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Sample records for accurate molecular classification

  1. Accurate molecular classification of cancer using simple rules

    OpenAIRE

    Gotoh Osamu; Wang Xiaosheng

    2009-01-01

    Abstract Background One intractable problem with using microarray data analysis for cancer classification is how to reduce the extremely high-dimensionality gene feature data to remove the effects of noise. Feature selection is often used to address this problem by selecting informative genes from among thousands or tens of thousands of genes. However, most of the existing methods of microarray-based cancer classification utilize too many genes to achieve accurate classification, which often ...

  2. Accurate molecular classification of cancer using simple rules

    Directory of Open Access Journals (Sweden)

    Gotoh Osamu

    2009-10-01

    Full Text Available Abstract Background One intractable problem with using microarray data analysis for cancer classification is how to reduce the extremely high-dimensionality gene feature data to remove the effects of noise. Feature selection is often used to address this problem by selecting informative genes from among thousands or tens of thousands of genes. However, most of the existing methods of microarray-based cancer classification utilize too many genes to achieve accurate classification, which often hampers the interpretability of the models. For a better understanding of the classification results, it is desirable to develop simpler rule-based models with as few marker genes as possible. Methods We screened a small number of informative single genes and gene pairs on the basis of their depended degrees proposed in rough sets. Applying the decision rules induced by the selected genes or gene pairs, we constructed cancer classifiers. We tested the efficacy of the classifiers by leave-one-out cross-validation (LOOCV of training sets and classification of independent test sets. Results We applied our methods to five cancerous gene expression datasets: leukemia (acute lymphoblastic leukemia [ALL] vs. acute myeloid leukemia [AML], lung cancer, prostate cancer, breast cancer, and leukemia (ALL vs. mixed-lineage leukemia [MLL] vs. AML. Accurate classification outcomes were obtained by utilizing just one or two genes. Some genes that correlated closely with the pathogenesis of relevant cancers were identified. In terms of both classification performance and algorithm simplicity, our approach outperformed or at least matched existing methods. Conclusion In cancerous gene expression datasets, a small number of genes, even one or two if selected correctly, is capable of achieving an ideal cancer classification effect. This finding also means that very simple rules may perform well for cancerous class prediction.

  3. Molecular classification of gastric cancer.

    Science.gov (United States)

    Chia, N-Y; Tan, P

    2016-05-01

    Gastric cancer (GC), a heterogeneous disease characterized by epidemiologic and histopathologic differences across countries, is a leading cause of cancer-related death. Treatment of GC patients is currently suboptimal due to patients being commonly treated in a uniform fashion irrespective of disease subtype. With the advent of next-generation sequencing and other genomic technologies, GCs are now being investigated in great detail at the molecular level. High-throughput technologies now allow a comprehensive study of genomic and epigenomic alterations associated with GC. Gene mutations, chromosomal aberrations, differential gene expression and epigenetic alterations are some of the genetic/epigenetic influences on GC pathogenesis. In addition, integrative analyses of molecular profiling data have led to the identification of key dysregulated pathways and importantly, the establishment of GC molecular classifiers. Recently, The Cancer Genome Atlas (TCGA) network proposed a four subtype classification scheme for GC based on the underlying tumor molecular biology of each subtype. This landmark study, together with other studies, has expanded our understanding on the characteristics of GC at the molecular level. Such knowledge may improve the medical management of GC in the future. PMID:26861606

  4. Redundancy-Free, Accurate Analytical Center Machine for Classification

    Institute of Scientific and Technical Information of China (English)

    ZHENGFanzi; QIUZhengding; LengYonggang; YueJianhai

    2005-01-01

    Analytical center machine (ACM) has remarkable generalization performance based on analytical center of version space and outperforms SVM. From the analysis of geometry of machine learning and principle of ACM, it is showed that some training patterns are redundant to the definition of version space. Redundant patterns push ACM classifier away from analytical center of the prime version space so that the generalization performance degrades, at the same time redundant patterns slow down the classifier and reduce the efficiency of storage. Thus, an incremental algorithm is proposed to remove redundant patterns and embed into the frame of ACM that yields a Redundancy free accurate-Analytical center machine (RFA-ACM) for classification. Experiments with Heart, Thyroid, Banana datasets demonstrate the validity of RFA-ACM.

  5. Accurate mobile malware detection and classification in the cloud.

    Science.gov (United States)

    Wang, Xiaolei; Yang, Yuexiang; Zeng, Yingzhi

    2015-01-01

    As the dominator of the Smartphone operating system market, consequently android has attracted the attention of s malware authors and researcher alike. The number of types of android malware is increasing rapidly regardless of the considerable number of proposed malware analysis systems. In this paper, by taking advantages of low false-positive rate of misuse detection and the ability of anomaly detection to detect zero-day malware, we propose a novel hybrid detection system based on a new open-source framework CuckooDroid, which enables the use of Cuckoo Sandbox's features to analyze Android malware through dynamic and static analysis. Our proposed system mainly consists of two parts: anomaly detection engine performing abnormal apps detection through dynamic analysis; signature detection engine performing known malware detection and classification with the combination of static and dynamic analysis. We evaluate our system using 5560 malware samples and 6000 benign samples. Experiments show that our anomaly detection engine with dynamic analysis is capable of detecting zero-day malware with a low false negative rate (1.16 %) and acceptable false positive rate (1.30 %); it is worth noting that our signature detection engine with hybrid analysis can accurately classify malware samples with an average positive rate 98.94 %. Considering the intensive computing resources required by the static and dynamic analysis, our proposed detection system should be deployed off-device, such as in the Cloud. The app store markets and the ordinary users can access our detection system for malware detection through cloud service. PMID:26543718

  6. Accurate mobile malware detection and classification in the cloud.

    Science.gov (United States)

    Wang, Xiaolei; Yang, Yuexiang; Zeng, Yingzhi

    2015-01-01

    As the dominator of the Smartphone operating system market, consequently android has attracted the attention of s malware authors and researcher alike. The number of types of android malware is increasing rapidly regardless of the considerable number of proposed malware analysis systems. In this paper, by taking advantages of low false-positive rate of misuse detection and the ability of anomaly detection to detect zero-day malware, we propose a novel hybrid detection system based on a new open-source framework CuckooDroid, which enables the use of Cuckoo Sandbox's features to analyze Android malware through dynamic and static analysis. Our proposed system mainly consists of two parts: anomaly detection engine performing abnormal apps detection through dynamic analysis; signature detection engine performing known malware detection and classification with the combination of static and dynamic analysis. We evaluate our system using 5560 malware samples and 6000 benign samples. Experiments show that our anomaly detection engine with dynamic analysis is capable of detecting zero-day malware with a low false negative rate (1.16 %) and acceptable false positive rate (1.30 %); it is worth noting that our signature detection engine with hybrid analysis can accurately classify malware samples with an average positive rate 98.94 %. Considering the intensive computing resources required by the static and dynamic analysis, our proposed detection system should be deployed off-device, such as in the Cloud. The app store markets and the ordinary users can access our detection system for malware detection through cloud service.

  7. Accurate phylogenetic classification of DNA fragments based onsequence composition

    Energy Technology Data Exchange (ETDEWEB)

    McHardy, Alice C.; Garcia Martin, Hector; Tsirigos, Aristotelis; Hugenholtz, Philip; Rigoutsos, Isidore

    2006-05-01

    Metagenome studies have retrieved vast amounts of sequenceout of a variety of environments, leading to novel discoveries and greatinsights into the uncultured microbial world. Except for very simplecommunities, diversity makes sequence assembly and analysis a verychallenging problem. To understand the structure a 5 nd function ofmicrobial communities, a taxonomic characterization of the obtainedsequence fragments is highly desirable, yet currently limited mostly tothose sequences that contain phylogenetic marker genes. We show that forclades at the rank of domain down to genus, sequence composition allowsthe very accurate phylogenetic 10 characterization of genomic sequence.We developed a composition-based classifier, PhyloPythia, for de novophylogenetic sequence characterization and have trained it on adata setof 340 genomes. By extensive evaluation experiments we show that themethodis accurate across all taxonomic ranks considered, even forsequences that originate fromnovel organisms and are as short as 1kb.Application to two metagenome datasets 15 obtained from samples ofphosphorus-removing sludge showed that the method allows the accurateclassification at genus level of most sequence fragments from thedominant populations, while at the same time correctly characterizingeven larger parts of the samples at higher taxonomic levels.

  8. Accurate Classification of RNA Structures Using Topological Fingerprints

    Science.gov (United States)

    Li, Kejie; Gribskov, Michael

    2016-01-01

    While RNAs are well known to possess complex structures, functionally similar RNAs often have little sequence similarity. While the exact size and spacing of base-paired regions vary, functionally similar RNAs have pronounced similarity in the arrangement, or topology, of base-paired stems. Furthermore, predicted RNA structures often lack pseudoknots (a crucial aspect of biological activity), and are only partially correct, or incomplete. A topological approach addresses all of these difficulties. In this work we describe each RNA structure as a graph that can be converted to a topological spectrum (RNA fingerprint). The set of subgraphs in an RNA structure, its RNA fingerprint, can be compared with the fingerprints of other RNA structures to identify and correctly classify functionally related RNAs. Topologically similar RNAs can be identified even when a large fraction, up to 30%, of the stems are omitted, indicating that highly accurate structures are not necessary. We investigate the performance of the RNA fingerprint approach on a set of eight highly curated RNA families, with diverse sizes and functions, containing pseudoknots, and with little sequence similarity–an especially difficult test set. In spite of the difficult test set, the RNA fingerprint approach is very successful (ROC AUC > 0.95). Due to the inclusion of pseudoknots, the RNA fingerprint approach both covers a wider range of possible structures than methods based only on secondary structure, and its tolerance for incomplete structures suggests that it can be applied even to predicted structures. Source code is freely available at https://github.rcac.purdue.edu/mgribsko/XIOS_RNA_fingerprint. PMID:27755571

  9. Medulloblastoma: molecular pathways and histopathological classification.

    Science.gov (United States)

    Borowska, Anna; Jóźwiak, Jarosław

    2016-06-01

    Malignant brain tumors are the leading cause of cancer death among pediatric patients, and medulloblastoma constitutes 20% of them. Currently, the treatment is risk-adapted. Maximum surgical resection is recommended, always followed by chemotherapy and neuroaxis radiotherapy. In spite of the improving survival rate, survivors succumb to treatment-induced side effects. To reduce toxic effects, molecular-targeted treatment is proposed. Medulloblastoma research is very robust, and new articles on the subject are published daily. In the current review we have tried to bring together molecular pathophysiology of the neoplasm and current pathological classification, thus making an effort to relate tumor biology and the histological picture. PMID:27279861

  10. INDUS - a composition-based approach for rapid and accurate taxonomic classification of metagenomic sequences

    OpenAIRE

    Mohammed, Monzoorul Haque; Ghosh, Tarini Shankar; Reddy, Rachamalla Maheedhar; Reddy, Chennareddy Venkata Siva Kumar; Singh, Nitin Kumar; Sharmila S Mande

    2011-01-01

    Background Taxonomic classification of metagenomic sequences is the first step in metagenomic analysis. Existing taxonomic classification approaches are of two types, similarity-based and composition-based. Similarity-based approaches, though accurate and specific, are extremely slow. Since, metagenomic projects generate millions of sequences, adopting similarity-based approaches becomes virtually infeasible for research groups having modest computational resources. In this study, we present ...

  11. A robust and accurate formulation of molecular and colloidal electrostatics

    Science.gov (United States)

    Sun, Qiang; Klaseboer, Evert; Chan, Derek Y. C.

    2016-08-01

    This paper presents a re-formulation of the boundary integral method for the Debye-Hückel model of molecular and colloidal electrostatics that removes the mathematical singularities that have to date been accepted as an intrinsic part of the conventional boundary integral equation method. The essence of the present boundary regularized integral equation formulation consists of subtracting a known solution from the conventional boundary integral method in such a way as to cancel out the singularities associated with the Green's function. This approach better reflects the non-singular physical behavior of the systems on boundaries with the benefits of the following: (i) the surface integrals can be evaluated accurately using quadrature without any need to devise special numerical integration procedures, (ii) being able to use quadratic or spline function surface elements to represent the surface more accurately and the variation of the functions within each element is represented to a consistent level of precision by appropriate interpolation functions, (iii) being able to calculate electric fields, even at boundaries, accurately and directly from the potential without having to solve hypersingular integral equations and this imparts high precision in calculating the Maxwell stress tensor and consequently, intermolecular or colloidal forces, (iv) a reliable way to handle geometric configurations in which different parts of the boundary can be very close together without being affected by numerical instabilities, therefore potentials, fields, and forces between surfaces can be found accurately at surface separations down to near contact, and (v) having the simplicity of a formulation that does not require complex algorithms to handle singularities will result in significant savings in coding effort and in the reduction of opportunities for coding errors. These advantages are illustrated using examples drawn from molecular and colloidal electrostatics.

  12. Transcriptome classification reveals molecular subtypes in psoriasis

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    Ainali Chrysanthi

    2012-09-01

    Full Text Available Abstract Background Psoriasis is an immune-mediated disease characterised by chronically elevated pro-inflammatory cytokine levels, leading to aberrant keratinocyte proliferation and differentiation. Although certain clinical phenotypes, such as plaque psoriasis, are well defined, it is currently unclear whether there are molecular subtypes that might impact on prognosis or treatment outcomes. Results We present a pipeline for patient stratification through a comprehensive analysis of gene expression in paired lesional and non-lesional psoriatic tissue samples, compared with controls, to establish differences in RNA expression patterns across all tissue types. Ensembles of decision tree predictors were employed to cluster psoriatic samples on the basis of gene expression patterns and reveal gene expression signatures that best discriminate molecular disease subtypes. This multi-stage procedure was applied to several published psoriasis studies and a comparison of gene expression patterns across datasets was performed. Conclusion Overall, classification of psoriasis gene expression patterns revealed distinct molecular sub-groups within the clinical phenotype of plaque psoriasis. Enrichment for TGFb and ErbB signaling pathways, noted in one of the two psoriasis subgroups, suggested that this group may be more amenable to therapies targeting these pathways. Our study highlights the potential biological relevance of using ensemble decision tree predictors to determine molecular disease subtypes, in what may initially appear to be a homogenous clinical group. The R code used in this paper is available upon request.

  13. Accurate crop classification using hierarchical genetic fuzzy rule-based systems

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    Topaloglou, Charalampos A.; Mylonas, Stelios K.; Stavrakoudis, Dimitris G.; Mastorocostas, Paris A.; Theocharis, John B.

    2014-10-01

    This paper investigates the effectiveness of an advanced classification system for accurate crop classification using very high resolution (VHR) satellite imagery. Specifically, a recently proposed genetic fuzzy rule-based classification system (GFRBCS) is employed, namely, the Hierarchical Rule-based Linguistic Classifier (HiRLiC). HiRLiC's model comprises a small set of simple IF-THEN fuzzy rules, easily interpretable by humans. One of its most important attributes is that its learning algorithm requires minimum user interaction, since the most important learning parameters affecting the classification accuracy are determined by the learning algorithm automatically. HiRLiC is applied in a challenging crop classification task, using a SPOT5 satellite image over an intensively cultivated area in a lake-wetland ecosystem in northern Greece. A rich set of higher-order spectral and textural features is derived from the initial bands of the (pan-sharpened) image, resulting in an input space comprising 119 features. The experimental analysis proves that HiRLiC compares favorably to other interpretable classifiers of the literature, both in terms of structural complexity and classification accuracy. Its testing accuracy was very close to that obtained by complex state-of-the-art classification systems, such as the support vector machines (SVM) and random forest (RF) classifiers. Nevertheless, visual inspection of the derived classification maps shows that HiRLiC is characterized by higher generalization properties, providing more homogeneous classifications that the competitors. Moreover, the runtime requirements for producing the thematic map was orders of magnitude lower than the respective for the competitors.

  14. HMM-FRAME: accurate protein domain classification for metagenomic sequences containing frameshift errors

    Directory of Open Access Journals (Sweden)

    Sun Yanni

    2011-05-01

    Full Text Available Abstract Background Protein domain classification is an important step in metagenomic annotation. The state-of-the-art method for protein domain classification is profile HMM-based alignment. However, the relatively high rates of insertions and deletions in homopolymer regions of pyrosequencing reads create frameshifts, causing conventional profile HMM alignment tools to generate alignments with marginal scores. This makes error-containing gene fragments unclassifiable with conventional tools. Thus, there is a need for an accurate domain classification tool that can detect and correct sequencing errors. Results We introduce HMM-FRAME, a protein domain classification tool based on an augmented Viterbi algorithm that can incorporate error models from different sequencing platforms. HMM-FRAME corrects sequencing errors and classifies putative gene fragments into domain families. It achieved high error detection sensitivity and specificity in a data set with annotated errors. We applied HMM-FRAME in Targeted Metagenomics and a published metagenomic data set. The results showed that our tool can correct frameshifts in error-containing sequences, generate much longer alignments with significantly smaller E-values, and classify more sequences into their native families. Conclusions HMM-FRAME provides a complementary protein domain classification tool to conventional profile HMM-based methods for data sets containing frameshifts. Its current implementation is best used for small-scale metagenomic data sets. The source code of HMM-FRAME can be downloaded at http://www.cse.msu.edu/~zhangy72/hmmframe/ and at https://sourceforge.net/projects/hmm-frame/.

  15. Molecular classification of Maize cytoplasms in a breeding program

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    Colombo. N * , Presello, D.A. , Kandus M. , G.E. Eyherabide and J.C. Salerno

    2012-06-01

    Full Text Available Cytoplasmic male sterility (CMS is maternally inherited in most of higher plants species. Together with nuclear restorer genes (Rf, CMS cytoplasms contribute significantly to the efficient production of hybrid seed. Three main types of male sterile cytoplasms are known in maize: T, S and C, which can be distinguished by crossing with specific restorer lines. Recently, PCR markers have been developed allowing the identification of different cytoplasms quickly and accurately. Our objective was to classify the cytoplasm type of maize inbred lines used in our breeding program and F1s obtained from crosses between CMS lines and elite maize lines using PCR multiplex. A multiplex PCR protocol was optimized for our conditions. We obtained the molecular classification of the analyzed cytoplasms. The optimized protocol is a valuable tool to trace male sterile cytoplasms and determine hybrid seed purity in our maize breeding program.

  16. Development of Classification and Story Building Data for Accurate Earthquake Damage Estimation

    Science.gov (United States)

    Sakai, Yuki; Fukukawa, Noriko; Arai, Kensuke

    We investigated the method of developing classification and story building data from census population database in order to estimate earthquake damage more accurately especially in the urban area presuming that there are correlation between numbers of non-wooden or high-rise buildings and the population. We formulated equations of estimating numbers of wooden houses, low-to-mid-rise(1-9 story) and high-rise(over 10 story) non-wooden buildings in the 1km mesh from night and daytime population database based on the building data we investigated and collected in the selected 20 meshs in Kanto area. We could accurately estimate the numbers of three classified buildings by the formulated equations, but in some special cases, such as the apartment block mesh, the estimated values are quite different from actual values.

  17. A refined molecular taxonomy of breast cancer. : molecular classification of breast cancer

    OpenAIRE

    Guedj, Michael; Marisa, Laëtitia; De Reynies, Aurélien; Orsetti, Béatrice; Schiappa, Renaud; Bibeau, Frédéric; MacGrogan, Gaëtan; Lerebours, Florence; Finetti, Pascal; Longy, Michel; Bertheau, Philippe; Bertrand, Françoise; Bonnet, Françoise; Martin, Anne-Laure; Feugeas, Jean-Paul

    2012-01-01

    International audience; The current histoclinical breast cancer classification is simple but imprecise. Several molecular classifications of breast cancers based on expression profiling have been proposed as alternatives. However, their reliability and clinical utility have been repeatedly questioned, notably because most of them were derived from relatively small initial patient populations. We analyzed the transcriptomes of 537 breast tumors using three unsupervised classification methods. ...

  18. Integrating tumor microenvironment with cancer molecular classifications

    OpenAIRE

    Becht, Etienne; De Reyniès, Aurélien; Fridman, Wolf H.

    2015-01-01

    Editorial summary The composition of the tumor microenvironment is associated with a patient's prognosis and can be therapeutically targeted. A link between the cellular composition and genomic features of the tumor and its response to immunotherapy is beginning to emerge. Analyzing the microenvironment of tumor molecular subgroups can be a useful approach to tailor immunotherapies.

  19. Clinical and molecular classification of cardiomyopathies

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    Franco Cecchi

    2012-07-01

    Full Text Available The term “cardiomyopathies” was used for the first time 55 years ago, in 1957. Since then awareness and knowledge of this important and complex group of heart muscle diseases have improved substantially. Over these past five decades a large number of definitions, nomenclature and schemes, have been advanced by experts and consensus panel, which reflect the fast and continued advance of the scientific understanding in the field. Cardiomyopathies are a heterogeneous group of inherited myocardial diseases, which represent an important cause of disability and adverse outcome. Although considered rare diseases, the overall estimated prevalence of all cardiomyopathies is at least 3% in the general population worldwide. Furthermore, their recognition is increasing due to advances in imaging techniques and greater awareness in both the public and medical community. Cardiomyopathies represent an ideal translational model of integration between basic and clinical sciences. A multidisciplinary approach is therefore essential in order to ensure their correct diagnosis and management. In the present work, we aim to provide a concise overview of the historical background, genetic and phenotypic spectrum and evolving concepts leading to the various attempts of cardiomyopathy classifications produced over the decades.

  20. Efficient molecular subtype classification of high-grade serous ovarian cancer.

    Science.gov (United States)

    Leong, Huei San; Galletta, Laura; Etemadmoghadam, Dariush; George, Joshy; Köbel, Martin; Ramus, Susan J; Bowtell, David

    2015-07-01

    High-grade serous carcinomas (HGSCs) account for approximately 70% of all epithelial ovarian cancers diagnosed. Using microarray gene expression profiling, we previously identified four molecular subtypes of HGSC: C1 (mesenchymal), C2 (immunoreactive), C4 (differentiated), and C5 (proliferative), which correlate with patient survival and have distinct biological features. Here, we describe molecular classification of HGSC based on a limited number of genes to allow cost-effective and high-throughput subtype analysis. We determined a minimal signature for accurate classification, including 39 differentially expressed and nine control genes from microarray experiments. Taqman-based (low-density arrays and Fluidigm), fluorescent oligonucleotides (Nanostring), and targeted RNA sequencing (Illumina) assays were then compared for their ability to correctly classify fresh and formalin-fixed, paraffin-embedded samples. All platforms achieved > 90% classification accuracy with RNA from fresh frozen samples. The Illumina and Nanostring assays were superior with fixed material. We found that the C1, C2, and C4 molecular subtypes were largely consistent across multiple surgical deposits from individual chemo-naive patients. In contrast, we observed substantial subtype heterogeneity in patients whose primary ovarian sample was classified as C5. The development of an efficient molecular classifier of HGSC should enable further biological characterization of molecular subtypes and the development of targeted clinical trials. PMID:25810134

  1. Pathological Bases for a Robust Application of Cancer Molecular Classification

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    Salvador J. Diaz-Cano

    2015-04-01

    Full Text Available Any robust classification system depends on its purpose and must refer to accepted standards, its strength relying on predictive values and a careful consideration of known factors that can affect its reliability. In this context, a molecular classification of human cancer must refer to the current gold standard (histological classification and try to improve it with key prognosticators for metastatic potential, staging and grading. Although organ-specific examples have been published based on proteomics, transcriptomics and genomics evaluations, the most popular approach uses gene expression analysis as a direct correlate of cellular differentiation, which represents the key feature of the histological classification. RNA is a labile molecule that varies significantly according with the preservation protocol, its transcription reflect the adaptation of the tumor cells to the microenvironment, it can be passed through mechanisms of intercellular transference of genetic information (exosomes, and it is exposed to epigenetic modifications. More robust classifications should be based on stable molecules, at the genetic level represented by DNA to improve reliability, and its analysis must deal with the concept of intratumoral heterogeneity, which is at the origin of tumor progression and is the byproduct of the selection process during the clonal expansion and progression of neoplasms. The simultaneous analysis of multiple DNA targets and next generation sequencing offer the best practical approach for an analytical genomic classification of tumors.

  2. A Highly Accurate Classification of TM Data through Correction of Atmospheric Effects

    OpenAIRE

    Bill Smith; Frank Scarpace; Widad Elmahboub

    2009-01-01

    Atmospheric correction impacts on the accuracy of satellite image-based land cover classification are a growing concern among scientists. In this study, the principle objective was to enhance classification accuracy by minimizing contamination effects from aerosol scattering in Landsat TM images due to the variation in solar zenith angle corresponding to cloud-free earth targets. We have derived a mathematical model for aerosols to compute and subtract the aerosol scattering noise per pixel o...

  3. A Highly Accurate Classification of TM Data through Correction of Atmospheric Effects

    Directory of Open Access Journals (Sweden)

    Bill Smith

    2009-07-01

    Full Text Available Atmospheric correction impacts on the accuracy of satellite image-based land cover classification are a growing concern among scientists. In this study, the principle objective was to enhance classification accuracy by minimizing contamination effects from aerosol scattering in Landsat TM images due to the variation in solar zenith angle corresponding to cloud-free earth targets. We have derived a mathematical model for aerosols to compute and subtract the aerosol scattering noise per pixel of different vegetation classes from TM images of Nicolet in north-eastern Wisconsin. An algorithm in C++ has been developed with iterations to simulate, model, and correct for the solar zenith angle influences on scattering. Results from a supervised classification with corrected TM images showed increased class accuracy for land cover types over uncorrected images. The overall accuracy of the supervised classification was improved substantially (between 13% and 18%. The z-score shows significant difference between the corrected data and the raw data (between 4.0 and 12.0. Therefore, the atmospheric correction was essential for enhancing the image classification.

  4. A practical approach to accurate classification and staging of mycosis fungoides and Sézary syndrome.

    Science.gov (United States)

    Thomas, Bjorn Rhys; Whittaker, Sean

    2012-12-01

    Cutaneous T-cell lymphomas are rare, distinct forms of non-Hodgkin's lymphomas. Of which, mycosis fungoides (MF) and Sézary syndrome (SS) are two of the most common forms. Careful, clear classification and staging of these lymphomas allow dermatologists to commence appropriate therapy and allow correct prognostic stratification for those patients affected. Of note, patients with more advanced disease will require multi-disciplinary input in determining specialist therapy. Literature has been summarized into an outline for classification/staging of MF and SS with the aim to provide clinical dermatologists with a concise review.

  5. Current Trends in the Molecular Classification of Renal Neoplasms

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    Andrew N. Young

    2006-01-01

    Full Text Available Renal cell carcinoma (RCC is the most common form of kidney cancer in adults. RCC is a significant challenge for pathologic diagnosis and clinical management. The primary approach to diagnosis is by light microscopy, using the World Health Organization (WHO classification system, which defines histopathologic tumor subtypes with distinct clinical behavior and underlying genetic mutations. However, light microscopic diagnosis of RCC subtypes is often difficult due to variable histology. In addition, the clinical behavior of RCC is highly variable and therapeutic response rates are poor. Few clinical assays are available to predict outcome in RCC or correlate behavior with histology. Therefore, novel RCC classification systems based on gene expression should be useful for diagnosis, prognosis, and treatment. Recent microarray studies have shown that renal tumors are characterized by distinct gene expression profiles, which can be used to discover novel diagnostic and prognostic biomarkers. Here, we review clinical features of kidney cancer, the WHO classification system, and the growing role of molecular classification for diagnosis, prognosis, and therapy of this disease.

  6. Molecular Pathological Classification of Neurodegenerative Diseases: Turning towards Precision Medicine.

    Science.gov (United States)

    Kovacs, Gabor G

    2016-01-01

    Neurodegenerative diseases (NDDs) are characterized by selective dysfunction and loss of neurons associated with pathologically altered proteins that deposit in the human brain but also in peripheral organs. These proteins and their biochemical modifications can be potentially targeted for therapy or used as biomarkers. Despite a plethora of modifications demonstrated for different neurodegeneration-related proteins, such as amyloid-β, prion protein, tau, α-synuclein, TAR DNA-binding protein 43 (TDP-43), or fused in sarcoma protein (FUS), molecular classification of NDDs relies on detailed morphological evaluation of protein deposits, their distribution in the brain, and their correlation to clinical symptoms together with specific genetic alterations. A further facet of the neuropathology-based classification is the fact that many protein deposits show a hierarchical involvement of brain regions. This has been shown for Alzheimer and Parkinson disease and some forms of tauopathies and TDP-43 proteinopathies. The present paper aims to summarize current molecular classification of NDDs, focusing on the most relevant biochemical and morphological aspects. Since the combination of proteinopathies is frequent, definition of novel clusters of patients with NDDs needs to be considered in the era of precision medicine. Optimally, neuropathological categorizing of NDDs should be translated into in vivo detectable biomarkers to support better prediction of prognosis and stratification of patients for therapy trials. PMID:26848654

  7. Genetic classification and molecular mechanisms of primary dystonia

    Institute of Scientific and Technical Information of China (English)

    Xueping Chen; Huifang Shang; Zuming Luo

    2008-01-01

    BACKGROUND: Primary dystonia is a heterogeneous disease, with a complex genetic basis. In previous studies, primary dystonia was classified according to age of onset, involved regions, and other clinical characteristics. With the development of molecular genetics, new virulence genes and sites have been discovered. Therefore, there is a gradual understanding of the various forms of dystonia, based on new viewpoints. There are 15 subtypes of dystonia, based on the molecular level, i.e., DYT1 to DYT15. OBJECTIVE: To analyze the genetic development of dystonia in detail, and to further investigate molecular mechanisms of dystonia. RETRIEVAL STRATEGY: A computer-based online search was conducted in PubMed for English language publications containing the keywords "dystonia and genetic" from January 1980 to March 2007. There were 105 articles in total. Inclusion criteria: ① the contents of the articles should closely address genetic classification and molecular mechanisms of primary dystonia; ② the articles published in recent years or in high-impact journals took preference. Exclusion criteria: duplicated articles. LITERATURE EVALUATION: The selected articles were on genetic classification and molecular genetics mechanism of primary dystonia. Of those, 27 were basic or clinical studies. DATA SYNTHESIS: ① Dystonia is a heterogeneous disease, with a complex genetic basis. According to the classification of the Human Genome Organization, there are 15 dystonia subtypes, based on genetics, i.e., DYT1-DYT15,including primary dystonia, dystonia plus syndrome, degeneration plus dystonia, and paroxysmal dyskinesia plus dystonia. ② To date, the chromosomes of 13 subtypes have been localized; however, DYT2 and DYT4 remain unclear. Six subtypes have been located within virulence genes. Specifically, torsinA gene expression results in the DYT1 genotype; autosomal dominant GTP cyclohydrolase I gene expression and recessive tyrosine hydroxylase expression result in the DYT5

  8. Molecular voting for glioma classification reflecting heterogeneity in the continuum of cancer progression.

    Science.gov (United States)

    Fuller, Gregory N; Mircean, Cristian; Tabus, Ioan; Taylor, Ellen; Sawaya, Raymond; Bruner, Janet M; Shmulevich, Ilya; Zhang, Wei

    2005-09-01

    Gliomas, the most common brain tumors, are generally categorized into two lineages (astrocytic and oligodendrocytic) and further classified as low-grade (astrocytoma and oligodendroglioma), mid-grade (anaplastic astrocytoma and anaplastic oligodendroglioma), and high-grade (glioblastoma multiforme) based on morphological features. A strict classification scheme has limitations because a specific glioma can be at any stage of the continuum of cancer progression and may contain mixed features. Thus, a more comprehensive classification based on molecular signatures may reflect the biological nature of specific tumors more accurately. In this study, we used microarray technology to profile the gene expression of 49 human brain tumors and applied the k-nearest neighbor algorithm for classification. We first trained the classification gene set with 19 of the most typical glioma cases and selected a set of genes that provide the lowest cross-validation classification error with k=5. We then applied this gene set to the 30 remaining cases, including several that do not belong to gliomas such as atypical meningioma. The results showed that not only does the algorithm correctly classify most of the gliomas, but the detailed voting results also provide more subtle information regarding the molecular similarities to neighboring classes. For atypical meningioma, the voting was equally split among the four classes, indicating a difficulty in placement of meningioma into the four classes of gliomas. Thus, the actual voting results, which are typically used only to decide the winning class label in k-nearest neighbor algorithms, provide a useful method for gaining deeper insight into the stage of a tumor in the continuum of cancer development.

  9. Classification algorithms with multi-modal data fusion could accurately distinguish neuromyelitis optica from multiple sclerosis

    Directory of Open Access Journals (Sweden)

    Arman Eshaghi

    2015-01-01

    Full Text Available Neuromyelitis optica (NMO exhibits substantial similarities to multiple sclerosis (MS in clinical manifestations and imaging results and has long been considered a variant of MS. With the advent of a specific biomarker in NMO, known as anti-aquaporin 4, this assumption has changed; however, the differential diagnosis remains challenging and it is still not clear whether a combination of neuroimaging and clinical data could be used to aid clinical decision-making. Computer-aided diagnosis is a rapidly evolving process that holds great promise to facilitate objective differential diagnoses of disorders that show similar presentations. In this study, we aimed to use a powerful method for multi-modal data fusion, known as a multi-kernel learning and performed automatic diagnosis of subjects. We included 30 patients with NMO, 25 patients with MS and 35 healthy volunteers and performed multi-modal imaging with T1-weighted high resolution scans, diffusion tensor imaging (DTI and resting-state functional MRI (fMRI. In addition, subjects underwent clinical examinations and cognitive assessments. We included 18 a priori predictors from neuroimaging, clinical and cognitive measures in the initial model. We used 10-fold cross-validation to learn the importance of each modality, train and finally test the model performance. The mean accuracy in differentiating between MS and NMO was 88%, where visible white matter lesion load, normal appearing white matter (DTI and functional connectivity had the most important contributions to the final classification. In a multi-class classification problem we distinguished between all of 3 groups (MS, NMO and healthy controls with an average accuracy of 84%. In this classification, visible white matter lesion load, functional connectivity, and cognitive scores were the 3 most important modalities. Our work provides preliminary evidence that computational tools can be used to help make an objective differential diagnosis

  10. Network analysis of genes regulated in renal diseases: implications for a molecular-based classification

    Directory of Open Access Journals (Sweden)

    Jagadish HV

    2009-09-01

    Full Text Available Abstract Background Chronic renal diseases are currently classified based on morphological similarities such as whether they produce predominantly inflammatory or non-inflammatory responses. However, such classifications do not reliably predict the course of the disease and its response to therapy. In contrast, recent studies in diseases such as breast cancer suggest that a classification which includes molecular information could lead to more accurate diagnoses and prediction of treatment response. This article describes how we extracted gene expression profiles from biopsies of patients with chronic renal diseases, and used network visualizations and associated quantitative measures to rapidly analyze similarities and differences between the diseases. Results The analysis revealed three main regularities: (1 Many genes associated with a single disease, and fewer genes associated with many diseases. (2 Unexpected combinations of renal diseases that share relatively large numbers of genes. (3 Uniform concordance in the regulation of all genes in the network. Conclusion The overall results suggest the need to define a molecular-based classification of renal diseases, in addition to hypotheses for the unexpected patterns of shared genes and the uniformity in gene concordance. Furthermore, the results demonstrate the utility of network analyses to rapidly understand complex relationships between diseases and regulated genes.

  11. Accurate Medium-Term Wind Power Forecasting in a Censored Classification Framework

    DEFF Research Database (Denmark)

    Dahl, Christian M.; Croonenbroeck, Carsten

    2014-01-01

    We provide a wind power forecasting methodology that exploits many of the actual data's statistical features, in particular both-sided censoring. While other tools ignore many of the important “stylized facts” or provide forecasts for short-term horizons only, our approach focuses on medium......-term forecasts, which are especially necessary for practitioners in the forward electricity markets of many power trading places; for example, NASDAQ OMX Commodities (formerly Nord Pool OMX Commodities) in northern Europe. We show that our model produces turbine-specific forecasts that are significantly more...... accurate in comparison to established benchmark models and present an application that illustrates the financial impact of more accurate forecasts obtained using our methodology....

  12. GPD: A Graph Pattern Diffusion Kernel for Accurate Graph Classification with Applications in Cheminformatics

    OpenAIRE

    Smalter, Aaron; Huan, Jun; Jia, Yi; Lushington, Gerald

    2010-01-01

    Graph data mining is an active research area. Graphs are general modeling tools to organize information from heterogeneous sources and have been applied in many scientific, engineering, and business fields. With the fast accumulation of graph data, building highly accurate predictive models for graph data emerges as a new challenge that has not been fully explored in the data mining community. In this paper, we demonstrate a novel technique called graph pattern diffusion (GPD) kernel. Our ide...

  13. Two fast and accurate heuristic RBF learning rules for data classification.

    Science.gov (United States)

    Rouhani, Modjtaba; Javan, Dawood S

    2016-03-01

    This paper presents new Radial Basis Function (RBF) learning methods for classification problems. The proposed methods use some heuristics to determine the spreads, the centers and the number of hidden neurons of network in such a way that the higher efficiency is achieved by fewer numbers of neurons, while the learning algorithm remains fast and simple. To retain network size limited, neurons are added to network recursively until termination condition is met. Each neuron covers some of train data. The termination condition is to cover all training data or to reach the maximum number of neurons. In each step, the center and spread of the new neuron are selected based on maximization of its coverage. Maximization of coverage of the neurons leads to a network with fewer neurons and indeed lower VC dimension and better generalization property. Using power exponential distribution function as the activation function of hidden neurons, and in the light of new learning approaches, it is proved that all data became linearly separable in the space of hidden layer outputs which implies that there exist linear output layer weights with zero training error. The proposed methods are applied to some well-known datasets and the simulation results, compared with SVM and some other leading RBF learning methods, show their satisfactory and comparable performance. PMID:26797472

  14. Novel approaches for the molecular classification of prostate cancer

    Institute of Scientific and Technical Information of China (English)

    Robert H. Getzenberg

    2010-01-01

    @@ Among the urologic cancers, prostate cancer is by far the most common, and it appears to have the potential to affect almost all men throughout the world as they age. A number of studies have shown that many men with prostate cancer will not die from their disease, but rather with the disease but from other causes. These men have a form of prostate cancer that is de-scribed as "very low risk" and has often been called indolent. There are however a group of men that have a form of prostate cancer that is much more aggressive and life threatening. Unlike other cancer types, we have few tools to provide for the molecular classification of prostate cancer.

  15. Classification of signaling proteins based on molecular star graph descriptors using Machine Learning models.

    Science.gov (United States)

    Fernandez-Lozano, Carlos; Cuiñas, Rubén F; Seoane, José A; Fernández-Blanco, Enrique; Dorado, Julian; Munteanu, Cristian R

    2015-11-01

    Signaling proteins are an important topic in drug development due to the increased importance of finding fast, accurate and cheap methods to evaluate new molecular targets involved in specific diseases. The complexity of the protein structure hinders the direct association of the signaling activity with the molecular structure. Therefore, the proposed solution involves the use of protein star graphs for the peptide sequence information encoding into specific topological indices calculated with S2SNet tool. The Quantitative Structure-Activity Relationship classification model obtained with Machine Learning techniques is able to predict new signaling peptides. The best classification model is the first signaling prediction model, which is based on eleven descriptors and it was obtained using the Support Vector Machines-Recursive Feature Elimination (SVM-RFE) technique with the Laplacian kernel (RFE-LAP) and an AUROC of 0.961. Testing a set of 3114 proteins of unknown function from the PDB database assessed the prediction performance of the model. Important signaling pathways are presented for three UniprotIDs (34 PDBs) with a signaling prediction greater than 98.0%. PMID:26297890

  16. A molecular classification of human mesenchymal stromal cells.

    Science.gov (United States)

    Rohart, Florian; Mason, Elizabeth A; Matigian, Nicholas; Mosbergen, Rowland; Korn, Othmar; Chen, Tyrone; Butcher, Suzanne; Patel, Jatin; Atkinson, Kerry; Khosrotehrani, Kiarash; Fisk, Nicholas M; Lê Cao, Kim-Anh; Wells, Christine A

    2016-01-01

    Mesenchymal stromal cells (MSC) are widely used for the study of mesenchymal tissue repair, and increasingly adopted for cell therapy, despite the lack of consensus on the identity of these cells. In part this is due to the lack of specificity of MSC markers. Distinguishing MSC from other stromal cells such as fibroblasts is particularly difficult using standard analysis of surface proteins, and there is an urgent need for improved classification approaches. Transcriptome profiling is commonly used to describe and compare different cell types; however, efforts to identify specific markers of rare cellular subsets may be confounded by the small sample sizes of most studies. Consequently, it is difficult to derive reproducible, and therefore useful markers. We addressed the question of MSC classification with a large integrative analysis of many public MSC datasets. We derived a sparse classifier (The Rohart MSC test) that accurately distinguished MSC from non-MSC samples with >97% accuracy on an internal training set of 635 samples from 41 studies derived on 10 different microarray platforms. The classifier was validated on an external test set of 1,291 samples from 65 studies derived on 15 different platforms, with >95% accuracy. The genes that contribute to the MSC classifier formed a protein-interaction network that included known MSC markers. Further evidence of the relevance of this new MSC panel came from the high number of Mendelian disorders associated with mutations in more than 65% of the network. These result in mesenchymal defects, particularly impacting on skeletal growth and function. The Rohart MSC test is a simple in silico test that accurately discriminates MSC from fibroblasts, other adult stem/progenitor cell types or differentiated stromal cells. It has been implemented in the www.stemformatics.org resource, to assist researchers wishing to benchmark their own MSC datasets or data from the public domain. The code is available from the CRAN

  17. Gene expression classification of colon cancer into molecular subtypes: characterization, validation, and prognostic value.

    Directory of Open Access Journals (Sweden)

    Laetitia Marisa

    Full Text Available BACKGROUND: Colon cancer (CC pathological staging fails to accurately predict recurrence, and to date, no gene expression signature has proven reliable for prognosis stratification in clinical practice, perhaps because CC is a heterogeneous disease. The aim of this study was to establish a comprehensive molecular classification of CC based on mRNA expression profile analyses. METHODS AND FINDINGS: Fresh-frozen primary tumor samples from a large multicenter cohort of 750 patients with stage I to IV CC who underwent surgery between 1987 and 2007 in seven centers were characterized for common DNA alterations, including BRAF, KRAS, and TP53 mutations, CpG island methylator phenotype, mismatch repair status, and chromosomal instability status, and were screened with whole genome and transcriptome arrays. 566 samples fulfilled RNA quality requirements. Unsupervised consensus hierarchical clustering applied to gene expression data from a discovery subset of 443 CC samples identified six molecular subtypes. These subtypes were associated with distinct clinicopathological characteristics, molecular alterations, specific enrichments of supervised gene expression signatures (stem cell phenotype-like, normal-like, serrated CC phenotype-like, and deregulated signaling pathways. Based on their main biological characteristics, we distinguished a deficient mismatch repair subtype, a KRAS mutant subtype, a cancer stem cell subtype, and three chromosomal instability subtypes, including one associated with down-regulated immune pathways, one with up-regulation of the Wnt pathway, and one displaying a normal-like gene expression profile. The classification was validated in the remaining 123 samples plus an independent set of 1,058 CC samples, including eight public datasets. Furthermore, prognosis was analyzed in the subset of stage II-III CC samples. The subtypes C4 and C6, but not the subtypes C1, C2, C3, and C5, were independently associated with shorter relapse

  18. Head and neck paragangliomas: clinical and molecular genetic classification.

    Science.gov (United States)

    Offergeld, Christian; Brase, Christoph; Yaremchuk, Svetlana; Mader, Irina; Rischke, Hans Christian; Gläsker, Sven; Schmid, Kurt W; Wiech, Thorsten; Preuss, Simon F; Suárez, Carlos; Kopeć, Tomasz; Patocs, Attila; Wohllk, Nelson; Malekpour, Mahdi; Boedeker, Carsten C; Neumann, Hartmut P H

    2012-01-01

    Head and neck paragangliomas are tumors arising from specialized neural crest cells. Prominent locations are the carotid body along with the vagal, jugular, and tympanic glomus. Head and neck paragangliomas are slowly growing tumors, with some carotid body tumors being reported to exist for many years as a painless lateral mass on the neck. Symptoms depend on the specific locations. In contrast to paraganglial tumors of the adrenals, abdomen and thorax, head and neck paragangliomas seldom release catecholamines and are hence rarely vasoactive. Petrous bone, jugular, and tympanic head and neck paragangliomas may cause hearing loss. The internationally accepted clinical classifications for carotid body tumors are based on the Shamblin Class I-III stages, which correspond to postoperative permanent side effects. For petrous-bone paragangliomas in the head and neck, the Fisch classification is used. Regarding the molecular genetics, head and neck paragangliomas have been associated with nine susceptibility genes: NF1, RET, VHL, SDHA, SDHB, SDHC, SDHD, SDHAF2 (SDH5), and TMEM127. Hereditary HNPs are mostly caused by mutations of the SDHD gene, but SDHB and SDHC mutations are not uncommon in such patients. Head and neck paragangliomas are rarely associated with mutations of VHL, RET, or NF1. The research on SDHA, SDHAF2 and TMEM127 is ongoing. Multiple head and neck paragangliomas are common in patients with SDHD mutations, while malignant head and neck paraganglioma is mostly seen in patients with SDHB mutations. The treatment of choice is surgical resection. Good postoperative results can be expected in carotid body tumors of Shamblin Class I and II, whereas operations on other carotid body tumors and other head and neck paragangliomas frequently result in deficits of the cranial nerves adjacent to the tumors. Slow growth and the tendency of hereditary head and neck paragangliomas to be multifocal may justify less aggressive treatment strategies. PMID:22584701

  19. Head and neck paragangliomas: clinical and molecular genetic classification

    Directory of Open Access Journals (Sweden)

    Christian Offergeld

    2012-01-01

    Full Text Available Head and neck paragangliomas are tumors arising from specialized neural crest cells. Prominent locations are the carotid body along with the vagal, jugular, and tympanic glomus. Head and neck paragangliomas are slowly growing tumors, with some carotid body tumors being reported to exist for many years as a painless lateral mass on the neck. Symptoms depend on the specific locations. In contrast to paraganglial tumors of the adrenals, abdomen and thorax, head and neck paragangliomas seldom release catecholamines and are hence rarely vasoactive. Petrous bone, jugular, and tympanic head and neck paragangliomas may cause hearing loss. The internationally accepted clinical classifications for carotid body tumors are based on the Shamblin Class I-III stages, which correspond to postoperative permanent side effects. For petrous-bone paragangliomas in the head and neck, the Fisch classification is used. Regarding the molecular genetics, head and neck paragangliomas have been associated with nine susceptibility genes: NF1, RET, VHL, SDHA, SDHB, SDHC, SDHD, SDHAF2 (SDH5, and TMEM127. Hereditary HNPs are mostly caused by mutations of the SDHD gene, but SDHB and SDHC mutations are not uncommon in such patients. Head and neck paragangliomas are rarely associated with mutations of VHL, RET, or NF1. The research on SDHA, SDHAF2 and TMEM127 is ongoing. Multiple head and neck paragangliomas are common in patients with SDHD mutations, while malignant head and neck paraganglioma is mostly seen in patients with SDHB mutations. The treatment of choice is surgical resection. Good postoperative results can be expected in carotid body tumors of Shamblin Class I and II, whereas operations on other carotid body tumors and other head and neck paragangliomas frequently result in deficits of the cranial nerves adjacent to the tumors. Slow growth and the tendency of hereditary head and neck paragangliomas to be multifocal may justify less aggressive treatment strategies.

  20. A simplified approach for the molecular classification of glioblastomas.

    Directory of Open Access Journals (Sweden)

    Marie Le Mercier

    Full Text Available Glioblastoma (GBM is the most common malignant primary brain tumors in adults and exhibit striking aggressiveness. Although GBM constitute a single histological entity, they exhibit considerable variability in biological behavior, resulting in significant differences in terms of prognosis and response to treatment. In an attempt to better understand the biology of GBM, many groups have performed high-scale profiling studies based on gene or protein expression. These studies have revealed the existence of several GBM subtypes. Although there remains to be a clear consensus, two to four major subtypes have been identified. Interestingly, these different subtypes are associated with both differential prognoses and responses to therapy. In the present study, we investigated an alternative immunohistochemistry (IHC-based approach to achieve a molecular classification for GBM. For this purpose, a cohort of 100 surgical GBM samples was retrospectively evaluated by immunohistochemical analysis of EGFR, PDGFRA and p53. The quantitative analysis of these immunostainings allowed us to identify the following two GBM subtypes: the "Classical-like" (CL subtype, characterized by EGFR-positive and p53- and PDGFRA-negative staining and the "Proneural-like" (PNL subtype, characterized by p53- and/or PDGFRA-positive staining. This classification represents an independent prognostic factor in terms of overall survival compared to age, extent of resection and adjuvant treatment, with a significantly longer survival associated with the PNL subtype. Moreover, these two GBM subtypes exhibited different responses to chemotherapy. The addition of temozolomide to conventional radiotherapy significantly improved the survival of patients belonging to the CL subtype, but it did not affect the survival of patients belonging to the PNL subtype. We have thus shown that it is possible to differentiate between different clinically relevant subtypes of GBM by using IHC

  1. Machine learning predictions of molecular properties: Accurate many-body potentials and nonlocality in chemical space

    International Nuclear Information System (INIS)

    Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstrate prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the 'holy grail' of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. The same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies

  2. Accurate studies on the full vibrational energy spectra and molecular dissociation energies for some electronic states of N2 molecule

    Institute of Scientific and Technical Information of China (English)

    REN; Weiyi; SUN; Weiguo; HOU; Shilin; FENG; Hao

    2005-01-01

    It is usually very difficult to directly obtain molecular dissociation energy De and all accurate high-lying vibrational energies for most diatomic electronic states using modern experimental techniques or quantum theories, and it is also very difficult to give accurate analytical expression for diatomic molecular dissociation energy. This study proposes a new analytical formula for obtaining accurate molecular dissociation energy based on the LeRoy and Bernstein's energy expression in dissociation limit. A set of full vibrational energy spectra for some electronic states of N2 molecule are studied using the algebraic method (AM) suggested recently, and the corresponding accurate molecular dissociation energies are evaluated using the proposed new formula and high-lying AM vibrational energies. The results show that the AM spectra and the new theoretical dissociation energies agree excellently with experimental data, and thereby providing a new physical approach to generating accurate dissociation energies for electronic states of diatomic molecules.

  3. Molecular Simulation of the Free Energy for the Accurate Determination of Phase Transition Properties of Molecular Solids

    Science.gov (United States)

    Sellers, Michael; Lisal, Martin; Brennan, John

    2015-06-01

    Investigating the ability of a molecular model to accurately represent a real material is crucial to model development and use. When the model simulates materials in extreme conditions, one such property worth evaluating is the phase transition point. However, phase transitions are often overlooked or approximated because of difficulty or inaccuracy when simulating them. Techniques such as super-heating or super-squeezing a material to induce a phase change suffer from inherent timescale limitations leading to ``over-driving,'' and dual-phase simulations require many long-time runs to seek out what frequently results in an inexact location of phase-coexistence. We present a compilation of methods for the determination of solid-solid and solid-liquid phase transition points through the accurate calculation of the chemical potential. The methods are applied to the Smith-Bharadwaj atomistic potential's representation of cyclotrimethylene trinitramine (RDX) to accurately determine its melting point (Tm) and the alpha to gamma solid phase transition pressure. We also determine Tm for a coarse-grain model of RDX, and compare its value to experiment and atomistic counterpart. All methods are employed via the LAMMPS simulator, resulting in 60-70 simulations that total 30-50 ns. Approved for public release. Distribution is unlimited.

  4. A large catalog of accurate distances to molecular clouds from PS1 photometry

    Energy Technology Data Exchange (ETDEWEB)

    Schlafly, E. F.; Rix, H.-W.; Martin, N. F. [Max Planck Institute for Astronomy, Königstuhl 17, D-69117 Heidelberg (Germany); Green, G.; Finkbeiner, D. P. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Bell, E. F. [Department of Astronomy, University of Michigan, 500 Church Street, Ann Arbor, MI 48109 (United States); Burgett, W. S.; Chambers, K. C.; Hodapp, K. W.; Kaiser, N.; Magnier, E. A.; Tonry, J. L. [Institute for Astronomy, University of Hawaii, 2680 Woodlawn Drive, Honolulu, HI 96822 (United States); Draper, P. W.; Metcalfe, N. [Department of Physics, Durham University, South Road, Durham DH1 3LE (United Kingdom); Price, P. A. [Department of Astrophysical Sciences, Princeton University, Princeton, NJ 08544 (United States)

    2014-05-01

    Distance measurements to molecular clouds are important but are often made separately for each cloud of interest, employing very different data and techniques. We present a large, homogeneous catalog of distances to molecular clouds, most of which are of unprecedented accuracy. We determine distances using optical photometry of stars along lines of sight toward these clouds, obtained from PanSTARRS-1. We simultaneously infer the reddenings and distances to these stars, tracking the full probability distribution function using a technique presented in Green et al. We fit these star-by-star measurements using a simple dust screen model to find the distance to each cloud. We thus estimate the distances to almost all of the clouds in the Magnani et al. catalog, as well as many other well-studied clouds, including Orion, Perseus, Taurus, Cepheus, Polaris, California, and Monoceros R2, avoiding only the inner Galaxy. Typical statistical uncertainties in the distances are 5%, though the systematic uncertainty stemming from the quality of our stellar models is about 10%. The resulting catalog is the largest catalog of accurate, directly measured distances to molecular clouds. Our distance estimates are generally consistent with available distance estimates from the literature, though in some cases the literature estimates are off by a factor of more than two.

  5. Molecular Classification of Gastric Cancer: A new paradigm

    Science.gov (United States)

    Shah, Manish A.; Khanin, Raya; Tang, Laura; Janjigian, Yelena Y.; Klimstra, David S.; Gerdes, Hans; Kelsen, David P.

    2011-01-01

    Purpose Gastric cancer may be subdivided into three distinct subtypes –proximal, diffuse, and distal gastric cancer– based on histopathologic and anatomic criteria. Each subtype is associated with unique epidemiology. Our aim is to test the hypothesis that these distinct gastric cancer subtypes may also be distinguished by gene expression analysis. Experimental Design Patients with localized gastric adenocarcinoma being screened for a phase II preoperative clinical trial (NCI 5917) underwent endoscopic biopsy for fresh tumor procurement. 4–6 targeted biopsies of the primary tumor were obtained. Macrodissection was performed to ensure >80% carcinoma in the sample. HG-U133A GeneChip (Affymetrix) was used for cDNA expression analysis, and all arrays were processed and analyzed using the Bioconductor R-package. Results Between November 2003 and January 2006, 57 patients were screened to identify 36 patients with localized gastric cancer who had adequate RNA for expression analysis. Using supervised analysis, we built a classifier to distinguish the three gastric cancer subtypes, successfully classifying each into tightly grouped clusters. Leave-one-out cross validation error was 0.14, suggesting that >85% of samples were classified correctly. Gene set analysis with the False Discovery Rate set at 0.25 identified several pathways that were differentially regulated when comparing each gastric cancer subtype to adjacent normal stomach. Conclusions Subtypes of gastric cancer that have epidemiologic and histologic distinction are also distinguished by gene expression data. These preliminary data suggest a new classification of gastric cancer with implications for improving our understanding of disease biology and identification of unique molecular drivers for each gastric cancer subtype. PMID:21430069

  6. PyVCI: A flexible open-source code for calculating accurate molecular infrared spectra

    Science.gov (United States)

    Sibaev, Marat; Crittenden, Deborah L.

    2016-06-01

    The PyVCI program package is a general purpose open-source code for simulating accurate molecular spectra, based upon force field expansions of the potential energy surface in normal mode coordinates. It includes harmonic normal coordinate analysis and vibrational configuration interaction (VCI) algorithms, implemented primarily in Python for accessibility but with time-consuming routines written in C. Coriolis coupling terms may be optionally included in the vibrational Hamiltonian. Non-negligible VCI matrix elements are stored in sparse matrix format to alleviate the diagonalization problem. CPU and memory requirements may be further controlled by algorithmic choices and/or numerical screening procedures, and recommended values are established by benchmarking using a test set of 44 molecules for which accurate analytical potential energy surfaces are available. Force fields in normal mode coordinates are obtained from the PyPES library of high quality analytical potential energy surfaces (to 6th order) or by numerical differentiation of analytic second derivatives generated using the GAMESS quantum chemical program package (to 4th order).

  7. Surface electron density models for accurate ab initio molecular dynamics with electronic friction

    Science.gov (United States)

    Novko, D.; Blanco-Rey, M.; Alducin, M.; Juaristi, J. I.

    2016-06-01

    Ab initio molecular dynamics with electronic friction (AIMDEF) is a valuable methodology to study the interaction of atomic particles with metal surfaces. This method, in which the effect of low-energy electron-hole (e-h) pair excitations is treated within the local density friction approximation (LDFA) [Juaristi et al., Phys. Rev. Lett. 100, 116102 (2008), 10.1103/PhysRevLett.100.116102], can provide an accurate description of both e-h pair and phonon excitations. In practice, its applicability becomes a complicated task in those situations of substantial surface atoms displacements because the LDFA requires the knowledge at each integration step of the bare surface electron density. In this work, we propose three different methods of calculating on-the-fly the electron density of the distorted surface and we discuss their suitability under typical surface distortions. The investigated methods are used in AIMDEF simulations for three illustrative adsorption cases, namely, dissociated H2 on Pd(100), N on Ag(111), and N2 on Fe(110). Our AIMDEF calculations performed with the three approaches highlight the importance of going beyond the frozen surface density to accurately describe the energy released into e-h pair excitations in case of large surface atom displacements.

  8. Warm gas in the rotating disk of the Red Rectangle: accurate models of molecular line emission

    CERN Document Server

    Bujarrabal, V

    2013-01-01

    We aim to study the excitation conditions of the molecular gas in the rotating disk of the Red Rectangle, the only post-Asymptotic-Giant-Branch object in which the existence of an equatorial rotating disk has been demonstrated. For this purpose, we developed a complex numerical code that accurately treats radiative transfer in 2-D, adapted to the study of molecular lines from rotating disks. We present far-infrared Herschel/HIFI observations of the 12CO and 13CO J=6-5, J=10-9, and J=16-15 transitions in the Red Rectangle. We also present our code in detail and discuss the accuracy of its predictions, from comparison with well-tested codes. Theoretical line profiles are compared with the empirical data to deduce the physical conditions in the disk by means of model fitting. We conclude that our code is very efficient and produces reliable results. The comparison of the theoretical predictions with our observations reveals that the temperature of the Red Rectangle disk is typically ~ 100-150 K, about twice as h...

  9. Hydration free energies of cyanide and hydroxide ions from molecular dynamics simulations with accurate force fields

    Science.gov (United States)

    Lee, M.W.; Meuwly, M.

    2013-01-01

    The evaluation of hydration free energies is a sensitive test to assess force fields used in atomistic simulations. We showed recently that the vibrational relaxation times, 1D- and 2D-infrared spectroscopies for CN(-) in water can be quantitatively described from molecular dynamics (MD) simulations with multipolar force fields and slightly enlarged van der Waals radii for the C- and N-atoms. To validate such an approach, the present work investigates the solvation free energy of cyanide in water using MD simulations with accurate multipolar electrostatics. It is found that larger van der Waals radii are indeed necessary to obtain results close to the experimental values when a multipolar force field is used. For CN(-), the van der Waals ranges refined in our previous work yield hydration free energy between -72.0 and -77.2 kcal mol(-1), which is in excellent agreement with the experimental data. In addition to the cyanide ion, we also study the hydroxide ion to show that the method used here is readily applicable to similar systems. Hydration free energies are found to sensitively depend on the intermolecular interactions, while bonded interactions are less important, as expected. We also investigate in the present work the possibility of applying the multipolar force field in scoring trajectories generated using computationally inexpensive methods, which should be useful in broader parametrization studies with reduced computational resources, as scoring is much faster than the generation of the trajectories.

  10. Pediatric Medulloblastoma – Update on Molecular Classification Driving Targeted Therapies

    OpenAIRE

    Ruth eDeSouza; Jones, Benjamin R. T.; Lowis, Stephen P.; Kurian, Kathreena M.

    2014-01-01

    As advances in the molecular and genetic profiling of paediatric medulloblastoma evolve, associations with prognosis and treatment are found (prognostic and predictive biomarkers) and research is directed at molecular therapies. Medulloblastoma typically affects young patients, where the implications of any treatment on the developing brain must be carefully considered. The aim of this article is to provide a clear comprehensible update on the role molecular profiling and subgroups in paediat...

  11. A molecular classification of human mesenchymal stromal cells

    OpenAIRE

    Rohart, Florian; Mason, Elizabeth A.; Matigian, Nicholas; Mosbergen, Rowland; Korn, Othmar; Chen, Tyrone; Butcher, Suzanne; Patel, Jatin; Atkinson, Kerry; Khosrotehrani, Kiarash; Fisk, Nicholas M.; Lê Cao, Kim-Anh; Wells, Christine A

    2016-01-01

    Mesenchymal stromal cells (MSC) are widely used for the study of mesenchymal tissue repair, and increasingly adopted for cell therapy, despite the lack of consensus on the identity of these cells. In part this is due to the lack of specificity of MSC markers. Distinguishing MSC from other stromal cells such as fibroblasts is particularly difficult using standard analysis of surface proteins, and there is an urgent need for improved classification approaches. Transcriptome profiling is commonl...

  12. A simple method to combine multiple molecular biomarkers for dichotomous diagnostic classification

    Directory of Open Access Journals (Sweden)

    Amin Manik A

    2006-10-01

    Full Text Available Abstract Background In spite of the recognized diagnostic potential of biomarkers, the quest for squelching noise and wringing in information from a given set of biomarkers continues. Here, we suggest a statistical algorithm that – assuming each molecular biomarker to be a diagnostic test – enriches the diagnostic performance of an optimized set of independent biomarkers employing established statistical techniques. We validated the proposed algorithm using several simulation datasets in addition to four publicly available real datasets that compared i subjects having cancer with those without; ii subjects with two different cancers; iii subjects with two different types of one cancer; and iv subjects with same cancer resulting in differential time to metastasis. Results Our algorithm comprises of three steps: estimating the area under the receiver operating characteristic curve for each biomarker, identifying a subset of biomarkers using linear regression and combining the chosen biomarkers using linear discriminant function analysis. Combining these established statistical methods that are available in most statistical packages, we observed that the diagnostic accuracy of our approach was 100%, 99.94%, 96.67% and 93.92% for the real datasets used in the study. These estimates were comparable to or better than the ones previously reported using alternative methods. In a synthetic dataset, we also observed that all the biomarkers chosen by our algorithm were indeed truly differentially expressed. Conclusion The proposed algorithm can be used for accurate diagnosis in the setting of dichotomous classification of disease states.

  13. Accurate molecular structure and spectroscopic properties for nucleobases: A combined computational - microwave investigation of 2-thiouracil as a case study

    Science.gov (United States)

    Puzzarini, Cristina; Biczysko, Malgorzata; Barone, Vincenzo; Peña, Isabel; Cabezas, Carlos; Alonso, José L.

    2015-01-01

    The computational composite scheme purposely set up for accurately describing the electronic structure and spectroscopic properties of small biomolecules has been applied to the first study of the rotational spectrum of 2-thiouracil. The experimental investigation was made possible thanks to the combination of the laser ablation technique with Fourier Transform Microwave spectrometers. The joint experimental – computational study allowed us to determine accurate molecular structure and spectroscopic properties for the title molecule, but more important, it demonstrates a reliable approach for the accurate investigation of isolated small biomolecules. PMID:24002739

  14. Review of current classification, molecular alterations, and tyrosine kinase inhibitor therapies in myeloproliferative disorders with hypereosinophilia

    Directory of Open Access Journals (Sweden)

    Havelange V

    2013-08-01

    Full Text Available Violaine Havelange,1,2 Jean-Baptiste Demoulin1 1de Duve Institute, Université catholique de Louvain, Brussels, Belgium; 2Department of Hematology, Cliniques universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium Abstract: Recent advances in our understanding of the molecular mechanisms underlying hypereosinophilia have led to the development of a 'molecular' classification of myeloproliferative disorders with eosinophilia. The revised 2008 World Health Organization classification of myeloid neoplasms included a new category called “myeloid and lymphoid neoplasms with eosinophilia and abnormalities of PDGFRA, PDGFRB or FGFR1.” Despite the molecular heterogeneity of PDGFR (platelet-derived growth factor receptor rearrangements, tyrosine kinase inhibitors at low dose induce rapid and complete hematological remission in the majority of these patients. Other kinase inhibitors are promising. Further discoveries of new molecular alterations will direct the development of new specific inhibitors. In this review, an update of the classifications of myeloproliferative disorders associated with hypereosinophilia is discussed together with open and controversial questions. Molecular mechanisms and promising results of tyrosine kinase inhibitor treatments are reviewed. Keywords: hypereosinophilia, classification, myeloproliferative disorders, molecular alterations, tyrosine kinase inhibitor

  15. Morphologic, Molecular, and Taxonomic Evolution of Renal Cell Carcinoma: A Conceptual Perspective With Emphasis on Updates to the 2016 World Health Organization Classification.

    Science.gov (United States)

    Udager, Aaron M; Mehra, Rohit

    2016-10-01

    Molecular and morphologic interrogation has driven a much-needed reexamination of renal cell carcinoma (RCC). Indeed, the recently released 2016 World Health Organization classification now recognizes 12 distinct RCC subtypes, as well as several other emerging/provisional RCC entities. From a clinical perspective, accurate RCC classification may have important implications for patients and their families, including prognostic risk stratification, targeted therapeutics selection, and identification for genetic testing. In this review, we provide a conceptual framework for approaching RCC diagnosis and classification by categorizing RCCs as tumors with clear cytoplasm, papillary architecture, and eosinophilic (oncocytic) cytoplasm. The currently recognized 2016 World Health Organization classification for RCC subtypes is briefly discussed, including new diagnostic entities (clear cell papillary RCC, hereditary leiomyomatosis and RCC-associated RCC, succinate dehydrogenase-deficient RCC, tubulocystic RCC, and acquired cystic disease-associated RCC) and areas of evolving RCC classification, such as transcription elongation factor B subunit 1 (TCEB1)-mutated RCC/RCC with angioleiomyoma-like stroma/RCC with leiomyomatous stroma, RCC associated with anaplastic lymphoma receptor tyrosine kinase (ALK) gene rearrangement, thyroidlike follicular RCC, and RCC in neuroblastoma survivors. For each RCC subtype, relevant clinical, molecular, gross, and microscopic findings are reviewed, and ancillary studies helpful for its differential diagnosis are presented, providing a practical approach to modern RCC classification. PMID:27684973

  16. Classification

    Science.gov (United States)

    Clary, Renee; Wandersee, James

    2013-01-01

    In this article, Renee Clary and James Wandersee describe the beginnings of "Classification," which lies at the very heart of science and depends upon pattern recognition. Clary and Wandersee approach patterns by first telling the story of the "Linnaean classification system," introduced by Carl Linnacus (1707-1778), who is…

  17. Topology representing network enables highly accurate classification of protein images taken by cryo electron-microscope without masking.

    Science.gov (United States)

    Ogura, Toshihiko; Iwasaki, Kenji; Sato, Chikara

    2003-09-01

    In single-particle analysis, a three-dimensional (3-D) structure of a protein is constructed using electron microscopy (EM). As these images are very noisy in general, the primary process of this 3-D reconstruction is the classification of images according to their Euler angles, the images in each classified group then being averaged to reduce the noise level. In our newly developed strategy of classification, we introduce a topology representing network (TRN) method. It is a modified method of a growing neural gas network (GNG). In this system, a network structure is automatically determined in response to the images input through a growing process. After learning without a masking procedure, the GNG creates clear averages of the inputs as unit coordinates in multi-dimensional space, which are then utilized for classification. In the process, connections are automatically created between highly related units and their positions are shifted where the inputs are distributed in multi-dimensional space. Consequently, several separated groups of connected units are formed. Although the interrelationship of units in this space are not easily understood, we succeeded in solving this problem by converting the unit positions into two-dimensional (2-D) space, and by further optimizing the unit positions with the simulated annealing (SA) method. In the optimized 2-D map, visualization of the connections of units provided rich information about clustering. As demonstrated here, this method is clearly superior to both the multi-variate statistical analysis (MSA) and the self-organizing map (SOM) as a classification method and provides a first reliable classification method which can be used without masking for very noisy images. PMID:14572474

  18. Appraisal of progenitor markers in the context of molecular classification of breast cancers

    OpenAIRE

    Haviv, Izhak

    2011-01-01

    Clinical management of breast cancer relies on case stratification, which increasingly employs molecular markers. The motivation behind delineating breast epithelial differentiation is to better target cancer cases through innate sensitivities bequeathed to the cancer from its normal progenitor state. A combination of histopathological and molecular classification of breast cancer cases suggests a role for progenitors in particular breast cancer cases. Although a remarkable fraction of the re...

  19. Molecular phylogeny of the Bothriocephalidea (Cestoda): molecular data challenge morphological classification.

    Science.gov (United States)

    Brabec, Jan; Waeschenbach, Andrea; Scholz, Tomáš; Littlewood, D Timothy J; Kuchta, Roman

    2015-10-01

    In this study, the relationships of the cestode order Bothriocephalidea, parasites of marine and freshwater bony fish, were assessed using multi-gene molecular phylogenetic analyses. The dataset included 59 species, covering approximately 70% of currently recognised genera, a sample of bothriocephalidean biodiversity gathered through an intense 15year effort. The order as currently circumscribed, while monophyletic, includes three non-monophyletic and one monophyletic families. Bothriocephalidae is monophyletic and forms the most derived lineage of the order, comprised of a single freshwater and several marine clades. Biogeographic patterns within the freshwater clade are indicative of past radiations having occurred in Africa and North America. The earliest diverging lineages of the order comprise a paraphyletic Triaenophoridae. The Echinophallidae, consisting nearly exclusively of parasites of pelagic fish, was also resolved as paraphyletic with respect to the Bothriocephalidae. Philobythoides sp., the only representative included from the Philobythiidae, a unique family of parasites of bathypelagic fish, was sister to the genus Eubothrium, the latter constituting one of the lineages of the paraphyletic Triaenophoridae. Due to the weak statistical support for most of the basal nodes of the Triaenophoridae and Echinophallidae, as well as the lack of obvious morphological synapomorphies shared by taxa belonging to the statistically well-supported lineages, the current family-level classification, although mostly non-monophyletic, is provisionally retained, with the exception of the family Philobythiidae, which is recognised as a synonym of the Triaenophoridae. In addition, Schyzocotyle is resurrected to accommodate the invasive Asian fish tapeworm, Schyzocotyle acheilognathi (Yamaguti, 1934) n. comb. (syn. Bothriocephalus acheilognathi Yamaguti, 1934), which is of veterinary importance, and Schyzocotyle nayarensis (Malhotra, 1983) n. comb. (syn. Ptychobothrium

  20. Molecular and Translational Classifications of DAMPs in Immunogenic Cell Death

    Directory of Open Access Journals (Sweden)

    Abhishek D Garg

    2015-11-01

    Full Text Available The immunogenicity of malignant cells has recently been acknowledged as a critical determinant of efficacy in cancer therapy. Thus, besides developing direct immunostimulatory regimens including dendritic cell-based vaccines, checkpoint-blocking therapies, and adoptive T-cell transfer, researchers have started to focus on the overall immunobiology of neoplastic cells. It is now clear that cancer cells can succumb to some anticancer therapies by undergoing a peculiar form of cell death that is characterized by an increased immunogenic potential, owing to the emission of so-called damage-associated molecular patterns (DAMPs. The emission of DAMPs and other immunostimulatory factors by cells succumbing to immunogenic cell death (ICD favors the establishment of a productive interface with the immune system. This results in the elicitation of tumor-targeting immune responses associated with the elimination of residual, treatment-resistant cancer cells, as well as with the establishment of immunological memory. Although ICD has been characterized with increased precision since its discovery, several questions remain to be addressed. Here, we summarize and tabulate the main molecular, immunological, preclinical and clinical aspects of ICD, in an attempt to capture the essence of this clinically relevant phenomenon, and identify future challenges for this rapidly expanding field of investigation.

  1. A non-contact method based on multiple signal classification algorithm to reduce the measurement time for accurately heart rate detection

    Science.gov (United States)

    Bechet, P.; Mitran, R.; Munteanu, M.

    2013-08-01

    Non-contact methods for the assessment of vital signs are of great interest for specialists due to the benefits obtained in both medical and special applications, such as those for surveillance, monitoring, and search and rescue. This paper investigates the possibility of implementing a digital processing algorithm based on the MUSIC (Multiple Signal Classification) parametric spectral estimation in order to reduce the observation time needed to accurately measure the heart rate. It demonstrates that, by proper dimensioning the signal subspace, the MUSIC algorithm can be optimized in order to accurately assess the heart rate during an 8-28 s time interval. The validation of the processing algorithm performance was achieved by minimizing the mean error of the heart rate after performing simultaneous comparative measurements on several subjects. In order to calculate the error the reference value of heart rate was measured using a classic measurement system through direct contact.

  2. Molecular and biochemical classification of plant-derived food allergens.

    Science.gov (United States)

    Breiteneder, H; Ebner, C

    2000-07-01

    Molecular biology and biochemical techniques have significantly advanced the knowledge of allergens derived from plant foods. Surprisingly, many of the known plant food allergens are homologous to pathogenesis-related proteins (PRs), proteins that are induced by pathogens, wounding, or certain environmental stresses. PRs have been classified into 14 families. Examples of allergens homologous to PRs include chitinases (PR-3 family) from avocado, banana, and chestnut; antifungal proteins such as the thaumatin-like proteins (PR-5) from cherry and apple; proteins homologous to the major birch pollen allergen Bet v 1 (PR-10) from vegetables and fruits; and lipid transfer proteins (PR-14) from fruits and cereals. Allergens other than PR homologs can be allotted to other well-known protein families such as inhibitors of alpha-amylases and trypsin from cereal seeds, profilins from fruits and vegetables, seed storage proteins from nuts and mustard seeds, and proteases from fruits. As more clinical data and structural information on allergenic molecules becomes available, we may finally be able to answer what characteristics of a molecule are responsible for its allergenicity.

  3. Laryngeal Squamous Intraepithelial Lesions: An Updated Review on Etiology, Classification, Molecular Changes, and Treatment.

    Science.gov (United States)

    Gale, Nina; Gnepp, Douglas R; Poljak, Mario; Strojan, Primož; Cardesa, Antonio; Helliwell, Tim; Šifrer, Robert; Volavšek, Metka; Sandison, Ann; Zidar, Nina

    2016-03-01

    Laryngeal carcinogenesis is a multistep process, characterized by an accumulation of genetic changes associated with architectural and cytologic alterations, ranging from squamous hyperplasia to carcinoma in situ and encompassed by the terminology of squamous intraepithelial lesions (SILs). The etiology, classification, genetic changes, and malignant progression of these lesions are reviewed. Tobacco remains the principal etiological factor with gastroesophageal reflux disease recently considered as a possible factor. In contrast, there is little evidence that microbiological agents, especially human papillomavirus infection, are frequently involved in laryngeal carcinogenesis and probably subjectivity, remains the mainstay of accurate diagnosis, prognosis, and guidance for a patient's treatment. The currently used classifications, the dysplasia system, squamous intraepithelial neoplasia, and the Ljubljana classification, reflect different standpoints on this important topic. The modified Ljubljana classification, with good interobserver agreement, could be considered as a proposal for a unified classification of laryngeal SILs. This review also briefly discusses recently discovered genetic changes, such as CDKN2A and CTNNB1 genes, and chromosome instability of chromosomes 1 and 7; however, none of these can at present improve histologic diagnosis. Malignant progression of precursor lesions varies from 2% to 74%, according to different studies. Cold-steel microinstruments, CO2 laser, and radiotherapy are used to treat the different grades of precursor lesions. There is as yet no worldwide agreement on the treatment of high-grade lesions and carcinoma in situ. PMID:26849814

  4. From Molecular Classification to Targeted Therapeutics: The Changing Face of Systemic Therapy in Metastatic Gastroesophageal Cancer

    Directory of Open Access Journals (Sweden)

    Adrian Murphy

    2015-01-01

    Full Text Available Histological classification of adenocarcinoma or squamous cell carcinoma for esophageal cancer or using the Lauren classification for intestinal and diffuse type gastric cancer has limited clinical utility in the management of advanced disease. Germline mutations in E-cadherin (CDH1 or mismatch repair genes (Lynch syndrome were identified many years ago but given their rarity, the identification of these molecular alterations does not substantially impact treatment in the advanced setting. Recent molecular profiling studies of upper GI tumors have added to our knowledge of the underlying biology but have not led to an alternative classification system which can guide clinician’s therapeutic decisions. Recently the Cancer Genome Atlas Research Network has proposed four subtypes of gastric cancer dividing tumors into those positive for Epstein-Barr virus, microsatellite unstable tumors, genomically stable tumors, and tumors with chromosomal instability. Unfortunately to date, many phase III clinical trials involving molecularly targeted agents have failed to meet their survival endpoints due to their use in unselected populations. Future clinical trials should utilize molecular profiling of individual tumors in order to determine the optimal use of targeted therapies in preselected patients.

  5. From molecular classification to targeted therapeutics: the changing face of systemic therapy in metastatic gastroesophageal cancer.

    Science.gov (United States)

    Murphy, Adrian; Kelly, Ronan J

    2015-01-01

    Histological classification of adenocarcinoma or squamous cell carcinoma for esophageal cancer or using the Lauren classification for intestinal and diffuse type gastric cancer has limited clinical utility in the management of advanced disease. Germline mutations in E-cadherin (CDH1) or mismatch repair genes (Lynch syndrome) were identified many years ago but given their rarity, the identification of these molecular alterations does not substantially impact treatment in the advanced setting. Recent molecular profiling studies of upper GI tumors have added to our knowledge of the underlying biology but have not led to an alternative classification system which can guide clinician's therapeutic decisions. Recently the Cancer Genome Atlas Research Network has proposed four subtypes of gastric cancer dividing tumors into those positive for Epstein-Barr virus, microsatellite unstable tumors, genomically stable tumors, and tumors with chromosomal instability. Unfortunately to date, many phase III clinical trials involving molecularly targeted agents have failed to meet their survival endpoints due to their use in unselected populations. Future clinical trials should utilize molecular profiling of individual tumors in order to determine the optimal use of targeted therapies in preselected patients.

  6. Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning

    CERN Document Server

    Rupp, Matthias; Müller, Klaus-Robert; von Lilienfeld, O Anatole

    2011-01-01

    We introduce a machine learning model to predict atomization energies of a diverse set of organic molecules, based on nuclear charges and atomic positions only. The problem of solving the molecular Schr\\"odinger equation is mapped onto a non-linear statistical regression problem of reduced complexity. Regression models are trained on and compared to atomization energies computed with hybrid density-functional theory. Cross-validation over more than seven thousand small organic molecules yields a mean absolute error of ~10 kcal/mol. Applicability is demonstrated for the prediction of molecular atomization potential energy curves.

  7. Fast, Simple and Accurate Handwritten Digit Classification by Training Shallow Neural Network Classifiers with the 'Extreme Learning Machine' Algorithm.

    Science.gov (United States)

    McDonnell, Mark D; Tissera, Migel D; Vladusich, Tony; van Schaik, André; Tapson, Jonathan

    2015-01-01

    Recent advances in training deep (multi-layer) architectures have inspired a renaissance in neural network use. For example, deep convolutional networks are becoming the default option for difficult tasks on large datasets, such as image and speech recognition. However, here we show that error rates below 1% on the MNIST handwritten digit benchmark can be replicated with shallow non-convolutional neural networks. This is achieved by training such networks using the 'Extreme Learning Machine' (ELM) approach, which also enables a very rapid training time (∼ 10 minutes). Adding distortions, as is common practise for MNIST, reduces error rates even further. Our methods are also shown to be capable of achieving less than 5.5% error rates on the NORB image database. To achieve these results, we introduce several enhancements to the standard ELM algorithm, which individually and in combination can significantly improve performance. The main innovation is to ensure each hidden-unit operates only on a randomly sized and positioned patch of each image. This form of random 'receptive field' sampling of the input ensures the input weight matrix is sparse, with about 90% of weights equal to zero. Furthermore, combining our methods with a small number of iterations of a single-batch backpropagation method can significantly reduce the number of hidden-units required to achieve a particular performance. Our close to state-of-the-art results for MNIST and NORB suggest that the ease of use and accuracy of the ELM algorithm for designing a single-hidden-layer neural network classifier should cause it to be given greater consideration either as a standalone method for simpler problems, or as the final classification stage in deep neural networks applied to more difficult problems.

  8. Fast, Simple and Accurate Handwritten Digit Classification by Training Shallow Neural Network Classifiers with the 'Extreme Learning Machine' Algorithm.

    Directory of Open Access Journals (Sweden)

    Mark D McDonnell

    Full Text Available Recent advances in training deep (multi-layer architectures have inspired a renaissance in neural network use. For example, deep convolutional networks are becoming the default option for difficult tasks on large datasets, such as image and speech recognition. However, here we show that error rates below 1% on the MNIST handwritten digit benchmark can be replicated with shallow non-convolutional neural networks. This is achieved by training such networks using the 'Extreme Learning Machine' (ELM approach, which also enables a very rapid training time (∼ 10 minutes. Adding distortions, as is common practise for MNIST, reduces error rates even further. Our methods are also shown to be capable of achieving less than 5.5% error rates on the NORB image database. To achieve these results, we introduce several enhancements to the standard ELM algorithm, which individually and in combination can significantly improve performance. The main innovation is to ensure each hidden-unit operates only on a randomly sized and positioned patch of each image. This form of random 'receptive field' sampling of the input ensures the input weight matrix is sparse, with about 90% of weights equal to zero. Furthermore, combining our methods with a small number of iterations of a single-batch backpropagation method can significantly reduce the number of hidden-units required to achieve a particular performance. Our close to state-of-the-art results for MNIST and NORB suggest that the ease of use and accuracy of the ELM algorithm for designing a single-hidden-layer neural network classifier should cause it to be given greater consideration either as a standalone method for simpler problems, or as the final classification stage in deep neural networks applied to more difficult problems.

  9. A Large Catalog of Accurate Distances to Molecular Clouds from PS1 Photometry

    CERN Document Server

    Schlafly, E F; Finkbeiner, D P; Rix, H -W; Bell, E F; Burgett, W S; Chambers, K C; Draper, P W; Hodapp, K W; Kaiser, N; Magnier, E A; Martin, N F; Metcalfe, N; Price, P A; Tonry, J L

    2014-01-01

    Distance measurements to molecular clouds are important, but are often made separately for each cloud of interest, employing very different different data and techniques. We present a large, homogeneous catalog of distances to molecular clouds, most of which are of unprecedented accuracy. We determine distances using optical photometry of stars along lines of sight toward these clouds, obtained from PanSTARRS-1. We simultaneously infer the reddenings and distances to these stars, tracking the full probability distribution function using a technique presented in Green et al. (2014). We fit these star-by-star measurements using a simple dust screen model to find the distance to each cloud. We thus estimate the distances to almost all of the clouds in the Magnani et al. (1985) catalog, as well as many other well-studied clouds, including Orion, Perseus, Taurus, Cepheus, Polaris, California, and Monoceros R2, avoiding only the inner Galaxy. Typical statistical uncertainties in the distances are 5%, though the sys...

  10. Utilizing fast multipole expansions for efficient and accurate quantum-classical molecular dynamics simulations.

    Science.gov (United States)

    Schwörer, Magnus; Lorenzen, Konstantin; Mathias, Gerald; Tavan, Paul

    2015-03-14

    Recently, a novel approach to hybrid quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) simulations has been suggested [Schwörer et al., J. Chem. Phys. 138, 244103 (2013)]. Here, the forces acting on the atoms are calculated by grid-based density functional theory (DFT) for a solute molecule and by a polarizable molecular mechanics (PMM) force field for a large solvent environment composed of several 10(3)-10(5) molecules as negative gradients of a DFT/PMM hybrid Hamiltonian. The electrostatic interactions are efficiently described by a hierarchical fast multipole method (FMM). Adopting recent progress of this FMM technique [Lorenzen et al., J. Chem. Theory Comput. 10, 3244 (2014)], which particularly entails a strictly linear scaling of the computational effort with the system size, and adapting this revised FMM approach to the computation of the interactions between the DFT and PMM fragments of a simulation system, here, we show how one can further enhance the efficiency and accuracy of such DFT/PMM-MD simulations. The resulting gain of total performance, as measured for alanine dipeptide (DFT) embedded in water (PMM) by the product of the gains in efficiency and accuracy, amounts to about one order of magnitude. We also demonstrate that the jointly parallelized implementation of the DFT and PMM-MD parts of the computation enables the efficient use of high-performance computing systems. The associated software is available online. PMID:25770527

  11. 善用《中图法》(第五版)改善图书文献归类准确性%Books and Documents'Accurate Classification by Using Chinese Library Classification ( Sth Edition)

    Institute of Scientific and Technical Information of China (English)

    汤彩霞

    2011-01-01

    从三个方面讨论如何善用《中图法》(第五版)(以下简称CLC5)改善图书文献归类准确性,分别是:做好和CLC5相关的前期准备工作,如新旧分类法的比对等;了解和掌握《中图法》(第五版)的部分通用分类规则;制定启用CLC5的本馆分类规定。%From three aspects, this paper discusses how to classify books and documents accurately by using the Chinese Library Classification (Sth Edition) (hereafter referred to as CLC5 ), such as: making a good preliminary preparation for CLCS, including the comparison of the new with the old classification, etc. ; Understanding and grasping some universal classification rules of CLCS; Making the regulations of launching CLC5 in our library.

  12. Accurate reaction-diffusion operator splitting on tetrahedral meshes for parallel stochastic molecular simulations.

    Science.gov (United States)

    Hepburn, I; Chen, W; De Schutter, E

    2016-08-01

    Spatial stochastic molecular simulations in biology are limited by the intense computation required to track molecules in space either in a discrete time or discrete space framework, which has led to the development of parallel methods that can take advantage of the power of modern supercomputers in recent years. We systematically test suggested components of stochastic reaction-diffusion operator splitting in the literature and discuss their effects on accuracy. We introduce an operator splitting implementation for irregular meshes that enhances accuracy with minimal performance cost. We test a range of models in small-scale MPI simulations from simple diffusion models to realistic biological models and find that multi-dimensional geometry partitioning is an important consideration for optimum performance. We demonstrate performance gains of 1-3 orders of magnitude in the parallel implementation, with peak performance strongly dependent on model specification. PMID:27497550

  13. A simple and accurate algorithm for path integral molecular dynamics with the Langevin thermostat

    Science.gov (United States)

    Liu, Jian; Li, Dezhang; Liu, Xinzijian

    2016-07-01

    We introduce a novel simple algorithm for thermostatting path integral molecular dynamics (PIMD) with the Langevin equation. The staging transformation of path integral beads is employed for demonstration. The optimum friction coefficients for the staging modes in the free particle limit are used for all systems. In comparison to the path integral Langevin equation thermostat, the new algorithm exploits a different order of splitting for the phase space propagator associated to the Langevin equation. While the error analysis is made for both algorithms, they are also employed in the PIMD simulations of three realistic systems (the H2O molecule, liquid para-hydrogen, and liquid water) for comparison. It is shown that the new thermostat increases the time interval of PIMD by a factor of 4-6 or more for achieving the same accuracy. In addition, the supplementary material shows the error analysis made for the algorithms when the normal-mode transformation of path integral beads is used.

  14. Accurate reaction-diffusion operator splitting on tetrahedral meshes for parallel stochastic molecular simulations

    Science.gov (United States)

    Hepburn, I.; Chen, W.; De Schutter, E.

    2016-08-01

    Spatial stochastic molecular simulations in biology are limited by the intense computation required to track molecules in space either in a discrete time or discrete space framework, which has led to the development of parallel methods that can take advantage of the power of modern supercomputers in recent years. We systematically test suggested components of stochastic reaction-diffusion operator splitting in the literature and discuss their effects on accuracy. We introduce an operator splitting implementation for irregular meshes that enhances accuracy with minimal performance cost. We test a range of models in small-scale MPI simulations from simple diffusion models to realistic biological models and find that multi-dimensional geometry partitioning is an important consideration for optimum performance. We demonstrate performance gains of 1-3 orders of magnitude in the parallel implementation, with peak performance strongly dependent on model specification.

  15. A simple and accurate algorithm for path integral molecular dynamics with the Langevin thermostat.

    Science.gov (United States)

    Liu, Jian; Li, Dezhang; Liu, Xinzijian

    2016-07-14

    We introduce a novel simple algorithm for thermostatting path integral molecular dynamics (PIMD) with the Langevin equation. The staging transformation of path integral beads is employed for demonstration. The optimum friction coefficients for the staging modes in the free particle limit are used for all systems. In comparison to the path integral Langevin equation thermostat, the new algorithm exploits a different order of splitting for the phase space propagator associated to the Langevin equation. While the error analysis is made for both algorithms, they are also employed in the PIMD simulations of three realistic systems (the H2O molecule, liquid para-hydrogen, and liquid water) for comparison. It is shown that the new thermostat increases the time interval of PIMD by a factor of 4-6 or more for achieving the same accuracy. In addition, the supplementary material shows the error analysis made for the algorithms when the normal-mode transformation of path integral beads is used.

  16. Quantification and classification of substituent effects in organic chemistry: a theoretical molecular electrostatic potential study.

    Science.gov (United States)

    Remya, Geetha S; Suresh, Cherumuttathu H

    2016-07-27

    Substituent effects in organic chemistry are generally described in terms of experimentally derived Hammett parameters whereas a convenient theoretical tool to study these effects in π-conjugated molecular systems is molecular electrostatic potential (MESP) analysis. The present study shows that the difference between MESP at the nucleus of the para carbon of substituted benzene and a carbon atom in benzene, designated as ΔVC, is very useful to quantify and classify substituent effects. On the basis of positive and negative ΔVC values, a broad classification of around 381 substituents into electron withdrawing and donating categories is made. Each category is again sorted based on the magnitude of ΔVC into subcategories such as very strong, strong, medium, and weak electron donating/withdrawing. Furthermore, the data are used to show the transferability and additivity of substituent effects in π-conjugated organic molecules such as condensed aromatic, olefinic, acetylenic, and heterocyclic systems. The transferability properties hold good for ΔVC in all these molecular systems. The additive properties of substituent effects are strongly reflected on ΔVC and the predictive power of the data to assign the total substituent effects of multi-substituted systems is verified. The ΔVC data and the present classification of substituents are very useful to design π-conjugated organic molecular systems with desired electron rich/poor character.

  17. Predicting accurate fluorescent spectra for high molecular weight polycyclic aromatic hydrocarbons using density functional theory

    Science.gov (United States)

    Powell, Jacob; Heider, Emily C.; Campiglia, Andres; Harper, James K.

    2016-10-01

    The ability of density functional theory (DFT) methods to predict accurate fluorescence spectra for polycyclic aromatic hydrocarbons (PAHs) is explored. Two methods, PBE0 and CAM-B3LYP, are evaluated both in the gas phase and in solution. Spectra for several of the most toxic PAHs are predicted and compared to experiment, including three isomers of C24H14 and a PAH containing heteroatoms. Unusually high-resolution experimental spectra are obtained for comparison by analyzing each PAH at 4.2 K in an n-alkane matrix. All theoretical spectra visually conform to the profiles of the experimental data but are systematically offset by a small amount. Specifically, when solvent is included the PBE0 functional overestimates peaks by 16.1 ± 6.6 nm while CAM-B3LYP underestimates the same transitions by 14.5 ± 7.6 nm. These calculated spectra can be empirically corrected to decrease the uncertainties to 6.5 ± 5.1 and 5.7 ± 5.1 nm for the PBE0 and CAM-B3LYP methods, respectively. A comparison of computed spectra in the gas phase indicates that the inclusion of n-octane shifts peaks by +11 nm on average and this change is roughly equivalent for PBE0 and CAM-B3LYP. An automated approach for comparing spectra is also described that minimizes residuals between a given theoretical spectrum and all available experimental spectra. This approach identifies the correct spectrum in all cases and excludes approximately 80% of the incorrect spectra, demonstrating that an automated search of theoretical libraries of spectra may eventually become feasible.

  18. Use of multivariate analysis to suggest a new molecular classification of colorectal cancer

    Science.gov (United States)

    Domingo, Enric; Ramamoorthy, Rajarajan; Oukrif, Dahmane; Rosmarin, Daniel; Presz, Michal; Wang, Haitao; Pulker, Hannah; Lockstone, Helen; Hveem, Tarjei; Cranston, Treena; Danielsen, Havard; Novelli, Marco; Davidson, Brian; Xu, Zheng-Zhou; Molloy, Peter; Johnstone, Elaine; Holmes, Christopher; Midgley, Rachel; Kerr, David; Sieber, Oliver; Tomlinson, Ian

    2013-01-01

    Abstract Molecular classification of colorectal cancer (CRC) is currently based on microsatellite instability (MSI), KRAS or BRAF mutation and, occasionally, chromosomal instability (CIN). Whilst useful, these categories may not fully represent the underlying molecular subgroups. We screened 906 stage II/III CRCs from the VICTOR clinical trial for somatic mutations. Multivariate analyses (logistic regression, clustering, Bayesian networks) identified the primary molecular associations. Positive associations occurred between: CIN and TP53 mutation; MSI and BRAF mutation; and KRAS and PIK3CA mutations. Negative associations occurred between: MSI and CIN; MSI and NRAS mutation; and KRAS mutation, and each of NRAS, TP53 and BRAF mutations. Some complex relationships were elucidated: KRAS and TP53 mutations had both a direct negative association and a weaker, confounding, positive association via TP53–CIN–MSI–BRAF–KRAS. Our results suggested a new molecular classification of CRCs: (1) MSI+ and/or BRAF-mutant; (2) CIN+ and/or TP53– mutant, with wild-type KRAS and PIK3CA; (3) KRAS- and/or PIK3CA-mutant, CIN+, TP53-wild-type; (4) KRAS– and/or PIK3CA-mutant, CIN–, TP53-wild-type; (5) NRAS-mutant; (6) no mutations; (7) others. As expected, group 1 cancers were mostly proximal and poorly differentiated, usually occurring in women. Unexpectedly, two different types of CIN+ CRC were found: group 2 cancers were usually distal and occurred in men, whereas group 3 showed neither of these associations but were of higher stage. CIN+ cancers have conventionally been associated with all three of these variables, because they have been tested en masse. Our classification also showed potentially improved prognostic capabilities, with group 3, and possibly group 1, independently predicting disease-free survival. Copyright © 2012 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. PMID:23165447

  19. Automated Analysis and Classification of Histological Tissue Features by Multi-Dimensional Microscopic Molecular Profiling.

    Directory of Open Access Journals (Sweden)

    Daniel P Riordan

    Full Text Available Characterization of the molecular attributes and spatial arrangements of cells and features within complex human tissues provides a critical basis for understanding processes involved in development and disease. Moreover, the ability to automate steps in the analysis and interpretation of histological images that currently require manual inspection by pathologists could revolutionize medical diagnostics. Toward this end, we developed a new imaging approach called multidimensional microscopic molecular profiling (MMMP that can measure several independent molecular properties in situ at subcellular resolution for the same tissue specimen. MMMP involves repeated cycles of antibody or histochemical staining, imaging, and signal removal, which ultimately can generate information analogous to a multidimensional flow cytometry analysis on intact tissue sections. We performed a MMMP analysis on a tissue microarray containing a diverse set of 102 human tissues using a panel of 15 informative antibody and 5 histochemical stains plus DAPI. Large-scale unsupervised analysis of MMMP data, and visualization of the resulting classifications, identified molecular profiles that were associated with functional tissue features. We then directly annotated H&E images from this MMMP series such that canonical histological features of interest (e.g. blood vessels, epithelium, red blood cells were individually labeled. By integrating image annotation data, we identified molecular signatures that were associated with specific histological annotations and we developed statistical models for automatically classifying these features. The classification accuracy for automated histology labeling was objectively evaluated using a cross-validation strategy, and significant accuracy (with a median per-pixel rate of 77% per feature from 15 annotated samples for de novo feature prediction was obtained. These results suggest that high-dimensional profiling may advance the

  20. The molecular subtype classification is a determinant of sentinel node positivity in early breast carcinoma.

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    Fabien Reyal

    Full Text Available INTRODUCTION: Several authors have underscored a strong relation between the molecular subtypes and the axillary status of breast cancer patients. The aim of our work was to decipher the interaction between this classification and the probability of a positive sentinel node biopsy. MATERIALS AND METHODS: Our dataset consisted of a total number of 2654 early-stage breast cancer patients. Patients treated at first by conservative breast surgery plus sentinel node biopsies were selected. A multivariate logistic regression model was trained and validated. Interaction covariate between ER and HER2 markers was a forced input of this model. The performance of the multivariate model in the training and the two validation sets was analyzed in terms of discrimination and calibration. Probability of axillary metastasis was detailed for each molecular subtype. RESULTS: The interaction covariate between ER and HER2 status was a stronger predictor (p = 0.0031 of positive sentinel node biopsy than the ER status by itself (p = 0.016. A multivariate model to determine the probability of sentinel node positivity was defined with the following variables; tumour size, lympho-vascular invasion, molecular subtypes and age at diagnosis. This model showed similar results in terms of discrimination (AUC = 0.72/0.73/0.72 and calibration (HL p = 0.28/0.05/0.11 in the training and validation sets. The interaction between molecular subtypes, tumour size and sentinel nodes status was approximated. DISCUSSION: We showed that biologically-driven analyses are able to build new models with higher performance in terms of breast cancer axillary status prediction. The molecular subtype classification strongly interacts with the axillary and distant metastasis process.

  1. History, Classification, Molecular Structure and Properties of Dendrimers which are a New Concept in Textile

    Directory of Open Access Journals (Sweden)

    Osman NAMIRTI

    2011-02-01

    Full Text Available Over the last 20 years polymer chemistry has created a number of non-lineer structures and introduction of a large number of branches during the polymer synthesis leads to obtain molecules with many end groups. Two types of these polymers are regularly branched "dendrimers" and "hyperbranched polymers" where branching is formed randomly. In this article knowledge about history, classification, molecular structure and properties of dendrimers which have found various application areas also in textile due to their special structures is given.

  2. Molecular classification of fatty liver by high-throughput profiling of protein post-translational modifications.

    Science.gov (United States)

    Urasaki, Yasuyo; Fiscus, Ronald R; Le, Thuc T

    2016-04-01

    We describe an alternative approach to classifying fatty liver by profiling protein post-translational modifications (PTMs) with high-throughput capillary isoelectric focusing (cIEF) immunoassays. Four strains of mice were studied, with fatty livers induced by different causes, such as ageing, genetic mutation, acute drug usage, and high-fat diet. Nutrient-sensitive PTMs of a panel of 12 liver metabolic and signalling proteins were simultaneously evaluated with cIEF immunoassays, using nanograms of total cellular protein per assay. Changes to liver protein acetylation, phosphorylation, and O-N-acetylglucosamine glycosylation were quantified and compared between normal and diseased states. Fatty liver tissues could be distinguished from one another by distinctive protein PTM profiles. Fatty liver is currently classified by morphological assessment of lipid droplets, without identifying the underlying molecular causes. In contrast, high-throughput profiling of protein PTMs has the potential to provide molecular classification of fatty liver.

  3. Bottom-up coarse-grained models that accurately describe the structure, pressure, and compressibility of molecular liquids

    Energy Technology Data Exchange (ETDEWEB)

    Dunn, Nicholas J. H.; Noid, W. G., E-mail: wnoid@chem.psu.edu [Department of Chemistry, The Pennsylvania State University, University Park, Pennsylvania 16802 (United States)

    2015-12-28

    The present work investigates the capability of bottom-up coarse-graining (CG) methods for accurately modeling both structural and thermodynamic properties of all-atom (AA) models for molecular liquids. In particular, we consider 1, 2, and 3-site CG models for heptane, as well as 1 and 3-site CG models for toluene. For each model, we employ the multiscale coarse-graining method to determine interaction potentials that optimally approximate the configuration dependence of the many-body potential of mean force (PMF). We employ a previously developed “pressure-matching” variational principle to determine a volume-dependent contribution to the potential, U{sub V}(V), that approximates the volume-dependence of the PMF. We demonstrate that the resulting CG models describe AA density fluctuations with qualitative, but not quantitative, accuracy. Accordingly, we develop a self-consistent approach for further optimizing U{sub V}, such that the CG models accurately reproduce the equilibrium density, compressibility, and average pressure of the AA models, although the CG models still significantly underestimate the atomic pressure fluctuations. Additionally, by comparing this array of models that accurately describe the structure and thermodynamic pressure of heptane and toluene at a range of different resolutions, we investigate the impact of bottom-up coarse-graining upon thermodynamic properties. In particular, we demonstrate that U{sub V} accounts for the reduced cohesion in the CG models. Finally, we observe that bottom-up coarse-graining introduces subtle correlations between the resolution, the cohesive energy density, and the “simplicity” of the model.

  4. Bottom-up coarse-grained models that accurately describe the structure, pressure, and compressibility of molecular liquids

    Science.gov (United States)

    Dunn, Nicholas J. H.; Noid, W. G.

    2015-12-01

    The present work investigates the capability of bottom-up coarse-graining (CG) methods for accurately modeling both structural and thermodynamic properties of all-atom (AA) models for molecular liquids. In particular, we consider 1, 2, and 3-site CG models for heptane, as well as 1 and 3-site CG models for toluene. For each model, we employ the multiscale coarse-graining method to determine interaction potentials that optimally approximate the configuration dependence of the many-body potential of mean force (PMF). We employ a previously developed "pressure-matching" variational principle to determine a volume-dependent contribution to the potential, UV(V), that approximates the volume-dependence of the PMF. We demonstrate that the resulting CG models describe AA density fluctuations with qualitative, but not quantitative, accuracy. Accordingly, we develop a self-consistent approach for further optimizing UV, such that the CG models accurately reproduce the equilibrium density, compressibility, and average pressure of the AA models, although the CG models still significantly underestimate the atomic pressure fluctuations. Additionally, by comparing this array of models that accurately describe the structure and thermodynamic pressure of heptane and toluene at a range of different resolutions, we investigate the impact of bottom-up coarse-graining upon thermodynamic properties. In particular, we demonstrate that UV accounts for the reduced cohesion in the CG models. Finally, we observe that bottom-up coarse-graining introduces subtle correlations between the resolution, the cohesive energy density, and the "simplicity" of the model.

  5. SpineAnalyzer™ is an accurate and precise method of vertebral fracture detection and classification on dual-energy lateral vertebral assessment scans

    International Nuclear Information System (INIS)

    Osteoporotic fractures of the spine are associated with significant morbidity, are highly predictive of hip fractures, but frequently do not present clinically. When there is a low to moderate clinical suspicion of vertebral fracture, which would not justify acquisition of a radiograph, vertebral fracture assessment (VFA) using Dual-energy X-ray Absorptiometry (DXA) offers a low-dose opportunity for diagnosis. Different approaches to the classification of vertebral fractures have been documented. The aim of this study was to measure the precision and accuracy of SpineAnalyzer™, a quantitative morphometry software program. Lateral vertebral assessment images of 64 men were analysed using SpineAnalyzer™ and standard GE Lunar software. The images were also analysed by two expert readers using a semi-quantitative approach. Agreement between groups ranged from 95.99% to 98.60%. The intra-rater precision for the application of SpineAnalyzer™ to vertebrae was poor in the upper thoracic regions, but good elsewhere. SpineAnalyzer™ is a reproducible and accurate method for measuring vertebral height and quantifying vertebral fractures from VFA scans. - Highlights: • Vertebral fracture assessment (VFA) using Dual-energy X-ray Absorptiometry (DXA) offers a low-dose opportunity for diagnosis. • Agreement between VFA software (SpineAnalyzer™) and expert readers is high. • Intra-rater precision of SpineAnalyzer™ applied to upper thoracic vertebrae is poor, but good elsewhere. • SpineAnalyzer™ is reproducible and accurate for vertebral height measurement and fracture quantification from VFA scans

  6. Stratification and prognostic relevance of Jass’s molecular classification of colorectal cancer

    Directory of Open Access Journals (Sweden)

    Inti eZlobec

    2012-02-01

    Full Text Available Background: The current proposed model of colorectal tumorigenesis is based primarily on CpG island methylator phenotype (CIMP, microsatellite instability (MSI, KRAS, BRAF, and methylation status of 0-6-Methylguanine DNA Methyltransferase (MGMT and classifies tumors into 5 subgroups. The aim of this study is to validate this molecular classification and test its prognostic relevance. Methods: 302 patients were included in this study. Molecular analysis was performed for 5 CIMP-related promoters (CRABP1, MLH1, p16INK4a, CACNA1G, NEUROG1, MGMT, MSI, KRAS and BRAF. Tumors were CIMP-high or CIMP-low if ≥4 and 1-3 promoters were methylated, respectively. Results: CIMP-high, CIMP-low and CIMP–negative were found in 7.1%, 43% and 49.9% cases, respectively. 123 tumors (41% could not be classified into any one of the proposed molecular subgroups, including 107 CIMP-low, 14 CIMP-high and 2 CIMP-negative cases. The 10-year survival rate for CIMP-high patients (22.6% (95%CI: 7-43 was significantly lower than for CIMP-low or CIMP-negative (p=0.0295. Only the combined analysis of BRAF and CIMP (negative versus low/high led to distinct prognostic subgroups. Conclusion: Although CIMP status has an effect on outcome, our results underline the need for standardized definitions of low- and high-level CIMP, which clearly hinders an effective prognostic and molecular classification of colorectal cancer.

  7. Molecular classification based on apomorphic amino acids (Arthropoda, Hexapoda): Integrative taxonomy in the era of phylogenomics.

    Science.gov (United States)

    Wu, Hao-Yang; Wang, Yan-Hui; Xie, Qiang; Ke, Yun-Ling; Bu, Wen-Jun

    2016-06-17

    With the great development of sequencing technologies and systematic methods, our understanding of evolutionary relationships at deeper levels within the tree of life has greatly improved over the last decade. However, the current taxonomic methodology is insufficient to describe the growing levels of diversity in both a standardised and general way due to the limitations of using only morphological traits to describe clades. Herein, we propose the idea of a molecular classification based on hierarchical and discrete amino acid characters. Clades are classified based on the results of phylogenetic analyses and described using amino acids with group specificity in phylograms. Practices based on the recently published phylogenomic datasets of insects together with 15 de novo sequenced transcriptomes in this study demonstrate that such a methodology can accommodate various higher ranks of taxonomy. Such an approach has the advantage of describing organisms in a standard and discrete way within a phylogenetic framework, thereby facilitating the recognition of clades from the view of the whole lineage, as indicated by PhyloCode. By combining identification keys and phylogenies, the molecular classification based on hierarchical and discrete characters may greatly boost the progress of integrative taxonomy.

  8. An accurate metalloprotein-specific scoring function and molecular docking program devised by a dynamic sampling and iteration optimization strategy.

    Science.gov (United States)

    Bai, Fang; Liao, Sha; Gu, Junfeng; Jiang, Hualiang; Wang, Xicheng; Li, Honglin

    2015-04-27

    Metalloproteins, particularly zinc metalloproteins, are promising therapeutic targets, and recent efforts have focused on the identification of potent and selective inhibitors of these proteins. However, the ability of current drug discovery and design technologies, such as molecular docking and molecular dynamics simulations, to probe metal-ligand interactions remains limited because of their complicated coordination geometries and rough treatment in current force fields. Herein we introduce a robust, multiobjective optimization algorithm-driven metalloprotein-specific docking program named MpSDock, which runs on a scheme similar to consensus scoring consisting of a force-field-based scoring function and a knowledge-based scoring function. For this purpose, in this study, an effective knowledge-based zinc metalloprotein-specific scoring function based on the inverse Boltzmann law was designed and optimized using a dynamic sampling and iteration optimization strategy. This optimization strategy can dynamically sample and regenerate decoy poses used in each iteration step of refining the scoring function, thus dramatically improving both the effectiveness of the exploration of the binding conformational space and the sensitivity of the ranking of the native binding poses. To validate the zinc metalloprotein-specific scoring function and its special built-in docking program, denoted MpSDockZn, an extensive comparison was performed against six universal, popular docking programs: Glide XP mode, Glide SP mode, Gold, AutoDock, AutoDock4Zn, and EADock DSS. The zinc metalloprotein-specific knowledge-based scoring function exhibited prominent performance in accurately describing the geometries and interactions of the coordination bonds between the zinc ions and chelating agents of the ligands. In addition, MpSDockZn had a competitive ability to sample and identify native binding poses with a higher success rate than the other six docking programs.

  9. 乳腺癌的分子分型%Molecular classification of breast cancer

    Institute of Scientific and Technical Information of China (English)

    张百红; 岳红云

    2014-01-01

    乳腺癌是一种分子水平异质性很高的疾病,分子分型可为乳腺癌的个体化治疗提供一个新视野.在分子病理学、分子生物学和系统生物学指导下,乳腺癌经历了4类分型、70种和21种基因蛋白谱以及基因组整合分类等不同分型.这些分型将为乳腺癌的精确治疗提供指导.%Breast cancer is a group of heterogeneous diseases.Molecular portraits provide a new insight for personalized cancer management in breast cancer.According to the molecular pathology,molecular biology and system biology,breast cancer goes through different typing methods,including four subclasses,geneexpression signature and integrated genomic classification.These major subtypes of breast cancer may provide guidance for precise therapeutics.

  10. Molecular phylogenetic evaluation of classification and scenarios of character evolution in calcareous sponges (Porifera, Class Calcarea.

    Directory of Open Access Journals (Sweden)

    Oliver Voigt

    Full Text Available Calcareous sponges (Phylum Porifera, Class Calcarea are known to be taxonomically difficult. Previous molecular studies have revealed many discrepancies between classically recognized taxa and the observed relationships at the order, family and genus levels; these inconsistencies question underlying hypotheses regarding the evolution of certain morphological characters. Therefore, we extended the available taxa and character set by sequencing the complete small subunit (SSU rDNA and the almost complete large subunit (LSU rDNA of additional key species and complemented this dataset by substantially increasing the length of available LSU sequences. Phylogenetic analyses provided new hypotheses about the relationships of Calcarea and about the evolution of certain morphological characters. We tested our phylogeny against competing phylogenetic hypotheses presented by previous classification systems. Our data reject the current order-level classification by again finding non-monophyletic Leucosolenida, Clathrinida and Murrayonida. In the subclass Calcinea, we recovered a clade that includes all species with a cortex, which is largely consistent with the previously proposed order Leucettida. Other orders that had been rejected in the current system were not found, but could not be rejected in our tests either. We found several additional families and genera polyphyletic: the families Leucascidae and Leucaltidae and the genus Leucetta in Calcinea, and in Calcaronea the family Amphoriscidae and the genus Ute. Our phylogeny also provided support for the vaguely suspected close relationship of several members of Grantiidae with giantortical diactines to members of Heteropiidae. Similarly, our analyses revealed several unexpected affinities, such as a sister group relationship between Leucettusa (Leucaltidae and Leucettidae and between Leucascandra (Jenkinidae and Sycon carteri (Sycettidae. According to our results, the taxonomy of Calcarea is in

  11. Nonlinear Optical Properties of Fluorescent Dyes Allow for Accurate Determination of Their Molecular Orientations in Phospholipid Membranes.

    Science.gov (United States)

    Timr, Štěpán; Brabec, Jiří; Bondar, Alexey; Ryba, Tomáš; Železný, Miloš; Lazar, Josef; Jungwirth, Pavel

    2015-07-30

    Several methods based on single- and two-photon fluorescence detected linear dichroism have recently been used to determine the orientational distributions of fluorescent dyes in lipid membranes. However, these determinations relied on simplified descriptions of nonlinear anisotropic properties of the dye molecules, using a transition dipole-moment-like vector instead of an absorptivity tensor. To investigate the validity of the vector approximation, we have now carried out a combination of computer simulations and polarization microscopy experiments on two representative fluorescent dyes (DiI and F2N12S) embedded in aqueous phosphatidylcholine bilayers. Our results indicate that a simplified vector-like treatment of the two-photon transition tensor is applicable for molecular geometries sampled in the membrane at ambient conditions. Furthermore, our results allow evaluation of several distinct polarization microscopy techniques. In combination, our results point to a robust and accurate experimental and computational treatment of orientational distributions of DiI, F2N12S, and related dyes (including Cy3, Cy5, and others), with implications to monitoring physiologically relevant processes in cellular membranes in a novel way. PMID:26146848

  12. Molecular classification and prognostication of 300 node-negative breast cancer cases: A tertiary care experience

    Science.gov (United States)

    Shemin, K. M. Zuhara; Smitha, N. V.; Jojo, Annie; Vijaykumar, D. K.

    2015-01-01

    Background: The proportion of node-negative breast cancer patients has been increasing with improvement of diagnostic modalities and early detection. However, there is a 20–30% recurrence in node-negative breast cancers. Determining who should receive adjuvant therapy is challenging, as the majority are cured by surgery alone. Hence, it requires further stratification using additional prognostic and predictive factors. Subjects and Methods: Ours is a single institution retrospective study, on 300 node-negative breast cancer cases, who underwent primary surgery over a period of 7 years (2005–2011). We excluded all cases who took NACT. Prognostic factors of age, size, lymphovascular emboli, estrogen receptor (ER), progesterone receptor (PR), HER2neu Ki-67, grade and molecular classification were analyzed with respect to those with and without early events (recurrence, metastases or second malignancy, death) using-Pearson Chi-square method and logistic regression method for statistical analysis. Results: Majority belonged to the age group of 50–70 years. On univariate analysis, size >5 cm (P = 0.03) and ER negativity had significant association (P = 0.05) for early failures; PR negativity and lymphovascular emboli (LVE) had borderline significance (P = 0.07). Multivariate analysis showed size >5 cm to be significant (P = 0.04) and LVE positivity showed borderline significant association (P = 0.07) with early failures. About 62% belonged to luminal category followed by basal-like (25%) in molecular classification. Conclusions: ER negativity, PR negativity, LVE/lymphovascular invasion positivity and size >5 cm (T3 and T4) are associated with poor prognosis in node-negative breast cancers. PMID:26981506

  13. Molecular classification and prognostication of 300 node-negative breast cancer cases: A tertiary care experience

    Directory of Open Access Journals (Sweden)

    K M Zuhara Shemin

    2015-01-01

    Full Text Available Background: The proportion of node-negative breast cancer patients has been increasing with improvement of diagnostic modalities and early detection. However, there is a 20-30% recurrence in node-negative breast cancers. Determining who should receive adjuvant therapy is challenging, as the majority are cured by surgery alone. Hence, it requires further stratification using additional prognostic and predictive factors. Subjects and Methods: Ours is a single institution retrospective study, on 300 node-negative breast cancer cases, who underwent primary surgery over a period of 7 years (2005-2011. We excluded all cases who took NACT. Prognostic factors of age, size, lymphovascular emboli, estrogen receptor (ER, progesterone receptor (PR, HER2neu Ki-67, grade and molecular classification were analyzed with respect to those with and without early events (recurrence, metastases or second malignancy, death using-Pearson Chi-square method and logistic regression method for statistical analysis. Results: Majority belonged to the age group of 50-70 years. On univariate analysis, size >5 cm (P = 0.03 and ER negativity had significant association (P = 0.05 for early failures; PR negativity and lymphovascular emboli (LVE had borderline significance (P = 0.07. Multivariate analysis showed size >5 cm to be significant (P = 0.04 and LVE positivity showed borderline significant association (P = 0.07 with early failures. About 62% belonged to luminal category followed by basal-like (25% in molecular classification. Conclusions: ER negativity, PR negativity, LVE/lymphovascular invasion positivity and size >5 cm (T3 and T4 are associated with poor prognosis in node-negative breast cancers.

  14. An Exploration of Hyperion Hyperspectral Imagery Combined with Different Supervised Classification Approaches Towards Obtaining More Accurate Land Use/Cover Cartography

    Science.gov (United States)

    Igityan, Nune

    2014-05-01

    Land use and land cover (LULC) constitutes a key variable of the Earth's system that has in general shown a close correlation with human activities and the physical environment. Describing the pattern and the spatial distribution of LULC is traditionally based on remote sensing data analysis and, evidently, one of the most commonly techniques applied has been image classification. The main objective of the present study has been to evaluate the combined use of Hyperion hyperspectral imagery with a range of supervised classification algorithms widely available today for discriminating LULC classes in a typical Mediterranean setting. Accuracy assessment of the derived thematic maps was based on the analysis of the classification confusion matrix statistics computed for each classification map, using for consistency the same set of validation points. Those were selected on the basis of photo-interpretation of high resolution aerial imagery and of panchromatic imagery available for the studied region at the time of the Hyperion overpass. Results indicated close classification accuracy between the different classifiers with the SVMs outperforming the other classification approaches. The higher classification accuracy by SVMs was attributed principally to the ability of this classifier to identify an optimal separating hyperplane for classes' separation which allows a low generalisation error, thus producing the best possible classes' separation. Although all classifiers produced close results, SVMs generally appeared most useful in describing the spatial distribution and the cover density of each land cover category. All in all, this study demonstrated that, provided that a Hyperion hyperspectral imagery can be made available at regular time intervals over a given region, when combined with SVMs classifiers, can potentially enable a wider approach in land use/cover mapping. This can be of particular importance, especially for regions like in the Mediterranean basin

  15. Molecular phylogeny of Arcoidea with emphasis on Arcidae species (Bivalvia: Pteriomorphia) along the coast of China: challenges to current classification of arcoids.

    Science.gov (United States)

    Feng, Yanwei; Li, Qi; Kong, Lingfeng

    2015-04-01

    The current classifications of arcoids are based on phenetic similarity, which display considerable convergence in several shell and anatomical characters, challenging phylogenetic analysis. Independent molecular analysis of DNA sequences is often necessary for accurate taxonomic assignments of arcoids, especially when morphological characters are equivocal. Here we present molecular evidence of the phylogenetic relationships among arcoid species based on Bayesian inference and Maximum Likelihood analyses of three nuclear genes (18SrRNA, 28SrRNA, and histone H3) and two mitochondrial genes (COI and 12S). Tree topologies are discussed by considering traditional arrangements of taxonomic units and previous molecular studies. The results confirm the monophyly of the order Arcoida, the family Noetiidae, and the subfamilies Anadarinae and Striarcinae, with support for the inclusion of the Glycymerididae in the Arcoidea. The subfamily Arcinae and the genera Arca, Barbatia, Scapharca, Anadara, and Glycymeris are non-monophyletic, suggesting that taxonomic issues still remain. The families Noetiidae, Cucullaeidae, and Glycymerididae appear as subgroups within, rather than sister groups to, the Arcidae. This study strongly suggests the need to carry out a taxonomic revision of the Arcoidea, especially the Arcidae, through combined analysis of morphological, paleontological, and molecular data.

  16. Immunohistochemical Expression of Survivin in Breast Carcinoma: Relationship with Clinico pathological Parameters, Proliferation and Molecular Classification

    International Nuclear Information System (INIS)

    Background and Objective: Survivin is a novel member of the inhibitor of apoptosis (IAP) gene family. It is associated with more aggressive behavior and parameters of poor prognosis in most human cancers including gastric, colorectal and bladder carcinomas. However, conflicting data exist on its prognostic effect in breast cancer. This current study is designed to assess survivin expression in breast carcinoma relating results with clinico pathological parameters, proliferation (MIB-1) and molecular classification. Material and Methods: Our retrospective study com- prised of 65 archived cases of breast carcinoma. Samples from the tumor and the adjacent normal breast tissue were immuno stained for survivin and MIB-1. Nuclear and cytoplasmic survivin expression was evaluated in normal breast tissue and carcinoma regarding both the intensity and the percentage of positive cells. ER, PR, HER2 were used as surrogate markers to classify the cases into four molecular subtypes. Results: Survivin expression was detected in 78.5% of breast carcinomas. The adjacent normal breast tissue was immuno negative. Survivin expression showed significant association with increased tumor size ( p <0.0001), high histologic grade ( p =0.04), lymph node metastases ( p <0.001), advanced tumor stage ( p <0.0001), MIB-1 expression ( p =0.02), negative estrogen receptor status ( p =0.01) and negative progesterone receptor status ( p <0.0001). The subcellular localization of survivin significantly related to histologic grade, stage and lymph node involvement. The percentage of TNP (triple negative phenotype) and HER2+/ER-PR- tumors expressing survivin were significantly higher compared to the Luminal subtypes ( p =0.01). Conclusion: Survivin expression was associated with parameters of poor prognosis in breast cancer. Moreover, the cancer-specific expression of survivin, coupled with its importance in inhibiting cell death and in regulating cell division, makes it a potential target for novel

  17. Molecular Phylogeny of the Cliff Ferns (Woodsiaceae: Polypodiales) with a Proposed Infrageneric Classification.

    Science.gov (United States)

    Shao, Yizhen; Wei, Ran; Zhang, Xianchun; Xiang, Qiaoping

    2015-01-01

    The cliff fern family Woodsiaceae has experienced frequent taxonomic changes at the familial and generic ranks since its establishment. The bulk of its species were placed in Woodsia, while Cheilanthopsis, Hymenocystis, Physematium, and Protowoodsia are segregates recognized by some authors. Phylogenetic relationships among the genera of Woodsiaceae remain unclear because of the extreme morphological diversity and inadequate taxon sampling in phylogenetic studies to date. In this study, we carry out comprehensive phylogenetic analyses of Woodsiaceae using molecular evidence from four chloroplast DNA markers (atpA, matK, rbcL and trnL-F) and covering over half the currently recognized species. Our results show three main clades in Woodsiaceae corresponding to Physematium (clade I), Cheilanthopsis-Protowoodsia (clade II) and Woodsia s.s. (clade III). In the interest of preserving monophyly and taxonomic stability, a broadly defined Woodsia including the other segregates is proposed, which is characterized by the distinctive indument and inferior indusia. Therefore, we present a new subgeneric classification of the redefined Woodsia based on phylogenetic and ancestral state reconstructions to better reflect the morphological variation, geographic distribution pattern, and evolutionary history of the genus. Our analyses of the cytological character evolution support multiple aneuploidy events that have resulted in the reduction of chromosome base number from 41 to 33, 37, 38, 39 and 40 during the evolutionary history of the cliff ferns.

  18. Molecular phylogeny of the families Pleuronectidae and Poecilopsettidae (PISCES, Pleuronectiformes) from Korea, with a Proposal for a new classification

    Science.gov (United States)

    Ji, Hwan-Sung; Kim, Jin-Koo; Kim, Byung-Jik

    2016-03-01

    A new classification of the Korean pleuronectids was proposed based on a molecular phylogeny using specimens collected from Korea (including some Japanese specimens) between 2008 and 2013. A molecular phylogeny based on partial sequences of the two mitochondrial DNA regions (COI and 16S rRNA) supported the reciprocal monophyly of the three genera, Cleisthenes, Pleuronectes and Pseudopleuronectes. We also found that the genus Poecilopsetta is clearly distinct from Pleuronectidae at the family level. Therefore, the previous classification of the Korean pleuronectids should be changed as follows; two families (Pleuronectidae and Poecilopsettidae), 18 genera, and 26 species. Further research is required to resolve the taxonomic uncertainty of the five species in the genus Limanda, which clustered into two clades in our analysis.

  19. The classification of gene products in the molecular biology domain: Realism, objectivity, and the limitations of the Gene Ontology

    OpenAIRE

    Mayor, Charlie

    2012-01-01

    Background: Controlled vocabularies in the molecular biology domain exist to facilitate data integration across database resources. One such tool is the Gene Ontology (GO), a classification designed to act as a universal index for gene products from any species. The Gene Ontology is used extensively in annotating gene products and analysing gene expression data, yet very little research exists from a library and information science perspective exploring the design principles, philosophy and s...

  20. Pharmacological Classification and Activity Evaluation of Furan and Thiophene Amide Derivatives Applying Semi-Empirical ab initio Molecular Modeling Methods

    OpenAIRE

    Leszek Bober; Tomasz Baczek; Piotr Kawczak

    2012-01-01

    Pharmacological and physicochemical classification of the furan and thiophene amide derivatives by multiple regression analysis and partial least square (PLS) based on semi-empirical ab initio molecular modeling studies and high-performance liquid chromatography (HPLC) retention data is proposed. Structural parameters obtained from the PCM (Polarizable Continuum Model) method and the literature values of biological activity (antiproliferative for the A431 cells) expressed...

  1. The Significance of Molecular Classification in Breast Cancer for Prognosis%乳腺癌分子分型对乳腺癌预后的意义

    Institute of Scientific and Technical Information of China (English)

    王会东

    2013-01-01

    Objective To investigate the molecular classification and prognosis of breast cancer and the relationship between . Methods Retrospective analysis of 316 cases of female primary breast cancer patients with the clinical pathological ,average age 54.5 years.According to estrogen receptor (ER),pregnancy hormone receptor (PR) and human epidermal growth factor receptor 2(HER2) immu-nohistochemical findings,breast cancer types as type Luminal A ,type Luminal B,triple-negative and HER2 positive type,differences in mo-lecular classification of breast cancer prognosis were observed ,various types of patients with postoperative disease -free survival were com-pared.Results The patients were followed up for 5~124 months,a median follow-up time of 58 months,32 patients had recurrence of metas-tasis or death,the single factor analysis showed that the breast cancer disease free survival and molecular types had relation .Conclusion The molecular classification of breast cancer accurately reflects the prognosis of breast cancer .Type Luminal has the best prognosis ,while triple-negative has the worst prognosis .%  目的 探讨乳腺癌分子分型与预后之间的关系。方法 回顾性分析316例原发性乳腺癌患者的临床病理资料,患者均为女性,平均年龄54.5岁。根据雌激素受体(ER)、孕激素受体(PR)及人类表皮生长因子受体2(HER2)的免疫组织化学结果,乳腺癌分型为Luminal A型、Luminal B型、三阴型及 HER2阳性型,观察不同分子分型乳腺癌的预后,比较各型患者术后的无病生存期。结果 随访5~124个月,中位随访时间58个月,32例患者复发转移或死亡,单因素分析示乳腺癌无病生存期与分子分型有关。结论 乳腺癌的分子分型能够准确反映乳腺癌的预后,Luminal型预后最好,而三阴型预后最差。

  2. Morphological and molecular characteristics do not confirm popular classification of the Brazil nut tree in Acre, Brazil.

    Science.gov (United States)

    Sujii, P S; Fernandes, E T M B; Azevedo, V C R; Ciampi, A Y; Martins, K; de O Wadt, L H

    2013-01-01

    In the State of Acre, the Brazil nut tree, Bertholletia excelsa (Lecythidaceae), is classified by the local population into two types according to morphological characteristics, including color and quality of wood, shape of the trunk and crown, and fruit production. We examined the reliability of this classification by comparing morphological and molecular data of four populations of Brazil nut trees from Vale do Rio Acre in the Brazilian Amazon. For the morphological analysis, we evaluated qualitative and quantitative information of the trees, fruits, and seeds. The molecular analysis was performed using RAPD and ISSR markers, with cluster analysis. Significant differences were found between the two types of Brazil nut trees for the characters diameter at breast height, fruit yield, fruit size, and number of seeds per fruit. Despite the significant correlation between the morphological characteristics and the popular classification, we observed all possible combinations of morphological characteristics in both types of Brazil nut trees. In some individuals, the classification did not correspond to any of the characteristics. The results obtained with molecular markers showed that the two locally classified types of Brazil nut trees did not differ genetically, indicating that there is no consistent separation between them.

  3. Rapid and accurate taxonomic classification of insect (class Insecta) cytochrome c oxidase subunit 1 (COI) DNA barcode sequences using a naïve Bayesian classifier

    OpenAIRE

    Porter, Teresita M.; Gibson, Joel F; Shokralla, Shadi; Baird, Donald J.; Golding, G. Brian; Hajibabaei, Mehrdad

    2014-01-01

    Current methods to identify unknown insect (class Insecta) cytochrome c oxidase (COI barcode) sequences often rely on thresholds of distances that can be difficult to define, sequence similarity cut-offs, or monophyly. Some of the most commonly used metagenomic classification methods do not provide a measure of confidence for the taxonomic assignments they provide. The aim of this study was to use a naïve Bayesian classifier (Wang et al. Applied and Environmental Microbiology, 2007; 73: 5261)...

  4. Molecular Classification of Pesticides Including Persistent Organic Pollutants, Phenylurea and Sulphonylurea Herbicides

    Directory of Open Access Journals (Sweden)

    Francisco Torrens

    2014-06-01

    Full Text Available Pesticide residues in wine were analyzed by liquid chromatography–tandem mass spectrometry. Retentions are modelled by structure–property relationships. Bioplastic evolution is an evolutionary perspective conjugating effect of acquired characters and evolutionary indeterminacy–morphological determination–natural selection principles; its application to design co-ordination index barely improves correlations. Fractal dimensions and partition coefficient differentiate pesticides. Classification algorithms are based on information entropy and its production. Pesticides allow a structural classification by nonplanarity, and number of O, S, N and Cl atoms and cycles; different behaviours depend on number of cycles. The novelty of the approach is that the structural parameters are related to retentions. Classification algorithms are based on information entropy. When applying procedures to moderate-sized sets, excessive results appear compatible with data suffering a combinatorial explosion. However, equipartition conjecture selects criterion resulting from classification between hierarchical trees. Information entropy permits classifying compounds agreeing with principal component analyses. Periodic classification shows that pesticides in the same group present similar properties; those also in equal period, maximum resemblance. The advantage of the classification is to predict the retentions for molecules not included in the categorization. Classification extends to phenyl/sulphonylureas and the application will be to predict their retentions.

  5. Accurate and Scalable O(N) Algorithm for First-Principles Molecular-Dynamics Computations on Large Parallel Computers

    Energy Technology Data Exchange (ETDEWEB)

    Osei-Kuffuor, Daniel [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Fattebert, Jean-Luc [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2014-01-01

    We present the first truly scalable first-principles molecular dynamics algorithm with O(N) complexity and controllable accuracy, capable of simulating systems with finite band gaps of sizes that were previously impossible with this degree of accuracy. By avoiding global communications, we provide a practical computational scheme capable of extreme scalability. Accuracy is controlled by the mesh spacing of the finite difference discretization, the size of the localization regions in which the electronic wave functions are confined, and a cutoff beyond which the components of the overlap matrix can be omitted when computing selected elements of its inverse. We demonstrate the algorithm's excellent parallel scaling for up to 101 952 atoms on 23 328 processors, with a wall-clock time of the order of 1 min per molecular dynamics time step and numerical error on the forces of less than 7x10-4 Ha/Bohr.

  6. Development of an accurate molecular mechanics model for buckling behavior of multi-walled carbon nanotubes under axial compression.

    Science.gov (United States)

    Safaei, B; Naseradinmousavi, P; Rahmani, A

    2016-04-01

    In the present paper, an analytical solution based on a molecular mechanics model is developed to evaluate the elastic critical axial buckling strain of chiral multi-walled carbon nanotubes (MWCNTs). To this end, the total potential energy of the system is calculated with the consideration of the both bond stretching and bond angular variations. Density functional theory (DFT) in the form of generalized gradient approximation (GGA) is implemented to evaluate force constants used in the molecular mechanics model. After that, based on the principle of molecular mechanics, explicit expressions are proposed to obtain elastic surface Young's modulus and Poisson's ratio of the single-walled carbon nanotubes corresponding to different types of chirality. Selected numerical results are presented to indicate the influence of the type of chirality, tube diameter, and number of tube walls in detailed. An excellent agreement is found between the present numerical results and those found in the literature which confirms the validity as well as the accuracy of the present closed-form solution. It is found that the value of critical axial buckling strain exhibit significant dependency on the type of chirality and number of tube walls.

  7. Accurate determination of genetic identity for a single cacao bean, using molecular markers with a nanofluidic system, ensures cocoa authentication.

    Science.gov (United States)

    Fang, Wanping; Meinhardt, Lyndel W; Mischke, Sue; Bellato, Cláudia M; Motilal, Lambert; Zhang, Dapeng

    2014-01-15

    Cacao (Theobroma cacao L.), the source of cocoa, is an economically important tropical crop. One problem with the premium cacao market is contamination with off-types adulterating raw premium material. Accurate determination of the genetic identity of single cacao beans is essential for ensuring cocoa authentication. Using nanofluidic single nucleotide polymorphism (SNP) genotyping with 48 SNP markers, we generated SNP fingerprints for small quantities of DNA extracted from the seed coat of single cacao beans. On the basis of the SNP profiles, we identified an assumed adulterant variety, which was unambiguously distinguished from the authentic beans by multilocus matching. Assignment tests based on both Bayesian clustering analysis and allele frequency clearly separated all 30 authentic samples from the non-authentic samples. Distance-based principle coordinate analysis further supported these results. The nanofluidic SNP protocol, together with forensic statistical tools, is sufficiently robust to establish authentication and to verify gourmet cacao varieties. This method shows significant potential for practical application.

  8. An accurate and scalable O(N) algorithm for First-Principles Molecular Dynamics computations on petascale computers and beyond

    Science.gov (United States)

    Osei-Kuffuor, Daniel; Fattebert, Jean-Luc

    2014-03-01

    We present a truly scalable First-Principles Molecular Dynamics algorithm with O(N) complexity and fully controllable accuracy, capable of simulating systems of sizes that were previously impossible with this degree of accuracy. By avoiding global communication, we have extended W. Kohn's condensed matter ``nearsightedness'' principle to a practical computational scheme capable of extreme scalability. Accuracy is controlled by the mesh spacing of the finite difference discretization, the size of the localization regions in which the electronic wavefunctions are confined, and a cutoff beyond which the components of the overlap matrix can be omitted when computing selected elements of its inverse. We demonstrate the algorithm's excellent parallel scaling for up to 100,000 atoms on 100,000 processors, with a wall-clock time of the order of one minute per molecular dynamics time step. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

  9. Accurate age classification of 6 and 12 month-old infants based on resting-state functional connectivity magnetic resonance imaging data

    Directory of Open Access Journals (Sweden)

    John R. Pruett, Jr.

    2015-04-01

    Full Text Available Human large-scale functional brain networks are hypothesized to undergo significant changes over development. Little is known about these functional architectural changes, particularly during the second half of the first year of life. We used multivariate pattern classification of resting-state functional connectivity magnetic resonance imaging (fcMRI data obtained in an on-going, multi-site, longitudinal study of brain and behavioral development to explore whether fcMRI data contained information sufficient to classify infant age. Analyses carefully account for the effects of fcMRI motion artifact. Support vector machines (SVMs classified 6 versus 12 month-old infants (128 datasets above chance based on fcMRI data alone. Results demonstrate significant changes in measures of brain functional organization that coincide with a special period of dramatic change in infant motor, cognitive, and social development. Explorations of the most different correlations used for SVM lead to two different interpretations about functional connections that support 6 versus 12-month age categorization.

  10. Olfaction-Inspired Sensing Using a Sensor System with Molecular Recognition and Optimal Classification Ability for Comprehensive Detection of Gases

    Directory of Open Access Journals (Sweden)

    Masahiro Imahashi

    2014-03-01

    Full Text Available In this study, we examined the comprehensive detection of numerous volatile molecules based on the olfactory information constructed by using olfaction-inspired sensor technology. The sensor system can simultaneously detect multiple odors by the separation and condensation ability of molecularly imprinted filtering adsorbents (MIFAs, where a MIP filter with a molecular sieve was deposited on a polydimethylsiloxane (PDMS substrate. The adsorption properties of MIFAs were evaluated using the solid-phase microextraction (SPME and gas chromatography-mass spectrometry (GC-MS. The results demonstrated that the system embedded with MIFAs possesses high sensitivity and specific selectivity. The digitization and comprehensive classification of odors were accomplished by using artificial odor maps constructed through this system.

  11. Accurate Treatment of Electrostatics during Molecular Adsorption in Nanoporous Crystals without Assigning Point Charges to Framework Atoms

    Energy Technology Data Exchange (ETDEWEB)

    Watanabe, T; Manz, TA; Sholl, DS

    2011-03-24

    Molecular simulations have become an important complement to experiments for studying gas adsorption and separation in crystalline nanoporous materials. Conventionally, these simulations use force fields that model adsorbate-pore interactions by assigning point charges to the atoms of the adsorbent. The assignment of framework charges always introduces ambiguity because there are many different choices for defining point charges, even when the true electron density of a material is known. We show how to completely avoid such ambiguity by using the electrostatic potential energy surface (EPES) calculated from plane wave density functional theory (DFT). We illustrate this approach by simulating CO(2) adsorption in four metal-organic frameworks (MOFs): IRMOF-1, ZIE-8, ZIE-90, and Zn(nicotinate)(2). The resulting CO(2) adsorption isotherms are insensitive to the exchange-correlation functional used in the DFT calculation of the EPES but are sensitive to changes in the crystal structure and lattice parameters. Isotherms computed from the DFT EPES are compared to those computed from several point charge models. This comparison makes possible, for the first time, an unbiased assessment of the accuracy of these point charge models for describing adsorption in MOFs. We find an unusually high Henry's constant (109 mmol/g.bar) and intermediate isosteric heat of adsorption (34.9 kJ/mol) for Zn(nicotinate)(2), which makes it a potentially attractive mateiial for CO(2) adsorption applications.

  12. Accurate Treatment of Electrostatics during Molecular Adsorption in Nanoporous Crystals without Assigning Point Charges to Framework Atoms

    Energy Technology Data Exchange (ETDEWEB)

    Watanabe, Taku [Georgia Inst. of Technology, Atlanta, GA (United States); Manz, Thomas A. [Georgia Inst. of Technology, Atlanta, GA (United States); Sholl, David S. [Georgia Inst. of Technology, Atlanta, GA (United States)

    2011-02-28

    Molecular simulations have become an important complement to experiments for studying gas adsorption and separation in crystalline nanoporous materials. Conventionally, these simulations use force fields that model adsorbate-pore interactions by assigning point charges to the atoms of the adsorbent. The assignment of framework charges always introduces ambiguity because there are many different choices for defining point charges, even when the true electron density of a material is known. We show how to completely avoid such ambiguity by using the electrostatic potential energy surface (EPES) calculated from plane wave density functional theory (DFT). We illustrate this approach by simulating CO2 adsorption in four metal-organic frameworks (MOFs): IRMOF-1, ZIF-8, ZIF-90, and Zn(nicotinate)2. The resulting CO2 adsorption isotherms are insensitive to the exchange-correlation functional used in the DFT calculation of the EPES but are sensitive to changes in the crystal structure and lattice parameters. Isotherms computed from the DFT EPES are compared to those computed from several point charge models. This comparison makes possible, for the first time, an unbiased assessment of the accuracy of these point charge models for describing adsorption in MOFs. We find an unusually high Henry’s constant (109 mmol/g·bar) and intermediate isosteric heat of adsorption (34.9 kJ/mol) for Zn(nicotinate)2, which makes it a potentially attractive material for CO2 adsorption applications.

  13. The need for improved identification and accurate classification of stages 3-5 Chronic Kidney Disease in primary care: retrospective cohort study.

    Directory of Open Access Journals (Sweden)

    Poorva Jain

    Full Text Available BACKGROUND: Around ten percent of the population have been reported as having Chronic Kidney Disease (CKD, which is associated with increased cardiovascular mortality. Few previous studies have ascertained the chronicity of CKD. In the UK, a payment for performance (P4P initiative incentivizes CKD (stages 3-5 recognition and management in primary care, but the impact of this has not been assessed. METHODS AND FINDINGS: Using data from 426 primary care practices (population 2,707,130, the age standardised prevalence of stages 3-5 CKD was identified using two consecutive estimated Glomerular Filtration Rates (eGFRs seven days apart. Additionally the accuracy of practice CKD registers and the relationship between accurate identification of CKD and the achievement of P4P indicators was determined. Between 2005 and 2009, the prevalence of stages 3-5 CKD increased from 0.3% to 3.9%. In 2009, 30,440 patients (1.1% unadjusted fulfilled biochemical criteria for CKD but were not on a practice CKD register (uncoded CKD and 60,705 patients (2.2% unadjusted were included on a practice CKD register but did not fulfil biochemical criteria (miscoded CKD. For patients with confirmed CKD, inclusion in a practice register was associated with increasing age, male sex, diabetes, hypertension, cardiovascular disease and increasing CKD stage (p<0.0001. Uncoded CKD patients compared to miscoded patients were less likely to achieve performance indicators for blood pressure (OR 0.84, 95% CI 0.82-0.86 p<0.001 or recorded albumin-creatinine ratio (OR 0.73, 0.70-0.76, p<0.001. CONCLUSIONS: The prevalence of stages 3-5 CKD, using two laboratory reported eGFRs, was lower than estimates from previous studies. Clinically significant discrepancies were identified between biochemically defined CKD and appearance on practice registers, with misclassification associated with sub-optimal care for some people with CKD.

  14. Communication: Rate coefficients of the H + CH4 → H2 + CH3 reaction from ring polymer molecular dynamics on a highly accurate potential energy surface

    International Nuclear Information System (INIS)

    The ring polymer molecular dynamics (RPMD) calculations are performed to calculate rate constants for the title reaction on the recently constructed potential energy surface based on permutation invariant polynomial (PIP) neural-network (NN) fitting [J. Li et al., J. Chem. Phys. 142, 204302 (2015)]. By inspecting convergence, 16 beads are used in computing free-energy barriers at 300 K ≤ T ≤ 1000 K, while different numbers of beads are used for transmission coefficients. The present RPMD rates are in excellent agreement with quantum rates computed on the same potential energy surface, as well as with the experimental measurements, demonstrating further that the RPMD is capable of producing accurate rates for polyatomic chemical reactions even at rather low temperatures

  15. Communication: Rate coefficients of the H + CH4 → H2 + CH3 reaction from ring polymer molecular dynamics on a highly accurate potential energy surface

    Science.gov (United States)

    Meng, Qingyong; Chen, Jun; Zhang, Dong H.

    2015-09-01

    The ring polymer molecular dynamics (RPMD) calculations are performed to calculate rate constants for the title reaction on the recently constructed potential energy surface based on permutation invariant polynomial (PIP) neural-network (NN) fitting [J. Li et al., J. Chem. Phys. 142, 204302 (2015)]. By inspecting convergence, 16 beads are used in computing free-energy barriers at 300 K ≤ T ≤ 1000 K, while different numbers of beads are used for transmission coefficients. The present RPMD rates are in excellent agreement with quantum rates computed on the same potential energy surface, as well as with the experimental measurements, demonstrating further that the RPMD is capable of producing accurate rates for polyatomic chemical reactions even at rather low temperatures.

  16. A new classification of viviparous brotulas (Bythitidae) - with family status for Dinematichthyidae - based on molecular, morphological and fossil data.

    Science.gov (United States)

    Møller, Peter Rask; Knudsen, Steen Wilhelm; Schwarzhans, Werner; Nielsen, Jørgen G

    2016-07-01

    The order Ophidiiformes is a large but not very well known group of fishes, unique among teleosts for showing high diversity in both deep sea and shallow reef habitats. The current classification includes more than 500 species, 115 genera and four families, based primarily on mode of reproduction: viviparous Aphyonidae and Bythitidae vs oviparous Carapidae and Ophidiidae. Since 2004 we revised the bythitid tribe Dinematichthyini, described more than 100 new species and noticed that this group has unique morphological characters, perhaps supporting a higher level of classification than the current status. Here we study the viviparous families phylogenetically with partial mitochondrial (nd4, 16s) and nuclear (Rag1) DNA sequences (2194bp). We use a fossil calibration of otolith-based taxa to calibrate the age of the clade comprising bythitid and dinematicththyid representatives, together with fossil calibrations adopted from previous phylogenetic studies. The separation of the order into two major lineages, the viviparous Bythitoidei and the oviparous Ophidioidei is confirmed. At the familial level, however, a new classification is presented for the viviparous clades, placing Aphyonidae as a derived, pedomorphic member of Bythitidae (new diagnosis provided, 33 genera and 118 species). The current subfamily Brosmophycinae is considered polyphyletic and we propose family status for Dinematichthyidae (25 genera, 114 species), supported by unique, morphological synapomorphic characters in the male copulatory apparatus. Previous use of the caudal fin separation or fusion with vertical fins is ambiguous. Age estimates based on calibrated molecular phylogeny agrees with fossil data, giving an origin within the Cretaceous (between 84 and 104mya) for a common ancestor to Ophidiiformes. PMID:27060424

  17. A Molecular Predictor Reassesses Classification of Human Grade II/III Gliomas.

    Directory of Open Access Journals (Sweden)

    Thierry Rème

    Full Text Available Diffuse gliomas are incurable brain tumors divided in 3 WHO grades (II; III; IV based on histological criteria. Grade II/III gliomas are clinically very heterogeneous and their prognosis somewhat unpredictable, preventing definition of appropriate treatment. On a cohort of 65 grade II/III glioma patients, a QPCR-based approach allowed selection of a biologically relevant gene list from which a gene signature significantly correlated to overall survival was extracted. This signature clustered the training cohort into two classes of low and high risk of progression and death, and similarly clustered two external independent test cohorts of 104 and 73 grade II/III patients. A 22-gene class predictor of the training clusters optimally distinguished poor from good prognosis patients (median survival of 13-20 months versus over 6 years in the validation cohorts. This classification was stronger at predicting outcome than the WHO grade II/III classification (P≤2.8E-10 versus 0.018. When compared to other prognosis factors (histological subtype and genetic abnormalities in a multivariate analysis, the 22-gene predictor remained significantly associated with overall survival. Early prediction of high risk patients (3% of WHO grade II, and low risk patients (29% of WHO grade III in clinical routine will allow the development of more appropriate follow-up and treatments.

  18. Radiolabelled nanoparticles: novel classification of radiopharmaceuticals for molecular imaging of cancer.

    Science.gov (United States)

    Mirshojaei, Seyedeh Fatemeh; Ahmadi, Amirhossein; Morales-Avila, Enrique; Ortiz-Reynoso, Mariana; Reyes-Perez, Horacio

    2016-01-01

    Nanotechnology has been used for every single modality in the molecular imaging arena for imaging purposes. Synergic advantages can be explored when multiple molecular imaging modalities are combined with respect to single imaging modalities. Multifunctional nanoparticles have large surface areas, where multiple functional moieties can be incorporated, including ligands for site-specific targeting and radionuclides, which can be detected to create 3D images. Recently, radiolabeled nanoparticles with individual properties have attracted great interest regarding their use in multimodality tumor imaging. Multifunctional nanoparticles can combine diagnostic and therapeutic capabilities for both target-specific diagnosis and the treatment of a given disease. The future of nanomedicine lies in multifunctional nanoplatforms that combine the diagnostic ability and therapeutic effects using appropriate ligands, drugs, responses and technological devices, which together are collectively called theranostic drugs. Co-delivery of radiolabeled nanoparticles is useful in multifunctional molecular imaging areas because it comprises several advantages based on nanoparticles architecture, pharmacokinetics and pharmacodynamic properties.

  19. Molecular classification of liver cirrhosis in a rat model by proteomics and bioinformatics.

    Science.gov (United States)

    Xu, Xiu-Qin; Leow, Chon K; Lu, Xin; Zhang, Xuegong; Liu, Jun S; Wong, Wing-Hung; Asperger, Arndt; Deininger, Sören; Eastwood Leung, Hon-Chiu

    2004-10-01

    Liver cirrhosis is a worldwide health problem. Reliable, noninvasive methods for early detection of liver cirrhosis are not available. Using a three-step approach, we classified sera from rats with liver cirrhosis following different treatment insults. The approach consisted of: (i) protein profiling using surface-enhanced laser desorption/ionization (SELDI) technology; (ii) selection of a statistically significant serum biomarker set using machine learning algorithms; and (iii) identification of selected serum biomarkers by peptide sequencing. We generated serum protein profiles from three groups of rats: (i) normal (n=8), (ii) thioacetamide-induced liver cirrhosis (n=22), and (iii) bile duct ligation-induced liver fibrosis (n=5) using a weak cation exchanger surface. Profiling data were further analyzed by a recursive support vector machine algorithm to select a panel of statistically significant biomarkers for class prediction. Sensitivity and specificity of classification using the selected protein marker set were higher than 92%. A consistently down-regulated 3495 Da protein in cirrhosis samples was one of the selected significant biomarkers. This 3495 Da protein was purified on-chip and trypsin digested. Further structural characterization of this biomarkers candidate was done by using cross-platform matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) peptide mass fingerprinting (PMF) and matrix-assisted laser desorption/ionization time of flight/time of flight (MALDI-TOF/TOF) tandem mass spectrometry (MS/MS). Combined data from PMF and MS/MS spectra of two tryptic peptides suggested that this 3495 Da protein shared homology to a histidine-rich glycoprotein. These results demonstrated a novel approach to discovery of new biomarkers for early detection of liver cirrhosis and classification of liver diseases. PMID:15378689

  20. Beyond laminar fate: toward a molecular classification of cortical projection/pyramidal neurons.

    NARCIS (Netherlands)

    Hevner, R.F.; Daza, R.A.; Rubenstein, J.L.; Stunnenberg, H.G.; Olavarria, J.F.; Englund, C.

    2003-01-01

    Cortical projection neurons exhibit diverse morphological, physiological, and molecular phenotypes, but it is unknown how many distinct types exist. Many projection cell phenotypes are associated with laminar fate (radial position), but each layer may also contain multiple types of projection cells.

  1. Self Organizing Map-Based Classification of Cathepsin k and S Inhibitors with Different Selectivity Profiles Using Different Structural Molecular Fingerprints: Design and Application for Discovery of Novel Hits.

    Science.gov (United States)

    Ihmaid, Saleh K; Ahmed, Hany E A; Zayed, Mohamed F; Abadleh, Mohammed M

    2016-01-30

    The main step in a successful drug discovery pipeline is the identification of small potent compounds that selectively bind to the target of interest with high affinity. However, there is still a shortage of efficient and accurate computational methods with powerful capability to study and hence predict compound selectivity properties. In this work, we propose an affordable machine learning method to perform compound selectivity classification and prediction. For this purpose, we have collected compounds with reported activity and built a selectivity database formed of 153 cathepsin K and S inhibitors that are considered of medicinal interest. This database has three compound sets, two K/S and S/K selective ones and one non-selective KS one. We have subjected this database to the selectivity classification tool 'Emergent Self-Organizing Maps' for exploring its capability to differentiate selective cathepsin inhibitors for one target over the other. The method exhibited good clustering performance for selective ligands with high accuracy (up to 100 %). Among the possibilites, BAPs and MACCS molecular structural fingerprints were used for such a classification. The results exhibited the ability of the method for structure-selectivity relationship interpretation and selectivity markers were identified for the design of further novel inhibitors with high activity and target selectivity.

  2. Molecular phylogenetic evaluation of classification and scenarios of character evolution in calcareous sponges (Porifera, Class Calcarea).

    OpenAIRE

    Oliver Voigt; Eilika Wülfing; Gert Wörheide

    2012-01-01

    Calcareous sponges (Phylum Porifera, Class Calcarea) are known to be taxonomically difficult. Previous molecular studies have revealed many discrepancies between classically recognized taxa and the observed relationships at the order, family and genus levels; these inconsistencies question underlying hypotheses regarding the evolution of certain morphological characters. Therefore, we extended the available taxa and character set by sequencing the complete small subunit (SSU) rDNA and the alm...

  3. Molecular classification and pharmacogenetics of primary plasma cell leukemia: an initial approach toward precision medicine

    OpenAIRE

    Vittorio Simeon; Katia Todoerti; Francesco La Rocca; Antonella Caivano; Stefania Trino; Marta Lionetti; Luca Agnelli; Luciana De Luca; Ilaria Laurenzana; Antonino Neri; Pellegrino Musto

    2015-01-01

    Primary plasma cell leukemia (pPCL) is a rare and aggressive variant of multiple myeloma (MM) which may represent a valid model for high-risk MM. This disease is associated with a very poor prognosis, and unfortunately, it has not significantly improved during the last three decades. New high-throughput technologies have allowed a better understanding of the molecular basis of this disease and moved toward risk stratification, providing insights for targeted therapy studies. This knowledge, ...

  4. Molecular classification of familial non-BRCA1/BRCA2 breast cancer.

    Science.gov (United States)

    Hedenfalk, Ingrid; Ringner, Markus; Ben-Dor, Amir; Yakhini, Zohar; Chen, Yidong; Chebil, Gunilla; Ach, Robert; Loman, Niklas; Olsson, Håkan; Meltzer, Paul; Borg, Ake; Trent, Jeffrey

    2003-03-01

    In the decade since their discovery, the two major breast cancer susceptibility genes BRCA1 and BRCA2, have been shown conclusively to be involved in a significant fraction of families segregating breast and ovarian cancer. However, it has become equally clear that a large proportion of families segregating breast cancer alone are not caused by mutations in BRCA1 or BRCA2. Unfortunately, despite intensive effort, the identification of additional breast cancer predisposition genes has so far been unsuccessful, presumably because of genetic heterogeneity, low penetrance, or recessive/polygenic mechanisms. These non-BRCA1/2 breast cancer families (termed BRCAx families) comprise a histopathologically heterogeneous group, further supporting their origin from multiple genetic events. Accordingly, the identification of a method to successfully subdivide BRCAx families into recognizable groups could be of considerable value to further genetic analysis. We have previously shown that global gene expression analysis can identify unique and distinct expression profiles in breast tumors from BRCA1 and BRCA2 mutation carriers. Here we show that gene expression profiling can discover novel classes among BRCAx tumors, and differentiate them from BRCA1 and BRCA2 tumors. Moreover, microarray-based comparative genomic hybridization (CGH) to cDNA arrays revealed specific somatic genetic alterations within the BRCAx subgroups. These findings illustrate that, when gene expression-based classifications are used, BRCAx families can be grouped into homogeneous subsets, thereby potentially increasing the power of conventional genetic analysis.

  5. Deceptive desmas: molecular phylogenetics suggests a new classification and uncovers convergent evolution of lithistid demosponges.

    Directory of Open Access Journals (Sweden)

    Astrid Schuster

    Full Text Available Reconciling the fossil record with molecular phylogenies to enhance the understanding of animal evolution is a challenging task, especially for taxa with a mostly poor fossil record, such as sponges (Porifera. 'Lithistida', a polyphyletic group of recent and fossil sponges, are an exception as they provide the richest fossil record among demosponges. Lithistids, currently encompassing 13 families, 41 genera and >300 recent species, are defined by the common possession of peculiar siliceous spicules (desmas that characteristically form rigid articulated skeletons. Their phylogenetic relationships are to a large extent unresolved and there has been no (taxonomically comprehensive analysis to formally reallocate lithistid taxa to their closest relatives. This study, based on the most comprehensive molecular and morphological investigation of 'lithistid' demosponges to date, corroborates some previous weakly-supported hypotheses, and provides novel insights into the evolutionary relationships of the previous 'order Lithistida'. Based on molecular data (partial mtDNA CO1 and 28S rDNA sequences, we show that 8 out of 13 'Lithistida' families belong to the order Astrophorida, whereas Scleritodermidae and Siphonidiidae form a separate monophyletic clade within Tetractinellida. Most lithistid astrophorids are dispersed between different clades of the Astrophorida and we propose to formally reallocate them, respectively. Corallistidae, Theonellidae and Phymatellidae are monophyletic, whereas the families Pleromidae and Scleritodermidae are polyphyletic. Family Desmanthidae is polyphyletic and groups within Halichondriidae--we formally propose a reallocation. The sister group relationship of the family Vetulinidae to Spongillida is confirmed and we propose here for the first time to include Vetulina into a new Order Sphaerocladina. Megascleres and microscleres possibly evolved and/or were lost several times independently in different 'lithistid' taxa, and

  6. Non-sentinel lymph node metastasis prediction in breast cancer with metastatic sentinel lymph node: impact of molecular subtypes classification.

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    Fabien Reyal

    Full Text Available INTRODUCTION: To decipher the interaction between the molecular subtype classification and the probability of a non-sentinel node metastasis in breast cancer patients with a metastatic sentinel lymph-node, we applied two validated predictors (Tenon Score and MSKCC Nomogram on two large independent datasets. MATERIALS AND METHODS: Our datasets consisted of 656 and 574 early-stage breast cancer patients with a metastatic sentinel lymph-node biopsy treated at first by surgery. We applied both predictors on the whole dataset and on each molecular immune-phenotype subgroups. The performances of the two predictors were analyzed in terms of discrimination and calibration. Probability of non-sentinel lymph node metastasis was detailed for each molecular subtype. RESULTS: Similar results were obtained with both predictors. We showed that the performance in terms of discrimination was as expected in ER Positive HER2 negative subgroup in both datasets (MSKCC AUC Dataset 1 = 0.73 [0.69-0.78], MSKCC AUC Dataset 2 = 0.71 (0.65-0.76, Tenon Score AUC Dataset 1 = 0.7 (0.65-0.75, Tenon Score AUC Dataset 2 = 0.72 (0.66-0.76. Probability of non-sentinel node metastatic involvement was slightly under-estimated. Contradictory results were obtained in other subgroups (ER negative HER2 negative, HER2 positive subgroups in both datasets probably due to a small sample size issue. We showed that merging the two datasets shifted the performance close to the ER positive HER2 negative subgroup. DISCUSSION: We showed that validated predictors like the Tenon Score or the MSKCC nomogram built on heterogeneous population of breast cancer performed equally on the different subgroups analyzed. Our present study re-enforce the idea that performing subgroup analysis of such predictors within less than 200 samples subgroup is at major risk of misleading conclusions.

  7. A molecular phylogeny for the leaf-roller moths (Lepidoptera: Tortricidae and its implications for classification and life history evolution.

    Directory of Open Access Journals (Sweden)

    Jerome C Regier

    Full Text Available BACKGROUND: Tortricidae, one of the largest families of microlepidopterans, comprise about 10,000 described species worldwide, including important pests, biological control agents and experimental models. Understanding of tortricid phylogeny, the basis for a predictive classification, is currently provisional. We present the first detailed molecular estimate of relationships across the tribes and subfamilies of Tortricidae, assess its concordance with previous morphological evidence, and re-examine postulated evolutionary trends in host plant use and biogeography. METHODOLOGY/PRINCIPAL FINDINGS: We sequenced up to five nuclear genes (6,633 bp in each of 52 tortricids spanning all three subfamilies and 19 of the 22 tribes, plus up to 14 additional genes, for a total of 14,826 bp, in 29 of those taxa plus all 14 outgroup taxa. Maximum likelihood analyses yield trees that, within Tortricidae, differ little among data sets and character treatments and are nearly always strongly supported at all levels of divergence. Support for several nodes was greatly increased by the additional 14 genes sequenced in just 29 of 52 tortricids, with no evidence of phylogenetic artifacts from deliberately incomplete gene sampling. There is strong support for the monophyly of Tortricinae and of Olethreutinae, and for grouping of these to the exclusion of Chlidanotinae. Relationships among tribes are robustly resolved in Tortricinae and mostly so in Olethreutinae. Feeding habit (internal versus external is strongly conserved on the phylogeny. Within Tortricinae, a clade characterized by eggs being deposited in large clusters, in contrast to singly or in small batches, has markedly elevated incidence of polyphagous species. The five earliest-branching tortricid lineages are all species-poor tribes with mainly southern/tropical distributions, consistent with a hypothesized Gondwanan origin for the family. CONCLUSIONS/SIGNIFICANCE: We present the first robustly supported

  8. Molecular Phylogenetic Classification of Streptomycetes Isolated from the Rhizosphere of Tropical Legume (Paraserianthes falcataria (L. Nielsen

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    LANGKAH SEMBIRING

    2009-09-01

    Full Text Available Intrageneric diversity of 556 streptomycetes isolated from the rhizosphere of tropical legume was determined by using molecular taxonomic method based on 16S rDNA. A total of 46 isolates were taken to represent 37 colour groups of the isolates. 16S rDNA were amplified and subsequently sequenced and the sequences data were aligned with streptomycete sequences retrieved from the ribosomal data base project (RDP data. Phylogenetic trees were generated by using the PHYLIP software package and the matrix of nucleotide similarity and nucleotide difference were generated by using PHYDIT software. The results confirmed and extended the value of 16S rDNA sequencing in streptomycete systematic. The 16S rDNA sequence data showed that most of the tested colour group representatives formed new centers of taxonomic variation within the genus Streptomyces. The generic assignment of these organisms was underpinned by 16S rDNA sequence data which also suggested that most of the strains represented new centers of taxonomic variation. The taxonomic data indicate that diverse populations of streptomycetes are associated with the roots of tropical legume (P. falcataria. Therefore, the combination of selective isolation and molecular taxonomic procedures used in this study provide a powerful way of uncovering new centers of taxonomic variation within the genus Streptomyces.

  9. New Brain Tumor Entities Emerge from Molecular Classification of CNS-PNETs.

    Science.gov (United States)

    Sturm, Dominik; Orr, Brent A; Toprak, Umut H; Hovestadt, Volker; Jones, David T W; Capper, David; Sill, Martin; Buchhalter, Ivo; Northcott, Paul A; Leis, Irina; Ryzhova, Marina; Koelsche, Christian; Pfaff, Elke; Allen, Sariah J; Balasubramanian, Gnanaprakash; Worst, Barbara C; Pajtler, Kristian W; Brabetz, Sebastian; Johann, Pascal D; Sahm, Felix; Reimand, Jüri; Mackay, Alan; Carvalho, Diana M; Remke, Marc; Phillips, Joanna J; Perry, Arie; Cowdrey, Cynthia; Drissi, Rachid; Fouladi, Maryam; Giangaspero, Felice; Łastowska, Maria; Grajkowska, Wiesława; Scheurlen, Wolfram; Pietsch, Torsten; Hagel, Christian; Gojo, Johannes; Lötsch, Daniela; Berger, Walter; Slavc, Irene; Haberler, Christine; Jouvet, Anne; Holm, Stefan; Hofer, Silvia; Prinz, Marco; Keohane, Catherine; Fried, Iris; Mawrin, Christian; Scheie, David; Mobley, Bret C; Schniederjan, Matthew J; Santi, Mariarita; Buccoliero, Anna M; Dahiya, Sonika; Kramm, Christof M; von Bueren, André O; von Hoff, Katja; Rutkowski, Stefan; Herold-Mende, Christel; Frühwald, Michael C; Milde, Till; Hasselblatt, Martin; Wesseling, Pieter; Rößler, Jochen; Schüller, Ulrich; Ebinger, Martin; Schittenhelm, Jens; Frank, Stephan; Grobholz, Rainer; Vajtai, Istvan; Hans, Volkmar; Schneppenheim, Reinhard; Zitterbart, Karel; Collins, V Peter; Aronica, Eleonora; Varlet, Pascale; Puget, Stephanie; Dufour, Christelle; Grill, Jacques; Figarella-Branger, Dominique; Wolter, Marietta; Schuhmann, Martin U; Shalaby, Tarek; Grotzer, Michael; van Meter, Timothy; Monoranu, Camelia-Maria; Felsberg, Jörg; Reifenberger, Guido; Snuderl, Matija; Forrester, Lynn Ann; Koster, Jan; Versteeg, Rogier; Volckmann, Richard; van Sluis, Peter; Wolf, Stephan; Mikkelsen, Tom; Gajjar, Amar; Aldape, Kenneth; Moore, Andrew S; Taylor, Michael D; Jones, Chris; Jabado, Nada; Karajannis, Matthias A; Eils, Roland; Schlesner, Matthias; Lichter, Peter; von Deimling, Andreas; Pfister, Stefan M; Ellison, David W; Korshunov, Andrey; Kool, Marcel

    2016-02-25

    Primitive neuroectodermal tumors of the central nervous system (CNS-PNETs) are highly aggressive, poorly differentiated embryonal tumors occurring predominantly in young children but also affecting adolescents and adults. Herein, we demonstrate that a significant proportion of institutionally diagnosed CNS-PNETs display molecular profiles indistinguishable from those of various other well-defined CNS tumor entities, facilitating diagnosis and appropriate therapy for patients with these tumors. From the remaining fraction of CNS-PNETs, we identify four new CNS tumor entities, each associated with a recurrent genetic alteration and distinct histopathological and clinical features. These new molecular entities, designated "CNS neuroblastoma with FOXR2 activation (CNS NB-FOXR2)," "CNS Ewing sarcoma family tumor with CIC alteration (CNS EFT-CIC)," "CNS high-grade neuroepithelial tumor with MN1 alteration (CNS HGNET-MN1)," and "CNS high-grade neuroepithelial tumor with BCOR alteration (CNS HGNET-BCOR)," will enable meaningful clinical trials and the development of therapeutic strategies for patients affected by poorly differentiated CNS tumors.

  10. Molecular profiling of liver tumors: classification and clinical translation for decision making.

    Science.gov (United States)

    Pinyol, Roser; Nault, Jean Charles; Quetglas, Iris M; Zucman-Rossi, Jessica; Llovet, Josep M

    2014-11-01

    Hepatocellular carcinoma (HCC) is a complex disease with a dismal prognosis. Consequently, a translational approach is required to personalized clinical decision making to improve survival of HCC patients. Molecular signatures from cirrhotic livers and single nucleotide polymorphism have been linked with HCC occurrence. Identification of high-risk populations will be useful to design chemopreventive trials. In addition, molecular signatures derived from tumor and nontumor samples are associated with early tumor recurrence due to metastasis and late tumor recurrence due to de novo carcinogenesis after curative treatment, respectively. Identification of patients with a high risk of relapse will guide adjuvant randomized trials. The genetic landscape drawn by next-generation sequencing has highlighted the genomic diversity of HCC. Genetic drivers recurrently mutated belong to different signaling pathways including telomere maintenance, cell-cycle regulators, chromatin remodeling, Wnt/b-catenin, RAS/RAF/MAPK kinase, and AKT/mTOR pathway. These cancer genes will be ideally targeted by biotherapies as a paradigm of stratified medicine adapted to tumor biology. PMID:25369299

  11. Ring polymer molecular dynamics fast computation of rate coefficients on accurate potential energy surfaces in local configuration space: Application to the abstraction of hydrogen from methane

    Science.gov (United States)

    Meng, Qingyong; Chen, Jun; Zhang, Dong H.

    2016-04-01

    To fast and accurately compute rate coefficients of the H/D + CH4 → H2/HD + CH3 reactions, we propose a segmented strategy for fitting suitable potential energy surface (PES), on which ring-polymer molecular dynamics (RPMD) simulations are performed. On the basis of recently developed permutation invariant polynomial neural-network approach [J. Li et al., J. Chem. Phys. 142, 204302 (2015)], PESs in local configuration spaces are constructed. In this strategy, global PES is divided into three parts, including asymptotic, intermediate, and interaction parts, along the reaction coordinate. Since less fitting parameters are involved in the local PESs, the computational efficiency for operating the PES routine is largely enhanced by a factor of ˜20, comparing with that for global PES. On interaction part, the RPMD computational time for the transmission coefficient can be further efficiently reduced by cutting off the redundant part of the child trajectories. For H + CH4, good agreements among the present RPMD rates and those from previous simulations as well as experimental results are found. For D + CH4, on the other hand, qualitative agreement between present RPMD and experimental results is predicted.

  12. Molecular Classification and Pharmacogenetics of Primary Plasma Cell Leukemia: An Initial Approach toward Precision Medicine.

    Science.gov (United States)

    Simeon, Vittorio; Todoerti, Katia; La Rocca, Francesco; Caivano, Antonella; Trino, Stefania; Lionetti, Marta; Agnelli, Luca; De Luca, Luciana; Laurenzana, Ilaria; Neri, Antonino; Musto, Pellegrino

    2015-07-30

    Primary plasma cell leukemia (pPCL) is a rare and aggressive variant of multiple myeloma (MM) which may represent a valid model for high-risk MM. This disease is associated with a very poor prognosis, and unfortunately, it has not significantly improved during the last three decades. New high-throughput technologies have allowed a better understanding of the molecular basis of this disease and moved toward risk stratification, providing insights for targeted therapy studies. This knowledge, added to the pharmacogenetic profile of new and old agents in the analysis of efficacy and safety, could contribute to help clinical decisions move toward a precision medicine and a better clinical outcome for these patients. In this review, we describe the available literature concerning the genomic characterization and pharmacogenetics of plasma cell leukemia (PCL).

  13. Choice of adjuvant drug therapy on the basis of the molecular classification of breast cancer

    Directory of Open Access Journals (Sweden)

    N. S. Besova

    2012-01-01

    Full Text Available Molecular genetic analysis identified some biological subtypes of breast cancer (BC: luminal A, luminal B, HER2 positive, and basal-like (including triple negative. The surrogate clinical and morphological criteria including the immunohistochemical determination of estrogen and progesterone receptors, the hyperexpression and/or amplification of HER2, Ki-67, or tumor grade (G are used to identify the biological subtypes of BC in clinical practice. The biological subtypes are distinguished by their biological course and susceptibility to various systemic treatments, which requires different therapeutic tactics. The paper presents tactics of adjuvant therapy for BC in relation to its biological subtype according to the recommendations of the 12th St. Gallen International Breast Cancer Conference (2011 and considers the place of taxans.

  14. Molecular Classification and Pharmacogenetics of Primary Plasma Cell Leukemia: An Initial Approach toward Precision Medicine

    Directory of Open Access Journals (Sweden)

    Vittorio Simeon

    2015-07-01

    Full Text Available Primary plasma cell leukemia (pPCL is a rare and aggressive variant of multiple myeloma (MM which may represent a valid model for high-risk MM. This disease is associated with a very poor prognosis, and unfortunately, it has not significantly improved during the last three decades. New high-throughput technologies have allowed a better understanding of the molecular basis of this disease and moved toward risk stratification, providing insights for targeted therapy studies. This knowledge, added to the pharmacogenetic profile of new and old agents in the analysis of efficacy and safety, could contribute to help clinical decisions move toward a precision medicine and a better clinical outcome for these patients. In this review, we describe the available literature concerning the genomic characterization and pharmacogenetics of plasma cell leukemia (PCL.

  15. Molecular Classification and Pharmacogenetics of Primary Plasma Cell Leukemia: An Initial Approach toward Precision Medicine.

    Science.gov (United States)

    Simeon, Vittorio; Todoerti, Katia; La Rocca, Francesco; Caivano, Antonella; Trino, Stefania; Lionetti, Marta; Agnelli, Luca; De Luca, Luciana; Laurenzana, Ilaria; Neri, Antonino; Musto, Pellegrino

    2015-01-01

    Primary plasma cell leukemia (pPCL) is a rare and aggressive variant of multiple myeloma (MM) which may represent a valid model for high-risk MM. This disease is associated with a very poor prognosis, and unfortunately, it has not significantly improved during the last three decades. New high-throughput technologies have allowed a better understanding of the molecular basis of this disease and moved toward risk stratification, providing insights for targeted therapy studies. This knowledge, added to the pharmacogenetic profile of new and old agents in the analysis of efficacy and safety, could contribute to help clinical decisions move toward a precision medicine and a better clinical outcome for these patients. In this review, we describe the available literature concerning the genomic characterization and pharmacogenetics of plasma cell leukemia (PCL). PMID:26263974

  16. Molecular Classification and Pharmacogenetics of Primary Plasma Cell Leukemia: An Initial Approach toward Precision Medicine

    Science.gov (United States)

    Simeon, Vittorio; Todoerti, Katia; La Rocca, Francesco; Caivano, Antonella; Trino, Stefania; Lionetti, Marta; Agnelli, Luca; De Luca, Luciana; Laurenzana, Ilaria; Neri, Antonino; Musto, Pellegrino

    2015-01-01

    Primary plasma cell leukemia (pPCL) is a rare and aggressive variant of multiple myeloma (MM) which may represent a valid model for high-risk MM. This disease is associated with a very poor prognosis, and unfortunately, it has not significantly improved during the last three decades. New high-throughput technologies have allowed a better understanding of the molecular basis of this disease and moved toward risk stratification, providing insights for targeted therapy studies. This knowledge, added to the pharmacogenetic profile of new and old agents in the analysis of efficacy and safety, could contribute to help clinical decisions move toward a precision medicine and a better clinical outcome for these patients. In this review, we describe the available literature concerning the genomic characterization and pharmacogenetics of plasma cell leukemia (PCL). PMID:26263974

  17. Molecular subtype classification is a determinant of non-sentinel lymph node metastasis in breast cancer patients with positive sentinel lymph nodes.

    Directory of Open Access Journals (Sweden)

    Wenbin Zhou

    Full Text Available BACKGROUND: Previous studies suggested that the molecular subtypes were strongly associated with sentinel lymph node (SLN status. The purpose of this study was to determine whether molecular subtype classification was associated with non-sentinel lymph nodes (NSLN metastasis in patients with a positive SLN. METHODOLOGY AND PRINCIPAL FINDINGS: Between January 2001 and March 2011, a total of 130 patients with a positive SLN were recruited. All these patients underwent a complete axillary lymph node dissection. The univariate and multivariate analyses of NSLN metastasis were performed. In univariate and multivariate analyses, large tumor size, macrometastasis and high tumor grade were all significant risk factors of NSLN metastasis in patients with a positive SLN. In univariate analysis, luminal B subgroup showed higher rate of NSLN metastasis than other subgroup (P = 0.027. When other variables were adjusted in multivariate analysis, the molecular subtype classification was a determinant of NSLN metastasis. Relative to triple negative subgroup, both luminal A (P = 0.047 and luminal B (P = 0.010 subgroups showed a higher risk of NSLN metastasis. Otherwise, HER2 over-expression subgroup did not have a higher risk than triple negative subgroup (P = 0.183. The area under the curve (AUC value was 0.8095 for the Cambridge model. When molecular subtype classification was added to the Cambridge model, the AUC value was 0.8475. CONCLUSIONS: Except for other factors, molecular subtype classification was a determinant of NSLN metastasis in patients with a positive SLN. The predictive accuracy of mathematical models including molecular subtype should be determined in the future.

  18. Molecular classification of non-invasive breast lesions for personalised therapy and chemoprevention.

    Science.gov (United States)

    Buckley, Niamh; Boyle, David; McArt, Darragh; Irwin, Gareth; Harkin, D Paul; Lioe, Tong; McQuaid, Stephen; James, Jacqueline A; Maxwell, Perry; Hamilton, Peter; Mullan, Paul B; Salto-Tellez, Manuel

    2015-12-22

    Breast cancer screening has led to a dramatic increase in the detection of pre-invasive breast lesions. While mastectomy is almost guaranteed to treat the disease, more conservative approaches could be as effective if patients can be stratified based on risk of co-existing or recurrent invasive disease.Here we use a range of biomarkers to interrogate and classify purely non-invasive lesions (PNL) and those with co-existing invasive breast cancer (CEIN). Apart from Ductal Carcinoma In Situ (DCIS), relative homogeneity is observed. DCIS contained a greater spread of molecular subtypes. Interestingly, high expression of p-mTOR was observed in all PNL with lower expression in DCIS and invasive carcinoma while the opposite expression pattern was observed for TOP2A.Comparing PNL with CEIN, we have identified p53 and Ki67 as predictors of CEIN with a combined PPV and NPV of 90.48% and 43.3% respectively. Furthermore, HER2 expression showed the best concordance between DCIS and its invasive counterpart.We propose that these biomarkers can be used to improve the management of patients with pre-invasive breast lesions following further validation and clinical trials. p53 and Ki67 could be used to stratify patients into low and high-risk groups for co-existing disease. Knowledge of expression of more actionable targets such as HER2 or TOP2A can be used to design chemoprevention or neo-adjuvant strategies. Increased knowledge of the molecular profile of pre-invasive lesions can only serve to enhance our understanding of the disease and, in the era of personalised medicine, bring us closer to improving breast cancer care. PMID:26657114

  19. Comparing implementations of magnetic-resonance-guided fluorescence molecular tomography for diagnostic classification of brain tumors

    Science.gov (United States)

    Davis, Scott C.; Samkoe, Kimberley S.; O'Hara, Julia A.; Gibbs-Strauss, Summer L.; Paulsen, Keith D.; Pogue, Brian W.

    2010-09-01

    Fluorescence molecular tomography (FMT) systems coupled to conventional imaging modalities such as magnetic resonance imaging (MRI) and computed tomography provide unique opportunities to combine data sets and improve image quality and content. Yet, the ideal approach to combine these complementary data is still not obvious. This preclinical study compares several methods for incorporating MRI spatial prior information into FMT imaging algorithms in the context of in vivo tissue diagnosis. Populations of mice inoculated with brain tumors that expressed either high or low levels of epidermal growth factor receptor (EGFR) were imaged using an EGF-bound near-infrared dye and a spectrometer-based MRI-FMT scanner. All data were spectrally unmixed to extract the dye fluorescence from the tissue autofluorescence. Methods to combine the two data sets were compared using student's t-tests and receiver operating characteristic analysis. Bulk fluorescence measurements that made up the optical imaging data set were also considered in the comparison. While most techniques were able to distinguish EGFR(+) tumors from EGFR(-) tumors and control animals, with area-under-the-curve values=1, only a handful were able to distinguish EGFR(-) tumors from controls. Bulk fluorescence spectroscopy techniques performed as well as most imaging techniques, suggesting that complex imaging algorithms may be unnecessary to diagnose EGFR status in these tissue volumes.

  20. Benign hepatocellular nodules: what have we learned using the patho-molecular classification.

    Science.gov (United States)

    Sempoux, Christine; Chang, Charissa; Gouw, Annette; Chiche, Laurence; Zucman-Rossi, Jessica; Balabaud, Charles; Bioulac-Sage, Paulette

    2013-09-01

    Focal nodular hyperplasia (FNH) and hepatocellular adenoma (HCA) are benign hepatocellular tumors that develop most frequently in females and in non-cirrhotic livers. HCA are prone to bleed and to transform into hepatocellular carcinoma (HCC). Four major subgroups of HCA have been thus far identified: HNF1α mutated HCA, inflammatory HCA (IHCA), β-catenin mutated HCA (b-HCA and b-IHCA), based on mutations in specific oncogenes and tumor suppressors. B-HCA and b-IHCA are strongly associated with HCC transformation. Benign hepatocellular tumors can be classified using immunohistochemistry (LFABP, CRP, GS, b-catenin). Analysis of HCA phenotypes has led to the identification of patients at risk of HCC transformation and therefore improved the indications provided by invasive and non-invasive diagnostic techniques, such as biopsies and MRI. These recent advances have broadened the clinical scope of HCA in various conditions, such as their presence in males, in obese patients, in patients suffering from liver vascular disorders, genetic diseases. However, specific immunohistochemistry has shown limitations particularly for the identification of b-HCA, thereby, outlining the importance of molecular studies to improve the diagnosis/prognosis of HCA. If evaluation of prognosis and treatment has benefited from these advances, much more needs to be done to obtain guidelines for good clinical practice. PMID:23876350

  1. Gastrointestinal B-cell lymphomas: From understanding B-cell physiology to classification and molecular pathology.

    Science.gov (United States)

    Sagaert, Xavier; Tousseyn, Thomas; Yantiss, Rhonda K

    2012-12-15

    The gut is the most common extranodal site where lymphomas arise. Although all histological lymphoma types may develop in the gut, small and large B-cell lymphomas predominate. The sometimes unexpected finding of a lymphoid lesion in an endoscopic biopsy of the gut may challenge both the clinician (who is not always familiar with lymphoma pathogenesis) and the pathologist (who will often be hampered in his/her diagnostic skill by the limited amount of available tissue). Moreover, the past 2 decades have spawned an avalanche of new data that encompasses both the function of the reactive B-cell as well as the pathogenic pathways that lead to its neoplastic counterpart, the B-cell lymphoma. Therefore, this review aims to offer clinicians an overview of B-cell lymphomas in the gut, and their pertinent molecular features that have led to new insights regarding lymphomagenesis. It addresses the question as how to incorporate all presently available information on normal and neoplastic B-cell differentiation, and how this knowledge can be applied in daily clinical practice (e.g., diagnostic tools, prognostic biomarkers or therapeutic targets) to optimalise the managment of this heterogeneous group of neoplasms. PMID:23443141

  2. Molecular and metabolic pattern classification for detection of brain glioma progression

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    Imani, Farzin, E-mail: imanif@upmc.edu [Department of Radiology, University of Pittsburgh Medical Center, PA (United States); Boada, Fernando E. [Department of Radiology, University of Pittsburgh Medical Center, PA (United States); Lieberman, Frank S. [Department of Neurology, University of Pittsburgh Medical Center, PA (United States); Davis, Denise K.; Mountz, James M. [Department of Radiology, University of Pittsburgh Medical Center, PA (United States)

    2014-02-15

    %. Conclusion: This study suggests that SVM models may improve detection of glioma progression more accurately than single parametric imaging methods. Research support: National Cancer Institute, Cancer Center Support Grant Supplement Award, Imaging Response Assessment Teams.

  3. Molecular and metabolic pattern classification for detection of brain glioma progression

    International Nuclear Information System (INIS)

    that SVM models may improve detection of glioma progression more accurately than single parametric imaging methods. Research support: National Cancer Institute, Cancer Center Support Grant Supplement Award, Imaging Response Assessment Teams

  4. Synergistic Effects of Combining Morphological and Molecular Data in Resolving the Intraspecific Classification in O. basilicum L.

    Directory of Open Access Journals (Sweden)

    Zlatko Šatović

    2010-03-01

    Full Text Available High levels of both morphological and chemical variability exist within the O. basilicum L. species. Long-term traditional uses and wide distribution throughout the world, as well as traditional selection and breeding efforts, have contributed to variability within the species. Morphological traits according to UPOV descriptor list and AFLP markers were utilized to define the extent of existing variation in the species analyzing 24 accessions. Phenotypic dissimilarities between pairs of accessions were calculated and the UPGMA dendrogram was constructed. A number of clearly defined clusters have been detected, giving a good representation of traditional taxonomic relationships. Genetic relationships were determined by Neighbour-Joining cluster analysis based on Dice’s distance matrix between accessions. Generally, morphologically similar accessions grouped together and a high congruence between trees was observed. Our analyses revealed a certain degree of correspondence between morphological and molecular data among O. basilicum L. accessions. Both AFLP markers and morphological descriptors can contribute in resolving existing problems concerning intraspecific classification in O. basilicum.

  5. Molecular classification of thyroid lesions by combined testing for miRNA gene expression and somatic gene alterations.

    Science.gov (United States)

    Wylie, Dennis; Beaudenon-Huibregtse, Sylvie; Haynes, Brian C; Giordano, Thomas J; Labourier, Emmanuel

    2016-04-01

    Multiple molecular markers contribute to the pathogenesis of thyroid cancer and can provide valuable information to improve disease diagnosis and patient management. We performed a comprehensive evaluation of miRNA gene expression in diverse thyroid lesions (n = 534) and developed predictive models for the classification of thyroid nodules, alone or in combination with genotyping. Expression profiling by reverse transcription-quantitative polymerase chain reaction in surgical specimens (n = 257) identified specific miRNAs differentially expressed in 17 histopathological categories. Eight supervised machine learning algorithms were trained to discriminate benign from malignant lesions and evaluated for accuracy and robustness. The selected models showed invariant area under the receiver operating characteristic curve (AUC) in cross-validation (0.89), optimal AUC (0.94) in an independent set of preoperative thyroid nodule aspirates (n = 235), and classified 92% of benign lesions as low risk/negative and 92% of malignant lesions as high risk/positive. Surgical and preoperative specimens were further tested for the presence of 17 validated oncogenic gene alterations in the BRAF, RAS, RET or PAX8 genes. The miRNA-based classifiers complemented and significantly improved the diagnostic performance of the 17-mutation panel (p management of patients with indeterminate thyroid nodules. PMID:27499919

  6. Molecular and morphological data supporting phylogenetic reconstruction of the genus Goniothalamus (Annonaceae, including a reassessment of previous infrageneric classifications

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    Chin Cheung Tang

    2015-09-01

    Full Text Available Data is presented in support of a phylogenetic reconstruction of the species-rich early-divergent angiosperm genus Goniothalamus (Annonaceae (Tang et al., Mol. Phylogenetic Evol., 2015 [1], inferred using chloroplast DNA (cpDNA sequences. The data includes a list of primers for amplification and sequencing for nine cpDNA regions: atpB-rbcL, matK, ndhF, psbA-trnH, psbM-trnD, rbcL, trnL-F, trnS-G, and ycf1, the voucher information and molecular data (GenBank accession numbers of 67 ingroup Goniothalamus accessions and 14 outgroup accessions selected from across the tribe Annoneae, and aligned data matrices for each gene region. We also present our Bayesian phylogenetic reconstructions for Goniothalamus, with information on previous infrageneric classifications superimposed to enable an evaluation of monophyly, together with a taxon-character data matrix (with 15 morphological characters scored for 66 Goniothalamus species and seven other species from the tribe Annoneae that are shown to be phylogenetically correlated.

  7. Clinical utility of reverse phase protein array for molecular classification of breast cancer.

    Science.gov (United States)

    Negm, Ola H; Muftah, Abir A; Aleskandarany, Mohammed A; Hamed, Mohamed R; Ahmad, Dena A J; Nolan, Christopher C; Diez-Rodriguez, Maria; Tighe, Patrick J; Ellis, Ian O; Rakha, Emad A; Green, Andrew R

    2016-01-01

    Reverse Phase Protein Array (RPPA) represents a sensitive and high-throughput technique allowing simultaneous quantitation of protein expression levels in biological samples. This study aimed to confirm the ability of RPPA to classify archival formalin-fixed paraffin-embedded (FFPE) breast cancer tissues into molecular classes used in the Nottingham prognostic index plus (NPI+) determined by immunohistochemistry (IHC). Proteins were extracted from FFPE breast cancer tissues using three extraction protocols: the Q-proteome FFPE Tissue Kit (Qiagen, Hilden, Germany) and two in-house methods using Laemmli buffer with either incubation for 20 min or 2 h at 105 °C. Two preparation methods, full-face sections and macrodissection, were used to assess the yield and quality of protein extracts. Ten biomarkers used for the NPI+ (ER, PgR, HER2, Cytokeratins 5/6 and 7/8, EGFR, HER3, HER4, p53 and Mucin 1) were quantified using RPPA and compared to results determined by IHC. The Q-proteome FFPE Tissue Kit produced significantly higher protein concentration and signal intensities. The intra- and inter-array reproducibility assessment indicated that RPPA using FFPE lysates was a highly reproducible and robust technique. Expression of the biomarkers individually and in combination using RPPA was highly consistent with IHC results. Macrodissection of the invasive tumour component gave more reliable results with the majority of biomarkers determined by IHC, (80 % concordance) compared with full-face sections (60 % concordance). Our results provide evidence for the technical feasibility of RPPA for high-throughput protein expression profiling of FFPE breast cancer tissues. The sensitivity of the technique is related to the quality of extracted protein and purity of tumour tissue. RPPA could provide a quantitative technique alternative to IHC for the biomarkers used in the NPI+.

  8. Synergistic Effects of Combining Morphological and Molecular Data in Resolving the Intraspecific Classification in O. basilicum L.

    Directory of Open Access Journals (Sweden)

    Klaudija Carović-Stanko

    2014-02-01

    Full Text Available Normal 0 false false false MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Obična tablica"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman"; mso-ansi-language:#0400; mso-fareast-language:#0400; mso-bidi-language:#0400;} High levels of both morphological and chemical variability exist within the O. basilicum L. species. Long-term traditional uses and wide distribution throughout the world, as well as traditional selection and breeding efforts, have contributed to variability within the species. Morphological traits according to UPOV descriptor list and AFLP markers were utilized to define the extent of existing variation in the species analyzing 24 accessions. Phenotypic dissimilarities between pairs of accessions were calculated and the UPGMA dendrogram was constructed. A number of clearly defined clusters have been detected, giving a good representation of traditional taxonomic relationships. Genetic relationships were determined by Neighbour-Joining cluster analysis based on Dice’s distance matrix between accessions. Generally, morphologically similar accessions grouped together and a high congruence between trees was observed. Our analyses revealed a certain degree of correspondence between morphological and molecular data among O. basilicum L. accessions. Both AFLP markers and morphological descriptors can contribute in resolving existing problems concerning intraspecific classification in O. basilicum.

  9. Classification: Molecular & Synaptic Mechanisms

    Science.gov (United States)

    Lussier, Marc P.; Gu, Xinglong; Lu, Wei; Roche, Katherine W.

    2014-01-01

    Controlling the density of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs) at synapses is essential for regulating the strength of excitatory neurotransmission. In particular, the phosphorylation of AMPARs is important for defining both synaptic expression and intracellular routing of receptors. Phosphorylation is a posttranslational modification known to regulate many cellular events and the C-termini of glutamate receptors are important targets. Recently, the first intracellular loop1 region of the GluA1 subunit of AMPARs was reported to regulate synaptic targeting through phosphorylation of S567 by Ca2+/calmodulin-dependent protein kinase II (CaMKII). Intriguingly, the loop1 region of all four AMPAR subunits contains many putative phosphorylation sites (S/T/Y), leaving the possibility that other kinases may regulate AMPAR surface expression via phosphorylation of the loop regions. To explore this hypothesis, we used in vitro phosphorylation assays with a small panel of purified kinases and found that casein kinase 2 (CK2) phosphorylates the GluA1 and GluA2 loop1 regions, but not GluA3 or GluA4. Interestingly, when we reduced the endogenous expression of CK2 using a specific shRNA against the regulatory subunit CK2β, we detected a reduction of GluA1 surface expression, whereas GluA2 was unchanged. Furthermore, we identified S579 of GluA1 as a substrate of CK2, and the expression of GluA1 phospho-deficient mutants in hippocampal neurons displayed reduced surface expression. Therefore, our study identifies CK2 as a regulator of GluA1 surface expression by phosphorylating the intracellular loop1 region. PMID:24712994

  10. Binary classification of chalcone derivatives with LDA or KNN based on their antileishmanial activity and molecular descriptors selected using the Successive Projections Algorithm feature-selection technique.

    Science.gov (United States)

    Goodarzi, Mohammad; Saeys, Wouter; de Araujo, Mario Cesar Ugulino; Galvão, Roberto Kawakami Harrop; Vander Heyden, Yvan

    2014-01-23

    Chalcones are naturally occurring aromatic ketones, which consist of an α-, β-unsaturated carbonyl system joining two aryl rings. These compounds are reported to exhibit several pharmacological activities, including antiparasitic, antibacterial, antifungal, anticancer, immunomodulatory, nitric oxide inhibition and anti-inflammatory effects. In the present work, a Quantitative Structure-Activity Relationship (QSAR) study is carried out to classify chalcone derivatives with respect to their antileishmanial activity (active/inactive) on the basis of molecular descriptors. For this purpose, two techniques to select descriptors are employed, the Successive Projections Algorithm (SPA) and the Genetic Algorithm (GA). The selected descriptors are initially employed to build Linear Discriminant Analysis (LDA) models. An additional investigation is then carried out to determine whether the results can be improved by using a non-parametric classification technique (One Nearest Neighbour, 1NN). In a case study involving 100 chalcone derivatives, the 1NN models were found to provide better rates of correct classification than LDA, both in the training and test sets. The best result was achieved by a SPA-1NN model with six molecular descriptors, which provided correct classification rates of 97% and 84% for the training and test sets, respectively.

  11. The accurate calculation of the band gap of liquid water by means of GW corrections applied to plane-wave density functional theory molecular dynamics simulations

    NARCIS (Netherlands)

    Fang, Changming; Li, Wun Fan; Koster, Rik S.; Klimeš, Jiří; Van Blaaderen, Alfons; Van Huis, Marijn A.

    2015-01-01

    Knowledge about the intrinsic electronic properties of water is imperative for understanding the behaviour of aqueous solutions that are used throughout biology, chemistry, physics, and industry. The calculation of the electronic band gap of liquids is challenging, because the most accurate ab initi

  12. Pharmacological Classification and Activity Evaluation of Furan and Thiophene Amide Derivatives Applying Semi-Empirical ab initio Molecular Modeling Methods

    Directory of Open Access Journals (Sweden)

    Leszek Bober

    2012-05-01

    Full Text Available Pharmacological and physicochemical classification of the furan and thiophene amide derivatives by multiple regression analysis and partial least square (PLS based on semi-empirical ab initio molecular modeling studies and high-performance liquid chromatography (HPLC retention data is proposed. Structural parameters obtained from the PCM (Polarizable Continuum Model method and the literature values of biological activity (antiproliferative for the A431 cells expressed as LD50 of the examined furan and thiophene derivatives was used to search for relationships. It was tested how variable molecular modeling conditions considered together, with or without HPLC retention data, allow evaluation of the structural recognition of furan and thiophene derivatives with respect to their pharmacological properties.

  13. Molecular phylogeny of the manakins (Ayes: Passeriformes: Pipridae), with a new classification and the description of a new genus

    DEFF Research Database (Denmark)

    Ohlson, Jan I.; Fjeldså, Jon; Ericson, Per G. P.

    2013-01-01

    the Piprinae into two principal clades: Ilicurini and Piprini. The genera Pipra and Chloropipo are found to be polyphyletic. Chloropipo species are placed in three different clades, including two species in an unresolved position alongside Ilicurini and Piprini. We propose a new classification of the family......, where the most important modifications include recognizing the genus Ceratopipra for five species formerly placed in Pipra and the erection of a new genus for Chloropipo holochlora. (C) 2013 Elsevier Inc. All rights reserved....

  14. Accurate molecular dynamics and nuclear quantum effects at low cost by multiple steps in real and imaginary time: Using density functional theory to accelerate wavefunction methods

    Energy Technology Data Exchange (ETDEWEB)

    Kapil, V.; Ceriotti, M., E-mail: michele.ceriotti@epfl.ch [Laboratory of Computational Science and Modelling, Institute of Materials, Ecole Polytechnique Fédérale de Lausanne, Lausanne (Switzerland); VandeVondele, J., E-mail: joost.vandevondele@mat.ethz.ch [Department of Materials, ETH Zurich, Wolfgang-Pauli-Strasse 27, CH-8093 Zurich (Switzerland)

    2016-02-07

    The development and implementation of increasingly accurate methods for electronic structure calculations mean that, for many atomistic simulation problems, treating light nuclei as classical particles is now one of the most serious approximations. Even though recent developments have significantly reduced the overhead for modeling the quantum nature of the nuclei, the cost is still prohibitive when combined with advanced electronic structure methods. Here we present how multiple time step integrators can be combined with ring-polymer contraction techniques (effectively, multiple time stepping in imaginary time) to reduce virtually to zero the overhead of modelling nuclear quantum effects, while describing inter-atomic forces at high levels of electronic structure theory. This is demonstrated for a combination of MP2 and semi-local DFT applied to the Zundel cation. The approach can be seamlessly combined with other methods to reduce the computational cost of path integral calculations, such as high-order factorizations of the Boltzmann operator or generalized Langevin equation thermostats.

  15. Accurate molecular dynamics and nuclear quantum effects at low cost by multiple steps in real and imaginary time: Using density functional theory to accelerate wavefunction methods

    International Nuclear Information System (INIS)

    The development and implementation of increasingly accurate methods for electronic structure calculations mean that, for many atomistic simulation problems, treating light nuclei as classical particles is now one of the most serious approximations. Even though recent developments have significantly reduced the overhead for modeling the quantum nature of the nuclei, the cost is still prohibitive when combined with advanced electronic structure methods. Here we present how multiple time step integrators can be combined with ring-polymer contraction techniques (effectively, multiple time stepping in imaginary time) to reduce virtually to zero the overhead of modelling nuclear quantum effects, while describing inter-atomic forces at high levels of electronic structure theory. This is demonstrated for a combination of MP2 and semi-local DFT applied to the Zundel cation. The approach can be seamlessly combined with other methods to reduce the computational cost of path integral calculations, such as high-order factorizations of the Boltzmann operator or generalized Langevin equation thermostats

  16. Simple and accurate scheme to compute electrostatic interaction: zero-dipole summation technique for molecular system and application to bulk water.

    Science.gov (United States)

    Fukuda, Ikuo; Kamiya, Narutoshi; Yonezawa, Yasushige; Nakamura, Haruki

    2012-08-01

    The zero-dipole summation method was extended to general molecular systems, and then applied to molecular dynamics simulations of an isotropic water system. In our previous paper [I. Fukuda, Y. Yonezawa, and H. Nakamura, J. Chem. Phys. 134, 164107 (2011)], for evaluating the electrostatic energy of a classical particle system, we proposed the zero-dipole summation method, which conceptually prevents the nonzero-charge and nonzero-dipole states artificially generated by a simple cutoff truncation. Here, we consider the application of this scheme to molecular systems, as well as some fundamental aspects of general cutoff truncation protocols. Introducing an idea to harmonize the bonding interactions and the electrostatic interactions in the scheme, we develop a specific algorithm. As in the previous study, the resulting energy formula is represented by a simple pairwise function sum, enabling facile applications to high-performance computation. The accuracy of the electrostatic energies calculated by the zero-dipole summation method with the atom-based cutoff was numerically investigated, by comparison with those generated by the Ewald method. We obtained an electrostatic energy error of less than 0.01% at a cutoff length longer than 13 Å for a TIP3P isotropic water system, and the errors were quite small, as compared to those obtained by conventional truncation methods. The static property and the stability in an MD simulation were also satisfactory. In addition, the dielectric constants and the distance-dependent Kirkwood factors were measured, and their coincidences with those calculated by the particle mesh Ewald method were confirmed, although such coincidences are not easily attained by truncation methods. We found that the zero damping-factor gave the best results in a practical cutoff distance region. In fact, in contrast to the zero-charge scheme, the damping effect was insensitive in the zero-charge and zero-dipole scheme, in the molecular system we

  17. A study on the relationship between breast cancer molecular classification and prognosis%乳腺癌分子分型与预后关系的研究

    Institute of Scientific and Technical Information of China (English)

    陈小松; 陆劲松; 韩企夏; 邵志敏; 沈镇宙; 沈坤炜; 马传栋; 陈灿铭; 杨文涛; 陆洪芬; 周晓燕; 柳光宇; 狄根红; 吴炅

    2008-01-01

    目的 探讨乳腺癌分子分型与预后之间的关系.方法 回顾性分析2002年1月至2003年12月接受手术治疗的708例原发性乳腺癌患者的临床资料.患者均为女性,平均年龄53岁.根据雌激素受体(ER)、孕激素受体(PR)及人类表皮生长因子受体2(HER2)状态的免疫组织化学结果,将全组乳腺癌分型为:内分泌高反应型、内分泌反应不完全型、三阴型及HER2阳性型,观察不同分子分型乳腺癌的预后,比较各型患者术后的累计生存率,多因素分析筛选预后相关因素.结果 本组内分泌高反应型、内分泌反应不完全型、HER2阳性型及三阴型乳腺癌所占的比例分别为33.2%(235/708)、23.6%(167/708)、21.3%(151/708)和21.9%(155/708).随访3~69个月,中位随访时间40.2个月,100例患者复发或死亡.单因素分析示乳腺癌预后与肿瘤大小、腋窝淋巴结状态、分子分型、术后辅助放疗及内分泌治疗有关;多因素分析示分子分型和淋巴结状态为乳腺癌的独立预后因素;生存分析示内分泌高反应型乳腺癌的预后好于其他三型.结论 乳腺癌分子分型是预后的独立预测因素,内分泌高反应型乳腺癌预后最好.%Objective To investigate the relationship between breast cancer molecular classification and prognosis.Methods From January 2002 to December 2003,708 female primary breast cancer patients with a mean age of 53 years old were retrospectively ana lyzed.The classification of breast cancer was according to the immunohistochemical results of estrogen receptor(ER),progesterone receptor(PR)and human epidermal growth factor receptor(HER2)status.Molecular classification definitions included highly endocrine responsive,incompletely endocrine responsive,triple negative,and HER2 positive.The prognosis among difierent molecular classifications of breast cancer was investigated.The survival rates of different classifations were compared by Log-rank test.Results The proportion of

  18. Trimodal color-fluorescence-polarization endoscopy aided by a tumor selective molecular probe accurately detects flat lesions in colitis-associated cancer

    Science.gov (United States)

    Charanya, Tauseef; York, Timothy; Bloch, Sharon; Sudlow, Gail; Liang, Kexian; Garcia, Missael; Akers, Walter J.; Rubin, Deborah; Gruev, Viktor; Achilefu, Samuel

    2014-12-01

    Colitis-associated cancer (CAC) arises from premalignant flat lesions of the colon, which are difficult to detect with current endoscopic screening approaches. We have developed a complementary fluorescence and polarization reporting strategy that combines the unique biochemical and physical properties of dysplasia and cancer for real-time detection of these lesions. Using azoxymethane-dextran sodium sulfate (AOM-DSS) treated mice, which recapitulates human CAC and dysplasia, we show that an octapeptide labeled with a near-infrared (NIR) fluorescent dye selectively identified all precancerous and cancerous lesions. A new thermoresponsive sol-gel formulation allowed topical application of the molecular probe during endoscopy. This method yielded high contrast-to-noise ratios (CNR) between adenomatous tumors (20.6±1.65) and flat lesions (12.1±1.03) and surrounding uninvolved colon tissue versus CNR of inflamed tissues (1.62±0.41). Incorporation of nanowire-filtered polarization imaging into NIR fluorescence endoscopy shows a high depolarization contrast in both adenomatous tumors and flat lesions in CAC, reflecting compromised structural integrity of these tissues. Together, the real-time polarization imaging provides real-time validation of suspicious colon tissue highlighted by molecular fluorescence endoscopy.

  19. Classifications within molecular subtypes enables identification of BRCA1/BRCA2 mutation carriers by RNA tumor profiling

    DEFF Research Database (Denmark)

    Larsen, Martin J; Kruse, Torben A; Tan, Qihua;

    2013-01-01

    Pathogenic germline mutations in BRCA1 or BRCA2 are detected in less than one third of families with a strong history of breast cancer. It is therefore expected that mutations still remain undetected by currently used screening methods. In addition, a growing number of BRCA1/2 sequence variants...... tumors by RNA profiling to investigate the classification potential of RNA profiles to predict BRCA1/2 mutation status. We found that breast tumors from BRCA1 and BRCA2 mutation carriers display characteristic RNA expression patterns, allowing them to be distinguished from sporadic tumors. The majority...

  20. Nominal classification

    OpenAIRE

    Senft, G.

    2007-01-01

    This handbook chapter summarizes some of the problems of nominal classification in language, presents and illustrates the various systems or techniques of nominal classification, and points out why nominal classification is one of the most interesting topics in Cognitive Linguistics.

  1. Taxonomy of Plant Genetic Resources – Use of Morphological, Molecular and Phytochemical Data in Order to Verify Existing Classifications

    Directory of Open Access Journals (Sweden)

    Ulrike Lohwasser

    2010-12-01

    Full Text Available Taxonomy of plant genetic resources is an important input in characterising and evaluating cultivated plants and it is essential for identification and documentation of the diversity of genebank collections. In former times taxonomical determination was based only on morphological characters. Nowadays, new molecular and chemical methods and techniques are available for providing additional information. As examples of the interaction of morphological, molecular and phytochemical data, investigations of a parsley (Petroselinum crispum [Mill.] Nyman, Apiaceae and an opium poppy (Papaver somniferum L., Papaveraceae collection of the German genebank are demonstrated. 220 parsley and 300 opium poppy accessions were cultivated and described morphologically. In addition, the molecular distance and the phylogenetic relationship of the accessions were performed with molecular marker analysis. Essential oil compound and content for parsley and the content of the five main alkaloids (morphine, codeine, thebaine, noscapine, papaverine for opium poppy were measured with GC (gas chromatography and HPLC (high pressure liquid chromatography, respectively. For parsley the results of the three methods support the existing taxonomy partly, a separation of root and leaf parsley was confirmed. However, the taxonomy of opium poppy should be revised because molecular and chemical data do not verify the morphological results. But nevertheless taxonomy of cultivated plants is an important tool to describe the variability of plant genetic resources.

  2. Comprehensive gene expression profiling and immunohistochemical studies support application of immunophenotypic algorithm for molecular subtype classification in diffuse large B-cell lymphoma

    DEFF Research Database (Denmark)

    Visco, C; Xu-Monette, Z Y; Miranda, R N;

    2012-01-01

    Gene expression profiling (GEP) has stratified diffuse large B-cell lymphoma (DLBCL) into molecular subgroups that correspond to different stages of lymphocyte development-namely germinal center B-cell like and activated B-cell like. This classification has prognostic significance, but GEP...... is expensive and not readily applicable into daily practice, which has lead to immunohistochemical algorithms proposed as a surrogate for GEP analysis. We assembled tissue microarrays from 475 de novo DLBCL patients who were treated with rituximab-CHOP chemotherapy. All cases were successfully profiled by GEP...... on formalin-fixed, paraffin-embedded tissue samples. Sections were stained with antibodies reactive with CD10, GCET1, FOXP1, MUM1 and BCL6 and cases were classified following a rationale of sequential steps of differentiation of B cells. Cutoffs for each marker were obtained using receiver...

  3. Histological and Molecular Pathology Classification in the Pathologic Diagnosis of Breast Cancer%组织学病理学和分子分类对乳腺癌的病理诊断价值

    Institute of Scientific and Technical Information of China (English)

    肖永波; 张晓; 黄小杏

    2015-01-01

    Objective To investigate the value of histological and molecular classification in the pathologic diagnosis of breast cancer .Methods Tissue sections of 745 cases of breast cancer received immunohistochemistry examination , and were classified by histological ,pathological and molecular classification ,and the characteristics were compared .Results 745 patients were divided into 5 molecular subtypes:235 cases of luminal A ,95 cases of luminal B type ,141 cases of over-expression of the ep-idermal growth factor receptor type ,142 cases of triple negative type ,and 132 cases unclassified.Conclusion The histological classification and molecular classification are related .Histological classification combined with molecular classification can help guide diagnosis and treatment of breast cancer .%目的:探讨组织学分类和分子分类在乳腺癌病理诊断中的价值。方法对745例乳腺癌患者组织切片进行免疫组织化学检验,分别进行组织学分类、病理学分类和分子分类,比较各自的分类特点。结果745例分为5种分子亚型:235例管腔A型,95例管腔B型,141例表皮生长因子受体过表达型,142例三阴性型,132例未分类。结论乳腺癌组织学分类与分子分类相关。联合组织学分类和分子分类,有助于指导乳腺癌的诊断和治疗。

  4. Elastic collisions between Si and D atoms at low temperatures and accurate analytic potential energy function and molecular constants of the SiD(X2∏) radical

    Institute of Scientific and Technical Information of China (English)

    Shi De-Heng; Zhang Jin-Ping; Sun Jin-Feng; Zhu Zun-Lue

    2009-01-01

    Interaction potential of the SiD(X2∏) radical is constructed by using the CCSD(T) theory in combination with the largest correlation-consistent quintuple basis set augmented with the diffuse functions in the valence range. Using the interaction potential, the spectroscopic parameters are accurately determined. The present D0, De, Re, ωe, αe and Be values are of 3.0956 eV, 3.1863 eV, 0.15223 nm, 1472.894 cm-1, 0.07799 cm-1 and 3.8717 cm-1, respectively,which are in excellent agreement with the measurements. A total of 26 vibrational states is predicted when J = 0 by solving the radial Schr(o)dinger equation of nuclear motion. The complete vibrational levels, classical turning points,initial rotation and centrifugal distortion constants when J = 0 are reported for the first time, which are in good accord with the available experiments. The total and various partial-wave cross sections are calculated for the elastic collisions between Si and D atoms in their ground states at 1.0×10-11-1.0×10-3 a.u. when the two atoms approach each other along the SiD(X2∏) potential energy curve. Four shape resonances are found in the total elastic cross sections, and their resonant energies are of 1.73×10-5, 4.0×10-5, 6.45×10-5 and 5.5×10-4 a.u., respectively. Each shape resonance in the total elastic cross sections is carefully investigated. The results show that the shape of the total elastic cross sections is mainly dominated by the s partial wave at very low temperatures. Because of the weakness of the shape resonances coming from the higher partial waves, most of them are passed into oblivion by the strong s partial-wave elastic cross sections.

  5. Novel, Precise, Accurate Ion-Pairing Method to Determine the Related Substances of the Fondaparinux Sodium Drug Substance: Low-Molecular-Weight Heparin.

    Science.gov (United States)

    Deshpande, Amol A; Madhavan, P; Deshpande, Girish R; Chandel, Ravi Kumar; Yarbagi, Kaviraj M; Joshi, Alok R; Moses Babu, J; Murali Krishna, R; Rao, I M

    2016-01-01

    Fondaparinux sodium is a synthetic low-molecular-weight heparin (LMWH). This medication is an anticoagulant or a blood thinner, prescribed for the treatment of pulmonary embolism and prevention and treatment of deep vein thrombosis. Its determination in the presence of related impurities was studied and validated by a novel ion-pair HPLC method. The separation of the drug and its degradation products was achieved with the polymer-based PLRPs column (250 mm × 4.6 mm; 5 μm) in gradient elution mode. The mixture of 100 mM n-hexylamine and 100 mM acetic acid in water was used as buffer solution. Mobile phase A and mobile phase B were prepared by mixing the buffer and acetonitrile in the ratio of 90:10 (v/v) and 20:80 (v/v), respectively. Mobile phases were delivered in isocratic mode (2% B for 0-5 min) followed by gradient mode (2-85% B in 5-60 min). An Evaporative Light Scattering Detector (ELSD) was connected to the LC system to detect the responses of chromatographic separation. Further, the drug was subjected to stress studies for acidic, basic, oxidative, photolytic, and thermal degradations as per ICH guidelines and the drug was found to be labile in acid, base hydrolysis, and oxidation, while stable in neutral, thermal, and photolytic degradation conditions. The method provided linear responses over the concentration range of the LOQ to 0.30% for each impurity with respect to the analyte concentration of 12.5 mg/mL, and regression analysis showed a correlation coefficient value (r(2)) of more than 0.99 for all the impurities. The LOD and LOQ were found to be 1.4 µg/mL and 4.1 µg/mL, respectively, for fondaparinux. The developed ion-pair method was validated as per ICH guidelines with respect to accuracy, selectivity, precision, linearity, and robustness. PMID:27110496

  6. Communication: Rate coefficients of the H + CH{sub 4} → H{sub 2} + CH{sub 3} reaction from ring polymer molecular dynamics on a highly accurate potential energy surface

    Energy Technology Data Exchange (ETDEWEB)

    Meng, Qingyong, E-mail: mengqingyong@dicp.ac.cn; Chen, Jun, E-mail: chenjun@dicp.ac.cn; Zhang, Dong H., E-mail: zhangdh@dicp.ac.cn [State Key Laboratory of Molecular Reaction Dynamics and Center for Theoretical and Computational Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Zhongshan Road 457, 116023 Dalian (China)

    2015-09-14

    The ring polymer molecular dynamics (RPMD) calculations are performed to calculate rate constants for the title reaction on the recently constructed potential energy surface based on permutation invariant polynomial (PIP) neural-network (NN) fitting [J. Li et al., J. Chem. Phys. 142, 204302 (2015)]. By inspecting convergence, 16 beads are used in computing free-energy barriers at 300 K ≤ T ≤ 1000 K, while different numbers of beads are used for transmission coefficients. The present RPMD rates are in excellent agreement with quantum rates computed on the same potential energy surface, as well as with the experimental measurements, demonstrating further that the RPMD is capable of producing accurate rates for polyatomic chemical reactions even at rather low temperatures.

  7. Classifications within molecular subtypes enables identification of BRCA1/BRCA2 mutation carriers by RNA tumor profiling.

    Directory of Open Access Journals (Sweden)

    Martin J Larsen

    Full Text Available Pathogenic germline mutations in BRCA1 or BRCA2 are detected in less than one third of families with a strong history of breast cancer. It is therefore expected that mutations still remain undetected by currently used screening methods. In addition, a growing number of BRCA1/2 sequence variants of unclear pathogen significance are found in the families, constituting an increasing clinical challenge. New methods are therefore needed to improve the detection rate and aid the interpretation of the clinically uncertain variants. In this study we analyzed a series of 33 BRCA1, 22 BRCA2, and 128 sporadic tumors by RNA profiling to investigate the classification potential of RNA profiles to predict BRCA1/2 mutation status. We found that breast tumors from BRCA1 and BRCA2 mutation carriers display characteristic RNA expression patterns, allowing them to be distinguished from sporadic tumors. The majority of BRCA1 tumors were basal-like while BRCA2 tumors were mainly luminal B. Using RNA profiles, we were able to distinguish BRCA1 tumors from sporadic tumors among basal-like tumors with 83% accuracy and BRCA2 from sporadic tumors among luminal B tumors with 89% accuracy. Furthermore, subtype-specific BRCA1/2 gene signatures were successfully validated in two independent data sets with high accuracies. Although additional validation studies are required, indication of BRCA1/2 involvement ("BRCAness" by RNA profiling could potentially be valuable as a tool for distinguishing pathogenic mutations from benign variants, for identification of undetected mutation carriers, and for selecting patients sensitive to new therapeutics such as PARP inhibitors.

  8. A molecular phylogeny for yponomeutoidea (insecta, Lepidoptera, ditrysia and its implications for classification, biogeography and the evolution of host plant use.

    Directory of Open Access Journals (Sweden)

    Jae-Cheon Sohn

    suggesting parallel phylogenesis. Our analyses suggest that previous characterizations of yponomeutoids as predominantly Holarctic were based on insufficient sampling. CONCLUSIONS/SIGNIFICANCE: We provide the first robust molecular phylogeny for Yponomeutoidea, together with a revised classification and new insights into their life history evolution and biogeography.

  9. Design and evaluation of a molecular fingerprint involving the transformation of property descriptor values into a binary classification scheme.

    Science.gov (United States)

    Xue, Ling; Godden, Jeffrey W; Stahura, Florence L; Bajorath, Jürgen

    2003-01-01

    A new fingerprint design concept is introduced that transforms molecular property descriptors into two-state descriptors and thus permits binary encoding. This transformation is based on the calculation of statistical medians of descriptor distributions in large compound collections and alleviates the need for value range encoding of these descriptors. For binary encoded property descriptors, bit positions that are set off capture as much information as bit positions that are set on, different from conventional fingerprint representations. Accordingly, a variant of the Tanimoto coefficient has been defined for comparison of these fingerprints. Following our design idea, a prototypic fingerprint termed MP-MFP was implemented by combining 61 binary encoded property descriptors with 110 structural fragment-type descriptors. The performance of this fingerprint was evaluated in systematic similarity search calculations in a database containing 549 molecules belonging to 38 different activity classes and 5000 background molecules. In these calculations, MP-MFP correctly recognized approximately 34% of all similarity relationships, with only 0.04% false positives, and performed better than previous designs and MACCS keys. The results suggest that combinations of simplified two-state property descriptors have predictive value in the analysis of molecular similarity.

  10. Accurate Molecular Dimensions from Stearic Acid Monolayers.

    Science.gov (United States)

    Lane, Charles A.; And Others

    1984-01-01

    Discusses modifications in the fatty acid monolayer experiment to reduce the inaccurate moleculary data students usually obtain. Copies of the experimental procedure used and a Pascal computer program to work up the data are available from the authors. (JN)

  11. A revised classification of the family Dasyatidae (Chondrichthyes: Myliobatiformes) based on new morphological and molecular insights.

    Science.gov (United States)

    Last, Peter R; Naylor, Gavin J P; Manjaji-Matsumoto, B Mabel

    2016-01-01

    The higher-level taxonomy of the stingrays (Dasyatidae) has never been comprehensively reviewed. Recent phylogenetic studies, supported by morphological data, have provided evidence that the group is monophyletic and consists of four major subgroups, the subfamilies Dasyatinae, Neotrygoninae, Urogymninae and Hypolophinae. A morphologically based review of 89 currently recognised species, undertaken for a guide to the world's rays, indicated that most of the currently recognised dasyatid genera are not monophyletic groups. These findings were supported by molecular analyses using the NADH2 gene for about 77 of these species, and this topology is supported by preliminary analyses base on whole mitochondrial genome comparisons. These molecular analyses, based on data generated from the Chondrichthyan Tree of Life project, are the most taxon-rich data available for this family. Material from all of the presently recognised genera (Dasyatis, Pteroplatytrygon and Taeniurops [Dasyatinae]; Neotrygon and Taeniura [Neotrygoninae]; Himantura and Urogymnus [Urogymninae]; and Makararaja and Pastinachus [Hypolophinae]), are included and their validity largely supported. Urogymnus and the two most species rich genera, Dasyatis and Himantura, are not considered to be monophyletic and were redefined based on external morphology. Seven new genus-level taxa are erected (Megatrygon and Telatrygon [Dasyatinae]; Brevitrygon, Fluvitrygon, Fontitrygon, Maculabatis and Pateobatis [Urogymninae], and an additional three (Bathytoshia, Hemitrygon and Hypanus [Dasyatinae]) are resurrected from the synonymy of Dasyatis. The monotypic genus Megatrygon clustered with 'amphi-American Himantura' outside the Dasyatidae, and instead as the sister group of the Potamotrygonidae and Urotrygonidae. Megatrygon is provisionally retained in the Dasyatinae pending further investigation of its internal anatomy. The morphologically divergent groups, Bathytoshia and Pteroplatytrygon, possibly form a single

  12. Classification of Omalisidae based on molecular data and morphology, with description of Paradrilinae subfam. nov. (Coleoptera: Elateroidea).

    Science.gov (United States)

    Kundrata, Robin; Baena, Manuel; Bocak, Ladislav

    2015-02-04

    Omalisidae, a species-poor family of elateroid beetles, are distributed mostly in the Mediterranean region. The morphology of females is modified due to neotenic development and the males share some traits with other neotenic lineages in Elateroidea, namely Drilini (Elateridae: Agrypninae) and Lyropaeinae (Lycidae). A molecular phylogeny was inferred from six omalisid species representing four genera and the previously published dataset of Elateroidea. The DNA based phylogeny suggests that small-bodied males, reduced pronotal carinae and missing elytral costae evolved independently in multiple elateroid lineages. The limits of Omalisidae are redefined and seven genera, i.e., Omalisus Geoffroy, 1762, Phaeopterus Costa, 1857, Thilmanus Gemminger, 1869, Euanoma Reitter, 1889, Pseudeuanoma Pic, 1901, Paradrilus Kiesenwetter, 1865 and Cimbrion Kazantsev, 2010, are currently placed in the family. Thilmaninae Kazantsev, 2005 and Paradrilus Kiesenwetter, 1865 are transferred from Drilini (Elateridae: Agrypninae) to Omalisidae and the Paradrilinae subfam. nov. is proposed. Paradrilus differs from other Omalisidae in prolonged cranium, wide robust prosternum with two apical processes and absent sharp edge of the pronotum. The morphology of Paradrilus is described in detail, illustrated and all taxa currently classified in Omalisidae are listed. 

  13. Evaluation of the use of partition coefficients and molecular surface properties as predictors of drug absorption: a provisional biopharmaceutical classification of the list of national essential medi

    Directory of Open Access Journals (Sweden)

    NU Rahman

    2011-05-01

    Full Text Available Background and the purpose of the study: Partition coefficients (log D and log P and molecular surface area (PSA are potential predictors of the intestinal permeability of drugs. The aim of this investigation was to evaluate and compare these intestinal permeability indicators.   Methods: Aqueous solubility data were obtained from literature or calculated using ACD/Labs and ALOGPS. Permeability data were predicted based on log P, log D at pH 6.0 (log D6.0, and PSA.  Results: Metoprolol's log P, log D6.0 and a PSA of <65 Å correctly predicted 55.9%, 50.8% and 54.2% of permeability classes, respectively. Labetalol's log P, log D6.0, and PSA correctly predicted 54.2%, 64.4% and 61% of permeability classes, respectively. Log D6.0 correlated well (81% with Caco-2 permeability (Papp. Of the list of national essential medicines, 135 orally administered drugs were classified into biopharmaceutical classification system (BCS. Of these, 57 (42.2%, 28 (20.7%, 44 (32.6%, and 6 (4.4% were class I, II, III and IV respectively. Conclusion: Log D6.0 showed better prediction capability than log P. Metoprolol as permeability internal standard was more conservative than labetalol.

  14. Síndromes mielodisplásicas: aspectos moleculares, laboratoriais e a classificação OMS 2008 Myelodysplasic symdrome: molecular and laboratorial aspects and the 2008 WHO classification

    Directory of Open Access Journals (Sweden)

    Ana Carolina R. Moraes

    2009-01-01

    defined etiology, or as secondary to chemotherapy or radiotherapy for other neoplasias. The evolution of diagnostic tests has improved comprehension of the process involved in the genesis and evolution of MDSs, making the development of earlier and more specific tests for diagnosis and follow ups possible. In 2008, the World Health Organization (WHO redefined the criteria for the classification of MDSs, dividing them into seven subgroups. This classification included new immunophenotypic, genetic, cytomorphologic and molecular features, which are essential for the diagnosis of MDSs and for a better comprehension of the disease. Despite technological advances, some details, such as the molecular basis of the transformation of MDS to AML, are still not completely understood, which makes further studies in this field necessary. Hence, the objective of this review is to make a compilation of recent molecular and laboratory aspects of MDS.

  15. A network-based classification model for deriving novel drug-disease associations and assessing their molecular actions.

    Science.gov (United States)

    Oh, Min; Ahn, Jaegyoon; Yoon, Youngmi

    2014-01-01

    The growing number and variety of genetic network datasets increases the feasibility of understanding how drugs and diseases are associated at the molecular level. Properly selected features of the network representations of existing drug-disease associations can be used to infer novel indications of existing drugs. To find new drug-disease associations, we generated an integrative genetic network using combinations of interactions, including protein-protein interactions and gene regulatory network datasets. Within this network, network adjacencies of drug-drug and disease-disease were quantified using a scored path between target sets of them. Furthermore, the common topological module of drugs or diseases was extracted, and thereby the distance between topological drug-module and disease (or disease-module and drug) was quantified. These quantified scores were used as features for the prediction of novel drug-disease associations. Our classifiers using Random Forest, Multilayer Perceptron and C4.5 showed a high specificity and sensitivity (AUC score of 0.855, 0.828 and 0.797 respectively) in predicting novel drug indications, and displayed a better performance than other methods with limited drug and disease properties. Our predictions and current clinical trials overlap significantly across the different phases of drug development. We also identified and visualized the topological modules of predicted drug indications for certain types of cancers, and for Alzheimer's disease. Within the network, those modules show potential pathways that illustrate the mechanisms of new drug indications, including propranolol as a potential anticancer agent and telmisartan as treatment for Alzheimer's disease.

  16. Bayesian Classification in Medicine: The Transferability Question *

    OpenAIRE

    Zagoria, Ronald J.; Reggia, James A.; Price, Thomas R.; Banko, Maryann

    1981-01-01

    Using probabilities derived from a geographically distant patient population, we applied Bayesian classification to categorize stroke patients by etiology. Performance was assessed both by error rate and with a new linear accuracy coefficient. This approach to patient classification was found to be surprisingly accurate when compared to classification by two neurologists and to classification by the Bayesian method using “low cost” local and subjective probabilities. We conclude that for some...

  17. Application of Data Mining in Protein Sequence Classification

    Directory of Open Access Journals (Sweden)

    Suprativ Saha

    2012-11-01

    Full Text Available Protein sequence classification involves feature selection for accurate classification. Popular protein sequence classification techniques involve extraction of specific features from the sequences. Researchers apply some well-known classification techniques like neural networks, Genetic algorithm, Fuzzy ARTMAP,Rough Set Classifier etc for accurate classification. This paper presents a review is with three different classification models such as neural network model, fuzzy ARTMAP model and Rough set classifier model.This is followed by a new technique for classifying protein sequences. The proposed model is typicallyimplemented with an own designed tool and tries to reduce the computational overheads encountered by earlier approaches and increase the accuracy of classification.

  18. Role of ASXL1 and TP53 mutations in the molecular classification and prognosis of acute myeloid leukemias with myelodysplasia-related changes

    Science.gov (United States)

    Devillier, Raynier; Prebet, Thomas; Bertoli, Sarah; Brecqueville, Mandy; Arnoulet, Christine; Recher, Christian; Vey, Norbert; Mozziconacci, Marie-Joelle; Delabesse, Eric; Birnbaum, Daniel

    2015-01-01

    Acute myeloid leukemias (AML) with myelodysplasia-related changes (AML-MRC) are defined by the presence of multilineage dysplasia (MLD), and/or myelodysplastic syndrome (MDS)-related cytogenetics, and/or previous MDS. The goal of this study was to identify distinct biological and prognostic subgroups based on mutations of ASXL1, RUNX1, DNMT3A, NPM1, FLT3 and TP53 in 125 AML-MRC patients according to the presence of MLD, cytogenetics and outcome. ASXL1 mutations (n=26, 21%) were associated with a higher proportion of marrow dysgranulopoiesis (mutant vs. wild-type: 75% vs. 55%, p=0.030) and were mostly found in intermediate cytogenetic AML (23/26) in which they predicted inferior 2-year overall survival (OS, mutant vs. wild-type: 14% vs. 37%, p=0.030). TP53 mutations (n=28, 22%) were mostly found in complex karyotype AML (26/28) and predicted poor outcome within unfavorable cytogenetic risk AML (mutant vs. wild-type: 9% vs. 40%, p=0.040). In multivariate analysis, the presence of either ASXL1 or TP53 mutation was the only independent factor associated with shorter OS (HR, 95%CI: 2.53, 1.40-4.60, p=0.002) while MLD, MDS-related cytogenetics and previous MDS history did not influence OS. We conclude that ASXL1 and TP53 mutations identify two molecular subgroups among AML-MRCs, with specific poor prognosis. This could be useful for future diagnostic and prognostic classifications. PMID:25860933

  19. Accurate mobile malware detection and classification in the cloud

    OpenAIRE

    Wang, Xiaolei; Yang, Yuexiang; Zeng, Yingzhi

    2015-01-01

    As the dominator of the Smartphone operating system market, consequently android has attracted the attention of s malware authors and researcher alike. The number of types of android malware is increasing rapidly regardless of the considerable number of proposed malware analysis systems. In this paper, by taking advantages of low false-positive rate of misuse detection and the ability of anomaly detection to detect zero-day malware, we propose a novel hybrid detection system based on a new op...

  20. An Innovative Imputation and Classification Approach for Accurate Disease Prediction

    OpenAIRE

    UshaRani, Yelipe; Sammulal, P.

    2016-01-01

    Imputation of missing attribute values in medical datasets for extracting hidden knowledge from medical datasets is an interesting research topic of interest which is very challenging. One cannot eliminate missing values in medical records. The reason may be because some tests may not been conducted as they are cost effective, values missed when conducting clinical trials, values may not have been recorded to name some of the reasons. Data mining researchers have been proposing various approa...

  1. Hubble Classification

    Science.gov (United States)

    Murdin, P.

    2000-11-01

    A classification scheme for galaxies, devised in its original form in 1925 by Edwin P Hubble (1889-1953), and still widely used today. The Hubble classification recognizes four principal types of galaxy—elliptical, spiral, barred spiral and irregular—and arranges these in a sequence that is called the tuning-fork diagram....

  2. ClassyFlu: Classification of Influenza A Viruses with Discriminatively Trained Profile-HMMs

    OpenAIRE

    Van der Auwera, Sandra; Bulla, Ingo; Ziller, Mario; Pohlmann, Anne; Harder, Timm; Stanke, Mario

    2014-01-01

    Accurate and rapid characterization of influenza A virus (IAV) hemagglutinin (HA) and neuraminidase (NA) sequences with respect to subtype and clade is at the basis of extended diagnostic services and implicit to molecular epidemiologic studies. ClassyFlu is a new tool and web service for the classification of IAV sequences of the HA and NA gene into subtypes and phylogenetic clades using discriminatively trained profile hidden Markov models (HMMs), one for each subtype or clade. ClassyFlu me...

  3. Research progress on the molecular classification of tumors by quantum dot-based nanotechnology%基于量子点标记探针技术的肿瘤分子分型研究进展

    Institute of Scientific and Technical Information of China (English)

    方敏; 彭春伟; 陈创; 庞代文; 李雁

    2014-01-01

    Malignant tumors are highly heterogeneous in terms of molecular phenotypes such that personalized therapy will be-come the standard for tumor therapy. Molecular classifications of cancer based on differences in biological behavior are important for selecting treatment strategies and prognostication. The unique optical and chemical properties of quantum dots have been widely used in biomedical applications such as tumor diagnosis, monitoring, pathogenesis, treatment, molecular pathology, and heterogeneity based on biological markers. In this study, we discuss the application of quantum dot-based nanotechnology and the molecular classification of cancer in personalized oncology.%恶性肿瘤在分子水平上具有高度异质性,是个体化治疗的依据。发展同时显示肿瘤原位多分子指标的技术对研究肿瘤生物学行为至关重要。量子点标记探针技术因其具有独特的光学和化学特性,在肿瘤诊断、监测、治疗、发病机制、分子分型及异质性研究中均有广阔应用前景。本文总结该技术在肿瘤分子分型方面的应用进展。

  4. Speaking Fluently And Accurately

    Institute of Scientific and Technical Information of China (English)

    JosephDeVeto

    2004-01-01

    Even after many years of study,students make frequent mistakes in English. In addition, many students still need a long time to think of what they want to say. For some reason, in spite of all the studying, students are still not quite fluent.When I teach, I use one technique that helps students not only speak more accurately, but also more fluently. That technique is dictations.

  5. Accurate Finite Difference Algorithms

    Science.gov (United States)

    Goodrich, John W.

    1996-01-01

    Two families of finite difference algorithms for computational aeroacoustics are presented and compared. All of the algorithms are single step explicit methods, they have the same order of accuracy in both space and time, with examples up to eleventh order, and they have multidimensional extensions. One of the algorithm families has spectral like high resolution. Propagation with high order and high resolution algorithms can produce accurate results after O(10(exp 6)) periods of propagation with eight grid points per wavelength.

  6. 过滤特征基因选择及演化硬件急性白血病分型%Molecular Classification of Acute Leukemia Using EHW with Filter-Based Gene Selection

    Institute of Scientific and Technical Information of China (English)

    王进; 丁凌; 孙开伟; 李钟浩

    2012-01-01

    A virtual reconfigurable architecture-based intrinsic evolvable hardware (EHW) is proposed for the molecular classification of cancer. To efficiently process DNA microarray datasets and cooperate with the hardware realization of EHW, five different filter-based gene selection methods are compared and discussed in this paper. The EHW classification system handles the selected informative genes through two stages: system learning and system classification. Empirical studies on a human acute leukemia dataset demonstrate that classification accuracy of the gene selection scheme based on signal-to-noise ratio outperforms its competitors. Classification accuracy of the proposed EHW is high comparable with other state-of-the-art pattern recognition methods. The system recognition time is reduced to 0.12 μs.%提出一种基于虚拟可重构结构的内部演化硬件癌症分子分型方法.为有效处理DNA微阵列数据和便于硬件实现,对比研究了5种基于过滤模式的信息基因选择方法.演化硬件通过系统学习和系统分类两个阶段对经过特征选择的信息基因进行处理,对急性白血病数据集的实验结果表明,基于信噪比信息基因选择方法的演化硬件分类器识别率最高.演化硬件具有和其他传统模式识别方法可比的识别率,识别时间仅需0.12μs.

  7. Molecular phylogeny of advanced snakes (Serpentes, Caenophidia with an emphasis on South American Xenodontines: a revised classification and descriptions of new taxa

    Directory of Open Access Journals (Sweden)

    Hussam Zaher

    2009-01-01

    Full Text Available We present a molecular phylogenetic analysis of caenophidian (advanced snakes using sequences from two mitochondrial genes (12S and 16S rRNA and one nuclear (c-mos gene (1681 total base pairs, and with 131 terminal taxa sampled from throughout all major caenophidian lineages but focussing on Neotropical xenodontines. Direct optimization parsimony analysis resulted in a well-resolved phylogenetic tree, which corroborates some clades identified in previous analyses and suggests new hypotheses for the composition and relationships of others. The major salient points of our analysis are: (1 placement of Acrochordus, Xenodermatids, and Pareatids as successive outgroups to all remaining caenophidians (including viperids, elapids, atractaspidids, and all other "colubrid" groups; (2 within the latter group, viperids and homalopsids are sucessive sister clades to all remaining snakes; (3 the following monophyletic clades within crown group caenophidians: Afro-Asian psammophiids (including Mimophis from Madagascar, Elapidae (including hydrophiines but excluding Homoroselaps, Pseudoxyrhophiinae, Colubrinae, Natricinae, Dipsadinae, and Xenodontinae. Homoroselaps is associated with atractaspidids. Our analysis suggests some taxonomic changes within xenodontines, including new taxonomy for Alsophis elegans, Liophis amarali, and further taxonomic changes within Xenodontini and the West Indian radiation of xenodontines. Based on our molecular analysis, we present a revised classification for caenophidians and provide morphological diagnoses for many of the included clades; we also highlight groups where much more work is needed. We name as new two higher taxonomic clades within Caenophidia, one new subfamily within Dipsadidae, and, within Xenodontinae five new tribes, six new genera and two resurrected genera. We synonymize Xenoxybelis and Pseudablabes with Philodryas; Erythrolamprus with Liophis; and Lystrophis and Waglerophis with Xenodon.Este trabalho

  8. HYBRID INTERNET TRAFFIC CLASSIFICATION TECHNIQUE1

    Institute of Scientific and Technical Information of China (English)

    Li Jun; Zhang Shunyi; Lu Yanqing; Yan Junrong

    2009-01-01

    Accurate and real-time classification of network traffic is significant to network operation and management such as QoS differentiation, traffic shaping and security surveillance. However, with many newly emerged P2P applications using dynamic port numbers, masquerading techniques, and payload encryption to avoid detection, traditional classification approaches turn to be ineffective. In this paper, we present a layered hybrid system to classify current Internet traffic, motivated by variety of network activities and their requirements of traffic classification. The proposed method could achieve fast and accurate traffic classification with low overheads and robustness to accommodate both known and unknown/encrypted applications. Furthermore, it is feasible to be used in the context of real-time traffic classification. Our experimental results show the distinct advantages of the proposed classification system, compared with the one-step Machine Learning (ML) approach.

  9. Breast Molecular Profiling and Radiotherapy Considerations.

    Science.gov (United States)

    Mahmoud, Omar; Haffty, Bruce G

    2016-01-01

    The last decade has seen major changes in the management of breast cancer. Heterogeneity regarding histology, therapeutic response, dissemination patterns, and patient outcome is evident. Molecular profiling provides an accurate tool to predict treatment outcome compared with classical clinicopathologic features. The genomic profiling unveiled the heterogeneity of breast cancer and identified distinct biologic subtypes. These advanced techniques were integrated into the clinical management; predicting systemic therapy benefit and overall survival. Utilizing genotyping to guide locoregional management decisions needs further characterization. In this chapter we will review available data on molecular classification of breast cancer, their association with locoregional outcome, their radiobiological properties and radiotherapy considerations. PMID:26987532

  10. Towards Automatic Classification of Neurons

    OpenAIRE

    Armañanzas, Rubén; Ascoli, Giorgio A.

    2015-01-01

    The classification of neurons into types has been much debated since the inception of modern neuroscience. Recent experimental advances are accelerating the pace of data collection. The resulting information growth of morphological, physiological, and molecular properties encourages efforts to automate neuronal classification by powerful machine learning techniques. We review state-of-the-art analysis approaches and availability of suitable data and resources, highlighting prominent challenge...

  11. Tissue Classification

    DEFF Research Database (Denmark)

    Van Leemput, Koen; Puonti, Oula

    2015-01-01

    Computational methods for automatically segmenting magnetic resonance images of the brain have seen tremendous advances in recent years. So-called tissue classification techniques, aimed at extracting the three main brain tissue classes (white matter, gray matter, and cerebrospinal fluid), are now...... well established. In their simplest form, these methods classify voxels independently based on their intensity alone, although much more sophisticated models are typically used in practice. This article aims to give an overview of often-used computational techniques for brain tissue classification...

  12. Molecular classification in breast cancer:a clinicopathological analysis of 745 cases%乳腺癌分子分类临床病理745例分析

    Institute of Scientific and Technical Information of China (English)

    刘德纯; 吴礼高; 赵云霞; 承泽农

    2011-01-01

    Objective:To explore the molecular classification in breast cancer and the clinicopathological features of variant subtypes. Methods: The expression of ER, PR and HER2 (C-erbB-2) in the cases of breast cancer detected immunohistochemically ( S-P method) were studied retrospectively. The cases were reclassified according to the standard of molecular classification,and the clinicopathological features were observed and compared with the WHO histological classification. Results:The invasive breast carcinomas 745 cases were divided into 5 subtypes according to the molecular classification. Among these cases,luminal A subtype accounted for 235 cases, luminal B subtype 95 casas,HER2 overexpressing subtype 141 cases and basal-like subtype( BLBC)/triple negative breast cancer 142 cases, respectively. The remainder was not classified. The clinicopathological features were described. Conclusions: The moleculai and histological classifications of breast cancer are partly responsive. lmmuohistochemical technique is helpful standardization to the molecular classification,which is more directly related to the therapy and prognosis and so worthy of wide employment and further standardization.%目的:探讨乳腺癌分子分类及其各种亚型的临床病理学特征.方法:回顾性分析既往研究中曾用免疫组织化学S-P法检测浸润性乳腺癌中癌细胞表达雌激素受体、孕激素受体和表皮生长因子受体蛋白表达的病例,按照分子分类的标准重新分类,观察各种亚型的临床病理学特点,并与WHO组织学分类相比较.结果:将符合标准的745例浸润性乳腺癌分为5种分子亚型:管腔A型235例,管腔B型95例,表皮生长因子受体过表达型141例,基底细胞样型/三阴性型142例,其余132例未确定分类.描述各亚型临床病理特点.结论:乳腺癌的分子分类与WHO组织学分类间有一定对应关系.免疫组织化学标记有助于分子分类,分子分类亚型对于治疗和预后具有

  13. Text Classification using Data Mining

    CERN Document Server

    Kamruzzaman, S M; Hasan, Ahmed Ryadh

    2010-01-01

    Text classification is the process of classifying documents into predefined categories based on their content. It is the automated assignment of natural language texts to predefined categories. Text classification is the primary requirement of text retrieval systems, which retrieve texts in response to a user query, and text understanding systems, which transform text in some way such as producing summaries, answering questions or extracting data. Existing supervised learning algorithms to automatically classify text need sufficient documents to learn accurately. This paper presents a new algorithm for text classification using data mining that requires fewer documents for training. Instead of using words, word relation i.e. association rules from these words is used to derive feature set from pre-classified text documents. The concept of Naive Bayes classifier is then used on derived features and finally only a single concept of Genetic Algorithm has been added for final classification. A system based on the...

  14. Text Classification using Artificial Intelligence

    CERN Document Server

    Kamruzzaman, S M

    2010-01-01

    Text classification is the process of classifying documents into predefined categories based on their content. It is the automated assignment of natural language texts to predefined categories. Text classification is the primary requirement of text retrieval systems, which retrieve texts in response to a user query, and text understanding systems, which transform text in some way such as producing summaries, answering questions or extracting data. Existing supervised learning algorithms for classifying text need sufficient documents to learn accurately. This paper presents a new algorithm for text classification using artificial intelligence technique that requires fewer documents for training. Instead of using words, word relation i.e. association rules from these words is used to derive feature set from pre-classified text documents. The concept of na\\"ive Bayes classifier is then used on derived features and finally only a single concept of genetic algorithm has been added for final classification. A syste...

  15. Transporter Classification Database (TCDB)

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Transporter Classification Database details a comprehensive classification system for membrane transport proteins known as the Transporter Classification (TC)...

  16. Histologic classification of gliomas.

    Science.gov (United States)

    Perry, Arie; Wesseling, Pieter

    2016-01-01

    Gliomas form a heterogeneous group of tumors of the central nervous system (CNS) and are traditionally classified based on histologic type and malignancy grade. Most gliomas, the diffuse gliomas, show extensive infiltration in the CNS parenchyma. Diffuse gliomas can be further typed as astrocytic, oligodendroglial, or rare mixed oligodendroglial-astrocytic of World Health Organization (WHO) grade II (low grade), III (anaplastic), or IV (glioblastoma). Other gliomas generally have a more circumscribed growth pattern, with pilocytic astrocytomas (WHO grade I) and ependymal tumors (WHO grade I, II, or III) as the most frequent representatives. This chapter provides an overview of the histology of all glial neoplasms listed in the WHO 2016 classification, including the less frequent "nondiffuse" gliomas and mixed neuronal-glial tumors. For multiple decades the histologic diagnosis of these tumors formed a useful basis for assessment of prognosis and therapeutic management. However, it is now fully clear that information on the molecular underpinnings often allows for a more robust classification of (glial) neoplasms. Indeed, in the WHO 2016 classification, histologic and molecular findings are integrated in the definition of several gliomas. As such, this chapter and Chapter 6 are highly interrelated and neither should be considered in isolation. PMID:26948349

  17. 5th International ACC Symposium: Classification of Adrenocortical Cancers from Pathology to Integrated Genomics: Real Advances or Lost in Translation?

    Science.gov (United States)

    de Krijger, Ronald E; Bertherat, Jérôme

    2016-02-01

    For the clinician, despite its rarity, adrenocortical cancer is a heterogeneous tumor both in term of steroid excess and tumor evolution. For patient management, it is crucial to have an accurate vision of this heterogeneity, in order to use a correct tumor classification. Pathology is the best way to classify operated adrenocortical tumors: to recognize their adrenocortical nature and to differentiate benign from malignant tumors. Among malignant tumors pathology also aims at prognosis assessment. Although progress has being made for prognosis assessment, there is still a need for improvement. Recent studies have established the value of Ki67 for adrenocortical cancer (ACC) prognostication, aiming also at standardization to reduce variability. The use of genomics to study adrenocortical tumors gives a very new insight in their pathogenesis and molecular classification. Genomics studies of ACC give now a clear description of the mRNA (transcriptome) and miRNA expression profile, as well as chromosomal and methylation alterations. Exome sequencing also established firmly the list of the main ACC driver genes. Interestingly, genomics study of ACC also revealed subtypes of malignant tumors with different pattern of molecular alterations, associated with different outcome. This leads to a new vision of adrenocortical tumors classification based on molecular analysis. Interestingly, these molecular classifications meet also the results of pathological analysis. This opens new perspectives on the development and use of various molecular tools to classify, along with pathological analysis, ACC, and guides patient management at the area of precision medicine. PMID:26676358

  18. Insights into the classification of small GTPases

    Directory of Open Access Journals (Sweden)

    Dominik Heider

    2010-05-01

    Full Text Available Dominik Heider1, Sascha Hauke3, Martin Pyka4, Daniel Kessler21Department of Bioinformatics, Center for Medical Biotechnology, 2Institute of Cell Biology (Cancer Research, University of Duisburg-Essen, Essen, Germany; 3Institute of Computer Science, University of Münster, Münster, Germany; 4Interdisciplinary Center for Clinical Research, University Hospital of Münster, Münster, GermanyAbstract: In this study we used a Random Forest-based approach for an assignment of small guanosine triphosphate proteins (GTPases to specific subgroups. Small GTPases represent an important functional group of proteins that serve as molecular switches in a wide range of fundamental cellular processes, including intracellular transport, movement and signaling events. These proteins have further gained a special emphasis in cancer research, because within the last decades a huge variety of small GTPases from different subgroups could be related to the development of all types of tumors. Using a random forest approach, we were able to identify the most important amino acid positions for the classification process within the small GTPases superfamily and its subgroups. These positions are in line with the results of earlier studies and have been shown to be the essential elements for the different functionalities of the GTPase families. Furthermore, we provide an accurate and reliable software tool (GTPasePred to identify potential novel GTPases and demonstrate its application to genome sequences.Keywords: cancer, machine learning, classification, Random Forests, proteins

  19. A genus-level classification of the family Thraupidae (Class Aves: Order Passeriformes).

    Science.gov (United States)

    Burns, Kevin J; Unitt, Philip; Mason, Nicholas A

    2016-01-01

    The tanagers (Thraupidae) are a major component of the Neotropical avifauna, and vary in plumage colors, behaviors, morphologies, and ecologies. Globally, they represent nearly 4% of all avian species and are the largest family of songbirds. However, many currently used tanager genera are not monophyletic, based on analyses of molecular data that have accumulated over the past 25 years. Current genus-level classifications of tanagers have not been revised according to newly documented relationships of tanagers for various reasons: 1) the lack of a comprehensive phylogeny, 2) reluctance to lump existing genera into larger groups, and 3) the lack of available names for newly defined smaller groups. Here, we present two alternative classifications based on a newly published comprehensive phylogeny of tanagers. One of these classifications uses existing generic names, but defines them broadly. The other, which we advocate and follow here, provides new generic names for more narrowly defined groups. Under the latter, we propose eleven new genera (Asemospiza, Islerothraupis, Maschalethraupis, Chrysocorypha, Kleinothraupis, Castanozoster, Ephippiospingus, Chionodacryon, Pseudosaltator, Poecilostreptus, Stilpnia), and resurrect several generic names to form monophyletic taxa. Either of these classifications would allow taxonomic authorities to reconcile classification with current understanding of tanager phylogenetic relationships. Having a more phylogenetically accurate classification for tanagers will facilitate the study and conservation of this important Neotropical radiation of songbirds. PMID:27394344

  20. Neuromuscular disease classification system.

    Science.gov (United States)

    Sáez, Aurora; Acha, Begoña; Montero-Sánchez, Adoración; Rivas, Eloy; Escudero, Luis M; Serrano, Carmen

    2013-06-01

    Diagnosis of neuromuscular diseases is based on subjective visual assessment of biopsies from patients by the pathologist specialist. A system for objective analysis and classification of muscular dystrophies and neurogenic atrophies through muscle biopsy images of fluorescence microscopy is presented. The procedure starts with an accurate segmentation of the muscle fibers using mathematical morphology and a watershed transform. A feature extraction step is carried out in two parts: 24 features that pathologists take into account to diagnose the diseases and 58 structural features that the human eye cannot see, based on the assumption that the biopsy is considered as a graph, where the nodes are represented by each fiber, and two nodes are connected if two fibers are adjacent. A feature selection using sequential forward selection and sequential backward selection methods, a classification using a Fuzzy ARTMAP neural network, and a study of grading the severity are performed on these two sets of features. A database consisting of 91 images was used: 71 images for the training step and 20 as the test. A classification error of 0% was obtained. It is concluded that the addition of features undetectable by the human visual inspection improves the categorization of atrophic patterns. PMID:23804164

  1. Molecular classification of anaplastic oligodendroglioma using next-generation sequencing: A report of the prospective randomized EORTC Brain Tumor Group 26951 phase III trial

    NARCIS (Netherlands)

    H.J. Dubbink (Erik Jan); P.N. Atmodimedjo; J.M. Kros (Johan); P.J. French (Pim); M. Sanson (Marc); A. Idbaih (Ahmed); P. Wesseling (Pieter); R. Enting (Roelien); W.G.M. Spliet (Wim); C.C. Tijssen (Cees); W.N.M. Dinjens (Winand); T.S. Gorlia (Thierry); M.J. van den Bent (Martin)

    2016-01-01

    textabstractBackground Histopathological diagnosis of diffuse gliomas is subject to interobserver variation and correlates modestly with major prognostic and predictive molecular abnormalities. We investigated a series of patients with locally diagnosed anaplastic oligodendroglial tumors included in

  2. [Eosinophilia--pathogenesis, classification and therapy

    DEFF Research Database (Denmark)

    Andersen, C.L.; Vestergaard, H.; Norgaard, P.;

    2009-01-01

    only by specific tests. The diagnostic and therapeutic approach, including a new classification for eosinophilia, is reviewed, and the importance of molecular biological technique is highlighted. Unexplained eosinophilia should be managed in collaboration with a haematology department Udgivelsesdato...

  3. Towards a unified classification of the ectodermal dysplasias: opportunities outweigh challenges.

    LENUS (Irish Health Repository)

    Irvine, Alan D

    2012-02-01

    The ectodermal dysplasias include a complex and highly diverse group of heritable disorders that share in common developmental abnormalities of ectodermal derivatives. The broader definition of ectodermal dysplasias (as heritable disorders involving at least two of the ectodermal derivatives nails, teeth, hair, and eccrine sweat glands) encompasses 170-200 conditions. Some conditions included by this definition are relatively common; others are rare and, in some cases, family-specific. Classification of the ectodermal dysplasias has largely been approached by categorizing patterns of clinical findings (phenotypic grouping). In the last 2 decades great progress has been made in understanding the molecular pathogenesis and inter-relatedness of some of these conditions and a new consensus approach to classification that incorporates this new information is needed. A comprehensive and definitive classification of these disorders would be highly valuable for the many stakeholders in ED. As disease-specific molecular treatments are developed, accurate classification will assume greater importance in designing registries to enable rapid identification of those with rare disorders who may wish to participate in clinical trials. Ideally a working classification of such a disparate collection of conditions would have a design and architecture that would facilitate easy accessibility by each of the key stakeholder groups and would encourage enhanced interaction between these parties. Attaining this objective is a major challenge but is achievable. This article reviews the historical-clinical perspective and the impact of recent developments in molecular biology in the field. Reflections are offered as to the future direction of classification systems in these disorders.

  4. Molecular Diagnostics

    OpenAIRE

    Choe, Hyonmin; Deirmengian, Carl A; Hickok, Noreen J.; Morrison, Tiffany N.; Tuan, Rocky S.

    2015-01-01

    Orthopaedic infections are complex conditions that require immediate diagnosis and accurate identification of the causative organisms to facilitate appropriate management. Conventional methodologies for diagnosis of these infections sometimes lack accuracy or sufficient rapidity. Current molecular diagnostics are an emerging area of bench-to-bedside research in orthopaedic infections. Examples of promising molecular diagnostics include measurement of a specific biomarker in the synovial fluid...

  5. Vehicle Classification by Lane Allowance

    Directory of Open Access Journals (Sweden)

    Vishakha Gaikwad

    2014-12-01

    Full Text Available Classification of vehicles from video is used for analysis of traffic, self-driving systems or security systems. This analysis is based on shape, size, velocity and track of vehicles. These features characterize vehicle in background subtraction and feature extraction methods. Extraction is done by active contours and morphological operations. Extracted vehicles are classified by applying various classification techniques. The combination of features and classification techniques varies with the application. Proposed system, Uses combination of K Nearest Neighbor (KNN and Decision Tree techniques to overcome constraints. These constraints are instances of an object, overlapping of objects, and scaling factor. KNN is utilized to classify vehicle by size and lane. Decision tree manipulates the combination of these two features to classify accurately which results increased performance. This system classifies objects into three classes. These classes are four wheeler, bikers and heavy duty vehicle extracted from video.

  6. Accurate phase-shift velocimetry in rock

    Science.gov (United States)

    Shukla, Matsyendra Nath; Vallatos, Antoine; Phoenix, Vernon R.; Holmes, William M.

    2016-06-01

    Spatially resolved Pulsed Field Gradient (PFG) velocimetry techniques can provide precious information concerning flow through opaque systems, including rocks. This velocimetry data is used to enhance flow models in a wide range of systems, from oil behaviour in reservoir rocks to contaminant transport in aquifers. Phase-shift velocimetry is the fastest way to produce velocity maps but critical issues have been reported when studying flow through rocks and porous media, leading to inaccurate results. Combining PFG measurements for flow through Bentheimer sandstone with simulations, we demonstrate that asymmetries in the molecular displacement distributions within each voxel are the main source of phase-shift velocimetry errors. We show that when flow-related average molecular displacements are negligible compared to self-diffusion ones, symmetric displacement distributions can be obtained while phase measurement noise is minimised. We elaborate a complete method for the production of accurate phase-shift velocimetry maps in rocks and low porosity media and demonstrate its validity for a range of flow rates. This development of accurate phase-shift velocimetry now enables more rapid and accurate velocity analysis, potentially helping to inform both industrial applications and theoretical models.

  7. Proteomic classification of breast cancer.

    LENUS (Irish Health Repository)

    Kamel, Dalia

    2012-11-01

    Being a significant health problem that affects patients in various age groups, breast cancer has been extensively studied to date. Recently, molecular breast cancer classification has advanced significantly with the availability of genomic profiling technologies. Proteomic technologies have also advanced from traditional protein assays including enzyme-linked immunosorbent assay, immunoblotting and immunohistochemistry to more comprehensive approaches including mass spectrometry and reverse phase protein lysate arrays (RPPA). The purpose of this manuscript is to review the current protein markers that influence breast cancer prediction and prognosis and to focus on novel advances in proteomic classification of breast cancer.

  8. Molecular Tools for Rapid and Accurate Detection of Black Truffle (Tuber melanosporum Vitt. in Inoculated Nursery Plants and Commercial Plantations in Chile Uso de Marcadores Moleculares para la Detección Rápida y Precisa de Trufa Negra (Tuber melanosporum Vitt. en Plantas de Vivero y Plantaciones Comerciales de Chile

    Directory of Open Access Journals (Sweden)

    Cecilia Cordero

    2011-09-01

    Full Text Available Truffle (Tuber melanosporum Vitt. culture is an agroforestry sector in Chile of increasing interest due to the high prices that truffles fetch in the national market and the recent evidence that its commercial production is possible in Chilean climatic and soil conditions. In this study, the efficiency of three methods of DNA extraction from a mix of 5 g of soil and roots from both nursery and field plants of Quercus ilex L. mycorrhized with T. melanosporum were evaluated, and a simple and reproducible protocol was established. Detection of T. melanosporum was performed by the technique of cleaved amplified polymorphic sequence (CAPS from amplicons generated with the primers ADL1 (5´-GTAACGATAAAGGCCATCTATAGG-3´ and ADL3 (5´-CGTTTTTCCTGAACTCTTCATCAC-3`, where a restriction fragment of 160 bp specific for T. melanosporum was generated, which allows the discrimination of this species from the rest of the species belonging to the Tuber sp. genus. Direct detection of T. melanosporum in one step was also obtained by polymerase chain reaction (PCR from total DNA isolated from mycorrhized roots and with the primers ITSML (5´-TGGCCATGTGTCAGATTTAGTA-3´ and ITSLNG (5´-TGATATGCTTAAGTTCAGCGGG-3´, generating a single amplicon of 440 bp. The molecular detection of T. melanosporum by the methods presented here will allow the rapid and accurate detection of mycorrhization of trees, both under nursery and field conditions. This technology will also provide more security to farmers by controlling the quality of the mycorrhized trees they will plant and also by following the mycorrhization status of established orchards.

  9. Automatic web services classification based on rough set theory

    Institute of Scientific and Technical Information of China (English)

    陈立; 张英; 宋自林; 苗壮

    2013-01-01

    With development of web services technology, the number of existing services in the internet is growing day by day. In order to achieve automatic and accurate services classification which can be beneficial for service related tasks, a rough set theory based method for services classification was proposed. First, the services descriptions were preprocessed and represented as vectors. Elicited by the discernibility matrices based attribute reduction in rough set theory and taking into account the characteristic of decision table of services classification, a method based on continuous discernibility matrices was proposed for dimensionality reduction. And finally, services classification was processed automatically. Through the experiment, the proposed method for services classification achieves approving classification result in all five testing categories. The experiment result shows that the proposed method is accurate and could be used in practical web services classification.

  10. Classification in Australia.

    Science.gov (United States)

    McKinlay, John

    Despite some inroads by the Library of Congress Classification and short-lived experimentation with Universal Decimal Classification and Bliss Classification, Dewey Decimal Classification, with its ability in recent editions to be hospitable to local needs, remains the most widely used classification system in Australia. Although supplemented at…

  11. Classification in context

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2004-01-01

    This paper surveys classification research literature, discusses various classification theories, and shows that the focus has traditionally been on establishing a scientific foundation for classification research. This paper argues that a shift has taken place, and suggests that contemporary...... classification research focus on contextual information as the guide for the design and construction of classification schemes....

  12. Multi-borders classification

    OpenAIRE

    Mills, Peter

    2014-01-01

    The number of possible methods of generalizing binary classification to multi-class classification increases exponentially with the number of class labels. Often, the best method of doing so will be highly problem dependent. Here we present classification software in which the partitioning of multi-class classification problems into binary classification problems is specified using a recursive control language.

  13. Efficient segmentation by sparse pixel classification

    DEFF Research Database (Denmark)

    Dam, Erik B; Loog, Marco

    2008-01-01

    Segmentation methods based on pixel classification are powerful but often slow. We introduce two general algorithms, based on sparse classification, for optimizing the computation while still obtaining accurate segmentations. The computational costs of the algorithms are derived, and they are dem......, and they are demonstrated on real 3-D magnetic resonance imaging and 2-D radiograph data. We show that each algorithm is optimal for specific tasks, and that both algorithms allow a speedup of one or more orders of magnitude on typical segmentation tasks.......Segmentation methods based on pixel classification are powerful but often slow. We introduce two general algorithms, based on sparse classification, for optimizing the computation while still obtaining accurate segmentations. The computational costs of the algorithms are derived...

  14. Molecular phylogeny of advanced snakes (Serpentes, Caenophidia) with an emphasis on South American Xenodontines: a revised classification and descriptions of new taxa

    OpenAIRE

    Hussam Zaher; Felipe Gobbi Grazziotin; John E. Cadle; Robert W Murphy; Julio Cesar de Moura-Leite; Sandro L. Bonatto

    2009-01-01

    We present a molecular phylogenetic analysis of caenophidian (advanced) snakes using sequences from two mitochondrial genes (12S and 16S rRNA) and one nuclear (c-mos) gene (1681 total base pairs), and with 131 terminal taxa sampled from throughout all major caenophidian lineages but focussing on Neotropical xenodontines. Direct optimization parsimony analysis resulted in a well-resolved phylogenetic tree, which corroborates some clades identified in previous analyses and suggests new hypothes...

  15. Interactive multiclass segmentation using superpixel classification

    OpenAIRE

    Mathieu, Bérengère; Crouzil, Alain; Puel, Jean-Baptiste

    2015-01-01

    This paper adresses the problem of interactive multiclass segmentation. We propose a fast and efficient new interactive segmentation method called Superpixel Classification-based Interactive Segmentation (SCIS). From a few strokes drawn by a human user over an image, this method extracts relevant semantic objects. To get a fast calculation and an accurate segmentation, SCIS uses superpixel over-segmentation and support vector machine classification. In this paper, we demonstrate that SCIS sig...

  16. Remote Sensing Information Classification

    Science.gov (United States)

    Rickman, Douglas L.

    2008-01-01

    This viewgraph presentation reviews the classification of Remote Sensing data in relation to epidemiology. Classification is a way to reduce the dimensionality and precision to something a human can understand. Classification changes SCALAR data into NOMINAL data.

  17. Research progress on molecular classification and heterogeneity of triple-negative breast cancer%三阴性乳腺癌分子分型与异质性的研究进展

    Institute of Scientific and Technical Information of China (English)

    张敏(综述); 张瑾(审校)

    2016-01-01

    三阴性乳腺癌(triple-negative breast cancer,TNBC)是指ER、PR及HER-2均为阴性的乳腺癌,占乳腺癌15%~20%。随着基因组学的发展,乳腺癌的分型已不仅局限于基于免疫组织化学的传统分子分型,其中TNBC也被认为是一类异质性疾病,其异质性在分子水平、病理学以及临床特征上也各不相同。因此,对TNBC进一步行分子分型将为靶向治疗带来极大获益,但TNBC分子分型尚无被广泛认可的统一标准,现就最新相关研究做一综述。%Triple-negative breast cancer (TNBC) is defined by the lack of estrogen receptors (ERs) and progesterone receptors (PRs) and by the human epidermal growth factor receptor 2 (HER2)-negative status. TNBC accounts for 15%to 20%of breast cancer cases. Genomic profiling studies have demonstrated that breast cancer heterogeneity extends beyond the classic immunohistochemistry (IHC)-based divisions. TNBC is also a heterogeneous disease on the molecular level, as well as on the pathologic and clinical levels. Thus, the molecular subclassification of TNBC will be of considerable value to the development of targeted therapies. However, no widely recognized standard for the molecular classification of TNBC exists. This review provides a brief summary on the latest research on TNBC.

  18. Ki67在不同分子类型乳腺癌组织中的表达及意义%Significance of Ki67 Expression in Different Molecular Classifications of Breast Cancer

    Institute of Scientific and Technical Information of China (English)

    沈三弟; 陈卓荣; 黄湛; 肖高芳; 雷睿文

    2012-01-01

    目的 探讨Ki67在不同分子类型乳腺癌组织中的表达及临床意义.方法 采用免疫组织化学法,检测368例乳腺癌组织标本中Ki67表达情况,采用Wilcoxon秩和检验分析Ki67在不同分子类型乳腺癌组织中的表达差异;采用Spearman秩相关方法,分析Ki67表达与原发肿瘤大小、腋窝淋巴结转移及病理分期等的相关性.结果 Lumina型、Her-2型及三阴型乳腺癌组织中Ki67表达强度无显著性差异(χ2=0.015,P=0.993);Ki67表达强度与Lumina型乳腺癌的原发肿瘤大小、腋窝淋巴结转移及病理分期呈正相关性(γs=0.167,P=0.013;γs=0.142,P=0.035;γs=0.165,P=0.014),而与Her-2型及三阴型乳腺癌的以上3个病理因素无显著性相关(P>0.05).结论 在Lumina型、Her-2型及三阴型乳腺癌组织中Ki67表达强度无显著性差异,Ki67表达强度与Lumina型乳腺癌的临床病理因素相关,是Lumina型乳腺癌的不良预后因素.%Objective To investigate the difference of Ki67 expression in three molecular classifications of breast cancer and clinic significance. Methods The Ki67 expression was detected in 368 cases of breast cancer tissue specimen by immuno-histochemistry( IHC ), The difference of Ki67 expression was analyzed by Wilcoxon rank sum test among three molecular classifications of breast cancer tissues; its correlation with primary tumor diameter( PTD ), axillary lymph node( ALN ) metastasis and pathological stage were analyzed by Spearman rank correlation. Results The difference of Ki67 expression was not significant a-mong the Lumina type,Her-2 type, triple-negative( TN ) type breast cancer tissues( x2=0.015,P=0. 993 );The intensity of Ki67 expression was correlate with PTD, ALN metastasis and pathological stage in Lumina type breast cancer ( ys =0. 167 ,P = 0. 013 ; yS = 0. 142 ,P = 0. 035; ys =0. 165 ,P = 0. 014 ), while not in Her-2 type and TN type breast cancer. Conclusion The intensity of Ki67 expression was not significant among three

  19. 乳腺癌新分子分型中的P53蛋白表达及临床评估%Expression of P53 protein in new molecular classification of breast cancer and clinical assessment

    Institute of Scientific and Technical Information of China (English)

    刘祖宏; 倪仰鹏; 黄绮国; 许文兵; 陈宋钦

    2013-01-01

    Objective: To investigate the expression of P53 protein in new molecular classification of breast cancer and clinical significance. Methods: Estrogen receptor (ER), progestrone receptor (PR), human epider mal receptor 2 (HER-2) , Ki-67 and P53 expression were performed by immunohistochemical staining in 92 surgi cal specimens of ductal breast carcinoma. The correlation between P53 expression and new molecular classification of breast cancer was analyzed. Results: P53 was negative in normal breast tissues while positive in 53. 3% cases of breast cancer (P <0. 05) ; The positive rate of P53 in HER-2 overexpression and triple-negative breast cancer was significantly higher than that those of Luminal A and B subtypes (P < 0. 05). Conclusion: Clinically, molecular classification of breast infiltrative ductal carcinoma via four items as ER, PR, HER-2, and ki-67 as well as detec tion of P53 are helpful for the assessment of tumor biological behavior and prognosis.%目的:探讨P53蛋白在乳腺浸润性导管癌新分子分型中表达及其临床意义.方法:采用免疫组织化学方法(二步法)检测92例乳腺癌组织中雌激素受体(ER)、孕激素受体(PR)、人表皮生长因子受体2 (HER-2)、Ki-67和P53蛋白的表达,并进行新的分子分型及与P53蛋白相关性分析.结果:乳腺浸润性导管癌P53蛋白阳性表达率为53.3%,正常乳腺组织表达为阴性,两者比较差异有统计学意义(P<0.05).HER-2过表达型和ER、PR、Ki-67三阴性型中P53蛋白阳性率明显高于Luminal A型、Luminal B1型、Luminal B2型,两者比较差异有统计学意义(P<0.05).此外,乳腺淋巴结转移与P53蛋白呈正相关(r2 =0.413,P<0.01).结论:临床在使用ER、PR、HER-2、Ki-67四种指标对乳腺浸润性导管癌进行分型时同时检测P53蛋白,有助于评估肿瘤的生物学行为及预后.

  20. Accurate structural correlations from maximum likelihood superpositions.

    Directory of Open Access Journals (Sweden)

    Douglas L Theobald

    2008-02-01

    Full Text Available The cores of globular proteins are densely packed, resulting in complicated networks of structural interactions. These interactions in turn give rise to dynamic structural correlations over a wide range of time scales. Accurate analysis of these complex correlations is crucial for understanding biomolecular mechanisms and for relating structure to function. Here we report a highly accurate technique for inferring the major modes of structural correlation in macromolecules using likelihood-based statistical analysis of sets of structures. This method is generally applicable to any ensemble of related molecules, including families of nuclear magnetic resonance (NMR models, different crystal forms of a protein, and structural alignments of homologous proteins, as well as molecular dynamics trajectories. Dominant modes of structural correlation are determined using principal components analysis (PCA of the maximum likelihood estimate of the correlation matrix. The correlations we identify are inherently independent of the statistical uncertainty and dynamic heterogeneity associated with the structural coordinates. We additionally present an easily interpretable method ("PCA plots" for displaying these positional correlations by color-coding them onto a macromolecular structure. Maximum likelihood PCA of structural superpositions, and the structural PCA plots that illustrate the results, will facilitate the accurate determination of dynamic structural correlations analyzed in diverse fields of structural biology.

  1. Clasificación en subtipos moleculares de tumores de mama de pequeños animales mediante métodos inmunohistoquímicos Classification in molecular subtypes of breast tumors of small animals through immunohistochemical methods

    Directory of Open Access Journals (Sweden)

    Mª V. Ortega García

    2013-03-01

    Full Text Available Antecedentes y Objetivos: Aplicar un panel de anticuerpos (anti -receptor de progesterona, -receptor de estrógenos, -receptor del factor de crecimiento epidérmico humano 2 y -citoqueratina 14 utilizando métodos inmunohistoquímicos en tumores mamarios de pequeños animales para analizar su clasificación en subtipos moleculares y su asociación con la invasión, el grado y el tipo histológico de las neoplasias. Material y Métodos: Muestras de tumores mamarios malignos, 10 de la especie canina y 3 de la felina. Control positivo interno: glándula mamaria no tumoral adyacente a las neoplasias. Resultados: El 23% (3/13 de los tumores fueron del subtipo luminal B, el 23% (3/13 fueron HER2 positivos, el 46% (6/13 fueron basales y el 7,6% (1/13 no se pudieron clasificar porque no expresaron ninguno de los marcadores tumorales analizados. Ningún caso fue del subtipo luminal A. Los 6 tumores basales fueron de grado II o III y presentaban o infiltración de solo el estroma o también invasión vascular. Dos tercios de los tumores HER2 positivos presentaban infiltración del estroma y 1/2 tumores resultó ser de grado II. Los tumores luminal B, 2/3 fueron de grado II o III. Todos los controles internos fueron positivos. No se encontraron diferencias significativas en la distribución de los subtipos moleculares entre los diferentes grupos de las variables invasión (p-valor=0,26, ni grado de malignidad (p-valor=0,42. Sí hubo diferencias en el límite de la significación estadística en la distribución de los subtipos moleculares entre los diferentes grupos de la variable tipo histológico (p=0,08. Conclusiones: La aplicación del panel de anticuerpos ha permitido descubrir 4 (luminal B, HER2, basal y sin clasificar de los 5 subtipos moleculares posibles.Antecedents and objectives: to apply an antibodies panel (anti-progesterone receptor -estrogen receptor, -human epidermal growth factor receptor 2 and cytokeratin 14 using immunohistochemical

  2. Revue bibliographique: les méthodes chimiques d'identification et de classification des champignons

    Directory of Open Access Journals (Sweden)

    Verscheure M.

    2002-01-01

    Full Text Available Chemotaxonomy of fungi : a review. For few years, advancements of molecular methods and analytical techniques enabled scientists to realise a classification of microorganisms based on biochemical characteristics. This classification, called chemotaxonomy, includes molecular methods and chemical methods which provide additional data and lead to a better identification and/or classification.

  3. Revue bibliographique: les méthodes chimiques d'identification et de classification des champignons

    OpenAIRE

    Verscheure M.; Lognay G.; Marlier M.

    2002-01-01

    Chemotaxonomy of fungi : a review. For few years, advancements of molecular methods and analytical techniques enabled scientists to realise a classification of microorganisms based on biochemical characteristics. This classification, called chemotaxonomy, includes molecular methods and chemical methods which provide additional data and lead to a better identification and/or classification.

  4. Revue bibliographique: les methodes chimiques d'identification et de classification des champignons.

    OpenAIRE

    Verscheure, M.; Lognay, Georges; Marlier, M.

    2002-01-01

    For few years, advancements of molecular methods and analytical techniques enabled scientists to realise a classification of microorganisms based on biochemical characteristics. This classification, called chemotaxonomy, includes molecular methods and chemical methods which provide additional data and lead to a better identification and/or classification.

  5. Towards accurate emergency response behavior

    International Nuclear Information System (INIS)

    Nuclear reactor operator emergency response behavior has persisted as a training problem through lack of information. The industry needs an accurate definition of operator behavior in adverse stress conditions, and training methods which will produce the desired behavior. Newly assembled information from fifty years of research into human behavior in both high and low stress provides a more accurate definition of appropriate operator response, and supports training methods which will produce the needed control room behavior. The research indicates that operator response in emergencies is divided into two modes, conditioned behavior and knowledge based behavior. Methods which assure accurate conditioned behavior, and provide for the recovery of knowledge based behavior, are described in detail

  6. Classification and molecular diagnostic procedure for Chacort-Marie-Tooth disease%腓骨肌萎缩症的分型与分子诊断流程

    Institute of Scientific and Technical Information of China (English)

    张如旭; 唐北沙

    2012-01-01

    Charcot-Marie-Tooth disease (CMT) is the most common form of hereditary neuropathy with significant clinical and genetic heterogeneity.So far 28 genes have been cloned.The main clinical manifestations of CMT include progressive distal muscle wasting and weakness,impaired distal sensation,and diminishing or loss of tendon reflex.Patients may be classified into demyelinating type (CMT1) and axonal type (CMT2) according to electrophysiological and pathological characteristics.Establishment of a standard diagnostic procedure based on clinical,electrophysiological and pathological findings will enable accurate diagnosis in most CMT patients and provide guidance for gene consulting and prognosis.%腓骨肌萎缩症(Charcot-Marie-Tooth disease,CMT)是一组最常见的具有高度临床和遗传异质性的周围神经单基因遗传病,目前已有28个疾病基因被克隆.主要临床症状包括进行性对称性肢体远端肌无力和肌萎缩,感觉障碍和腱反射减退或消失.根据电生理和病理特点,CMT可分为脱髓鞘型和轴突型.通过临床表现、电生理病理特点进行临床和遗传学分型,选择可能的疾病基因进行突变分析等一系列具有逻辑性的诊断流程,可明确分子诊断,为疾病预后和遗传咨询提供指导性意见.

  7. Improving the accuracy of gene expression profile classification with Lorenz curves and Gini ratios.

    Science.gov (United States)

    Tran, Quoc-Nam

    2011-01-01

    Microarrays are a new technology with great potential to provide accurate medical diagnostics, help to find the right treatment for many diseases such as cancers, and provide a detailed genome-wide molecular portrait of cellular states. In this chapter, we show how Lorenz Curves and Gini Ratios can be modified to improve the accuracy of gene expression profile classification. Experimental results with different classification algorithms using additional techniques and strategies for improving the accuracy such as the principal component analysis, the correlation-based feature subset selection, and the consistency subset evaluation technique for the task of classifying lung adenocarcinomas from gene expression show that our method find more optimal genes than SAM. PMID:21431549

  8. Classification of the web

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2004-01-01

    This paper discusses the challenges faced by investigations into the classification of the Web and outlines inquiries that are needed to use principles for bibliographic classification to construct classifications of the Web. This paper suggests that the classification of the Web meets challenges...

  9. 肺癌细胞病理学样本组织学分类及分子病理学检测%Histological classification and molecular pathology of lung cancer cytopathology sample

    Institute of Scientific and Technical Information of China (English)

    徐海苗; 程晔; 孙文勇

    2013-01-01

    Objective To study histological classification and molecular detection solutions of cytopathology samples in lung cancer.Methods 120 cases of lung cancer cytopathology samples have made qualitative diagnosis in conventional smear,and have made the histological classification in part,and then carried out 8 immunohistochemical staining of thyroid transcription factor 1 (TIF-1),p63,E-calcium mucins (E-CAD),creatine kinase 5/6 (CK5/6),epithelial membrane antigen (EMA),synaptic element (Syn),neural cell adhesion molecule 56 (CD56),chromogranin A (CgA) and Calretinin (CR) combined with cell block section,classification again and comparative study both;Part cases of adenocarcinoma have made epidermal growth factor receptor (EGFR) mutation detection.Results Overall parting rate of conventional smear lung cancer histologic and parting rate of non-small cell carcinoma were significantly lower than that in parting rate basis on cell block combined with immunohistochemical stains (39.2% vs.88.3% ;29.7% vs.85.1%,x2 =60.359,72.098,P <0.01),EGFR mutation detection 94.7% (36/38) success.Conclusion Lung cancer cell biology sample should be conducted conventional smear,cell blocksection and combined with immunohistochemical staining,and then make histologic classification;Cell blockprovides a effective platform for cytopathology samples detection.%目的 探讨肺癌在细胞病理学样本组织学分类及分子学检测解决方案.方法 120例肺癌细胞学样本在常规涂片做出定性诊断并部分予以组织学分类后,结合细胞蜡块切片进行甲状腺转录因子-1(TTF-1)、p63、E-钙黏蛋白(E-cad)、细胞角蛋白(CK5/6)、上皮膜抗原(EMA)、突触素(Syn)、神经细胞黏附分子(CD56)、嗜铬素A(CgA)、视网膜钙蛋白(CR)等8项的免疫组织化学染色后再分类并对两者进行比较;部分腺癌病例进行表皮生长因子受体(EGFR)突变检测.结果 常规涂片肺癌组织学总体分型率及非小细胞癌的分

  10. Classification of neocortical interneurons using affinity propagation

    OpenAIRE

    Santana, Roberto; McGarry, Laura M.; Bielza, Concha; Larrañaga, Pedro; Yuste, Rafael

    2013-01-01

    In spite of over a century of research on cortical circuits, it is still unknown how many classes of cortical neurons exist. In fact, neuronal classification is a difficult problem because it is unclear how to designate a neuronal cell class and what are the best characteristics to define them. Recently, unsupervised classifications using cluster analysis based on morphological, physiological, or molecular characteristics, have provided quantitative and unbiased identification of distinct neu...

  11. Classification of neocortical interneurons using affinity propagation

    OpenAIRE

    Roberto eSantana; Laura eMcGarry; Concha eBielza; Pedro eLarrañaga; Rafael eYuste

    2013-01-01

    In spite of over a century of research on cortical circuits, it is still unknown how many classes of cortical neurons exist. Neuronal classification has been a difficult problem because it is unclear what a neuronal cell class actually is and what are the best characteristics are to define them. Recently, unsupervised classifications using cluster analysis based on morphological, physiological or molecular characteristics, when applied to selected datasets, have provided quantitative and unbi...

  12. Towards functional classification of neuronal types

    OpenAIRE

    Sharpee, Tatyana O.

    2014-01-01

    How many types of neurons are there in the brain? This basic neuroscience question remains unsettled despite many decades of research. Classification schemes have been proposed based on anatomical, electrophysiological or molecular properties. However, different schemes do not always agree with each other. This raises the question of whether one can classify neurons based on their function directly. For example, among sensory neurons, can a classification scheme be devised that is based on th...

  13. Accurate Modeling of Advanced Reflectarrays

    DEFF Research Database (Denmark)

    Zhou, Min

    Analysis and optimization methods for the design of advanced printed re ectarrays have been investigated, and the study is focused on developing an accurate and efficient simulation tool. For the analysis, a good compromise between accuracy and efficiency can be obtained using the spectral domain...

  14. Clasificación en subtipos moleculares de tumores de mama de pequeños animales mediante métodos inmunohistoquímicos Classification in molecular subtypes of breast tumors of small animals through immunohistochemical methods

    OpenAIRE

    Mª V. Ortega García; J.A. Galán Torres; Y. Millán Ruiz; R. Sánchez Céspedes; J. Martín de las Mulas González-Albo

    2013-01-01

    Antecedentes y Objetivos: Aplicar un panel de anticuerpos (anti -receptor de progesterona, -receptor de estrógenos, -receptor del factor de crecimiento epidérmico humano 2 y -citoqueratina 14) utilizando métodos inmunohistoquímicos en tumores mamarios de pequeños animales para analizar su clasificación en subtipos moleculares y su asociación con la invasión, el grado y el tipo histológico de las neoplasias. Material y Métodos: Muestras de tumores mamarios malignos, 10 de la especie canina y 3...

  15. Establishment and application of medication error classification standards in nursing care based on the International Classification of Patient Safety

    Directory of Open Access Journals (Sweden)

    Xiao-Ping Zhu

    2014-09-01

    Conclusion: Application of this classification system will help nursing administrators to accurately detect system- and process-related defects leading to medication errors, and enable the factors to be targeted to improve the level of patient safety management.

  16. Molecular Morphology

    OpenAIRE

    Donath, Alexander

    2011-01-01

    A fundamental problem in biology is the reconstruction of the relatedness of all (extant) species. Traditionally, systematists employ visually recognizable characters of organisms for classification and evolutionary analysis. Recent developments in molecular and computational biology, however, lead to a whole different perspective on how to address the problem of inferring relatedness. The discovery of molecules, carrying genetic information, and the comparison of their primary structure h...

  17. Towards the automatic classification of neurons.

    Science.gov (United States)

    Armañanzas, Rubén; Ascoli, Giorgio A

    2015-05-01

    The classification of neurons into types has been much debated since the inception of modern neuroscience. Recent experimental advances are accelerating the pace of data collection. The resulting growth of information about morphological, physiological, and molecular properties encourages efforts to automate neuronal classification by powerful machine learning techniques. We review state-of-the-art analysis approaches and the availability of suitable data and resources, highlighting prominent challenges and opportunities. The effective solution of the neuronal classification problem will require continuous development of computational methods, high-throughput data production, and systematic metadata organization to enable cross-laboratory integration. PMID:25765323

  18. Molecular Classification and Individual Treatment of Type 2 Diabetes Mellitus%2型糖尿病分子分型和个体化诊疗技术

    Institute of Scientific and Technical Information of China (English)

    韩学尧; 张思敏; 胡承; 梁华; 邢丹

    2016-01-01

    In this year, this group has been working hard on establishing and improving the study cohorts including random samples, samples with pre-diabetes, samples with diabetes and coronary heart disease (CHD), pre-diabetes samples with different interventions, samples with treatments of different anti-diabetic drugs. Several cross sectional studies and prospective studies are conducting, a lot of clinical information and biological samples were colected, and some biomarkers were screened for predicting type 2 diabetes and its large vessel complication. By exome sequencing, we identified an insulin mutation, which is being confirmed to cause diabetes through molecular biological laboratory methods. By case control study, we confirmed the association of PAX4-rs10229583 with type 2 diabetes in Chinese Han. By proteomics study, we screened three special protein associated with NOS1AP-rs12742393, which was proven to relate to the risk for type 2 diabetes in Chinese Han. Some genetic markers of KCNQ1 were found to have an effect on QTc of EKG. In pre-diabetes cohort, we found a few of SNPs might associate with weight changes or insulin sensitivity folowing interventions of life style and pioglitazone. In type 2 diabetes cohort with treatment of metformin, we screened some DNA variations maybe contributing to the different responses to metfromin in lowering blood glucose and weight loss.In type 2 diabetes with CHD, nonalcoholic fat liver, higher blood glucose, radialis bone mass and mild increased urinary albumin excretion might increase the risk of CHD.In addition, Mir-22 also were identified to associate with obesity, fat liver and insulin resistance. Al the finding need to be confirmed in independent studies,and some might become the real biaomarker for predicting the development of diabetes and CHD, responses to anti-diabetic drugs,molecular typing of type 2 diabetes, and regimens of individualized treatment of diabetes.%本年度课题组继续完善建设各种研究队

  19. A time-calibrated molecular phylogeny of the precious corals: reconciling discrepancies in the taxonomic classification and insights into their evolutionary history

    Directory of Open Access Journals (Sweden)

    Ardila Néstor E

    2012-12-01

    delineated 11 morphospecies that were congruent with the general mixed Yule-coalescent (GMYC model. A multilocus species-tree approach also identified the same two well-supported clades, being Clade I-B more recent in the species tree (18.0-15.9 mya than in the gene tree (35.2-15.9 mya. In contrast, the diversification times for Clade II were more ancient in the species tree (136.4-41.7 mya than in the gene tree (66.3-16.9 mya. Conclusions Our results provide no support for the taxonomic status of the two currently recognized genera in the family Coralliidae. Given that Paracorallium species were all nested within Corallium, we recognize the coralliid genus Corallium, which includes the type species of the family, and thus consider Paracorallium a junior synonym of Corallium. We propose the use of the genus Hemicorallium Gray for clade I-B (species with long rod sclerites, cylindrical autozooids and smooth axis. Species delimitation in clade I-B remains unclear and the molecular resolution for Coralliidae species is inconsistent in the two main clades. Some species have wide distributions, recent diversification times and low mtDNA divergence whereas other species exhibit narrower allopatric distributions, older diversification times and greater levels of mtDNA resolution.

  20. Profitable capitation requires accurate costing.

    Science.gov (United States)

    West, D A; Hicks, L L; Balas, E A; West, T D

    1996-01-01

    In the name of costing accuracy, nurses are asked to track inventory use on per treatment basis when more significant costs, such as general overhead and nursing salaries, are usually allocated to patients or treatments on an average cost basis. Accurate treatment costing and financial viability require analysis of all resources actually consumed in treatment delivery, including nursing services and inventory. More precise costing information enables more profitable decisions as is demonstrated by comparing the ratio-of-cost-to-treatment method (aggregate costing) with alternative activity-based costing methods (ABC). Nurses must participate in this costing process to assure that capitation bids are based upon accurate costs rather than simple averages. PMID:8788799

  1. Texture Classification based on Gabor Wavelet

    Directory of Open Access Journals (Sweden)

    Amandeep Kaur

    2012-07-01

    Full Text Available This paper presents the comparison of Texture classification algorithms based on Gabor Wavelets. The focus of this paper is on feature extraction scheme for texture classification. The texture feature for an image can be classified using texture descriptors. In this paper we have used Homogeneous texture descriptor that uses Gabor Wavelets concept. For texture classification, we have used online texture database that is Brodatz’s database and three advanced well known classifiers: Support Vector Machine, K-nearest neighbor method and decision tree induction method. The results shows that classification using Support vector machines gives better results as compare to the other classifiers. It can accurately discriminate between a testing image data and training data.

  2. Voxel classification methodology for rapid Monte Carlo simulation of light propagation in complex media

    Institute of Scientific and Technical Information of China (English)

    Nunu Ren; Heng Zhao; Shouping Zhu; Xiaochao Qu; Hongliang Liu; Zhenhua Hu; Jimin Liang; Jie Tian

    2011-01-01

    @@ Monte Carlo (MC) method is a statistical method for simulating photon propagation in media in the optical molecular imaging field.However, obtaining an accurate result using the method is quite time-consuming,especially because the boundary of the media is complex.A voxel classification method is proposed to reduce the computation cost.All the voxels generated by dividing the media are classified into three types (outside, boundary, and inside) according to the position of the voxel.The classified information is used to determine the relative position of the photon and the intersection between photon path and media boundary in the MC method.The influencing factor8 and effectiveness of the proposed method are analyzed and validated by simulation experiments.%Monte Carlo (MC) method is a statistical method for simulating photon propagation in media in the optical molecular imaging field. However, obtaining an accurate result using the method is quite time-consuming,especially because the boundary of the media is complex. A voxel classification method is proposed to reduce the computation cost. All the voxels generated by dividing the media are classified into three types (outside, boundary, and inside) according to the position of the voxel. The classified information is used to determine the relative position of the photon and the intersection between photon path and media boundary in the MC method. The influencing factors and effectiveness of the proposed method are analyzed and validated by simulation experiments.

  3. On the importance of having accurate data for astrophysical modelling

    Science.gov (United States)

    Lique, Francois

    2016-06-01

    The Herschel telescope and the ALMA and NOEMA interferometers have opened new windows of observation for wavelengths ranging from far infrared to sub-millimeter with spatial and spectral resolutions previously unmatched. To make the most of these observations, an accurate knowledge of the physical and chemical processes occurring in the interstellar and circumstellar media is essential.In this presentation, I will discuss what are the current needs of astrophysics in terms of molecular data and I will show that accurate molecular data are crucial for the proper determination of the physical conditions in molecular clouds.First, I will focus on collisional excitation studies that are needed for molecular lines modelling beyond the Local Thermodynamic Equilibrium (LTE) approach. In particular, I will show how new collisional data for the HCN and HNC isomers, two tracers of star forming conditions, have allowed solving the problem of their respective abundance in cold molecular clouds. I will also present the last collisional data that have been computed in order to analyse new highly resolved observations provided by the ALMA interferometer.Then, I will present the calculation of accurate rate constants for the F+H2 → HF+H and Cl+H2 ↔ HCl+H reactions, which have allowed a more accurate determination of the physical conditions in diffuse molecular clouds. I will also present the recent work on the ortho-para-H2 conversion due to hydrogen exchange that allow more accurate determination of the ortho-to-para-H2 ratio in the universe and that imply a significant revision of the cooling mechanism in astrophysical media.

  4. Quantitatively accurate calculations of conductance and thermopower of molecular junctions

    DEFF Research Database (Denmark)

    Markussen, Troels; Jin, Chengjun; Thygesen, Kristian Sommer

    2013-01-01

    ) connected to gold electrodes using first‐principles calculations. We find excellent agreement with experiments for both molecules when exchange–correlation effects are described by the many‐body GW approximation. In contrast, results from standard density functional theory (DFT) deviate from experiments......‐principles calculations when exchange–correlation effects are taken properly into account....

  5. Accurate Kirkwood-Buff Integrals from Molecular Dynamics Simulations

    DEFF Research Database (Denmark)

    Wedberg, Nils Hejle Rasmus Ingemar; O'Connell, John P.; Peters, Günther H.J.;

    2010-01-01

    theoretical limiting behaviour on the corresponding direct correlation function. The method is evaluated for the pure Lennard-Jones and Stockmayer fluids. The results are verified by comparing pure fluid isothermal compressibilities obtained from the KB integrals with values from derivatives of equations of...

  6. Inter-rater reliability of the EPUAP pressure ulcer classification system using photographs.

    NARCIS (Netherlands)

    Defloor, T.; Schoonhoven, L.

    2004-01-01

    BACKGROUND: Many classification systems for grading pressure ulcers are discussed in the literature. Correct identification and classification of a pressure ulcer is important for accurate reporting of the magnitude of the problem, and for timely prevention. The reliability of pressure ulcer classif

  7. Typology, classification and systematization of innovative projects and initiatives in the company

    Directory of Open Access Journals (Sweden)

    Baklanova Julia O.

    2012-04-01

    Full Text Available The author presents a comparison of definitions of typology, classification and systematization, and treats them as an example of innovative projects and initiatives of the company. The basis of typology and classification laid methodical Benko K., Mc Farlan. In order to obtain a more accurate result it is necessary to integrate the task typology, classification and systematization.

  8. The identification value of diffusion weighted imaging in different molecular subtypes for breast cancer classification%磁共振 DWI 对乳腺癌分子亚型的鉴别诊断应用价值

    Institute of Scientific and Technical Information of China (English)

    金观桥; 苏丹柯; 罗殿中; 赖少侣; 罗宁斌; 康巍; 黄向阳; 方献柳

    2015-01-01

    目的:探讨 MR 扩散加权成像(DWI)对乳腺癌不同分子亚型的鉴别诊断价值。方法乳腺癌患者依据 ER、Ki-67、PR、HER2的组化结果分成4种分子亚型,即 Luminal A、Luminal B、人类表皮生长因子受体2(HER2-OE)阳性和三阴型(triple nega-tive breast cancer,TNBC)。所有患者于乳腺癌手术/活检至少前2周进行 MR 检查,测定肿瘤最大横断面的 ADC 值(包括最大ADC 值、最小 ADC 值、平均 ADC 值)。采用单因素方差分析、LSD-t 进行统计学分析。结果72例乳腺癌中,Luninal A 亚型21例,Luminal B 亚型22例,HER2-OE 亚型17例,TNBC 亚型12例。4种亚型中,年龄、瘤灶大小均数的差异无统计学意义(P >0.05)。经 AVONA 统计,Luminal A,Luminal B,HER2-OE 和 TNBC 亚型的最大 ADC 值、平均 ADC 值以及最小 ADC 值的均数之间差异有统计学意义(P =0.025,0.039,0.041)。Luminal A,Luminal B,HER2-OE 和 TNBC 亚型的最大 ADC 值、平均 ADC 值以及最小 ADC 值的均数多重比较中,每一个均数两两比较差异不能同时均有统计学意义。结论手术或活检前,MR DWI 对乳腺癌不同分子亚型的鉴别诊断价值具有一定局限性。%Objective To investigate the value of diffusion weighted imaging (DWI)in identification of different molecular sub-types for breast cancer classifications.Methods All patients with breast cancer were divided into four subtypes groups by immuno-histochemistry results including Luminal A subtype,Luminal B subtype,HER2-over expressing (HER2-OE)subtype,and triple negative breast cancer (TNBC),respectively.The means of maximum,average,and minimum ADC of the lesions in all patients were recorded.The analysis of ANOVA and least significant difference test (LSD-t )were used for the statistical evaluation.Results There were significant differences in maximum ADC,average ADC,and minimum ADC among Luminal A subtype (n=21),Lu-minal B subtype (n=22),HER2-OE subtype (n=1 7)and TNBC subtype (n=12)groups (P

  9. 乳腺癌分子分型与拓扑异构酶Ⅱα基因异常关系的研究%Correlation between breast cancer molecular classification and topoisomerase Ⅱ α gene anomaly

    Institute of Scientific and Technical Information of China (English)

    徐恩伟; 王跃华; 王晋芬

    2012-01-01

    Objective To study the correlation between breast cancer molecular classification and topoisomerase Ⅱα gene anomaly. Methods Immunohistochemistry assay was employed to detect estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor (Her-2) in 142 patients with breast cancer. HER2 gene expression was assayed via chromogenic in situ hybridization (CISH), and fluorescent in situ hybridization was applied to measure TOP2A gene amplification or deletion. Results Of 142 cases with breast cancer, Luminal A, Luminal B and Her-2 overexpression were observed in 53, 27 and 49 cases, respectively, while triple-negative expression was noted in 13 cases. Of all molecular classifications, TOP2A gene yielded a significant difference in the state of amplification (19 cases with and 123 without amplification, χ2=11.25, P<0.05), mostly in those with Her-2 and Luminal B overexpression. Conclusion Conventional immunohistochemistry assay followed by TOP2A gene detection should be conducted in patients with breast cancer who had Her-2 and Luminal B overexpression as a result of potential TOP2A amplification in those with Her-2 gene amplification.%目的 探讨乳腺癌分子分型与拓扑异构酶Ⅱα基因(TOP2A)扩增或缺失的关系.方法 采用免疫组织化学的方法,检测142例乳腺癌患者雌激素受体(ER)、孕激素受体(PR)及人类表皮生长因子受体2(Her2),同时采用显色原位杂交(CISH)检测Her-2基因情况,根据结果进行分子分型,应用荧光原位杂交(FISH)检测TOP2A基因扩增或缺失状况.结果 142例中,Luminal A型53例,Luminal B型27例,Her-2过表达型49例,三阴型13例.TOP2A基因扩增19例,未扩增123例.不同分子分型中TOP2A基因的扩增情况差异有统计学意义( x2=11.25,P<0.05),主要发生在Her-2型及Luminal B型.结论 TOP2A基因扩增主要存在于HER2基因扩增患者中,因此常规免疫组织化学检测之后,分子分型为Her-2型及Luminal B型

  10. Accurate determination of antenna directivity

    DEFF Research Database (Denmark)

    Dich, Mikael

    1997-01-01

    The derivation of a formula for accurate estimation of the total radiated power from a transmitting antenna for which the radiated power density is known in a finite number of points on the far-field sphere is presented. The main application of the formula is determination of directivity from power......-pattern measurements. The derivation is based on the theory of spherical wave expansion of electromagnetic fields, which also establishes a simple criterion for the required number of samples of the power density. An array antenna consisting of Hertzian dipoles is used to test the accuracy and rate of convergence...

  11. FREE RADICALS, REACTIVE OXYGEN SPECIES, OXIDATIVE STRESSES AND THEIR CLASSIFICATIONS.

    Science.gov (United States)

    Lushchak, V I

    2015-01-01

    The phrases "free radicals" and "reactive oxygen species" (ROS) are frequently used interchangeably although this is not always correct. This article gives a brief description of two mentioned oxygen forms. During the first two-three decades after ROS discovery in biological systems (1950-1970 years) they were considered only as damaging agents, but later their involvement in organism protection and regulation of the expression of certain genes was found. The physiological state of increased steady-state ROS level along with certain physiological effects has been called oxidative stress. This paper describes ROS homeostasis and provides several classifications of oxidative stresses. The latter are based on time-course and intensity principles. Therefore distinguishing between acute and chronic stresses on the basis of the dynamics, and the basal oxidative stress, low intensity oxidative stress, strong oxidative stress, and finally a very strong oxidative stress based on the intensity of the action of the inductor of the stress are described. Potential areas of research include the development of this field with complex classification of oxidative stresses, an accurate identification of cellular targets of ROS action, determination of intracellular spatial and temporal distribution of ROS and their effects, deciphering the molecular mechanisms responsible for cell response to ROS attacks, and their participation in the normal cellular functions, i.e. cellular homeostasis and its regulation.

  12. Molecular classification of non-muscle-invasive bladder cancer (pTa low-grade, pT1 low-grade, and pT1 high-grade subgroups) using methylation of tumor-suppressor genes.

    Science.gov (United States)

    Sacristan, Raquel; Gonzalez, Carolina; Fernández-Gómez, Jesus M; Fresno, Florentino; Escaf, Safwan; Sánchez-Carbayo, Marta

    2014-09-01

    The role of epigenetics in distinguishing pathological and clinical subgroups in bladder cancer is not fully characterized. We evaluated whether methylation of tumor-suppressor genes (TSGs) would classify non-muscle-invasive (NMI) bladder cancer subgroups and predict outcome. A retrospective design included the following paraffin-embedded primary NMI tumor types (n = 251): pTa low grade (LG) (n = 79), pT1LG (n = 81), and pT1 high grade (HG) (n = 91). Methylation of 25 TSGs was measured using methylation-specific, multiplex, ligation-dependent probe amplification. The TSGs most frequently methylated in the overall series were STK11 (96.8%), MGMT2 (64.5%), RARB (63.0%), and GATA5 (63.0%). TSG methylation correlated to clinicopathological variables in each subgroup and in the overall NMI series. Methylation of RARB, CD44, PAX5A, GSTP1, IGSF4 (CADM1), PYCARD, CDH13, TP53, and GATA5 classified pTa versus pT1 tumors whereas RARB, CD44, GSTP1, IGSF4, CHFR, PYCARD, TP53, STK11, and GATA5 distinguished LG versus HG tumors. Multivariate analyses indicated that PAX5A, WT1, and BRCA1 methylation independently predicted recurrence in pTaLG, PAX6, ATM, CHFR, and RB1 in pT1LG disease; PYCARD, in pT1HG disease; and PAX5A and RB1, in the overall series. Methylation of TSGs provided a molecular classification of NMI disease according to clinicopathological factors. Furthermore, TSG methylation predicted recurrence in NMI subgroups. PMID:24998186

  13. $H_{2}^{+}$ ion in strong magnetic field an accurate calculation

    CERN Document Server

    López, J C; Turbiner, A V

    1997-01-01

    Using a unique trial function we perform an accurate calculation of the ground state $1\\sigma_g$ of the hydrogenic molecular ion $H^+_2$ in a constant uniform magnetic field ranging $0-10^{13}$ G. We show that this trial function also makes it possible to study the negative parity ground state $1\\sigma_u$.

  14. Hand eczema classification

    DEFF Research Database (Denmark)

    Diepgen, T L; Andersen, Klaus Ejner; Brandao, F M;

    2008-01-01

    of the disease is rarely evidence based, and a classification system for different subdiagnoses of hand eczema is not agreed upon. Randomized controlled trials investigating the treatment of hand eczema are called for. For this, as well as for clinical purposes, a generally accepted classification system...... A classification system for hand eczema is proposed. Conclusions It is suggested that this classification be used in clinical work and in clinical trials....

  15. Aircraft Operations Classification System

    Science.gov (United States)

    Harlow, Charles; Zhu, Weihong

    2001-01-01

    Accurate data is important in the aviation planning process. In this project we consider systems for measuring aircraft activity at airports. This would include determining the type of aircraft such as jet, helicopter, single engine, and multiengine propeller. Some of the issues involved in deploying technologies for monitoring aircraft operations are cost, reliability, and accuracy. In addition, the system must be field portable and acceptable at airports. A comparison of technologies was conducted and it was decided that an aircraft monitoring system should be based upon acoustic technology. A multimedia relational database was established for the study. The information contained in the database consists of airport information, runway information, acoustic records, photographic records, a description of the event (takeoff, landing), aircraft type, and environmental information. We extracted features from the time signal and the frequency content of the signal. A multi-layer feed-forward neural network was chosen as the classifier. Training and testing results were obtained. We were able to obtain classification results of over 90 percent for training and testing for takeoff events.

  16. Parameters for accurate genome alignment

    Directory of Open Access Journals (Sweden)

    Hamada Michiaki

    2010-02-01

    Full Text Available Abstract Background Genome sequence alignments form the basis of much research. Genome alignment depends on various mundane but critical choices, such as how to mask repeats and which score parameters to use. Surprisingly, there has been no large-scale assessment of these choices using real genomic data. Moreover, rigorous procedures to control the rate of spurious alignment have not been employed. Results We have assessed 495 combinations of score parameters for alignment of animal, plant, and fungal genomes. As our gold-standard of accuracy, we used genome alignments implied by multiple alignments of proteins and of structural RNAs. We found the HOXD scoring schemes underlying alignments in the UCSC genome database to be far from optimal, and suggest better parameters. Higher values of the X-drop parameter are not always better. E-values accurately indicate the rate of spurious alignment, but only if tandem repeats are masked in a non-standard way. Finally, we show that γ-centroid (probabilistic alignment can find highly reliable subsets of aligned bases. Conclusions These results enable more accurate genome alignment, with reliability measures for local alignments and for individual aligned bases. This study was made possible by our new software, LAST, which can align vertebrate genomes in a few hours http://last.cbrc.jp/.

  17. Classification of articulators.

    Science.gov (United States)

    Rihani, A

    1980-03-01

    A simple classification in familiar terms with definite, clear characteristics can be adopted. This classification system is based on the number of records used and the adjustments necessary for the articulator to accept these records. The classification divides the articulators into nonadjustable, semiadjustable, and fully adjustable articulators (Table I). PMID:6928204

  18. Cirrhosis Classification Based on Texture Classification of Random Features

    Directory of Open Access Journals (Sweden)

    Hui Liu

    2014-01-01

    Full Text Available Accurate staging of hepatic cirrhosis is important in investigating the cause and slowing down the effects of cirrhosis. Computer-aided diagnosis (CAD can provide doctors with an alternative second opinion and assist them to make a specific treatment with accurate cirrhosis stage. MRI has many advantages, including high resolution for soft tissue, no radiation, and multiparameters imaging modalities. So in this paper, multisequences MRIs, including T1-weighted, T2-weighted, arterial, portal venous, and equilibrium phase, are applied. However, CAD does not meet the clinical needs of cirrhosis and few researchers are concerned with it at present. Cirrhosis is characterized by the presence of widespread fibrosis and regenerative nodules in the hepatic, leading to different texture patterns of different stages. So, extracting texture feature is the primary task. Compared with typical gray level cooccurrence matrix (GLCM features, texture classification from random features provides an effective way, and we adopt it and propose CCTCRF for triple classification (normal, early, and middle and advanced stage. CCTCRF does not need strong assumptions except the sparse character of image, contains sufficient texture information, includes concise and effective process, and makes case decision with high accuracy. Experimental results also illustrate the satisfying performance and they are also compared with typical NN with GLCM.

  19. Accurate ab initio spin densities

    CERN Document Server

    Boguslawski, Katharina; Legeza, Örs; Reiher, Markus

    2012-01-01

    We present an approach for the calculation of spin density distributions for molecules that require very large active spaces for a qualitatively correct description of their electronic structure. Our approach is based on the density-matrix renormalization group (DMRG) algorithm to calculate the spin density matrix elements as basic quantity for the spatially resolved spin density distribution. The spin density matrix elements are directly determined from the second-quantized elementary operators optimized by the DMRG algorithm. As an analytic convergence criterion for the spin density distribution, we employ our recently developed sampling-reconstruction scheme [J. Chem. Phys. 2011, 134, 224101] to build an accurate complete-active-space configuration-interaction (CASCI) wave function from the optimized matrix product states. The spin density matrix elements can then also be determined as an expectation value employing the reconstructed wave function expansion. Furthermore, the explicit reconstruction of a CA...

  20. The Accurate Particle Tracer Code

    CERN Document Server

    Wang, Yulei; Qin, Hong; Yu, Zhi

    2016-01-01

    The Accurate Particle Tracer (APT) code is designed for large-scale particle simulations on dynamical systems. Based on a large variety of advanced geometric algorithms, APT possesses long-term numerical accuracy and stability, which are critical for solving multi-scale and non-linear problems. Under the well-designed integrated and modularized framework, APT serves as a universal platform for researchers from different fields, such as plasma physics, accelerator physics, space science, fusion energy research, computational mathematics, software engineering, and high-performance computation. The APT code consists of seven main modules, including the I/O module, the initialization module, the particle pusher module, the parallelization module, the field configuration module, the external force-field module, and the extendible module. The I/O module, supported by Lua and Hdf5 projects, provides a user-friendly interface for both numerical simulation and data analysis. A series of new geometric numerical methods...

  1. Accurate thickness measurement of graphene

    Science.gov (United States)

    Shearer, Cameron J.; Slattery, Ashley D.; Stapleton, Andrew J.; Shapter, Joseph G.; Gibson, Christopher T.

    2016-03-01

    Graphene has emerged as a material with a vast variety of applications. The electronic, optical and mechanical properties of graphene are strongly influenced by the number of layers present in a sample. As a result, the dimensional characterization of graphene films is crucial, especially with the continued development of new synthesis methods and applications. A number of techniques exist to determine the thickness of graphene films including optical contrast, Raman scattering and scanning probe microscopy techniques. Atomic force microscopy (AFM), in particular, is used extensively since it provides three-dimensional images that enable the measurement of the lateral dimensions of graphene films as well as the thickness, and by extension the number of layers present. However, in the literature AFM has proven to be inaccurate with a wide range of measured values for single layer graphene thickness reported (between 0.4 and 1.7 nm). This discrepancy has been attributed to tip-surface interactions, image feedback settings and surface chemistry. In this work, we use standard and carbon nanotube modified AFM probes and a relatively new AFM imaging mode known as PeakForce tapping mode to establish a protocol that will allow users to accurately determine the thickness of graphene films. In particular, the error in measuring the first layer is reduced from 0.1-1.3 nm to 0.1-0.3 nm. Furthermore, in the process we establish that the graphene-substrate adsorbate layer and imaging force, in particular the pressure the tip exerts on the surface, are crucial components in the accurate measurement of graphene using AFM. These findings can be applied to other 2D materials.

  2. Accurate thickness measurement of graphene.

    Science.gov (United States)

    Shearer, Cameron J; Slattery, Ashley D; Stapleton, Andrew J; Shapter, Joseph G; Gibson, Christopher T

    2016-03-29

    Graphene has emerged as a material with a vast variety of applications. The electronic, optical and mechanical properties of graphene are strongly influenced by the number of layers present in a sample. As a result, the dimensional characterization of graphene films is crucial, especially with the continued development of new synthesis methods and applications. A number of techniques exist to determine the thickness of graphene films including optical contrast, Raman scattering and scanning probe microscopy techniques. Atomic force microscopy (AFM), in particular, is used extensively since it provides three-dimensional images that enable the measurement of the lateral dimensions of graphene films as well as the thickness, and by extension the number of layers present. However, in the literature AFM has proven to be inaccurate with a wide range of measured values for single layer graphene thickness reported (between 0.4 and 1.7 nm). This discrepancy has been attributed to tip-surface interactions, image feedback settings and surface chemistry. In this work, we use standard and carbon nanotube modified AFM probes and a relatively new AFM imaging mode known as PeakForce tapping mode to establish a protocol that will allow users to accurately determine the thickness of graphene films. In particular, the error in measuring the first layer is reduced from 0.1-1.3 nm to 0.1-0.3 nm. Furthermore, in the process we establish that the graphene-substrate adsorbate layer and imaging force, in particular the pressure the tip exerts on the surface, are crucial components in the accurate measurement of graphene using AFM. These findings can be applied to other 2D materials.

  3. A higher-level phylogenetic classification of the Fungi

    NARCIS (Netherlands)

    Hibbett, D.S.; Binder, M.; Bischoff, J.F.; Blackwell, M.; Cannon, P.F.; Eriksson, O.E.; Huhndorf, S.; James, T.; Kirk, P.M.; Lücking, R.; Thorsten Lumbsch, H.; Lutzoni, F.; Brandon Matheny, P.; McLaughlin, D.J.; Powell, M.J.; Redhead, S.; Schoch, C.L.; Spatafora, J.W.; Stalpers, J.A.; Vilgalys, R.; Aime, M.C.; Aptroot, A.; Bauer, R.; Begerow, D.; Benny, G.L.; Castlebury, L.A.; Crous, P.W.; Dai, Y.C.; Gams, W.; Geiser, D.M.; Griffith, G.W.; Gueidan, C.; Hawksworth, D.L.; Hestmark, G.; Hosaka, K.; Humber, R.A.; Hyde, K.D.; Ironside, J.E.; Koljalg, U.; Kurtzman, C.P.; Larsson, K.H.; Lichtwardt, R.; Longcore, J.; Miadlikowska, J.; Miller, A.; Moncalvo, J.M.; Mozley-Standridge, S.; Oberwinkler, F.; Parmasto, E.; Reeb, V.; Rogers, J.D.; Roux, Le C.; Ryvarden, L.; Sampaio, J.P.; Schüssler, A.; Sugiyama, J.; Thorn, R.G.; Tibell, L.; Untereiner, W.A.; Walker, C.; Wang, Z.; Weir, A.; Weiss, M.; White, M.M.; Winka, K.; Yao, Y.J.; Zhang, N.

    2007-01-01

    A comprehensive phylogenetic classification of the kingdom Fungi is proposed, with reference to recent molecular phylogenetic analyses, and with input from diverse members of the fungal taxonomic community. The classification includes 195 taxa, down to the level of order, of which 16 are described o

  4. Classification, disease, and diagnosis.

    Science.gov (United States)

    Jutel, Annemarie

    2011-01-01

    Classification shapes medicine and guides its practice. Understanding classification must be part of the quest to better understand the social context and implications of diagnosis. Classifications are part of the human work that provides a foundation for the recognition and study of illness: deciding how the vast expanse of nature can be partitioned into meaningful chunks, stabilizing and structuring what is otherwise disordered. This article explores the aims of classification, their embodiment in medical diagnosis, and the historical traditions of medical classification. It provides a brief overview of the aims and principles of classification and their relevance to contemporary medicine. It also demonstrates how classifications operate as social framing devices that enable and disable communication, assert and refute authority, and are important items for sociological study.

  5. Acute pancreatitis: international classification and nomenclature.

    Science.gov (United States)

    Bollen, T L

    2016-02-01

    The incidence of acute pancreatitis (AP) is increasing and it is associated with a major healthcare concern. New insights in the pathophysiology, better imaging techniques, and novel treatment options for complicated AP prompted the update of the 1992 Atlanta Classification. Updated nomenclature for pancreatic collections based on imaging criteria is proposed. Adoption of the newly Revised Classification of Acute Pancreatitis 2012 by radiologists should help standardise reports and facilitate accurate conveyance of relevant findings to referring physicians involved in the care of patients with AP. This review will clarify the nomenclature of pancreatic collections in the setting of AP. PMID:26602933

  6. Concerning a new classification of tricyanides

    Science.gov (United States)

    Krafft, F.; Vonhansen, A.

    1979-01-01

    A new classification series of tricyanides is presented. Several tricyanides are synthesized by a simple method from aluminum chloride, benzonitrile, and a respective alkyl or phenyl chloride, purified by recrystallization and distillation, and then analyzed. Structural formulae are suggested, and molecular weights, melting points, and boiling points are determined for each.

  7. The Heidelberg classification of renal cell tumours

    NARCIS (Netherlands)

    Kovacs, G; Akhtar, M; Beckwith, BJ; Bugert, P; Cooper, CS; Delahunt, B; Eble, JN; Fleming, S; Ljungberg, B; Medeiros, LJ; Moch, H; Reuter, VE; Ritz, E; Roos, G; Schmidt, D; Srigley, [No Value; Storkel, S; VandenBerg, E; Zbar, B

    1997-01-01

    This paper presents the conclusions of a workshop entitled 'Impact of Molecular Genetics on the Classification of Renal Cell Tumours', which was held in Heidelberg in October 1996, The focus on 'renal cell tumours' excludes any discussion of Wilms' tumour and its variants, or of tumours metastatic t

  8. Automatic classification of blank substrate defects

    Science.gov (United States)

    Boettiger, Tom; Buck, Peter; Paninjath, Sankaranarayanan; Pereira, Mark; Ronald, Rob; Rost, Dan; Samir, Bhamidipati

    2014-10-01

    Mask preparation stages are crucial in mask manufacturing, since this mask is to later act as a template for considerable number of dies on wafer. Defects on the initial blank substrate, and subsequent cleaned and coated substrates, can have a profound impact on the usability of the finished mask. This emphasizes the need for early and accurate identification of blank substrate defects and the risk they pose to the patterned reticle. While Automatic Defect Classification (ADC) is a well-developed technology for inspection and analysis of defects on patterned wafers and masks in the semiconductors industry, ADC for mask blanks is still in the early stages of adoption and development. Calibre ADC is a powerful analysis tool for fast, accurate, consistent and automatic classification of defects on mask blanks. Accurate, automated classification of mask blanks leads to better usability of blanks by enabling defect avoidance technologies during mask writing. Detailed information on blank defects can help to select appropriate job-decks to be written on the mask by defect avoidance tools [1][4][5]. Smart algorithms separate critical defects from the potentially large number of non-critical defects or false defects detected at various stages during mask blank preparation. Mechanisms used by Calibre ADC to identify and characterize defects include defect location and size, signal polarity (dark, bright) in both transmitted and reflected review images, distinguishing defect signals from background noise in defect images. The Calibre ADC engine then uses a decision tree to translate this information into a defect classification code. Using this automated process improves classification accuracy, repeatability and speed, while avoiding the subjectivity of human judgment compared to the alternative of manual defect classification by trained personnel [2]. This paper focuses on the results from the evaluation of Automatic Defect Classification (ADC) product at MP Mask

  9. Quality-Oriented Classification of Aircraft Material Based on SVM

    Directory of Open Access Journals (Sweden)

    Hongxia Cai

    2014-01-01

    Full Text Available The existing material classification is proposed to improve the inventory management. However, different materials have the different quality-related attributes, especially in the aircraft industry. In order to reduce the cost without sacrificing the quality, we propose a quality-oriented material classification system considering the material quality character, Quality cost, and Quality influence. Analytic Hierarchy Process helps to make feature selection and classification decision. We use the improved Kraljic Portfolio Matrix to establish the three-dimensional classification model. The aircraft materials can be divided into eight types, including general type, key type, risk type, and leveraged type. Aiming to improve the classification accuracy of various materials, the algorithm of Support Vector Machine is introduced. Finally, we compare the SVM and BP neural network in the application. The results prove that the SVM algorithm is more efficient and accurate and the quality-oriented material classification is valuable.

  10. A More Accurate Fourier Transform

    CERN Document Server

    Courtney, Elya

    2015-01-01

    Fourier transform methods are used to analyze functions and data sets to provide frequencies, amplitudes, and phases of underlying oscillatory components. Fast Fourier transform (FFT) methods offer speed advantages over evaluation of explicit integrals (EI) that define Fourier transforms. This paper compares frequency, amplitude, and phase accuracy of the two methods for well resolved peaks over a wide array of data sets including cosine series with and without random noise and a variety of physical data sets, including atmospheric $\\mathrm{CO_2}$ concentrations, tides, temperatures, sound waveforms, and atomic spectra. The FFT uses MIT's FFTW3 library. The EI method uses the rectangle method to compute the areas under the curve via complex math. Results support the hypothesis that EI methods are more accurate than FFT methods. Errors range from 5 to 10 times higher when determining peak frequency by FFT, 1.4 to 60 times higher for peak amplitude, and 6 to 10 times higher for phase under a peak. The ability t...

  11. Recursive heuristic classification

    Science.gov (United States)

    Wilkins, David C.

    1994-01-01

    The author will describe a new problem-solving approach called recursive heuristic classification, whereby a subproblem of heuristic classification is itself formulated and solved by heuristic classification. This allows the construction of more knowledge-intensive classification programs in a way that yields a clean organization. Further, standard knowledge acquisition and learning techniques for heuristic classification can be used to create, refine, and maintain the knowledge base associated with the recursively called classification expert system. The method of recursive heuristic classification was used in the Minerva blackboard shell for heuristic classification. Minerva recursively calls itself every problem-solving cycle to solve the important blackboard scheduler task, which involves assigning a desirability rating to alternative problem-solving actions. Knowing these ratings is critical to the use of an expert system as a component of a critiquing or apprenticeship tutoring system. One innovation of this research is a method called dynamic heuristic classification, which allows selection among dynamically generated classification categories instead of requiring them to be prenumerated.

  12. Security classification of information

    Energy Technology Data Exchange (ETDEWEB)

    Quist, A.S.

    1993-04-01

    This document is the second of a planned four-volume work that comprehensively discusses the security classification of information. The main focus of Volume 2 is on the principles for classification of information. Included herein are descriptions of the two major types of information that governments classify for national security reasons (subjective and objective information), guidance to use when determining whether information under consideration for classification is controlled by the government (a necessary requirement for classification to be effective), information disclosure risks and benefits (the benefits and costs of classification), standards to use when balancing information disclosure risks and benefits, guidance for assigning classification levels (Top Secret, Secret, or Confidential) to classified information, guidance for determining how long information should be classified (classification duration), classification of associations of information, classification of compilations of information, and principles for declassifying and downgrading information. Rules or principles of certain areas of our legal system (e.g., trade secret law) are sometimes mentioned to .provide added support to some of those classification principles.

  13. 男性乳腺癌36例分子分型和临床特征分析%Analysis of molecular classification and clinical characteristics in 36 patients with male breast cancer

    Institute of Scientific and Technical Information of China (English)

    于晶晶; 孙强; 沈松杰

    2013-01-01

    Objective To analyze molecular classification and male breast cancer (MBC) triggers,clinical characteristics in patients with MBC and evaluate the prognosis.Methods 36 MBC patients enrolled in the past 5 years were retrospectively analyzed.100 patients with women breast cancer (WBC) in the same period were randomly selected as control group.The primary pathological type of MBC was the infiltrating ductal carcinoma.According to the expressions of estrogen receptor (ER),progesterone receptor (PR),and the epidermal growth factor receptor 2 (Her-2),the MBC can be divided into 4 kinds of molecular subtypes,Luminal type A,Luminal type B,Her-2 type,and Basal-like type.Results The ratio of MBC patients with grade Ⅲ was lower in the Luminal group A than that in the Luminal group B.There were significant differences (x2 =1.197,P < 0.05) between these two groups.Conclusion The incidence rate of MBC is low but the prognosis is poor.The primary pathological type is the infiltrating ductal carcinoma.The ratio of MBC patients with grade Ⅲ is lower in the common Luminal group A than that in the common Luminal group B.%目的 研究男性乳腺癌(MBC)的发病因素、分子分型、手术方式等并对其预后进行评估.方法 回顾性分析近5年住院的MBC患者36例,选取同期女性乳腺癌(WBC)患者100例作为对照组,病理类型以浸润性导管癌为主;根据雌激素受体(ER)、孕激素受体(PR)和人类表皮生长因子受体2(Her-2)的表达情况将MBC分为4种分子亚型,即Luminal A型、Luminal B型、Her-2型和Basal-like型.结果 LuminalA组较LuminalB组乳腺癌患者组织学Ⅲ级的比例低,差异有统计学意义(x2=1.197,P< 0.05).结论 MBC发病率低,预后较差,病理类型以浸润性导管癌为主.MBC患者多见Luminal A型和Luminal B型,Luminal A型较Luminal B型乳腺癌患者组织学Ⅲ级的比例低.

  14. AGN Zoo and Classifications of Active Galaxies

    Science.gov (United States)

    Mickaelian, Areg M.

    2015-07-01

    We review the variety of Active Galactic Nuclei (AGN) classes (so-called "AGN zoo") and classification schemes of galaxies by activity types based on their optical emission-line spectrum, as well as other parameters and other than optical wavelength ranges. A historical overview of discoveries of various types of active galaxies is given, including Seyfert galaxies, radio galaxies, QSOs, BL Lacertae objects, Starbursts, LINERs, etc. Various kinds of AGN diagnostics are discussed. All known AGN types and subtypes are presented and described to have a homogeneous classification scheme based on the optical emission-line spectra and in many cases, also other parameters. Problems connected with accurate classifications and open questions related to AGN and their classes are discussed and summarized.

  15. Text Classification Using Sentential Frequent Itemsets

    Institute of Scientific and Technical Information of China (English)

    Shi-Zhu Liu; He-Ping Hu

    2007-01-01

    Text classification techniques mostly rely on single term analysis of the document data set, while more concepts,especially the specific ones, are usually conveyed by set of terms. To achieve more accurate text classifier, more informative feature including frequent co-occurring words in the same sentence and their weights are particularly important in such scenarios. In this paper, we propose a novel approach using sentential frequent itemset, a concept comes from association rule mining, for text classification, which views a sentence rather than a document as a transaction, and uses a variable precision rough set based method to evaluate each sentential frequent itemset's contribution to the classification. Experiments over the Reuters and newsgroup corpus are carried out, which validate the practicability of the proposed system.

  16. An Ensemble Classification Algorithm for Hyperspectral Images

    Directory of Open Access Journals (Sweden)

    K.Kavitha

    2014-04-01

    Full Text Available Hyperspectral image analysis has been used for many purposes in environmental monitoring, remote sensing, vegetation research and also for land cover classification. A hyperspectral image consists of many layers in which each layer represents a specific wavelength. The layers stack on top of one another making a cube-like image for entire spectrum. This work aims to classify the hyperspectral images and to produce a thematic map accurately. Spatial information of hyperspectral images is collected by applying morphological profile and local binary pattern. Support vector machine is an efficient classification algorithm for classifying the hyperspectral images. Genetic algorithm is used to obtain the best feature subjected for classification. Selected features are classified for obtaining the classes and to produce a thematic map. Experiment is carried out with AVIRIS Indian Pines and ROSIS Pavia University. Proposed method produces accuracy as 93% for Indian Pines and 92% for Pavia University.

  17. Ontologies vs. Classification Systems

    DEFF Research Database (Denmark)

    Madsen, Bodil Nistrup; Erdman Thomsen, Hanne

    2009-01-01

    What is an ontology compared to a classification system? Is a taxonomy a kind of classification system or a kind of ontology? These are questions that we meet when working with people from industry and public authorities, who need methods and tools for concept clarification, for developing meta...... data sets or for obtaining advanced search facilities. In this paper we will present an attempt at answering these questions. We will give a presentation of various types of ontologies and briefly introduce terminological ontologies. Furthermore we will argue that classification systems, e.g. product...... classification systems and meta data taxonomies, should be based on ontologies....

  18. Classification of Itch.

    Science.gov (United States)

    Ständer, Sonja

    2016-01-01

    Chronic pruritus has diverse forms of presentation and can appear not only on normal skin [International Forum for the Study of Itch (IFSI) classification group II], but also in the company of dermatoses (IFSI classification group I). Scratching, a natural reflex, begins in response to itch. Enough damage can be done to the skin by scratching to cause changes in the primary clinical picture, often leading to a clinical picture predominated by the development of chronic scratch lesions (IFSI classification group III). An internationally recognized, standardized classification system was created by the IFSI to not only aid in clarifying terms and definitions, but also to harmonize the global nomenclature for itch. PMID:27578063

  19. Adenocarcinoma of Mullerian origin: review of pathogenesis, molecular biology, and emerging treatment paradigms.

    Science.gov (United States)

    Cobb, Lauren Patterson; Gaillard, Stephanie; Wang, Yihong; Shih, Ie-Ming; Secord, Angeles Alvarez

    2015-01-01

    Traditionally, epithelial ovarian, tubal, and peritoneal cancers have been viewed as separate entities with disparate origins, pathogenesis, clinical features, and outcomes. Additionally, previous classification systems for ovarian cancer have proposed two primary histologic groups that encompass the standard histologic subtypes. Recent data suggest that these groupings no longer accurately reflect our knowledge surrounding these cancers. In this review, we propose that epithelial ovarian, tubal, and peritoneal carcinomas represent a spectrum of disease that originates in the Mullerian compartment. We will discuss the incidence, classification, origin, molecular determinants, and pathologic analysis of these cancers that support the conclusion they should be collectively referred to as adenocarcinomas of Mullerian origin. As our understanding of the molecular and pathologic profiling of adenocarcinomas of Mullerian origin advances, we anticipate treatment paradigms will shift towards genomic driven therapeutic interventions.

  20. Accurate free energy calculation along optimized paths.

    Science.gov (United States)

    Chen, Changjun; Xiao, Yi

    2010-05-01

    The path-based methods of free energy calculation, such as thermodynamic integration and free energy perturbation, are simple in theory, but difficult in practice because in most cases smooth paths do not exist, especially for large molecules. In this article, we present a novel method to build the transition path of a peptide. We use harmonic potentials to restrain its nonhydrogen atom dihedrals in the initial state and set the equilibrium angles of the potentials as those in the final state. Through a series of steps of geometrical optimization, we can construct a smooth and short path from the initial state to the final state. This path can be used to calculate free energy difference. To validate this method, we apply it to a small 10-ALA peptide and find that the calculated free energy changes in helix-helix and helix-hairpin transitions are both self-convergent and cross-convergent. We also calculate the free energy differences between different stable states of beta-hairpin trpzip2, and the results show that this method is more efficient than the conventional molecular dynamics method in accurate free energy calculation.

  1. Concepts of Classification and Taxonomy. Phylogenetic Classification

    CERN Document Server

    Fraix-Burnet, Didier

    2016-01-01

    Phylogenetic approaches to classification have been heavily developed in biology by bioinformaticians. But these techniques have applications in other fields, in particular in linguistics. Their main characteristics is to search for relationships between the objects or species in study, instead of grouping them by similarity. They are thus rather well suited for any kind of evolutionary objects. For nearly fifteen years, astrocladistics has explored the use of Maximum Parsimony (or cladistics) for astronomical objects like galaxies or globular clusters. In this lesson we will learn how it works. 1 Why phylogenetic tools in astrophysics? 1.1 History of classification The need for classifying living organisms is very ancient, and the first classification system can be dated back to the Greeks. The goal was very practical since it was intended to distinguish between eatable and toxic aliments, or kind and dangerous animals. Simple resemblance was used and has been used for centuries. Basically, until the XVIIIth...

  2. Acute pancreatitis - severity classification, complications and outcome

    OpenAIRE

    Andersson, Bodil

    2010-01-01

    Acute pancreatitis, with an annual incidence of approximately 35 per 100 000 inhabitants in Sweden, is in most cases mild and self-limiting. Severe acute pancreatitis, affecting 10-15% of the cases is, however, associated with severe complications and even death. The optimal management of acute pancreatitis includes accurate early prediction of the disease severity. The aims of this thesis were to investigate early severity classification, complications and outcome in acute pancreatitis patie...

  3. Ensemble methods for noise in classification problems

    OpenAIRE

    Verbaeten, Sofie; Van Assche, Anneleen

    2003-01-01

    Ensemble methods combine a set of classifiers to construct a new classifier that is (often) more accurate than any of its component classifiers. In this paper, we use ensemble methods to identify noisy training examples. More precisely, we consider the problem of mislabeled training examples in classification tasks, and address this problem by pre-processing the training set, i.e. by identifying and removing outliers from the training set. We study a number of filter techniques that are based...

  4. BIOPHARMACEUTICAL CLASSIFICATION SYSTEM AND BIOWAVER: AN OVERVIEW

    OpenAIRE

    Puranik Prashant K; Kasar Sagar Ashok; Gadade Deepak Dilip; Mali Prabha R

    2011-01-01

    The biopharmaceutical classification system (BCS) has been developed to provide a scientific approach for classifying drug compounds based on solubility as related to dose and intestinal permeability in combination with the dissolution properties of the oral immediate release dosage form. BCS is to provide a regulatory tool for replacing certain bioequivalence (BE) studies by accurate in vitro dissolution tests. This review gives three dimensionless numbers which are used in BCS are absorptio...

  5. Independent Comparison of Popular DPI Tools for Traffic Classification

    DEFF Research Database (Denmark)

    Bujlow, Tomasz; Carela-Español, Valentín; Barlet-Ros, Pere

    2015-01-01

    Deep Packet Inspection (DPI) is the state-of-the-art technology for traffic classification. According to the conventional wisdom, DPI is the most accurate classification technique. Consequently, most popular products, either commercial or open-source, rely on some sort of DPI for traffic classifi......Deep Packet Inspection (DPI) is the state-of-the-art technology for traffic classification. According to the conventional wisdom, DPI is the most accurate classification technique. Consequently, most popular products, either commercial or open-source, rely on some sort of DPI for traffic......, application and web service). We carefully built a labeled dataset with more than 750K flows, which contains traffic from popular applications. We used the Volunteer-Based System (VBS), developed at Aalborg University, to guarantee the correct labeling of the dataset. We released this dataset, including full...

  6. A jackknife-like method for classification and uncertainty assessment of multi-category tumor samples using gene expression information

    Directory of Open Access Journals (Sweden)

    Bertrand Keith

    2010-04-01

    Full Text Available Abstract Background The use of gene expression profiling for the classification of human cancer tumors has been widely investigated. Previous studies were successful in distinguishing several tumor types in binary problems. As there are over a hundred types of cancers, and potentially even more subtypes, it is essential to develop multi-category methodologies for molecular classification for any meaningful practical application. Results A jackknife-based supervised learning method called paired-samples test algorithm (PST, coupled with a binary classification model based on linear regression, was proposed and applied to two well known and challenging datasets consisting of 14 (GCM dataset and 9 (NC160 dataset tumor types. The results showed that the proposed method improved the prediction accuracy of the test samples for the GCM dataset, especially when t-statistic was used in the primary feature selection. For the NCI60 dataset, the application of PST improved prediction accuracy when the numbers of used genes were relatively small (100 or 200. These improvements made the binary classification method more robust to the gene selection mechanism and the size of genes to be used. The overall prediction accuracies were competitive in comparison to the most accurate results obtained by several previous studies on the same datasets and with other methods. Furthermore, the relative confidence R(T provided a unique insight into the sources of the uncertainty shown in the statistical classification and the potential variants within the same tumor type. Conclusion We proposed a novel bagging method for the classification and uncertainty assessment of multi-category tumor samples using gene expression information. The strengths were demonstrated in the application to two bench datasets.

  7. 38 CFR 4.46 - Accurate measurement.

    Science.gov (United States)

    2010-07-01

    ... 38 Pensions, Bonuses, and Veterans' Relief 1 2010-07-01 2010-07-01 false Accurate measurement. 4... RATING DISABILITIES Disability Ratings The Musculoskeletal System § 4.46 Accurate measurement. Accurate measurement of the length of stumps, excursion of joints, dimensions and location of scars with respect...

  8. Library Classification 2020

    Science.gov (United States)

    Harris, Christopher

    2013-01-01

    In this article the author explores how a new library classification system might be designed using some aspects of the Dewey Decimal Classification (DDC) and ideas from other systems to create something that works for school libraries in the year 2020. By examining what works well with the Dewey Decimal System, what features should be carried…

  9. Musings on galaxy classification

    International Nuclear Information System (INIS)

    Classification schemes and their utility are discussed with a number of examples, particularly for cD galaxies. Data suggest that primordial turbulence rather than tidal torques is responsible for most of the presently observed angular momentum of galaxies. Finally, some of the limitations on present-day schemes for galaxy classification are pointed out. 54 references, 4 figures, 3 tables

  10. A proposal for the morphological classification and nomenclature of neurons

    Institute of Scientific and Technical Information of China (English)

    Rong Jiang; Qiang Liu; Quan Liu; Shenquan Liu

    2011-01-01

    The morphological and functional characteristics of neurons are quite varied and complex. There is a need for a comprehensive approach for distinguishing and classifying neurons. Similar to the biological species classification system, this study proposes a morphological classification system for neurons based on principal component analysis. Based on four principal components of neuronal morphology derived from principal component analysis, a nomenclature system for neurons was obtained. This system can accurately distinguish between the same type of neuron from different species.

  11. Multi-Organ Cancer Classification and Survival Analysis

    OpenAIRE

    Bauer, Stefan; Carion, Nicolas; Schüffler, Peter; Fuchs, Thomas; Wild, Peter; Buhmann, Joachim M.

    2016-01-01

    Accurate and robust cell nuclei classification is the cornerstone for a wider range of tasks in digital and Computational Pathology. However, most machine learning systems require extensive labeling from expert pathologists for each individual problem at hand, with no or limited abilities for knowledge transfer between datasets and organ sites. In this paper we implement and evaluate a variety of deep neural network models and model ensembles for nuclei classification in renal cell cancer (RC...

  12. Enhancing Accuracy of Plant Leaf Classification Techniques

    Directory of Open Access Journals (Sweden)

    C. S. Sumathi

    2014-03-01

    Full Text Available Plants have become an important source of energy, and are a fundamental piece in the puzzle to solve the problem of global warming. Living beings also depend on plants for their food, hence it is of great importance to know about the plants growing around us and to preserve them. Automatic plant leaf classification is widely researched. This paper investigates the efficiency of learning algorithms of MLP for plant leaf classification. Incremental back propagation, Levenberg–Marquardt and batch propagation learning algorithms are investigated. Plant leaf images are examined using three different Multi-Layer Perceptron (MLP modelling techniques. Back propagation done in batch manner increases the accuracy of plant leaf classification. Results reveal that batch training is faster and more accurate than MLP with incremental training and Levenberg– Marquardt based learning for plant leaf classification. Various levels of semi-batch training used on 9 species of 15 sample each, a total of 135 instances show a roughly linear increase in classification accuracy.

  13. Photometric Supernova Classification with Machine Learning

    Science.gov (United States)

    Lochner, Michelle; McEwen, Jason D.; Peiris, Hiranya V.; Lahav, Ofer; Winter, Max K.

    2016-08-01

    Automated photometric supernova classification has become an active area of research in recent years in light of current and upcoming imaging surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope, given that spectroscopic confirmation of type for all supernovae discovered will be impossible. Here, we develop a multi-faceted classification pipeline, combining existing and new approaches. Our pipeline consists of two stages: extracting descriptive features from the light curves and classification using a machine learning algorithm. Our feature extraction methods vary from model-dependent techniques, namely SALT2 fits, to more independent techniques that fit parametric models to curves, to a completely model-independent wavelet approach. We cover a range of representative machine learning algorithms, including naive Bayes, k-nearest neighbors, support vector machines, artificial neural networks, and boosted decision trees (BDTs). We test the pipeline on simulated multi-band DES light curves from the Supernova Photometric Classification Challenge. Using the commonly used area under the curve (AUC) of the Receiver Operating Characteristic as a metric, we find that the SALT2 fits and the wavelet approach, with the BDTs algorithm, each achieve an AUC of 0.98, where 1 represents perfect classification. We find that a representative training set is essential for good classification, whatever the feature set or algorithm, with implications for spectroscopic follow-up. Importantly, we find that by using either the SALT2 or the wavelet feature sets with a BDT algorithm, accurate classification is possible purely from light curve data, without the need for any redshift information.

  14. Information Classification on University Websites

    DEFF Research Database (Denmark)

    Nawaz, Ather; Clemmensen, Torkil; Hertzum, Morten

    2011-01-01

    classification of 14 Danish and 14 Pakistani students and compares it with the information classification of their university website. Brainstorming, card sorting and task exploration activities were used to discover similarities and differences in the participating students’ classification of website...

  15. Information Classification on University Websites

    DEFF Research Database (Denmark)

    Nawaz, Ather; Clemmensen, Torkil; Hertzum, Morten

    2011-01-01

    classification of 14 Danish and 14 Pakistani students and compares it with the information classification of their university website. Brainstorming, card sorting, and task exploration activities were used to discover similarities and differences in the participating students’ classification of website...

  16. Behavior Based Social Dimensions Extraction for Multi-Label Classification.

    Directory of Open Access Journals (Sweden)

    Le Li

    Full Text Available Classification based on social dimensions is commonly used to handle the multi-label classification task in heterogeneous networks. However, traditional methods, which mostly rely on the community detection algorithms to extract the latent social dimensions, produce unsatisfactory performance when community detection algorithms fail. In this paper, we propose a novel behavior based social dimensions extraction method to improve the classification performance in multi-label heterogeneous networks. In our method, nodes' behavior features, instead of community memberships, are used to extract social dimensions. By introducing Latent Dirichlet Allocation (LDA to model the network generation process, nodes' connection behaviors with different communities can be extracted accurately, which are applied as latent social dimensions for classification. Experiments on various public datasets reveal that the proposed method can obtain satisfactory classification results in comparison to other state-of-the-art methods on smaller social dimensions.

  17. Behavior Based Social Dimensions Extraction for Multi-Label Classification.

    Science.gov (United States)

    Li, Le; Xu, Junyi; Xiao, Weidong; Ge, Bin

    2016-01-01

    Classification based on social dimensions is commonly used to handle the multi-label classification task in heterogeneous networks. However, traditional methods, which mostly rely on the community detection algorithms to extract the latent social dimensions, produce unsatisfactory performance when community detection algorithms fail. In this paper, we propose a novel behavior based social dimensions extraction method to improve the classification performance in multi-label heterogeneous networks. In our method, nodes' behavior features, instead of community memberships, are used to extract social dimensions. By introducing Latent Dirichlet Allocation (LDA) to model the network generation process, nodes' connection behaviors with different communities can be extracted accurately, which are applied as latent social dimensions for classification. Experiments on various public datasets reveal that the proposed method can obtain satisfactory classification results in comparison to other state-of-the-art methods on smaller social dimensions. PMID:27049849

  18. Behavior Based Social Dimensions Extraction for Multi-Label Classification

    Science.gov (United States)

    Li, Le; Xu, Junyi; Xiao, Weidong; Ge, Bin

    2016-01-01

    Classification based on social dimensions is commonly used to handle the multi-label classification task in heterogeneous networks. However, traditional methods, which mostly rely on the community detection algorithms to extract the latent social dimensions, produce unsatisfactory performance when community detection algorithms fail. In this paper, we propose a novel behavior based social dimensions extraction method to improve the classification performance in multi-label heterogeneous networks. In our method, nodes’ behavior features, instead of community memberships, are used to extract social dimensions. By introducing Latent Dirichlet Allocation (LDA) to model the network generation process, nodes’ connection behaviors with different communities can be extracted accurately, which are applied as latent social dimensions for classification. Experiments on various public datasets reveal that the proposed method can obtain satisfactory classification results in comparison to other state-of-the-art methods on smaller social dimensions. PMID:27049849

  19. Intraregional classification of wine via ICP-MS elemental fingerprinting.

    Science.gov (United States)

    Coetzee, P P; van Jaarsveld, F P; Vanhaecke, F

    2014-12-01

    The feasibility of elemental fingerprinting in the classification of wines according to their provenance vineyard soil was investigated in the relatively small geographical area of a single wine district. Results for the Stellenbosch wine district (Western Cape Wine Region, South Africa), comprising an area of less than 1,000 km(2), suggest that classification of wines from different estates (120 wines from 23 estates) is indeed possible using accurate elemental data and multivariate statistical analysis based on a combination of principal component analysis, cluster analysis, and discriminant analysis. This is the first study to demonstrate the successful classification of wines at estate level in a single wine district in South Africa. The elements B, Ba, Cs, Cu, Mg, Rb, Sr, Tl and Zn were identified as suitable indicators. White and red wines were grouped in separate data sets to allow successful classification of wines. Correlation between wine classification and soil type distributions in the area was observed.

  20. The Evolution of Tumor Classification: A Role for Genomics?

    OpenAIRE

    Bunn, Paul A.; Franklin, Wilbur; Doebele, Robert C.

    2013-01-01

    Lung cancers are divided into four types according to their histologic appearance. Therapeutic decisions are partly based on histology. A recent study indicates that certain molecular alterations associate with histology and therapies directed to these molecular changes improve outcome, indicating that genomic information should be incorporated into future tumor classification.

  1. Hyperspectral Data Classification Using Factor Graphs

    Science.gov (United States)

    Makarau, A.; Müller, R.; Palubinskas, G.; Reinartz, P.

    2012-07-01

    Accurate classification of hyperspectral data is still a competitive task and new classification methods are developed to achieve desired tasks of hyperspectral data use. The objective of this paper is to develop a new method for hyperspectral data classification ensuring the classification model properties like transferability, generalization, probabilistic interpretation, etc. While factor graphs (undirected graphical models) are unfortunately not widely employed in remote sensing tasks, these models possess important properties such as representation of complex systems to model estimation/decision making tasks. In this paper we present a new method for hyperspectral data classification using factor graphs. Factor graph (a bipartite graph consisting of variables and factor vertices) allows factorization of a more complex function leading to definition of variables (employed to store input data), latent variables (allow to bridge abstract class to data), and factors (defining prior probabilities for spectral features and abstract classes; input data mapping to spectral features mixture and further bridging of the mixture to an abstract class). Latent variables play an important role by defining two-level mapping of the input spectral features to a class. Configuration (learning) on training data of the model allows calculating a parameter set for the model to bridge the input data to a class. The classification algorithm is as follows. Spectral bands are separately pre-processed (unsupervised clustering is used) to be defined on a finite domain (alphabet) leading to a representation of the data on multinomial distribution. The represented hyperspectral data is used as input evidence (evidence vector is selected pixelwise) in a configured factor graph and an inference is run resulting in the posterior probability. Variational inference (Mean field) allows to obtain plausible results with a low calculation time. Calculating the posterior probability for each class

  2. Morphological classification of plant cell deaths

    DEFF Research Database (Denmark)

    van Doorn, W.G.; Beers, E.P.; Dangl, J.L.;

    2011-01-01

    Programmed cell death (PCD) is an integral part of plant development and of responses to abiotic stress or pathogens. Although the morphology of plant PCD is, in some cases, well characterised and molecular mechanisms controlling plant PCD are beginning to emerge, there is still confusion about...... the classification of PCD in plants. Here we suggest a classification based on morphological criteria. According to this classification, the use of the term 'apoptosis' is not justified in plants, but at least two classes of PCD can be distinguished: vacuolar cell death and necrosis. During vacuolar cell death......, the cell contents are removed by a combination of autophagy-like process and release of hydrolases from collapsed lytic vacuoles. Necrosis is characterised by early rupture of the plasma membrane, shrinkage of the protoplast and absence of vacuolar cell death features. Vacuolar cell death is common during...

  3. Cancer classification based on gene expression using neural networks.

    Science.gov (United States)

    Hu, H P; Niu, Z J; Bai, Y P; Tan, X H

    2015-12-21

    Based on gene expression, we have classified 53 colon cancer patients with UICC II into two groups: relapse and no relapse. Samples were taken from each patient, and gene information was extracted. Of the 53 samples examined, 500 genes were considered proper through analyses by S-Kohonen, BP, and SVM neural networks. Classification accuracy obtained by S-Kohonen neural network reaches 91%, which was more accurate than classification by BP and SVM neural networks. The results show that S-Kohonen neural network is more plausible for classification and has a certain feasibility and validity as compared with BP and SVM neural networks.

  4. Cluster Based Text Classification Model

    DEFF Research Database (Denmark)

    Nizamani, Sarwat; Memon, Nasrullah; Wiil, Uffe Kock

    2011-01-01

    We propose a cluster based classification model for suspicious email detection and other text classification tasks. The text classification tasks comprise many training examples that require a complex classification model. Using clusters for classification makes the model simpler and increases......, the classifier is trained on each cluster having reduced dimensionality and less number of examples. The experimental results show that the proposed model outperforms the existing classification models for the task of suspicious email detection and topic categorization on the Reuters-21578 and 20 Newsgroups...... datasets. Our model also outperforms A Decision Cluster Classification (ADCC) and the Decision Cluster Forest Classification (DCFC) models on the Reuters-21578 dataset....

  5. Classification of hand eczema

    DEFF Research Database (Denmark)

    Agner, T; Aalto-Korte, K; Andersen, K E;

    2015-01-01

    BACKGROUND: Classification of hand eczema (HE) is mandatory in epidemiological and clinical studies, and also important in clinical work. OBJECTIVES: The aim was to test a recently proposed classification system of HE in clinical practice in a prospective multicentre study. METHODS: Patients were......%) could not be classified. 38% had one additional diagnosis and 26% had two or more additional diagnoses. Eczema on feet was found in 30% of the patients, statistically significantly more frequently associated with hyperkeratotic and vesicular endogenous eczema. CONCLUSION: We find that the classification...

  6. Pitch Based Sound Classification

    OpenAIRE

    Nielsen, Andreas Brinch; Hansen, Lars Kai; Kjems, U.

    2006-01-01

    A sound classification model is presented that can classify signals into music, noise and speech. The model extracts the pitch of the signal using the harmonic product spectrum. Based on the pitch estimate and a pitch error measure, features are created and used in a probabilistic model with soft-max output function. Both linear and quadratic inputs are used. The model is trained on 2 hours of sound and tested on publicly available data. A test classification error below 0.05 with 1 s classif...

  7. Molecular classification of cervical squamous cell carcinoma using cDNA microarrays%利用cDNA微阵列进行宫颈鳞癌的分子筛查

    Institute of Scientific and Technical Information of China (English)

    吴素慧; 解军; 李颖; 张静; 郭素堂; 何显峰; 牛勃; 王泽华

    2006-01-01

    metastases, all 677 genes were identified with differential expression, 494 of which showed increased expression(72.97% ), 183 decreased expression (27.03%), and ESTs were 61(9.01% ), including genes of metabolism,development, signal transduction and differentiation. Thereinto, 14 6-fold differential genes were up-regulated except that nel (chicken)-like 2 was down-regulated. The results of RT-PCR and immunohistochemistry were in agreement with the microarray data.Conclusion The results demonstrate that gene expression profiling can be used as a predictor of lymph node metastasis and prognosis of cervical carcinoma. The prediction of cervical malignancy based on the lack of Cx43 and superabundance of ETV5 and integrin alpha 2 might serve as specific diagnostic biomarkers for ICC. These expression may be suitable for molecular classification of disease stages and prediction of treatment response in cervical carcinoma.

  8. 78 FR 54970 - Cotton Futures Classification: Optional Classification Procedure

    Science.gov (United States)

    2013-09-09

    ... process in March 2012 (77 FR 5379). When verified by a futures classification, Smith-Doxey data serves as... Classification: Optional Classification Procedure AGENCY: Agricultural Marketing Service, USDA. ACTION: Proposed... for the addition of an optional cotton futures classification procedure--identified and known...

  9. Pitch Based Sound Classification

    DEFF Research Database (Denmark)

    Nielsen, Andreas Brinch; Hansen, Lars Kai; Kjems, U

    2006-01-01

    A sound classification model is presented that can classify signals into music, noise and speech. The model extracts the pitch of the signal using the harmonic product spectrum. Based on the pitch estimate and a pitch error measure, features are created and used in a probabilistic model with soft......-max output function. Both linear and quadratic inputs are used. The model is trained on 2 hours of sound and tested on publicly available data. A test classification error below 0.05 with 1 s classification windows is achieved. Further more it is shown that linear input performs as well as a quadratic......, and that even though classification gets marginally better, not much is achieved by increasing the window size beyond 1 s....

  10. Classification in Medical Imaging

    DEFF Research Database (Denmark)

    Chen, Chen

    Classification is extensively used in the context of medical image analysis for the purpose of diagnosis or prognosis. In order to classify image content correctly, one needs to extract efficient features with discriminative properties and build classifiers based on these features. In addition......, a good metric is required to measure distance or similarity between feature points so that the classification becomes feasible. Furthermore, in order to build a successful classifier, one needs to deeply understand how classifiers work. This thesis focuses on these three aspects of classification...... and explores these challenging areas. The first focus of the thesis is to properly combine different local feature experts and prior information to design an effective classifier. The preliminary classification results, provided by the experts, are fused in order to develop an automatic segmentation method...

  11. Learning Apache Mahout classification

    CERN Document Server

    Gupta, Ashish

    2015-01-01

    If you are a data scientist who has some experience with the Hadoop ecosystem and machine learning methods and want to try out classification on large datasets using Mahout, this book is ideal for you. Knowledge of Java is essential.

  12. Latent classification models

    DEFF Research Database (Denmark)

    Langseth, Helge; Nielsen, Thomas Dyhre

    2005-01-01

    parametric family ofdistributions.  In this paper we propose a new set of models forclassification in continuous domains, termed latent classificationmodels. The latent classification model can roughly be seen ascombining the \\NB model with a mixture of factor analyzers,thereby relaxing the assumptions...... classification model, and wedemonstrate empirically that the accuracy of the proposed model issignificantly higher than the accuracy of other probabilisticclassifiers....

  13. Classification of Sleep Disorders

    OpenAIRE

    Michael J. Thorpy

    2012-01-01

    The classification of sleep disorders is necessary to discriminate between disorders and to facilitate an understanding of symptoms, etiology, and pathophysiology that allows for appropriate treatment. The earliest classification systems, largely organized according to major symptoms (insomnia, excessive sleepiness, and abnormal events that occur during sleep), were unable to be based on pathophysiology because the cause of most sleep disorders was unknown. These 3 symptom-based categories ar...

  14. Inhibition in multiclass classification

    OpenAIRE

    Huerta, Ramón; Vembu, Shankar; Amigó, José M.; Nowotny, Thomas; Elkan, Charles

    2012-01-01

    The role of inhibition is investigated in a multiclass support vector machine formalism inspired by the brain structure of insects. The so-called mushroom bodies have a set of output neurons, or classification functions, that compete with each other to encode a particular input. Strongly active output neurons depress or inhibit the remaining outputs without knowing which is correct or incorrect. Accordingly, we propose to use a classification function that embodies unselective inhibition and ...

  15. Classification of Dams

    OpenAIRE

    Berg, Johan; Linder, Maria

    2013-01-01

    In a comparing survey this thesis investigates classification systems for dams in Sweden, Norway, Finland, Switzerland, Canada and USA. The investigation is aiming at an understanding of how potential consequences of a dam failure are taken into account when classifying dams. Furthermore, the significance of the classification, regarding the requirements on the dam owner and surveillance authorities concerning dam safety is considered and reviewed. The thesis is pointing out similarities and ...

  16. A New Classification Approach Based on Multiple Classification Rules

    OpenAIRE

    Zhongmei Zhou

    2014-01-01

    A good classifier can correctly predict new data for which the class label is unknown, so it is important to construct a high accuracy classifier. Hence, classification techniques are much useful in ubiquitous computing. Associative classification achieves higher classification accuracy than some traditional rule-based classification approaches. However, the approach also has two major deficiencies. First, it generates a very large number of association classification rules, especially when t...

  17. Progressive Classification Using Support Vector Machines

    Science.gov (United States)

    Wagstaff, Kiri; Kocurek, Michael

    2009-01-01

    An algorithm for progressive classification of data, analogous to progressive rendering of images, makes it possible to compromise between speed and accuracy. This algorithm uses support vector machines (SVMs) to classify data. An SVM is a machine learning algorithm that builds a mathematical model of the desired classification concept by identifying the critical data points, called support vectors. Coarse approximations to the concept require only a few support vectors, while precise, highly accurate models require far more support vectors. Once the model has been constructed, the SVM can be applied to new observations. The cost of classifying a new observation is proportional to the number of support vectors in the model. When computational resources are limited, an SVM of the appropriate complexity can be produced. However, if the constraints are not known when the model is constructed, or if they can change over time, a method for adaptively responding to the current resource constraints is required. This capability is particularly relevant for spacecraft (or any other real-time systems) that perform onboard data analysis. The new algorithm enables the fast, interactive application of an SVM classifier to a new set of data. The classification process achieved by this algorithm is characterized as progressive because a coarse approximation to the true classification is generated rapidly and thereafter iteratively refined. The algorithm uses two SVMs: (1) a fast, approximate one and (2) slow, highly accurate one. New data are initially classified by the fast SVM, producing a baseline approximate classification. For each classified data point, the algorithm calculates a confidence index that indicates the likelihood that it was classified correctly in the first pass. Next, the data points are sorted by their confidence indices and progressively reclassified by the slower, more accurate SVM, starting with the items most likely to be incorrectly classified. The user

  18. Hierarchical classification of social groups

    OpenAIRE

    Витковская, Мария

    2001-01-01

    Classification problems are important for every science, and for sociology as well. Social phenomena, examined from the aspect of classification of social groups, can be examined deeper. At present one common classification of groups does not exist. This article offers the hierarchical classification of social group.

  19. Iris Image Classification Based on Hierarchical Visual Codebook.

    Science.gov (United States)

    Zhenan Sun; Hui Zhang; Tieniu Tan; Jianyu Wang

    2014-06-01

    Iris recognition as a reliable method for personal identification has been well-studied with the objective to assign the class label of each iris image to a unique subject. In contrast, iris image classification aims to classify an iris image to an application specific category, e.g., iris liveness detection (classification of genuine and fake iris images), race classification (e.g., classification of iris images of Asian and non-Asian subjects), coarse-to-fine iris identification (classification of all iris images in the central database into multiple categories). This paper proposes a general framework for iris image classification based on texture analysis. A novel texture pattern representation method called Hierarchical Visual Codebook (HVC) is proposed to encode the texture primitives of iris images. The proposed HVC method is an integration of two existing Bag-of-Words models, namely Vocabulary Tree (VT), and Locality-constrained Linear Coding (LLC). The HVC adopts a coarse-to-fine visual coding strategy and takes advantages of both VT and LLC for accurate and sparse representation of iris texture. Extensive experimental results demonstrate that the proposed iris image classification method achieves state-of-the-art performance for iris liveness detection, race classification, and coarse-to-fine iris identification. A comprehensive fake iris image database simulating four types of iris spoof attacks is developed as the benchmark for research of iris liveness detection. PMID:26353275

  20. Product Classification in Supply Chain

    OpenAIRE

    Xing, Lihong; Xu, Yaoxuan

    2010-01-01

    Oriflame is a famous international direct sale cosmetics company with complicated supply chain operation but it lacks of a product classification system. It is vital to design a product classification method in order to support Oriflame global supply planning and improve the supply chain performance. This article is aim to investigate and design the multi-criteria of product classification, propose the classification model, suggest application areas of product classification results and intro...

  1. A Novel Vehicle Classification Using Embedded Strain Gauge Sensors

    Directory of Open Access Journals (Sweden)

    Qi Wang

    2008-11-01

    Full Text Available Abstract: This paper presents a new vehicle classification and develops a traffic monitoring detector to provide reliable vehicle classification to aid traffic management systems. The basic principle of this approach is based on measuring the dynamic strain caused by vehicles across pavement to obtain the corresponding vehicle parameters – wheelbase and number of axles – to then accurately classify the vehicle. A system prototype with five embedded strain sensors was developed to validate the accuracy and effectiveness of the classification method. According to the special arrangement of the sensors and the different time a vehicle arrived at the sensors one can estimate the vehicle’s speed accurately, corresponding to the estimated vehicle wheelbase and number of axles. Because of measurement errors and vehicle characteristics, there is a lot of overlap between vehicle wheelbase patterns. Therefore, directly setting up a fixed threshold for vehicle classification often leads to low-accuracy results. Using the machine learning pattern recognition method to deal with this problem is believed as one of the most effective tools. In this study, support vector machines (SVMs were used to integrate the classification features extracted from the strain sensors to automatically classify vehicles into five types, ranging from small vehicles to combination trucks, along the lines of the Federal Highway Administration vehicle classification guide. Test bench and field experiments will be introduced in this paper. Two support vector machines classification algorithms (one-against-all, one-against-one are used to classify single sensor data and multiple sensor combination data. Comparison of the two classification method results shows that the classification accuracy is very close using single data or multiple data. Our results indicate that using multiclass SVM-based fusion multiple sensor data significantly improves

  2. Challenging of Facial Expressions Classification Systems: Survey, Critical Considerations and Direction of Future Work

    OpenAIRE

    Amir Jamshidnezhad; M.D. Jan Nordin

    2012-01-01

    The main purpose of this study is analysis of the parameters and the affects of those on the performance of the facial expressions classification systems. In recent years understanding of emotions is a basic requirement in the development of Human Computer Interaction (HCI) systems. Therefore, an HCI is highly depended on accurate understanding of facial expression. Classification module is the main part of facial expressions recognition system. Numerous classification techniques were propose...

  3. A Fuzzy Logic Based Sentiment Classification

    Directory of Open Access Journals (Sweden)

    J.I.Sheeba

    2014-07-01

    Full Text Available Sentiment classification aims to detect information such as opinions, explicit , implicit feelings expressed in text. The most existing approaches are able to detect either explicit expressions or implicit expressions of sentiments in the text separately. In this proposed framework it will detect both Implicit and Explicit expressions available in the meeting transcripts. It will classify the Positive, Negative, Neutral words and also identify the topic of the particular meeting transcripts by using fuzzy logic. This paper aims to add some additional features for improving the classification method. The quality of the sentiment classification is improved using proposed fuzzy logic framework .In this fuzzy logic it includes the features like Fuzzy rules and Fuzzy C-means algorithm.The quality of the output is evaluated using the parameters such as precision, recall, f-measure. Here Fuzzy C-means Clustering technique measured in terms of Purity and Entropy. The data set was validated using 10-fold cross validation method and observed 95% confidence interval between the accuracy values .Finally, the proposed fuzzy logic method produced more than 85 % accurate results and error rate is very less compared to existing sentiment classification techniques.

  4. Classification Algorithms for Determining Handwritten Digit

    Directory of Open Access Journals (Sweden)

    Hayder Naser Khraibet AL-Behadili

    2016-06-01

    Full Text Available Data-intensive science is a critical science paradigm that interferes with all other sciences. Data mining (DM is a powerful and useful technology with wide potential users focusing on important meaningful patterns and discovers a new knowledge from a collected dataset. Any predictive task in DM uses some attribute to classify an unknown class. Classification algorithms are a class of prominent mathematical techniques in DM. Constructing a model is the core aspect of such algorithms. However, their performance highly depends on the algorithm behavior upon manipulating data. Focusing on binarazaition as an approach for preprocessing, this paper analysis and evaluates different classification algorithms when construct a model based on accuracy in the classification task. The Mixed National Institute of Standards and Technology (MNIST handwritten digits dataset provided by Yann LeCun has been used in evaluation. The paper focuses on machine learning approaches for handwritten digits detection. Machine learning establishes classification methods, such as K-Nearest Neighbor(KNN, Decision Tree (DT, and Neural Networks (NN. Results showed that the knowledge-based method, i.e. NN algorithm, is more accurate in determining the digits as it reduces the error rate. The implication of this evaluation is providing essential insights for computer scientists and practitioners for choosing the suitable DM technique that fit with their data.

  5. Concepts of Classification and Taxonomy Phylogenetic Classification

    Science.gov (United States)

    Fraix-Burnet, D.

    2016-05-01

    Phylogenetic approaches to classification have been heavily developed in biology by bioinformaticians. But these techniques have applications in other fields, in particular in linguistics. Their main characteristics is to search for relationships between the objects or species in study, instead of grouping them by similarity. They are thus rather well suited for any kind of evolutionary objects. For nearly fifteen years, astrocladistics has explored the use of Maximum Parsimony (or cladistics) for astronomical objects like galaxies or globular clusters. In this lesson we will learn how it works.

  6. GPCRTree: online hierarchical classification of GPCR function

    Directory of Open Access Journals (Sweden)

    Timmis Jon

    2008-08-01

    Full Text Available Abstract Background G protein-coupled receptors (GPCRs play important physiological roles transducing extracellular signals into intracellular responses. Approximately 50% of all marketed drugs target a GPCR. There remains considerable interest in effectively predicting the function of a GPCR from its primary sequence. Findings Using techniques drawn from data mining and proteochemometrics, an alignment-free approach to GPCR classification has been devised. It uses a simple representation of a protein's physical properties. GPCRTree, a publicly-available internet server, implements an algorithm that classifies GPCRs at the class, sub-family and sub-subfamily level. Conclusion A selective top-down classifier was developed which assigns sequences within a GPCR hierarchy. Compared to other publicly available GPCR prediction servers, GPCRTree is considerably more accurate at every level of classification. The server has been available online since March 2008 at URL: http://igrid-ext.cryst.bbk.ac.uk/gpcrtree/.

  7. Prediction and classification of respiratory motion

    CERN Document Server

    Lee, Suk Jin

    2014-01-01

    This book describes recent radiotherapy technologies including tools for measuring target position during radiotherapy and tracking-based delivery systems. This book presents a customized prediction of respiratory motion with clustering from multiple patient interactions. The proposed method contributes to the improvement of patient treatments by considering breathing pattern for the accurate dose calculation in radiotherapy systems. Real-time tumor-tracking, where the prediction of irregularities becomes relevant, has yet to be clinically established. The statistical quantitative modeling for irregular breathing classification, in which commercial respiration traces are retrospectively categorized into several classes based on breathing pattern are discussed as well. The proposed statistical classification may provide clinical advantages to adjust the dose rate before and during the external beam radiotherapy for minimizing the safety margin. In the first chapter following the Introduction  to this book, we...

  8. Search techniques in intelligent classification systems

    CERN Document Server

    Savchenko, Andrey V

    2016-01-01

    A unified methodology for categorizing various complex objects is presented in this book. Through probability theory, novel asymptotically minimax criteria suitable for practical applications in imaging and data analysis are examined including the special cases such as the Jensen-Shannon divergence and the probabilistic neural network. An optimal approximate nearest neighbor search algorithm, which allows faster classification of databases is featured. Rough set theory, sequential analysis and granular computing are used to improve performance of the hierarchical classifiers. Practical examples in face identification (including deep neural networks), isolated commands recognition in voice control system and classification of visemes captured by the Kinect depth camera are included. This approach creates fast and accurate search procedures by using exact probability densities of applied dissimilarity measures. This book can be used as a guide for independent study and as supplementary material for a technicall...

  9. An analysis of network traffic classification for botnet detection

    DEFF Research Database (Denmark)

    Stevanovic, Matija; Pedersen, Jens Myrup

    2015-01-01

    Botnets represent one of the most serious threats to the Internet security today. This paper explores how can network traffic classification be used for accurate and efficient identification of botnet network activity at local and enterprise networks. The paper examines the effectiveness of detec...... to the optimization of traffic analysis and the correlation of findings from the three analysis methods in order to identify compromised hosts within the network.......Botnets represent one of the most serious threats to the Internet security today. This paper explores how can network traffic classification be used for accurate and efficient identification of botnet network activity at local and enterprise networks. The paper examines the effectiveness...... of detecting botnet network traffic using three methods that target protocols widely considered as the main carriers of botnet Command and Control (C&C) and attack traffic, i.e. TCP, UDP and DNS. We propose three traffic classification methods based on capable Random Forests classifier. The proposed methods...

  10. Application of fuzzy classification in modern primary dental care

    Directory of Open Access Journals (Sweden)

    Yauheni Veryha

    2005-03-01

    Full Text Available This paper describes a framework for implementing fuzzy classifications in primary dental care services. Dental practices aim to provide the highest quality services for their patients. To achieve this, it is important that dentists are able to obtain patients' opinions about their experiences in the dental practice and are able to accurately evaluate this. We propose the use of fuzzy classification to combine various assessment criteria into one general measure to assess patients' satisfaction with primary dental care services. The proposed framework can be used in conventional dental practice information systems and easily integrated with those already used. The benefits of using the proposed fuzzy classification approach include more flexible and accurate analysis of patients' feedback, combining verbal and numeric data. To confirm our theory, a prototype was developed based on the Microsoft TM SQL Server database management system for two criteria used in dental practices, namely making an appointment with a dentist and waiting time for dental care services.

  11. Refinements in Sarcoma Classification in the Current 2013 World Health Organization Classification of Tumours of Soft Tissue and Bone.

    Science.gov (United States)

    Jo, Vickie Y; Doyle, Leona A

    2016-10-01

    The fourth edition of the World Health Organization (WHO) Classification of Tumours of Soft Tissue and Bone was published in February 2013. The 2013 WHO volume provides an updated classification scheme and reproducible diagnostic criteria, which are based on recent clinicopathologic studies and genetic and molecular data that facilitated refined definition of established tumor types, recognition of novel entities, and the development of novel diagnostic markers. This article reviews updates and changes in the classification of bone and soft tissue tumors from the 2002 volume. PMID:27591490

  12. Information gathering for CLP classification

    Directory of Open Access Journals (Sweden)

    Ida Marcello

    2011-01-01

    Full Text Available Regulation 1272/2008 includes provisions for two types of classification: harmonised classification and self-classification. The harmonised classification of substances is decided at Community level and a list of harmonised classifications is included in the Annex VI of the classification, labelling and packaging Regulation (CLP. If a chemical substance is not included in the harmonised classification list it must be self-classified, based on available information, according to the requirements of Annex I of the CLP Regulation. CLP appoints that the harmonised classification will be performed for carcinogenic, mutagenic or toxic to reproduction substances (CMR substances and for respiratory sensitisers category 1 and for other hazard classes on a case-by-case basis. The first step of classification is the gathering of available and relevant information. This paper presents the procedure for gathering information and to obtain data. The data quality is also discussed.

  13. The paradox of atheoretical classification

    DEFF Research Database (Denmark)

    Hjørland, Birger

    2016-01-01

    A distinction can be made between “artificial classifications” and “natural classifications,” where artificial classifications may adequately serve some limited purposes, but natural classifications are overall most fruitful by allowing inference and thus many different purposes. There is strong...... support for the view that a natural classification should be based on a theory (and, of course, that the most fruitful theory provides the most fruitful classification). Nevertheless, atheoretical (or “descriptive”) classifications are often produced. Paradoxically, atheoretical classifications may...... be very successful. The best example of a successful “atheoretical” classification is probably the prestigious Diagnostic and Statistical Manual of Mental Disorders (DSM) since its third edition from 1980. Based on such successes one may ask: Should the claim that classifications ideally are natural...

  14. Sound classification of dwellings

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2012-01-01

    National schemes for sound classification of dwellings exist in more than ten countries in Europe, typically published as national standards. The schemes define quality classes reflecting different levels of acoustical comfort. Main criteria concern airborne and impact sound insulation between....... Descriptors, range of quality levels, number of quality classes, class intervals, denotations and descriptions vary across Europe. The diversity is an obstacle for exchange of experience about constructions fulfilling different classes, implying also trade barriers. Thus, a harmonized classification scheme...... is needed, and a European COST Action TU0901 "Integrating and Harmonizing Sound Insulation Aspects in Sustainable Urban Housing Constructions", has been established and runs 2009-2013, one of the main objectives being to prepare a proposal for a European sound classification scheme with a number of quality...

  15. Bosniak Classification system

    DEFF Research Database (Denmark)

    Graumann, Ole; Osther, Susanne Sloth; Karstoft, Jens;

    2014-01-01

    Background: The Bosniak classification is a diagnostic tool for the differentiation of cystic changes in the kidney. The process of categorizing renal cysts may be challenging, involving a series of decisions that may affect the final diagnosis and clinical outcome such as surgical management....... Purpose: To investigate the inter- and intra-observer agreement among experienced uroradiologists when categorizing complex renal cysts according to the Bosniak classification. Material and Methods: The original categories of 100 cystic renal masses were chosen as “Gold Standard” (GS), established...... to the calculated weighted κ all readers performed “very good” for both inter-observer and intra-observer variation. Most variation was seen in cysts catagorized as Bosniak II, IIF, and III. These results show that radiologists who evaluate complex renal cysts routinely may apply the Bosniak classification...

  16. Bosniak classification system

    DEFF Research Database (Denmark)

    Graumann, Ole; Osther, Susanne Sloth; Karstoft, Jens;

    2016-01-01

    BACKGROUND: The Bosniak classification was originally based on computed tomographic (CT) findings. Magnetic resonance (MR) and contrast-enhanced ultrasonography (CEUS) imaging may demonstrate findings that are not depicted at CT, and there may not always be a clear correlation between the findings...... at MR and CEUS imaging and those at CT. PURPOSE: To compare diagnostic accuracy of MR, CEUS, and CT when categorizing complex renal cystic masses according to the Bosniak classification. MATERIAL AND METHODS: From February 2011 to June 2012, 46 complex renal cysts were prospectively evaluated by three...... readers. Each mass was categorized according to the Bosniak classification and CT was chosen as gold standard. Kappa was calculated for diagnostic accuracy and data was compared with pathological results. RESULTS: CT images found 27 BII, six BIIF, seven BIII, and six BIV. Forty-three cysts could...

  17. Classification problem in CBIR

    Directory of Open Access Journals (Sweden)

    Tatiana Jaworska

    2013-04-01

    Full Text Available At present a great deal of research is being done in different aspects of Content-Based Im-age Retrieval (CBIR. Image classification is one of the most important tasks in image re-trieval that must be dealt with. The primary issue we have addressed is: how can the fuzzy set theory be used to handle crisp image data. We propose fuzzy rule-based classification of image objects. To achieve this goal we have built fuzzy rule-based classifiers for crisp data. In this paper we present the results of fuzzy rule-based classification in our CBIR. Further-more, these results are used to construct a search engine taking into account data mining.

  18. Vertebral fracture classification

    Science.gov (United States)

    de Bruijne, Marleen; Pettersen, Paola C.; Tankó, László B.; Nielsen, Mads

    2007-03-01

    A novel method for classification and quantification of vertebral fractures from X-ray images is presented. Using pairwise conditional shape models trained on a set of healthy spines, the most likely unfractured shape is estimated for each of the vertebrae in the image. The difference between the true shape and the reconstructed normal shape is an indicator for the shape abnormality. A statistical classification scheme with the two shapes as features is applied to detect, classify, and grade various types of deformities. In contrast with the current (semi-)quantitative grading strategies this method takes the full shape into account, it uses a patient-specific reference by combining population-based information on biological variation in vertebra shape and vertebra interrelations, and it provides a continuous measure of deformity. Good agreement with manual classification and grading is demonstrated on 204 lateral spine radiographs with in total 89 fractures.

  19. Accurate studies on dissociation energies of diatomic molecules

    Institute of Scientific and Technical Information of China (English)

    SUN; WeiGuo; FAN; QunChao

    2007-01-01

    The molecular dissociation energies of some electronic states of hydride and N2 molecules were studied using a parameter-free analytical formula suggested in this study and the algebraic method (AM) proposed recently. The results show that the accurate AM dissociation energies DeAM agree excellently with experimental dissociation energies Deexpt, and that the dissociation energy of an electronic state such as the 23△g state of 7Li2 whose experimental value is not available can be predicted using the new formula.

  20. POPULAR MOLECULAR MARKERS IN BACTERIA

    OpenAIRE

    Weilong, Liu; Lv, Li; MD. ASADUZZAMAN KHAN AND FEIZHOU ZHU

    2012-01-01

    Molecular markers are defined as the fragments of DNA sequence associated with a genome, which are used to identify a particular DNA sequence. Nowadays, with the explosive growth of genetic research and bacterial classification, molecular marker is an important tool to identify bacterial species. Taking account to its significant roles in clinic, medicine and food industry, in this review article, we summarize the traditional research and new development about molecular markers (also called g...

  1. A Classification of Feminist Theories

    Directory of Open Access Journals (Sweden)

    Karen Wendling

    2008-09-01

    Full Text Available In this paper I criticize Alison Jaggar’s descriptions of feminist political theories. I propose an alternative classification of feminist theories that I think more accurately reflects the multiplication of feminist theories and philosophies. There are two main categories, “street theory” and academic theories, each with two sub-divisions, political spectrum and “differences” under street theory, and directly and indirectly political analyses under academic theories. My view explains why there are no radical feminists outside of North America and why there are so few socialist feminists inside North America. I argue, controversially, that radical feminism is a radical version of liberalism. I argue that “difference” feminist theories – theory by and about feminists of colour, queer feminists, feminists with disabilities and so on – belong in a separate sub-category of street theory, because they’ve had profound effects on feminist activism not tracked by traditional left-to-right classifications. Finally, I argue that, while academic feminist theories such as feminist existentialism or feminist sociological theory are generally unconnected to movement activism, they provide important feminist insights that may become importantby showing the advantages of my classification over Jaggar’s views. Une analyse critique de la description des théories politiques féministes révèle qu’une classification alternative à celle de Jaggar permettrait de répertorier plus adéquatement les différents courants féministes qui ont évolués au cours des dernières décennies. La nouvelle cartographie que nous proposons comprend deux familles de féminisme : activiste et académique. Cette nouvelle manière de localiser et situer les féminismes aide à comprendre pourquoi il n’y a pas de féminisme radical à l’extérieur de l’Amérique du Nord et aussi pourquoi il y a si peu de féministes socialistes en Amérique du Nord

  2. Classification problem in CBIR

    OpenAIRE

    Tatiana Jaworska

    2013-01-01

    At present a great deal of research is being done in different aspects of Content-Based Im-age Retrieval (CBIR). Image classification is one of the most important tasks in image re-trieval that must be dealt with. The primary issue we have addressed is: how can the fuzzy set theory be used to handle crisp image data. We propose fuzzy rule-based classification of image objects. To achieve this goal we have built fuzzy rule-based classifiers for crisp data. In this paper we present the results ...

  3. Classification des rongeurs

    OpenAIRE

    Mignon, Jacques; Hardouin, Jacques

    2003-01-01

    Les lecteurs du Bulletin BEDIM semblent parfois avoir des difficultés avec la classification scientifique des animaux connus comme "rongeurs" dans le langage courant. Vu les querelles existant encore aujourd'hui dans la mise en place de cette classification, nous ne nous en étonnerons guère. La brève synthèse qui suit concerne les animaux faisant ou susceptibles de faire partie du mini-élevage. The note aims at providing the main characteristics of the principal families of rodents relevan...

  4. Acoustic classification of dwellings

    DEFF Research Database (Denmark)

    Berardi, Umberto; Rasmussen, Birgit

    2014-01-01

    insulation performance, national schemes for sound classification of dwellings have been developed in several European countries. These schemes define acoustic classes according to different levels of sound insulation. Due to the lack of coordination among countries, a significant diversity in terms...... of descriptors, number of classes, and class intervals occurred between national schemes. However, a proposal “acoustic classification scheme for dwellings” has been developed recently in the European COST Action TU0901 with 32 member countries. This proposal has been accepted as an ISO work item. This paper...

  5. Minimum Error Entropy Classification

    CERN Document Server

    Marques de Sá, Joaquim P; Santos, Jorge M F; Alexandre, Luís A

    2013-01-01

    This book explains the minimum error entropy (MEE) concept applied to data classification machines. Theoretical results on the inner workings of the MEE concept, in its application to solving a variety of classification problems, are presented in the wider realm of risk functionals. Researchers and practitioners also find in the book a detailed presentation of practical data classifiers using MEE. These include multi‐layer perceptrons, recurrent neural networks, complexvalued neural networks, modular neural networks, and decision trees. A clustering algorithm using a MEE‐like concept is also presented. Examples, tests, evaluation experiments and comparison with similar machines using classic approaches, complement the descriptions.

  6. Classification of syringomyelia.

    Science.gov (United States)

    Milhorat, T H

    2000-01-01

    Syringomyelia poses special challenges for the clinician because of its complex symptomatology, uncertain pathogenesis, and multiple options of treatment. The purpose of this study was to classify intramedullary cavities according to their most salient pathological and clinical features. Pathological findings obtained in 175 individuals with tubular cavitations of the spinal cord were correlated with clinical and magnetic resonance (MR) imaging findings in a database of 927 patients. A classification system was developed in which the morbid anatomy, cause, and pathogenesis of these lesions are emphasized. The use of a disease-based classification of syringomyelia facilitates diagnosis and the interpretation of MR imaging findings and provides a guide to treatment. PMID:16676921

  7. Laboratory Building for Accurate Determination of Plutonium

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    <正>The accurate determination of plutonium is one of the most important assay techniques of nuclear fuel, also the key of the chemical measurement transfer and the base of the nuclear material balance. An

  8. Ensemble polarimetric SAR image classification based on contextual sparse representation

    Science.gov (United States)

    Zhang, Lamei; Wang, Xiao; Zou, Bin; Qiao, Zhijun

    2016-05-01

    Polarimetric SAR image interpretation has become one of the most interesting topics, in which the construction of the reasonable and effective technique of image classification is of key importance. Sparse representation represents the data using the most succinct sparse atoms of the over-complete dictionary and the advantages of sparse representation also have been confirmed in the field of PolSAR classification. However, it is not perfect, like the ordinary classifier, at different aspects. So ensemble learning is introduced to improve the issue, which makes a plurality of different learners training and obtained the integrated results by combining the individual learner to get more accurate and ideal learning results. Therefore, this paper presents a polarimetric SAR image classification method based on the ensemble learning of sparse representation to achieve the optimal classification.

  9. Land Cover Classification Using ALOS Imagery For Penang, Malaysia

    International Nuclear Information System (INIS)

    This paper presents the potential of integrating optical and radar remote sensing data to improve automatic land cover mapping. The analysis involved standard image processing, and consists of spectral signature extraction and application of a statistical decision rule to identify land cover categories. A maximum likelihood classifier is utilized to determine different land cover categories. Ground reference data from sites throughout the study area are collected for training and validation. The land cover information was extracted from the digital data using PCI Geomatica 10.3.2 software package. The variations in classification accuracy due to a number of radar imaging processing techniques are studied. The relationship between the processing window and the land classification is also investigated. The classification accuracies from the optical and radar feature combinations are studied. Our research finds that fusion of radar and optical significantly improved classification accuracies. This study indicates that the land cover/use can be mapped accurately by using this approach

  10. A Syntactic Classification based Web Page Ranking Algorithm

    CERN Document Server

    Mukhopadhyay, Debajyoti; Kim, Young-Chon

    2011-01-01

    The existing search engines sometimes give unsatisfactory search result for lack of any categorization of search result. If there is some means to know the preference of user about the search result and rank pages according to that preference, the result will be more useful and accurate to the user. In the present paper a web page ranking algorithm is being proposed based on syntactic classification of web pages. Syntactic Classification does not bother about the meaning of the content of a web page. The proposed approach mainly consists of three steps: select some properties of web pages based on user's demand, measure them, and give different weightage to each property during ranking for different types of pages. The existence of syntactic classification is supported by running fuzzy c-means algorithm and neural network classification on a set of web pages. The change in ranking for difference in type of pages but for same query string is also being demonstrated.

  11. Spectral classification using convolutional neural networks

    CERN Document Server

    Hála, Pavel

    2014-01-01

    There is a great need for accurate and autonomous spectral classification methods in astrophysics. This thesis is about training a convolutional neural network (ConvNet) to recognize an object class (quasar, star or galaxy) from one-dimension spectra only. Author developed several scripts and C programs for datasets preparation, preprocessing and postprocessing of the data. EBLearn library (developed by Pierre Sermanet and Yann LeCun) was used to create ConvNets. Application on dataset of more than 60000 spectra yielded success rate of nearly 95%. This thesis conclusively proved great potential of convolutional neural networks and deep learning methods in astrophysics.

  12. Classification of neocortical interneurons using affinity propagation

    Science.gov (United States)

    Santana, Roberto; McGarry, Laura M.; Bielza, Concha; Larrañaga, Pedro; Yuste, Rafael

    2013-01-01

    In spite of over a century of research on cortical circuits, it is still unknown how many classes of cortical neurons exist. In fact, neuronal classification is a difficult problem because it is unclear how to designate a neuronal cell class and what are the best characteristics to define them. Recently, unsupervised classifications using cluster analysis based on morphological, physiological, or molecular characteristics, have provided quantitative and unbiased identification of distinct neuronal subtypes, when applied to selected datasets. However, better and more robust classification methods are needed for increasingly complex and larger datasets. Here, we explored the use of affinity propagation, a recently developed unsupervised classification algorithm imported from machine learning, which gives a representative example or exemplar for each cluster. As a case study, we applied affinity propagation to a test dataset of 337 interneurons belonging to four subtypes, previously identified based on morphological and physiological characteristics. We found that affinity propagation correctly classified most of the neurons in a blind, non-supervised manner. Affinity propagation outperformed Ward's method, a current standard clustering approach, in classifying the neurons into 4 subtypes. Affinity propagation could therefore be used in future studies to validly classify neurons, as a first step to help reverse engineer neural circuits. PMID:24348339

  13. Classification of neocortical interneurons using affinity propagation

    Directory of Open Access Journals (Sweden)

    Roberto eSantana

    2013-12-01

    Full Text Available In spite of over a century of research on cortical circuits, it is still unknown how many classes of cortical neurons exist. Neuronal classification has been a difficult problem because it is unclear what a neuronal cell class actually is and what are the best characteristics are to define them. Recently, unsupervised classifications using cluster analysis based on morphological, physiological or molecular characteristics, when applied to selected datasets, have provided quantitative and unbiased identification of distinct neuronal subtypes. However, better and more robust classification methods are needed for increasingly complex and larger datasets. We explored the use of affinity propagation, a recently developed unsupervised classification algorithm imported from machine learning, which gives a representative example or exemplar for each cluster. As a case study, we applied affinity propagation to a test dataset of 337 interneurons belonging to four subtypes, previously identified based on morphological and physiological characteristics. We found that affinity propagation correctly classified most of the neurons in a blind, non-supervised manner. In fact, using a combined anatomical/physiological dataset, our algorithm differentiated parvalbumin from somatostatin interneurons in 49 out of 50 cases. Affinity propagation could therefore be used in future studies to validly classify neurons, as a first step to help reverse engineer neural circuits.

  14. Application of kernel functions for accurate similarity search in large chemical databases

    OpenAIRE

    2010-01-01

    Background Similaritysearch in chemical structure databases is an important problem with many applications in chemical genomics, drug design, and efficient chemical probe screening among others. It is widely believed that structure based methods provide an efficient way to do the query. Recently various graph kernel functions have been designed to capture the intrinsic similarity of graphs. Though successful in constructing accurate predictive and classification models, graph kernel functions...

  15. Improved Surgical Site Infection (SSI) rate through accurately assessed surgical wounds

    OpenAIRE

    John, Honeymol; Nimeri, Abdelrahman; Ellahham, Samer

    2015-01-01

    Sheikh Khalifa Medical City's (SKMC) Surgery Institute was identified as a high outlier in Surgical Site Infections (SSI) based on the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) - Semi-Annual Report (SAR) in January 2012. The aim of this project was to improve SSI rates through accurate wound classification. We identified SSI rate reduction as a performance improvement and safety priority at SKMC, a tertiary referral center. We used the American Col...

  16. A method for accurate, non-destructive diagnosis of congenital heart defects from heart specimens

    OpenAIRE

    Schleich, Jean-Marc; Abdulla, Tariq; Houyel, Lucile; Paul, Jean-François; Summers, Ron; Dillenseger, Jean-Louis

    2013-01-01

    International audience The accurate analysis of congenital heart defect (CHD) specimens is often difficult and up to now required the opening of the heart. The objective of this study is to define a non-destructive method that allows for the precise analysis of each specimen and its different cardiac components in order to improve classification of the defect and thus provide an indication of underpinning causal mechanisms. We propose a method in which the heart volume is acquired by a CT ...

  17. Validation and Classification of Web Services using Equalization Validation Classification

    Directory of Open Access Journals (Sweden)

    ALAMELU MUTHUKRISHNAN

    2012-12-01

    Full Text Available In the business process world, web services present a managed and middleware to connect huge number of services. Web service transaction is a mechanism to compose services with their desired quality parameters. If enormous transactions occur, the provider could not acquire the accurate data at the correct time. So it is necessary to reduce the overburden of web service t ransactions. In order to reduce the excess of transactions form customers to providers, this paper propose a new method called Equalization Validation Classification. This method introduces a new weight - reducing algorithm called Efficient Trim Down algorit hm to reduce the overburden of the incoming client requests. When this proposed algorithm is compared with Decision tree algorithms of (J48, Random Tree, Random Forest, AD Tree it produces a better accuracy and Validation than the existing algorithms. The proposed trimming method was analyzed with the Decision tree algorithms and the results implementation shows that the ETD algorithm provides better performance in terms of improved accuracy with Effective Validation. Therefore, the proposed method provide s a good gateway to reduce the overburden of the client requests in web services. Moreover analyzing the requests arrived from a vast number of clients and preventing the illegitimate requests save the service provider time

  18. Sandwich classification theorem

    Directory of Open Access Journals (Sweden)

    Alexey Stepanov

    2015-09-01

    Full Text Available The present note arises from the author's talk at the conference ``Ischia Group Theory 2014''. For subgroups FleN of a group G denote by Lat(F,N the set of all subgroups of N , containing F . Let D be a subgroup of G . In this note we study the lattice LL=Lat(D,G and the lattice LL ′ of subgroups of G , normalized by D . We say that LL satisfies sandwich classification theorem if LL splits into a disjoint union of sandwiches Lat(F,N G (F over all subgroups F such that the normal closure of D in F coincides with F . Here N G (F denotes the normalizer of F in G . A similar notion of sandwich classification is introduced for the lattice LL ′ . If D is perfect, i.,e. coincides with its commutator subgroup, then it turns out that sandwich classification theorem for LL and LL ′ are equivalent. We also show how to find basic subroup F of sandwiches for LL ′ and review sandwich classification theorems in algebraic groups over rings.

  19. Dynamic Latent Classification Model

    DEFF Research Database (Denmark)

    Zhong, Shengtong; Martínez, Ana M.; Nielsen, Thomas Dyhre;

    as possible. Motivated by this problem setting, we propose a generative model for dynamic classification in continuous domains. At each time point the model can be seen as combining a naive Bayes model with a mixture of factor analyzers (FA). The latent variables of the FA are used to capture the dynamics...

  20. Classifications in popular music

    NARCIS (Netherlands)

    A. van Venrooij; V. Schmutz

    2015-01-01

    The categorical system of popular music, such as genre categories, is a highly differentiated and dynamic classification system. In this article we present work that studies different aspects of these categorical systems in popular music. Following the work of Paul DiMaggio, we focus on four questio

  1. Classification of waste packages

    Energy Technology Data Exchange (ETDEWEB)

    Mueller, H.P.; Sauer, M.; Rojahn, T. [Versuchsatomkraftwerk GmbH, Kahl am Main (Germany)

    2001-07-01

    A barrel gamma scanning unit has been in use at the VAK for the classification of radioactive waste materials since 1998. The unit provides the facility operator with the data required for classification of waste barrels. Once these data have been entered into the AVK data processing system, the radiological status of raw waste as well as pre-treated and processed waste can be tracked from the point of origin to the point at which the waste is delivered to a final storage. Since the barrel gamma scanning unit was commissioned in 1998, approximately 900 barrels have been measured and the relevant data required for classification collected and analyzed. Based on the positive results of experience in the use of the mobile barrel gamma scanning unit, the VAK now offers the classification of barrels as a service to external users. Depending upon waste quantity accumulation, this measurement unit offers facility operators a reliable and time-saving and cost-effective means of identifying and documenting the radioactivity inventory of barrels scheduled for final storage. (orig.)

  2. Improving Student Question Classification

    Science.gov (United States)

    Heiner, Cecily; Zachary, Joseph L.

    2009-01-01

    Students in introductory programming classes often articulate their questions and information needs incompletely. Consequently, the automatic classification of student questions to provide automated tutorial responses is a challenging problem. This paper analyzes 411 questions from an introductory Java programming course by reducing the natural…

  3. Nearest convex hull classification

    NARCIS (Netherlands)

    G.I. Nalbantov (Georgi); P.J.F. Groenen (Patrick); J.C. Bioch (Cor)

    2006-01-01

    textabstractConsider the classification task of assigning a test object to one of two or more possible groups, or classes. An intuitive way to proceed is to assign the object to that class, to which the distance is minimal. As a distance measure to a class, we propose here to use the distance to the

  4. Classification system: Netherlands

    NARCIS (Netherlands)

    Hartemink, A.E.

    2006-01-01

    Although people have always classified soils, it is only since the mid 19th century that soil classification emerged as an important topic within soil science. It forced soil scientists to think systematically about soils and its genesis and developed to facilitate communication between soil scienti

  5. Shark Teeth Classification

    Science.gov (United States)

    Brown, Tom; Creel, Sally; Lee, Velda

    2009-01-01

    On a recent autumn afternoon at Harmony Leland Elementary in Mableton, Georgia, students in a fifth-grade science class investigated the essential process of classification--the act of putting things into groups according to some common characteristics or attributes. While they may have honed these skills earlier in the week by grouping their own…

  6. The Classification Conundrum.

    Science.gov (United States)

    Granger, Charles R.

    1983-01-01

    Argues against the five-kingdom scheme of classification as using inconsistent criteria, ending up with divisions that are forced, not natural. Advocates an approach using cell type/complexity and modification of the metabolic machinery, recommending the five-kingdom scheme as starting point for class discussion on taxonomy and its conceptual…

  7. Changing Histopathological Diagnostics by Genome-Based Tumor Classification

    Directory of Open Access Journals (Sweden)

    Michael Kloth

    2014-05-01

    Full Text Available Traditionally, tumors are classified by histopathological criteria, i.e., based on their specific morphological appearances. Consequently, current therapeutic decisions in oncology are strongly influenced by histology rather than underlying molecular or genomic aberrations. The increase of information on molecular changes however, enabled by the Human Genome Project and the International Cancer Genome Consortium as well as the manifold advances in molecular biology and high-throughput sequencing techniques, inaugurated the integration of genomic information into disease classification. Furthermore, in some cases it became evident that former classifications needed major revision and adaption. Such adaptations are often required by understanding the pathogenesis of a disease from a specific molecular alteration, using this molecular driver for targeted and highly effective therapies. Altogether, reclassifications should lead to higher information content of the underlying diagnoses, reflecting their molecular pathogenesis and resulting in optimized and individual therapeutic decisions. The objective of this article is to summarize some particularly important examples of genome-based classification approaches and associated therapeutic concepts. In addition to reviewing disease specific markers, we focus on potentially therapeutic or predictive markers and the relevance of molecular diagnostics in disease monitoring.

  8. Many accurate small-discriminatory feature subsets exist in microarray transcript data: biomarker discovery

    Directory of Open Access Journals (Sweden)

    Grate Leslie R

    2005-04-01

    Full Text Available Abstract Background Molecular profiling generates abundance measurements for thousands of gene transcripts in biological samples such as normal and tumor tissues (data points. Given such two-class high-dimensional data, many methods have been proposed for classifying data points into one of the two classes. However, finding very small sets of features able to correctly classify the data is problematic as the fundamental mathematical proposition is hard. Existing methods can find "small" feature sets, but give no hint how close this is to the true minimum size. Without fundamental mathematical advances, finding true minimum-size sets will remain elusive, and more importantly for the microarray community there will be no methods for finding them. Results We use the brute force approach of exhaustive search through all genes, gene pairs (and for some data sets gene triples. Each unique gene combination is analyzed with a few-parameter linear-hyperplane classification method looking for those combinations that form training error-free classifiers. All 10 published data sets studied are found to contain predictive small feature sets. Four contain thousands of gene pairs and 6 have single genes that perfectly discriminate. Conclusion This technique discovered small sets of genes (3 or less in published data that form accurate classifiers, yet were not reported in the prior publications. This could be a common characteristic of microarray data, thus making looking for them worth the computational cost. Such small gene sets could indicate biomarkers and portend simple medical diagnostic tests. We recommend checking for small gene sets routinely. We find 4 gene pairs and many gene triples in the large hepatocellular carcinoma (HCC, Liver cancer data set of Chen et al. The key component of these is the "placental gene of unknown function", PLAC8. Our HMM modeling indicates PLAC8 might have a domain like part of lP59's crystal structure (a Non

  9. Machine learning of parameters for accurate semiempirical quantum chemical calculations

    International Nuclear Information System (INIS)

    We investigate possible improvements in the accuracy of semiempirical quantum chemistry (SQC) methods through the use of machine learning (ML) models for the parameters. For a given class of compounds, ML techniques require sufficiently large training sets to develop ML models that can be used for adapting SQC parameters to reflect changes in molecular composition and geometry. The ML-SQC approach allows the automatic tuning of SQC parameters for individual molecules, thereby improving the accuracy without deteriorating transferability to molecules with molecular descriptors very different from those in the training set. The performance of this approach is demonstrated for the semiempirical OM2 method using a set of 6095 constitutional isomers C7H10O2, for which accurate ab initio atomization enthalpies are available. The ML-OM2 results show improved average accuracy and a much reduced error range compared with those of standard OM2 results, with mean absolute errors in atomization enthalpies dropping from 6.3 to 1.7 kcal/mol. They are also found to be superior to the results from specific OM2 reparameterizations (rOM2) for the same set of isomers. The ML-SQC approach thus holds promise for fast and reasonably accurate high-throughput screening of materials and molecules

  10. Invariant Image Watermarking Using Accurate Zernike Moments

    Directory of Open Access Journals (Sweden)

    Ismail A. Ismail

    2010-01-01

    Full Text Available problem statement: Digital image watermarking is the most popular method for image authentication, copyright protection and content description. Zernike moments are the most widely used moments in image processing and pattern recognition. The magnitudes of Zernike moments are rotation invariant so they can be used just as a watermark signal or be further modified to carry embedded data. The computed Zernike moments in Cartesian coordinate are not accurate due to geometrical and numerical error. Approach: In this study, we employed a robust image-watermarking algorithm using accurate Zernike moments. These moments are computed in polar coordinate, where both approximation and geometric errors are removed. Accurate Zernike moments are used in image watermarking and proved to be robust against different kind of geometric attacks. The performance of the proposed algorithm is evaluated using standard images. Results: Experimental results show that, accurate Zernike moments achieve higher degree of robustness than those approximated ones against rotation, scaling, flipping, shearing and affine transformation. Conclusion: By computing accurate Zernike moments, the embedded bits watermark can be extracted at low error rate.

  11. Etiologic Classification in Ischemic Stroke

    OpenAIRE

    Hakan Ay

    2011-01-01

    Ischemic stroke is an etiologically heterogenous disorder. Classification of ischemic stroke etiology into categories with discrete phenotypic, therapeutic, and prognostic features is indispensible to generate consistent information from stroke research. In addition, a functional classification of stroke etiology is critical to ensure unity among physicians and comparability among studies. There are two major approaches to etiologic classification in stroke. Phenotypic systems define subtypes...

  12. Sequence Classification: 890247 [

    Lifescience Database Archive (English)

    Full Text Available cient and accurate synthesis of DNA opposite cyclobutane pyrimidine dimers; homolog of human POLH and bacterial DinB proteins; Rad30p || http://www.ncbi.nlm.nih.gov/protein/6320627 ...

  13. Accurate tracking control in LOM application

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    The fabrication of accurate prototype from CAD model directly in short time depends on the accurate tracking control and reference trajectory planning in (Laminated Object Manufacture) LOM application. An improvement on contour accuracy is acquired by the introduction of a tracking controller and a trajectory generation policy. A model of the X-Y positioning system of LOM machine is developed as the design basis of tracking controller. The ZPETC (Zero Phase Error Tracking Controller) is used to eliminate single axis following error, thus reduce the contour error. The simulation is developed on a Maltab model based on a retrofitted LOM machine and the satisfied result is acquired.

  14. Ground-Level Classification of a Coral Reef Using a Hyperspectral Camera

    Directory of Open Access Journals (Sweden)

    Tamir Caras

    2015-06-01

    Full Text Available Especially in the remote sensing context, thematic classification is a desired product for coral reef surveys. This study presents a novel statistical-based image classification approach, namely Partial Least Square Discriminant Analysis (PLS-DA, capable of doing so. Three classification models were built and implemented for the images while the fourth was a combination of spectra from all three images together. The classification was optimised by using pre-processing transformations (PPTs and post-classification low-pass filtering. Despite the fact that the images were acquired under different conditions and quality, the best classification model was achieved by combining spectral training samples from three images (accuracy 0.63 for all classes. PPTs improved the classification accuracy by 5%–15% and post-classification treatments further increased the final accuracy by 10%–20%. The fourth classification model was the most accurate one, suggesting that combining spectra from differ conditions improves thematic classification. Despite some limitations, available aerial sensors already provide an opportunity to implement the described classification and mark the next investigation step. Nonetheless, the findings of this study are relevant both to the field of remote sensing in general and to the niche of coral reef spectroscopy.

  15. Fast Image Texture Classification Using Decision Trees

    Science.gov (United States)

    Thompson, David R.

    2011-01-01

    Texture analysis would permit improved autonomous, onboard science data interpretation for adaptive navigation, sampling, and downlink decisions. These analyses would assist with terrain analysis and instrument placement in both macroscopic and microscopic image data products. Unfortunately, most state-of-the-art texture analysis demands computationally expensive convolutions of filters involving many floating-point operations. This makes them infeasible for radiation- hardened computers and spaceflight hardware. A new method approximates traditional texture classification of each image pixel with a fast decision-tree classifier. The classifier uses image features derived from simple filtering operations involving integer arithmetic. The texture analysis method is therefore amenable to implementation on FPGA (field-programmable gate array) hardware. Image features based on the "integral image" transform produce descriptive and efficient texture descriptors. Training the decision tree on a set of training data yields a classification scheme that produces reasonable approximations of optimal "texton" analysis at a fraction of the computational cost. A decision-tree learning algorithm employing the traditional k-means criterion of inter-cluster variance is used to learn tree structure from training data. The result is an efficient and accurate summary of surface morphology in images. This work is an evolutionary advance that unites several previous algorithms (k-means clustering, integral images, decision trees) and applies them to a new problem domain (morphology analysis for autonomous science during remote exploration). Advantages include order-of-magnitude improvements in runtime, feasibility for FPGA hardware, and significant improvements in texture classification accuracy.

  16. Nominated Texture Based Cervical Cancer Classification

    Directory of Open Access Journals (Sweden)

    Edwin Jayasingh Mariarputham

    2015-01-01

    Full Text Available Accurate classification of Pap smear images becomes the challenging task in medical image processing. This can be improved in two ways. One way is by selecting suitable well defined specific features and the other is by selecting the best classifier. This paper presents a nominated texture based cervical cancer (NTCC classification system which classifies the Pap smear images into any one of the seven classes. This can be achieved by extracting well defined texture features and selecting best classifier. Seven sets of texture features (24 features are extracted which include relative size of nucleus and cytoplasm, dynamic range and first four moments of intensities of nucleus and cytoplasm, relative displacement of nucleus within the cytoplasm, gray level cooccurrence matrix, local binary pattern histogram, tamura features, and edge orientation histogram. Few types of support vector machine (SVM and neural network (NN classifiers are used for the classification. The performance of the NTCC algorithm is tested and compared to other algorithms on public image database of Herlev University Hospital, Denmark, with 917 Pap smear images. The output of SVM is found to be best for the most of the classes and better results for the remaining classes.

  17. BIOPHARMACEUTICAL CLASSIFICATION SYSTEM AND BIOWAVER: AN OVERVIEW

    Directory of Open Access Journals (Sweden)

    Puranik Prashant K

    2011-05-01

    Full Text Available The biopharmaceutical classification system (BCS has been developed to provide a scientific approach for classifying drug compounds based on solubility as related to dose and intestinal permeability in combination with the dissolution properties of the oral immediate release dosage form. BCS is to provide a regulatory tool for replacing certain bioequivalence (BE studies by accurate in vitro dissolution tests. This review gives three dimensionless numbers which are used in BCS are absorption number, dissolution number, dose number.Biowaver is an important tool for formulation development. Bioavailability (BA and BE play a central role in pharmaceutical product development, and BE studies are presently being conducted for New Drug Applications (NDAs of new compounds, in supplementary NDAs for new medical indications and product line extensions, in Abbreviated New Drug Applications (ANDAs of generic products, and in applications for scale-up and post-approval changes. The principles of the BCS classification system can be applied to NDA and ANDA approvals as well as to scale-up and post approval changes in drug manufacturing. BCS classification can therefore save pharmaceutical companies a significant amount in development time and reduce costs. The aim of the present review is to present the status of BCS and discuss its future application in pharmaceutical product development.

  18. Soil Classification Using GATree

    CERN Document Server

    Bhargavi, P

    2010-01-01

    This paper details the application of a genetic programming framework for classification of decision tree of Soil data to classify soil texture. The database contains measurements of soil profile data. We have applied GATree for generating classification decision tree. GATree is a decision tree builder that is based on Genetic Algorithms (GAs). The idea behind it is rather simple but powerful. Instead of using statistic metrics that are biased towards specific trees we use a more flexible, global metric of tree quality that try to optimize accuracy and size. GATree offers some unique features not to be found in any other tree inducers while at the same time it can produce better results for many difficult problems. Experimental results are presented which illustrate the performance of generating best decision tree for classifying soil texture for soil data set.

  19. Multilingual documentation and classification.

    Science.gov (United States)

    Donnelly, Kevin

    2008-01-01

    Health care providers around the world have used classification systems for decades as a basis for documentation, communications, statistical reporting, reimbursement and research. In more recent years machine-readable medical terminologies have taken on greater importance with the adoption of electronic health records and the need for greater granularity of data in clinical systems. Use of a clinical terminology harmonised with classifications, implemented within a clinical information system, will enable the delivery of many patient health benefits including electronic clinical decision support, disease screening and enhanced patient safety. In order to be usable these systems must be translated into the language of use, without losing meaning. It is evident that today one system cannot meet all requirements which call for collaboration and harmonisation in order to achieve true interoperability on a multilingual basis.

  20. Automated, high accuracy classification of Parkinsonian disorders: a pattern recognition approach.

    Directory of Open Access Journals (Sweden)

    Andre F Marquand

    Full Text Available Progressive supranuclear palsy (PSP, multiple system atrophy (MSA and idiopathic Parkinson's disease (IPD can be clinically indistinguishable, especially in the early stages, despite distinct patterns of molecular pathology. Structural neuroimaging holds promise for providing objective biomarkers for discriminating these diseases at the single subject level but all studies to date have reported incomplete separation of disease groups. In this study, we employed multi-class pattern recognition to assess the value of anatomical patterns derived from a widely available structural neuroimaging sequence for automated classification of these disorders. To achieve this, 17 patients with PSP, 14 with IPD and 19 with MSA were scanned using structural MRI along with 19 healthy controls (HCs. An advanced probabilistic pattern recognition approach was employed to evaluate the diagnostic value of several pre-defined anatomical patterns for discriminating the disorders, including: (i a subcortical motor network; (ii each of its component regions and (iii the whole brain. All disease groups could be discriminated simultaneously with high accuracy using the subcortical motor network. The region providing the most accurate predictions overall was the midbrain/brainstem, which discriminated all disease groups from one another and from HCs. The subcortical network also produced more accurate predictions than the whole brain and all of its constituent regions. PSP was accurately predicted from the midbrain/brainstem, cerebellum and all basal ganglia compartments; MSA from the midbrain/brainstem and cerebellum and IPD from the midbrain/brainstem only. This study demonstrates that automated analysis of structural MRI can accurately predict diagnosis in individual patients with Parkinsonian disorders, and identifies distinct patterns of regional atrophy particularly useful for this process.

  1. Subphenotyping and Classification of Orofacial Clefts: Need for Orofacial Cleft Subphenotyping Calls for Revised Classification.

    Science.gov (United States)

    McBride, W A; McIntyre, G T; Carroll, K; Mossey, P A

    2016-09-01

    Nonsyndromic orofacial clefting (OFC) describes a range of phenotypes that represent the most common craniofacial birth defects in humans, with an overall birth prevalence of 1:700 live births. Because of the lifelong negative implications on health and well-being associated with OFC and the numbers of people affected, quality research into its etiology, diagnosis, treatment outcomes, and preventative strategies is essential. A range of different methods is used for recording and classifying OFC subphenotypes, one of which is the International Classification of Diseases (ICD) system. However, there is a general perception that research is being hampered by a lack of sensitivity and specificity in grouping those with OFC into subphenotypes, with potential heterogeneity and confounding in epidemiologic, genetic, and genotype-phenotype correlation studies. This article provides a background to the necessity of OFC research, discusses current controversies within cleft subphenotyping, and provides a brief overview of current OFC classifications as well as their limitations. The LAHSHAL classification is described in the context of a potentially useful tool for OFC that could complement the ICD-10/ICD-11 Beta coding systems to become a simply understood, universally accepted, clinically friendly, and research-sensitive instrument. Empowering registries, clinicians, and researchers to use a common classification system would have significant implications for OFC research across the world at a time when accurate subphenotyping is crucial and health care research is becoming increasingly tailored toward the individual. PMID:26171570

  2. Classification of nanopolymers

    Energy Technology Data Exchange (ETDEWEB)

    Larena, A; Tur, A [Department of Chemical Industrial Engineering and Environment, Universidad Politecnica de Madrid, E.T.S. Ingenieros Industriales, C/ Jose Gutierrez Abascal, Madrid (Spain); Baranauskas, V [Faculdade de Engenharia Eletrica e Computacao, Departamento de Semicondutores, Instrumentos e Fotonica, Universidade Estadual de Campinas, UNICAMP, Av. Albert Einstein N.400, 13 083-852 Campinas SP Brasil (Brazil)], E-mail: alarena@etsii.upm.es

    2008-03-15

    Nanopolymers with different structures, shapes, and functional forms have recently been prepared using several techniques. Nanopolymers are the most promising basic building blocks for mounting complex and simple hierarchical nanosystems. The applications of nanopolymers are extremely broad and polymer-based nanotechnologies are fast emerging. We propose a nanopolymer classification scheme based on self-assembled structures, non self-assembled structures, and on the number of dimensions in the nanometer range (nD)

  3. Qatar content classification

    OpenAIRE

    Handosa, Mohamed

    2014-01-01

    Short title: Qatar content classification. Long title: Develop methods and software for classifying Arabic texts into a taxonomy using machine learning. Contact person and their contact information: Tarek Kanan, . Project description: Starting 4/1/2012, and running through 12/31/2015, is a project to advance digital libraries in the country of Qatar. This is led by VT, but also involves Penn State, Texas A&M, and Qatar University. Tarek is a GRA on this effort. His di...

  4. Evolvement of Classification Society

    Institute of Scientific and Technical Information of China (English)

    Xu Hua

    2011-01-01

    As an independent industry, the emergence of the classification society was perhaps the demand of beneficial interests between shipowners, cargo owners and insurers at the earliest time. Today, as an indispensable link of the international maritime industry, class role has changed fundamentally. Start off from the demand of the insurersSeaborne trade, transport and insurance industries began to emerge successively in the 17th century. The massive risk and benefit brought by seaborne transport provided a difficult problem to insurers.

  5. Estuary Classification Revisited

    OpenAIRE

    Guha, Anirban; Lawrence, Gregory A.

    2012-01-01

    This paper presents the governing equations of a tidally-averaged, width-averaged, rectangular estuary in completely nondimensionalized forms. Subsequently, we discover that the dynamics of an estuary is entirely controlled by only two variables: (i) the Estuarine Froude number, and (ii) a nondimensional number related to the Estuarine Aspect ratio and the Tidal Froude number. Motivated by this new observation, the problem of estuary classification is re-investigated. Our analysis shows that ...

  6. Classification of myocardial infarction

    DEFF Research Database (Denmark)

    Saaby, Lotte; Poulsen, Tina Svenstrup; Hosbond, Susanne Elisabeth;

    2013-01-01

    The classification of myocardial infarction into 5 types was introduced in 2007 as an important component of the universal definition. In contrast to the plaque rupture-related type 1 myocardial infarction, type 2 myocardial infarction is considered to be caused by an imbalance between demand...... and supply of oxygen in the myocardium. However, no specific criteria for type 2 myocardial infarction have been established....

  7. Accurate atomic data for industrial plasma applications

    Energy Technology Data Exchange (ETDEWEB)

    Griesmann, U.; Bridges, J.M.; Roberts, J.R.; Wiese, W.L.; Fuhr, J.R. [National Inst. of Standards and Technology, Gaithersburg, MD (United States)

    1997-12-31

    Reliable branching fraction, transition probability and transition wavelength data for radiative dipole transitions of atoms and ions in plasma are important in many industrial applications. Optical plasma diagnostics and modeling of the radiation transport in electrical discharge plasmas (e.g. in electrical lighting) depend on accurate basic atomic data. NIST has an ongoing experimental research program to provide accurate atomic data for radiative transitions. The new NIST UV-vis-IR high resolution Fourier transform spectrometer has become an excellent tool for accurate and efficient measurements of numerous transition wavelengths and branching fractions in a wide wavelength range. Recently, the authors have also begun to employ photon counting techniques for very accurate measurements of branching fractions of weaker spectral lines with the intent to improve the overall accuracy for experimental branching fractions to better than 5%. They have now completed their studies of transition probabilities of Ne I and Ne II. The results agree well with recent calculations and for the first time provide reliable transition probabilities for many weak intercombination lines.

  8. Energy functions for protein design I: Efficient and accurate continuum electrostatics and solvation

    OpenAIRE

    Pokala, Navin; Handel, Tracy M.

    2004-01-01

    Electrostatics and solvation energies are important for defining protein stability, structural specificity, and molecular recognition. Because these energies are difficult to compute quickly and accurately, they are often ignored or modeled very crudely in computational protein design. To address this problem, we have developed a simple, fast, and accurate approximation for calculating Born radii in the context of protein design calculations. When these approximate Born radii are used with th...

  9. Short Text Classification: A Survey

    Directory of Open Access Journals (Sweden)

    Ge Song

    2014-05-01

    Full Text Available With the recent explosive growth of e-commerce and online communication, a new genre of text, short text, has been extensively applied in many areas. So many researches focus on short text mining. It is a challenge to classify the short text owing to its natural characters, such as sparseness, large-scale, immediacy, non-standardization. It is difficult for traditional methods to deal with short text classification mainly because too limited words in short text cannot represent the feature space and the relationship between words and documents. Several researches and reviews on text classification are shown in recent times. However, only a few of researches focus on short text classification. This paper discusses the characters of short text and the difficulty of short text classification. Then we introduce the existing popular works on short text classifiers and models, including short text classification using sematic analysis, semi-supervised short text classification, ensemble short text classification, and real-time classification. The evaluations of short text classification are analyzed in our paper. Finally we summarize the existing classification technology and prospect for development trend of short text classification

  10. Classification of Meteorological Drought

    Institute of Scientific and Technical Information of China (English)

    Zhang Qiang; Zou Xukai; Xiao Fengjin; Lu Houquan; Liu Haibo; Zhu Changhan; An Shunqing

    2011-01-01

    Background The national standard of the Classification of Meteorological Drought (GB/T 20481-2006) was developed by the National Climate Center in cooperation with Chinese Academy of Meteorological Sciences,National Meteorological Centre and Department of Forecasting and Disaster Mitigation under the China Meteorological Administration (CMA),and was formally released and implemented in November 2006.In 2008,this Standard won the second prize of the China Standard Innovation and Contribution Awards issued by SAC.Developed through independent innovation,it is the first national standard published to monitor meteorological drought disaster and the first standard in China and around the world specifying the classification of drought.Since its release in 2006,the national standard of Classification of Meteorological Drought has been used by CMA as the operational index to monitor and drought assess,and gradually used by provincial meteorological sureaus,and applied to the drought early warning release standard in the Methods of Release and Propagation of Meteorological Disaster Early Warning Signal.

  11. Maximum mutual information regularized classification

    KAUST Repository

    Wang, Jim Jing-Yan

    2014-09-07

    In this paper, a novel pattern classification approach is proposed by regularizing the classifier learning to maximize mutual information between the classification response and the true class label. We argue that, with the learned classifier, the uncertainty of the true class label of a data sample should be reduced by knowing its classification response as much as possible. The reduced uncertainty is measured by the mutual information between the classification response and the true class label. To this end, when learning a linear classifier, we propose to maximize the mutual information between classification responses and true class labels of training samples, besides minimizing the classification error and reducing the classifier complexity. An objective function is constructed by modeling mutual information with entropy estimation, and it is optimized by a gradient descend method in an iterative algorithm. Experiments on two real world pattern classification problems show the significant improvements achieved by maximum mutual information regularization.

  12. Sequence Classification: 398797 [

    Lifescience Database Archive (English)

    Full Text Available Non-TMB TMH TMB TMB TMB Non-TMB >gi|15609513|ref|NP_216892.1| LOW MOLECULAR WEIGHT ...ANTIGEN CFP2 (LOW MOLECULAR WEIGHT PROTEIN ANTIGEN 2) (CFP-2) || http://www.ncbi.nlm.nih.gov/protein/15609513 ...

  13. Sequence Classification: 389042 [

    Lifescience Database Archive (English)

    Full Text Available Non-TMB TMH TMB TMB TMB Non-TMB >gi|31793553|ref|NP_856046.1| LOW MOLECULAR WEIGHT ...ANTIGEN CFP2 (LOW MOLECULAR WEIGHT PROTEIN ANTIGEN 2) (CFP-2) || http://www.ncbi.nlm.nih.gov/protein/31793553 ...

  14. Application of ant colony optimization in NPP classification fault location

    International Nuclear Information System (INIS)

    Nuclear Power Plant is a highly complex structural system with high safety requirements. Fault location appears to be particularly important to enhance its safety. Ant Colony Optimization is a new type of optimization algorithm, which is used in the fault location and classification of nuclear power plants in this paper. Taking the main coolant system of the first loop as the study object, using VB6.0 programming technology, the NPP fault location system is designed, and is tested against the related data in the literature. Test results show that the ant colony optimization can be used in the accurate classification fault location in the nuclear power plants. (authors)

  15. Molecular epidemiology of Blastocystis

    Directory of Open Access Journals (Sweden)

    Fadime Eroğlu

    2015-12-01

    Full Text Available Blastocystis pathogenicity and classification was newly illuminated with molecular genetic studies and recently the parasite was found in the focus of many researchers. Several molecular methods such as; polymerase chain reaction (PCR, PCR-restriction fragment length polymorphism, random amplified polymorphic DNA, real-time polymerase chain reaction and DNA sequencing analyses can be used in genotyping of Blastocystis. Blastocystis parasites may cause diarrhea, abdominal pain, bloating, gas, irritability, anorexia, cramps, vomiting, dehydration, insomnia, nausea, loss of appetite, weight loss, fatigue symptoms and also could be asymptomatic cases. In this review, it was aimed to summarize the associations between Blastocystis subtypes and pathogenicity.

  16. Polarimetric Synthetic Aperture Radar Image Classification by a Hybrid Method

    Institute of Scientific and Technical Information of China (English)

    Kamran Ullah Khan; YANG Jian

    2007-01-01

    Different methods proposed so far for accurate classification of land cover types in polarimetric synthetic aperture radar (SAR) image are data specific and no general method is available. A novel hybrid framework for this classification was developed in this work. A set of effective features derived from the coherence matrix of polarimetric SARdata was proposed.Constituents of the feature set are wavelet,texture,and nonlinear features.The proposed feature set has a strong discrimination power. A neural network was used as the classification engine in a unique way. By exploiting the speed of the conjugate gradient method and the convergence rate of the Levenberg-Marquardt method (near the optimal point), an overall speed up of the classification procedure was achieved. Principal component analysis(PCA)was used to shrink the dimension of the feature vector without sacrificing much of the classification accuracy. The proposed approach is compared with the maximum likelihood estimator (MLE)based on the complex Wishart distribution and the results show the superiority of the proposed method,with the average classification accuracy by the proposed method(95.4%)higher than that of the MLE(93.77%). Use of PCA to reduce the dimensionality of the feature vector helps reduce the memory requirements and computational cost, thereby enhancing the speed of the process.

  17. Exploiting multi-context analysis in semantic image classification

    Institute of Scientific and Technical Information of China (English)

    TIAN Yong-hong; HUANG Tie-jun; GAO Wen

    2005-01-01

    As the popularity of digital images is rapidly increasing on the Internet, research on technologies for semantic image classification has become an important research topic. However, the well-known content-based image classification methods do not overcome the so-called semantic gap problem in which low-level visual features cannot represent the high-level semantic content of images. Image classification using visual and textual information often performs poorly since the extracted textual features are often too limited to accurately represent the images. In this paper, we propose a semantic image classification approach using multi-context analysis. For a given image, we model the relevant textual information as its multi-modal context, and regard the related images connected by hyperlinks as its link context. Two kinds of context analysis models, i.e., cross-modal correlation analysis and link-based correlation model, are used to capture the correlation among different modals of features and the topical dependency among images induced by the link structure. We propose a new collective classification model called relational support vector classifier (RSVC) based on the well-known Support Vector Machines (SVMs) and the link-based correlation model. Experiments showed that the proposed approach significantly improved classification accuracy over that of SVM classifiers using visual and/or textual features.

  18. Producing Accurate Stereographic Images with a Flashlight and Layers of Glass: A Source for Stereopsis via Slides or Overhead Projection.

    Science.gov (United States)

    Strauss, Michael J.; Levine, Shellie H.

    1985-01-01

    Describes an extremely simple technique (using only Dreiding or Framework molecular models, a flashlight, small sheets of glass, and a piece of cardboard) which produces extremely accurate line drawings of stereoscopic images. Advantages of using the system are noted. (JN)

  19. The European Clinical, Molecular, and Pathological (ECMP) Criteria and the 2007/2008 Revisions of the World Health Organization for the Diagnosis, Classification, and Staging of Prefibrotic Myeloproliferative Neoplasms Carrying the JAK2V617F Mutation

    OpenAIRE

    Jan Jacques Michiels; Fibo Ten Kate; Lam, King H.; Wilfried Schroyens; Zwi Berneman; Hendrik De Raeve

    2014-01-01

    OBJECTIVE: The prefibrotic stages of JAK2V617F essential thrombocythemia (ET) and JAK2V617F polycythemia vera (PV) can easily be diagnosed clinically without use of bone marrow biopsy histology. We assessed the 2008 WHO and European Clinical, Molecular, and Pathological (ECMP) criteria for the diagnosis of myeloproliferative neoplasms (MPNs). METHODS: Studied patients included 6 JAK2V617F-mutated ET and 4 PV patients during long-term follow-up in view of critical analysis of the literature...

  20. Resear ch on the correlation of breas t cancer molecular classification with the expression of GST-πand Topo-Ⅱbeofre and after neoadjuvant chemotherapy%乳腺癌分子分型与新辅助化疗前后GST-π和Topo-Ⅱ表达的相关性研究

    Institute of Scientific and Technical Information of China (English)

    张艳霞; 马东华; 孙冬霞; 李军澎; 骆向利; 石晓鹏

    2015-01-01

    Objective It is to investigate the correlation of breast cancer molecular classification with the expression of GST-πand Topo-Ⅱbefore and after neoadjuvant chemotherapy.Methods 155 patients with breast cancer were selected to carry on the molecular classification, the expression of GST-πand Topo-Ⅱwere detected by using immunohistochemical de-tection EnVison ldpe-g-nvp in patients with different parting, and the data were analyzed combining the pathological fea-tures.Results The expression of GST-πin HER2 expression type and Basal-like type was higher than LuminalA and Lumi-nalB type (all P0.05).There was no significant correlation between the expression of GST-πin patients with different parting and neoadjuvant chemotherapy curative effect ( P>0.05) , but the To-po-II expression in different classification was related to the curative effect of neoadjuvant chemotherapy in patients with difference parting (P<0.05 ).Conclusion The expression of GST-πin breast cancer has no significant correlation with neo-adjuvant chemotherapy curative effect, but the Topo-Ⅱexpression in different classification is related to the curative effect of neoadjuvant chemotherapy in patients with difference parting.The expression of Topo-Ⅱ can help to judge the prognosis of breast cancer and provide basis for the selection of drug.%目的:探讨乳腺癌不同分子分型与新辅助化疗前后GST-π和Topo-Ⅱ表达的相关性。方法对155例乳腺癌患者进行分子分型,采用免疫组织化学EnVison二步法检测不同分型患者GST-π和Topo-Ⅱ表达情况,并结合病理特点进行分析。结果 HER2过表达型及Basal-like型GST-π表达率高于Luminal A 型和Luminal B 型(P均<0.05)。HER2过表达型及Basal-like型Topo-Ⅱ表达率低于Luminal A型和Luminal B型,但差异无统计学意义( P均>0.05)。不同分型患者GST-π表达情况与患者新辅助化疗疗效之间无明显相关性(P>0.05

  1. Feedback about more accurate versus less accurate trials: differential effects on self-confidence and activation.

    Science.gov (United States)

    Badami, Rokhsareh; VaezMousavi, Mohammad; Wulf, Gabriele; Namazizadeh, Mahdi

    2012-06-01

    One purpose of the present study was to examine whether self-confidence or anxiety would be differentially affected byfeedback from more accurate rather than less accurate trials. The second purpose was to determine whether arousal variations (activation) would predict performance. On day 1, participants performed a golf putting task under one of two conditions: one group received feedback on the most accurate trials, whereas another group received feedback on the least accurate trials. On day 2, participants completed an anxiety questionnaire and performed a retention test. Shin conductance level, as a measure of arousal, was determined. The results indicated that feedback about more accurate trials resulted in more effective learning as well as increased self-confidence. Also, activation was a predictor of performance. PMID:22808705

  2. LABEL: fast and accurate lineage assignment with assessment of H5N1 and H9N2 influenza A hemagglutinins.

    Directory of Open Access Journals (Sweden)

    Samuel S Shepard

    Full Text Available The evolutionary classification of influenza genes into lineages is a first step in understanding their molecular epidemiology and can inform the subsequent implementation of control measures. We introduce a novel approach called Lineage Assignment By Extended Learning (LABEL to rapidly determine cladistic information for any number of genes without the need for time-consuming sequence alignment, phylogenetic tree construction, or manual annotation. Instead, LABEL relies on hidden Markov model profiles and support vector machine training to hierarchically classify gene sequences by their similarity to pre-defined lineages. We assessed LABEL by analyzing the annotated hemagglutinin genes of highly pathogenic (H5N1 and low pathogenicity (H9N2 avian influenza A viruses. Using the WHO/FAO/OIE H5N1 evolution working group nomenclature, the LABEL pipeline quickly and accurately identified the H5 lineages of uncharacterized sequences. Moreover, we developed an updated clade nomenclature for the H9 hemagglutinin gene and show a similarly fast and reliable phylogenetic assessment with LABEL. While this study was focused on hemagglutinin sequences, LABEL could be applied to the analysis of any gene and shows great potential to guide molecular epidemiology activities, accelerate database annotation, and provide a data sorting tool for other large-scale bioinformatic studies.

  3. Accurate estimation of indoor travel times

    DEFF Research Database (Denmark)

    Prentow, Thor Siiger; Blunck, Henrik; Stisen, Allan;

    2014-01-01

    are collected within the building complex. Results indicate that InTraTime is superior with respect to metrics such as deployment cost, maintenance cost and estimation accuracy, yielding an average deviation from actual travel times of 11.7 %. This accuracy was achieved despite using a minimal-effort setup......The ability to accurately estimate indoor travel times is crucial for enabling improvements within application areas such as indoor navigation, logistics for mobile workers, and facility management. In this paper, we study the challenges inherent in indoor travel time estimation, and we propose...... the InTraTime method for accurately estimating indoor travel times via mining of historical and real-time indoor position traces. The method learns during operation both travel routes, travel times and their respective likelihood---both for routes traveled as well as for sub-routes thereof. In...

  4. Accurate guitar tuning by cochlear implant musicians.

    Directory of Open Access Journals (Sweden)

    Thomas Lu

    Full Text Available Modern cochlear implant (CI users understand speech but find difficulty in music appreciation due to poor pitch perception. Still, some deaf musicians continue to perform with their CI. Here we show unexpected results that CI musicians can reliably tune a guitar by CI alone and, under controlled conditions, match simultaneously presented tones to <0.5 Hz. One subject had normal contralateral hearing and produced more accurate tuning with CI than his normal ear. To understand these counterintuitive findings, we presented tones sequentially and found that tuning error was larger at ∼ 30 Hz for both subjects. A third subject, a non-musician CI user with normal contralateral hearing, showed similar trends in performance between CI and normal hearing ears but with less precision. This difference, along with electric analysis, showed that accurate tuning was achieved by listening to beats rather than discriminating pitch, effectively turning a spectral task into a temporal discrimination task.

  5. Accurate Finite Difference Methods for Option Pricing

    OpenAIRE

    Persson, Jonas

    2006-01-01

    Stock options are priced numerically using space- and time-adaptive finite difference methods. European options on one and several underlying assets are considered. These are priced with adaptive numerical algorithms including a second order method and a more accurate method. For American options we use the adaptive technique to price options on one stock with and without stochastic volatility. In all these methods emphasis is put on the control of errors to fulfill predefined tolerance level...

  6. Accurate variational forms for multiskyrmion configurations

    Energy Technology Data Exchange (ETDEWEB)

    Jackson, A.D.; Weiss, C.; Wirzba, A.; Lande, A.

    1989-04-17

    Simple variational forms are suggested for the fields of a single skyrmion on a hypersphere, S/sub 3/(L), and of a face-centered cubic array of skyrmions in flat space, R/sub 3/. The resulting energies are accurate at the level of 0.2%. These approximate field configurations provide a useful alternative to brute-force solutions of the corresponding Euler equations.

  7. Efficient Accurate Context-Sensitive Anomaly Detection

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    For program behavior-based anomaly detection, the only way to ensure accurate monitoring is to construct an efficient and precise program behavior model. A new program behavior-based anomaly detection model,called combined pushdown automaton (CPDA) model was proposed, which is based on static binary executable analysis. The CPDA model incorporates the optimized call stack walk and code instrumentation technique to gain complete context information. Thereby the proposed method can detect more attacks, while retaining good performance.

  8. Fast and Accurate Large-Scale Detection of β-Lactamase Genes Conferring Antibiotic Resistance

    OpenAIRE

    Lee, Jae Jin; Lee, Jung Hun; Kwon, Dae Beom; Jeon, Jeong Ho; Park, Kwang Seung; Lee, Chang-Ro; Lee, Sang Hee

    2015-01-01

    Fast detection of β-lactamase (bla) genes allows improved surveillance studies and infection control measures, which can minimize the spread of antibiotic resistance. Although several molecular diagnostic methods have been developed to detect limited bla gene types, these methods have significant limitations, such as their failure to detect almost all clinically available bla genes. We developed a fast and accurate molecular method to overcome these limitations using 62 primer pairs, which we...

  9. Biomarker Selection and Classification of “-Omics” Data Using a Two-Step Bayes Classification Framework

    Directory of Open Access Journals (Sweden)

    Anunchai Assawamakin

    2013-01-01

    Full Text Available Identification of suitable biomarkers for accurate prediction of phenotypic outcomes is a goal for personalized medicine. However, current machine learning approaches are either too complex or perform poorly. Here, a novel two-step machine-learning framework is presented to address this need. First, a Naïve Bayes estimator is used to rank features from which the top-ranked will most likely contain the most informative features for prediction of the underlying biological classes. The top-ranked features are then used in a Hidden Naïve Bayes classifier to construct a classification prediction model from these filtered attributes. In order to obtain the minimum set of the most informative biomarkers, the bottom-ranked features are successively removed from the Naïve Bayes-filtered feature list one at a time, and the classification accuracy of the Hidden Naïve Bayes classifier is checked for each pruned feature set. The performance of the proposed two-step Bayes classification framework was tested on different types of -omics datasets including gene expression microarray, single nucleotide polymorphism microarray (SNParray, and surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF proteomic data. The proposed two-step Bayes classification framework was equal to and, in some cases, outperformed other classification methods in terms of prediction accuracy, minimum number of classification markers, and computational time.

  10. Classification of LiDAR Data with Point Based Classification Methods

    Science.gov (United States)

    Yastikli, N.; Cetin, Z.

    2016-06-01

    LiDAR is one of the most effective systems for 3 dimensional (3D) data collection in wide areas. Nowadays, airborne LiDAR data is used frequently in various applications such as object extraction, 3D modelling, change detection and revision of maps with increasing point density and accuracy. The classification of the LiDAR points is the first step of LiDAR data processing chain and should be handled in proper way since the 3D city modelling, building extraction, DEM generation, etc. applications directly use the classified point clouds. The different classification methods can be seen in recent researches and most of researches work with the gridded LiDAR point cloud. In grid based data processing of the LiDAR data, the characteristic point loss in the LiDAR point cloud especially vegetation and buildings or losing height accuracy during the interpolation stage are inevitable. In this case, the possible solution is the use of the raw point cloud data for classification to avoid data and accuracy loss in gridding process. In this study, the point based classification possibilities of the LiDAR point cloud is investigated to obtain more accurate classes. The automatic point based approaches, which are based on hierarchical rules, have been proposed to achieve ground, building and vegetation classes using the raw LiDAR point cloud data. In proposed approaches, every single LiDAR point is analyzed according to their features such as height, multi-return, etc. then automatically assigned to the class which they belong to. The use of un-gridded point cloud in proposed point based classification process helped the determination of more realistic rule sets. The detailed parameter analyses have been performed to obtain the most appropriate parameters in the rule sets to achieve accurate classes. The hierarchical rule sets were created for proposed Approach 1 (using selected spatial-based and echo-based features) and Approach 2 (using only selected spatial-based features

  11. On the Classification of Psychology in General Library Classification Schemes.

    Science.gov (United States)

    Soudek, Miluse

    1980-01-01

    Holds that traditional library classification systems are inadequate to handle psychological literature, and advocates the establishment of new theoretical approaches to bibliographic organization. (FM)

  12. Remote Sensing Classification Uncertainty: Validating Probabilistic Pixel Level Classification

    Science.gov (United States)

    Vrettas, Michail; Cornford, Dan; Bastin, Lucy; Pons, Xavier; Sevillano, Eva; Moré, Gerard; Serra, Pere; Ninyerola, Miquel

    2013-04-01

    There already exists an extensive literature on classification of remotely sensed imagery, and indeed classification more widely, that considers a wide range of probabilistic and non-probabilistic classification methodologies. Although for many probabilistic classification methodologies posterior class probabilities are produced per pixel (observation) these are often not communicated at the pixel level, and typically not validated at the pixel level. Most often the probabilistic classification in converted into a hard classification (of the most probable class) and the accuracy of the resulting classification is reported in terms of a global confusion matrix, or some score derived from this. For applications where classification accuracy is spatially variable and where pixel level estimates of uncertainty can be meaningfully exploited in workflows that propagate uncertainty validating and communicating the pixel level uncertainty opens opportunities for more refined and accountable modelling. In this work we describe our recent work applying and validation of a range of probabilistic classifiers. Using a multi-temporal Landsat data set of the Ebro Delta in Catalonia, which has been carefully radiometrically and geometrically corrected, we present a range of Bayesian classifiers from simple Bayesian linear discriminant analysis to a complex variational Gaussian process based classifier. Field study derived labelled data, classified into 8 classes, which primarily consider land use and the degree of flooding in what is a rice growing region, are used to train the pixel level classifiers. Our focus is not so much on the classification accuracy, but rather the validation of the probabilistic classification made by all methods. We present a range of validation plots and scores, many of which are used for probabilistic weather forecast verification, but are new to remote sensing classification including of course the standard measures of misclassification, but also

  13. Data cache organization for accurate timing analysis

    DEFF Research Database (Denmark)

    Schoeberl, Martin; Huber, Benedikt; Puffitsch, Wolfgang

    2013-01-01

    different data areas, such as stack, global data, and heap allocated data, share the same cache. Some addresses are known statically, other addresses are only known at runtime. With a standard cache organization all those different data areas must be considered by worst-case execution time analysis......Caches are essential to bridge the gap between the high latency main memory and the fast processor pipeline. Standard processor architectures implement two first-level caches to avoid a structural hazard in the pipeline: an instruction cache and a data cache. For tight worst-case execution times...... it is important to classify memory accesses as either cache hit or cache miss. The addresses of instruction fetches are known statically and static cache hit/miss classification is possible for the instruction cache. The access to data that is cached in the data cache is harder to predict statically. Several...

  14. High Frequency QRS ECG Accurately Detects Cardiomyopathy

    Science.gov (United States)

    Schlegel, Todd T.; Arenare, Brian; Poulin, Gregory; Moser, Daniel R.; Delgado, Reynolds

    2005-01-01

    High frequency (HF, 150-250 Hz) analysis over the entire QRS interval of the ECG is more sensitive than conventional ECG for detecting myocardial ischemia. However, the accuracy of HF QRS ECG for detecting cardiomyopathy is unknown. We obtained simultaneous resting conventional and HF QRS 12-lead ECGs in 66 patients with cardiomyopathy (EF = 23.2 plus or minus 6.l%, mean plus or minus SD) and in 66 age- and gender-matched healthy controls using PC-based ECG software recently developed at NASA. The single most accurate ECG parameter for detecting cardiomyopathy was an HF QRS morphological score that takes into consideration the total number and severity of reduced amplitude zones (RAZs) present plus the clustering of RAZs together in contiguous leads. This RAZ score had an area under the receiver operator curve (ROC) of 0.91, and was 88% sensitive, 82% specific and 85% accurate for identifying cardiomyopathy at optimum score cut-off of 140 points. Although conventional ECG parameters such as the QRS and QTc intervals were also significantly longer in patients than controls (P less than 0.001, BBBs excluded), these conventional parameters were less accurate (area under the ROC = 0.77 and 0.77, respectively) than HF QRS morphological parameters for identifying underlying cardiomyopathy. The total amplitude of the HF QRS complexes, as measured by summed root mean square voltages (RMSVs), also differed between patients and controls (33.8 plus or minus 11.5 vs. 41.5 plus or minus 13.6 mV, respectively, P less than 0.003), but this parameter was even less accurate in distinguishing the two groups (area under ROC = 0.67) than the HF QRS morphologic and conventional ECG parameters. Diagnostic accuracy was optimal (86%) when the RAZ score from the HF QRS ECG and the QTc interval from the conventional ECG were used simultaneously with cut-offs of greater than or equal to 40 points and greater than or equal to 445 ms, respectively. In conclusion 12-lead HF QRS ECG employing

  15. Relationship between the expression of Ki-67 and molecular classification and clinical patho-logical features in breast cancer%Ki-67表达与乳腺癌分子分型及临床病理特征的关系

    Institute of Scientific and Technical Information of China (English)

    张莹; 任占平; 张芫

    2014-01-01

    目的:观察不同分子亚型乳腺癌中Ki-67的表达及其与乳腺癌临床病理特征的关系及意义。方法采用免疫组化En-Vision两步法检测245例乳腺癌组织中ER、PR、HER-2及Ki-67的表达,并比较Ki-67表达与乳腺癌临床病理参数的关系。结果不同分子分型乳腺癌中Ki-67的增殖指数差异有统计学意义( P50岁组的Ki-67增殖指数差异无统计学意义;患者按≤40岁及≥60岁分为年轻组及老年组时,年轻组Ki-67增殖指数明显高于老年组。结论 Ki-67在三阴型乳腺癌、年轻患者、伴腋窝淋巴结转移、肿块较大及ER、PR阴性组中的增殖指数较高。 Ki-67可作为判断乳腺癌预后的重要指标。%Purpose To study the expression of Ki-67 in breast cancer with different molecular classification, and to discuss the rela-tionship between the expression of Ki-67 and clinical pathological features in breast cancer. Methods All 245 patients with breast cancer were divided into different molecular classification through detecting the expression of ER, PR, HER-2 by immunohistochemical method. The expression of Ki-67 was also detected, and to study relationship between the expression and clinical pathological features. Results The difference of Ki-67 index was statistically significant in different molecular classification of breast cancer. Ki-67 index in patients with lymph node metastasis and larger tumor size were higher than that with no metastasis and smaller tumor size. Ki-67 index in patients with ER and PR positive were lower than that negative, the difference was statistically significant. Ki-67 expression differ-ence was not statistically significant between the two groups according to the median age (50 years old). But when patients were divid-ed into young and elderly groups by≤40 and≥60 years old, Ki-67 index in young group was more higher than that in elderly group. Conclusion Ki-67 index in patients with triple-negative breast cancer, young

  16. SPORT FOOD ADDITIVE CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    I. P. Prokopenko

    2015-01-01

    Full Text Available Correctly organized nutritive and pharmacological support is an important component of an athlete's preparation for competitions, an optimal shape maintenance, fast recovery and rehabilitation after traumas and defatigation. Special products of enhanced biological value (BAS for athletes nutrition are used with this purpose. Easy-to-use energy sources are administered into athlete's organism, yielded materials and biologically active substances which regulate and activate exchange reactions which proceed with difficulties during certain physical trainings. The article presents sport supplements classification which can be used before warm-up and trainings, after trainings and in competitions breaks.

  17. Sequence Classification: 893607 [

    Lifescience Database Archive (English)

    Full Text Available ial component of the MIND kinetochore complex (Mtw1p Including Nnf1p-Nsl1p-Dsn1p) which joins kinetochore subunits contact...ing DNA to those contacting microtubules; required for accurate chromosome segregation; Nsl1p || http://www.ncbi.nlm.nih.gov/protein/6325023 ...

  18. Sequence Classification: 894861 [

    Lifescience Database Archive (English)

    Full Text Available ial component of the MIND kinetochore complex (Mtw1p Including Nnf1p-Nsl1p-Dsn1p) which joins kinetochore subunits contact...ing DNA to those contacting microtubules; required for accurate chromosome segregation; Nnf1p || http://www.ncbi.nlm.nih.gov/protein/6322572 ...

  19. Accurate macroscale modelling of spatial dynamics in multiple dimensions

    CERN Document Server

    Roberts, A ~J; Bunder, J ~E

    2011-01-01

    Developments in dynamical systems theory provides new support for the macroscale modelling of pdes and other microscale systems such as Lattice Boltzmann, Monte Carlo or Molecular Dynamics simulators. By systematically resolving subgrid microscale dynamics the dynamical systems approach constructs accurate closures of macroscale discretisations of the microscale system. Here we specifically explore reaction-diffusion problems in two spatial dimensions as a prototype of generic systems in multiple dimensions. Our approach unifies into one the modelling of systems by a type of finite elements, and the `equation free' macroscale modelling of microscale simulators efficiently executing only on small patches of the spatial domain. Centre manifold theory ensures that a closed model exist on the macroscale grid, is emergent, and is systematically approximated. Dividing space either into overlapping finite elements or into spatially separated small patches, the specially crafted inter-element\\slash patch coupling als...

  20. The future of general classification

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2013-01-01

    Discusses problems related to accessing multiple collections using a single retrieval language. Surveys the concepts of interoperability and switching language. Finds that mapping between more indexing languages always will be an approximation. Surveys the issues related to general classification...... and contrasts that to special classifications. Argues for the use of general classifications to provide access to collections nationally and internationally. © 2003 by The Haworth Press, Inc. All rights reserved....

  1. Classification and Labelling for Biocides

    OpenAIRE

    Rubbiani, Maristella

    2015-01-01

    CLP and biocides The EU Regulation (EC) No 1272/2008 on Classification, Labelling and Packaging of Substances and Mixtures, the CLP-Regulation, entered into force on 20th January, 2009. Since 1st December, 2010 the classification, labelling and packaging of substances has to comply with this Regulation. For mixtures, the rules of this Regulation are mandatory from 1st June, 2015; this means that until this date classification, labelling and packaging could either be carried out according to D...

  2. DCC Briefing Paper: Genre classification

    OpenAIRE

    Abbott, Daisy; Kim, Yunhyong

    2008-01-01

    Genre classification is the process of grouping objects together based on defined similarities such as subject, format, style, or purpose. Genre classification as a means of managing information is already established in music (e.g. folk, blues, jazz) and text and is used, alongside topic classification, to organise materials in the commercial sector (the children's section of a bookshop) and intellectually (for example, in the Usenet newsgroup directory hierarchy). However, in the case o...

  3. Random Forests for Poverty Classification

    OpenAIRE

    Ruben Thoplan

    2014-01-01

    This paper applies a relatively novel method in data mining to address the issue of poverty classification in Mauritius. The random forests algorithm is applied to the census data in view of improving classification accuracy for poverty status. The analysis shows that the numbers of hours worked, age, education and sex are the most important variables in the classification of the poverty status of an individual. In addition, a clear poverty-gender gap is identified as women have higher chance...

  4. Clinical research between axillary lymph node metastasis of breast cancer and tumor size and molecular classification%乳腺癌患者腋淋巴结转移与肿瘤大小及分子分型间关系的临床研究

    Institute of Scientific and Technical Information of China (English)

    王锡宏; 马小鹏; 孔源

    2012-01-01

    目的 探讨乳腺癌患者腋窝淋巴结转移与肿瘤分子分型及肿瘤大小的关系.方法回顾性分析246例乳腺癌患者手术方式、有无腋窝淋巴结转移、转移淋巴结数目、肿瘤大小及肿瘤的分子分型.结果 246例乳腺癌患者中,术后病理证实淋巴结转移者108例.其中Luminal A型28例,淋巴结转移4例,转移率14.29%;Luminal B型156例,淋巴结转移92例,转移率58.97%;HER-2阳性型56例,淋巴结转移12例,转移率21.43%;三阴性乳腺癌(Basal-like型)6例,淋巴结均无转移.随肿瘤体积的增大,腋窝淋巴结转移率明显增高.结论乳腺癌患者腋窝淋巴结转移与肿瘤分子分型及肿瘤大小有相关性.%Objective To explore the relationship between axillary lymph nodes metastasis (ALNM) and the tumor size and molecular classification. Methods The clinical data of 246 patients of breast cancer, the surgical methods, and the axillary lymph nodes were retrospectively analysed and discussed. Results 108 cases developed axillary lymph node metastases, 4 of 28 cases in Luminal A had lymph node metastases(58.97%), and 92 of 156 cases in Luminal B had lymph node metastases(21.43%), 6 cases of Basal-like had not lymph node metas- tases. The bigger the tumor, the more metastases of lymph nodes. Conclusion There is relevance between axillary lymph node metastasis of breast cancer and molecular classification and the tumor size.

  5. Decision Fusion Based on Hyperspectral and Multispectral Satellite Imagery for Accurate Forest Species Mapping

    Directory of Open Access Journals (Sweden)

    Dimitris G. Stavrakoudis

    2014-07-01

    Full Text Available This study investigates the effectiveness of combining multispectral very high resolution (VHR and hyperspectral satellite imagery through a decision fusion approach, for accurate forest species mapping. Initially, two fuzzy classifications are conducted, one for each satellite image, using a fuzzy output support vector machine (SVM. The classification result from the hyperspectral image is then resampled to the multispectral’s spatial resolution and the two sources are combined using a simple yet efficient fusion operator. Thus, the complementary information provided from the two sources is effectively exploited, without having to resort to computationally demanding and time-consuming typical data fusion or vector stacking approaches. The effectiveness of the proposed methodology is validated in a complex Mediterranean forest landscape, comprising spectrally similar and spatially intermingled species. The decision fusion scheme resulted in an accuracy increase of 8% compared to the classification using only the multispectral imagery, whereas the increase was even higher compared to the classification using only the hyperspectral satellite image. Perhaps most importantly, its accuracy was significantly higher than alternative multisource fusion approaches, although the latter are characterized by much higher computation, storage, and time requirements.

  6. Fully Automatic System for Accurate Localisation and Analysis of Cephalometric Landmarks in Lateral Cephalograms.

    Science.gov (United States)

    Lindner, Claudia; Wang, Ching-Wei; Huang, Cheng-Ta; Li, Chung-Hsing; Chang, Sheng-Wei; Cootes, Tim F

    2016-01-01

    Cephalometric tracing is a standard analysis tool for orthodontic diagnosis and treatment planning. The aim of this study was to develop and validate a fully automatic landmark annotation (FALA) system for finding cephalometric landmarks in lateral cephalograms and its application to the classification of skeletal malformations. Digital cephalograms of 400 subjects (age range: 7-76 years) were available. All cephalograms had been manually traced by two experienced orthodontists with 19 cephalometric landmarks, and eight clinical parameters had been calculated for each subject. A FALA system to locate the 19 landmarks in lateral cephalograms was developed. The system was evaluated via comparison to the manual tracings, and the automatically located landmarks were used for classification of the clinical parameters. The system achieved an average point-to-point error of 1.2 mm, and 84.7% of landmarks were located within the clinically accepted precision range of 2.0 mm. The automatic landmark localisation performance was within the inter-observer variability between two clinical experts. The automatic classification achieved an average classification accuracy of 83.4% which was comparable to an experienced orthodontist. The FALA system rapidly and accurately locates and analyses cephalometric landmarks in lateral cephalograms, and has the potential to significantly improve the clinical work flow in orthodontic treatment. PMID:27645567

  7. Robust tissue classification for reproducible wound assessment in telemedicine environments

    Science.gov (United States)

    Wannous, Hazem; Treuillet, Sylvie; Lucas, Yves

    2010-04-01

    In telemedicine environments, a standardized and reproducible assessment of wounds, using a simple free-handled digital camera, is an essential requirement. However, to ensure robust tissue classification, particular attention must be paid to the complete design of the color processing chain. We introduce the key steps including color correction, merging of expert labeling, and segmentation-driven classification based on support vector machines. The tool thus developed ensures stability under lighting condition, viewpoint, and camera changes, to achieve accurate and robust classification of skin tissues. Clinical tests demonstrate that such an advanced tool, which forms part of a complete 3-D and color wound assessment system, significantly improves the monitoring of the healing process. It achieves an overlap score of 79.3 against 69.1% for a single expert, after mapping on the medical reference developed from the image labeling by a college of experts.

  8. Classification of Pulse Waveforms Using Edit Distance with Real Penalty

    Directory of Open Access Journals (Sweden)

    Zhang Dongyu

    2010-01-01

    Full Text Available Abstract Advances in sensor and signal processing techniques have provided effective tools for quantitative research in traditional Chinese pulse diagnosis (TCPD. Because of the inevitable intraclass variation of pulse patterns, the automatic classification of pulse waveforms has remained a difficult problem. In this paper, by referring to the edit distance with real penalty (ERP and the recent progress in -nearest neighbors (KNN classifiers, we propose two novel ERP-based KNN classifiers. Taking advantage of the metric property of ERP, we first develop an ERP-induced inner product and a Gaussian ERP kernel, then embed them into difference-weighted KNN classifiers, and finally develop two novel classifiers for pulse waveform classification. The experimental results show that the proposed classifiers are effective for accurate classification of pulse waveform.

  9. AdaBoost for Improved Voice-Band Signal Classification

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    A good voice-band signal classification can not only enable the safe application of speech coding techniques,the implementation of a Digital Signal Interpolation (DSI)system, but also facilitate network administration and planning by providing accurate voice-band traffic analysis.A new method is proposed to detect and classify the presence of various voice-band signals on the General Switched Telephone Network ( GSTN ). The method uses a combination of simple base classifiers through the AdaBoost algorithm. The conventional classification features for voiceband data classification are combined and optimized by the AdaBoost algorithm and spectral subtraction method.Experiments show the simpleness, effectiveness, efficiency and flexibility of the method.

  10. PSC: protein surface classification.

    Science.gov (United States)

    Tseng, Yan Yuan; Li, Wen-Hsiung

    2012-07-01

    We recently proposed to classify proteins by their functional surfaces. Using the structural attributes of functional surfaces, we inferred the pairwise relationships of proteins and constructed an expandable database of protein surface classification (PSC). As the functional surface(s) of a protein is the local region where the protein performs its function, our classification may reflect the functional relationships among proteins. Currently, PSC contains a library of 1974 surface types that include 25,857 functional surfaces identified from 24,170 bound structures. The search tool in PSC empowers users to explore related surfaces that share similar local structures and core functions. Each functional surface is characterized by structural attributes, which are geometric, physicochemical or evolutionary features. The attributes have been normalized as descriptors and integrated to produce a profile for each functional surface in PSC. In addition, binding ligands are recorded for comparisons among homologs. PSC allows users to exploit related binding surfaces to reveal the changes in functionally important residues on homologs that have led to functional divergence during evolution. The substitutions at the key residues of a spatial pattern may determine the functional evolution of a protein. In PSC (http://pocket.uchicago.edu/psc/), a pool of changes in residues on similar functional surfaces is provided.

  11. Cost Sensitive Sequential Classification

    CERN Document Server

    Trapeznikov, Kirill; Castanon, David

    2012-01-01

    In many decision systems, sensing modalities have different acquisition costs. It is often unnecessary to use every sensor to classify a majority of examples. We study a multi-stage system in a prediction time cost reduction setting, where all the modalities are available for training, but for a test example, measurements in a new modality can be acquired at each stage for an additional cost. We seek decision rules to reduce the average acquisition cost. We construct an empirical risk minimization problem (ERM) for a multi-stage reject classifier, wherein the stage $k$ classifier either classifies a sample using only the measurements acquired so far or rejects it to the next stage where more attributes can be acquired for a cost. To solve the ERM problem, we factorize the loss function into classification and rejection decisions. We then transform reject decisions into a binary classification problem. We formulate stage-by-stage global surrogate risk and introduce an iterative algorithm in the boosting framew...

  12. Mimicking human texture classification

    Science.gov (United States)

    van Rikxoort, Eva M.; van den Broek, Egon L.; Schouten, Theo E.

    2005-03-01

    In an attempt to mimic human (colorful) texture classification by a clustering algorithm three lines of research have been encountered, in which as test set 180 texture images (both their color and gray-scale equivalent) were drawn from the OuTex and VisTex databases. First, a k-means algorithm was applied with three feature vectors, based on color/gray values, four texture features, and their combination. Second, 18 participants clustered the images using a newly developed card sorting program. The mutual agreement between the participants was 57% and 56% and between the algorithm and the participants it was 47% and 45%, for respectively color and gray-scale texture images. Third, in a benchmark, 30 participants judged the algorithms' clusters with gray-scale textures as more homogeneous then those with colored textures. However, a high interpersonal variability was present for both the color and the gray-scale clusters. So, despite the promising results, it is questionable whether average human texture classification can be mimicked (if it exists at all).

  13. Holistic facial expression classification

    Science.gov (United States)

    Ghent, John; McDonald, J.

    2005-06-01

    This paper details a procedure for classifying facial expressions. This is a growing and relatively new type of problem within computer vision. One of the fundamental problems when classifying facial expressions in previous approaches is the lack of a consistent method of measuring expression. This paper solves this problem by the computation of the Facial Expression Shape Model (FESM). This statistical model of facial expression is based on an anatomical analysis of facial expression called the Facial Action Coding System (FACS). We use the term Action Unit (AU) to describe a movement of one or more muscles of the face and all expressions can be described using the AU's described by FACS. The shape model is calculated by marking the face with 122 landmark points. We use Principal Component Analysis (PCA) to analyse how the landmark points move with respect to each other and to lower the dimensionality of the problem. Using the FESM in conjunction with Support Vector Machines (SVM) we classify facial expressions. SVMs are a powerful machine learning technique based on optimisation theory. This project is largely concerned with statistical models, machine learning techniques and psychological tools used in the classification of facial expression. This holistic approach to expression classification provides a means for a level of interaction with a computer that is a significant step forward in human-computer interaction.

  14. CLASSIFICATION OF CRIMINAL GROUPS

    Directory of Open Access Journals (Sweden)

    Natalia Romanova

    2013-06-01

    Full Text Available New types of criminal groups are emerging in modern society.  These types have their special criminal subculture. The research objective is to develop new parameters of classification of modern criminal groups, create a new typology of criminal groups and identify some features of their subculture. Research methodology is based on the system approach that includes using the method of analysis of documentary sources (materials of a criminal case, method of conversations with themembers of the criminal group, method of testing the members of the criminal group and method of observation. As a result of the conducted research, we have created a new classification of criminal groups. The first type is a lawful group in its form and criminal according to its content (i.e., its target is criminal enrichment. The second type is a criminal organization which is run by so-called "white-collars" that "remain in the shadow". The third type is traditional criminal groups.  The fourth type is the criminal group, which openly demonstrates its criminal activity.

  15. Accurate measurement of unsteady state fluid temperature

    Science.gov (United States)

    Jaremkiewicz, Magdalena

    2016-07-01

    In this paper, two accurate methods for determining the transient fluid temperature were presented. Measurements were conducted for boiling water since its temperature is known. At the beginning the thermometers are at the ambient temperature and next they are immediately immersed into saturated water. The measurements were carried out with two thermometers of different construction but with the same housing outer diameter equal to 15 mm. One of them is a K-type industrial thermometer widely available commercially. The temperature indicated by the thermometer was corrected considering the thermometers as the first or second order inertia devices. The new design of a thermometer was proposed and also used to measure the temperature of boiling water. Its characteristic feature is a cylinder-shaped housing with the sheath thermocouple located in its center. The temperature of the fluid was determined based on measurements taken in the axis of the solid cylindrical element (housing) using the inverse space marching method. Measurements of the transient temperature of the air flowing through the wind tunnel using the same thermometers were also carried out. The proposed measurement technique provides more accurate results compared with measurements using industrial thermometers in conjunction with simple temperature correction using the inertial thermometer model of the first or second order. By comparing the results, it was demonstrated that the new thermometer allows obtaining the fluid temperature much faster and with higher accuracy in comparison to the industrial thermometer. Accurate measurements of the fast changing fluid temperature are possible due to the low inertia thermometer and fast space marching method applied for solving the inverse heat conduction problem.

  16. Use of manual densitometry in land cover classification

    Science.gov (United States)

    Jordan, D. C.; Graves, D. H.; Hammetter, M. C.

    1978-01-01

    Through use of manual spot densitometry values derived from multitemporal 1:24,000 color infrared aircraft photography, areas as small as one hectare in the Cumberland Plateau in Kentucky were accurately classified into one of eight ground cover groups. If distinguishing between undisturbed and disturbed forest areas is the sole criterion of interest, classification results are highly accurate if based on imagery taken during foliated ground cover conditions. Multiseasonal imagery analysis was superior to single data analysis, and transparencies from prefoliated conditions gave better separation of conifers and hardwoods than did those from foliated conditions.

  17. New law requires 'medically accurate' lesson plans.

    Science.gov (United States)

    1999-09-17

    The California Legislature has passed a bill requiring all textbooks and materials used to teach about AIDS be medically accurate and objective. Statements made within the curriculum must be supported by research conducted in compliance with scientific methods, and published in peer-reviewed journals. Some of the current lesson plans were found to contain scientifically unsupported and biased information. In addition, the bill requires material to be "free of racial, ethnic, or gender biases." The legislation is supported by a wide range of interests, but opposed by the California Right to Life Education Fund, because they believe it discredits abstinence-only material.

  18. Niche Genetic Algorithm with Accurate Optimization Performance

    Institute of Scientific and Technical Information of China (English)

    LIU Jian-hua; YAN De-kun

    2005-01-01

    Based on crowding mechanism, a novel niche genetic algorithm was proposed which can record evolutionary direction dynamically during evolution. After evolution, the solutions's precision can be greatly improved by means of the local searching along the recorded direction. Simulation shows that this algorithm can not only keep population diversity but also find accurate solutions. Although using this method has to take more time compared with the standard GA, it is really worth applying to some cases that have to meet a demand for high solution precision.

  19. Investigations on Accurate Analysis of Microstrip Reflectarrays

    DEFF Research Database (Denmark)

    Zhou, Min; Sørensen, S. B.; Kim, Oleksiy S.;

    2011-01-01

    An investigation on accurate analysis of microstrip reflectarrays is presented. Sources of error in reflectarray analysis are examined and solutions to these issues are proposed. The focus is on two sources of error, namely the determination of the equivalent currents to calculate the radiation...... pattern, and the inaccurate mutual coupling between array elements due to the lack of periodicity. To serve as reference, two offset reflectarray antennas have been designed, manufactured and measured at the DTUESA Spherical Near-Field Antenna Test Facility. Comparisons of simulated and measured data are...

  20. Accurate diagnosis is essential for amebiasis

    Institute of Scientific and Technical Information of China (English)

    2004-01-01

    @@ Amebiasis is one of the three most common causes of death from parasitic disease, and Entamoeba histolytica is the most widely distributed parasites in the world. Particularly, Entamoeba histolytica infection in the developing countries is a significant health problem in amebiasis-endemic areas with a significant impact on infant mortality[1]. In recent years a world wide increase in the number of patients with amebiasis has refocused attention on this important infection. On the other hand, improving the quality of parasitological methods and widespread use of accurate tecniques have improved our knowledge about the disease.

  1. Universality: Accurate Checks in Dyson's Hierarchical Model

    Science.gov (United States)

    Godina, J. J.; Meurice, Y.; Oktay, M. B.

    2003-06-01

    In this talk we present high-accuracy calculations of the susceptibility near βc for Dyson's hierarchical model in D = 3. Using linear fitting, we estimate the leading (γ) and subleading (Δ) exponents. Independent estimates are obtained by calculating the first two eigenvalues of the linearized renormalization group transformation. We found γ = 1.29914073 ± 10 -8 and, Δ = 0.4259469 ± 10-7 independently of the choice of local integration measure (Ising or Landau-Ginzburg). After a suitable rescaling, the approximate fixed points for a large class of local measure coincide accurately with a fixed point constructed by Koch and Wittwer.

  2. Hydrologic landscape regionalisation using deductive classification and random forests.

    Directory of Open Access Journals (Sweden)

    Stuart C Brown

    Full Text Available Landscape classification and hydrological regionalisation studies are being increasingly used in ecohydrology to aid in the management and research of aquatic resources. We present a methodology for classifying hydrologic landscapes based on spatial environmental variables by employing non-parametric statistics and hybrid image classification. Our approach differed from previous classifications which have required the use of an a priori spatial unit (e.g. a catchment which necessarily results in the loss of variability that is known to exist within those units. The use of a simple statistical approach to identify an appropriate number of classes eliminated the need for large amounts of post-hoc testing with different number of groups, or the selection and justification of an arbitrary number. Using statistical clustering, we identified 23 distinct groups within our training dataset. The use of a hybrid classification employing random forests extended this statistical clustering to an area of approximately 228,000 km2 of south-eastern Australia without the need to rely on catchments, landscape units or stream sections. This extension resulted in a highly accurate regionalisation at both 30-m and 2.5-km resolution, and a less-accurate 10-km classification that would be more appropriate for use at a continental scale. A smaller case study, of an area covering 27,000 km2, demonstrated that the method preserved the intra- and inter-catchment variability that is known to exist in local hydrology, based on previous research. Preliminary analysis linking the regionalisation to streamflow indices is promising suggesting that the method could be used to predict streamflow behaviour in ungauged catchments. Our work therefore simplifies current classification frameworks that are becoming more popular in ecohydrology, while better retaining small-scale variability in hydrology, thus enabling future attempts to explain and visualise broad-scale hydrologic

  3. 78 FR 68983 - Cotton Futures Classification: Optional Classification Procedure

    Science.gov (United States)

    2013-11-18

    ...-Doxey data into the cotton futures classification process in March 2012 (77 FR 5379). When verified by a... October 9, 2013 (78 FR 54970). AMS received two comments: one from a national trade organization... Agricultural Marketing Service 7 CFR Part 27 RIN 0581-AD33 Cotton Futures Classification:...

  4. The European Clinical, Molecular, and Pathological (ECMP Criteria and the 2007/2008 Revisions of the World Health Organization for the Diagnosis, Classification, and Staging of Prefibrotic Myeloproliferative Neoplasms Carrying the JAK2V617F Mutation

    Directory of Open Access Journals (Sweden)

    Jan Jacques Michiels

    2014-09-01

    Full Text Available OBJECTIVE: The prefibrotic stages of JAK2V617F essential thrombocythemia (ET and JAK2V617F polycythemia vera (PV can easily be diagnosed clinically without use of bone marrow biopsy histology. We assessed the 2008 WHO and European Clinical, Molecular, and Pathological (ECMP criteria for the diagnosis of myeloproliferative neoplasms (MPNs. METHODS: Studied patients included 6 JAK2V617F-mutated ET and 4 PV patients during long-term follow-up in view of critical analysis of the literature. The bone marrow biopsy histology diagnosis without use of clinical data was PV in 7 (of which 3 were cases of ET with features of early prodromal PV and classical PV in 4. RESULTS: The ECMP criteria distinguish 3 sequential phenotypes (1, 2, or 3 of JAK2V617F-mutated ET: normocellular ET-1; ET-2, with clinical and bone marrow features of PV (prodromal PV, and ET-3, with hypercellular dysmorphic megakaryocytic and granulocytic myeloproliferation (ET.MGM. The 3 patients with ET-2 or prodromal PV developed slow-onset PV after a follow-up of about 10 years. Bone marrow biopsy histology differentiates MPNs of various molecular etiologies from all variants of primary or secondary erythrocytoses and thrombocytoses with sensitivity and specificity of near 100%. CONCLUSION: Normocellular ET (WHO-ET, prodromal PV, and classical PV show overlapping bone marrow biopsy histology features with similar pleomorphic clustered megakaryocytes in the prefibrotic stages of JAK2V617F mutated MPN. Erythrocytes are below 6x1012/L in normocellular ET and prodromal PV, and are consistently above 6x1012/L in classical PV and at the time of transition from prodromal PV into classical PV. Red cell count at a cut-off level of 6x1012/L separates ET from PV and obviates the need for red cell mass measurement when bone marrow histology and JAK2V617F mutation screening are included in the diagnostic work-up of MPNs.

  5. Identification of Microorganisms by High Resolution Tandem Mass Spectrometry with Accurate Statistical Significance

    Science.gov (United States)

    Alves, Gelio; Wang, Guanghui; Ogurtsov, Aleksey Y.; Drake, Steven K.; Gucek, Marjan; Suffredini, Anthony F.; Sacks, David B.; Yu, Yi-Kuo

    2016-02-01

    Correct and rapid identification of microorganisms is the key to the success of many important applications in health and safety, including, but not limited to, infection treatment, food safety, and biodefense. With the advance of mass spectrometry (MS) technology, the speed of identification can be greatly improved. However, the increasing number of microbes sequenced is challenging correct microbial identification because of the large number of choices present. To properly disentangle candidate microbes, one needs to go beyond apparent morphology or simple `fingerprinting'; to correctly prioritize the candidate microbes, one needs to have accurate statistical significance in microbial identification. We meet these challenges by using peptidome profiles of microbes to better separate them and by designing an analysis method that yields accurate statistical significance. Here, we present an analysis pipeline that uses tandem MS (MS/MS) spectra for microbial identification or classification. We have demonstrated, using MS/MS data of 81 samples, each composed of a single known microorganism, that the proposed pipeline can correctly identify microorganisms at least at the genus and species levels. We have also shown that the proposed pipeline computes accurate statistical significances, i.e., E-values for identified peptides and unified E-values for identified microorganisms. The proposed analysis pipeline has been implemented in MiCId, a freely available software for Microorganism Classification and Identification. MiCId is available for download at http://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html.

  6. Accurate, noninvasive detection of Helicobacter pylori DNA from stool samples: potential usefulness for monitoring treatment.

    Science.gov (United States)

    Shuber, Anthony P; Ascaño, Jennifer J; Boynton, Kevin A; Mitchell, Anastasia; Frierson, Henry F; El-Rifai, Wa'el; Powell, Steven M

    2002-01-01

    A novel DNA assay demonstrating sensitive and accurate detection of Helicobacter pylori from stool samples is reported. Moreover, in three individuals tested for therapeutic response, the assay showed the disappearance of H. pylori DNA during treatment. Thus, this noninvasive molecular biology-based assay has the potential to be a powerful diagnostic tool given its ability to specifically identify H. pylori DNA.

  7. Accurate, Noninvasive Detection of Helicobacter pylori DNA from Stool Samples: Potential Usefulness for Monitoring Treatment

    OpenAIRE

    Shuber, Anthony P; Ascaño, Jennifer J.; Boynton, Kevin A.; Mitchell, Anastasia; Frierson, Henry F.; El-Rifai, Wa’el; Powell, Steven M

    2002-01-01

    A novel DNA assay demonstrating sensitive and accurate detection of Helicobacter pylori from stool samples is reported. Moreover, in three individuals tested for therapeutic response, the assay showed the disappearance of H. pylori DNA during treatment. Thus, this noninvasive molecular biology-based assay has the potential to be a powerful diagnostic tool given its ability to specifically identify H. pylori DNA.

  8. SPIDERz: SuPport vector classification for IDEntifying Redshifts

    Science.gov (United States)

    Jones, Evan; Singal, J.

    2016-08-01

    SPIDERz (SuPport vector classification for IDEntifying Redshifts) applies powerful support vector machine (SVM) optimization and statistical learning techniques to custom data sets to obtain accurate photometric redshift (photo-z) estimations. It is written for the IDL environment and can be applied to traditional data sets consisting of photometric band magnitudes, or alternatively to data sets with additional galaxy parameters (such as shape information) to investigate potential correlations between the extra galaxy parameters and redshift.

  9. Reconstruction-classification method for quantitative photoacoustic tomography

    CERN Document Server

    Malone, Emma; Cox, Ben T; Arridge, Simon R

    2015-01-01

    We propose a combined reconstruction-classification method for simultaneously recovering absorption and scattering in turbid media from images of absorbed optical energy. This method exploits knowledge that optical parameters are determined by a limited number of classes to iteratively improve their estimate. Numerical experiments show that the proposed approach allows for accurate recovery of absorption and scattering in 2 and 3 dimensions, and delivers superior image quality with respect to traditional reconstruction-only approaches.

  10. Automated Feature Design for Time Series Classification by Genetic Programming

    OpenAIRE

    Harvey, Dustin Yewell

    2014-01-01

    Time series classification (TSC) methods discover and exploit patterns in time series and other one-dimensional signals. Although many accurate, robust classifiers exist for multivariate feature sets, general approaches are needed to extend machine learning techniques to make use of signal inputs. Numerous applications of TSC can be found in structural engineering, especially in the areas of structural health monitoring and non-destructive evaluation. Additionally, the fields of process contr...

  11. IMAGE RECONSTRUCTION AND OBJECT CLASSIFICATION IN CT IMAGING SYSTEM

    Institute of Scientific and Technical Information of China (English)

    张晓明; 蒋大真; 等

    1995-01-01

    By obtaining a feasible filter function,reconstructed images can be got with linear interpolation and filtered backoprojection techniques.Considering the gray and spatial correlation neighbour informations of each pixel,a new supervised classification method is put forward for the reconstructed images,and an experiment with noise image is done,the result shows that the method is feasible and accurate compared with ideal phantoms.

  12. Accurate vibrational energy spectra and dissociationenergies of some diatomic electronic states

    Institute of Scientific and Technical Information of China (English)

    Wei-guo SUN; Xiu-ying LIU; Yu-jie WANG; Yan ZHAN; Qun-chao FAN

    2008-01-01

    An algebraic method (AM) used to study the full vibrational spectra of diatomic systems, and an analytical formula used to calculate accurate molecular dissociation energies are applied to study the full vi-brational spectra and molecular dissociation energies of some electronic states of homonuclear and heteronuclear diatomic molecules and diatomic ions. Studies show that the AM method and the analytical expression are reli-able and economical physical methods for studying full vibrational spectra and molecular dissociation energies of diatomic electronic systems theoretically. They are par-ticularly useful for those diatomic systems whose high-lying vibrational energies may not be available.

  13. Accurate radiative transfer calculations for layered media.

    Science.gov (United States)

    Selden, Adrian C

    2016-07-01

    Simple yet accurate results for radiative transfer in layered media with discontinuous refractive index are obtained by the method of K-integrals. These are certain weighted integrals applied to the angular intensity distribution at the refracting boundaries. The radiative intensity is expressed as the sum of the asymptotic angular intensity distribution valid in the depth of the scattering medium and a transient term valid near the boundary. Integrated boundary equations are obtained, yielding simple linear equations for the intensity coefficients, enabling the angular emission intensity and the diffuse reflectance (albedo) and transmittance of the scattering layer to be calculated without solving the radiative transfer equation directly. Examples are given of half-space, slab, interface, and double-layer calculations, and extensions to multilayer systems are indicated. The K-integral method is orders of magnitude more accurate than diffusion theory and can be applied to layered scattering media with a wide range of scattering albedos, with potential applications to biomedical and ocean optics. PMID:27409700

  14. Accurate pose estimation for forensic identification

    Science.gov (United States)

    Merckx, Gert; Hermans, Jeroen; Vandermeulen, Dirk

    2010-04-01

    In forensic authentication, one aims to identify the perpetrator among a series of suspects or distractors. A fundamental problem in any recognition system that aims for identification of subjects in a natural scene is the lack of constrains on viewing and imaging conditions. In forensic applications, identification proves even more challenging, since most surveillance footage is of abysmal quality. In this context, robust methods for pose estimation are paramount. In this paper we will therefore present a new pose estimation strategy for very low quality footage. Our approach uses 3D-2D registration of a textured 3D face model with the surveillance image to obtain accurate far field pose alignment. Starting from an inaccurate initial estimate, the technique uses novel similarity measures based on the monogenic signal to guide a pose optimization process. We will illustrate the descriptive strength of the introduced similarity measures by using them directly as a recognition metric. Through validation, using both real and synthetic surveillance footage, our pose estimation method is shown to be accurate, and robust to lighting changes and image degradation.

  15. How Accurately can we Calculate Thermal Systems?

    Energy Technology Data Exchange (ETDEWEB)

    Cullen, D; Blomquist, R N; Dean, C; Heinrichs, D; Kalugin, M A; Lee, M; Lee, Y; MacFarlan, R; Nagaya, Y; Trkov, A

    2004-04-20

    I would like to determine how accurately a variety of neutron transport code packages (code and cross section libraries) can calculate simple integral parameters, such as K{sub eff}, for systems that are sensitive to thermal neutron scattering. Since we will only consider theoretical systems, we cannot really determine absolute accuracy compared to any real system. Therefore rather than accuracy, it would be more precise to say that I would like to determine the spread in answers that we obtain from a variety of code packages. This spread should serve as an excellent indicator of how accurately we can really model and calculate such systems today. Hopefully, eventually this will lead to improvements in both our codes and the thermal scattering models that they use in the future. In order to accomplish this I propose a number of extremely simple systems that involve thermal neutron scattering that can be easily modeled and calculated by a variety of neutron transport codes. These are theoretical systems designed to emphasize the effects of thermal scattering, since that is what we are interested in studying. I have attempted to keep these systems very simple, and yet at the same time they include most, if not all, of the important thermal scattering effects encountered in a large, water-moderated, uranium fueled thermal system, i.e., our typical thermal reactors.

  16. Accurate basis set truncation for wavefunction embedding

    Science.gov (United States)

    Barnes, Taylor A.; Goodpaster, Jason D.; Manby, Frederick R.; Miller, Thomas F.

    2013-07-01

    Density functional theory (DFT) provides a formally exact framework for performing embedded subsystem electronic structure calculations, including DFT-in-DFT and wavefunction theory-in-DFT descriptions. In the interest of efficiency, it is desirable to truncate the atomic orbital basis set in which the subsystem calculation is performed, thus avoiding high-order scaling with respect to the size of the MO virtual space. In this study, we extend a recently introduced projection-based embedding method [F. R. Manby, M. Stella, J. D. Goodpaster, and T. F. Miller III, J. Chem. Theory Comput. 8, 2564 (2012)], 10.1021/ct300544e to allow for the systematic and accurate truncation of the embedded subsystem basis set. The approach is applied to both covalently and non-covalently bound test cases, including water clusters and polypeptide chains, and it is demonstrated that errors associated with basis set truncation are controllable to well within chemical accuracy. Furthermore, we show that this approach allows for switching between accurate projection-based embedding and DFT embedding with approximate kinetic energy (KE) functionals; in this sense, the approach provides a means of systematically improving upon the use of approximate KE functionals in DFT embedding.

  17. Accurate pattern registration for integrated circuit tomography

    Energy Technology Data Exchange (ETDEWEB)

    Levine, Zachary H.; Grantham, Steven; Neogi, Suneeta; Frigo, Sean P.; McNulty, Ian; Retsch, Cornelia C.; Wang, Yuxin; Lucatorto, Thomas B.

    2001-07-15

    As part of an effort to develop high resolution microtomography for engineered structures, a two-level copper integrated circuit interconnect was imaged using 1.83 keV x rays at 14 angles employing a full-field Fresnel zone plate microscope. A major requirement for high resolution microtomography is the accurate registration of the reference axes in each of the many views needed for a reconstruction. A reconstruction with 100 nm resolution would require registration accuracy of 30 nm or better. This work demonstrates that even images that have strong interference fringes can be used to obtain accurate fiducials through the use of Radon transforms. We show that we are able to locate the coordinates of the rectilinear circuit patterns to 28 nm. The procedure is validated by agreement between an x-ray parallax measurement of 1.41{+-}0.17 {mu}m and a measurement of 1.58{+-}0.08 {mu}m from a scanning electron microscope image of a cross section.

  18. Accurate determination of characteristic relative permeability curves

    Science.gov (United States)

    Krause, Michael H.; Benson, Sally M.

    2015-09-01

    A recently developed technique to accurately characterize sub-core scale heterogeneity is applied to investigate the factors responsible for flowrate-dependent effective relative permeability curves measured on core samples in the laboratory. The dependency of laboratory measured relative permeability on flowrate has long been both supported and challenged by a number of investigators. Studies have shown that this apparent flowrate dependency is a result of both sub-core scale heterogeneity and outlet boundary effects. However this has only been demonstrated numerically for highly simplified models of porous media. In this paper, flowrate dependency of effective relative permeability is demonstrated using two rock cores, a Berea Sandstone and a heterogeneous sandstone from the Otway Basin Pilot Project in Australia. Numerical simulations of steady-state coreflooding experiments are conducted at a number of injection rates using a single set of input characteristic relative permeability curves. Effective relative permeability is then calculated from the simulation data using standard interpretation methods for calculating relative permeability from steady-state tests. Results show that simplified approaches may be used to determine flowrate-independent characteristic relative permeability provided flow rate is sufficiently high, and the core heterogeneity is relatively low. It is also shown that characteristic relative permeability can be determined at any typical flowrate, and even for geologically complex models, when using accurate three-dimensional models.

  19. Detection of Acanthamoeba on the ocular surface in a Spanish population using the Schirmer strip test: pathogenic potential, molecular classification and evaluation of the sensitivity to chlorhexidine and voriconazole of the isolated Acanthamoeba strains.

    Science.gov (United States)

    Rocha-Cabrera, Pedro; Reyes-Batlle, María; Martín-Navarro, Carmen María; Dorta-Gorrín, Alexis; López-Arencibia, Atteneri; Sifaoui, Ines; Martínez-Carretero, Enrique; Piñero, José E; Martín-Barrera, Fernando; Valladares, Basilio; Lorenzo-Morales, Jacob

    2015-08-01

    Pathogenic strains of Acanthamoeba are causative agents of a sight-threatening infection of the cornea known as Acanthamoeba keratitis, which is often associated with the misuse of contact lenses. However, there is still a question remaining to be answered, which is whether these micro-organisms are present on the ocular surface of healthy individuals. Therefore, the aim of this study was to determine the presence of Acanthamoeba on the ocular surface in healthy patients and also in those with other ocular surface infections. Sterile Schirmer test strips were used to collect samples from a group of patients who attended an ophthalmology consultation at the Hospital del Norte, Icod de los Vinos, Tenerife, Canary Islands. Most of the patients (46 individuals, 79.31  %) presented ocular surface pathologies such as blepharitis or conjunctivitis; the rest did not present any pathology. None of the patients included in the study wore contact lenses. The collected samples were cultured in 2  % non-nutrient agar plates and positive plates were then cultured in axenic conditions for further analyses. Molecular analysis classified all isolated strains as belonging to Acanthamoeba genotype tbl4, and osmotolerance and thermotolerance assays revealed that all strains were potentially pathogenic. Furthermore, all strains were assayed for sensitivity against voriconazole and chlorhexidine. Assays showed that both drugs were active against the tested strains. In conclusion, the Schirmer strip test is proposed as an effective tool for the detection of Acanthamoeba on the ocular surface.

  20. 15 CFR 2008.9 - Classification guides.

    Science.gov (United States)

    2010-01-01

    ... 15 Commerce and Foreign Trade 3 2010-01-01 2010-01-01 false Classification guides. 2008.9 Section... REPRESENTATIVE Derivative Classification § 2008.9 Classification guides. Classification guides shall be issued by... direct derivative classification, shall identify the information to be protected in specific and...

  1. 32 CFR 2400.15 - Classification guides.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Classification guides. 2400.15 Section 2400.15... Derivative Classification § 2400.15 Classification guides. (a) OSTP shall issue and maintain classification guides to facilitate the proper and uniform derivative classification of information. These guides...

  2. 14 CFR 1203.412 - Classification guides.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 5 2010-01-01 2010-01-01 false Classification guides. 1203.412 Section... PROGRAM Guides for Original Classification § 1203.412 Classification guides. (a) General. A classification guide, based upon classification determinations made by appropriate program and...

  3. 7 CFR 27.34 - Classification procedure.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Classification procedure. 27.34 Section 27.34... REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification and Micronaire Determinations § 27.34 Classification procedure. Classification shall proceed as rapidly as possible, but...

  4. 22 CFR 9.6 - Derivative classification.

    Science.gov (United States)

    2010-04-01

    ... CFR 2001.22. (c) Department of State Classification Guide. The Department of State Classification... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Derivative classification. 9.6 Section 9.6... classification. (a) Definition. Derivative classification is the incorporating, paraphrasing, restating...

  5. 22 CFR 9.4 - Original classification.

    Science.gov (United States)

    2010-04-01

    ... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Original classification. 9.4 Section 9.4... classification. (a) Definition. Original classification is the initial determination that certain information... classification. (b) Classification levels. (1) Top Secret shall be applied to information the...

  6. Retinal connectomics: towards complete, accurate networks.

    Science.gov (United States)

    Marc, Robert E; Jones, Bryan W; Watt, Carl B; Anderson, James R; Sigulinsky, Crystal; Lauritzen, Scott

    2013-11-01

    Connectomics is a strategy for mapping complex neural networks based on high-speed automated electron optical imaging, computational assembly of neural data volumes, web-based navigational tools to explore 10(12)-10(15) byte (terabyte to petabyte) image volumes, and annotation and markup tools to convert images into rich networks with cellular metadata. These collections of network data and associated metadata, analyzed using tools from graph theory and classification theory, can be merged with classical systems theory, giving a more completely parameterized view of how biologic information processing systems are implemented in retina and brain. Networks have two separable features: topology and connection attributes. The first findings from connectomics strongly validate the idea that the topologies of complete retinal networks are far more complex than the simple schematics that emerged from classical anatomy. In particular, connectomics has permitted an aggressive refactoring of the retinal inner plexiform layer, demonstrating that network function cannot be simply inferred from stratification; exposing the complex geometric rules for inserting different cells into a shared network; revealing unexpected bidirectional signaling pathways between mammalian rod and cone systems; documenting selective feedforward systems, novel candidate signaling architectures, new coupling motifs, and the highly complex architecture of the mammalian AII amacrine cell. This is but the beginning, as the underlying principles of connectomics are readily transferrable to non-neural cell complexes and provide new contexts for assessing intercellular communication. PMID:24016532

  7. Genotype phenotype classification of hepatocellular adenoma

    Institute of Scientific and Technical Information of China (English)

    Paulette Bioulac-Sage; Jean Frédéric Blanc; Sandra Rebouissou; Charles Balabaud; Jessica Zucman-Rossi

    2007-01-01

    Studies that compare tumor genotype with phenotype have provided the basis of a new histological/molecular classification of hepatocellular adenomas. Based on two molecular criteria (presence of a TCF1/HNF1α or β-catenin mutation), and an additional histological criterion (presence or absence of an inflammatory infiltrate), subgroups of hepatocellular adenoma can be defined and distinguished from focal nodular hyperplasia. Analysis of 96 hepatocellular adenomas performed by a French collaborative network showed that they can be divided into four broad subgroups: the first one is defined by the presence of mutations in TCF1 gene inactivating the hepatocyte nuclear factor 1 (HNF1α); the second by the presence of β-catenin activating mutations; the category without mutations of HNF1α or β-catenin is further divided into 2 subgroups depending on the presence or absence of inflammation. Therefore, the approach to the diagnosis of problematic benign hepatocytic nodules may be entering a new era directed by new molecular information. It is hoped that immunohistological tools will improve significantly diagnosis of liver biopsy in our ability to distinguish hepatocellular adenoma from focal nodular hyperplasia (FNH), and to delineate clinically meaningful entities within each group to define the best clinical management. The optimal care of patients with a liver nodule will benefit from the recent knowledge coming from molecular biology and the combined expertise of hepatologists, pathologists, radiologists, and surgeons.

  8. Automatic classification of protein structures using physicochemical parameters.

    Science.gov (United States)

    Mohan, Abhilash; Rao, M Divya; Sunderrajan, Shruthi; Pennathur, Gautam

    2014-09-01

    Protein classification is the first step to functional annotation; SCOP and Pfam databases are currently the most relevant protein classification schemes. However, the disproportion in the number of three dimensional (3D) protein structures generated versus their classification into relevant superfamilies/families emphasizes the need for automated classification schemes. Predicting function of novel proteins based on sequence information alone has proven to be a major challenge. The present study focuses on the use of physicochemical parameters in conjunction with machine learning algorithms (Naive Bayes, Decision Trees, Random Forest and Support Vector Machines) to classify proteins into their respective SCOP superfamily/Pfam family, using sequence derived information. Spectrophores™, a 1D descriptor of the 3D molecular field surrounding a structure was used as a benchmark to compare the performance of the physicochemical parameters. The machine learning algorithms were modified to select features based on information gain for each SCOP superfamily/Pfam family. The effect of combining physicochemical parameters and spectrophores on classification accuracy (CA) was studied. Machine learning algorithms trained with the physicochemical parameters consistently classified SCOP superfamilies and Pfam families with a classification accuracy above 90%, while spectrophores performed with a CA of around 85%. Feature selection improved classification accuracy for both physicochemical parameters and spectrophores based machine learning algorithms. Combining both attributes resulted in a marginal loss of performance. Physicochemical parameters were able to classify proteins from both schemes with classification accuracy ranging from 90-96%. These results suggest the usefulness of this method in classifying proteins from amino acid sequences.

  9. An accurate and simple quantum model for liquid water.

    Science.gov (United States)

    Paesani, Francesco; Zhang, Wei; Case, David A; Cheatham, Thomas E; Voth, Gregory A

    2006-11-14

    The path-integral molecular dynamics and centroid molecular dynamics methods have been applied to investigate the behavior of liquid water at ambient conditions starting from a recently developed simple point charge/flexible (SPC/Fw) model. Several quantum structural, thermodynamic, and dynamical properties have been computed and compared to the corresponding classical values, as well as to the available experimental data. The path-integral molecular dynamics simulations show that the inclusion of quantum effects results in a less structured liquid with a reduced amount of hydrogen bonding in comparison to its classical analog. The nuclear quantization also leads to a smaller dielectric constant and a larger diffusion coefficient relative to the corresponding classical values. Collective and single molecule time correlation functions show a faster decay than their classical counterparts. Good agreement with the experimental measurements in the low-frequency region is obtained for the quantum infrared spectrum, which also shows a higher intensity and a redshift relative to its classical analog. A modification of the original parametrization of the SPC/Fw model is suggested and tested in order to construct an accurate quantum model, called q-SPC/Fw, for liquid water. The quantum results for several thermodynamic and dynamical properties computed with the new model are shown to be in a significantly better agreement with the experimental data. Finally, a force-matching approach was applied to the q-SPC/Fw model to derive an effective quantum force field for liquid water in which the effects due to the nuclear quantization are explicitly distinguished from those due to the underlying molecular interactions. Thermodynamic and dynamical properties computed using standard classical simulations with this effective quantum potential are found in excellent agreement with those obtained from significantly more computationally demanding full centroid molecular dynamics

  10. Nonlinear estimation and classification

    CERN Document Server

    Hansen, Mark; Holmes, Christopher; Mallick, Bani; Yu, Bin

    2003-01-01

    Researchers in many disciplines face the formidable task of analyzing massive amounts of high-dimensional and highly-structured data This is due in part to recent advances in data collection and computing technologies As a result, fundamental statistical research is being undertaken in a variety of different fields Driven by the complexity of these new problems, and fueled by the explosion of available computer power, highly adaptive, non-linear procedures are now essential components of modern "data analysis," a term that we liberally interpret to include speech and pattern recognition, classification, data compression and signal processing The development of new, flexible methods combines advances from many sources, including approximation theory, numerical analysis, machine learning, signal processing and statistics The proposed workshop intends to bring together eminent experts from these fields in order to exchange ideas and forge directions for the future

  11. Estuary Classification Revisited

    CERN Document Server

    Guha, Anirban

    2012-01-01

    The governing equations of a tidally averaged, width averaged, rectangular estuary has been investigated. It's theoretically shown that the dynamics of an estuary is entirely controlled by three parameters: (i) the Estuarine Froude number, (ii) the Tidal Froude number and (iii) the Estuarine Aspect ratio. The momentum, salinity and integral salt balance equations can be completely expressed in terms of these control variables. The estuary classification problem has also been reinvestigated. It's found that these three control variables can completely specify the estuary type. Comparison with real estuary data shows very good match. Additionally, we show that the well accepted leading order estuarine integral salt balance equation is inconsitent with the leading order salinity equation in an order of magnitude sense.

  12. Classification-based reasoning

    Science.gov (United States)

    Gomez, Fernando; Segami, Carlos

    1991-01-01

    A representation formalism for N-ary relations, quantification, and definition of concepts is described. Three types of conditions are associated with the concepts: (1) necessary and sufficient properties, (2) contingent properties, and (3) necessary properties. Also explained is how complex chains of inferences can be accomplished by representing existentially quantified sentences, and concepts denoted by restrictive relative clauses as classification hierarchies. The representation structures that make possible the inferences are explained first, followed by the reasoning algorithms that draw the inferences from the knowledge structures. All the ideas explained have been implemented and are part of the information retrieval component of a program called Snowy. An appendix contains a brief session with the program.

  13. Seismic texture classification. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Vinther, R.

    1997-12-31

    The seismic texture classification method, is a seismic attribute that can both recognize the general reflectivity styles and locate variations from these. The seismic texture classification performs a statistic analysis for the seismic section (or volume) aiming at describing the reflectivity. Based on a set of reference reflectivities the seismic textures are classified. The result of the seismic texture classification is a display of seismic texture categories showing both the styles of reflectivity from the reference set and interpolations and extrapolations from these. The display is interpreted as statistical variations in the seismic data. The seismic texture classification is applied to seismic sections and volumes from the Danish North Sea representing both horizontal stratifications and salt diapers. The attribute succeeded in recognizing both general structure of successions and variations from these. Also, the seismic texture classification is not only able to display variations in prospective areas (1-7 sec. TWT) but can also be applied to deep seismic sections. The seismic texture classification is tested on a deep reflection seismic section (13-18 sec. TWT) from the Baltic Sea. Applied to this section the seismic texture classification succeeded in locating the Moho, which could not be located using conventional interpretation tools. The seismic texture classification is a seismic attribute which can display general reflectivity styles and deviations from these and enhance variations not found by conventional interpretation tools. (LN)

  14. A New Classification of Sandstone.

    Science.gov (United States)

    Brewer, Roger Clay; And Others

    1990-01-01

    Introduced is a sandstone classification scheme intended for use with thin-sections and hand specimens. Detailed is a step-by-step classification scheme. A graphic presentation of the scheme is presented. This method is compared with other existing schemes. (CW)

  15. Classification of Rainbows

    Science.gov (United States)

    Ricard, J. L.; Peter, A. L.; Barckicke, J.

    2015-12-01

    CLASSIFICATION OF RAINBOWS Jean Louis Ricard,1,2,* Peter Adams ,2 and Jean Barckicke 2,3 1CNRM, Météo-France,42 Avenue Gaspard Coriolis, 31057 Toulouse, France 2CEPAL, 148 Himley Road, Dudley, West Midlands DY1 2QH, United Kingdom 3DP/Compas,Météo-France,42 Avenue Gaspard Coriolis, 31057 Toulouse, France *Corresponding author: Dr_Jean_Ricard@yahoo,co,ukRainbows are the most beautiful and most spectacular optical atmospheric phenomenon. Humphreys (1964) pointedly noted that "the "explanations" generally given of the rainbow [ in textbooks] may well be said to explain beautifully that which does not occur, and to leave unexplained which does" . . . "The records of close observations of rainbows soon show that not even the colors are always the same". Textbooks stress that the main factor affecting the aspect of the rainbow is the radius of the water droplets. In his well-known textbook entitled "the nature of light & colour in the open air", Minnaert (1954) gives the chief features of the rainbow depending on the diameter of the drops producing it. For this study, we have gathered hundreds of pictures of primary bows. We sort out the pictures into classes. The classes are defined in a such way that rainbows belonging to the same class look similar. Our results are surprising and do not confirm Minnaert's classification. In practice, the size of the water droplets is only a minor factor controlling the overall aspect of the rainbow. The main factor appears to be the height of the sun above the horizon. At sunset, the width of the red band increases, while the width of the other bands of colours decreases. The orange, the violet, the blue and the green bands disappear completely in this order. At the end, the primary bow is mainly red and slightly yellow. Picture = Contrast-enhanced photograph of a primary bow picture (prepared by Andrew Dunn).

  16. Lubricant characterization by molecular simulation

    Energy Technology Data Exchange (ETDEWEB)

    Moore, J.D.; Cui, S.T.; Cummings, P.T.; Cochran, H.D. [Univ. of Tennessee, Knoxville, TN (United States). Dept. of Chemical Engineering]|[Oak Ridge National Lab., TN (United States). Chemical Technology Div.

    1997-12-01

    The authors have reported the calculation of the kinematic viscosity index of squalane from nonequilibrium molecular dynamics simulations. This represents the first accurate quantitative prediction of this measure of lubricant performance by molecular simulation. Using the same general alkane potential model, this computational approach offers the possibility of predicting the performance of potential lubricants prior to synthesis. Consequently, molecular simulation is poised to become an important tool for future lubricant development.

  17. Invasive breast cancer molecular classification and the choice of adjuvant chemotherapy regimens%浸润性乳腺癌分子分型与辅助化疗方案选择

    Institute of Scientific and Technical Information of China (English)

    陈嘉健; 柳光宇

    2011-01-01

    随着基因表达谱与基因芯片技术的开展,乳腺癌在分子水平上表现出的高度异质性也逐渐受到关注.不同分子分型的乳腺癌,其流行病学危险因素、疾病自然进展过程以及对全身或局部治疗的反应性都不尽相同;对于乳腺癌的准确分型能够较为精确地反映肿瘤的生物学行为,对于判断预后、制定更具个体化的治疗策略具有深刻的意义.2011年的St.Gallen共识已针对不同的乳腺癌分子分型给出了原则性的治疗建议,标志着乳腺癌的治疗已逐步进入了在规范化多学科综合治疗模式的基础上,倡导个体化治疗的时代.%With the adoption and development of gene expression technique, the heterogeneity at the molecular level of the breast cancer has attracted attention gradually. The different breast cancer subtypes have different epidemiological risk factors, different natural histories and different responses to systemic and local therapies. To identify the exact subtype of the breast cancer has profound significance on making individualized therapies. The consensus of St. Gallen BreastCancer Conference 2011 has provided different treatment suggestions according to different subtypes, which indicates that the management of breast cancer has entered the age of advocating individualized treatment on the basis of the standardization multi-disciplinary treatment gradually.

  18. Information Classification on University Websites

    DEFF Research Database (Denmark)

    Nawaz, Ather; Clemmensen, Torkil; Hertzum, Morten

    2011-01-01

    information and their ability to navigate the websites. The results of the study indicate group differences in user classification and related task-performance differences. The main implications of the study are that (a) the edit distance appears a useful measure in cross-country HCI research and practice......Websites are increasingly used as a medium for providing information to university students. The quality of a university website depends on how well the students’ information classification fits with the structure of the information on the website. This paper investigates the information...... classification of 14 Danish and 14 Pakistani students and compares it with the information classification of their university website. Brainstorming, card sorting, and task exploration activities were used to discover similarities and differences in the participating students’ classification of website...

  19. [Classification of viruses by computer].

    Science.gov (United States)

    Ageeva, O N; Andzhaparidze, O G; Kibardin, V M; Nazarova, G M; Pleteneva, E A

    1982-01-01

    The study used the information mass containing information on 83 viruses characterized by 41 markers. The suitability of one of the variants of cluster analysis for virus classification was demonstrated. It was established that certain stages of automatic allotment of viruses into groups by the degree of similarity of their properties end the formation of groups which consist of viruses sufficiently close to each other by their properties and are sufficiently isolated. Comparison of these groups with the classification proposed by the ICVT established their correspondence to individual families. Analysis of the obtained classification system permits sufficiently grounded conclusions to be drawn with regard to the classification position of certain viruses, the classification of which has not yet been completed by the ICVT.

  20. Dynamic Ensemble Selection Approach for Hyperspectral Image Classification With Joint Spectral and Spatial Information

    OpenAIRE

    Damodaran, Bharath Bhushan; Rao Nidamanuri, Rama; Tarabalka, Yuliya

    2015-01-01

    Accurate generation of a land cover map using hyperspectral data is an important application of remote sensing. Multiple classifier system (MCS) is an effective tool for hyperspec-tral image classification. However, most of the research in MCS addressed the problem of classifier combination, while the potential of selecting classifiers dynamically is least explored for hyper-spectral image classification. The goal of this paper is to assess the potential of dynamic classifier selection/dynami...

  1. Classification of Ancient Mammal Individuals Using Dental Pulp MALDI-TOF MS Peptide Profiling

    OpenAIRE

    Thi-Nguyen-Ny Tran; Gérard Aboudharam; Armelle Gardeisen; Bernard Davoust; Jean-Pierre Bocquet-Appel; Christophe Flaudrops; Maya Belghazi; Didier Raoult; Michel Drancourt

    2011-01-01

    BACKGROUND: The classification of ancient animal corpses at the species level remains a challenging task for forensic scientists and anthropologists. Severe damage and mixed, tiny pieces originating from several skeletons may render morphological classification virtually impossible. Standard approaches are based on sequencing mitochondrial and nuclear targets. METHODOLOGY/PRINCIPAL FINDINGS: We present a method that can accurately classify mammalian species using dental pulp and mass spectrom...

  2. Classification of coronary artery bifurcation lesions and treatments: Time for a consensus!

    DEFF Research Database (Denmark)

    Louvard, Yves; Thomas, Martyn; Dzavik, Vladimir;

    2007-01-01

    , heterogeneity, and inadequate description of techniques implemented. Methods: The aim is to propose a consensus established by the European Bifurcation Club (EBC), on the definition and classification of bifurcation lesions and treatments implemented with the purpose of allowing comparisons between techniques...... proposes a new classification of bifurcation lesions and their treatments to permit accurate comparisons of well described techniques in homogeneous lesion groups. (c) 2008 Wiley-Liss, Inc. Udgivelsesdato: 2007-Nov-5...

  3. Classification and Segmentation of Satellite Orthoimagery Using Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    Martin Längkvist

    2016-04-01

    Full Text Available The availability of high-resolution remote sensing (HRRS data has opened up the possibility for new interesting applications, such as per-pixel classification of individual objects in greater detail. This paper shows how a convolutional neural network (CNN can be applied to multispectral orthoimagery and a digital surface model (DSM of a small city for a full, fast and accurate per-pixel classification. The predicted low-level pixel classes are then used to improve the high-level segmentation. Various design choices of the CNN architecture are evaluated and analyzed. The investigated land area is fully manually labeled into five categories (vegetation, ground, roads, buildings and water, and the classification accuracy is compared to other per-pixel classification works on other land areas that have a similar choice of categories. The results of the full classification and segmentation on selected segments of the map show that CNNs are a viable tool for solving both the segmentation and object recognition task for remote sensing data.

  4. Agent Collaborative Target Localization and Classification in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Sheng Wang

    2007-07-01

    Full Text Available Wireless sensor networks (WSNs are autonomous networks that have beenfrequently deployed to collaboratively perform target localization and classification tasks.Their autonomous and collaborative features resemble the characteristics of agents. Suchsimilarities inspire the development of heterogeneous agent architecture for WSN in thispaper. The proposed agent architecture views WSN as multi-agent systems and mobileagents are employed to reduce in-network communication. According to the architecture,an energy based acoustic localization algorithm is proposed. In localization, estimate oftarget location is obtained by steepest descent search. The search algorithm adapts tomeasurement environments by dynamically adjusting its termination condition. With theagent architecture, target classification is accomplished by distributed support vectormachine (SVM. Mobile agents are employed for feature extraction and distributed SVMlearning to reduce communication load. Desirable learning performance is guaranteed bycombining support vectors and convex hull vectors. Fusion algorithms are designed tomerge SVM classification decisions made from various modalities. Real world experimentswith MICAz sensor nodes are conducted for vehicle localization and classification.Experimental results show the proposed agent architecture remarkably facilitates WSNdesigns and algorithm implementation. The localization and classification algorithms alsoprove to be accurate and energy efficient.

  5. Cardiac arrhythmia classification using multi-modal signal analysis.

    Science.gov (United States)

    Kalidas, V; Tamil, L S

    2016-08-01

    In this paper, as a contribution to the Physionet/Computing in Cardiology 2015 Challenge, we present individual algorithms to accurately classify five different life threatening arrhythmias with the goal of suppressing false alarm generation in intensive care units. Information obtained by analysing electrocardiogram, photoplethysmogram and arterial blood pressure signals was utilized to develop the classification models. Prior to classification, the signals were subject to a signal pre-processing stage for quality analysis. Classification was performed using a combination of support vector machine based machine learning approach and logical analysis techniques. The predicted result for a certain arrhythmia classification model was verified by logical analysis to aid in reduction of false alarms. Separate feature vectors were formed for predicting the presence or absence of each arrhythmia, using both spectral and time-domain information. The training and test data were obtained from the Physionet/CinC Challenge 2015 database. Classification algorithms were written for two different categories of data, namely real-time and retrospective, whose data lengths were 10 s and an additional 30 s, respectively. For the real-time test dataset, sensitivity of 94% and specificity of 82% were obtained. Similarly, for the retrospective test dataset, sensitivity of 94% and specificity of 86% were obtained. PMID:27454417

  6. A Soft Intelligent Risk Evaluation Model for Credit Scoring Classification

    Directory of Open Access Journals (Sweden)

    Mehdi Khashei

    2015-09-01

    Full Text Available Risk management is one of the most important branches of business and finance. Classification models are the most popular and widely used analytical group of data mining approaches that can greatly help financial decision makers and managers to tackle credit risk problems. However, the literature clearly indicates that, despite proposing numerous classification models, credit scoring is often a difficult task. On the other hand, there is no universal credit-scoring model in the literature that can be accurately and explanatorily used in all circumstances. Therefore, the research for improving the efficiency of credit-scoring models has never stopped. In this paper, a hybrid soft intelligent classification model is proposed for credit-scoring problems. In the proposed model, the unique advantages of the soft computing techniques are used in order to modify the performance of the traditional artificial neural networks in credit scoring. Empirical results of Australian credit card data classifications indicate that the proposed hybrid model outperforms its components, and also other classification models presented for credit scoring. Therefore, the proposed model can be considered as an appropriate alternative tool for binary decision making in business and finance, especially in high uncertainty conditions.

  7. USING GOOGLE’S KEYWORD RELATION IN MULTIDOMAIN DOCUMENT CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    Ping-I Chen

    2013-07-01

    Full Text Available People can collect all kinds of knowledge from search engines to improve the quality of decision making, and use document classification systems to manage the knowledge repository. Document classification systems always need to construct a keyword vector, which always contains thousands of words, to represent the knowledge domain. Thus, the computation complexity of the classification algorithm is very high. Also, users need to download all the documents before extracting the keywords and classifying the documents. In our previous work, we described a new algorithm called “Word AdHoc Network” (WANET and used it to extract the most important sequences of keywords for each document. In this paper, we adapt the WANET system to make it more precise. We will also use a new similarity measurement algorithm, called “Google Purity,” to calculate the similarity between the extracted keyword sequences to classify similar documents together. By using this system, we can easily classify the information in different knowledge domains at the same time, and all the executions are without any pre-established keyword repository. Our experiments show that the classification results are very accurate and useful. This new system can improve the efficiency of document classification and make it more usable in Web-based information management.

  8. Toward Accurate and Quantitative Comparative Metagenomics

    Science.gov (United States)

    Nayfach, Stephen; Pollard, Katherine S.

    2016-01-01

    Shotgun metagenomics and computational analysis are used to compare the taxonomic and functional profiles of microbial communities. Leveraging this approach to understand roles of microbes in human biology and other environments requires quantitative data summaries whose values are comparable across samples and studies. Comparability is currently hampered by the use of abundance statistics that do not estimate a meaningful parameter of the microbial community and biases introduced by experimental protocols and data-cleaning approaches. Addressing these challenges, along with improving study design, data access, metadata standardization, and analysis tools, will enable accurate comparative metagenomics. We envision a future in which microbiome studies are replicable and new metagenomes are easily and rapidly integrated with existing data. Only then can the potential of metagenomics for predictive ecological modeling, well-powered association studies, and effective microbiome medicine be fully realized. PMID:27565341

  9. Toward Accurate and Quantitative Comparative Metagenomics.

    Science.gov (United States)

    Nayfach, Stephen; Pollard, Katherine S

    2016-08-25

    Shotgun metagenomics and computational analysis are used to compare the taxonomic and functional profiles of microbial communities. Leveraging this approach to understand roles of microbes in human biology and other environments requires quantitative data summaries whose values are comparable across samples and studies. Comparability is currently hampered by the use of abundance statistics that do not estimate a meaningful parameter of the microbial community and biases introduced by experimental protocols and data-cleaning approaches. Addressing these challenges, along with improving study design, data access, metadata standardization, and analysis tools, will enable accurate comparative metagenomics. We envision a future in which microbiome studies are replicable and new metagenomes are easily and rapidly integrated with existing data. Only then can the potential of metagenomics for predictive ecological modeling, well-powered association studies, and effective microbiome medicine be fully realized. PMID:27565341

  10. Accurate guitar tuning by cochlear implant musicians.

    Science.gov (United States)

    Lu, Thomas; Huang, Juan; Zeng, Fan-Gang

    2014-01-01

    Modern cochlear implant (CI) users understand speech but find difficulty in music appreciation due to poor pitch perception. Still, some deaf musicians continue to perform with their CI. Here we show unexpected results that CI musicians can reliably tune a guitar by CI alone and, under controlled conditions, match simultaneously presented tones to tuning with CI than his normal ear. To understand these counterintuitive findings, we presented tones sequentially and found that tuning error was larger at ∼ 30 Hz for both subjects. A third subject, a non-musician CI user with normal contralateral hearing, showed similar trends in performance between CI and normal hearing ears but with less precision. This difference, along with electric analysis, showed that accurate tuning was achieved by listening to beats rather than discriminating pitch, effectively turning a spectral task into a temporal discrimination task. PMID:24651081

  11. How accurate are SuperCOSMOS positions?

    CERN Document Server

    Schaefer, Adam; Johnston, Helen

    2014-01-01

    Optical positions from the SuperCOSMOS Sky Survey have been compared in detail with accurate radio positions that define the second realisation of the International Celestial Reference Frame (ICRF2). The comparison was limited to the IIIaJ plates from the UK/AAO and Oschin (Palomar) Schmidt telescopes. A total of 1373 ICRF2 sources was used, with the sample restricted to stellar objects brighter than $B_J=20$ and Galactic latitudes $|b|>10^{\\circ}$. Position differences showed an rms scatter of $0.16''$ in right ascension and declination. While overall systematic offsets were $<0.1''$ in each hemisphere, both the systematics and scatter were greater in the north.

  12. Accurate renormalization group analyses in neutrino sector

    Energy Technology Data Exchange (ETDEWEB)

    Haba, Naoyuki [Graduate School of Science and Engineering, Shimane University, Matsue 690-8504 (Japan); Kaneta, Kunio [Kavli IPMU (WPI), The University of Tokyo, Kashiwa, Chiba 277-8568 (Japan); Takahashi, Ryo [Graduate School of Science and Engineering, Shimane University, Matsue 690-8504 (Japan); Yamaguchi, Yuya [Department of Physics, Faculty of Science, Hokkaido University, Sapporo 060-0810 (Japan)

    2014-08-15

    We investigate accurate renormalization group analyses in neutrino sector between ν-oscillation and seesaw energy scales. We consider decoupling effects of top quark and Higgs boson on the renormalization group equations of light neutrino mass matrix. Since the decoupling effects are given in the standard model scale and independent of high energy physics, our method can basically apply to any models beyond the standard model. We find that the decoupling effects of Higgs boson are negligible, while those of top quark are not. Particularly, the decoupling effects of top quark affect neutrino mass eigenvalues, which are important for analyzing predictions such as mass squared differences and neutrinoless double beta decay in an underlying theory existing at high energy scale.

  13. Accurate Telescope Mount Positioning with MEMS Accelerometers

    CERN Document Server

    Mészáros, László; Pál, András; Csépány, Gergely

    2014-01-01

    This paper describes the advantages and challenges of applying microelectromechanical accelerometer systems (MEMS accelerometers) in order to attain precise, accurate and stateless positioning of telescope mounts. This provides a completely independent method from other forms of electronic, optical, mechanical or magnetic feedback or real-time astrometry. Our goal is to reach the sub-arcminute range which is well smaller than the field-of-view of conventional imaging telescope systems. Here we present how this sub-arcminute accuracy can be achieved with very cheap MEMS sensors and we also detail how our procedures can be extended in order to attain even finer measurements. In addition, our paper discusses how can a complete system design be implemented in order to be a part of a telescope control system.

  14. Accurate Weather Forecasting for Radio Astronomy

    Science.gov (United States)

    Maddalena, Ronald J.

    2010-01-01

    The NRAO Green Bank Telescope routinely observes at wavelengths from 3 mm to 1 m. As with all mm-wave telescopes, observing conditions depend upon the variable atmospheric water content. The site provides over 100 days/yr when opacities are low enough for good observing at 3 mm, but winds on the open-air structure reduce the time suitable for 3-mm observing where pointing is critical. Thus, to maximum productivity the observing wavelength needs to match weather conditions. For 6 years the telescope has used a dynamic scheduling system (recently upgraded; www.gb.nrao.edu/DSS) that requires accurate multi-day forecasts for winds and opacities. Since opacity forecasts are not provided by the National Weather Services (NWS), I have developed an automated system that takes available forecasts, derives forecasted opacities, and deploys the results on the web in user-friendly graphical overviews (www.gb.nrao.edu/ rmaddale/Weather). The system relies on the "North American Mesoscale" models, which are updated by the NWS every 6 hrs, have a 12 km horizontal resolution, 1 hr temporal resolution, run to 84 hrs, and have 60 vertical layers that extend to 20 km. Each forecast consists of a time series of ground conditions, cloud coverage, etc, and, most importantly, temperature, pressure, humidity as a function of height. I use the Liebe's MWP model (Radio Science, 20, 1069, 1985) to determine the absorption in each layer for each hour for 30 observing wavelengths. Radiative transfer provides, for each hour and wavelength, the total opacity and the radio brightness of the atmosphere, which contributes substantially at some wavelengths to Tsys and the observational noise. Comparisons of measured and forecasted Tsys at 22.2 and 44 GHz imply that the forecasted opacities are good to about 0.01 Nepers, which is sufficient for forecasting and accurate calibration. Reliability is high out to 2 days and degrades slowly for longer-range forecasts.

  15. Sleep Stage Classification Using Unsupervised Feature Learning

    Directory of Open Access Journals (Sweden)

    Martin Längkvist

    2012-01-01

    Full Text Available Most attempts at training computers for the difficult and time-consuming task of sleep stage classification involve a feature extraction step. Due to the complexity of multimodal sleep data, the size of the feature space can grow to the extent that it is also necessary to include a feature selection step. In this paper, we propose the use of an unsupervised feature learning architecture called deep belief nets (DBNs and show how to apply it to sleep data in order to eliminate the use of handmade features. Using a postprocessing step of hidden Markov model (HMM to accurately capture sleep stage switching, we compare our results to a feature-based approach. A study of anomaly detection with the application to home environment data collection is also presented. The results using raw data with a deep architecture, such as the DBN, were comparable to a feature-based approach when validated on clinical datasets.

  16. [The study of M dwarf spectral classification].

    Science.gov (United States)

    Yi, Zhen-Ping; Pan, Jing-Chang; Luo, A-Li

    2013-08-01

    As the most common stars in the galaxy, M dwarfs can be used to trace the structure and evolution of the Milky Way. Besides, investigating M dwarfs is important for searching for habitability of extrasolar planets orbiting M dwarfs. Spectral classification of M dwarfs is a fundamental work. The authors used DR7 M dwarf sample of SLOAN to extract important features from the range of 600-900 nm by random forest method. Compared to the features used in Hammer Code, the authors added three new indices. Our test showed that the improved Hammer with new indices is more accurate. Our method has been applied to classify M dwarf spectra of LAMOST. PMID:24159887

  17. Fusing Heterogeneous Data for Alzheimer's Disease Classification.

    Science.gov (United States)

    Pillai, Parvathy Sudhir; Leong, Tze-Yun

    2015-01-01

    In multi-view learning, multimodal representations of a real world object or situation are integrated to learn its overall picture. Feature sets from distinct data sources carry different, yet complementary, information which, if analysed together, usually yield better insights and more accurate results. Neuro-degenerative disorders such as dementia are characterized by changes in multiple biomarkers. This work combines the features from neuroimaging and cerebrospinal fluid studies to distinguish Alzheimer's disease patients from healthy subjects. We apply statistical data fusion techniques on 101 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We examine whether fusion of biomarkers helps to improve diagnostic accuracy and how the methods compare against each other for this problem. Our results indicate that multimodal data fusion improves classification accuracy. PMID:26262148

  18. Single-trial EEG RSVP classification using convolutional neural networks

    Science.gov (United States)

    Shamwell, Jared; Lee, Hyungtae; Kwon, Heesung; Marathe, Amar R.; Lawhern, Vernon; Nothwang, William

    2016-05-01

    Traditionally, Brain-Computer Interfaces (BCI) have been explored as a means to return function to paralyzed or otherwise debilitated individuals. An emerging use for BCIs is in human-autonomy sensor fusion where physiological data from healthy subjects is combined with machine-generated information to enhance the capabilities of artificial systems. While human-autonomy fusion of physiological data and computer vision have been shown to improve classification during visual search tasks, to date these approaches have relied on separately trained classification models for each modality. We aim to improve human-autonomy classification performance by developing a single framework that builds codependent models of human electroencephalograph (EEG) and image data to generate fused target estimates. As a first step, we developed a novel convolutional neural network (CNN) architecture and applied it to EEG recordings of subjects classifying target and non-target image presentations during a rapid serial visual presentation (RSVP) image triage task. The low signal-to-noise ratio (SNR) of EEG inherently limits the accuracy of single-trial classification and when combined with the high dimensionality of EEG recordings, extremely large training sets are needed to prevent overfitting and achieve accurate classification from raw EEG data. This paper explores a new deep CNN architecture for generalized multi-class, single-trial EEG classification across subjects. We compare classification performance from the generalized CNN architecture trained across all subjects to the individualized XDAWN, HDCA, and CSP neural classifiers which are trained and tested on single subjects. Preliminary results show that our CNN meets and slightly exceeds the performance of the other classifiers despite being trained across subjects.

  19. 75 FR 10529 - Mail Classification Change

    Science.gov (United States)

    2010-03-08

    ... Mail Classification Change AGENCY: Postal Regulatory Commission. ACTION: Notice. SUMMARY: The... Classification Schedule. The change affects a change in terminology. This notice addresses procedural steps....90 et seq. concerning a change in classification which reflects a change in terminology from...

  20. 75 FR 70754 - Postal Classification Changes

    Science.gov (United States)

    2010-11-18

    ... Postal Classification Changes AGENCY: Postal Regulatory Commission. ACTION: Notice. SUMMARY: The Commission is noticing a recently-filed Postal Service request announcing a classification change affecting... Notice with the Commission announcing a classification change ] established by the Governors.\\1\\...