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Sample records for cancer cellular model

  1. Lobular breast cancer : molecular basis, mouse and cellular models

    NARCIS (Netherlands)

    Christgen, Matthias; Derksen, Patrick W B

    2015-01-01

    Infiltrating lobular breast cancer (ILC) is the most common special breast cancer subtype. With mutational or epigenetic inactivation of the cell adhesion molecule E-cadherin (CDH1) being confined almost exclusively to ILC, this tumor entity stands out from all other types of breast cancers. The

  2. A Novel Cellular Model to Study Angiotensin II AT2 Receptor Function in Breast Cancer Cells

    OpenAIRE

    Sylvie Rodrigues-Ferreira; Marina Morel; Rosana I Reis; Françoise Cormier; Véronique Baud; Costa-Neto, Claudio M.; Clara Nahmias

    2012-01-01

    Recent studies have highlighted the AT1 receptor as a potential therapeutic target in breast cancer, while the role of the AT2 subtype in this disease has remained largely neglected. The present study describes the generation and characterization of a new cellular model of human invasive breast cancer cells (D3H2LN-AT2) stably expressing high levels of Flag-tagged human AT2 receptor (Flag-hAT2). These cells exhibit high-affinity binding sites for AngII, and total binding can be displaced by t...

  3. Treatment Analysis in a Cancer Stem Cell Context Using a Tumor Growth Model Based on Cellular Automata.

    Science.gov (United States)

    Monteagudo, Ángel; Santos, José

    2015-01-01

    Cancer can be viewed as an emergent behavior in terms of complex system theory and artificial life, Cellular Automata (CA) being the tool most used for studying and characterizing the emergent behavior. Different approaches with CA models were used to model cancer growth. The use of the abstract model of acquired cancer hallmarks permits the direct modeling at cellular level, where a cellular automaton defines the mitotic and apoptotic behavior of cells, and allows for an analysis of different dynamics of the cellular system depending on the presence of the different hallmarks. A CA model based on the presence of hallmarks in the cells, which includes a simulation of the behavior of Cancer Stem Cells (CSC) and their implications for the resultant growth behavior of the multicellular system, was employed. This modeling of cancer growth, in the avascular phase, was employed to analyze the effect of cancer treatments in a cancer stem cell context. The model clearly explains why, after treatment against non-stem cancer cells, the regrowth capability of CSCs generates a faster regrowth of tumor behavior, and also shows that a continuous low-intensity treatment does not favor CSC proliferation and differentiation, thereby allowing an unproblematic control of future tumor regrowth. The analysis performed indicates that, contrary to the current attempts at CSC control, trying to make CSC proliferation more difficult is an important point to consider, especially in the immediate period after a standard treatment for controlling non-stem cancer cell proliferation.

  4. Treatment Analysis in a Cancer Stem Cell Context Using a Tumor Growth Model Based on Cellular Automata.

    Directory of Open Access Journals (Sweden)

    Ángel Monteagudo

    Full Text Available Cancer can be viewed as an emergent behavior in terms of complex system theory and artificial life, Cellular Automata (CA being the tool most used for studying and characterizing the emergent behavior. Different approaches with CA models were used to model cancer growth. The use of the abstract model of acquired cancer hallmarks permits the direct modeling at cellular level, where a cellular automaton defines the mitotic and apoptotic behavior of cells, and allows for an analysis of different dynamics of the cellular system depending on the presence of the different hallmarks. A CA model based on the presence of hallmarks in the cells, which includes a simulation of the behavior of Cancer Stem Cells (CSC and their implications for the resultant growth behavior of the multicellular system, was employed. This modeling of cancer growth, in the avascular phase, was employed to analyze the effect of cancer treatments in a cancer stem cell context. The model clearly explains why, after treatment against non-stem cancer cells, the regrowth capability of CSCs generates a faster regrowth of tumor behavior, and also shows that a continuous low-intensity treatment does not favor CSC proliferation and differentiation, thereby allowing an unproblematic control of future tumor regrowth. The analysis performed indicates that, contrary to the current attempts at CSC control, trying to make CSC proliferation more difficult is an important point to consider, especially in the immediate period after a standard treatment for controlling non-stem cancer cell proliferation.

  5. Inferring predominant pathways in cellular models of breast cancer using limited sample proteomic profiling

    Directory of Open Access Journals (Sweden)

    Klinke David J

    2010-06-01

    Full Text Available Abstract Background Molecularly targeted drugs inhibit aberrant signaling within oncogenic pathways. Identifying the predominant pathways at work within a tumor is a key step towards tailoring therapies to the patient. Clinical samples pose significant challenges for proteomic profiling, an attractive approach for identifying predominant pathways. The objective of this study was to determine if information obtained from a limited sample (i.e., a single gel replicate can provide insight into the predominant pathways in two well-characterized breast cancer models. Methods A comparative proteomic analysis of total cell lysates was obtained from two cellular models of breast cancer, BT474 (HER2+/ER+ and SKBR3 (HER2+/ER-, using two-dimensional electrophoresis and MALDI-TOF mass spectrometry. Protein interaction networks and canonical pathways were extracted from the Ingenuity Pathway Knowledgebase (IPK based on association with the observed pattern of differentially expressed proteins. Results Of the 304 spots that were picked, 167 protein spots were identified. A threshold of 1.5-fold was used to select 62 proteins used in the analysis. IPK analysis suggested that metabolic pathways were highly associated with protein expression in SKBR3 cells while cell motility pathways were highly associated with BT474 cells. Inferred protein networks were confirmed by observing an up-regulation of IGF-1R and profilin in BT474 and up-regulation of Ras and enolase in SKBR3 using western blot. Conclusion When interpreted in the context of prior information, our results suggest that the overall patterns of differential protein expression obtained from limited samples can still aid in clinical decision making by providing an estimate of the predominant pathways that underpin cellular phenotype.

  6. Modeling cellular systems

    CERN Document Server

    Matthäus, Franziska; Pahle, Jürgen

    2017-01-01

    This contributed volume comprises research articles and reviews on topics connected to the mathematical modeling of cellular systems. These contributions cover signaling pathways, stochastic effects, cell motility and mechanics, pattern formation processes, as well as multi-scale approaches. All authors attended the workshop on "Modeling Cellular Systems" which took place in Heidelberg in October 2014. The target audience primarily comprises researchers and experts in the field, but the book may also be beneficial for graduate students.

  7. Cellular based cancer vaccines

    DEFF Research Database (Denmark)

    Hansen, Morten; Met, O; Svane, I M

    2012-01-01

    Cancer vaccines designed to re-calibrate the existing host-tumour interaction, tipping the balance from tumor acceptance towards tumor control holds huge potential to complement traditional cancer therapies. In general, limited success has been achieved with vaccines composed of tumor...... in vitro migration via autocrine receptor-mediated endocytosis of CCR7. In the current review, we discuss optimal design of DC maturation focused on pre-clinical as well as clinical results from standard and polarized dendritic cell based cancer vaccines....

  8. Cellular based cancer vaccines

    DEFF Research Database (Denmark)

    Hansen, M; Met, Ö; Svane, I M

    2012-01-01

    Cancer vaccines designed to re-calibrate the existing host-tumour interaction, tipping the balance from tumor acceptance towards tumor control holds huge potential to complement traditional cancer therapies. In general, limited success has been achieved with vaccines composed of tumor...... to transiently affect in vitro migration via autocrine receptor-mediated endocytosis of CCR7. In the current review, we discuss optimal design of DC maturation focused on pre-clinical as well as clinical results from standard and polarized dendritic cell based cancer vaccines....

  9. Fasting vs dietary restriction in cellular protection and cancer treatment: from model organisms to patients.

    Science.gov (United States)

    Lee, C; Longo, V D

    2011-07-28

    The dietary recommendation for cancer patients receiving chemotherapy, as described by the American Cancer Society, is to increase calorie and protein intake. Yet, in simple organisms, mice, and humans, fasting--no calorie intake--induces a wide range of changes associated with cellular protection, which would be difficult to achieve even with a cocktail of potent drugs. In mammals, the protective effect of fasting is mediated, in part, by an over 50% reduction in glucose and insulin-like growth factor 1 (IGF-I) levels. Because proto-oncogenes function as key negative regulators of the protective changes induced by fasting, cells expressing oncogenes, and therefore the great majority of cancer cells, should not respond to the protective signals generated by fasting, promoting the differential protection (differential stress resistance) of normal and cancer cells. Preliminary reports indicate that fasting for up to 5 days followed by a normal diet, may also protect patients against chemotherapy without causing chronic weight loss. By contrast, the long-term 20 to 40% restriction in calorie intake (dietary restriction, DR), whose effects on cancer progression have been studied extensively for decades, requires weeks-months to be effective, causes much more modest changes in glucose and/or IGF-I levels, and promotes chronic weight loss in both rodents and humans. In this study, we review the basic as well as clinical studies on fasting, cellular protection and chemotherapy resistance, and compare them to those on DR and cancer treatment. Although additional pre-clinical and clinical studies are necessary, fasting has the potential to be translated into effective clinical interventions for the protection of patients and the improvement of therapeutic index.

  10. Quantitative modeling of clinical, cellular, and extracellular matrix variables suggest prognostic indicators in cancer: a model in neuroblastoma.

    Science.gov (United States)

    Tadeo, Irene; Piqueras, Marta; Montaner, David; Villamón, Eva; Berbegall, Ana P; Cañete, Adela; Navarro, Samuel; Noguera, Rosa

    2014-02-01

    Risk classification and treatment stratification for cancer patients is restricted by our incomplete picture of the complex and unknown interactions between the patient's organism and tumor tissues (transformed cells supported by tumor stroma). Moreover, all clinical factors and laboratory studies used to indicate treatment effectiveness and outcomes are by their nature a simplification of the biological system of cancer, and cannot yet incorporate all possible prognostic indicators. A multiparametric analysis on 184 tumor cylinders was performed. To highlight the benefit of integrating digitized medical imaging into this field, we present the results of computational studies carried out on quantitative measurements, taken from stromal and cancer cells and various extracellular matrix fibers interpenetrated by glycosaminoglycans, and eight current approaches to risk stratification systems in patients with primary and nonprimary neuroblastoma. New tumor tissue indicators from both fields, the cellular and the extracellular elements, emerge as reliable prognostic markers for risk stratification and could be used as molecular targets of specific therapies. The key to dealing with personalized therapy lies in the mathematical modeling. The use of bioinformatics in patient-tumor-microenvironment data management allows a predictive model in neuroblastoma.

  11. Aging, Cellular Senescence, and Cancer

    OpenAIRE

    Campisi, Judith

    2012-01-01

    For most species, aging promotes a host of degenerative pathologies that are characterized by debilitating losses of tissue or cellular function. However, especially among vertebrates, aging also promotes hyperplastic pathologies, the most deadly of which is cancer. In contrast to the loss of function that characterizes degenerating cells and tissues, malignant (cancerous) cells must acquire new (albeit aberrant) functions that allow them to develop into a lethal tumor. This review discusses ...

  12. Aging, Cellular Senescence, and Cancer

    Science.gov (United States)

    Campisi, Judith

    2014-01-01

    For most species, aging promotes a host of degenerative pathologies that are characterized by debilitating losses of tissue or cellular function. However, especially among vertebrates, aging also promotes hyperplastic pathologies, the most deadly of which is cancer. In contrast to the loss of function that characterizes degenerating cells and tissues, malignant (cancerous) cells must acquire new (albeit aberrant) functions that allow them to develop into a lethal tumor. This review discusses the idea that, despite seemingly opposite characteristics, the degenerative and hyperplastic pathologies of aging are at least partly linked by a common biological phenomenon: a cellular stress response known as cellular senescence. The senescence response is widely recognized as a potent tumor suppressive mechanism. However, recent evidence strengthens the idea that it also drives both degenerative and hyper-plastic pathologies, most likely by promoting chronic inflammation. Thus, the senescence response may be the result of antagonistically pleiotropic gene action. PMID:23140366

  13. Cosserat modeling of cellular solids

    NARCIS (Netherlands)

    Onck, P.R.

    2002-01-01

    Cellular solids inherit their macroscopic mechanical properties directly from the cellular microstructure. However, the characteristic material length scale is often not small compared to macroscopic dimensions, which limits the applicability of classical continuum-type constitutive models. Cosserat

  14. DREW-UCLA Breast Cancer Research and Training Program: Molecular/Cellular Pathogenesis Model

    Science.gov (United States)

    2007-03-01

    including the Na+-dependent amino acid transporters system A, ASC, N, B0, XAG, Gly, andβ-Alanine/ Taurine , and the Na+-independent amino acid transporters L...Cancer DIVISION DEPARTMENT Tobacco Research OBGYN Dean College of Science and Health Hem/Onc Internal Medicine RCMI Family Medicine RCMI Psychiatry

  15. A cellular Potts model for the MMP-dependent and -independent cancer cell migration in matrix microtracks of different dimensions

    Science.gov (United States)

    Scianna, Marco; Preziosi, Luigi

    2014-03-01

    Cell migration is fundamental in a wide variety of physiological and pathological phenomena, among other in cancer invasion and development. In particular, the migratory/invasive capability of single metastatic cells is fundamental in determining the malignancy of a solid tumor. Specific cell migration phenotypes result for instance from the reciprocal interplay between the biophysical and biochemical properties of both the malignant cells themselves and of the surrounding environment. In particular, the extracellular matrices (ECMs) forming connective tissues can provide both loosely organized zones and densely packed barriers, which may impact cell invasion mode and efficiency. The critical processes involved in cell movement within confined spaces are (i) the proteolytic activity of matrix metalloproteinases (MMPs) and (ii) the deformation of the entire cell body, and in particular of the nucleus. We here present an extended cellular Potts model (CPM) to simulate a bio-engineered matrix system, which tests the active motile behavior of a single cancer cell into narrow channels of different widths. As distinct features of our approach, the cell is modeled as a compartmentalized discrete element, differentiated in the nucleus and in the cytosolic region, while a directional shape-dependent movement is explicitly driven by the evolution of its polarity vector. As outcomes, we find that, in a large track, the tumor cell is not able to maintain a directional movement. On the contrary, a structure of subcellular width behaves as a contact guidance sustaining cell persistent locomotion. In particular, a MMP-deprived cell is able to repolarize and follow the micropattern geometry, while a full MMP activity leads to a secondary track expansion by degrading the matrix structure. Finally, we confirm that cell movement within a subnuclear structure can be achieved either by pericellular proteolysis or by a significant deformation of cell nucleus.

  16. Regulation of Cellular Identity in Cancer.

    Science.gov (United States)

    Roy, Nilotpal; Hebrok, Matthias

    2015-12-21

    Neoplastic transformation requires changes in cellular identity. Emerging evidence increasingly points to cellular reprogramming, a process during which fully differentiated and functional cells lose aspects of their identity while gaining progenitor characteristics, as a critical early step during cancer initiation. This cell identity crisis persists even at the malignant stage in certain cancers, suggesting that reactivation of progenitor functions supports tumorigenicity. Here, we review recent findings that establish the essential role of cellular reprogramming during neoplastic transformation and the major players involved in it with a special emphasis on pancreatic cancer. Copyright © 2015 Elsevier Inc. All rights reserved.

  17. The roles of cellular nanomechanics in cancer.

    Science.gov (United States)

    Yallapu, Murali M; Katti, Kalpana S; Katti, Dinesh R; Mishra, Sanjay R; Khan, Sheema; Jaggi, Meena; Chauhan, Subhash C

    2015-01-01

    The biomechanical properties of cells and tissues may be instrumental in increasing our understanding of cellular behavior and cellular manifestations of diseases such as cancer. Nanomechanical properties can offer clinical translation of therapies beyond what are currently employed. Nanomechanical properties, often measured by nanoindentation methods using atomic force microscopy, may identify morphological variations, cellular binding forces, and surface adhesion behaviors that efficiently differentiate normal cells and cancer cells. The aim of this review is to examine current research involving the general use of atomic force microscopy/nanoindentation in measuring cellular nanomechanics; various factors and instrumental conditions that influence the nanomechanical properties of cells; and implementation of nanoindentation methods to distinguish cancer cells from normal cells or tissues. Applying these fundamental nanomechanical properties to current discoveries in clinical treatment may result in greater efficiency in diagnosis, treatment, and prevention of cancer, which ultimately can change the lives of patients. © 2014 Wiley Periodicals, Inc.

  18. Reduction by coffee consumption of prostate cancer risk: Evidence from the Moli-sani cohort and cellular models.

    Science.gov (United States)

    Pounis, George; Tabolacci, Claudio; Costanzo, Simona; Cordella, Martina; Bonaccio, Marialaura; Rago, Livia; D'Arcangelo, Daniela; Filippo Di Castelnuovo, Augusto; de Gaetano, Giovanni; Donati, Maria Benedetta; Iacoviello, Licia; Facchiano, Francesco

    2017-07-01

    Meta-analytic data on the effect of coffee in prostate cancer risk are controversial. Caffeine as a bioactive compound of coffee has not yet been studied in deep in vitro. Our study aimed at evaluating in a population cohort the effect of Italian-style coffee consumption on prostate cancer risk and at investigating in vitro the potential antiproliferative and antimetastatic activity of caffeine on prostate cancer cell lines. 6,989 men of the Moli-sani cohort aged ≥50 years were followed for a mean of 4.24 ± 1.35 years and 100 new prostate cancer cases were identified. The European Prospective Investigation into Cancer and Nutrition-Food Frequency Questionnaire was used for the dietary assessment and the evaluation of Italian-style coffee consumption. Two human prostate cancer cell lines, PC-3 and DU145, were tested with increasing concentrations of caffeine, and their proliferative/metastatic features were evaluated. The newly diagnosed prostate cancer participants presented lower coffee consumption (60.1 ± 51.3 g/day) compared to the disease-free population (74.0 ± 51.7 g/day) (p 3 cups/day) had 53% lower prostate cancer risk as compared to participants at the lowest consumption (0-2 cups/day) (p = 0.02). Both human prostate cancer cell lines treated with caffeine showed a significant reduction in their proliferative and metastatic behaviors (p coffee consumption of prostate cancer risk (>3 cups/day) was observed in epidemiological level. Caffeine appeared to exert both antiproliferative and antimetastatic activity on two prostate cancer cell lines, thus providing a cellular confirmation for the cohort study results. © 2017 UICC.

  19. Cellular telephone use and cancer risk

    DEFF Research Database (Denmark)

    Schüz, Joachim; Jacobsen, Rune; Olsen, Jørgen H.

    2006-01-01

    BACKGROUND: The widespread use of cellular telephones has heightened concerns about possible adverse health effects. The objective of this study was to investigate cancer risk among Danish cellular telephone users who were followed for up to 21 years. METHODS: This study is an extended follow-up ...

  20. Regulation of Cellular Identity in Cancer

    OpenAIRE

    Roy, Nilotpal; Hebrok, Matthias

    2015-01-01

    Neoplastic transformation requires changes in cellular identity. Emerging evidence increasingly points to cellular reprogramming, a process during which fully differentiated and functional cells lose aspects of their identity while gaining progenitor characteristics, as a critical early step during cancer initiation. This cell identity crisis persists even at the malignant stage in certain cancers, suggesting that reactivation of progenitor functions supports tumorigenicity. Here, we review r...

  1. Cellular Hyperproliferation and Cancer as Evolutionary Variables

    Science.gov (United States)

    Alvarado, Alejandro Sánchez

    2012-01-01

    Technological advances in biology have begun to dramatically change the way we think about evolution, development, health and disease. The ability to sequence the genomes of many individuals within a population, and across multiple species, has opened the door to the possibility of answering some long-standing and perplexing questions about our own genetic heritage. One such question revolves around the nature of cellular hyperproliferation. This cellular behavior is used to effect wound healing in most animals, as well as, in some animals, the regeneration of lost body parts. Yet at the same time, cellular hyperproliferation is the fundamental pathological condition responsible for cancers in humans. Here, I will discuss why microevolution, macroevolution and developmental biology all have to be taken into consideration when interpreting studies of both normal and malignant hyperproliferation. I will also illustrate how a synthesis of evolutionary sciences and developmental biology through the study of diverse model organisms can inform our understanding of both health and disease. PMID:22975008

  2. A cellular dynamics model of experimental bladder cancer: analysis of the effect of sodium saccharin in the rat.

    Science.gov (United States)

    Ellwein, L B; Cohen, S M

    1988-06-01

    To make the methodology of risk assessment more consistent with the realities of biological processes, a computer-based model of the carcinogenic process may be used. A previously developed probabilistic model, which is based on a two-stage theory of carcinogenesis, represents urinary bladder carcinogenesis at the cellular level with emphasis on quantification of cell dynamics: cell mitotic rates, cell loss and birth rates, and irreversible cellular transitions from normal to initiated to transformed states are explicitly accounted for. Analyses demonstrate the sensitivity of tumor incidence to the timing and magnitude of changes to these cellular variables. It is demonstrated that response in rats following administration of nongenotoxic compounds, such as sodium saccharin, can be explained entirely on the basis of cytotoxicity and consequent hyperplasia alone.

  3. Exogenous coenzyme Q10 modulates MMP-2 activity in MCF-7 cell line as a breast cancer cellular model

    Directory of Open Access Journals (Sweden)

    Mirmiranpour Hossein

    2010-11-01

    Full Text Available Abstract Background/Aims Matrix Metalloproteinases 2 is a key molecule in cellular invasion and metastasis. Mitochondrial ROS has been established as a mediator of MMP activity. Coenzyme Q10 contributes to intracellular ROS regulation. Coenzyme Q10 beneficial effects on cancer are still in controversy but there are indications of Coenzyme Q10 complementing effect on tamoxifen receiving breast cancer patients. Methods In this study we aimed to investigate the correlation of the effects of co-incubation of coenzyme Q10 and N-acetyl-L-cysteine (NAC on intracellular H2O2 content and Matrix Metalloproteinase 2 (MMP-2 activity in MCF-7 cell line. Results and Discussion Our experiment was designed to assess the effect in a time and dose related manner. Gelatin zymography and Flowcytometric measurement of H2O2 by 2'7',-dichlorofluorescin-diacetate probe were employed. The results showed that both coenzyme Q10 and N-acetyl-L-cysteine reduce MMP-2 activity along with the pro-oxidant capacity of the MCF-7 cell in a dose proportionate manner. Conclusions Collectively, the present study highlights the significance of Coenzyme Q10 effect on the cell invasion/metastasis effecter molecules.

  4. Roles of Apoptosis and Cellular Senescence in Cancer and Aging.

    Science.gov (United States)

    Cerella, Claudia; Grandjenette, Cindy; Dicato, Mario; Diederich, Marc

    2016-01-01

    Cancer and aging are two similar processes representing the final outcome of timedependent accumulation of various irreversible dysfunctions, mainly caused by stress-induced DNA and cellular damages. Apoptosis and senescence are two types of cellular response to damages that are altered in both cancer and aging, albeit through different mechanisms. Carcinogenesis is associated with a progressive reduction in the ability of the cells to trigger apoptosis and senescence. In contrast, in aging tissues, there is an increased accumulation of senescent cells, and the nature of apoptosis deregulation varies depending on the tissue. Thus, the prevailing model suggests that apoptosis and cellular senescence function as two essential tumor-suppressor mechanisms, ensuring the health of the individual during early and reproductive stages of life, but become detrimental and promote aging later in life. The recent discovery that various anticancer agents, including canonical inducers of apoptosis, act also as inducers of cellular senescence indicates that pro-senescence strategies may have applications in cancer prevention therapy. Therefore, dissection of the mechanisms mediating the delicate balance between apoptosis and cellular senescence will be beneficial in the therapeutic exploitation of both processes in the development of future anticancer and anti-aging strategies, including minimizing the side effects of such strategies. Here, we provide an overview of the roles of apoptosis and cellular senescence in cancer and aging.

  5. Cellular automata a parallel model

    CERN Document Server

    Mazoyer, J

    1999-01-01

    Cellular automata can be viewed both as computational models and modelling systems of real processes. This volume emphasises the first aspect. In articles written by leading researchers, sophisticated massive parallel algorithms (firing squad, life, Fischer's primes recognition) are treated. Their computational power and the specific complexity classes they determine are surveyed, while some recent results in relation to chaos from a new dynamic systems point of view are also presented. Audience: This book will be of interest to specialists of theoretical computer science and the parallelism challenge.

  6. Theoretical aspects and modelling of cellular decision making, cell killing and information-processing in photodynamic therapy of cancer.

    Science.gov (United States)

    Gkigkitzis, Ioannis

    2013-01-01

    The aim of this report is to provide a mathematical model of the mechanism for making binary fate decisions about cell death or survival, during and after Photodynamic Therapy (PDT) treatment, and to supply the logical design for this decision mechanism as an application of rate distortion theory to the biochemical processing of information by the physical system of a cell. Based on system biology models of the molecular interactions involved in the PDT processes previously established, and regarding a cellular decision-making system as a noisy communication channel, we use rate distortion theory to design a time dependent Blahut-Arimoto algorithm where the input is a stimulus vector composed of the time dependent concentrations of three PDT related cell death signaling molecules and the output is a cell fate decision. The molecular concentrations are determined by a group of rate equations. The basic steps are: initialize the probability of the cell fate decision, compute the conditional probability distribution that minimizes the mutual information between input and output, compute the cell probability of cell fate decision that minimizes the mutual information and repeat the last two steps until the probabilities converge. Advance to the next discrete time point and repeat the process. Based on the model from communication theory described in this work, and assuming that the activation of the death signal processing occurs when any of the molecular stimulants increases higher than a predefined threshold (50% of the maximum concentrations), for 1800s of treatment, the cell undergoes necrosis within the first 30 minutes with probability range 90.0%-99.99% and in the case of repair/survival, it goes through apoptosis within 3-4 hours with probability range 90.00%-99.00%. Although, there is no experimental validation of the model at this moment, it reproduces some patterns of survival ratios of predicted experimental data. Analytical modeling based on cell death

  7. Selective regain of egfr gene copies in CD44+/CD24-/low breast cancer cellular model MDA-MB-468

    Directory of Open Access Journals (Sweden)

    Andreas Antje

    2010-03-01

    Full Text Available Abstract Background Increased transcription of oncogenes like the epidermal growth factor receptor (EGFR is frequently caused by amplification of the whole gene or at least of regulatory sequences. Aim of this study was to pinpoint mechanistic parameters occurring during egfr copy number gains leading to a stable EGFR overexpression and high sensitivity to extracellular signalling. A deeper understanding of those marker events might improve early diagnosis of cancer in suspect lesions, early detection of cancer progression and the prediction of egfr targeted therapies. Methods The basal-like/stemness type breast cancer cell line subpopulation MDA-MB-468 CD44high/CD24-/low, carrying high egfr amplifications, was chosen as a model system in this study. Subclones of the heterogeneous cell line expressing low and high EGF receptor densities were isolated by cell sorting. Genomic profiling was carried out for these by means of SNP array profiling, qPCR and FISH. Cell cycle analysis was performed using the BrdU quenching technique. Results Low and high EGFR expressing MDA-MB-468 CD44+/CD24-/low subpopulations separated by cell sorting showed intermediate and high copy numbers of egfr, respectively. However, during cell culture an increase solely for egfr gene copy numbers in the intermediate subpopulation occurred. This shift was based on the formation of new cells which regained egfr gene copies. By two parametric cell cycle analysis clonal effects mediated through growth advantage of cells bearing higher egfr gene copy numbers could most likely be excluded for being the driving force. Subsequently, the detection of a fragile site distal to the egfr gene, sustaining uncapped telomere-less chromosomal ends, the ladder-like structure of the intrachromosomal egfr amplification and a broader range of egfr copy numbers support the assumption that dynamic chromosomal rearrangements, like breakage-fusion-bridge-cycles other than proliferation drive the gain

  8. A review of spatial computational models for multi-cellular systems, with regard to intestinal crypts and colorectal cancer development.

    Science.gov (United States)

    De Matteis, Giovanni; Graudenzi, Alex; Antoniotti, Marco

    2013-06-01

    Colon rectal cancers (CRC) are the result of sequences of mutations which lead the intestinal tissue to develop in a carcinoma following a "progression" of observable phenotypes. The actual modeling and simulation of the key biological structures involved in this process is of interest to biologists and physicians and, at the same time, it poses significant challenges from the mathematics and computer science viewpoints. In this report we give an overview of some mathematical models for cell sorting (a basic phenomenon that underlies several dynamical processes in an organism), intestinal crypt dynamics and related problems and open questions. In particular, major attention is devoted to the survey of so-called in-lattice (or grid) models and off-lattice (off-grid) models. The current work is the groundwork for future research on semi-automated hypotheses formation and testing about the behavior of the various actors taking part in the adenoma-carcinoma progression, from regulatory processes to cell-cell signaling pathways.

  9. Effects of pluronic and doxorubicin on drug uptake, cellular metabolism, apoptosis and tumor inhibition in animal models of MDR cancers.

    Science.gov (United States)

    Batrakova, Elena V; Li, Shu; Brynskikh, Anna M; Sharma, Amit K; Li, Yili; Boska, Michael; Gong, Nan; Mosley, R Lee; Alakhov, Valery Yu; Gendelman, Howard E; Kabanov, Alexander V

    2010-05-10

    Cancer chemotherapy is believed to be impeded by multidrug resistance (MDR). Pluronic (triblock copolymers of poly(ethylene oxide) (PEO) and poly(propylene oxide) (PPO), PEO-b-PPO-b-PEO) were previously shown to sensitize MDR tumors to antineoplastic agents. This study uses animal models of Lewis lung carcinoma (3LL-M27) and T-lymphocytic leukemia (P388/ADR and P388) derived solid tumors to delineate mechanisms of sensitization of MDR tumors by Pluronic P85 (P85) in vivo. First, non-invasive single photon emission computed tomography (SPECT) and tumor tissue radioactivity sampling demonstrate that intravenous co-administration of P85 with a Pgp substrate, 99Tc-sestamibi, greatly increases the tumor uptake of this substrate in the MDR tumors. Second, 31P magnetic resonance spectroscopy (31P-MRS) in live animals and tumor tissue sampling for ATP suggest that P85 and doxorubicin (Dox) formulations induce pronounced ATP depletion in MDR tumors. Third, these formulations are shown to increase tumor apoptosis in vivo by terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assay and reverse transcription polymerase chain reaction (RT-PCR) for caspases 8 and 9. Altogether, formulation of Dox with P85 results in increased inhibition of the growth solid tumors in mice and represents novel and promising strategy for therapy of drug resistant cancers. Published by Elsevier B.V.

  10. Pomegranate Extracts and Cancer Prevention: Molecular and Cellular Activities

    Science.gov (United States)

    Syed, Deeba N.; Chamcheu, Jean-Christopher; Adhami, Vaqar M.; Mukhtar, Hasan

    2014-01-01

    There is increased appreciation by the scientific community that dietary phytochemicals can be potential weapons in the fight against cancer. Emerging data has provided new insights into the molecular and cellular framework needed to establish novel mechanism-based strategies for cancer prevention by selective bioactive food components. The unique chemical composition of the pomegranate fruit, rich in antioxidant tannins and flavonoids has drawn the attention of many investigators. Polyphenol rich fractions derived from the pomegranate fruit have been studied for their potential chemopreventive and/or cancer therapeutic effects in several animal models. Although data from in vitro and in vivo studies look convincing, well designed clinical trials in humans are needed to ascertain whether pomegranate can become part of our armamentarium against cancer. This review summarizes the available literature on the effects of pomegranate against various cancers. PMID:23094914

  11. 'P-cadherin functional role is dependent on E-cadherin cellular context: a proof of concept using the breast cancer model'.

    Science.gov (United States)

    2016-05-01

    This article corrects: P-cadherin functional role is dependent on E-cadherin cellular context: a proof of concept using the breast cancer model Volume 229, Issue 5, 705–718, Article first published online: 24 January 2013. By Ana Sofia Ribeiro, Bárbara Sousa, Laura Carreto, Nuno Mendes, Ana Rita Nobre, Sara Ricardo, André Albergaria, Jorge F Cameselle-Teijeiro, Rene Gerhard, Ola Söderberg, Raquel Seruca, Manuel A Santos, Fernando Schmitt and Joana Paredes, J Pathol 2013; 229: 708–718. DOI: 10.1002/path.4143. The above article, published online on 24 January 2013 on Wiley Online Library (wileyonlinelibrary.com). The funding information, “This work was also funded by FEDER funds through the Operational Programme for Competitiveness Factors - COMPETE (FCOMP-01-0124-FEDER-021209).” was omitted from the Acknowledgements section. We apologise for any inconvenience caused.

  12. [Cellular phones and cancer: current status].

    Science.gov (United States)

    Colonna, Anne

    2005-07-01

    Evaluation of the impact of new technologies on the human body is essential in order to impose regulations to limit health risks. The appearance and evolution of cellular phones have been one of the fastest in the history of innovation. Research reported worldwide has tried to evaluate any potential link between adverse health effects and the mobile phone and its broadcasting stations. This article gives an overview of current research knowledge on the impact of radiofrequency waves on health. Epidemiologic, cellular and animal studies have been carried out, but none of them have reached definitive conclusions. Although some biological effects on cell culture have been observed, their link with human cancer development is far from established. Most of the animal studies show negative results. Epidemiologic studies lack a sufficient perspective to be able to evaluate the effect of evolving technologies used today. High levels of concern by the public have urged mobile phone operators, manufacturers and governmental authorities to finance a number of scientific projects aimed at defining adapted and effective regulations.

  13. Cancer stem cells display extremely large evolvability: alternating plastic and rigid networks as a potential Mechanism: network models, novel therapeutic target strategies, and the contributions of hypoxia, inflammation and cellular senescence.

    Science.gov (United States)

    Csermely, Peter; Hódsági, János; Korcsmáros, Tamás; Módos, Dezső; Perez-Lopez, Áron R; Szalay, Kristóf; Veres, Dániel V; Lenti, Katalin; Wu, Ling-Yun; Zhang, Xiang-Sun

    2015-02-01

    Cancer is increasingly perceived as a systems-level, network phenomenon. The major trend of malignant transformation can be described as a two-phase process, where an initial increase of network plasticity is followed by a decrease of plasticity at late stages of tumor development. The fluctuating intensity of stress factors, like hypoxia, inflammation and the either cooperative or hostile interactions of tumor inter-cellular networks, all increase the adaptation potential of cancer cells. This may lead to the bypass of cellular senescence, and to the development of cancer stem cells. We propose that the central tenet of cancer stem cell definition lies exactly in the indefinability of cancer stem cells. Actual properties of cancer stem cells depend on the individual "stress-history" of the given tumor. Cancer stem cells are characterized by an extremely large evolvability (i.e. a capacity to generate heritable phenotypic variation), which corresponds well with the defining hallmarks of cancer stem cells: the possession of the capacity to self-renew and to repeatedly re-build the heterogeneous lineages of cancer cells that comprise a tumor in new environments. Cancer stem cells represent a cell population, which is adapted to adapt. We argue that the high evolvability of cancer stem cells is helped by their repeated transitions between plastic (proliferative, symmetrically dividing) and rigid (quiescent, asymmetrically dividing, often more invasive) phenotypes having plastic and rigid networks. Thus, cancer stem cells reverse and replay cancer development multiple times. We describe network models potentially explaining cancer stem cell-like behavior. Finally, we propose novel strategies including combination therapies and multi-target drugs to overcome the Nietzschean dilemma of cancer stem cell targeting: "what does not kill me makes me stronger". Copyright © 2014 Elsevier Ltd. All rights reserved.

  14. On complexity and homogeneity measures in predicting biological aggressiveness of prostate cancer; Implication of the cellular automata model of tumor growth.

    Science.gov (United States)

    Tanase, Mihai; Waliszewski, Przemyslaw

    2015-12-01

    We propose a novel approach for the quantitative evaluation of aggressiveness in prostate carcinomas. The spatial distribution of cancer cell nuclei was characterized by the global spatial fractal dimensions D0, D1, and D2. Two hundred eighteen prostate carcinomas were stratified into the classes of equivalence using results of ROC analysis. A simulation of the cellular automata mix defined a theoretical frame for a specific geometric representation of the cell nuclei distribution called a local structure correlation diagram (LSCD). The LSCD and dispersion Hd were computed for each carcinoma. Data mining generated some quantitative criteria describing tumor aggressiveness. Alterations in tumor architecture along progression were associated with some changes in both shape and the quantitative characteristics of the LSCD consistent with those in the automata mix model. Low-grade prostate carcinomas with low complexity and very low biological aggressiveness are defined by the condition D0 1.764 and Hd < 38. The novel homogeneity measure Hd identifies carcinomas with very low aggressiveness within the class of complexity C1 or carcinomas with very high aggressiveness in the class C7. © 2015 Wiley Periodicals, Inc.

  15. Cellular Plasticity and Heterogeneity of EGFR Mutant Lung Cancer

    Science.gov (United States)

    2016-11-01

    AWARD NUMBER: W81XWH-14-1-0177 TITLE: Cellular Plasticity and Heterogeneity of EGFR Mutant Lung Cancer PRINCIPAL INVESTIGATOR: Katerina...5a. CONTRACT NUMBER Cellular Plasticity and Heterogeneity of EGFR Mutant Lung Cancer 5b. GRANT NUMBER W81XWH-14-1-0177 5c. PROGRAM ELEMENT NUMBER...epigenomic landscape of EGFR mutant SCLCs and their corresponding pre- treatment LUADs. These are very rare specimens. Through our Yale rebiopsy program

  16. [The influence of fibronectin on the formation of multi-cellular spheroid of ovarian cancer].

    Science.gov (United States)

    Xie, Xiao-Yan; Liu, Shan-Ling; Wang, He; Lin, Lin; Zhu, Hong-Mei; Zhang, Jian-Jun; Zheng, Ying

    2014-03-01

    To investigate the role of Fibronectin in the formation of multi-cellular spheroid of ovarian cancer and the integrin receptor involved in the process. In vitro model of multi-cellular spheroid of SKOV3 was constructed by liguid overlay technique. The influence of fibronectin on the formation of the spheroid was observed. The gene expressions of potential integrin receptors were examined from the levels of mRNA and protein using real time reverse transcription PCR and Western-blot. Fibronctin stimulated the formation of multi-cellular spheroid of ovarian cancer larger than 250 microm. fibronectin suppressed the expression of subtype of integrin receptor ITGA5. Fibronectin can enhance the formation of multi-cellular spheroid of ovarian cancer. The subtype of integrin receptor ITGA5 is probably involved in the process.

  17. Nonheritable cellular variability accelerates the evolutionary processes of cancer.

    Directory of Open Access Journals (Sweden)

    Steven A Frank

    Full Text Available Recent cancer studies emphasize that genetic and heritable epigenetic changes drive the evolutionary rate of cancer progression and drug resistance. We discuss the ways in which nonheritable aspects of cellular variability may significantly increase evolutionary rate. Nonheritable variability arises by stochastic fluctuations in cells and by physiological responses of cells to the environment. New approaches to drug design may be required to control nonheritable variability and the evolution of resistance to chemotherapy.

  18. Novel Immune Modulating Cellular Vaccine for Prostate Cancer Immunotherapy

    Science.gov (United States)

    2016-10-01

    cellular vaccine product. 15. SUBJECT TERMS dendritic cell vaccine, dendritic cells electroporated with RNA, immune checkpoint blockade, local CTLA-4...dendritic cell vaccine, dendritic cells electroporated with RNA, immune checkpoint blockade, local CTLA4 modulation, prostate cancer...7: Monitor tumor burden (time to palpable tumor) and monitor survival. Harvest prostate complex/tumor and analyze tumor weight , tumor grade

  19. A cellular automata model of bone formation.

    Science.gov (United States)

    Van Scoy, Gabrielle K; George, Estee L; Opoku Asantewaa, Flora; Kerns, Lucy; Saunders, Marnie M; Prieto-Langarica, Alicia

    2017-04-01

    Bone remodeling is an elegantly orchestrated process by which osteocytes, osteoblasts and osteoclasts function as a syncytium to maintain or modify bone. On the microscopic level, bone consists of cells that create, destroy and monitor the bone matrix. These cells interact in a coordinated manner to maintain a tightly regulated homeostasis. It is this regulation that is responsible for the observed increase in bone gain in the dominant arm of a tennis player and the observed increase in bone loss associated with spaceflight and osteoporosis. The manner in which these cells interact to bring about a change in bone quality and quantity has yet to be fully elucidated. But efforts to understand the multicellular complexity can ultimately lead to eradication of metabolic bone diseases such as osteoporosis and improved implant longevity. Experimentally validated mathematical models that simulate functional activity and offer eventual predictive capabilities offer tremendous potential in understanding multicellular bone remodeling. Here we undertake the initial challenge to develop a mathematical model of bone formation validated with in vitro data obtained from osteoblastic bone cells induced to mineralize and quantified at 26 days of culture. A cellular automata model was constructed to simulate the in vitro characterization. Permutation tests were performed to compare the distribution of the mineralization in the cultures and the distribution of the mineralization in the mathematical models. The results of the permutation test show the distribution of mineralization from the characterization and mathematical model come from the same probability distribution, therefore validating the cellular automata model. Copyright © 2017 Elsevier Inc. All rights reserved.

  20. Urban sprawl modeling using cellular automata

    Directory of Open Access Journals (Sweden)

    Shikhar Deep

    2014-12-01

    Full Text Available The population settlements in the fast-growing urban world need to be monitored in order to design a sustainable urban habitat. The remote sensing and GIS are considered as an effective monitoring and decision-support tool in urban planning. This study compiles the results of a study undertaken to measure the urban sprawl in Dehradun city, India through cellular automata CA-Markov model. CA-Markov model can effectively be used to study the urban dynamics in rapidly growing cities. Being an effective tool for encoding spatial structures, the information generated by it could be used to predict urban scenarios for sustainable growth. To achieve the goal, the temporal images of LISS IV were used to analyse the spatial pattern of land cover change in the area and the future growth was modeled by applying CA-Markov model. The results clearly suggest that major changes between the periods of 2004 and 2009 occurred in built up classes (about 27% followed by agriculture (17.7% and fallow land (10.2%. The projection as predicted using CA-Markov model suggested a value of kappa coefficient = 0.91 which indicates the validity of the model to predict future projections. Modeling suggested a clear trend of various land use classes’ transformation in the area of urban built up expansions. It is concluded that RS and GIS can be an effective decision support tool for policy makers to design sustainable urban habitats.

  1. Agent-based models of cellular systems.

    Science.gov (United States)

    Cannata, Nicola; Corradini, Flavio; Merelli, Emanuela; Tesei, Luca

    2013-01-01

    Software agents are particularly suitable for engineering models and simulations of cellular systems. In a very natural and intuitive manner, individual software components are therein delegated to reproduce "in silico" the behavior of individual components of alive systems at a given level of resolution. Individuals' actions and interactions among individuals allow complex collective behavior to emerge. In this chapter we first introduce the readers to software agents and multi-agent systems, reviewing the evolution of agent-based modeling of biomolecular systems in the last decade. We then describe the main tools, platforms, and methodologies available for programming societies of agents, possibly profiting also of toolkits that do not require advanced programming skills.

  2. A mathematical model of antibody-dependent cellular cytotoxicity (ADCC).

    Science.gov (United States)

    Hoffman, F; Gavaghan, D; Osborne, J; Barrett, I P; You, T; Ghadially, H; Sainson, R; Wilkinson, R W; Byrne, H M

    2018-01-07

    Immunotherapies exploit the immune system to target and kill cancer cells, while sparing healthy tissue. Antibody therapies, an important class of immunotherapies, involve the binding to specific antigens on the surface of the tumour cells of antibodies that activate natural killer (NK) cells to kill the tumour cells. Preclinical assessment of molecules that may cause antibody-dependent cellular cytotoxicity (ADCC) involves co-culturing cancer cells, NK cells and antibody in vitro for several hours and measuring subsequent levels of tumour cell lysis. Here we develop a mathematical model of such an in vitro ADCC assay, formulated as a system of time-dependent ordinary differential equations and in which NK cells kill cancer cells at a rate which depends on the amount of antibody bound to each cancer cell. Numerical simulations generated using experimentally-based parameter estimates reveal that the system evolves on two timescales: a fast timescale on which antibodies bind to receptors on the surface of the tumour cells, and NK cells form complexes with the cancer cells, and a longer time-scale on which the NK cells kill the cancer cells. We construct approximate model solutions on each timescale, and show that they are in good agreement with numerical simulations of the full system. Our results show how the processes involved in ADCC change as the initial concentration of antibody and NK-cancer cell ratio are varied. We use these results to explain what information about the tumour cell kill rate can be extracted from the cytotoxicity assays. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Sub-cellular force microscopy in single normal and cancer cells

    Energy Technology Data Exchange (ETDEWEB)

    Babahosseini, H. [VT MEMS Laboratory, The Bradley Department of Electrical and Computer Engineering, Blacksburg, VA 24061 (United States); Carmichael, B. [Nonlinear Intelligent Structures Laboratory, Department of Mechanical Engineering, University of Alabama, Tuscaloosa, AL 35487-0276 (United States); Strobl, J.S. [VT MEMS Laboratory, The Bradley Department of Electrical and Computer Engineering, Blacksburg, VA 24061 (United States); Mahmoodi, S.N., E-mail: nmahmoodi@eng.ua.edu [Nonlinear Intelligent Structures Laboratory, Department of Mechanical Engineering, University of Alabama, Tuscaloosa, AL 35487-0276 (United States); Agah, M., E-mail: agah@vt.edu [VT MEMS Laboratory, The Bradley Department of Electrical and Computer Engineering, Blacksburg, VA 24061 (United States)

    2015-08-07

    This work investigates the biomechanical properties of sub-cellular structures of breast cells using atomic force microscopy (AFM). The cells are modeled as a triple-layered structure where the Generalized Maxwell model is applied to experimental data from AFM stress-relaxation tests to extract the elastic modulus, the apparent viscosity, and the relaxation time of sub-cellular structures. The triple-layered modeling results allow for determination and comparison of the biomechanical properties of the three major sub-cellular structures between normal and cancerous cells: the up plasma membrane/actin cortex, the mid cytoplasm/nucleus, and the low nuclear/integrin sub-domains. The results reveal that the sub-domains become stiffer and significantly more viscous with depth, regardless of cell type. In addition, there is a decreasing trend in the average elastic modulus and apparent viscosity of the all corresponding sub-cellular structures from normal to cancerous cells, which becomes most remarkable in the deeper sub-domain. The presented modeling in this work constitutes a unique AFM-based experimental framework to study the biomechanics of sub-cellular structures. - Highlights: • The cells are modeled as a triple-layered structure using Generalized Maxwell model. • The sub-domains include membrane/cortex, cytoplasm/nucleus, and nuclear/integrin. • Biomechanics of corresponding sub-domains are compared among normal and cancer cells. • Viscoelasticity of sub-domains show a decreasing trend from normal to cancer cells. • The decreasing trend becomes most significant in the deeper sub-domain.

  4. Sub-cellular force microscopy in single normal and cancer cells.

    Science.gov (United States)

    Babahosseini, H; Carmichael, B; Strobl, J S; Mahmoodi, S N; Agah, M

    2015-08-07

    This work investigates the biomechanical properties of sub-cellular structures of breast cells using atomic force microscopy (AFM). The cells are modeled as a triple-layered structure where the Generalized Maxwell model is applied to experimental data from AFM stress-relaxation tests to extract the elastic modulus, the apparent viscosity, and the relaxation time of sub-cellular structures. The triple-layered modeling results allow for determination and comparison of the biomechanical properties of the three major sub-cellular structures between normal and cancerous cells: the up plasma membrane/actin cortex, the mid cytoplasm/nucleus, and the low nuclear/integrin sub-domains. The results reveal that the sub-domains become stiffer and significantly more viscous with depth, regardless of cell type. In addition, there is a decreasing trend in the average elastic modulus and apparent viscosity of the all corresponding sub-cellular structures from normal to cancerous cells, which becomes most remarkable in the deeper sub-domain. The presented modeling in this work constitutes a unique AFM-based experimental framework to study the biomechanics of sub-cellular structures. Copyright © 2015 Elsevier Inc. All rights reserved.

  5. CAF cellular glycolysis: linking cancer cells with the microenvironment.

    Science.gov (United States)

    Roy, Amrita; Bera, Soumen

    2016-07-01

    Cancers have long being hallmarked as cells relying heavily on their glycolysis for energy generation in spite of having functional mitochondria. The metabolic status of the cancer cells have been revisited time and again to get better insight into the overall carcinogenesis process which revealed the apparent crosstalks between the cancer cells with the fibroblasts present in the tumour microenvironment. This review focuses on the mechanisms of transformations of normal fibroblasts to cancer-associated fibroblasts (CAF), the participation of the CAF in tumour progression with special interest to the role of CAF cellular glycolysis in the overall tumorigenesis. The fibroblasts, when undergoes the transformation process, distinctly switches to a more glycolytic phenotype in order to provide the metabolic intermediates necessary for carrying out the mitochondrial pathways of ATP generation in cancer cells. This review will also discuss the molecular mechanisms responsible for this metabolic make over promoting glycolysis in CAF cells. A thorough investigation of the pathways and molecules involved will not only help in understanding the process of activation and metabolic reprogramming in CAF cells but also might open up new targets for cancer therapy.

  6. Defining the cellular precursors to human breast cancer

    Science.gov (United States)

    Keller, Patricia J.; Arendt, Lisa M.; Skibinski, Adam; Logvinenko, Tanya; Klebba, Ina; Dong, Shumin; Smith, Avi E.; Prat, Aleix; Perou, Charles M.; Gilmore, Hannah; Schnitt, Stuart; Naber, Stephen P.; Garlick, Jonathan A.; Kuperwasser, Charlotte

    2012-01-01

    Human breast cancers are broadly classified based on their gene-expression profiles into luminal- and basal-type tumors. These two major tumor subtypes express markers corresponding to the major differentiation states of epithelial cells in the breast: luminal (EpCAM+) and basal/myoepithelial (CD10+). However, there are also rare types of breast cancers, such as metaplastic carcinomas, where tumor cells exhibit features of alternate cell types that no longer resemble breast epithelium. Until now, it has been difficult to identify the cell type(s) in the human breast that gives rise to these various forms of breast cancer. Here we report that transformation of EpCAM+ epithelial cells results in the formation of common forms of human breast cancer, including estrogen receptor-positive and estrogen receptor-negative tumors with luminal and basal-like characteristics, respectively, whereas transformation of CD10+ cells results in the development of rare metaplastic tumors reminiscent of the claudin-low subtype. We also demonstrate the existence of CD10+ breast cells with metaplastic traits that can give rise to skin and epidermal tissues. Furthermore, we show that the development of metaplastic breast cancer is attributable, in part, to the transformation of these metaplastic breast epithelial cells. These findings identify normal cellular precursors to human breast cancers and reveal the existence of a population of cells with epidermal progenitor activity within adult human breast tissues. PMID:21940501

  7. Fracture of Cellular Media: A Foam Model

    Science.gov (United States)

    Hilgenfeldt, S.; Arif, S.; Tsai, J.

    2008-12-01

    Aqueous foam, almost entirely made of a Newtonian liquid and an ideal gas, shows surprisingly rich rheological behavior, including viscoelasticity and power-law shear thinning. The bubble mesostructure of the foam (seen as a cellular medium) is at the heart of the nontrivial rheology. Quantitative constitutive relations can be derived when properly accounting for the bubble geometry. Beyond linear and nonlinear rheology, we have investigated fracture in a quasi-two-dimensional foam sample as induced by the injection of additional fluid (gas). Depending on the rate and magnitude of applied pressure, the foam yields by either brittle or ductile fracture. The former is characterized by breaking thin films and small strains, the latter involves defect formation and motion (T1 transitions) without cell breakage. The experiments can be interpreted in two ways, both as a model of fracture in (regular, crystalline) atomic solids and as a model of failure in an (irregular, disordered) solid with heterogeneous domains, depending on the foam preparation and scale of the experiment. The latter view offers strong analogies to fracture of soil and its dependence on grain structure and water content.

  8. Mathematical deconvolution uncovers the genetic regulatory signal of cancer cellular heterogeneity on resistance to paclitaxel.

    Science.gov (United States)

    Morilla, Ian; Ranea, Juan A

    2017-08-01

    Drug resistance remains a major problem in combating malignancies, resulting critical the resistance to paclitaxel used in the treatment of many different cancers. Elucidating the cellular heterogeneity composition of tumours may be relevant to designing more effective treatment strategies on drug resistance. In particular, such heterogeneity correlates with the measurement of gene expression below the population level. However, experimental assays capturing differential response are limited and cannot discern the variation in gene expression specific to different cellular types in tumour populations. These limitations led us to consider a mathematical modelling approach, in which the gene expression of cellular subpopulations is recovered by deconvolution. Mathematically, the deconvolution is a multi-linear regression-based problem. We combined herein data on cellular subpopulation frequency composition with gene expression values from 16 tumour lines (8 resistant and 8 sensitive to paclitaxel treatment) to find genes that are differentially expressed between paclitaxel resistant and paclitaxel sensitive tumour lines in different cellular subpopulations. The results indicate that many genes differentially expressed between paclitaxel resistant and sensitive cancer lines are only detected when considering their heterogeneous cellular composition. Overall, our methodology is thought to keep in mind phenotypic heterogeneity improving our resolution in the identification of biomarkers on resistance to chemo-therapeutic agents.

  9. Analysis of Closed Social Structure Models using the Cellular Automaton

    OpenAIRE

    安達, 康生; 安高, 真一郎; 植松, 康祐; アダチ, ヤスオ; アタカ, シンイチロウ; ウエマツ, コウユウ; Adachi, Yasuo; Ataka, Shinichiro; Uematsu, Koyu

    2016-01-01

    The cellular automaton was created by John Von Neumann and Stanislaw Marcin Ulam. What Von Neumann was interested in was a machine which could replicate itself and the first such machine in the logical world was the Neumann cellular automaton. Since then, the cellular automaton has been expanded to many fields such as biology, history, and complex systems. This paper suggests closed social structure models with the method based on the cellular automaton. We succeeded in finding some interesti...

  10. Brain cancer incidence trends in relation to cellular telephone use in the United States

    Science.gov (United States)

    Inskip, Peter D.; Hoover, Robert N.; Devesa, Susan S.

    2010-01-01

    The use of cellular telephones has grown explosively during the past two decades, and there are now more than 279 million wireless subscribers in the United States. If cellular phone use causes brain cancer, as some suggest, the potential public health implications could be considerable. One might expect the effects of such a prevalent exposure to be reflected in general population incidence rates, unless the induction period is very long or confined to very long-term users. To address this issue, we examined temporal trends in brain cancer incidence rates in the United States, using data collected by the Surveillance, Epidemiology, and End Results (SEER) Program. Log-linear models were used to estimate the annual percent change in rates among whites. With the exception of the 20–29-year age group, the trends for 1992–2006 were downward or flat. Among those aged 20–29 years, there was a statistically significant increasing trend between 1992 and 2006 among females but not among males. The recent trend in 20–29-year-old women was driven by a rising incidence of frontal lobe cancers. No increases were apparent for temporal or parietal lobe cancers, or cancers of the cerebellum, which involve the parts of the brain that would be more highly exposed to radiofrequency radiation from cellular phones. Frontal lobe cancer rates also rose among 20–29-year-old males, but the increase began earlier than among females and before cell phone use was highly prevalent. Overall, these incidence data do not provide support to the view that cellular phone use causes brain cancer. PMID:20639214

  11. The Unique Molecular and Cellular Microenvironment of Ovarian Cancer

    Science.gov (United States)

    Worzfeld, Thomas; Pogge von Strandmann, Elke; Huber, Magdalena; Adhikary, Till; Wagner, Uwe; Reinartz, Silke; Müller, Rolf

    2017-01-01

    The reciprocal interplay of cancer cells and host cells is an indispensable prerequisite for tumor growth and progression. Cells of both the innate and adaptive immune system, in particular tumor-associated macrophages (TAMs) and T cells, as well as cancer-associated fibroblasts enter into a malicious liaison with tumor cells to create a tumor-promoting and immunosuppressive tumor microenvironment (TME). Ovarian cancer, the most lethal of all gynecological malignancies, is characterized by a unique TME that enables specific and efficient metastatic routes, impairs immune surveillance, and mediates therapy resistance. A characteristic feature of the ovarian cancer TME is the role of resident host cells, in particular activated mesothelial cells, which line the peritoneal cavity in huge numbers, as well as adipocytes of the omentum, the preferred site of metastatic lesions. Another crucial factor is the peritoneal fluid, which enables the transcoelomic spread of tumor cells to other pelvic and peritoneal organs, and occurs at more advanced stages as a malignancy-associated effusion. This ascites is rich in tumor-promoting soluble factors, extracellular vesicles and detached cancer cells as well as large numbers of T cells, TAMs, and other host cells, which cooperate with resident host cells to support tumor progression and immune evasion. In this review, we summarize and discuss our current knowledge of the cellular and molecular interactions that govern this interplay with a focus on signaling networks formed by cytokines, lipids, and extracellular vesicles; the pathophysiologial roles of TAMs and T cells; the mechanism of transcoelomic metastasis; and the cell type selective processing of signals from the TME. PMID:28275576

  12. A dynamic cellular vertex model of growing epithelial tissues

    Science.gov (United States)

    Lin, Shao-Zhen; Li, Bo; Feng, Xi-Qiao

    2017-04-01

    Intercellular interactions play a significant role in a wide range of biological functions and processes at both the cellular and tissue scales, for example, embryogenesis, organogenesis, and cancer invasion. In this paper, a dynamic cellular vertex model is presented to study the morphomechanics of a growing epithelial monolayer. The regulating role of stresses in soft tissue growth is revealed. It is found that the cells originating from the same parent cell in the monolayer can orchestrate into clustering patterns as the tissue grows. Collective cell migration exhibits a feature of spatial correlation across multiple cells. Dynamic intercellular interactions can engender a variety of distinct tissue behaviors in a social context. Uniform cell proliferation may render high and heterogeneous residual compressive stresses, while stress-regulated proliferation can effectively release the stresses, reducing the stress heterogeneity in the tissue. The results highlight the critical role of mechanical factors in the growth and morphogenesis of epithelial tissues and help understand the development and invasion of epithelial tumors.

  13. A Cellular Automata Models of Evolution of Transportation Networks

    Directory of Open Access Journals (Sweden)

    Mariusz Paszkowski

    2002-01-01

    Full Text Available We present a new approach to modelling of transportation networks. Supply of resources and their influence on the evolution of the consuming environment is a princqral problem considered. ne present two concepts, which are based on cellular automata paradigm. In the first model SCAM4N (Simple Cellular Automata Model of Anastomosing Network, the system is represented by a 2D mesh of elementary cells. The rules of interaction between them are introduced for modelling ofthe water flow and other phenomena connected with anastomosing river: Due to limitations of SCAMAN model, we introduce a supplementary model. The MANGraCA (Model of Anastomosing Network with Graph of Cellular Automata model beside the classical mesh of automata, introduces an additional structure: the graph of cellular automata, which represents the network pattern. Finally we discuss the prospective applications ofthe models. The concepts of juture implementation are also presented.

  14. Extended Cellular Automata Models of Particles and Space-Time

    Science.gov (United States)

    Beedle, Michael

    2005-04-01

    Models of particles and space-time are explored through simulations and theoretical models that use Extended Cellular Automata models. The expanded Cellular Automata Models consist go beyond simple scalar binary cell-fields, into discrete multi-level group representations like S0(2), SU(2), SU(3), SPIN(3,1). The propagation and evolution of these expanded cellular automatas are then compared to quantum field theories based on the "harmonic paradigm" i.e. built by an infinite number of harmonic oscillators, and with gravitational models.

  15. Fuzzy cellular model of signal controlled traffic stream

    OpenAIRE

    Płaczek, Bartłomiej

    2011-01-01

    Microscopic traffic models have recently gained considerable importance as a mean of optimising traffic control strategies. Computationally efficient and sufficiently accurate microscopic traffic models have been developed based on the cellular automata theory. However, the real-time application of the available cellular automata models in traffic control systems is a difficult task due to their discrete and stochastic nature. This paper introduces a novel method of traffic streams modelling,...

  16. Cannabinoids inhibit cellular respiration of human oral cancer cells.

    Science.gov (United States)

    Whyte, Donna A; Al-Hammadi, Suleiman; Balhaj, Ghazala; Brown, Oliver M; Penefsky, Harvey S; Souid, Abdul-Kader

    2010-01-01

    The primary cannabinoids, Delta(9)-tetrahydrocannabinol (Delta(9)-THC) and Delta(8)-tetrahydrocannabinol (Delta(8)-THC) are known to disturb the mitochondrial function and possess antitumor activities. These observations prompted us to investigate their effects on the mitochondrial O(2) consumption in human oral cancer cells (Tu183). This epithelial cell line overexpresses bcl-2 and is highly resistant to anticancer drugs. A phosphorescence analyzer that measures the time-dependence of O(2) concentration in cellular or mitochondrial suspensions was used for this purpose. A rapid decline in the rate of respiration was observed when Delta(9)-THC or Delta(8)-THC was added to the cells. The inhibition was concentration-dependent, and Delta(9)-THC was the more potent of the two compounds. Anandamide (an endocannabinoid) was ineffective; suggesting the effects of Delta(9)-THC and Delta(8)-THC were not mediated by the cannabinoidreceptors. Inhibition of O(2) consumption by cyanide confirmed the oxidations occurred in the mitochondrial respiratory chain. Delta(9)-THC inhibited the respiration of isolated mitochondria from beef heart. These results show the cannabinoids are potent inhibitors of Tu183 cellular respiration and are toxic to this highly malignant tumor.

  17. The effect of oral consumption of shark cartilage on the cellular immune responses of cancer patients

    Directory of Open Access Journals (Sweden)

    somaye Shahrokhi

    2006-11-01

    Conclusion: It seems that shark cartilage could help strengthen cellular immunity which is important in tumor regression in breast cancer patients. So we suppose that it could be a good candidate for cancer treatment along with conventional medicine.

  18. Human amniotic fluid-derived stem cells expressing cytosine deaminase and thymidine kinase inhibits the growth of breast cancer cells in cellular and xenograft mouse models.

    Science.gov (United States)

    Kang, N-H; Hwang, K-A; Yi, B-R; Lee, H J; Jeung, E-B; Kim, S U; Choi, K-C

    2012-06-01

    As human amniotic fluid-derived stem cells (hAFSCs) are capable of multiple lineage differentiation, extensive self-renewal and tumor targeting, they may be valuable for clinical anticancer therapies. In this study, we used hAFSCs as vehicles for targeted delivery of therapeutic suicide genes to breast cancer cells. hAFSCs were engineered to produce AF2.CD-TK cells in order to express two suicide genes encoding bacterial cytosine deaminase (CD) and herpes simplex virus thymidine kinase (HSV-TK) that convert non-toxic prodrugs, 5-fluorocytosine (5-FC) and mono-phosphorylate ganciclovir (GCV-MP), into cytotoxic metabolites, 5-fluorouracil (5-FU) and triphosphate ganciclovir (GCV-TP), respectively. In cell viability test in vitro, AF2.CD-TK cells inhibited the growth of MDA-MB-231 human breast cancer cells in the presence of the 5-FC or GCV prodrugs, or a combination of these two reagents. When the mixture of 5-FC and GCV was treated together, an additive cytotoxic effect was observed in the cell viability. In animal experiments using female BALB/c nude mouse xenografts, which developed by injecting MDA-MB-231 cells, treatment with AF2.CD-TK cells in the presence of 5-FC and GCV significantly reduced tumor volume and weight to the same extent seen in the mice treated with 5-FU. Histopathological and fluorescent staining assays further showed that AF2.CD-TK cells were located exactly at the site of tumor formation. Furthermore, breast tissues treated with AF2.CD-TK cells and two prodrugs maintained their normal structures (for example, the epidermis and reticular layers) while breast tissue structures in 5-FU-treated mice were almost destroyed by the potent cytotoxicity of the drug. Taken together, these results indicate that AF2.CD-TK cells can serve as excellent vehicles in a novel therapeutic cell-based gene-directed prodrug system to selectively target breast malignancies.

  19. Modeling and Analysis of Cellular CDMA Forward Channel

    National Research Council Canada - National Science Library

    Tighe, Jan

    2001-01-01

    In this thesis, we develop the forward channel model for a DS-CDMA cellular system operating in a slow-flat Rayleigh fading and log normal shadowing environment, which incorporates the extended Hata...

  20. Cellular Potts modeling of complex multicellular behaviors in tissue morphogenesis

    NARCIS (Netherlands)

    T. Hirashima (Tsuyoshi); E.G. Rens (Lisanne); R.M.H. Merks (Roeland)

    2017-01-01

    textabstractMathematical modeling is an essential approach for the understanding of complex multicellular behaviors in tissue morphogenesis. Here, we review the cellular Potts model (CPM; also known as the Glazier-Graner-Hogeweg model), an effective computational modeling framework. We discuss its

  1. Cellular automaton for realistic modelling of landslides

    CERN Document Server

    Segrè, E; Enrico Segre; Chiara Deangeli

    1994-01-01

    We develop a numerical model for the simulation of debris flow in landslides over a complex three dimensional topography. The model is based on a lattice, in which debris can be transferred among nearest neighbours according to established empirical relationships for granular flows. The model is validated comparing its results with reported field data. Our model is in fact a realistic elaboration of simpler ``sandpile automata'', which have in recent years been studied as supposedly paradigmatic of ``self organized criticality''. Statistics and scaling properties of the simulation are examined, showing that the model has an intermittent behaviour.

  2. Mapping of cellular iron using hyperspectral fluorescence imaging in a cellular model of Parkinson's disease

    Science.gov (United States)

    Oh, Eung Seok; Heo, Chaejeong; Kim, Ji Seon; Lee, Young Hee; Kim, Jong Min

    2013-05-01

    Parkinson's disease (PD) is characterized by progressive dopaminergic cell loss in the substantianigra (SN) and elevated iron levels demonstrated by autopsy and with 7-Tesla magnetic resonance imaging. Direct visualization of iron with live imaging techniques has not yet been successful. The aim of this study is to visualize and quantify the distribution of cellular iron using an intrinsic iron hyperspectral fluorescence signal. The 1-methyl-4-phenylpyridinium (MPP+)-induced cellular model of PD was established in SHSY5Y cells. The cells were exposed to iron by treatment with ferric ammonium citrate (FAC, 100 μM) for up to 6 hours. The hyperspectral fluorescence imaging signal of iron was examined usinga high- resolution dark-field optical microscope system with signal absorption for the visible/ near infrared (VNIR) spectral range. The 6-hour group showed heavy cellular iron deposition compared with the small amount of iron accumulation in the 1-hour group. The cellular iron was dispersed in a small, particulate form, whereas extracellular iron was detected in an aggregated form. In addition, iron particles were found to be concentrated on the cell membrane/edge of shrunken cells. The cellular iron accumulation readily occurred in MPP+-induced cells, which is consistent with previous studies demonstrating elevated iron levels in the SN in PD. This direct iron imaging methodology could be applied to analyze the physiological role of iron in PD, and its application might be expanded to various neurological disorders involving other metals, such as copper, manganese or zinc.

  3. Animal models of ovarian cancer

    Directory of Open Access Journals (Sweden)

    Shaw Tanya J

    2003-10-01

    Full Text Available Abstract Ovarian cancer is the most lethal of all of the gynecological cancers and can arise from any cell type of the ovary, including germ cells, granulosa or stromal cells. However, the majority of ovarian cancers arise from the surface epithelium, a single layer of cells that covers the surface of the ovary. The lack of a reliable and specific method for the early detection of epithelial ovarian cancer results in diagnosis occurring most commonly at late clinical stages, when treatment is less effective. In part, the deficiency in diagnostic tools is due to the lack of markers for the detection of preneoplastic or early neoplastic changes in the epithelial cells, which reflects our rather poor understanding of this process. Animal models which accurately represent the cellular and molecular changes associated with the initiation and progression of human ovarian cancer have significant potential to facilitate the development of better methods for the early detection and treatment of ovarian cancer. This review describes some of the experimental animal models of ovarian tumorigenesis that have been reported, including those involving specific reproductive factors and environmental toxins. Consideration has also been given to the recent progress in modeling ovarian cancer using genetically engineered mice.

  4. Computational model of cellular metabolic dynamics

    DEFF Research Database (Denmark)

    Li, Yanjun; Solomon, Thomas; Haus, Jacob M

    2010-01-01

    , by application of mechanism M.3, the model predicts metabolite concentration changes and glucose partitioning patterns consistent with experimental data. The reaction rate fluxes quantified by this detailed model of insulin/glucose metabolism provide information that can be used to evaluate the development......, pyruvate dehydrogenase); or M.3, parallel activation by a phenomenological insulin-mediated intracellular signal that modifies reaction rate coefficients. These simulations indicated that models M.1 and M.2 were not sufficient to explain the experimentally measured metabolic responses. However...... of the cytosol and mitochondria. The model simulated skeletal muscle metabolic responses to insulin corresponding to human hyperinsulinemic-euglycemic clamp studies. Insulin-mediated rate of glucose disposal was the primary model input. For model validation, simulations were compared with experimental data...

  5. Agent-Based Modeling of Mitochondria Links Sub-Cellular Dynamics to Cellular Homeostasis and Heterogeneity.

    Directory of Open Access Journals (Sweden)

    Giovanni Dalmasso

    Full Text Available Mitochondria are semi-autonomous organelles that supply energy for cellular biochemistry through oxidative phosphorylation. Within a cell, hundreds of mobile mitochondria undergo fusion and fission events to form a dynamic network. These morphological and mobility dynamics are essential for maintaining mitochondrial functional homeostasis, and alterations both impact and reflect cellular stress states. Mitochondrial homeostasis is further dependent on production (biogenesis and the removal of damaged mitochondria by selective autophagy (mitophagy. While mitochondrial function, dynamics, biogenesis and mitophagy are highly-integrated processes, it is not fully understood how systemic control in the cell is established to maintain homeostasis, or respond to bioenergetic demands. Here we used agent-based modeling (ABM to integrate molecular and imaging knowledge sets, and simulate population dynamics of mitochondria and their response to environmental energy demand. Using high-dimensional parameter searches we integrated experimentally-measured rates of mitochondrial biogenesis and mitophagy, and using sensitivity analysis we identified parameter influences on population homeostasis. By studying the dynamics of cellular subpopulations with distinct mitochondrial masses, our approach uncovered system properties of mitochondrial populations: (1 mitochondrial fusion and fission activities rapidly establish mitochondrial sub-population homeostasis, and total cellular levels of mitochondria alter fusion and fission activities and subpopulation distributions; (2 restricting the directionality of mitochondrial mobility does not alter morphology subpopulation distributions, but increases network transmission dynamics; and (3 maintaining mitochondrial mass homeostasis and responding to bioenergetic stress requires the integration of mitochondrial dynamics with the cellular bioenergetic state. Finally, (4 our model suggests sources of, and stress conditions

  6. Hyperelastic models for hydration of cellular tissue

    NARCIS (Netherlands)

    Sman, Van Der R.G.M.

    2015-01-01

    In this paper we present hyperelastic models for swelling elastic shells, due to pressurization of the internal cavity. These shells serve as model systems for cells having cell walls, as can be found in bacteria, plants and fungi. The pressurized internal cavity represents the cell vacuole with

  7. Senescence-Inflammatory Regulation of Reparative Cellular Reprogramming in Aging and Cancer.

    Science.gov (United States)

    Menendez, Javier A; Alarcón, Tomás

    2017-01-01

    The inability of adult tissues to transitorily generate cells with functional stem cell-like properties is a major obstacle to tissue self-repair. Nuclear reprogramming-like phenomena that induce a transient acquisition of epigenetic plasticity and phenotype malleability may constitute a reparative route through which human tissues respond to injury, stress, and disease. However, tissue rejuvenation should involve not only the transient epigenetic reprogramming of differentiated cells, but also the committed re-acquisition of the original or alternative committed cell fate. Chronic or unrestrained epigenetic plasticity would drive aging phenotypes by impairing the repair or the replacement of damaged cells; such uncontrolled phenomena of in vivo reprogramming might also generate cancer-like cellular states. We herein propose that the ability of senescence-associated inflammatory signaling to regulate in vivo reprogramming cycles of tissue repair outlines a threshold model of aging and cancer. The degree of senescence/inflammation-associated deviation from the homeostatic state may delineate a type of thresholding algorithm distinguishing beneficial from deleterious effects of in vivo reprogramming. First, transient activation of NF-κB-related innate immunity and senescence-associated inflammatory components (e.g., IL-6) might facilitate reparative cellular reprogramming in response to acute inflammatory events. Second, para-inflammation switches might promote long-lasting but reversible refractoriness to reparative cellular reprogramming. Third, chronic senescence-associated inflammatory signaling might lock cells in highly plastic epigenetic states disabled for reparative differentiation. The consideration of a cellular reprogramming-centered view of epigenetic plasticity as a fundamental element of a tissue's capacity to undergo successful repair, aging degeneration or malignant transformation should provide challenging stochastic insights into the current

  8. Senescence-Inflammatory Regulation of Reparative Cellular Reprogramming in Aging and Cancer

    Directory of Open Access Journals (Sweden)

    Javier A. Menendez

    2017-05-01

    Full Text Available The inability of adult tissues to transitorily generate cells with functional stem cell-like properties is a major obstacle to tissue self-repair. Nuclear reprogramming-like phenomena that induce a transient acquisition of epigenetic plasticity and phenotype malleability may constitute a reparative route through which human tissues respond to injury, stress, and disease. However, tissue rejuvenation should involve not only the transient epigenetic reprogramming of differentiated cells, but also the committed re-acquisition of the original or alternative committed cell fate. Chronic or unrestrained epigenetic plasticity would drive aging phenotypes by impairing the repair or the replacement of damaged cells; such uncontrolled phenomena of in vivo reprogramming might also generate cancer-like cellular states. We herein propose that the ability of senescence-associated inflammatory signaling to regulate in vivo reprogramming cycles of tissue repair outlines a threshold model of aging and cancer. The degree of senescence/inflammation-associated deviation from the homeostatic state may delineate a type of thresholding algorithm distinguishing beneficial from deleterious effects of in vivo reprogramming. First, transient activation of NF-κB-related innate immunity and senescence-associated inflammatory components (e.g., IL-6 might facilitate reparative cellular reprogramming in response to acute inflammatory events. Second, para-inflammation switches might promote long-lasting but reversible refractoriness to reparative cellular reprogramming. Third, chronic senescence-associated inflammatory signaling might lock cells in highly plastic epigenetic states disabled for reparative differentiation. The consideration of a cellular reprogramming-centered view of epigenetic plasticity as a fundamental element of a tissue's capacity to undergo successful repair, aging degeneration or malignant transformation should provide challenging stochastic insights

  9. Multiple Molecular and Cellular Mechanisms of Action of Lycopene in Cancer Inhibition

    Directory of Open Access Journals (Sweden)

    Cristina Trejo-Solís

    2013-01-01

    Full Text Available Epidemiological studies suggest that including fruits, vegetables, and whole grains in regular dietary intake might prevent and reverse cellular carcinogenesis, reducing the incidence of primary tumours. Bioactive components present in food can simultaneously modulate more than one carcinogenic process, including cancer metabolism, hormonal balance, transcriptional activity, cell-cycle control, apoptosis, inflammation, angiogenesis and metastasis. Some studies have shown an inverse correlation between a diet rich in fruits, vegetables, and carotenoids and a low incidence of different types of cancer. Lycopene, the predominant carotenoid found in tomatoes, exhibits a high antioxidant capacity and has been shown to prevent cancer, as evidenced by clinical trials and studies in cell culture and animal models. In vitro studies have shown that lycopene treatment can selectively arrest cell growth and induce apoptosis in cancer cells without affecting normal cells. In vivo studies have revealed that lycopene treatment inhibits tumour growth in the liver, lung, prostate, breast, and colon. Clinical studies have shown that lycopene protects against prostate cancer. One of the main challenges in cancer prevention is the integration of new molecular findings into clinical practice. Thus, the identification of molecular biomarkers associated with lycopene levels is essential for improving our understanding of the mechanisms underlying its antineoplastic activity.

  10. A cellular automaton model of wildfire propagation and extinction

    Science.gov (United States)

    Keith C. Clarke; James A. Brass; Phillip J. Riggan

    1994-01-01

    We propose a new model to predict the spatial and temporal behavior of wildfires. Fire spread and intensity were simulated using a cellular automaton model. Monte Carlo techniques were used to provide fire risk probabilities for areas where fuel loadings and topography are known. The model assumes predetermined or measurable environmental variables such as wind...

  11. Modeling urban expansion by using variable weights logistic cellular automata

    NARCIS (Netherlands)

    Shu, Bangrong; Bakker, Martha M.; Zhang, Honghui; Li, Yongle; Qin, Wei; Carsjens, Gerrit J.

    2017-01-01

    Simulation models based on cellular automata (CA) are widely used for understanding and simulating complex urban expansion process. Among these models, logistic CA (LCA) is commonly adopted. However, the performance of LCA models is often limited because the fixed coefficients obtained from binary

  12. Modeling Evacuation of Emergency Vehicles by Cellular Automata Models

    Science.gov (United States)

    Moussa, Najem

    An evacuation of the emergency vehicle (EV) from an origin point (e.g., accident location) to a destination point (e.g., hospital) in lower and higher congestions is simulated using city cellular automata models. We find that the mean speed of the EV and its arrival time all depend enormously on the cars density, the route length of the EV and the turn capability of the cars. Dangerous situations that occurred during the evacuation of the EV are also investigated. By allowing high turning capabilities to cars, considerable improvements are obtained. Indeed, the EV mean speed is enhanced and its arrival time is optimized. Moreover, at relatively high density, a significant reduction of the risk of accident is expected.

  13. Minimal model for complex dynamics in cellular processes

    Science.gov (United States)

    Suguna, C.; Chowdhury, Kanchan K.; Sinha, Somdatta

    1999-11-01

    Cellular functions are controlled and coordinated by the complex circuitry of biochemical pathways regulated by genetic and metabolic feedback processes. This paper aims to show, with the help of a minimal model of a regulated biochemical pathway, that the common nonlinearities and control structures present in biomolecular interactions are capable of eliciting a variety of functional dynamics, such as homeostasis, periodic, complex, and chaotic oscillations, including transients, that are observed in various cellular processes.

  14. Stiffening response of a cellular tensegrity model.

    Science.gov (United States)

    Wendling, S; Oddou, C; Isabey, D

    1999-02-07

    Living cells exhibit, as most biological tissues, a stiffening (strain-hardening) response which reflects the nonlinearity of the stress-strain relationship. Tensegrity structures have been proposed as a comprehensive model of such a cell's mechanical response. Based on a theoretical model of a 30-element tensegrity structure, we propose a quantitative analysis of its nonlinear mechanical behavior under static conditions and large deformations. This study provides theoretical foundation to the passage from large-scale tensegrity models to microscale living cells, as well as the comparison between results obtained in biological specimens of different sizes. We found two non-dimensional parameters (L*-normalized element length and T*-normalized elastic tension) which govern the mechanical response of the structure for three types of loading tested (extension, compression and shear). The linear strain-hardening is uniquely observed for extension but differed for the two other types of loading tested. The stiffening response of the theoretical model was compared and discussed with the living cells stiffening response observed by different methods (shear flow experiments, micromanipulation and magnetocytometry).

  15. Cellular Automaton Model for Immunology of Tumor Growth

    CERN Document Server

    Voitikova, M

    1998-01-01

    The stochastic discrete space-time model of an immune response on tumor spreading in a two-dimensional square lattice has been developed. The immunity-tumor interactions are described at the cellular level and then transferred into the setting of cellular automata (CA). The multistate CA model for system, in which all statesoflattice sites, composing of both immune and tumor cells populations, are the functions of the states of the 12 nearest neighbors. The CA model incorporates the essential featuresof the immunity-tumor system. Three regimes of neoplastic evolution including metastatic tumor growth and screen effect by inactive immune cells surrounding a tumor have been predicted.

  16. Cellular and Developmental Biology of TRPM7 Channel-Kinase: Implicated Roles in Cancer

    Directory of Open Access Journals (Sweden)

    Nelson S. Yee

    2014-07-01

    Full Text Available The transient receptor potential melastatin-subfamily member 7 (TRPM7 is a ubiquitously expressed cation-permeable ion channel with intrinsic kinase activity that plays important roles in various physiological functions. Biochemical and electrophysiological studies, in combination with molecular analyses of TRPM7, have generated insights into its functions as a cellular sensor and transducer of physicochemical stimuli. Accumulating evidence indicates that TRPM7 channel-kinase is essential for cellular processes, such as proliferation, survival, differentiation, growth, and migration. Experimental studies in model organisms, such as zebrafish, mouse, and frog, have begun to elucidate the pleiotropic roles of TRPM7 during embryonic development from gastrulation to organogenesis. Aberrant expression and/or activity of the TRPM7 channel-kinase have been implicated in human diseases including a variety of cancer. Studying the functional roles of TRPM7 and the underlying mechanisms in normal cells and developmental processes is expected to help understand how TRPM7 channel-kinase contributes to pathogenesis, such as malignant neoplasia. On the other hand, studies of TRPM7 in diseases, particularly cancer, will help shed new light in the normal functions of TRPM7 under physiological conditions. In this article, we will provide an updated review of the structural features and biological functions of TRPM7, present a summary of current knowledge of its roles in development and cancer, and discuss the potential of TRPM7 as a clinical biomarker and therapeutic target in malignant diseases.

  17. Physical Model of Cellular Symmetry Breaking

    Science.gov (United States)

    van der Gucht, Jasper; Sykes, Cécile

    2009-01-01

    Cells can polarize in response to external signals, such as chemical gradients, cell–cell contacts, and electromagnetic fields. However, cells can also polarize in the absence of an external cue. For example, a motile cell, which initially has a more or less round shape, can lose its symmetry spontaneously even in a homogeneous environment and start moving in random directions. One of the principal determinants of cell polarity is the cortical actin network that underlies the plasma membrane. Tension in this network generated by myosin motors can be relaxed by rupture of the shell, leading to polarization. In this article, we discuss how simplified model systems can help us to understand the physics that underlie the mechanics of symmetry breaking. PMID:20066077

  18. Modeling integrated cellular machinery using hybrid Petri-Boolean networks.

    Directory of Open Access Journals (Sweden)

    Natalie Berestovsky

    Full Text Available The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and produces valid hypotheses. The abstract nature of our model and the ease of its construction makes it a very good candidate for modeling integrated networks from qualitative data. The results it produces can guide the practitioner to zoom into components and interconnections and investigate them

  19. Lattice gas cellular automata and lattice Boltzmann models an introduction

    CERN Document Server

    Wolf-Gladrow, Dieter A

    2000-01-01

    Lattice-gas cellular automata (LGCA) and lattice Boltzmann models (LBM) are relatively new and promising methods for the numerical solution of nonlinear partial differential equations. The book provides an introduction for graduate students and researchers. Working knowledge of calculus is required and experience in PDEs and fluid dynamics is recommended. Some peculiarities of cellular automata are outlined in Chapter 2. The properties of various LGCA and special coding techniques are discussed in Chapter 3. Concepts from statistical mechanics (Chapter 4) provide the necessary theoretical background for LGCA and LBM. The properties of lattice Boltzmann models and a method for their construction are presented in Chapter 5.

  20. Cellular Morphology-Mediated Proliferation and Drug Sensitivity of Breast Cancer Cells

    Directory of Open Access Journals (Sweden)

    Ryota Domura

    2017-06-01

    Full Text Available The interpretation of the local microenvironment of the extracellular matrix for malignant tumor cells is in intimate relation with metastatic spread of cancer cells involving the associated issues of cellular proliferation and drug responsiveness. This study was aimed to assess the combination of both surface topographies (fiber alignments and different stiffness of the polymeric substrates (poly(l-lactic acid and poly(ε-caprolactone, PLLA and PCL, respectively as well as collagen substrates (coat and gel to elucidate the effect of the cellular morphology on cellular proliferation and drug sensitivities of two different types of breast cancer cells (MDA-MB-231 and MCF-7. The morphological spreading parameter (nucleus/cytoplasm area ratio induced by the anthropogenic substrates has correlated intimately with the cellular proliferation and the drug sensitivity the half maximal inhibitory concentration (IC50 of cancer cells. This study demonstrated the promising results of the parameter for the evaluation of cancer cell malignancy.

  1. Obesity and cancer: At the crossroads of cellular metabolism and proliferation

    Science.gov (United States)

    O’Rourke, Robert W.

    2014-01-01

    Obesity is associated with an increased risk of cancer. The mechanisms underlying this association include but are not limited to increased systemic inflammation, an anabolic hormonal milieu, and adipocyte-cancer crosstalk, aberrant stimuli that conspire to promote neoplastic transformation. Cellular proliferation is uncoupled from nutrient availability in malignant cells, promoting tumor progression. Elucidation of the mechanisms underlying the obesity-cancer connection will lead to the development of novel metabolism-based agents for cancer prevention and treatment. PMID:25264328

  2. Cellular origin and procoagulant activity of tissue factor-exposing microparticles in cancer patients

    NARCIS (Netherlands)

    Kleinjan, A.; Berckmans, R.J.; Böing, A.N.; Sturk, A.; Büller, H.R.; Kamphuisen, P.W.; Nieuwland, R.

    2012-01-01

    Background: In patients with cancer, tissue factor-exposing microparticles (TF-exposing MP) have been associated with disease progression and thrombosis. The cellular origin and coagulant activity of TF-exposing MP, however, remain disputed. Therefore, we investigated the cellular origin of the

  3. A sub-cellular viscoelastic model for cell population mechanics.

    Directory of Open Access Journals (Sweden)

    Yousef Jamali

    Full Text Available Understanding the biomechanical properties and the effect of biomechanical force on epithelial cells is key to understanding how epithelial cells form uniquely shaped structures in two or three-dimensional space. Nevertheless, with the limitations and challenges posed by biological experiments at this scale, it becomes advantageous to use mathematical and 'in silico' (computational models as an alternate solution. This paper introduces a single-cell-based model representing the cross section of a typical tissue. Each cell in this model is an individual unit containing several sub-cellular elements, such as the elastic plasma membrane, enclosed viscoelastic elements that play the role of cytoskeleton, and the viscoelastic elements of the cell nucleus. The cell membrane is divided into segments where each segment (or point incorporates the cell's interaction and communication with other cells and its environment. The model is capable of simulating how cells cooperate and contribute to the overall structure and function of a particular tissue; it mimics many aspects of cellular behavior such as cell growth, division, apoptosis and polarization. The model allows for investigation of the biomechanical properties of cells, cell-cell interactions, effect of environment on cellular clusters, and how individual cells work together and contribute to the structure and function of a particular tissue. To evaluate the current approach in modeling different topologies of growing tissues in distinct biochemical conditions of the surrounding media, we model several key cellular phenomena, namely monolayer cell culture, effects of adhesion intensity, growth of epithelial cell through interaction with extra-cellular matrix (ECM, effects of a gap in the ECM, tensegrity and tissue morphogenesis and formation of hollow epithelial acini. The proposed computational model enables one to isolate the effects of biomechanical properties of individual cells and the

  4. Cancer metabolism: a modeling perspective

    Directory of Open Access Journals (Sweden)

    Pouyan eGhaffari Nouran

    2015-12-01

    Full Text Available Tumor cells alter their metabolism to maintain unregulated cellular proliferation and survival, but this transformation leaves them reliant on constant supply of nutrients and energy. In addition to the widely studied dysregulated glucose metabolism to fuel tumor cell growth, accumulating evidences suggest that utilization of amino acids and lipids contributes significantly to cancer cell metabolism. Also recent progresses in our understanding of carcinogenesis have revealed that cancer is a complex disease and cannot be understood through simple investigation of genetic mutations of cancerous cells. Cancer cells present in complex tumor tissues communicate with the surrounding microenvironment and develop traits which promote their growth, survival and metastasis. Decoding the full scope and targeting dysregulated metabolic pathways that support neoplastic transformations and their preservation requires both the advancement of experimental technologies for more comprehensive measurement of omics as well as the advancement of robust computational methods for accurate analysis of the generated data. Here, we review cancer-associated reprogramming of metabolism and highlight the capability of genome-scale metabolic modeling approaches in perceiving a system-level perspective of cancer metabolism and in detecting novel selective drug targets

  5. Tracking cellular telephones as an input for developing transport models

    CSIR Research Space (South Africa)

    Cooper, Antony K

    2010-08-01

    Full Text Available of tracking cellular telephones and using the data to populate transport and other models. We report here on one of the pilots, known as DYNATRACK (Dynamic Daily Path Tracking), a larger experiment conducted in 2007 with a more heterogeneous group of commuters...

  6. A generalized cellular automata approach to modeling first order ...

    Indian Academy of Sciences (India)

    kuleuven.be ... is observed that cellular automata can capture the essential features of a discrete real system, consisting of space, time and ... istry, can be achieved through stochastic modeling (Seybold et al 1997). In fact, the intrinsic nature of any ...

  7. Radio Channel Modelling for UAV Communication over Cellular Networks

    DEFF Research Database (Denmark)

    Amorim, Rafhael Medeiros de; Nguyen, Huan Cong; Mogensen, Preben Elgaard

    2017-01-01

    The main goal of this paper is to obtain models for path loss exponents and shadowing for the radio channel between airborne Unmanned Aerial Vehicles (UAVs) and cellular networks. In this pursuit, field measurements were conducted in live LTE networks at the 800 MHz frequency band, using a commer...

  8. Complex Automata: Multi-scale Modeling with Coupled Cellular Automata

    NARCIS (Netherlands)

    Hoekstra, A.G.; Caiazzo, A.; Lorenz, E.; Falcone, J.-L.; Chopard, B.; Hoekstra, A.G.; Kroc, J.; Sloot, P.M.A.

    2010-01-01

    Cellular Automata (CA) are generally acknowledged to be a powerful way to describe and model natural phenomena [1-3]. There are even tempting claims that nature itself is one big (quantum) information processing system, e.g. [4], and that CA may actually be nature’s way to do this processing [5-7].

  9. Modelling and analyzing the watershed dynamics using Cellular ...

    Indian Academy of Sciences (India)

    Improper practices of land use and land cover (LULC) including deforestation, expansion of agriculture and infrastructure development are deteriorating watershed conditions. Here, we have utilized remote sensing and GIS tools to study LULC dynamics using Cellular Automata (CA)–Markov model and predicted the future ...

  10. Common Genetic Variation In Cellular Transport Genes and Epithelial Ovarian Cancer (EOC Risk.

    Directory of Open Access Journals (Sweden)

    Ganna Chornokur

    Full Text Available Defective cellular transport processes can lead to aberrant accumulation of trace elements, iron, small molecules and hormones in the cell, which in turn may promote the formation of reactive oxygen species, promoting DNA damage and aberrant expression of key regulatory cancer genes. As DNA damage and uncontrolled proliferation are hallmarks of cancer, including epithelial ovarian cancer (EOC, we hypothesized that inherited variation in the cellular transport genes contributes to EOC risk.In total, DNA samples were obtained from 14,525 case subjects with invasive EOC and from 23,447 controls from 43 sites in the Ovarian Cancer Association Consortium (OCAC. Two hundred seventy nine SNPs, representing 131 genes, were genotyped using an Illumina Infinium iSelect BeadChip as part of the Collaborative Oncological Gene-environment Study (COGS. SNP analyses were conducted using unconditional logistic regression under a log-additive model, and the FDR q<0.2 was applied to adjust for multiple comparisons.The most significant evidence of an association for all invasive cancers combined and for the serous subtype was observed for SNP rs17216603 in the iron transporter gene HEPH (invasive: OR = 0.85, P = 0.00026; serous: OR = 0.81, P = 0.00020; this SNP was also associated with the borderline/low malignant potential (LMP tumors (P = 0.021. Other genes significantly associated with EOC histological subtypes (p<0.05 included the UGT1A (endometrioid, SLC25A45 (mucinous, SLC39A11 (low malignant potential, and SERPINA7 (clear cell carcinoma. In addition, 1785 SNPs in six genes (HEPH, MGST1, SERPINA, SLC25A45, SLC39A11 and UGT1A were imputed from the 1000 Genomes Project and examined for association with INV EOC in white-European subjects. The most significant imputed SNP was rs117729793 in SLC39A11 (per allele, OR = 2.55, 95% CI = 1.5-4.35, p = 5.66x10-4.These results, generated on a large cohort of women, revealed associations between inherited cellular

  11. A predictive model of pathologic response based on tumor cellularity and tumor-infiltrating lymphocytes (CelTIL) in HER2-positive breast cancer treated with chemo-free dual HER2 blockade.

    Science.gov (United States)

    Nuciforo, P; Pascual, T; Cortés, J; Llombart-Cussac, A; Fasani, R; Paré, L; Oliveira, M; Galvan, P; Martínez, N; Bermejo, B; Vidal, M; Pernas, S; López, R; Muñoz, M; Garau, I; Manso, L; Alarcón, J; Martínez, E; Rodrik-Outmezguine, V; Brase, J C; Villagrasa, P; Prat, A; Holgado, E

    2018-01-01

    The presence of stromal tumor-infiltrating lymphocytes (TILs) is associated with increased pathologic complete response (pCR) and improved outcomes in HER2-positive early-breast cancer (BC) treated with anti-HER2-based chemotherapy. In the absence of chemotherapy, the association of TILs with pCR following anti-HER2 therapy-only is largely unknown. The PAMELA neoadjuvant trial treated 151 women with HER2-positive BC with lapatinib and trastuzumab [and hormonal therapy if hormone receptor (HR)-positive] for 18 weeks. Percentage of TILs and tumor cellularity were determined at baseline (N = 148) and at day 15 (D15) of treatment (N = 134). Associations of TILs and tumor cellularity with pCR in the breast were evaluated. A combined score based on tumor cellularity and TILs (CelTIL) measured at D15 was derived in PAMELA, and validated in D15 samples from 65 patients with HER2-positive disease recruited in the LPT109096 neoadjuvant trial, where anti-HER2 therapy-only was administer for 2 weeks, then standard chemotherapy was added for 24 weeks. In PAMELA, baseline and D15 TILs were significantly associated with pCR in univariate analysis. In multivariable analysis, D15 TILs, but not baseline TILs, were significantly associated with pCR. At D15, TILs and tumor cellularity were found independently associated with pCR. A combined score (CelTIL) taking into account both variables was derived. CelTIL at D15 as a continuous variable was significantly associated with pCR, and patients with CelTIL-low and CelTIL-high scores had a pCR rate of 0% and 33%, respectively. In LPT109096, CelTIL at D15 was found associated with pCR both as a continuous variable and as group categories using a pre-defined cut-off (75.0% versus 33.3%). On-treatment TILs, but not baseline TILs, are independently associated with response following anti-HER2 therapy-only. A combined score of TILs and tumor cellularity measured at D15 provides independent predictive information upon completion

  12. Modeling cellular networks in fading environments with dominant specular components

    KAUST Repository

    AlAmmouri, Ahmad

    2016-07-26

    Stochastic geometry (SG) has been widely accepted as a fundamental tool for modeling and analyzing cellular networks. However, the fading models used with SG analysis are mainly confined to the simplistic Rayleigh fading, which is extended to the Nakagami-m fading in some special cases. However, neither the Rayleigh nor the Nakagami-m accounts for dominant specular components (DSCs) which may appear in realistic fading channels. In this paper, we present a tractable model for cellular networks with generalized two-ray (GTR) fading channel. The GTR fading explicitly accounts for two DSCs in addition to the diffuse components and offers high flexibility to capture diverse fading channels that appear in realistic outdoor/indoor wireless communication scenarios. It also encompasses the famous Rayleigh and Rician fading as special cases. To this end, the prominent effect of DSCs is highlighted in terms of average spectral efficiency. © 2016 IEEE.

  13. Novel Immune-Modulating Cellular Vaccine for Prostate Cancer Immunotherapy

    Science.gov (United States)

    2015-10-01

    immune checkpoint blockade, local CTLA-4 modulation, prostate cancer immunotherapy, prostatic acid phosphatase (PAP), RNA-based vaccines 16...immune checkpoint blockade, local CTLA4 modulation, prostate cancer immunotherapy, prostatic acid phosphatase (PAP), and RNA-based vaccines OVERALL...months): Harvest tumors from 30-week old mice to analyze tumor weight , tumor grade, tumor apoptosis and immune infiltrates and harvest mouse organs

  14. A cellular automata model of Ebola virus dynamics

    Science.gov (United States)

    Burkhead, Emily; Hawkins, Jane

    2015-11-01

    We construct a stochastic cellular automaton (SCA) model for the spread of the Ebola virus (EBOV). We make substantial modifications to an existing SCA model used for HIV, introduced by others and studied by the authors. We give a rigorous analysis of the similarities between models due to the spread of virus and the typical immune response to it, and the differences which reflect the drastically different timing of the course of EBOV. We demonstrate output from the model and compare it with clinical data.

  15. Simulation of glioblastoma multiforme (GBM) tumor cells using ising model on the Creutz Cellular Automaton

    Science.gov (United States)

    Züleyha, Artuç; Ziya, Merdan; Selçuk, Yeşiltaş; Kemal, Öztürk M.; Mesut, Tez

    2017-11-01

    Computational models for tumors have difficulties due to complexity of tumor nature and capacities of computational tools, however, these models provide visions to understand interactions between tumor and its micro environment. Moreover computational models have potential to develop strategies for individualized treatments for cancer. To observe a solid brain tumor, glioblastoma multiforme (GBM), we present a two dimensional Ising Model applied on Creutz cellular automaton (CCA). The aim of this study is to analyze avascular spherical solid tumor growth, considering transitions between non tumor cells and cancer cells are like phase transitions in physical system. Ising model on CCA algorithm provides a deterministic approach with discrete time steps and local interactions in position space to view tumor growth as a function of time. Our simulation results are given for fixed tumor radius and they are compatible with theoretical and clinic data.

  16. Simulations of Living Cell Origins Using a Cellular Automata Model

    Science.gov (United States)

    Ishida, Takeshi

    2014-04-01

    Understanding the generalized mechanisms of cell self-assembly is fundamental for applications in various fields, such as mass producing molecular machines in nanotechnology. Thus, the details of real cellular reaction networks and the necessary conditions for self-organized cells must be elucidated. We constructed a 2-dimensional cellular automata model to investigate the emergence of biological cell formation, which incorporated a looped membrane and a membrane-bound information system (akin to a genetic code and gene expression system). In particular, with an artificial reaction system coupled with a thermal system, the simultaneous formation of a looped membrane and an inner reaction process resulted in a more stable structure. These double structures inspired the primitive biological cell formation process from chemical evolution stage. With a model to simulate cellular self-organization in a 2-dimensional cellular automata model, 3 phenomena could be realized: (1) an inner reaction system developed as an information carrier precursor (akin to DNA); (2) a cell border emerged (akin to a cell membrane); and (3) these cell structures could divide into 2. This double-structured cell was considered to be a primary biological cell. The outer loop evolved toward a lipid bilayer membrane, and inner polymeric particles evolved toward precursor information carriers (evolved toward DNA). This model did not completely clarify all the necessary and sufficient conditions for biological cell self-organization. Further, our virtual cells remained unstable and fragile. However, the "garbage bag model" of Dyson proposed that the first living cells were deficient; thus, it would be reasonable that the earliest cells were more unstable and fragile than the simplest current unicellular organisms.

  17. Simulations of living cell origins using a cellular automata model.

    Science.gov (United States)

    Ishida, Takeshi

    2014-04-01

    Understanding the generalized mechanisms of cell self-assembly is fundamental for applications in various fields, such as mass producing molecular machines in nanotechnology. Thus, the details of real cellular reaction networks and the necessary conditions for self-organized cells must be elucidated. We constructed a 2-dimensional cellular automata model to investigate the emergence of biological cell formation, which incorporated a looped membrane and a membrane-bound information system (akin to a genetic code and gene expression system). In particular, with an artificial reaction system coupled with a thermal system, the simultaneous formation of a looped membrane and an inner reaction process resulted in a more stable structure. These double structures inspired the primitive biological cell formation process from chemical evolution stage. With a model to simulate cellular self-organization in a 2-dimensional cellular automata model, 3 phenomena could be realized: (1) an inner reaction system developed as an information carrier precursor (akin to DNA); (2) a cell border emerged (akin to a cell membrane); and (3) these cell structures could divide into 2. This double-structured cell was considered to be a primary biological cell. The outer loop evolved toward a lipid bilayer membrane, and inner polymeric particles evolved toward precursor information carriers (evolved toward DNA). This model did not completely clarify all the necessary and sufficient conditions for biological cell self-organization. Further, our virtual cells remained unstable and fragile. However, the "garbage bag model" of Dyson proposed that the first living cells were deficient; thus, it would be reasonable that the earliest cells were more unstable and fragile than the simplest current unicellular organisms.

  18. Mathematical model for flood routing based on cellular automaton

    Directory of Open Access Journals (Sweden)

    Xin CAI

    2014-04-01

    Full Text Available Increasing frequency and severity of flooding have caused tremendous damage in China, requiring more essential countermeasures to alleviate the damage. In this study, the dynamic simulation property of a cellular automaton was used to make further progress in flood routing. In consideration of terrain’s influence on flood routing, we regarded the terrain elevation as an auxiliary attribute of a two-dimensional cellular automaton in path selection for flood routing and developed a mathematical model based on a cellular automaton. A numerical case of propagation of an outburst flood in an area of the lower Yangtze River was analyzed with both the fixed-step and variable-step models. The results show that the flood does not spread simultaneously in all directions, but flows into the lower place first, and that the submerged area grows quickly at the beginning, but slowly later on. The final submerged areas obtained from the two different models are consistent, and the flood volume balance test shows that the flood volume meets the requirement of the total volume balance. The analysis of the case shows that the proposed model can be a valuable tool for flood routing.

  19. An improved Burgers cellular automaton model for bicycle flow

    Science.gov (United States)

    Xue, Shuqi; Jia, Bin; Jiang, Rui; Li, Xingang; Shan, Jingjing

    2017-12-01

    As an energy-efficient and healthy transport mode, bicycling has recently attracted the attention of governments, transport planners, and researchers. The dynamic characteristics of the bicycle flow must be investigated to improve the facility design and traffic operation of bicycling. We model the bicycle flow by using an improved Burgers cellular automaton model. Through a following move mechanism, the modified model enables bicycles to move smoothly and increase the critical density to a more rational level than the original model. The model is calibrated and validated by using experimental data and field data. The results show that the improved model can effectively simulate the bicycle flow. The performance of the model under different parameters is investigated and discussed. Strengths and limitations of the improved model are suggested for future work.

  20. The potential legacy of cancer nanotechnology: cellular selection.

    Science.gov (United States)

    Patra, Hirak K; Turner, Anthony P F

    2014-01-01

    Overexpression of oncogenes or loss of tumour suppressors can transform a normal cell to a cancerous one, resulting in uncontrolled regulation of intracellular signalling pathways and immunity to stresses, which both pose therapeutic challenges. Conventional approaches to cancer therapy, although they are effective at killing cancer cells, may still fail due to inadequate biodistribution and unwanted side effects. Nanotechnology-based approaches provide a promising alternative, with the possibility of targeting cells at an early stage, during their transformation into cancer cells. This review considers techniques that specifically target those molecular changes, which begin in only a very small percentage of normal cells as they undergo transformation. These techniques are crucial for early-stage diagnosis and therapy. Copyright © 2013 Elsevier Ltd. All rights reserved.

  1. Endometrial cancer: correlation of apparent diffusion coefficient (ADC) with tumor cellularity and tumor grade.

    Science.gov (United States)

    Kishimoto, Keiko; Tajima, Shinya; Maeda, Ichiro; Takagi, Masayuki; Ueno, Takahiko; Suzuki, Nao; Nakajima, Yasuo

    2016-08-01

    Diffusion-weighted imaging (DWI) and the apparent diffusion coefficient (ADC) are widely used for detecting uterine endometrial cancer. The relationships between ADC values and pathological features of endometrial cancer have not yet been established. To investigate whether ADC values of endometrial cancer vary according to histologic tumor cellularity and tumor grade. We retrospectively reviewed 30 pathologically confirmed endometrial cancers. All patients underwent conventional non-enhanced magnetic resonance imaging (MRI) and DWI procedures, and ADC values were calculated. Tumor cellularity was evaluated by counting cancer cells in three high-power ( × 400) fields. The correlation between ADC values and tumor cellularity was assessed using Pearson's correlation coefficient test for statistical analysis. The mean ± standard deviation (SD) ADC value ( ×10(-3) mm(2)/s) of endometrial cancer was 0.85 ± 0.22 (range, 0.55-1.71). The mean ± SD tumor cellularity was 528.36 ± 16.89 (range, 298.0-763.6). ADC values were significantly inversely correlated with tumor cellularity. No significant relationship was observed between ADC values and tumor grade (mean ADC values: G1, 0.88 ± 0.265 × 10(-3) mm(2)/s; G2, 0.80 ± 0.178 × 10(-3) mm(2)/s; G3, 0.81 ± 0.117 × 10(-3) mm(2)/s). There is a significant inverse relationship between ADC values and tumor cellularity in endometrial cancer. No significant differences in average ADC value were observed between G1, G2, and G3 tumors. However, the lower the tumor grade, the wider the SD. © The Foundation Acta Radiologica 2015.

  2. Unified Stochastic Geometry Model for MIMO Cellular Networks with Retransmissions

    KAUST Repository

    Afify, Laila H.

    2016-10-11

    This paper presents a unified mathematical paradigm, based on stochastic geometry, for downlink cellular networks with multiple-input-multiple-output (MIMO) base stations (BSs). The developed paradigm accounts for signal retransmission upon decoding errors, in which the temporal correlation among the signal-to-interference-plus-noise-ratio (SINR) of the original and retransmitted signals is captured. In addition to modeling the effect of retransmission on the network performance, the developed mathematical model presents twofold analysis unification for MIMO cellular networks literature. First, it integrates the tangible decoding error probability and the abstracted (i.e., modulation scheme and receiver type agnostic) outage probability analysis, which are largely disjoint in the literature. Second, it unifies the analysis for different MIMO configurations. The unified MIMO analysis is achieved by abstracting unnecessary information conveyed within the interfering signals by Gaussian signaling approximation along with an equivalent SISO representation for the per-data stream SINR in MIMO cellular networks. We show that the proposed unification simplifies the analysis without sacrificing the model accuracy. To this end, we discuss the diversity-multiplexing tradeoff imposed by different MIMO schemes and shed light on the diversity loss due to the temporal correlation among the SINRs of the original and retransmitted signals. Finally, several design insights are highlighted.

  3. The cellular cancer resistance of the SR/CR mouse

    DEFF Research Database (Denmark)

    Koch, Janne; Hau, Jann; Jensen, Henrik Elvang

    2012-01-01

    , macrophages and natural killer cells. A relative decrease in influx of B-cells compared with controls was demonstrated. Increased proportions of leukocytes belonging to the innate immune system were also demonstrated in splenocytes of SR/CR mice. Cytospins of peritoneal fluid from SR/CR mice after cancer cell......, macrophages and NK cells into the peritoneum of the SR/CR mouse in response to intraperitoneal injection of S180 cancer cells. The cell composition of spleens of SR/CR mice reflected the differential regulation of the innate immune cells in peritoneal exudates. Both peritoneal exudates and the spleens of SR......-activated cell sorting analysis, the immune response of SR/CR mice after intraperitoneal injection of cancer cells was investigated and compared with parent strain mice. A massive influx of leukocytes into the peritoneal cavity was found. A large fraction of these leukocytes were polymorphonuclear granulocytes...

  4. Interplay between Cellular and Molecular Inflammatory Mediators in Lung Cancer

    Directory of Open Access Journals (Sweden)

    Mario Orozco-Morales

    2016-01-01

    Full Text Available Inflammation is a component of the tumor microenvironment and represents the 7th hallmark of cancer. Chronic inflammation plays a critical role in tumorigenesis. Tumor infiltrating inflammatory cells mediate processes associated with progression, immune suppression, promotion of neoangiogenesis and lymphangiogenesis, remodeling of extracellular matrix, invasion and metastasis, and, lastly, the inhibition of vaccine-induced antitumor T cell response. Accumulating evidence indicates a critical role of myeloid cells in the pathophysiology of human cancers. In contrast to the well-characterized tumor-associated macrophages (TAMs, the significance of granulocytes in cancer has only recently begun to emerge with the characterization of tumor-associated neutrophils (TANs. Recent studies show the importance of CD47 in the interaction with macrophages inhibiting phagocytosis and promoting the migration of neutrophils, increasing inflammation which can lead to recurrence and progression in lung cancer. Currently, therapies are targeted towards blocking CD47 and enhancing macrophage-mediated phagocytosis. However, antibody-based therapies may have adverse effects that limit its use.

  5. Cellular radiosensitivity of small-cell lung cancer cell lines

    DEFF Research Database (Denmark)

    Krarup, M; Poulsen, H S; Spang-Thomsen, M

    1997-01-01

    PURPOSE: The objective of this study was to determine the radiobiological characteristics of a panel of small-cell lung cancer (SCLC) cell lines by use of a clonogenic assay. In addition, we tested whether comparable results could be obtained by employing a growth extrapolation method based...

  6. Cellular immortality in brain tumours: an integration of the cancer stem cell paradigm.

    Science.gov (United States)

    Rahman, Ruman; Heath, Rachel; Grundy, Richard

    2009-04-01

    Brain tumours are a diverse group of neoplasms that continue to present a formidable challenge in our attempt to achieve curable intervention. Our conceptual framework of human brain cancer has been redrawn in the current decade. There is a gathering acceptance that brain tumour formation is a phenotypic outcome of dysregulated neurogenesis, with tumours viewed as abnormally differentiated neural tissue. In relation, there is accumulating evidence that brain tumours, similar to leukaemia and many solid tumours, are organized as a developmental hierarchy which is maintained by a small fraction of cells endowed with many shared properties of tissue stem cells. Proof that neurogenesis persists throughout adult life, compliments this concept. Although the cancer cell of origin is unclear, the proliferative zones that harbour stem cells in the embryonic, post-natal and adult brain are attractive candidates within which tumour-initiation may ensue. Dysregulated, unlimited proliferation and an ability to bypass senescence are acquired capabilities of cancerous cells. These abilities in part require the establishment of a telomere maintenance mechanism for counteracting the shortening of chromosomal termini. A strategy based upon the synthesis of telomeric repeat sequences by the ribonucleoprotein telomerase, is prevalent in approximately 90% of human tumours studied, including the majority of brain tumours. This review will provide a developmental perspective with respect to normal (neurogenesis) and aberrant (tumourigenesis) cellular turnover, differentiation and function. Within this context our current knowledge of brain tumour telomere/telomerase biology will be discussed with respect to both its developmental and therapeutic relevance to the hierarchical model of brain tumourigenesis presented by the cancer stem cell paradigm.

  7. A Fluid Model for Performance Analysis in Cellular Networks

    Directory of Open Access Journals (Sweden)

    Coupechoux Marceau

    2010-01-01

    Full Text Available We propose a new framework to study the performance of cellular networks using a fluid model and we derive from this model analytical formulas for interference, outage probability, and spatial outage probability. The key idea of the fluid model is to consider the discrete base station (BS entities as a continuum of transmitters that are spatially distributed in the network. This model allows us to obtain simple analytical expressions to reveal main characteristics of the network. In this paper, we focus on the downlink other-cell interference factor (OCIF, which is defined for a given user as the ratio of its outer cell received power to its inner cell received power. A closed-form formula of the OCIF is provided in this paper. From this formula, we are able to obtain the global outage probability as well as the spatial outage probability, which depends on the location of a mobile station (MS initiating a new call. Our analytical results are compared to Monte Carlo simulations performed in a traditional hexagonal network. Furthermore, we demonstrate an application of the outage probability related to cell breathing and densification of cellular networks.

  8. Traffic modeling in the integrated cellular ad hoc network system

    Science.gov (United States)

    Yamanaka, Sachiko; Shimohara, Katsunori

    2005-10-01

    We present the modeling and evaluation in the integrated cellular and ad hoc network system. The system is modeled using queueing theory and we derive some characteristic values. As regards a system model of two cells, M channels are assigned to each cell and a relay station is set in the overlapped area of two cells. New calls in cellA can be relayed to cellB if the channels in cellA are all busy and the mobile stations are in the covered area by a relay station. Handoff calls select the channels of the cell that the number of empty channels are more in the two cells. If the channels of the both cells are all busy, handoff calls can wait in a queue with the capacity Q while mobile stations are in the handoff area. However, so as not to make handoff calls possess channels prior to new calls, we manage it with the method being different from the other researches. This system is more flexible than cellular networks, the bias of traffic gets smaller and it leads to an efficient channel using. We model and evaluate our system by assuming that the dwelling time is distributed with non-exponential distribution as well as exponential one. In numerical results, we compare the characteristic values in our system with those in non-relaying system, see how the characteristic values are affected when the covered area by a relay station changes, and verify the effectiveness of our system.

  9. Integrating cellular metabolism into a multiscale whole-body model.

    Directory of Open Access Journals (Sweden)

    Markus Krauss

    Full Text Available Cellular metabolism continuously processes an enormous range of external compounds into endogenous metabolites and is as such a key element in human physiology. The multifaceted physiological role of the metabolic network fulfilling the catalytic conversions can only be fully understood from a whole-body perspective where the causal interplay of the metabolic states of individual cells, the surrounding tissue and the whole organism are simultaneously considered. We here present an approach relying on dynamic flux balance analysis that allows the integration of metabolic networks at the cellular scale into standardized physiologically-based pharmacokinetic models at the whole-body level. To evaluate our approach we integrated a genome-scale network reconstruction of a human hepatocyte into the liver tissue of a physiologically-based pharmacokinetic model of a human adult. The resulting multiscale model was used to investigate hyperuricemia therapy, ammonia detoxification and paracetamol-induced toxication at a systems level. The specific models simultaneously integrate multiple layers of biological organization and offer mechanistic insights into pathology and medication. The approach presented may in future support a mechanistic understanding in diagnostics and drug development.

  10. Redox Homeostasis and Cellular Antioxidant Systems: Crucial Players in Cancer Growth and Therapy

    Directory of Open Access Journals (Sweden)

    Barbara Marengo

    2016-01-01

    Full Text Available Reactive oxygen species (ROS and their products are components of cell signaling pathways and play important roles in cellular physiology and pathophysiology. Under physiological conditions, cells control ROS levels by the use of scavenging systems such as superoxide dismutases, peroxiredoxins, and glutathione that balance ROS generation and elimination. Under oxidative stress conditions, excessive ROS can damage cellular proteins, lipids, and DNA, leading to cell damage that may contribute to carcinogenesis. Several studies have shown that cancer cells display an adaptive response to oxidative stress by increasing expression of antioxidant enzymes and molecules. As a double-edged sword, ROS influence signaling pathways determining beneficial or detrimental outcomes in cancer therapy. In this review, we address the role of redox homeostasis in cancer growth and therapy and examine the current literature regarding the redox regulatory systems that become upregulated in cancer and their role in promoting tumor progression and resistance to chemotherapy.

  11. Multifocal Breast Cancer in Young Women with Prolonged Contact between Their Breasts and Their Cellular Phones

    OpenAIRE

    West, John G.; Kapoor, Nimmi S.; Liao, Shu-Yuan; Chen, June W.; Bailey, Lisa; Nagourney, Robert A.

    2013-01-01

    Breast cancer occurring in women under the age of 40 is uncommon in the absence of family history or genetic predisposition, and prompts the exploration of other possible exposures or environmental risks. We report a case series of four young women—ages from 21 to 39—with multifocal invasive breast cancer that raises the concern of a possible association with nonionizing radiation of electromagnetic field exposures from cellular phones. All patients regularly carried their smartphones directl...

  12. Decomposing Oncogenic Transcriptional Signatures to Generate Maps of Divergent Cellular States* | Office of Cancer Genomics

    Science.gov (United States)

    The systematic sequencing of the cancer genome has led to the identification of numerous genetic alterations in cancer. However, a deeper understanding of the functional consequences of these alterations is necessary to guide appropriate therapeutic strategies. Here, we describe Onco-GPS (OncoGenic Positioning System), a data-driven analysis framework to organize individual tumor samples with shared oncogenic alterations onto a reference map defined by their underlying cellular states.

  13. Dynamic computational model suggests that cellular citizenship is fundamental for selective tumor apoptosis.

    Directory of Open Access Journals (Sweden)

    Megan Olsen

    Full Text Available Computational models in the field of cancer research have focused primarily on estimates of biological events based on laboratory generated data. We introduce a novel in-silico technology that takes us to the next level of prediction models and facilitates innovative solutions through the mathematical system. The model's building blocks are cells defined phenotypically as normal or tumor, with biological processes translated into equations describing the life protocols of the cells in a quantitative and stochastic manner. The essentials of communication in a society composed of normal and tumor cells are explored to reveal "protocols" for selective tumor eradication. Results consistently identify "citizenship properties" among cells that are essential for the induction of healing processes in a healthy system invaded by cancer. These properties act via inter-cellular communication protocols that can be optimized to induce tumor eradication along with system recovery. Within the computational systems, the protocols universally succeed in removing a wide variety of tumors defined by proliferation rates, initial volumes, and apoptosis resistant phenotypes; they show high adaptability for biological details and allow incorporation of population heterogeneity. These protocols work as long as at least 32% of cells obey extra-cellular commands and at least 28% of cancer cells report their deaths. This low percentage implies that the protocols are resilient to the suboptimal situations often seen in biological systems. We conclude that our in-silico model is a powerful tool to investigate, to propose, and to exercise logical anti-cancer solutions. Functional results should be confirmed in a biological system and molecular findings should be loaded into the computational model for the next level of directed experiments.

  14. Model for urban and indoor cellular propagation using percolation theory

    Science.gov (United States)

    Franceschetti, G.; Marano, S.; Pasquino, N.; Pinto, I. M.

    2000-03-01

    A method for the analysis and statistical characterization of wave propagation in indoor and urban cellular radio channels is presented, based on a percolation model. Pertinent principles of the theory are briefly reviewed, and applied to the problem of interest. Relevant quantities, such as pulsed-signal arrival rate, number of reflections against obstacles, and path lengths are deduced and related to basic environment parameters such as obstacle density and transmitter-receiver separation. Results are found to be in good agreement with alternative simulations and measurements.

  15. A Cellular Automata Model of Infection Control on Medical Implants

    Science.gov (United States)

    Prieto-Langarica, Alicia; Kojouharov, Hristo; Chen-Charpentier, Benito; Tang, Liping

    2011-01-01

    S. epidermidis infections on medically implanted devices are a common problem in modern medicine due to the abundance of the bacteria. Once inside the body, S. epidermidis gather in communities called biofilms and can become extremely hard to eradicate, causing the patient serious complications. We simulate the complex S. epidermidis-Neutrophils interactions in order to determine the optimum conditions for the immune system to be able to contain the infection and avoid implant rejection. Our cellular automata model can also be used as a tool for determining the optimal amount of antibiotics for combating biofilm formation on medical implants. PMID:23543851

  16. Simulation of root forms using cellular automata model

    Energy Technology Data Exchange (ETDEWEB)

    Winarno, Nanang, E-mail: nanang-winarno@upi.edu; Prima, Eka Cahya [International Program on Science Education, Universitas Pendidikan Indonesia, Jl. Dr. Setiabudi no 229, Bandung40154 (Indonesia); Afifah, Ratih Mega Ayu [Department of Physics Education, Post Graduate School, Universitas Pendidikan Indonesia, Jl. Dr. Setiabudi no 229, Bandung40154 (Indonesia)

    2016-02-08

    This research aims to produce a simulation program for root forms using cellular automata model. Stephen Wolfram in his book entitled “A New Kind of Science” discusses the formation rules based on the statistical analysis. In accordance with Stephen Wolfram’s investigation, the research will develop a basic idea of computer program using Delphi 7 programming language. To best of our knowledge, there is no previous research developing a simulation describing root forms using the cellular automata model compared to the natural root form with the presence of stone addition as the disturbance. The result shows that (1) the simulation used four rules comparing results of the program towards the natural photographs and each rule had shown different root forms; (2) the stone disturbances prevent the root growth and the multiplication of root forms had been successfully modeled. Therefore, this research had added some stones, which have size of 120 cells placed randomly in the soil. Like in nature, stones cannot be penetrated by plant roots. The result showed that it is very likely to further develop the program of simulating root forms by 50 variations.

  17. Metabolic autofluorescence imaging of head and neck cancer organoids quantifies cellular heterogeneity and treatment response (Conference Presentation)

    Science.gov (United States)

    Shah, Amy T.; Heaster, Tiffany M.; Skala, Melissa C.

    2017-02-01

    Treatment options for head and neck cancer are limited, and can cause an impaired ability to eat, talk, and breathe. Therefore, optimized and personalized therapies could reduce unnecessary toxicities from ineffective treatments. Organoids are generated from primary tumor tissue and provide a physiologically-relevant in vitro model to measure drug response. Additionally, multiphoton fluorescence lifetime imaging (FLIM) of the metabolic cofactors NAD(P)H and FAD can resolve dynamic cellular response to anti-cancer treatment. This study applies FLIM of NAD(P)H and FAD to head and neck cancer organoids. Head and neck cancer tissue was digested and grown in culture as three-dimensional organoids. Gold standard measures of therapeutic response in vivo indicate stable disease after treatment with cetuximab (antibody therapy) or cisplatin (chemotherapy), and treatment response after combination treatment. In parallel, organoids were treated with cetuximab, cisplatin, or combination therapy for 24 hours. Treated organoids exhibit decreased NAD(P)H lifetime (p<0.05) and increased FAD lifetime (p<0.05) compared with control organoids. Additionally, analysis of cellular heterogeneity identifies distinct subpopulations of cells in response to treatment. A quantitative heterogeneity index predicts in vivo treatment response and demonstrates increased cellular heterogeneity in organoids treated with cetuximab or cisplatin compared with combination treatment. Mapping of cell subpopulations enables characterization of spatial relationships between cell subpopulations. Ultimately, an organoid model combined with metabolic fluorescence imaging could provide a high-throughput platform for drug discovery. Organoids grown from patient tissue could enable individualized treatment planning. These achievements could optimize quality of life and treatment outcomes for head and neck cancer patients.

  18. Cellular and Molecular Mechanisms of 3,3′-Diindolylmethane in Gastrointestinal Cancer

    Directory of Open Access Journals (Sweden)

    Soo Mi Kim

    2016-07-01

    Full Text Available Studies in humans have shown that 3,3′-diindolylmethane (DIM, which is found in cruciferous vegetables, such as cabbage and broccoli, is effective in the attenuation of gastrointestinal cancers. This review presents the latest findings on the use, targets, and modes of action of DIM for the treatment of human gastrointestinal cancers. DIM acts upon several cellular and molecular processes in gastrointestinal cancer cells, including apoptosis, autophagy, invasion, cell cycle regulation, metastasis, angiogenesis, and endoplasmic reticulum (ER stress. In addition, DIM increases the efficacy of other drugs or therapeutic chemicals when used in combinatorial treatment for gastrointestinal cancer. The studies to date offer strong evidence to support the use of DIM as an anticancer and therapeutic agent for gastrointestinal cancer. Therefore, this review provides a comprehensive understanding of the preventive and therapeutic properties of DIM in addition to its different perspective on the safety of DIM in clinical applications for the treatment of gastrointestinal cancers.

  19. Cellular diamine levels in cancer chemoprevention: modulation by ibuprofen and membrane plasmalogens

    Directory of Open Access Journals (Sweden)

    Wood Paul L

    2011-11-01

    Full Text Available Abstract Background To develop effective strategies in cancer chemoprevention, an increased understanding of endogenous biochemical mediators that block metastatic processes is critically needed. Dietary lipids and non-steroidal anti-inflammatory drugs (NSAIDs have a published track record of providing protection against gastrointestinal malignancies. In this regard, we examined the effects of membrane plasmalogens and ibuprofen on regulation of cellular levels of diamines, polyamine mediators that are augmented in cancer cells. For these studies we utilized Chinese hamster ovary (CHO cells and NRel-4 cells, a CHO cell line with defective plasmalogen synthesis. Results NRel-4 cells, which possess cellular plasmalogen levels that are 10% of control CHO cells, demonstrated 2- to 3-fold increases in cellular diamine levels. These diamine levels were normalized by plasmalogen replacement and significantly reduced by ibuprofen. In both cases the mechanism of action appears to mainly involve increased diamine efflux via the diamine exporter. The actions of ibuprofen were not stereospecific, supporting previous studies that cyclooxygenase (COX inhibition is unlikely to be involved in the ability of NSAIDs to reduce intracellular diamine levels. Conclusions Our data demonstrate that ibuprofen, a drug known to reduce the risk of colorectal cancer, reduces cellular diamine levels via augmentation of diamine efflux. Similarly, augmentation of membrane plasmalogens can increase diamine export from control and plasmalogen-deficient cells. These data support the concept that membrane transporter function may be a therapeutic point of intervention for dietary and pharmacological approaches to cancer chemoprevention.

  20. Common Genetic Variation In Cellular Transport Genes and Epithelial Ovarian Cancer (EOC) Risk

    DEFF Research Database (Denmark)

    Chornokur, Ganna; Lin, Hui-Yi; Tyrer, Jonathan P

    2015-01-01

    BACKGROUND: Defective cellular transport processes can lead to aberrant accumulation of trace elements, iron, small molecules and hormones in the cell, which in turn may promote the formation of reactive oxygen species, promoting DNA damage and aberrant expression of key regulatory cancer genes. ...

  1. Cellular transfer and AFM imaging of cancer cells using Bioimprint

    Directory of Open Access Journals (Sweden)

    Melville DOS

    2006-01-01

    Full Text Available Abstract A technique for permanently capturing a replica impression of biological cells has been developed to facilitate analysis using nanometer resolution imaging tools, namely the atomic force microscope (AFM. The method, termed Bioimprint™, creates a permanent cell 'footprint' in a non-biohazardous Poly (dimethylsiloxane (PDMS polymer composite. The transfer of nanometer scale biological information is presented as an alternative imaging technique at a resolution beyond that of optical microscopy. By transferring cell topology into a rigid medium more suited for AFM imaging, many of the limitations associated with scanning of biological specimens can be overcome. Potential for this technique is demonstrated by analyzing Bioimprint™ replicas created from human endometrial cancer cells. The high resolution transfer of this process is further detailed by imaging membrane morphological structures consistent with exocytosis. The integration of soft lithography to replicate biological materials presents an enhanced method for the study of biological systems at the nanoscale.

  2. Investigating cellular network heterogeneity and modularity in cancer: a network entropy and unbalanced motif approach.

    Science.gov (United States)

    Cheng, Feixiong; Liu, Chuang; Shen, Bairong; Zhao, Zhongming

    2016-08-26

    Cancer is increasingly recognized as a cellular system phenomenon that is attributed to the accumulation of genetic or epigenetic alterations leading to the perturbation of the molecular network architecture. Elucidation of network properties that can characterize tumor initiation and progression, or pinpoint the molecular targets related to the drug sensitivity or resistance, is therefore of critical importance for providing systems-level insights into tumorigenesis and clinical outcome in the molecularly targeted cancer therapy. In this study, we developed a network-based framework to quantitatively examine cellular network heterogeneity and modularity in cancer. Specifically, we constructed gene co-expressed protein interaction networks derived from large-scale RNA-Seq data across 8 cancer types generated in The Cancer Genome Atlas (TCGA) project. We performed gene network entropy and balanced versus unbalanced motif analysis to investigate cellular network heterogeneity and modularity in tumor versus normal tissues, different stages of progression, and drug resistant versus sensitive cancer cell lines. We found that tumorigenesis could be characterized by a significant increase of gene network entropy in all of the 8 cancer types. The ratio of the balanced motifs in normal tissues is higher than that of tumors, while the ratio of unbalanced motifs in tumors is higher than that of normal tissues in all of the 8 cancer types. Furthermore, we showed that network entropy could be used to characterize tumor progression and anticancer drug responses. For example, we found that kinase inhibitor resistant cancer cell lines had higher entropy compared to that of sensitive cell lines using the integrative analysis of microarray gene expression and drug pharmacological data collected from the Genomics of Drug Sensitivity in Cancer database. In addition, we provided potential network-level evidence that smoking might increase cancer cellular network heterogeneity and

  3. A cellular automaton model for ship traffic flow in waterways

    Science.gov (United States)

    Qi, Le; Zheng, Zhongyi; Gang, Longhui

    2017-04-01

    With the development of marine traffic, waterways become congested and more complicated traffic phenomena in ship traffic flow are observed. It is important and necessary to build a ship traffic flow model based on cellular automata (CAs) to study the phenomena and improve marine transportation efficiency and safety. Spatial discretization rules for waterways and update rules for ship movement are two important issues that are very different from vehicle traffic. To solve these issues, a CA model for ship traffic flow, called a spatial-logical mapping (SLM) model, is presented. In this model, the spatial discretization rules are improved by adding a mapping rule. And the dynamic ship domain model is considered in the update rules to describe ships' interaction more exactly. Take the ship traffic flow in the Singapore Strait for example, some simulations were carried out and compared. The simulations show that the SLM model could avoid ship pseudo lane-change efficiently, which is caused by traditional spatial discretization rules. The ship velocity change in the SLM model is consistent with the measured data. At finally, from the fundamental diagram, the relationship between traffic ability and the lengths of ships is explored. The number of ships in the waterway declines when the proportion of large ships increases.

  4. A cellular automation model accounting for bicycle's group behavior

    Science.gov (United States)

    Tang, Tie-Qiao; Rui, Ying-Xu; Zhang, Jian; Shang, Hua-Yan

    2018-02-01

    Recently, bicycle has become an important traffic tool in China, again. Due to the merits of bicycle, the group behavior widely exists in urban traffic system. However, little effort has been made to explore the impacts of the group behavior on bicycle flow. In this paper, we propose a CA (cellular automaton) model with group behavior to explore the complex traffic phenomena caused by shoulder group behavior and following group behavior on an open road. The numerical results illustrate that the proposed model can qualitatively describe the impacts of the two kinds of group behaviors on bicycle flow and that the effects are related to the mode and size of group behaviors. The results can help us to better understand the impacts of the bicycle's group behaviors on urban traffic system and effectively control the bicycle's group behavior.

  5. Functional and genetic deconstruction of the cellular origin in liver cancer

    DEFF Research Database (Denmark)

    Marquardt, Jens U; Andersen, Jesper B; Thorgeirsson, Snorri S

    2015-01-01

    of the cellular origin of liver cancer has been much less explored. Therefore, in this Review, we emphasize the importance and complexity of the cellular origin in tumour initiation and progression, and attempt to integrate this aspect with recent discoveries in tumour genomics and the contribution......During the past decade, research on primary liver cancers has particularly highlighted the uncommon plasticity of differentiated parenchymal liver cells (that is, hepatocytes and cholangiocytes (also known as biliary epithelial cells)), the role of liver progenitor cells in malignant transformation......, the importance of the tumour microenvironment and the molecular complexity of liver tumours. Whereas other reviews have focused on the landscape of genetic alterations that promote development and progression of primary liver cancers and the role of the tumour microenvironment, the crucial importance...

  6. Facile Synthesis of Biocompatible Fluorescent Nanoparticles for Cellular Imaging and Targeted Detection of Cancer Cells.

    Science.gov (United States)

    Tang, Fu; Wang, Chun; Wang, Xiaoyu; Li, Lidong

    2015-11-18

    In this work, we report the facile synthesis of functional core-shell structured nanoparticles with fluorescence enhancement, which show specific targeting of cancer cells. Biopolymer poly-l-lysine was used to coat the silver core with various shell thicknesses. Then, the nanoparticles were functionalized with folic acid as a targeting agent for folic acid receptor. The metal-enhanced fluorescence effect was observed when the fluorophore (5-(and-6)-carboxyfluorescein-succinimidyl ester) was conjugated to the modified nanoparticle surface. Cellular imaging assay of the nanoparticles in folic acid receptor-positive cancer cells showed their excellent biocompatibility and selectivity. The as-prepared functional nanoparticles demonstrate the efficiency of the metal-enhanced fluorescence effect and provide an alternative approach for the cellular imaging and targeting of cancer cells.

  7. Epithelial Ovarian Cancer Experimental Models

    Science.gov (United States)

    Lengyel, E; Burdette, JE; Kenny, HA; Matei, D; Pilrose, J; Haluska, P.; Nephew, KP; Hales, DB; Stack, MS

    2014-01-01

    Epithelial ovarian cancer (OvCa) is associated with high mortality and, as the majority (>75%) of women with OvCa have metastatic disease at the time of diagnosis, rates of survival have not changed appreciably over 30 years. A mechanistic understanding of OvCa initiation and progression is hindered by the complexity of genetic and/or environmental initiating events and lack of clarity regarding the cell(s) or tissue(s) of origin. Metastasis of OvCa involves direct extension or exfoliation of cells and cellular aggregates into the peritoneal cavity, survival of matrix-detached cells in a complex ascites fluid phase, and subsequent adhesion to the mesothelium lining covering abdominal organs to establish secondary lesions containing host stromal and inflammatory components. Development of experimental models to recapitulate this unique mechanism of metastasis presents a remarkable scientific challenge and many approaches used to study other solid tumors (lung, colon, and breast, for example) are not transferable to OvCa research given the distinct metastasis pattern and unique tumor microenvironment. This review will discuss recent progress in the development and refinement of experimental models to study OvCa. Novel cellular, three-dimensional organotypic, and ex vivo models are considered and the current in vivo models summarized. The review critically evaluates currently available genetic mouse models of OvCa, the emergence of xenopatients, and the utility of the hen model to study OvCa prevention, tumorigenesis, metastasis, and chemoresistance. As these new approaches more accurately recapitulate the complex tumor microenvironment, it is predicted that new opportunities for enhanced understanding of disease progression, metastasis and therapeutic response will emerge. PMID:23934194

  8. Antiproliferative Activity and Cellular Uptake of Evodiamine and Rutaecarpine Based on 3D Tumor Models

    Directory of Open Access Journals (Sweden)

    Hui Guo

    2016-07-01

    Full Text Available Evodiamine (EVO and rutaecarpine (RUT are promising anti-tumor drug candidates. The evaluation of the anti-proliferative activity and cellular uptake of EVO and RUT in 3D multicellular spheroids of cancer cells would better recapitulate the native situation and thus better reflect an in vivo response to the treatment. Herein, we employed the 3D culture of MCF-7 and SMMC-7721 cells based on hanging drop method and evaluated the anti-proliferative activity and cellular uptake of EVO and RUT in 3D multicellular spheroids, and compared the results with those obtained from 2D monolayers. The drugs’ IC50 values were significantly increased from the range of 6.4–44.1 μM in 2D monolayers to 21.8–138.0 μM in 3D multicellular spheroids, which may be due to enhanced mass barrier and reduced drug penetration in 3D models. The fluorescence of EVO and RUT was measured via fluorescence spectroscopy and the cellular uptake of both drugs was characterized in 2D tumor models. The results showed that the cellular uptake concentrations of RUT increased with increasing drug concentrations. However, the EVO concentrations uptaken by the cells showed only a small change with increasing drug concentrations, which may be due to the different solubility of EVO and Rut in solvents. Overall, this study provided a new vision of the anti-tumor activity of EVO and RUT via 3D multicellular spheroids and cellular uptake through the fluorescence of compounds.

  9. A mathematical model of cellular swelling in Neuromyelitis optica.

    Science.gov (United States)

    Laranjeira, Simão; Symmonds, Mkael; Palace, Jacqueline; Payne, Stephen J; Orlowski, Piotr

    2017-11-21

    Neuromyelitis Optica (NMO) is a severe neuro-inflammatory disease of the central nervous system characterized by predominant damage to the optic nerve and of the spinal cord. The pathogenic antibody found in the majority of patients targets the AQP4 channels on astrocytic endfeet and causes the cells to swell. Although, the pathophysiology of the disease is broadly known, there are no specific targeted treatments for this process clinically available nor accurate prognostic markers both during attacks and for predicting long term neuronal damage. This lack is, in part, due to the rarity of the disease and its relatively recent pathogenic clarity. Hence, the ability to mathematically model the progress of the condition to test prospective therapies in silico would be a step forward. This paper combines state of the art models of cellular metabolism and cytotoxic oedema in neurons and astrocytes and augments it with a detailed characterization of water transport across the cellular membrane. In particular, we capture the process of perforation of the cell through the human complement cascade and resulting water and ionic fluxes. Simulating NMO by injecting its antibody and human complement into the extracellular space showed a 25% increase of the astrocytic volume after 12 h from onset. Most of the volume change occurred during the first 30 min of simulation with a peak volume change of 38%. The model was further adapted to simulate the therapeutic potential of CD59. It was found that there is a threshold of CD59 concentration that can prevent the swelling of astrocytes. Since the astrocyte volume changes mostly during the first hour, further experimental work should focus on this time scale to provide data for further model refinement and validation. Copyright © 2017. Published by Elsevier Ltd.

  10. Discrimination of liver cancer in cellular level based on backscatter micro-spectrum with PCA algorithm and BP neural network

    Science.gov (United States)

    Yang, Jing; Wang, Cheng; Cai, Gan; Dong, Xiaona

    2016-10-01

    The incidence and mortality rate of the primary liver cancer are very high and its postoperative metastasis and recurrence have become important factors to the prognosis of patients. Circulating tumor cells (CTC), as a new tumor marker, play important roles in the early diagnosis and individualized treatment. This paper presents an effective method to distinguish liver cancer based on the cellular scattering spectrum, which is a non-fluorescence technique based on the fiber confocal microscopic spectrometer. Combining the principal component analysis (PCA) with back propagation (BP) neural network were utilized to establish an automatic recognition model for backscatter spectrum of the liver cancer cells from blood cell. PCA was applied to reduce the dimension of the scattering spectral data which obtained by the fiber confocal microscopic spectrometer. After dimensionality reduction by PCA, a neural network pattern recognition model with 2 input layer nodes, 11 hidden layer nodes, 3 output nodes was established. We trained the network with 66 samples and also tested it. Results showed that the recognition rate of the three types of cells is more than 90%, the relative standard deviation is only 2.36%. The experimental results showed that the fiber confocal microscopic spectrometer combining with the algorithm of PCA and BP neural network can automatically identify the liver cancer cell from the blood cells. This will provide a better tool for investigating the metastasis of liver cancers in vivo, the biology metabolic characteristics of liver cancers and drug transportation. Additionally, it is obviously referential in practical application.

  11. Mouse models for cancer research

    OpenAIRE

    Zhang, Wei; Moore, Lynette; Ji, Ping

    2011-01-01

    Mouse models of cancer enable researchers to learn about tumor biology in complicated and dynamic physiological systems. Since the development of gene targeting in mice, cancer biologists have been among the most frequent users of transgenic mouse models, which have dramatically increased knowledge about how cancers form and grow. The Chinese Journal of Cancer will publish a series of papers reporting the use of mouse models in studying genetic events in cancer cases. This editorial is an ove...

  12. An FE model of a cellular polypropylene: exploring mechanical properties

    Science.gov (United States)

    Sgardelis, Pavlos; Pozzi, Michele

    2017-05-01

    Several analytical models have been suggested to describe the changes in the electromechanical properties of Cellular Polypropylene (Cell-PP) due to charging. However, there is a limited number of studies considering the non-linear dependence of the piezoelectric coefficient d33 on the mechanical load applied. One of the main reasons for this nonlinearity is the stiffness of the film that increases proportionally to the applied mechanical load. Moreover the size and shape distribution of the enclosed voids is an important determinant of the electromechanical properties. In this work, the geometry of a 3D model of Cell-PP is designed on the basis of analytical Splines. Both the manufacturing procedure of Cell-PP films (bi-axial stretching) and the pressure expansion treatment were simulated in order to account for a realistic void distribution. The FEA is done on a 2D cross-section of the modelled film. The modelled mechanical response is analysed based on increasing mechanical load applied. The load-deflection curves obtained from the analysis are then compared to the experimental results acquired via Dynamical Mechanical Analyzer (DMA) to validate the model. Four types of Cell-PP films, expanded at different pressures, were used in this validation. The aim is to develop a model that describes the effect of morphological parameters on the stiffness of the films by simulating the manufacturing procedure.

  13. Model of cellular mechanotransduction via actin stress fibers.

    Science.gov (United States)

    Gouget, Cecile L M; Hwang, Yongyun; Barakat, Abdul I

    2016-04-01

    Mechanical stresses due to blood flow regulate vascular endothelial cell structure and function and play a key role in arterial physiology and pathology. In particular, the development of atherosclerosis has been shown to correlate with regions of disturbed blood flow where endothelial cells are round and have a randomly organized cytoskeleton. Thus, deciphering the relation between the mechanical environment, cell structure, and cell function is a key step toward understanding the early development of atherosclerosis. Recent experiments have demonstrated very rapid (∼100 ms) and long-distance (∼10 μm) cellular mechanotransduction in which prestressed actin stress fibers play a critical role. Here, we develop a model of mechanical signal transmission within a cell by describing strains in a network of prestressed viscoelastic stress fibers following the application of a force to the cell surface. We find force transmission dynamics that are consistent with experimental results. We also show that the extent of stress fiber alignment and the direction of the applied force relative to this alignment are key determinants of the efficiency of mechanical signal transmission. These results are consistent with the link observed experimentally between cytoskeletal organization, mechanical stress, and cellular responsiveness to stress. Based on these results, we suggest that mechanical strain of actin stress fibers under force constitutes a key link in the mechanotransduction chain.

  14. Cellular communication and “non-targeted effects”: Modelling approaches

    Science.gov (United States)

    Ballarini, Francesca; Facoetti, Angelica; Mariotti, Luca; Nano, Rosanna; Ottolenghi, Andrea

    2009-10-01

    During the last decade, a large number of experimental studies on the so-called "non-targeted effects", in particular bystander effects, outlined that cellular communication plays a significant role in the pathways leading to radiobiological damage. Although it is known that two main types of cellular communication (i.e. via gap junctions and/or molecular messengers diffusing in the extra-cellular environment, such as cytokines, NO etc.) play a major role, it is of utmost importance to better understand the underlying mechanisms, and how such mechanisms can be modulated by ionizing radiation. Though the "final" goal is of course to elucidate the in vivo scenario, in the meanwhile also in vitro studies can provide useful insights. In the present paper we will discuss key issues on the mechanisms underlying non-targeted effects and cell communication, for which theoretical models and simulation codes can be of great help. In this framework, we will present in detail three literature models, as well as an approach under development at the University of Pavia. More specifically, we will first focus on a version of the "State-Vector Model" including bystander-induced apoptosis of initiated cells, which was successfully fitted to in vitro data on neoplastic transformation supporting the hypothesis of a protective bystander effect mediated by apoptosis. The second analyzed model, focusing on the kinetics of bystander effects in 3D tissues, was successfully fitted to data on bystander damage in an artificial 3D skin system, indicating a signal range of the order of 0.7-1 mm. A third model for bystander effect, taking into account of spatial location, cell killing and repopulation, showed dose-response curves increasing approximately linearly at low dose rates but quickly flattening out for higher dose rates, also predicting an effect augmentation following dose fractionation. Concerning the Pavia approach, which can model the release, diffusion and depletion/degradation of

  15. Simulations of Forest Fires by the Cellular Automata Model "ABBAMPAU"

    Science.gov (United States)

    di Gregorio, S.; Bendicenti, E.

    2003-04-01

    Forest fires represent a serious environmental problem, whose negative impact is becoming day by day more worrisome. Forest fires are very complex phenomena; that need an interdisciplinary approach. The adopted method to modelling involves the definition of local rules, from which the global behaviour of the system can emerge. The paradigm of Cellular Automata was applied and the model ABBAMPAU was projected to simulate the evolution of forest fires. Cellular Automata features (parallelism and a-centrism) seem to match the system "forest fire"; the parameters, describing globally a forest fire, i.e. propagation rate, flame length and direction, fireline intensity, fire duration time et c. are mainly depending on some local characteristics i.e. vegetation type (live and dead fuel), relative humidity, fuel moisture, heat, territory morphology (altitude, slope), et c.. The only global characteristic is given by wind velocity and direction, but wind velocity and direction is locally altered according to the morphology; therefore wind has also to be considered at local level. ABBAMPAU accounts for the following aspects of the phenomenon: effects of combustion in surface and crown fire inside the cell, crown fire triggering off; surface and crown fire spread, determination of the local wind rate and direction. A validation of ABBAMPAU was tested on a real case of forest fire, in the territory of Villaputzu, Sardinia island, August 22nd, 1998. First simulations account for the main characteristics of the phenomenon and agree with the observations. The results show that the model could be applied for the forest fire preventions, the productions of risk scenarios and the evaluation of the forest fire environmental impact.

  16. A Computational Model of Cellular Response to Modulated Radiation Fields

    Energy Technology Data Exchange (ETDEWEB)

    McMahon, Stephen J., E-mail: stephen.mcmahon@qub.ac.uk [Centre for Cancer Research and Cell Biology, Queen' s University Belfast, Belfast, Northern Ireland (United Kingdom); Butterworth, Karl T. [Centre for Cancer Research and Cell Biology, Queen' s University Belfast, Belfast, Northern Ireland (United Kingdom); McGarry, Conor K. [Centre for Cancer Research and Cell Biology, Queen' s University Belfast, Belfast, Northern Ireland (United Kingdom); Radiotherapy Physics, Northern Ireland Cancer Centre, Belfast Health and Social Care Trust, Northern Ireland (United Kingdom); Trainor, Colman [Centre for Cancer Research and Cell Biology, Queen' s University Belfast, Belfast, Northern Ireland (United Kingdom); O' Sullivan, Joe M. [Centre for Cancer Research and Cell Biology, Queen' s University Belfast, Belfast, Northern Ireland (United Kingdom); Clinical Oncology, Northern Ireland Cancer Centre, Belfast Health and Social Care Trust, Belfast, Northern Ireland (United Kingdom); Hounsell, Alan R. [Centre for Cancer Research and Cell Biology, Queen' s University Belfast, Belfast, Northern Ireland (United Kingdom); Radiotherapy Physics, Northern Ireland Cancer Centre, Belfast Health and Social Care Trust, Northern Ireland (United Kingdom); Prise, Kevin M. [Centre for Cancer Research and Cell Biology, Queen' s University Belfast, Belfast, Northern Ireland (United Kingdom)

    2012-09-01

    Purpose: To develop a model to describe the response of cell populations to spatially modulated radiation exposures of relevance to advanced radiotherapies. Materials and Methods: A Monte Carlo model of cellular radiation response was developed. This model incorporated damage from both direct radiation and intercellular communication including bystander signaling. The predictions of this model were compared to previously measured survival curves for a normal human fibroblast line (AGO1522) and prostate tumor cells (DU145) exposed to spatially modulated fields. Results: The model was found to be able to accurately reproduce cell survival both in populations which were directly exposed to radiation and those which were outside the primary treatment field. The model predicts that the bystander effect makes a significant contribution to cell killing even in uniformly irradiated cells. The bystander effect contribution varies strongly with dose, falling from a high of 80% at low doses to 25% and 50% at 4 Gy for AGO1522 and DU145 cells, respectively. This was verified using the inducible nitric oxide synthase inhibitor aminoguanidine to inhibit the bystander effect in cells exposed to different doses, which showed significantly larger reductions in cell killing at lower doses. Conclusions: The model presented in this work accurately reproduces cell survival following modulated radiation exposures, both in and out of the primary treatment field, by incorporating a bystander component. In addition, the model suggests that the bystander effect is responsible for a significant portion of cell killing in uniformly irradiated cells, 50% and 70% at doses of 2 Gy in AGO1522 and DU145 cells, respectively. This description is a significant departure from accepted radiobiological models and may have a significant impact on optimization of treatment planning approaches if proven to be applicable in vivo.

  17. Effects of Mechanical Properties on Tumor Invasion: Insights from a Cellular Model

    KAUST Repository

    Li, YZ

    2014-08-01

    Understanding the regulating mechanism of tumor invasion is of crucial importance for both fundamental cancer research and clinical applications. Previous in vivo experiments have shown that invasive cancer cells dissociate from the primary tumor and invade into the stroma, forming an irregular invasive morphology. Although cell movements involved in tumor invasion are ultimately driven by mechanical forces of cell-cell interactions and tumor-host interactions, how these mechanical properties affect tumor invasion is still poorly understood. In this study, we use a recently developed two-dimensional cellular model to study the effects of mechanical properties on tumor invasion. We study the effects of cell-cell adhesions as well as the degree of degradation and stiffness of extracellular matrix (ECM). Our simulation results show that cell-cell adhesion relationship must be satisfied for tumor invasion. Increased adhesion to ECM and decreased adhesion among tumor cells result in invasive tumor behaviors. When this invasive behavior occurs, ECM plays an important role for both tumor morphology and the shape of invasive cancer cells. Increased stiffness and stronger degree of degradation of ECM promote tumor invasion, generating more aggressive tumor invasive morphologies. It can also generate irregular shape of invasive cancer cells, protruding towards ECM. The capability of our model suggests it a useful tool to study tumor invasion and might be used to propose optimal treatment in clinical applications.

  18. A cellular automata model for avascular solid tumor growth under the effect of therapy

    Science.gov (United States)

    Reis, E. A.; Santos, L. B. L.; Pinho, S. T. R.

    2009-04-01

    Tumor growth has long been a target of investigation within the context of mathematical and computer modeling. The objective of this study is to propose and analyze a two-dimensional stochastic cellular automata model to describe avascular solid tumor growth, taking into account both the competition between cancer cells and normal cells for nutrients and/or space and a time-dependent proliferation of cancer cells. Gompertzian growth, characteristic of some tumors, is described and some of the features of the time-spatial pattern of solid tumors, such as compact morphology with irregular borders, are captured. The parameter space is studied in order to analyze the occurrence of necrosis and the response to therapy. Our findings suggest that transitions exist between necrotic and non-necrotic phases (no-therapy cases), and between the states of cure and non-cure (therapy cases). To analyze cure, the control and order parameters are, respectively, the highest probability of cancer cell proliferation and the probability of the therapeutic effect on cancer cells. With respect to patterns, it is possible to observe the inner necrotic core and the effect of the therapy destroying the tumor from its outer borders inwards.

  19. Modeling cancer metabolism on a genome scale

    Science.gov (United States)

    Yizhak, Keren; Chaneton, Barbara; Gottlieb, Eyal; Ruppin, Eytan

    2015-01-01

    Cancer cells have fundamentally altered cellular metabolism that is associated with their tumorigenicity and malignancy. In addition to the widely studied Warburg effect, several new key metabolic alterations in cancer have been established over the last decade, leading to the recognition that altered tumor metabolism is one of the hallmarks of cancer. Deciphering the full scope and functional implications of the dysregulated metabolism in cancer requires both the advancement of a variety of omics measurements and the advancement of computational approaches for the analysis and contextualization of the accumulated data. Encouragingly, while the metabolic network is highly interconnected and complex, it is at the same time probably the best characterized cellular network. Following, this review discusses the challenges that genome-scale modeling of cancer metabolism has been facing. We survey several recent studies demonstrating the first strides that have been done, testifying to the value of this approach in portraying a network-level view of the cancer metabolism and in identifying novel drug targets and biomarkers. Finally, we outline a few new steps that may further advance this field. PMID:26130389

  20. Modeling dynamics of HIV infected cells using stochastic cellular automaton

    Science.gov (United States)

    Precharattana, Monamorn; Triampo, Wannapong

    2014-08-01

    Ever since HIV was first diagnosed in human, a great number of scientific works have been undertaken to explore the biological mechanisms involved in the infection and progression of the disease. Several cellular automata (CA) models have been introduced to gain insights into the dynamics of the disease progression but none of them has taken into account effects of certain immune cells such as the dendritic cells (DCs) and the CD8+ T lymphocytes (CD8+ T cells). In this work, we present a CA model, which incorporates effects of the HIV specific immune response focusing on the cell-mediated immunities, and investigate the interaction between the host immune response and the HIV infected cells in the lymph nodes. The aim of our work is to propose a model more realistic than the one in Precharattana et al. (2010) [10], by incorporating roles of the DCs, the CD4+ T cells, and the CD8+ T cells into the model so that it would reproduce the HIV infection dynamics during the primary phase of HIV infection.

  1. Cellular and molecular mechanisms underlying alcohol-induced aggressiveness of breast cancer.

    Science.gov (United States)

    Wang, Yongchao; Xu, Mei; Ke, Zun-Ji; Luo, Jia

    2017-01-01

    /ErbB2 signaling contributes to the cellular and molecular events associated with breast cancer aggressiveness. We also discuss the potential therapeutic approaches for cancer patients who drink alcoholic beverages. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. Cellular automaton model of crowd evacuation inspired by slime mould

    Science.gov (United States)

    Kalogeiton, V. S.; Papadopoulos, D. P.; Georgilas, I. P.; Sirakoulis, G. Ch.; Adamatzky, A. I.

    2015-04-01

    In all the living organisms, the self-preservation behaviour is almost universal. Even the most simple of living organisms, like slime mould, is typically under intense selective pressure to evolve a response to ensure their evolution and safety in the best possible way. On the other hand, evacuation of a place can be easily characterized as one of the most stressful situations for the individuals taking part on it. Taking inspiration from the slime mould behaviour, we are introducing a computational bio-inspired model crowd evacuation model. Cellular Automata (CA) were selected as a fully parallel advanced computation tool able to mimic the Physarum's behaviour. In particular, the proposed CA model takes into account while mimicking the Physarum foraging process, the food diffusion, the organism's growth, the creation of tubes for each organism, the selection of optimum tube for each human in correspondence to the crowd evacuation under study and finally, the movement of all humans at each time step towards near exit. To test the model's efficiency and robustness, several simulation scenarios were proposed both in virtual and real-life indoor environments (namely, the first floor of office building B of the Department of Electrical and Computer Engineering of Democritus University of Thrace). The proposed model is further evaluated in a purely quantitative way by comparing the simulation results with the corresponding ones from the bibliography taken by real data. The examined fundamental diagrams of velocity-density and flow-density are found in full agreement with many of the already published corresponding results proving the adequacy, the fitness and the resulting dynamics of the model. Finally, several real Physarum experiments were conducted in an archetype of the aforementioned real-life environment proving at last that the proposed model succeeded in reproducing sufficiently the Physarum's recorded behaviour derived from observation of the aforementioned

  3. Optical quantification of cellular mass, volume and density of circulating tumor cells identified in an ovarian cancer patient

    Directory of Open Access Journals (Sweden)

    Kevin Gregory Phillips

    2012-07-01

    Full Text Available Clinical studies have demonstrated that circulating tumor cells (CTCs are present in the blood of cancer patients with known metastatic disease across the major types of epithelial malignancies. Recent studies have shown that the concentration of CTCs in the blood is prognostic of overall survival in breast, prostate, colorectal and non-small cell lung cancer. This study characterizes CTCs identified using the high-definition (HD-CTC assay in an ovarian cancer patient with stage IIIC disease. We characterized the physical properties of 31 HD-CTCs and 50 normal leukocytes from a single blood draw taken just prior to the initial debulking surgery. We utilized a non-interferometric quantitative phase microscopy technique using brightfield imagery to measure cellular dry mass. Next we used a quantitative differential interference contrast microscopy technique to measure cellular volume. These techniques were combined to determine cellular dry mass density. We found that HD-CTCs were more massive than leukocytes: 33.6 ± 3.2 pg (HD-CTC compared to 18.7 ± 0.6 pg (leukocytes, p < 0.001; had greater volumes: 518.3 ± 24.5 fL (HD-CTC compared to 230.9 ± 78.5 fL (leukocyte, p<0.001; and possessed a decreased dry mass density with respect to leukocytes: 0.065 ± 0.006 pg/fL (HD-CTC compared to 0.085 ± 0.004 pg/fL (leukocyte, p < 0.006. Quantification of HD-CTC dry mass content and volume provide key insights into the fluid dynamics of cancer, and may provide the rationale for strategies to isolate, monitor or target CTCs based on their physical properties. The parameters reported here can also be incorporated into blood cell flow models to better understand metastasis.

  4. A cellular Potts model of germband retraction and dorsal closure

    Science.gov (United States)

    Hutson, M. Shane; Rohner, Jason; Crews, Sarah; McCleery, W. Tyler; Robinson, W. Bradley

    2011-03-01

    Germband retraction and dorsal closure are critical morphogenetic events in fruit fly embryogenesis. Both involve the coordinated reshaping of two epitheloid tissues -- germband (GB) and amnioserosa (AS). The GB is initially curled into a U-shape with the AS between the arms of the U. Retraction leaves the embryo's dorsal surface covered by AS cells which then contract to pull lateral parts of the GB up to cover the dorsal surface. We have simulated these events using a cellular Potts model. The model is 3D with several generalized cell types: a central yolk; a surrounding monolayer of AS and GB cells with epithelial polarization; and an outer vitelline membrane enclosing the cells and a perivitelline fluid. The model also incorporates several critical cell behaviors: polarized apical constriction of AS cells; controlled relaxation of stretched GB cells; and differentiation of GB cells at the GB-AS interface so that these cells then contract a supracellular purse-string and extend filopodia that reach across the AS and zip together the GB's approaching lateral flanks. We will discuss how all of these components are necessary to reproduce normal tissue motions and those observed during laser microsurgery experiments. Supported by NSF Grant IOB-0545679.

  5. A Computational model for compressed sensing RNAi cellular screening

    Directory of Open Access Journals (Sweden)

    Tan Hua

    2012-12-01

    Full Text Available Abstract Background RNA interference (RNAi becomes an increasingly important and effective genetic tool to study the function of target genes by suppressing specific genes of interest. This system approach helps identify signaling pathways and cellular phase types by tracking intensity and/or morphological changes of cells. The traditional RNAi screening scheme, in which one siRNA is designed to knockdown one specific mRNA target, needs a large library of siRNAs and turns out to be time-consuming and expensive. Results In this paper, we propose a conceptual model, called compressed sensing RNAi (csRNAi, which employs a unique combination of group of small interfering RNAs (siRNAs to knockdown a much larger size of genes. This strategy is based on the fact that one gene can be partially bound with several small interfering RNAs (siRNAs and conversely, one siRNA can bind to a few genes with distinct binding affinity. This model constructs a multi-to-multi correspondence between siRNAs and their targets, with siRNAs much fewer than mRNA targets, compared with the conventional scheme. Mathematically this problem involves an underdetermined system of equations (linear or nonlinear, which is ill-posed in general. However, the recently developed compressed sensing (CS theory can solve this problem. We present a mathematical model to describe the csRNAi system based on both CS theory and biological concerns. To build this model, we first search nucleotide motifs in a target gene set. Then we propose a machine learning based method to find the effective siRNAs with novel features, such as image features and speech features to describe an siRNA sequence. Numerical simulations show that we can reduce the siRNA library to one third of that in the conventional scheme. In addition, the features to describe siRNAs outperform the existing ones substantially. Conclusions This csRNAi system is very promising in saving both time and cost for large-scale RNAi

  6. MicroRNAs linking inflamm-aging, cellular senescence and cancer.

    Science.gov (United States)

    Olivieri, Fabiola; Rippo, Maria Rita; Monsurrò, Vladia; Salvioli, Stefano; Capri, Miriam; Procopio, Antonio Domenico; Franceschi, Claudio

    2013-09-01

    Epidemiological and experimental data demonstrate a strong correlation between age-related chronic inflammation (inflamm-aging) and cancer development. However, a comprehensive approach is needed to clarify the underlying molecular mechanisms. Chronic inflammation has mainly been attributed to continuous immune cells activation, but the cellular senescence process, which may involve acquisition of a senescence-associated secretory phenotype (SASP), can be another important contributor, especially in the elderly. MicroRNAs (miRs), a class of molecules involved in gene expression regulation, are emerging as modulators of some pathways, including NF-κB, mTOR, sirtuins, TGF-β and Wnt, that may be related to inflammation, cellular senescence and age-related diseases, cancer included. Interestingly, cancer development is largely avoided or delayed in centenarians, where changes in some miRs are found in plasma and leukocytes. We identified miRs that can be considered as senescence-associated (SA-miRs), inflammation-associated (inflamma-miRs) and cancer-associated (onco-miRs). Here we review recent findings concerning three of them, miR-21, -126 and -146a, which target mRNAs belonging to the NF-κB pathway; we discuss their ability to link cellular senescence, inflamm-aging and cancer and their changes in centenarians, and provide an update on the possibility of using miRs to block accumulation of senescent cells to prevent formation of a microenvironment favoring cancer development and progression. Copyright © 2013 Elsevier B.V. All rights reserved.

  7. Cellular retinol binding protein 1 could be a tumor suppressor gene in cervical cancer

    OpenAIRE

    Mendoza-Rodriguez, Mónica; Arreola, Hugo; Valdivia, Alejandra; Peralta, Raúl; Serna, Humberto,; Villegas, Vanessa; Romero, Pablo; Alvarado-Hernández, Beatriz; Paniagua, Lucero; Marrero-Rodríguez, Daniel; Meraz, Marco A; Salcedo,Mauricio

    2013-01-01

    Aims: Cervical Cancer (CC) is one of the most important health problems in women. It frequently presents genetic changes at chromosome region 3q21. This region contains the Cellular Retinol Binding Protein 1 gene (CRBP1) which has been implicated as an important element in the development of other types of cancer. The main goal of the present work was to determine the molecular alterations of CRBP1 and its relationship to CC. Methods: To determine the molecular alterations of CRBP1 gene in CC...

  8. MDR in cancer: Addressing the underlying cellular alterations with the use of nanocarriers.

    Science.gov (United States)

    Singh, Manu S; Tammam, Salma N; Shetab Boushehri, Maryam A; Lamprecht, Alf

    2017-07-29

    Multidrug resistance (MDR) is associated with a wide range of pathological changes at different cellular and intracellular levels. Nanoparticles (NPs) have been extensively exploited as the carriers of MDR reversing payloads to resistant tumor cells. However, when properly formulated in terms of chemical composition and physicochemical properties, NPs can serve as beyond delivery systems and help overcome MDR even without carrying a load of chemosensitizers or MDR reversing molecular cargos. Whether serving as drug carriers or beyond, a wise design of the nanoparticulate systems to overcome the cellular and intracellular alterations underlying the resistance is imperative. Within the current review, we will initially discuss the cellular changes occurring in resistant cells and how such changes lead to chemotherapy failure and cancer cell survival. We will then focus on different mechanisms through which nanosystems with appropriate chemical composition and physicochemical properties can serve as MDR reversing units at different cellular and intracellular levels according to the changes that underlie the resistance. Finally, we will conclude by discussing logical grounds for a wise and rational design of MDR reversing nanoparticulate systems to improve the cancer therapeutic approaches. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Organizing the Cellular and Molecular Heterogeneity in High Grade Serous Ovarian Cancer by Mass Cytometry

    Science.gov (United States)

    2015-10-01

    the vast array of genetic events found in cancer all converge on three essential cellular processes, cell fate, cell survival and genome maintenance...developed: from the Nolan Lab: Citrus 12, X-shift (unpublished), Gatefinder (unpublished), Pe’er Lab: DREMI 13. A manuscript describing X-shift has been...checked with other clustering algorithms such as used by the Citrus algorithm 12 as well as manual gating of the CyTOF data. The latter is considered

  10. MRI-Derived Cellularity Index as a Potential Noninvasive Imaging Biomarker of Prostate Cancer

    Science.gov (United States)

    2016-12-01

    and RSI plus T2 to predict high grade cancer. (McCammack et al., Abdominal Radiology, 2016) 7) Evaluation of RSI-MRI at voxel-level resolution...Preliminary experience in glioma surgery with intraoperative high -field MRI. Acta Neurochir Suppl 2003;88:21–9. 64. Nimsky C, Grummich P, Sorensen AG...discriminate between brain tumors and adjacent normal tissue with high accuracy and high signal to noise, we hypothesize that the RSI cellularity index will

  11. Organoids as Models for Neoplastic Transformation | Office of Cancer Genomics

    Science.gov (United States)

    Cancer models strive to recapitulate the incredible diversity inherent in human tumors. A key challenge in accurate tumor modeling lies in capturing the panoply of homo- and heterotypic cellular interactions within the context of a three-dimensional tissue microenvironment. To address this challenge, researchers have developed organotypic cancer models (organoids) that combine the 3D architecture of in vivo tissues with the experimental facility of 2D cell lines.

  12. Stochastic cellular automata model for stock market dynamics.

    Science.gov (United States)

    Bartolozzi, M; Thomas, A W

    2004-04-01

    In the present work we introduce a stochastic cellular automata model in order to simulate the dynamics of the stock market. A direct percolation method is used to create a hierarchy of clusters of active traders on a two-dimensional grid. Active traders are characterized by the decision to buy, sigma(i) (t)=+1, or sell, sigma(i) (t)=-1, a stock at a certain discrete time step. The remaining cells are inactive, sigma(i) (t)=0. The trading dynamics is then determined by the stochastic interaction between traders belonging to the same cluster. Extreme, intermittent events, such as crashes or bubbles, are triggered by a phase transition in the state of the bigger clusters present on the grid, where almost all the active traders come to share the same spin orientation. Most of the stylized aspects of the financial market time series, including multifractal proprieties, are reproduced by the model. A direct comparison is made with the daily closures of the S&P 500 index.

  13. Stochastic cellular automata model for stock market dynamics

    Science.gov (United States)

    Bartolozzi, M.; Thomas, A. W.

    2004-04-01

    In the present work we introduce a stochastic cellular automata model in order to simulate the dynamics of the stock market. A direct percolation method is used to create a hierarchy of clusters of active traders on a two-dimensional grid. Active traders are characterized by the decision to buy, σi (t)=+1 , or sell, σi (t)=-1 , a stock at a certain discrete time step. The remaining cells are inactive, σi (t)=0 . The trading dynamics is then determined by the stochastic interaction between traders belonging to the same cluster. Extreme, intermittent events, such as crashes or bubbles, are triggered by a phase transition in the state of the bigger clusters present on the grid, where almost all the active traders come to share the same spin orientation. Most of the stylized aspects of the financial market time series, including multifractal proprieties, are reproduced by the model. A direct comparison is made with the daily closures of the S&P500 index.

  14. Breast Cancer: Modelling and Detection

    OpenAIRE

    Gavaghan, D. J.; Brady, J. M.; Behrenbruch, C. P.; Highnam, R. P.; Maini, P. K.

    2002-01-01

    This paper reviews a number of the mathematical models used in cancer modelling and then chooses a specific cancer, breast carcinoma, to illustrate how the modelling can be used in aiding detection. We then discuss mathematical models that underpin mammographic image analysis, which complements models of tumour growth and facilitates diagnosis and treatment of cancer. Mammographic images are notoriously difficult to interpret, and we give an overview of the primary image enhancement technolog...

  15. Proteomics analyses of prostate cancer cells reveal cellular pathways associated with androgen resistance.

    Science.gov (United States)

    Höti, Naseruddin; Shah, Punit; Hu, Yingwei; Yang, Shuang; Zhang, Hui

    2017-03-01

    While significant advances have been made in the diagnosis and treatment of prostate cancer, each year tens of thousands of men still die from prostate cancer in the United States. Thus, greater understanding of cellular pathways and molecular basis of prostate cancer progression in the development of androgen resistance is needed to treat these lethal phenotypes. To dissect the mechanism of androgen resistance, we utilize a proteomics approach to study the development of androgen resistance in LNCaP prostate cancer cells. Our results showed the predominant involvement of metabolic pathways that were elevated in androgen resistance phenotype. We further found the amplification of PI3K/AKT pathway and the overexpression of proteasome proteins while the mitochondrial oxidation phosphorylation was severely hampered in castration-resistant LNCaP-95 cells compared to LNCaP cells. Interestingly, we also found the induction of Dicer, a cytoplasmic endoribonuclease microRNA regulator in the androgen-ablated LNCaP-95 prostate cancer cells. We verified some of these data by orthogonal methods including Western blot analysis and in castrated animal xenograft studies. To our knowledge, this is the first report showing induced expression of proteasome proteins in androgen ablation prostate cancer cells. If validated in clinical studies, the findings will have significant implications in understanding the complexity of biochemical recurrence in prostate cancer. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Cellular automaton model for mixed traffic flow with motorcycles

    Science.gov (United States)

    Meng, Jian-ping; Dai, Shi-qiang; Dong, Li-yun; Zhang, Jie-fang

    2007-07-01

    A single-lane cellular automaton model is proposed to simulate mixed traffic with motorcycles. By performing numerical simulations under the periodic boundary condition, some density-flow relations and the “lane-changing” behavior of motorcycles are investigated in detail. It is found that the maximum car flow decreases because of the “lane-changing” behavior of motorcycles. The maximum total flow increases first and then decreases with increasing motorcycle density. Moreover, the transition of the total flow from the free flow to the congested flow is smooth in this model. The “lane-changing” rate of motorcycles will decrease to zero finally with the increase of the car density. But its evolutionary trend is considerably complex. Another interesting fact is that, with the increase of the motorcycle density, the “lane-changing” rate increases first and decreases later. This phenomenon is very similar to the findings in other papers on multi-lane car flows. The“lane-changing” is almost of no use in increasing the flow of motorcycles as the motorcycle density is small. But it distinctly causes the increase in the flow of motorcycles when the motorcycle density is sufficiently large, and in this density regime, the flow of motorcycles gradually decreases to the one given with the Nagel-Schreckenberg model for motorcycles with the increase of the car density. The simulation results indicate that it is necessary to set a barrier or a lane for separating the motorcycle flow from the car flow except in some special density regime.

  17. Multifocal Breast Cancer in Young Women with Prolonged Contact between Their Breasts and Their Cellular Phones

    Directory of Open Access Journals (Sweden)

    John G. West

    2013-01-01

    Full Text Available Breast cancer occurring in women under the age of 40 is uncommon in the absence of family history or genetic predisposition, and prompts the exploration of other possible exposures or environmental risks. We report a case series of four young women—ages from 21 to 39—with multifocal invasive breast cancer that raises the concern of a possible association with nonionizing radiation of electromagnetic field exposures from cellular phones. All patients regularly carried their smartphones directly against their breasts in their brassieres for up to 10 hours a day, for several years, and developed tumors in areas of their breasts immediately underlying the phones. All patients had no family history of breast cancer, tested negative for BRCA1 and BRCA2, and had no other known breast cancer risks. Their breast imaging is reviewed, showing clustering of multiple tumor foci in the breast directly under the area of phone contact. Pathology of all four cases shows striking similarity; all tumors are hormone-positive, low-intermediate grade, having an extensive intraductal component, and all tumors have near identical morphology. These cases raise awareness to the lack of safety data of prolonged direct contact with cellular phones.

  18. Multifocal Breast Cancer in Young Women with Prolonged Contact between Their Breasts and Their Cellular Phones.

    Science.gov (United States)

    West, John G; Kapoor, Nimmi S; Liao, Shu-Yuan; Chen, June W; Bailey, Lisa; Nagourney, Robert A

    2013-01-01

    Breast cancer occurring in women under the age of 40 is uncommon in the absence of family history or genetic predisposition, and prompts the exploration of other possible exposures or environmental risks. We report a case series of four young women-ages from 21 to 39-with multifocal invasive breast cancer that raises the concern of a possible association with nonionizing radiation of electromagnetic field exposures from cellular phones. All patients regularly carried their smartphones directly against their breasts in their brassieres for up to 10 hours a day, for several years, and developed tumors in areas of their breasts immediately underlying the phones. All patients had no family history of breast cancer, tested negative for BRCA1 and BRCA2, and had no other known breast cancer risks. Their breast imaging is reviewed, showing clustering of multiple tumor foci in the breast directly under the area of phone contact. Pathology of all four cases shows striking similarity; all tumors are hormone-positive, low-intermediate grade, having an extensive intraductal component, and all tumors have near identical morphology. These cases raise awareness to the lack of safety data of prolonged direct contact with cellular phones.

  19. Viral and Cellular Biomarkers in the Diagnosis of Cervical Intraepithelial Neoplasia and Cancer

    Directory of Open Access Journals (Sweden)

    Maria Lina Tornesello

    2013-01-01

    Full Text Available Cervical cancer arises from cells localized in the ectoendocervical squamocolumnar junction of the cervix persistently infected with one of about 13 human papillomavirus (HPV genotypes. The majority of HPV infections induces low grade squamous epithelial lesions that in more than 90% of cases spontaneously regress and in about 10% eventually progress to high grade lesions and even less frequently evolve to invasive cancer. Tumor progression is characterized by (1 increased expression of E6 and E7 genes of high risk HPVs, known to bind to and inactivate p53 and pRb oncosuppressors, respectively; (2 integration of viral DNA into host genome, with disruption of E2 viral genes and host chromosomal loci; and (3 molecular alterations of key regulators of cell cycle. Molecular markers with high sensitivity and specificity in differentiating viral infections associated with cellular abnormalities with high risk of progression are strongly needed for cervical cancer screening and triage. This review will focus on the analysis of clinical validated or candidate biomarkers, such as HPV DNA, HPV E6/E7 mRNA, HPV proteins, p16(INK4a and Ki67, TOP2A and MCM2 cellular factors, and DNA methylation profiles, which will likely improve the identification of premalignant lesions that have a high risk to evolve into invasive cervical cancer.

  20. A MULTISCALE, CELL-BASED FRAMEWORK FOR MODELING CANCER DEVELOPMENT

    Energy Technology Data Exchange (ETDEWEB)

    JIANG, YI [Los Alamos National Laboratory

    2007-01-16

    Cancer remains to be one of the leading causes of death due to diseases. We use a systems approach that combines mathematical modeling, numerical simulation, in vivo and in vitro experiments, to develop a predictive model that medical researchers can use to study and treat cancerous tumors. The multiscale, cell-based model includes intracellular regulations, cellular level dynamics and intercellular interactions, and extracellular level chemical dynamics. The intracellular level protein regulations and signaling pathways are described by Boolean networks. The cellular level growth and division dynamics, cellular adhesion and interaction with the extracellular matrix is described by a lattice Monte Carlo model (the Cellular Potts Model). The extracellular dynamics of the signaling molecules and metabolites are described by a system of reaction-diffusion equations. All three levels of the model are integrated through a hybrid parallel scheme into a high-performance simulation tool. The simulation results reproduce experimental data in both avasular tumors and tumor angiogenesis. By combining the model with experimental data to construct biologically accurate simulations of tumors and their vascular systems, this model will enable medical researchers to gain a deeper understanding of the cellular and molecular interactions associated with cancer progression and treatment.

  1. Cellular automata model of magnetospheric-ionospheric coupling

    Directory of Open Access Journals (Sweden)

    B. V. Kozelov

    2003-09-01

    Full Text Available We propose a cellular automata model (CAM to describe the substorm activity of the magnetospheric-ionospheric system. The state of each cell in the model is described by two numbers that correspond to the energy content in a region of the current sheet in the magnetospheric tail and to the conductivity of the ionospheric domain that is magnetically connected with this region. The driving force of the system is supposed to be provided by the solar wind that is convected along the two boundaries of the system. The energy flux inside is ensured by the penetration of the energy from the solar wind into the array of cells (magnetospheric tail with a finite velocity. The third boundary (near to the Earth is closed and the fourth boundary is opened, thereby modeling the flux far away from the tail. The energy dissipation in the system is quite similar to other CAM models, when the energy in a particular cell exceeds some pre-defined threshold, and the part of the energy excess is redistributed between the neighbouring cells. The second number attributed to each cell mimics ionospheric conductivity that can allow for a part of the energy to be shed on field-aligned currents. The feedback between "ionosphere" and "magnetospheric tail" is provided by the change in a part of the energy, which is redistributed in the tail when the threshold is surpassed. The control parameter of the model is the z-component of the interplanetary magnetic field (Bz IMF, "frozen" into the solar wind. To study the internal dynamics of the system at the beginning, this control parameter is taken to be constant. The dynamics of the system undergoes several bifurcations, when the constant varies from - 0.6 to - 6.0. The Bz IMF input results in the periodic transients (activation regions and the inter-transient period decreases with the decrease of Bz. At the same time the onset of activations in the array shifts towards the "Earth". When the modulus of the Bz IMF exceeds some

  2. Cellular automata model of magnetospheric-ionospheric coupling

    Directory of Open Access Journals (Sweden)

    B. V. Kozelov

    Full Text Available We propose a cellular automata model (CAM to describe the substorm activity of the magnetospheric-ionospheric system. The state of each cell in the model is described by two numbers that correspond to the energy content in a region of the current sheet in the magnetospheric tail and to the conductivity of the ionospheric domain that is magnetically connected with this region. The driving force of the system is supposed to be provided by the solar wind that is convected along the two boundaries of the system. The energy flux inside is ensured by the penetration of the energy from the solar wind into the array of cells (magnetospheric tail with a finite velocity. The third boundary (near to the Earth is closed and the fourth boundary is opened, thereby modeling the flux far away from the tail. The energy dissipation in the system is quite similar to other CAM models, when the energy in a particular cell exceeds some pre-defined threshold, and the part of the energy excess is redistributed between the neighbouring cells. The second number attributed to each cell mimics ionospheric conductivity that can allow for a part of the energy to be shed on field-aligned currents. The feedback between "ionosphere" and "magnetospheric tail" is provided by the change in a part of the energy, which is redistributed in the tail when the threshold is surpassed. The control parameter of the model is the z-component of the interplanetary magnetic field (Bz IMF, "frozen" into the solar wind. To study the internal dynamics of the system at the beginning, this control parameter is taken to be constant. The dynamics of the system undergoes several bifurcations, when the constant varies from - 0.6 to - 6.0. The Bz IMF input results in the periodic transients (activation regions and the inter-transient period decreases with the decrease of Bz. At the same time the onset of activations in the array shifts towards the "Earth". When the modulus of the Bz IMF exceeds some

  3. Recapitulating and Correcting Marfan Syndrome in a Cellular Model

    Science.gov (United States)

    Park, Jung Woo; Yan, Li; Stoddard, Chris; Wang, Xiaofang; Yue, Zhichao; Crandall, Leann; Robinson, Tiwanna; Chang, Yuxiao; Denton, Kyle; Li, Enqin; Jiang, Bin; Zhang, Zhenwu; Martins-Taylor, Kristen; Yee, Siu-Pok; Nie, Hong; Gu, Feng; Si, Wei; Xie, Ting; Yue, Lixia; Xu, Ren-He

    2017-01-01

    Marfan syndrome (MFS) is a connective tissue disorder caused by mutations in FBN1 gene, which encodes a key extracellular matrix protein FIBRILLIN-1. The haplosufficiency of FBN1 has been implicated in pathogenesis of MFS with manifestations primarily in cardiovascular, muscular, and ocular tissues. Due to limitations in animal models to study the late-onset diseases, human pluripotent stem cells (PSCs) offer a homogeneic tool for dissection of cellular and molecular pathogenic mechanism for MFS in vitro. Here, we first derived induced PSCs (iPSCs) from a MFS patient with a FBN1 mutation and corrected the mutation, thereby generating an isogenic “gain-of-function” control cells for the parental MFS iPSCs. Reversely, we knocked out FBN1 in both alleles in a wild-type (WT) human embryonic stem cell (ESC) line, which served as a loss-of-function model for MFS with the WT cells as an isogenic control. Mesenchymal stem cells derived from both FBN1-mutant iPSCs and -ESCs demonstrated reduced osteogenic differentiation and microfibril formation. We further demonstrated that vascular smooth muscle cells derived from FBN1-mutant iPSCs showed less sensitivity to carbachol as demonstrated by contractility and Ca2+ influx assay, compared to the isogenic controls cells. These findings were further supported by transcriptomic anaylsis of the cells. Therefore, this study based on both gain- and loss-of-function approaches confirmed the pathogenetic role of FBN1 mutations in these MFS-related phenotypic changes. PMID:28539832

  4. Utilizing an enhanced cellular automata model for data mining

    OpenAIRE

    Adwan, Omar; Huneiti, Ammar; Ayyal Awwad, Aiman; Al Damari, Ibrahim; Ortega, Alfonso; Abu Dalhoum, Abdel Latif; Alfonseca, Manuel

    2013-01-01

    Data mining deals with clustering and classifying large amounts of data, in order to discover new knowledge from the existent data by identifying correlations and relationships between various data-sets. Cellular automata have been used before for classification purposes. This paper presents a cellular automata enhanced classification algorithm for data mining. Experimental results show that the proposed enhancement gives better performance in terms of accuracy and execution time than previou...

  5. Downregulation of SREBP inhibits tumor growth and initiation by altering cellular metabolism in colon cancer.

    Science.gov (United States)

    Wen, Yang-An; Xiong, Xiaopeng; Zaytseva, Yekaterina Y; Napier, Dana L; Vallee, Emma; Li, Austin T; Wang, Chi; Weiss, Heidi L; Evers, B Mark; Gao, Tianyan

    2018-02-15

    Sterol regulatory element-binding proteins (SREBPs) belong to a family of transcription factors that regulate the expression of genes required for the synthesis of fatty acids and cholesterol. Three SREBP isoforms, SREBP1a, SREBP1c, and SREBP2, have been identified in mammalian cells. SREBP1a and SREBP1c are derived from a single gene through the use of alternative transcription start sites. Here we investigated the role of SREBP-mediated lipogenesis in regulating tumor growth and initiation in colon cancer. Knockdown of either SREBP1 or SREBP2 decreased levels of fatty acids as a result of decreased expression of SREBP target genes required for lipid biosynthesis in colon cancer cells. Bioenergetic analysis revealed that silencing SREBP1 or SREBP2 expression reduced the mitochondrial respiration, glycolysis, as well as fatty acid oxidation indicating an alteration in cellular metabolism. Consequently, the rate of cell proliferation and the ability of cancer cells to form tumor spheroids in suspension culture were significantly decreased. Similar results were obtained in colon cancer cells in which the proteolytic activation of SREBP was blocked. Importantly, knockdown of either SREBP1 or SREBP2 inhibited xenograft tumor growth in vivo and decreased the expression of genes associated with cancer stem cells. Taken together, our findings establish the molecular basis of SREBP-dependent metabolic regulation and provide a rationale for targeting lipid biosynthesis as a promising approach in colon cancer treatment.

  6. Emergent Behavior from A Cellular Automaton Model for Invasive Tumor Growth in Heterogeneous Microenvironments

    CERN Document Server

    Jiao, Yang

    2011-01-01

    Understanding tumor invasion and metastasis is of crucial importance for both fundamental cancer research and clinical practice. In vitro experiments have established that the invasive growth of malignant tumors is characterized by the dendritic invasive branches composed of chains of tumor cells emanating from the primary tumor mass. The preponderance of previous tumor simulations focused on non-invasive (or proliferative) growth. The formation of the invasive cell chains and their interactions with the primary tumor mass and host microenvironment are not well understood. Here, we present a novel cellular automaton (CA) model that enables one to efficiently simulate invasive tumor growth in a heterogeneous host microenvironment. By taking into account a variety of microscopic-scale tumor-host interactions, including the short-range mechanical interactions between tumor cells and tumor stroma, degradation of extracellular matrix by the invasive cells and oxygen/nutrient gradient driven cell motions, our CA mo...

  7. Knowledge-guided fuzzy logic modeling to infer cellular signaling networks from proteomic data

    Science.gov (United States)

    Liu, Hui; Zhang, Fan; Mishra, Shital Kumar; Zhou, Shuigeng; Zheng, Jie

    2016-10-01

    Modeling of signaling pathways is crucial for understanding and predicting cellular responses to drug treatments. However, canonical signaling pathways curated from literature are seldom context-specific and thus can hardly predict cell type-specific response to external perturbations; purely data-driven methods also have drawbacks such as limited biological interpretability. Therefore, hybrid methods that can integrate prior knowledge and real data for network inference are highly desirable. In this paper, we propose a knowledge-guided fuzzy logic network model to infer signaling pathways by exploiting both prior knowledge and time-series data. In particular, the dynamic time warping algorithm is employed to measure the goodness of fit between experimental and predicted data, so that our method can model temporally-ordered experimental observations. We evaluated the proposed method on a synthetic dataset and two real phosphoproteomic datasets. The experimental results demonstrate that our model can uncover drug-induced alterations in signaling pathways in cancer cells. Compared with existing hybrid models, our method can model feedback loops so that the dynamical mechanisms of signaling networks can be uncovered from time-series data. By calibrating generic models of signaling pathways against real data, our method supports precise predictions of context-specific anticancer drug effects, which is an important step towards precision medicine.

  8. Cancer stem cell overexpression of nicotinamide N-methyltransferase enhances cellular radiation resistance

    DEFF Research Database (Denmark)

    D’Andrea, Filippo P.; Safwat, Akmal; Kassem, Moustapha

    2011-01-01

    validated with q-RT-PCR using TaqMan probes. ResultsThe CE8 clone was more radiation resistant than the BB3 clone. From a pool of 15 validated genes with altered expression in the CE8 clone, we found the enzyme nicotinamide N-methyltransferase (NNMT) more than 5-fold upregulated. In-depth pathway analysis...... found the genes involved in cancer, proliferation, DNA repair and cell death. ConclusionsThe higher radiation resistance in clone CE8 is likely due to NNMT overexpression. The higher levels of NNMT could affect the cellular damage resistance through depletion of the accessible amounts of nicotinamide......, which is a known inhibitor of cellular DNA repair mechanisms....

  9. The Role of Pontin and Reptin in Cellular Physiology and Cancer Etiology

    Directory of Open Access Journals (Sweden)

    Yu-Qian Mao

    2017-08-01

    Full Text Available Pontin (RUVBL1, TIP49, TIP49a, Rvb1 and Reptin (RUVBL2, TIP48, TIP49b, Rvb2 are highly conserved ATPases of the AAA+ (ATPases Associated with various cellular Activities superfamily and are involved in various cellular processes that are important for oncogenesis. First identified as being upregulated in hepatocellular carcinoma and colorectal cancer, their overexpression has since been shown in multiple cancer types such as breast, lung, gastric, esophageal, pancreatic, kidney, bladder as well as lymphatic, and leukemic cancers. However, their exact functions are still quite unknown as they interact with many molecular complexes with vastly different downstream effectors. Within the nucleus, Pontin and Reptin participate in the TIP60 and INO80 complexes important for chromatin remodeling. Although not transcription factors themselves, Pontin and Reptin modulate the transcriptional activities of bona fide proto-oncogenes such as MYC and β-catenin. They associate with proteins involved in DNA damage repair such as PIKK complexes as well as with the core complex of Fanconi anemia pathway. They have also been shown to be important for cell cycle progression, being involved in assembly of telomerase, mitotic spindle, RNA polymerase II, and snoRNPs. When the two ATPases localize to the cytoplasm, they were reported to promote cancer cell invasion and metastasis. Due to their various roles in carcinogenesis, it is not surprising that Pontin and Reptin are proving to be important biomarkers for diagnosis and prognosis of various cancers. They are also current targets for the development of new therapeutic anticancer drugs.

  10. Extracellular vesicles – biomarkers and effectors of the cellular interactome in cancer

    Directory of Open Access Journals (Sweden)

    Janusz eRak

    2013-03-01

    Full Text Available In multicellular organisms both health and disease are defined by patterns of communications between the constituent cells. In addition to networks of soluble mediators, cells are also programmed to exchange complex messages pre-assembled as multimolecular cargo of membraneous structures known extracellular vesicles (EV. Several biogenetic pathways produce EVs with different properties and known as exosomes, ectosomes and apoptotic bodies. In cancer, EVs carry molecular signatures and effectors of the disease, such as mutant oncoproteins, oncogenic transcripts, microRNA and DNA sequences. Intercellular trafficking of such EVs (oncosomes may contribute to horizontal cellular transformation, phenotypic reprogramming and functional re-education of recipient cells, both locally and systemically. The EV-mediated, reciprocal molecular exchange also includes tumor suppressors, phosphoproteins, proteases, growth factors and bioactive lipids, all of which participate in the functional integration of multiple cells and their collective involved in tumor angiogenesis, inflammation, immunity, coagulopathy, mobilization of bone marrow derived effectors, metastasis, drug resistance or cellular stemness. In cases where the EV involvement is rate limiting their production and uptake may represent and unexplored anticancer therapy target. Moreover, oncosomes circulating in biofluids of cancer patients offer an unprecedented, remote and non-invasive access to crucial molecular information about cancer cells, including their driver mutations, classifiers, molecular subtypes, therapeutic targets and biomarkers of drug resistance. New nanotechnologies are being developed to exploit this unique biomarker platform. Indeed, embracing the notion that human cancers are defined not only by processes occurring within cancer cells, but also between them, and amidst the altered tumor and systemic microenvironment may open new diagnostic and therapeutic opportunities.

  11. Comprehensive analysis of cellular galectin-3 reveals no consistent oncogenic function in pancreatic cancer cells.

    Directory of Open Access Journals (Sweden)

    Alexander Hann

    Full Text Available Galectin-3 (Gal-3, a 31 kDa member of the family of beta-galactoside-binding proteins, has been implicated in the progression of different human cancers. However, the proposed roles differ widely, ranging from tumor-promoting cellular functions and negative impact on patient prognosis to tumor-suppressive properties and positive prognostic impact. We and others have previously identified Gal-3 as overexpressed in pancreatic cancer as compared to chronic pancreatitis and normal pancreatic tissue. The purpose of this study was thus the comprehensive analysis of putative cellular functions of Gal-3 by transient as well as stable silencing or overexpression of Gal-3 in a panel of 6 well-established pancreatic cancer cell lines. Our results confirm that galectin-3 is upregulated at the mRNA level in pancreatic cancer and strongly expressed in the majority of pancreatic cancer cell lines. In individual cell lines, transient knockdown of Gal-3 expression resulted in moderate inhibitory effects on proliferation, migration or anchorage-independent growth of the cells, but these effects were not consistent across the spectrum of analyzed cell lines. Moreover, functional effects of the modulation of Gal-3 expression were not observed in stable knockdown or overexpression approaches in vitro and did not alter the growth characteristics of nude mouse xenograft tumors in vivo. Our data thus do not support a direct functional role of Gal-3 in the malignant transformation of pancreatic epithelial cells, although paracrine or systemic effects of Gal-3 expression are not excluded.

  12. Potential Mechanisms for Cancer Resistance in Elephants and Comparative Cellular Response to DNA Damage in Humans.

    Science.gov (United States)

    Abegglen, Lisa M; Caulin, Aleah F; Chan, Ashley; Lee, Kristy; Robinson, Rosann; Campbell, Michael S; Kiso, Wendy K; Schmitt, Dennis L; Waddell, Peter J; Bhaskara, Srividya; Jensen, Shane T; Maley, Carlo C; Schiffman, Joshua D

    2015-11-03

    Evolutionary medicine may provide insights into human physiology and pathophysiology, including tumor biology. To identify mechanisms for cancer resistance in elephants and compare cellular response to DNA damage among elephants, healthy human controls, and cancer-prone patients with Li-Fraumeni syndrome (LFS). A comprehensive survey of necropsy data was performed across 36 mammalian species to validate cancer resistance in large and long-lived organisms, including elephants (n = 644). The African and Asian elephant genomes were analyzed for potential mechanisms of cancer resistance. Peripheral blood lymphocytes from elephants, healthy human controls, and patients with LFS were tested in vitro in the laboratory for DNA damage response. The study included African and Asian elephants (n = 8), patients with LFS (n = 10), and age-matched human controls (n = 11). Human samples were collected at the University of Utah between June 2014 and July 2015. Ionizing radiation and doxorubicin. Cancer mortality across species was calculated and compared by body size and life span. The elephant genome was investigated for alterations in cancer-related genes. DNA repair and apoptosis were compared in elephant vs human peripheral blood lymphocytes. Across mammals, cancer mortality did not increase with body size and/or maximum life span (eg, for rock hyrax, 1% [95% CI, 0%-5%]; African wild dog, 8% [95% CI, 0%-16%]; lion, 2% [95% CI, 0%-7%]). Despite their large body size and long life span, elephants remain cancer resistant, with an estimated cancer mortality of 4.81% (95% CI, 3.14%-6.49%), compared with humans, who have 11% to 25% cancer mortality. While humans have 1 copy (2 alleles) of TP53, African elephants have at least 20 copies (40 alleles), including 19 retrogenes (38 alleles) with evidence of transcriptional activity measured by reverse transcription polymerase chain reaction. In response to DNA damage, elephant lymphocytes underwent p53-mediated apoptosis

  13. Modeling of coupled differential equations for cellular chemical signaling pathways: Implications for assay protocols utilized in cellular engineering.

    Science.gov (United States)

    O'Clock, George D

    2016-08-01

    Cellular engineering involves modification and control of cell properties, and requires an understanding of fundamentals and mechanisms of action for cellular derived product development. One of the keys to success in cellular engineering involves the quality and validity of results obtained from cell chemical signaling pathway assays. The accuracy of the assay data cannot be verified or assured if the effect of positive feedback, nonlinearities, and interrelationships between cell chemical signaling pathway elements are not understood, modeled, and simulated. Nonlinearities and positive feedback in the cell chemical signaling pathway can produce significant aberrations in assay data collection. Simulating the pathway can reveal potential instability problems that will affect assay results. A simulation, using an electrical analog for the coupled differential equations representing each segment of the pathway, provides an excellent tool for assay validation purposes. With this approach, voltages represent pathway enzyme concentrations and operational amplifier feedback resistance and input resistance values determine pathway gain and rate constants. The understanding provided by pathway modeling and simulation is strategically important in order to establish experimental controls for assay protocol structure, time frames specified between assays, and assay concentration variation limits; to ensure accuracy and reproducibility of results.

  14. Downregulation of microRNA-498 in colorectal cancers and its cellular effects

    Energy Technology Data Exchange (ETDEWEB)

    Gopalan, Vinod; Smith, Robert A.; Lam, Alfred K.-Y., E-mail: a.lam@griffith.edu.au

    2015-01-15

    miR-498 is a non-coding RNA located intergenically in 19q13.41. Due to its predicted targeting of several genes involved in control of cellular growth, we examined the expression of miR-498 in colon cancer cell lines and a large cohort of patients with colorectal adenocarcinoma. Two colon cancer cancer cell lines (SW480 and SW48) and one normal colonic epithelial cell line (FHC) were recruited. The expression of miR-498 was tested in these cell lines by using quantitative real-time polymerase chain reaction (qRT-PCR). Tissues from 80 patients with surgical resection of colorectum (60 adenocarcinomas and 20 non-neoplastic tissues) were tested for miR-498 expression by qRT-PCR. In addition, an exogenous miR-498 (mimic) was used to detect the miRNA's effects on cell proliferation and cell cycle events in SW480 using MTT calorimetric assay and flow cytometry respectively. The colon cancer cell lines showed reduced expression of miR-498 compared to a normal colonic epithelial cell line. Mimic driven over expression of miR-498 in the SW480 cell line resulted in reduced cell proliferation and increased proportions of G2-M phase cells. In tissues, miR-498 expression was too low to be detected in all colorectal adenocarcinoma compared to non-neoplastic tissues. This suggests that the down regulation of miR-498 in colorectal cancer tissues and the direct suppressive cellular effect noted in cancer cell lines implies that miR-498 has some direct or indirect role in the pathogenesis of colorectal adenocarcinomas. - Highlights: • miR-498 is a non-coding RNA located in 19q13.41. • Colon cancer cell lines showed reduced expression of miR-498. • Mimic driven over expression of miR-498 in colon cancer cells resulted in lower cell proliferation. • miR-498 expression was down regulated in all colorectal adenocarcinoma tissues.

  15. The dynamics of shifting cultivation captured in an extended Constrained Cellular Automata land use model

    NARCIS (Netherlands)

    Wickramasuriya, R.C.; Bregt, A.K.; Delden, van H.; Hagen-Zanker, A.

    2009-01-01

    This paper presents an extension to the Constrained Cellular Automata (CCA) land use model of White et al. [White, R., Engelen, G., Uljee, I., 1997. The use of constrained cellular automata for high-resolution modelling of urban land-use dynamics. Environment and Planning B: Planning and Design

  16. A Model of How Different Biology Experts Explain Molecular and Cellular Mechanisms

    Science.gov (United States)

    Trujillo, Caleb M.; Anderson, Trevor R.; Pelaez, Nancy J.

    2015-01-01

    Constructing explanations is an essential skill for all science learners. The goal of this project was to model the key components of expert explanation of molecular and cellular mechanisms. As such, we asked: What is an appropriate model of the components of explanation used by biology experts to explain molecular and cellular mechanisms? Do…

  17. Pathloss Measurements and Modeling for UAVs Connected to Cellular Networks

    DEFF Research Database (Denmark)

    Amorim, Rafhael Medeiros de; Mogensen, Preben Elgaard; Sørensen, Troels Bundgaard

    2017-01-01

    This paper assess field measurements, as part of the investigation of the suitability of cellular networks for providing connectivity to UAVs (unmanned aerial vehicles). Evaluation is done by means of field measurements obtained in a rural environment in Denmark with an airbone UAV. The measureme...

  18. Endogenous Molecular-Cellular Network Cancer Theory: A Systems Biology Approach.

    Science.gov (United States)

    Wang, Gaowei; Yuan, Ruoshi; Zhu, Xiaomei; Ao, Ping

    2018-01-01

    In light of ever apparent limitation of the current dominant cancer mutation theory, a quantitative hypothesis for cancer genesis and progression, endogenous molecular-cellular network hypothesis has been proposed from the systems biology perspective, now for more than 10 years. It was intended to include both the genetic and epigenetic causes to understand cancer. Its development enters the stage of meaningful interaction with experimental and clinical data and the limitation of the traditional cancer mutation theory becomes more evident. Under this endogenous network hypothesis, we established a core working network of hepatocellular carcinoma (HCC) according to the hypothesis and quantified the working network by a nonlinear dynamical system. We showed that the two stable states of the working network reproduce the main known features of normal liver and HCC at both the modular and molecular levels. Using endogenous network hypothesis and validated working network, we explored genetic mutation pattern in cancer and potential strategies to cure or relieve HCC from a totally new perspective. Patterns of genetic mutations have been traditionally analyzed by posteriori statistical association approaches in light of traditional cancer mutation theory. One may wonder the possibility of a priori determination of any mutation regularity. Here, we found that based on the endogenous network theory the features of genetic mutations in cancers may be predicted without any prior knowledge of mutation propensities. Normal hepatocyte and cancerous hepatocyte stable states, specified by distinct patterns of expressions or activities of proteins in the network, provide means to directly identify a set of most probable genetic mutations and their effects in HCC. As the key proteins and main interactions in the network are conserved through cell types in an organism, similar mutational features may also be found in other cancers. This analysis yielded straightforward and testable

  19. Factor models for cancer signatures

    Science.gov (United States)

    Kakushadze, Zura; Yu, Willie

    2016-11-01

    We present a novel method for extracting cancer signatures by applying statistical risk models (http://ssrn.com/abstract=2732453) from quantitative finance to cancer genome data. Using 1389 whole genome sequenced samples from 14 cancers, we identify an ;overall; mode of somatic mutational noise. We give a prescription for factoring out this noise and source code for fixing the number of signatures. We apply nonnegative matrix factorization (NMF) to genome data aggregated by cancer subtype and filtered using our method. The resultant signatures have substantially lower variability than those from unfiltered data. Also, the computational cost of signature extraction is cut by about a factor of 10. We find 3 novel cancer signatures, including a liver cancer dominant signature (96% contribution) and a renal cell carcinoma signature (70% contribution). Our method accelerates finding new cancer signatures and improves their overall stability. Reciprocally, the methods for extracting cancer signatures could have interesting applications in quantitative finance.

  20. Modeling chemical systems using cellular automata a textbook and laboratory manual

    CERN Document Server

    Kier, Lemont B; Cheng, Chao-Kun

    2005-01-01

    There are few publications on Cellular Automata and certainly no direct competition Insight into a new modeling paradigm Novel approach to the use of in silico modeling to replace or supplement costly labs.

  1. Cancer control through principles of systems science, complexity, and chaos theory: a model.

    Science.gov (United States)

    Janecka, Ivo P

    2007-06-05

    Cancer is a significant medical and societal problem. This reality arises from the fact that an exponential and an unrestricted cellular growth destabilizes human body as a system. From this perspective, cancer is a manifestation of a system-in-failing.A model of normal and abnormal cell cycle oscillations has been developed incorporating systems science, complexity, and chaos theories. Using this model, cancer expresses a failing subsystem and is characterized by a positive exponential growth taking place in the outer edge of chaos. The overall survival of human body as a system is threatened. This model suggests, however, that cancer's exponential cellular growth and disorganized complexity could be controlled through the process of induction of differentiation of cancer stem cells into cells of low and basic functionality. This concept would imply reorientation of current treatment principles from cellular killing (cyto-toxic therapies) to cellular retraining (cyto-education).

  2. Magnolol Affects Cellular Proliferation, Polyamine Biosynthesis and Catabolism-Linked Protein Expression and Associated Cellular Signaling Pathways in Human Prostate Cancer Cells in vitro

    Directory of Open Access Journals (Sweden)

    Brendan T. McKeown

    2015-01-01

    Full Text Available Background: Prostate cancer is the most commonly diagnosed form of cancer in men in Canada and the United States. Both genetic and environmental factors contribute to the development and progression of many cancers, including prostate cancer. Context and purpose of this study: This study investigated the effects of magnolol, a compound found in the roots and bark of the magnolia tree Magnolia officinalis, on cellular proliferation and proliferation-linked activities of PC3 human prostate cancer cells in vitro. Results: PC3 cells exposed to magnolol at a concentration of 80 μM for 6 hours exhibited decreased protein expression of ornithine decarboxylase, a key regulator in polyamine biosynthesis, as well as affecting the expression of other proteins involved in polyamine biosynthesis and catabolism. Furthermore, protein expression of the R2 subunit of ribonucleotide reductase, a key regulatory protein associated with DNA synthesis, was significantly decreased. Finally, the MAPK (mitogen-activated protein kinase, PI3K (phosphatidylinositol 3-kinase, NFκB (nuclear factor of kappa-light-chain-enhancer of activated B cells and AP-1 (activator protein 1 cellular signaling pathways were assayed to determine which, if any, of these pathways magnolol exposure would alter. Protein expressions of p-JNK-1 and c-jun were significantly increased while p-p38, JNK-1/2, PI3Kp85, p-PI3Kp85, p-Akt, NFκBp65, p-IκBα and IκBα protein expressions were significantly decreased. Conclusions: These alterations further support the anti-proliferative effects of magnolol on PC3 human prostate cancer cells in vitro and suggest that magnolol may have potential as a novel anti-prostate cancer agent.

  3. Biology of cancer and aging: a complex association with cellular senescence.

    Science.gov (United States)

    Falandry, Claire; Bonnefoy, Marc; Freyer, Gilles; Gilson, Eric

    2014-08-20

    Over the last 50 years, major improvements have been made in our understanding of the driving forces, both parallel and opposing, that lead to aging and cancer. Many theories on aging first proposed in the 1950s, including those associated with telomere biology, senescence, and adult stem-cell regulation, have since gained support from cumulative experimental evidence. These views suggest that the accumulation of mutations might be a common driver of both aging and cancer. Moreover, some tumor suppressor pathways lead to aging in line with the theory of antagonist pleiotropy. According to the evolutionary-selected disposable soma theory, aging should affect primarily somatic cells. At the cellular level, both intrinsic and extrinsic pathways regulate aging and senescence. However, increasing lines of evidence support the hypothesis that these driving forces might be regulated by evolutionary-conserved pathways that modulate energy balance. According to the hyperfunction theory, aging is a quasi-program favoring both age-related diseases and cancer that could be inhibited by the regulation of longevity pathways. This review summarizes these hypotheses, as well as the experimental data that have accumulated over the last 60 years linking aging and cancer.

  4. An Exploration of the Role of Cellular Neuroplasticity in Large Scale Models of Biological Neural Networks

    OpenAIRE

    Skorheim, Steven W.

    2014-01-01

    Cellular level learning is vital to almost all brain function, and extensive homeostatic plasticity is required to maintain brain functionality. While much has been learned about cellular level plasticity in vivo, how these mechanisms affect higher level functionality is not readily apparent. The cellular level circuitry of most networks that process information is unknown. A variety of models were developed to better understand plasticity in both learning and homeostasis. Spike time dependen...

  5. The role of nutraceuticals in pancreatic cancer prevention and therapy: Targeting cellular signaling, miRNAs and epigenome

    Science.gov (United States)

    Li, Yiwei; Go, Vay Liang W.; Sarkar, Fazlul H.

    2014-01-01

    Pancreatic cancer is one of the most aggressive malignancies in US adults. The experimental studies have found that antioxidant nutrients could reduce oxidative DNA damage, suggesting that these antioxidants may protect against pancreatic carcinogenesis. Several epidemiologic studies showed that dietary intake of antioxidants was inversely associated with the risk of pancreatic cancer, demonstrating the inhibitory effects of antioxidants on pancreatic carcinogenesis. Moreover, nutraceuticals, the anti-cancer agents from diet or natural plants, have been found to inhibit the development and progression of pancreatic cancer through the regulation of cellular signaling pathways. Importantly, nutraceuticals also up-regulate the expression of tumor suppressive miRNAs and down-regulate the expression of oncogenic miRNAs, leading to the inhibition of pancreatic cancer cell growth and pancreatic Cancer Stem Cell (CSC) self-renewal through modulation of cellular signaling network. Furthermore, nutraceuticals also regulate epigenetically deregulated DNAs and miRNAs, leading to the normalization of altered cellular signaling in pancreatic cancer cells. Therefore, nutraceuticals could have much broader use in the prevention and/or treatment of pancreatic cancer in combination with conventional chemotherapeutics. However, more in vitro mechanistic experiments, in vivo animal studies, and clinical trials are needed to realize the true value of nutraceuticals in the prevention and/or treatment of pancreatic cancer. PMID:25493373

  6. Development of in vitro models for cellular and molecular studies in toxicology and chemoprevention

    Energy Technology Data Exchange (ETDEWEB)

    Mace, K.; Offord, E.A.; Harris, C.C.; Pfeifer, A.M.A. [Nestle Research Center, Lausanne (Switzerland)

    1998-12-31

    Many natural dietary phytochemicals found compounds found in fruits, vegetables, spices and tea have been shown in recent years to be protective against cancer in various animal models. In the light of the potential impact of these compounds on human health it is important to elucidate the mechanisms involved. We therefore developed and characterized relevant in vitro models using immortalized human epithelial cell lines derived from target tissues in carcinogenesis, such as lung, liver and colon. Assays were established, allowing the evaluation of the cytotoxic and genotoxic effects of various procarcinogens, including nitrosamines, mycotoxins and heterocyclic amines on these metabolically-competent human epithelial cell lines. These cellular models appeared to be a useful tool to study the capacity of certain food components to block the initiation stage of carcinogenesis. The ability of carnosol and carnosic acid from rosemary as well as the synthetic dithiolethione, oltipraz, to block the formation of DNA adducts, and their effects on the expression of phase I and phase II enzymes was investigated. We have observed that both rosemary extracts and oltiprax inhibited benzo(a)pyrene- or aflatoxin B{sub 1}-induced DNA adduct formation by strongly inhibiting CYP{sub 450} activities and inducing the expression of glutathione S-transferase. These results in human cell models give some insight into the different mechanisms involved in the chemopreventive action of both natural and synthetic compounds in relation to phase I and phase II enzymes. (orig.)

  7. Integration of high-risk human papillomavirus into cellular cancer-related genes in head and neck cancer cell lines.

    Science.gov (United States)

    Walline, Heather M; Goudsmit, Christine M; McHugh, Jonathan B; Tang, Alice L; Owen, John H; Teh, Bin T; McKean, Erin; Glover, Thomas W; Graham, Martin P; Prince, Mark E; Chepeha, Douglas B; Chinn, Steven B; Ferris, Robert L; Gollin, Susanne M; Hoffmann, Thomas K; Bier, Henning; Brakenhoff, Ruud; Bradford, Carol R; Carey, Thomas E

    2017-05-01

    Human papillomavirus (HPV)-positive oropharyngeal cancer is generally associated with excellent response to therapy, but some HPV-positive tumors progress despite aggressive therapy. The purpose of this study was to evaluate viral oncogene expression and viral integration sites in HPV16- and HPV18-positive squamous cell carcinoma lines. E6/E7 alternate transcripts were assessed by reverse transcriptase-polymerase chain reaction (RT-PCR). Detection of integrated papillomavirus sequences (DIPS-PCR) and sequencing identified viral insertion sites and affected host genes. Cellular gene expression was assessed across viral integration sites. All HPV-positive cell lines expressed alternate HPVE6/E7 splicing indicative of active viral oncogenesis. HPV integration occurred within cancer-related genes TP63, DCC, JAK1, TERT, ATR, ETV6, PGR, PTPRN2, and TMEM237 in 8 head and neck squamous cell carcinoma (HNSCC) lines but UM-SCC-105 and UM-GCC-1 had only intergenic integration. HPV integration into cancer-related genes occurred in 7 of 9 HPV-positive cell lines and of these 6 were from tumors that progressed. HPV integration into cancer-related genes may be a secondary carcinogenic driver in HPV-driven tumors. © 2017 Wiley Periodicals, Inc. Head Neck 39: 840-852, 2017. © 2017 Wiley Periodicals, Inc.

  8. Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model

    Science.gov (United States)

    Khajavigodellou, Yousef; Alesheikh, Ali A.; Mohammed, Abdulrazak A. S.; Chapi, Kamran

    2014-09-01

    Recently, the interaction between humans and their environment is the one of important challenges in the world. Landuse/ cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. The complexity and dynamics of urban systems make the applicable practice of urban modeling very difficult. With the increased computational power and the greater availability of spatial data, micro-simulation such as the agent based and cellular automata simulation methods, has been developed by geographers, planners, and scholars, and it has shown great potential for representing and simulating the complexity of the dynamic processes involved in urban growth and land use change. This paper presents Fuzzy Cellular Automata in Geospatial Information System and remote Sensing to simulated and predicted urban expansion pattern. These FCA-based dynamic spatial urban models provide an improved ability to forecast and assess future urban growth and to create planning scenarios, allowing us to explore the potential impacts of simulations that correspond to urban planning and management policies. A fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on Land use change is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. The model integrates an ABM (agent-based model) and FCA (Fuzzy Cellular Automata) to investigate a complex decision-making process and future urban dynamic processes. Based on this model rapid development and green land protection under the influences of the behaviors and decision modes of regional authority agents, real estate developer agents, resident agents and non- resident agents and their interactions have been applied to predict the future development patterns of the Erbil metropolitan region.

  9. A mathematical model of amphibian skin epithelium with two types of transporting cellular units

    DEFF Research Database (Denmark)

    Larsen, Erik Hviid; Rasmussen, B E

    1985-01-01

    A computer model of ion transport across amphibian skin epithelium containing two types of cellular units, their relative number and sizes, and a paracellular pathway has been developed. The two cellular units are, a large Na+ transporting compartment representing the major epithelium from stratum...

  10. Effect of morphology on water sorption in cellular solid foods. Part I: Pore scale network model

    NARCIS (Netherlands)

    Esveld, D.C.; Sman, van der R.G.M.; Dalen, van G.; Duynhoven, van J.P.M.; Meinders, M.B.J.

    2012-01-01

    A pore scale network model is developed to predict the dynamics of moisture diffusion into complex cellular solid foods like bread, crackers, and cereals. The morphological characteristics of the sample, including the characteristics of each cellular void and the open pore connections between them

  11. Predictive model to describe water migration in cellular solid foods during storage

    NARCIS (Netherlands)

    Voogt, J.A.; Hirte, A.; Meinders, M.B.J.

    2011-01-01

    BACKGROUND: Water migration in cellular solid foods during storage causes loss of crispness. To improve crispness retention, physical understanding of this process is needed. Mathematical models are suitable tools to gain this physical knowledge. RESULTS: Water migration in cellular solid foods

  12. Predictive model to describe water migration in cellular solid foods during storage

    NARCIS (Netherlands)

    Voogt, J.A.; Hirte, A.; Meinders, M.B.J.

    2011-01-01

    Background: Water migration in cellular solid foods during storage causes loss of crispness. To improve crispness retention, physical understanding of this process is needed. Mathematical models are suitable tools to gain this physical knowledge. Results: Water migration in cellular solid foods

  13. Multi-scale modeling with cellular automata: The complex automata approach

    NARCIS (Netherlands)

    Hoekstra, A.G.; Falcone, J.-L.; Caiazzo, A.; Chopard, B.

    2008-01-01

    Cellular Automata are commonly used to describe complex natural phenomena. In many cases it is required to capture the multi-scale nature of these phenomena. A single Cellular Automata model may not be able to efficiently simulate a wide range of spatial and temporal scales. It is our goal to

  14. The Emerging Role of Skeletal Muscle Metabolism as a Biological Target and Cellular Regulator of Cancer-Induced Muscle Wasting

    Science.gov (United States)

    Carson, James A.; Hardee, Justin P.; VanderVeen, Brandon N.

    2015-01-01

    While skeletal muscle mass is an established primary outcome related to understanding cancer cachexia mechanisms, considerable gaps exist in our understanding of muscle biochemical and functional properties that have recognized roles in systemic health. Skeletal muscle quality is a classification beyond mass, and is aligned with muscle’s metabolic capacity and substrate utilization flexibility. This supplies an additional role for the mitochondria in cancer-induced muscle wasting. While the historical assessment of mitochondria content and function during cancer-induced muscle loss was closely aligned with energy flux and wasting susceptibility, this understanding has expanded to link mitochondria dysfunction to cellular processes regulating myofiber wasting. The primary objective of this article is to highlight muscle mitochondria and oxidative metabolism as a biological target of cancer cachexia and also as a cellular regulator of cancer-induced muscle wasting. Initially, we examine the role of muscle metabolic phenotype and mitochondria content in cancer-induced wasting susceptibility. We then assess the evidence for cancer-induced regulation of skeletal muscle mitochondrial biogenesis, dynamics, mitophagy, and oxidative stress. In addition, we discuss environments associated with cancer cachexia that can impact the regulation of skeletal muscle oxidative metabolism. The article also examines the role of cytokine-mediated regulation of mitochondria function regulation, followed by the potential role of cancer-induced hypogonadism. Lastly, a role for decreased muscle use in cancer-induced mitochondrial dysfunction is reviewed. PMID:26593326

  15. Colorectal Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing colorectal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  16. Cervical Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  17. Liver Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing liver cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  18. Ovarian Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing ovarian cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  19. Bladder Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing bladder cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  20. Potential Mechanisms for Cancer Resistance in Elephants and Comparative Cellular Response to DNA Damage in Humans

    Science.gov (United States)

    Abegglen, Lisa M.; Caulin, Aleah F.; Chan, Ashley; Lee, Kristy; Robinson, Rosann; Campbell, Michael S.; Kiso, Wendy K.; Schmitt, Dennis L.; Waddell, Peter J; Bhaskara, Srividya; Jensen, Shane T.; Maley, Carlo C.; Schiffman, Joshua D.

    2016-01-01

    IMPORTANCE Evolutionary medicine may provide insights into human physiology and pathophysiology, including tumor biology. OBJECTIVE To identify mechanisms for cancer resistance in elephants and compare cellular response to DNA damage among elephants, healthy human controls, and cancer-prone patients with Li-Fraumeni syndrome (LFS). DESIGN, SETTING, AND PARTICIPANTS A comprehensive survey of necropsy data was performed across 36 mammalian species to validate cancer resistance in large and long-lived organisms, including elephants (n = 644). The African and Asian elephant genomes were analyzed for potential mechanisms of cancer resistance. Peripheral blood lymphocytes from elephants, healthy human controls, and patients with LFS were tested in vitro in the laboratory for DNA damage response. The study included African and Asian elephants (n = 8), patients with LFS (n = 10), and age-matched human controls (n = 11). Human samples were collected at the University of Utah between June 2014 and July 2015. EXPOSURES Ionizing radiation and doxorubicin. MAIN OUTCOMES AND MEASURES Cancer mortality across species was calculated and compared by body size and life span. The elephant genome was investigated for alterations in cancer-related genes. DNA repair and apoptosis were compared in elephant vs human peripheral blood lymphocytes. RESULTS Across mammals, cancer mortality did not increase with body size and/or maximum life span (eg, for rock hyrax, 1% [95%CI, 0%–5%]; African wild dog, 8%[95%CI, 0%–16%]; lion, 2%[95%CI, 0% –7%]). Despite their large body size and long life span, elephants remain cancer resistant, with an estimated cancer mortality of 4.81% (95%CI, 3.14%–6.49%), compared with humans, who have 11% to 25%cancer mortality. While humans have 1 copy (2 alleles) of TP53, African elephants have at least 20 copies (40 alleles), including 19 retrogenes (38 alleles) with evidence of transcriptional activity measured by reverse transcription polymerase chain

  1. The accessory proteins REEP5 and REEP6 refine CXCR1-mediated cellular responses and lung cancer progression.

    Science.gov (United States)

    Park, Cho Rong; You, Dong-Joo; Park, Sumi; Mander, Sunam; Jang, Da-Eun; Yeom, Su-Cheong; Oh, Seong-Hyun; Ahn, Curie; Lee, Sang Heon; Seong, Jae Young; Hwang, Jong-Ik

    2016-12-14

    Some G-protein-coupled receptors have been reported to require accessory proteins with specificity for proper functional expression. In this study, we found that CXCR1 interacted with REEP5 and REEP6, but CXCR2 did not. Overexpression of REEP5 and REEP6 enhanced IL-8-stimulated cellular responses through CXCR1, whereas depletion of the proteins led to the downregulation of the responses. Although REEPs enhanced the expression of a subset of GPCRs, in the absence of REEP5 and REEP6, CXCR1 was expressed in the plasma membrane, but receptor internalization and intracellular clustering of β-arrestin2 following IL-8 treatment were impaired, suggesting that REEP5 and REEP6 might be involved in the ligand-stimulated endocytosis of CXCR1 rather than membrane expression, which resulted in strong cellular responses. In A549 lung cancer cells, which endogenously express CXCR1, the depletion of REEP5 and REEP6 significantly reduced growth and invasion by downregulating IL-8-stimulated ERK phosphorylation, actin polymerization and the expression of genes related to metastasis. Furthermore, an in vivo xenograft model showed that proliferation and metastasis of A549 cells lacking REEP5 and REEP6 were markedly decreased compared to the control group. Thus, REEP5 and REEP6 could be novel regulators of G-protein-coupled receptor signaling whose functional mechanisms differ from other accessory proteins.

  2. KPNA2 is overexpressed in human and mouse endometrial cancers and promotes cellular proliferation.

    Science.gov (United States)

    Ikenberg, Kristian; Valtcheva, Nadejda; Brandt, Simone; Zhong, Qing; Wong, Christine E; Noske, Aurelia; Rechsteiner, Markus; Rueschoff, Jan H; Caduff, Rosmarie; Dellas, Athanassios; Obermann, Ellen; Fink, Daniel; Fuchs, Thomas; Krek, Wilhelm; Moch, Holger; Frew, Ian J; Wild, Peter J

    2014-10-01

    Endometrial cancer is the most frequently occurring malignancy of the female genital tract in Western countries. Although in many cases surgically curable, about 30% of the tumours represent an aggressive and untreatable disease. In an attempt to establish a reliable prognostic marker for endometrial carcinomas disregarding their histological diversity, we investigated the expression of KPNA2, a mediator of nucleocytoplasmic transport, and other cell proliferation-associated proteins and their correlation with cancer progression. We analysed patient tissue microarrays (TMAs) assembled from 527 endometrial cancer tissue specimens and uterus samples from a Trp53 knockout mouse model of endometrial cancer. Our data show that KPNA2 expression was significantly up-regulated in human endometrial carcinomas and associated with higher tumour grade (p = 0.026), higher FIGO stage (p = 0.027), p53 overexpression (p endometrial cancer subtype was detected. In the mouse model, KPNA2 showed increased expression levels from precancerous (EmgD, EIC) to far-advanced invasive lesions. We further investigated the cell proliferation capacity after siRNA-mediated KPNA2 knockdown in the human endometrial cancer cell line MFE-296. KPNA2 silencing led to decreased proliferation of the cancer cells, suggesting interplay of the protein with the cell cycle. Taken together, increased expression of KPNA2 is an independent prognostic marker for poor survival. The mechanism of enhanced nucleocytoplasmic transport by KPNA2 overexpression seems a common event in aggressive cancers since we have shown a significant correlation of KPNA2 expression and tumour aggressiveness in a large variety of other solid tumour entities. Introducing KPNA2 immunohistochemistry in routine diagnostics may allow for the identification of patients who need more aggressive treatment regimens. Copyright © 2014 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

  3. Mouse Models of Gastric Cancer

    Science.gov (United States)

    Hayakawa, Yoku; Fox, James G.; Gonda, Tamas; Worthley, Daniel L.; Muthupalani, Sureshkumar; Wang, Timothy C.

    2013-01-01

    Animal models have greatly enriched our understanding of the molecular mechanisms of numerous types of cancers. Gastric cancer is one of the most common cancers worldwide, with a poor prognosis and high incidence of drug-resistance. However, most inbred strains of mice have proven resistant to gastric carcinogenesis. To establish useful models which mimic human gastric cancer phenotypes, investigators have utilized animals infected with Helicobacter species and treated with carcinogens. In addition, by exploiting genetic engineering, a variety of transgenic and knockout mouse models of gastric cancer have emerged, such as INS-GAS mice and TFF1 knockout mice. Investigators have used the combination of carcinogens and gene alteration to accelerate gastric cancer development, but rarely do mouse models show an aggressive and metastatic gastric cancer phenotype that could be relevant to preclinical studies, which may require more specific targeting of gastric progenitor cells. Here, we review current gastric carcinogenesis mouse models and provide our future perspectives on this field. PMID:24216700

  4. Dynamic Fluorescence Microscopy of Cellular Uptake of Intercalating Model Drugs by Ultrasound-Activated Microbubbles

    NARCIS (Netherlands)

    Lammertink, B.H.A.; Deckers, R.; Derieppe, M.; De Cock, I.; Lentacker, I.; Storm, G.; Moonen, C. T.W.; Bos, C.

    2017-01-01

    Purpose: The combination of ultrasound and microbubbles can facilitate cellular uptake of (model) drugs via transient permeabilization of the cell membrane. By using fluorescent molecules, this process can be studied conveniently with confocal fluorescence microscopy. This study aimed to investigate

  5. Synthesis and cellular uptake of folic acid-conjugated cellulose nanocrystals for cancer targeting.

    Science.gov (United States)

    Dong, Shuping; Cho, Hyung Joon; Lee, Yong Woo; Roman, Maren

    2014-05-12

    Elongated nanoparticles have recently been shown to have distinct advantages over spherical ones in targeted drug delivery applications. In addition to their oblong geometry, their lack of cytotoxicity and numerous surface hydroxyl groups make cellulose nanocrystals (CNCs) promising drug delivery vectors. Herein we report the synthesis of folic acid-conjugated CNCs for the targeted delivery of chemotherapeutic agents to folate receptor-positive cancer cells. Folate receptor-mediated cellular binding/uptake of the conjugate was demonstrated on human (DBTRG-05MG, H4) and rat (C6) brain tumor cells. Folate receptor expression of the cells was verified by immunofluorescence staining. Cellular binding/uptake of the conjugate by DBTRG-05MG, H4, and C6 cells was 1452, 975, and 46 times higher, respectively, than that of nontargeted CNCs. The uptake mechanism was determined by preincubation of the cells with the uptake inhibitors chlorpromazine or genistein. DBTRG-05MG and C6 cells internalized the conjugate primarily via caveolae-mediated endocytosis, whereas H4 cells internalized the conjugate primarily via clathrin-mediated endocytosis.

  6. Investigation of the Causes of Breast Cancer at the Cellular Level: Isolation of In Vivo Binding Sites of the Human Origin Recognition Complex

    National Research Council Canada - National Science Library

    Mendez, Juan

    2000-01-01

    ... of cellular life tipically lost in cancer. In order to unravel the molecular mechanisms of human DNA replication in normal and cancer cells, we have started a search for human DNA sequences that serve as replicators", this is, binding sites...

  7. Understanding Cellular Mechanisms Underlying Airway Epithelial Repair: Selecting the Most Appropriate Animal Models

    OpenAIRE

    Yahaya, B.

    2012-01-01

    Understanding the mechanisms underlying the process of regeneration and repair of airway epithelial structures demands close characterization of the associated cellular and molecular events. The choice of an animal model system to study these processes and the role of lung stem cells is debatable since ideally the chosen animal model should offer a valid comparison with the human lung. Species differences may include the complex three-dimensional lung structures, cellular composition of the l...

  8. Cellular automata model for use with real freeway data

    Science.gov (United States)

    2002-01-01

    The exponential rate of increase in freeway traffic is expanding the need for accurate and : realistic methods to model and predict traffic flow. Traffic modeling and simulation facilitates an : examination of both microscopic and macroscopic views o...

  9. Human mammary microenvironment better regulates the biology of human breast cancer in humanized mouse model.

    Science.gov (United States)

    Zheng, Ming-Jie; Wang, Jue; Xu, Lu; Zha, Xiao-Ming; Zhao, Yi; Ling, Li-Jun; Wang, Shui

    2015-02-01

    During the past decades, many efforts have been made in mimicking the clinical progress of human cancer in mouse models. Previously, we developed a human breast tissue-derived (HB) mouse model. Theoretically, it may mimic the interactions between "species-specific" mammary microenvironment of human origin and human breast cancer cells. However, detailed evidences are absent. The present study (in vivo, cellular, and molecular experiments) was designed to explore the regulatory role of human mammary microenvironment in the progress of human breast cancer cells. Subcutaneous (SUB), mammary fat pad (MFP), and HB mouse models were developed for in vivo comparisons. Then, the orthotopic tumor masses from three different mouse models were collected for primary culture. Finally, the biology of primary cultured human breast cancer cells was compared by cellular and molecular experiments. Results of in vivo mouse models indicated that human breast cancer cells grew better in human mammary microenvironment. Cellular and molecular experiments confirmed that primary cultured human breast cancer cells from HB mouse model showed a better proliferative and anti-apoptotic biology than those from SUB to MFP mouse models. Meanwhile, primary cultured human breast cancer cells from HB mouse model also obtained the migratory and invasive biology for "species-specific" tissue metastasis to human tissues. Comprehensive analyses suggest that "species-specific" mammary microenvironment of human origin better regulates the biology of human breast cancer cells in our humanized mouse model of breast cancer, which is more consistent with the clinical progress of human breast cancer.

  10. A Compact Synchronous Cellular Model of Nonlinear Calcium Dynamics: Simulation and FPGA Synthesis Results.

    Science.gov (United States)

    Soleimani, Hamid; Drakakis, Emmanuel M

    2017-06-01

    Recent studies have demonstrated that calcium is a widespread intracellular ion that controls a wide range of temporal dynamics in the mammalian body. The simulation and validation of such studies using experimental data would benefit from a fast large scale simulation and modelling tool. This paper presents a compact and fully reconfigurable cellular calcium model capable of mimicking Hopf bifurcation phenomenon and various nonlinear responses of the biological calcium dynamics. The proposed cellular model is synthesized on a digital platform for a single unit and a network model. Hardware synthesis, physical implementation on FPGA, and theoretical analysis confirm that the proposed cellular model can mimic the biological calcium behaviors with considerably low hardware overhead. The approach has the potential to speed up large-scale simulations of slow intracellular dynamics by sharing more cellular units in real-time. To this end, various networks constructed by pipelining 10 k to 40 k cellular calcium units are compared with an equivalent simulation run on a standard PC workstation. Results show that the cellular hardware model is, on average, 83 times faster than the CPU version.

  11. Apc Restoration Promotes Cellular Differentiation and Reestablishes Crypt Homeostasis in Colorectal Cancer

    NARCIS (Netherlands)

    Dow, Lukas E; O'Rourke, Kevin P; Simon, Janelle; Tschaharganeh, Darjus F; van Es, Johan H; Clevers, Hans; Lowe, Scott W

    2015-01-01

    The adenomatous polyposis coli (APC) tumor suppressor is mutated in the vast majority of human colorectal cancers (CRC) and leads to deregulated Wnt signaling. To determine whether Apc disruption is required for tumor maintenance, we developed a mouse model of CRC whereby Apc can be conditionally

  12. Multi-Grid Model for Crowd’s Evacuation in Ships Based on Cellular Automata

    Directory of Open Access Journals (Sweden)

    Chen Miao

    2015-09-01

    Full Text Available In order to enhance the authenticity and accuracy simulation of passengers’ evacuation in ships, a new multi-grid model is proposed on the basis of cellular automata theory. By finer lattice the multi-grid model could enhance the continuity of passengers’ track and the precision of boundary’s qualification compared with traditional cellular automata model. Attraction, repulsion and friction are also quantized in the multi-grid model to present the impact of interaction force among pedestrians. Furthermore, crowd’s evacuation simulated by traditional cellular automata and multi-grid model in single exit room and typical cabin environment have been taken as examples to analyze crowd’s motion laws. It is found that the laws of passengers’ evacuation simulated by the two models are similar, and the simulation authenticity and accuracy is enhanced by the multi-grid model.

  13. Three-dimensional tissue culture models in cancer biology.

    Science.gov (United States)

    Kim, Jong Bin

    2005-10-01

    Three-dimensional (3D) tissue culture models have an invaluable role in tumour biology today providing some very important insights into cancer biology. As well as increasing our understanding of homeostasis, cellular differentiation and tissue organization they provide a well defined environment for cancer research in contrast to the complex host environment of an in vivo model. Due to their enormous potential 3D tumour cultures are currently being exploited by many branches of biomedical science with therapeutically orientated studies becoming the major focus of research. Recent advances in 3D culture and tissue engineering techniques have enabled the development of more complex heterologous 3D tumour models.

  14. Logical Modeling and Dynamical Analysis of Cellular Networks.

    Science.gov (United States)

    Abou-Jaoudé, Wassim; Traynard, Pauline; Monteiro, Pedro T; Saez-Rodriguez, Julio; Helikar, Tomáš; Thieffry, Denis; Chaouiya, Claudine

    2016-01-01

    The logical (or logic) formalism is increasingly used to model regulatory and signaling networks. Complementing these applications, several groups contributed various methods and tools to support the definition and analysis of logical models. After an introduction to the logical modeling framework and to several of its variants, we review here a number of recent methodological advances to ease the analysis of large and intricate networks. In particular, we survey approaches to determine model attractors and their reachability properties, to assess the dynamical impact of variations of external signals, and to consistently reduce large models. To illustrate these developments, we further consider several published logical models for two important biological processes, namely the differentiation of T helper cells and the control of mammalian cell cycle.

  15. Modeling Human Cancers in Drosophila.

    Science.gov (United States)

    Sonoshita, M; Cagan, R L

    2017-01-01

    Cancer is a complex disease that affects multiple organs. Whole-body animal models provide important insights into oncology that can lead to clinical impact. Here, we review novel concepts that Drosophila studies have established for cancer biology, drug discovery, and patient therapy. Genetic studies using Drosophila have explored the roles of oncogenes and tumor-suppressor genes that when dysregulated promote cancer formation, making Drosophila a useful model to study multiple aspects of transformation. Not limited to mechanism analyses, Drosophila has recently been showing its value in facilitating drug development. Flies offer rapid, efficient platforms by which novel classes of drugs can be identified as candidate anticancer leads. Further, we discuss the use of Drosophila as a platform to develop therapies for individual patients by modeling the tumor's genetic complexity. Drosophila provides both a classical and a novel tool to identify new therapeutics, complementing other more traditional cancer tools. © 2017 Elsevier Inc. All rights reserved.

  16. Breast cancer cellular proliferation indexes and 99mTc-sesta Mibi capture: what correlation?

    Science.gov (United States)

    Bonazzi, G; Cistaro, A; Bellò, M; Bessone, M; Tetti, M; Villata, E; Coluccia, C; Ardine, M; Moz, G; Massaioli, N; Bisi, G

    2001-03-01

    Aim of this study was to verify existing correlations between breast cancer 99mTc-sestaMIBI cells uptake and their cytological characteristics. Forty-five patients with clinically and/or mammographically suspect breast cancer were enrolled. In all patients 99mTc-sestaMIBI scintimammography was performed and malignant lesions were detected in 44 cases and benign in one case. In positive uptake (PU) lesions with diameter <1.5cm, 85.7% showed a high tumor grade (II-III degrees) while in negative uptake (NU) lesions with diameter <1.5cm, 100% showed a low tumor grade (I degrees). In PU lesions, 70% had expressed a high value of Ki 67, while 100% of the NU lesions showed normal values. In this series, tumor diameter does not play a basic role, while the correlations between uptake and the histological grade (G) and/or cellular kinetics (Ki67) seem to be more important. Further studies are needed to confirm our present results.

  17. Changes in cellular mechanical properties during onset or progression of colorectal cancer

    Science.gov (United States)

    Ciasca, Gabriele; Papi, Massimiliano; Minelli, Eleonora; Palmieri, Valentina; De Spirito, Marco

    2016-01-01

    Colorectal cancer (CRC) development represents a multistep process starting with specific mutations that affect proto-oncogenes and tumour suppressor genes. These mutations confer a selective growth advantage to colonic epithelial cells that form first dysplastic crypts, and then malignant tumours and metastases. All these steps are accompanied by deep mechanical changes at the cellular and the tissue level. A growing consensus is emerging that such modifications are not merely a by-product of the malignant progression, but they could play a relevant role in the cancer onset and accelerate its progression. In this review, we focus on recent studies investigating the role of the biomechanical signals in the initiation and the development of CRC. We show that mechanical cues might contribute to early phases of the tumour initiation by controlling the Wnt pathway, one of most important regulators of cell proliferation in various systems. We highlight how physical stimuli may be involved in the differentiation of non-invasive cells into metastatic variants and how metastatic cells modify their mechanical properties, both stiffness and adhesion, to survive the mechanical stress associated with intravasation, circulation and extravasation. A deep comprehension of these mechanical modifications may help scientist to define novel molecular targets for the cure of CRC. PMID:27621568

  18. Cellular cardiac electrophysiology modeling with Chaste and CellML

    Science.gov (United States)

    Cooper, Jonathan; Spiteri, Raymond J.; Mirams, Gary R.

    2014-01-01

    Chaste is an open-source C++ library for computational biology that has well-developed cardiac electrophysiology tissue simulation support. In this paper, we introduce the features available for performing cardiac electrophysiology action potential simulations using a wide range of models from the Physiome repository. The mathematics of the models are described in CellML, with units for all quantities. The primary idea is that the model is defined in one place (the CellML file), and all model code is auto-generated at compile or run time; it never has to be manually edited. We use ontological annotation to identify model variables describing certain biological quantities (membrane voltage, capacitance, etc.) to allow us to import any relevant CellML models into the Chaste framework in consistent units and to interact with them via consistent interfaces. This approach provides a great deal of flexibility for analysing different models of the same system. Chaste provides a wide choice of numerical methods for solving the ordinary differential equations that describe the models. Fixed-timestep explicit and implicit solvers are provided, as discussed in previous work. Here we introduce the Rush–Larsen and Generalized Rush–Larsen integration techniques, made available via symbolic manipulation of the model equations, which are automatically rearranged into the forms required by these approaches. We have also integrated the CVODE solvers, a ‘gold standard’ for stiff systems, and we have developed support for symbolic computation of the Jacobian matrix, yielding further increases in the performance and accuracy of CVODE. We discuss some of the technical details of this work and compare the performance of the available numerical methods. Finally, we discuss how this is generalized in our functional curation framework, which uses a domain-specific language for defining complex experiments as a basis for comparison of model behavior. PMID:25610400

  19. Fisetin inhibits cellular proliferation and induces mitochondria-dependent apoptosis in human gastric cancer cells.

    Science.gov (United States)

    Sabarwal, Akash; Agarwal, Rajesh; Singh, Rana P

    2017-02-01

    The anticancer effects of fisetin, a dietary agent, are largely unknown against human gastric cancer. Herein, we investigated the mechanisms of fisetin-induced inhibition of growth and survival of human gastric carcinoma AGS and SNU-1 cells. Fisetin (25-100 μM) caused significant decrease in the levels of G1 phase cyclins and CDKs, and increased the levels of p53 and its S15 phosphorylation in gastric cancer cells. We also observed that growth suppression and death of non-neoplastic human intestinal FHs74int cells were minimally affected by fisetin. Fisetin strongly increased apoptotic cells and showed mitochondrial membrane depolarization in gastric cancer cells. DNA damage was observed as early as 3 h after fisetin treatment which was accompanied with gamma-H2A.X(S139) phosphorylation and cleavage of PARP. Fisetin-induced apoptosis was observed to be independent of p53. DCFDA and MitoSOX analyses showed an increase in mitochondrial ROS generation in time- and dose-dependent fashion. It also increased cellular nitrite and superoxide generation. Pre-treatment with N-acetyl cysteine (NAC) inhibited ROS generation and also caused protection from fisetin-induced DNA damage. The formation of comets were observed in only fisetin treated cells which was blocked by NAC pre-treatment. Further investigation of the source of ROS, using mitochondrial respiratory chain (MRC) complex inhibitors, suggested that fisetin caused ROS generation specifically through complex I. Collectively, these results for the first time demonstrated that fisetin possesses anticancer potential through ROS production most likely via MRC complex I leading to apoptosis in human gastric carcinoma cells. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  20. Sipuleucel-T: Autologous Cellular Immunotherapy for Men with Asymptomatic or Minimally Symptomatic Metastatic Castrate Resistant Prostate Cancer

    Directory of Open Access Journals (Sweden)

    Robert B. Sims

    2011-01-01

    Full Text Available Sipuleucel T is an autologous cellular immunotherapy designed to stimulate an immune response in men diagnosed with asymptomatic or minimally symptomatic metastatic castrate resistant (hormone refractory prostate cancer. Sipuleucel T improves overall survival and provides an additional treatment option for this patient population.

  1. Animal models for cancer cachexia.

    Science.gov (United States)

    Ballarò, Riccardo; Costelli, Paola; Penna, Fabio

    2016-12-01

    Cancer cachexia is a frequent syndrome that affects patient quality of life, anticancer treatment effectiveness, and overall survival. The lack of anticancer cachexia therapies likely relies on the complexity of the syndrome that renders difficult to design appropriate clinical trials and, conversely, on the insufficient knowledge of the underlying pathogenetic mechanisms. The aim of this review is to collect the most relevant latest information regarding cancer cachexia with a special focus on the experimental systems adopted for modeling the disease in translational studies. The scenario of preclinical models for the study of cancer cachexia is not static and is rapidly evolving in parallel with new prospective treatment options. The well established syngeneic models using rodent cancer cells injected ectopically are now used alongside new ones featuring orthotopic injection, human cancer cell or patient-derived xenograft, or spontaneous tumors in genetically engineered mice. The use of more complex animal models that better resemble cancer cachexia, ideally including also the administration of chemotherapy, will expand the understanding of the underlying mechanisms and will allow a more reliable evaluation of prospective drugs for translational purposes.

  2. Stochastic Geometric Coverage Analysis in mmWave Cellular Networks with a Realistic Channel Model

    DEFF Research Database (Denmark)

    Rebato, Mattia; Park, Jihong; Popovski, Petar

    2017-01-01

    Millimeter-wave (mmWave) bands have been attracting growing attention as a possible candidate for next-generation cellular networks, since the available spectrum is orders of magnitude larger than in current cellular allocations. To precisely design mmWave systems, it is important to examine mmWave...... interference and SIR coverage under large-scale deployments. For this purpose, we apply an accurate mmWave channel model, derived from experiments, into an analytical framework based on stochastic geometry. In this way we obtain a closed-form SIR coverage probability in large-scale mmWave cellular networks....

  3. Modelling of photo-thermal control of biological cellular oscillators.

    Science.gov (United States)

    Assanov, Gani S; Zhanabaev, Zeinulla Zh; Govorov, Alexander O; Neiman, Alexander B

    2013-10-01

    We study the transient dynamics of biological oscillators subjected to brief heat pulses. A prospective well-defined experimental system for thermal control of oscillators is the peripheral electroreceptors in paddlefish. Epithelial cells in these receptors show spontaneous voltage oscillations which are known to be temperature sensitive. We use a computational model to predict the effect of brief thermal pulses in this system. In our model thermal stimulation is realized through the light excitation of gold nanoparticles delivered in close proximity to epithelial cells and generating heat due to plasmon resonance. We use an ensemble of modified Morris-Lecar systems to model oscillatory epithelial cells. First, we validate that the model quantitatively reproduces the dynamics of epithelial oscillations in paddlefish electroreceptors, including responses to static and slow temperature changes. Second, we use the model to predict transient responses to short heat pulses generated by the light actuated gold nanoparticles. The model predicts that the epithelial oscillators can be partially synchronized by brief 5 - 15 ms light stimuli resulting in a large-amplitude oscillations of the mean field potential.

  4. Dynamical modeling and analysis of large cellular regulatory networks

    Science.gov (United States)

    Bérenguier, D.; Chaouiya, C.; Monteiro, P. T.; Naldi, A.; Remy, E.; Thieffry, D.; Tichit, L.

    2013-06-01

    The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.

  5. Dynamical modeling and analysis of large cellular regulatory networks.

    Science.gov (United States)

    Bérenguier, D; Chaouiya, C; Monteiro, P T; Naldi, A; Remy, E; Thieffry, D; Tichit, L

    2013-06-01

    The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.

  6. Spatiotemporal Stochastic Modeling of IoT Enabled Cellular Networks: Scalability and Stability Analysis

    KAUST Repository

    Gharbieh, Mohammad

    2017-05-02

    The Internet of Things (IoT) is large-scale by nature, which is manifested by the massive number of connected devices as well as their vast spatial existence. Cellular networks, which provide ubiquitous, reliable, and efficient wireless access, will play fundamental rule in delivering the first-mile access for the data tsunami to be generated by the IoT. However, cellular networks may have scalability problems to provide uplink connectivity to massive numbers of connected things. To characterize the scalability of cellular uplink in the context of IoT networks, this paper develops a traffic-aware spatiotemporal mathematical model for IoT devices supported by cellular uplink connectivity. The developed model is based on stochastic geometry and queueing theory to account for the traffic requirement per IoT device, the different transmission strategies, and the mutual interference between the IoT devices. To this end, the developed model is utilized to characterize the extent to which cellular networks can accommodate IoT traffic as well as to assess and compare three different transmission strategies that incorporate a combination of transmission persistency, backoff, and power-ramping. The analysis and the results clearly illustrate the scalability problem imposed by IoT on cellular network and offer insights into effective scenarios for each transmission strategy.

  7. A cellular automaton model for the rise of magma

    Science.gov (United States)

    Piegari, Ester; di Maio, Rosa; Milano, Leopoldo; Scandone, Roberto

    2010-05-01

    Eruptions of volcanoes are complex natural events highly variable in size and time. Over the last couple of decades, statistical analyses of erupted volume and repose time catalogues have been performed for a large number of volcanoes. The aim of such analyses is either to predict future eruptive events or to define physical models for improving our understanding of the volcanic processes that cause eruptions. In particular, for this latter purpose we study a statistical model of eruption triggering caused by the fracturing of the crust above a magma reservoir residing in the crust. When the fracturing reaches the reservoir, magma is allowed to ascend because of its buoyancy. It will be found in batches along the transport region and it will ascend as long as fractures are developed to its tip; when a path is opened to the surface, an eruption occurs involving all batches connected to the opening. We model the vertical section of a volcanic edifice by means of a two-dimensional grid and characterize the state of each cell of the grid by assigning the values of two dynamical variables: a time dependent variable e describing the status of the local stress and a time-dependent variable n describing the presence of magma. At first step of approximation, we treat the magma presence field n as a diffusing lattice gas, and, therefore, we assume its value to be either zero or one if the corresponding cell is empty or filled by magma, respectively. We study the probability distribution, P(V), of eruptions of volume V and the probability distribution, P(t), of inter-event time t and find that the model is able to reproduce, at least in a descriptive way, the essential statistical features of the activity of volcanoes. A key component of magma is the quantity of dissolved gas as it gives magma its explosive character, because the volume of gas expands as the pressure decreases on raising towards the surface. Then, to more accurately describe the rise of magma in a volcanic

  8. A quantitative model of cellular elasticity based on tensegrity.

    Science.gov (United States)

    Stamenović, D; Coughlin, M F

    2000-02-01

    A tensegrity structure composed of six struts interconnected with 24 elastic cables is used as a quantitative model of the steady-state elastic response of cells, with the struts and cables representing microtubules and actin filaments, respectively. The model is stretched uniaxially and the Young's modulus (E0) is obtained from the initial slope of the stress versus strain curve of an equivalent continuum. It is found that E0 is directly proportional to the pre-existing tension in the cables (or compression in the struts) and inversely proportional to the cable (or strut) length square. This relationship is used to predict the upper and lower bounds of E0 of cells, assuming that the cable tension equals the yield force of actin (approximately 400 pN) for the upper bound, and that the strut compression equals the critical buckling force of microtubules for the lower bound. The cable (or strut) length is determined from the assumption that model dimensions match the diameter of probes used in standard mechanical tests on cells. Predicted values are compared to reported data for the Young's modulus of various cells. If the probe diameter is greater than or equal to 3 microns, these data are closer to the lower bound than to the upper bound. This, in turn, suggests that microtubules of the CSK carry initial compression that exceeds their critical buckling force (order of 10(0)-10(1) pN), but is much smaller than the yield force of actin. If the probe diameter is less than or equal to 2 microns, experimental data fall outside the region defined by the upper and lower bounds.

  9. Stochastic Model of Maturation and Vesicular Exchange in Cellular Organelles

    CERN Document Server

    Vagne, Quentin

    2016-01-01

    The dynamical organization of membrane-bound organelles along intracellular transport pathways relies on vesicular exchange between organelles and on biochemical maturation of the organelle content by specific enzymes. The relative importance of each mechanism in controlling organelle dynamics remains controversial, in particular for transport through the Golgi apparatus. Using a stochastic model, we show that full maturation of membrane-bound compartments can be seen as the stochastic escape from a steady-state in which export is dominated by vesicular exchange. We show that full maturation can contribute a significant fraction of the total out-flux for small organelles such as endosomes and Golgi cisternae.

  10. A preliminary comparison of dendritic cell maturation by total cellular RNA to total cellular lysate derived from breast cancer stem cells

    Directory of Open Access Journals (Sweden)

    Phong Minh Le

    2016-06-01

    Full Text Available Introduction: Dendritic cells (DCs have been widely considered as the most potent antigen-presenting cells. As such, DC-based vaccines are regarded as a promising strategy in cancer vaccination and therapy. This study compared the maturation of DCs induced by total cellular RNA and cell lysate (i.e. nucleic acid and protein. Methods: Both total RNA and cell lysate were isolated from breast cancer stem cells (BCSCs. The lysates were used to incubate with monocyte-derived immature DCs. To track the transfection efficiency, the BCSCs were stably transfected with green fluorescent protein (GFP. The maturation of DCs was evaluated by expression of costimulatory molecules including CD40, CD80, and CD86. Transfections were confirmed by evaluating GFP expression in DCs at 24 hours post transfection. Results: The results of this study showed that GFP is expressed in DCs after both total RNA and lysate incubation. The expression of costimulatory molecules (CD40, CD80, and CD86 was significantly higher in RNA-transfected DCs than in cell lysate-primed DCs. Conclusion: Our findings suggest that total RNA primed BCSCs can be a suitable platform for DC-based vaccine therapy of breast cancer. [Biomed Res Ther 2016; 3(6.000: 679-686

  11. Equal Distribution Model of Epidemic Drugs Based on a Cellular Automata Model

    Directory of Open Access Journals (Sweden)

    Huang Xinyi

    2015-01-01

    Full Text Available The epidemic spreading of infectious disease is a process of evolution over time. Based on the cellular automata model[1], this paper analyzes the epidemic spreading rules, and establishes an efficient equal distribution model of drugs in a broad sense. For multiple regions, in case of demand of drugs exceeding supply, the drugs shall be distributed according to the proportion of a total number of people in each region, the number of patients, the number of the isolated, and the number of deaths. It is necessary to simulate based on these four schemes to obtain simulation results. The results show that, when the drugs are distributed by the proportion of the number of deaths, it is optimal for controlling over epidemic situations.

  12. Genomic instability and cellular stress in organ biopsies and peripheral blood lymphocytes from patients with colorectal cancer and predisposing pathologies

    Science.gov (United States)

    Lombardi, Sara; Fuoco, Ilenia; di Fluri, Giorgia; Costa, Francesco; Ricchiuti, Angelo; Biondi, Graziano; Nardini, Vincenzo; Scarpato, Roberto

    2015-01-01

    Inflammatory bowel disease (IBD) and polyps, are common colorectal pathologies in western society and are risk factors for development of colorectal cancer (CRC). Genomic instability is a cancer hallmark and is connected to changes in chromosomal structure, often caused by double strand break formation (DSB), and aneuploidy. Cellular stress, may contribute to genomic instability. In colorectal biopsies and peripheral blood lymphocytes of patients with IBD, polyps and CRC, we evaluated 1) genomic instability using the γH2AX assay as marker of DSB and micronuclei in mononuclear lymphocytes kept under cytodieresis inhibition, and 2) cellular stress through expression and cellular localization of glutathione-S-transferase omega 1 (GSTO1). Colon biopsies showed γH2AX increase starting from polyps, while lymphocytes already from IBD. Micronuclei frequency began to rise in lymphocytes of subjects with polyps, suggesting a systemic genomic instability condition. Colorectal tissues lost GSTO1 expression but increased nuclear localization with pathology progression. Lymphocytes did not change GSTO1 expression and localization until CRC formation, where enzyme expression was increased. We propose that the growing genomic instability found in our patients is connected with the alteration of cellular environment. Evaluation of genomic damage and cellular stress in colorectal pathologies may facilitate prevention and management of CRC. PMID:26046795

  13. Downregulation of the non-integrin laminin receptor reduces cellular viability by inducing apoptosis in lung and cervical cancer cells.

    Directory of Open Access Journals (Sweden)

    Kiashanee Moodley

    Full Text Available The non-integrin laminin receptor, here designated the 37-kDa/67-kDa laminin receptor (LRP/LR, is involved in many physiologically relevant processes, as well as numerous pathological conditions. The overexpression of LRP/LR on various cancerous cell lines plays critical roles in tumour metastasis and angiogenesis. This study investigated whether LRP/LR is implicated in the maintenance of cellular viability in lung and cervical cancer cell lines. Here we show a significant reduction in cellular viability in the aforementioned cell lines as a result of the siRNA-mediated downregulation of LRP. This reduction in cellular viability is due to increased apoptotic processes, reflected by the loss of nuclear integrity and the significant increase in the activity of caspase-3. These results indicate that LRP/LR is involved in the maintenance of cellular viability in tumorigenic lung and cervix uteri cells through the blockage of apoptosis. Knockdown of LRP/LR by siRNA might represent an alternative therapeutic strategy for the treatment of lung and cervical cancer.

  14. Role of Crk Adaptor Proteins in Cellular Migration and Invasion in Human Breast Cancer

    National Research Council Canada - National Science Library

    Fathers, Kelly E

    2007-01-01

    The Crk adaptor proteins (CrkI, CrkII and CrkL) play an important role during cellular signalling by mediating the formation of protein-protein complexes and are involved in cellular migration, invasion, and adhesion...

  15. Role of Crk Adaptor Proteins in Cellular Migration and Invasion in Human Breast Cancer

    National Research Council Canada - National Science Library

    Fathers, Kelly E

    2008-01-01

    The Crk adaptor proteins (CrkI, CrkII and CrkL) play an important role during cellular signalling by mediating the formation of protein-protein complexes and are involved in cellular migration, invasion, and adhesion...

  16. Evaluating the Progenitor Cells of Ovarian Cancer: Analysis of Current Animal Models

    OpenAIRE

    King, Shelby M.; Burdette, Joanna E.

    2011-01-01

    Serous ovarian cancer is one of the most lethal gynecological malignancies. Progress on effective diagnostics and therapeutics for this disease are hampered by ambiguity as to the cellular origins of this histotype of ovarian cancer, as well as limited suitable animal models to analyze early stages of disease. In this report, we will review current animal models with respect to the two proposed progenitor cells for serous ovarian cancer, the ovarian surface epithelium and the fallopian tube e...

  17. Cytotoxicity and cellular uptake of different sized gold nanoparticles in ovarian cancer cells

    Science.gov (United States)

    Kumar, Dhiraj; Mutreja, Isha; Chitcholtan, Kenny; Sykes, Peter

    2017-11-01

    Nanomedicine has advanced the biomedical field with the availability of multifunctional nanoparticles (NPs) systems that can target a disease site enabling drug delivery and helping to monitor the disease. In this paper, we synthesised the gold nanoparticles (AuNPs) with an average size 18, 40, 60 and 80 nm, and studied the effect of nanoparticles size, concentration and incubation time on ovarian cancer cells namely, OVCAR5, OVCAR8, and SKOV3. The size measured by transmission electron microscopy images was slightly smaller than the hydrodynamic diameter; measured size by ImageJ as 14.55, 38.13, 56.88 and 78.56 nm. The cellular uptake was significantly controlled by the AuNPs size, concentration, and the cell type. The nanoparticles uptake increased with increasing concentration, and 18 and 80 nm AuNPs showed higher uptake ranging from 1.3 to 5.4 μg depending upon the concentration and cell type. The AuNPs were associated with a temporary reduction in metabolic activity, but metabolic activity remained more than 60% for all sample types; NPs significantly affected the cell proliferation activity in first 12 h. The increase in nanoparticle size and concentration induced the production of reactive oxygen species in 24 h.

  18. Reverse engineering cellular decisions for hybrid reconfigurable network modeling

    Science.gov (United States)

    Blair, Howard A.; Saranak, Jureepan; Foster, Kenneth W.

    2011-06-01

    Cells as microorganisms and within multicellular organisms make robust decisions. Knowing how these complex cells make decisions is essential to explain, predict or mimic their behavior. The discovery of multi-layer multiple feedback loops in the signaling pathways of these modular hybrid systems suggests their decision making is sophisticated. Hybrid systems coordinate and integrate signals of various kinds: discrete on/off signals, continuous sensory signals, and stochastic and continuous fluctuations to regulate chemical concentrations. Such signaling networks can form reconfigurable networks of attractors and repellors giving them an extra level of organization that has resilient decision making built in. Work on generic attractor and repellor networks and on the already identified feedback networks and dynamic reconfigurable regulatory topologies in biological cells suggests that biological systems probably exploit such dynamic capabilities. We present a simple behavior of the swimming unicellular alga Chlamydomonas that involves interdependent discrete and continuous signals in feedback loops. We show how to rigorously verify a hybrid dynamical model of a biological system with respect to a declarative description of a cell's behavior. The hybrid dynamical systems we use are based on a unification of discrete structures and continuous topologies developed in prior work on convergence spaces. They involve variables of discrete and continuous types, in the sense of type theory in mathematical logic. A unification such as afforded by convergence spaces is necessary if one wants to take account of the affect of the structural relationships within each type on the dynamics of the system.

  19. Network modeling links breast cancer susceptibility and centrosome dysfunction.

    Science.gov (United States)

    Pujana, Miguel Angel; Han, Jing-Dong J; Starita, Lea M; Stevens, Kristen N; Tewari, Muneesh; Ahn, Jin Sook; Rennert, Gad; Moreno, Víctor; Kirchhoff, Tomas; Gold, Bert; Assmann, Volker; Elshamy, Wael M; Rual, Jean-François; Levine, Douglas; Rozek, Laura S; Gelman, Rebecca S; Gunsalus, Kristin C; Greenberg, Roger A; Sobhian, Bijan; Bertin, Nicolas; Venkatesan, Kavitha; Ayivi-Guedehoussou, Nono; Solé, Xavier; Hernández, Pilar; Lázaro, Conxi; Nathanson, Katherine L; Weber, Barbara L; Cusick, Michael E; Hill, David E; Offit, Kenneth; Livingston, David M; Gruber, Stephen B; Parvin, Jeffrey D; Vidal, Marc

    2007-11-01

    Many cancer-associated genes remain to be identified to clarify the underlying molecular mechanisms of cancer susceptibility and progression. Better understanding is also required of how mutations in cancer genes affect their products in the context of complex cellular networks. Here we have used a network modeling strategy to identify genes potentially associated with higher risk of breast cancer. Starting with four known genes encoding tumor suppressors of breast cancer, we combined gene expression profiling with functional genomic and proteomic (or 'omic') data from various species to generate a network containing 118 genes linked by 866 potential functional associations. This network shows higher connectivity than expected by chance, suggesting that its components function in biologically related pathways. One of the components of the network is HMMR, encoding a centrosome subunit, for which we demonstrate previously unknown functional associations with the breast cancer-associated gene BRCA1. Two case-control studies of incident breast cancer indicate that the HMMR locus is associated with higher risk of breast cancer in humans. Our network modeling strategy should be useful for the discovery of additional cancer-associated genes.

  20. Tools and Models for Integrating Multiple Cellular Networks

    Energy Technology Data Exchange (ETDEWEB)

    Gerstein, Mark [Yale Univ., New Haven, CT (United States). Gerstein Lab.

    2015-11-06

    CRIT for correlation analysis in systems biology [5]. For Aim 3, we have further investigated the scaling relationship that the number of Transcription Factors (TFs) in a genome is proportional to the square of the total number of genes. We have extended the analysis from transcription factors to various classes of functional categories, and from individual categories to joint distribution [6]. By introducing a new analytical framework, we have generalized the original toolbox model to take into account of metabolic network with arbitrary network topology [7].

  1. Cancer systems biology and modeling: microscopic scale and multiscale approaches.

    Science.gov (United States)

    Masoudi-Nejad, Ali; Bidkhori, Gholamreza; Hosseini Ashtiani, Saman; Najafi, Ali; Bozorgmehr, Joseph H; Wang, Edwin

    2015-02-01

    Cancer has become known as a complex and systematic disease on macroscopic, mesoscopic and microscopic scales. Systems biology employs state-of-the-art computational theories and high-throughput experimental data to model and simulate complex biological procedures such as cancer, which involves genetic and epigenetic, in addition to intracellular and extracellular complex interaction networks. In this paper, different systems biology modeling techniques such as systems of differential equations, stochastic methods, Boolean networks, Petri nets, cellular automata methods and agent-based systems are concisely discussed. We have compared the mentioned formalisms and tried to address the span of applicability they can bear on emerging cancer modeling and simulation approaches. Different scales of cancer modeling, namely, microscopic, mesoscopic and macroscopic scales are explained followed by an illustration of angiogenesis in microscopic scale of the cancer modeling. Then, the modeling of cancer cell proliferation and survival are examined on a microscopic scale and the modeling of multiscale tumor growth is explained along with its advantages. Copyright © 2014 Elsevier Ltd. All rights reserved.

  2. Murine model of hepatic breast cancer.

    Science.gov (United States)

    Rikhi, Rishi; Wilson, Elizabeth M; Deas, Olivier; Svalina, Matthew N; Bial, John; Mansoor, Atiya; Cairo, Stefano; Keller, Charles

    2016-12-01

    Breast cancer is the most common cancer in women and the second leading cause of cancer-related deaths in this population. Breast cancer related deaths have declined due to screening and adjuvant therapies, yet a driving clinical need exists to better understand the cause of the deadliest aspect of breast cancer, metastatic disease. Breast cancer metastasizes to several distant organs, the liver being the third most common site. To date, very few murine models of hepatic breast cancer exist. In this study, a novel murine model of liver breast cancer using the MDA-MB-231 cell line is introduced as an experimental (preclinical) model. Histological typing revealed consistent hepatic breast cancer tumor foci. Common features of the murine model were vascular invasion, lung metastasis and peritoneal seeding. The novel murine model of hepatic breast cancer established in this study provides a tool to be used to investigate mechanisms of hepatic metastasis and to test potential therapeutic interventions.

  3. Kinetic theory approach to modeling of cellular repair mechanisms under genome stress.

    Directory of Open Access Journals (Sweden)

    Jinpeng Qi

    Full Text Available Under acute perturbations from outer environment, a normal cell can trigger cellular self-defense mechanism in response to genome stress. To investigate the kinetics of cellular self-repair process at single cell level further, a model of DNA damage generating and repair is proposed under acute Ion Radiation (IR by using mathematical framework of kinetic theory of active particles (KTAP. Firstly, we focus on illustrating the profile of Cellular Repair System (CRS instituted by two sub-populations, each of which is made up of the active particles with different discrete states. Then, we implement the mathematical framework of cellular self-repair mechanism, and illustrate the dynamic processes of Double Strand Breaks (DSBs and Repair Protein (RP generating, DSB-protein complexes (DSBCs synthesizing, and toxins accumulating. Finally, we roughly analyze the capability of cellular self-repair mechanism, cellular activity of transferring DNA damage, and genome stability, especially the different fates of a certain cell before and after the time thresholds of IR perturbations that a cell can tolerate maximally under different IR perturbation circumstances.

  4. GIM3E: condition-specific models of cellular metabolism developed from metabolomics and expression data.

    Science.gov (United States)

    Schmidt, Brian J; Ebrahim, Ali; Metz, Thomas O; Adkins, Joshua N; Palsson, Bernhard Ø; Hyduke, Daniel R

    2013-11-15

    Genome-scale metabolic models have been used extensively to investigate alterations in cellular metabolism. The accuracy of these models to represent cellular metabolism in specific conditions has been improved by constraining the model with omics data sources. However, few practical methods for integrating metabolomics data with other omics data sources into genome-scale models of metabolism have been developed. GIM(3)E (Gene Inactivation Moderated by Metabolism, Metabolomics and Expression) is an algorithm that enables the development of condition-specific models based on an objective function, transcriptomics and cellular metabolomics data. GIM(3)E establishes metabolite use requirements with metabolomics data, uses model-paired transcriptomics data to find experimentally supported solutions and provides calculations of the turnover (production/consumption) flux of metabolites. GIM(3)E was used to investigate the effects of integrating additional omics datasets to create increasingly constrained solution spaces of Salmonella Typhimurium metabolism during growth in both rich and virulence media. This integration proved to be informative and resulted in a requirement of additional active reactions (12 in each case) or metabolites (26 or 29, respectively). The addition of constraints from transcriptomics also impacted the allowed solution space, and the cellular metabolites with turnover fluxes that were necessarily altered by the change in conditions increased from 118 to 271 of 1397. GIM(3)E has been implemented in Python and requires a COBRApy 0.2.x. The algorithm and sample data described here are freely available at: http://opencobra.sourceforge.net/ brianjamesschmidt@gmail.com

  5. CSE1L/CAS, the cellular apoptosis susceptibility protein, enhances invasion and metastasis but not proliferation of cancer cells

    Directory of Open Access Journals (Sweden)

    Chen Ying-Chun

    2008-07-01

    Full Text Available Abstract Background The cellular apoptosis susceptibility (CAS protein is regarded as a proliferation-associated protein that associates with tumour proliferation as it associates with microtubule and functions in the mitotic spindle checkpoint. However, there is no any actual experimental study showing CAS (or CSE1 and CSE1L can increase the proliferation of cancer cells. Previous pathological study has reported that CAS was strongly positive stained in all of the metastasis melanoma that be examined. Thus, CAS may regulate the invasion and metastasis of cancers. CAS is highly expressed in cancers; if CAS is associated with cancer proliferation, then increased CAS expression should be able to increase the proliferation of cancer cells. We studied whether increased CAS expression can increase cancer cell proliferation and whether CAS regulates the invasion of cancer cells. Methods We enhanced or reduced CAS expression by transfecting CAS or anti-CAS expression vectors into human MCF-7 breast cancer cells. The proliferations of cells were determined by trypan blue exclusion assay and flow cytometry analysis. Invasion of cancer cells were determined by matrigel-based invasion assay. Results Our studies showed that increased CAS expression was unable to enhance cancer cell proliferation. Immunofluorescence showed CAS was distributed in cytoplasm areas near cell membrane and cell protrusions. CAS was localized in cytoplasmic vesicle and immunogold electronmicroscopy showed CAS was located in vesicle membrane. CAS overexpression enhanced matrix metalloproteinase-2 (MMP-2 secretion and cancer cell invasion. Animal experiments showed CAS reduction inhibited the metastasis of B16-F10 melanoma cells by 56% in C57BL/6 mice. Conclusion Our results indicate that CAS increases the invasion but not the proliferation of cancer cells. Thus, CAS plus ECM-degradation proteinases may be used as the markers for predicting the advance of tumour metastasis.

  6. A Continuum Damage Mechanics Model for the Static and Cyclic Fatigue of Cellular Composites

    Science.gov (United States)

    Huber, Otto

    2017-01-01

    The fatigue behavior of a cellular composite with an epoxy matrix and glass foam granules is analyzed and modeled by means of continuum damage mechanics. The investigated cellular composite is a particular type of composite foam, and is very similar to syntactic foams. In contrast to conventional syntactic foams constituted by hollow spherical particles (balloons), cellular glass, mineral, or metal place holders are combined with the matrix material (metal or polymer) in the case of cellular composites. A microstructural investigation of the damage behavior is performed using scanning electron microscopy. For the modeling of the fatigue behavior, the damage is separated into pure static and pure cyclic damage and described in terms of the stiffness loss of the material using damage models for cyclic and creep damage. Both models incorporate nonlinear accumulation and interaction of damage. A cycle jumping procedure is developed, which allows for a fast and accurate calculation of the damage evolution for constant load frequencies. The damage model is applied to examine the mean stress effect for cyclic fatigue and to investigate the frequency effect and the influence of the signal form in the case of static and cyclic damage interaction. The calculated lifetimes are in very good agreement with experimental results. PMID:28809806

  7. Cellular automata and integrodifferential equation models for cell renewal in mosaic tissues

    Science.gov (United States)

    Bloomfield, J. M.; Sherratt, J. A.; Painter, K. J.; Landini, G.

    2010-01-01

    Mosaic tissues are composed of two or more genetically distinct cell types. They occur naturally, and are also a useful experimental method for exploring tissue growth and maintenance. By marking the different cell types, one can study the patterns formed by proliferation, renewal and migration. Here, we present mathematical modelling suggesting that small changes in the type of interaction that cells have with their local cellular environment can lead to very different outcomes for the composition of mosaics. In cell renewal, proliferation of each cell type may depend linearly or nonlinearly on the local proportion of cells of that type, and these two possibilities produce very different patterns. We study two variations of a cellular automaton model based on simple rules for renewal. We then propose an integrodifferential equation model, and again consider two different forms of cellular interaction. The results of the continuous and cellular automata models are qualitatively the same, and we observe that changes in local environment interaction affect the dynamics for both. Furthermore, we demonstrate that the models reproduce some of the patterns seen in actual mosaic tissues. In particular, our results suggest that the differing patterns seen in organ parenchymas may be driven purely by the process of cell replacement under different interaction scenarios. PMID:20375040

  8. A Cellular Automata-based Model for Simulating Restitution Property in a Single Heart Cell.

    Science.gov (United States)

    Sabzpoushan, Seyed Hojjat; Pourhasanzade, Fateme

    2011-01-01

    Ventricular fibrillation is the cause of the most sudden mortalities. Restitution is one of the specific properties of ventricular cell. The recent findings have clearly proved the correlation between the slope of restitution curve with ventricular fibrillation. This; therefore, mandates the modeling of cellular restitution to gain high importance. A cellular automaton is a powerful tool for simulating complex phenomena in a simple language. A cellular automaton is a lattice of cells where the behavior of each cell is determined by the behavior of its neighboring cells as well as the automata rule. In this paper, a simple model is depicted for the simulation of the property of restitution in a single cardiac cell using cellular automata. At first, two state variables; action potential and recovery are introduced in the automata model. In second, automata rule is determined and then recovery variable is defined in such a way so that the restitution is developed. In order to evaluate the proposed model, the generated restitution curve in our study is compared with the restitution curves from the experimental findings of valid sources. Our findings indicate that the presented model is not only capable of simulating restitution in cardiac cell, but also possesses the capability of regulating the restitution curve.

  9. Mathematical Modeling and Experimental Validation of Nanoemulsion-Based Drug Transport across Cellular Barriers.

    Science.gov (United States)

    Kadakia, Ekta; Shah, Lipa; Amiji, Mansoor M

    2017-07-01

    Nanoemulsions have shown potential in delivering drug across epithelial and endothelial cell barriers, which express efflux transporters. However, their transport mechanisms are not entirely understood. Our goal was to investigate the cellular permeability of nanoemulsion-encapsulated drugs and apply mathematical modeling to elucidate transport mechanisms and sensitive nanoemulsion attributes. Transport studies were performed in Caco-2 cells, using fish oil nanoemulsions and a model substrate, rhodamine-123. Permeability data was modeled using a semi-mechanistic approach, capturing the following cellular processes: endocytotic uptake of the nanoemulsion, release of rhodamine-123 from the nanoemulsion, efflux and passive permeability of rhodamine-123 in aqueous solution. Nanoemulsions not only improved the permeability of rhodamine-123, but were also less sensitive to efflux transporters. The model captured bidirectional permeability results and identified sensitive processes, such as the release of the nanoemulsion-encapsulated drug and cellular uptake of the nanoemulsion. Mathematical description of cellular processes, improved our understanding of transport mechanisms, such as nanoemulsions don't inhibit efflux to improve drug permeability. Instead, their endocytotic uptake, results in higher intracellular drug concentrations, thereby increasing the concentration gradient and transcellular permeability across biological barriers. Modeling results indicated optimizing nanoemulsion attributes like the droplet size and intracellular drug release rate, may further improve drug permeability.

  10. The integrin alphav beta3 increases cellular stiffness and cytoskeletal remodeling dynamics to facilitate cancer cell invasion

    Science.gov (United States)

    Mierke, Claudia Tanja

    2013-01-01

    The process of cancer cell invasion through the extracellular matrix (ECM) of connective tissue plays a prominent role in tumor progression and is based fundamentally on biomechanics. Cancer cell invasion usually requires cell adhesion to the ECM through the cell-matrix adhesion receptors integrins. The expression of the αvβ3 integrin is increased in several tumor types and is consistently associated with increased metastasis formation in patients. The hypothesis was that the αvβ3 integrin expression increases the invasiveness of cancer cells through increased cellular stiffness, and increased cytoskeletal remodeling dynamics. Here, the invasion of cancer cells with different αvβ3 integrin expression levels into dense three-dimensional (3D) ECMs has been studied. Using a cell sorter, two subcell lines expressing either high or low amounts of αvβ3 integrins (αvβ3high or αvβ3low cells, respectively) have been isolated from parental MDA-MB-231 breast cancer cells. αvβ3high cells showed a threefold increased cell invasion compared to αvβ3low cells. Similar results were obtained for A375 melanoma, 786-O kidney and T24 bladder carcinoma cells, and cells in which the β3 integrin subunit was knocked down using specific siRNA. To investigate whether contractile forces are essential for αvβ3 integrin-mediated increased cellular stiffness and subsequently enhanced cancer cell invasion, invasion assays were performed in the presence of myosin light chain kinase inhibitor ML-7 and Rho kinase inhibitor Y27632. Indeed, cancer cell invasiveness was reduced after addition of ML-7 and Y27632 in αvβ3high cells but not in αvβ3low cells. Moreover, after addition of the contractility enhancer calyculin A, an increase in pre-stress in αvβ3low cells was observed, which enhanced cellular invasiveness. In addition, inhibition of the Src kinase, STAT3 or Rac1 strongly reduced the invasiveness of αvβ3high cells, whereas the invasiveness of β3 specific knock

  11. a Predator-Prey Model Based on the Fully Parallel Cellular Automata

    Science.gov (United States)

    He, Mingfeng; Ruan, Hongbo; Yu, Changliang

    We presented a predator-prey lattice model containing moveable wolves and sheep, which are characterized by Penna double bit strings. Sexual reproduction and child-care strategies are considered. To implement this model in an efficient way, we build a fully parallel Cellular Automata based on a new definition of the neighborhood. We show the roles played by the initial densities of the populations, the mutation rate and the linear size of the lattice in the evolution of this model.

  12. A predator-prey model based on fully parallel cellular automata

    OpenAIRE

    He, Mingfeng; Ruan, Hongbo; Yu, Changliang

    2003-01-01

    We presented a predator-prey lattice model containing moveable wolves and sheep, which are characterized by Penna double bit strings. Sexual reproduction and child-care strategies are considered. To implement this model in an efficient way, we build a fully parallel Cellular Automata based on a new definition of the neighborhood. We show the roles played by the initial densities of the populations, the mutation rate and the linear size of the lattice in the evolution of this model.

  13. A Novel Cellular Senescence Gene, SENEX, Is Involved in Peripheral Regulatory T Cells Accumulation in Aged Urinary Bladder Cancer

    Science.gov (United States)

    Chen, Tianping; Wang, Huiping; Zhang, Zhiqiang; Li, Qing; Yan, Kaili; Tao, Qianshan; Ye, Qianling; Xiong, Shudao; Wang, Yiping; Zhai, Zhimin

    2014-01-01

    Regulatory T cells (Tregs) play an essential role in sustaining self-tolerance and immune homeostasis. Despite many studies on the correlation between Tregs accumulation and age, or malignancies, the related mechanism hasn’t been well explored. To find out the mechanism of Tregs accumulation in aged urinary bladder cancer, we examined the novel cellular senesence gene SENEX and relevant apoptosis gene mRNA expression in sorted CD4+CD25hi Tregs from aged UBC donors, evaluated serum cytokine profiles related to tumor immunopathology, and further explored the relationship between SENEX expression, apoptosis gene expression and cytokine secretion. After having silenced down SENEX gene expression with RNA interference, we also evaluated the cellular apoptosis of Tregs sorted from aged UBC patients in response to H2O2-mediated stress. Our data indicated that upregulated SENEX mRNA expression in Tregs of aged UBC patients was correlated with pro-apoptotic gene expression and cytokine concentration. Silencing SENEX gene expression increased cellular apoptosis and pro-apoptotic gene expression of Tregs, in response to H2O2-mediated stress. Upregulated SENEX mRNA expression together with decreased pro-apoptotic gene expression and disturbances in cytokines synthesis may contribute to the Tregs proliferation and promote tumorigenesis and metastasis. Overall, upregulation of cellular senescence gene SENEX, was associated to regulatory T cells accumulation in aged urinary bladder cancer. Our study provides a new insight into understanding of peripheral Tregs accumulation in aged malignancies. PMID:24505313

  14. Cellular Basis of Antiproliferative and Antitumor Activity of the Novel Camptothecin Derivative, Gimatecan, in Bladder Carcinoma Models

    Directory of Open Access Journals (Sweden)

    Paola Ulivi

    2005-02-01

    Full Text Available To investigate the cellular/molecular basis of the activity of a novel lipophilic camptothecin, gimatecan (ST1481, against slowly proliferating cells, we performed a comparative study of topotecan and gimatecan in human bladder cancer models (HT1376 and MCR. Gimatecan was significantly more effective than topotecan in inhibiting the growth of HT1376 tumor, thus reflecting anti proliferative potency. In both HT1376 and MCR cells, gimatecan caused a persistent S-phase arrest, indicating an efficient DNA damage checkpoint. This response was consistent with a cytostatic effect, because no evidence of apoptosis was detected. In contrast to gimatecan, topotecan at equitoxic concentrations caused an early and persistent downregulation of topoisomerase I. Modulation of protein level could not be solely ascribed to the proteasome-mediated degradation of the enzyme because the proteasome inhibitor PS341 sensitized MCR but not HT1376 cells to camptothecins, suggesting alternative mechanisms of drug-induced topoisomerase I downregulation. Indeed, the two camptothecins caused a differential inhibition of topoisomerase I transcription, which is more marked in topotecan-treated cells. The HT1376 model was more sensitive to this immediate decrease of mRNA level. Our data document a marked antitumor activity of gimatecan against a bladder carcinoma model. A limited downregulation of topoisomerase I by gimatecan provides additional insights into the cellular basis of drug potency.

  15. miR-300 regulates cellular radiosensitivity through targeting p53 and apaf1 in human lung cancer cells.

    Science.gov (United States)

    He, Jinpeng; Feng, Xiu; Hua, Junrui; Wei, Li; Lu, Zhiwei; Wei, Wenjun; Cai, Hui; Wang, Bing; Shi, Wengui; Ding, Nan; Li, He; Zhang, Yanan; Wang, Jufang

    2017-10-18

    microRNAs (miRNAs) play a crucial role in mediation of the cellular sensitivity to ionizing radiation (IR). Previous studies revealed that miR-300 was involved in the cellular response to IR or chemotherapy drug. However, whether miR-300 could regulate the DNA damage responses induced by extrinsic genotoxic stress in human lung cancer and the underlying mechanism remain unknown. In this study, the expression of miR-300 was examined in lung cancer cells treated with IR, and the effects of miR-300 on DNA damage repair, cell cycle arrest, apoptosis and senescence induced by IR were investigated. It was found that IR induced upregulation of endogenous miR-300, and ectopic expression of miR-300 by transfected with miR-300 mimics not only greatly enhanced the cellular DNA damage repair ability but also substantially abrogated the G2 cell cycle arrest and apoptosis induced by IR. Bioinformatic analysis predicted that p53 and apaf1 were potential targets of miR-300, and the luciferase reporter assay showed that miR-300 significantly suppressed the luciferase activity through binding to the 3'-UTR of p53 or apaf1 mRNA. In addition, overexpression of miR-300 significantly reduced p53/apaf1 and/or IR-induced p53/apaf1 protein expression levels. Flow cytomertry analysis and colony formation assay showed that miR-300 desensitized lung cancer cells to IR by suppressing p53-dependent G2 cell cycle arrest, apoptosis and senescence. These data demonstrate that miR-300 regulates the cellular sensitivity to IR through targeting p53 and apaf1 in lung cancer cells.

  16. 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

  17. CRISPR-Cas9: A Revolutionary Tool for Cancer Modelling

    Directory of Open Access Journals (Sweden)

    Raul Torres-Ruiz

    2015-09-01

    Full Text Available The cancer-modelling field is now experiencing a conversion with the recent emergence of the RNA-programmable CRISPR-Cas9 system, a flexible methodology to produce essentially any desired modification in the genome. Cancer is a multistep process that involves many genetic mutations and other genome rearrangements. Despite their importance, it is difficult to recapitulate the degree of genetic complexity found in patient tumors. The CRISPR-Cas9 system for genome editing has been proven as a robust technology that makes it possible to generate cellular and animal models that recapitulate those cooperative alterations rapidly and at low cost. In this review, we will discuss the innovative applications of the CRISPR-Cas9 system to generate new models, providing a new way to interrogate the development and progression of cancers.

  18. Patentability aspects of computational cancer models

    Science.gov (United States)

    Lishchuk, Iryna

    2017-07-01

    Multiscale cancer models, implemented in silico, simulate tumor progression at various spatial and temporal scales. Having the innovative substance and possessing the potential of being applied as decision support tools in clinical practice, patenting and obtaining patent rights in cancer models seems prima facie possible. What legal hurdles the cancer models need to overcome for being patented we inquire from this paper.

  19. A mathematical model representing cellular immune development and response to Salmonella of chicken intestinal tissue

    NARCIS (Netherlands)

    Schokker, D.; Bannink, A.; Smits, M.A.; Rebel, J.M.J.

    2013-01-01

    The aim of this study was to create a dynamic mathematical model of the development of the cellular branch of the intestinal immune system of poultry during the first 42 days of life and of its response towards an oral infection with Salmonella enterica serovar Enteritidis. The system elements were

  20. Stochastic Geometric Coverage Analysis in mmWave Cellular Networks with a Realistic Channel Model

    DEFF Research Database (Denmark)

    Rebato, Mattia; Park, Jihong; Popovski, Petar

    2017-01-01

    Wave interference and SIR coverage under large-scale deployments. For this purpose, we apply an accurate mmWave channel model, derived from experiments, into an analytical framework based on stochastic geometry. In this way we obtain a closed-form SIR coverage probability in large-scale mmWave cellular networks....

  1. Idealized Mesoscale Model Simulations of Open Cellular Convection Over the Sea

    DEFF Research Database (Denmark)

    Vincent, Claire Louise; Hahmann, Andrea N.; Kelly, Mark C.

    2012-01-01

    The atmospheric conditions during an observed case of open cellular convection over the North Sea were simulated using the Weather Research and Forecasting (WRF) numerical model. Wind, temperature and water vapour mixing ratio profiles from the WRF simulation were used to initialize an idealized ...

  2. A cellular automata model of land cover change to integrate urban growth with open space conservation

    Science.gov (United States)

    The preservation of riparian zones and other environmentally sensitive areas has long been recognized as one of the most cost-effective methods of managing stormwater and providing a broad range of ecosystem services. In this research, a cellular automata (CA)—Markov chain model ...

  3. An agent-based model of cellular dynamics and circadian variability in human endotoxemia.

    Directory of Open Access Journals (Sweden)

    Tung T Nguyen

    Full Text Available As cellular variability and circadian rhythmicity play critical roles in immune and inflammatory responses, we present in this study an agent-based model of human endotoxemia to examine the interplay between circadian controls, cellular variability and stochastic dynamics of inflammatory cytokines. The model is qualitatively validated by its ability to reproduce circadian dynamics of inflammatory mediators and critical inflammatory responses after endotoxin administration in vivo. Novel computational concepts are proposed to characterize the cellular variability and synchronization of inflammatory cytokines in a population of heterogeneous leukocytes. Our results suggest that there is a decrease in cell-to-cell variability of inflammatory cytokines while their synchronization is increased after endotoxin challenge. Model parameters that are responsible for IκB production stimulated by NFκB activation and for the production of anti-inflammatory cytokines have large impacts on system behaviors. Additionally, examining time-dependent systemic responses revealed that the system is least vulnerable to endotoxin in the early morning and most vulnerable around midnight. Although much remains to be explored, proposed computational concepts and the model we have pioneered will provide important insights for future investigations and extensions, especially for single-cell studies to discover how cellular variability contributes to clinical implications.

  4. Cancer drug discovery: recent innovative approaches to tumor modeling.

    Science.gov (United States)

    Lovitt, Carrie J; Shelper, Todd B; Avery, Vicky M

    2016-09-01

    Cell culture models have been at the heart of anti-cancer drug discovery programs for over half a century. Advancements in cell culture techniques have seen the rapid evolution of more complex in vitro cell culture models investigated for use in drug discovery. Three-dimensional (3D) cell culture research has become a strong focal point, as this technique permits the recapitulation of the tumor microenvironment. Biologically relevant 3D cellular models have demonstrated significant promise in advancing cancer drug discovery, and will continue to play an increasing role in the future. In this review, recent advances in 3D cell culture techniques and their application in tumor modeling and anti-cancer drug discovery programs are discussed. The topics include selection of cancer cells, 3D cell culture assays (associated endpoint measurements and analysis), 3D microfluidic systems and 3D bio-printing. Although advanced cancer cell culture models and techniques are becoming commonplace in many research groups, the use of these approaches has yet to be fully embraced in anti-cancer drug applications. Furthermore, limitations associated with analyzing information-rich biological data remain unaddressed.

  5. On the derivation of approximations to cellular automata models and the assumption of independence.

    Science.gov (United States)

    Davies, K J; Green, J E F; Bean, N G; Binder, B J; Ross, J V

    2014-07-01

    Cellular automata are discrete agent-based models, generally used in cell-based applications. There is much interest in obtaining continuum models that describe the mean behaviour of the agents in these models. Previously, continuum models have been derived for agents undergoing motility and proliferation processes, however, these models only hold under restricted conditions. In order to narrow down the reason for these restrictions, we explore three possible sources of error in deriving the model. These sources are the choice of limiting arguments, the use of a discrete-time model as opposed to a continuous-time model and the assumption of independence between the state of sites. We present a rigorous analysis in order to gain a greater understanding of the significance of these three issues. By finding a limiting regime that accurately approximates the conservation equation for the cellular automata, we are able to conclude that the inaccuracy between our approximation and the cellular automata is completely based on the assumption of independence. Copyright © 2014 Elsevier Inc. All rights reserved.

  6. Modeling and Analysis of Cellular Networks using Stochastic Geometry: A Tutorial

    KAUST Repository

    Elsawy, Hesham

    2016-11-03

    This paper presents a tutorial on stochastic geometry (SG) based analysis for cellular networks. This tutorial is distinguished by its depth with respect to wireless communication details and its focus on cellular networks. The paper starts by modeling and analyzing the baseband interference in a baseline single-tier downlink cellular network with single antenna base stations and universal frequency reuse. Then, it characterizes signal-to-interference-plus-noise-ratio (SINR) and its related performance metrics. In particular, a unified approach to conduct error probability, outage probability, and transmission rate analysis is presented. Although the main focus of the paper is on cellular networks, the presented unified approach applies for other types of wireless networks that impose interference protection around receivers. The paper then extends the unified approach to capture cellular network characteristics (e.g., frequency reuse, multiple antenna, power control, etc.). It also presents numerical examples associated with demonstrations and discussions. To this end, the paper highlights the state-of-the- art research and points out future research directions.

  7. Stochastic processes, multiscale modeling, and numerical methods for computational cellular biology

    CERN Document Server

    2017-01-01

    This book focuses on the modeling and mathematical analysis of stochastic dynamical systems along with their simulations. The collected chapters will review fundamental and current topics and approaches to dynamical systems in cellular biology. This text aims to develop improved mathematical and computational methods with which to study biological processes. At the scale of a single cell, stochasticity becomes important due to low copy numbers of biological molecules, such as mRNA and proteins that take part in biochemical reactions driving cellular processes. When trying to describe such biological processes, the traditional deterministic models are often inadequate, precisely because of these low copy numbers. This book presents stochastic models, which are necessary to account for small particle numbers and extrinsic noise sources. The complexity of these models depend upon whether the biochemical reactions are diffusion-limited or reaction-limited. In the former case, one needs to adopt the framework of s...

  8. Modeling cell adhesion and proliferation: a cellular-automata based approach.

    Science.gov (United States)

    Vivas, J; Garzón-Alvarado, D; Cerrolaza, M

    Cell adhesion is a process that involves the interaction between the cell membrane and another surface, either a cell or a substrate. Unlike experimental tests, computer models can simulate processes and study the result of experiments in a shorter time and lower costs. One of the tools used to simulate biological processes is the cellular automata, which is a dynamic system that is discrete both in space and time. This work describes a computer model based on cellular automata for the adhesion process and cell proliferation to predict the behavior of a cell population in suspension and adhered to a substrate. The values of the simulated system were obtained through experimental tests on fibroblast monolayer cultures. The results allow us to estimate the cells settling time in culture as well as the adhesion and proliferation time. The change in the cells morphology as the adhesion over the contact surface progress was also observed. The formation of the initial link between cell and the substrate of the adhesion was observed after 100 min where the cell on the substrate retains its spherical morphology during the simulation. The cellular automata model developed is, however, a simplified representation of the steps in the adhesion process and the subsequent proliferation. A combined framework of experimental and computational simulation based on cellular automata was proposed to represent the fibroblast adhesion on substrates and changes in a macro-scale observed in the cell during the adhesion process. The approach showed to be simple and efficient.

  9. Human Cancer Models Initiative | Office of Cancer Genomics

    Science.gov (United States)

    The Human Cancer Models Initiative (HCMI) is an international consortium that is generating novel human tumor-derived culture models, which are annotated with genomic and clinical data. In an effort to advance cancer research and more fully understand how in vitro findings are related to clinical biology, HCMI-developed models and related data will be available as a community resource for cancer and other research.

  10. Proteomic analysis of ovarian cancer cells reveals dynamic processes of protein secretion and shedding of extra-cellular domains.

    Directory of Open Access Journals (Sweden)

    Vitor M Faça

    Full Text Available BACKGROUND: Elucidation of the repertoire of secreted and cell surface proteins of tumor cells is relevant to molecular diagnostics, tumor imaging and targeted therapies. We have characterized the cell surface proteome and the proteins released into the extra-cellular milieu of three ovarian cancer cell lines, CaOV3, OVCAR3 and ES2 and of ovarian tumor cells enriched from ascites fluid. METHODOLOGY AND FINDINGS: To differentiate proteins released into the media from protein constituents of media utilized for culture, cells were grown in the presence of [(13C]-labeled lysine. A biotinylation-based approach was used to capture cell surface associated proteins. Our general experimental strategy consisted of fractionation of proteins from individual compartments followed by proteolytic digestion and LC-MS/MS analysis. In total, some 6,400 proteins were identified with high confidence across all specimens and fractions. CONCLUSIONS AND SIGNIFICANCE: Protein profiles of the cell lines had substantial similarity to the profiles of human ovarian cancer cells from ascites fluid and included protein markers known to be associated with ovarian cancer. Proteomic analysis indicated extensive shedding from extra-cellular domains of proteins expressed on the cell surface, and remarkably high secretion rates for some proteins (nanograms per million cells per hour. Cell surface and secreted proteins identified by in-depth proteomic profiling of ovarian cancer cells may provide new targets for diagnosis and therapy.

  11. An EMT-driven alternative splicing program occurs in human breast cancer and modulates cellular phenotype.

    Directory of Open Access Journals (Sweden)

    Irina M Shapiro

    2011-08-01

    Full Text Available Epithelial-mesenchymal transition (EMT, a mechanism important for embryonic development, plays a critical role during malignant transformation. While much is known about transcriptional regulation of EMT, alternative splicing of several genes has also been correlated with EMT progression, but the extent of splicing changes and their contributions to the morphological conversion accompanying EMT have not been investigated comprehensively. Using an established cell culture model and RNA-Seq analyses, we determined an alternative splicing signature for EMT. Genes encoding key drivers of EMT-dependent changes in cell phenotype, such as actin cytoskeleton remodeling, regulation of cell-cell junction formation, and regulation of cell migration, were enriched among EMT-associated alternatively splicing events. Our analysis suggested that most EMT-associated alternative splicing events are regulated by one or more members of the RBFOX, MBNL, CELF, hnRNP, or ESRP classes of splicing factors. The EMT alternative splicing signature was confirmed in human breast cancer cell lines, which could be classified into basal and luminal subtypes based exclusively on their EMT-associated splicing pattern. Expression of EMT-associated alternative mRNA transcripts was also observed in primary breast cancer samples, indicating that EMT-dependent splicing changes occur commonly in human tumors. The functional significance of EMT-associated alternative splicing was tested by expression of the epithelial-specific splicing factor ESRP1 or by depletion of RBFOX2 in mesenchymal cells, both of which elicited significant changes in cell morphology and motility towards an epithelial phenotype, suggesting that splicing regulation alone can drive critical aspects of EMT-associated phenotypic changes. The molecular description obtained here may aid in the development of new diagnostic and prognostic markers for analysis of breast cancer progression.

  12. An EMT-driven alternative splicing program occurs in human breast cancer and modulates cellular phenotype.

    Science.gov (United States)

    Shapiro, Irina M; Cheng, Albert W; Flytzanis, Nicholas C; Balsamo, Michele; Condeelis, John S; Oktay, Maja H; Burge, Christopher B; Gertler, Frank B

    2011-08-01

    Epithelial-mesenchymal transition (EMT), a mechanism important for embryonic development, plays a critical role during malignant transformation. While much is known about transcriptional regulation of EMT, alternative splicing of several genes has also been correlated with EMT progression, but the extent of splicing changes and their contributions to the morphological conversion accompanying EMT have not been investigated comprehensively. Using an established cell culture model and RNA-Seq analyses, we determined an alternative splicing signature for EMT. Genes encoding key drivers of EMT-dependent changes in cell phenotype, such as actin cytoskeleton remodeling, regulation of cell-cell junction formation, and regulation of cell migration, were enriched among EMT-associated alternatively splicing events. Our analysis suggested that most EMT-associated alternative splicing events are regulated by one or more members of the RBFOX, MBNL, CELF, hnRNP, or ESRP classes of splicing factors. The EMT alternative splicing signature was confirmed in human breast cancer cell lines, which could be classified into basal and luminal subtypes based exclusively on their EMT-associated splicing pattern. Expression of EMT-associated alternative mRNA transcripts was also observed in primary breast cancer samples, indicating that EMT-dependent splicing changes occur commonly in human tumors. The functional significance of EMT-associated alternative splicing was tested by expression of the epithelial-specific splicing factor ESRP1 or by depletion of RBFOX2 in mesenchymal cells, both of which elicited significant changes in cell morphology and motility towards an epithelial phenotype, suggesting that splicing regulation alone can drive critical aspects of EMT-associated phenotypic changes. The molecular description obtained here may aid in the development of new diagnostic and prognostic markers for analysis of breast cancer progression.

  13. GIM3E: Condition-specific Models of Cellular Metabolism Developed from Metabolomics and Expression Data

    Energy Technology Data Exchange (ETDEWEB)

    Schmidt, Brian; Ebrahim, Ali; Metz, Thomas O.; Adkins, Joshua N.; Palsson, Bernard O.; Hyduke, Daniel R.

    2013-11-15

    Motivation: Genome-scale metabolic models have been used extensively to investigate alterations in cellular metabolism. The accuracy of these models to represent cellular metabolism in specific conditions has been improved by constraining the model with omics data sources. However, few practical methods for integrating metabolomics data with other omics data sources into genome-scale models of metabolism have been reported. Results: GIMMME (Gene Inactivation Moderated by Metabolism, Metabolomics, and Expression) is an algorithm that enables the development of condition-specific models based on an objective function, transcriptomics, and intracellular metabolomics data. GIMMME establishes metabolite utilization requirements with metabolomics data, uses model-paired transcriptomics data to find experimentally supported solutions, and also provides calculations of the turnover (production / consumption) flux of metabolites. GIMMME was employed to investigate the effects of integrating additional omics datasets to create increasingly constrained solution spaces of Salmonella Typhimurium metabolism during growth in both rich and virulence media. This integration proved to be informative and resulted in a requirement of additional active reactions (12 in each case) or metabolites (26 or 29, respectively). The addition of constraints from transcriptomics also impacted the allowed solution space, and the cellular metabolites with turnover fluxes that were necessarily altered by the change in conditions increased from 118 to 271 of 1397. Availability: GIMMME has been implemented in Python and requires a COBRApy 0.2.x. The algorithm and sample data described here are freely available at: http://opencobra.sourceforge.net/

  14. One-pot synthesis of FePt/CNTs nanocomposites for efficient cellular imaging and cancer therapy

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Weihong; Zheng, Xiuwen, E-mail: xwzheng1976@163.com [Linyi University, School of Chemistry & Chemical Engineering, Shandong Provincial Key Laboratory of Detection Technology for Tumor Makers (China); Li, Shulian [Linyi Tumor Hospital (China); Zhang, Wei; Wen, Xin [Linyi University, School of Chemistry & Chemical Engineering, Shandong Provincial Key Laboratory of Detection Technology for Tumor Makers (China); Yue, Ludan [Shandong Normal University (China); Wang, Jinlong [Shandong University of Technology (China)

    2015-11-15

    Here, we developed a facile route to synthesize carbon nanotube-based FePt nanocomposites (FePt/CNTs) as a potential theranostic platform in the cancer treatment. FePt/CNTs were firstly synthesized via one-pot polyol route, and then functionalized with 6-arm-polyethylene glycol-amine polymer. The average size of FePt nanoparticles (NPs) is 3–4 nm, which is dispersed on the CNT surface (ca.50–150 nm). The as-prepared FePt NPs display high cytotoxicity by highly reactive oxygen species in cancer cells. Folic acid and fluorescein isothiocyanate are assembled onto the surface of FePt/CNTs for effective targeting of folate receptor-positive cancer cells and simultaneously for the visualization of cellular uptake. Therefore, the FePt/CNTs NPs capability of simultaneously performing diagnosis, therapy, and targeting is, therefore, promising for future potential widespread application in biomedicine.

  15. Efficient inference of parsimonious phenomenological models of cellular dynamics using S-systems and alternating regression.

    Directory of Open Access Journals (Sweden)

    Bryan C Daniels

    Full Text Available The nonlinearity of dynamics in systems biology makes it hard to infer them from experimental data. Simple linear models are computationally efficient, but cannot incorporate these important nonlinearities. An adaptive method based on the S-system formalism, which is a sensible representation of nonlinear mass-action kinetics typically found in cellular dynamics, maintains the efficiency of linear regression. We combine this approach with adaptive model selection to obtain efficient and parsimonious representations of cellular dynamics. The approach is tested by inferring the dynamics of yeast glycolysis from simulated data. With little computing time, it produces dynamical models with high predictive power and with structural complexity adapted to the difficulty of the inference problem.

  16. An Extended Cellular Automaton Model for Train Traffic Flow on the Dedicated Passenger Lines

    Directory of Open Access Journals (Sweden)

    Wenbo Zhao

    2014-01-01

    Full Text Available As one of the key components for the railway transportation system, the Train Operation Diagram can be greatly influenced by many extrinsic and intrinsic factors. Therefore, the railway train flow has shown the strong nonlinear characteristics, which makes it quite difficult to take further relative studies. Fortunately, the cellular automaton model has its own advantages in solving nonlinear problems and traffic flow simulation. Considering the mixed features of multispeed running trains on the passenger dedicated lines, this paper presents a new train model under the moving block system with different types of trains running with the cellular automaton idea. By analyzing such key factors as the maintenance skylight, the proportion of the multispeed running trains, and the distance between adjacent stations and departure intervals, the corresponding running rules for the cellular automaton model are reestablished herewith. By means of this CA model, the program of train running system is designed to analyze the potential impact on railway carrying capacity by various factors; the model can also be implemented to simulate the actual train running process and to draw the train operation diagram by computers. Basically the theory can be applied to organize the train operation on the dedicated passenger lines.

  17. To Be or Not to Be: Controlling Cellular Suicide | Center for Cancer Research

    Science.gov (United States)

    When a cell is damaged and can no longer function properly, a complex series of molecular steps is triggered that allows it to die in a controlled manner. This cellular suicide is called programmed cell death, or apoptosis.

  18. A Geometrical-Based Model for Cochannel Interference Analysis and Capacity Estimation of CDMA Cellular Systems

    Directory of Open Access Journals (Sweden)

    Konstantinos B. Baltzis

    2008-10-01

    Full Text Available A common assumption in cellular communications is the circular-cell approximation. In this paper, an alternative analysis based on the hexagonal shape of the cells is presented. A geometrical-based stochastic model is proposed to describe the angle of arrival of the interfering signals in the reverse link of a cellular system. Explicit closed form expressions are derived, and simulations performed exhibit the characteristics and validate the accuracy of the proposed model. Applications in the capacity estimation of WCDMA cellular networks are presented. Dependence of system capacity of the sectorization of the cells and the base station antenna radiation pattern is explored. Comparisons with data in literature validate the accuracy of the proposed model. The degree of error of the hexagonal and the circular-cell approaches has been investigated indicating the validity of the proposed model. Results have also shown that, in many cases, the two approaches give similar results when the radius of the circle equals to the hexagon inradius. A brief discussion on how the proposed technique may be applied to broadband access networks is finally made.

  19. A Geometrical-Based Model for Cochannel Interference Analysis and Capacity Estimation of CDMA Cellular Systems

    Directory of Open Access Journals (Sweden)

    Baltzis KonstantinosB

    2008-01-01

    Full Text Available Abstract A common assumption in cellular communications is the circular-cell approximation. In this paper, an alternative analysis based on the hexagonal shape of the cells is presented. A geometrical-based stochastic model is proposed to describe the angle of arrival of the interfering signals in the reverse link of a cellular system. Explicit closed form expressions are derived, and simulations performed exhibit the characteristics and validate the accuracy of the proposed model. Applications in the capacity estimation of WCDMA cellular networks are presented. Dependence of system capacity of the sectorization of the cells and the base station antenna radiation pattern is explored. Comparisons with data in literature validate the accuracy of the proposed model. The degree of error of the hexagonal and the circular-cell approaches has been investigated indicating the validity of the proposed model. Results have also shown that, in many cases, the two approaches give similar results when the radius of the circle equals to the hexagon inradius. A brief discussion on how the proposed technique may be applied to broadband access networks is finally made.

  20. Cellular automata model for human articular chondrocytes migration, proliferation and cell death: An in vitro validation.

    Science.gov (United States)

    Vaca-González, J J; Gutiérrez, M L; Guevara, J M; Garzón-Alvarado, D A

    2017-01-01

    Articular cartilage is characterized by low cell density of only one cell type, chondrocytes, and has limited self-healing properties. When articular cartilage is affected by traumatic injuries, a therapeutic strategy such as autologous chondrocyte implantation is usually proposed for its treatment. This approach requires in vitro chondrocyte expansion to yield high cell number for cell transplantation. To improve the efficiency of this procedure, it is necessary to assess cell dynamics such as migration, proliferation and cell death during culture. Computational models such as cellular automata can be used to simulate cell dynamics in order to enhance the result of cell culture procedures. This methodology has been implemented for several cell types; however, an experimental validation is required for each one. For this reason, in this research a cellular automata model, based on random-walk theory, was devised in order to predict articular chondrocyte behavior in monolayer culture during cell expansion. Results demonstrated that the cellular automata model corresponded to cell dynamics and computed-accurate quantitative results. Moreover, it was possible to observe that cell dynamics depend on weighted probabilities derived from experimental data and cell behavior varies according to the cell culture period. Thus, depending on whether cells were just seeded or proliferated exponentially, culture time probabilities differed in percentages in the CA model. Furthermore, in the experimental assessment a decreased chondrocyte proliferation was observed along with increased passage number. This approach is expected to having other uses as in enhancing articular cartilage therapies based on tissue engineering and regenerative medicine.

  1. Multiplicity of Mathematical Modeling Strategies to Search for Molecular and Cellular Insights into Bacteria Lung Infection.

    Science.gov (United States)

    Cantone, Martina; Santos, Guido; Wentker, Pia; Lai, Xin; Vera, Julio

    2017-01-01

    Even today two bacterial lung infections, namely pneumonia and tuberculosis, are among the 10 most frequent causes of death worldwide. These infections still lack effective treatments in many developing countries and in immunocompromised populations like infants, elderly people and transplanted patients. The interaction between bacteria and the host is a complex system of interlinked intercellular and the intracellular processes, enriched in regulatory structures like positive and negative feedback loops. Severe pathological condition can emerge when the immune system of the host fails to neutralize the infection. This failure can result in systemic spreading of pathogens or overwhelming immune response followed by a systemic inflammatory response. Mathematical modeling is a promising tool to dissect the complexity underlying pathogenesis of bacterial lung infection at the molecular, cellular and tissue levels, and also at the interfaces among levels. In this article, we introduce mathematical and computational modeling frameworks that can be used for investigating molecular and cellular mechanisms underlying bacterial lung infection. Then, we compile and discuss published results on the modeling of regulatory pathways and cell populations relevant for lung infection and inflammation. Finally, we discuss how to make use of this multiplicity of modeling approaches to open new avenues in the search of the molecular and cellular mechanisms underlying bacterial infection in the lung.

  2. Cancer models in C. elegans

    Science.gov (United States)

    Kirienko, Natalia V.; Mani, Kumaran; Fay, David S.

    2013-01-01

    Although now dogma, the idea that non-vertebrate organisms such as yeast, worms, and flies could inform, and in some cases even revolutionize, our understanding of oncogenesis in humans was not immediately obvious. Aided by the conservative nature of evolution and the persistence of a cohort of devoted researchers, the role of model organisms as a key tool in solving the cancer problem has, however, become widely accepted. In this review, we focus on the nematode Caenorhabditis elegans and its diverse and sometimes surprising contributions to our understanding of the tumorigenic process. Specifically, we discuss findings in the worm that address a well-defined set of processes known to be deregulated in cancer cells including cell cycle progression, growth factor signaling, terminal differentiation, apoptosis, the maintenance of genome stability, and developmental mechanisms relevant to invasion and metastasis. PMID:20175192

  3. Evaluation of blood T-lymphocyte subpopulations involved in host cellular immunity in dogs with mammary cancer.

    Science.gov (United States)

    Karayannopoulou, Maria; Anagnostou, Tilemachos; Margariti, Apostolia; Kostakis, Charalampos; Kritsepi-Konstantinou, Maria; Psalla, Dimitra; Savvas, Ioannis

    2017-04-01

    Cancer-bearing patients are often immunosuppressed. In dogs with mammary or other cancers, various alterations in blood cell populations involved in host cellular immunity have been reported; among these cell populations some T-lymphocyte subsets play an important role against cancer. The purpose of the present study was to investigate any alterations in circulating T-lymphocyte subpopulations involved in cellular immunity in bitches with mammary cancer, in comparison to age-matched healthy intact bitches. Twenty eight dogs with mammary cancer and 14 control dogs were included in this study. Twelve out of the 28 bitches had mammary cancer of clinical stage II and 16/28 of stage III. Histological examination revealed that 23/28 animals had carcinomas, 3/28 sarcomas and 2/28 carcinosarcomas. White blood cell, neutrophil and lymphocyte absolute numbers were measured by complete blood count. Furthermore, blood T-lymphocyte population (CD3(+)) and the subpopulations CD4(+), CD8(+) and CD5(low+) were assessed by flow cytometry. White blood cell and neutrophil but not lymphocyte absolute numbers were higher (P=0.003 and P=0.001, respectively) in cancer patients than controls. Flow cytometric analysis revealed that the relative percentage of T-lymphocytes (CD3(+)) and of CD4(+), CD8(+) subpopulations was lower (the CD4(+)/CD8(+) ratio was higher), whereas the percentage of CD5(low+) T-cells was higher, in dogs with cancer compared to controls; however, a statistically significant difference was found only in the case of CD8(+) T-cells (P=0.014), whereas in the case of the CD4(+)/CD8(+) ratio the difference almost reached statistical significance (P=0.059). Based on these findings, it can be suggested that, although the absolute number of blood lymphocytes is unchanged, the relative percentages of T-lymphocyte subpopulations involved in host cell-mediated immunity are altered, but only cytotoxic CD8(+) T-cells are significantly suppressed, in dogs with mammary cancer of

  4. Differences in p53 status significantly influence the cellular response and cell survival to 1,25-dihydroxyvitamin D3-metformin cotreatment in colorectal cancer cells.

    Science.gov (United States)

    Abu El Maaty, Mohamed A; Strassburger, Wendy; Qaiser, Tooba; Dabiri, Yasamin; Wölfl, Stefan

    2017-11-01

    Mutations in the tumor suppressor p53 are highly prevalent in cancers and are known to influence the sensitivity of cells to various chemotherapeutics including the anti-cancer candidates 1,25-dihydrovitamin D3 [1,25D3] and metformin. Previous studies have demonstrated additive/synergistic anti-cancer effects of the 1,25D3-metformin combination in different models, however, the influence of p53 status on the efficacy of this regimen has not been investigated. The CRC colorectal cancer (CRC) cell lines HCT116 wild-type (wt), HCT116 p53-/-, and HT-29 (mutant; R273H) were employed, covering three different p53 variations. Synergistic effects of the combination were confirmed in all cell lines using MTT assay. Detailed evaluation of the combination's effects was performed, including on-line measurements of cellular metabolism (glycolysis/respiration) using a biosensor chip system, analyses of mitochondrial activity (membrane potential and ATP/ROS production), mRNA expression analysis of WNT/β-catenin pathway players, and a comprehensive proteomic screen using immunoblotting and ELISA microarrays. AMPK signaling was found to be more strongly induced in response to all treatments in HCT116 wt cells compared to other cell lines, an observation that was coupled to a stronger accumulation of intracellular ROS in response to metformin/combination, and finally an induction in autophagy, depicted by an increase in LC3II:LC3I ratio in combination-treated cells compared to mono-treatments. An induction in apoptotic signaling was observed in the other cell lines in response to the combination, illustrated by a decrease in expression of pro-survival Bcl2 family members. P53 status impacts cellular responses to the combination but does not hamper its anti-proliferative synergy. © 2017 Wiley Periodicals, Inc.

  5. Modeling virtualized downlink cellular networks with ultra-dense small cells

    KAUST Repository

    Ibrahim, Hazem

    2015-09-11

    The unrelenting increase in the mobile users\\' populations and traffic demand drive cellular network operators to densify their infrastructure. Network densification increases the spatial frequency reuse efficiency while maintaining the signal-to-interference-plus-noise-ratio (SINR) performance, hence, increases the spatial spectral efficiency and improves the overall network performance. However, control signaling in such dense networks consumes considerable bandwidth and limits the densification gain. Radio access network (RAN) virtualization via control plane (C-plane) and user plane (U-plane) splitting has been recently proposed to lighten the control signaling burden and improve the network throughput. In this paper, we present a tractable analytical model for virtualized downlink cellular networks, using tools from stochastic geometry. We then apply the developed modeling framework to obtain design insights for virtualized RANs and quantify associated performance improvement. © 2015 IEEE.

  6. Hyperspectral fluorescence imaging for cellular iron mapping in the in vitro model of Parkinson's disease

    Science.gov (United States)

    Oh, Eung Seok; Heo, Chaejeong; Kim, Ji Seon; Suh, Minah; Lee, Young Hee; Kim, Jong-Min

    2014-05-01

    Parkinson's disease (PD) is characterized by progressive dopaminergic cell loss in the substantia nigra (SN) and elevated iron levels demonstrated by autopsy. Direct visualization of iron with live imaging techniques has not yet been successful. The aim of this study is to visualize and quantify the distribution of cellular iron using an intrinsic iron hyperspectral fluorescence signal. The 1-methyl-4-phenylpyridinium (MPP+)-induced cellular model of PD was established in SHSY5Y cells exposed to iron with ferric ammonium citrate (FAC, 100 μM). The hyperspectral fluorescence signal of iron was examined using a high-resolution dark-field optical microscope system with signal absorption for the visible/near infrared spectral range. The 6-h group showed heavy cellular iron deposition compared with the 1-h group. The cellular iron was dispersed in a small particulate form, whereas the extracellular iron was aggregated. In addition, iron particles were found to be concentrated on the cell membrane/edge of shrunken cells. The iron accumulation readily occurred in MPP+-induced cells, which is consistent with previous studies demonstrating elevated iron levels in the SN. This direct iron imaging could be applied to analyze the physiological role of iron, and its application might be expanded to various neurological disorders involving metals, such as copper, manganese, or zinc.

  7. Spherical Cancer Models in Tumor Biology

    Directory of Open Access Journals (Sweden)

    Louis-Bastien Weiswald

    2015-01-01

    Full Text Available Three-dimensional (3D in vitro models have been used in cancer research as an intermediate model between in vitro cancer cell line cultures and in vivo tumor. Spherical cancer models represent major 3D in vitro models that have been described over the past 4 decades. These models have gained popularity in cancer stem cell research using tumorospheres. Thus, it is crucial to define and clarify the different spherical cancer models thus far described. Here, we focus on in vitro multicellular spheres used in cancer research. All these spherelike structures are characterized by their well-rounded shape, the presence of cancer cells, and their capacity to be maintained as free-floating cultures. We propose a rational classification of the four most commonly used spherical cancer models in cancer research based on culture methods for obtaining them and on subsequent differences in sphere biology: the multicellular tumor spheroid model, first described in the early 70s and obtained by culture of cancer cell lines under nonadherent conditions; tumorospheres, a model of cancer stem cell expansion established in a serum-free medium supplemented with growth factors; tissue-derived tumor spheres and organotypic multicellular spheroids, obtained by tumor tissue mechanical dissociation and cutting. In addition, we describe their applications to and interest in cancer research; in particular, we describe their contribution to chemoresistance, radioresistance, tumorigenicity, and invasion and migration studies. Although these models share a common 3D conformation, each displays its own intrinsic properties. Therefore, the most relevant spherical cancer model must be carefully selected, as a function of the study aim and cancer type.

  8. Tai chi, cellular inflammation, and transcriptome dynamics in breast cancer survivors with insomnia: a randomized controlled trial.

    Science.gov (United States)

    Irwin, Michael R; Olmstead, Richard; Breen, Elizabeth C; Witarama, Tuff; Carrillo, Carmen; Sadeghi, Nina; Arevalo, Jesusa M G; Ma, Jeffrey; Nicassio, Perry; Ganz, Patricia A; Bower, Julienne E; Cole, Steve

    2014-11-01

    Mind-body therapies such as Tai Chi are widely used by breast cancer survivors, yet effects on inflammation are not known. This study hypothesized that Tai Chi Chih (TCC) would reduce systemic, cellular, and genomic markers of inflammation as compared with cognitive behavioral therapy for insomnia (CBT-I). In this randomized trial for the treatment of insomnia, 90 breast cancer survivors with insomnia were assigned to TCC or CBT-I for 2-hour sessions weekly for 3 months. At baseline and postintervention, blood samples were obtained for measurement of C-reactive protein and toll-like receptor-4-activated monocyte production of interleukin-6 (IL-6) and tumor necrosis factor-α (TNF), with a random subsample (n = 48) analyzed by genome-wide transcriptional profiling. Levels of C-reactive protein did not change in the TCC and CBT-I groups. Levels of toll-like receptor-4-activated monocyte production of IL-6 and TNF combined showed an overall reduction in TCC versus CBT-I (P TCC versus CBT-I (P = .001). TELiS promoter-based bioinformatics analyses implicated a reduction of activity of the proinflammatory transcription factor, nuclear factor-κB, in structuring these differences. Among breast cancer survivors with insomnia, 3 months of TCC reduced cellular inflammatory responses, and reduced expression of genes encoding proinflammatory mediators. Given the link between inflammation and cancer, these findings provide an evidence-based molecular framework to understand the potential salutary effects of TCC on cancer survivorship. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  9. Novel water-soluble polyurethane nanomicelles for cancer chemotherapy: physicochemical characterization and cellular activities

    Directory of Open Access Journals (Sweden)

    Khosroushahi Ahmad

    2012-01-01

    Full Text Available Abstract Background Efficient delivery of anticancer chemotherapies such as paclitaxel (PTX can improve treatment strategy in a variety of tumors such as breast and ovarian cancers. Accordingly, researches on polymeric nanomicelles continue to find suitable delivery systems. However, due to biocompatibility concerns, a few micellar nanoformulations have exquisitely been translated into clinical uses. Here, we report the synthesis of novel water-soluble nanomicelles using bioactive polyurethane (PU polymer and efficient delivery of PTX in the human breast cancer MCF-7 cells. Results The amphiphilic polyurethane was prepared through formation of urethane bounds between hydroxyl groups in poly (tetramethylene ether glycol (PTMEG and dimethylol propionic acid with isocyanate groups in toluene diisocyanate (TDI. The free isocyanate groups were blocked with phenol, while the free carboxyl groups of dimethylol propionic acid were reacted with triethylamine to attain ionic centers in the polymer backbone. These hydrophobic PTMEG blocks displayed self-assembly forming polymeric nanomicelles in water. The PTX loaded PU nanomicelles showed suitable physical stability, negative zeta potential charge (-43 and high loading efficiency (80% with low level of critical micelle concentration (CMC. In vitro drug release profile showed a faster rate of drug liberation at pH 5.4 as compared to that of pH 7.4, implying involvement of a pH-sensitive mechanism for drug release from the nanomicelles. The kinetic of release exquisitely obeyed the Higuchi model, confirming involvement of diffusion and somewhat erosion at pH 5.4. These nanomicelles significantly inhibited the growth and proliferation of the human breast cancer MCF-7 cells, leading them to apoptosis. The real time RT-PCR analysis confirmed the activation of apoptosis as result of liberation of cytochrome c in the cells treated with the PTX loaded PU nanomicelles. The comet assay analysis showed somewhat DNA

  10. Cellular and molecular processes in ovarian cancer metastasis. A Review in the Theme: Cell and Molecular Processes in Cancer Metastasis

    Science.gov (United States)

    Yeung, Tsz-Lun; Leung, Cecilia S.; Yip, Kay-Pong; Au Yeung, Chi Lam; Wong, Stephen T. C.

    2015-01-01

    Ovarian cancer is the most lethal gynecological malignancy. It is usually diagnosed at a late stage, with a 5-yr survival rate of ovarian cancer cases are diagnosed after tumors have widely spread within the peritoneal cavity, limiting the effectiveness of debulking surgery and chemotherapy. Owing to a substantially lower survival rate at late stages of disease than at earlier stages, the major cause of ovarian cancer deaths is believed to be therapy-resistant metastasis. Although metastasis plays a crucial role in promoting ovarian tumor progression and decreasing patient survival rates, the underlying mechanisms of ovarian cancer spread have yet to be thoroughly explored. For many years, researchers have believed that ovarian cancer metastasizes via a passive mechanism by which ovarian cancer cells are shed from the primary tumor and carried by the physiological movement of peritoneal fluid to the peritoneum and omentum. However, the recent discovery of hematogenous metastasis of ovarian cancer to the omentum via circulating tumor cells instigated rethinking of the mode of ovarian cancer metastasis and the importance of the “seed-and-soil” hypothesis for ovarian cancer metastasis. In this review we discuss the possible mechanisms by which ovarian cancer cells metastasize from the primary tumor to the omentum, the cross-talk signaling events between ovarian cancer cells and various stromal cells that play crucial roles in ovarian cancer metastasis, and the possible clinical implications of these findings in the management of this deadly, highly metastatic disease. PMID:26224579

  11. Identifying anti-growth factors for human cancer cell lines through genome-scale metabolic modeling

    DEFF Research Database (Denmark)

    Ghaffari, Pouyan; Mardinoglu, Adil; Asplund, Anna

    2015-01-01

    Human cancer cell lines are used as important model systems to study molecular mechanisms associated with tumor growth, hereunder how genomic and biological heterogeneity found in primary tumors affect cellular phenotypes. We reconstructed Genome scale metabolic models (GEMs) for eleven cell line...

  12. Modeling approaches for qualitative and semi-quantitative analysis of cellular signaling networks.

    Science.gov (United States)

    Samaga, Regina; Klamt, Steffen

    2013-06-26

    A central goal of systems biology is the construction of predictive models of bio-molecular networks. Cellular networks of moderate size have been modeled successfully in a quantitative way based on differential equations. However, in large-scale networks, knowledge of mechanistic details and kinetic parameters is often too limited to allow for the set-up of predictive quantitative models.Here, we review methodologies for qualitative and semi-quantitative modeling of cellular signal transduction networks. In particular, we focus on three different but related formalisms facilitating modeling of signaling processes with different levels of detail: interaction graphs, logical/Boolean networks, and logic-based ordinary differential equations (ODEs). Albeit the simplest models possible, interaction graphs allow the identification of important network properties such as signaling paths, feedback loops, or global interdependencies. Logical or Boolean models can be derived from interaction graphs by constraining the logical combination of edges. Logical models can be used to study the basic input-output behavior of the system under investigation and to analyze its qualitative dynamic properties by discrete simulations. They also provide a suitable framework to identify proper intervention strategies enforcing or repressing certain behaviors. Finally, as a third formalism, Boolean networks can be transformed into logic-based ODEs enabling studies on essential quantitative and dynamic features of a signaling network, where time and states are continuous.We describe and illustrate key methods and applications of the different modeling formalisms and discuss their relationships. In particular, as one important aspect for model reuse, we will show how these three modeling approaches can be combined to a modeling pipeline (or model hierarchy) allowing one to start with the simplest representation of a signaling network (interaction graph), which can later be refined to logical

  13. pH effect on cellular uptake of Sn(IV) chlorine e6 dichloride trisodium salt by cancer cells in vitro.

    Science.gov (United States)

    Al-Khaza'leh, Khaled A; Omar, Khalid; Jaafar, M S

    2011-01-01

    The effects of pH value and presence of serum in an incubation medium on photosensitizer drug cellular uptake in MCF7 cancer cells have been investigated. The results showed that the presence of serum in an incubation medium reduced the drug cellular uptake at all pH values. It has been found that decreasing on pH values of the incubation medium increased the cellular uptake of the drug, demonstrating selective uptake of the sensitizer. The HepG2 liver cancer cells exhibited more drug cellular uptake than CCD-18CO normal colon cells, which assessed the selectivity uptake of photosensitizer on cancerous cells. The concentration of photosensitizer measured in 10(6) cells showed a good correlation to the incubation time. Fluorescence and absorption spectroscopy been have used to examine the cells.

  14. A Fork in the Road: The Effects of Different Cellular Pathways on Melanoma | Center for Cancer Research

    Science.gov (United States)

    Malignant melanoma is one of the most deadly forms of cancer because of its high capacity to metastasize and because there are few treatments effective in stopping its progression. The extensive body of research on melanoma has identified several important protein mutations that contribute to development of the disease. One of these proteins, Ras, is mutated in 25 percent of cutaneous malignant melanomas. These mutations disrupt Ras regulation, switching the protein permanently "on," leading to constant signaling of cellular messengers and stimulating growth without normal checks and balances.

  15. Silver Nanoparticle-Mediated Cellular Responses in Various Cell Lines: An in Vitro Model

    Directory of Open Access Journals (Sweden)

    Xi-Feng Zhang

    2016-09-01

    Full Text Available Silver nanoparticles (AgNPs have attracted increased interest and are currently used in various industries including medicine, cosmetics, textiles, electronics, and pharmaceuticals, owing to their unique physical and chemical properties, particularly as antimicrobial and anticancer agents. Recently, several studies have reported both beneficial and toxic effects of AgNPs on various prokaryotic and eukaryotic systems. To develop nanoparticles for mediated therapy, several laboratories have used a variety of cell lines under in vitro conditions to evaluate the properties, mode of action, differential responses, and mechanisms of action of AgNPs. In vitro models are simple, cost-effective, rapid, and can be used to easily assess efficacy and performance. The cytotoxicity, genotoxicity, and biocompatibility of AgNPs depend on many factors such as size, shape, surface charge, surface coating, solubility, concentration, surface functionalization, distribution of particles, mode of entry, mode of action, growth media, exposure time, and cell type. Cellular responses to AgNPs are different in each cell type and depend on the physical and chemical nature of AgNPs. This review evaluates significant contributions to the literature on biological applications of AgNPs. It begins with an introduction to AgNPs, with particular attention to their overall impact on cellular effects. The main objective of this review is to elucidate the reasons for different cell types exhibiting differential responses to nanoparticles even when they possess similar size, shape, and other parameters. Firstly, we discuss the cellular effects of AgNPs on a variety of cell lines; Secondly, we discuss the mechanisms of action of AgNPs in various cellular systems, and try to elucidate how AgNPs interact with different mammalian cell lines and produce significant effects; Finally, we discuss the cellular activation of various signaling molecules in response to AgNPs, and conclude with

  16. Silver Nanoparticle-Mediated Cellular Responses in Various Cell Lines: An in Vitro Model

    Science.gov (United States)

    Zhang, Xi-Feng; Shen, Wei; Gurunathan, Sangiliyandi

    2016-01-01

    Silver nanoparticles (AgNPs) have attracted increased interest and are currently used in various industries including medicine, cosmetics, textiles, electronics, and pharmaceuticals, owing to their unique physical and chemical properties, particularly as antimicrobial and anticancer agents. Recently, several studies have reported both beneficial and toxic effects of AgNPs on various prokaryotic and eukaryotic systems. To develop nanoparticles for mediated therapy, several laboratories have used a variety of cell lines under in vitro conditions to evaluate the properties, mode of action, differential responses, and mechanisms of action of AgNPs. In vitro models are simple, cost-effective, rapid, and can be used to easily assess efficacy and performance. The cytotoxicity, genotoxicity, and biocompatibility of AgNPs depend on many factors such as size, shape, surface charge, surface coating, solubility, concentration, surface functionalization, distribution of particles, mode of entry, mode of action, growth media, exposure time, and cell type. Cellular responses to AgNPs are different in each cell type and depend on the physical and chemical nature of AgNPs. This review evaluates significant contributions to the literature on biological applications of AgNPs. It begins with an introduction to AgNPs, with particular attention to their overall impact on cellular effects. The main objective of this review is to elucidate the reasons for different cell types exhibiting differential responses to nanoparticles even when they possess similar size, shape, and other parameters. Firstly, we discuss the cellular effects of AgNPs on a variety of cell lines; Secondly, we discuss the mechanisms of action of AgNPs in various cellular systems, and try to elucidate how AgNPs interact with different mammalian cell lines and produce significant effects; Finally, we discuss the cellular activation of various signaling molecules in response to AgNPs, and conclude with future perspectives

  17. Setup of IN VIVO Breast Cancer Models for Nanodrug Testing

    DEFF Research Database (Denmark)

    Schifter, Søren

    2013-01-01

    RNA/aptamer conjugates, or carriers such as liposome/chitosan/micelle spheres. As a first step towards testing of the efficacy of siRNA delivery in vivo via different conjugates and complexes, we aimed at developing a standardized breast cancer model system in mice. In this conception, a reporter gene is used...... for detection of the primary tumor and metastasis and the efficacy of siRNA delivery is measured by reporter gene-targeting siRNAs and in vivo imaging. The use of a uniform siRNA not affecting cellular processes would allow for standardized assessment of siRNA delivery to cancer cells without interferences via...... differential knockdown efficacies and the readout can directly be performed by quantitative imaging using a Caliper IVIS system. In one line of experiments, we engineered non-metastatic MCF-7 breast cancer cells to express the luminescent reporter firefly luciferase (Luc2) along with a pro-metastatic micro...

  18. Unified tractable model for downlink MIMO cellular networks using stochastic geometry

    KAUST Repository

    Afify, Laila H.

    2016-07-26

    Several research efforts are invested to develop stochastic geometry models for cellular networks with multiple antenna transmission and reception (MIMO). On one hand, there are models that target abstract outage probability and ergodic rate for simplicity. On the other hand, there are models that sacrifice simplicity to target more tangible performance metrics such as the error probability. Both types of models are completely disjoint in terms of the analytic steps to obtain the performance measures, which makes it challenging to conduct studies that account for different performance metrics. This paper unifies both techniques and proposes a unified stochastic-geometry based mathematical paradigm to account for error probability, outage probability, and ergodic rates in MIMO cellular networks. The proposed model is also unified in terms of the antenna configurations and leads to simpler error probability analysis compared to existing state-of-the-art models. The core part of the analysis is based on abstracting unnecessary information conveyed within the interfering signals by assuming Gaussian signaling. To this end, the accuracy of the proposed framework is verified against state-of-the-art models as well as system level simulations. We provide via this unified study insights on network design by reflecting system parameters effect on different performance metrics. © 2016 IEEE.

  19. A Model of How Different Biology Experts Explain Molecular and Cellular Mechanisms

    Science.gov (United States)

    Trujillo, Caleb M.; Anderson, Trevor R.; Pelaez, Nancy J.

    2015-01-01

    Constructing explanations is an essential skill for all science learners. The goal of this project was to model the key components of expert explanation of molecular and cellular mechanisms. As such, we asked: What is an appropriate model of the components of explanation used by biology experts to explain molecular and cellular mechanisms? Do explanations made by experts from different biology subdisciplines at a university support the validity of this model? Guided by the modeling framework of R. S. Justi and J. K. Gilbert, the validity of an initial model was tested by asking seven biologists to explain a molecular mechanism of their choice. Data were collected from interviews, artifacts, and drawings, and then subjected to thematic analysis. We found that biologists explained the specific activities and organization of entities of the mechanism. In addition, they contextualized explanations according to their biological and social significance; integrated explanations with methods, instruments, and measurements; and used analogies and narrated stories. The derived methods, analogies, context, and how themes informed the development of our final MACH model of mechanistic explanations. Future research will test the potential of the MACH model as a guiding framework for instruction to enhance the quality of student explanations. PMID:25999313

  20. An improved multi-value cellular automata model for heterogeneous bicycle traffic flow

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Sheng [College of Civil Engineering and Architecture, Zhejiang University, Hangzhou, 310058 China (China); Qu, Xiaobo [Griffith School of Engineering, Griffith University, Gold Coast, 4222 Australia (Australia); Xu, Cheng [Department of Transportation Management Engineering, Zhejiang Police College, Hangzhou, 310053 China (China); College of Transportation, Jilin University, Changchun, 130022 China (China); Ma, Dongfang, E-mail: mdf2004@zju.edu.cn [Ocean College, Zhejiang University, Hangzhou, 310058 China (China); Wang, Dianhai [College of Civil Engineering and Architecture, Zhejiang University, Hangzhou, 310058 China (China)

    2015-10-16

    This letter develops an improved multi-value cellular automata model for heterogeneous bicycle traffic flow taking the higher maximum speed of electric bicycles into consideration. The update rules of both regular and electric bicycles are improved, with maximum speeds of two and three cells per second respectively. Numerical simulation results for deterministic and stochastic cases are obtained. The fundamental diagrams and multiple states effects under different model parameters are analyzed and discussed. Field observations were made to calibrate the slowdown probabilities. The results imply that the improved extended Burgers cellular automata (IEBCA) model is more consistent with the field observations than previous models and greatly enhances the realism of the bicycle traffic model. - Highlights: • We proposed an improved multi-value CA model with higher maximum speed. • Update rules are introduced for heterogeneous bicycle traffic with maximum speed 2 and 3 cells/s. • Simulation results of the proposed model are consistent with field bicycle data. • Slowdown probabilities of both regular and electric bicycles are calibrated.

  1. Graph Cellular Automata with Relation-Based Neighbourhoods of Cells for Complex Systems Modelling: A Case of Traffic Simulation

    Directory of Open Access Journals (Sweden)

    Krzysztof Małecki

    2017-12-01

    Full Text Available A complex system is a set of mutually interacting elements for which it is possible to construct a mathematical model. This article focuses on the cellular automata theory and the graph theory in order to compare various types of cellular automata and to analyse applications of graph structures together with cellular automata. It proposes a graph cellular automaton with a variable configuration of cells and relation-based neighbourhoods (r–GCA. The developed mechanism enables modelling of phenomena found in complex systems (e.g., transport networks, urban logistics, social networks taking into account the interaction between the existing objects. As an implementation example, modelling of moving vehicles has been made and r–GCA was compared to the other cellular automata models simulating the road traffic and used in the computer simulation process.

  2. A cellular tensegrity model to analyse the structural viscoelasticity of the cytoskeleton.

    Science.gov (United States)

    Cañadas, Patrick; Laurent, Valerie M; Oddou, Christian; Isabey, Daniel; Wendling, Sylvie

    2002-09-21

    This study describes the viscoelastic properties of a refined cellular-tensegrity model composed of six rigid bars connected to a continuous network of 24 viscoelastic pre-stretched cables (Voigt bodies) in order to analyse the role of the cytoskeleton spatial rearrangement on the viscoelastic response of living adherent cells. This structural contribution was determined from the relationships between the global viscoelastic properties of the tensegrity model, i.e., normalized viscosity modulus (eta(*)), normalized elasticity modulus (E(*)), and the physical properties of the constitutive elements, i.e., their normalized length (L(*)) and normalized initial internal tension (T(*)). We used a numerical method to simulate the deformation of the structure in response to different types of loading, while varying by several orders of magnitude L(*) and T(*). The numerical results obtained reveal that eta(*) remains almost independent of changes in T(*) (eta(*) proportional, variant T(*+0.1)), whereas E(*) increases with approximately the square root of the internal tension T(*) (from E(*) proportional, variant T(*+0.3) to E(*) proportional, variant T(*+0.7)). Moreover, structural viscosity eta(*) and elasticity E(*) are both inversely proportional to the square of the size of the structure (eta(*) proportional, variant L(*-2) and E(*) proportional, variant L(*-2)). These structural properties appear consistent with cytoskeleton (CSK) mechanical properties measured experimentally by various methods which are specific to the CSK micromanipulation in living adherent cells. Present results suggest, for the first time, that the effect of structural rearrangement of CSK elements on global CSK behavior is characterized by a faster cellular mechanical response relatively to the CSK element response, which thus contributes to the solidification process observed in adherent cells. In extending to the viscoelastic properties the analysis of the mechanical response of the cellular

  3. Optimizing mouse models for precision cancer prevention.

    Science.gov (United States)

    Le Magnen, Clémentine; Dutta, Aditya; Abate-Shen, Cory

    2016-03-01

    As cancer has become increasingly prevalent, cancer prevention research has evolved towards placing a greater emphasis on reducing cancer deaths and minimizing the adverse consequences of having cancer. 'Precision cancer prevention' takes into account the collaboration of intrinsic and extrinsic factors in influencing cancer incidence and aggressiveness in the context of the individual, as well as recognizing that such knowledge can improve early detection and enable more accurate discrimination of cancerous lesions. However, mouse models, and particularly genetically engineered mouse (GEM) models, have yet to be fully integrated into prevention research. In this Opinion article, we discuss opportunities and challenges for precision mouse modelling, including the essential criteria of mouse models for prevention research, representative success stories and opportunities for more refined analyses in future studies.

  4. Guided Inquiry and Consensus-Building Used to Construct Cellular Models

    Directory of Open Access Journals (Sweden)

    Joel I. Cohen

    2015-02-01

    Full Text Available Using models helps students learn from a “whole systems” perspective when studying the cell. This paper describes a model that employs guided inquiry and requires consensus building among students for its completion. The model is interactive, meaning that it expands upon a static model which, once completed, cannot be altered and additionally relates various levels of biological organization (molecular, organelle, and cellular to define cell and organelle function and interaction. Learning goals are assessed using data summed from final grades and from images of the student’s final cell model (plant, bacteria, and yeast taken from diverse seventh grade classes. Instructional figures showing consensus-building pathways and seating arrangements are discussed. Results suggest that the model leads to a high rate of participation, facilitates guided inquiry, and fosters group and individual exploration by challenging student understanding of the living cell.

  5. Antibody dependent cellular phagocytosis (ADCP) and antibody dependent cellular cytotoxicity (ADCC) of breast cancer cells mediated by bispecific antibody, MDX-210.

    Science.gov (United States)

    Watanabe, M; Wallace, P K; Keler, T; Deo, Y M; Akewanlop, C; Hayes, D F

    1999-02-01

    MDX-210 is a bispecific antibody (BsAb) with specificity for both the proto-oncogene product of HER-2/neu (c-erbB-2) and FcgammaRI (CD64). HER-2/neu is overexpressed in malignant tissue of approximately 30% of patients with breast cancer, and FcgammaRI is expressed on human monocytes, macrophages, and IFN-gamma activated granulocytes. We investigated phagocytosis and cytolysis of cultured human breast cancer cells by human monocyte-derived macrophages (MDM) mediated by BsAb MDX-210, its partially humanized derivative (MDX-H210), and its parent MoAb 520C9 (anti-HER-2/neu) under various conditions. Purified monocytes were cultured with GM-CSF, M-CSF, or no cytokine for five or six days. Antibody dependent cellular phagocytosis (ADCP) and cytolysis (ADCC) assays were performed with the MDM and HER-2/neu positive target cells (SK-BR-3). ADCP was measured by two-color fluorescence flow cytometry using PKH2 (green fluorescent dye) and phycoerythrin-conjugated (red) monoclonal antibodies (MoAb) against human CD14 and CD11b. ADCC was measured with a non-radioactive LDH detection kit. Both BsAb MDX-210 (via FcgammaRI) and MoAb 520C9 (mouse IgG1, via FcgammaRII) mediated similar levels of ADCP and ADCC. ADCP mediated by BsAb MDX-H210 was identical to that mediated by BsAb MDX-210. Confocal microscopy demonstrated that dual-labeled cells represented true phagocytosis. Both ADCP and ADCC were higher when MDM were pre-incubated with GM-CSF than when incubated with M-CSF. BsAb MDX-210 is as active in vitro as the parent MoAb 520C9 in inducing both phagocytosis and cytolysis of MDM. MDX-210 and its partially humanized derivative, MDX-H210, mediated similar levels of ADCP. GM-CSF appears to superior to M-CSF in inducing MDM-mediated ADCC and ADCP. These studies support the ongoing clinical investigations of BsAb MDX-210 and its partially humanized derivative.

  6. Addressing population heterogeneity and distribution in epidemics models using a cellular automata approach.

    Science.gov (United States)

    López, Leonardo; Burguerner, Germán; Giovanini, Leonardo

    2014-04-12

    The spread of an infectious disease is determined by biological and social factors. Models based on cellular automata are adequate to describe such natural systems consisting of a massive collection of simple interacting objects. They characterize the time evolution of the global system as the emergent behaviour resulting from the interaction of the objects, whose behaviour is defined through a set of simple rules that encode the individual behaviour and the transmission dynamic. An epidemic is characterized trough an individual-based-model built upon cellular automata. In the proposed model, each individual of the population is represented by a cell of the automata. This way of modeling an epidemic situation allows to individually define the characteristic of each individual, establish different scenarios and implement control strategies. A cellular automata model to study the time evolution of a heterogeneous populations through the various stages of disease was proposed, allowing the inclusion of individual heterogeneity, geographical characteristics and social factors that determine the dynamic of the desease. Different assumptions made to built the classical model were evaluated, leading to following results: i) for low contact rate (like in quarantine process or low density population areas) the number of infective individuals is lower than other areas where the contact rate is higher, and ii) for different initial spacial distributions of infected individuals different epidemic dynamics are obtained due to its influence on the transition rate and the reproductive ratio of disease. The contact rate and spatial distributions have a central role in the spread of a disease. For low density populations the spread is very low and the number of infected individuals is lower than in highly populated areas. The spacial distribution of the population and the disease focus as well as the geographical characteristic of the area play a central role in the dynamics of the

  7. Linking Cellular and Mechanical Processes in Articular Cartilage Lesion Formation: A Mathematical Model

    Directory of Open Access Journals (Sweden)

    Georgi I Kapitanov

    2016-10-01

    Full Text Available Post-traumatic osteoarthritis affects almost 20% of the adult US population. An injurious impact applies a significant amount of physical stress on articular cartilage and can initiate a cascade of biochemical reactions that can lead to the development of osteoarthritis. In our effort to understand the underlying biochemical mechanisms of this debilitating disease, we have constructed a multiscale mathematical model of the process with three components: cellular, chemical, and mechanical. The cellular component describes the different chondrocyte states according to the chemicals these cells release. The chemical component models the change in concentrations of those chemicals. The mechanical component contains a simulation of a blunt impact applied onto a cartilage explant and the resulting strains that initiate the biochemical processes. The scales are modeled through a system of partial-differential equations and solved numerically. The results of the model qualitatively capture the results of laboratory experiments of drop-tower impacts on cartilage explants. The model creates a framework for incorporating explicit mechanics, simulated by finite element analysis, into a theoretical biology framework. The effort is a step toward a complete virtual platform for modeling the development of post-traumatic osteoarthritis, which will be used to inform biomedical researchers on possible non-invasive strategies for mitigating the disease.

  8. Predictive modeling of multicellular structure formation by using Cellular Particle Dynamics simulations

    Science.gov (United States)

    McCune, Matthew; Shafiee, Ashkan; Forgacs, Gabor; Kosztin, Ioan

    2014-03-01

    Cellular Particle Dynamics (CPD) is an effective computational method for describing and predicting the time evolution of biomechanical relaxation processes of multicellular systems. A typical example is the fusion of spheroidal bioink particles during post bioprinting structure formation. In CPD cells are modeled as an ensemble of cellular particles (CPs) that interact via short-range contact interactions, characterized by an attractive (adhesive interaction) and a repulsive (excluded volume interaction) component. The time evolution of the spatial conformation of the multicellular system is determined by following the trajectories of all CPs through integration of their equations of motion. CPD was successfully applied to describe and predict the fusion of 3D tissue construct involving identical spherical aggregates. Here, we demonstrate that CPD can also predict tissue formation involving uneven spherical aggregates whose volumes decrease during the fusion process. Work supported by NSF [PHY-0957914]. Computer time provided by the University of Missouri Bioinformatics Consortium.

  9. Modeling of urban growth using cellular automata (CA) optimized by Particle Swarm Optimization (PSO)

    Science.gov (United States)

    Khalilnia, M. H.; Ghaemirad, T.; Abbaspour, R. A.

    2013-09-01

    In this paper, two satellite images of Tehran, the capital city of Iran, which were taken by TM and ETM+ for years 1988 and 2010 are used as the base information layers to study the changes in urban patterns of this metropolis. The patterns of urban growth for the city of Tehran are extracted in a period of twelve years using cellular automata setting the logistic regression functions as transition functions. Furthermore, the weighting coefficients of parameters affecting the urban growth, i.e. distance from urban centers, distance from rural centers, distance from agricultural centers, and neighborhood effects were selected using PSO. In order to evaluate the results of the prediction, the percent correct match index is calculated. According to the results, by combining optimization techniques with cellular automata model, the urban growth patterns can be predicted with accuracy up to 75 %.

  10. Modeling the suppression of cellular detonation in a hydrogen-air mixture by inert particles

    Science.gov (United States)

    Bedarev, I. A.; Fedorov, A. V.

    2017-10-01

    A technique for calculating two-dimensional detonation flows in a system consisting of a reacting gas mixture and inert particles has been developed to analyze problems related to the suppression of cellular detonation. The results of numerical simulation of the interaction of a cellular detonation wave with a cloud of fixed isothermal particles are presented. The calculations were carried out for a two-dimensional inviscid model using the ANSYS Fluent software. The interaction with particles of diameter 100 μm with a volume concentration of 10-4 ÷ 10-2 was investigated. The volume concentrations leading to a change in the size of the detonation cell, attenuation of the detonation wave, and detonation failure were obtained.

  11. Atomic force microscope-based single cell force spectroscopy of breast cancer cell lines: an approach for evaluating cellular invasion.

    Science.gov (United States)

    Omidvar, Ramin; Tafazzoli-Shadpour, Mohammad; Shokrgozar, Mohammad Ali; Rostami, Mostafa

    2014-10-17

    The adhesiveness of cancerous cells to their neighboring cells significantly contributes to tumor progression and metastasis. The single-cell force spectroscopy (SCFS) approach was implemented to survey the cell-cell adhesion force between cancerous cells in three cancerous breast cell lines (MCF-7, T47D, and MDA-MB-231). The gene expression levels of two dominant cell adhesion markers (E-cadherin and N-cadherin) were quantified by real-time PCR. Additionally, the local stiffness of the cell bodies was measured by atomic force microscopy (AFM), and the actin cytoskeletal organization was examined by confocal microscopy. Results indicated that the adhesion force between cells was conversely correlated with their invasion potential. The highest adhesion force was observed in the MCF-7 cells. A reduction in cell-cell adhesion, which is required for the detachment of cells from the main tumor during metastasis, is partly due to the loss of E-cadherin expression and the enhanced expression of N-cadherins. The reduced adhesion was accompanied by the softening of cells, as described by the rearrangement of actin filaments through confocal microscopy observations. The softening of the cell body and the reduced cellular adhesiveness are two adaptive mechanisms through which malignant cells achieve the increased deformability, motility, and strong metastasis potential necessary for passage through endothelial junctions and positioning in host tissue. This study presented application of SCFS to survey cell phenotype transformation during cancer progression. The results can be implemented as a platform for further investigations that target the manipulation of cellular adhesiveness and stiffness as a therapeutic choice. Copyright © 2014 Elsevier Ltd. All rights reserved.

  12. Effects of On- and Off-Ramps in Cellular Automata Models for Traffic Flow

    Science.gov (United States)

    Diedrich, G.; Santen, L.; Schadschneider, A.; Zittartz, J.

    We present results on the modeling of on- and off-ramps in cellular automata for traffic flow, especially the Nagel-Schreckenberg model. We study two different types of on-ramps that cause qualitatively the same effects. In a certain density regime ρlowjammed states exist. This phase separation is the reason for the plateau formation and implies a behavior analogous to that of stationary defects. This analogy allows to perform very fast simulations of complex traffic networks with a large number of on- and off-ramps because one can parametrise on-ramps in an exceedingly easy way.

  13. Stochastic modeling for dynamics of HIV-1 infection using cellular automata: A review.

    Science.gov (United States)

    Precharattana, Monamorn

    2016-02-01

    Recently, the description of immune response by discrete models has emerged to play an important role to study the problems in the area of human immunodeficiency virus type 1 (HIV-1) infection, leading to AIDS. As infection of target immune cells by HIV-1 mainly takes place in the lymphoid tissue, cellular automata (CA) models thus represent a significant step in understanding when the infected population is dispersed. Motivated by these, the studies of the dynamics of HIV-1 infection using CA in memory have been presented to recognize how CA have been developed for HIV-1 dynamics, which issues have been studied already and which issues still are objectives in future studies.

  14. Multiplex profiling of cellular invasion in 3D cell culture models.

    Directory of Open Access Journals (Sweden)

    Gerald Burgstaller

    Full Text Available To-date, most invasion or migration assays use a modified Boyden chamber-like design to assess migration as single-cell or scratch assays on coated or uncoated planar plastic surfaces. Here, we describe a 96-well microplate-based, high-content, three-dimensional cell culture assay capable of assessing invasion dynamics and molecular signatures thereof. On applying our invasion assay, we were able to demonstrate significant effects on the invasion capacity of fibroblast cell lines, as well as primary lung fibroblasts. Administration of epidermal growth factor resulted in a substantial increase of cellular invasion, thus making this technique suitable for high-throughput pharmacological screening of novel compounds regulating invasive and migratory pathways of primary cells. Our assay also correlates cellular invasiveness to molecular events. Thus, we argue of having developed a powerful and versatile toolbox for an extensive profiling of invasive cells in a 96-well format. This will have a major impact on research in disease areas like fibrosis, metastatic cancers, or chronic inflammatory states.

  15. Building a better model of cancer

    Directory of Open Access Journals (Sweden)

    DeGregori James

    2006-10-01

    Full Text Available Abstract The 2006 Cold Spring Harbor Laboratory meeting on the Mechanisms and Models of Cancer was held August 16–20. The meeting featured several hundred presentations of many short talks (mostly selected from the abstracts and posters, with the airing of a number of exciting new discoveries. We will focus this meeting review on models of cancer (primarily mouse models, highlighting recent advances in new mouse models that better recapitulate sporadic tumorigenesis, demonstrations of tumor addiction to tumor suppressor inactivation, new insight into senescence as a tumor barrier, improved understanding of the evolutionary paths of cancer development, and environmental/immunological influences on cancer.

  16. Urinary bladder cancer in dogs, a naturally occurring model for cancer biology and drug development.

    Science.gov (United States)

    Knapp, Deborah W; Ramos-Vara, José A; Moore, George E; Dhawan, Deepika; Bonney, Patty L; Young, Kirsten E

    2014-01-01

    Each year more than 65,000 people are diagnosed with urinary bladder cancer, and more than 14,000 people die from the disease in the United States. Studies in relevant animal models are essential to improve the management of bladder cancer. Naturally occurring bladder cancer in dogs very closely mimics human invasive bladder cancer, specifically high-grade invasive transitional cell carcinoma (TCC; also referred to as invasive urothelial carcinoma) in cellular and molecular features; biological behavior, including sites and frequency of metastasis; and response to therapy. Canine bladder cancer complements experimentally induced rodent tumors in regard to animal models of bladder cancer. Results of cellular and molecular studies and -omics analyses in dogs are expected to lead to improved detection of TCC and preneoplastic lesions, earlier intervention, better prediction of patient outcome, and more effective TCC management overall. Studies in dogs are being used to help define heritable risks (through very strong breed-associated risk) and environment risks and to evaluate prevention and treatment approaches that benefit humans as well as dogs. Clinical treatment trials in pet dogs with TCC are considered a win-win scenario by clinician scientists and pet owners. The individual dog benefits from effective treatment, the results are expected to help other dogs, and the findings are expected to ultimately help humans with TCC. This article provides an overview of canine TCC, a summary of the similarities and differences between canine and human invasive TCC, and examples of the types of valuable translational research that can be done using dogs with naturally occurring TCC. © The Author 2014. Published by Oxford University Press on behalf of the Institute for Laboratory Animal Research. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  17. Logic-Based and Cellular Pharmacodynamic Modeling of Bortezomib Responses in U266 Human Myeloma Cells.

    Science.gov (United States)

    Chudasama, Vaishali L; Ovacik, Meric A; Abernethy, Darrell R; Mager, Donald E

    2015-09-01

    Systems models of biological networks show promise for informing drug target selection/qualification, identifying lead compounds and factors regulating disease progression, rationalizing combinatorial regimens, and explaining sources of intersubject variability and adverse drug reactions. However, most models of biological systems are qualitative and are not easily coupled with dynamical models of drug exposure-response relationships. In this proof-of-concept study, logic-based modeling of signal transduction pathways in U266 multiple myeloma (MM) cells is used to guide the development of a simple dynamical model linking bortezomib exposure to cellular outcomes. Bortezomib is a commonly used first-line agent in MM treatment; however, knowledge of the signal transduction pathways regulating bortezomib-mediated cell cytotoxicity is incomplete. A Boolean network model of 66 nodes was constructed that includes major survival and apoptotic pathways and was updated using responses to several chemical probes. Simulated responses to bortezomib were in good agreement with experimental data, and a reduction algorithm was used to identify key signaling proteins. Bortezomib-mediated apoptosis was not associated with suppression of nuclear factor κB (NFκB) protein inhibition in this cell line, which contradicts a major hypothesis of bortezomib pharmacodynamics. A pharmacodynamic model was developed that included three critical proteins (phospho-NFκB, BclxL, and cleaved poly (ADP ribose) polymerase). Model-fitted protein dynamics and cell proliferation profiles agreed with experimental data, and the model-predicted IC50 (3.5 nM) is comparable to the experimental value (1.5 nM). The cell-based pharmacodynamic model successfully links bortezomib exposure to MM cellular proliferation via protein dynamics, and this model may show utility in exploring bortezomib-based combination regimens. U.S. Government work not protected by U.S. copyright.

  18. Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity

    NARCIS (Netherlands)

    Almendro, Vanessa; Cheng, Yu-Kang; Randles, Amanda; Itzkovitz, Shalev; Marusyk, Andriy; Ametller, Elisabet; Gonzalez-Farre, Xavier; Muñoz, Montse; Russnes, Hege G; Helland, Aslaug; Rye, Inga H; Borresen-Dale, Anne-Lise; Maruyama, Reo; van Oudenaarden, Alexander; Dowsett, Mitchell; Jones, Robin L; Reis-Filho, Jorge; Gascon, Pere; Gönen, Mithat; Michor, Franziska; Polyak, Kornelia

    2014-01-01

    Cancer therapy exerts a strong selection pressure that shapes tumor evolution, yet our knowledge of how tumors change during treatment is limited. Here, we report the analysis of cellular heterogeneity for genetic and phenotypic features and their spatial distribution in breast tumors pre- and

  19. Propagation Path Loss Models for 5G Urban Micro- and Macro-Cellular Scenarios

    DEFF Research Database (Denmark)

    Sun, Shu; Rappaport, Theodore S.; Rangan, Sundeep

    2016-01-01

    This paper presents and compares two candidate large-scale propagation path loss models, the alpha-beta-gamma (ABG) model and the close-in (CI) free space reference distance model, for the design of fifth generation (5G) wireless communication systems in urban micro- and macro-cellular scenarios....... Comparisons are made using the data obtained from 20 propagation measurement campaigns or ray-tracing studies from 2 GHz to 73.5 GHz over distances ranging from 5 m to 1429 m. The results show that the one-parameter CI model has a very similar goodness of fit (i.e., the shadow fading standard deviation......) in both line-of-sight and non-line-of-sight environments, while offering substantial simplicity and more stable behavior across frequencies and distances, as compared to the three-parameter ABG model....

  20. Multiscale Systems Analysis of Root Growth and Development: Modeling Beyond the Network and Cellular Scales

    Science.gov (United States)

    Band, Leah R.; Fozard, John A.; Godin, Christophe; Jensen, Oliver E.; Pridmore, Tony; Bennett, Malcolm J.; King, John R.

    2012-01-01

    Over recent decades, we have gained detailed knowledge of many processes involved in root growth and development. However, with this knowledge come increasing complexity and an increasing need for mechanistic modeling to understand how those individual processes interact. One major challenge is in relating genotypes to phenotypes, requiring us to move beyond the network and cellular scales, to use multiscale modeling to predict emergent dynamics at the tissue and organ levels. In this review, we highlight recent developments in multiscale modeling, illustrating how these are generating new mechanistic insights into the regulation of root growth and development. We consider how these models are motivating new biological data analysis and explore directions for future research. This modeling progress will be crucial as we move from a qualitative to an increasingly quantitative understanding of root biology, generating predictive tools that accelerate the development of improved crop varieties. PMID:23110897

  1. Gas1 is a pleiotropic regulator of cellular functions: from embryonic development to molecular actions in cancer gene therapy.

    Science.gov (United States)

    Segovia, José; Zarco, Natanael

    2014-01-01

    Cellular homeostasis is governed by a precise regulation of the molecular mechanisms of action of several proteins in a given time. There is a group of proteins that have a particular role depending on the cellular context in which they are present and are known as pleiotropic proteins. The Gas1 (Growth Arrest Specific 1) gene was isolated from a subtraction library from serum arrested versus growing NIH3T3 mouse fibroblast. Gas1 is a member of the alpha receptors (GFRα) for the family of GDNF ligands (GFL), we have previously shown that Gas1 acts as a negative modulator of the GDNF-induced intracellular signaling and induces cell arrest and apoptosis. This modulating activity is the cause of the capacity of Gas1 to act as a tumor suppressor. On the other hand, several studies have shown the interaction between Gas1 and Hh (Hedgehog) proteins to potentiate the positive regulation of this pathway, which is involved in the development of the nervous system, and in both the origin and progression of different tumors. This review summarizes our current understanding of the structure of Gas1 and the molecular mechanism of action in different cellular functions, both during embryonic development, in the adult and its effects inhibiting cell growth and inducing apoptosis of cancer cells.

  2. Grape seed extracts modify the outcome of oxaliplatin in colon cancer cells by interfering with cellular mechanisms of drug cytotoxicity.

    Science.gov (United States)

    Porcelli, Letizia; Iacobazzi, Rosa Maria; Quatrale, Anna Elisa; Bergamini, Carlo; Denora, Nunzio; Crupi, Pasquale; Antonacci, Donato; Mangia, Anita; Simone, Giovanni; Silvestris, Nicola; Azzariti, Amalia

    2017-08-01

    Grape seed extracts are commonly utilized as dietary supplements for their antioxidant properties, even from cancer patients. However, whether these natural extracts interfere with chemotherapeutics utilized in colon cancer treatment is still poorly investigated. The cytotoxicity of extracts from Italia and Palieri cultivars either alone or in combination with oxaliplatin was evaluated in colon cancer cells. Grape seed extracts displayed anti-proliferative activity depending on the concentration utilized through apoptosis induction. In combination, they affected the activation of Erk1/2 and counteracted the intrinsic and the extrinsic pathway of apoptosis, the DNA damage and the generation of ROS induced by oxaliplatin. Noteworthy grape seed extracts strongly enhanced the uptake of oxaliplatin into all cells, by affecting the cell transport system of platinum. The addition of these natural extracts to oxaliplatin strongly reduced the cellular response to oxaliplatin and allowed a huge accumulation of platinum into cells. Here, we shed light on the chemical biology underlying the combination of grape seed extracts and oxaliplatin, demonstrating that they might be detrimental to oxaliplatin effectiveness in colon cancer therapy.

  3. A heuristic computational model of basic cellular processes and oxygenation during spheroid-dependent biofabrication.

    Science.gov (United States)

    Sego, T J; Kasacheuski, U; Hauersperger, D; Tovar, A; Moldovan, N I

    2017-06-15

    An emerging approach in biofabrication is the creation of 3D tissue constructs through scaffold-free, cell spheroid-only methods. The basic mechanism in this technology is spheroid fusion, which is driven by the minimization of energy, the same biophysical mechanism that governs spheroid formation. However, other factors such as oxygen and metabolite accessibility within spheroids impact on spheroid properties and their ability to form larger-scale structures. The goal of our work is to develop a simulation platform eventually capable of predicting the conditions that minimize metabolism-related cell loss within spheroids. To describe the behavior and dynamic properties of the cells in response to their neighbors and to transient nutrient concentration fields, we developed a hybrid discrete-continuous heuristic model, combining a cellular Potts-type approach with field equations applied to a randomly populated spheroid cross-section of prescribed cell-type constituency. This model allows for the description of: (i) cellular adhesiveness and motility; (ii) interactions with concentration fields, including diffusivity and oxygen consumption; and (iii) concentration-dependent, stochastic cell dynamics, driven by metabolite-dependent cell death. Our model readily captured the basic steps of spheroid-based biofabrication (as specifically dedicated to scaffold-free bioprinting), including intra-spheroid cell sorting (both in 2D and 3D implementations), spheroid defect closure, and inter-spheroid fusion. Moreover, we found that when hypoxia occurring at the core of the spheroid was set to trigger cell death, this was amplified upon spheroid fusion, but could be mitigated by external oxygen supplementation. In conclusion, optimization and further development of scaffold-free bioprinting techniques could benefit from our computational model which is able to simultaneously account for both cellular dynamics and metabolism in constructs obtained by scaffold

  4. Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox.

    Science.gov (United States)

    Becker, Scott A; Feist, Adam M; Mo, Monica L; Hannum, Gregory; Palsson, Bernhard Ø; Herrgard, Markus J

    2007-01-01

    The manner in which microorganisms utilize their metabolic processes can be predicted using constraint-based analysis of genome-scale metabolic networks. Herein, we present the constraint-based reconstruction and analysis toolbox, a software package running in the Matlab environment, which allows for quantitative prediction of cellular behavior using a constraint-based approach. Specifically, this software allows predictive computations of both steady-state and dynamic optimal growth behavior, the effects of gene deletions, comprehensive robustness analyses, sampling the range of possible cellular metabolic states and the determination of network modules. Functions enabling these calculations are included in the toolbox, allowing a user to input a genome-scale metabolic model distributed in Systems Biology Markup Language format and perform these calculations with just a few lines of code. The results are predictions of cellular behavior that have been verified as accurate in a growing body of research. After software installation, calculation time is minimal, allowing the user to focus on the interpretation of the computational results.

  5. A Local Land Use Competition Cellular Automata Model and Its Application

    Directory of Open Access Journals (Sweden)

    Jun Yang

    2016-06-01

    Full Text Available Cellular automaton (CA is an important method in land use and cover change studies, however, the majority of research focuses on the discovery of macroscopic factors affecting LUCC, which results in ignoring the local effects within the neighborhoods. This paper introduces a Local Land Use Competition Cellular Automata (LLUC-CA model, based on local land use competition, land suitability evaluation, demand analysis of the different land use types, and multi-target land use competition allocation algorithm to simulate land use change at a micro level. The model is applied to simulate land use changes at Jinshitan National Tourist Holiday Resort from 1988 to 2012. The results show that the simulation accuracies were 64.46%, 77.21%, 85.30% and 99.14% for the agricultural land, construction land, forestland and water, respectively. In addition, comparing the simulation results of the LLUC-CA and CA-Markov model with the real land use data, their overall spatial accuracies were found to be 88.74% and 86.82%, respectively. In conclusion, the results from this study indicated that the model was an acceptable method for the simulation of large-scale land use changes, and the approach used here is applicable to analyzing the land use change driven forces and assist in decision-making.

  6. A general allometric and life-history model for cellular differentiation in the transition to multicellularity.

    Science.gov (United States)

    Solari, Cristian A; Kessler, John O; Goldstein, Raymond E

    2013-03-01

    The transition from unicellular, to colonial, to larger multicellular organisms has benefits, costs, and requirements. Here we present a model inspired by the volvocine green algae that explains the dynamics involved in the unicellular-multicellular transition using life-history theory and allometry. We model the two fitness components (fecundity and viability) and compare the fitness of hypothetical colonies of different sizes with varying degrees of cellular differentiation to understand the general principles that underlie the evolution of multicellularity. We argue that germ-soma separation may have evolved to counteract the increasing costs and requirements of larger multicellular colonies. The model shows that the cost of investing in soma decreases with size. For lineages such as the Volvocales, as reproduction costs increase with size for undifferentiated colonies, soma specialization benefits the colony indirectly by decreasing such costs and directly by helping reproductive cells acquire resources for their metabolic needs. Germ specialization is favored once soma evolves and takes care of vegetative functions. To illustrate the model, we use some allometric relationships measured in Volvocales. Our analysis shows that the cost of reproducing an increasingly larger group has likely played an important role in the transition to multicellularity and cellular differentiation.

  7. Simulation of emotional contagion using modified SIR model: A cellular automaton approach

    Science.gov (United States)

    Fu, Libi; Song, Weiguo; Lv, Wei; Lo, Siuming

    2014-07-01

    Emotion plays an important role in the decision-making of individuals in some emergency situations. The contagion of emotion may induce either normal or abnormal consolidated crowd behavior. This paper aims to simulate the dynamics of emotional contagion among crowds by modifying the epidemiological SIR model to a cellular automaton approach. This new cellular automaton model, entitled the “CA-SIRS model”, captures the dynamic process ‘susceptible-infected-recovered-susceptible', which is based on SIRS contagion in epidemiological theory. Moreover, in this new model, the process is integrated with individual movement. The simulation results of this model show that multiple waves and dynamical stability around a mean value will appear during emotion spreading. It was found that the proportion of initial infected individuals had little influence on the final stable proportion of infected population in a given system, and that infection frequency increased with an increase in the average crowd density. Our results further suggest that individual movement accelerates the spread speed of emotion and increases the stable proportion of infected population. Furthermore, decreasing the duration of an infection and the probability of reinfection can markedly reduce the number of infected individuals. It is hoped that this study will be helpful in crowd management and evacuation organization.

  8. Cellular automata model for traffic flow at intersections in internet of vehicles

    Science.gov (United States)

    Zhao, Han-Tao; Liu, Xin-Ru; Chen, Xiao-Xu; Lu, Jian-Cheng

    2018-03-01

    Considering the effect of the front vehicle's speed, the influence of the brake light and the conflict of the traffic flow, we established a cellular automata model called CE-NS for traffic flow at the intersection in the non-vehicle networking environment. According to the information interaction of Internet of Vehicles (IoV), introducing parameters describing the congestion and the accurate speed of the front vehicle into the CE-NS model, we improved the rules of acceleration, deceleration and conflict, and finally established a cellular automata model for traffic flow at intersections of IoV. The relationship between traffic parameters such as vehicle speed, flow and average travel time is obtained by numerical simulation of two models. Based on this, we compared the traffic situation of the non-vehicle networking environment with conditions of IoV environment, and analyzed the influence of the different degree of IoV on the traffic flow. The results show that the traffic speed is increased, the travel time is reduced, the flux of intersections is increased and the traffic flow is more smoothly under IoV environment. After the vehicle which achieves IoV reaches a certain proportion, the operation effect of the traffic flow begins to improve obviously.

  9. A Unique Cellular and Molecular Microenvironment Is Present in Tertiary Lymphoid Organs of Patients with Spontaneous Prostate Cancer Regression

    Directory of Open Access Journals (Sweden)

    María de la Luz García-Hernández

    2017-05-01

    Full Text Available ObjectiveMultiple solid cancers contain tertiary lymphoid organs (TLO. However, it is unclear whether they promote tumor rejection, facilitate tumor evasion, or simply whether they are a byproduct of chronic inflammation. We hypothesize that although chronic inflammation induces TLO formation, the tumor milieu can modulate TLO organization and functions in prostate cancer. Therefore, our study seeks to elucidate the cellular and molecular signatures in unique prostatectomy specimens from evanescent carcinoma patients to identify markers of cancer regression, which could be harnessed to modulate local immunosuppression or potentially enhance TLO function.MethodsWe used multicolor immunofluorescence to stain prostate tissues, collected at different stages of cancer progression (prostatic intraepithelial neoplasia, intermediate and advanced cancer or from patients with evanescent prostate carcinoma. Tissues were stained with antibodies specific for pro-inflammatory molecules (cyclooxygenase 2, CXCL10, IL17, tumor-infiltrating immune cells (mature DC-LAMP+ dendritic cells, CD3+ T cells, CD3+Foxp3+ regulatory T cells (Treg, T bet+ Th1 cells, granzyme B+ cytotoxic cells, and stromal cell populations (lymphatic vessels, tumor neovessels, high endothelial venules (HEV, stromal cells, which promote prostate tumor growth or are critical components of tumor-associated TLO.ResultsGenerally, inflammatory cells are located at the margins of tumors. Unexpectedly, we found TLO within prostate tumors from patients at different stages of cancer and in unique samples from patients with spontaneous cancer remission. In evanescent prostate carcinomas, accumulation of Treg was compromised, while Tbet+ T cells and CD8 T cells were abundant in tumor-associated TLO. In addition, we found a global decrease in tumor neovascularization and the coverage by cells positive for cyclooxygenase 2 (COX2. Finally, consistent with tumor regression, prostate stem cell antigen was

  10. Bacille Calmette-Guerin can induce cellular apoptosis of urothelial cancer directly through toll-like receptor 7 activation

    Directory of Open Access Journals (Sweden)

    Dah-Shyong Yu

    2015-08-01

    Full Text Available Immunotherapy using bacille Calmette-Guerin (BCG instillation is the mainstay treatment modality for superficial urothelial cancer (UC through toll-like receptor (TLR activation of cognitive immune response. We investigated the roles of TLR7 in the activation of apoptosis in UC cells after BCG treatment. The in vitro cytotoxicity effect of BCG on UC cells was measured by a modified 3-(4,5-dimethylthiazo-2-yl-2,5-diphenyl tetrazolium assay. Expressions of TLR7 mRNA and protein in native UC cells prior to and after BCG treatment were analyzed using real-time quantitative polymerase chain reaction and western blot methods. Phagocytotic processes after BCG treatment in UC cells were observed microscopically using a specific immunostain, subsequent cellular apoptosis-related signals induced by TLR7 were analyzed by western blot. Low-grade UC cells, TSGH8301, showed significant cellular death (4.23-fold higher than the high-grade UC cells T24 and J82 when treated with BCG and the BCG cytotoxicity was displayed in a dose–time-dependent manner. TSGH8301 cells had the highest content of TLR7 mRNA, 7.2- and 4.5-fold higher than that of T24 and J82 cells, respectively. TLR7 protein expression was also significantly increased in TSGH8301 cells. Phagocytosis-related markers, including beclin 1, ATG2, and LC3, were increased when TSGH8301 cells were treated by BCG. Interleukin-1 receptor-associated kinases 2 and 4 were also increased markedly in TSGH8301 cells. On the contrary, cellular apoptosis of TSGH8301 cells decreased by 34% when TLR7 activation was suppressed by the TLR antagonist IRS661 after BCG treatment. Our findings suggest that well differentiated TCC cells have higher expression of TLR7 and BCG can drive cellular death of TCC cells directly via TLR7 activation and related apoptotic pathway.

  11. Temporal logic patterns for querying dynamic models of cellular interaction networks.

    Science.gov (United States)

    Monteiro, Pedro T; Ropers, Delphine; Mateescu, Radu; Freitas, Ana T; de Jong, Hidde

    2008-08-15

    Models of the dynamics of cellular interaction networks have become increasingly larger in recent years. Formal verification based on model checking provides a powerful technology to keep up with this increase in scale and complexity. The application of modelchecking approaches is hampered, however, by the difficulty for nonexpert users to formulate appropriate questions in temporal logic. In order to deal with this problem, we propose the use of patterns, that is, high-level query templates that capture recurring biological questions and can be automatically translated into temporal logic. The applicability of the developed set of patterns has been investigated by the analysis of an extended model of the network of global regulators controlling the carbon starvation response in Escherichia coli. GNA and the model of the carbon starvation response network are available at http://www-helix.inrialpes.fr/gna.

  12. Cellular automaton modeling of ductile iron microstructure in the thin wall

    Directory of Open Access Journals (Sweden)

    A.A. Burbelko

    2011-10-01

    Full Text Available The mathematical model of the globular eutectic solidification in 2D was designed. Proposed model is based on the Cellular Automaton Finite Differences (CA-FD calculation method. Model has been used for studies of the primary austenite and of globular eutectic grains growth during the solidification of the ductile iron with different carbon equivalent in the thin wall casting. Model takes into account, among other things, non-uniform temperature distribution in the casting wall cross-section, kinetics of the austenite and graphite grains nucleation, and non-equilibrium nature of the interphase boundary migration. Solidification of the DI with different carbon equivalents was analyzed. Obtained results were compared with the solidification path calculated by CALPHAD method.

  13. Modelling of Eutectic Saturation Influence on Microstructure in Thin Wall Ductile Iron Casting Using Cellular Automata

    Directory of Open Access Journals (Sweden)

    Burbelko A.A.

    2012-12-01

    Full Text Available The mathematical model of the globular eutectic solidification in 2D was designed. Proposed model is based on the Cellular Automaton Finite Differences (CA-FD calculation method. Model has been used for studies of the primary austenite and of globular eutectic grains growth during the ductile iron solidification in the thin wall casting. Model takes into account, among other things, non-uniform temperature distribution in the casting wall cross-section, kinetics of the austenite and graphite grains nucleation, and non-equilibrium nature of the interphase boundary migration. Calculation of eutectic saturation influence (Sc = 0.9 - 1.1 on microstructure (austenite and graphite fraction, density of austenite and graphite grains and temperature curves in 2 mm wall ductile iron casting has been done.

  14. Modelling of Eutectic Saturation Influence on Microstructure in Thin Wall Ductile Iron Casting Using Cellular Automata

    Directory of Open Access Journals (Sweden)

    M. Górny

    2012-12-01

    Full Text Available The mathematical model of the globular eutectic solidification in 2D was designed. Proposed model is based on the Cellular AutomatonFinite Differences (CA-FD calculation method. Model has been used for studies of the primary austenite and of globular eutectic grainsgrowth during the ductile iron solidification in the thin wall casting. Model takes into account, among other things, non-uniformtemperature distribution in the casting wall cross-section, kinetics of the austenite and graphite grains nucleation, and non-equilibriumnature of the interphase boundary migration. Calculation of eutectic saturation influence (Sc = 0.9 - 1.1 on microstructure (austenite and graphite fraction, density of austenite and graphite grains and temperature curves in 2 mm wall ductile iron casting has been done.

  15. Simulation analysis of an integrated model for dynamic cellular manufacturing system

    Science.gov (United States)

    Hao, Chunfeng; Luan, Shichao; Kong, Jili

    2017-05-01

    Application of dynamic cellular manufacturing system (DCMS) is a well-known strategy to improve manufacturing efficiency in the production environment with high variety and low volume of production. Often, neither the trade-off of inter and intra-cell material movements nor the trade-off of hiring and firing of operators are examined in details. This paper presents simulation results of an integrated mixed-integer model including sensitivity analysis for several numerical examples. The comprehensive model includes cell formation, inter and intracellular materials handling, inventory and backorder holding, operator assignment (including resource adjustment) and flexible production routing. The model considers multi-production planning with flexible resources (machines and operators) where each period has different demands. The results verify the validity and sensitivity of the proposed model using a genetic algorithm.

  16. Evaluating thermodynamic models of enhancer activity on cellular resolution gene expression data.

    Science.gov (United States)

    Samee, Abul Hassan; Sinha, Saurabh

    2013-07-15

    With the advent of high throughput sequencing and high resolution transcriptomic technologies, there exists today an unprecedented opportunity to understand gene regulation at a quantitative level. State of the art models of the relationship between regulatory sequence and gene expression have shown great promise, but also suffer from some major shortcomings. In this paper, we identify and address methodological challenges pertaining to quantitative modeling of gene expression from sequence, and test our models on the anterior-posterior patterning system in the Drosophila embryo. We first develop a framework to process cellular resolution three-dimensional gene expression data from the Drosophila embryo and create data sets on which quantitative models can be trained. Next we propose a new score, called 'weighted pattern generating potential' (w-PGP), to evaluate model predictions, and show its advantages over the two most common scoring schemes in use today. The model building exercise uses w-PGP as the evaluation score and adopts a systematic strategy to increase a model's complexity while guarding against over-fitting. Our model identifies three transcription factors--ZELDA, SLOPPY-PAIRED, and NUBBIN--that have not been previously incorporated in quantitative models of this system, as having significant regulatory influence. Finally, we show how fitting quantitative models on data sets comprising a handful of enhancers, as reported in earlier work, may lead to unreliable models. Copyright © 2013. Published by Elsevier Inc.

  17. Dual pH-sensitive micelles with charge-switch for controlling cellular uptake and drug release to treat metastatic breast cancer.

    Science.gov (United States)

    Tang, Shan; Meng, Qingshuo; Sun, Huiping; Su, Jinghan; Yin, Qi; Zhang, Zhiwen; Yu, Haijun; Chen, Lingli; Gu, Wangwen; Li, Yaping

    2017-01-01

    For successful chemotherapy against metastatic breast cancer, the great efforts are still required for designing drug delivery systems that can be selectively internalized by tumor cells and release the cargo in a controlled manner. In this work, the chemotherapeutic agent paclitaxel (PTX) was loaded with the dual-pH sensitive micelle (DPM), which consisted of a pH-sensitive core, an acid-cleavable anionic shell, and a polyethylene glycol (PEG) corona. In the slightly acidic environment of tumor tissues, the anionic shell was taken off, inducing the conversion of the surface charge of DPM from negative to positive, which resulted in more efficient cellular uptake, stronger cytotoxicity and higher intra-tumor accumulation of PTX in the murine breast cancer 4T1 tumor-bearing mice models compared to the micelles with irremovable anionic or non-ionic shell. Meanwhile, the pH-sensitive core endowed DPM with rapid drug release in endo/lysosomes. The inhibitory rates of DPM against tumor growth and lung metastasis achieved 77.7% and 88.3%, respectively, without significant toxicity. Therefore, DPM is a promising nanocarrier for effective therapy of metastatic breast cancer due to satisfying the requirements of both selective uptake by tumor cells and sufficient and fast intracellular drug release. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Coordinating Center: Molecular and Cellular Findings of Screen-Detected Lesions | Division of Cancer Prevention

    Science.gov (United States)

    DESCRIPTION (provided by applicant): The Molecular and Cellular Characterization of Screen?Detected Lesions ? Coordinating Center and Data Management Group will provide support for the participating studies responding to RFA CA14?10. The coordinating center supports three main domains: network coordination, statistical support and computational analysis and protocol development and database support. Support for communication is provided through an interactive web portal, management of conference calls, and meeting support. |

  19. Discovery of a New Cellular Motion and Its Relevance to Breast Cancer and Involution

    Science.gov (United States)

    2014-02-01

    motion (CAMo), live cell imaging , confocal microscopy Overall Project Summary: During this first year of funding we have concentrated our work to...cell types in 3D cultures and in vivo. Subtask 1.1a: Real time live cell imaging using confocal microscopy will be used to image cellular movement...exciting as they are important steps in understanding behavior of normal myoepithelial cells using live cell imaging in physiologically

  20. In situ sensing and modeling of molecular events at the cellular level

    Science.gov (United States)

    Yang, Ruiguo

    We developed the Atomic Force Microscopy (AFM) based nanorobot in combination with other nanomechanical sensors for the investigation of cell signaling pathways. The AFM nanorobotics hinge on the superior spatial resolution of AFM in imaging and extends it into the measurement of biological processes and manipulation of biological matters. A multiple input single output control system was designed and implemented to solve the issues of nanomanipulation of biological materials, feedback, response frequency and nonlinearity. The AFM nanorobotic system therefore provide the human-directed position, velocity and force control with high frequency feedback, and more importantly it can feed the operator with the real-time imaging of manipulation result from the fast-imaging based local scanning. The use of the system has taken the study of cellular process at the molecular scale into a new level. The cellular response to the physiological conditions can be significantly manifested in cellular mechanics. Dynamic mechanical property has been regarded as biomarkers, sometimes even regulators of the signaling and physiological processes, thus the name mechanobiology. We sought to characterize the relationship between the structural dynamics and the molecular dynamics and the role of them in the regulation of cell behavior. We used the AFM nanorobotics to investigate the mechanical properties in real-time of cells that are stimulated by different chemical species. These reagents could result in similar ion channel responses but distinctive mechanical behaviors. We applied these measurement results to establish a model that describes the cellular stimulation and the mechanical property change, a "two-hit" model that comprises the loss of cell adhesion and the initiation of cell apoptosis. The first hit was verified by functional experiments: depletion of Calcium and nanosurgery to disrupt the cellular adhesion. The second hit was tested by a labeling of apoptotic markers that

  1. Using exploratory regression to identify optimal driving factors for cellular automaton modeling of land use change.

    Science.gov (United States)

    Feng, Yongjiu; Tong, Xiaohua

    2017-09-22

    Defining transition rules is an important issue in cellular automaton (CA)-based land use modeling because these models incorporate highly correlated driving factors. Multicollinearity among correlated driving factors may produce negative effects that must be eliminated from the modeling. Using exploratory regression under pre-defined criteria, we identified all possible combinations of factors from the candidate factors affecting land use change. Three combinations that incorporate five driving factors meeting pre-defined criteria were assessed. With the selected combinations of factors, three logistic regression-based CA models were built to simulate dynamic land use change in Shanghai, China, from 2000 to 2015. For comparative purposes, a CA model with all candidate factors was also applied to simulate the land use change. Simulations using three CA models with multicollinearity eliminated performed better (with accuracy improvements about 3.6%) than the model incorporating all candidate factors. Our results showed that not all candidate factors are necessary for accurate CA modeling and the simulations were not sensitive to changes in statistically non-significant driving factors. We conclude that exploratory regression is an effective method to search for the optimal combinations of driving factors, leading to better land use change models that are devoid of multicollinearity. We suggest identification of dominant factors and elimination of multicollinearity before building land change models, making it possible to simulate more realistic outcomes.

  2. A material optimization model to approximate energy bounds for cellular materials under multiload conditions

    DEFF Research Database (Denmark)

    Guedes, J.M.; Rodrigues, H.C.; Bendsøe, Martin P.

    2003-01-01

    bounds within this class of composites. A comparison of the computational results with the globally optimal bounds given via rank-N layered composites illustrates the behaviour for tension and shear load situations, as well as the importance of considering the shape of the basic unit cell as part......This paper describes a computational model, based on inverse homogenization and topology design, for approximating energy bounds for two-phase composites under multiple load cases. The approach allows for the identification of possible single-scale cellular materials that give rise to the optimal...

  3. a Modified Cellular Automaton Model for Ring Road Traffic with Velocity Guidance

    Science.gov (United States)

    Mei, C. Q.; Huang, H. J.; Tang, T. Q.

    We present a modified cellular automaton model to study the traffic flow on a signal controlled ring road with velocity guidance. The velocity guidance is such a strategy that when vehicles approach the traffic light, suggested velocities are provided for avoiding the vehicles' sharp brakes in front of red light. Simulation results show that this strategy may significantly reduce the vehicles' stopping rate and the effect size is dependent upon the traffic density, the detector position, the signal's cycle time and the obedience rate of vehicles to the guidance.

  4. Transition between immune and disease states in a cellular automaton model of clonal immune response

    CERN Document Server

    Bezzi, M; Ruffo, S; Seiden, P E; Bezzi, Michele; Celada, Franco; Ruffo, Stefano; Seiden, Philip E.

    1997-01-01

    In this paper we extend the Celada-Seiden (CS) model of the humoral immune response to include infectious virus and cytotoxic T lymphocytes (cellular response). The response of the system to virus involves a competition between the ability of the virus to kill the host cells and the host's ability to eliminate the virus. We find two basins of attraction in the dynamics of this system, one is identified with disease and the other with the immune state. There is also an oscillating state that exists on the border of these two stable states. Fluctuations in the population of virus or antibody can end the oscillation and drive the system into one of the stable states. The introduction of mechanisms of cross-regulation between the two responses can bias the system towards one of them. We also study a mean field model, based on coupled maps, to investigate virus-like infections. This simple model reproduces the attractors for average populations observed in the cellular automaton. All the dynamical behavior connect...

  5. Simulation of Cellular Energy Restriction in Quiescence (ERiQ)-A Theoretical Model for Aging.

    Science.gov (United States)

    Alfego, David; Kriete, Andres

    2017-12-12

    Cellular responses to energy stress involve activation of pro-survival signaling nodes, compensation in regulatory pathways and adaptations in organelle function. Specifically, energy restriction in quiescent cells (ERiQ) through energetic perturbations causes adaptive changes in response to reduced ATP, NAD+ and NADP levels in a regulatory network spanned by AKT, NF-κB, p53 and mTOR. Based on the experimental ERiQ platform, we have constructed a minimalistic theoretical model consisting of feedback motifs that enable investigation of stress-signaling pathways. The computer simulations reveal responses to acute energetic perturbations, promoting cellular survival and recovery to homeostasis. We speculated that the very same stress mechanisms are activated during aging in post-mitotic cells. To test this hypothesis, we modified the model to be deficient in protein damage clearance and demonstrate the formation of energy stress. Contrasting the network's pro-survival role in acute energetic challenges, conflicting responses in aging disrupt mitochondrial maintenance and contribute to a lockstep progression of decline when chronically activated. The model was analyzed by a local sensitivity analysis with respect to lifespan and makes predictions consistent with inhibitory and gain-of-function experiments in aging.

  6. A model of how different biology experts explain molecular and cellular mechanisms.

    Science.gov (United States)

    Trujillo, Caleb M; Anderson, Trevor R; Pelaez, Nancy J

    2015-01-01

    Constructing explanations is an essential skill for all science learners. The goal of this project was to model the key components of expert explanation of molecular and cellular mechanisms. As such, we asked: What is an appropriate model of the components of explanation used by biology experts to explain molecular and cellular mechanisms? Do explanations made by experts from different biology subdisciplines at a university support the validity of this model? Guided by the modeling framework of R. S. Justi and J. K. Gilbert, the validity of an initial model was tested by asking seven biologists to explain a molecular mechanism of their choice. Data were collected from interviews, artifacts, and drawings, and then subjected to thematic analysis. We found that biologists explained the specific activities and organization of entities of the mechanism. In addition, they contextualized explanations according to their biological and social significance; integrated explanations with methods, instruments, and measurements; and used analogies and narrated stories. The derived methods, analogies, context, and how themes informed the development of our final MACH model of mechanistic explanations. Future research will test the potential of the MACH model as a guiding framework for instruction to enhance the quality of student explanations. © 2015 C. M. Trujillo et al. CBE—Life Sciences Education © 2015 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

  7. Cellular calcium dynamics in lactation and breast cancer: from physiology to pathology.

    Science.gov (United States)

    Cross, Brandie M; Breitwieser, Gerda E; Reinhardt, Timothy A; Rao, Rajini

    2014-03-15

    Breast cancer is the second leading cause of cancer mortality in women, estimated at nearly 40,000 deaths and more than 230,000 new cases diagnosed in the U.S. this year alone. One of the defining characteristics of breast cancer is the radiographic presence of microcalcifications. These palpable mineral precipitates are commonly found in the breast after formation of a tumor. Since free Ca(2+) plays a crucial role as a second messenger inside cells, we hypothesize that these chelated precipitates may be a result of dysregulated Ca(2+) secretion associated with tumorigenesis. Transient and sustained elevations of intracellular Ca(2+) regulate cell proliferation, apoptosis and cell migration, and offer numerous therapeutic possibilities in controlling tumor growth and metastasis. During lactation, a developmentally determined program of gene expression controls the massive transcellular mobilization of Ca(2+) from the blood into milk by the coordinated action of calcium transporters, including pumps, channels, sensors and buffers, in a functional module that we term CALTRANS. Here we assess the evidence implicating genes that regulate free and buffered Ca(2+) in normal breast epithelium and cancer cells and discuss mechanisms that are likely to contribute to the pathological characteristics of breast cancer.

  8. Cellular automata-based modelling and simulation of biofilm structure on multi-core computers.

    Science.gov (United States)

    Skoneczny, Szymon

    2015-01-01

    The article presents a mathematical model of biofilm growth for aerobic biodegradation of a toxic carbonaceous substrate. Modelling of biofilm growth has fundamental significance in numerous processes of biotechnology and mathematical modelling of bioreactors. The process following double-substrate kinetics with substrate inhibition proceeding in a biofilm has not been modelled so far by means of cellular automata. Each process in the model proposed, i.e. diffusion of substrates, uptake of substrates, growth and decay of microorganisms and biofilm detachment, is simulated in a discrete manner. It was shown that for flat biofilm of constant thickness, the results of the presented model agree with those of a continuous model. The primary outcome of the study was to propose a mathematical model of biofilm growth; however a considerable amount of focus was also placed on the development of efficient algorithms for its solution. Two parallel algorithms were created, differing in the way computations are distributed. Computer programs were created using OpenMP Application Programming Interface for C++ programming language. Simulations of biofilm growth were performed on three high-performance computers. Speed-up coefficients of computer programs were compared. Both algorithms enabled a significant reduction of computation time. It is important, inter alia, in modelling and simulation of bioreactor dynamics.

  9. Cellular automata model for drug release from binary matrix and reservoir polymeric devices.

    Science.gov (United States)

    Johannes Laaksonen, Timo; Mikael Laaksonen, Hannu; Tapio Hirvonen, Jouni; Murtomäki, Lasse

    2009-04-01

    Kinetics of drug release from polymeric tablets, inserts and implants is an important and widely studied area. Here we present a new and widely applicable cellular automata model for diffusion and erosion processes occurring during drug release from polymeric drug release devices. The model divides a 2D representation of the release device into an array of cells. Each cell contains information about the material, drug, polymer or solvent that the domain contains. Cells are then allowed to rearrange according to statistical rules designed to match realistic drug release. Diffusion is modeled by a random walk of mobile cells and kinetics of chemical or physical processes by probabilities of conversion from one state to another. This is according to the basis of diffusion coefficients and kinetic rate constants, which are on fundamental level just probabilities for certain occurrences. The model is applied to three kinds of devices with different release mechanisms: erodable matrices, diffusion through channels or pores and membrane controlled release. The dissolution curves obtained are compared to analytical models from literature and the validity of the model is considered. The model is shown to be compatible with all three release devices, highlighting easy adaptability of the model to virtually any release system and geometry. Further extension and applications of the model are envisioned.

  10. A cellular automaton model for the ventricular myocardium considering the layer structure

    Science.gov (United States)

    Deng, Min-Yi; Dai, Jing-Yu; Zhang, Xue-Liang

    2015-09-01

    A cellular automaton model for the ventricular myocardium considering the layer structure has been established. The three types of cells in this model differ principally in the repolarization characteristics. For the normal travelling waves in this model, the computer simulation results show the R, S, and T waves and they are qualitatively in agreement with the standard electrocardiograph. Phenomena such as the potential decline of point J and segment ST and the rise of the potential line after the T wave appear when the ischemia occurs in the endocardium. The spiral wave has also been simulated, and the corresponding potential has a lower amplitude, higher frequency, and wider R wave, which accords with the distinguishing feature of the clinical electrocardiograph. Mechanisms underlying the above phenomena are analyzed briefly. Project supported by the National Natural Science Foundation of China (Grant Nos. 11365003 and 11165004).

  11. An Urban Growth Model Based on a Cellular Automata Phenomenological Framework

    Science.gov (United States)

    Iannone, G.; Troisi, A.; Guarnaccia, C.; D'Agostino, P. P.; Quartieri, J.

    In this paper we adopt a phenomenological approach in order to develop a suitable Cellular Automata (CA) model capable to satisfactory mimic city growth and urban sprawl. The use of CA in urban expansion modeling is well known since many years, but very rarely it has been related with a down-top approach which considers inhabitants' preferences as a driving tool to characterize the CA algorithm. In addition, we consider as a control mechanism of the cell conversion rate (i.e. the number of cells experiencing conversion into urban use) the logistic function. This function is tuned on the free space (cells) at disposal for the urban development. In this paper we present the basics of the model and we perform a simple simulation in the case of a generic geographic pattern.

  12. Modeling of the competition life cycle using the software complex of cellular automata PyCAlab

    Science.gov (United States)

    Berg, D. B.; Beklemishev, K. A.; Medvedev, A. N.; Medvedeva, M. A.

    2015-11-01

    The aim of the work is to develop a numerical model of the life cycle of competition on the basis of software complex cellular automata PyCAlab. The model is based on the general patterns of growth of various systems in resource-limited settings. At examples it is shown that the period of transition from an unlimited growth of the market agents to the stage of competitive growth takes quite a long time and may be characterized as monotonic. During this period two main strategies of competitive selection coexist: 1) capture of maximum market space with any reasonable costs; 2) saving by reducing costs. The obtained results allow concluding that the competitive strategies of companies must combine two mentioned types of behavior, and this issue needs to be given adequate attention in the academic literature on management. The created numerical model may be used for market research when developing of the strategies for promotion of new goods and services.

  13. A mathematical model in cellular manufacturing system considering subcontracting approach under constraints

    Directory of Open Access Journals (Sweden)

    Kamran Forghani

    2012-10-01

    Full Text Available In this paper, a new mathematical model in cellular manufacturing systems (CMSs has been presented. In order to increase the performance of manufacturing system, the production quantity of parts has been considered as a decision variable, i.e. each part can be produced and outsourced, simultaneously. This extension would be minimized the unused capacity of machines. The exceptional elements (EEs are taken into account and would be totally outsourced to the external supplier in order to remove intercellular material handling cost. The problem has been formulated as a mixed-integer programming to minimize the sum of manufacturing variable costs under budget, machines capacity and demand constraints. Also, to evaluate advantages of the model, several illustrative numerical examples have been provided to compare the performance of the proposed model with the available classical approaches in the literature.

  14. A parallelized three-dimensional cellular automaton model for grain growth during additive manufacturing

    Science.gov (United States)

    Lian, Yanping; Lin, Stephen; Yan, Wentao; Liu, Wing Kam; Wagner, Gregory J.

    2018-01-01

    In this paper, a parallelized 3D cellular automaton computational model is developed to predict grain morphology for solidification of metal during the additive manufacturing process. Solidification phenomena are characterized by highly localized events, such as the nucleation and growth of multiple grains. As a result, parallelization requires careful treatment of load balancing between processors as well as interprocess communication in order to maintain a high parallel efficiency. We give a detailed summary of the formulation of the model, as well as a description of the communication strategies implemented to ensure parallel efficiency. Scaling tests on a representative problem with about half a billion cells demonstrate parallel efficiency of more than 80% on 8 processors and around 50% on 64; loss of efficiency is attributable to load imbalance due to near-surface grain nucleation in this test problem. The model is further demonstrated through an additive manufacturing simulation with resulting grain structures showing reasonable agreement with those observed in experiments.

  15. Designing a mathematical model for integrating dynamic cellular manufacturing into supply chain system

    Science.gov (United States)

    Aalaei, Amin; Davoudpour, Hamid

    2012-11-01

    This article presents designing a new mathematical model for integrating dynamic cellular manufacturing into supply chain system with an extensive coverage of important manufacturing features consideration of multiple plants location, multi-markets allocation, multi-period planning horizons with demand and part mix variation, machine capacity, and the main constraints are demand of markets satisfaction in each period, machine availability, machine time-capacity, worker assignment, available time of worker, production volume for each plant and the amounts allocated to each market. The aim of the proposed model is to minimize holding and outsourcing costs, inter-cell material handling cost, external transportation cost, procurement & maintenance and overhead cost of machines, setup cost, reconfiguration cost of machines installation and removal, hiring, firing and salary worker costs. Aimed to prove the potential benefits of such a design, presented an example is shown using a proposed model.

  16. Operator-sum models of quantum decoherence in molecular quantum-dot cellular automata

    Science.gov (United States)

    Ramsey, Jackson S.; Blair, Enrique P.

    2017-08-01

    Quantum-dot cellular automata is a paradigm for classical computing which departs from the transistor paradigm and provides a system in which quantum phenomena may be studied. Here, the elementary computing device is a cell, a structure having multiple quantum dots and a few mobile charges. A specific operator-sum representation is developed for an exactly modeled double-dot, molecular cell within an environment of N similar neighboring molecules. While an operator-sum representation is not unique, a specific model can be determined by selecting a particular environmental basis. We select the environment's computational basis and calculate the specific and full set of 2N Kraus operators, which match exactly previous models of quantum decoherence in this system. Finally, the timescale for environmental interaction is characterized, enabling the reduction of the large set of Kraus operators to an approximate pair of Kraus operators, exact in the limit of large N.

  17. An Integrated Framework to Model Cellular Phenotype as a Component of Biochemical Networks

    Directory of Open Access Journals (Sweden)

    Michael Gormley

    2011-01-01

    Full Text Available Identification of regulatory molecules in signaling pathways is critical for understanding cellular behavior. Given the complexity of the transcriptional gene network, the relationship between molecular expression and phenotype is difficult to determine using reductionist experimental methods. Computational models provide the means to characterize regulatory mechanisms and predict phenotype in the context of gene networks. Integrating gene expression data with phenotypic data in transcriptional network models enables systematic identification of critical molecules in a biological network. We developed an approach based on fuzzy logic to model cell budding in Saccharomyces cerevisiae using time series expression microarray data of the cell cycle. Cell budding is a phenotype of viable cells undergoing division. Predicted interactions between gene expression and phenotype reflected known biological relationships. Dynamic simulation analysis reproduced the behavior of the yeast cell cycle and accurately identified genes and interactions which are essential for cell viability.

  18. Increased expression of fatty acid synthase provides a survival advantage to colorectal cancer cells via upregulation of cellular respiration.

    Science.gov (United States)

    Zaytseva, Yekaterina Y; Harris, Jennifer W; Mitov, Mihail I; Kim, Ji Tae; Butterfield, D Allan; Lee, Eun Y; Weiss, Heidi L; Gao, Tianyan; Evers, B Mark

    2015-08-07

    Fatty acid synthase (FASN), a lipogenic enzyme, is upregulated in colorectal cancer (CRC). Increased de novo lipid synthesis is thought to be a metabolic adaptation of cancer cells that promotes survival and metastasis; however, the mechanisms for this phenomenon are not fully understood. We show that FASN plays a role in regulation of energy homeostasis by enhancing cellular respiration in CRC. We demonstrate that endogenously synthesized lipids fuel fatty acid oxidation, particularly during metabolic stress, and maintain energy homeostasis. Increased FASN expression is associated with a decrease in activation of energy-sensing pathways and accumulation of lipid droplets in CRC cells and orthotopic CRCs. Immunohistochemical evaluation demonstrated increased expression of FASN and p62, a marker of autophagy inhibition, in primary CRCs and liver metastases compared to matched normal colonic mucosa. Our findings indicate that overexpression of FASN plays a crucial role in maintaining energy homeostasis in CRC via increased oxidation of endogenously synthesized lipids. Importantly, activation of fatty acid oxidation and consequent downregulation of stress-response signaling pathways may be key adaptation mechanisms that mediate the effects of FASN on cancer cell survival and metastasis, providing a strong rationale for targeting this pathway in advanced CRC.

  19. Effect of surgical treatment on the cellular immune response of gastric cancer patients

    Directory of Open Access Journals (Sweden)

    Barbieri C.

    2003-01-01

    Full Text Available Patients with gastric cancer have a variety of immunological abnormalities. In the present study the lymphocytes and their subsets were determined in the peripheral blood of patients with gastric cancer (N = 41 both before and after surgical treatment. The percent of helper/inducer CD4 T cells (43.6 ± 8.9 was not different after tumor resection (43.6 ± 8.2. The percent of the cytotoxic CD8+ T cell population decreased significantly, whether patients were treated surgically (27.2 ± 5.8%, N = 20 or not (27.3 ± 7.3%, N = 20 compared to individuals with inflammatory disease (30.9 ± 7.5% or to healthy individuals (33.2 ± 7.6%. The CD4/CD8 ratio consequently increased in the group of cancer patients. The peripheral blood lymphocytes of gastric cancer patients showed reduced responsiveness to mitogens. The defective blastogenic response of the lymphocytes was not associated with the production of transforming growth factor beta (TGF-ß since the patients with cancer had reduced production of TGF-ß1 (269 ± 239 pg/ml, N = 20 in comparison to the normal individuals (884 ± 175 pg/ml, N = 20. These results indicate that the immune response of gastric cancer patients was not significantly modified by surgical treatment when evaluated four weeks after surgery and that the immunosuppression observed was not due to an increase in TGF-ß1 production by peripheral leukocytes.

  20. Cellular Expression of Cyclooxygenase, Aromatase, Adipokines, Inflammation and Cell Proliferation Markers in Breast Cancer Specimen.

    Directory of Open Access Journals (Sweden)

    Samar Basu

    Full Text Available Current evidences suggest that expression of Ki67, cyclooxygenase (COX, aromatase, adipokines, prostaglandins, free radicals, β-catenin and α-SMA might be involved in breast cancer pathogenesis. The main objective of this study was to compare expression/localization of these potential compounds in breast cancer tissues with tissues collected adjacent to the tumor using immunohistochemistry and correlated with clinical pathology. The breast cancer specimens were collected from 30 women aged between 49 and 89 years who underwent breast surgery following cancer diagnosis. Expression levels of molecules by different stainings were graded as a score on a scale based upon staining intensity and proportion of positive cells/area or individually. AdipoR1, adiponectin, Ob-R, leptin, COX-1, COX-2, aromatase, PGF2α, F2-isoprostanes and α-SMA were localised on higher levels in the breast tissues adjacent to the tumor compared to tumor specimens when considering either score or staining area whereas COX-2 and AdipoR2 were found to be higher considering staining intensity and Ki67 on score level in the tumor tissue. There was no significant difference observed on β-catenin either on score nor on staining area and intensity between tissues adjacent to the tumor and tumor tissues. A positive correlation was found between COX-1 and COX-2 in the tumor tissues. In conclusion, these suggest that Ki67, COXs, aromatase, prostaglandin, free radicals, adipokines, β-catenin and α-SMA are involved in breast cancer. These further focus the need of examination of tissues adjacent to tumor, tumor itself and compare them with normal or benign breast tissues for a better understanding of breast cancer pathology and future evaluation of therapeutic benefit.

  1. A possible primary cause of cancer: deficient cellular interactions in endocrine pancreas

    Directory of Open Access Journals (Sweden)

    Israël Maurice

    2012-09-01

    Full Text Available Abstract Background Cancer is a devastating type of disease. New and innovative ways to tackle cancers that have so far proved refractive to conventional therapies is urgently needed. It is becoming increasingly clear that, in addition to conventional therapeutics targeting by small molecules, that tumor cell metabolism presents new opportunities to target selectively specific cancer cell populations. Metabolic defects in cancer cells can be manifested in many ways that might not be readily apparent, such as altering epigenetic gene regulation for example. The complex rewiring of metabolic pathways gives tumor cells a special advantage over differentiated cells, since they deplete body stores as fuel for their growth and proliferation. Tumor metabolism looks simpler when we consider that some enzymatic switches are in a neoglucogenic direction thereby depleting body stores. However, these pathways may be inadequately switched on by catabolic hormones (glucagon, epinephrine and cortisol in a specific situation where anabolism is activated by, for example insulin released from beta pancreatic cells or IGF, inducing mitosis and synthesis that are powered by glucose catabolism. Such a hybrid metabolic situation would be reached if a pancreatic beta cell mechanism, mediated by GABA, failed to silence neighboring alpha cells and delta cells. The inhibitory transmitter GABA hyperpolarizes alpha and delta cells via their GABA A receptors, and blocks the release of glucagon and somatostatin. Alternatively, an anomaly of alpha cell channels, would lead to a similar situation. Whatever is the alteration, anabolism fails to silence catabolism and enzymatic switches controlled by kinases and phosphatases adopt an inadequate direction, leading to a hybrid metabolic rewiring found in cancer. It is daring to formulate such a hypothesis as this. However, it is quite possible that the starting point in cancer is an alteration of the endocrine pancreas

  2. Oxidative Damage and Cellular Defense Mechanisms in Sea Urchin Models of Aging

    Science.gov (United States)

    Du, Colin; Anderson, Arielle; Lortie, Mae; Parsons, Rachel; Bodnar, Andrea

    2013-01-01

    The free radical or oxidative stress theory of aging proposes that the accumulation of oxidative cellular damage is a major contributor to the aging process and a key determinant of species longevity. This study investigates the oxidative stress theory in a novel model for aging research, the sea urchin. Sea urchins present a unique model for the study of aging due to the existence of species with tremendously different natural life spans including some species with extraordinary longevity and negligible senescence. Cellular oxidative damage, antioxidant capacity and proteasome enzyme activities were measured in the tissues of three sea urchin species: short-lived Lytechinus variegatus, long-lived Strongylocentrotus franciscanus and Strongylocentrotus purpuratus which has an intermediate lifespan. Levels of protein carbonyls and 4-hydroxynonenal (HNE) measured in tissues (muscle, nerve, esophagus, gonad, coelomocytes, ampullae) and 8-hydroxy-2’-deoxyguanosine (8-OHdG) measured in cell-free coelomic fluid showed no general increase with age. The fluorescent age-pigment lipofuscin measured in muscle, nerve and esophagus, increased with age however it appeared to be predominantly extracellular. Antioxidant mechanisms (total antioxidant capacity, superoxide dismutase) and proteasome enzyme activities were maintained with age. In some instances, levels of oxidative damage were lower and antioxidant activity higher in cells or tissues of the long-lived species compared to the short-lived species, however further studies are required to determine the relationship between oxidative damage and longevity in these animals. Consistent with the predictions of the oxidative stress theory of aging, the results suggest that negligible senescence is accompanied by a lack of accumulation of cellular oxidative damage with age and maintenance of antioxidant capacity and proteasome enzyme activities may be important mechanisms to mitigate damage. PMID:23707327

  3. Liver cancer mortality rate model in Thailand

    Science.gov (United States)

    Sriwattanapongse, Wattanavadee; Prasitwattanaseree, Sukon

    2013-09-01

    Liver Cancer has been a leading cause of death in Thailand. The purpose of this study was to model and forecast liver cancer mortality rate in Thailand using death certificate reports. A retrospective analysis of the liver cancer mortality rate was conducted. Numbering of 123,280 liver cancer causes of death cases were obtained from the national vital registration database for the 10-year period from 2000 to 2009, provided by the Ministry of Interior and coded as cause-of-death using ICD-10 by the Ministry of Public Health. Multivariate regression model was used for modeling and forecasting age-specific liver cancer mortality rates in Thailand. Liver cancer mortality increased with increasing age for each sex and was also higher in the North East provinces. The trends of liver cancer mortality remained stable in most age groups with increases during ten-year period (2000 to 2009) in the Northern and Southern. Liver cancer mortality was higher in males and increase with increasing age. There is need of liver cancer control measures to remain on a sustained and long-term basis for the high liver cancer burden rate of Thailand.

  4. The biopsychosocial model in cancer pain.

    Science.gov (United States)

    Novy, Diane M; Aigner, Carrie J

    2014-06-01

    The purpose of this review is to provide the reader with an up-to-date overview on the biopsychosocial model in cancer pain. This review contains articles published from 2012 to 2014, which advance our understanding of biopsychosocial factors related to the cancer pain experience and psychosocial treatment for cancer pain. Greater depression, anxiety, and distress, and lower quality of life are related to greater pain intensity in cancer patients. Recent publications have expanded on this research by examining how psychosocial factors relate to the development of chronic pain conditions after cancer treatment. Recent publications have also advanced our understanding of psychosocial interventions for cancer pain and symptom management. In the last few years, several reviews have emerged, which have found modest effect sizes for psychosocial interventions in cancer pain management. The biopsychosocial model is a helpful way to comprehensively approach the conceptualization and treatment of pain in cancer patients at all stages of the disease process. We currently have an established base of research on the importance of biopsychosocial model in cancer pain. Our ability to treat patients with cancer pain effectively will improve as we gain a better understanding of which treatments work for which patients.

  5. Use of Computational Modeling to Evaluate Hypotheses About the Molecular and Cellular Mechanisms of Bystander Effects

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Yuchao; Conolly, Rory B; Andersen, Melvin E.

    2006-11-21

    This report describes the development of a computational systems biology approach to evaluate the hypotheses of molecular and cellular mechanisms of adaptive response to low dose ionizing radiation. Our concept is that computational models of signaling pathways can be developed and linked to biologically based dose response models to evaluate the underlying molecular mechanisms which lead to adaptive response. For development of quantitatively accurate, predictive models, it will be necessary to describe tissues consisting of multiple cell types where the different types each contribute in their own way to the overall function of the tissue. Such a model will probably need to incorporate not only cell type-specific data but also spatial information on the architecture of the tissue and on intercellular signaling. The scope of the current model was more limited. Data obtained in a number of different biological systems were synthesized to describe a chimeric, “average” population cell. Biochemical signaling pathways involved in sensing of DNA damage and in the activation of cell cycle checkpoint controls and the apoptotic path were also included. As with any computational modeling effort, it was necessary to develop these simplified initial descriptions (models) that can be iteratively refined. This preliminary model is a starting point which, with time, can evolve to a level of refinement where large amounts of detailed biological information are synthesized and a capability for robust predictions of dose- and time-response behaviors is obtained.

  6. A hybrid cellular automaton model of solid tumor growth and bioreductive drug transport.

    Science.gov (United States)

    Kazmi, Nabila; Hossain, M A; Phillips, Roger M

    2012-01-01

    Bioreductive drugs are a class of hypoxia selective drugs that are designed to eradicate the hypoxic fraction of solid tumors. Their activity depends upon a number of biological and pharmacological factors and we used a mathematical modeling approach to explore the dynamics of tumor growth, infusion, and penetration of the bioreductive drug Tirapazamine (TPZ). An in-silico model is implemented to calculate the tumor mass considering oxygen and glucose as key microenvironmental parameters. The next stage of the model integrated extra cellular matrix (ECM), cell-cell adhesion, and cell movement parameters as growth constraints. The tumor microenvironments strongly influenced tumor morphology and growth rates. Once the growth model was established, a hybrid model was developed to study drug dynamics inside the hypoxic regions of tumors. The model used 10, 50 and 100 \\mu {\\rm M} as TPZ initial concentrations and determined TPZ pharmacokinetic (PK) (transport) and pharmacodynamics (cytotoxicity) properties inside hypoxic regions of solid tumor. The model results showed that diminished drug transport is a reason for TPZ failure and recommend the optimization of the drug transport properties in the emerging TPZ generations. The modeling approach used in this study is novel and can be a step to explore the behavioral dynamics of TPZ.

  7. Single and Multiple Gene Manipulations in Mouse Models of Human Cancer

    Directory of Open Access Journals (Sweden)

    Heather L. Lehman

    2015-01-01

    Full Text Available Mouse models of human cancer play a critical role in understanding the molecular and cellular mechanisms of tumorigenesis. Advances continue to be made in modeling human disease in a mouse, though the relevance of a mouse model often relies on how closely it is able to mimic the histologic, molecular, and physiologic characteristics of the respective human cancer. A classic use of a genetically engineered mouse in studying cancer is through the overexpression or deletion of a gene. However, the manipulation of a single gene often falls short of mimicking all the characteristics of the carcinoma in humans; thus a multiple gene approach is needed. Here we review genetic mouse models of cancers and their abilities to recapitulate human carcinoma with single versus combinatorial approaches with genes commonly involved in cancer.

  8. Oleuropein Prevents Neuronal Death, Mitigates Mitochondrial Superoxide Production and Modulates Autophagy in a Dopaminergic Cellular Model

    Directory of Open Access Journals (Sweden)

    Imène Achour

    2016-08-01

    Full Text Available Parkinson’s disease (PD is a progressive neurodegenerative disorder, primarily affecting dopaminergic neurons in the substantia nigra. There is currently no cure for PD and present medications aim to alleviate clinical symptoms, thus prevention remains the ideal strategy to reduce the prevalence of this disease. The goal of this study was to investigate whether oleuropein (OLE, the major phenolic compound in olive derivatives, may prevent neuronal degeneration in a cellular dopaminergic model of PD, differentiated PC12 cells exposed to the potent parkinsonian toxin 6-hydroxydopamine (6-OHDA. We also investigated OLE’s ability to mitigate mitochondrial oxidative stress and modulate the autophagic flux. Our results obtained by measuring cytotoxicity and apoptotic events demonstrate that OLE significantly decreases neuronal death. OLE could also reduce mitochondrial production of reactive oxygen species resulting from blocking superoxide dismutase activity. Moreover, quantification of autophagic and acidic vesicles in the cytoplasm alongside expression of specific autophagic markers uncovered a regulatory role for OLE against autophagic flux impairment induced by bafilomycin A1. Altogether, our results define OLE as a neuroprotective, anti-oxidative and autophagy-regulating molecule, in a neuronal dopaminergic cellular model.

  9. Organizing the Cellular and Molecular Heterogeneity in High-Grade Serous Ovarian Cancer by Mass Cytometry

    Science.gov (United States)

    Tumor heterogeneity in high grade serous ovarian cancer (HG-SOC) represents a significant barrier for successful therapeutic intervention. To further...understand the cell types contributing to this heterogeneity we performed a comprehensive phenotypic characterization of 22 primary ovarian tumor...also showed greater overall phenotypic heterogeneity quantified by Simpsons Diversity Index. Importantly the novel cell types identified have the

  10. Oxygen-Related Differences in Cellular and Vesicular Phenotypes Observed for Ovarian Cell Cancer Lines

    DEFF Research Database (Denmark)

    Søndergaard, Evo K. Lindersson; Pugholm, Lotte Hatting; Bæk, Rikke

    2016-01-01

    Extracellular vesicles (EVs) are one of several tools that cells use to communicate with each other. This communication is facilitated by a number of surface-associated proteins and the cargo of the vesicles. For several cancer types, the amount of EVs is observed to be up-regulated in patients...

  11. Implications of Extracellular Vesicle Transfer on Cellular Heterogeneity in Cancer : What Are the Potential Clinical Ramifications?

    NARCIS (Netherlands)

    Zomer, Anoek; van Rheenen, Jacco

    2016-01-01

    The functional and phenotypic heterogeneity of tumor cells represents one of the greatest challenges in the successful treatment of cancer patients, because it increases the risk that certain individual tumor cells possess the ability to, for example, metastasize or to tolerate cytotoxic drugs. This

  12. Specific and redundant activities of ETV1 and ETV4 in prostate cancer aggressiveness revealed by co-overexpression cellular contexts.

    Science.gov (United States)

    Mesquita, Diana; Barros-Silva, João D; Santos, Joana; Skotheim, Rolf I; Lothe, Ragnhild A; Paulo, Paula; Teixeira, Manuel R

    2015-03-10

    Genomic rearrangements involving ETS transcription factors are found in 50-70% of prostate carcinomas. While the large majority of the rearrangements involve ERG, around 10% involve members of the PEA3 subfamily (ETV1, ETV4 and ETV5). Using a panel of prostate cancer cell lines we found co-overexpression of ETV1 and ETV4 in two cell line models of advanced prostate cancer (MDA-PCa-2b and PC3) and questioned whether these PEA3 family members would cooperate in the acquisition of oncogenic properties or show functional redundancy. Using shRNAs we found that ETV1 and ETV4 have partially overlapping functions, with ETV1 being more relevant for cell invasion and ETV4 for anchorage-independent growth. In vitro expression signatures revealed the regulation of both specific and shared candidate targets that may resemble cellular mechanisms in vivo by interaction with the same intermediate partners. By combining the phenotypic impact data and the gene expression profiles of in vitro models with clinico-pathological features and gene expression profiles of ETS-subtyped tumors, we identified a set of eight genes associated with advanced stage and a set of three genes associated with higher Gleason score, supporting an oncogenic role of ETV1 and ETV4 overexpression and revealing gene sets that may be useful as prognostic markers.

  13. Protein subcellular location pattern classification in cellular images using latent discriminative models.

    Science.gov (United States)

    Li, Jieyue; Xiong, Liang; Schneider, Jeff; Murphy, Robert F

    2012-06-15

    Knowledge of the subcellular location of a protein is crucial for understanding its functions. The subcellular pattern of a protein is typically represented as the set of cellular components in which it is located, and an important task is to determine this set from microscope images. In this article, we address this classification problem using confocal immunofluorescence images from the Human Protein Atlas (HPA) project. The HPA contains images of cells stained for many proteins; each is also stained for three reference components, but there are many other components that are invisible. Given one such cell, the task is to classify the pattern type of the stained protein. We first randomly select local image regions within the cells, and then extract various carefully designed features from these regions. This region-based approach enables us to explicitly study the relationship between proteins and different cell components, as well as the interactions between these components. To achieve these two goals, we propose two discriminative models that extend logistic regression with structured latent variables. The first model allows the same protein pattern class to be expressed differently according to the underlying components in different regions. The second model further captures the spatial dependencies between the components within the same cell so that we can better infer these components. To learn these models, we propose a fast approximate algorithm for inference, and then use gradient-based methods to maximize the data likelihood. In the experiments, we show that the proposed models help improve the classification accuracies on synthetic data and real cellular images. The best overall accuracy we report in this article for classifying 942 proteins into 13 classes of patterns is about 84.6%, which to our knowledge is the best so far. In addition, the dependencies learned are consistent with prior knowledge of cell organization. http://murphylab.web.cmu.edu/software/.

  14. Dielectric properties modelling of cellular structures with PDMS for micro-sensor applications

    Science.gov (United States)

    Kachroudi, Achraf; Basrour, Skandar; Rufer, Libor; Sylvestre, Alain; Jomni, Fathi

    2015-12-01

    Electro-active polymers are emerging in the fields of actuators and micro-sensors because their good dielectric and mechanical properties makes them suitable for such applications. In this work, we focus on micro-structured (cellular) polymer materials (referred as piezoelectrets or ferroelectrets) that need prior charging to attain piezoelectric behaviour. The development of such applications requires an in-depth knowledge of the intrinsic dielectric properties of such structures and models to enable the accurate prediction of a given micro-structured material’s dielectric properties. Various polymers including polypropylene, polytetrafluoroethylene, fluoroethylenepropylene, cyclo-olefines and poly(ethylene terephthalate) in a cellular form have been studied by researchers over the last fifteen years. However, there is still a lack of information on the intrinsic dielectric properties of the most recently used dielectric polymer (polydimethylsiloxane, PDMS) over wide frequency and temperature ranges. In this work, we shall propose an exhaustive equivalent electrical circuit model and explain how it can be used to predict the micro-structured PDMS complex permittivity versus frequency and temperature. The results obtained from the model were found to be in good agreement with experimental data for various micro-structured PDMS materials. Typically, for micro-sensor applications, the dielectric constant and dielectric losses are key factors which need to be minimized. We have developed a configuration which enables both to be strongly reduced with a reduction of 16% in the dielectric constant of a micro-structured PDMS compared with the bulk material. In addition, the phenomena responsible for dielectric losses variations with frequency and temperature are discussed and correlated with the theoretical model. Our model is thus proved to be a powerful tool for the control of the dielectric properties of micro-structured PDMS material for micro-sensor applications.

  15. Free-Radical Polymer Science Structural Cancer Model: A Review

    Science.gov (United States)

    Petersen, Richard C.

    2013-01-01

    Polymer free-radical lipid alkene chain-growth biological models particularly for hypoxic cellular mitochondrial metabolic waste can be used to better understand abnormal cancer cell morphology and invasive metastasis. Without oxygen as the final electron acceptor for mitochondrial energy synthesis, protons cannot combine to form water and instead mitochondria produce free radicals and acid during hypoxia. Nonuniform bond-length shrinkage of membranes related to erratic free-radical covalent crosslinking can explain cancer-cell pleomorphism with epithelial-mesenchymal transition for irregular membrane borders that “ruffle” and warp over stiff underlying actin fibers. Further, mitochondrial hypoxic conditions produce acid that can cause molecular degradation. Subsequent low pH-activated enzymes then provide paths for invasive cell movement through tissue and eventually blood-born metastasis. Although free-radical crosslinking creates irregularly shaped membranes with structural actin-polymerized fiber extensions as filopodia and lamellipodia, due to rapid cell division the overall cell modulus (approximately stiffness) is lower than normal cells. When combined with low pH-activated enzymes and lower modulus cells, smaller cancer stem cells subsequently have a large advantage to follow molecular destructive pathways and leave the central tumor. In addition, forward structural spike-like lamellipodia protrusions can leverage to force lower-modulus cancer cells through narrow openings. By squeezing and deforming even smaller to allow for easier movement through difficult passageways, cancer cells can travel into adjacent tissues or possibly metastasize through the blood to new tissue. PMID:24278767

  16. Free-Radical Polymer Science Structural Cancer Model: A Review

    Directory of Open Access Journals (Sweden)

    Richard C. Petersen

    2013-01-01

    Full Text Available Polymer free-radical lipid alkene chain-growth biological models particularly for hypoxic cellular mitochondrial metabolic waste can be used to better understand abnormal cancer cell morphology and invasive metastasis. Without oxygen as the final electron acceptor for mitochondrial energy synthesis, protons cannot combine to form water and instead mitochondria produce free radicals and acid during hypoxia. Nonuniform bond-length shrinkage of membranes related to erratic free-radical covalent crosslinking can explain cancer-cell pleomorphism with epithelial-mesenchymal transition for irregular membrane borders that “ruffle” and warp over stiff underlying actin fibers. Further, mitochondrial hypoxic conditions produce acid that can cause molecular degradation. Subsequent low pH-activated enzymes then provide paths for invasive cell movement through tissue and eventually blood-born metastasis. Although free-radical crosslinking creates irregularly shaped membranes with structural actin-polymerized fiber extensions as filopodia and lamellipodia, due to rapid cell division the overall cell modulus (approximately stiffness is lower than normal cells. When combined with low pH-activated enzymes and lower modulus cells, smaller cancer stem cells subsequently have a large advantage to follow molecular destructive pathways and leave the central tumor. In addition, forward structural spike-like lamellipodia protrusions can leverage to force lower-modulus cancer cells through narrow openings. By squeezing and deforming even smaller to allow for easier movement through difficult passageways, cancer cells can travel into adjacent tissues or possibly metastasize through the blood to new tissue.

  17. A cellular automata model for traffic flow based on kinetics theory, vehicles capabilities and driver reactions

    Science.gov (United States)

    Guzmán, H. A.; Lárraga, M. E.; Alvarez-Icaza, L.; Carvajal, J.

    2018-02-01

    In this paper, a reliable cellular automata model oriented to faithfully reproduce deceleration and acceleration according to realistic reactions of drivers, when vehicles with different deceleration capabilities are considered is presented. The model focuses on describing complex traffic phenomena by coding in its rules the basic mechanisms of drivers behavior, vehicles capabilities and kinetics, while preserving simplicity. In particular, vehiclés kinetics is based on uniform accelerated motion, rather than in impulsive accelerated motion as in most existing CA models. Thus, the proposed model calculates in an analytic way three safe preserving distances to determine the best action a follower vehicle can take under a worst case scenario. Besides, the prediction analysis guarantees that under the proper assumptions, collision between vehicles may not happen at any future time. Simulations results indicate that all interactions of heterogeneous vehicles (i.e., car-truck, truck-car, car-car and truck-truck) are properly reproduced by the model. In addition, the model overcomes one of the major limitations of CA models for traffic modeling: the inability to perform smooth approach to slower or stopped vehicles. Moreover, the model is also capable of reproducing most empirical findings including the backward speed of the downstream front of the traffic jam, and different congested traffic patterns induced by a system with open boundary conditions with an on-ramp. Like most CA models, integer values are used to make the model run faster, which makes the proposed model suitable for real time traffic simulation of large networks.

  18. Potential Field Cellular Automata Model for Pedestrian Evacuation in a Domain with a Ramp

    Directory of Open Access Journals (Sweden)

    Xiao-Xia Jian

    2014-01-01

    Full Text Available We propose a potential field cellular automata model with a pushing force field to simulate the pedestrian evacuation in a domain with a ramp. We construct a cost potential depending on the ramp angle and introduce a function to evaluate the pushing force, which is related to the cost and the desired direction of pedestrian. With increase of crowd density, there is no empty space for pedestrian moving forward; pedestrian will purposefully push another pedestrian on her or his desired location to arrive the destination quickly. We analyse the relationship between the slope of ramp and the pushing force and investigate the changing of injured situations with the changing of the slope of ramp. When the number of pedestrians and the ramp angle arrive at certain critical points, the Domino effect will be simulated by this proposed model.

  19. Modeling and Simulation for Urban Rail Traffic Problem Based on Cellular Automata

    Science.gov (United States)

    Xu, Yan; Cao, Cheng-Xun; Li, Ming-Hua; Luo, Jin-Long

    2012-12-01

    Based on the Nagel-Schreckenberg model, we propose a new cellular automata model to simulate the urban rail traffic flow under moving block system and present a new minimum instantaneous distance formula under pure moving block. We also analyze the characteristics of the urban rail traffic flow under the influence of train density, station dwell times, the length of train, and the train velocity. Train delays can be decreased effectively through flexible departure intervals according to the preceding train type before its departure. The results demonstrate that a suitable adjustment of the current train velocity based on the following train velocity can greatly shorten the minimum departure intervals and then increase the capacity of rail transit.

  20. Study on queueing behavior in pedestrian evacuation by extended cellular automata model

    Science.gov (United States)

    Hu, Jun; You, Lei; Zhang, Hong; Wei, Juan; Guo, Yangyong

    2018-01-01

    This paper proposes a pedestrian evacuation model for effective simulation of evacuation efficiency based on extended cellular automata. In the model, pedestrians' momentary transition probability to a target position is defined in terms of the floor field and queueing time, and the critical time is defined as the waiting time threshold in a queue. Queueing time and critical time are derived using Fractal Brownian Motion through analysis of pedestrian arrival characteristics. Simulations using the platform and actual evacuations were conducted to study the relationships among system evacuation time, average system velocity, pedestrian density, flow rate, and critical time. The results demonstrate that at low pedestrian density, evacuation efficiency can be improved through adoption of the shortest route strategy, and critical time has an inverse relationship with average system velocity. Conversely, at higher pedestrian densities, it is better to adopt the shortest queueing time strategy, and critical time is inversely related to flow rate.

  1. Genome editing of human pluripotent stem cells to generate human cellular disease models

    Directory of Open Access Journals (Sweden)

    Kiran Musunuru

    2013-07-01

    Full Text Available Disease modeling with human pluripotent stem cells has come into the public spotlight with the awarding of the Nobel Prize in Physiology or Medicine for 2012 to Drs John Gurdon and Shinya Yamanaka for the discovery that mature cells can be reprogrammed to become pluripotent. This discovery has opened the door for the generation of pluripotent stem cells from individuals with disease and the differentiation of these cells into somatic cell types for the study of disease pathophysiology. The emergence of genome-editing technology over the past few years has made it feasible to generate and investigate human cellular disease models with even greater speed and efficiency. Here, recent technological advances in genome editing, and its utility in human biology and disease studies, are reviewed.

  2. Early Cellular Changes in the Ascending Aorta and Myocardium in a Swine Model of Metabolic Syndrome.

    Science.gov (United States)

    Saraf, Rabya; Huang, Thomas; Mahmood, Feroze; Owais, Khurram; Bardia, Amit; Khabbaz, Kamal R; Liu, David; Senthilnathan, Venkatachalam; Lassaletta, Antonio D; Sellke, Frank; Matyal, Robina

    2016-01-01

    Metabolic syndrome is associated with pathological remodeling of the heart and adjacent vessels. The early biochemical and cellular changes underlying the vascular damage are not fully understood. In this study, we sought to establish the nature, extent, and initial timeline of cytochemical derangements underlying reduced ventriculo-arterial compliance in a swine model of metabolic syndrome. Yorkshire swine (n = 8 per group) were fed a normal diet (ND) or a high-cholesterol (HCD) for 12 weeks. Myocardial function and blood flow was assessed before harvesting the heart. Immuno-blotting and immuno-histochemical staining were used to assess the cellular changes in the myocardium, ascending aorta and left anterior descending artery (LAD). There was significant increase in body mass index, blood glucose and mean arterial pressures (p = 0.002, p = 0.001 and p = 0.024 respectively) in HCD group. At the cellular level there was significant increase in anti-apoptotic factors p-Akt (p = 0.007 and p = 0.002) and Bcl-xL (p = 0.05 and p = 0.01) in the HCD aorta and myocardium, respectively. Pro-fibrotic markers TGF-β (p = 0.01), pSmad1/5 (p = 0.03) and MMP-9 (p = 0.005) were significantly increased in the HCD aorta. The levels of pro-apoptotic p38MAPK, Apaf-1 and cleaved Caspase3 were significantly increased in aorta of HCD (p = 0.03, p = 0.04 and p = 0.007 respectively). Similar changes in coronary arteries were not observed in either group. Functionally, the high cholesterol diet resulted in significant increase in ventricular end systolic pressure and-dp/dt (p = 0.05 and p = 0.007 respectively) in the HCD group. Preclinical metabolic syndrome initiates pro-apoptosis and pro-fibrosis pathways in the heart and ascending aorta, while sparing coronary arteries at this early stage of dietary modification.

  3. Effects of octreotide and insulin on colon cancer cellular proliferation and correlation with hTERT activity.

    Science.gov (United States)

    Ayiomamitis, Georgios D; Notas, George; Zaravinos, Apostolos; Drygiannakis, Ioannis; Georgiadou, Maria; Sfakianaki, Ourania; Mastrodimou, Niki; Thermos, Kyriaki; Kouroumalis, Elias

    2014-01-01

    Peptide hormone somatostatin and its receptors have a wide range of physiological functions and play a role in the treatment of numerous human diseases, including colorectal cancer. Octreotide, a synthetic somatostatin-analog peptide, inhibits growth of colonic cancer cells primarily by binding to G-protein coupled receptors and elicits cellular responses through second-messenger systems. Insulin also initiates mitogenic signals in certain cell types. The objective of the present study was to explore the effects of octreotide with or without insulin treatment, on Caco-2 and HT-29 human colon-cancer cell proliferation and to correlate their effects with the activation of telomerase reverse transcriptase (hTERT). The involvement of protein tyrosine phosphatases in the regulation of the anti-proliferative effect of octreotide was also evaluated. Sodium orthovanadate was used to reverse the anti- proliferative effect of octreotide. Telomerase activity was determined for each time point under octreotide and/or insulin treatment. Elevated expression of sst1, sst2 and sst5 was confirmed in both cell lines by RT-PCR. Immunocytochemistry detected sst1, sst2A, sst2B, sst3, sst4 and sst5 protein expression in the membranes of both cell lines. Octreotide inhibited the proliferation of Caco-2 and HT-29 cells in a time and dose-dependent manner. Insulin exerted proliferative effects in Caco-2 cells and octreotide reversed its effect in both cell lines. Sodium orthovanadate suppressed the anti-proliferative effect of octreotide both in Caco-2 and HT-29 cells. Telomerase activity was significantly reduced when Caco-2 cells were exposed to octreotide, under serum-free cultured medium. On the other hand, telomerase attenuation after octreotide treatment could not counteract the actions of insulin on both cells. Our data indicate that the use of octreotide could provide a possible therapeutic approach to the management of certain patients who suffer from colon cancer.

  4. Effects of octreotide and insulin on colon cancer cellular proliferation and correlation with hTERT activity

    Science.gov (United States)

    Ayiomamitis, Georgios D.; Notas, George; Zaravinos, Apostolos; Drygiannakis, Ioannis; Georgiadou, Maria; Sfakianaki, Ourania; Mastrodimou, Niki; Thermos, Kyriaki; Kouroumalis, Elias

    2014-01-01

    Peptide hormone somatostatin and its receptors have a wide range of physiological functions and play a role in the treatment of numerous human diseases, including colorectal cancer. Octreotide, a synthetic somatostatin-analog peptide, inhibits growth of colonic cancer cells primarily by binding to G-protein coupled receptors and elicits cellular responses through second-messenger systems. Insulin also initiates mitogenic signals in certain cell types. The objective of the present study was to explore the effects of octreotide with or without insulin treatment, on Caco-2 and HT-29 human colon-cancer cell proliferation and to correlate their effects with the activation of telomerase reverse transcriptase (hTERT). The involvement of protein tyrosine phosphatases in the regulation of the anti-proliferative effect of octreotide was also evaluated. Sodium orthovanadate was used to reverse the anti- proliferative effect of octreotide. Telomerase activity was determined for each time point under octreotide and/or insulin treatment. Elevated expression of sst1, sst2 and sst5 was confirmed in both cell lines by RT-PCR. Immunocytochemistry detected sst1, sst2A, sst2B, sst3, sst4 and sst5 protein expression in the membranes of both cell lines. Octreotide inhibited the proliferation of Caco-2 and HT-29 cells in a time and dose-dependent manner. Insulin exerted proliferative effects in Caco-2 cells and octreotide reversed its effect in both cell lines. Sodium orthovanadate suppressed the anti-proliferative effect of octreotide both in Caco-2 and HT-29 cells. Telomerase activity was significantly reduced when Caco-2 cells were exposed to octreotide, under serum-free cultured medium. On the other hand, telomerase attenuation after octreotide treatment could not counteract the actions of insulin on both cells. Our data indicate that the use of octreotide could provide a possible therapeutic approach to the management of certain patients who suffer from colon cancer. PMID:25594044

  5. An Urban Cellular Automata Model for Simulating Dynamic States on a Local Scale

    Directory of Open Access Journals (Sweden)

    Jenni Partanen

    2016-12-01

    Full Text Available In complex systems, flexibility and adaptability to changes are crucial to the systems’ dynamic stability and evolution. Such resilience requires that the system is able to respond to disturbances by self-organizing, which implies a certain level of entropy within the system. Dynamic states (static, cyclical/periodic, complex, and chaotic reflect this generative capacity, and correlate with the level of entropy. For planning complex cities, we need to develop methods to guide such autonomous progress in an optimal manner. A classical apparatus, cellular automaton (CA, provides such a tool. Applications of CA help us to study temporal dynamics in self-organizing urban systems. By exploring the dynamic states of the model’s dynamics resulting from different border conditions it is possible to discover favorable set(s of rules conductive to the self-organizing dynamics and enable the system’s recovery at the time of crises. Level of entropy is a relevant measurement for evaluation of these dynamic states. The 2-D urban cellular automaton model studied here is based on the microeconomic principle that similar urban activities are attracted to each other, especially in certain self-organizing areas, and that the local dynamics of these enclaves affect the dynamics of the urban region by channeling flows of information, goods and people. The results of the modeling experiment indicate that the border conditions have a major impact on the model’s dynamics generating various dynamic states of the system. Most importantly, it seemed that the model could simulate a favorable, complex dynamic state with medium entropy level which may refer to the continuous self-organization of the system. The model provides a tool for exploring and understanding the effects of boundary conditions in the planning process as various scenarios are tested: resulting dynamics of the system can be explored with such “planning rules” prior to decisions, helping to

  6. Breast cancer risks and risk prediction models.

    Science.gov (United States)

    Engel, Christoph; Fischer, Christine

    2015-02-01

    BRCA1/2 mutation carriers have a considerably increased risk to develop breast and ovarian cancer. The personalized clinical management of carriers and other at-risk individuals depends on precise knowledge of the cancer risks. In this report, we give an overview of the present literature on empirical cancer risks, and we describe risk prediction models that are currently used for individual risk assessment in clinical practice. Cancer risks show large variability between studies. Breast cancer risks are at 40-87% for BRCA1 mutation carriers and 18-88% for BRCA2 mutation carriers. For ovarian cancer, the risk estimates are in the range of 22-65% for BRCA1 and 10-35% for BRCA2. The contralateral breast cancer risk is high (10-year risk after first cancer 27% for BRCA1 and 19% for BRCA2). Risk prediction models have been proposed to provide more individualized risk prediction, using additional knowledge on family history, mode of inheritance of major genes, and other genetic and non-genetic risk factors. User-friendly software tools have been developed that serve as basis for decision-making in family counseling units. In conclusion, further assessment of cancer risks and model validation is needed, ideally based on prospective cohort studies. To obtain such data, clinical management of carriers and other at-risk individuals should always be accompanied by standardized scientific documentation.

  7. A Nanoflare-Based Cellular Automaton Model and the Observed Properties of the Coronal Plasma

    Science.gov (United States)

    Lopez-Fuentes, Marcelo; Klimchuk, James Andrew

    2016-01-01

    We use the cellular automaton model described in Lopez Fuentes and Klimchuk to study the evolution of coronal loop plasmas. The model, based on the idea of a critical misalignment angle in tangled magnetic fields, produces nanoflares of varying frequency with respect to the plasma cooling time. We compare the results of the model with active region (AR) observations obtained with the Hinode/XRT and SDOAIA instruments. The comparison is based on the statistical properties of synthetic and observed loop light curves. Our results show that the model reproduces the main observational characteristics of the evolution of the plasma in AR coronal loops. The typical intensity fluctuations have amplitudes of 10 percent - 15 percent both for the model and the observations. The sign of the skewness of the intensity distributions indicates the presence of cooling plasma in the loops. We also study the emission measure (EM) distribution predicted by the model and obtain slopes in log(EM) versus log(T) between 2.7 and 4.3, in agreement with published observational values.

  8. Using Cellular Proteins to Reveal Mechanisms of HIV Infection | Center for Cancer Research

    Science.gov (United States)

    A vital step in HIV infection is the insertion of viral DNA into the genome of the host cell. In order for the insertion to occur, viral nucleic acid must be transported through the membrane that separates the main cellular compartment (the cytoplasm) from the nucleus, where the host DNA is located. Scientists are actively studying the mechanism used to transport viral DNA into the nucleus in the hopes of targeting this step with future anti-HIV treatments. Up to this point, researchers have identified some of the viral components that play a role in nuclear transport, but they have not determined how viral interactions with other molecules in the cell contribute to the process.

  9. Multifocality and recurrence risk: a quantitative model of field cancerization.

    Science.gov (United States)

    Foo, Jasmine; Leder, Kevin; Ryser, Marc D

    2014-08-21

    Primary tumors often emerge within genetically altered fields of premalignant cells that appear histologically normal but have a high chance of progression to malignancy. Clinical observations have suggested that these premalignant fields pose high risks for emergence of recurrent tumors if left behind after surgical removal of the primary tumor. In this work, we develop a spatio-temporal stochastic model of epithelial carcinogenesis, combining cellular dynamics with a general framework for multi-stage genetic progression to cancer. Using the model, we investigate how various properties of the premalignant fields depend on microscopic cellular properties of the tissue. In particular, we provide analytic results for the size-distribution of the histologically undetectable premalignant fields at the time of diagnosis, and investigate how the extent and the geometry of these fields depend upon key groups of parameters associated with the tissue and genetic pathways. We also derive analytical results for the relative risks of local vs. distant secondary tumors for different parameter regimes, a critical aspect for the optimal choice of post-operative therapy in carcinoma patients. This study contributes to a growing literature seeking to obtain a quantitative understanding of the spatial dynamics in cancer initiation. Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. Mathematical model of cancer with competition

    Science.gov (United States)

    Chrobak, Joanna M.; Herrero, Henar

    2009-05-01

    In this paper we present a model of tumor based on the use of an autonomous system of ordinary differential equations (ODE). The model assumes that normal cells and cancer cells coexist in an environment as two different species which compete for nutrients and space. The immune system and the tumor cells fight against each other. The analysis of the linear stability of the fixed points of the model yields to two groups of solutions. In the first one, the immune system wins against the tumor cells, so the cancer disappears. In the second one, the cancer grows until some fixed level and then stabilizes.

  11. Distinctive behavioral and cellular responses to fluoxetine in the mouse model for Fragile X syndrome

    Directory of Open Access Journals (Sweden)

    Marko eUutela

    2014-05-01

    Full Text Available Fluoxetine is used as a therapeutic agent for autism spectrum disorder (ASD, including Fragile X syndrome (FXS. The treatment often associates with disruptive behaviors such as agitation and disinhibited behaviors in FXS. To identify mechanisms that increase the risk to poor treatment outcome, we investigated the behavioral and cellular effects of fluoxetine on adult Fmr1 knockout (KO mice, a mouse model for FXS. We found that fluoxetine reduced anxiety-like behavior of both wild type and Fmr1 KO mice seen as shortened latency to enter the center area in the open field test. In Fmr1 KO mice, fluoxetine normalized locomotor hyperactivity but abnormally increased exploratory activity. Reduced Brain-derived neurotrophic factor (BDNF and increased TrkB receptor expression levels in the hippocampus of Fmr1 KO mice associated with inappropriate coping responses under stressful condition and abolished antidepressant activity of fluoxetine. Fluoxetine response in the cell proliferation was also missing in the hippocampus of Fmr1 KO mice when compared with wild type controls. The postnatal expression of serotonin transporter was reduced in the thalamic nuclei of Fmr1 KO mice during the time of transient innervation of somatosensory neurons suggesting that developmental changes of serotonin transporter (SERT expression were involved in the differential cellular and behavioral responses to fluoxetine in wild type and Fmr1 mice. The results indicate that changes of BDNF/TrkB signaling contribute to differential behavioral responses to fluoxetine among individuals with ASD.

  12. Particle-based membrane model for mesoscopic simulation of cellular dynamics

    Science.gov (United States)

    Sadeghi, Mohsen; Weikl, Thomas R.; Noé, Frank

    2018-01-01

    We present a simple and computationally efficient coarse-grained and solvent-free model for simulating lipid bilayer membranes. In order to be used in concert with particle-based reaction-diffusion simulations, the model is purely based on interacting and reacting particles, each representing a coarse patch of a lipid monolayer. Particle interactions include nearest-neighbor bond-stretching and angle-bending and are parameterized so as to reproduce the local membrane mechanics given by the Helfrich energy density over a range of relevant curvatures. In-plane fluidity is implemented with Monte Carlo bond-flipping moves. The physical accuracy of the model is verified by five tests: (i) Power spectrum analysis of equilibrium thermal undulations is used to verify that the particle-based representation correctly captures the dynamics predicted by the continuum model of fluid membranes. (ii) It is verified that the input bending stiffness, against which the potential parameters are optimized, is accurately recovered. (iii) Isothermal area compressibility modulus of the membrane is calculated and is shown to be tunable to reproduce available values for different lipid bilayers, independent of the bending rigidity. (iv) Simulation of two-dimensional shear flow under a gravity force is employed to measure the effective in-plane viscosity of the membrane model and show the possibility of modeling membranes with specified viscosities. (v) Interaction of the bilayer membrane with a spherical nanoparticle is modeled as a test case for large membrane deformations and budding involved in cellular processes such as endocytosis. The results are shown to coincide well with the predicted behavior of continuum models, and the membrane model successfully mimics the expected budding behavior. We expect our model to be of high practical usability for ultra coarse-grained molecular dynamics or particle-based reaction-diffusion simulations of biological systems.

  13. Preventing clonal evolutionary processes in cancer: Insights from mathematical models.

    Science.gov (United States)

    Rodriguez-Brenes, Ignacio A; Wodarz, Dominik

    2015-07-21

    Clonal evolutionary processes can drive pathogenesis in human diseases, with cancer being a prominent example. To prevent or treat cancer, mechanisms that can potentially interfere with clonal evolutionary processes need to be understood better. Mathematical modeling is an important research tool that plays an ever-increasing role in cancer research. This paper discusses how mathematical models can be useful to gain insights into mechanisms that can prevent disease initiation, help analyze treatment responses, and aid in the design of treatment strategies to combat the emergence of drug-resistant cells. The discussion will be done in the context of specific examples. Among defense mechanisms, we explore how replicative limits and cellular senescence induced by telomere shortening can influence the emergence and evolution of tumors. Among treatment approaches, we consider the targeted treatment of chronic lymphocytic leukemia (CLL) with tyrosine kinase inhibitors. We illustrate how basic evolutionary mathematical models have the potential to make patient-specific predictions about disease and treatment outcome, and argue that evolutionary models could become important clinical tools in the field of personalized medicine.

  14. Logistic regression and cellular automata-based modelling of retail, commercial and residential development in the city of Ahmedabad, India

    NARCIS (Netherlands)

    Munshi, T.; Zuidgeest, M.H.P.; Brussel, M.J.G.; van Maarseveen, M.F.A.M.

    2014-01-01

    This study presents a hybrid simulation model that combines logistic regression and cellular automata-based modelling to simulate future urban growth and development for the city of Ahmedabad in India. The model enables to visualize the consequence of development projections in combination with

  15. Genome scale metabolic modeling of cancer

    DEFF Research Database (Denmark)

    Nilsson, Avlant; Nielsen, Jens

    2017-01-01

    Cancer cells reprogram metabolism to support rapid proliferation and survival. Energy metabolism is particularly important for growth and genes encoding enzymes involved in energy metabolism are frequently altered in cancer cells. A genome scale metabolic model (GEM) is a mathematical formalization...... of metabolism which allows simulation and hypotheses testing of metabolic strategies. It has successfully been applied to many microorganisms and is now used to study cancer metabolism. Generic models of human metabolism have been reconstructed based on the existence of metabolic genes in the human genome....... Cancer specific models of metabolism have also been generated by reducing the number of reactions in the generic model based on high throughput expression data, e.g. transcriptomics and proteomics. Targets for drugs and bio markers for diagnostics have been identified using these models. They have also...

  16. Genetically engineered mouse models of prostate cancer

    NARCIS (Netherlands)

    Nawijn, Martijn C.; Bergman, Andreas M.; van der Poel, Henk G.

    Objectives: Mouse models of prostate cancer are used to test the contribution of individual genes to the transformation process, evaluate the collaboration between multiple genetic lesions observed in a single tumour, and perform preclinical intervention studies in prostate cancer research. Methods:

  17. A Model for Counselling Cancer Patients.

    Science.gov (United States)

    Jevne, Ronna F.; Nekolaichuk, Cheryl L.; Williamson, F. Helen A.

    1998-01-01

    Describes a model for counseling cancer patients that integrates the unique features of the cancer experience within a basic counseling framework. It combines a nine-step problem-solving approach with a biopsychosocial perspective, placing greater emphasis on the person than the problem. Utilizes innovative questioning techniques and strategies.…

  18. Analysis of individual cell trajectories in lattice-gas cellular automaton models for migrating cell populations.

    Science.gov (United States)

    Mente, Carsten; Voss-Böhme, Anja; Deutsch, Andreas

    2015-04-01

    Collective dynamics of migrating cell populations drive key processes in tissue formation and maintenance under normal and diseased conditions. Collective cell behavior at the tissue level is typically characterized by considering cell density patterns such as clusters and moving cell fronts. However, there are also important observables of collective dynamics related to individual cell behavior. In particular, individual cell trajectories are footprints of emergent behavior in populations of migrating cells. Lattice-gas cellular automata (LGCA) have proven successful to model and analyze collective behavior arising from interactions of migrating cells. There are well-established methods to analyze cell density patterns in LGCA models. Although LGCA dynamics are defined by cell-based rules, individual cells are not distinguished. Therefore, individual cell trajectories cannot be analyzed in LGCA so far. Here, we extend the classical LGCA framework to allow labeling and tracking of individual cells. We consider cell number conserving LGCA models of migrating cell populations where cell interactions are regulated by local cell density and derive stochastic differential equations approximating individual cell trajectories in LGCA. This result allows the prediction of complex individual cell trajectories emerging in LGCA models and is a basis for model-experiment comparisons at the individual cell level.

  19. On the Geometric Modeling of the Uplink Channel in a Cellular System

    Directory of Open Access Journals (Sweden)

    K. B. Baltzis

    2008-01-01

    Full Text Available To meet the challenges of present and future wireless communications realistic propagation models that consider both spatial and temporal channel characteristics are used. However, the complexity of the complete characterization of the wireless medium has pointed out the importance of approximate but simple approaches. The geometrically based methods are typical examples of low–complexity but adequate solutions. Geometric modeling idealizes the aforementioned wireless propagation environment via a geometric abstraction of the spatial relationships among the transmitter, the receiver, and the scatterers. The paper tries to present an efficient way to simulate mobile channels using geometrical–based stochastic scattering models. In parallel with an overview of the most commonly used propagation models, the basic principles of the method as well the main assumptions made are presented. The study is focused on three well–known proposals used for the description of the Angle–of –Arrival and Time–of–Arrival statistics of the incoming multipaths in the uplink of a cellular communication system. In order to demonstrate the characteristics of these models illustrative examples are given. The physical mechanism and motivations behind them are also included providing us with a better understanding of the physical insight of the propagation medium.

  20. Estimation of the spatiotemporal dynamics of snow covered area by using cellular automata models

    Science.gov (United States)

    Pardo-Igúzquiza, Eulogio; Collados-Lara, Antonio-Juan; Pulido-Velazquez, David

    2017-07-01

    Given the need to consider the cryosphere in water resources management for mountainous regions, the purpose of this paper is to model the daily spatially distributed dynamics of snow covered area (SCA) by using calibrated cellular automata models. For the operational use of the calibrated model, the only data requirements are the altitude of each cell of the spatial discretization of the area of interest and precipitation and temperature indexes for the area of interest. For the calibration step, experimental snow covered area data are needed. Potential uses of the model are to estimate the snow covered area when satellite data are absent, or when they provide a temporal resolution different from the operational resolution, or when the satellite images are useless because they are covered by clouds or because there has been a sensor failure. Another interesting application is the simulation of SCA dynamics for the snow covered area under future climatic scenarios. The model is applied to the Sierra Nevada mountain range, in southern Spain, which is home to significant biodiversity, contains important water resources in its snowpack, and contains the most meridional ski resort in Europe.

  1. Modeling urban land use changes in Lanzhou based on artificial neural network and cellular automata

    Science.gov (United States)

    Xu, Xibao; Zhang, Jianming; Zhou, Xiaojian

    2008-10-01

    This paper presented a model to simulate urban land use changes based on artificial neural network (ANN) and cellular automata (CA). The model was scaled down at the intra-urban level with subtle land use categorization, developed with Matlab 7.2 and loosely coupled with GIS. Urban land use system is a very complicated non-linear social system influenced by many factors. In this paper, four aspects of a totality 17 factors, including physical, social-economic, neighborhoods and policy, were considered synthetically. ANN was proposed as a solution of CA model calibration through its training to acquire the multitudinous parameters as a substitute for the complex transition rules. A stochastic perturbation parameter v was added into the model, and five different scenarios with different values of v and the threshold were designed for simulations and predictions to explore their effects on urban land use changes. Simulations of 2005 and predictions of 2015 under the five different scenarios were made and evaluated. Finally, the advantages and disadvantages of the model were discussed.

  2. TWO-DIMENSIONAL CELLULAR AUTOMATON MODEL FOR THE EVOLUTION OF ACTIVE REGION CORONAL PLASMAS

    Energy Technology Data Exchange (ETDEWEB)

    López Fuentes, Marcelo [Instituto de Astronomía y Física del Espacio, CONICET-UBA, CC. 67, Suc. 28, 1428 Buenos Aires (Argentina); Klimchuk, James A., E-mail: lopezf@iafe.uba.ar [NASA Goddard Space Flight Center, Code 671, Greenbelt, MD 20771 (United States)

    2015-02-01

    We study a two-dimensional cellular automaton (CA) model for the evolution of coronal loop plasmas. The model is based on the idea that coronal loops are made of elementary magnetic strands that are tangled and stressed by the displacement of their footpoints by photospheric motions. The magnetic stress accumulated between neighbor strands is released in sudden reconnection events or nanoflares that heat the plasma. We combine the CA model with the Enthalpy Based Thermal Evolution of Loops model to compute the response of the plasma to the heating events. Using the known response of the X-Ray Telescope on board Hinode, we also obtain synthetic data. The model obeys easy-to-understand scaling laws relating the output (nanoflare energy, temperature, density, intensity) to the input parameters (field strength, strand length, critical misalignment angle). The nanoflares have a power-law distribution with a universal slope of –2.5, independent of the input parameters. The repetition frequency of nanoflares, expressed in terms of the plasma cooling time, increases with strand length. We discuss the implications of our results for the problem of heating and evolution of active region coronal plasmas.

  3. Cancer Metabolism: A Modeling Perspective

    DEFF Research Database (Denmark)

    Ghaffari, Pouyan; Mardinoglu, Adil; Nielsen, Jens

    2015-01-01

    Tumor cells alter their metabolism to maintain unregulated cellular proliferation and survival, but this transformation leaves them reliant on constant supply of nutrients and energy. In addition to the widely studied dysregulated glucose metabolism to fuel tumor cell growth, accumulating evidenc...

  4. Cucurbitacin B exerts anti-cancer activities in human multiple myeloma cells in vitro and in vivo by modulating multiple cellular pathways

    Science.gov (United States)

    Huang, Ning; Zhong, Yueling; Zeng, Ting; Wei, Rong; Wu, Zhongjun; Xiao, Cui; Cao, Xiaohua; Li, Minhui; Li, Limei; Han, Bin; Yu, Xiaoping; Li, Hua; Zou, Qiang

    2017-01-01

    Cucurbitacin B (CuB), a triterpenoid compound isolated from the stems of Cucumis melo, has long been used to treat hepatitis and hepatoma in China. Although its remarkable anti-cancer activities have been reported, the mechanism by which it achieves this therapeutic activity remains unclear. This study was designed to investigate the molecular mechanisms by which CuB inhibits cancer cell proliferation. Our results indicate that CuB is a novel inhibitor of Aurora A in multiple myeloma (MM) cells, arresting cells in the G2/M phase. CuB also inhibited IL-10-induced STAT3 phosphorylation, synergistically increasing the anti-tumor activity of Adriamycin in vitro. CuB induced dephosphorylation of cofilin, resulting in the loss of mitochondrial membrane potential, release of cytochrome c, and activation of caspase-8. CuB inhibited MM tumor growth in a murine MM model, without host toxicity. In conclusion, these results indicate that CuB interferes with multiple cellular pathways in MM cells. CuB thus represents a promising therapeutic tool for the treatment of MM. PMID:27418139

  5. Modeling Alexander disease with patient iPSCs reveals cellular and molecular pathology of astrocytes.

    Science.gov (United States)

    Kondo, Takayuki; Funayama, Misato; Miyake, Michiyo; Tsukita, Kayoko; Era, Takumi; Osaka, Hitoshi; Ayaki, Takashi; Takahashi, Ryosuke; Inoue, Haruhisa

    2016-07-11

    Alexander disease is a fatal neurological illness characterized by white-matter degeneration and formation of Rosenthal fibers, which contain glial fibrillary acidic protein as astrocytic inclusion. Alexander disease is mainly caused by a gene mutation encoding glial fibrillary acidic protein, although the underlying pathomechanism remains unclear. We established induced pluripotent stem cells from Alexander disease patients, and differentiated induced pluripotent stem cells into astrocytes. Alexander disease patient astrocytes exhibited Rosenthal fiber-like structures, a key Alexander disease pathology, and increased inflammatory cytokine release compared to healthy control. These results suggested that Alexander disease astrocytes contribute to leukodystrophy and a variety of symptoms as an inflammatory source in the Alexander disease patient brain. Astrocytes, differentiated from induced pluripotent stem cells of Alexander disease, could be a cellular model for future translational medicine.

  6. Molecular modeling of the conformational dynamics of the cellular prion protein

    Science.gov (United States)

    Nguyen, Charles; Colling, Ian; Bartz, Jason; Soto, Patricia

    2014-03-01

    Prions are infectious agents responsible for transmissible spongiform encephalopathies (TSEs), a type of fatal neurodegenerative disease in mammals. Prions propagate biological information by conversion of the non-pathological version of the prion protein to the infectious conformation, PrPSc. A wealth of knowledge has shed light on the nature and mechanism of prion protein conversion. In spite of the significance of this problem, we are far from fully understanding the conformational dynamics of the cellular isoform. To remedy this situation we employ multiple biomolecular modeling techniques such as docking and molecular dynamics simulations to map the free energy landscape and determine what specific regions of the prion protein are most conductive to binding. The overall goal is to characterize the conformational dynamics of the cell form of the prion protein, PrPc, to gain insight into inhibition pathways against misfolding. NE EPSCoR FIRST Award to Patricia Soto.

  7. Phase transition in the economically modeled growth of a cellular nervous system

    CERN Document Server

    Nicosia, Vincenzo; Schafer, William R; Latora, Vito; Bullmore, Edward T; 10.1073/pnas.1300753110

    2013-01-01

    Spatially-embedded complex networks, such as nervous systems, the Internet and transportation networks, generally have non-trivial topological patterns of connections combined with nearly minimal wiring costs. However the growth rules shaping these economical trade-offs between cost and topology are not well understood. Here we study the cellular nervous system of the nematode worm C. elegans, together with information on the birth times of neurons and on their spatial locations. We find that the growth of this network undergoes a transition from an accelerated to a constant increase in the number of links (synaptic connections) as a function of the number of nodes (neurons). The time of this phase transition coincides closely with the observed moment of hatching, when development switches metamorphically from oval to larval stages. We use graph analysis and generative modelling to show that the transition between different growth regimes, as well as its coincidence with the moment of hatching, can be explain...

  8. Evaluation of toxicity of two pesticides: flucycloxuron and diflubenzuron on a cellular model, Paramecium sp.

    Science.gov (United States)

    Rouabhi, R; Berrebbah, H; Djebar, M R

    2006-01-01

    The effect of two pesticides, the diflubenzuron (DFB) and the Flucycloxuron (FCX) has been studied on a cellular model: Paramecium sp., a ciliated protiste. The treatment with the DFB in the concentrations of 10 and 20 microg/ml reduces the growth of this protiste appreciably. The survey of the respiratory metabolism by the polarography technique (Oxygen electrode) shows a sensitive inhibition of the oxygen consumption by the studied protiste. In the case of the FCX, the treatment with the two concentrations (10 and 20 microg/ml) reveals an inhibition of the ciliated protiste growth; however, this pesticide inhibits the respiratory metabolism of ciliated protiste. This effect is a lot more marked with the FCX that with the DFB. The coloration with neutral red showed a perturbation in cuticle level, translated by the penetration quantity of the color in treated cells, especially at 20 microg/ml of FCX.

  9. Electoral surveys’ influence on the voting processes: a cellular automata model

    Science.gov (United States)

    Alves, S. G.; Oliveira Neto, N. M.; Martins, M. L.

    2002-12-01

    Nowadays, in societies threatened by atomization, selfishness, short-term thinking, and alienation from political life, there is a renewed debate about classical questions concerning the quality of democratic decision making. In this work a cellular automata model for the dynamics of free elections, based on the social impact theory is proposed. By using computer simulations, power-law distributions for the size of electoral clusters and decision time have been obtained. The major role of broadcasted electoral surveys in guiding opinion formation and stabilizing the “status quo” was demonstrated. Furthermore, it was shown that in societies where these surveys are manipulated within the universally accepted statistical error bars, even a majoritary opposition could be hindered from reaching power through the electoral path.

  10. A Cellular Automaton / Finite Element model for predicting grain texture development in galvanized coatings

    Science.gov (United States)

    Guillemot, G.; Avettand-Fènoël, M.-N.; Iosta, A.; Foct, J.

    2011-01-01

    Hot-dipping galvanizing process is a widely used and efficient way to protect steel from corrosion. We propose to master the microstructure of zinc grains by investigating the relevant process parameters. In order to improve the texture of this coating, we model grain nucleation and growth processes and simulate the zinc solid phase development. A coupling scheme model has been applied with this aim. This model improves a previous two-dimensional model of the solidification process. It couples a cellular automaton (CA) approach and a finite element (FE) method. CA grid and FE mesh are superimposed on the same domain. The grain development is simulated at the micro-scale based on the CA grid. A nucleation law is defined using a Gaussian probability and a random set of nucleating cells. A crystallographic orientation is defined for each one with a choice of Euler's angle (Ψ,θ,φ). A small growing shape is then associated to each cell in the mushy domain and a dendrite tip kinetics is defined using the model of Kurz [2]. The six directions of basal plane and the two perpendicular directions develop in each mushy cell. During each time step, cell temperature and solid fraction are then determined at micro-scale using the enthalpy conservation relation and variations are reassigned at macro-scale. This coupling scheme model enables to simulate the three-dimensional growing kinetics of the zinc grain in a two-dimensional approach. Grain structure evolutions for various cooling times have been simulated. Final grain structure has been compared to EBSD measurements. We show that the preferentially growth of dendrite arms in the basal plane of zinc grains is correctly predicted. The described coupling scheme model could be applied for simulated other product or manufacturing processes. It constitutes an approach gathering both micro and macro scale models.

  11. Mathematical Models of Breast and Ovarian Cancers

    Science.gov (United States)

    Botesteanu, Dana-Adriana; Lipkowitz, Stanley; Lee, Jung-Min; Levy, Doron

    2016-01-01

    Women constitute the majority of the aging United States (US) population, and this has substantial implications on cancer population patterns and management practices. Breast cancer is the most common women's malignancy, while ovarian cancer is the most fatal gynecological malignancy in the US. In this review we focus on these subsets of women's cancers, seen more commonly in postmenopausal and elderly women. In order to systematically investigate the complexity of cancer progression and response to treatment in breast and ovarian malignancies, we assert that integrated mathematical modeling frameworks viewed from a systems biology perspective are needed. Such integrated frameworks could offer innovative contributions to the clinical women's cancers community, since answers to clinical questions cannot always be reached with contemporary clinical and experimental tools. Here, we recapitulate clinically known data regarding the progression and treatment of the breast and ovarian cancers. We compare and contrast the two malignancies whenever possible, in order to emphasize areas where substantial contributions could be made by clinically inspired and validated mathematical modeling. We show how current paradigms in the mathematical oncology community focusing on the two malignancies do not make comprehensive use of, nor substantially reflect existing clinical data, and we highlight the modeling areas in most critical need of clinical data integration. We emphasize that the primary goal of any mathematical study of women's cancers should be to address clinically relevant questions. PMID:27259061

  12. Correlation of particle properties with cytotoxicity and cellular uptake of hydroxyapatite nanoparticles in human gastric cancer cells

    Energy Technology Data Exchange (ETDEWEB)

    Cui, Xinhui [State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai 200237 (China); Liang, Tong [Engineering Research Center for Biomedical Materials of Ministry of Education, East China University of Science and Technology, Shanghai 200237 (China); Liu, Changsheng [State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai 200237 (China); Engineering Research Center for Biomedical Materials of Ministry of Education, East China University of Science and Technology, Shanghai 200237 (China); Yuan, Yuan, E-mail: yyuan@ecust.edu.cn [Engineering Research Center for Biomedical Materials of Ministry of Education, East China University of Science and Technology, Shanghai 200237 (China); Qian, Jiangchao, E-mail: jiangchaoqian@ecust.edu.cn [State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai 200237 (China)

    2016-10-01

    Three types of hydroxyapatite nanoparticles (HAPNs) were synthesized employing a sonochemistry-assisted microwave method by changing microwave power (from 200 to 300 W) or using calcination treatment: L200 (200 W, lyophilization), L300 (300 W, lyophilization) and C200 (200 W, lyophilization & calcination). Their physiochemical properties were characterized and correlated with cytotoxicity to human gastric cancer cells (MGC80-3). The major differences among these HAPN preparations were their size and specific surface area, with the L200 showing a smaller size and higher specific surface area. Although all HAPNs inhibited cell proliferation and induced apoptosis of cancer cells, L200 exhibited the greatest toxicity. All types of HAPNs were internalized through energy-dependent pathways, but the L200 nanoparticles were more efficiently uptaken by MGC80-3 cells. Inhibitor studies with dynasore and methyl-β-cyclodextrin suggested that caveolae-mediated endocytosis and, to a much lesser extent, clathrin-mediated endocytosis, were involved in cellular uptake of the various preparations, whereas the inhibition of endocytosis was more obvious for L200. Using fluorescein isothiocyanate-labeled HAPNs and laser-scanning confocal microscopy, we found that all forms of nanoparticles were present in the cytoplasm, and some L200 HAPNs were even found within nuclei. Treatment with all HAPN preparations led to the increase in the intracellular calcium level with the highest level detected for L200. - Highlights: • Three types of HAPNs (L200, L300 and C200) were synthesized employing a sonochemistry-assisted microwave method. • L200 exhibited the greatest cytotoxicity to human gastric cancer (MGC80-3) cells. • L200 showed a smaller size and higher specific surface area. • The L200 nanoparticles were more efficiently uptaken by MGC80-3 cells through energy-dependent pathways. • L200 caused the most significant increase in the intracellular calcium level.

  13. Orientation selection of equiaxed dendritic growth by three-dimensional cellular automaton model

    Energy Technology Data Exchange (ETDEWEB)

    Wei Lei [State Key Laboratory of Solidification Processing, Northwestern Polytechnical University, Xi' an 710072 (China); Lin Xin, E-mail: xlin@nwpu.edu.cn [State Key Laboratory of Solidification Processing, Northwestern Polytechnical University, Xi' an 710072 (China); Wang Meng; Huang Weidong [State Key Laboratory of Solidification Processing, Northwestern Polytechnical University, Xi' an 710072 (China)

    2012-07-01

    A three-dimensional (3-D) adaptive mesh refinement (AMR) cellular automata (CA) model is developed to simulate the equiaxed dendritic growth of pure substance. In order to reduce the mesh induced anisotropy by CA capture rules, a limited neighbor solid fraction (LNSF) method is presented. It is shown that the LNSF method reduced the mesh induced anisotropy based on the simulated morphologies for isotropic interface free energy. An expansion description using two interface free energy anisotropy parameters ({epsilon}{sub 1}, {epsilon}{sub 2}) is used in the present 3-D CA model. It is illustrated by present 3-D CA model that the positive {epsilon}{sub 1} favors the dendritic growth with the Left-Pointing-Angle-Bracket 100 Right-Pointing-Angle-Bracket preferred directions, and negative {epsilon}{sub 2} favors dendritic growth with the Left-Pointing-Angle-Bracket 110 Right-Pointing-Angle-Bracket preferred directions, which has a good agreement with the prediction of the spherical plot of the inverse of the interfacial stiffness. The dendritic growths with the orientation selection between Left-Pointing-Angle-Bracket 100 Right-Pointing-Angle-Bracket and Left-Pointing-Angle-Bracket 110 Right-Pointing-Angle-Bracket are also discussed using the different {epsilon}{sub 1} with {epsilon}{sub 2}=-0.02. It is found that the simulated morphologies by present CA model are as expected from the minimum stiffness criterion.

  14. An Integrative Model of the Cardiovascular System Coupling Heart Cellular Mechanics with Arterial Network Hemodynamics

    Science.gov (United States)

    Kim, Young-Tae; Lee, Jeong Sang; Youn, Chan-Hyun; Choi, Jae-Sung

    2013-01-01

    The current study proposes a model of the cardiovascular system that couples heart cell mechanics with arterial hemodynamics to examine the physiological role of arterial blood pressure (BP) in left ventricular hypertrophy (LVH). We developed a comprehensive multiphysics and multiscale cardiovascular model of the cardiovascular system that simulates physiological events, from membrane excitation and the contraction of a cardiac cell to heart mechanics and arterial blood hemodynamics. Using this model, we delineated the relationship between arterial BP or pulse wave velocity and LVH. Computed results were compared with existing clinical and experimental observations. To investigate the relationship between arterial hemodynamics and LVH, we performed a parametric study based on arterial wall stiffness, which was obtained in the model. Peak cellular stress of the left ventricle and systolic blood pressure (SBP) in the brachial and central arteries also increased; however, further increases were limited for higher arterial stiffness values. Interestingly, when we doubled the value of arterial stiffness from the baseline value, the percentage increase of SBP in the central artery was about 6.7% whereas that of the brachial artery was about 3.4%. It is suggested that SBP in the central artery is more critical for predicting LVH as compared with other blood pressure measurements. PMID:23960442

  15. Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion

    Science.gov (United States)

    Jokar Arsanjani, Jamal; Helbich, Marco; Kainz, Wolfgang; Darvishi Boloorani, Ali

    2013-04-01

    This research analyses the suburban expansion in the metropolitan area of Tehran, Iran. A hybrid model consisting of logistic regression model, Markov chain (MC), and cellular automata (CA) was designed to improve the performance of the standard logistic regression model. Environmental and socio-economic variables dealing with urban sprawl were operationalised to create a probability surface of spatiotemporal states of built-up land use for the years 2006, 2016, and 2026. For validation, the model was evaluated by means of relative operating characteristic values for different sets of variables. The approach was calibrated for 2006 by cross comparing of actual and simulated land use maps. The achieved outcomes represent a match of 89% between simulated and actual maps of 2006, which was satisfactory to approve the calibration process. Thereafter, the calibrated hybrid approach was implemented for forthcoming years. Finally, future land use maps for 2016 and 2026 were predicted by means of this hybrid approach. The simulated maps illustrate a new wave of suburban development in the vicinity of Tehran at the western border of the metropolis during the next decades.

  16. Traffic Control Models Based on Cellular Automata for At-Grade Intersections in Autonomous Vehicle Environment

    Directory of Open Access Journals (Sweden)

    Wei Wu

    2017-01-01

    Full Text Available Autonomous vehicle is able to facilitate road safety and traffic efficiency and has become a promising trend of future development. With a focus on highways, existing literatures studied the feasibility of autonomous vehicle in continuous traffic flows and the controllability of cooperative driving. However, rare efforts have been made to investigate the traffic control strategies in autonomous vehicle environment on urban roads, especially in urban intersections. In autonomous vehicle environment, it is possible to achieve cooperative driving with V2V and V2I wireless communication. Without signal control, conflicted traffic flows could pass intersections through mutual cooperative, which is a remarkable improvement to existing traffic control methods. This paper established a cellular automata model with greedy algorithm for the traffic control of intersections in autonomous vehicle environment, with autonomous vehicle platoon as the optimization object. NetLogo multiagent simulation platform model was employed to simulate the proposed model. The simulation results are compared with the traffic control programs in conventional Synchro optimization. The findings suggest that, on the premises of ensuring traffic safety, the control strategy of the proposed model significantly reduces average delays and number of stops as well as increasing traffic capacity.

  17. An integrative model of the cardiovascular system coupling heart cellular mechanics with arterial network hemodynamics.

    Science.gov (United States)

    Kim, Young-Tae; Lee, Jeong Sang; Youn, Chan-Hyun; Choi, Jae-Sung; Shim, Eun Bo

    2013-08-01

    The current study proposes a model of the cardiovascular system that couples heart cell mechanics with arterial hemodynamics to examine the physiological role of arterial blood pressure (BP) in left ventricular hypertrophy (LVH). We developed a comprehensive multiphysics and multiscale cardiovascular model of the cardiovascular system that simulates physiological events, from membrane excitation and the contraction of a cardiac cell to heart mechanics and arterial blood hemodynamics. Using this model, we delineated the relationship between arterial BP or pulse wave velocity and LVH. Computed results were compared with existing clinical and experimental observations. To investigate the relationship between arterial hemodynamics and LVH, we performed a parametric study based on arterial wall stiffness, which was obtained in the model. Peak cellular stress of the left ventricle and systolic blood pressure (SBP) in the brachial and central arteries also increased; however, further increases were limited for higher arterial stiffness values. Interestingly, when we doubled the value of arterial stiffness from the baseline value, the percentage increase of SBP in the central artery was about 6.7% whereas that of the brachial artery was about 3.4%. It is suggested that SBP in the central artery is more critical for predicting LVH as compared with other blood pressure measurements.

  18. The role of topography in the scaling distribution of landslide areas: A cellular automata modeling approach

    Science.gov (United States)

    Liucci, Luisa; Melelli, Laura; Suteanu, Cristian; Ponziani, Francesco

    2017-08-01

    Power law scaling has been widely observed in the frequency distribution of landslide sizes. The exponent of the power-law characterizes the probability of landslide magnitudes and it thus represents an important parameter for hazard assessment. The reason for the universal scaling behavior of landslides is still debated and the role of topography has been explored in terms of possible explanation for this type of behavior. We built a simple cellular automata model to investigate this issue, as well as the relationships between the scaling properties of landslide areas and the changes suffered by the topographic surface affected by landslides. The dynamics of the model is controlled by a temporal rate of weakening, which drives the system to instability, and by topography, which defines both the quantity of the displaced mass and the direction of the movement. Results show that the model is capable of reproducing the scaling behavior of real landslide areas and suggest that topography is a good candidate to explain their scale-invariance. In the model, the values of the scaling exponents depend on how fast the system is driven to instability; they are less sensitive to the duration of the driving rate, thus suggesting that the probability of landslide areas could depend on the intensity of the triggering mechanism rather than on its duration, and on the topographic setting of the area. Topography preserves the information concerning the statistical distribution of areas of landslides caused by a driving mechanism of given intensity and duration.

  19. Effectiveness of aromatherapy with light thai massage for cellular immunity improvement in colorectal cancer patients receiving chemotherapy.

    Science.gov (United States)

    Khiewkhern, Santisith; Promthet, Supannee; Sukprasert, Aemkhea; Eunhpinitpong, Wichai; Bradshaw, Peter

    2013-01-01

    Patients with colorectal cancer are usually treated with chemotherapy, which reduces the number of blood cells, especially white blood cells, and consequently increases the risk of infections. Some research studies have reported that aromatherapy massage affects the immune system and improves immune function by, for example, increasing the numbers of natural killer cells and peripheral blood lymphocytes. However, there has been no report of any study which provided good evidence as to whether aromatherapy with Thai massage could improve the immune system in patients with colorectal cancer. The objectives of this study were to determine whether the use of aromatherapy with light Thai massage in patients with colorectal cancer, who have received chemotherapy, can result in improvement of the cellular immunity and reduce the severity of the common symptoms of side effects. Sixty-six patients with colorectal cancer in Phichit Hospital, Thailand, were enrolled in a single-blind, randomised-controlled trial. The intervention consisted of three massage sessions with ginger and coconut oil over a 1-week period. The control group received standard supportive care only. Assessments were conducted at pre-assessment and at the end of one week of massage or standard care. Changes from pre-assessment to the end of treatment were measured in terms of white blood cells, neutrophils, lymphocytes, CD4 and CD8 cells and the CD4/CD8 ratio and also the severity of self-rated symptom scores. The main finding was that after adjusting for pre-assessment values the mean lymphocyte count at the post-assessment was significantly higher (P=0.04) in the treatment group than in the controls. The size of this difference suggested that aromatherapy with Thai massage could boost lymphocyte numbers by 11%. The secondary outcomes were that at the post assessment the symptom severity scores for fatigue, presenting symptom, pain and stress were significantly lower in the massage group than in the

  20. Lipid Replacement Therapy: a Functional Food Approach with New Formulations for Reducing Cellular Oxidative Damage, Cancer-Associated Fatigue and the Adverse Effects of Cancer Therapy

    Directory of Open Access Journals (Sweden)

    Garth L. Nicolson

    2011-04-01

    Full Text Available Backgroud:Cancer-associated fatigue and the chronic adverse effects of cancer therapy can be reduced by Lipid Replacement Therapy (LRT using membrane phospholipid mixtures given as food supplements.Methods:This is a review of the published literature on LRT and its uses.Results: LRT significantly reduced fatigue in cancer patients as well as patients suffering from chronic fatiguing illnesses and other medical conditions. It also reduced the adverse effects of chemotherapy, resulting in improvements in incidence of fatigue, nausea, diarrhea, impaired taste, constipation, insomnia and other quality of life indicators. In other diseases, such as chronic fatigue syndrome, fibromyalgia syndrome and other chronic fatiguing illnesses, LRT reduced fatigue by 35.5-43.1% in different clinical trials and increased mitochondrial function.Conclusions: LRT formulations appear to be useful as non-toxic dietary supplements for direct use or placed in functional foods to reduce fatigue and restore mitochondrial and other cellular membrane functions. Formulations of LRT phospholipids are suitable for addition to variousfood products for the treatment of a variety of chronic illnesses as well as their application inanti-aging and other health supplements and products.

  1. Drug discovery in prostate cancer mouse models.

    Science.gov (United States)

    Valkenburg, Kenneth C; Pienta, Kenneth J

    2015-01-01

    The mouse is an important, though imperfect, organism with which to model human disease and to discover and test novel drugs in a preclinical setting. Many experimental strategies have been used to discover new biological and molecular targets in the mouse, with the hopes of translating these discoveries into novel drugs to treat prostate cancer in humans. Modeling prostate cancer in the mouse, however, has been challenging, and often drugs that work in mice have failed in human trials. The authors discuss the similarities and differences between mice and men; the types of mouse models that exist to model prostate cancer; practical questions one must ask when using a mouse as a model; and potential reasons that drugs do not often translate to humans. They also discuss the current value in using mouse models for drug discovery to treat prostate cancer and what needs are still unmet in field. With proper planning and following practical guidelines by the researcher, the mouse is a powerful experimental tool. The field lacks genetically engineered metastatic models, and xenograft models do not allow for the study of the immune system during the metastatic process. There remain several important limitations to discovering and testing novel drugs in mice for eventual human use, but these can often be overcome. Overall, mouse modeling is an essential part of prostate cancer research and drug discovery. Emerging technologies and better and ever-increasing forms of communication are moving the field in a hopeful direction.

  2. How students learn to coordinate knowledge of physical and mathematical models in cellular physiology

    Science.gov (United States)

    Lira, Matthew

    This dissertation explores the Knowledge in Pieces (KiP) theory to account for how students learn to coordinate knowledge of mathematical and physical models in biology education. The KiP approach characterizes student knowledge as a fragmented collection of knowledge elements as opposed to stable and theory-like knowledge. This dissertation sought to use this theoretical lens to account for how students understand and learn with mathematical models and representations, such as equations. Cellular physiology provides a quantified discipline that leverages concepts from mathematics, physics, and chemistry to understand cellular functioning. Therefore, this discipline provides an exemplary context for assessing how biology students think and learn with mathematical models. In particular, the resting membrane potential provides an exemplary concept well defined by models of dynamic equilibrium borrowed from physics and chemistry. In brief, membrane potentials, or voltages, "rest" when the electrical and chemical driving forces for permeable ionic species are equal in magnitude but opposite in direction. To assess students' understandings of this concept, this dissertation employed three studies: the first study employed the cognitive clinical interview to assess student thinking in the absence and presence of equations. The second study employed an intervention to assess student learning and the affordances of an innovative assessment. The third student employed a human-computer-interaction paradigm to assess how students learn with a novel multi-representational technology. Study 1 revealed that students saw only one influence--the chemical gradient--and that students coordinated knowledge of only this gradient with the related equations. Study 2 revealed that students benefited from learning with the multi-representational technology and that the assessment detected performance gains across both calculation and explanation tasks. Last, Study 3 revealed how students

  3. Large-scale parallel lattice Boltzmann-cellular automaton model of two-dimensional dendritic growth

    Science.gov (United States)

    Jelinek, Bohumir; Eshraghi, Mohsen; Felicelli, Sergio; Peters, John F.

    2014-03-01

    An extremely scalable lattice Boltzmann (LB)-cellular automaton (CA) model for simulations of two-dimensional (2D) dendritic solidification under forced convection is presented. The model incorporates effects of phase change, solute diffusion, melt convection, and heat transport. The LB model represents the diffusion, convection, and heat transfer phenomena. The dendrite growth is driven by a difference between actual and equilibrium liquid composition at the solid-liquid interface. The CA technique is deployed to track the new interface cells. The computer program was parallelized using the Message Passing Interface (MPI) technique. Parallel scaling of the algorithm was studied and major scalability bottlenecks were identified. Efficiency loss attributable to the high memory bandwidth requirement of the algorithm was observed when using multiple cores per processor. Parallel writing of the output variables of interest was implemented in the binary Hierarchical Data Format 5 (HDF5) to improve the output performance, and to simplify visualization. Calculations were carried out in single precision arithmetic without significant loss in accuracy, resulting in 50% reduction of memory and computational time requirements. The presented solidification model shows a very good scalability up to centimeter size domains, including more than ten million of dendrites. Catalogue identifier: AEQZ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEQZ_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, UK Licensing provisions: Standard CPC license, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 29,767 No. of bytes in distributed program, including test data, etc.: 3131,367 Distribution format: tar.gz Programming language: Fortran 90. Computer: Linux PC and clusters. Operating system: Linux. Has the code been vectorized or parallelized?: Yes. Program is parallelized using MPI

  4. HIV Integration Site Analysis of Cellular Models of HIV Latency with a Probe-Enriched Next-Generation Sequencing Assay.

    Science.gov (United States)

    Sunshine, Sara; Kirchner, Rory; Amr, Sami S; Mansur, Leandra; Shakhbatyan, Rimma; Kim, Michelle; Bosque, Alberto; Siliciano, Robert F; Planelles, Vicente; Hofmann, Oliver; Ho Sui, Shannan; Li, Jonathan Z

    2016-05-01

    Antiretroviral therapy (ART) is successful in the suppression of HIV but cannot target and eradicate the latent proviral reservoir. The location of retroviral integration into the human genome is thought to play a role in the clonal expansion of infected cells and HIV persistence. We developed a high-throughput targeted sequence capture assay that uses a pool of HIV-specific probes to enrich Illumina libraries prior to deep sequencing. Using an expanded clonal population of ACH-2 cells, we demonstrate that this sequence capture assay has an extremely low false-positive rate. This assay assessed four cellular models commonly used to study HIV latency and latency-reversing agents: ACH-2 cells, J-Lat cells, the Bcl-2-transduced primary CD4(+)model, and the cultured TCM(central memory) CD4(+)model. HIV integration site characteristics and genes were compared between these cellular models and to previously reported patient data sets. Across these cellular models, there were significant differences in integration site characteristics, including orientation relative to that of the host gene, the proportion of clonally expanded sites, and the proportion located within genic regions and exons. Despite a greater diversity of minority integration sites than expected in ACH-2 cells, their integration site characteristics consistently differed from those of the other models and from the patient samples. Gene ontology analysis of highly represented genes from the patient samples found little overlap with HIV-containing genes from the cell lines. These findings show that integration site differences exist among the commonly used cellular models of HIV latency and in comparison to integration sites found in patient samples. Despite the success of ART, currently there is no successful therapy to eradicate integrated proviruses. Cellular models of HIV latency are used to test the efficacy of latency-reversing agents, but it is unclear how well these models reflect HIV integration

  5. p53-Dependent Nestin Regulation Links Tumor Suppression to Cellular Plasticity in Liver Cancer

    DEFF Research Database (Denmark)

    Tschaharganeh, Darjus F; Xue, Wen; Calvisi, Diego F

    2014-01-01

    The p53 tumor suppressor coordinates a series of antiproliferative responses that restrict the expansion of malignant cells, and as a consequence, p53 is lost or mutated in the majority of human cancers. Here, we show that p53 restricts expression of the stem and progenitor-cell-associated protein...... nestin in an Sp1/3 transcription-factor-dependent manner and that Nestin is required for tumor initiation in vivo. Moreover, loss of p53 facilitates dedifferentiation of mature hepatocytes into nestin-positive progenitor-like cells, which are poised to differentiate into hepatocellular carcinomas (HCCs......) or cholangiocarcinomas (CCs) in response to lineage-specific mutations that target Wnt and Notch signaling, respectively. Many human HCCs and CCs show elevated nestin expression, which correlates with p53 loss of function and is associated with decreased patient survival. Therefore, transcriptional repression of Nestin...

  6. Reprogramming cancer cells: a novel approach for cancer therapy or a tool for disease-modeling?

    Science.gov (United States)

    Yilmazer, Açelya; de Lázaro, Irene; Taheri, Hadiseh

    2015-12-01

    Chromatin dynamics have been the major focus of many physiological and pathological processes over the past 20 years. Epigenetic mechanisms have been shown to be reshaped during both cellular reprogramming and tumorigenesis. For this reason, cancer cell reprogramming can provide a powerful tool to better understand both regenerative and cancer-fate processes, with a potential to develop novel therapeutic approaches. Recent studies showed that cancer cells can be reprogrammed to a pluripotent state by the overexpression of reprogramming transcription factors. Activation of transcription factors and modification of chromatin regulators may result in the remodeling of epigenetic status and refueling of tumorigenicity in these reprogrammed cancer cells. However, studies focusing on cancer cell reprogramming are contradictory; some studies reported increased tumor progression whereas others showed that cellular reprogramming has a treatment potential for cancer. In this review, first, the current knowledge on the epigenetic mechanisms involved during cancer development and cellular reprogramming will be presented. Later, different reports and key factors about pluripotency-based reprogramming of cancer cells will be reviewed in detail. New insights will be provided on cancer biology and therapy in the light of cellular reprogramming. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  7. Genetically Engineered Mouse Models in Cancer Research

    Science.gov (United States)

    Walrath, Jessica C.; Hawes, Jessica J.; Van Dyke, Terry; Reilly, Karlyne M.

    2012-01-01

    Mouse models of human cancer have played a vital role in understanding tumorigenesis and answering experimental questions that other systems cannot address. Advances continue to be made that allow better understanding of the mechanisms of tumor development, and therefore the identification of better therapeutic and diagnostic strategies. We review major advances that have been made in modeling cancer in the mouse and specific areas of research that have been explored with mouse models. For example, although there are differences between mice and humans, new models are able to more accurately model sporadic human cancers by specifically controlling timing and location of mutations, even within single cells. As hypotheses are developed in human and cell culture systems, engineered mice provide the most tractable and accurate test of their validity in vivo. For example, largely through the use of these models, the microenvironment has been established to play a critical role in tumorigenesis, since tumor development and the interaction with surrounding stroma can be studied as both evolve. These mouse models have specifically fueled our understanding of cancer initiation, immune system roles, tumor angiogenesis, invasion, and metastasis, and the relevance of molecular diversity observed among human cancers. Currently, these models are being designed to facilitate in vivo imaging to track both primary and metastatic tumor development from much earlier stages than previously possible. Finally, the approaches developed in this field to achieve basic understanding are emerging as effective tools to guide much needed development of treatment strategies, diagnostic strategies, and patient stratification strategies in clinical research. PMID:20399958

  8. Human Cancer Classification: A Systems Biology- Based Model Integrating Morphology, Cancer Stem Cells, Proteomics, and Genomics

    Directory of Open Access Journals (Sweden)

    Halliday A Idikio

    2011-01-01

    Full Text Available Human cancer classification is currently based on the idea of cell of origin, light and electron microscopic attributes of the cancer. What is not yet integrated into cancer classification are the functional attributes of these cancer cells. Recent innovative techniques in biology have provided a wealth of information on the genomic, transcriptomic and proteomic changes in cancer cells. The emergence of the concept of cancer stem cells needs to be included in a classification model to capture the known attributes of cancer stem cells and their potential contribution to treatment response, and metastases. The integrated model of cancer classification presented here incorporates all morphology, cancer stem cell contributions, genetic, and functional attributes of cancer. Integrated cancer classification models could eliminate the unclassifiable cancers as used in current classifications. Future cancer treatment may be advanced by using an integrated model of cancer classification.

  9. Channel modeling for fifth generation cellular networks and wireless sensor networks

    Science.gov (United States)

    Torabi, Amir

    In view of exponential growth in data traffic demand, the wireless communications industry has aimed to increase the capacity of existing networks by 1000 times over the next 20 years. A combination of extreme cell densification, more bandwidth, and higher spectral efficiency is needed to support the data traffic requirements for fifth generation (5G) cellular communications. In this research, the potential improvements achieved by using three major 5G enabling technologies (i.e., small cells, millimeter-wave spectrum, and massive MIMO) in rural and urban environments are investigated. This work develops SPM and KA-based ray models to investigate the impact of geometrical parameters on terrain-based multiuser MIMO channel characteristic. Moreover, a new directional 3D channel model is developed for urban millimeter-wave (mmW) small cells. Path-loss, spatial correlation, coverage distance, and coherence length are studied in urban areas. Exploiting physical optics (PO) and geometric optics (GO) solutions, closed form expressions are derived for spatial correlation. Achievable spatial diversity is evaluated using horizontal and vertical linear arrays as well as planar 2D arrays. In another study, a versatile near-ground field prediction model is proposed to facilitate accurate wireless sensor network (WSN) simulations. Monte Carlo simulations are used to investigate the effects of antenna height, frequency of operation, polarization, and terrain dielectric and roughness properties on WSNs performance.

  10. A computational approach to modeling cellular-scale blood flow in complex geometry

    Science.gov (United States)

    Balogh, Peter; Bagchi, Prosenjit

    2017-04-01

    We present a computational methodology for modeling cellular-scale blood flow in arbitrary and highly complex geometry. Our approach is based on immersed-boundary methods, which allow modeling flows in arbitrary geometry while resolving the large deformation and dynamics of every blood cell with high fidelity. The present methodology seamlessly integrates different modeling components dealing with stationary rigid boundaries of complex shape, moving rigid bodies, and highly deformable interfaces governed by nonlinear elasticity. Thus it enables us to simulate 'whole' blood suspensions flowing through physiologically realistic microvascular networks that are characterized by multiple bifurcating and merging vessels, as well as geometrically complex lab-on-chip devices. The focus of the present work is on the development of a versatile numerical technique that is able to consider deformable cells and rigid bodies flowing in three-dimensional arbitrarily complex geometries over a diverse range of scenarios. After describing the methodology, a series of validation studies are presented against analytical theory, experimental data, and previous numerical results. Then, the capability of the methodology is demonstrated by simulating flows of deformable blood cells and heterogeneous cell suspensions in both physiologically realistic microvascular networks and geometrically intricate microfluidic devices. It is shown that the methodology can predict several complex microhemodynamic phenomena observed in vascular networks and microfluidic devices. The present methodology is robust and versatile, and has the potential to scale up to very large microvascular networks at organ levels.

  11. Safety impacts of red light cameras at signalized intersections based on cellular automata models.

    Science.gov (United States)

    Chai, C; Wong, Y D; Lum, K M

    2015-01-01

    This study applies a simulation technique to evaluate the hypothesis that red light cameras (RLCs) exert important effects on accident risks. Conflict occurrences are generated by simulation and compared at intersections with and without RLCs to assess the impact of RLCs on several conflict types under various traffic conditions. Conflict occurrences are generated through simulating vehicular interactions based on an improved cellular automata (CA) model. The CA model is calibrated and validated against field observations at approaches with and without RLCs. Simulation experiments are conducted for RLC and non-RLC intersections with different geometric layouts and traffic demands to generate conflict occurrences that are analyzed to evaluate the hypothesis that RLCs exert important effects on road safety. The comparison of simulated conflict occurrences show favorable safety impacts of RLCs on crossing conflicts and unfavorable impacts for rear-end conflicts during red/amber phases. Corroborative results are found from broad analysis of accident occurrence. RLCs are found to have a mixed effect on accident risk at signalized intersections: crossing collisions are reduced, whereas rear-end collisions may increase. The specially developed CA model is found to be a feasible safety assessment tool.

  12. Understanding the cellular mode of action of vernakalant using a computational model: answers and new questions

    Directory of Open Access Journals (Sweden)

    Loewe Axel

    2015-09-01

    Full Text Available Vernakalant is a new antiarrhythmic agent for the treatment of atrial fibrillation. While it has proven to be effective in a large share of patients in clinical studies, its underlying mode of action is not fully understood. In this work, we aim to link experimental data from the subcellular, tissue, and system level using an in-silico approach. A Hill’s equation-based drug model was extended to cover the frequency dependence of sodium channel block. Two model variants were investigated: M1 based on subcellular data and M2 based on tissue level data. 6 action potential (AP markers were evaluated regarding their dose, frequency and substrate dependence. M1 comprising potassium, sodium, and calcium channel block reproduced the reported prolongation of the refractory period. M2 not including the effects on potassium channels reproduced reported AP morphology changes on the other hand. The experimentally observed increase of ERP accompanied by a shortening of APD90 was not reproduced. Thus, explanations for the drug-induced changes are provided while none of the models can explain the effects in their entirety. These results foster the understanding of vernakalant’s cellular mode of action and point out relevant gaps in our current knowledge to be addressed in future in-silico and experimental research on this aspiring antiarrhythmic agent.

  13. Complementary models reveal cellular responses to contact stresses that contribute to post-traumatic osteoarthritis.

    Science.gov (United States)

    Martin, James A; Anderson, Donald D; Goetz, Jessica E; Fredericks, Douglas; Pedersen, Douglas R; Ayati, Bruce P; Marsh, J Lawrence; Buckwalter, Joseph A

    2017-03-01

    Two categories of joint overloading cause post-traumatic osteoarthritis (PTOA): single acute traumatic loads/impactions and repetitive overloading due to incongruity/instability. We developed and refined three classes of complementary models to define relationships between joint overloading and progressive cartilage loss across the spectrum of acute injuries and chronic joint abnormalities: explant and whole joint models that allow probing of cellular responses to mechanical injury and contact stresses, animal models that enable study of PTOA pathways in living joints and pre-clinical testing of treatments, and patient-specific computational models that define the overloading that causes OA in humans. We coordinated methodologies across models so that results from each informed the others, maximizing the benefit of this complementary approach. We are incorporating results from these investigations into biomathematical models to provide predictions of PTOA risk and guide treatment. Each approach has limitations, but each provides opportunities to elucidate PTOA pathogenesis. Taken together, they help define levels of joint overloading that cause cartilage destruction, show that both forms of overloading can act through the same biologic pathways, and create a framework for initiating clinical interventions that decrease PTOA risk. Considered collectively, studies extending from explants to humans show that thresholds of joint overloading that cause cartilage loss can be defined, that to at least some extent both forms of joint overloading act through the same biologic pathways, and interventions that interrupt these pathways prevent cartilage damage. These observations suggest that treatments that decrease the risk of all forms of OA progression can be discovered. © 2016 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:515-523, 2017. © 2016 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

  14. The cellular level of histone H3 lysine 4 dimethylation correlates with response to adjuvant gemcitabine in Japanese pancreatic cancer patients treated with surgery.

    Science.gov (United States)

    Watanabe, T; Morinaga, S; Akaike, M; Numata, M; Tamagawa, H; Yamamoto, N; Shiozawa, M; Ohkawa, S; Kameda, Y; Nakamura, Y; Miyagi, Y

    2012-11-01

    To search for biomarkers identifying pancreatic cancer patients likely to benefit from adjuvant gemcitabine chemotherapy, we investigated the status of several histone modifications in pancreatic tumors and their relationship to clinicopathological features and outcomes. Sixty one pancreatic cancer patients, primarily treated by surgical removal of tumors, were involved in the study. Thirty patients completed postoperative adjuvant gemcitabine, and in 31 it was discontinued. Tumor specimens were examined using immunohistochemistry for di- and tri-methylation of histone H3 lysine 4 (H3K4me2 and H3K4me3), dimethylation and acetylation of histone H3 lysine 9 (H3K9me2 and H3K9ac), and acetylation of histone H3 lysine 18 (H3K18ac). Positive tumor staining for each histone modification was used to classify patients into low- and high-staining groups, which were examined for relationships to clinicopathological features and clinical outcomes. High expression of H3K4me3 was related to the well and moderately differentiated tumor histological type (p = 0.012) and low expression of H3K4me2 was related to the presence of perineural invasion (p = 0.007). No cellular histone modifications were associated with overall or disease-free survival of patients as a whole. In the subgroup analyses, a low level of H3K4me2 was significantly associated with worse disease free survival in patients that completed adjuvant gemcitabine (p = 0.0239). Univariate and multivariate hazard models also indicated that a low level of H3K4me2 was a significant independent predictor of disease-free survival (p = 0.007). H3K4me2 was found to be a predictor of response to adjuvant gemcitabine in Asian patients with pancreatic cancer. Copyright © 2012 Elsevier Ltd. All rights reserved.

  15. Stochastic cellular automata model of cell migration, proliferation and differentiation: validation with in vitro cultures of muscle satellite cells.

    Science.gov (United States)

    Garijo, N; Manzano, R; Osta, R; Perez, M A

    2012-12-07

    Cell migration and proliferation has been modelled in the literature as a process similar to diffusion. However, using diffusion models to simulate the proliferation and migration of cells tends to create a homogeneous distribution in the cell density that does not correlate to empirical observations. In fact, the mechanism of cell dispersal is not diffusion. Cells disperse by crawling or proliferation, or are transported in a moving fluid. The use of cellular automata, particle models or cell-based models can overcome this limitation. This paper presents a stochastic cellular automata model to simulate the proliferation, migration and differentiation of cells. These processes are considered as completely stochastic as well as discrete. The model developed was applied to predict the behaviour of in vitro cell cultures performed with adult muscle satellite cells. Moreover, non homogeneous distribution of cells has been observed inside the culture well and, using the above mentioned stochastic cellular automata model, we have been able to predict this heterogeneous cell distribution and compute accurate quantitative results. Differentiation was also incorporated into the computational simulation. The results predicted the myotube formation that typically occurs with adult muscle satellite cells. In conclusion, we have shown how a stochastic cellular automata model can be implemented and is capable of reproducing the in vitro behaviour of adult muscle satellite cells. Copyright © 2012 Elsevier Ltd. All rights reserved.

  16. In silico characterization of cell-cell interactions using a cellular automata model of cell culture.

    Science.gov (United States)

    Kihara, Takanori; Kashitani, Kosuke; Miyake, Jun

    2017-07-14

    Cell proliferation is a key characteristic of eukaryotic cells. During cell proliferation, cells interact with each other. In this study, we developed a cellular automata model to estimate cell-cell interactions using experimentally obtained images of cultured cells. We used four types of cells; HeLa cells, human osteosarcoma (HOS) cells, rat mesenchymal stem cells (MSCs), and rat smooth muscle A7r5 cells. These cells were cultured and stained daily. The obtained cell images were binarized and clipped into squares containing about 104 cells. These cells showed characteristic cell proliferation patterns. The growth curves of these cells were generated from the cell proliferation images and we determined the doubling time of these cells from the growth curves. We developed a simple cellular automata system with an easily accessible graphical user interface. This system has five variable parameters, namely, initial cell number, doubling time, motility, cell-cell adhesion, and cell-cell contact inhibition (of proliferation). Within these parameters, we obtained initial cell numbers and doubling times experimentally. We set the motility at a constant value because the effect of the parameter for our simulation was restricted. Therefore, we simulated cell proliferation behavior with cell-cell adhesion and cell-cell contact inhibition as variables. By comparing growth curves and proliferation cell images, we succeeded in determining the cell-cell interaction properties of each cell. Simulated HeLa and HOS cells exhibited low cell-cell adhesion and weak cell-cell contact inhibition. Simulated MSCs exhibited high cell-cell adhesion and positive cell-cell contact inhibition. Simulated A7r5 cells exhibited low cell-cell adhesion and strong cell-cell contact inhibition. These simulated results correlated with the experimental growth curves and proliferation images. Our simulation approach is an easy method for evaluating the cell-cell interaction properties of cells.

  17. Expression of cellular components in granulomatous inflammatory response in Piaractus mesopotamicus model.

    Directory of Open Access Journals (Sweden)

    Wilson Gómez Manrique

    Full Text Available The present study aimed to describe and characterize the cellular components during the evolution of chronic granulomatous inflammation in the teleost fish pacus (P. mesopotamicus induced by Bacillus Calmette-Guerin (BCG, using S-100, iNOS and cytokeratin antibodies. 50 fish (120±5.0 g were anesthetized and 45 inoculated with 20 μL (40 mg/mL (2.0 x 10(6 CFU/mg and five inoculated with saline (0,65% into muscle tissue in the laterodorsal region. To evaluate the inflammatory process, nine fish inoculated with BCG and one control were sampled in five periods: 3rd, 7th, 14th, 21st and 33rd days post-inoculation (DPI. Immunohistochemical examination showed that the marking with anti-S-100 protein and anti-iNOS antibodies was weak, with a diffuse pattern, between the third and seventh DPI. From the 14th to the 33rd day, the marking became stronger and marked the cytoplasm of the macrophages. Positivity for cytokeratin was initially observed in the 14th DPI, and the stronger immunostaining in the 33rd day, period in which the epithelioid cells were more evident and the granuloma was fully formed. Also after the 14th day, a certain degree of cellular organization was observed, due to the arrangement of the macrophages around the inoculated material, with little evidence of edema. The arrangement of the macrophages around the inoculum, the fibroblasts, the lymphocytes and, in most cases, the presence of melanomacrophages formed the granuloma and kept the inoculum isolated in the 33rd DPI. The present study suggested that the granulomatous experimental model using teleost fish P. mesopotamicus presented a similar response to those observed in mammals, confirming its importance for studies of chronic inflammatory reaction.

  18. Modeling cancer-immune responses to therapy.

    Science.gov (United States)

    dePillis, L G; Eladdadi, A; Radunskaya, A E

    2014-10-01

    Cancer therapies that harness the actions of the immune response, such as targeted monoclonal antibody treatments and therapeutic vaccines, are relatively new and promising in the landscape of cancer treatment options. Mathematical modeling and simulation of immune-modifying therapies can help to offset the costs of drug discovery and development, and encourage progress toward new immunotherapies. Despite advances in cancer immunology research, questions such as how the immune system interacts with a growing tumor, and which components of the immune system play significant roles in responding to immunotherapy are still not well understood. Mathematical modeling and simulation are powerful tools that provide an analytical framework in which to address such questions. A quantitative understanding of the kinetics of the immune response to treatment is crucial in designing treatment strategies, such as dosing, timing, and predicting the response to a specific treatment. These models can be used both descriptively and predictively. In this chapter, various mathematical models that address different cancer treatments, including cytotoxic chemotherapy, immunotherapy, and combinations of both treatments, are presented. The aim of this chapter is to highlight the importance of mathematical modeling and simulation in the design of immunotherapy protocols for cancer treatment. The results demonstrate the power of these approaches in explaining determinants that are fundamental to cancer-immune dynamics, therapeutic success, and the development of efficient therapies.

  19. Comparative lipidomic study of urothelial cancer models: association with urothelial cancer cell invasiveness.

    Science.gov (United States)

    Yu, Yang; Skočaj, Matej; Kreft, Mateja Erdani; Resnik, Nataša; Veranič, Peter; Franceschi, Pietro; Sepčić, Kristina; Guella, Graziano

    2016-10-18

    Comparative lipidomic studies were performed across the RT4 versus T24 urothelial cancer cell lines, as models for noninvasive urothelial papilloma cells (with a relatively high level of differentiation) and invasive urothelial carcinoma cells (with low level of differentiation), respectively. The aim was to investigate the differences in lipid profile associated with different levels of urothelial cancer cell invasiveness. The cellular lipidomes were characterized using our previously developed joint methodology of liquid chromatography-mass spectrometry and high-resolution nuclear magnetic resonance, which included analysis of the phospholipids and ceramide-based glycosphingolipids. This study shows that the invasive T24 cells have 3-fold lower levels of 1-alkyl (ether)-2-acyl phosphocholine species, which are accompanied by greater length and higher unsaturation of acyl chains of several lipid classes. Moreover, d18:1-based glycosphingolipids show different profiles; in particular, α-hydroxylated glucosylceramides have lower levels in the T24 cells, along with increased lactosyl ceramides. These differences between RT4 and T24 cells suggest significantly different organization of the cellular membranes, which can affect the membrane fluidity and membrane-dependent functions, and contribute to the lower stiffness of plasma membrane and reduced cell-cell adhesion required for movement and invasiveness of these T24 urothelial carcinoma cells with a high metastatic potential.

  20. Beyond the antigen receptor: editing the genome of T-cells for cancer adoptive cellular therapies

    Directory of Open Access Journals (Sweden)

    Angharad eLloyd

    2013-08-01

    Full Text Available Recent early-stage clinical trials evaluating the adoptive transfer of patient CD8+ T-cells re-directed with antigen receptors recognising tumours have shown very encouraging results. These reports provide strong support for further development of the therapeutic concept as a curative cancer treatment. In this respect combining the adoptive transfer of tumour-specific T-cells with therapies that increase their anti-tumour capacity is viewed as a promising strategy to improve treatment outcome. The ex-vivo genetic engineering step that underlies T-cell re-direction offers a unique angle to combine antigen receptor delivery with the targeting of cell intrinsic pathways that restrict T-cell effector functions. Recent progress in genome editing technologies such as protein- and RNA-guided endonucleases raise the possibility of disrupting gene expression in T-cells in order to enhance effector functions or to bypass tumour immune suppression. This approach would avoid the systemic administration of compounds that disrupt immune homeostasis, potentially avoiding autoimmune adverse effects, and could improve the efficacy of T-cell based adoptive therapies.

  1. Modeling the Aneuploidy Control of Cancer

    Directory of Open Access Journals (Sweden)

    Wang Zhong

    2010-07-01

    Full Text Available Abstract Background Aneuploidy has long been recognized to be associated with cancer. A growing body of evidence suggests that tumorigenesis, the formation of new tumors, can be attributed to some extent to errors occurring at the mitotic checkpoint, a major cell cycle control mechanism that acts to prevent chromosome missegregation. However, so far no statistical model has been available quantify the role aneuploidy plays in determining cancer. Methods We develop a statistical model for testing the association between aneuploidy loci and cancer risk in a genome-wide association study. The model incorporates quantitative genetic principles into a mixture-model framework in which various genetic effects, including additive, dominant, imprinting, and their interactions, are estimated by implementing the EM algorithm. Results Under the new model, a series of hypotheses tests are formulated to explain the pattern of the genetic control of cancer through aneuploid loci. Simulation studies were performed to investigate the statistical behavior of the model. Conclusions The model will provide a tool for estimating the effects of genetic loci on aneuploidy abnormality in genome-wide studies of cancer cells.

  2. Hypergravity Loading the Cultured Osteoblasts: Modeling and Experimental Analysis of Cellular Morphology and the Cytoskeleton

    Science.gov (United States)

    Searby, N. D.; Steele, C. R.; Globus, R. K.; Dalton, Bonnie P. (Technical Monitor)

    2001-01-01

    Bone forming cells, osteoblasts, respond to various mechanical forces, including mechanical strain and fluid-induced shear stress. This study examined whether osteoblasts detect changes in gravity as a mechanical force, as assessed by cellular morphology and dimensions of the cytoskeletal network. We used modeling to evaluate how gravity influences cell morphology given theoretical differences in densities between the surrounding medium, cytoplasm, and nucleus. A mechanical model was built based on analysis of axisymmetric shell structures (Fast4 software) to study the effects of 10 times gravity (10G) on cell height. The model indicated 0.02% decrease in overall cell height when the medium was 10% denser than the nucleus or cytoplasm, 5.9 x 10(exp-5)% decrease when the nucleus was 10% denser than the cytoplasm or medium, and 1.3 x 10(exp-5)% decrease when the cell cytoplasm was 10% denser than the nucleus or medium. To experimentally evaluate the influence of gravity, cultured primary fetal rat osteoblasts were grown to near confluence and centrifuged at 10G for 3 hours. Actin, microtubules, and nuclei were fluorescently labeled and analyzed by confocal microscopy to determine overall microtubule and actin network height. Centrifugation led to an apparent reduction in height of both the microtubule (-16%) and the actin (-20%) networks relative to stationary controls. Thus, both modeling and experiments indicate that hypergravity reduces the height of the osteoblast cell layer and their microtubule and actin networks. This combination of modeling and experimental analyses will help us to better understand the mechanical loading of osteoblasts.

  3. Extracts from two ubiquitous Mediterranean plants ameliorate cellular and animal models of neurodegenerative proteinopathies.

    Science.gov (United States)

    Briffa, Michelle; Ghio, Stephanie; Neuner, Johanna; Gauci, Alison J; Cacciottolo, Rebecca; Marchal, Christelle; Caruana, Mario; Cullin, Christophe; Vassallo, Neville; Cauchi, Ruben J

    2017-01-18

    A signature feature of age-related neurodegenerative proteinopathies is the misfolding and aggregation of proteins, typically amyloid-β (Aβ) in Alzheimer's disease (AD) and α-synuclein (α-syn) in Parkinson's disease (PD), into soluble oligomeric structures that are highly neurotoxic. Cellular and animal models that faithfully replicate the hallmark features of these disorders are being increasing exploited to identify disease-modifying compounds. Natural compounds have been identified as a useful source of bioactive molecules with promising neuroprotective capabilities. In the present report, we investigated whether extracts derived from two ubiquitous Mediterranean plants namely, the prickly pear Opuntia ficus-indica (EOFI) and the brown alga Padina pavonica (EPP) alleviate neurodegenerative phenotypes in yeast (Saccharomyces cerevisiae) and fly (Drosophila melanogaster) models of AD and PD. Pre-treatment with EPP or EOFI in the culture medium significantly improved the viability of yeast expressing the Arctic Aβ42 (E22G) mutant. Supplementing food with EOFI or EPP dramatically ameliorated lifespan and behavioural signs of flies with brain-specific expression of wild-type Aβ42 (model of late-onset AD) or the Arctic Aβ42 variant (model of early-onset AD). Additionally, we show that either extract prolonged the survival of a PD fly model based on transgenic expression of the human α-syn A53T mutant. Taken together, our findings suggest that the plant-derived extracts interfere with shared mechanisms of neurodegeneration in AD and PD. This notion is strengthened by evidence demonstrating that EOFI and to a greater extent EPP, while strongly inhibiting the fibrillogenesis of both Aβ42 and α-syn, accumulate remodelled oligomeric aggregates that are less effective at disrupting lipid membrane integrity. Our work therefore opens new avenues for developing therapeutic applications of these natural plant extracts in the treatment of amyloidogenic

  4. Computation of interface curvature in modelling of solidification by the method of cellular automaton

    Directory of Open Access Journals (Sweden)

    Burbelko A. A.

    2007-01-01

    Full Text Available Modelling of solidification process by the method of cellular automaton (CA requires determination of geometrical characteristics of the interface, i.e. of its direction and curvature. In previous studies the authors proposed a method to reduce the well-known effect of an artificial symmetry of the simulation results caused by the anisotropy of the CA computation grid (e.g. a preferred growth of the main dendrite arms along the grid lines or at an angle of 45° in the case of grids with square cells. The aim was achieved by application of the developed methods of computation of the transformation rate and front direction. In this study the authors examined the problem of an accuracy of the computations of an interface curvature. The obtained results show us that the error of the curvature computation introduced by some well-known methods exceeds by 100% a nominal value of this parameter. A method to estimate the accuracy of the applied solution has been proposed. Practical application of the proposed tests enables selection of a best solution, including the authors' own solutions, thus considerably improving an accuracy of the solidification modelling by the method of CA.

  5. Animal models of retinal detachment and reattachment: identifying cellular events that may affect visual recovery.

    Science.gov (United States)

    Lewis, G P; Charteris, D G; Sethi, C S; Fisher, S K

    2002-07-01

    Retinal detachment continues to be a significant cause of visual impairment, either through the direct effects of macular detachment or through secondary complications such as subretinal fibrosis or proliferative vitreoretinopathy. Animal models can provide us with an understanding of the cellular mechanisms at work that account for the retinopathy induced by detachment and for the generation of secondary effects. As we understand the mechanisms involved, animal models can also provide us with opportunities to test therapeutic agents that may reduce the damaging effects of detachment or improve the outcome of reattachment surgery. They may also reveal information of use to understanding other causes of blindness rooted in retinal defects or injuries. Understanding the effects of detachment (and reattachment) are likely to become even more important as surgeons gain skills in subretinal surgical techniques and macular translocation, both of which will generate short-lived detachments. Here we discuss the fundamental events that occur after detachment, present changes associated with reattachment, and discuss retinal changes that may affect the return of vision.

  6. Inferring cellular regulatory networks with Bayesian model averaging for linear regression (BMALR).

    Science.gov (United States)

    Huang, Xun; Zi, Zhike

    2014-08-01

    Bayesian network and linear regression methods have been widely applied to reconstruct cellular regulatory networks. In this work, we propose a Bayesian model averaging for linear regression (BMALR) method to infer molecular interactions in biological systems. This method uses a new closed form solution to compute the posterior probabilities of the edges from regulators to the target gene within a hybrid framework of Bayesian model averaging and linear regression methods. We have assessed the performance of BMALR by benchmarking on both in silico DREAM datasets and real experimental datasets. The results show that BMALR achieves both high prediction accuracy and high computational efficiency across different benchmarks. A pre-processing of the datasets with the log transformation can further improve the performance of BMALR, leading to a new top overall performance. In addition, BMALR can achieve robust high performance in community predictions when it is combined with other competing methods. The proposed method BMALR is competitive compared to the existing network inference methods. Therefore, BMALR will be useful to infer regulatory interactions in biological networks. A free open source software tool for the BMALR algorithm is available at https://sites.google.com/site/bmalr4netinfer/.

  7. Fibrogenesis. IV. Fibrosis and inflammatory bowel disease: cellular mediators and animal models.

    Science.gov (United States)

    Pucilowska, J B; Williams, K L; Lund, P K

    2000-10-01

    The cellular mediators of intestinal fibrosis and the relationship between fibrosis and normal repair are not understood. Identification of the types of intestinal mesenchymal cells that produce collagen during normal healing and fibrosis is vital for elucidating the answers to these questions. Acute injury may cause normal mesenchymal cells to convert to a fibrogenic phenotype that is not maintained during normal healing but may lead to fibrosis when inappropriately sustained. Proliferation of normal or fibrogenic mesenchymal cells may lead to muscularis overgrowth associated with fibrosis. The presence of increased numbers of vimentin-positive cells within fibrotic, hypertrophied muscularis in Crohn's disease suggests that changes in mesenchymal cell phenotype and number may indeed be associated with fibrosis. Fibrosis is induced in rats by peptidoglycan polysaccharides or trinitrobenzene sulfonic acid-ethanol administration, but inducing fibrosis in mice has been technically challenging. The development of current mouse models of colitis, such as dextran sodium sulfate or trinitrobenzene sulfonic acid-ethanol administration, into models of fibrosis will allow us to use genetic manipulation to study molecular mediators of fibrosis.

  8. Load-aware modeling for uplink cellular networks in a multi-channel environment

    KAUST Repository

    AlAmmouri, Ahmad

    2014-09-01

    We exploit tools from stochastic geometry to develop a tractable analytical approach for modeling uplink cellular networks. The developed model is load aware and accounts for per-user power control as well as the limited transmit power constraint for the users\\' equipment (UEs). The proposed analytical paradigm is based on a simple per-user power control scheme in which each user inverts his path-loss such that the signal is received at his serving base station (BS) with a certain power threshold ρ Due to the limited transmit power of the UEs, users that cannot invert their path-loss to their serving BSs are allowed to transmit with their maximum transmit power. We show that the proposed power control scheme not only provides a balanced cell center and cell edge user performance, it also facilitates the analysis when compared to the state-of-the-art approaches in the literature. To this end, we discuss how to manipulate the design variable ρ in response to the network parameters to optimize one or more of the performance metrics such as the outage probability, the network capacity, and the energy efficiency.

  9. Understanding the genetic and molecular pathogenesis of Friedreich's ataxia through animal and cellular models.

    Science.gov (United States)

    Martelli, Alain; Napierala, Marek; Puccio, Hélène

    2012-03-01

    In 1996, a link was identified between Friedreich's ataxia (FRDA), the most common inherited ataxia in men, and alterations in the gene encoding frataxin (FXN). Initial studies revealed that the disease is caused by a unique, most frequently biallelic, expansion of the GAA sequence in intron 1 of FXN. Since the identification of this link, there has been tremendous progress in understanding frataxin function and the mechanism of FRDA pathology, as well as in developing diagnostics and therapeutic approaches for the disease. These advances were the subject of the 4th International Friedreich's Ataxia Conference held on 5th-7th May in the Institut de Génétique et de Biologie Moléculaire et Cellulaire, Illkirch, France. More than 200 scientists gathered from all over the world to present the results of research spanning all areas of investigation into FRDA (including clinical aspects, FRDA pathogenesis, genetics and epigenetics of the disease, development of new models of FRDA, and drug discovery). This review provides an update on the understanding of frataxin function, developments of animal and cellular models of the disease, and recent advances in trying to uncover potential molecules for therapy.

  10. [A Cellular Automata Model for a Community Comprising Two Plant Species of Different Growth Forms].

    Science.gov (United States)

    Frolov, P V; Zubkova, E V; Komarov, A S

    2015-01-01

    A cellular automata computer model for the interactions between two plant species of different growth forms--the lime hairgrass Deschampsia caespitosa (L.) P. Beauv., a sod cereal, and the moneywort Lysimachia nummularia L., a ground creeping perennial herb--is considered. Computer experiments on the self-maintenance of the populations of each species against the background of a gradual increase in the share of randomly eliminated individuals, coexistence of the populations of two species, and the effect of the phytogenous field have been conducted. As has been shown, all the studied factors determine the number of individuals and self-sustainability of the simulated populations by the degree of their impact. The limits of action have been determined for individual factors; within these limits, the specific features in plant reproduction and dispersal provide sustainable coexistence of the simulated populations. It has been demonstrated that the constructed model allows for studying the long-term developmental dynamics of the plants belonging to the selected growth forms.

  11. Mammalian cellular culture models of Trypanosoma cruzi infection: a review of the published literature

    Directory of Open Access Journals (Sweden)

    Duran-Rehbein Gabriel Alberto

    2014-01-01

    Full Text Available Cellular culture infection with Trypanosoma cruzi is a tool used to dissect the biological mechanisms behind Chagas disease as well as to screen potential trypanocidal compounds. Data on these models are highly heterogeneous, which represents a challenge when attempting to compare different studies. The purpose of this review is to provide an overview of the cell culture infectivity assays performed to date. Scientific journal databases were searched for articles in which cultured cells were infected with any Trypanosoma cruzi strain or isolate regardless of the study’s goal. From these articles the cell type, parasite genotype, culture conditions and infectivity results were extracted. This review represents an initial step toward the unification of infectivity model data. Important differences were detected when comparing the pathophysiology of Chagas disease with the experimental conditions used in the analyzed studies. While Trypanosoma cruzi preferentially infects stromal cells in vivo, most of the assays employ epithelial cell lines. Furthermore, the most commonly used parasite strain (Tulahuen-TcVI is associated with chagasic cardiomyopathy only in the Southern Cone of South America. Suggestions to overcome these discrepancies include the use of stromal cell lines and parasite genotypes associated with the known characteristics of the natural history of Chagas disease.

  12. Mammalian cellular culture models of Trypanosoma cruzi infection: a review of the published literature.

    Science.gov (United States)

    Duran-Rehbein, Gabriel Alberto; Vargas-Zambrano, Juan Camilo; Cuéllar, Adriana; Puerta, Concepción Judith; Gonzalez, John Mario

    2014-01-01

    Cellular culture infection with Trypanosoma cruzi is a tool used to dissect the biological mechanisms behind Chagas disease as well as to screen potential trypanocidal compounds. Data on these models are highly heterogeneous, which represents a challenge when attempting to compare different studies. The purpose of this review is to provide an overview of the cell culture infectivity assays performed to date. Scientific journal databases were searched for articles in which cultured cells were infected with any Trypanosoma cruzi strain or isolate regardless of the study's goal. From these articles the cell type, parasite genotype, culture conditions and infectivity results were extracted. This review represents an initial step toward the unification of infectivity model data. Important differences were detected when comparing the pathophysiology of Chagas disease with the experimental conditions used in the analyzed studies. While Trypanosoma cruzi preferentially infects stromal cells in vivo, most of the assays employ epithelial cell lines. Furthermore, the most commonly used parasite strain (Tulahuen-TcVI) is associated with chagasic cardiomyopathy only in the Southern Cone of South America. Suggestions to overcome these discrepancies include the use of stromal cell lines and parasite genotypes associated with the known characteristics of the natural history of Chagas disease. © G.A. Duran-Rehbein et al., published by EDP Sciences, 2014.

  13. Cellular Automata Based Modeling for Evaluating Different Bus Stop Designs in China

    Directory of Open Access Journals (Sweden)

    Haoyang Ding

    2015-01-01

    Full Text Available A cellular automaton model is proposed to simulate mixed traffic flow composed of motor vehicles and bicycles near bus stops. Three typical types of bus stops which are common in China are considered in the model, including two types of curbside bus stops and one type of bus bay stops. Passenger transport capacity of three types of bus stops, which is applied to evaluate the bus stop design, is calculated based on the corresponding traffic flow rate. According to the simulation results, the flow rates of both motor vehicles and bicycles exhibit phase transition from free flow to the saturation one at the critical point. The results also show that the larger the interaction between motor vehicle and bicycle flow is near curbside bus stops, the more the value of saturated flows drops. Curbside bus stops are more suitable when the conflicts between two flows are small and the inflow rate of motor vehicles is low. On the contrary, bus bay stops should be applied due to their ability to reduce traffic conflicts. Findings of this study can provide useful suggestions on bus stop selection considering different inflow rate of motor vehicles and bicycles simultaneously.

  14. Understanding the genetic and molecular pathogenesis of Friedreich’s ataxia through animal and cellular models

    Science.gov (United States)

    Martelli, Alain; Napierala, Marek; Puccio, Hélène

    2012-01-01

    In 1996, a link was identified between Friedreich’s ataxia (FRDA), the most common inherited ataxia in men, and alterations in the gene encoding frataxin (FXN). Initial studies revealed that the disease is caused by a unique, most frequently biallelic, expansion of the GAA sequence in intron 1 of FXN. Since the identification of this link, there has been tremendous progress in understanding frataxin function and the mechanism of FRDA pathology, as well as in developing diagnostics and therapeutic approaches for the disease. These advances were the subject of the 4th International Friedreich’s Ataxia Conference held on 5th–7th May in the Institut de Génétique et de Biologie Moléculaire et Cellulaire, Illkirch, France. More than 200 scientists gathered from all over the world to present the results of research spanning all areas of investigation into FRDA (including clinical aspects, FRDA pathogenesis, genetics and epigenetics of the disease, development of new models of FRDA, and drug discovery). This review provides an update on the understanding of frataxin function, developments of animal and cellular models of the disease, and recent advances in trying to uncover potential molecules for therapy. PMID:22382366

  15. Mathematical modeling and computational prediction of cancer drug resistance.

    Science.gov (United States)

    Sun, Xiaoqiang; Hu, Bin

    2017-06-23

    Diverse forms of resistance to anticancer drugs can lead to the failure of chemotherapy. Drug resistance is one of the most intractable issues for successfully treating cancer in current clinical practice. Effective clinical approaches that could counter drug resistance by restoring the sensitivity of tumors to the targeted agents are urgently needed. As numerous experimental results on resistance mechanisms have been obtained and a mass of high-throughput data has been accumulated, mathematical modeling and computational predictions using systematic and quantitative approaches have become increasingly important, as they can potentially provide deeper insights into resistance mechanisms, generate novel hypotheses or suggest promising treatment strategies for future testing. In this review, we first briefly summarize the current progress of experimentally revealed resistance mechanisms of targeted therapy, including genetic mechanisms, epigenetic mechanisms, posttranslational mechanisms, cellular mechanisms, microenvironmental mechanisms and pharmacokinetic mechanisms. Subsequently, we list several currently available databases and Web-based tools related to drug sensitivity and resistance. Then, we focus primarily on introducing some state-of-the-art computational methods used in drug resistance studies, including mechanism-based mathematical modeling approaches (e.g. molecular dynamics simulation, kinetic model of molecular networks, ordinary differential equation model of cellular dynamics, stochastic model, partial differential equation model, agent-based model, pharmacokinetic-pharmacodynamic model, etc.) and data-driven prediction methods (e.g. omics data-based conventional screening approach for node biomarkers, static network approach for edge biomarkers and module biomarkers, dynamic network approach for dynamic network biomarkers and dynamic module network biomarkers, etc.). Finally, we discuss several further questions and future directions for the use of

  16. Simulating debris flows through a hexagonal cellular automata model: SCIDDICA S3–hex

    Directory of Open Access Journals (Sweden)

    D. D’Ambrosio

    2003-01-01

    Full Text Available Cellular Automata (CA represent a formal frame for dynamical systems, which evolve on the base of local interactions. Some types of landslide, such as debris flows, match well this requirement. The latest hexagonal release (S3–hex of the deterministic model SCIDDICA, specifically developed for simulating debris flows, is described. For CA simulation purposes, landslides can be viewed as a dynamical system, subdivided into elementary parts, whose state evolves exclusively as a consequence of local interactions within a spatial and temporal discretum. Space is the world of the CA, here constituted by hexagonal cells. The attributes of each cell ("substates" describe physical characteristics. For computational reasons, the natural phenomenon is "decomposed" into a number of elementary processes, whose proper composition makes up the "transition function" of the CA. By simultaneously applying this function to all the cells, the evolution of the phenomenon can be simulated in terms of modifications of the substates. SCIDDICA S3–hex exhibits a great flexibility in modelling debris flows. With respect to the previous releases of the model, the mechanism of progressive erosion of the soil cover has been added to the transition function. Considered substates are: altitude; thickness and energy of landslide debris; depth of erodable soil cover; debris outflows. Considered elementary processes are: mobilisation triggering and effect (T1, debris outflows (I1, update of landslide debris thickness and energy (I2, and energy loss (T2.  Simulations of real debris flows, occurred in Campania (Southern Italy in May 1998 (Sarno and December 1999 (San Martino V.C. and Cervinara, have been performed for model calibration purposes; some examples of analysis are briefly described. Possible applications of the method are: risk mapping, also based on a statistical approach; evaluating the effects of mitigation actions (e.g. stream deviations, topographic

  17. A new in vitro model to study cellular responses after thermomechanical damage in monolayer cultures.

    Science.gov (United States)

    Hettler, Alice; Werner, Simon; Eick, Stefan; Laufer, Stefan; Weise, Frank

    2013-01-01

    Although electrosurgical instruments are widely used in surgery to cut tissue layers or to achieve hemostasis by coagulation (electrocautery), only little information is available concerning the inflammatory or immune response towards the debris generated. Given the elevated local temperatures required for successful electrocautery, the remaining debris is likely to contain a plethora of compounds entirely novel to the intracorporal setting. A very common in vitro method to study cell migration after mechanical damage is the scratch assay, however, there is no established model for thermomechanical damage to characterise cellular reactions. In this study, we established a new in vitro model to investigate exposure to high temperature in a carefully controlled cell culture system. Heatable thermostat-controlled aluminium stamps were developed to induce local damage in primary human umbilical vein endothelial cells (HUVEC). The thermomechanical damage invoked is reproducibly locally confined, therefore allowing studies, under the same experimental conditions, of cells affected to various degrees as well as of unaffected cells. We show that the unaffected cells surrounding the thermomechanical damage zone are able to migrate into the damaged area, resulting in a complete closure of the 'wound' within 48 h. Initial studies have shown that there are significant morphological and biological differences in endothelial cells after thermomechanical damage compared to the mechanical damage inflicted by using the unheated stamp as a control. Accordingly, after thermomechanical damage, cell death as well as cell protection programs were activated. Mononuclear cells adhered in the area adjacent to thermomechanical damage, but not to the zone of mechanical damage. Therefore, our model can help to understand the differences in wound healing during the early phase of regeneration after thermomechanical vs. mechanical damage. Furthermore, this model lends itself to study the

  18. A new in vitro model to study cellular responses after thermomechanical damage in monolayer cultures.

    Directory of Open Access Journals (Sweden)

    Alice Hettler

    Full Text Available Although electrosurgical instruments are widely used in surgery to cut tissue layers or to achieve hemostasis by coagulation (electrocautery, only little information is available concerning the inflammatory or immune response towards the debris generated. Given the elevated local temperatures required for successful electrocautery, the remaining debris is likely to contain a plethora of compounds entirely novel to the intracorporal setting. A very common in vitro method to study cell migration after mechanical damage is the scratch assay, however, there is no established model for thermomechanical damage to characterise cellular reactions. In this study, we established a new in vitro model to investigate exposure to high temperature in a carefully controlled cell culture system. Heatable thermostat-controlled aluminium stamps were developed to induce local damage in primary human umbilical vein endothelial cells (HUVEC. The thermomechanical damage invoked is reproducibly locally confined, therefore allowing studies, under the same experimental conditions, of cells affected to various degrees as well as of unaffected cells. We show that the unaffected cells surrounding the thermomechanical damage zone are able to migrate into the damaged area, resulting in a complete closure of the 'wound' within 48 h. Initial studies have shown that there are significant morphological and biological differences in endothelial cells after thermomechanical damage compared to the mechanical damage inflicted by using the unheated stamp as a control. Accordingly, after thermomechanical damage, cell death as well as cell protection programs were activated. Mononuclear cells adhered in the area adjacent to thermomechanical damage, but not to the zone of mechanical damage. Therefore, our model can help to understand the differences in wound healing during the early phase of regeneration after thermomechanical vs. mechanical damage. Furthermore, this model lends itself

  19. Modeling amyloid-beta as homogeneous dodecamers and in complex with cellular prion protein.

    Directory of Open Access Journals (Sweden)

    Steven L Gallion

    Full Text Available Soluble amyloid beta (Aβ peptide has been linked to the pathology of Alzheimer's disease. A variety of soluble oligomers have been observed to be toxic, ranging from dimers to protofibrils. No tertiary structure has been identified as a single biologically relevant form, though many models are comprised of highly ordered β-sheets. Evidence exists for much less ordered toxic oligomers. The mechanism of toxicity remains highly debated and probably involves multiple pathways. Interaction of Aβ oligomers with the N-terminus of the cellular form of the prion protein (PrP(c has recently been proposed. The intrinsically disordered nature of this protein and the highly polymorphic nature of Aβ oligomers make structural resolution of the complex exceptionally challenging. In this study, molecular dynamics simulations are performed for dodecameric assemblies of Aβ comprised of monomers having a single, short antiparallel β-hairpin at the C-terminus. The resulting models, devoid of any intermolecular hydrogen bonds, are shown to correlate well with experimental data and are found to be quite stable within the hydrophobic core, whereas the α-helical N-termini transform to a random coil state. This indicates that highly ordered assemblies are not required for stability and less ordered oligomers are a viable component in the population of soluble oligomers. In addition, a tentative model is proposed for the association of Aβ dimers with a double deletion mutant of the intrinsically disordered N-terminus of PrP(c. This may be useful as a conceptual working model for the binding of higher order oligomers and in the design of further experiments.

  20. Evolving Transport Networks With Cellular Automata Models Inspired by Slime Mould.

    Science.gov (United States)

    Tsompanas, Michail-Antisthenis I; Sirakoulis, Georgios Ch; Adamatzky, Andrew I

    2015-09-01

    Man-made transport networks and their design are closely related to the shortest path problem and considered amongst the most debated problems of computational intelligence. Apart from using conventional or bio-inspired computer algorithms, many researchers tried to solve this kind of problem using biological computing substrates, gas-discharge solvers, prototypes of a mobile droplet, and hot ice computers. In this aspect, another example of biological computer is the plasmodium of acellular slime mould Physarum polycephalum (P. polycephalum), which is a large single cell visible by an unaided eye and has been proven as a reliable living substrate for implementing biological computing devices for computational geometry, graph-theoretical problems, and optimization and imitation of transport networks. Although P. polycephalum is easy to experiment with, computing devices built with the living slime mould are extremely slow; it takes slime mould days to execute a computation. Consequently, mapping key computing mechanisms of the slime mould onto silicon would allow us to produce efficient bio-inspired computing devices to tackle with hard to solve computational intelligence problems like the aforementioned. Toward this direction, a cellular automaton (CA)-based, Physarum-inspired, network designing model is proposed. This novel CA-based model is inspired by the propagating strategy, the formation of tubular networks, and the computing abilities of the plasmodium of P. polycephalum. The results delivered by the CA model demonstrate a good match with several previously published results of experimental laboratory studies on imitation of man-made transport networks with P. polycephalum. Consequently, the proposed CA model can be used as a virtual, easy-to-access, and biomimicking laboratory emulator that will economize large time periods needed for biological experiments while producing networks almost identical to the tubular networks of the real-slime mould.

  1. Modeling of the static recrystallization for 7055 aluminum alloy by cellular automaton

    Science.gov (United States)

    Zhang, Tao; Lu, Shi-hong; Zhang, Jia-bin; Li, Zheng-fang; Chen, Peng; Gong, Hai; Wu, Yun-xin

    2017-09-01

    In order to simulate the flow behavior and microstructure evolution during the pass interval period of the multi-pass deformation process, models of static recovery (SR) and static recrystallization (SRX) by the cellular automaton (CA) method for the 7055 aluminum alloy were established. Double-pass hot compression tests were conducted to acquire flow stress and microstructure variation during the pass interval period. With the basis of the material constants obtained from the compression tests, models of the SR, incubation period, nucleation rate and grain growth were fitted by least square method. A model of the grain topology and a statistical computation of the CA results were also introduced. The effects of the pass interval time, temperature, strain, strain rate and initial grain size on the microstructure variation for the SRX of the 7055 aluminum alloy were studied. The results show that a long pass interval time, large strain, high temperature and large strain rate are beneficial for finer grains during the pass interval period. The stable size of the static recrystallized grain is not concerned with the initial grain size, but mainly depends on the strain rate and temperature. The SRX plays a vital role in grain refinement, while the SR has no effect on the variation of microstructure morphology. Using flow stress and microstructure comparisons of the simulated and experimental CA results, the established CA models can accurately predict the flow stress and microstructure evolution during the pass interval period, and provide guidance for the selection of optimized parameters for the multi-pass deformation process.

  2. Hypoxia in models of lung cancer

    DEFF Research Database (Denmark)

    Graves, Edward E; Vilalta, Marta; Cecic, Ivana K

    2010-01-01

    PURPOSE: To efficiently translate experimental methods from bench to bedside, it is imperative that laboratory models of cancer mimic human disease as closely as possible. In this study, we sought to compare patterns of hypoxia in several standard and emerging mouse models of lung cancer...... to establish the appropriateness of each for evaluating the role of oxygen in lung cancer progression and therapeutic response. EXPERIMENTAL DESIGN: Subcutaneous and orthotopic human A549 lung carcinomas growing in nude mice as well as spontaneous K-ras or Myc-induced lung tumors grown in situ......H2AX foci in vitro and in vivo. Finally, our findings were compared with oxygen electrode measurements of human lung cancers. RESULTS: Minimal fluoroazomycin arabinoside and pimonidazole accumulation was seen in tumors growing within the lungs, whereas subcutaneous tumors showed substantial trapping...

  3. [Spiritual care model for terminal cancer patients].

    Science.gov (United States)

    Cheng, Ju-Fen; Lin, Ya-Ching; Huang, Pai-Ho; Wei, Chih-Hsin; Sun, Jia-Ling

    2014-12-01

    Providing spiritual care to patients with advanced cancer may improve the quality of life of these patients and help them experience a good death. Cancer patients are eager for additional spiritual care and for a sense of peace at the end of their life. However, spirituality is an abstract concept. The literature on spiritual care focuses primarily on elaborations of spirituality theory. Thus, first-line medical care professionals lack clear guidelines for managing the spiritual needs of terminal cancer patients. The purposes of this article were to: 1) introduce a spiritual care model based on the concept of repair and recovery of relationships that addresses the relationship between the self and God, others, id, and objects and 2) set out a four-step strategy for this model that consists of understanding, empathizing, guiding, and growing. This article provides operational guidelines for the spiritual care of terminal cancer patients.

  4. fA cellular automaton model of crystalline cellulose hydrolysis by cellulases

    Directory of Open Access Journals (Sweden)

    Little Bryce A

    2011-10-01

    Full Text Available Abstract Background Cellulose from plant biomass is an abundant, renewable material which could be a major feedstock for low emissions transport fuels such as cellulosic ethanol. Cellulase enzymes that break down cellulose into fermentable sugars are composed of different types - cellobiohydrolases I and II, endoglucanase and β-glucosidase - with separate functions. They form a complex interacting network between themselves, soluble hydrolysis product molecules, solution and solid phase substrates and inhibitors. There have been many models proposed for enzymatic saccharification however none have yet employed a cellular automaton approach, which allows important phenomena, such as enzyme crowding on the surface of solid substrates, denaturation and substrate inhibition, to be considered in the model. Results The Cellulase 4D model was developed de novo taking into account the size and composition of the substrate and surface-acting enzymes were ascribed behaviors based on their movements, catalytic activities and rates, affinity for, and potential for crowding of, the cellulose surface, substrates and inhibitors, and denaturation rates. A basic case modeled on literature-derived parameters obtained from Trichoderma reesei cellulases resulted in cellulose hydrolysis curves that closely matched curves obtained from published experimental data. Scenarios were tested in the model, which included variation of enzyme loadings, adsorption strengths of surface acting enzymes and reaction periods, and the effect on saccharide production over time was assessed. The model simulations indicated an optimal enzyme loading of between 0.5 and 2 of the base case concentrations where a balance was obtained between enzyme crowding on the cellulose crystal, and that the affinities of enzymes for the cellulose surface had a large effect on cellulose hydrolysis. In addition, improvements to the cellobiohydrolase I activity period substantially improved overall

  5. Combinatorial Microenvironments Impose a Continuum of Cellular Responses to a Single Pathway-Targeted Anti-cancer Compound

    Directory of Open Access Journals (Sweden)

    Chun-Han Lin

    2017-10-01

    Full Text Available Tumor microenvironments are a driver of resistance to anti-cancer drugs. Dissecting cell-microenvironment interactions into tractable units of study presents a challenge. Here, we assess the impact of hundreds of tumor-inspired microenvironments, in parallel, on lapatinib responses in four cancer cell lines. Combinations of ECM and soluble factors were printed on stiffness-tunable substrata to generate a collection of controlled microenvironments in which to explore cell-based functional responses. Proliferation, HER2 protein expression and phosphorylation, and morphology were measured in single cells. Using dimension reduction and linear modeling, the effects of microenvironment constituents were identified and then validated empirically. Each of the cell lines exhibits unique microenvironment-response patterns. Fibronectin, type IV collagen, and matrix rigidity are significant regulators of lapatinib resistance in HER2-amplified breast cancer cells. Small-molecule inhibitors were identified that could attenuate microenvironment-imposed resistance. Thus, we demonstrate a strategy to identify resistance- and sensitivity-driving microenvironments to improve the efficacy of anti-cancer therapeutics.

  6. Microsatellite instability, KRAS mutations and cellular distribution of TRAIL-receptors in early stage colorectal cancer.

    Directory of Open Access Journals (Sweden)

    Lydia Kriegl

    Full Text Available BACKGROUND: The fact that the receptors for the TNF-related apoptosis inducing ligand (TRAIL are almost invariably expressed in colorectal cancer (CRC represents the rationale for the employment of TRAIL-receptors targeting compounds for the therapy of patients affected by this tumor. Yet, first reports on the use of these bioactive agents provided disappointing results. We therefore hypothesized that loss of membrane-bound TRAIL-R might be a feature of some CRC and that the evaluation of membrane staining rather than that of the overall expression of TRAIL-R might predict the response to TRAIL-R targeting compounds in this tumor. AIM AND METHODS: Thus, we evaluated the immunofluorescence pattern of TRAIL-receptors and E-cadherin to assess the fraction of membrane-bound TRAIL-receptors in 231 selected patients with early-stage CRC undergoing surgical treatment only. Moreover, we investigated whether membrane staining for TRAIL-receptors as well as the presence of KRAS mutations or of microsatellite instability (MSI had an effect on survival and thus a prognostic effect. RESULTS: As expected, almost all CRC samples stained positive for TRAIL-R1 and 2. Instead, membrane staining for these receptors was positive in only 71% and 16% of samples respectively. No correlation between KRAS mutation status or MSI-phenotype and prognosis could be detected. TRAIL-R1 staining intensity correlated with survival in univariate analysis, but only membranous staining of TRAIL-R1 and TRAIL-R2 on cell membranes was an independent predictor of survival (cox multivariate analysis: TRAIL-R1: p = 0.019, RR 2.06[1.12-3.77]; TRAIL-R2: p = 0.033, RR 3.63[1.11-11.84]. CONCLUSIONS: In contrast to the current assumptions, loss of membrane staining for TRAIL-receptors is a common feature of early stage CRC which supersedes the prognostic significance of their staining intensity. Failure to achieve therapeutic effects in recent clinical trials using TRAIL-receptors targeting

  7. Confocal Light Absorption and Scattering Spectroscopic (CLASS) imaging: From cancer detection to sub-cellular function

    Science.gov (United States)

    Qiu, Le

    Light scattering spectroscopy (LSS), an optical technique that relates the spectroscopic properties of light elastically scattered by small particles to their size, refractive index and shape, has been recently successfully employed for sensing morphological and biochemical properties of epithelial tissues and cells in vivo. LSS does not require exogenous markers, is non-invasive, and, due to its multispectral nature, can sense biological structures well beyond the diffraction limit. All that makes LSS be a very good candidate to be used both in clinical medicine for in vivo detection of disease and in cell biology to monitor cell function on the organelle scale. Recently we developed two LSS-based imaging modalities: clinical Polarized LSS (PLSS) Endoscopic Technique for locating early pre-cancerous changes in GI tract and Confocal Light Absorption and Scattering Spectroscopic (CLASS) Microscopy for studying cells in vivo without exogenous markers. One important application of the clinical PLSS endoscopic instrument, a noncontact scanning imaging device compatible with the standard clinical endoscopes and capable of detecting dysplastic changes, is to serve as a guide for biopsy in Barrett's esophagus (BE). The instrument detects parallel and perpendicular components of the polarized light, backscattered from epithelial tissues, and determines characteristics of epithelial nuclei from the residual spectra. It also can find tissue oxygenation, hemoglobin content and other properties from the diffuse light component. By rapidly scanning esophagus the PLSS endoscopic instrument makes sure the entire BE portion is scanned and examined for the presence of dysplasia. CLASS microscopy, on the other hand, combines principles of light scattering spectroscopy (LSS) with confocal microscopy. Its main purpose is to image cells on organelle scale in vivo without the use of exogenous labels which may affect the cell function. The confocal geometry selects specific region and

  8. Mouse models for gastric cancer: Matching models to biological questions

    Science.gov (United States)

    Poh, Ashleigh R; O'Donoghue, Robert J J

    2016-01-01

    Abstract Gastric cancer is the third leading cause of cancer‐related mortality worldwide. This is in part due to the asymptomatic nature of the disease, which often results in late‐stage diagnosis, at which point there are limited treatment options. Even when treated successfully, gastric cancer patients have a high risk of tumor recurrence and acquired drug resistance. It is vital to gain a better understanding of the molecular mechanisms underlying gastric cancer pathogenesis to facilitate the design of new‐targeted therapies that may improve patient survival. A number of chemically and genetically engineered mouse models of gastric cancer have provided significant insight into the contribution of genetic and environmental factors to disease onset and progression. This review outlines the strengths and limitations of current mouse models of gastric cancer and their relevance to the pre‐clinical development of new therapeutics. PMID:26809278

  9. The GH/IGF-1 axis in a critical period early in life determines cellular DNA repair capacity by altering transcriptional regulation of DNA repair-related genes: implications for the developmental origins of cancer.

    Science.gov (United States)

    Podlutsky, Andrej; Valcarcel-Ares, Marta Noa; Yancey, Krysta; Podlutskaya, Viktorija; Nagykaldi, Eszter; Gautam, Tripti; Miller, Richard A; Sonntag, William E; Csiszar, Anna; Ungvari, Zoltan

    2017-04-01

    Experimental, clinical, and epidemiological findings support the concept of developmental origins of health and disease (DOHAD), suggesting that early-life hormonal influences during a sensitive period around adolescence have a powerful impact on cancer morbidity later in life. The endocrine changes that occur during puberty are highly conserved across mammalian species and include dramatic increases in circulating GH and IGF-1 levels. Importantly, patients with developmental IGF-1 deficiency due to GH insensitivity (Laron syndrome) do not develop cancer during aging. Rodents with developmental GH/IGF-1 deficiency also exhibit significantly decreased cancer incidence at old age, marked resistance to chemically induced carcinogenesis, and cellular resistance to genotoxic stressors. Early-life treatment of GH/IGF-1-deficient mice and rats with GH reverses the cancer resistance phenotype; however, the underlying molecular mechanisms remain elusive. The present study was designed to test the hypothesis that developmental GH/IGF-1 status impacts cellular DNA repair mechanisms. To achieve that goal, we assessed repair of γ-irradiation-induced DNA damage (single-cell gel electrophoresis/comet assay) and basal and post-irradiation expression of DNA repair-related genes (qPCR) in primary fibroblasts derived from control rats, Lewis dwarf rats (a model of developmental GH/IGF-1 deficiency), and GH-replete dwarf rats (GH administered beginning at 5 weeks of age, for 30 days). We found that developmental GH/IGF-1 deficiency resulted in persisting increases in cellular DNA repair capacity and upregulation of several DNA repair-related genes (e.g., Gadd45a, Bbc3). Peripubertal GH treatment reversed the radiation resistance phenotype. Fibroblasts of GH/IGF-1-deficient Snell dwarf mice also exhibited improved DNA repair capacity, showing that the persisting influence of peripubertal GH/IGF-1 status is not species-dependent. Collectively, GH/IGF-1 levels during a critical period

  10. Evaluation of Residual Cellularity and Proliferation on Preoperatively Treated Breast Cancer: A Comparison between Image Analysis and Light Microscopy Analysis

    Directory of Open Access Journals (Sweden)

    Valentina Corletto

    1998-01-01

    Full Text Available Histopathology has been suggested as a reliable method for tumour reduction evaluation of preoperatively treated breast cancer. Immunocytochemistry can be used to enhance the visibility of residual tumour cellularity and in the evaluation of its proliferative activity. We compared Image Analysis (IA with Light Microscopy Analysis (LMA on sections of breast carcinomas treated with preoperative chemo‐ or chemo/radiotherapy in the evaluation of the Neoplastic Cell Density (NCD (69 cases and the Proliferation Index (PI (35 cases. NCD was expressed as the immunoreactive area to cytokeratin over the total original neoplastic area and PI was expressed as the number of immunostained tumoural nuclei with MIB1 MoAb over the total of tumoural nuclei. The intraobserver agreement and that between IA and LMA for both indices were estimated by the common (Kw and the jackknife weighted kappa statistic (K˜w. The extent of agreement of each considered category was also assessed by means of the category‐specific kappa statistics (Kcs. The intraobserver agreement within LMA for NCD and PI and that between IA and LMA for PI were both satisfactory. Upon evaluation of the NCD, the agreement between IA and LMA showed unsatisfactory results, especially when the ratio between the residual tumour cells and the background was critical.

  11. [Endometrial cancer: Predictive models and clinical impact].

    Science.gov (United States)

    Bendifallah, Sofiane; Ballester, Marcos; Daraï, Emile

    2017-12-01

    In France, in 2015, endometrial cancer (CE) is the first gynecological cancer in terms of incidence and the fourth cause of cancer of the woman. About 8151 new cases and nearly 2179 deaths have been reported. Treatments (surgery, external radiotherapy, brachytherapy and chemotherapy) are currently delivered on the basis of an estimation of the recurrence risk, an estimation of lymph node metastasis or an estimate of survival probability. This risk is determined on the basis of prognostic factors (clinical, histological, imaging, biological) taken alone or grouped together in the form of classification systems, which are currently insufficient to account for the evolutionary and prognostic heterogeneity of endometrial cancer. For endometrial cancer, the concept of mathematical modeling and its application to prediction have developed in recent years. These biomathematical tools have opened a new era of care oriented towards the promotion of targeted therapies and personalized treatments. Many predictive models have been published to estimate the risk of recurrence and lymph node metastasis, but a tiny fraction of them is sufficiently relevant and of clinical utility. The optimization tracks are multiple and varied, suggesting the possibility in the near future of a place for these mathematical models. The development of high-throughput genomics is likely to offer a more detailed molecular characterization of the disease and its heterogeneity. Copyright © 2017 Société Française du Cancer. Published by Elsevier Masson SAS. All rights reserved.

  12. Model Development and Process Analysis for Lean Cellular Design Planning in Aerospace Assembly and Manufacturing

    Science.gov (United States)

    Hilburn, Monty D.

    Successful lean manufacturing and cellular manufacturing execution relies upon a foundation of leadership commitment and strategic planning built upon solid data and robust analysis. The problem for this study was to create and employ a simple lean transformation planning model and review process that could be used to identify functional support staff resources required to plan and execute lean manufacturing cells within aerospace assembly and manufacturing sites. The lean planning model was developed using available literature for lean manufacturing kaizen best practices and validated through a Delphi panel of lean experts. The resulting model and a standardized review process were used to assess the state of lean transformation planning at five sites of an international aerospace manufacturing and assembly company. The results of the three day, on-site review were compared with baseline plans collected from each of the five sites to determine if there analyzed, with focus on three critical areas of lean planning: the number and type of manufacturing cells identified, the number, type, and duration of planned lean and continuous kaizen events, and the quantity and type of functional staffing resources planned to support the kaizen schedule. Summarized data of the baseline and on-site reviews was analyzed with descriptive statistics. ANOVAs and paired-t tests at 95% significance level were conducted on the means of data sets to determine if null hypotheses related to cell, kaizen event, and support resources could be rejected. The results of the research found significant differences between lean transformation plans developed by site leadership and plans developed utilizing the structured, on-site review process and lean transformation planning model. The null hypothesis that there was no difference between the means of pre-review and on-site cell counts was rejected, as was the null hypothesis that there was no significant difference in kaizen event plans. These

  13. Cellular, molecular and functional characterisation of YAC transgenic mouse models of Friedreich ataxia.

    Directory of Open Access Journals (Sweden)

    Sara Anjomani Virmouni

    Full Text Available Friedreich ataxia (FRDA is an autosomal recessive neurodegenerative disorder, caused by a GAA repeat expansion mutation within intron 1 of the FXN gene. We have previously established and performed preliminary characterisation of several human FXN yeast artificial chromosome (YAC transgenic FRDA mouse models containing GAA repeat expansions, Y47R (9 GAA repeats, YG8R (90 and 190 GAA repeats and YG22R (190 GAA repeats.We now report extended cellular, molecular and functional characterisation of these FXN YAC transgenic mouse models. FXN transgene copy number analysis of the FRDA mice demonstrated that the YG22R and Y47R lines each have a single copy of the FXN transgene while the YG8R line has two copies. Single integration sites of all transgenes were confirmed by fluorescence in situ hybridisation (FISH analysis of metaphase and interphase chromosomes. We identified significant functional deficits, together with a degree of glucose intolerance and insulin hypersensitivity, in YG8R and YG22R FRDA mice compared to Y47R and wild-type control mice. We also confirmed increased somatic GAA repeat instability in the cerebellum and brain of YG22R and YG8R mice, together with significantly reduced levels of FXN mRNA and protein in the brain and liver of YG8R and YG22R compared to Y47R.Together these studies provide a detailed characterisation of our GAA repeat expansion-based YAC transgenic FRDA mouse models that will help investigations of FRDA disease mechanisms and therapy.

  14. Analyzing the Influence of Mobile Phone Use of Drivers on Traffic Flow Based on an Improved Cellular Automaton Model

    OpenAIRE

    Yao Xiao; Jing Shi

    2015-01-01

    This paper aimed to analyze the influence of drivers’ behavior of phone use while driving on traffic flow, including both traffic efficiency and traffic safety. An improved cellular automaton model was proposed to simulate traffic flow with distracted drivers based on the Nagel-Schreckenberg model. The driving characters of drivers using a phone were first discussed and a value representing the probability to use a phone while driving was put into the CA model. Simulation results showed that ...

  15. Dose-response modeling of early molecular and cellular key events in the CAR-mediated hepatocarcinogenesis pathway.

    Science.gov (United States)

    Geter, David R; Bhat, Virunya S; Gollapudi, B Bhaskar; Sura, Radhakrishna; Hester, Susan D

    2014-04-01

    Low-dose extrapolation and dose-related transitions are paramount in the ongoing debate regarding the quantification of cancer risks for nongenotoxic carcinogens. Phenobarbital (PB) is a prototypical nongenotoxic carcinogen that activates the constitutive androstane receptor (CAR) resulting in rodent liver tumors. In this study, male and female CD-1 mice administered dietary PB at 0, 0.15, 1.5, 15, 75, or 150 mg/kg-day for 2 or 7 days to characterize multiple apical and molecular endpoints below, at (∼75 mg/kg-day), and above the carcinogenic dose level of PB and examine these responses using benchmark dose modeling. Linear toxicokinetics were observed for all doses. Increased liver weight, hepatocellular hypertrophy, and mitotic figures were seen at 75 and 150 mg/kg-day. CAR activation, based on Cyp2b qPCR and pentoxyresorufin dealkylase activity, occurred at doses ≥ 1.5 mg/kg-day. The no-observable transcriptional effect level for global gene expression was 15 mg/kg-day. At 2 days, several xenobiotic metabolism and cell protective pathways were activated at lower doses and to a greater degree in females. However, hepatocellular proliferation, quantified by bromodeoxyuridine immunohistochemistry, was the most sensitive indicator of PB exposure with female mice more sensitive than males, contrary to sex-specific differences in sensitivity to hepatocarcinogenesis. Taken together, the identification of low-dose cellular and molecular transitions in the subtumorigenic dose range aids the understanding of early key events in CAR-mediated hepatocarcinogenesis.

  16. Modelling the interaction of aeolian and fluvial processes with a combined cellular model of sand dunes and river systems

    Science.gov (United States)

    Liu, Baoli; Coulthard, Tom J.

    2017-09-01

    Aeolian and fluvial processes are important agents for shaping the surface of the Earth, but are largely studied in isolation despite there being many locations where both processes are acting together and influencing each other. Using field data to investigate fluvial-aeolian interactions is, however, hampered by our short length of record and low temporal resolution of observations. Here we use numerical modelling to investigate, for the first time, the interplay between aeolian (sand dunes) and fluvial (river channel) processes. This modelling is carried out by combining two existing cellular models of aeolian and fluvial processes that requires considerable consideration of the different process representation and time stepping used. The result is a fully coupled (in time and space) sand dune - river model. Over a thousand-year simulation the model shows how the migration of sand dunes is readily blocked by rivers, yet aeolian processes can push the channel downwind. Over time cyclic channel avulsions develop indicating that aeolian action on fluvial systems may play an important part in governing avulsion frequency, and thus alluvial architecture.

  17. Branching process models of cancer

    CERN Document Server

    Durrett, Richard

    2015-01-01

    This volume develops results on continuous time branching processes and applies them to study rate of tumor growth, extending classic work on the Luria-Delbruck distribution. As a consequence, the authors calculate the probability that mutations that confer resistance to treatment are present at detection and quantify the extent of tumor heterogeneity. As applications, the authors evaluate ovarian cancer screening strategies and give rigorous proofs for results of Heano and Michor concerning tumor metastasis. These notes should be accessible to students who are familiar with Poisson processes and continuous time. Richard Durrett is mathematics professor at Duke University, USA. He is the author of 8 books, over 200 journal articles, and has supervised more than 40 Ph.D. students. Most of his current research concerns the applications of probability to biology: ecology, genetics, and most recently cancer.

  18. A 3-D Propagation Model for Emerging Land Mobile Radio Cellular Environments

    Science.gov (United States)

    Ahmed, Abrar; Nawaz, Syed Junaid; Gulfam, Sardar Muhammad

    2015-01-01

    A tunable stochastic geometry based Three-Dimensional (3-D) scattering model for emerging land mobile radio cellular systems is proposed. Uniformly distributed scattering objects are assumed around the Mobile Station (MS) bounded within an ellipsoidal shaped Scattering Region (SR) hollowed with an elliptically-cylindric scattering free region in immediate vicinity of MS. To ensure the degree of expected accuracy, the proposed model is designed to be tunable (as required) with nine degrees of freedom, unlike its counterparts in the existing literature. The outer and inner boundaries of SR are designed as independently scalable along all the axes and rotatable in horizontal plane around their origin centered at MS. The elevated Base Station (BS) is considered outside the SR at a certain adjustable distance and height w.r.t. position of MS. Closed-form analytical expressions for joint and marginal Probability Density Functions (PDFs) of Angle-of-Arrival (AoA) and Time-of-Arrival (ToA) are derived for both up- and down-links. The obtained analytical results for angular and temporal statistics of the channel are presented along with a thorough analysis. The impact of various physical model parameters on angular and temporal characteristics of the channel is presented, which reveals the comprehensive insight on the proposed results. To evaluate the robustness of the proposed analytical model, a comparison with experimental datasets and simulation results is also presented. The obtained analytical results for PDF of AoA observed at BS are seen to fit a vast range of empirical datasets in the literature taken for various outdoor propagation environments. In order to establish the validity of the obtained analytical results for spatial and temporal characteristics of the channel, a comparison of the proposed analytical results with the simulation results is shown, which illustrates a good fit for 107 scattering points. Moreover, the proposed model is shown to degenerate to

  19. Synergistic anti-Parkinsonism activity of high doses of B vitamins in a chronic cellular model.

    Science.gov (United States)

    Jia, Haiqun; Liu, Zhongbo; Li, Xin; Feng, Zhihui; Hao, Jiejie; Li, Xuesen; Shen, Weili; Zhang, Hongyu; Liu, Jiankang

    2010-04-01

    We propose that elevation of mitochondrial enzyme cofactors may prevent or ameliorate neurodegenerative diseases by improving mitochondrial function. In the present study, we investigated the effects of high doses of B vitamins, the precursors of mitochondrial enzyme cofactors, on mitochondrial dysfunction, oxidative stress, and Parkinsonism in a 4-week long rotenone treatment-induced cellular model of Parkinson's disease (PD). Pretreatment with B vitamins (also 4 weeks) prevented rotenone-induced: (1) mitochondrial dysfunction, including reduced mitochondrial membrane potential and activities of complex I; (2) oxidative stress, including increase in reactive oxygen species, oxidative DNA damage and protein oxidation, and (3) Parkinsonism parameters, including accumulation of alpha-synuclein and poly-ubiquitin. The optimum doses were found around 2.5- and 5-fold of that in normal MEM medium. The 4-week pretreatment was chosen based on time-dependent experiments that pretreatments longer than 2 weeks resulted in a decrease in oxidants, an increase in oxygen consumption, and up-regulation of complex I activity and PGC-1alpha expression. Individual B vitamins at the same doses did not show a similar effect suggesting that these B vitamins work synergistically. These results suggest that administration of high doses of B vitamins sufficient to elevate mitochondrial enzyme cofactors may be effective in preventing PD by reducing oxidative stress and improving mitochondrial function. Copyright (c) 2008 Elsevier Inc. All rights reserved.

  20. Impact of time delay on the dynamics of SEIR epidemic model using cellular automata

    Science.gov (United States)

    Sharma, Natasha; Gupta, Arvind Kumar

    2017-04-01

    The delay of an infectious disease is significant when aiming to predict its strength and spreading patterns. In this paper the SEIR ​(susceptible-exposed-infected-recovered) epidemic spread with time delay is analyzed through a two-dimensional cellular automata model. The time delay corresponding to the infectious span, predominantly, includes death during the latency period in due course of infection. The advancement of whole system is described by SEIR transition function complemented with crucial factors like inhomogeneous population distribution, birth and disease independent mortality. Moreover, to reflect more realistic population dynamics some stochastic parameters like population movement and connections at local level are also considered. The existence and stability of disease free equilibrium is investigated. Two prime behavioral patterns of disease dynamics is found depending on delay. The critical value of delay, beyond which there are notable variations in spread patterns, is computed. The influence of important parameters affecting the disease dynamics on basic reproduction number is also examined. The results obtained show that delay plays an affirmative role to control disease progression in an infected host.

  1. Cellular automaton for migration in ecosystem: Application of traffic model to a predator-prey system

    Science.gov (United States)

    Nagatani, Takashi; Tainaka, Kei-ichi

    2018-01-01

    In most cases, physicists have studied the migration of biospecies by the use of random walk. In the present article, we apply cellular automaton of traffic model. For simplicity, we deal with an ecosystem contains a prey and predator, and use one-dimensional lattice with two layers. Preys stay on the first layer, but predators uni-directionally move on the second layer. The spatial and temporal evolution is numerically explored. It is shown that the migration has the important effect on populations of both prey and predator. Without migration, the phase transition between a prey-phase and coexisting-phase occurs. In contrast, the phase transition disappears by migration. This is because predator can survive due to migration. We find another phase transition for spatial distribution: in one phase, prey and predator form a stripe pattern of condensation and rarefaction, while in the other phase, they uniformly distribute. The self-organized stripe may be similar to the migration patterns in real ecosystems.

  2. Cellular and molecular etiology of hepatocyte injury in a murine model of environmentally induced liver abnormality.

    Science.gov (United States)

    Al-Griw, M A; Alghazeer, R O; Al-Azreg, S A; Bennour, E M

    2016-01-01

    Exposures to a wide variety of environmental substances are negatively associated with many biological cell systems both in humans and rodents. Trichloroethane (TCE), a ubiquitous environmental toxicant, is used in large quantities as a dissolvent, metal degreaser, chemical intermediate, and component of consumer products. This increases the likelihood of human exposure to these compounds through dermal, inhalation and oral routes. The present in vivo study was aimed to investigate the possible cellular and molecular etiology of liver abnormality induced by early exposure to TCE using a murine model. The results showed a significant increase in liver weight. Histopathological examination revealed a TCE-induced hepatotoxicity which appeared as heavily congested central vein and blood sinusoids as well as leukocytic infiltration. Mitotic figures and apoptotic changes such as chromatin condensation and nuclear fragments were also identified. Cell death analysis demonstrates hepatocellular apoptosis was evident in the treated mice compared to control. TCE was also found to induce oxidative stress as indicated by an increase in the levels of lipid peroxidation, an oxidative stress marker. There was also a significant decrease in the DNA content of the hepatocytes of the treated groups compared to control. Agarose gel electrophoresis also provided further biochemical evidence of apoptosis by showing internucleosomal DNA fragmentation in the liver cells, indicating oxidative stress as the cause of DNA damage. These results suggest the need for a complete risk assessment of any new chemical prior to its arrival into the consumer market.

  3. Modeling and Simulation of Polarization in Internet Group Opinions Based on Cellular Automata

    Directory of Open Access Journals (Sweden)

    Yaofeng Zhang

    2015-01-01

    Full Text Available Hot events on Internet always attract many people who usually form one or several opinion camps through discussion. For the problem of polarization in Internet group opinions, we propose a new model based on Cellular Automata by considering neighbors, opinion leaders, and external influences. Simulation results show the following: (1 It is easy to form the polarization for both continuous opinions and discrete opinions when we only consider neighbors influence, and continuous opinions are more effective in speeding the polarization of group. (2 Coevolution mechanism takes more time to make the system stable, and the global coupling mechanism leads the system to consensus. (3 Opinion leaders play an important role in the development of consensus in Internet group opinions. However, both taking the opinion leaders as zealots and taking some randomly selected individuals as zealots are not conductive to the consensus. (4 Double opinion leaders with consistent opinions will accelerate the formation of group consensus, but the opposite opinions will lead to group polarization. (5 Only small external influences can change the evolutionary direction of Internet group opinions.

  4. Computer simulation of a cellular automata model for the immune response in a retrovirus system

    Science.gov (United States)

    Pandey, R. B.

    1989-02-01

    Immune response in a retrovirus system is modeled by a network of three binary cell elements to take into account some of the main functional features of T4 cells, T8 cells, and viruses. Two different intercell interactions are introduced, one of which leads to three fixed points while the other yields bistable fixed points oscillating between a healthy state and a sick state in a mean field treatment. Evolution of these cells is studied for quenched and annealed random interactions on a simple cubic lattice with a nearest neighbor interaction using inhomogenous cellular automata. Populations of T4 cells and viral cells oscillate together with damping (with constant amplitude) for annealed (quenched) interaction on increasing the value of mixing probability B from zero to a characteristic value B ca ( B cq). For higher B, the average number of T4 cells increases while that of the viral infected cells decreases monotonically on increasing B, suggesting a phase transition at B ca ( B cq).

  5. Collective Cellular Decision-Making Gives Developmental Plasticity: A Model of Signaling in Branching Roots

    Science.gov (United States)

    McCleery, W. Tyler; Mohd-Radzman, Nadiatul A.; Grieneisen, Veronica A.

    Cells within tissues can be regarded as autonomous entities that respond to their local environment and signaling from neighbors. Cell coordination is particularly important in plants, where root architecture must strategi