoning System for Radiotherapy Treatment Planning

    Science.gov (United States)

    Khussainova, Gulmira; Petrovic, Sanja; Jagannathan, Rupa

    2015-05-01

    Radiotherapy treatment planning aims to deliver a sufficient radiation dose to cancerous tumour cells while sparing healthy organs in the tumour surrounding area. This is a trial and error process highly dependent on the medical staff's experience and knowledge. Case-Based Reasoning (CBR) is an artificial intelligence tool that uses past experiences to solve new problems. A CBR system has been developed to facilitate radiotherapy treatment planning for brain cancer. Given a new patient case the existing CBR system retrieves a similar case from an archive of successfully treated patient cases with the suggested treatment plan. The next step requires adaptation of the retrieved treatment plan to meet the specific demands of the new case. The CBR system was tested by medical physicists for the new patient cases. It was discovered that some of the retrieved cases were not suitable and could not be adapted for the new cases. This motivated us to revise the retrieval mechanism of the existing CBR system by adding a clustering stage that clusters cases based on their tumour positions. A number of well-known clustering methods were investigated and employed in the retrieval mechanism. Results using real world brain cancer patient cases have shown that the success rate of the new CBR retrieval is higher than that of the original system.

  7. Retrieval with Clustering in a Case-Based Reasoning System for Radiotherapy Treatment Planning

    International Nuclear Information System (INIS)

    Khussainova, Gulmira; Petrovic, Sanja; Jagannathan, Rupa

    2015-01-01

    Radiotherapy treatment planning aims to deliver a sufficient radiation dose to cancerous tumour cells while sparing healthy organs in the tumour surrounding area. This is a trial and error process highly dependent on the medical staff's experience and knowledge. Case-Based Reasoning (CBR) is an artificial intelligence tool that uses past experiences to solve new problems. A CBR system has been developed to facilitate radiotherapy treatment planning for brain cancer. Given a new patient case the existing CBR system retrieves a similar case from an archive of successfully treated patient cases with the suggested treatment plan. The next step requires adaptation of the retrieved treatment plan to meet the specific demands of the new case. The CBR system was tested by medical physicists for the new patient cases. It was discovered that some of the retrieved cases were not suitable and could not be adapted for the new cases. This motivated us to revise the retrieval mechanism of the existing CBR system by adding a clustering stage that clusters cases based on their tumour positions. A number of well-known clustering methods were investigated and employed in the retrieval mechanism. Results using real world brain cancer patient cases have shown that the success rate of the new CBR retrieval is higher than that of the original system. (paper)

  8. MO-DE-207B-03: Improved Cancer Classification Using Patient-Specific Biological Pathway Information Via Gene Expression Data

    Energy Technology Data Exchange (ETDEWEB)

    Young, M; Craft, D [Massachusetts General Hospital and Harvard Medical School, Boston, MA (United States)

    2016-06-15

    Purpose: To develop an efficient, pathway-based classification system using network biology statistics to assist in patient-specific response predictions to radiation and drug therapies across multiple cancer types. Methods: We developed PICS (Pathway Informed Classification System), a novel two-step cancer classification algorithm. In PICS, a matrix m of mRNA expression values for a patient cohort is collapsed into a matrix p of biological pathways. The entries of p, which we term pathway scores, are obtained from either principal component analysis (PCA), normal tissue centroid (NTC), or gene expression deviation (GED). The pathway score matrix is clustered using both k-means and hierarchical clustering, and a clustering is judged by how well it groups patients into distinct survival classes. The most effective pathway scoring/clustering combination, per clustering p-value, thus generates various ‘signatures’ for conventional and functional cancer classification. Results: PICS successfully regularized large dimension gene data, separated normal and cancerous tissues, and clustered a large patient cohort spanning six cancer types. Furthermore, PICS clustered patient cohorts into distinct, statistically-significant survival groups. For a suboptimally-debulked ovarian cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00127) showed significant improvement over that of a prior gene expression-classified study (p = .0179). For a pancreatic cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00141) showed significant improvement over that of a prior gene expression-classified study (p = .04). Pathway-based classification confirmed biomarkers for the pyrimidine, WNT-signaling, glycerophosphoglycerol, beta-alanine, and panthothenic acid pathways for ovarian cancer. Despite its robust nature, PICS requires significantly less run time than current pathway scoring methods. Conclusion: This work validates the PICS method to improve

  9. Neoadjuvant chemoradiotherapy plus surgery versus active surveillance for oesophageal cancer: a stepped-wedge cluster randomised trial.

    Science.gov (United States)

    Noordman, Bo Jan; Wijnhoven, Bas P L; Lagarde, Sjoerd M; Boonstra, Jurjen J; Coene, Peter Paul L O; Dekker, Jan Willem T; Doukas, Michael; van der Gaast, Ate; Heisterkamp, Joos; Kouwenhoven, Ewout A; Nieuwenhuijzen, Grard A P; Pierie, Jean-Pierre E N; Rosman, Camiel; van Sandick, Johanna W; van der Sangen, Maurice J C; Sosef, Meindert N; Spaander, Manon C W; Valkema, Roelf; van der Zaag, Edwin S; Steyerberg, Ewout W; van Lanschot, J Jan B

    2018-02-06

    Neoadjuvant chemoradiotherapy (nCRT) plus surgery is a standard treatment for locally advanced oesophageal cancer. With this treatment, 29% of patients have a pathologically complete response in the resection specimen. This provides the rationale for investigating an active surveillance approach. The aim of this study is to assess the (cost-)effectiveness of active surveillance vs. standard oesophagectomy after nCRT for oesophageal cancer. This is a phase-III multi-centre, stepped-wedge cluster randomised controlled trial. A total of 300 patients with clinically complete response (cCR, i.e. no local or disseminated disease proven by histology) after nCRT will be randomised to show non-inferiority of active surveillance to standard oesophagectomy (non-inferiority margin 15%, intra-correlation coefficient 0.02, power 80%, 2-sided α 0.05, 12% drop-out). Patients will undergo a first clinical response evaluation (CRE-I) 4-6 weeks after nCRT, consisting of endoscopy with bite-on-bite biopsies of the primary tumour site and other suspected lesions. Clinically complete responders will undergo a second CRE (CRE-II), 6-8 weeks after CRE-I. CRE-II will include 18F-FDG-PET-CT, followed by endoscopy with bite-on-bite biopsies and ultra-endosonography plus fine needle aspiration of suspected lymph nodes and/or PET- positive lesions. Patients with cCR at CRE-II will be assigned to oesophagectomy (first phase) or active surveillance (second phase of the study). The duration of the first phase is determined randomly over the 12 centres, i.e., stepped-wedge cluster design. Patients in the active surveillance arm will undergo diagnostic evaluations similar to CRE-II at 6/9/12/16/20/24/30/36/48 and 60 months after nCRT. In this arm, oesophagectomy will be offered only to patients in whom locoregional regrowth is highly suspected or proven, without distant dissemination. The main study parameter is overall survival; secondary endpoints include percentage of patients who do not

  10. Evaluation of a specialized oncology nursing supportive care intervention in newly diagnosed breast and colorectal cancer patients following surgery: a cluster randomized trial.

    Science.gov (United States)

    Sussman, Jonathan; Bainbridge, Daryl; Whelan, Timothy J; Brazil, Kevin; Parpia, Sameer; Wiernikowski, Jennifer; Schiff, Susan; Rodin, Gary; Sergeant, Myles; Howell, Doris

    2018-05-01

    Better coordination of supportive services during the early phases of cancer care has been proposed to improve the care experience of patients. We conducted a randomized trial to test a community-based nurse-led coordination of care intervention in cancer patients. Surgical practices were cluster randomized to a control group involving usual care practices or a standardized nursing intervention consisting of an in-person supportive care assessment with ongoing support to meet identified needs, including linkage to community services. Newly diagnosed breast and colorectal cancer patients within 7 days of cancer surgery were eligible. The primary outcome was the patient-reported outcome (PRO) of continuity of care (CCCQ) measured at 3 weeks. Secondary outcomes included unmet supportive care needs (SCNS), quality of life (EORTC QLQ-C30), health resource utilization, and level of uncertainty with care trajectory (MUIS) at 3 and/or 8 weeks. A total of 121 breast and 72 colorectal patients were randomized through 28 surgical practices. There was a small improvement in the informational domain of continuity of care (difference 0.29 p = 0.05) and a trend to less emergency room use (15.8 vs 7.1%) (p = 0.07). There were no significant differences between groups on unmet need, quality of life, or uncertainty. We did not find substantial gaps in the PROs measured immediately following surgery for breast and colorectal cancer patients. The results of this study support a more targeted approach based on need and inform future research focused on improving navigation during the initial phases of cancer treatment. ClinicalTrials.gov Identifier: NCT00182234. SONICS-Effectiveness of Specialist Oncology Nursing.

  11. Robustness and backbone motif of a cancer network regulated by miR-17-92 cluster during the G1/S transition.

    Directory of Open Access Journals (Sweden)

    Lijian Yang

    Full Text Available Based on interactions among transcription factors, oncogenes, tumor suppressors and microRNAs, a Boolean model of cancer network regulated by miR-17-92 cluster is constructed, and the network is associated with the control of G1/S transition in the mammalian cell cycle. The robustness properties of this regulatory network are investigated by virtue of the Boolean network theory. It is found that, during G1/S transition in the cell cycle process, the regulatory networks are robustly constructed, and the robustness property is largely preserved with respect to small perturbations to the network. By using the unique process-based approach, the structure of this network is analyzed. It is shown that the network can be decomposed into a backbone motif which provides the main biological functions, and a remaining motif which makes the regulatory system more stable. The critical role of miR-17-92 in suppressing the G1/S cell cycle checkpoint and increasing the uncontrolled proliferation of the cancer cells by targeting a genetic network of interacting proteins is displayed with our model.

  12. Ensemble-based computational approach discriminates functional activity of p53 cancer and rescue mutants.

    Directory of Open Access Journals (Sweden)

    Özlem Demir

    2011-10-01

    Full Text Available The tumor suppressor protein p53 can lose its function upon single-point missense mutations in the core DNA-binding domain ("cancer mutants". Activity can be restored by second-site suppressor mutations ("rescue mutants". This paper relates the functional activity of p53 cancer and rescue mutants to their overall molecular dynamics (MD, without focusing on local structural details. A novel global measure of protein flexibility for the p53 core DNA-binding domain, the number of clusters at a certain RMSD cutoff, was computed by clustering over 0.7 µs of explicitly solvated all-atom MD simulations. For wild-type p53 and a sample of p53 cancer or rescue mutants, the number of clusters was a good predictor of in vivo p53 functional activity in cell-based assays. This number-of-clusters (NOC metric was strongly correlated (r(2 = 0.77 with reported values of experimentally measured ΔΔG protein thermodynamic stability. Interpreting the number of clusters as a measure of protein flexibility: (i p53 cancer mutants were more flexible than wild-type protein, (ii second-site rescue mutations decreased the flexibility of cancer mutants, and (iii negative controls of non-rescue second-site mutants did not. This new method reflects the overall stability of the p53 core domain and can discriminate which second-site mutations restore activity to p53 cancer mutants.

  13. Hough transform for clustered microcalcifications detection in full-field digital mammograms

    Science.gov (United States)

    Fanizzi, A.; Basile, T. M. A.; Losurdo, L.; Amoroso, N.; Bellotti, R.; Bottigli, U.; Dentamaro, R.; Didonna, V.; Fausto, A.; Massafra, R.; Moschetta, M.; Tamborra, P.; Tangaro, S.; La Forgia, D.

    2017-09-01

    Many screening programs use mammography as principal diagnostic tool for detecting breast cancer at a very early stage. Despite the efficacy of the mammograms in highlighting breast diseases, the detection of some lesions is still doubtless for radiologists. In particular, the extremely minute and elongated salt-like particles of microcalcifications are sometimes no larger than 0.1 mm and represent approximately half of all cancer detected by means of mammograms. Hence the need for automatic tools able to support radiologists in their work. Here, we propose a computer assisted diagnostic tool to support radiologists in identifying microcalcifications in full (native) digital mammographic images. The proposed CAD system consists of a pre-processing step, that improves contrast and reduces noise by applying Sobel edge detection algorithm and Gaussian filter, followed by a microcalcification detection step performed by exploiting the circular Hough transform. The procedure performance was tested on 200 images coming from the Breast Cancer Digital Repository (BCDR), a publicly available database. The automatically detected clusters of microcalcifications were evaluated by skilled radiologists which asses the validity of the correctly identified regions of interest as well as the system error in case of missed clustered microcalcifications. The system performance was evaluated in terms of Sensitivity and False Positives per images (FPi) rate resulting comparable to the state-of-art approaches. The proposed model was able to accurately predict the microcalcification clusters obtaining performances (sensibility = 91.78% and FPi rate = 3.99) which favorably compare to other state-of-the-art approaches.

  14. Impact of socioeconomic inequalities on geographic disparities in cancer incidence: comparison of methods for spatial disease mapping.

    Science.gov (United States)

    Goungounga, Juste Aristide; Gaudart, Jean; Colonna, Marc; Giorgi, Roch

    2016-10-12

    The reliability of spatial statistics is often put into question because real spatial variations may not be found, especially in heterogeneous areas. Our objective was to compare empirically different cluster detection methods. We assessed their ability to find spatial clusters of cancer cases and evaluated the impact of the socioeconomic status (e.g., the Townsend index) on cancer incidence. Moran's I, the empirical Bayes index (EBI), and Potthoff-Whittinghill test were used to investigate the general clustering. The local cluster detection methods were: i) the spatial oblique decision tree (SpODT); ii) the spatial scan statistic of Kulldorff (SaTScan); and, iii) the hierarchical Bayesian spatial modeling (HBSM) in a univariate and multivariate setting. These methods were used with and without introducing the Townsend index of socioeconomic deprivation known to be related to the distribution of cancer incidence. Incidence data stemmed from the Cancer Registry of Isère and were limited to prostate, lung, colon-rectum, and bladder cancers diagnosed between 1999 and 2007 in men only. The study found a spatial heterogeneity (p 1.2). The multivariate HBSM found a spatial correlation between lung and bladder cancers (r = 0.6). In spatial analysis of cancer incidence, SpODT and HBSM may be used not only for cluster detection but also for searching for confounding or etiological factors in small areas. Moreover, the multivariate HBSM offers a flexible and meaningful modeling of spatial variations; it shows plausible previously unknown associations between various cancers.

  15. Efficient nonparametric and asymptotic Bayesian model selection methods for attributed graph clustering

    KAUST Repository

    Xu, Zhiqiang

    2017-02-16

    Attributed graph clustering, also known as community detection on attributed graphs, attracts much interests recently due to the ubiquity of attributed graphs in real life. Many existing algorithms have been proposed for this problem, which are either distance based or model based. However, model selection in attributed graph clustering has not been well addressed, that is, most existing algorithms assume the cluster number to be known a priori. In this paper, we propose two efficient approaches for attributed graph clustering with automatic model selection. The first approach is a popular Bayesian nonparametric method, while the second approach is an asymptotic method based on a recently proposed model selection criterion, factorized information criterion. Experimental results on both synthetic and real datasets demonstrate that our approaches for attributed graph clustering with automatic model selection significantly outperform the state-of-the-art algorithm.

  16. Efficient nonparametric and asymptotic Bayesian model selection methods for attributed graph clustering

    KAUST Repository

    Xu, Zhiqiang; Cheng, James; Xiao, Xiaokui; Fujimaki, Ryohei; Muraoka, Yusuke

    2017-01-01

    Attributed graph clustering, also known as community detection on attributed graphs, attracts much interests recently due to the ubiquity of attributed graphs in real life. Many existing algorithms have been proposed for this problem, which are either distance based or model based. However, model selection in attributed graph clustering has not been well addressed, that is, most existing algorithms assume the cluster number to be known a priori. In this paper, we propose two efficient approaches for attributed graph clustering with automatic model selection. The first approach is a popular Bayesian nonparametric method, while the second approach is an asymptotic method based on a recently proposed model selection criterion, factorized information criterion. Experimental results on both synthetic and real datasets demonstrate that our approaches for attributed graph clustering with automatic model selection significantly outperform the state-of-the-art algorithm.

  17. PREFACE: Nuclear Cluster Conference; Cluster'07

    Science.gov (United States)

    Freer, Martin

    2008-05-01

    The Cluster Conference is a long-running conference series dating back to the 1960's, the first being initiated by Wildermuth in Bochum, Germany, in 1969. The most recent meeting was held in Nara, Japan, in 2003, and in 2007 the 9th Cluster Conference was held in Stratford-upon-Avon, UK. As the name suggests the town of Stratford lies upon the River Avon, and shortly before the conference, due to unprecedented rainfall in the area (approximately 10 cm within half a day), lay in the River Avon! Stratford is the birthplace of the `Bard of Avon' William Shakespeare, and this formed an intriguing conference backdrop. The meeting was attended by some 90 delegates and the programme contained 65 70 oral presentations, and was opened by a historical perspective presented by Professor Brink (Oxford) and closed by Professor Horiuchi (RCNP) with an overview of the conference and future perspectives. In between, the conference covered aspects of clustering in exotic nuclei (both neutron and proton-rich), molecular structures in which valence neutrons are exchanged between cluster cores, condensates in nuclei, neutron-clusters, superheavy nuclei, clusters in nuclear astrophysical processes and exotic cluster decays such as 2p and ternary cluster decay. The field of nuclear clustering has become strongly influenced by the physics of radioactive beam facilities (reflected in the programme), and by the excitement that clustering may have an important impact on the structure of nuclei at the neutron drip-line. It was clear that since Nara the field had progressed substantially and that new themes had emerged and others had crystallized. Two particular topics resonated strongly condensates and nuclear molecules. These topics are thus likely to be central in the next cluster conference which will be held in 2011 in the Hungarian city of Debrechen. Martin Freer Participants and Cluster'07

  18. Quality of prostate cancer screening information on the websites of nationally recognized cancer centers and health organizations.

    Science.gov (United States)

    Manole, Bogdan-Alexandru; Wakefield, Daniel V; Dove, Austin P; Dulaney, Caleb R; Marcrom, Samuel R; Schwartz, David L; Farmer, Michael R

    2017-12-24

    The purpose of this study was to survey the accessibility and quality of prostate-specific antigen (PSA) screening information from National Cancer Institute (NCI) cancer center and public health organization Web sites. We surveyed the December 1, 2016, version of all 63 NCI-designated cancer center public Web sites and 5 major online clearinghouses from allied public/private organizations (cancer.gov, cancer.org, PCF.org, USPSTF.org, and CDC.gov). Web sites were analyzed according to a 50-item list of validated health care information quality measures. Web sites were graded by 2 blinded reviewers. Interrater agreement was confirmed by Cohen kappa coefficient. Ninety percent of Web sites addressed PSA screening. Cancer center sites covered 45% of topics surveyed, whereas organization Web sites addressed 70%. All organizational Web pages addressed the possibility of false-positive screening results; 41% of cancer center Web pages did not. Forty percent of cancer center Web pages also did not discuss next steps if a PSA test was positive. Only 6% of cancer center Web pages were rated by our reviewers as "superior" (eg, addressing >75% of the surveyed topics) versus 20% of organizational Web pages. Interrater agreement between our reviewers was high (kappa coefficient = 0.602). NCI-designated cancer center Web sites publish lower quality public information about PSA screening than sites run by major allied organizations. Nonetheless, information and communication deficiencies were observed across all surveyed sites. In an age of increasing patient consumerism, prospective prostate cancer patients would benefit from improved online PSA screening information from provider and advocacy organizations. Validated cancer patient Web educational standards remain an important, understudied priority. Copyright © 2018. Published by Elsevier Inc.

  19. Bridging the age gap in breast cancer: evaluation of decision support interventions for older women with operable breast cancer: protocol for a cluster randomised controlled trial.

    Science.gov (United States)

    Collins, Karen; Reed, Malcolm; Lifford, Kate; Burton, Maria; Edwards, Adrian; Ring, Alistair; Brain, Katherine; Harder, Helena; Robinson, Thompson; Cheung, Kwok Leung; Morgan, Jenna; Audisio, Riccardo; Ward, Susan; Richards, Paul; Martin, Charlene; Chater, Tim; Pemberton, Kirsty; Nettleship, Anthony; Murray, Christopher; Walters, Stephen; Bortolami, Oscar; Armitage, Fiona; Leonard, Robert; Gath, Jacqui; Revell, Deirdre; Green, Tracy; Wyld, Lynda

    2017-07-31

    While breast cancer outcomes are improving steadily in younger women due to advances in screening and improved therapies, there has been little change in outcomes among the older age group. It is inevitable that comorbidities/frailty rates are higher, which may increase the risks of some breast cancer treatments such as surgery and chemotherapy, many older women are healthy and may benefit from their use. Adjusting treatment regimens appropriately for age/comorbidity/frailty is variable and largely non-evidence based, specifically with regard to rates of surgery for operable oestrogen receptor-positive disease and rates of chemotherapy for high-risk disease. This multicentre, parallel group, pragmatic cluster randomised controlled trial (RCT) (2015-18) reported here is nested within a larger ongoing 'Age Gap Cohort Study' (2012-18RP-PG-1209-10071), aims to evaluate the effectiveness of a complex intervention of decision support interventions to assist in the treatment decision making for early breast cancer in older women. The interventions include two patient decision aids (primary endocrine therapy vs surgery/antioestrogen therapy and chemotherapy vs no chemotherapy) and a clinical treatment outcomes algorithm for clinicians. National and local ethics committee approval was obtained for all UK participating sites. Results from the trial will be submitted for publication in international peer-reviewed scientific journals. 115550. European Union Drug Regulating Authorities Clinical Trials (EudraCT) number 2015-004220-61;Pre-results. Sponsor's Protocol Code Number Sheffield Teaching Hospitals STH17086. ISRCTN 32447*. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  20. LGBT Populations' Barriers to Cancer Care.

    Science.gov (United States)

    Boehmer, Ulrike

    2018-02-01

    To describe lesbian, gay, bisexual, and transgender (LGBT) individuals' barriers to accessing and receiving quality cancer care. Published data on cancer care and studies of LGBT individuals. There is a clustering of barriers among LGBT individuals, which suggests multiple inequities exist in LGBT individuals' cancer care, although data on disparities along the cancer control continuum are not consistently available. Nurses can make a difference in LGBT individuals' cancer care by obtaining training on LGBT health and their cancer-related needs and by providing a welcoming and respectful relationship with LGBT patients. Copyright © 2017 Elsevier Inc. All rights reserved.

  1. Geospatial cryptography: enabling researchers to access private, spatially referenced, human subjects data for cancer control and prevention.

    Science.gov (United States)

    Jacquez, Geoffrey M; Essex, Aleksander; Curtis, Andrew; Kohler, Betsy; Sherman, Recinda; Emam, Khaled El; Shi, Chen; Kaufmann, Andy; Beale, Linda; Cusick, Thomas; Goldberg, Daniel; Goovaerts, Pierre

    2017-07-01

    As the volume, accuracy and precision of digital geographic information have increased, concerns regarding individual privacy and confidentiality have come to the forefront. Not only do these challenge a basic tenet underlying the advancement of science by posing substantial obstacles to the sharing of data to validate research results, but they are obstacles to conducting certain research projects in the first place. Geospatial cryptography involves the specification, design, implementation and application of cryptographic techniques to address privacy, confidentiality and security concerns for geographically referenced data. This article defines geospatial cryptography and demonstrates its application in cancer control and surveillance. Four use cases are considered: (1) national-level de-duplication among state or province-based cancer registries; (2) sharing of confidential data across cancer registries to support case aggregation across administrative geographies; (3) secure data linkage; and (4) cancer cluster investigation and surveillance. A secure multi-party system for geospatial cryptography is developed. Solutions under geospatial cryptography are presented and computation time is calculated. As services provided by cancer registries to the research community, de-duplication, case aggregation across administrative geographies and secure data linkage are often time-consuming and in some instances precluded by confidentiality and security concerns. Geospatial cryptography provides secure solutions that hold significant promise for addressing these concerns and for accelerating the pace of research with human subjects data residing in our nation's cancer registries. Pursuit of the research directions posed herein conceivably would lead to a geospatially encrypted geographic information system (GEGIS) designed specifically to promote the sharing and spatial analysis of confidential data. Geospatial cryptography holds substantial promise for accelerating the

  2. A fully Bayesian latent variable model for integrative clustering analysis of multi-type omics data.

    Science.gov (United States)

    Mo, Qianxing; Shen, Ronglai; Guo, Cui; Vannucci, Marina; Chan, Keith S; Hilsenbeck, Susan G

    2018-01-01

    Identification of clinically relevant tumor subtypes and omics signatures is an important task in cancer translational research for precision medicine. Large-scale genomic profiling studies such as The Cancer Genome Atlas (TCGA) Research Network have generated vast amounts of genomic, transcriptomic, epigenomic, and proteomic data. While these studies have provided great resources for researchers to discover clinically relevant tumor subtypes and driver molecular alterations, there are few computationally efficient methods and tools for integrative clustering analysis of these multi-type omics data. Therefore, the aim of this article is to develop a fully Bayesian latent variable method (called iClusterBayes) that can jointly model omics data of continuous and discrete data types for identification of tumor subtypes and relevant omics features. Specifically, the proposed method uses a few latent variables to capture the inherent structure of multiple omics data sets to achieve joint dimension reduction. As a result, the tumor samples can be clustered in the latent variable space and relevant omics features that drive the sample clustering are identified through Bayesian variable selection. This method significantly improve on the existing integrative clustering method iClusterPlus in terms of statistical inference and computational speed. By analyzing TCGA and simulated data sets, we demonstrate the excellent performance of the proposed method in revealing clinically meaningful tumor subtypes and driver omics features. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  3. Frequency of breast cancer, lung cancer, and tobacco use articles in women's magazines from 1987 to 2003.

    Science.gov (United States)

    Tobler, Kyle J; Wilson, Philip K; Napolitano, Peter G

    2009-01-01

    The objective of this study was to compare the frequency of articles in women's magazines that address breast cancer, lung cancer, and tobacco use from 1987-2003 and to ascertain whether the annual number of articles reflected corresponding cancer mortality rates from breast cancer and lung cancer and the number of female smokers throughout this time period. We reviewed 13 women's magazines published in the United States from 1987-2003 using the search terms breast cancer, lung cancer, smoking, and tobacco. We reviewed the abstracts or entire articles to determine relevance. A total of 1044 articles addressed breast cancer, lung cancer, or tobacco use: 681 articles related to breast cancer, 47 related to lung cancer, and 316 related to tobacco use. The greater number of breast cancer articles compared to lung cancer articles was statistically significant (P value magazines from 1987-2003 despite the increase in lung cancer mortality, a decrease in breast cancer mortality, and an insignificant change in the number of female smokers.

  4. Coronal Mass Ejection Data Clustering and Visualization of Decision Trees

    Science.gov (United States)

    Ma, Ruizhe; Angryk, Rafal A.; Riley, Pete; Filali Boubrahimi, Soukaina

    2018-05-01

    Coronal mass ejections (CMEs) can be categorized as either “magnetic clouds” (MCs) or non-MCs. Features such as a large magnetic field, low plasma-beta, and low proton temperature suggest that a CME event is also an MC event; however, so far there is neither a definitive method nor an automatic process to distinguish the two. Human labeling is time-consuming, and results can fluctuate owing to the imprecise definition of such events. In this study, we approach the problem of MC and non-MC distinction from a time series data analysis perspective and show how clustering can shed some light on this problem. Although many algorithms exist for traditional data clustering in the Euclidean space, they are not well suited for time series data. Problems such as inadequate distance measure, inaccurate cluster center description, and lack of intuitive cluster representations need to be addressed for effective time series clustering. Our data analysis in this work is twofold: clustering and visualization. For clustering we compared the results from the popular hierarchical agglomerative clustering technique to a distance density clustering heuristic we developed previously for time series data clustering. In both cases, dynamic time warping will be used for similarity measure. For classification as well as visualization, we use decision trees to aggregate single-dimensional clustering results to form a multidimensional time series decision tree, with averaged time series to present each decision. In this study, we achieved modest accuracy and, more importantly, an intuitive interpretation of how different parameters contribute to an MC event.

  5. Effectiveness of work-related medical rehabilitation in cancer patients: study protocol of a cluster-randomized multicenter trial.

    Science.gov (United States)

    Wienert, Julian; Schwarz, Betje; Bethge, Matthias

    2016-07-27

    Work is a central resource for cancer survivors as it not only provides income but also impacts health and quality of life. Additionally, work helps survivors to cope with the perceived critical life event. The German Pension Insurance provides medical rehabilitation for working-age patients with chronic diseases to improve and restore their work ability, and support returning to or staying at work, and thus tries to sustainably avoid health-related early retirement. Past research showed that conventional medical rehabilitation programs do not support returning to work sufficiently and that work-related medical rehabilitation programs report higher return-to-work rates across several health conditions, when compared to medical rehabilitation. Therefore, the current study protocol outlines an effectiveness study of such a program for cancer survivors. To evaluate the effectiveness of work-related medical rehabilitation in cancer patients we conduct a cluster-randomized multicenter trial. In total, 504 rehabilitation patients between 18 and 60 years with a Karnofsky Performance Status of ≥70 %, a preliminary positive social-medical prognosis of employability for at least 3 h/day within the next 6 months and an elevated risk of not returning to work will be recruited in four inpatient rehabilitation centers. Patients are randomized to the work-related medical rehabilitation program or the conventional medical rehabilitation program based on their week of arrival at each rehabilitation center. The work-related medical rehabilitation program comprises additional work-related diagnostics, multi-professional team meetings, an introductory session as well as work-related functional capacity training, work-related psychological groups, and social counseling. All additional components are aimed at the adjustment of the patients' capacity in relation to their individual job demands. Role functioning defines the main study outcome and will be assessed with the EORTC

  6. Improving quality of life through the routine use of the patient concerns inventory for head and neck cancer patients: a cluster preference randomized controlled trial.

    Science.gov (United States)

    Rogers, Simon N; Lowe, Derek; Lowies, Cher; Yeo, Seow Tien; Allmark, Christine; Mcavery, Dominic; Humphris, Gerald M; Flavel, Robert; Semple, Cherith; Thomas, Steven J; Kanatas, Anastasios

    2018-04-18

    The consequences of treatment for Head and Neck cancer (HNC) patients has profound detrimental impacts such as impaired QOL, emotional distress, delayed recovery and frequent use of healthcare. The aim of this trial is to determine if the routine use of the Patients Concerns Inventory (PCI) package in review clinics during the first year following treatment can improve overall quality of life, reduce the social-emotional impact of cancer and reduce levels of distress. Furthermore, we aim to describe the economic costs and benefits of using the PCI. This will be a cluster preference randomised control trial with consultants either 'using' or 'not using' the PCI package at clinic. It will involve two centres Leeds and Liverpool. 416 eligible patients from at least 10 consultant clusters are required to show a clinically meaningful difference in the primary outcome. The primary outcome is the percentage of participants with less than good overall quality of life at the final one-year clinic as measured by the University of Washington QOL questionnaire version 4 (UWQOLv4). Secondary outcomes at one-year are the mean social-emotional subscale (UWQOLv4) score, Distress Thermometer (DT) score ≥ 4, and key health economic measures (QALY-EQ-5D-5 L; CSRI). This trial will provide knowledge on the effectiveness of a consultation intervention package based around the PCI used at routine follow-up clinics following treatment of head and neck cancer with curative intent. If this intervention is (cost) effective for patients, the next step will be to promote wider use of this approach as standard care in clinical practice. 32,382. Clinical Trials Identifier, NCT03086629 . Version 3.0, 1st July 2017.

  7. Formation of stable products from cluster-cluster collisions

    International Nuclear Information System (INIS)

    Alamanova, Denitsa; Grigoryan, Valeri G; Springborg, Michael

    2007-01-01

    The formation of stable products from copper cluster-cluster collisions is investigated by using classical molecular-dynamics simulations in combination with an embedded-atom potential. The dependence of the product clusters on impact energy, relative orientation of the clusters, and size of the clusters is studied. The structures and total energies of the product clusters are analysed and compared with those of the colliding clusters before impact. These results, together with the internal temperature, are used in obtaining an increased understanding of cluster fusion processes

  8. Some statistical properties of gene expression clustering for array data

    DEFF Research Database (Denmark)

    Abreu, G C G; Pinheiro, A; Drummond, R D

    2010-01-01

    DNA array data without a corresponding statistical error measure. We propose an easy-to-implement and simple-to-use technique that uses bootstrap re-sampling to evaluate the statistical error of the nodes provided by SOM-based clustering. Comparisons between SOM and parametric clustering are presented...... for simulated as well as for two real data sets. We also implement a bootstrap-based pre-processing procedure for SOM, that improves the false discovery ratio of differentially expressed genes. Code in Matlab is freely available, as well as some supplementary material, at the following address: https...

  9. Clustering microcalcifications techniques in digital mammograms

    Science.gov (United States)

    Díaz, Claudia. C.; Bosco, Paolo; Cerello, Piergiorgio

    2008-11-01

    Breast cancer has become a serious public health problem around the world. However, this pathology can be treated if it is detected in early stages. This task is achieved by a radiologist, who should read a large amount of mammograms per day, either for a screening or diagnostic purpose in mammography. However human factors could affect the diagnosis. Computer Aided Detection is an automatic system, which can help to specialists in the detection of possible signs of malignancy in mammograms. Microcalcifications play an important role in early detection, so we focused on their study. The two mammographic features that indicate the microcalcifications could be probably malignant are small size and clustered distribution. We worked with density techniques for automatic clustering, and we applied them on a mammography CAD prototype developed at INFN-Turin, Italy. An improvement of performance is achieved analyzing images from a Perugia-Assisi Hospital, in Italy.

  10. Document clustering methods, document cluster label disambiguation methods, document clustering apparatuses, and articles of manufacture

    Science.gov (United States)

    Sanfilippo, Antonio [Richland, WA; Calapristi, Augustin J [West Richland, WA; Crow, Vernon L [Richland, WA; Hetzler, Elizabeth G [Kennewick, WA; Turner, Alan E [Kennewick, WA

    2009-12-22

    Document clustering methods, document cluster label disambiguation methods, document clustering apparatuses, and articles of manufacture are described. In one aspect, a document clustering method includes providing a document set comprising a plurality of documents, providing a cluster comprising a subset of the documents of the document set, using a plurality of terms of the documents, providing a cluster label indicative of subject matter content of the documents of the cluster, wherein the cluster label comprises a plurality of word senses, and selecting one of the word senses of the cluster label.

  11. Addressing Cancer Control Needs of African-born Immigrants in the US: A Systematic Literature Review

    Science.gov (United States)

    Hurtado-de-Mendoza, Alejandra; Song, Minna; Kigen, Ocla; Jennings, Yvonne; Nwabukwu, Ify; Sheppard, Vanessa B.

    2014-01-01

    Compared to non-Hispanic Whites, African immigrants have worse cancer outcomes. However, there is little research about cancer behaviors and/or interventions in this growing population as they are generally grouped with populations from America or the Caribbean. This systematic review examines cancer-related studies that included African-born participants. We searched PsychINFO, Ovid Medline, Pubmed, CINHAL, and Web of Science for articles focusing on any type of cancer that included African-born immigrant participants. Twenty articles met study inclusion criteria; only two were interventions. Most articles focused on one type of cancer (n=11) (e.g., breast cancer) and were conducted in disease-free populations (n=15). Studies included African participants mostly from Nigeria (n=8) and Somalia (n=6). However, many papers (n=7) did not specify nationality or had small percentages (African immigrants (n=5). Studies found lower screening rates in African immigrants compared to other subpopulations (e.g. US born). Awareness of screening practices was limited. Higher acculturation levels were associated with higher screening rates. Barriers to screening included access (e.g. insurance), pragmatic (e.g. transportation), and psychosocial barriers (e.g. shame). Interventions to improve cancer outcomes in African immigrants are needed. Research that includes larger samples with diverse African subgroups including cancer survivors are necessary to inform future directions. PMID:25034729

  12. Cluster Policy in the Light of Institutional Context—A Comparative Study of Transition Countries

    OpenAIRE

    Tine Lehmann; Maximilian Benner

    2015-01-01

    The business environment in transition countries is often extraordinarily challenging for companies. The transition process these countries find themselves in leads to constant changes in the institutional environment. Hence, institutional voids prevail. These institutional voids cause competitive disadvantages for small and medium enterprises. Cluster policy can address these competitive disadvantages. As cluster policy generally aims at supporting companies’ competitive advantage by spurrin...

  13. Sleep, Dietary, and Exercise Behavioral Clusters Among Truck Drivers With Obesity: Implications for Interventions.

    Science.gov (United States)

    Olson, Ryan; Thompson, Sharon V; Wipfli, Brad; Hanson, Ginger; Elliot, Diane L; Anger, W Kent; Bodner, Todd; Hammer, Leslie B; Hohn, Elliot; Perrin, Nancy A

    2016-03-01

    The objectives of the study were to describe a sample of truck drivers, identify clusters of drivers with similar patterns in behaviors affecting energy balance (sleep, diet, and exercise), and test for cluster differences in health safety, and psychosocial factors. Participants' (n = 452, body mass index M = 37.2, 86.4% male) self-reported behaviors were dichotomized prior to hierarchical cluster analysis, which identified groups with similar behavior covariation. Cluster differences were tested with generalized estimating equations. Five behavioral clusters were identified that differed significantly in age, smoking status, diabetes prevalence, lost work days, stress, and social support, but not in body mass index. Cluster 2, characterized by the best sleep quality, had significantly lower lost workdays and stress than other clusters. Weight management interventions for drivers should explicitly address sleep, and may be maximally effective after establishing socially supportive work environments that reduce stress exposures.

  14. Distinct ADHD Symptom Clusters Differentially Associated with Personality Traits

    Science.gov (United States)

    McKinney, Ashley A.; Canu, Will H.; Schneider, H. G.

    2013-01-01

    Objective: ADHD has been linked to various constructs, yet there is a lack of focus on how its symptom clusters differentially associate with personality, which this study addresses. Method: The current study examines the relationship between impulsive and inattentive ADHD traits and personality, indexed by the Revised NEO Personality Inventory…

  15. The Role of Semantic Clustering in Optimal Memory Foraging

    Science.gov (United States)

    Montez, Priscilla; Thompson, Graham; Kello, Christopher T.

    2015-01-01

    Recent studies of semantic memory have investigated two theories of optimal search adopted from the animal foraging literature: Lévy flights and marginal value theorem. Each theory makes different simplifying assumptions and addresses different findings in search behaviors. In this study, an experiment is conducted to test whether clustering in…

  16. Finding reproducible cluster partitions for the k-means algorithm.

    Science.gov (United States)

    Lisboa, Paulo J G; Etchells, Terence A; Jarman, Ian H; Chambers, Simon J

    2013-01-01

    K-means clustering is widely used for exploratory data analysis. While its dependence on initialisation is well-known, it is common practice to assume that the partition with lowest sum-of-squares (SSQ) total i.e. within cluster variance, is both reproducible under repeated initialisations and also the closest that k-means can provide to true structure, when applied to synthetic data. We show that this is generally the case for small numbers of clusters, but for values of k that are still of theoretical and practical interest, similar values of SSQ can correspond to markedly different cluster partitions. This paper extends stability measures previously presented in the context of finding optimal values of cluster number, into a component of a 2-d map of the local minima found by the k-means algorithm, from which not only can values of k be identified for further analysis but, more importantly, it is made clear whether the best SSQ is a suitable solution or whether obtaining a consistently good partition requires further application of the stability index. The proposed method is illustrated by application to five synthetic datasets replicating a real world breast cancer dataset with varying data density, and a large bioinformatics dataset.

  17. Promoting Breast Cancer Screening through Storytelling by Chamorro Cancer Survivors

    Science.gov (United States)

    Manglona, Rosa Duenas; Robert, Suzanne; Isaacson, Lucy San Nicolas; Garrido, Marie; Henrich, Faye Babauta; Santos, Lola Sablan; Le, Daisy; Peters, Ruth

    2017-01-01

    The largest Chamorro population outside of Guam and the Mariana Islands reside in California. Cancer health disparities disproportionally affect Pacific Islander communities, including the Chamorro, and breast cancer is the most common cancer affecting women. To address health concerns such as cancer, Pacific Islander women frequently utilize storytelling to initiate conversations about health and to address sensitive topics such as breast health and cancer. One form of storytelling used in San Diego is a play that conveys the message of breast cancer screening to the community in a culturally and linguistically appropriate way. This play, Nan Nena’s Mammogram, tells the story of an older woman in the community who learns about breast cancer screening from her young niece. The story builds upon the underpinnings of Chamorro culture - family, community, support, and humor - to portray discussing breast health, getting support for breast screening, and visiting the doctor. The story of Nan Nena’s Mammogram reflects the willingness of a few pioneering Chamorro women to use their personal experiences of cancer survivorship to promote screening for others. Through the support of a Chamorro community-based organization, these Chamorro breast cancer survivors have used the success of Nan Nena’s Mammogram to expand their education activities and to form a new cancer survivor organization for Chamorro women in San Diego.

  18. Detection of secondary structure elements in proteins by hydrophobic cluster analysis.

    Science.gov (United States)

    Woodcock, S; Mornon, J P; Henrissat, B

    1992-10-01

    Hydrophobic cluster analysis (HCA) is a protein sequence comparison method based on alpha-helical representations of the sequences where the size, shape and orientation of the clusters of hydrophobic residues are primarily compared. The effectiveness of HCA has been suggested to originate from its potential ability to focus on the residues forming the hydrophobic core of globular proteins. We have addressed the robustness of the bidimensional representation used for HCA in its ability to detect the regular secondary structure elements of proteins. Various parameters have been studied such as those governing cluster size and limits, the hydrophobic residues constituting the clusters as well as the potential shift of the cluster positions with respect to the position of the regular secondary structure elements. The following results have been found to support the alpha-helical bidimensional representation used in HCA: (i) there is a positive correlation (clearly above background noise) between the hydrophobic clusters and the regular secondary structure elements in proteins; (ii) the hydrophobic clusters are centred on the regular secondary structure elements; (iii) the pitch of the helical representation which gives the best correspondence is that of an alpha-helix. The correspondence between hydrophobic clusters and regular secondary structure elements suggests a way to implement variable gap penalties during the automatic alignment of protein sequences.

  19. Evolving Information Needs among Colon, Breast, and Prostate Cancer Survivors: Results from a Longitudinal Mixed-Effects Analysis.

    Science.gov (United States)

    Tan, Andy S L; Nagler, Rebekah H; Hornik, Robert C; DeMichele, Angela

    2015-07-01

    This study describes how cancer survivors' information needs about recurrence, late effects, and family risks of cancer evolve over the course of their survivorship period. Three annual surveys were conducted from 2006 to 2008 in a cohort of Pennsylvania cancer survivors diagnosed with colon, breast, or prostate cancer in 2005 (round 1, N = 2,013; round 2, N = 1,293; round 3, N = 1,128). Outcomes were information seeking about five survivorship topics. Key predictors were survey round, cancer diagnosis, and the interaction between these variables. Mixed-effects logistic regression analyses were performed to predict information seeking about each topic, adjusting for demographic variables, clinical characteristics, and clustering of repeated observations within individuals. Information seeking about reducing risks of cancer recurrence was the most frequently reported topic across survivors and over time. Breast cancer survivors were more likely to seek about survivorship topics at round 1 compared with other survivors. In general, information seeking declined over time, but cancer-specific patterns emerged: the decline was sharpest for breast cancer survivors, whereas in later years female colon cancer survivors actually sought more information (about how to reduce the risk of family members getting colon cancer or a different cancer). Cancer survivors' information needs varied over time depending on the topic, and these trends differed by cancer type. Clinicians may need to intervene at distinct points during the survivorship period with information to address concerns about cancer recurrence, late effects, and family members' risks. ©2015 American Association for Cancer Research.

  20. Nuclear clustering - a cluster core model study

    International Nuclear Information System (INIS)

    Paul Selvi, G.; Nandhini, N.; Balasubramaniam, M.

    2015-01-01

    Nuclear clustering, similar to other clustering phenomenon in nature is a much warranted study, since it would help us in understanding the nature of binding of the nucleons inside the nucleus, closed shell behaviour when the system is highly deformed, dynamics and structure at extremes. Several models account for the clustering phenomenon of nuclei. We present in this work, a cluster core model study of nuclear clustering in light mass nuclei

  1. Mechanisms and Barriers in Cancer Nanomedicine: Addressing Challenges, Looking for Solutions.

    Science.gov (United States)

    Anchordoquy, Thomas J; Barenholz, Yechezkel; Boraschi, Diana; Chorny, Michael; Decuzzi, Paolo; Dobrovolskaia, Marina A; Farhangrazi, Z Shadi; Farrell, Dorothy; Gabizon, Alberto; Ghandehari, Hamidreza; Godin, Biana; La-Beck, Ninh M; Ljubimova, Julia; Moghimi, S Moein; Pagliaro, Len; Park, Ji-Ho; Peer, Dan; Ruoslahti, Erkki; Serkova, Natalie J; Simberg, Dmitri

    2017-01-24

    Remarkable progress has recently been made in the synthesis and characterization of engineered nanoparticles for imaging and treatment of cancers, resulting in several promising candidates in clinical trials. Despite these advances, clinical applications of nanoparticle-based therapeutic/imaging agents remain limited by biological, immunological, and translational barriers. In order to overcome the existing status quo in drug delivery, there is a need for open and frank discussion in the nanomedicine community on what is needed to make qualitative leaps toward translation. In this Nano Focus, we present the main discussion topics and conclusions from a recent workshop: "Mechanisms and Barriers in Nanomedicine". The focus of this informal meeting was on biological, toxicological, immunological, and translational aspects of nanomedicine and approaches to move the field forward productively. We believe that these topics reflect the most important issues in cancer nanomedicine.

  2. Radio continuum processes in clusters of galaxies; Proceedings of the Workshop, Green Bank, WV, Aug. 4-8, 1986

    International Nuclear Information System (INIS)

    O'dea, C.P.; Uson, J.M.

    1986-01-01

    Recent observational and theoretical investigations of clusters of galaxies are examined in reviews and reports. Topics addressed include radio surveys of clusters, accretion flows, wide-angle-tail radio sources, the interaction of radio sources with the intracluster medium, diffuse emission in clusters, cluster dynamics, and the environment of powerful radio sources. Particular attention is given to a local perspective on galaxies in rich clusters, X-ray observations of clusters, VLA observations of distant clusters, the halo of Vir A at 327 MHz, Exosat observations of the Vir Cluster, accretion flows in elliptical galaxies, jet disruption in wide-angle-tail radio galaxies, beam trajectories in the intracluster medium, the Suniaev-Zel'dovich effect, dark matter in clusters, and the H I environment of high-redshift quasars

  3. Cluster analysis of typhoid cases in Kota Bharu, Kelantan, Malaysia

    Directory of Open Access Journals (Sweden)

    Nazarudin Safian

    2008-09-01

    Full Text Available Typhoid fever is still a major public health problem globally as well as in Malaysia. This study was done to identify the spatial epidemiology of typhoid fever in the Kota Bharu District of Malaysia as a first step to developing more advanced analysis of the whole country. The main characteristic of the epidemiological pattern that interested us was whether typhoid cases occurred in clusters or whether they were evenly distributed throughout the area. We also wanted to know at what spatial distances they were clustered. All confirmed typhoid cases that were reported to the Kota Bharu District Health Department from the year 2001 to June of 2005 were taken as the samples. From the home address of the cases, the location of the house was traced and a coordinate was taken using handheld GPS devices. Spatial statistical analysis was done to determine the distribution of typhoid cases, whether clustered, random or dispersed. The spatial statistical analysis was done using CrimeStat III software to determine whether typhoid cases occur in clusters, and later on to determine at what distances it clustered. From 736 cases involved in the study there was significant clustering for cases occurring in the years 2001, 2002, 2003 and 2005. There was no significant clustering in year 2004. Typhoid clustering also occurred strongly for distances up to 6 km. This study shows that typhoid cases occur in clusters, and this method could be applicable to describe spatial epidemiology for a specific area. (Med J Indones 2008; 17: 175-82Keywords: typhoid, clustering, spatial epidemiology, GIS

  4. Cluster fusion algorithm: application to Lennard-Jones clusters

    DEFF Research Database (Denmark)

    Solov'yov, Ilia; Solov'yov, Andrey V.; Greiner, Walter

    2006-01-01

    paths up to the cluster size of 150 atoms. We demonstrate that in this way all known global minima structures of the Lennard-Jones clusters can be found. Our method provides an efficient tool for the calculation and analysis of atomic cluster structure. With its use we justify the magic number sequence......We present a new general theoretical framework for modelling the cluster structure and apply it to description of the Lennard-Jones clusters. Starting from the initial tetrahedral cluster configuration, adding new atoms to the system and absorbing its energy at each step, we find cluster growing...... for the clusters of noble gas atoms and compare it with experimental observations. We report the striking correspondence of the peaks in the dependence of the second derivative of the binding energy per atom on cluster size calculated for the chain of the Lennard-Jones clusters based on the icosahedral symmetry...

  5. Cluster fusion algorithm: application to Lennard-Jones clusters

    DEFF Research Database (Denmark)

    Solov'yov, Ilia; Solov'yov, Andrey V.; Greiner, Walter

    2008-01-01

    paths up to the cluster size of 150 atoms. We demonstrate that in this way all known global minima structures of the Lennard-Jones clusters can be found. Our method provides an efficient tool for the calculation and analysis of atomic cluster structure. With its use we justify the magic number sequence......We present a new general theoretical framework for modelling the cluster structure and apply it to description of the Lennard-Jones clusters. Starting from the initial tetrahedral cluster configuration, adding new atoms to the system and absorbing its energy at each step, we find cluster growing...... for the clusters of noble gas atoms and compare it with experimental observations. We report the striking correspondence of the peaks in the dependence of the second derivative of the binding energy per atom on cluster size calculated for the chain of the Lennard-Jones clusters based on the icosahedral symmetry...

  6. Clustering predicts memory performance in networks of spiking and non-spiking neurons

    Directory of Open Access Journals (Sweden)

    Weiliang eChen

    2011-03-01

    Full Text Available The problem we address in this paper is that of finding effective and parsimonious patterns of connectivity in sparse associative memories. This problem must be addressed in real neuronal systems, so that results in artificial systems could throw light on real systems. We show that there are efficient patterns of connectivity and that these patterns are effective in models with either spiking or non-spiking neurons. This suggests that there may be some underlying general principles governing good connectivity in such networks. We also show that the clustering of the network, measured by Clustering Coefficient, has a strong linear correlation to the performance of associative memory. This result is important since a purely static measure of network connectivity appears to determine an important dynamic property of the network.

  7. Oral mucosal color changes as a clinical biomarker for cancer detection.

    Science.gov (United States)

    Latini, Giuseppe; De Felice, Claudio; Barducci, Alessandro; Chitano, Giovanna; Pignatelli, Antonietta; Grimaldi, Luca; Tramacere, Francesco; Laurini, Ricardo; Andreassi, Maria Grazia; Portaluri, Maurizio

    2012-07-01

    Screening is a key tool for early cancer detection/prevention and potentially saves lives. Oral mucosal vascular aberrations and color changes have been reported in hereditary nonpolyposis colorectal cancer patients, possibly reflecting a subclinical extracellular matrix abnormality implicated in the general process of cancer development. Reasoning that physicochemical changes of a tissue should affect its optical properties, we investigated the diagnostic ability of oral mucosal color to identify patients with several types of cancer. A total of 67 patients with several histologically proven malignancies at different stages were enrolled along with a group of 60 healthy controls of comparable age and sex ratio. Oral mucosal color was measured in selected areas, and then univariate, cluster, and principal component analyses were carried out. Lower red and green and higher blue values were significantly associated with evidence of cancer (all Pgreen coordinates. Likewise, the second principal component coordinate of the red-green clusters discriminated patients from controls with 98.2% sensitivity and 95% specificity (cut-off criterion≤0.4547; P=0.0001). The scatterplots of the chrominances revealed the formation of two well separated clusters, separating cancer patients from controls with a 99.4% probability of correct classification. These findings highlight the ability of oral color to encode clinically relevant biophysical information. In the near future, this low-cost and noninvasive method may become a useful tool for early cancer detection.

  8. Improvement of pain-related self-management for cancer patients through a modular transitional nursing intervention: a cluster-randomized multicenter trial.

    Science.gov (United States)

    Jahn, Patrick; Kuss, Oliver; Schmidt, Heike; Bauer, Alexander; Kitzmantel, Maria; Jordan, Karin; Krasemann, Susann; Landenberger, Margarete

    2014-04-01

    Patients' self-management skills are affected by their knowledge, activities, and attitudes toward pain management. This trial aimed to test the Self Care Improvement through Oncology Nursing (SCION)-PAIN program, a multimodular structured intervention to reduce patients' barriers to self-management of cancer pain. Two hundred sixty-three patients with diagnosed malignancy, pain>3 days, and average pain > or = 3/10 participated in a cluster-randomized trial on 18 wards in 2 German university hospitals. Patients on the intervention wards received, in addition to standard pain treatment, the SCION-PAIN program consisting of 3 modules: pharmacologic, nonpharmacologic pain management, and discharge management. The intervention was conducted by specially trained cancer nurses and included components of patient education, skills training, and counseling. Starting with admission, patients received booster sessions every third day and one follow-up telephone counseling session within 2 to 3 days after discharge. Patients in the control group received standard care. Primary end point was the group difference in patient-related barriers to self-management of cancer pain (Barriers Questionnaire-BQ II) 7 days after discharge. The SCION-PAIN program resulted in a significant reduction of patient-related barriers to pain management 1 week after discharge from the hospital: mean difference on BQ II was -0.49 points (95% confidence interval -0.87 points to -0.12 points; P=0.02). Furthermore, patients showed improved adherence to pain medication; odds ratio 8.58 (95% confidence interval 1.66-44.40; P=0.02). A post hoc analysis indicated reduced average and worst pain intensity as well as improved quality of life. This trial reveals the positive impact of a nursing intervention to improve patients' self-management of cancer pain. Copyright © 2014 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

  9. TRUSTWORTHY OPTIMIZED CLUSTERING BASED TARGET DETECTION AND TRACKING FOR WIRELESS SENSOR NETWORK

    Directory of Open Access Journals (Sweden)

    C. Jehan

    2016-06-01

    Full Text Available In this paper, an efficient approach is proposed to address the problem of target tracking in wireless sensor network (WSN. The problem being tackled here uses adaptive dynamic clustering scheme for tracking the target. It is a specific problem in object tracking. The proposed adaptive dynamic clustering target tracking scheme uses three steps for target tracking. The first step deals with the identification of clusters and cluster heads using OGSAFCM. Here, kernel fuzzy c-means (KFCM and gravitational search algorithm (GSA are combined to create clusters. At first, oppositional gravitational search algorithm (OGSA is used to optimize the initial clustering center and then the KFCM algorithm is availed to guide the classification and the cluster formation process. In the OGSA, the concept of the opposition based population initialization in the basic GSA to improve the convergence profile. The identified clusters are changed dynamically. The second step deals with the data transmission to the cluster heads. The third step deals with the transmission of aggregated data to the base station as well as the detection of target. From the experimental results, the proposed scheme efficiently and efficiently identifies the target. As a result the tracking error is minimized.

  10. Clusters and strategy in regional economic development

    OpenAIRE

    Feser, Edward

    2009-01-01

    Many economic development practitioners view cluster theory and analysis as constituting a general approach to strategy making in economic development, which may lead them to prioritize policy and planning interventions that cannot address the actual development challenges in their cities and regions. This paper discusses the distinction between strategy formation and strategic planning, where the latter is the programming of development strategies that are identified through a blend of exper...

  11. PSMA-Targeted Polygadolinium Clusters: A Novel Agent for Imaging Prostate Cancer

    National Research Council Canada - National Science Library

    Messerle, Louis

    2007-01-01

    Controlled hydrolysis of lanthanide element or yttrium salts in the presence of aminoacids yields a series of polynuclear clusters with two, four, twelve, fourteen, and fifteen lanthanide or yttrium...

  12. Prospective molecular profiling of canine cancers provides a clinically relevant comparative model for evaluating personalized medicine (PMed trials.

    Directory of Open Access Journals (Sweden)

    Melissa Paoloni

    Full Text Available Molecularly-guided trials (i.e. PMed now seek to aid clinical decision-making by matching cancer targets with therapeutic options. Progress has been hampered by the lack of cancer models that account for individual-to-individual heterogeneity within and across cancer types. Naturally occurring cancers in pet animals are heterogeneous and thus provide an opportunity to answer questions about these PMed strategies and optimize translation to human patients. In order to realize this opportunity, it is now necessary to demonstrate the feasibility of conducting molecularly-guided analysis of tumors from dogs with naturally occurring cancer in a clinically relevant setting.A proof-of-concept study was conducted by the Comparative Oncology Trials Consortium (COTC to determine if tumor collection, prospective molecular profiling, and PMed report generation within 1 week was feasible in dogs. Thirty-one dogs with cancers of varying histologies were enrolled. Twenty-four of 31 samples (77% successfully met all predefined QA/QC criteria and were analyzed via Affymetrix gene expression profiling. A subsequent bioinformatics workflow transformed genomic data into a personalized drug report. Average turnaround from biopsy to report generation was 116 hours (4.8 days. Unsupervised clustering of canine tumor expression data clustered by cancer type, but supervised clustering of tumors based on the personalized drug report clustered by drug class rather than cancer type.Collection and turnaround of high quality canine tumor samples, centralized pathology, analyte generation, array hybridization, and bioinformatic analyses matching gene expression to therapeutic options is achievable in a practical clinical window (<1 week. Clustering data show robust signatures by cancer type but also showed patient-to-patient heterogeneity in drug predictions. This lends further support to the inclusion of a heterogeneous population of dogs with cancer into the preclinical

  13. Spatial epidemiology of cancer: a review of data sources, methods and risk factors

    Directory of Open Access Journals (Sweden)

    Rita Roquette

    2017-05-01

    Full Text Available Cancer is a major concern among chronic diseases today. Spatial epidemiology plays a relevant role in this matter and we present here a review of this subject, including a discussion of the literature in terms of the level of geographic data aggregation, risk factors and methods used to analyse the spatial distribution of patterns and spatial clusters. For this purpose, we performed a websearch in the Pubmed and Web of Science databases including studies published between 1979 and 2015. We found 180 papers from 63 journals and noted that spatial epidemiology of cancer has been addressed with more emphasis during the last decade with research based on data mostly extracted from cancer registries and official mortality statistics. In general, the research questions present in the reviewed papers can be classified into three different sets: i analysis of spatial distribution of cancer and/or its temporal evolution; ii risk factors; iii development of data analysis methods and/or evaluation of results obtained from application of existing methods. This review is expected to help promote research in this area through the identification of relevant knowledge gaps. Cancer’s spatial epidemiology represents an important concern, mainly for public health policies design aimed to minimise the impact of chronic disease in specific populations.

  14. Engineering Hematopoietic Cells for Cancer Immunotherapy: Strategies to Address Safety and Toxicity Concerns.

    Science.gov (United States)

    Resetca, Diana; Neschadim, Anton; Medin, Jeffrey A

    2016-09-01

    Advances in cancer immunotherapies utilizing engineered hematopoietic cells have recently generated significant clinical successes. Of great promise are immunotherapies based on chimeric antigen receptor-engineered T (CAR-T) cells that are targeted toward malignant cells expressing defined tumor-associated antigens. CAR-T cells harness the effector function of the adaptive arm of the immune system and redirect it against cancer cells, overcoming the major challenges of immunotherapy, such as breaking tolerance to self-antigens and beating cancer immune system-evasion mechanisms. In early clinical trials, CAR-T cell-based therapies achieved complete and durable responses in a significant proportion of patients. Despite clinical successes and given the side effect profiles of immunotherapies based on engineered cells, potential concerns with the safety and toxicity of various therapeutic modalities remain. We discuss the concerns associated with the safety and stability of the gene delivery vehicles for cell engineering and with toxicities due to off-target and on-target, off-tumor effector functions of the engineered cells. We then overview the various strategies aimed at improving the safety of and resolving toxicities associated with cell-based immunotherapies. Integrating failsafe switches based on different suicide gene therapy systems into engineered cells engenders promising strategies toward ensuring the safety of cancer immunotherapies in the clinic.

  15. Countdown for the Cluster quartet

    Science.gov (United States)

    2000-07-01

    Following the successful completion of the Cluster II Flight Readiness Review on 23 June, final launch preparations are progressing smoothly and combined operations with the Soyuz-Fregat launch vehicle are now under way. The dual launches, each involving two Cluster spacecraft built under the prime contractorship of Astrium (former Dornier Satellitensysteme GmbH, Germany), are currently scheduled for 15 July with a launch window opening at 14:40 CEST, 12:40 GMT and lasting 6 minutes, and 9 August from Baikonur Space Centre in Kazakhstan. A number of press events have been organised in various countries to coincide with both launches. The main press centre for the first launch will be located at ESA's European Space Operations Centre (ESOC) at Darmstadt in Germany. Local press centres are also being set up in the other ESA establishments: ESRIN (Italy), ESTEC (The Netherlands), and VILSPA (Spain). See attachment for more detailed information and reply form to register at the various sites. Details of the second launch press event, which will be held in London (UK), will be available at a later date. Cluster II Competition Attracts Record Entries. A highlight of the first launch event at ESOC will be the announcement of the overall winner of ESA's "Name the Cluster quartet" competition and the chosen names of the four Cluster II satellites. Last February, members of the public in all of ESA's 15 member states were asked to suggest the most suitable names for the Cluster II spacecraft. The satellites are currently known as flight models (FM) 5, 6, 7 and 8. Competitors were asked to propose a set of four names (places, people, or things from history, mythology, or fiction, but not living persons) and explain in a few sentences the reasons for their choice. After sifting through more than 5,000 entries from all over Europe and debating at length the merits of the various suggestions, the multinational jury eventually produced a list of 15 national prize winners - one

  16. Seasonal clustering of sinopulmonary mucormycosis in patients with hematologic malignancies at a large comprehensive cancer center

    Directory of Open Access Journals (Sweden)

    Shobini Sivagnanam

    2017-12-01

    Full Text Available Abstract Background Invasive Mucorales infections (IMI lead to significant morbidity and mortality in immunocompromised hosts. The role of season and climatic conditions in case clustering of IMI remain poorly understood. Methods Following detection of a cluster of sinopulmonary IMIs in patients with hematologic malignancies, we reviewed center-based medical records of all patients with IMIs and other invasive fungal infections (IFIs between January of 2012 and August of 2015 to assess for case clustering in relation to seasonality. Results A cluster of 7 patients were identified with sinopulmonary IMIs (Rhizopus microsporus/azygosporus, 6; Rhizomucor pusillus, 1 during a 3 month period between June and August of 2014. All patients died or were discharged to hospice. The cluster was managed with institution of standardized posaconazole prophylaxis to high-risk patients and patient use of N-95 masks when outside of protected areas on the inpatient service. Review of an earlier study period identified 11 patients with IMIs of varying species over the preceding 29 months without evidence of clustering. There were 9 total IMIs in the later study period (12 month post-initial cluster with 5 additional cases in the summer months, again suggesting seasonal clustering. Extensive environmental sampling did not reveal a source of mold. Using local climatological data abstracted from National Centers for Environmental Information the clusters appeared to be associated with high temperatures and low precipitation. Conclusions Sinopulmonary Mucorales clusters at our center had a seasonal variation which appeared to be related to temperature and precipitation. Given the significant mortality associated with IMIs, local climatic conditions may need to be considered when considering center specific fungal prevention and prophylaxis strategies for high-risk patients.

  17. Evaluating the Efficacy of the Cloud for Cluster Computation

    Science.gov (United States)

    Knight, David; Shams, Khawaja; Chang, George; Soderstrom, Tom

    2012-01-01

    Computing requirements vary by industry, and it follows that NASA and other research organizations have computing demands that fall outside the mainstream. While cloud computing made rapid inroads for tasks such as powering web applications, performance issues on highly distributed tasks hindered early adoption for scientific computation. One venture to address this problem is Nebula, NASA's homegrown cloud project tasked with delivering science-quality cloud computing resources. However, another industry development is Amazon's high-performance computing (HPC) instances on Elastic Cloud Compute (EC2) that promises improved performance for cluster computation. This paper presents results from a series of benchmarks run on Amazon EC2 and discusses the efficacy of current commercial cloud technology for running scientific applications across a cluster. In particular, a 240-core cluster of cloud instances achieved 2 TFLOPS on High-Performance Linpack (HPL) at 70% of theoretical computational performance. The cluster's local network also demonstrated sub-100 ?s inter-process latency with sustained inter-node throughput in excess of 8 Gbps. Beyond HPL, a real-world Hadoop image processing task from NASA's Lunar Mapping and Modeling Project (LMMP) was run on a 29 instance cluster to process lunar and Martian surface images with sizes on the order of tens of gigapixels. These results demonstrate that while not a rival of dedicated supercomputing clusters, commercial cloud technology is now a feasible option for moderately demanding scientific workloads.

  18. Interactive K-Means Clustering Method Based on User Behavior for Different Analysis Target in Medicine.

    Science.gov (United States)

    Lei, Yang; Yu, Dai; Bin, Zhang; Yang, Yang

    2017-01-01

    Clustering algorithm as a basis of data analysis is widely used in analysis systems. However, as for the high dimensions of the data, the clustering algorithm may overlook the business relation between these dimensions especially in the medical fields. As a result, usually the clustering result may not meet the business goals of the users. Then, in the clustering process, if it can combine the knowledge of the users, that is, the doctor's knowledge or the analysis intent, the clustering result can be more satisfied. In this paper, we propose an interactive K -means clustering method to improve the user's satisfactions towards the result. The core of this method is to get the user's feedback of the clustering result, to optimize the clustering result. Then, a particle swarm optimization algorithm is used in the method to optimize the parameters, especially the weight settings in the clustering algorithm to make it reflect the user's business preference as possible. After that, based on the parameter optimization and adjustment, the clustering result can be closer to the user's requirement. Finally, we take an example in the breast cancer, to testify our method. The experiments show the better performance of our algorithm.

  19. Cluster-cluster correlations and constraints on the correlation hierarchy

    Science.gov (United States)

    Hamilton, A. J. S.; Gott, J. R., III

    1988-01-01

    The hypothesis that galaxies cluster around clusters at least as strongly as they cluster around galaxies imposes constraints on the hierarchy of correlation amplitudes in hierachical clustering models. The distributions which saturate these constraints are the Rayleigh-Levy random walk fractals proposed by Mandelbrot; for these fractal distributions cluster-cluster correlations are all identically equal to galaxy-galaxy correlations. If correlation amplitudes exceed the constraints, as is observed, then cluster-cluster correlations must exceed galaxy-galaxy correlations, as is observed.

  20. DAFi: A directed recursive data filtering and clustering approach for improving and interpreting data clustering identification of cell populations from polychromatic flow cytometry data.

    Science.gov (United States)

    Lee, Alexandra J; Chang, Ivan; Burel, Julie G; Lindestam Arlehamn, Cecilia S; Mandava, Aishwarya; Weiskopf, Daniela; Peters, Bjoern; Sette, Alessandro; Scheuermann, Richard H; Qian, Yu

    2018-04-17

    Computational methods for identification of cell populations from polychromatic flow cytometry data are changing the paradigm of cytometry bioinformatics. Data clustering is the most common computational approach to unsupervised identification of cell populations from multidimensional cytometry data. However, interpretation of the identified data clusters is labor-intensive. Certain types of user-defined cell populations are also difficult to identify by fully automated data clustering analysis. Both are roadblocks before a cytometry lab can adopt the data clustering approach for cell population identification in routine use. We found that combining recursive data filtering and clustering with constraints converted from the user manual gating strategy can effectively address these two issues. We named this new approach DAFi: Directed Automated Filtering and Identification of cell populations. Design of DAFi preserves the data-driven characteristics of unsupervised clustering for identifying novel cell subsets, but also makes the results interpretable to experimental scientists through mapping and merging the multidimensional data clusters into the user-defined two-dimensional gating hierarchy. The recursive data filtering process in DAFi helped identify small data clusters which are otherwise difficult to resolve by a single run of the data clustering method due to the statistical interference of the irrelevant major clusters. Our experiment results showed that the proportions of the cell populations identified by DAFi, while being consistent with those by expert centralized manual gating, have smaller technical variances across samples than those from individual manual gating analysis and the nonrecursive data clustering analysis. Compared with manual gating segregation, DAFi-identified cell populations avoided the abrupt cut-offs on the boundaries. DAFi has been implemented to be used with multiple data clustering methods including K-means, FLOCK, FlowSOM, and

  1. CONSTRAINING CLUSTER PHYSICS WITH THE SHAPE OF X-RAY CLUSTERS: COMPARISON OF LOCAL X-RAY CLUSTERS VERSUS ΛCDM CLUSTERS

    International Nuclear Information System (INIS)

    Lau, Erwin T.; Nagai, Daisuke; Kravtsov, Andrey V.; Vikhlinin, Alexey; Zentner, Andrew R.

    2012-01-01

    Recent simulations of cluster formation have demonstrated that condensation of baryons into central galaxies during cluster formation can drive the shape of the gas distribution in galaxy clusters significantly rounder out to their virial radius. These simulations generally predict stellar fractions within cluster virial radii that are ∼2-3 times larger than the stellar masses deduced from observations. In this paper, we compare ellipticity profiles of simulated clusters performed with varying input physics (radiative cooling, star formation, and supernova feedback) to the cluster ellipticity profiles derived from Chandra and ROSAT observations, in an effort to constrain the fraction of gas that cools and condenses into the central galaxies within clusters. We find that local relaxed clusters have an average ellipticity of ε = 0.18 ± 0.05 in the radial range of 0.04 ≤ r/r 500 ≤ 1. At larger radii r > 0.1r 500 , the observed ellipticity profiles agree well with the predictions of non-radiative simulations. In contrast, the ellipticity profiles of simulated clusters that include dissipative gas physics deviate significantly from the observed ellipticity profiles at all radii. The dissipative simulations overpredict (underpredict) ellipticity in the inner (outer) regions of galaxy clusters. By comparing simulations with and without dissipative gas physics, we show that gas cooling causes the gas distribution to be more oblate in the central regions, but makes the outer gas distribution more spherical. We find that late-time gas cooling and star formation are responsible for the significantly oblate gas distributions in cluster cores, but the gas shapes outside of cluster cores are set primarily by baryon dissipation at high redshift (z ≥ 2). Our results indicate that the shapes of X-ray emitting gas in galaxy clusters, especially at large radii, can be used to place constraints on cluster gas physics, making it potential probes of the history of baryonic

  2. Effects of occupation on risks of avoidable cancers in the Nordic countries

    DEFF Research Database (Denmark)

    Kjaerheim, K; Martinsen, J I; Lynge, E

    2010-01-01

    Knowledge of cancer risk according to occupational affiliation is an essential part of formatting preventive actions aimed at the adult population. Herein, data on 10 major cancer sites amenable by life style exposures from the Nordic Occupational Cancer Study (NOCCA) are presented. All subjects...... ratios (SIRs) were computed. Variation in risk across occupations was generally larger in men than in women. In men, the most consistent cluster with high risk of numerous cancer types included waiters, cooks and stewards, beverage workers, seamen, and chimney sweeps. Two clusters of occupations...... with generally low cancer risks were seen in both men and women. The first one comprised farmers, gardeners, and forestry workers, the second one included groups with high education, specifically those in health and pedagogical work. Although cancer risk varies by occupation, only a smaller part of the variation...

  3. Cytokine profile determined by data-mining analysis set into clusters of non-small-cell lung cancer patients according to prognosis.

    Science.gov (United States)

    Barrera, L; Montes-Servín, E; Barrera, A; Ramírez-Tirado, L A; Salinas-Parra, F; Bañales-Méndez, J L; Sandoval-Ríos, M; Arrieta, Ó

    2015-02-01

    Immunoregulatory cytokines may play a fundamental role in tumor growth and metastases. Their effects are mediated through complex regulatory networks. Human cytokine profiles could define patient subgroups and represent new potential biomarkers. The aim of this study was to associate a cytokine profile obtained through data mining with the clinical characteristics of patients with advanced non-small-cell lung cancer (NSCLC). We conducted a prospective study of the plasma levels of 14 immunoregulatory cytokines by ELISA and a cytometric bead array assay in 110 NSCLC patients before chemotherapy and 25 control subjects. Cytokine levels and data-mining profiles were associated with clinical, quality of life and pathological outcomes. NSCLC patients had higher levels of interleukin (IL)-6, IL-8, IL-12p70, IL-17a and interferon (IFN)-γ, and lower levels of IL-33 and IL-29 compared with controls. The pro-inflammatory cytokines IL-1b, IL-6 and IL-8 were associated with lower hemoglobin levels, worse functional performance status (Eastern Cooperative Oncology Group, ECOG), fatigue and hyporexia. The anti-inflammatory cytokines IL-4, IL-10 and IL-33 were associated with anorexia and lower body mass index. We identified three clusters of patients according to data-mining analysis with different overall survival (OS; 25.4, 16.8 and 5.09 months, respectively, P = 0.0012). Multivariate analysis showed that ECOG performance status and data-mining clusters were significantly associated with OS (RR 3.59, [95% CI 1.9-6.7], P < 0.001 and 2.2, [1.2-3.8], P = 0.005). Our results provide evidence that complex cytokine networks may be used to identify patient subgroups with different prognoses in advanced NSCLC. These cytokines may represent potential biomarkers, particularly in the immunotherapy era in cancer research. © The Author 2014. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email

  4. A novel artificial bee colony based clustering algorithm for categorical data.

    Science.gov (United States)

    Ji, Jinchao; Pang, Wei; Zheng, Yanlin; Wang, Zhe; Ma, Zhiqiang

    2015-01-01

    Data with categorical attributes are ubiquitous in the real world. However, existing partitional clustering algorithms for categorical data are prone to fall into local optima. To address this issue, in this paper we propose a novel clustering algorithm, ABC-K-Modes (Artificial Bee Colony clustering based on K-Modes), based on the traditional k-modes clustering algorithm and the artificial bee colony approach. In our approach, we first introduce a one-step k-modes procedure, and then integrate this procedure with the artificial bee colony approach to deal with categorical data. In the search process performed by scout bees, we adopt the multi-source search inspired by the idea of batch processing to accelerate the convergence of ABC-K-Modes. The performance of ABC-K-Modes is evaluated by a series of experiments in comparison with that of the other popular algorithms for categorical data.

  5. A phylogenomic gene cluster resource: The phylogeneticallyinferred groups (PhlGs) database

    Energy Technology Data Exchange (ETDEWEB)

    Dehal, Paramvir S.; Boore, Jeffrey L.

    2005-08-25

    We present here the PhIGs database, a phylogenomic resource for sequenced genomes. Although many methods exist for clustering gene families, very few attempt to create truly orthologous clusters sharing descent from a single ancestral gene across a range of evolutionary depths. Although these non-phylogenetic gene family clusters have been used broadly for gene annotation, errors are known to be introduced by the artifactual association of slowly evolving paralogs and lack of annotation for those more rapidly evolving. A full phylogenetic framework is necessary for accurate inference of function and for many studies that address pattern and mechanism of the evolution of the genome. The automated generation of evolutionary gene clusters, creation of gene trees, determination of orthology and paralogy relationships, and the correlation of this information with gene annotations, expression information, and genomic context is an important resource to the scientific community.

  6. Deconstructing Cancer Patient Information Seeking in a Consumer Health Library Toward Developing a Virtual Information Consult for Cancer Patients and Their Caregivers: A Qualitative, Instrumental Case Study.

    Science.gov (United States)

    Papadakos, Janet; Trang, Aileen; Cyr, Alaina B; Abdelmutti, Nazek; Giuliani, Meredith E; Snow, Michelle; McCurdie, Tara; Pulandiran, Menaka; Urowitz, Sara; Wiljer, David

    2017-05-24

    Cancer patients and their caregivers want information about their disease and are interested in finding health information online. Despite the abundance of cancer information online, it is often fragmented, its quality is highly variable, and it can be difficult to navigate without expert-level knowledge of the cancer system. The Patient & Family Library at the Princess Margaret Cancer Centre offers a broad collection of high-quality cancer health information and staff are available to help patrons refine their questions and explore information needs that they may not have considered. The purpose of this research study was to deconstruct patrons' information-seeking behaviors in the library to assess the feasibility of replicating the services provided in the library through a Web app, extending the service beyond the walls of the cancer centre. The specific aims of this research were to understand (1) how patrons approach information seeking in the library (interface design), (2) how patrons communicate their informational needs (information categorization and metadata requirements), and (3) what resources are provided to address the patrons' information needs (collection development). We employed a qualitative, instrumental case study to deconstruct patrons' health information-seeking behavior. The study population included patients, the librarian, and library volunteers. Ethnographic observation was conducted at the library over 3 days and key informant interviews with library staff were conducted to address the first aim. A closed card-sorting activity was conducted to address the second aim and the library shift logs and Search Request Forms (SRFs) were reviewed to address the third aim. A total of 55 interactions were recorded during the ethnographic observation and nine semistructured interviews were conducted during the key informant interviews. Seven library patron personas were identified: (1) Newbie, (2) Seasoned, (3) Direct, (4) Window Shopper, (5

  7. A research about breast cancer detection using different neural networks and K-MICA algorithm

    Directory of Open Access Journals (Sweden)

    A A Kalteh

    2013-01-01

    Full Text Available Breast cancer is the second leading cause of death for women all over the world. The correct diagnosis of breast cancer is one of the major problems in the medical field. From the literature it has been found that different pattern recognition techniques can help them to improve in this domain. This paper presents a novel hybrid intelligent method for detection of breast cancer. The proposed method includes two main modules: Clustering module and the classifier module. In the clustering module, first the input data will be clustered by a new technique. This technique is a suitable combination of the modified imperialist competitive algorithm (MICA and K-means algorithm. Then the Euclidean distance of each pattern is computed from the determined clusters. The classifier module determines the membership of the patterns using the computed distance. In this module, several neural networks, such as the multilayer perceptron, probabilistic neural networks and the radial basis function neural networks are investigated. Using the experimental study, we choose the best classifier in order to recognize the breast cancer. The proposed system is tested on Wisconsin Breast Cancer (WBC database and the simulation results show that the recommended system has high accuracy.

  8. Oxide-supported metal clusters: models for heterogeneous catalysts

    International Nuclear Information System (INIS)

    Santra, A K; Goodman, D W

    2003-01-01

    Understanding the size-dependent electronic, structural and chemical properties of metal clusters on oxide supports is an important aspect of heterogeneous catalysis. Recently model oxide-supported metal catalysts have been prepared by vapour deposition of catalytically relevant metals onto ultra-thin oxide films grown on a refractory metal substrate. Reactivity and spectroscopic/microscopic studies have shown that these ultra-thin oxide films are excellent models for the corresponding bulk oxides, yet are sufficiently electrically conductive for use with various modern surface probes including scanning tunnelling microscopy (STM). Measurements on metal clusters have revealed a metal to nonmetal transition as well as changes in the crystal and electronic structures (including lattice parameters, band width, band splitting and core-level binding energy shifts) as a function of cluster size. Size-dependent catalytic reactivity studies have been carried out for several important reactions, and time-dependent catalytic deactivation has been shown to arise from sintering of metal particles under elevated gas pressures and/or reactor temperatures. In situ STM methodologies have been developed to follow the growth and sintering kinetics on a cluster-by-cluster basis. Although several critical issues have been addressed by several groups worldwide, much more remains to be done. This article highlights some of these accomplishments and summarizes the challenges that lie ahead. (topical review)

  9. Design and methods for a cluster randomized trial of the Sunless Study: A skin cancer prevention intervention promoting sunless tanning among beach visitors

    Directory of Open Access Journals (Sweden)

    Merriam Philip

    2009-02-01

    Full Text Available Abstract Background Skin cancer is the most prevalent yet most preventable cancer in the US. While protecting oneself from ultraviolet radiation (UVR can largely reduce risk, rates of unprotected sun exposure remain high. Because the desire to be tan often outweighs health concerns among sunbathers, very few interventions have been successful at reducing sunbathing behavior. Sunless tanning (self-tanners and spray tans, a method of achieving the suntanned look without UVR exposure, might be an effective supplement to prevention interventions. Methods and Design This cluster randomized trial will examine whether a beach-based intervention that promotes sunless tanning as a substitute for sunbathing and includes sun damage imaging and sun safety recommendations is superior to a questionnaire only control group in reducing sunbathing frequency. Female beach visitors (N = 250 will be recruited from 2 public beaches in eastern Massachusetts. Beach site will be the unit of randomization. Follow-up assessment will occur at the end of the summer (1-month following intervention and 1 year later. The primary outcome is average sunbathing time per week. The study was designed to provide 90% power for detecting a difference of .70 hours between conditions (standard deviation of 2.0 at 1-year with an intra-cluster correlation coefficient of 0.01 and assuming a 25% rate of loss to follow-up. Secondary outcomes include frequency of sunburns, use of sunless tanning products, and sun protection behavior. Discussion Interventions might be improved by promoting behavioral substitutes for sun exposure, such as sunless tanners, that create a tanned look without exposure to UVR. Trial registration NCT00403377

  10. Clustering algorithm in initialization of multi-hop wireless sensor networks

    NARCIS (Netherlands)

    Guo, Peng; Tao, Jiang; Zhang, Kui; Chen, Hsiao-Hwa

    2009-01-01

    In most application scenarios of wireless sensor networks (WSN), sensor nodes are usually deployed randomly and do not have any knowledge about the network environment or even their ID's at the initial stage of their operations. In this paper, we address the clustering problems with a newly deployed

  11. Special issue on cluster algebras in mathematical physics

    Science.gov (United States)

    Di Francesco, Philippe; Gekhtman, Michael; Kuniba, Atsuo; Yamazaki, Masahito

    2014-02-01

    2014. This deadline will allow the special issue to appear at the end of 2014. There is no strict regulation on article size, but as a guide the preferable size is 15-30 pages for contributed papers and 40-60 pages for reviews. Further advice on publishing your work in Journal of Physics A may be found at iopscience.iop.org/jphysa. Contributions to the special issue should be submitted by web upload via ScholarOne Manuscripts, quoting 'JPhysA special issue on cluster algebras in mathematical physics'. Submissions should ideally be in standard LaTeX form. Please see the website for further information on electronic submissions. All contributions should be accompanied by a read-me file or covering letter giving the postal and e-mail addresses for correspondence. The Publishing Office should be notified of any subsequent change of address. The special issue will be published in the print and online versions of the journal.

  12. Care for a Patient With Cancer As a Project: Management of Complex Task Interdependence in Cancer Care Delivery

    OpenAIRE

    Trosman, Julia R.; Carlos, Ruth C.; Simon, Melissa A.; Madden, Debra L.; Gradishar, William J.; Benson, Al B.; Rapkin, Bruce D.; Weiss, Elisa S.; Gareen, Ilana F.; Wagner, Lynne I.; Khan, Seema A.; Bunce, Mikele M.; Small, Art; Weldon, Christine B.

    2016-01-01

    Cancer care is highly complex and suffers from fragmentation and lack of coordination across provider specialties and clinical domains. As a result, patients often find that they must coordinate care on their own. Coordinated delivery teams may address these challenges and improve quality of cancer care. Task interdependence is a core principle of rigorous teamwork and is essential to addressing the complexity of cancer care, which is highly interdependent across specialties and modalities. W...

  13. Cluster management.

    Science.gov (United States)

    Katz, R

    1992-11-01

    Cluster management is a management model that fosters decentralization of management, develops leadership potential of staff, and creates ownership of unit-based goals. Unlike shared governance models, there is no formal structure created by committees and it is less threatening for managers. There are two parts to the cluster management model. One is the formation of cluster groups, consisting of all staff and facilitated by a cluster leader. The cluster groups function for communication and problem-solving. The second part of the cluster management model is the creation of task forces. These task forces are designed to work on short-term goals, usually in response to solving one of the unit's goals. Sometimes the task forces are used for quality improvement or system problems. Clusters are groups of not more than five or six staff members, facilitated by a cluster leader. A cluster is made up of individuals who work the same shift. For example, people with job titles who work days would be in a cluster. There would be registered nurses, licensed practical nurses, nursing assistants, and unit clerks in the cluster. The cluster leader is chosen by the manager based on certain criteria and is trained for this specialized role. The concept of cluster management, criteria for choosing leaders, training for leaders, using cluster groups to solve quality improvement issues, and the learning process necessary for manager support are described.

  14. Long non-coding RNA H19 suppresses retinoblastoma progression via counteracting miR-17-92 cluster.

    Science.gov (United States)

    Zhang, Aihui; Shang, Weiwei; Nie, Qiaoli; Li, Ting; Li, Suhui

    2018-04-01

    Long non-coding RNAs (lncRNAs) are frequently dysregulated and play important roles in many cancers. lncRNA H19 is one of the earliest discovered lncRNAs which has diverse roles in different cancers. However, the expression, roles, and action mechanisms of H19 in retinoblastoma are still largely unknown. In this study, we found that H19 is downregulated in retinoblastoma tissues and cell lines. Gain-of-function and loss-of-function assays showed that H19 inhibits retinoblastoma cell proliferation, induces retinoblastoma cell cycle arrest and cell apoptosis. Mechanistically, we identified seven miR-17-92 cluster binding sites on H19, and found that H19 directly bound to miR-17-92 cluster via these seven binding sites. Through binding to miR-17-92 cluster, H19 relieves the suppressing roles of miR-17-92 cluster on p21. Furthermore, H19 represses STAT3 activation induced by miR-17-92 cluster. Hence, our results revealed that H19 upregulates p21 expression, inhibits STAT3 phosphorylation, and downregulates the expression of STAT3 target genes BCL2, BCL2L1, and BIRC5. In addition, functional assays demonstrated that the mutation of miR-17-92 cluster binding sites on H19 abolished the proliferation inhibiting, cell cycle arrest and cell apoptosis inducing roles of H19 in retinoblastoma. In conclusion, our data suggested that H19 inhibits retinoblastoma progression via counteracting the roles of miR-17-92 cluster, and implied that enhancing the action of H19 may be a promising therapeutic strategy for retinoblastoma. © 2017 Wiley Periodicals, Inc.

  15. The Globular Cluster NGC 6402 (M14). II. Variable Stars

    DEFF Research Database (Denmark)

    Contreras Peña, C.; Catelan, M.; Grundahl, F.

    2018-01-01

    approaches for the calibration of the absolute magnitudes of RR Lyrae stars. The possible presence of second-overtone RR Lyrae in M14 is critically addressed, with our results arguing against this possibility. By considering all of the RR Lyrae stars as members of the cluster, we derive =0.589 {{d...

  16. Comparing the OpenMP, MPI, and Hybrid Programming Paradigm on an SMP Cluster

    Science.gov (United States)

    Jost, Gabriele; Jin, Hao-Qiang; anMey, Dieter; Hatay, Ferhat F.

    2003-01-01

    Clusters of SMP (Symmetric Multi-Processors) nodes provide support for a wide range of parallel programming paradigms. The shared address space within each node is suitable for OpenMP parallelization. Message passing can be employed within and across the nodes of a cluster. Multiple levels of parallelism can be achieved by combining message passing and OpenMP parallelization. Which programming paradigm is the best will depend on the nature of the given problem, the hardware components of the cluster, the network, and the available software. In this study we compare the performance of different implementations of the same CFD benchmark application, using the same numerical algorithm but employing different programming paradigms.

  17. Metabolic cooperation between cancer and non-cancerous stromal cells is pivotal in cancer progression.

    Science.gov (United States)

    Lopes-Coelho, Filipa; Gouveia-Fernandes, Sofia; Serpa, Jacinta

    2018-02-01

    The way cancer cells adapt to microenvironment is crucial for the success of carcinogenesis, and metabolic fitness is essential for a cancer cell to survive and proliferate in a certain organ/tissue. The metabolic remodeling in a tumor niche is endured not only by cancer cells but also by non-cancerous cells that share the same microenvironment. For this reason, tumor cells and stromal cells constitute a complex network of signal and organic compound transfer that supports cellular viability and proliferation. The intensive dual-address cooperation of all components of a tumor sustains disease progression and metastasis. Herein, we will detail the role of cancer-associated fibroblasts, cancer-associated adipocytes, and inflammatory cells, mainly monocytes/macrophages (tumor-associated macrophages), in the remodeling and metabolic adaptation of tumors.

  18. Effect of denoising on supervised lung parenchymal clusters

    Science.gov (United States)

    Jayamani, Padmapriya; Raghunath, Sushravya; Rajagopalan, Srinivasan; Karwoski, Ronald A.; Bartholmai, Brian J.; Robb, Richard A.

    2012-03-01

    Denoising is a critical preconditioning step for quantitative analysis of medical images. Despite promises for more consistent diagnosis, denoising techniques are seldom explored in clinical settings. While this may be attributed to the esoteric nature of the parameter sensitve algorithms, lack of quantitative measures on their ecacy to enhance the clinical decision making is a primary cause of physician apathy. This paper addresses this issue by exploring the eect of denoising on the integrity of supervised lung parenchymal clusters. Multiple Volumes of Interests (VOIs) were selected across multiple high resolution CT scans to represent samples of dierent patterns (normal, emphysema, ground glass, honey combing and reticular). The VOIs were labeled through consensus of four radiologists. The original datasets were ltered by multiple denoising techniques (median ltering, anisotropic diusion, bilateral ltering and non-local means) and the corresponding ltered VOIs were extracted. Plurality of cluster indices based on multiple histogram-based pair-wise similarity measures were used to assess the quality of supervised clusters in the original and ltered space. The resultant rank orders were analyzed using the Borda criteria to nd the denoising-similarity measure combination that has the best cluster quality. Our exhaustive analyis reveals (a) for a number of similarity measures, the cluster quality is inferior in the ltered space; and (b) for measures that benet from denoising, a simple median ltering outperforms non-local means and bilateral ltering. Our study suggests the need to judiciously choose, if required, a denoising technique that does not deteriorate the integrity of supervised clusters.

  19. A two-stage approach to estimate spatial and spatio-temporal disease risks in the presence of local discontinuities and clusters.

    Science.gov (United States)

    Adin, A; Lee, D; Goicoa, T; Ugarte, María Dolores

    2018-01-01

    Disease risk maps for areal unit data are often estimated from Poisson mixed models with local spatial smoothing, for example by incorporating random effects with a conditional autoregressive prior distribution. However, one of the limitations is that local discontinuities in the spatial pattern are not usually modelled, leading to over-smoothing of the risk maps and a masking of clusters of hot/coldspot areas. In this paper, we propose a novel two-stage approach to estimate and map disease risk in the presence of such local discontinuities and clusters. We propose approaches in both spatial and spatio-temporal domains, where for the latter the clusters can either be fixed or allowed to vary over time. In the first stage, we apply an agglomerative hierarchical clustering algorithm to training data to provide sets of potential clusters, and in the second stage, a two-level spatial or spatio-temporal model is applied to each potential cluster configuration. The superiority of the proposed approach with regard to a previous proposal is shown by simulation, and the methodology is applied to two important public health problems in Spain, namely stomach cancer mortality across Spain and brain cancer incidence in the Navarre and Basque Country regions of Spain.

  20. Lifting to cluster-tilting objects in higher cluster categories

    OpenAIRE

    Liu, Pin

    2008-01-01

    In this note, we consider the $d$-cluster-tilted algebras, the endomorphism algebras of $d$-cluster-tilting objects in $d$-cluster categories. We show that a tilting module over such an algebra lifts to a $d$-cluster-tilting object in this $d$-cluster category.

  1. Counting addressing method: Command addressable element and extinguishing module

    Directory of Open Access Journals (Sweden)

    Ristić Jovan D.

    2009-01-01

    Full Text Available The specific requirements that appear in addressable fire detection and alarm systems and the shortcomings of the existing addressing methods were discussed. A new method of addressing of detectors was proposed. The basic principles of addressing and responding of a called element are stated. Extinguishing module is specific subsystem in classic fire detection and alarm systems. Appearing of addressable fire detection and alarm systems didn't caused essential change in the concept of extinguishing module because of long calling period of such systems. Addressable fire security system based on counting addressing method reaches high calling rates and enables integrating of the extinguishing module in addressable system. Solutions for command addressable element and integrated extinguishing module are given in this paper. The counting addressing method was developed for specific requirements in fire detection and alarm systems, yet its speed and reliability justifies its use in the acquisition of data on slowly variable parameters under industrial conditions. .

  2. Emerging critical roles of Fe-S clusters in DNA replication and repair

    Science.gov (United States)

    Fuss, Jill O.; Tsai, Chi-Lin; Ishida, Justin P.; Tainer, John A.

    2015-01-01

    Fe-S clusters are partners in the origin of life that predate cells, acetyl-CoA metabolism, DNA, and the RNA world. The double helix solved the mystery of DNA replication by base pairing for accurate copying. Yet, for genome stability necessary to life, the double helix has equally important implications for damage repair. Here we examine striking advances that uncover Fe-S cluster roles both in copying the genetic sequence by DNA polymerases and in crucial repair processes for genome maintenance, as mutational defects cause cancer and degenerative disease. Moreover, we examine an exciting, controversial role for Fe-S clusters in a third element required for life – the long-range coordination and regulation of replication and repair events. By their ability to delocalize electrons over both Fe and S centers, Fe-S clusters have unbeatable features for protein conformational control and charge transfer via double-stranded DNA that may fundamentally transform our understanding of life, replication, and repair. PMID:25655665

  3. Image Coding Based on Address Vector Quantization.

    Science.gov (United States)

    Feng, Yushu

    Image coding is finding increased application in teleconferencing, archiving, and remote sensing. This thesis investigates the potential of Vector Quantization (VQ), a relatively new source coding technique, for compression of monochromatic and color images. Extensions of the Vector Quantization technique to the Address Vector Quantization method have been investigated. In Vector Quantization, the image data to be encoded are first processed to yield a set of vectors. A codeword from the codebook which best matches the input image vector is then selected. Compression is achieved by replacing the image vector with the index of the code-word which produced the best match, the index is sent to the channel. Reconstruction of the image is done by using a table lookup technique, where the label is simply used as an address for a table containing the representative vectors. A code-book of representative vectors (codewords) is generated using an iterative clustering algorithm such as K-means, or the generalized Lloyd algorithm. A review of different Vector Quantization techniques are given in chapter 1. Chapter 2 gives an overview of codebook design methods including the Kohonen neural network to design codebook. During the encoding process, the correlation of the address is considered and Address Vector Quantization is developed for color image and monochrome image coding. Address VQ which includes static and dynamic processes is introduced in chapter 3. In order to overcome the problems in Hierarchical VQ, Multi-layer Address Vector Quantization is proposed in chapter 4. This approach gives the same performance as that of the normal VQ scheme but the bit rate is about 1/2 to 1/3 as that of the normal VQ method. In chapter 5, a Dynamic Finite State VQ based on a probability transition matrix to select the best subcodebook to encode the image is developed. In chapter 6, a new adaptive vector quantization scheme, suitable for color video coding, called "A Self -Organizing

  4. Data Clustering

    Science.gov (United States)

    Wagstaff, Kiri L.

    2012-03-01

    On obtaining a new data set, the researcher is immediately faced with the challenge of obtaining a high-level understanding from the observations. What does a typical item look like? What are the dominant trends? How many distinct groups are included in the data set, and how is each one characterized? Which observable values are common, and which rarely occur? Which items stand out as anomalies or outliers from the rest of the data? This challenge is exacerbated by the steady growth in data set size [11] as new instruments push into new frontiers of parameter space, via improvements in temporal, spatial, and spectral resolution, or by the desire to "fuse" observations from different modalities and instruments into a larger-picture understanding of the same underlying phenomenon. Data clustering algorithms provide a variety of solutions for this task. They can generate summaries, locate outliers, compress data, identify dense or sparse regions of feature space, and build data models. It is useful to note up front that "clusters" in this context refer to groups of items within some descriptive feature space, not (necessarily) to "galaxy clusters" which are dense regions in physical space. The goal of this chapter is to survey a variety of data clustering methods, with an eye toward their applicability to astronomical data analysis. In addition to improving the individual researcher’s understanding of a given data set, clustering has led directly to scientific advances, such as the discovery of new subclasses of stars [14] and gamma-ray bursts (GRBs) [38]. All clustering algorithms seek to identify groups within a data set that reflect some observed, quantifiable structure. Clustering is traditionally an unsupervised approach to data analysis, in the sense that it operates without any direct guidance about which items should be assigned to which clusters. There has been a recent trend in the clustering literature toward supporting semisupervised or constrained

  5. Bayesian Nonparametric Clustering for Positive Definite Matrices.

    Science.gov (United States)

    Cherian, Anoop; Morellas, Vassilios; Papanikolopoulos, Nikolaos

    2016-05-01

    Symmetric Positive Definite (SPD) matrices emerge as data descriptors in several applications of computer vision such as object tracking, texture recognition, and diffusion tensor imaging. Clustering these data matrices forms an integral part of these applications, for which soft-clustering algorithms (K-Means, expectation maximization, etc.) are generally used. As is well-known, these algorithms need the number of clusters to be specified, which is difficult when the dataset scales. To address this issue, we resort to the classical nonparametric Bayesian framework by modeling the data as a mixture model using the Dirichlet process (DP) prior. Since these matrices do not conform to the Euclidean geometry, rather belongs to a curved Riemannian manifold,existing DP models cannot be directly applied. Thus, in this paper, we propose a novel DP mixture model framework for SPD matrices. Using the log-determinant divergence as the underlying dissimilarity measure to compare these matrices, and further using the connection between this measure and the Wishart distribution, we derive a novel DPM model based on the Wishart-Inverse-Wishart conjugate pair. We apply this model to several applications in computer vision. Our experiments demonstrate that our model is scalable to the dataset size and at the same time achieves superior accuracy compared to several state-of-the-art parametric and nonparametric clustering algorithms.

  6. Historical Perspective on Familial Gastric CancerSummary

    OpenAIRE

    C. Richard Boland; Matthew B. Yurgelun

    2017-01-01

    Gastric cancer is a common disease worldwide, typically associated with acquired chronic inflammation in the stomach, related in most instances to infection by Helicobacter pylori. A small percentage of cases occurs in familial clusters, and some of these can be linked to specific germline mutations. This article reviews the historical background to the current understanding of familial gastric cancer, focuses on the entity of hereditary diffuse gastric cancer, and also reviews the risks for ...

  7. Beyond treatment – Psychosocial and behavioural issues in cancer survivorship research and practice

    Directory of Open Access Journals (Sweden)

    Neil K. Aaronson

    2014-06-01

    Full Text Available The population of cancer survivors has grown steadily over the past several decades. Surviving cancer, however, is not synonymous with a life free of problems related to the disease and its treatment. In this paper we provide a brief overview of selected physical and psychosocial health problems prevalent among cancer survivors, namely pain, fatigue, psychological distress and work participation. We also address issues surrounding self-management and e-Health interventions for cancer survivors, and programmes to encourage survivors to adopt healthier lifestyles. Finally, we discuss approaches to assessing health-related quality of life in cancer survivors, and the use of cancer registries in conducting psychosocial survivorship research. We highlight research and practice priorities in each of these areas. While the priorities vary per topic, common themes that emerged included: (1 Symptoms should not be viewed in isolation, but rather as part of a cluster of interrelated symptoms. This has implications for both understanding the aetiology of symptoms and for their treatment; (2 Psychosocial interventions need to be evidence-based, and where possible should be tailored to the needs of the individual cancer survivor. Relatively low cost interventions with self-management and e-Health elements may be appropriate for the majority of survivors, with resource intensive interventions being reserved for those most in need; (3 More effort should be devoted to disseminating and implementing interventions in practice, and to evaluating their cost-effectiveness; and (4 Greater attention should be paid to the needs of vulnerable and high-risk populations of survivors, including the socioeconomically disadvantaged and the elderly.

  8. Dense Fe cluster-assembled films by energetic cluster deposition

    International Nuclear Information System (INIS)

    Peng, D.L.; Yamada, H.; Hihara, T.; Uchida, T.; Sumiyama, K.

    2004-01-01

    High-density Fe cluster-assembled films were produced at room temperature by an energetic cluster deposition. Though cluster-assemblies are usually sooty and porous, the present Fe cluster-assembled films are lustrous and dense, revealing a soft magnetic behavior. Size-monodispersed Fe clusters with the mean cluster size d=9 nm were synthesized using a plasma-gas-condensation technique. Ionized clusters are accelerated electrically and deposited onto the substrate together with neutral clusters from the same cluster source. Packing fraction and saturation magnetic flux density increase rapidly and magnetic coercivity decreases remarkably with increasing acceleration voltage. The Fe cluster-assembled film obtained at the acceleration voltage of -20 kV has a packing fraction of 0.86±0.03, saturation magnetic flux density of 1.78±0.05 Wb/m 2 , and coercivity value smaller than 80 A/m. The resistivity at room temperature is ten times larger than that of bulk Fe metal

  9. Effect of Policy Analysis on Indonesia’s Maritime Cluster Development Using System Dynamics Modeling

    Science.gov (United States)

    Nursyamsi, A.; Moeis, A. O.; Komarudin

    2018-03-01

    As an archipelago with two third of its territory consist of water, Indonesia should address more attention to its maritime industry development. One of the catalyst to fasten the maritime industry growth is by developing a maritime cluster. The purpose of this research is to gain understanding of the effect if Indonesia implement maritime cluster policy to the growth of maritime economic and its role to enhance the maritime cluster performance, hence enhancing Indonesia’s maritime industry as well. The result of the constructed system dynamic model simulation shows that with the effect of maritime cluster, the growth of employment rate and maritime economic is much bigger that the business as usual case exponentially. The result implies that the government should act fast to form a legitimate cluster maritime organizer institution so that there will be a synergize, sustainable, and positive maritime cluster environment that will benefit the performance of Indonesia’s maritime industry.

  10. Cluster Physics with Merging Galaxy Clusters

    Directory of Open Access Journals (Sweden)

    Sandor M. Molnar

    2016-02-01

    Full Text Available Collisions between galaxy clusters provide a unique opportunity to study matter in a parameter space which cannot be explored in our laboratories on Earth. In the standard LCDM model, where the total density is dominated by the cosmological constant ($Lambda$ and the matter density by cold dark matter (CDM, structure formation is hierarchical, and clusters grow mostly by merging.Mergers of two massive clusters are the most energetic events in the universe after the Big Bang,hence they provide a unique laboratory to study cluster physics.The two main mass components in clusters behave differently during collisions:the dark matter is nearly collisionless, responding only to gravity, while the gas is subject to pressure forces and dissipation, and shocks and turbulenceare developed during collisions. In the present contribution we review the different methods used to derive the physical properties of merging clusters. Different physical processes leave their signatures on different wavelengths, thusour review is based on a multifrequency analysis. In principle, the best way to analyze multifrequency observations of merging clustersis to model them using N-body/HYDRO numerical simulations. We discuss the results of such detailed analyses.New high spatial and spectral resolution ground and space based telescopeswill come online in the near future. Motivated by these new opportunities,we briefly discuss methods which will be feasible in the near future in studying merging clusters.

  11. Symptom structure of PTSD following breast cancer.

    Science.gov (United States)

    Cordova, M J; Studts, J L; Hann, D M; Jacobsen, P B; Andrykowski, M A

    2000-04-01

    Identification of posttraumatic stress disorder (PTSD) symptoms and diagnoses in survivors of cancer is a growing area of research, but no published data exist regarding the symptom structure of PTSD in survivors of malignant disease. Findings from investigations of the PTSD symptom structure in other trauma populations have been inconsistent and have not been concordant with the re-experiencing, avoidance/numbing, and arousal symptom clusters specified in DSM-IV. The present study employed confirmatory factor analysis to evaluate the extent to which the implied second-order factor structure of PTSD was replicated in a sample of 142 breast cancer survivors. PTSD symptoms were measured using the PTSD Checklist--Civilian Version (PCL-C). Fit indices reflected a moderate fit of the symptom structure implied by the DSM-IV. These findings provide some tentative support for the DSM-IV clustering of PTSD symptoms and for the validity of cancer-related PTSD.

  12. [Space-time suicide clustering in the community of Antequera (Spain)].

    Science.gov (United States)

    Pérez-Costillas, Lucía; Blasco-Fontecilla, Hilario; Benítez, Nicolás; Comino, Raquel; Antón, José Miguel; Ramos-Medina, Valentín; Lopez, Amalia; Palomo, José Luis; Madrigal, Lucía; Alcalde, Javier; Perea-Millá, Emilio; Artieda-Urrutia, Paula; de León-Martínez, Victoria; de Diego Otero, Yolanda

    2015-01-01

    Approximately 3,500 people commit suicide every year in Spain. The main aim of this study is to explore if a spatial and temporal clustering of suicide exists in the region of Antequera (Málaga, España). Sample and procedure: All suicides from January 1, 2004 to December 31, 2008 were identified using data from the Forensic Pathology Department of the Institute of Legal Medicine, Málaga (España). Geolocalisation. Google Earth was used to calculate the coordinates for each suicide decedent's address. Statistical analysis. A spatiotemporal permutation scan statistic and the Ripley's K function were used to explore spatiotemporal clustering. Pearson's chi-squared was used to determine whether there were differences between suicides inside and outside the spatiotemporal clusters. A total of 120 individuals committed suicide within the region of Antequera, of which 96 (80%) were included in our analyses. Statistically significant evidence for 7 spatiotemporal suicide clusters emerged within critical limits for the 0-2.5 km distance and for the first and second semanas (P<.05 in both cases) after suicide. There was not a single subject diagnosed with a current psychotic disorder, among suicides within clusters, whereas outside clusters, 20% had this diagnosis (X2=4.13; df=1; P<.05). There are spatiotemporal suicide clusters in the area surrounding Antequera. Patients diagnosed with current psychotic disorder are less likely to be influenced by the factors explaining suicide clustering. Copyright © 2013 SEP y SEPB. Published by Elsevier España. All rights reserved.

  13. Class Restricted Clustering and Micro-Perturbation for Data Privacy.

    Science.gov (United States)

    Li, Xiao-Bai; Sarkar, Sumit

    2013-04-01

    The extensive use of information technologies by organizations to collect and share personal data has raised strong privacy concerns. To respond to the public's demand for data privacy, a class of clustering-based data masking techniques is increasingly being used for privacy-preserving data sharing and analytics. Traditional clustering-based approaches for masking numeric attributes, while addressing re-identification risks, typically do not consider the disclosure risk of categorical confidential attributes. We propose a new approach to deal with this problem. The proposed method clusters data such that the data points within a group are similar in the non-confidential attribute values whereas the confidential attribute values within a group are well distributed . To accomplish this, the clustering method, which is based on a minimum spanning tree (MST) technique, uses two risk-utility tradeoff measures in the growing and pruning stages of the MST technique respectively. As part of our approach we also propose a novel cluster-level micro-perturbation method for masking data that overcomes a common problem of traditional clustering-based methods for data masking, which is their inability to preserve important statistical properties such as the variance of attributes and the covariance across attributes. We show that the mean vector and the covariance matrix of the masked data generated using the micro-perturbation method are unbiased estimates of the original mean vector and covariance matrix. An experimental study on several real-world datasets demonstrates the effectiveness of the proposed approach.

  14. Gold nanoparticles for cancer detection and treatment: The role of adhesion

    Energy Technology Data Exchange (ETDEWEB)

    Oni, Y. [Princeton Institute for Science and Technology of Materials (PRISM), Princeton University, 70 Prospect Street, Princeton, New Jersey 08544 (United States); Department of Mechanical and Aerospace Engineering, Princeton University, Princeton, New Jersey 08544 (United States); Hao, K. [Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States); Dozie-Nwachukwu, S.; Odusanya, O. S. [African University of Science and Technology (AUST), Kilometer 10, Airport Road, Abuja, Federal Capital Territory (Nigeria); Sheda Science and Technology Complex (SHESTCO), Gwagwalada, Abuja, Federal Capital Territory (Nigeria); Obayemi, J.D. [African University of Science and Technology (AUST), Kilometer 10, Airport Road, Abuja, Federal Capital Territory (Nigeria); Anuku, N. [Department of Mechanical and Aerospace Engineering, Princeton University, Princeton, New Jersey 08544 (United States); Department of Chemistry and Chemical Technology, Bronx Community College, New York, New York 10453 (United States); Soboyejo, W. O. [Princeton Institute for Science and Technology of Materials (PRISM), Princeton University, 70 Prospect Street, Princeton, New Jersey 08544 (United States); Department of Mechanical and Aerospace Engineering, Princeton University, Princeton, New Jersey 08544 (United States); African University of Science and Technology (AUST), Kilometer 10, Airport Road, Abuja, Federal Capital Territory (Nigeria)

    2014-02-28

    This paper presents the results of an experimental study of the effects of adhesion between gold nanoparticles and surfaces that are relevant to the potential applications in cancer detection and treatment. Adhesion is measured using a dip coating/atomic force microscopy (DC/AFM) technique. The adhesion forces are obtained for dip-coated gold nanoparticles that interact with peptide or antibody-based molecular recognition units (MRUs) that attach specifically to breast cancer cells. They include MRUs that attach specifically to receptors on breast cancer cells. Adhesion forces between anti-cancer drugs such as paclitaxel, and the constituents of MRU-conjugated Au nanoparticle clusters, are measured using force microscopy techniques. The implications of the results are then discussed for the design of robust gold nanoparticle clusters and for potential applications in localized drug delivery and hyperthermia.

  15. Gold nanoparticles for cancer detection and treatment: The role of adhesion

    International Nuclear Information System (INIS)

    Oni, Y.; Hao, K.; Dozie-Nwachukwu, S.; Odusanya, O. S.; Obayemi, J.D.; Anuku, N.; Soboyejo, W. O.

    2014-01-01

    This paper presents the results of an experimental study of the effects of adhesion between gold nanoparticles and surfaces that are relevant to the potential applications in cancer detection and treatment. Adhesion is measured using a dip coating/atomic force microscopy (DC/AFM) technique. The adhesion forces are obtained for dip-coated gold nanoparticles that interact with peptide or antibody-based molecular recognition units (MRUs) that attach specifically to breast cancer cells. They include MRUs that attach specifically to receptors on breast cancer cells. Adhesion forces between anti-cancer drugs such as paclitaxel, and the constituents of MRU-conjugated Au nanoparticle clusters, are measured using force microscopy techniques. The implications of the results are then discussed for the design of robust gold nanoparticle clusters and for potential applications in localized drug delivery and hyperthermia

  16. Confirming the least massive members of the Pleiades star cluster

    Science.gov (United States)

    Zapatero Osorio, M. R.; Béjar, V. J. S.; Lodieu, N.; Manjavacas, E.

    2018-03-01

    We present optical photometry (i and Z band) and low-resolution spectroscopy (640-1015 nm) of very faint candidate members (J = 20.2-21.2 mag) of the Pleiades star cluster (120 Myr). The main goal is to address their cluster membership via photometric, astrometric, and spectroscopic studies, and to determine the properties of the least massive population of the cluster through the comparison of the data with younger and older spectral counterparts and state-of-the art model atmospheres. We confirm three bona fide Pleiades members that have extremely red optical and infrared colours, effective temperatures of ≈1150 and ≈1350 K, and masses in the interval 11-20 MJup, and one additional likely member that shares the same motion as the cluster but does not appear to be as red as the other members with similar brightness. This latter object requires further near-infrared spectroscopy to fully address its membership in the Pleiades. The optical spectra of two bona fide members were classified as L6-L7 and show features of K I, a tentative detection of Cs I, hydrides, and water vapour with an intensity similar to high-gravity dwarfs of related classification despite their young age. The properties of the Pleiades L6-L7 members clearly indicate that very red colours of L dwarfs are not a direct evidence of ages younger than ≈100 Myr. We also report on the determination of the bolometric corrections for the coolest Pleiades members. These data can be used to interpret the observations of the atmospheres of exoplanets orbiting stars.

  17. Topology based data analysis identifies a subgroup of breast cancers with a unique mutational profile and excellent survival.

    Science.gov (United States)

    Nicolau, Monica; Levine, Arnold J; Carlsson, Gunnar

    2011-04-26

    High-throughput biological data, whether generated as sequencing, transcriptional microarrays, proteomic, or other means, continues to require analytic methods that address its high dimensional aspects. Because the computational part of data analysis ultimately identifies shape characteristics in the organization of data sets, the mathematics of shape recognition in high dimensions continues to be a crucial part of data analysis. This article introduces a method that extracts information from high-throughput microarray data and, by using topology, provides greater depth of information than current analytic techniques. The method, termed Progression Analysis of Disease (PAD), first identifies robust aspects of cluster analysis, then goes deeper to find a multitude of biologically meaningful shape characteristics in these data. Additionally, because PAD incorporates a visualization tool, it provides a simple picture or graph that can be used to further explore these data. Although PAD can be applied to a wide range of high-throughput data types, it is used here as an example to analyze breast cancer transcriptional data. This identified a unique subgroup of Estrogen Receptor-positive (ER(+)) breast cancers that express high levels of c-MYB and low levels of innate inflammatory genes. These patients exhibit 100% survival and no metastasis. No supervised step beyond distinction between tumor and healthy patients was used to identify this subtype. The group has a clear and distinct, statistically significant molecular signature, it highlights coherent biology but is invisible to cluster methods, and does not fit into the accepted classification of Luminal A/B, Normal-like subtypes of ER(+) breast cancers. We denote the group as c-MYB(+) breast cancer.

  18. The fragmentation of proto-globular clusters. I. Thermal instabilities

    International Nuclear Information System (INIS)

    Murray, S.D.; Lin, D.N.C.

    1989-01-01

    The metal abundances among the stars within a typical globular cluster are remarkably homogeneous. This indicates that star formation in these systems was a globally coordinated event which occurred over a time span less than or comparable to the collapse time scale of the cluster. This issue is addressed by assuming that the fragmentation of a proto-globular cluster cloud proceeded in two steps. In the first step, thermal instability led to the rapid growth of initial fluctuations. This led to a large contrast in the dynamical time scales between the perturbations and the parent cloud, and the perturbations then underwent gravitational instabilities on short time scales. This process is modeled using one-dimensional hydrodynamic simulations of clouds both with and without external heat sources and self-gravity. The models include the effects of a non-equilibrium H2 abundance. The results indicate that fragmentation can occur on time scales significantly less than the dynamical time scale of the parent cloud. 21 refs

  19. Are clusters of dietary patterns and cluster membership stable over time? Results of a longitudinal cluster analysis study.

    Science.gov (United States)

    Walthouwer, Michel Jean Louis; Oenema, Anke; Soetens, Katja; Lechner, Lilian; de Vries, Hein

    2014-11-01

    Developing nutrition education interventions based on clusters of dietary patterns can only be done adequately when it is clear if distinctive clusters of dietary patterns can be derived and reproduced over time, if cluster membership is stable, and if it is predictable which type of people belong to a certain cluster. Hence, this study aimed to: (1) identify clusters of dietary patterns among Dutch adults, (2) test the reproducibility of these clusters and stability of cluster membership over time, and (3) identify sociodemographic predictors of cluster membership and cluster transition. This study had a longitudinal design with online measurements at baseline (N=483) and 6 months follow-up (N=379). Dietary intake was assessed with a validated food frequency questionnaire. A hierarchical cluster analysis was performed, followed by a K-means cluster analysis. Multinomial logistic regression analyses were conducted to identify the sociodemographic predictors of cluster membership and cluster transition. At baseline and follow-up, a comparable three-cluster solution was derived, distinguishing a healthy, moderately healthy, and unhealthy dietary pattern. Male and lower educated participants were significantly more likely to have a less healthy dietary pattern. Further, 251 (66.2%) participants remained in the same cluster, 45 (11.9%) participants changed to an unhealthier cluster, and 83 (21.9%) participants shifted to a healthier cluster. Men and people living alone were significantly more likely to shift toward a less healthy dietary pattern. Distinctive clusters of dietary patterns can be derived. Yet, cluster membership is unstable and only few sociodemographic factors were associated with cluster membership and cluster transition. These findings imply that clusters based on dietary intake may not be suitable as a basis for nutrition education interventions. Copyright © 2014 Elsevier Ltd. All rights reserved.

  20. 2009 Clusters, Nanocrystals & Nanostructures GRC

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Lai-Sheng [Washington State Univ., Pullman, WA (United States)

    2009-07-19

    For over thirty years, this Gordon Conference has been the premiere meeting for the field of cluster science, which studies the phenomena that arise when matter becomes small. During its history, participants have witnessed the discovery and development of many novel materials, including C60, carbon nanotubes, semiconductor and metal nanocrystals, and nanowires. In addition to addressing fundamental scientific questions related to these materials, the meeting has always included a discussion of their potential applications. Consequently, this conference has played a critical role in the birth and growth of nanoscience and engineering. The goal of the 2009 Gordon Conference is to continue the forward-looking tradition of this meeting and discuss the most recent advances in the field of clusters, nanocrystals, and nanostructures. As in past meetings, this will include new topics that broaden the field. In particular, a special emphasis will be placed on nanomaterials related to the efficient use, generation, or conversion of energy. For example, we anticipate presentations related to batteries, catalysts, photovoltaics, and thermoelectrics. In addition, we expect to address the controversy surrounding carrier multiplication with a session in which recent results addressing this phenomenon will be discussed and debated. The atmosphere of the conference, which emphasizes the presentation of unpublished results and lengthy discussion periods, ensures that attendees will enjoy a valuable and stimulating experience. Because only a limited number of participants are allowed to attend this conference, and oversubscription is anticipated, we encourage all interested researchers from academia, industry, and government institutions to apply as early as possible. An invitation is not required. We also encourage all attendees to submit their latest results for presentation at the poster sessions. We anticipate that several posters will be selected for 'hot topic' oral

  1. MD Anderson's Population Health Approaches to Cancer Prevention.

    Science.gov (United States)

    Foxhall, Lewis; Moreno, Mark; Hawk, Ernest

    2018-02-01

    Texas's size and unique population demographics present challenges to addressing the state's cancer burden. The University of Texas MD Anderson Cancer Center is one of 69 National Cancer Institute-designated cancer centers across the United States. While these centers traditionally have focused on research, education and training, and providing research-driven patient care, they are in a unique position to collaboratively advance population health through cancer control. Unlike the traditional academic model of a three-legged stool representing research, education, and patient care, MD Anderson's mission includes a fourth leg that incorporates population health approaches. MD Anderson has leveraged state- and national-level data and freely available resources to develop population-health priorities and a set of evidence-based actions across policy, public and professional education, and community-based clinical service domains to address these priorities. Population health approaches complement dissemination and implementation research and treatment, and will be increasingly needed to address the growing cancer burden in Texas and the nation.

  2. The 2013 Clusters, Nanocrystals & Nanostructures Gordon Research Conference/Gordon Research Seminar

    Energy Technology Data Exchange (ETDEWEB)

    Krauss, Todd D. [University of Rochester

    2014-11-25

    The fundamental properties of small particles and their potential for groundbreaking applications are among the most exciting areas of study in modern physics, chemistry, and materials science. The Clusters, Nanocrystals & Nanostructures Gordon ResearchConference and Gordon Research Seminar synthesize contributions from these inter-related fields that reflect the pivotal role of nano-particles at the interface between these disciplines. Size-dependent optical, electronic, magnetic and catalytic properties offer prospects for applications in many fields, and possible solutions for many of the grand challenges facing energy generation, consumption, delivery, and storage in the 21st century. The goal of the 2013 Clusters, Nanocrystals & Nanostructures Gordon Research Conference and Gordon Research Seminar is to continue the historical interdisciplinary tradition of this series and discuss the most recent advances, basic scientific questions, and emerging applications of clusters, nanocrystals, and nanostructures. The Clusters, Nanocrystals & Nanostructures GRC/GRS traditionally brings together the leading scientific groups that have made significant recent advances in one or more fundamental nanoscience or nanotechnology areas. Broad interests of the DOE BES and Solar Photochemistry Program addressed by this meeting include the areas of solar energy to fuels conversion, new photovoltaic systems, fundamental characterization of nanomaterials, magnetism, catalysis, and quantum physics. The vast majority of speakers and attendees will address either directly the topic of nanotechnology for photoinduced charge transfer, charge transport, and catalysis, or will have made significant contributions to related areas that will impact these fields indirectly. These topics have direct relevance to the mission of the DOE BES since it is this cutting-edge basic science that underpins our energy future.

  3. Addressing the psychosocial wellbeing of teenage children of cancer patients and survivors.

    Science.gov (United States)

    Annunziata, Maria Antonietta; Muzzatti, Barbara; Surbone, Antonella

    2016-02-01

    Thomas is 13 years old. His parents report a sharp decline in his school grades caused, according to his teachers' opinions, by listlessness and lack of concentration. The parents of Julia, 16 years old, describe her as restless, evasive, isolated, and withdrawn from others and from her usual activities. Linda, 18 years old, is described by her parents as indecisive, uncertain, and almost lethargic. Normally resolute and a high academic achiever, she appears locked in herself, unable to make choices. We first learned about them through the accounts of their concerned parents. Claire, 19 years old, lost weight and exercised hard enough to induce amenorrhea after her young mother underwent treatment for breast cancer, including antihormonal treatment. These four teenagers have in common a parent diagnosed with cancer, undergoing or having just completed treatment.

  4. Studies in the X-Ray Emission of Clusters of Galaxies and Other Topics

    Science.gov (United States)

    Vrtilek, Jan; Thronson, Harley (Technical Monitor)

    2001-01-01

    The paper discusses the following: (1) X-ray study of groups of galaxies with Chandra and XMM. (2) X-ray properties of point sources in Chandra deep fields. (3) Study of cluster substructure using wavelet techniques. (4) Combined study of galaxy clusters with X-ray and the S-Z effect. Groups of galaxies are the fundamental building blocks of large scale structure in the Universe. X-ray study of the intragroup medium offers a powerful approach to addressing some of the major questions that still remain about almost all aspects of groups: their ages, origins, importance of composition of various galaxy types, relations to clusters, and origin and enrichment of the intragroup gas. Long exposures with Chandra have opened new opportunities for the study of X-ray background. The presence of substructure within clusters of galaxies has substantial implications for our understanding of cluster evolution as well as fundamental questions in cosmology.

  5. Incidence and mortality of gastric cancer in China

    OpenAIRE

    Yang, L

    2006-01-01

    Gastric cancer is one of the most frequent cancers in the world; almost two-thirds of gastric cancer cases and deaths occur in less developed regions. In China, based on two national mortality surveys conducted in 1970s and 1990s, there is an obvious clustering of geographical distribution of gastric cancer in the country, with the high mortality being mostly located in rural areas, especially in Gansu, Henan, Hebei, Shanxi and Shaanxi Provinces in the middle-western part of China. Despite a ...

  6. Clusters and how to make it work : Cluster Strategy Toolkit

    NARCIS (Netherlands)

    Manickam, Anu; van Berkel, Karel

    2014-01-01

    Clusters are the magic answer to regional economic development. Firms in clusters are more innovative; cluster policy dominates EU policy; ‘top-sectors’ and excellence are the choice of national policy makers; clusters are ‘in’. But, clusters are complex, clusters are ‘messy’; there is no clear

  7. Cluster dynamics at different cluster size and incident laser wavelengths

    International Nuclear Information System (INIS)

    Desai, Tara; Bernardinello, Andrea

    2002-01-01

    X-ray emission spectra from aluminum clusters of diameter -0.4 μm and gold clusters of dia. ∼1.25 μm are experimentally studied by irradiating the cluster foil targets with 1.06 μm laser, 10 ns (FWHM) at an intensity ∼10 12 W/cm 2 . Aluminum clusters show a different spectra compared to bulk material whereas gold cluster evolve towards bulk gold. Experimental data are analyzed on the basis of cluster dimension, laser wavelength and pulse duration. PIC simulations are performed to study the behavior of clusters at higher intensity I≥10 17 W/cm 2 for different size of the clusters irradiated at different laser wavelengths. Results indicate the dependence of cluster dynamics on cluster size and incident laser wavelength

  8. Text Clustering Algorithm Based on Random Cluster Core

    Directory of Open Access Journals (Sweden)

    Huang Long-Jun

    2016-01-01

    Full Text Available Nowadays clustering has become a popular text mining algorithm, but the huge data can put forward higher requirements for the accuracy and performance of text mining. In view of the performance bottleneck of traditional text clustering algorithm, this paper proposes a text clustering algorithm with random features. This is a kind of clustering algorithm based on text density, at the same time using the neighboring heuristic rules, the concept of random cluster is introduced, which effectively reduces the complexity of the distance calculation.

  9. Cluster as a Service for Disaster Recovery in Intercloud Systems: Design and Modeling

    OpenAIRE

    Mohammad Ali Khoshkholghi

    2014-01-01

    Nowadays, all modern IT technologies aim to create dynamic and flexible environments. For this reason, InterCloud has been designed to provide a vast and flexible virtualized environment in which many clouds can interact with one another in a dynamic way. Disaster recovery is one of the main applications of InterCloud which can be supported by Cluster as a Service. However, the previous studies addressed disaster recovery and Cluster as a Service separately. In addition, system backup and dis...

  10. Some elements of understanding about the cluster ejection accident in the EPR

    International Nuclear Information System (INIS)

    Vignon, Dominique

    2010-01-01

    The author answers to a publication made by an association (Sortir du Nucleaire) which is provided in appendix (some parts of this text are highlighted) and denounced risks associated with a cluster ejection accident in an EPR in relationship with steering modes which, according to this association, would be essentially related to an objective of economic profitability. The author first recalls some elements regarding the control and neutron stopping of pressurized water reactors. Then, after having outlined some specific aspects of the EPR design, he addresses the cluster ejection accident: safety approach and its application to this type of accident. He recalls the conclusions of studies of cluster ejection performed by EDF and AREVA, comments the consequences for the EPR power

  11. [Sexy cancer--sexuality for cancer patients].

    Science.gov (United States)

    Peleg-Nesher, Sharon; Yachini, Brurya; Inbar, Moshe

    2009-09-01

    Sexuality is a basic need for every human being as long as he or she is alive, irrespective of age or health status. Approximately 23,500 individuals are diagnosed with cancer each year in Israel and join the 120,000 cancer patients currently living in Israel. The results of cancer treatments are traditionally assessed and based on the outcome regarding mortality versus survival. An equally important aspect to be addressed in this assessment must relate to quality of life. One of the more painful insults to the quality of life of cancer patients relates to the deleterious effects on sexuality. This article aims to present physicians with the spectrum of sexuality-related issues which are encountered by cancer patients and their partners, starting from the moment of diagnosis, throughout the various stages of treatment and to provide basic knowledge. Many individuals contracting cancer have difficulty dealing with the issue of sexuality. They are typically embarrassed and feel uneasy when asking health care providers about such a non-life threatening issue. Partners similarly feel both shame and guilt. In many cases sexuality, intimacy and emotional attachment are important aspects and may be essential for survival. Addressing these issues during treatment can provide patients with a sense of security, avoiding embarrassment and further exacerbation of such problems. Unfortunately, little has been done to develop an optimal interventional program, although standard sexual treatments have often been applied. Prospective clinical research and outcomes are missing. The physician can use the well-known PLISSIT model (1978): to provide sexuality involvement on different levels. The very new BETTER model (2004) can help emphasize that cancer treatment and the disease have an influence on intimacy and sexuality.

  12. Low tobacco-related cancer incidence in offspring of long-lived siblings

    DEFF Research Database (Denmark)

    Pedersen, Jacob K; Skytthe, Axel; McGue, Matt

    2015-01-01

    PURPOSE: Familial clustering of longevity is well documented and includes both genetic and other familial factors, but the specific underlying mechanisms are largely unknown. We examined whether low incidence of specific cancers is a mechanism for familial clustering of longevity. METHODS: The st...

  13. Cluster emergence and network evolution A longitudinal analysis of the inventor network in Sophia-Antipolis

    OpenAIRE

    Anne L. J. ter Wal

    2008-01-01

    Abstract It is increasingly acknowledged that clusters do not necessarily exhibit networks of local collective learning. This paper addresses the question under which conditions this is the case. Through a longitudinal case study of the business park Sophia-Antipolis it investigates how networks of collective learning emerged throughout the growth of the cluster. Network reconstruction with patent data shows that an innovation network emerged only in Information Technology, in whic...

  14. On clusters and clustering from atoms to fractals

    CERN Document Server

    Reynolds, PJ

    1993-01-01

    This book attempts to answer why there is so much interest in clusters. Clusters occur on all length scales, and as a result occur in a variety of fields. Clusters are interesting scientifically, but they also have important consequences technologically. The division of the book into three parts roughly separates the field into small, intermediate, and large-scale clusters. Small clusters are the regime of atomic and molecular physics and chemistry. The intermediate regime is the transitional regime, with its characteristics including the onset of bulk-like behavior, growth and aggregation, a

  15. [Electronic and structural properties of individual nanometer-size supported metallic clusters]. Final performance report

    Energy Technology Data Exchange (ETDEWEB)

    Reifenberger, R.

    1993-09-01

    This report summarizes the work performed under contract DOE-FCO2-84ER45162. During the past ten years, our study of electron emission from laser-illuminated field emission tips has taken on a broader scope by addressing problems of direct interest to those concerned with the unique physical and chemical properties of nanometer-size clusters. The work performed has demonstrated that much needed data can be obtained on individual nanometer-size clusters supported on a wide-variety of different substrates. The work was performed in collaboration with R.P. Andres in the School of Chemical Engineering at Purdue University. The Multiple Expansion Cluster Source developed by Andres and his students was essential for producing the nanometer-size clusters studied. The following report features a discussion of these results. This report provides a motivation for studying the properties of nanometer-size clusters and summarizes the results obtained.

  16. Understanding PSA and its derivatives in prediction of tumor volume: Addressing health disparities in prostate cancer risk stratification.

    Science.gov (United States)

    Chinea, Felix M; Lyapichev, Kirill; Epstein, Jonathan I; Kwon, Deukwoo; Smith, Paul Taylor; Pollack, Alan; Cote, Richard J; Kryvenko, Oleksandr N

    2017-03-28

    To address health disparities in risk stratification of U.S. Hispanic/Latino men by characterizing influences of prostate weight, body mass index, and race/ethnicity on the correlation of PSA derivatives with Gleason score 6 (Grade Group 1) tumor volume in a diverse cohort. Using published PSA density and PSA mass density cutoff values, men with higher body mass indices and prostate weights were less likely to have a tumor volume PSA derivatives when predicting for tumor volume. In receiver operator characteristic analysis, area under the curve values for all PSA derivatives varied across race/ethnicity with lower optimal cutoff values for Hispanic/Latino (PSA=2.79, PSA density=0.06, PSA mass=0.37, PSA mass density=0.011) and Non-Hispanic Black (PSA=3.75, PSA density=0.07, PSA mass=0.46, PSA mass density=0.008) compared to Non-Hispanic White men (PSA=4.20, PSA density=0.11 PSA mass=0.53, PSA mass density=0.014). We retrospectively analyzed 589 patients with low-risk prostate cancer at radical prostatectomy. Pre-operative PSA, patient height, body weight, and prostate weight were used to calculate all PSA derivatives. Receiver operating characteristic curves were constructed for each PSA derivative per racial/ethnic group to establish optimal cutoff values predicting for tumor volume ≥0.5 cm3. Increasing prostate weight and body mass index negatively influence PSA derivatives for predicting tumor volume. PSA derivatives' ability to predict tumor volume varies significantly across race/ethnicity. Hispanic/Latino and Non-Hispanic Black men have lower optimal cutoff values for all PSA derivatives, which may impact risk assessment for prostate cancer.

  17. Confronting human papilloma virus/oropharyngeal cancer: a model for interprofessional collaboration.

    Science.gov (United States)

    Fried, Jacquelyn L

    2014-06-01

    A collaborative practice model related to Human Papilloma Virus (HPV) associated oropharyngeal cancer highlights the role of the dental hygienist in addressing this condition. The incidence of HPV associated head and neck cancer is rising. Multiple professionals including the dental hygienist can work collaboratively to confront this growing public health concern. A critical review applies the growth and utilization of interprofessional education (IPE) and interprofessional collaboration (IPC) to multi-disciplinary models addressing the human papilloma virus and oropharyngeal cancers. A model related to HPV associated oropharyngeal cancer addresses an oral systemic condition that supports the inclusion of a dental hygienist on collaborative teams addressing prevention, detection, treatment and cure of OPC. Copyright © 2014 Elsevier Inc. All rights reserved.

  18. Sun Protection Motivational Stages and Behavior: Skin Cancer Risk Profiles

    Science.gov (United States)

    Pagoto, Sherry L.; McChargue, Dennis E.; Schneider, Kristin; Cook, Jessica Werth

    2004-01-01

    Objective: To create skin cancer risk profiles that could be used to predict sun protection among Midwest beachgoers. Method: Cluster analysis was used with study participants (N=239), who provided information about sun protection motivation and behavior, perceived risk, burn potential, and tan importance. Participants were clustered according to…

  19. GibbsCluster: unsupervised clustering and alignment of peptide sequences

    DEFF Research Database (Denmark)

    Andreatta, Massimo; Alvarez, Bruno; Nielsen, Morten

    2017-01-01

    motif characterizing each cluster. Several parameters are available to customize cluster analysis, including adjustable penalties for small clusters and overlapping groups and a trash cluster to remove outliers. As an example application, we used the server to deconvolute multiple specificities in large......-scale peptidome data generated by mass spectrometry. The server is available at http://www.cbs.dtu.dk/services/GibbsCluster-2.0....

  20. Diametrical clustering for identifying anti-correlated gene clusters.

    Science.gov (United States)

    Dhillon, Inderjit S; Marcotte, Edward M; Roshan, Usman

    2003-09-01

    Clustering genes based upon their expression patterns allows us to predict gene function. Most existing clustering algorithms cluster genes together when their expression patterns show high positive correlation. However, it has been observed that genes whose expression patterns are strongly anti-correlated can also be functionally similar. Biologically, this is not unintuitive-genes responding to the same stimuli, regardless of the nature of the response, are more likely to operate in the same pathways. We present a new diametrical clustering algorithm that explicitly identifies anti-correlated clusters of genes. Our algorithm proceeds by iteratively (i). re-partitioning the genes and (ii). computing the dominant singular vector of each gene cluster; each singular vector serving as the prototype of a 'diametric' cluster. We empirically show the effectiveness of the algorithm in identifying diametrical or anti-correlated clusters. Testing the algorithm on yeast cell cycle data, fibroblast gene expression data, and DNA microarray data from yeast mutants reveals that opposed cellular pathways can be discovered with this method. We present systems whose mRNA expression patterns, and likely their functions, oppose the yeast ribosome and proteosome, along with evidence for the inverse transcriptional regulation of a number of cellular systems.

  1. Partitional clustering algorithms

    CERN Document Server

    2015-01-01

    This book summarizes the state-of-the-art in partitional clustering. Clustering, the unsupervised classification of patterns into groups, is one of the most important tasks in exploratory data analysis. Primary goals of clustering include gaining insight into, classifying, and compressing data. Clustering has a long and rich history that spans a variety of scientific disciplines including anthropology, biology, medicine, psychology, statistics, mathematics, engineering, and computer science. As a result, numerous clustering algorithms have been proposed since the early 1950s. Among these algorithms, partitional (nonhierarchical) ones have found many applications, especially in engineering and computer science. This book provides coverage of consensus clustering, constrained clustering, large scale and/or high dimensional clustering, cluster validity, cluster visualization, and applications of clustering. Examines clustering as it applies to large and/or high-dimensional data sets commonly encountered in reali...

  2. Prospective molecular profiling of canine cancers provides a clinically relevant comparative model for evaluating personalized medicine (PMed) trials.

    Science.gov (United States)

    Paoloni, Melissa; Webb, Craig; Mazcko, Christina; Cherba, David; Hendricks, William; Lana, Susan; Ehrhart, E J; Charles, Brad; Fehling, Heather; Kumar, Leena; Vail, David; Henson, Michael; Childress, Michael; Kitchell, Barbara; Kingsley, Christopher; Kim, Seungchan; Neff, Mark; Davis, Barbara; Khanna, Chand; Trent, Jeffrey

    2014-01-01

    Molecularly-guided trials (i.e. PMed) now seek to aid clinical decision-making by matching cancer targets with therapeutic options. Progress has been hampered by the lack of cancer models that account for individual-to-individual heterogeneity within and across cancer types. Naturally occurring cancers in pet animals are heterogeneous and thus provide an opportunity to answer questions about these PMed strategies and optimize translation to human patients. In order to realize this opportunity, it is now necessary to demonstrate the feasibility of conducting molecularly-guided analysis of tumors from dogs with naturally occurring cancer in a clinically relevant setting. A proof-of-concept study was conducted by the Comparative Oncology Trials Consortium (COTC) to determine if tumor collection, prospective molecular profiling, and PMed report generation within 1 week was feasible in dogs. Thirty-one dogs with cancers of varying histologies were enrolled. Twenty-four of 31 samples (77%) successfully met all predefined QA/QC criteria and were analyzed via Affymetrix gene expression profiling. A subsequent bioinformatics workflow transformed genomic data into a personalized drug report. Average turnaround from biopsy to report generation was 116 hours (4.8 days). Unsupervised clustering of canine tumor expression data clustered by cancer type, but supervised clustering of tumors based on the personalized drug report clustered by drug class rather than cancer type. Collection and turnaround of high quality canine tumor samples, centralized pathology, analyte generation, array hybridization, and bioinformatic analyses matching gene expression to therapeutic options is achievable in a practical clinical window (strategies may aid cancer drug development.

  3. Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer. | Office of Cancer Genomics

    Science.gov (United States)

    We report a comprehensive analysis of 412 muscle-invasive bladder cancers characterized by multiple TCGA analytical platforms. Fifty-eight genes were significantly mutated, and the overall mutational load was associated with APOBEC-signature mutagenesis. Clustering by mutation signature identified a high-mutation subset with 75% 5-year survival.

  4. Summer Student Breast Cancer Research Training Program

    National Research Council Canada - National Science Library

    Zaloga, Gary P

    2005-01-01

    ... projects addressed the effects of omega-3 lipids upon breast cancer cells. 0mega-3 lipids were found to decrease breast cancer-induced muscle cell proteolysis and to induce apoptosis in cancer cells...

  5. Discovery of Multiseeded Multimode Formation of Embedded Clusters in the Rosette Molecular Complex

    Science.gov (United States)

    Li, Jin Zeng; Smith, Michael D.

    2005-02-01

    An investigation based on data from the spatially complete Two Micron All Sky Survey (2MASS) reveals that a remarkable burst of clustered star formation is taking place throughout the southeast quadrant of the Rosette Molecular Cloud. Compact clusters are forming in a multiseeded mode, in parallel and at various places. In addition, sparse aggregates of embedded young stars are extensively distributed. In this study we report the primary results and implications for high-mass and clustered star formation in giant molecular clouds. In particular, we incorporate for the first time the birth of medium- to low-mass stars into the scenario of sequential formation of OB clusters. Following the emergence of the young OB cluster NGC 2244, a variety of manifestations of forming clusters of medium to high mass appears in the vicinity of the swept-up layer of the H II region as well as farther into the molecular cloud. The embedded clusters appear to form in a structured manner, which suggests they follow tracks laid out by the decay of macroturbulence. We address the possible origins of the turbulence. This leads us to propose a tree model to interpret the neat spatial distribution of clusters within a large section of the Rosette complex. Prominent new-generation OB clusters are identified at the root of the tree pattern.

  6. Cluster Policy in the Light of Institutional Context—A Comparative Study of Transition Countries

    Directory of Open Access Journals (Sweden)

    Tine Lehmann

    2015-10-01

    Full Text Available The business environment in transition countries is often extraordinarily challenging for companies. The transition process these countries find themselves in leads to constant changes in the institutional environment. Hence, institutional voids prevail. These institutional voids cause competitive disadvantages for small and medium enterprises. Cluster policy can address these competitive disadvantages. As cluster policy generally aims at supporting companies’ competitive advantage by spurring innovation and productivity, it can help to bridge institutional voids. This article’s research question aims at analyzing and comparing cluster policies in the institutional context of two transition countries (Serbia and Tunisia and analyzes to what extent cluster policies in these two countries are adapted to institutional voids prevailing there. The case studies offer insights into apparent difficulties of clusters in bridging formal institutional voids, as well as, notably, into the informal void of skill mismatches in the labor market. Still, for some specific voids, clusters do at least implicitly assume a bridging role. While the cluster policies examined do not explicitly target the institutional voids identified, cluster management can—in the course of time—align its service offering more closely with these voids. Bottom-up designed cluster policies can play an especially important role in such an evolution towards bridging institutional voids.

  7. Simulation modeling for stratified breast cancer screening - a systematic review of cost and quality of life assumptions.

    Science.gov (United States)

    Arnold, Matthias

    2017-12-02

    The economic evaluation of stratified breast cancer screening gains momentum, but produces also very diverse results. Systematic reviews so far focused on modeling techniques and epidemiologic assumptions. However, cost and utility parameters received only little attention. This systematic review assesses simulation models for stratified breast cancer screening based on their cost and utility parameters in each phase of breast cancer screening and care. A literature review was conducted to compare economic evaluations with simulation models of personalized breast cancer screening. Study quality was assessed using reporting guidelines. Cost and utility inputs were extracted, standardized and structured using a care delivery framework. Studies were then clustered according to their study aim and parameters were compared within the clusters. Eighteen studies were identified within three study clusters. Reporting quality was very diverse in all three clusters. Only two studies in cluster 1, four studies in cluster 2 and one study in cluster 3 scored high in the quality appraisal. In addition to the quality appraisal, this review assessed if the simulation models were consistent in integrating all relevant phases of care, if utility parameters were consistent and methodological sound and if cost were compatible and consistent in the actual parameters used for screening, diagnostic work up and treatment. Of 18 studies, only three studies did not show signs of potential bias. This systematic review shows that a closer look into the cost and utility parameter can help to identify potential bias. Future simulation models should focus on integrating all relevant phases of care, using methodologically sound utility parameters and avoiding inconsistent cost parameters.

  8. The remarkable geographical pattern of gastric cancer mortality in Ecuador.

    Science.gov (United States)

    Montero-Oleas, Nadia; Núñez-González, Solange; Simancas-Racines, Daniel

    2017-12-01

    This study was aimed to describe the gastric cancer mortality trend, and to analyze the spatial distribution of gastric cancer mortality in Ecuador, between 2004 and 2015. Data were collected from the National Institute of Statistics and Census (INEC) database. Crude gastric cancer mortality rates, standardized mortality ratios (SMRs) and indirect standardized mortality rates (ISMRs) were calculated per 100,000 persons. For time trend analysis, joinpoint regression was used. The annual percentage rate change (APC) and the average annual percent change (AAPC) was computed for each province. Spatial age-adjusted analysis was used to detect high risk clusters of gastric cancer mortality, from 2010 to 2015, using Kulldorff spatial scan statistics. In Ecuador, between 2004 and 2015, gastric cancer caused a total of 19,115 deaths: 10,679 in men and 8436 in women. When crude rates were analyzed, a significant decline was detected (AAPC: -1.8%; p<0.001). ISMR also decreased, but this change was not statistically significant (APC: -0.53%; p=0.36). From 2004 to 2007 and from 2008 to 2011 the province with the highest ISMR was Carchi; and, from 2012 to 2015, was Cotopaxi. The most likely high occurrence cluster included Bolívar, Los Ríos, Chimborazo, Tungurahua, and Cotopaxi provinces, with a relative risk of 1.34 (p<0.001). There is a substantial geographic variation in gastric cancer mortality rates among Ecuadorian provinces. The spatial analysis indicates the presence of high occurrence clusters throughout the Andes Mountains. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  9. Patient-Centered Care in Breast Cancer Genetic Clinics

    Directory of Open Access Journals (Sweden)

    Anne Brédart

    2018-02-01

    Full Text Available With advances in breast cancer (BC gene panel testing, risk counseling has become increasingly complex, potentially leading to unmet psychosocial needs. We assessed psychosocial needs and correlates in women initiating testing for high genetic BC risk in clinics in France and Germany, and compared these results with data from a literature review. Among the 442 counselees consecutively approached, 212 (83% in France and 180 (97% in Germany, mostly BC patients (81% and 92%, respectively, returned the ‘Psychosocial Assessment in Hereditary Cancer’ questionnaire. Based on the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA BC risk estimation model, the mean BC lifetime risk estimates were 19% and 18% in France and Germany, respectively. In both countries, the most prevalent needs clustered around the “living with cancer” and “children-related issues” domains. In multivariate analyses, a higher number of psychosocial needs were significantly associated with younger age (b = −0.05, higher anxiety (b = 0.78, and having children (b = 1.51, but not with country, educational level, marital status, depression, or loss of a family member due to hereditary cancer. These results are in line with the literature review data. However, this review identified only seven studies that quantitatively addressed psychosocial needs in the BC genetic counseling setting. Current data lack understandings of how cancer risk counseling affects psychosocial needs, and improves patient-centered care in that setting.

  10. ADVANCED CLUSTER BASED IMAGE SEGMENTATION

    Directory of Open Access Journals (Sweden)

    D. Kesavaraja

    2011-11-01

    Full Text Available This paper presents efficient and portable implementations of a useful image segmentation technique which makes use of the faster and a variant of the conventional connected components algorithm which we call parallel Components. In the Modern world majority of the doctors are need image segmentation as the service for various purposes and also they expect this system is run faster and secure. Usually Image segmentation Algorithms are not working faster. In spite of several ongoing researches in Conventional Segmentation and its Algorithms might not be able to run faster. So we propose a cluster computing environment for parallel image Segmentation to provide faster result. This paper is the real time implementation of Distributed Image Segmentation in Clustering of Nodes. We demonstrate the effectiveness and feasibility of our method on a set of Medical CT Scan Images. Our general framework is a single address space, distributed memory programming model. We use efficient techniques for distributing and coalescing data as well as efficient combinations of task and data parallelism. The image segmentation algorithm makes use of an efficient cluster process which uses a novel approach for parallel merging. Our experimental results are consistent with the theoretical analysis and practical results. It provides the faster execution time for segmentation, when compared with Conventional method. Our test data is different CT scan images from the Medical database. More efficient implementations of Image Segmentation will likely result in even faster execution times.

  11. Association of brain cancer with dental x-rays and occupation in Missouri

    International Nuclear Information System (INIS)

    Neuberger, J.S.; Brownson, R.C.; Morantz, R.A.; Chin, T.D.

    1991-01-01

    This investigation of a brain cancer cluster in Missouri used two approaches to investigate associations with potential risk factors. In a case-control study in a rural town, we interviewed surrogates of cases and controls about potential risk factors. We found a statistically significant positive association of brain cancer with reported exposure to dental x-rays. Occupation was not associated with the cluster in the rural town. In a standardized proportional mortality study for the state of Missouri, we calculated the observed and expected proportion of brain cancers by occupation and industry in Missouri decedents. We found that motor vehicle manufacturers, beauty shop workers, managers and administrators, elementary school teachers, and hairdressers and cosmetologists had significantly elevated proportions of brain cancer. Brain tumors are inconsistently associated with occupation in the literature. Further study of brain cancer etiology with respect to dental x-ray exposures seems warranted

  12. Addressing the complexity of water chemistry in environmental fate modeling for engineered nanoparticles.

    Science.gov (United States)

    Sani-Kast, Nicole; Scheringer, Martin; Slomberg, Danielle; Labille, Jérôme; Praetorius, Antonia; Ollivier, Patrick; Hungerbühler, Konrad

    2015-12-01

    Engineered nanoparticle (ENP) fate models developed to date - aimed at predicting ENP concentration in the aqueous environment - have limited applicability because they employ constant environmental conditions along the modeled system or a highly specific environmental representation; both approaches do not show the effects of spatial and/or temporal variability. To address this conceptual gap, we developed a novel modeling strategy that: 1) incorporates spatial variability in environmental conditions in an existing ENP fate model; and 2) analyzes the effect of a wide range of randomly sampled environmental conditions (representing variations in water chemistry). This approach was employed to investigate the transport of nano-TiO2 in the Lower Rhône River (France) under numerous sets of environmental conditions. The predicted spatial concentration profiles of nano-TiO2 were then grouped according to their similarity by using cluster analysis. The analysis resulted in a small number of clusters representing groups of spatial concentration profiles. All clusters show nano-TiO2 accumulation in the sediment layer, supporting results from previous studies. Analysis of the characteristic features of each cluster demonstrated a strong association between the water conditions in regions close to the ENP emission source and the cluster membership of the corresponding spatial concentration profiles. In particular, water compositions favoring heteroaggregation between the ENPs and suspended particulate matter resulted in clusters of low variability. These conditions are, therefore, reliable predictors of the eventual fate of the modeled ENPs. The conclusions from this study are also valid for ENP fate in other large river systems. Our results, therefore, shift the focus of future modeling and experimental research of ENP environmental fate to the water characteristic in regions near the expected ENP emission sources. Under conditions favoring heteroaggregation in these

  13. Alignment and integration of complex networks by hypergraph-based spectral clustering

    Science.gov (United States)

    Michoel, Tom; Nachtergaele, Bruno

    2012-11-01

    Complex networks possess a rich, multiscale structure reflecting the dynamical and functional organization of the systems they model. Often there is a need to analyze multiple networks simultaneously, to model a system by more than one type of interaction, or to go beyond simple pairwise interactions, but currently there is a lack of theoretical and computational methods to address these problems. Here we introduce a framework for clustering and community detection in such systems using hypergraph representations. Our main result is a generalization of the Perron-Frobenius theorem from which we derive spectral clustering algorithms for directed and undirected hypergraphs. We illustrate our approach with applications for local and global alignment of protein-protein interaction networks between multiple species, for tripartite community detection in folksonomies, and for detecting clusters of overlapping regulatory pathways in directed networks.

  14. Cluster Matters

    DEFF Research Database (Denmark)

    Gulati, Mukesh; Lund-Thomsen, Peter; Suresh, Sangeetha

    2018-01-01

    sell their products successfully in international markets, but there is also an increasingly large consumer base within India. Indeed, Indian industrial clusters have contributed to a substantial part of this growth process, and there are several hundred registered clusters within the country...... of this handbook, which focuses on the role of CSR in MSMEs. Hence we contribute to the literature on CSR in industrial clusters and specifically CSR in Indian industrial clusters by investigating the drivers of CSR in India’s industrial clusters....

  15. Weighted Clustering

    DEFF Research Database (Denmark)

    Ackerman, Margareta; Ben-David, Shai; Branzei, Simina

    2012-01-01

    We investigate a natural generalization of the classical clustering problem, considering clustering tasks in which different instances may have different weights.We conduct the first extensive theoretical analysis on the influence of weighted data on standard clustering algorithms in both...... the partitional and hierarchical settings, characterizing the conditions under which algorithms react to weights. Extending a recent framework for clustering algorithm selection, we propose intuitive properties that would allow users to choose between clustering algorithms in the weighted setting and classify...

  16. Accounting for regional background and population size in the detection of spatial clusters and outliers using geostatistical filtering and spatial neutral models: the case of lung cancer in Long Island, New York

    Directory of Open Access Journals (Sweden)

    Goovaerts Pierre

    2004-07-01

    Full Text Available Abstract Background Complete Spatial Randomness (CSR is the null hypothesis employed by many statistical tests for spatial pattern, such as local cluster or boundary analysis. CSR is however not a relevant null hypothesis for highly complex and organized systems such as those encountered in the environmental and health sciences in which underlying spatial pattern is present. This paper presents a geostatistical approach to filter the noise caused by spatially varying population size and to generate spatially correlated neutral models that account for regional background obtained by geostatistical smoothing of observed mortality rates. These neutral models were used in conjunction with the local Moran statistics to identify spatial clusters and outliers in the geographical distribution of male and female lung cancer in Nassau, Queens, and Suffolk counties, New York, USA. Results We developed a typology of neutral models that progressively relaxes the assumptions of null hypotheses, allowing for the presence of spatial autocorrelation, non-uniform risk, and incorporation of spatially heterogeneous population sizes. Incorporation of spatial autocorrelation led to fewer significant ZIP codes than found in previous studies, confirming earlier claims that CSR can lead to over-identification of the number of significant spatial clusters or outliers. Accounting for population size through geostatistical filtering increased the size of clusters while removing most of the spatial outliers. Integration of regional background into the neutral models yielded substantially different spatial clusters and outliers, leading to the identification of ZIP codes where SMR values significantly depart from their regional background. Conclusion The approach presented in this paper enables researchers to assess geographic relationships using appropriate null hypotheses that account for the background variation extant in real-world systems. In particular, this new

  17. Support Policies in Clusters: Prioritization of Support Needs by Cluster Members According to Cluster Life Cycle

    Directory of Open Access Journals (Sweden)

    Gulcin Salıngan

    2012-07-01

    Full Text Available Economic development has always been a moving target. Both the national and local governments have been facing the challenge of implementing the effective and efficient economic policy and program in order to best utilize their limited resources. One of the recent approaches in this area is called cluster-based economic analysis and strategy development. This study reviews key literature and some of the cluster based economic policies adopted by different governments. Based on this review, it proposes “the cluster life cycle” as a determining factor to identify the support requirements of clusters. A survey, designed based on literature review of International Cluster support programs, was conducted with 30 participants from 3 clusters with different maturity stage. This paper discusses the results of this study conducted among the cluster members in Eskişehir- Bilecik-Kütahya Region in Turkey on the requirement of the support to foster the development of related clusters.

  18. Using imputation to provide location information for nongeocoded addresses.

    Directory of Open Access Journals (Sweden)

    Frank C Curriero

    2010-02-01

    Full Text Available The importance of geography as a source of variation in health research continues to receive sustained attention in the literature. The inclusion of geographic information in such research often begins by adding data to a map which is predicated by some knowledge of location. A precise level of spatial information is conventionally achieved through geocoding, the geographic information system (GIS process of translating mailing address information to coordinates on a map. The geocoding process is not without its limitations, though, since there is always a percentage of addresses which cannot be converted successfully (nongeocodable. This raises concerns regarding bias since traditionally the practice has been to exclude nongeocoded data records from analysis.In this manuscript we develop and evaluate a set of imputation strategies for dealing with missing spatial information from nongeocoded addresses. The strategies are developed assuming a known zip code with increasing use of collateral information, namely the spatial distribution of the population at risk. Strategies are evaluated using prostate cancer data obtained from the Maryland Cancer Registry. We consider total case enumerations at the Census county, tract, and block group level as the outcome of interest when applying and evaluating the methods. Multiple imputation is used to provide estimated total case counts based on complete data (geocodes plus imputed nongeocodes with a measure of uncertainty. Results indicate that the imputation strategy based on using available population-based age, gender, and race information performed the best overall at the county, tract, and block group levels.The procedure allows for the potentially biased and likely under reported outcome, case enumerations based on only the geocoded records, to be presented with a statistically adjusted count (imputed count with a measure of uncertainty that are based on all the case data, the geocodes and imputed

  19. Cancer and Social Media: A Comparison of Traffic about Breast Cancer, Prostate Cancer, and Other Reproductive Cancers on Twitter and Instagram.

    Science.gov (United States)

    Vraga, Emily K; Stefanidis, Anthony; Lamprianidis, Georgios; Croitoru, Arie; Crooks, Andrew T; Delamater, Paul L; Pfoser, Dieter; Radzikowski, Jacek R; Jacobsen, Kathryn H

    2018-01-01

    Social media are often heralded as offering cancer campaigns new opportunities to reach the public. However, these campaigns may not be equally successful, depending on the nature of the campaign itself, the type of cancer being addressed, and the social media platform being examined. This study is the first to compare social media activity on Twitter and Instagram across three time periods: #WorldCancerDay in February, the annual month-long campaigns of National Breast Cancer Awareness Month (NBCAM) in October and Movember in November, and during the full year outside of these campaigns. Our results suggest that women's reproductive cancers - especially breast cancer - tend to outperform men's reproductive cancer - especially prostate cancer - across campaigns and social media platforms. Twitter overall generates substantially more activity than Instagram for both cancer campaigns, suggesting Instagram may be an untapped resource. However, the messaging for both campaigns tends to focus on awareness and support rather than on concrete actions and behaviors. We suggest health communication efforts need to focus on effective messaging and building engaged communities for cancer communication across social media platforms.

  20. Expression and function of the miR-143/145 cluster in vitro and in vivo in human breast cancer.

    Directory of Open Access Journals (Sweden)

    Charles Johannessen

    Full Text Available MicroRNAs (miRNAs are small non-coding RNAs that function as post-transcriptional regulators of gene expression and are dysregulated in cancer. Studies of miRNAs to explore their potential as diagnostic and prognostic markers are of great scientific interest. Here, we investigate the functional properties and expression of the miR-143/145 cluster in breast cancer (BC in vitro and in vivo. The ER positive MCF7, the HER2 positive SK-BR-3, and the triple negative cell line MDA-MB-231 were used to assess cell proliferation and cell invasion. Expression of miRNA in 108 breast cancers in the Norwegian Women and Cancer Study and 44 benign tissue controls were analyzed by microarray and validated by RT-PCR. Further, in situ hybridization (ISH was used to study the cellular and subcellular distribution of the miRNAs. In vitro, miR-143 promoted proliferation of MCF7 and MDA-MB-231 cells, whereas miR-145 and the cotransfection of both miRNAs inhibited proliferation in all three cell lines. The cells' invasive capacity was reduced after transfection and cotransfection of the miRNAs. In line with the tumor suppressive functions in vitro, the expression of miR-143 and miR-145 was lower in malignant compared to benign breast tissue, and lower in the more aggressive tumors with higher tumor grade, loss of ER and the basal-like phenotype. ISH revealed miR-143 to be cytoplasmatic and predominantly expressed in luminal cells in benign tissue, whilst miR-145 was nuclear and with strong staining in myoepithelial cells. Both miRNAs were present in malignant epithelial cells and stromal fibroblasts in BC. This study demonstrates that miR-143 and -145 have functional properties and expression patterns typical for tumor suppressors, but the function is influenced by cellular factors such as cell type and miRNA cotransfection. Further, the nuclear functions of miR-145 should be explored for a more complete understanding of the complexity of miRNA regulation and function

  1. Addressing Burnout in Oncology: Why Cancer Care Clinicians Are At Risk, What Individuals Can Do, and How Organizations Can Respond.

    Science.gov (United States)

    Hlubocky, Fay J; Back, Anthony L; Shanafelt, Tait D

    2016-01-01

    Despite their benevolent care of others, today, more than ever, the cancer care professional who experiences overwhelming feelings of exhaustion, cynicism, and inefficacy is in grave jeopardy of developing burnout. Clinicians are repeatedly physically and emotionally exposed to exceedingly long hours in direct care with seriously ill patients/families, limited autonomy over daily responsibilities, endless electronic documentation, and a shifting medical landscape. The physical and emotional well-being of the cancer care clinician is critical to the impact on quality care, patient satisfaction, and overall success of their organizations. The prevention of burnout as well as targeting established burnout need to be proactively addressed at the individual level and organizational level. In fact, confronting burnout and promoting wellness are the shared responsibility of both oncology clinicians and their organizations. From an individual perspective, oncology clinicians must be empowered to play a crucial role in enhancing their own wellness by identification of burnout symptoms in both themselves and their colleagues, learning resilience strategies (e.g., mindful self-compassion), and cultivating positive relationships with fellow clinician colleagues. At the organizational level, leadership must recognize the importance of oncology clinician well-being; engage leaders and physicians in collaborative action planning, improve overall practice environment, and provide institutional wellness resources to physicians. These effective individual and organizational interventions are crucial for the prevention and improvement of overall clinician wellness and must be widely and systematically integrated into oncology care.

  2. On the absence of radio haloes in clusters with double relics

    Science.gov (United States)

    Bonafede, A.; Cassano, R.; Brüggen, M.; Ogrean, G. A.; Riseley, C. J.; Cuciti, V.; de Gasperin, F.; Golovich, N.; Kale, R.; Venturi, T.; van Weeren, R. J.; Wik, D. R.; Wittman, D.

    2017-09-01

    Pairs of radio relics are believed to form during cluster mergers, and are best observed when the merger occurs in the plane of the sky. Mergers can also produce radio haloes, through complex processes likely linked to turbulent re-acceleration of cosmic ray electrons. However, only some clusters with double relics also show a radio halo. Here, we present a novel method to derive upper limits on the radio halo emission, and analyse archival X-ray Chandra data, as well as galaxy velocity dispersions and lensing data, in order to understand the key parameter that switches on radio halo emission. We place upper limits on the halo power below the P1.4 GHz-M500 correlation for some clusters, confirming that clusters with double relics have different radio properties. Computing X-ray morphological indicators, we find that clusters with double relics are associated with the most disturbed clusters. We also investigate the role of different mass-ratios and time-since-merger. Data do not indicate that the merger mass-ratio has an impact on the presence or absence of radio haloes (the null hypothesis that the clusters belong to the same group cannot be rejected). However, the data suggest that the absence of radio haloes could be associated with early and late mergers, but the sample is too small to perform a statistical test. Our study is limited by the small number of clusters with double relics. Future surveys with LOFAR, ASKAP, MeerKat and SKA will provide larger samples to better address this issue.

  3. Particle Simulation of Oxidation Induced Band 3 Clustering in Human Erythrocytes.

    Directory of Open Access Journals (Sweden)

    Hanae Shimo

    2015-06-01

    Full Text Available Oxidative stress mediated clustering of membrane protein band 3 plays an essential role in the clearance of damaged and aged red blood cells (RBCs from the circulation. While a number of previous experimental studies have observed changes in band 3 distribution after oxidative treatment, the details of how these clusters are formed and how their properties change under different conditions have remained poorly understood. To address these issues, a framework that enables the simultaneous monitoring of the temporal and spatial changes following oxidation is needed. In this study, we established a novel simulation strategy that incorporates deterministic and stochastic reactions with particle reaction-diffusion processes, to model band 3 cluster formation at single molecule resolution. By integrating a kinetic model of RBC antioxidant metabolism with a model of band 3 diffusion, we developed a model that reproduces the time-dependent changes of glutathione and clustered band 3 levels, as well as band 3 distribution during oxidative treatment, observed in prior studies. We predicted that cluster formation is largely dependent on fast reverse reaction rates, strong affinity between clustering molecules, and irreversible hemichrome binding. We further predicted that under repeated oxidative perturbations, clusters tended to progressively grow and shift towards an irreversible state. Application of our model to simulate oxidation in RBCs with cytoskeletal deficiency also suggested that oxidation leads to more enhanced clustering compared to healthy RBCs. Taken together, our model enables the prediction of band 3 spatio-temporal profiles under various situations, thus providing valuable insights to potentially aid understanding mechanisms for removing senescent and premature RBCs.

  4. Particle Simulation of Oxidation Induced Band 3 Clustering in Human Erythrocytes.

    Science.gov (United States)

    Shimo, Hanae; Arjunan, Satya Nanda Vel; Machiyama, Hiroaki; Nishino, Taiko; Suematsu, Makoto; Fujita, Hideaki; Tomita, Masaru; Takahashi, Koichi

    2015-06-01

    Oxidative stress mediated clustering of membrane protein band 3 plays an essential role in the clearance of damaged and aged red blood cells (RBCs) from the circulation. While a number of previous experimental studies have observed changes in band 3 distribution after oxidative treatment, the details of how these clusters are formed and how their properties change under different conditions have remained poorly understood. To address these issues, a framework that enables the simultaneous monitoring of the temporal and spatial changes following oxidation is needed. In this study, we established a novel simulation strategy that incorporates deterministic and stochastic reactions with particle reaction-diffusion processes, to model band 3 cluster formation at single molecule resolution. By integrating a kinetic model of RBC antioxidant metabolism with a model of band 3 diffusion, we developed a model that reproduces the time-dependent changes of glutathione and clustered band 3 levels, as well as band 3 distribution during oxidative treatment, observed in prior studies. We predicted that cluster formation is largely dependent on fast reverse reaction rates, strong affinity between clustering molecules, and irreversible hemichrome binding. We further predicted that under repeated oxidative perturbations, clusters tended to progressively grow and shift towards an irreversible state. Application of our model to simulate oxidation in RBCs with cytoskeletal deficiency also suggested that oxidation leads to more enhanced clustering compared to healthy RBCs. Taken together, our model enables the prediction of band 3 spatio-temporal profiles under various situations, thus providing valuable insights to potentially aid understanding mechanisms for removing senescent and premature RBCs.

  5. Centrosome Clustering in the Development of Bovine Binucleate Trophoblast Giant Cells.

    Science.gov (United States)

    Klisch, Karl; Schraner, Elisabeth M; Boos, Alois

    2017-01-01

    Binucleate trophoblast giant cells (BNC) are the characteristic feature of the ruminant placenta. During their development, BNC pass through 2 acytokinetic mitoses and become binucleate with 2 tetraploid nuclei. In this study, we investigate the number and location of centrosomes in bovine BNC. Centrosomes typically consist of 2 centrioles surrounded by electron-dense pericentriolar material. Duplication of centrosomes is tightly linked to the cell cycle, which ensures that the number of centrosomes remains constant in proliferating diploid cells. Alterations of the cell cycle, which affect the number of chromosome sets, also affect the number of centrosomes. In this study, we use placentomal tissue from pregnant cows (gestational days 80-230) for immunohistochemical staining of γ-tubulin (n = 3) and transmission electron microscopy (n = 3). We show that mature BNC have 4 centrosomes with 8 centrioles, clustered in the angle between the 2 cell nuclei. During the second acytokinetic mitosis, the centrosomes must be clustered to form the poles of a bipolar spindle. In rare cases, centrosome clustering fails and tripolar mitosis leads to the formation of trinucleate "BNC". Generally, centrosome clustering occurs in polyploid tumor cells, which have an increased number of centrioles, but it is absent in proliferating diploid cells. Thus, inhibition of centrosome clustering in tumor cells is a novel promising strategy for cancer treatment. BNC are a cell population in which centrosome clustering occurs as part of the normal life history. Thus, they might be a good model for the study of the molecular mechanisms of centrosome clustering. © 2016 S. Karger AG, Basel.

  6. MUSE integral-field spectroscopy towards the Frontier Fields Cluster Abell S1063

    DEFF Research Database (Denmark)

    Karman, W.; Caputi, K. I.; Grillo, C.

    2015-01-01

    We present the first observations of the Frontier Fields Cluster Abell S1063 taken with the newly commissioned Multi Unit Spectroscopic Explorer (MUSE) integral field spectrograph. Because of the relatively large field of view (1 arcmin^2), MUSE is ideal to simultaneously target multiple galaxies...... the cluster, we find 17 galaxies at higher redshift, including three previously unknown Lyman-alpha emitters at z>3, and five multiply-lensed galaxies. We report the detection of a new z=4.113 multiply lensed galaxy, with images that are consistent with lensing model predictions derived for the Frontier...... of scientific topics that can be addressed with a single MUSE pointing. We conclude that MUSE is a very efficient instrument to observe galaxy clusters, enabling their mass modelling, and to perform a blind search for high-redshift galaxies....

  7. Hox gene cluster of the ascidian, Halocynthia roretzi, reveals multiple ancient steps of cluster disintegration during ascidian evolution.

    Science.gov (United States)

    Sekigami, Yuka; Kobayashi, Takuya; Omi, Ai; Nishitsuji, Koki; Ikuta, Tetsuro; Fujiyama, Asao; Satoh, Noriyuki; Saiga, Hidetoshi

    2017-01-01

    Hox gene clusters with at least 13 paralog group (PG) members are common in vertebrate genomes and in that of amphioxus. Ascidians, which belong to the subphylum Tunicata (Urochordata), are phylogenetically positioned between vertebrates and amphioxus, and traditionally divided into two groups: the Pleurogona and the Enterogona. An enterogonan ascidian, Ciona intestinalis ( Ci ), possesses nine Hox genes localized on two chromosomes; thus, the Hox gene cluster is disintegrated. We investigated the Hox gene cluster of a pleurogonan ascidian, Halocynthia roretzi ( Hr ) to investigate whether Hox gene cluster disintegration is common among ascidians, and if so, how such disintegration occurred during ascidian or tunicate evolution. Our phylogenetic analysis reveals that the Hr Hox gene complement comprises nine members, including one with a relatively divergent Hox homeodomain sequence. Eight of nine Hr Hox genes were orthologous to Ci-Hox1 , 2, 3, 4, 5, 10, 12 and 13. Following the phylogenetic classification into 13 PGs, we designated Hr Hox genes as Hox1, 2, 3, 4, 5, 10, 11/12/13.a , 11/12/13.b and HoxX . To address the chromosomal arrangement of the nine Hox genes, we performed two-color chromosomal fluorescent in situ hybridization, which revealed that the nine Hox genes are localized on a single chromosome in Hr , distinct from their arrangement in Ci . We further examined the order of the nine Hox genes on the chromosome by chromosome/scaffold walking. This analysis suggested a gene order of Hox1 , 11/12/13.b, 11/12/13.a, 10, 5, X, followed by either Hox4, 3, 2 or Hox2, 3, 4 on the chromosome. Based on the present results and those previously reported in Ci , we discuss the establishment of the Hox gene complement and disintegration of Hox gene clusters during the course of ascidian or tunicate evolution. The Hox gene cluster and the genome must have experienced extensive reorganization during the course of evolution from the ancestral tunicate to Hr and Ci

  8. Oriented cluster perforating technology and its application in horizontal wells

    Directory of Open Access Journals (Sweden)

    Huabin Chen

    2016-11-01

    Full Text Available An oriented cluster perforating technology, which integrates both advantages of cluster and oriented perforating, will help solve a series of technical complexities in horizontal well drilling. For realizing its better application in oil and gas development, a series of technologies were developed including perforator self-weight eccentricity, matching of the electronic selective module codes with the surface program control, axial centralized contact signal transmission, and post-perforation intercluster sealing insulation. In this way, the following functions could be realized, such as cable-transmission horizontal well perforator self-weight orientation, dynamic signal transmission, reliable addressing & selective perforation and post-perforation intercluster sealing. The combined perforation and bridge plug or the multi-cluster perforation can be fulfilled in one trip of perforation string. As a result, the horizontal-well oriented cluster perforating technology based on cable conveying was developed. This technology was successfully applied in unconventional gas reservoir exploitation, such as shale gas and coalbed methane, with accurate orientation, reliable selective perforation and satisfactory inter-cluster sealing. The horizontal-well oriented cluster perforating technology benefits the orientation of horizontal well drilling with a definite target and direction, which provides a powerful support for the subsequent reservoir stimulation. It also promotes the fracturing fluid to sweep the principal pay zones to the maximum extent. Moreover, it is conductive to the formation of complex fracture networks in the reservoirs, making quality and efficient development of unconventional gas reservoirs possible.

  9. Discovery of path nearby clusters in spatial networks

    KAUST Repository

    Shang, Shuo

    2015-06-01

    The discovery of regions of interest in large cities is an important challenge. We propose and investigate a novel query called the path nearby cluster (PNC) query that finds regions of potential interest (e.g., sightseeing places and commercial districts) with respect to a user-specified travel route. Given a set of spatial objects O (e.g., POIs, geo-tagged photos, or geo-tagged tweets) and a query route q , if a cluster c has high spatial-object density and is spatially close to q , it is returned by the query (a cluster is a circular region defined by a center and a radius). This query aims to bring important benefits to users in popular applications such as trip planning and location recommendation. Efficient computation of the PNC query faces two challenges: how to prune the search space during query processing, and how to identify clusters with high density effectively. To address these challenges, a novel collective search algorithm is developed. Conceptually, the search process is conducted in the spatial and density domains concurrently. In the spatial domain, network expansion is adopted, and a set of vertices are selected from the query route as expansion centers. In the density domain, clusters are sorted according to their density distributions and they are scanned from the maximum to the minimum. A pair of upper and lower bounds are defined to prune the search space in the two domains globally. The performance of the PNC query is studied in extensive experiments based on real and synthetic spatial data. © 2014 IEEE.

  10. Heterogeneous Gpu&Cpu Cluster For High Performance Computing In Cryptography

    Directory of Open Access Journals (Sweden)

    Michał Marks

    2012-01-01

    Full Text Available This paper addresses issues associated with distributed computing systems andthe application of mixed GPU&CPU technology to data encryption and decryptionalgorithms. We describe a heterogenous cluster HGCC formed by twotypes of nodes: Intel processor with NVIDIA graphics processing unit and AMDprocessor with AMD graphics processing unit (formerly ATI, and a novel softwareframework that hides the heterogeneity of our cluster and provides toolsfor solving complex scientific and engineering problems. Finally, we present theresults of numerical experiments. The considered case study is concerned withparallel implementations of selected cryptanalysis algorithms. The main goal ofthe paper is to show the wide applicability of the GPU&CPU technology tolarge scale computation and data processing.

  11. Channel Parameter Estimation for Scatter Cluster Model Using Modified MUSIC Algorithm

    Directory of Open Access Journals (Sweden)

    Jinsheng Yang

    2012-01-01

    Full Text Available Recently, the scatter cluster models which precisely evaluate the performance of the wireless communication system have been proposed in the literature. However, the conventional SAGE algorithm does not work for these scatter cluster-based models because it performs poorly when the transmit signals are highly correlated. In this paper, we estimate the time of arrival (TOA, the direction of arrival (DOA, and Doppler frequency for scatter cluster model by the modified multiple signal classification (MUSIC algorithm. Using the space-time characteristics of the multiray channel, the proposed algorithm combines the temporal filtering techniques and the spatial smoothing techniques to isolate and estimate the incoming rays. The simulation results indicated that the proposed algorithm has lower complexity and is less time-consuming in the dense multipath environment than SAGE algorithm. Furthermore, the estimations’ performance increases with elements of receive array and samples length. Thus, the problem of the channel parameter estimation of the scatter cluster model can be effectively addressed with the proposed modified MUSIC algorithm.

  12. Clusters and how to make it work : toolkit for cluster strategy

    NARCIS (Netherlands)

    Manickam, Anu; van Berkel, Karel

    2013-01-01

    Clusters are the magic answer to regional economic development. Firms in clusters are more innovative; cluster policy dominates EU policy; ‘top-sectors’ and excellence are the choice of national policy makers; clusters are ‘in’. But, clusters are complex, clusters are ‘messy’; there is no clear

  13. A Survey on the Taxonomy of Cluster-Based Routing Protocols for Homogeneous Wireless Sensor Networks

    Science.gov (United States)

    Naeimi, Soroush; Ghafghazi, Hamidreza; Chow, Chee-Onn; Ishii, Hiroshi

    2012-01-01

    The past few years have witnessed increased interest among researchers in cluster-based protocols for homogeneous networks because of their better scalability and higher energy efficiency than other routing protocols. Given the limited capabilities of sensor nodes in terms of energy resources, processing and communication range, the cluster-based protocols should be compatible with these constraints in either the setup state or steady data transmission state. With focus on these constraints, we classify routing protocols according to their objectives and methods towards addressing the shortcomings of clustering process on each stage of cluster head selection, cluster formation, data aggregation and data communication. We summarize the techniques and methods used in these categories, while the weakness and strength of each protocol is pointed out in details. Furthermore, taxonomy of the protocols in each phase is given to provide a deeper understanding of current clustering approaches. Ultimately based on the existing research, a summary of the issues and solutions of the attributes and characteristics of clustering approaches and some open research areas in cluster-based routing protocols that can be further pursued are provided. PMID:22969350

  14. GOClonto: an ontological clustering approach for conceptualizing PubMed abstracts.

    Science.gov (United States)

    Zheng, Hai-Tao; Borchert, Charles; Kim, Hong-Gee

    2010-02-01

    Concurrent with progress in biomedical sciences, an overwhelming of textual knowledge is accumulating in the biomedical literature. PubMed is the most comprehensive database collecting and managing biomedical literature. To help researchers easily understand collections of PubMed abstracts, numerous clustering methods have been proposed to group similar abstracts based on their shared features. However, most of these methods do not explore the semantic relationships among groupings of documents, which could help better illuminate the groupings of PubMed abstracts. To address this issue, we proposed an ontological clustering method called GOClonto for conceptualizing PubMed abstracts. GOClonto uses latent semantic analysis (LSA) and gene ontology (GO) to identify key gene-related concepts and their relationships as well as allocate PubMed abstracts based on these key gene-related concepts. Based on two PubMed abstract collections, the experimental results show that GOClonto is able to identify key gene-related concepts and outperforms the STC (suffix tree clustering) algorithm, the Lingo algorithm, the Fuzzy Ants algorithm, and the clustering based TRS (tolerance rough set) algorithm. Moreover, the two ontologies generated by GOClonto show significant informative conceptual structures.

  15. Segmentasi Citra USG (Ultrasonography Kanker Payudara Menggunakan Fuzzy C-Means Clustering

    Directory of Open Access Journals (Sweden)

    Ri Munarto

    2018-01-01

    Full Text Available Health is a valuable treasure in survival and can be used as a parameter of quality assurance of human life. Some people even tend to ignore of health, so don’t care about the disease that will them attack and finally to death. Noted the main disease that causes death in the world is cancer. Cancer has many types, but the greatest death in each year is caused by breast cancer. Indonesia found more than 80% of cases in advanced stage, it is estimated that the incidence get 12 people from 10000 women. These numbers will to grow when there is no such treatment as prevention or early diagnosis. Growing of breast cancer patients inversely proportional to the percentage of complaints patients to doctors diagnosis in USG (Ultrasonography breast cancer 20%. The problem is ultrasound imaging which is distorted by speckle noise. The solution is to help easier for doctors to diagnose the presence and form of breast cancer using USG. Speckle noise on USG is able to good reduce using SRAD (Speckle Reducing Anisotropic Diffusion. The filtering results are then well segmented using Fuzzy C-Means Clustering with an accuracy 91.43% of 35 samples USG image breast cancer.

  16. The Heritability of Prostate Cancer in the Nordic Twin Study of Cancer

    DEFF Research Database (Denmark)

    Hjelmborg, Jacob B; Scheike, Thomas; Holst, Klaus

    2014-01-01

    Background: Prostate cancer is thought to be the most heritable cancer, although little is known about how this genetic contribution varies across age. Methods: To address this question, we undertook the world's largest prospective study in the Nordic Twin Study of Cancer cohort, including 18,680....... The role of genetic factors is consistently high across age Impact: Findings impact the search for genetic and epigenetic markers and frame prevention efforts....

  17. A LOOP-BASED APPROACH IN CLUSTERING AND ROUTING IN MOBILE AD HOC NETWORKS

    Institute of Scientific and Technical Information of China (English)

    Li Yanping; Wang Xin; Xue Xiangyang; C.K. Toh

    2006-01-01

    Although clustering is a convenient framework to enable traffic control and service support in Mobile Ad hoc NETworks (MANETs), it is seldom adopted in practice due to the additional traffic overhead it leads to for the resource limited ad hoc network. In order to address this problem, we proposed a loop-based approach to combine clustering and routing. By employing loop topologies, topology information is disseminated with a loop instead of a single node, which provides better robustness, and the nature of a loop that there are two paths between each pair of nodes within a loop suggests smart route recovery strategy. Our approach is composed of setup procedure, regular procedure and recovery procedure to achieve clustering, routing and emergent route recovering.

  18. ICGE: an R package for detecting relevant clusters and atypical units in gene expression

    Directory of Open Access Journals (Sweden)

    Irigoien Itziar

    2012-02-01

    Full Text Available Abstract Background Gene expression technologies have opened up new ways to diagnose and treat cancer and other diseases. Clustering algorithms are a useful approach with which to analyze genome expression data. They attempt to partition the genes into groups exhibiting similar patterns of variation in expression level. An important problem associated with gene classification is to discern whether the clustering process can find a relevant partition as well as the identification of new genes classes. There are two key aspects to classification: the estimation of the number of clusters, and the decision as to whether a new unit (gene, tumor sample... belongs to one of these previously identified clusters or to a new group. Results ICGE is a user-friendly R package which provides many functions related to this problem: identify the number of clusters using mixed variables, usually found by applied biomedical researchers; detect whether the data have a cluster structure; identify whether a new unit belongs to one of the pre-identified clusters or to a novel group, and classify new units into the corresponding cluster. The functions in the ICGE package are accompanied by help files and easy examples to facilitate its use. Conclusions We demonstrate the utility of ICGE by analyzing simulated and real data sets. The results show that ICGE could be very useful to a broad research community.

  19. Investigating role stress in frontline bank employees: A cluster based approach

    Directory of Open Access Journals (Sweden)

    Arti Devi

    2013-09-01

    Full Text Available An effective role stress management programme would benefit from a segmentation of employees based on their experience of role stressors. This study explores role stressor based segments of frontline bank employees towards providing a framework for designing such a programme. Cluster analysis on a random sample of 501 frontline employees of commercial banks in Jammu and Kashmir (India revealed three distinct segments – “overloaded employees”, “unclear employees”, and “underutilised employees”, based on their experience of role stressors. The findings suggest a customised approach to role stress management, with the role stress management programme designed to address cluster specific needs.

  20. Clustering analysis of water distribution systems: identifying critical components and community impacts.

    Science.gov (United States)

    Diao, K; Farmani, R; Fu, G; Astaraie-Imani, M; Ward, S; Butler, D

    2014-01-01

    Large water distribution systems (WDSs) are networks with both topological and behavioural complexity. Thereby, it is usually difficult to identify the key features of the properties of the system, and subsequently all the critical components within the system for a given purpose of design or control. One way is, however, to more explicitly visualize the network structure and interactions between components by dividing a WDS into a number of clusters (subsystems). Accordingly, this paper introduces a clustering strategy that decomposes WDSs into clusters with stronger internal connections than external connections. The detected cluster layout is very similar to the community structure of the served urban area. As WDSs may expand along with urban development in a community-by-community manner, the correspondingly formed distribution clusters may reveal some crucial configurations of WDSs. For verification, the method is applied to identify all the critical links during firefighting for the vulnerability analysis of a real-world WDS. Moreover, both the most critical pipes and clusters are addressed, given the consequences of pipe failure. Compared with the enumeration method, the method used in this study identifies the same group of the most critical components, and provides similar criticality prioritizations of them in a more computationally efficient time.

  1. Determination of atomic cluster structure with cluster fusion algorithm

    DEFF Research Database (Denmark)

    Obolensky, Oleg I.; Solov'yov, Ilia; Solov'yov, Andrey V.

    2005-01-01

    We report an efficient scheme of global optimization, called cluster fusion algorithm, which has proved its reliability and high efficiency in determination of the structure of various atomic clusters.......We report an efficient scheme of global optimization, called cluster fusion algorithm, which has proved its reliability and high efficiency in determination of the structure of various atomic clusters....

  2. Large-Scale Multi-Dimensional Document Clustering on GPU Clusters

    Energy Technology Data Exchange (ETDEWEB)

    Cui, Xiaohui [ORNL; Mueller, Frank [North Carolina State University; Zhang, Yongpeng [ORNL; Potok, Thomas E [ORNL

    2010-01-01

    Document clustering plays an important role in data mining systems. Recently, a flocking-based document clustering algorithm has been proposed to solve the problem through simulation resembling the flocking behavior of birds in nature. This method is superior to other clustering algorithms, including k-means, in the sense that the outcome is not sensitive to the initial state. One limitation of this approach is that the algorithmic complexity is inherently quadratic in the number of documents. As a result, execution time becomes a bottleneck with large number of documents. In this paper, we assess the benefits of exploiting the computational power of Beowulf-like clusters equipped with contemporary Graphics Processing Units (GPUs) as a means to significantly reduce the runtime of flocking-based document clustering. Our framework scales up to over one million documents processed simultaneously in a sixteennode GPU cluster. Results are also compared to a four-node cluster with higher-end GPUs. On these clusters, we observe 30X-50X speedups, which demonstrates the potential of GPU clusters to efficiently solve massive data mining problems. Such speedups combined with the scalability potential and accelerator-based parallelization are unique in the domain of document-based data mining, to the best of our knowledge.

  3. Membership determination of open clusters based on a spectral clustering method

    Science.gov (United States)

    Gao, Xin-Hua

    2018-06-01

    We present a spectral clustering (SC) method aimed at segregating reliable members of open clusters in multi-dimensional space. The SC method is a non-parametric clustering technique that performs cluster division using eigenvectors of the similarity matrix; no prior knowledge of the clusters is required. This method is more flexible in dealing with multi-dimensional data compared to other methods of membership determination. We use this method to segregate the cluster members of five open clusters (Hyades, Coma Ber, Pleiades, Praesepe, and NGC 188) in five-dimensional space; fairly clean cluster members are obtained. We find that the SC method can capture a small number of cluster members (weak signal) from a large number of field stars (heavy noise). Based on these cluster members, we compute the mean proper motions and distances for the Hyades, Coma Ber, Pleiades, and Praesepe clusters, and our results are in general quite consistent with the results derived by other authors. The test results indicate that the SC method is highly suitable for segregating cluster members of open clusters based on high-precision multi-dimensional astrometric data such as Gaia data.

  4. Soft and diffractive scattering with the cluster model in Herwig

    Energy Technology Data Exchange (ETDEWEB)

    Gieseke, Stefan; Loshaj, Frasher; Kirchgaesser, Patrick [Karlsruhe Institute of Technology, Institute for Theoretical Physics, Karlsruhe (Germany)

    2017-03-15

    We present a new model for soft interactions in the event-generator Herwig. The model consists of two components. One to model diffractive final states on the basis of the cluster hadronization model and a second component that addresses soft multiple interactions as multiple particle production in multiperipheral kinematics. We present much improved results for minimum-bias measurements at various LHC energies. (orig.)

  5. Group sequential designs for stepped-wedge cluster randomised trials.

    Science.gov (United States)

    Grayling, Michael J; Wason, James Ms; Mander, Adrian P

    2017-10-01

    The stepped-wedge cluster randomised trial design has received substantial attention in recent years. Although various extensions to the original design have been proposed, no guidance is available on the design of stepped-wedge cluster randomised trials with interim analyses. In an individually randomised trial setting, group sequential methods can provide notable efficiency gains and ethical benefits. We address this by discussing how established group sequential methodology can be adapted for stepped-wedge designs. Utilising the error spending approach to group sequential trial design, we detail the assumptions required for the determination of stepped-wedge cluster randomised trials with interim analyses. We consider early stopping for efficacy, futility, or efficacy and futility. We describe first how this can be done for any specified linear mixed model for data analysis. We then focus on one particular commonly utilised model and, using a recently completed stepped-wedge cluster randomised trial, compare the performance of several designs with interim analyses to the classical stepped-wedge design. Finally, the performance of a quantile substitution procedure for dealing with the case of unknown variance is explored. We demonstrate that the incorporation of early stopping in stepped-wedge cluster randomised trial designs could reduce the expected sample size under the null and alternative hypotheses by up to 31% and 22%, respectively, with no cost to the trial's type-I and type-II error rates. The use of restricted error maximum likelihood estimation was found to be more important than quantile substitution for controlling the type-I error rate. The addition of interim analyses into stepped-wedge cluster randomised trials could help guard against time-consuming trials conducted on poor performing treatments and also help expedite the implementation of efficacious treatments. In future, trialists should consider incorporating early stopping of some kind into

  6. Health-related hot topic detection in online communities using text clustering.

    Directory of Open Access Journals (Sweden)

    Yingjie Lu

    Full Text Available Recently, health-related social media services, especially online health communities, have rapidly emerged. Patients with various health conditions participate in online health communities to share their experiences and exchange healthcare knowledge. Exploring hot topics in online health communities helps us better understand patients' needs and interest in health-related knowledge. However, the statistical topic analysis employed in previous studies is becoming impractical for processing the rapidly increasing amount of online data. Automatic topic detection based on document clustering is an alternative approach for extracting health-related hot topics in online communities. In addition to the keyword-based features used in traditional text clustering, we integrate medical domain-specific features to represent the messages posted in online health communities. Three disease discussion boards, including boards devoted to lung cancer, breast cancer and diabetes, from an online health community are used to test the effectiveness of topic detection. Experiment results demonstrate that health-related hot topics primarily include symptoms, examinations, drugs, procedures and complications. Further analysis reveals that there also exist some significant differences among the hot topics discussed on different types of disease discussion boards.

  7. Cluster headache

    Science.gov (United States)

    Histamine headache; Headache - histamine; Migrainous neuralgia; Headache - cluster; Horton's headache; Vascular headache - cluster ... Doctors do not know exactly what causes cluster headaches. They ... (chemical in the body released during an allergic response) or ...

  8. Spectroscopic constraints on the form of the stellar cluster mass function

    Science.gov (United States)

    Bastian, N.; Konstantopoulos, I. S.; Trancho, G.; Weisz, D. R.; Larsen, S. S.; Fouesneau, M.; Kaschinski, C. B.; Gieles, M.

    2012-05-01

    This contribution addresses the question of whether the initial cluster mass function (ICMF) has a fundamental limit (or truncation) at high masses. The shape of the ICMF at high masses can be studied using the most massive young (advantages are that more clusters can be used and that the ICMF leaves a distinct pattern on the global relation between the cluster luminosity and median age within a population. If a truncation is present, a generic prediction (nearly independent of the cluster disruption law adopted) is that the median age of bright clusters should be younger than that of fainter clusters. In the case of an non-truncated ICMF, the median age should be independent of cluster luminosity. Here, we present optical spectroscopy of twelve young stellar clusters in the face-on spiral galaxy NGC 2997. The spectra are used to estimate the age of each cluster, and the brightness of the clusters is taken from the literature. The observations are compared with the model expectations of Larsen (2009, A&A, 494, 539) for various ICMF forms and both mass dependent and mass independent cluster disruption. While there exists some degeneracy between the truncation mass and the amount of mass independent disruption, the observations favour a truncated ICMF. For low or modest amounts of mass independent disruption, a truncation mass of 5-6 × 105 M⊙ is estimated, consistent with previous determinations. Additionally, we investigate possible truncations in the ICMF in the spiral galaxy M 83, the interacting Antennae galaxies, and the collection of spiral and dwarf galaxies present in Larsen (2009, A&A, 494, 539) based on photometric catalogues taken from the literature, and find that all catalogues are consistent with having a truncation in the cluster mass functions. However for the case of the Antennae, we find a truncation mass of a few × 106M⊙ , suggesting a dependence on the environment, as has been previously suggested.

  9. Cancer Trends: Influencing Care and Research Priorities

    Science.gov (United States)

    Many of the trends being seen in cancer are changing how we view cancer and how we address it, from prompting research to identify the underlying causes of cancers increasing in incidence to informing research on treatment and prevention.

  10. Evaluation of community level interventions to address social and structural determinants of health: a cluster randomised controlled trial

    Directory of Open Access Journals (Sweden)

    Draper Alizon

    2009-06-01

    Full Text Available Abstract Background In London and the rest of the UK, diseases associated with poor diet, inadequate physical activity and mental illness account for a large proportion of area based health inequality. There is a lack of evidence on interventions promoting healthier behaviours especially in marginalised populations, at a structural or ecological level and utilising a community development approach. The Well London project financed by the Big Lottery 'Wellbeing' Fund and implemented by a consortium of London based agencies led by the Greater London Authority and the London Health Commission is implementing a set of complex interventions across 20 deprived areas of London. The interventions focus on healthy eating, healthy physical activity and mental health and wellbeing and are designed and executed with community participation complementing existing facilities and services. Methods/Design The programme will be evaluated through a cluster randomised controlled trial. Forty areas across London were chosen based on deprivation scores. Areas were characterised by high proportion of Black and Minority Ethnic residents, worklessness, ill-health and poor physical environments. Twenty areas were randomly assigned to the intervention arm of Well London project and twenty 'matched' areas assigned as controls. Measures of physical activity, diet and mental health are collected at start and end of the project and compared to assess impact. The quantitative element will be complemented by a longitudinal qualitative study elucidating pathways of influence between intervention activities and health outcomes. A related element of the study investigates the health-related aspects of the structural and ecological characteristics of the project areas. The project 'process' will also be evaluated. Discussion The size of the project and the fact that the interventions are 'complex' in the sense that firstly, there are a number of interacting components with a wide

  11. Clustering gene expression regulators: new approach to disease subtyping.

    Directory of Open Access Journals (Sweden)

    Mikhail Pyatnitskiy

    Full Text Available One of the main challenges in modern medicine is to stratify different patient groups in terms of underlying disease molecular mechanisms as to develop more personalized approach to therapy. Here we propose novel method for disease subtyping based on analysis of activated expression regulators on a sample-by-sample basis. Our approach relies on Sub-Network Enrichment Analysis algorithm (SNEA which identifies gene subnetworks with significant concordant changes in expression between two conditions. Subnetwork consists of central regulator and downstream genes connected by relations extracted from global literature-extracted regulation database. Regulators found in each patient separately are clustered together and assigned activity scores which are used for final patients grouping. We show that our approach performs well compared to other related methods and at the same time provides researchers with complementary level of understanding of pathway-level biology behind a disease by identification of significant expression regulators. We have observed the reasonable grouping of neuromuscular disorders (triggered by structural damage vs triggered by unknown mechanisms, that was not revealed using standard expression profile clustering. For another experiment we were able to suggest the clusters of regulators, responsible for colorectal carcinoma vs adenoma discrimination and identify frequently genetically changed regulators that could be of specific importance for the individual characteristics of cancer development. Proposed approach can be regarded as biologically meaningful feature selection, reducing tens of thousands of genes down to dozens of clusters of regulators. Obtained clusters of regulators make possible to generate valuable biological hypotheses about molecular mechanisms related to a clinical outcome for individual patient.

  12. Ant Colony Optimization Approaches to Clustering of Lung Nodules from CT Images

    Directory of Open Access Journals (Sweden)

    Ravichandran C. Gopalakrishnan

    2014-01-01

    Full Text Available Lung cancer is becoming a threat to mankind. Applying machine learning algorithms for detection and segmentation of irregular shaped lung nodules remains a remarkable milestone in CT scan image analysis research. In this paper, we apply ACO algorithm for lung nodule detection. We have compared the performance against three other algorithms, namely, Otsu algorithm, watershed algorithm, and global region based segmentation. In addition, we suggest a novel approach which involves variations of ACO, namely, refined ACO, logical ACO, and variant ACO. Variant ACO shows better reduction in false positives. In addition we propose black circular neighborhood approach to detect nodule centers from the edge detected image. Genetic algorithm based clustering is performed to cluster the nodules based on intensity, shape, and size. The performance of the overall approach is compared with hierarchical clustering to establish the improvisation in the proposed approach.

  13. Efficient Record Linkage Algorithms Using Complete Linkage Clustering.

    Science.gov (United States)

    Mamun, Abdullah-Al; Aseltine, Robert; Rajasekaran, Sanguthevar

    2016-01-01

    Data from different agencies share data of the same individuals. Linking these datasets to identify all the records belonging to the same individuals is a crucial and challenging problem, especially given the large volumes of data. A large number of available algorithms for record linkage are prone to either time inefficiency or low-accuracy in finding matches and non-matches among the records. In this paper we propose efficient as well as reliable sequential and parallel algorithms for the record linkage problem employing hierarchical clustering methods. We employ complete linkage hierarchical clustering algorithms to address this problem. In addition to hierarchical clustering, we also use two other techniques: elimination of duplicate records and blocking. Our algorithms use sorting as a sub-routine to identify identical copies of records. We have tested our algorithms on datasets with millions of synthetic records. Experimental results show that our algorithms achieve nearly 100% accuracy. Parallel implementations achieve almost linear speedups. Time complexities of these algorithms do not exceed those of previous best-known algorithms. Our proposed algorithms outperform previous best-known algorithms in terms of accuracy consuming reasonable run times.

  14. A Comparison Study on Similarity and Dissimilarity Measures in Clustering Continuous Data.

    Directory of Open Access Journals (Sweden)

    Ali Seyed Shirkhorshidi

    Full Text Available Similarity or distance measures are core components used by distance-based clustering algorithms to cluster similar data points into the same clusters, while dissimilar or distant data points are placed into different clusters. The performance of similarity measures is mostly addressed in two or three-dimensional spaces, beyond which, to the best of our knowledge, there is no empirical study that has revealed the behavior of similarity measures when dealing with high-dimensional datasets. To fill this gap, a technical framework is proposed in this study to analyze, compare and benchmark the influence of different similarity measures on the results of distance-based clustering algorithms. For reproducibility purposes, fifteen publicly available datasets were used for this study, and consequently, future distance measures can be evaluated and compared with the results of the measures discussed in this work. These datasets were classified as low and high-dimensional categories to study the performance of each measure against each category. This research should help the research community to identify suitable distance measures for datasets and also to facilitate a comparison and evaluation of the newly proposed similarity or distance measures with traditional ones.

  15. A Novel Energy-Aware Distributed Clustering Algorithm for Heterogeneous Wireless Sensor Networks in the Mobile Environment.

    Science.gov (United States)

    Gao, Ying; Wkram, Chris Hadri; Duan, Jiajie; Chou, Jarong

    2015-12-10

    In order to prolong the network lifetime, energy-efficient protocols adapted to the features of wireless sensor networks should be used. This paper explores in depth the nature of heterogeneous wireless sensor networks, and finally proposes an algorithm to address the problem of finding an effective pathway for heterogeneous clustering energy. The proposed algorithm implements cluster head selection according to the degree of energy attenuation during the network's running and the degree of candidate nodes' effective coverage on the whole network, so as to obtain an even energy consumption over the whole network for the situation with high degree of coverage. Simulation results show that the proposed clustering protocol has better adaptability to heterogeneous environments than existing clustering algorithms in prolonging the network lifetime.

  16. Comparative Investigation of Shared Filesystems for the LHCb Online Cluster

    International Nuclear Information System (INIS)

    Vijay Kartik, S; Neufeld, Niko

    2012-01-01

    This paper describes the investigative study undertaken to evaluate shared filesystem performance and suitability in the LHCb Online environment. Particular focus is given to the measurements and field tests designed and performed on an in-house OpenAFS setup; related comparisons with NFSv4 and GPFS (a clustered filesystem from IBM) are presented. The motivation for the investigation and the test setup arises from the need to serve common user-space like home directories, experiment software and control areas, and clustered log areas. Since the operational requirements on such user-space are stringent in terms of read-write operations (in frequency and access speed) and unobtrusive data relocation, test results are presented with emphasis on file-level performance, stability and “high-availability” of the shared filesystems. Use cases specific to the experiment operation in LHCb, including the specific handling of shared filesystems served to a cluster of 1500 diskless nodes, are described. Issues of prematurely expiring authenticated sessions are explicitly addressed, keeping in mind long-running analysis jobs on the Online cluster. In addition, quantitative test results are also presented with alternatives including NFSv4. Comparative measurements of filesystem performance benchmarks are presented, which are seen to be used as reference for decisions on potential migration of the current storage solution deployed in the LHCb online cluster.

  17. Single-cluster dynamics for the random-cluster model

    NARCIS (Netherlands)

    Deng, Y.; Qian, X.; Blöte, H.W.J.

    2009-01-01

    We formulate a single-cluster Monte Carlo algorithm for the simulation of the random-cluster model. This algorithm is a generalization of the Wolff single-cluster method for the q-state Potts model to noninteger values q>1. Its results for static quantities are in a satisfactory agreement with those

  18. Targeted Alpha Therapy Approach to the Management of Pancreatic Cancer

    International Nuclear Information System (INIS)

    Allen, Barry J.; Abbas Rizvi, Syed M.; Qu, Chang F.; Smith, Ross C.

    2011-01-01

    Evidence for the efficacy of targeted alpha therapy for the control of pancreatic cancer in preclinical models is reviewed. Results are given for in vitro pancreatic cancer cells and clusters and micro-metastatic cancer lesions in vivo. Two complementary targeting vectors are examined. These are the C595 monoclonal antibody that targets the MUC1 antigen and the PAI2 ligand that targets the uPA receptor. The expression of the tumor-associated antigen MUC-1 and the uPA receptor on three pancreatic cancer cell lines is reported for cell clusters, human mouse xenografts and lymph node metastases, as well as for human pancreatic cancer tissues, using immuno-histochemistry, confocal microscopy and flow cytometry. The targeting vectors C595 and PAI2 were labeled with the alpha emitting radioisotope 213 Bi using the chelators cDTPA and CHX-A″ to form the alpha-conjugates (AC). Cell clusters were incubated with the AC and examined at 48 hours. Apoptosis was documented using the TUNEL assay. In vivo, the anti-proliferative effect for tumors was tested at two days post-subcutaneous cell inoculation. Mice were injected with different concentrations of AC by local or systemic administration. Changes in tumor progression were assessed by tumor size. MUC-1 and uPA are strongly expressed on CFPAC-1, PANC-1 and moderate expression was found CAPAN-1 cell clusters and tumor xenografts. The ACs can target pancreatic cells and regress cell clusters (∼100 μm diameter), causing apoptosis in some 70–90 % of cells. At two days post-cell inoculation in mice, a single local injection of 74 MBq/kg of AC causes complete inhibition of tumor growth. Systemic injections of 111, 222 and 333 MBq/kg of alpha-conjugate caused significant tumor growth delay in a dose dependent manner after 16 weeks, compared with the non-specific control at 333 MBq/kg. Cytotoxicity was assessed by the MTS and TUNEL assays. The C595 and PAI2-alpha conjugates are indicated for the treatment of micro

  19. Cluster Analysis of the Newcastle Electronic Corpus of Tyneside English: A Comparison of Methods

    NARCIS (Netherlands)

    Moisl, Hermann; Jones, Valerie M.

    2005-01-01

    This article examines the feasibility of an empirical approach to sociolinguistic analysis of the Newcastle Electronic Corpus of Tyneside English using exploratory multivariate methods. It addresses a known problem with one class of such methods, hierarchical cluster analysis—that different

  20. Reducing confounding and suppression effects in TCGA data: an integrated analysis of chemotherapy response in ovarian cancer

    Directory of Open Access Journals (Sweden)

    Hsu Fang-Han

    2012-10-01

    Full Text Available Abstract Background Despite initial response in adjuvant chemotherapy, ovarian cancer patients treated with the combination of paclitaxel and carboplatin frequently suffer from recurrence after few cycles of treatment, and the underlying mechanisms causing the chemoresistance remain unclear. Recently, The Cancer Genome Atlas (TCGA research network concluded an ovarian cancer study and released the dataset to the public. The TCGA dataset possesses large sample size, comprehensive molecular profiles, and clinical outcome information; however, because of the unknown molecular subtypes in ovarian cancer and the great diversity of adjuvant treatments TCGA patients went through, studying chemotherapeutic response using the TCGA data is difficult. Additionally, factors such as sample batches, patient ages, and tumor stages further confound or suppress the identification of relevant genes, and thus the biological functions and disease mechanisms. Results To address these issues, herein we propose an analysis procedure designed to reduce suppression effect by focusing on a specific chemotherapeutic treatment, and to remove confounding effects such as batch effect, patient's age, and tumor stages. The proposed procedure starts with a batch effect adjustment, followed by a rigorous sample selection process. Then, the gene expression, copy number, and methylation profiles from the TCGA ovarian cancer dataset are analyzed using a semi-supervised clustering method combined with a novel scoring function. As a result, two molecular classifications, one with poor copy number profiles and one with poor methylation profiles, enriched with unfavorable scores are identified. Compared with the samples enriched with favorable scores, these two classifications exhibit poor progression-free survival (PFS and might be associated with poor chemotherapy response specifically to the combination of paclitaxel and carboplatin. Significant genes and biological processes are

  1. Occupational asbestos exposure and risk of pleural mesothelioma, lung cancer, and laryngeal cancer in the prospective netherlands cohort study

    NARCIS (Netherlands)

    Offermans, N.S.M.; Vermeulen, R.; Burdorf, A.; Goldbohm, R.A.; Kauppinen, T.; Kromhout, H.; Brandt, P.A. van den

    2014-01-01

    OBJECTIVE:: To study the association between occupational asbestos exposure and pleural mesothelioma, lung cancer, and laryngeal cancer, specifically addressing risk associated with the lower end of the exposure distribution, risk of cancer subtypes, and the interaction between asbestos and smoking.

  2. clusterMaker: a multi-algorithm clustering plugin for Cytoscape

    Directory of Open Access Journals (Sweden)

    Morris John H

    2011-11-01

    Full Text Available Abstract Background In the post-genomic era, the rapid increase in high-throughput data calls for computational tools capable of integrating data of diverse types and facilitating recognition of biologically meaningful patterns within them. For example, protein-protein interaction data sets have been clustered to identify stable complexes, but scientists lack easily accessible tools to facilitate combined analyses of multiple data sets from different types of experiments. Here we present clusterMaker, a Cytoscape plugin that implements several clustering algorithms and provides network, dendrogram, and heat map views of the results. The Cytoscape network is linked to all of the other views, so that a selection in one is immediately reflected in the others. clusterMaker is the first Cytoscape plugin to implement such a wide variety of clustering algorithms and visualizations, including the only implementations of hierarchical clustering, dendrogram plus heat map visualization (tree view, k-means, k-medoid, SCPS, AutoSOME, and native (Java MCL. Results Results are presented in the form of three scenarios of use: analysis of protein expression data using a recently published mouse interactome and a mouse microarray data set of nearly one hundred diverse cell/tissue types; the identification of protein complexes in the yeast Saccharomyces cerevisiae; and the cluster analysis of the vicinal oxygen chelate (VOC enzyme superfamily. For scenario one, we explore functionally enriched mouse interactomes specific to particular cellular phenotypes and apply fuzzy clustering. For scenario two, we explore the prefoldin complex in detail using both physical and genetic interaction clusters. For scenario three, we explore the possible annotation of a protein as a methylmalonyl-CoA epimerase within the VOC superfamily. Cytoscape session files for all three scenarios are provided in the Additional Files section. Conclusions The Cytoscape plugin cluster

  3. Identifying Determinants of PARP Inhibitor Sensitivity in Ovarian Cancer

    Science.gov (United States)

    2017-10-01

    Cancer Center Philadelphia, PA 19111 REPORT DATE: TYPE OF REPORT: Annual PREPARED FOR: U.S. Army Medical Research and Materiel Command Fort Detrick...in Ovarian Cancer October 2017 The views, opinions and/or findings contained in this report are those of the author(s) and should not be construed...ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT NUMBER The Research Institute of Fox Chase Cancer Center 333 Cottman Avenue Philadelphia

  4. NeatMap--non-clustering heat map alternatives in R.

    Science.gov (United States)

    Rajaram, Satwik; Oono, Yoshi

    2010-01-22

    The clustered heat map is the most popular means of visualizing genomic data. It compactly displays a large amount of data in an intuitive format that facilitates the detection of hidden structures and relations in the data. However, it is hampered by its use of cluster analysis which does not always respect the intrinsic relations in the data, often requiring non-standardized reordering of rows/columns to be performed post-clustering. This sometimes leads to uninformative and/or misleading conclusions. Often it is more informative to use dimension-reduction algorithms (such as Principal Component Analysis and Multi-Dimensional Scaling) which respect the topology inherent in the data. Yet, despite their proven utility in the analysis of biological data, they are not as widely used. This is at least partially due to the lack of user-friendly visualization methods with the visceral impact of the heat map. NeatMap is an R package designed to meet this need. NeatMap offers a variety of novel plots (in 2 and 3 dimensions) to be used in conjunction with these dimension-reduction techniques. Like the heat map, but unlike traditional displays of such results, it allows the entire dataset to be displayed while visualizing relations between elements. It also allows superimposition of cluster analysis results for mutual validation. NeatMap is shown to be more informative than the traditional heat map with the help of two well-known microarray datasets. NeatMap thus preserves many of the strengths of the clustered heat map while addressing some of its deficiencies. It is hoped that NeatMap will spur the adoption of non-clustering dimension-reduction algorithms.

  5. Relevant Subspace Clustering

    DEFF Research Database (Denmark)

    Müller, Emmanuel; Assent, Ira; Günnemann, Stephan

    2009-01-01

    Subspace clustering aims at detecting clusters in any subspace projection of a high dimensional space. As the number of possible subspace projections is exponential in the number of dimensions, the result is often tremendously large. Recent approaches fail to reduce results to relevant subspace...... clusters. Their results are typically highly redundant, i.e. many clusters are detected multiple times in several projections. In this work, we propose a novel model for relevant subspace clustering (RESCU). We present a global optimization which detects the most interesting non-redundant subspace clusters...... achieves top clustering quality while competing approaches show greatly varying performance....

  6. Horticultural cluster

    OpenAIRE

    SHERSTIUK S.V.; POSYLAYEVA K.I.

    2013-01-01

    In the article there are the theoretical and methodological approaches to the nature and existence of the cluster. The cluster differences from other kinds of cooperative and integration associations. Was develop by scientific-practical recommendations for forming a competitive horticultur cluster.

  7. The effectiveness of the Screening Inventory of Psychosocial Problems (SIPP) in cancer patients treated with radiotherapy: design of a cluster randomised controlled trial

    International Nuclear Information System (INIS)

    Braeken, Anna PBM; Lechner, Lilian; Gils, Francis CJM van; Houben, Ruud MA; Eekers, Daniëlle; Ambergen, Ton; Kempen, Gertrudis IJM

    2009-01-01

    The Screening Inventory of Psychosocial Problems (SIPP) is a short, validated self-reported questionnaire to identify psychosocial problems in Dutch cancer patients. The one-page 24-item questionnaire assesses physical complaints, psychological complaints and social and sexual problems. Very little is known about the effects of using the SIPP in consultation settings. Our study aims are to test the hypotheses that using the SIPP (a) may contribute to adequate referral to relevant psychosocial caregivers, (b) should facilitate communication between radiotherapists and cancer patients about psychosocial distress and (c) may prevent underdiagnosis of early symptoms reflecting psychosocial problems. This paper presents the design of a cluster randomised controlled trial (CRCT) evaluating the effectiveness of using the SIPP in cancer patients treated with radiotherapy. A CRCT is developed using a Solomon four-group design (two intervention and two control groups) to evaluate the effects of using the SIPP. Radiotherapists, instead of cancer patients, are randomly allocated to the experimental or control groups. Within these groups, all included cancer patients are randomised into two subgroups: with and without pre-measurement. Self-reported assessments are conducted at four times: a pre-test at baseline before the first consultation and a post-test directly following the first consultation, and three and 12 months after baseline measurement. The primary outcome measures are the number and types of referrals of cancer patients with psychosocial problems to relevant (psychosocial) caregivers. The secondary outcome measures are patients' satisfaction with the radiotherapist-patient communication, psychosocial distress and quality of life. Furthermore, a process evaluation will be carried out. Data of the effect-evaluation will be analysed according to the intention-to-treat principle and data regarding the types of referrals to health care providers and patient

  8. Applying evolutionary biology to address global challenges

    Science.gov (United States)

    Carroll, Scott P.; Jørgensen, Peter Søgaard; Kinnison, Michael T.; Bergstrom, Carl T.; Denison, R. Ford; Gluckman, Peter; Smith, Thomas B.; Strauss, Sharon Y.; Tabashnik, Bruce E.

    2014-01-01

    Two categories of evolutionary challenges result from escalating human impacts on the planet. The first arises from cancers, pathogens and pests that evolve too quickly, and the second from the inability of many valued species to adapt quickly enough. Applied evolutionary biology provides a suite of strategies to address these global challenges that threaten human health, food security, and biodiversity. This review highlights both progress and gaps in genetic, developmental and environmental manipulations across the life sciences that either target the rate and direction of evolution, or reduce the mismatch between organisms and human-altered environments. Increased development and application of these underused tools will be vital in meeting current and future targets for sustainable development. PMID:25213376

  9. TreeCluster: Massively scalable transmission clustering using phylogenetic trees

    OpenAIRE

    Moshiri, Alexander

    2018-01-01

    Background: The ability to infer transmission clusters from molecular data is critical to designing and evaluating viral control strategies. Viral sequencing datasets are growing rapidly, but standard methods of transmission cluster inference do not scale well beyond thousands of sequences. Results: I present TreeCluster, a cross-platform tool that performs transmission cluster inference on a given phylogenetic tree orders of magnitude faster than existing inference methods and supports multi...

  10. Development of a community-based participatory colorectal cancer screening intervention to address disparities, Arkansas, 2008-2009.

    Science.gov (United States)

    Yeary, Karen; Flowers, Eric; Ford, Gemessia; Burroughs, Desiree; Burton, Jackie; Woods, Delores; Stewart, Chara; Mehta, Paulette; Greene, Paul; Henry-Tillman, Ronda

    2011-03-01

    The death rate from colorectal cancer is high and affects poor and medically underserved populations disproportionately. In the United States, health disparities are particularly acute in the Lower Mississippi River Delta region. Because many in the region have limited access to basic health care resources, they are not screened for cancer, even though screening is one of the most effective strategies to prevent colorectal cancer. Community-based participatory research is a promising approach to prevent colorectal cancer in this population. The Empowering Communities for Life program was implemented in 2 underserved counties in the Arkansas Lower Mississippi River Delta. The program arose from a 9-year partnership between the University of Arkansas for Medical Sciences and 9 cancer councils across Arkansas. Empowering Communities for Life is a community-based participatory intervention designed to increase colorectal cancer screening in rural, underserved communities through fecal occult blood testing. Community and academic partners collaborated to develop research infrastructure, intervention materials and methods, and the assessment instrument. Project outcomes were strengthened community-academic partnerships, certification of community partners in conducting human subjects research, development of a randomized controlled design to test the intervention's efficacy, an interactive PowerPoint presentation, an informational pamphlet, the certification of 6 lay health advisors and 22 role models to provide the intervention, and an assessment tool using an audience response system. Lessons learned in working collaboratively with diverse groups include the importance of meeting face to face and listening.

  11. Voting-based consensus clustering for combining multiple clusterings of chemical structures

    Directory of Open Access Journals (Sweden)

    Saeed Faisal

    2012-12-01

    Full Text Available Abstract Background Although many consensus clustering methods have been successfully used for combining multiple classifiers in many areas such as machine learning, applied statistics, pattern recognition and bioinformatics, few consensus clustering methods have been applied for combining multiple clusterings of chemical structures. It is known that any individual clustering method will not always give the best results for all types of applications. So, in this paper, three voting and graph-based consensus clusterings were used for combining multiple clusterings of chemical structures to enhance the ability of separating biologically active molecules from inactive ones in each cluster. Results The cumulative voting-based aggregation algorithm (CVAA, cluster-based similarity partitioning algorithm (CSPA and hyper-graph partitioning algorithm (HGPA were examined. The F-measure and Quality Partition Index method (QPI were used to evaluate the clusterings and the results were compared to the Ward’s clustering method. The MDL Drug Data Report (MDDR dataset was used for experiments and was represented by two 2D fingerprints, ALOGP and ECFP_4. The performance of voting-based consensus clustering method outperformed the Ward’s method using F-measure and QPI method for both ALOGP and ECFP_4 fingerprints, while the graph-based consensus clustering methods outperformed the Ward’s method only for ALOGP using QPI. The Jaccard and Euclidean distance measures were the methods of choice to generate the ensembles, which give the highest values for both criteria. Conclusions The results of the experiments show that consensus clustering methods can improve the effectiveness of chemical structures clusterings. The cumulative voting-based aggregation algorithm (CVAA was the method of choice among consensus clustering methods.

  12. GRISEOFULVIN ANALOGUES FOR THE TREATMENT OF CANCER BY INHIBITION OF CENTROSOMAL CLUSTERING

    DEFF Research Database (Denmark)

    2010-01-01

    The invention relates to compounds of the formula (I), where the symbols have the meaning given in the specification, for use in a method for treating cancer, to use of these compounds for the manufacture of a pharmaceutical composition for the treatment of cancer, and to methods of treatment...

  13. OBSERVED SCALING RELATIONS FOR STRONG LENSING CLUSTERS: CONSEQUENCES FOR COSMOLOGY AND CLUSTER ASSEMBLY

    International Nuclear Information System (INIS)

    Comerford, Julia M.; Moustakas, Leonidas A.; Natarajan, Priyamvada

    2010-01-01

    Scaling relations of observed galaxy cluster properties are useful tools for constraining cosmological parameters as well as cluster formation histories. One of the key cosmological parameters, σ 8 , is constrained using observed clusters of galaxies, although current estimates of σ 8 from the scaling relations of dynamically relaxed galaxy clusters are limited by the large scatter in the observed cluster mass-temperature (M-T) relation. With a sample of eight strong lensing clusters at 0.3 8 , but combining the cluster concentration-mass relation with the M-T relation enables the inclusion of unrelaxed clusters as well. Thus, the resultant gains in the accuracy of σ 8 measurements from clusters are twofold: the errors on σ 8 are reduced and the cluster sample size is increased. Therefore, the statistics on σ 8 determination from clusters are greatly improved by the inclusion of unrelaxed clusters. Exploring cluster scaling relations further, we find that the correlation between brightest cluster galaxy (BCG) luminosity and cluster mass offers insight into the assembly histories of clusters. We find preliminary evidence for a steeper BCG luminosity-cluster mass relation for strong lensing clusters than the general cluster population, hinting that strong lensing clusters may have had more active merging histories.

  14. Cytologic studies on irradiated gestric cancer cells

    Energy Technology Data Exchange (ETDEWEB)

    Isono, S; Takeda, T; Amakasu, H; Asakawa, H; Yamada, S [Miyagi Prefectural Adult Disease Center, Natori (Japan)

    1981-06-01

    The smears of the biopsy and resected specimens obtained from 74 cases of irradiated gastric cancer were cytologically analyzed for effects of irradiation. Irradiation increased the amount of both necrotic materials and neutrophils in the smears. Cancer cells were decreased in number almost in inverse proportion to irradiation dose. Clusters of cancer cells shrank in size and cells were less stratified after irradiation. Irradiated cytoplasms were swollen, vacuolated and stained abnormally. Irradiation with less than 3,000 rads gave rise to swelling of cytoplasms in almost all cases. Nuclei became enlarged, multiple, pyknotic and/or stained pale after irradiation. Nuclear swelling was more remarkable in cancer cells of differentiated adenocarcinomas.

  15. Cluster Headache

    OpenAIRE

    Pearce, Iris

    1985-01-01

    Cluster headache is the most severe primary headache with recurrent pain attacks described as worse than giving birth. The aim of this paper was to make an overview of current knowledge on cluster headache with a focus on pathophysiology and treatment. This paper presents hypotheses of cluster headache pathophysiology, current treatment options and possible future therapy approaches. For years, the hypothalamus was regarded as the key structure in cluster headache, but is now thought to be pa...

  16. Understanding the Role of Muscle and Body Composition in Studies of Cancer Risk and Prognosis in Cancer Survivors

    Science.gov (United States)

    The purpose of this conference is to bring together a community of researchers across the cancer control continuum using geospatial tools, models and approaches to address cancer prevention and control.

  17. Integrative subtype discovery in glioblastoma using iCluster.

    Directory of Open Access Journals (Sweden)

    Ronglai Shen

    Full Text Available Large-scale cancer genome projects, such as the Cancer Genome Atlas (TCGA project, are comprehensive molecular characterization efforts to accelerate our understanding of cancer biology and the discovery of new therapeutic targets. The accumulating wealth of multidimensional data provides a new paradigm for important research problems including cancer subtype discovery. The current standard approach relies on separate clustering analyses followed by manual integration. Results can be highly data type dependent, restricting the ability to discover new insights from multidimensional data. In this study, we present an integrative subtype analysis of the TCGA glioblastoma (GBM data set. Our analysis revealed new insights through integrated subtype characterization. We found three distinct integrated tumor subtypes. Subtype 1 lacks the classical GBM events of chr 7 gain and chr 10 loss. This subclass is enriched for the G-CIMP phenotype and shows hypermethylation of genes involved in brain development and neuronal differentiation. The tumors in this subclass display a Proneural expression profile. Subtype 2 is characterized by a near complete association with EGFR amplification, overrepresentation of promoter methylation of homeobox and G-protein signaling genes, and a Classical expression profile. Subtype 3 is characterized by NF1 and PTEN alterations and exhibits a Mesenchymal-like expression profile. The data analysis workflow we propose provides a unified and computationally scalable framework to harness the full potential of large-scale integrated cancer genomic data for integrative subtype discovery.

  18. Fatigue in lung cancer patients: symptom burden and management of challenges

    Directory of Open Access Journals (Sweden)

    Carnio S

    2016-05-01

    Full Text Available Simona Carnio, Rosario Francesco Di Stefano, Silvia Novello Oncology Department, University of Turin, AOU San Luigi, Orbassano, Italy Abstract: Lung cancer (LC remains the most common cause of cancer death in several countries across the world. Fatigue is the most frequently reported symptom in LC patients throughout the entire course of disease, and all international guidelines recommend early screening for cancer-related fatigue (CRF and symptoms that can affect patients' quality of life. In patients with LC, fatigue belongs to the symptom cluster of pain, depression, and insomnia, which are commonly observed simultaneously, but are typically treated as separate although they may have common biological mechanisms. The treatment of CRF remains one of the difficult areas in the oncology field: scarce evidence supports pharmacological therapies, while some interesting data arising indicates alternative remedies and physical exercise seem to be one of the most effective approaches for CRF at any stage of LC. Keywords: fatigue, lung cancer, symptom cluster, quality of life

  19. Global Analysis of miRNA Gene Clusters and Gene Families Reveals Dynamic and Coordinated Expression

    Directory of Open Access Journals (Sweden)

    Li Guo

    2014-01-01

    Full Text Available To further understand the potential expression relationships of miRNAs in miRNA gene clusters and gene families, a global analysis was performed in 4 paired tumor (breast cancer and adjacent normal tissue samples using deep sequencing datasets. The compositions of miRNA gene clusters and families are not random, and clustered and homologous miRNAs may have close relationships with overlapped miRNA species. Members in the miRNA group always had various expression levels, and even some showed larger expression divergence. Despite the dynamic expression as well as individual difference, these miRNAs always indicated consistent or similar deregulation patterns. The consistent deregulation expression may contribute to dynamic and coordinated interaction between different miRNAs in regulatory network. Further, we found that those clustered or homologous miRNAs that were also identified as sense and antisense miRNAs showed larger expression divergence. miRNA gene clusters and families indicated important biological roles, and the specific distribution and expression further enrich and ensure the flexible and robust regulatory network.

  20. Properties of an ionised-cluster beam from a vaporised-cluster ion source

    International Nuclear Information System (INIS)

    Takagi, T.; Yamada, I.; Sasaki, A.

    1978-01-01

    A new type of ion source vaporised-metal cluster ion source, has been developed for deposition and epitaxy. A cluster consisting of 10 2 to 10 3 atoms coupled loosely together is formed by adiabatic expansion ejecting the vapour of materials into a high-vacuum region through the nozzle of a heated crucible. The clusters are ionised by electron bombardment and accelerated with neutral clusters toward a substrate. In this paper, mechanisms of cluster formation experimental results of the cluster size (atoms/cluster) and its distribution, and characteristics of the cluster ion beams are reported. The size is calculated from the kinetic equation E = (1/2)mNVsub(ej) 2 , where E is the cluster beam energy, Vsub(ej) is the ejection velocity, m is the mass of atom and N is the cluster size. The energy and the velocity of the cluster are measured by an electrostatic 127 0 energy analyser and a rotating disc system, respectively. The cluster size obtained for Ag is about 5 x 10 2 to 2 x 10 3 atoms. The retarding potential method is used to confirm the results for Ag. The same dependence on cluster size for metals such as Ag, Cu and Pb has been obtained in previous experiments. In the cluster state the cluster ion beam is easily produced by electron bombardment. About 50% of ionised clusters are obtained under typical operation conditions, because of the large ionisation cross sections of the clusters. To obtain a uniform spatial distribution, the ionising electrode system is also discussed. The new techniques are termed ionised-cluster beam deposition (ICBD) and epitaxy (ICBE). (author)