Science.gov

Sample records for cluster enrichment analysis

  1. IGSA: Individual Gene Sets Analysis, including Enrichment and Clustering

    PubMed Central

    Liu, Lei; Ma, Hongzhe; Yang, Jingbo; Xie, Hongbo; Liu, Bo; Jin, Qing

    2016-01-01

    Analysis of gene sets has been widely applied in various high-throughput biological studies. One weakness in the traditional methods is that they neglect the heterogeneity of genes expressions in samples which may lead to the omission of some specific and important gene sets. It is also difficult for them to reflect the severities of disease and provide expression profiles of gene sets for individuals. We developed an application software called IGSA that leverages a powerful analytical capacity in gene sets enrichment and samples clustering. IGSA calculates gene sets expression scores for each sample and takes an accumulating clustering strategy to let the samples gather into the set according to the progress of disease from mild to severe. We focus on gastric, pancreatic and ovarian cancer data sets for the performance of IGSA. We also compared the results of IGSA in KEGG pathways enrichment with David, GSEA, SPIA, ssGSEA and analyzed the results of IGSA clustering and different similarity measurement methods. Notably, IGSA is proved to be more sensitive and specific in finding significant pathways, and can indicate related changes in pathways with the severity of disease. In addition, IGSA provides with significant gene sets profile for each sample. PMID:27764138

  2. Using Enrichment Clusters for Performance Based Identification.

    ERIC Educational Resources Information Center

    Renzulli, Joseph S.

    2000-01-01

    This article describes an enrichment cluster approach designed to create highly challenging learning opportunities that allow high potential students to identify themselves. The enrichment clusters focus students' attention on authentic learning applied to real-life problems. Guidelines for enrichment clusters are discussed, along with the teacher…

  3. The self-enrichment of globular clusters

    SciTech Connect

    Morgan, S.; Lake, G.

    1989-04-01

    It is shown that protoglobular clusters of primordial gas can confine the supernovae needed to enrich themselves. The required protocluster cloud masses and structural parameters are the same as those currently observed for the clusters. Two causal scenarios for star formation are examined to calculate the initial enrichment of primordial clouds. In the 'Christmas tree' scheme, the maximum final (Fe/H) is about 0.1. Since the time scale for formation and evolution of massive stars at the center of a cluster is nearly an order of magnitude less than the collapse time of the cluster, every globular cluster may have to survive a supernova detonation. If this is the case, the minimum mass of a globular cluster is about 10 to the 4.6th solar mass. 24 refs.

  4. How To Develop an Authentic Enrichment Cluster.

    ERIC Educational Resources Information Center

    Renzulli, Joseph S.

    This paper describes how educators can develop authentic enrichment clusters to provide highly engaging learning activities that make schools enjoyable places for gifted students. Part 1 of the paper discusses the importance of authentic learning, in which the student applies relevant knowledge, thinking skills, and interpersonal skills to the…

  5. Assessment of air quality in the coastal area of South Korea using principal component analysis combined with cluster analysis and enrichment factor

    NASA Astrophysics Data System (ADS)

    Yoo, H.; Kwack, W.; Ha, H.; Choe, C.; Kim, Y.; Zoh, K.; Yi, S.

    2009-12-01

    The interpretation of ambiet air pollution in relation with meteorological parameters is a topic of great interest to maintain and manage ambient air quality in the coastal region of South Korea. The objectives of this study were: (i) to locate emission sources qualitatitively and quantitatively, (ii) to identify air quality by day with similar air pollution behaviors; and (iii) to evaluate the effect of sea salt on the aerosols. Two statistical techniques, principal components analysis(PCA) and cluster analysis(CA) were applied to the concentrations of five pollutants(PM10, SO2, NO2, CO and O3). The enrichment factor(EF) representing the ratio of Cl/Na in aerosol to Cl/Na in sea water was calculated with 2 soluble ions(Na+ and Cl-) in PM10 analyzed by ion chromatograph in coastal urban area of Incheon city, South Korea from January to December 2008. PCA results show three emission sources; (i) high PM10, NO2 and CO with low temperature, radiation and wind speed(35.9%), (ii) high O3 with high radiation and wind speed, and low humidity(18.2%), (iii) high NO2 and O3 with high temperature and radiation, and low wind speed(11.2%), respectively. CA results show three groups; (i) Friday (high PM10 and NO2, low O3), (ii) Sunday (low PM10 and NO2, high O3), (iii) Monday/Tuesday/Wednesday/Thursday/Saturday (medium PM10, NO2 and O3). EF was 1.02 implying contribution of sea salt on the aerosol level with various anthropogenic sources. In conclusion, PCA and CA are suitable for idenfying and estimating the sources of air pollution. EF allows for investigating the effect of sea salt on the PM10 in the region where sea-land breezes. It was conclueded that the sea wind had an important contribution towards the variation of air pollutants. Key words : air pollutants, principal component analysis, cluster analysis, enrichment factor Fig. 1. Dendrogram using average linkage of cluster analysis for PM10 at coastal urban area of Incheon, South Korea. Table 1 Main results of PCA

  6. Economic Analysis. Enrichment.

    ERIC Educational Resources Information Center

    Sterling Inst., Washington, DC. Educational Technology Center.

    A multimedia course in economic analysis was prepared for the United States Naval Academy. (ED 043 790 and ED 043 791 are the final reports of the project evaluation and development model.) This report presents enrichment segments for selected core segments in concept areas one and two, covering a spectrum of economic systems, the influence of…

  7. The Application of Enrichment Clusters to Teachers' Classroom Practices.

    ERIC Educational Resources Information Center

    Reis, Sally M.; Gentry, Marcia; Maxfield, Lori R.

    1998-01-01

    A study investigated the effects of providing one type of gifted-education pedagogy, enrichment clusters, to the entire population of two urban elementary schools. The teaching practices of classroom teachers who participated as cluster facilitators were positively affected both in the enrichment clusters and in regular classrooms. (Author/CR)

  8. Chemical Enrichment in the Third Closest Galaxy Cluster

    NASA Astrophysics Data System (ADS)

    Million, Evan

    2011-10-01

    We propose a 180 ks XMM-Newton observation of the Antlia Cluster, the third closest galaxy cluster in the sky. We will determine the central temperature, Si and Fe abundance structure of the cluster to constrain detailed chemical enrichment processes in the nearest cluster without a strong cool core. The detailed abundance structure of the cluster will be resolved at the best physical resolution of any non-cool core cluster to date.

  9. Gene set enrichment analysis.

    PubMed

    Tilford, Charles A; Siemers, Nathan O

    2009-01-01

    Set enrichment analytical methods have become commonplace tools applied to the analysis and interpretation of biological data. The statistical techniques are used to identify categorical biases within lists of genes, proteins, or metabolites. The goal is to discover the shared functions or properties of the biological items represented within the lists. Application of these methods can provide great biological insight, including the discovery of participation in the same biological activity or pathway, shared interacting genes or regulators, common cellular compartmentalization, or association with disease. The methods require ordered or unordered lists of biological items as input, understanding of the reference set from which the lists were selected, categorical classifiers describing the items, and a statistical algorithm to assess bias of each classifier. Due to the complexity of most algorithms and the number of calculations performed, computer software is almost always used for execution of the algorithm, as well as for presentation of the results. This chapter will provide an overview of the statistical methods used to perform an enrichment analysis. Guidelines for assembly of the requisite information will be presented, with a focus on careful definition of the sets used by the statistical algorithms. The need for multiple test correction when working with large libraries of classifiers is emphasized, and we outline several options for performing the corrections. Finally, interpreting the results of such analysis will be discussed along with examples of recent research utilizing the techniques.

  10. A Clustering-Based Approach to Enriching Code Foraging Environment.

    PubMed

    Niu, Nan; Jin, Xiaoyu; Niu, Zhendong; Cheng, Jing-Ru C; Li, Ling; Kataev, Mikhail Yu

    2016-09-01

    Developers often spend valuable time navigating and seeking relevant code in software maintenance. Currently, there is a lack of theoretical foundations to guide tool design and evaluation to best shape the code base to developers. This paper contributes a unified code navigation theory in light of the optimal food-foraging principles. We further develop a novel framework for automatically assessing the foraging mechanisms in the context of program investigation. We use the framework to examine to what extent the clustering of software entities affects code foraging. Our quantitative analysis of long-lived open-source projects suggests that clustering enriches the software environment and improves foraging efficiency. Our qualitative inquiry reveals concrete insights into real developer's behavior. Our research opens the avenue toward building a new set of ecologically valid code navigation tools. PMID:25910273

  11. MicroRNA-Target Network Inference and Local Network Enrichment Analysis Identify Two microRNA Clusters with Distinct Functions in Head and Neck Squamous Cell Carcinoma

    PubMed Central

    Sass, Steffen; Pitea, Adriana; Unger, Kristian; Hess, Julia; Mueller, Nikola S.; Theis, Fabian J.

    2015-01-01

    MicroRNAs represent ~22 nt long endogenous small RNA molecules that have been experimentally shown to regulate gene expression post-transcriptionally. One main interest in miRNA research is the investigation of their functional roles, which can typically be accomplished by identification of mi-/mRNA interactions and functional annotation of target gene sets. We here present a novel method “miRlastic”, which infers miRNA-target interactions using transcriptomic data as well as prior knowledge and performs functional annotation of target genes by exploiting the local structure of the inferred network. For the network inference, we applied linear regression modeling with elastic net regularization on matched microRNA and messenger RNA expression profiling data to perform feature selection on prior knowledge from sequence-based target prediction resources. The novelty of miRlastic inference originates in predicting data-driven intra-transcriptome regulatory relationships through feature selection. With synthetic data, we showed that miRlastic outperformed commonly used methods and was suitable even for low sample sizes. To gain insight into the functional role of miRNAs and to determine joint functional properties of miRNA clusters, we introduced a local enrichment analysis procedure. The principle of this procedure lies in identifying regions of high functional similarity by evaluating the shortest paths between genes in the network. We can finally assign functional roles to the miRNAs by taking their regulatory relationships into account. We thoroughly evaluated miRlastic on a cohort of head and neck cancer (HNSCC) patients provided by The Cancer Genome Atlas. We inferred an mi-/mRNA regulatory network for human papilloma virus (HPV)-associated miRNAs in HNSCC. The resulting network best enriched for experimentally validated miRNA-target interaction, when compared to common methods. Finally, the local enrichment step identified two functional clusters of mi

  12. Implementing Enrichment Clusters in Elementary Schools: Lessons Learned

    ERIC Educational Resources Information Center

    Fiddyment, Gail E.

    2014-01-01

    Enrichment clusters offer a way for schools to encourage a high level of learning as students and adults work together to develop a product, service, or performance by applying advanced knowledge and authentic processes to real-world problems. This study utilized a qualitative research design to examine the perceptions and experiences of two…

  13. Enrichment by supernovae in globular clusters with multiple populations.

    PubMed

    Lee, Jae-Woo; Kang, Young-Woon; Lee, Jina; Lee, Young-Wook

    2009-11-26

    The most massive globular cluster in the Milky Way, omega Centauri, is thought to be the remaining core of a disrupted dwarf galaxy, as expected within the model of hierarchical merging. It contains several stellar populations having different heavy elemental abundances supplied by supernovae-a process known as metal enrichment. Although M 22 appears to be similar to omega Cen, other peculiar globular clusters do not. Therefore omega Cen and M 22 are viewed as exceptional, and the presence of chemical inhomogeneities in other clusters is seen as 'pollution' from the intermediate-mass asymptotic-giant-branch stars expected in normal globular clusters. Here we report Ca abundances for seven globular clusters and compare them to omega Cen. Calcium and other heavy elements can only be supplied through numerous supernovae explosions of massive stars in these stellar systems, but the gravitational potentials of the present-day clusters cannot preserve most of the ejecta from such explosions. We conclude that these globular clusters, like omega Cen, are most probably the relics of more massive primeval dwarf galaxies that merged and disrupted to form the proto-Galaxy. PMID:19940919

  14. Chemical Enrichment RGS cluster Sample (CHEERS): Constraints on turbulence

    NASA Astrophysics Data System (ADS)

    Pinto, Ciro; Sanders, Jeremy S.; Werner, Norbert; de Plaa, Jelle; Fabian, Andrew C.; Zhang, Yu-Ying; Kaastra, Jelle S.; Finoguenov, Alexis; Ahoranta, Jussi

    2015-03-01

    Context. Feedback from active galactic nuclei, galactic mergers, and sloshing are thought to give rise to turbulence, which may prevent cooling in clusters. Aims: We aim to measure the turbulence in clusters of galaxies and compare the measurements to some of their structural and evolutionary properties. Methods: It is possible to measure the turbulence of the hot gas in clusters by estimating the velocity widths of their X-ray emission lines. The Reflection Grating Spectrometers aboard XMM-Newton are currently the only instruments provided with sufficient effective area and spectral resolution in this energy domain. We benefited from excellent 1.6 Ms new data provided by the Chemical Enrichment RGS cluster Sample (CHEERS) project. Results: The new observations improve the quality of the archival data and allow us to place constraints for some clusters, which were not accessible in previous work. One-half of the sample shows upper limits on turbulence less than 500 km s-1. For several sources, our data are consistent with relatively strong turbulence with upper limits on the velocity widths that are larger than 1000 km s-1. The NGC 507 group of galaxies shows transonic velocities, which are most likely associated with the merging phenomena and bulk motions occurring in this object. Where both low- and high-ionization emission lines have good enough statistics, we find larger upper limits for the hot gas, which is partly due to the different spatial extents of the hot and cool gas phases. Our upper limits are larger than the Mach numbers required to balance cooling, suggesting that dissipation of turbulence may prevent cooling, although other heating processes could be dominant. The systematics associated with the spatial profile of the source continuum make this technique very challenging, though still powerful, for current instruments. In a forthcoming paper we will use the resonant-scattering technique to place lower-limits on the velocity broadening and provide

  15. Enrichment Clusters: A Practical Plan for Real-World, Student-Driven Learning.

    ERIC Educational Resources Information Center

    Renzulli, Joseph S.; Gentry, Marcia; Reis, Sally M.

    This guidebook provides a rationale and guidelines for implementing a student-driven learning approach using enrichment clusters. Enrichment clusters allow students who share a common interest to meet each week to produce a product, performance, or targeted service based on that common interest. Chapter 1 discusses different models of learning.…

  16. INSIGHTS INTO PRE-ENRICHMENT OF STAR CLUSTERS AND SELF-ENRICHMENT OF DWARF GALAXIES FROM THEIR INTRINSIC METALLICITY DISPERSIONS

    SciTech Connect

    Leaman, Ryan

    2012-12-01

    Star clusters are known to have smaller intrinsic metallicity spreads than dwarf galaxies due to their shorter star formation timescales. Here we use individual spectroscopic [Fe/H] measurements of stars in 19 Local Group dwarf galaxies, 13 Galactic open clusters, and 49 globular clusters to show that star cluster and dwarf galaxy linear metallicity distributions are binomial in form, with all objects showing strong correlations between their mean linear metallicity Z-bar and intrinsic spread in metallicity {sigma}(Z){sup 2}. A plot of {sigma}(Z){sup 2} versus Z-bar shows that the correlated relationships are offset for the dwarf galaxies from the star clusters. The common binomial nature of these linear metallicity distributions can be explained with a simple inhomogeneous chemical evolution model, where the star cluster and dwarf galaxy behavior in the {sigma}(Z){sup 2}- Z-bar diagram is reproduced in terms of the number of enrichment events, covering fraction, and intrinsic size of the enriched regions. The inhomogeneity of the self-enrichment sets the slope for the observed dwarf galaxy {sigma}(Z){sup 2}- Z-bar correlation. The offset of the star cluster sequence from that of the dwarf galaxies is due to pre-enrichment, and the slope of the star cluster sequence represents the remnant signature of the self-enriched history of their host galaxies. The offset can be used to separate star clusters from dwarf galaxies without a priori knowledge of their luminosity or dynamical mass. The application of the inhomogeneous model to the {sigma}(Z){sup 2}- Z-bar relationship provides a numerical formalism to connect the self-enrichment and pre-enrichment between star clusters and dwarf galaxies using physically motivated chemical enrichment parameters. Therefore we suggest that the {sigma}(Z){sup 2}- Z-bar relationship can provide insight into what drives the efficiency of star formation and chemical evolution in galaxies, and is an important prediction for galaxy

  17. Probing the Large Magellanic Cloud's recent chemical enrichment history through its star clusters

    NASA Astrophysics Data System (ADS)

    Palma, T.; Clariá, J. J.; Geisler, D.; Gramajo, L. V.; Ahumada, A. V.

    2015-06-01

    We present Washington system colour-magnitude diagrams (CMDs) for 17 practically unstudied star clusters located in the bar as well as in the inner disc and outer regions of the Large Magellanic Cloud (LMC). Cluster sizes were estimated from star counts distributed throughout the entire observed fields. Based on the best fits of theoretical isochrones to the cleaned (C - T1, T1) CMDs, as well as on the δT1 parameter and the standard giant branch method, we derive ages and metallicities for the cluster sample. Four objects are found to be intermediate-age clusters (1.8-2.5 Gyr), with [Fe/H] ranging from -0.66 to -0.84. With the exception of SL 263, a very young cluster (˜16 Myr), the remaining 12 objects are aged between 0.32 and 0.89 Gyr, with their [Fe/H] values ranging from -0.19 to -0.50. We combined our results with those for other 231 clusters studied in a similar way using the Washington system. The resulting age-metallicity relationship shows a significant dispersion in metallicities, whatever age is considered. Although there seems to exist a clear tendency for the younger clusters to be more metal rich than the intermediate ones, we believe that none of the chemical evolution models currently available in the literature reasonably well represents the recent chemical enrichment processes in the LMC clusters. The present sample of 17 clusters is part of our ongoing project of generating a data base of LMC clusters homogeneously studied using the Washington photometric system and applying the same analysis procedure.

  18. Heating and Chemical Enrichment in the Core of the Antlia Cluster

    NASA Astrophysics Data System (ADS)

    Hawley, William

    2011-08-01

    The dynamical processes responsible for heating and chemical enrichment of the ICM depend upon the environment and thus the cluster's evolutionary stage. These processes create distinct X-ray signatures in the hot cluster gas. We use a 53 ks XMM exposure of the core of the Antlia cluster, a galaxy cluster in an intermediate merger stage without a cool core, to study the transport of energy and metals throughout the ICM. We construct density, temperature, pressure, entropy and abundance maps to identify gas motions and heat flows, relate these motions to metal abundance ratios and gradients, and test simple models for chemical enrichment and heating of the Antlia cluster gas.

  19. ToppCluster: a multiple gene list feature analyzer for comparative enrichment clustering and network-based dissection of biological systems.

    PubMed

    Kaimal, Vivek; Bardes, Eric E; Tabar, Scott C; Jegga, Anil G; Aronow, Bruce J

    2010-07-01

    ToppCluster is a web server application that leverages a powerful enrichment analysis and underlying data environment for comparative analyses of multiple gene lists. It generates heatmaps or connectivity networks that reveal functional features shared or specific to multiple gene lists. ToppCluster uses hypergeometric tests to obtain list-specific feature enrichment P-values for currently 17 categories of annotations of human-ortholog genes, and provides user-selectable cutoffs and multiple testing correction methods to control false discovery. Each nameable gene list represents a column input to a resulting matrix whose rows are overrepresented features, and individual cells per-list P-values and corresponding genes per feature. ToppCluster provides users with choices of tabular outputs, hierarchical clustering and heatmap generation, or the ability to interactively select features from the functional enrichment matrix to be transformed into XGMML or GEXF network format documents for use in Cytoscape or Gephi applications, respectively. Here, as example, we demonstrate the ability of ToppCluster to enable identification of list-specific phenotypic and regulatory element features (both cis-elements and 3'UTR microRNA binding sites) among tissue-specific gene lists. ToppCluster's functionalities enable the identification of specialized biological functions and regulatory networks and systems biology-based dissection of biological states. ToppCluster can be accessed freely at http://toppcluster.cchmc.org.

  20. ANISOTROPIC METAL-ENRICHED OUTFLOWS DRIVEN BY ACTIVE GALACTIC NUCLEI IN CLUSTERS OF GALAXIES

    SciTech Connect

    Kirkpatrick, C. C.; McNamara, B. R.; Cavagnolo, K. W.

    2011-04-20

    We present an analysis of the spatial distribution of metal-rich gas in 10 galaxy clusters using deep observations from the Chandra X-ray Observatory. The brightest cluster galaxies (BCGs) have experienced recent active galactic nucleus activity in the forms of bright radio emission, cavities, and shock fronts embedded in the hot atmospheres. The heavy elements are distributed anisotropically and are aligned with the large-scale radio and cavity axes. They are apparently being transported from the halo of the BCG into the intracluster medium along large-scale outflows driven by the radio jets. The radial ranges of the metal-enriched outflows are found to scale with jet power as R{sub Fe} {proportional_to} P {sup 0.42}{sub jet}, with a scatter of only 0.5 dex. The heavy elements are transported beyond the extent of the inner cavities in all clusters, suggesting that this is a long-lasting effect sustained over multiple generations of outbursts. Black holes in BCGs will likely have difficulty ejecting metal-enriched gas beyond 1 Mpc unless their masses substantially exceed 10{sup 9} M{sub sun}.

  1. [Cluster analysis in biomedical researches].

    PubMed

    Akopov, A S; Moskovtsev, A A; Dolenko, S A; Savina, G D

    2013-01-01

    Cluster analysis is one of the most popular methods for the analysis of multi-parameter data. The cluster analysis reveals the internal structure of the data, group the separate observations on the degree of their similarity. The review provides a definition of the basic concepts of cluster analysis, and discusses the most popular clustering algorithms: k-means, hierarchical algorithms, Kohonen networks algorithms. Examples are the use of these algorithms in biomedical research. PMID:24640781

  2. Enriching Planning through Industry Analysis

    ERIC Educational Resources Information Center

    Martinez, Mario; Wolverton, Mimi

    2009-01-01

    Strategic planning is an important tool, but the sole dependence on it across departments and campuses has resulted in the underutilization of equally important methods of analysis. The evolution of higher and postsecondary education necessitates a systemic industry analysis, as the combination of new providers and delivery mechanisms and changing…

  3. STAR CLUSTERS IN M31. V. EVIDENCE FOR SELF-ENRICHMENT IN OLD M31 CLUSTERS FROM INTEGRATED SPECTROSCOPY

    SciTech Connect

    Schiavon, Ricardo P.; Caldwell, Nelson; Conroy, Charlie; Graves, Genevieve J.; Strader, Jay; MacArthur, Lauren A.; Courteau, Stéphane; Harding, Paul E-mail: caldwell@cfa.harvard.edu E-mail: graves@astro.princeton.edu E-mail: Lauren.MacArthur@nrc-cnrc.gc.ca E-mail: paul.harding@case.edu

    2013-10-10

    In the past decade, the notion that globular clusters (GCs) are composed of coeval stars with homogeneous initial chemical compositions has been challenged by growing evidence that they host an intricate stellar population mix, likely indicative of a complex history of star formation and chemical enrichment. Several models have been proposed to explain the existence of multiple stellar populations in GCs, but no single model provides a fully satisfactory match to existing data. Correlations between chemistry and global parameters such as cluster mass or luminosity are fundamental clues to the physics of GC formation. In this Letter, we present an analysis of the mean abundances of Fe, Mg, C, N, and Ca for 72 old GCs from the Andromeda galaxy. We show for the first time that there is a correlation between the masses of GCs and the mean stellar abundances of nitrogen, spanning almost two decades in mass. This result sheds new light on the formation of GCs, providing important constraints on their internal chemical evolution and mass loss history.

  4. Massive binary stars and self-enrichment of globular clusters

    NASA Astrophysics Data System (ADS)

    Izzard, R. G.; de Mink, S. E.; Pols, O. R.; Langer, N.; Sana, H.; de Koter, A.

    ~Globular clusters contain many stars with surface abundance patterns indicating contributions from hydrogen burning products, as seen in the anti-correlated elemental abundances of e.g. sodium and oxygen, and magnesium and aluminium. Multiple generations of stars can explain this phenomenon, with the second generation forming from a mixture of pristine gas and ejecta from the first generation. We show that massive binary stars may be a source of much of the material that makes this second generation of stars. Mass transfer in binaries is often non-conservative and the ejected matter moves slowly enough that it can remain inside a globular cluster and remain available for subsequent star formation. Recent studies show that there are more short-period massive binaries than previously thought, hence also more stars that interact and eject nuclear-processed material.

  5. Hemagglutinin clusters in the plasma membrane are not enriched with cholesterol and sphingolipids.

    PubMed

    Wilson, Robert L; Frisz, Jessica F; Klitzing, Haley A; Zimmerberg, Joshua; Weber, Peter K; Kraft, Mary L

    2015-04-01

    The clusters of the influenza envelope protein, hemagglutinin, within the plasma membrane are hypothesized to be enriched with cholesterol and sphingolipids. Here, we directly tested this hypothesis by using high-resolution secondary ion mass spectrometry to image the distributions of antibody-labeled hemagglutinin and isotope-labeled cholesterol and sphingolipids in the plasma membranes of fibroblast cells that stably express hemagglutinin. We found that the hemagglutinin clusters were neither enriched with cholesterol nor colocalized with sphingolipid domains. Thus, hemagglutinin clustering and localization in the plasma membrane is not controlled by cohesive interactions between hemagglutinin and liquid-ordered domains enriched with cholesterol and sphingolipids, or from specific binding interactions between hemagglutinin, cholesterol, and/or the majority of sphingolipid species in the plasma membrane. PMID:25863057

  6. Hemagglutinin Clusters in the Plasma Membrane Are Not Enriched with Cholesterol and Sphingolipids

    PubMed Central

    Wilson, Robert L.; Frisz, Jessica F.; Klitzing, Haley A.; Zimmerberg, Joshua; Weber, Peter K.; Kraft, Mary L.

    2015-01-01

    The clusters of the influenza envelope protein, hemagglutinin, within the plasma membrane are hypothesized to be enriched with cholesterol and sphingolipids. Here, we directly tested this hypothesis by using high-resolution secondary ion mass spectrometry to image the distributions of antibody-labeled hemagglutinin and isotope-labeled cholesterol and sphingolipids in the plasma membranes of fibroblast cells that stably express hemagglutinin. We found that the hemagglutinin clusters were neither enriched with cholesterol nor colocalized with sphingolipid domains. Thus, hemagglutinin clustering and localization in the plasma membrane is not controlled by cohesive interactions between hemagglutinin and liquid-ordered domains enriched with cholesterol and sphingolipids, or from specific binding interactions between hemagglutinin, cholesterol, and/or the majority of sphingolipid species in the plasma membrane. PMID:25863057

  7. Sample Level Enrichment Analysis of KEGG Pathways Identifies Clinically Relevant Subtypes of Glioblastoma

    PubMed Central

    Wanggou, Siyi; Feng, Chengyuan; Xie, Yuanyang; Ye, Linrong; Wang, Feiyifan; Li, Xuejun

    2016-01-01

    Background: Glioblastoma is the most lethal primary brain tumor in adults. Aberrant signal transduction pathways, associated with the progression of glioblastoma, have been identified recently and may offer a potential gene therapy strategy. Methods and Findings: We first used the sample level enrichment analysis to transfer gene expression profile of TCGA dataset into pathway enrichment z-score matrix. Then, we classified glioblastoma into five subtypes (Cluster A to Cluster E) by the consensus clustering and silhouette analysis. Principle component analysis showed the five subtype could be separated by first three principle components. Integrative omics data showed that mesenchymal subtype was rich in Cluster A, neural subtype was centered in Cluster D and proneural subtype was gathered in Cluster E, while Cluster E showed a high percentage of G-CIMP subtype. Additionally, according to analyze the overall survival and progression free survival of each subtype by Kaplan-Merie analysis and Cox hazard proportion model, we identified Cluster D and Cluster E received a better prognosis. Conclusions: We report a clinically relevant classification of glioblastoma based on sample level KEGG pathway enrichment profile and this novel classification system provided new insights into the heterogeneity of glioblastoma, and may be used as an important clinical tool to predict the prognosis.

  8. Globular clusters in the far-ultraviolet: evidence for He-enriched second populations in extra-galactic globular clusters?

    NASA Astrophysics Data System (ADS)

    Peacock, Mark B.; Zepf, Stephen E.; Kundu, Arunav; Chael, Julia

    2016-09-01

    We investigate the integrated far-ultraviolet (FUV) emission from globular clusters. We present new FUV photometry of M 87's clusters based on archival HST WFPC2 F170W observations. We use these data to test the reliability of published photometry based on HST STIS FUV-MAMA observations, which are now known to suffer from significant red-leak. We generally confirm these previous FUV detections, but suggest they may be somewhat fainter. We compare the FUV emission from bright (MV < -9.0) clusters in the Milky Way, M 31, M 81 and M 87 to each other and to the predictions from stellar populations models. Metal-rich globular clusters show a large spread in FUV - V, with some clusters in M 31, M 81 and M 87 being much bluer than standard predictions. This requires that some metal-rich clusters host a significant population of blue/extreme horizontal branch (HB) stars. These hot HB stars are not traditionally expected in metal-rich environments, but are a natural consequence of multiple populations in clusters - since the enriched population is observed to be He-enhanced and will therefore produce bluer HB stars, even at high metallicity. We conclude that the observed FUV emission from metal-rich clusters in M 31, M 81 and M 87 provides evidence that He-enhanced second populations, similar to those observed directly in the Milky Way, may be a ubiquitous feature of globular clusters in the local universe. Future HST FUV photometry is required to both confirm our interpretation of these archival data and provide constraints on He-enriched second populations of stars in extra-galactic globular clusters.

  9. The colour-magnitude relation of globular clusters in Centaurus and Hydra. Constraints on star cluster self-enrichment with a link to massive Milky Way globular clusters

    NASA Astrophysics Data System (ADS)

    Fensch, J.; Mieske, S.; Müller-Seidlitz, J.; Hilker, M.

    2014-07-01

    Aims: We investigate the colour-magnitude relation of metal-poor globular clusters, the so-called blue tilt, in the Hydra and Centaurus galaxy clusters and constrain the primordial conditions for star cluster self-enrichment. Methods: We analyse U,I photometry for about 2500 globular clusters in the central regions of Hydra and Centaurus, based on VLT/FORS1 data. We measure the relation between mean colour and luminosity for the blue and red subpopulation of the globular cluster samples. We convert these relations into mass-metallicity space and compare the obtained GC mass-metallicity relation with predictions from the star cluster self-enrichment model by Bailin & Harris (2009, ApJ, 695, 1082). For this we include effects of dynamical and stellar evolution and a physically well motivated primordial mass-radius scaling. Results: We obtain a mass-metallicity scaling of Z ∝ M0.27 ± 0.05 for Centaurus GCs and Z ∝ M0.40 ± 0.06 for Hydra GCs, consistent with the range of observed relations in other environments. We find that the GC mass-metallicity relation already sets in at present-day masses of a few and is well established in the luminosity range of massive MW clusters like ω Centauri. The inclusion of a primordial mass-radius scaling of star clusters significantly improves the fit of the self-enrichment model to the data. The self-enrichment model accurately reproduces the observed relations for average primordial half-light radii rh ~ 1-1.5 pc, star formation efficiencies f⋆ ~ 0.3-0.4, and pre-enrichment levels of [Fe/H] - 1.7 dex. The slightly steeper blue tilt for Hydra can be explained either by a ~30% smaller average rh at fixed f⋆ ~ 0.3, or analogously by a ~20% smaller f⋆ at fixed rh ~ 1.5 pc. Within the self-enrichment scenario, the observed blue tilt implies a correlation between GC mass and width of the stellar metallicity distribution. We find that this implied correlation matches the trend of width with GC mass measured in Galactic GCs

  10. Clusters of Antibiotic Resistance Genes Enriched Together Stay Together in Swine Agriculture

    PubMed Central

    Johnson, Timothy A.; Stedtfeld, Robert D.; Wang, Qiong; Cole, James R.; Hashsham, Syed A.; Looft, Torey; Zhu, Yong-Guan

    2016-01-01

    ABSTRACT   Antibiotic resistance is a worldwide health risk, but the influence of animal agriculture on the genetic context and enrichment of individual antibiotic resistance alleles remains unclear. Using quantitative PCR followed by amplicon sequencing, we quantified and sequenced 44 genes related to antibiotic resistance, mobile genetic elements, and bacterial phylogeny in microbiomes from U.S. laboratory swine and from swine farms from three Chinese regions. We identified highly abundant resistance clusters: groups of resistance and mobile genetic element alleles that cooccur. For example, the abundance of genes conferring resistance to six classes of antibiotics together with class 1 integrase and the abundance of IS6100-type transposons in three Chinese regions are directly correlated. These resistance cluster genes likely colocalize in microbial genomes in the farms. Resistance cluster alleles were dramatically enriched (up to 1 to 10% as abundant as 16S rRNA) and indicate that multidrug-resistant bacteria are likely the norm rather than an exception in these communities. This enrichment largely occurred independently of phylogenetic composition; thus, resistance clusters are likely present in many bacterial taxa. Furthermore, resistance clusters contain resistance genes that confer resistance to antibiotics independently of their particular use on the farms. Selection for these clusters is likely due to the use of only a subset of the broad range of chemicals to which the clusters confer resistance. The scale of animal agriculture and its wastes, the enrichment and horizontal gene transfer potential of the clusters, and the vicinity of large human populations suggest that managing this resistance reservoir is important for minimizing human risk. PMID:27073098

  11. Clusters of antibiotic resistance genes enriched together stay together in swine agriculture

    DOE PAGES

    Johnson, Timothy A.; Stedtfeld, Robert D.; Wang, Qiong; Cole, James R.; Hashsham, Syed A.; Looft, Torey; Zhu, Yong -Guan; Tiedje, James M.

    2016-04-12

    Antibiotic resistance is a worldwide health risk, but the influence of animal agriculture on the genetic context and enrichment of individual antibiotic resistance alleles remains unclear. Using quantitative PCR followed by amplicon sequencing, we quantified and sequenced 44 genes related to antibiotic resistance, mobile genetic elements, and bacterial phylogeny in microbiomes from U.S. laboratory swine and from swine farms from three Chinese regions. We identified highly abundant resistance clusters: groups of resistance and mobile genetic element alleles that cooccur. For example, the abundance of genes conferring resistance to six classes of antibiotics together with class 1 integrase and the abundancemore » of IS6100-type transposons in three Chinese regions are directly correlated. These resistance cluster genes likely colocalize in microbial genomes in the farms. Resistance cluster alleles were dramatically enriched (up to 1 to 10% as abundant as 16S rRNA) and indicate that multidrug-resistant bacteria are likely the norm rather than an exception in these communities. This enrichment largely occurred independently of phylogenetic composition; thus, resistance clusters are likely present in many bacterial taxa. Furthermore, resistance clusters contain resistance genes that confer resistance to antibiotics independently of their particular use on the farms. Selection for these clusters is likely due to the use of only a subset of the broad range of chemicals to which the clusters confer resistance. The scale of animal agriculture and its wastes, the enrichment and horizontal gene transfer potential of the clusters, and the vicinity of large human populations suggest that managing this resistance reservoir is important for minimizing human risk.Agricultural antibiotic use results in clusters of cooccurring resistance genes that together confer resistance to multiple antibiotics. The use of a single antibiotic could select for an entire suite of resistance

  12. A Component Analysis of Marriage Enrichment.

    ERIC Educational Resources Information Center

    Buston, Beverley G.; And Others

    Although marriage enrichment programs have been shown to be effective for many couples, a multidimensional approach to assessment is needed in investigating these groups. The components of information and social support in successful marriage enrichment programs were compared in a completely crossed 2 x 2 factorial design with repeated measures.…

  13. Network Analysis Tools: from biological networks to clusters and pathways.

    PubMed

    Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Vanderstocken, Gilles; van Helden, Jacques

    2008-01-01

    Network Analysis Tools (NeAT) is a suite of computer tools that integrate various algorithms for the analysis of biological networks: comparison between graphs, between clusters, or between graphs and clusters; network randomization; analysis of degree distribution; network-based clustering and path finding. The tools are interconnected to enable a stepwise analysis of the network through a complete analytical workflow. In this protocol, we present a typical case of utilization, where the tasks above are combined to decipher a protein-protein interaction network retrieved from the STRING database. The results returned by NeAT are typically subnetworks, networks enriched with additional information (i.e., clusters or paths) or tables displaying statistics. Typical networks comprising several thousands of nodes and arcs can be analyzed within a few minutes. The complete protocol can be read and executed in approximately 1 h.

  14. On Iron Enrichment, Star Formation, and Type Ia Supernovae in Galaxy Clusters

    NASA Technical Reports Server (NTRS)

    Loewenstein, Michael

    2006-01-01

    The nature of star formation and Type Ia supernovae (SNIa) in galaxies in the field and in rich galaxy clusters are contrasted by juxtaposing the buildup of heavy metals in the universe inferred from observed star formation and supernovae rate histories with data on the evolution of Fe abundances in the intracluster medium (ICM). Models for the chemical evolution of Fe in these environments are constructed, subject to observational constraints, for this purpose. While models with a mean delay for SNIa of 3 Gyr and standard initial mass function (IMF) are fully consistent with observations in the field, cluster Fe enrichment immediately tracked a rapid, top-heavy phase of star formation - although transport of Fe into the ICM may have been more prolonged and star formation likely continued beyond redshift 1. The means of this prompt enrichment consisted of SNII yielding greater than or equal to 0.1 solar mass per explosion (if the SNIa rate normalization is scaled down from its value in the field according to the relative number of candidate progenitor stars in the 3 - 8 solar mass range) and/or SNIa with short delay times originating during the rapid star formation epoch. Star formation is greater than 3 times more efficient in rich clusters than in the field, mitigating the overcooling problem in numerical cluster simulations. Both the fraction of baryons cycled through stars, and the fraction of the total present-day stellar mass in the form of stellar remnants, are substantially greater in clusters than in the field.

  15. Chemical enrichment in the hot intra-cluster medium seen with XMM-Newton/EPIC

    NASA Astrophysics Data System (ADS)

    Mernier, F.; de Plaa, J.; Pinto, C.; Kaastra, J.; Kosec, P.; Zhang, Y.; Mao, J.; Werner, N.

    2016-06-01

    The intra-cluster medium (ICM), permeating the large gravitational potential well of galaxy clusters and groups, is rich in metals, which can be detected via their emission lines in the soft X-ray band. These heavy elements (typically from O to Ni) have been synthesized by Type Ia (SNIa) and core-collapse (SNcc) supernovae within the galaxy members, and continuously enrich the ICM since the cosmic star formation peak (z ≃ 2-3). Because the predicted chemical yields of supernovae depend on either their explosion mechanisms (SNIa) or the initial mass and metallicity of their progenitors (SNcc), measuring the abundances in the ICM can help to constrain supernovae models. In this study, we use XMM-Newton/EPIC to measure the abundances of 9 elements (Mg, Si, S, Ar, Ca, Cr, Mn, Fe and Ni) in a sample of 44 cool-core galaxy clusters, groups and ellipticals (the CHEERS catalog). Combining these results with the O and Ne abundances measured using RGS, we establish an average X/Fe abundance pattern in the ICM, and we determine the best-fit SNIa and SNcc models, as well as the relative fraction of SNIa/SNcc responsible for the enrichment.

  16. IPAD: the Integrated Pathway Analysis Database for Systematic Enrichment Analysis

    PubMed Central

    2012-01-01

    Background Next-Generation Sequencing (NGS) technologies and Genome-Wide Association Studies (GWAS) generate millions of reads and hundreds of datasets, and there is an urgent need for a better way to accurately interpret and distill such large amounts of data. Extensive pathway and network analysis allow for the discovery of highly significant pathways from a set of disease vs. healthy samples in the NGS and GWAS. Knowledge of activation of these processes will lead to elucidation of the complex biological pathways affected by drug treatment, to patient stratification studies of new and existing drug treatments, and to understanding the underlying anti-cancer drug effects. There are approximately 141 biological human pathway resources as of Jan 2012 according to the Pathguide database. However, most currently available resources do not contain disease, drug or organ specificity information such as disease-pathway, drug-pathway, and organ-pathway associations. Systematically integrating pathway, disease, drug and organ specificity together becomes increasingly crucial for understanding the interrelationships between signaling, metabolic and regulatory pathway, drug action, disease susceptibility, and organ specificity from high-throughput omics data (genomics, transcriptomics, proteomics and metabolomics). Results We designed the Integrated Pathway Analysis Database for Systematic Enrichment Analysis (IPAD, http://bioinfo.hsc.unt.edu/ipad), defining inter-association between pathway, disease, drug and organ specificity, based on six criteria: 1) comprehensive pathway coverage; 2) gene/protein to pathway/disease/drug/organ association; 3) inter-association between pathway, disease, drug, and organ; 4) multiple and quantitative measurement of enrichment and inter-association; 5) assessment of enrichment and inter-association analysis with the context of the existing biological knowledge and a "gold standard" constructed from reputable and reliable sources; and 6

  17. Pancreatic islet enhancer clusters enriched in type 2 diabetes risk-associated variants.

    PubMed

    Pasquali, Lorenzo; Gaulton, Kyle J; Rodríguez-Seguí, Santiago A; Mularoni, Loris; Miguel-Escalada, Irene; Akerman, Ildem; Tena, Juan J; Morán, Ignasi; Gómez-Marín, Carlos; van de Bunt, Martijn; Ponsa-Cobas, Joan; Castro, Natalia; Nammo, Takao; Cebola, Inês; García-Hurtado, Javier; Maestro, Miguel Angel; Pattou, François; Piemonti, Lorenzo; Berney, Thierry; Gloyn, Anna L; Ravassard, Philippe; Gómez-Skarmeta, José Luis; Müller, Ferenc; McCarthy, Mark I; Ferrer, Jorge

    2014-02-01

    Type 2 diabetes affects over 300 million people, causing severe complications and premature death, yet the underlying molecular mechanisms are largely unknown. Pancreatic islet dysfunction is central in type 2 diabetes pathogenesis, and understanding islet genome regulation could therefore provide valuable mechanistic insights. We have now mapped and examined the function of human islet cis-regulatory networks. We identify genomic sequences that are targeted by islet transcription factors to drive islet-specific gene activity and show that most such sequences reside in clusters of enhancers that form physical three-dimensional chromatin domains. We find that sequence variants associated with type 2 diabetes and fasting glycemia are enriched in these clustered islet enhancers and identify trait-associated variants that disrupt DNA binding and islet enhancer activity. Our studies illustrate how islet transcription factors interact functionally with the epigenome and provide systematic evidence that the dysregulation of islet enhancers is relevant to the mechanisms underlying type 2 diabetes. PMID:24413736

  18. Pancreatic islet enhancer clusters enriched in type 2 diabetes risk–associated variants

    PubMed Central

    Mularoni, Loris; Miguel-Escalada, Irene; Akerman, İldem; Tena, Juan J.; Morán, Ignasi; Gómez-Marín, Carlos; van de Bunt, Martijn; Ponsa-Cobas, Joan; Castro, Natalia; Nammo, Takao; Cebola, Inês; García-Hurtado, Javier; Maestro, Miguel Angel; Pattou, François; Piemonti, Lorenzo; Berney, Thierry; Gloyn, Anna L.; Ravassard, Philippe; Skarmeta, José Luis Gómez; Müller, Ferenc; McCarthy, Mark I.; Ferrer, Jorge

    2013-01-01

    Type 2 diabetes affects over 300 million people, causing severe complications and premature death, yet the underlying molecular mechanisms are largely unknown. Pancreatic islet dysfunction is central for type 2 diabetes pathogenesis, and therefore understanding islet genome regulation could provide valuable mechanistic insights. We have now mapped and examined the function of human islet cis-regulatory networks. We identify genomic sequences that are targeted by islet transcription factors to drive islet-specific gene activity, and show that most such sequences reside in clusters of enhancers that form physical 3D chromatin domains. We find that sequence variants associated with type 2 diabetes and fasting glycemia are enriched in these clustered islet enhancers, and identify trait-associated variants that disrupt DNA-binding and islet enhancer activity. Our studies illustrate how islet transcription factors interact functionally with the epigenome, and provide systematic evidence that dysregulation of islet enhancers is relevant to the mechanisms underlying type 2 diabetes. PMID:24413736

  19. EVIDENCE FOR ENRICHMENT BY SUPERNOVAE IN THE GLOBULAR CLUSTER NGC 6273

    SciTech Connect

    Han, Sang-Il; Lim, Dongwook; Seo, Hyunju; Lee, Young-Wook

    2015-11-10

    In our recent investigation, we showed that narrowband photometry can be combined with low-resolution spectroscopy to effectively search for globular clusters (GCs) with supernova (SN) enrichments. Here we apply this technique to the metal-poor bulge GC NGC 6273 and find that the red giant branch stars in this GC are clearly divided into two distinct subpopulations with different calcium abundances. The Ca rich subpopulation in this GC is also enhanced in CN and CH, showing a positive correlation between them. This trend is identical to the result we found in M22, suggesting that this might be a ubiquitous nature of GCs more strongly affected by SNe in their chemical evolution. Our results suggest that NGC 6273 was massive enough to retain SN ejecta, which would place this cluster in the growing group of GCs with Galactic building block characteristics, such as ω Centauri and Terzan 5.

  20. A time course analysis of enriched composition.

    PubMed

    McElree, Brian; Pylkkänen, Liina; Pickering, Martin J; Traxler, Matthew J

    2006-02-01

    Linguistic analyses suggest that common and seemingly simple expressions, such as began the book, cannot be interpreted with simple compositional processes; rather, they require enriched composition to provide an interpretation, such as began reading the book (Jackendoff, 1997; Pustejovsky, 1995). Recent reading time studies have supported these accounts by providing evidence that these expressions are more costly to process than are minimally contrasting controls (e.g., McElree, Traxler, Pickering, Seely, and Jackendoff, 2001). We report a response signal speed-accuracy trade-off (SAT) study in which two types of expressions that are thought to require enriched composition were examined. Analyses of the full time course SAT data indicate that these expressions were interpreted less accurately and, most importantly, more slowly than control sentences. The latter finding suggests that enriched composition requires the online deployment of complex compositional operations.

  1. Functional Gene Networks: R/Bioc package to generate and analyse gene networks derived from functional enrichment and clustering

    PubMed Central

    Aibar, Sara; Fontanillo, Celia; Droste, Conrad; De Las Rivas, Javier

    2015-01-01

    Summary: Functional Gene Networks (FGNet) is an R/Bioconductor package that generates gene networks derived from the results of functional enrichment analysis (FEA) and annotation clustering. The sets of genes enriched with specific biological terms (obtained from a FEA platform) are transformed into a network by establishing links between genes based on common functional annotations and common clusters. The network provides a new view of FEA results revealing gene modules with similar functions and genes that are related to multiple functions. In addition to building the functional network, FGNet analyses the similarity between the groups of genes and provides a distance heatmap and a bipartite network of functionally overlapping genes. The application includes an interface to directly perform FEA queries using different external tools: DAVID, GeneTerm Linker, TopGO or GAGE; and a graphical interface to facilitate the use. Availability and implementation: FGNet is available in Bioconductor, including a tutorial. URL: http://bioconductor.org/packages/release/bioc/html/FGNet.html Contact: jrivas@usal.es Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25600944

  2. SUPERMODEL ANALYSIS OF GALAXY CLUSTERS

    SciTech Connect

    Fusco-Femiano, R.; Cavaliere, A.; Lapi, A.

    2009-11-01

    We present the analysis of the X-ray brightness and temperature profiles for six clusters belonging to both the Cool Core (CC) and Non Cool Core (NCC) classes, in terms of the Supermodel (SM) developed by Cavaliere et al. Based on the gravitational wells set by the dark matter (DM) halos, the SM straightforwardly expresses the equilibrium of the intracluster plasma (ICP) modulated by the entropy deposited at the boundary by standing shocks from gravitational accretion, and injected at the center by outgoing blast waves from mergers or from outbursts of active galactic nuclei. The cluster set analyzed here highlights not only how simply the SM represents the main dichotomy CC versus NCC clusters in terms of a few ICP parameters governing the radial entropy run, but also how accurately it fits even complex brightness and temperature profiles. For CC clusters like A2199 and A2597, the SM with a low level of central entropy straightforwardly yields the characteristic peaked profile of the temperature marked by a decline toward the center, without requiring currently strong radiative cooling and high mass deposition rates. NCC clusters like A1656 require instead a central entropy floor of a substantial level, and some like A2256 and even more A644 feature structured temperature profiles that also call for a definite floor extension; in such conditions the SM accurately fits the observations, and suggests that in these clusters the ICP has been just remolded by a merger event, in the way of a remnant cool core. The SM also predicts that DM halos with high concentration should correlate with flatter entropy profiles and steeper brightness in the outskirts; this is indeed the case with A1689, for which from X-rays we find concentration values c approx 10, the hallmark of an early halo formation. Thus, we show the SM to constitute a fast tool not only to provide wide libraries of accurate fits to X-ray temperature and density profiles, but also to retrieve from the ICP

  3. The SMART CLUSTER METHOD - adaptive earthquake cluster analysis and declustering

    NASA Astrophysics Data System (ADS)

    Schaefer, Andreas; Daniell, James; Wenzel, Friedemann

    2016-04-01

    Earthquake declustering is an essential part of almost any statistical analysis of spatial and temporal properties of seismic activity with usual applications comprising of probabilistic seismic hazard assessments (PSHAs) and earthquake prediction methods. The nature of earthquake clusters and subsequent declustering of earthquake catalogues plays a crucial role in determining the magnitude-dependent earthquake return period and its respective spatial variation. Various methods have been developed to address this issue from other researchers. These have differing ranges of complexity ranging from rather simple statistical window methods to complex epidemic models. This study introduces the smart cluster method (SCM), a new methodology to identify earthquake clusters, which uses an adaptive point process for spatio-temporal identification. Hereby, an adaptive search algorithm for data point clusters is adopted. It uses the earthquake density in the spatio-temporal neighbourhood of each event to adjust the search properties. The identified clusters are subsequently analysed to determine directional anisotropy, focussing on a strong correlation along the rupture plane and adjusts its search space with respect to directional properties. In the case of rapid subsequent ruptures like the 1992 Landers sequence or the 2010/2011 Darfield-Christchurch events, an adaptive classification procedure is applied to disassemble subsequent ruptures which may have been grouped into an individual cluster using near-field searches, support vector machines and temporal splitting. The steering parameters of the search behaviour are linked to local earthquake properties like magnitude of completeness, earthquake density and Gutenberg-Richter parameters. The method is capable of identifying and classifying earthquake clusters in space and time. It is tested and validated using earthquake data from California and New Zealand. As a result of the cluster identification process, each event in

  4. Multi-viewpoint clustering analysis

    NASA Technical Reports Server (NTRS)

    Mehrotra, Mala; Wild, Chris

    1993-01-01

    In this paper, we address the feasibility of partitioning rule-based systems into a number of meaningful units to enhance the comprehensibility, maintainability and reliability of expert systems software. Preliminary results have shown that no single structuring principle or abstraction hierarchy is sufficient to understand complex knowledge bases. We therefore propose the Multi View Point - Clustering Analysis (MVP-CA) methodology to provide multiple views of the same expert system. We present the results of using this approach to partition a deployed knowledge-based system that navigates the Space Shuttle's entry. We also discuss the impact of this approach on verification and validation of knowledge-based systems.

  5. The s-process enrichment of the globular clusters M4 and M22

    SciTech Connect

    Shingles, Luke J.; Karakas, Amanda I.; Fishlock, Cherie K.; Yong, David; Da Costa, Gary S.; Marino, Anna F.; Hirschi, Raphael

    2014-11-01

    We investigate the enrichment in elements produced by the slow neutron-capture process (s-process) in the globular clusters M4 (NGC 6121) and M22 (NGC 6656). Stars in M4 have homogeneous abundances of Fe and neutron-capture elements, but the entire cluster is enhanced in s-process elements (Sr, Y, Ba, Pb) relative to other clusters with a similar metallicity. In M22, two stellar groups exhibit different abundances of Fe and s-process elements. By subtracting the mean abundances of s-poor from s-rich stars, we derive s-process residuals or empirical s-process distributions for M4 and M22. We find that the s-process distribution in M22 is more weighted toward the heavy s-peak (Ba, La, Ce) and Pb than M4, which has been enriched mostly with light s-peak elements (Sr, Y, Zr). We construct simple chemical evolution models using yields from massive star models that include rotation, which dramatically increases s-process production at low metallicity. We show that our massive star models with rotation rates of up to 50% of the critical (break-up) velocity and changes to the preferred {sup 17}O(α, γ){sup 21}Ne rate produce insufficient heavy s-elements and Pb to match the empirical distributions. For models that incorporate asymptotic giant branch yields, we find that intermediate-mass yields (with a {sup 22}Ne neutron source) alone do not reproduce the light-to-heavy s-element ratios for M4 and M22, and that a small contribution from models with a {sup 13}C pocket is required. With our assumption that {sup 13}C pockets form for initial masses below a transition range between 3.0 and 3.5 M {sub ☉}, we match the light-to-heavy s-element ratio in the s-process residual of M22 and predict a minimum enrichment timescale of between 240 and 360 Myr. Our predicted value is consistent with the 300 Myr upper limit age difference between the two groups derived from isochrone fitting.

  6. Analysis of mosses and topsoils for detecting sources of heavy metal pollution: multivariate and enrichment factor analysis.

    PubMed

    Dragović, S; Mihailović, N

    2009-10-01

    In order to assess the contribution of emission sources to the pollution of areas remote from industrial facilities, a combined approach of enrichment factor analysis and multivariate statistics was used for detecting the origin of heavy metal pollution in the Zlatibor ecosystem, in Serbia. Samples of moss (Pleurozium schreberi, Hylocomium splendens, Scleropodium purum, Hypnum cupressiforme and Thuidum delicatulum) and of topsoil (0-5 cm) were collected in 2005. The concentrations of seven heavy metals (Cd, Cr, Cu, Mn, Ni, Pb and Zn) were determined in moss and soil samples by atomic absorption spectrometry. The results obtained by enrichment factor analysis and two multivariate statistical methods, principal component analysis and cluster analysis, enabled discrimination of the lithologic and anthropogenic sources of heavy metals in the mosses. Enrichment factors, calculated to evaluate the contribution to the metal content in moss from anthropogenic sources, revealed pollution of the investigated area by Cd and Pb, originating from long-range transport and fossil fuel burning.

  7. miEAA: microRNA enrichment analysis and annotation

    PubMed Central

    Backes, Christina; Khaleeq, Qurratulain T.; Meese, Eckart; Keller, Andreas

    2016-01-01

    Similar to the development of gene set enrichment and gene regulatory network analysis tools over a decade ago, microRNA enrichment tools are currently gaining importance. Building on our experience with the gene set analysis toolkit GeneTrail, we implemented the miRNA Enrichment Analysis and Annotation tool (miEAA). MiEAA is a web-based application that offers a variety of commonly applied statistical tests such as over-representation analysis and miRNA set enrichment analysis, which is similar to Gene Set Enrichment Analysis. Besides the different statistical tests, miEAA also provides rich functionality in terms of miRNA categories. Altogether, over 14 000 miRNA sets have been added, including pathways, diseases, organs and target genes. Importantly, our tool can be applied for miRNA precursors as well as mature miRNAs. To make the tool as useful as possible we additionally implemented supporting tools such as converters between different miRBase versions and converters from miRNA names to precursor names. We evaluated the performance of miEAA on two sets of miRNAs that are affected in lung adenocarcinomas and have been detected by array analysis. The web-based application is freely accessible at: http://www.ccb.uni-saarland.de/mieaa_tool/. PMID:27131362

  8. Multivariate Analysis of the Globular Clusters in M87

    NASA Astrophysics Data System (ADS)

    Das, Sukanta; Chattopadhayay, Tanuka; Davoust, Emmanuel

    2015-11-01

    An objective classification of 147 globular clusters (GCs) in the inner region of the giant elliptical galaxy M87 is carried out with the help of two methods of multivariate analysis. First, independent component analysis (ICA) is used to determine a set of independent variables that are linear combinations of various observed parameters (mostly Lick indices) of the GCs. Next, K-means cluster analysis (CA) is applied on the independent components (ICs), to find the optimum number of homogeneous groups having an underlying structure. The properties of the four groups of GCs thus uncovered are used to explain the formation mechanism of the host galaxy. It is suggested that M87 formed in two successive phases. First a monolithic collapse, which gave rise to an inner group of metal-rich clusters with little systematic rotation and an outer group of metal-poor clusters in eccentric orbits. In a second phase, the galaxy accreted low-mass satellites in a dissipationless fashion, from the gas of which the two other groups of GCs formed. Evidence is given for a blue stellar population in the more metal rich clusters, which we interpret by Helium enrichment. Finally, it is found that the clusters of M87 differ in some of their chemical properties (NaD, TiO1, light-element abundances) from GCs in our Galaxy and M31.

  9. A general abundance problem for all self-enrichment scenarios for the origin of multiple populations in globular clusters

    NASA Astrophysics Data System (ADS)

    Bastian, Nate; Cabrera-Ziri, Ivan; Salaris, Maurizio

    2015-05-01

    A number of stellar sources have been advocated as the origin of the enriched material required to explain the abundance anomalies seen in ancient globular clusters (GCs). Most studies to date have compared the yields from potential sources [asymptotic giant branch stars (AGBs), fast rotating massive stars (FRMS), high-mass interacting binaries (IBs), and very massive stars (VMS)] with observations of specific elements that are observed to vary from star-to-star in GCs, focusing on extreme GCs such as NGC 2808, which display large He variations. However, a consistency check between the results of fitting extreme cases with the requirements of more typical clusters, has rarely been done. Such a check is particularly timely given the constraints on He abundances in GCs now available. Here, we show that all of the popular enrichment sources fail to reproduce the observed trends in GCs, focusing primarily on Na, O and He. In particular, we show that any model that can fit clusters like NGC 2808, will necessarily fail (by construction) to fit more typical clusters like 47 Tuc or NGC 288. All sources severely overproduce He for most clusters. Additionally, given the large differences in He spreads between clusters, but similar spreads observed in Na-O, only sources with large degrees of stochasticity in the resulting yields will be able to fit the observations. We conclude that no enrichment source put forward so far (AGBs, FRMS, IBs, VMS - or combinations thereof) is consistent with the observations of GCs. Finally, the observed trends of increasing [N/Fe] and He spread with increasing cluster mass cannot be resolved within a self-enrichment framework, without further exacerbating the mass-budget problem.

  10. Quantitative mass spectrometric analysis of glycoproteins combined with enrichment methods.

    PubMed

    Ahn, Yeong Hee; Kim, Jin Young; Yoo, Jong Shin

    2015-01-01

    Mass spectrometry (MS) has been a core technology for high sensitive and high-throughput analysis of the enriched glycoproteome in aspects of quantitative assays as well as qualitative profiling of glycoproteins. Because it has been widely recognized that aberrant glycosylation in a glycoprotein may involve in progression of a certain disease, the development of efficient analysis tool for the aberrant glycoproteins is very important for deep understanding about pathological function of the glycoprotein and new biomarker development. This review first describes the protein glycosylation-targeting enrichment technologies mainly employing solid-phase extraction methods such as hydrizide-capturing, lectin-specific capturing, and affinity separation techniques based on porous graphitized carbon, hydrophilic interaction chromatography, or immobilized boronic acid. Second, MS-based quantitative analysis strategies coupled with the protein glycosylation-targeting enrichment technologies, by using a label-free MS, stable isotope-labeling, or targeted multiple reaction monitoring (MRM) MS, are summarized with recent published studies. PMID:24889823

  11. Quantitative mass spectrometric analysis of glycoproteins combined with enrichment methods.

    PubMed

    Ahn, Yeong Hee; Kim, Jin Young; Yoo, Jong Shin

    2015-01-01

    Mass spectrometry (MS) has been a core technology for high sensitive and high-throughput analysis of the enriched glycoproteome in aspects of quantitative assays as well as qualitative profiling of glycoproteins. Because it has been widely recognized that aberrant glycosylation in a glycoprotein may involve in progression of a certain disease, the development of efficient analysis tool for the aberrant glycoproteins is very important for deep understanding about pathological function of the glycoprotein and new biomarker development. This review first describes the protein glycosylation-targeting enrichment technologies mainly employing solid-phase extraction methods such as hydrizide-capturing, lectin-specific capturing, and affinity separation techniques based on porous graphitized carbon, hydrophilic interaction chromatography, or immobilized boronic acid. Second, MS-based quantitative analysis strategies coupled with the protein glycosylation-targeting enrichment technologies, by using a label-free MS, stable isotope-labeling, or targeted multiple reaction monitoring (MRM) MS, are summarized with recent published studies.

  12. An XMM-Newton Study of the Core of the Antlia Cluster: Heating and Chemical Enrichment in a Galaxy Cluster without a Cool Core

    NASA Astrophysics Data System (ADS)

    Hawley, William; Machacek, M.; Kraft, R. P.

    2011-09-01

    A fundamental question for models of structure formation is how energy and heavy elements are distributed throughout the intra-cluster medium (ICM) as the cluster evolves hierarchically by sub-cluster mergers along filaments in the cosmic web. The dominant dynamical processes -- hydrodynamic and tidal stripping, supernovae and stellar winds, bulk gas motions induced by mergers, and matter entrainment uplifted by AGN driven jets and buoyant bubbles -- create distinct X-ray signatures in surface brightness images and temperature and abundance maps of the cluster gas. The relative efficiencies of these processes during the early stages of cluster evolution are not well understood. We use a 53 ks XMM-Newton exposure of the inner 12 arcminutes of the Antlia cluster, the nearest example of a galaxy cluster in an intermediate merger stage without a cool core, to study energy and metal transport throughout the cluster gas. We construct density, temperature, pressure, entropy and abundance maps to identify gas motions and heat flows, relate these motions to the metal abundance ratios and gradients, and test simple models for chemical enrichment and heating of the Antlia cluster ICM.

  13. Network Enrichment Analysis in Complex Experiments*

    PubMed Central

    Shojaie, Ali; Michailidis, George

    2010-01-01

    Cellular functions of living organisms are carried out through complex systems of interacting components. Including such interactions in the analysis, and considering sub-systems defined by biological pathways instead of individual components (e.g. genes), can lead to new findings about complex biological mechanisms. Networks are often used to capture such interactions and can be incorporated in models to improve the efficiency in estimation and inference. In this paper, we propose a model for incorporating external information about interactions among genes (proteins/metabolites) in differential analysis of gene sets. We exploit the framework of mixed linear models and propose a flexible inference procedure for analysis of changes in biological pathways. The proposed method facilitates the analysis of complex experiments, including multiple experimental conditions and temporal correlations among observations. We propose an efficient iterative algorithm for estimation of the model parameters and show that the proposed framework is asymptotically robust to the presence of noise in the network information. The performance of the proposed model is illustrated through the analysis of gene expression data for environmental stress response (ESR) in yeast, as well as simulated data sets. PMID:20597848

  14. Cluster analysis of multiple planetary flow regimes

    NASA Technical Reports Server (NTRS)

    Mo, Kingtse; Ghil, Michael

    1987-01-01

    A modified cluster analysis method was developed to identify spatial patterns of planetary flow regimes, and to study transitions between them. This method was applied first to a simple deterministic model and second to Northern Hemisphere (NH) 500 mb data. The dynamical model is governed by the fully-nonlinear, equivalent-barotropic vorticity equation on the sphere. Clusters of point in the model's phase space are associated with either a few persistent or with many transient events. Two stationary clusters have patterns similar to unstable stationary model solutions, zonal, or blocked. Transient clusters of wave trains serve as way stations between the stationary ones. For the NH data, cluster analysis was performed in the subspace of the first seven empirical orthogonal functions (EOFs). Stationary clusters are found in the low-frequency band of more than 10 days, and transient clusters in the bandpass frequency window between 2.5 and 6 days. In the low-frequency band three pairs of clusters determine, respectively, EOFs 1, 2, and 3. They exhibit well-known regional features, such as blocking, the Pacific/North American (PNA) pattern and wave trains. Both model and low-pass data show strong bimodality. Clusters in the bandpass window show wave-train patterns in the two jet exit regions. They are related, as in the model, to transitions between stationary clusters.

  15. Separate enrichment analysis of pathways for up- and downregulated genes.

    PubMed

    Hong, Guini; Zhang, Wenjing; Li, Hongdong; Shen, Xiaopei; Guo, Zheng

    2014-03-01

    Two strategies are often adopted for enrichment analysis of pathways: the analysis of all differentially expressed (DE) genes together or the analysis of up- and downregulated genes separately. However, few studies have examined the rationales of these enrichment analysis strategies. Using both microarray and RNA-seq data, we show that gene pairs with functional links in pathways tended to have positively correlated expression levels, which could result in an imbalance between the up- and downregulated genes in particular pathways. We then show that the imbalance could greatly reduce the statistical power for finding disease-associated pathways through the analysis of all-DE genes. Further, using gene expression profiles from five types of tumours, we illustrate that the separate analysis of up- and downregulated genes could identify more pathways that are really pertinent to phenotypic difference. In conclusion, analysing up- and downregulated genes separately is more powerful than analysing all of the DE genes together.

  16. First solid-state NMR analysis of uniformly ¹³C-enriched major light-harvesting complexes from Chlamydomonas reinhardtii and identification of protein and cofactor spin clusters.

    PubMed

    Pandit, Anjali; Morosinotto, Tomas; Reus, Michael; Holzwarth, Alfred R; Bassi, Roberto; de Groot, Huub J M

    2011-04-01

    The light-harvesting complex II (LHCII) is the main component of the antenna system of plants and green algae and plays a major role in the capture of sun light for photosynthesis. The LHCII complexes have also been proposed to play a key role in the optimization of photosynthetic efficiency through the process of state 1-state 2 transitions and are involved in down-regulation of photosynthesis under excess light by energy dissipation through non-photochemical quenching (NPQ). We present here the first solid-state magic-angle spinning (MAS) NMR data of the major light-harvesting complex (LHCII) of Chlamydomonas reinhardtii, a eukaryotic green alga. We are able to identify nuclear spin clusters of the protein and of its associated chlorophyll pigments in ¹³C-¹³C dipolar homonuclear correlation spectra on a uniformly ¹³C-labeled sample. In particular, we were able to resolve several chlorophyll 13¹ carbon resonances that are sensitive to hydrogen bonding to the 13¹-keto carbonyl group. The data show that ¹³C NMR signals of the pigments and protein sites are well resolved, thus paving the way to study possible structural reorganization processes involved in light-harvesting regulation through MAS solid-state NMR. PMID:21276419

  17. Central Elemental Abundance Ratios In the Perseus Cluster: Resonant Scattering or SN Ia Enrichment?

    NASA Technical Reports Server (NTRS)

    Dupke, Renato A.; Arnaud, Keith; White, Nicholas E. (Technical Monitor)

    2001-01-01

    We have determined abundance ratios in the core of the Perseus Cluster for several elements. These ratios indicate a central dominance of Type 1a supernova (SN Ia) ejects similar to that found for A496, A2199 and A3571. Simultaneous analysis of ASCA spectra from SIS1, GIS2, and GIS3 shows that the ratio of Ni to Fe abundances is approx. 3.4 +/- 1.1 times solar within the central 4'. This ratio is consistent with (and more precise than) that observed in other clusters whose central regions are dominated by SN Ia ejecta. Such a large Ni overabundance is predicted by "convective deflagration" explosion models for SNe Ia such as W7 but is inconsistent with delayed detonation models. We note that with current instrumentation the Ni K(alpha) line is confused with Fe K(beta) and that the Ni overabundance we observe has been interpreted by others as an anomalously large ratio of Fe K(beta) to Fe K(alpha) caused by resonant scattering in the Fe K(alpha) line. We argue that a central enhancement of SN Ia ejecta and hence a high ratio of Ni to Fe abundances are naturally explained by scenarios that include the generation of chemical gradients by suppressed SN Ia winds or ram pressure stripping of cluster galaxies. It is not necessary to suppose that the intracluster gas is optically thick to resonant scattering of the Fe K(alpha) line.

  18. Increasing the performance of tritium analysis by electrolytic enrichment.

    PubMed

    Groning, M; Auer, R; Brummer, D; Jaklitsch, M; Sambandam, C; Tanweer, A; Tatzber, H

    2009-06-01

    Several improvements are described for the existing tritium enrichment system at the Isotope Hydrology Laboratory of the International Atomic Energy Agency for processing natural water samples. The improvements include a simple method for pretreatment of electrolytic cells to ensure a high tritium separation factor, an improved design of the exhaust system for explosive gases, and a vacuum distillation line for faster initial preparation of water samples for electrolytic enrichment and for tritium analysis. Achievements included the reduction of variation of individual enrichment parameters of all cells to less than 1% and an improvement of 50% of the stability of the background mean. It resulted in an improved detection limit of less than 0.4 TU (at 2s), important for application of tritium measurements in the future at low concentration levels, and resulted in measurement precisions of+/-0.2 TU and+/-0.15 TU for liquid scintillation counting and for gas proportional counting, respectively. PMID:20183225

  19. Cluster Analysis of Adolescent Blogs

    ERIC Educational Resources Information Center

    Liu, Eric Zhi-Feng; Lin, Chun-Hung; Chen, Feng-Yi; Peng, Ping-Chuan

    2012-01-01

    Emerging web applications and networking systems such as blogs have become popular, and they offer unique opportunities and environments for learners, especially for adolescent learners. This study attempts to explore the writing styles and genres used by adolescents in their blogs by employing content, factor, and cluster analyses. Factor…

  20. Cluster Analysis of the Malaysian Hipposideros

    NASA Astrophysics Data System (ADS)

    Sazali, Siti Nurlydia; Laman, Charlie J.; Abdullah, M. T.

    2008-01-01

    A preliminary study on the morphometric variations among species in the genus Hipposideros was conducted using voucher specimens from the Universiti Malaysia Sarawak (UNIMAS) Zoological Museum and the Department of Wildlife and National Park (DWNP) Kuala Lumpur. A total of 24 individuals from six species of this genus were morphologically studied where all related measurements of body, skull and dental were measured and recorded. The statistical data subjected to the cluster analysis shows that the genus Hipposideros is divided into two major clusters where each species was clearly separated. The cluster analysis among Hipposideros species is useful for aiding in species identification.

  1. The mechanism of solute-enriched clusters formation in neutron-irradiated pressure vessel steels: The case of Fe-Cu model alloys

    NASA Astrophysics Data System (ADS)

    Subbotin, A. V.; Panyukov, S. V.

    2016-08-01

    Mechanism of solute-enriched clusters formation in neutron-irradiated pressure vessel steels is proposed and developed in case of Fe-Cu model alloys. The suggested solute-drag mechanism is analogous to the well-known zone-refining process. We show that the obtained results are in good agreement with available experimental data on the parameters of clusters enriched with the alloying elements. Our model explains why the formation of solute-enriched clusters does not happen in austenitic stainless steels with fcc lattice structure. It also allows to quantify the method of evaluation of neutron irradiation dose for the process of RPV steels hardening.

  2. Correcting an analysis of variance for clustering.

    PubMed

    Hedges, Larry V; Rhoads, Christopher H

    2011-02-01

    A great deal of educational and social data arises from cluster sampling designs where clusters involve schools, classrooms, or communities. A mistake that is sometimes encountered in the analysis of such data is to ignore the effect of clustering and analyse the data as if it were based on a simple random sample. This typically leads to an overstatement of the precision of results and too liberal conclusions about precision and statistical significance of mean differences. This paper gives simple corrections to the test statistics that would be computed in an analysis of variance if clustering were (incorrectly) ignored. The corrections are multiplicative factors depending on the total sample size, the cluster size, and the intraclass correlation structure. For example, the corrected F statistic has Fisher's F distribution with reduced degrees of freedom. The corrected statistic reduces to the F statistic computed by ignoring clustering when the intraclass correlations are zero. It reduces to the F statistic computed using cluster means when the intraclass correlations are unity, and it is in between otherwise. A similar adjustment to the usual statistic for testing a linear contrast among group means is described.

  3. Onsite Gaseous Centrifuge Enrichment Plant UF6 Cylinder Destructive Analysis

    SciTech Connect

    Anheier, Norman C.; Cannon, Bret D.; Qiao, Hong; Carter, Jennifer C.; McNamara, Bruce K.; O'Hara, Matthew J.; Phillips, Jon R.; Curtis, Michael M.

    2012-07-17

    The IAEA safeguards approach for gaseous centrifuge enrichment plants (GCEPs) includes measurements of gross, partial, and bias defects in a statistical sampling plan. These safeguard methods consist principally of mass and enrichment nondestructive assay (NDA) verification. Destructive assay (DA) samples are collected from a limited number of cylinders for high precision offsite mass spectrometer analysis. DA is typically used to quantify bias defects in the GCEP material balance. Under current safeguards measures, the operator collects a DA sample from a sample tap following homogenization. The sample is collected in a small UF6 sample bottle, then sealed and shipped under IAEA chain of custody to an offsite analytical laboratory. Current practice is expensive and resource intensive. We propose a new and novel approach for performing onsite gaseous UF6 DA analysis that provides rapid and accurate assessment of enrichment bias defects. DA samples are collected using a custom sampling device attached to a conventional sample tap. A few micrograms of gaseous UF6 is chemically adsorbed onto a sampling coupon in a matter of minutes. The collected DA sample is then analyzed onsite using Laser Ablation Absorption Ratio Spectrometry-Destructive Assay (LAARS-DA). DA results are determined in a matter of minutes at sufficient accuracy to support reliable bias defect conclusions, while greatly reducing DA sample volume, analysis time, and cost.

  4. QUANTITATIVE MASS SPECTROMETRIC ANALYSIS OF GLYCOPROTEINS COMBINED WITH ENRICHMENT METHODS

    PubMed Central

    Ahn, Yeong Hee; Kim, Jin Young; Yoo, Jong Shin

    2015-01-01

    Mass spectrometry (MS) has been a core technology for high sensitive and high-throughput analysis of the enriched glycoproteome in aspects of quantitative assays as well as qualitative profiling of glycoproteins. Because it has been widely recognized that aberrant glycosylation in a glycoprotein may involve in progression of a certain disease, the development of efficient analysis tool for the aberrant glycoproteins is very important for deep understanding about pathological function of the glycoprotein and new biomarker development. This review first describes the protein glycosylation-targeting enrichment technologies mainly employing solid-phase extraction methods such as hydrizide-capturing, lectin-specific capturing, and affinity separation techniques based on porous graphitized carbon, hydrophilic interaction chromatography, or immobilized boronic acid. Second, MS-based quantitative analysis strategies coupled with the protein glycosylation-targeting enrichment technologies, by using a label-free MS, stable isotope-labeling, or targeted multiple reaction monitoring (MRM) MS, are summarized with recent published studies. © 2014 The Authors. Mass Spectrometry Reviews Published by Wiley Periodicals, Inc. Rapid Commun. Mass Spec Rev 34:148–165, 2015. PMID:24889823

  5. ASteCA: Automated Stellar Cluster Analysis

    NASA Astrophysics Data System (ADS)

    Perren, G. I.; Vázquez, R. A.; Piatti, A. E.

    2015-04-01

    We present the Automated Stellar Cluster Analysis package (ASteCA), a suit of tools designed to fully automate the standard tests applied on stellar clusters to determine their basic parameters. The set of functions included in the code make use of positional and photometric data to obtain precise and objective values for a given cluster's center coordinates, radius, luminosity function and integrated color magnitude, as well as characterizing through a statistical estimator its probability of being a true physical cluster rather than a random overdensity of field stars. ASteCA incorporates a Bayesian field star decontamination algorithm capable of assigning membership probabilities using photometric data alone. An isochrone fitting process based on the generation of synthetic clusters from theoretical isochrones and selection of the best fit through a genetic algorithm is also present, which allows ASteCA to provide accurate estimates for a cluster's metallicity, age, extinction and distance values along with its uncertainties. To validate the code we applied it on a large set of over 400 synthetic MASSCLEAN clusters with varying degrees of field star contamination as well as a smaller set of 20 observed Milky Way open clusters (Berkeley 7, Bochum 11, Czernik 26, Czernik 30, Haffner 11, Haffner 19, NGC 133, NGC 2236, NGC 2264, NGC 2324, NGC 2421, NGC 2627, NGC 6231, NGC 6383, NGC 6705, Ruprecht 1, Tombaugh 1, Trumpler 1, Trumpler 5 and Trumpler 14) studied in the literature. The results show that ASteCA is able to recover cluster parameters with an acceptable precision even for those clusters affected by substantial field star contamination. ASteCA is written in Python and is made available as an open source code which can be downloaded ready to be used from its official site.

  6. Using Cluster Analysis to Examine Husband-Wife Decision Making

    ERIC Educational Resources Information Center

    Bonds-Raacke, Jennifer M.

    2006-01-01

    Cluster analysis has a rich history in many disciplines and although cluster analysis has been used in clinical psychology to identify types of disorders, its use in other areas of psychology has been less popular. The purpose of the current experiments was to use cluster analysis to investigate husband-wife decision making. Cluster analysis was…

  7. LISSAT Analysis of a Generic Centrifuge Enrichment Plant

    SciTech Connect

    Lambert, H; Elayat, H A; O?Connell, W J; Szytel, L; Dreicer, M

    2007-05-31

    The U.S. Department of Energy (DOE) is interested in developing tools and methods for use in designing and evaluating safeguards systems for current and future plants in the nuclear power fuel cycle. The DOE is engaging several DOE National Laboratories in efforts applied to safeguards for chemical conversion plants and gaseous centrifuge enrichment plants. As part of the development, Lawrence Livermore National Laboratory has developed an integrated safeguards system analysis tool (LISSAT). This tool provides modeling and analysis of facility and safeguards operations, generation of diversion paths, and evaluation of safeguards system effectiveness. The constituent elements of diversion scenarios, including material extraction and concealment measures, are structured using directed graphs (digraphs) and fault trees. Statistical analysis evaluates the effectiveness of measurement verification plans and randomly timed inspections. Time domain simulations analyze significant scenarios, especially those involving alternate time ordering of events or issues of timeliness. Such simulations can provide additional information to the fault tree analysis and can help identify the range of normal operations and, by extension, identify additional plant operational signatures of diversions. LISSAT analyses can be used to compare the diversion-detection probabilities for individual safeguards technologies and to inform overall strategy implementations for present and future plants. Additionally, LISSAT can be the basis for a rigorous cost-effectiveness analysis of safeguards and design options. This paper will describe the results of a LISSAT analysis of a generic centrifuge enrichment plant. The paper will describe the diversion scenarios analyzed and the effectiveness of various safeguards systems alternatives.

  8. Clustering analysis of seismicity and aftershock identification.

    PubMed

    Zaliapin, Ilya; Gabrielov, Andrei; Keilis-Borok, Vladimir; Wong, Henry

    2008-07-01

    We introduce a statistical methodology for clustering analysis of seismicity in the time-space-energy domain and use it to establish the existence of two statistically distinct populations of earthquakes: clustered and nonclustered. This result can be used, in particular, for nonparametric aftershock identification. The proposed approach expands the analysis of Baiesi and Paczuski [Phys. Rev. E 69, 066106 (2004)10.1103/PhysRevE.69.066106] based on the space-time-magnitude nearest-neighbor distance eta between earthquakes. We show that for a homogeneous Poisson marked point field with exponential marks, the distance eta has the Weibull distribution, which bridges our results with classical correlation analysis for point fields. The joint 2D distribution of spatial and temporal components of eta is used to identify the clustered part of a point field. The proposed technique is applied to several seismicity models and to the observed seismicity of southern California.

  9. MAVTgsa: An R Package for Gene Set (Enrichment) Analysis

    DOE PAGES

    Chien, Chih-Yi; Chang, Ching-Wei; Tsai, Chen-An; Chen, James J.

    2014-01-01

    Gene semore » t analysis methods aim to determine whether an a priori defined set of genes shows statistically significant difference in expression on either categorical or continuous outcomes. Although many methods for gene set analysis have been proposed, a systematic analysis tool for identification of different types of gene set significance modules has not been developed previously. This work presents an R package, called MAVTgsa, which includes three different methods for integrated gene set enrichment analysis. (1) The one-sided OLS (ordinary least squares) test detects coordinated changes of genes in gene set in one direction, either up- or downregulation. (2) The two-sided MANOVA (multivariate analysis variance) detects changes both up- and downregulation for studying two or more experimental conditions. (3) A random forests-based procedure is to identify gene sets that can accurately predict samples from different experimental conditions or are associated with the continuous phenotypes. MAVTgsa computes the P values and FDR (false discovery rate) q -value for all gene sets in the study. Furthermore, MAVTgsa provides several visualization outputs to support and interpret the enrichment results. This package is available online.« less

  10. Bayesian Analysis of Multiple Populations in Galactic Globular Clusters

    NASA Astrophysics Data System (ADS)

    Wagner-Kaiser, Rachel A.; Sarajedini, Ata; von Hippel, Ted; Stenning, David; Piotto, Giampaolo; Milone, Antonino; van Dyk, David A.; Robinson, Elliot; Stein, Nathan

    2016-01-01

    We use GO 13297 Cycle 21 Hubble Space Telescope (HST) observations and archival GO 10775 Cycle 14 HST ACS Treasury observations of Galactic Globular Clusters to find and characterize multiple stellar populations. Determining how globular clusters are able to create and retain enriched material to produce several generations of stars is key to understanding how these objects formed and how they have affected the structural, kinematic, and chemical evolution of the Milky Way. We employ a sophisticated Bayesian technique with an adaptive MCMC algorithm to simultaneously fit the age, distance, absorption, and metallicity for each cluster. At the same time, we also fit unique helium values to two distinct populations of the cluster and determine the relative proportions of those populations. Our unique numerical approach allows objective and precise analysis of these complicated clusters, providing posterior distribution functions for each parameter of interest. We use these results to gain a better understanding of multiple populations in these clusters and their role in the history of the Milky Way.Support for this work was provided by NASA through grant numbers HST-GO-10775 and HST-GO-13297 from the Space Telescope Science Institute, which is operated by AURA, Inc., under NASA contract NAS5-26555. This material is based upon work supported by the National Aeronautics and Space Administration under Grant NNX11AF34G issued through the Office of Space Science. This project was supported by the National Aeronautics & Space Administration through the University of Central Florida's NASA Florida Space Grant Consortium.

  11. RHAPSODY-G simulations - II. Baryonic growth and metal enrichment in massive galaxy clusters

    NASA Astrophysics Data System (ADS)

    Martizzi, Davide; Hahn, Oliver; Wu, Hao-Yi; Evrard, August E.; Teyssier, Romain; Wechsler, Risa H.

    2016-07-01

    We study the evolution of the stellar component and the metallicity of both the intracluster medium and of stars in massive (Mvir ≈ 6 × 1014 M⊙ h-1) simulated galaxy clusters from the RHAPSODY-G suite in detail and compare them to observational results. The simulations were performed with the AMR code RAMSES and include the effect of active galactic nucleus (AGN) feedback at the subgrid level. AGN feedback is required to produce realistic galaxy and cluster properties and plays a role in mixing material in the central regions and regulating star formation in the central galaxy. In both our low- and high-resolution runs with fiducial stellar yields, we find that stellar and ICM metallicities are a factor of 2 lower than in observations. We find that cool core clusters exhibit steeper metallicity gradients than non-cool core clusters, in qualitative agreement with observations. We verify that the ICM metallicities measured in the simulation can be explained by a simple `regulator' model in which the metallicity is set by a balance of stellar yield and gas accretion. It is plausible that a combination of higher resolution and higher metal yield in AMR simulation would allow the metallicity of simulated clusters to match observed values; however, this hypothesis needs to be tested with future simulations. Comparison to recent literature highlights that results concerning the metallicity of clusters and cluster galaxies might depend sensitively on the scheme chosen to solve the hydrodynamics.

  12. Cluster and constraint analysis in tetrahedron packings.

    PubMed

    Jin, Weiwei; Lu, Peng; Liu, Lufeng; Li, Shuixiang

    2015-04-01

    The disordered packings of tetrahedra often show no obvious macroscopic orientational or positional order for a wide range of packing densities, and it has been found that the local order in particle clusters is the main order form of tetrahedron packings. Therefore, a cluster analysis is carried out to investigate the local structures and properties of tetrahedron packings in this work. We obtain a cluster distribution of differently sized clusters, and peaks are observed at two special clusters, i.e., dimer and wagon wheel. We then calculate the amounts of dimers and wagon wheels, which are observed to have linear or approximate linear correlations with packing density. Following our previous work, the amount of particles participating in dimers is used as an order metric to evaluate the order degree of the hierarchical packing structure of tetrahedra, and an order map is consequently depicted. Furthermore, a constraint analysis is performed to determine the isostatic or hyperstatic region in the order map. We employ a Monte Carlo algorithm to test jamming and then suggest a new maximally random jammed packing of hard tetrahedra from the order map with a packing density of 0.6337.

  13. Identifying Peer Institutions Using Cluster Analysis

    ERIC Educational Resources Information Center

    Boronico, Jess; Choksi, Shail S.

    2012-01-01

    The New York Institute of Technology's (NYIT) School of Management (SOM) wishes to develop a list of peer institutions for the purpose of benchmarking and monitoring/improving performance against other business schools. The procedure utilizes relevant criteria for the purpose of establishing this peer group by way of a cluster analysis. The…

  14. An application of MeSH enrichment analysis in livestock.

    PubMed

    Morota, G; Peñagaricano, F; Petersen, J L; Ciobanu, D C; Tsuyuzaki, K; Nikaido, I

    2015-08-01

    An integral part of functional genomics studies is to assess the enrichment of specific biological terms in lists of genes found to be playing an important role in biological phenomena. Contrasting the observed frequency of annotated terms with those of the background is at the core of overrepresentation analysis (ORA). Gene Ontology (GO) is a means to consistently classify and annotate gene products and has become a mainstay in ORA. Alternatively, Medical Subject Headings (MeSH) offers a comprehensive life science vocabulary including additional categories that are not covered by GO. Although MeSH is applied predominantly in human and model organism research, its full potential in livestock genetics is yet to be explored. In this study, MeSH ORA was evaluated to discern biological properties of identified genes and contrast them with the results obtained from GO enrichment analysis. Three published datasets were employed for this purpose, representing a gene expression study in dairy cattle, the use of SNPs for genome-wide prediction in swine and the identification of genomic regions targeted by selection in horses. We found that several overrepresented MeSH annotations linked to these gene sets share similar concepts with those of GO terms. Moreover, MeSH yielded unique annotations, which are not directly provided by GO terms, suggesting that MeSH has the potential to refine and enrich the representation of biological knowledge. We demonstrated that MeSH can be regarded as another choice of annotation to draw biological inferences from genes identified via experimental analyses. When used in combination with GO terms, our results indicate that MeSH can enhance our functional interpretations for specific biological conditions or the genetic basis of complex traits in livestock species.

  15. Systematization of actinides using cluster analysis

    SciTech Connect

    Kopyrin, A.A.; Terent`eva, T.N.; Khramov, N.N.

    1994-11-01

    A representation of the actinides in multidimensional property space is proposed for systematization of these elements using cluster analysis. Literature data for their atomic properties are used. Owing to the wide variation of published ionization potentials, medians are used to estimate them. Vertical dendograms are used for classification on the basis of distances between the actinides in atomic-property space. The properties of actinium and lawrencium are furthest removed from the main group. Thorium and mendelevium exhibit individualized properties. A cluster based on the einsteinium-fermium pair is joined by californium.

  16. Improved Methods for the Enrichment and Analysis of Glycated Peptides

    SciTech Connect

    Zhang, Qibin; Schepmoes, Athena A; Brock, Jonathan W; Wu, Si; Moore, Ronald J; Purvine, Samuel O; Baynes, John; Smith, Richard D; Metz, Thomas O

    2008-12-15

    Non-enzymatic glycation of tissue proteins has important implications in the development of complications of diabetes mellitus. Herein we report improved methods for the enrichment and analysis of glycated peptides using boronate affinity chromatography and electron transfer dissociation mass spectrometry, respectively. The enrichment of glycated peptides was improved by replacing an off-line desalting step with an on-line wash of column-bound glycated peptides using 50 mM ammonium acetate. The analysis of glycated peptides by MS/MS was improved by considering only higher charged (≥3) precursor-ions during data-dependent acquisition, which increased the number of glycated peptide identifications. Similarly, the use of supplemental collisional activation after electron transfer (ETcaD) resulted in more glycated peptide identifications when the MS survey scan was acquired with enhanced resolution. In general, acquiring ETD-MS/MS data at a normal MS survey scan rate, in conjunction with the rejection of both 1+ and 2+ precursor-ions, increased the number of identified glycated peptides relative to ETcaD or the enhanced MS survey scan rate. Finally, an evaluation of trypsin, Arg-C, and Lys-C showed that tryptic digestion of glycated proteins was comparable to digestion with Lys-C and that both were better than Arg-C in terms of the number glycated peptides identified by LC-MS/MS.

  17. Bacterial isolates from polysaccharide enrichments cluster by host origin for Firmicutes but not Bacteroidetes.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The intestinal microbiota allows mammals to recover energy stored in plant biomass through fermentation of plant cell walls, primarily cellulose and hemicellulose. Bacteria were isolated from 8 week continuous culture enrichments with cellulose and xylan/pectin from cow (C, n=4), goat (G, n=4), huma...

  18. Using Enrichment Clusters to Address the Needs of Culturally and Linguistically Diverse Learners

    ERIC Educational Resources Information Center

    Allen, Jennifer K.; Robbins, Margaret A.; Payne, Yolanda Denise; Brown, Katherine Backes

    2016-01-01

    Using data from teacher interviews, classroom observations, and a professional development workshop, this article explains how one component of the schoolwide enrichment model (SEM) has been implemented at a culturally diverse elementary school serving primarily Latina/o and African American students. Based on a broadened conception of giftedness,…

  19. A Multivariate Analysis of Galaxy Cluster Properties

    NASA Astrophysics Data System (ADS)

    Ogle, P. M.; Djorgovski, S.

    1993-05-01

    We have assembled from the literature a data base on on 394 clusters of galaxies, with up to 16 parameters per cluster. They include optical and x-ray luminosities, x-ray temperatures, galaxy velocity dispersions, central galaxy and particle densities, optical and x-ray core radii and ellipticities, etc. In addition, derived quantities, such as the mass-to-light ratios and x-ray gas masses are included. Doubtful measurements have been identified, and deleted from the data base. Our goal is to explore the correlations between these parameters, and interpret them in the framework of our understanding of evolution of clusters and large-scale structure, such as the Gott-Rees scaling hierarchy. Among the simple, monovariate correlations we found, the most significant include those between the optical and x-ray luminosities, x-ray temperatures, cluster velocity dispersions, and central galaxy densities, in various mutual combinations. While some of these correlations have been discussed previously in the literature, generally smaller samples of objects have been used. We will also present the results of a multivariate statistical analysis of the data, including a principal component analysis (PCA). Such an approach has not been used previously for studies of cluster properties, even though it is much more powerful and complete than the simple monovariate techniques which are commonly employed. The observed correlations may lead to powerful constraints for theoretical models of formation and evolution of galaxy clusters. P.M.O. was supported by a Caltech graduate fellowship. S.D. acknowledges a partial support from the NASA contract NAS5-31348 and the NSF PYI award AST-9157412.

  20. Cluster analysis of respiratory time series.

    PubMed

    Adams, J M; Attinger, E O; Attinger, F M

    1978-03-01

    We have investigated the respiratory control system with the hypothesis that, although many variables such as minute ventilation (VI), tidal volume (VT), breathing period (TT), inspiratory duration (TI), and expiratory duration (TE) may be observed, the controller functions more simply by manipulating only 2 or 3 of these. Thus, if tidal volume is the only independent variable, TI being determined by the "off-switch" threshold, these variables should have very similar time courses. Anesthetized dogs were subjected to CO2 breathing and carotid sinus perfusion to stimulate both chemoreceptors. The time series of the variables VI, VT, TT, TE, and TI as well as PACO2 were determined on a breath by breath basis. Derived characteristics of these time series were compared using Cluster Analysis and the latent dimensionality of respiratory control determined by Factor Analysis. The characteristics of the time series clustered into 4 groups: magnitude (of the response), speed, variability and relative change. One respiratory factor accounted for 86% of the variance for the variability characteristics, 2 factors for magnitude (91%) and relative change (85%) and 3 factors for speed (89%). The respiratory variables were analysed for each of the 4 groups of characteristics with the following results: VT and TI clustered together only for the magnitude and relative change characteristics where as TT and TE clustered closely for all four characteristics. One latent factor was associated with the [TT-TE] group and the other usually with PACO2.

  1. Analysis of Enriched Uranyl Nitrate in Nested Annular Tank Array

    SciTech Connect

    John D. Bess; James D. Cleaver

    2009-06-01

    Two series of experiments were performed at the Rocky Flats Critical Mass Laboratory during the 1980s using highly enriched (93%) uranyl nitrate solution in annular tanks. [1, 2] Tanks were of typical sizes found in nuclear production plants. Experiments looked at tanks of varying radii in a co-located set of nested tanks, a 1 by 2 array, and a 1 by 3 array. The co-located set of tanks had been analyzed previously [3] as a benchmark for inclusion within the International Handbook of Evaluated Criticality Safety Benchmark Experiments. [4] The current study represents the benchmark analysis of the 1 by 3 array of a series of nested annular tanks. Of the seventeen configurations performed in this set of experiments, twelve were evaluated and nine were judged as acceptable benchmarks.

  2. ClusterViz: A Cytoscape APP for Cluster Analysis of Biological Network.

    PubMed

    Wang, Jianxin; Zhong, Jiancheng; Chen, Gang; Li, Min; Wu, Fang-xiang; Pan, Yi

    2015-01-01

    Cluster analysis of biological networks is one of the most important approaches for identifying functional modules and predicting protein functions. Furthermore, visualization of clustering results is crucial to uncover the structure of biological networks. In this paper, ClusterViz, an APP of Cytoscape 3 for cluster analysis and visualization, has been developed. In order to reduce complexity and enable extendibility for ClusterViz, we designed the architecture of ClusterViz based on the framework of Open Services Gateway Initiative. According to the architecture, the implementation of ClusterViz is partitioned into three modules including interface of ClusterViz, clustering algorithms and visualization and export. ClusterViz fascinates the comparison of the results of different algorithms to do further related analysis. Three commonly used clustering algorithms, FAG-EC, EAGLE and MCODE, are included in the current version. Due to adopting the abstract interface of algorithms in module of the clustering algorithms, more clustering algorithms can be included for the future use. To illustrate usability of ClusterViz, we provided three examples with detailed steps from the important scientific articles, which show that our tool has helped several research teams do their research work on the mechanism of the biological networks. PMID:26357321

  3. AMOEBA clustering revisited. [cluster analysis, classification, and image display program

    NASA Technical Reports Server (NTRS)

    Bryant, Jack

    1990-01-01

    A description of the clustering, classification, and image display program AMOEBA is presented. Using a difficult high resolution aircraft-acquired MSS image, the steps the program takes in forming clusters are traced. A number of new features are described here for the first time. Usage of the program is discussed. The theoretical foundation (the underlying mathematical model) is briefly presented. The program can handle images of any size and dimensionality.

  4. Cluster analysis of contaminated sediment data: nodal analysis.

    PubMed

    Hartwell, S Ian; Claflin, Larry W

    2005-07-01

    The objective of the present study was to explore the use of multivariate statistical methods as a means to discern relationships between contaminants and biological and/or toxicological effects in a representative data set from the National Status and Trends (NS&T) Program. Data from the National Oceanic and Atmospheric Administration, NS&T Program's Bioeffects Survey of Delaware Bay, USA, were examined using various univariate and multivariate statistical techniques, including cluster analysis. Each approach identified consistent patterns and relationships between the three types of triad data. The analyses also identified factors that bias the interpretation of the data, primarily the presence of rare and unique species and the dependence of species distributions on physical parameters. Sites and species were clustered with the unweighted pair-group method using arithmetic averages clustering with the Jaccard coefficient that clustered species and sites into mutually consistent groupings. Pearson product moment correlation coefficients, normalized for salinity, also were clustered. The most informative analysis, termed nodal analysis, was the intersection of species cluster analysis with site cluster analysis. This technique produced a visual representation of species association patterns among site clusters. Site characteristics, such as salinity and grain size, not contaminant concentrations, appeared to be the primary factors determining species distributions. This suggests the sediment-quality triad needs to use physical parameters as a distinct leg from chemical concentrations to improve sediment-quality assessments in large bodies of water. Because the Delaware Bay system has confounded gradients of contaminants and physical parameters, analyses were repeated with data from northern Chesapeake Bay, USA, with similar results. PMID:16050601

  5. Equivalent damage validation by variable cluster analysis

    NASA Astrophysics Data System (ADS)

    Drago, Carlo; Ferlito, Rachele; Zucconi, Maria

    2016-06-01

    The main aim of this work is to perform a clustering analysis on the damage relieved in the old center of L'Aquila after the earthquake occurred on April 6, 2009 and to validate an Indicator of Equivalent Damage ED that summarizes the information reported on the AeDES card regarding the level of damage and their extension on the surface of the buildings. In particular we used a sample of 13442 masonry buildings located in an area characterized by a Macroseismic Intensity equal to 8 [1]. The aim is to ensure the coherence between the clusters and its hierarchy identified in the data of damage detected and in the data of the ED elaborated.

  6. Chaotic map clustering algorithm for EEG analysis

    NASA Astrophysics Data System (ADS)

    Bellotti, R.; De Carlo, F.; Stramaglia, S.

    2004-03-01

    The non-parametric chaotic map clustering algorithm has been applied to the analysis of electroencephalographic signals, in order to recognize the Huntington's disease, one of the most dangerous pathologies of the central nervous system. The performance of the method has been compared with those obtained through parametric algorithms, as K-means and deterministic annealing, and supervised multi-layer perceptron. While supervised neural networks need a training phase, performed by means of data tagged by the genetic test, and the parametric methods require a prior choice of the number of classes to find, the chaotic map clustering gives a natural evidence of the pathological class, without any training or supervision, thus providing a new efficient methodology for the recognition of patterns affected by the Huntington's disease.

  7. Constructing storyboards based on hierarchical clustering analysis

    NASA Astrophysics Data System (ADS)

    Hasebe, Satoshi; Sami, Mustafa M.; Muramatsu, Shogo; Kikuchi, Hisakazu

    2005-07-01

    There are growing needs for quick preview of video contents for the purpose of improving accessibility of video archives as well as reducing network traffics. In this paper, a storyboard that contains a user-specified number of keyframes is produced from a given video sequence. It is based on hierarchical cluster analysis of feature vectors that are derived from wavelet coefficients of video frames. Consistent use of extracted feature vectors is the key to avoid a repetition of computationally-intensive parsing of the same video sequence. Experimental results suggest that a significant reduction in computational time is gained by this strategy.

  8. Estimating the number of clusters via system evolution for cluster analysis of gene expression data.

    PubMed

    Wang, Kaijun; Zheng, Jie; Zhang, Junying; Dong, Jiyang

    2009-09-01

    The estimation of the number of clusters (NC) is one of crucial problems in the cluster analysis of gene expression data. Most approaches available give their answers without the intuitive information about separable degrees between clusters. However, this information is useful for understanding cluster structures. To provide this information, we propose system evolution (SE) method to estimate NC based on partitioning around medoids (PAM) clustering algorithm. SE analyzes cluster structures of a dataset from the viewpoint of a pseudothermodynamics system. The system will go to its stable equilibrium state, at which the optimal NC is found, via its partitioning process and merging process. The experimental results on simulated and real gene expression data demonstrate that the SE works well on the data with well-separated clusters and the one with slightly overlapping clusters. PMID:19527960

  9. Gag Induces the Coalescence of Clustered Lipid Rafts and Tetraspanin-Enriched Microdomains at HIV-1 Assembly Sites on the Plasma Membrane ▿

    PubMed Central

    Hogue, Ian B.; Grover, Jonathan R.; Soheilian, Ferri; Nagashima, Kunio; Ono, Akira

    2011-01-01

    The HIV-1 structural protein Gag associates with two types of plasma membrane microdomains, lipid rafts and tetraspanin-enriched microdomains (TEMs), both of which have been proposed to be platforms for HIV-1 assembly. However, a variety of studies have demonstrated that lipid rafts and TEMs are distinct microdomains in the absence of HIV-1 infection. To measure the impact of Gag on microdomain behaviors, we took advantage of two assays: an antibody-mediated copatching assay and a Förster resonance energy transfer (FRET) assay that measures the clustering of microdomain markers in live cells without antibody-mediated patching. We found that lipid rafts and TEMs copatched and clustered to a greater extent in the presence of membrane-bound Gag in both assays, suggesting that Gag induces the coalescence of lipid rafts and TEMs. Substitutions in membrane binding motifs of Gag revealed that, while Gag membrane binding is necessary to induce coalescence of lipid rafts and TEMs, either acylation of Gag or binding of phosphatidylinositol-(4,5)-bisphosphate is sufficient. Finally, a Gag derivative that is defective in inducing membrane curvature appeared less able to induce lipid raft and TEM coalescence. A higher-resolution analysis of assembly sites by correlative fluorescence and scanning electron microscopy showed that coalescence of clustered lipid rafts and TEMs occurs predominately at completed cell surface virus-like particles, whereas a transmembrane raft marker protein appeared to associate with punctate Gag fluorescence even in the absence of cell surface particles. Together, these results suggest that different membrane microdomain components are recruited in a stepwise manner during assembly. PMID:21813604

  10. [Enrichment Characteristics and Source Analysis of Metal Elements in PM₂.₅ in Autumn in Nanchang City].

    PubMed

    Lin, Xiao-hui; Zhao, Yang; Fan, Xiao-jun; Hu, Gong-ren; Yu, Rui-lian

    2016-01-15

    PM₂.₅ samples were collected in six different functional zones in Nanchang City during autumn in 2013. PM₂.₅ mass concentration and enrichment characteristics of eighteen metal elements (Mg, Al, K, Ca, Ti, V, Ba, Co, Cr, Mn, Fe, Ni, Cu, Zn, Cd, Pb, As and Hg) were analyzed. The pollution sources of the above elements in PM₂.₅ were discussed based on the results of multivariate statistical analysis. The results showed that the average daily mass concentration of PM₂.₅ during autumn in Nanchang City met the secondary standard limit (≤ 75 µg · m⁻³) of National Ambient Air Quality Standards (GB 3095-2012). The enrichment factors of Mn, Ti, Al and V were lower than 1.0, indicating that these elements were barely enriched. The enrichment factors of Fe, Cr, Co, K, Mg, Ba, Ca, Cu and As ranged from 1.7 to 7.8, suggesting the influence of both natural sources and anthropogenic sources. Hg, Zn, Pb, Ni and Cd were obviously affected by anthropogenic emissions since their enrichment factors ranged from 21. 9 to 481.2. The combined results of correlation analysis, principal components analysis and cluster analysis revealed the pollution sources of these metals in PM₂.₅: Mg, K, Al, Ca and Ti mainly came from natural soil and building material dust; As and Hg were mainly from coal combustion; Ba, Ni and Mn were mainly from industrial emission of metal smelting; V, Cu, Fe, Cd, Pb, Cr and Co mainly came from traffic sources; Zn was influenced by metal smelting and coal burning. PMID:27078938

  11. [Enrichment Characteristics and Source Analysis of Metal Elements in PM₂.₅ in Autumn in Nanchang City].

    PubMed

    Lin, Xiao-hui; Zhao, Yang; Fan, Xiao-jun; Hu, Gong-ren; Yu, Rui-lian

    2016-01-15

    PM₂.₅ samples were collected in six different functional zones in Nanchang City during autumn in 2013. PM₂.₅ mass concentration and enrichment characteristics of eighteen metal elements (Mg, Al, K, Ca, Ti, V, Ba, Co, Cr, Mn, Fe, Ni, Cu, Zn, Cd, Pb, As and Hg) were analyzed. The pollution sources of the above elements in PM₂.₅ were discussed based on the results of multivariate statistical analysis. The results showed that the average daily mass concentration of PM₂.₅ during autumn in Nanchang City met the secondary standard limit (≤ 75 µg · m⁻³) of National Ambient Air Quality Standards (GB 3095-2012). The enrichment factors of Mn, Ti, Al and V were lower than 1.0, indicating that these elements were barely enriched. The enrichment factors of Fe, Cr, Co, K, Mg, Ba, Ca, Cu and As ranged from 1.7 to 7.8, suggesting the influence of both natural sources and anthropogenic sources. Hg, Zn, Pb, Ni and Cd were obviously affected by anthropogenic emissions since their enrichment factors ranged from 21. 9 to 481.2. The combined results of correlation analysis, principal components analysis and cluster analysis revealed the pollution sources of these metals in PM₂.₅: Mg, K, Al, Ca and Ti mainly came from natural soil and building material dust; As and Hg were mainly from coal combustion; Ba, Ni and Mn were mainly from industrial emission of metal smelting; V, Cu, Fe, Cd, Pb, Cr and Co mainly came from traffic sources; Zn was influenced by metal smelting and coal burning.

  12. Evaluating gene set enrichment analysis via a hybrid data model.

    PubMed

    Hua, Jianping; Bittner, Michael L; Dougherty, Edward R

    2014-01-01

    Gene set enrichment analysis (GSA) methods have been widely adopted by biological labs to analyze data and generate hypotheses for validation. Most of the existing comparison studies focus on whether the existing GSA methods can produce accurate P-values; however, practitioners are often more concerned with the correct gene-set ranking generated by the methods. The ranking performance is closely related to two critical goals associated with GSA methods: the ability to reveal biological themes and ensuring reproducibility, especially for small-sample studies. We have conducted a comprehensive simulation study focusing on the ranking performance of seven representative GSA methods. We overcome the limitation on the availability of real data sets by creating hybrid data models from existing large data sets. To build the data model, we pick a master gene from the data set to form the ground truth and artificially generate the phenotype labels. Multiple hybrid data models can be constructed from one data set and multiple data sets of smaller sizes can be generated by resampling the original data set. This approach enables us to generate a large batch of data sets to check the ranking performance of GSA methods. Our simulation study reveals that for the proposed data model, the Q2 type GSA methods have in general better performance than other GSA methods and the global test has the most robust results. The properties of a data set play a critical role in the performance. For the data sets with highly connected genes, all GSA methods suffer significantly in performance.

  13. Theoretical analysis of aqueous residues incineration with oxygen enriched flames

    SciTech Connect

    Lacava, P.T.; Pimenta, A.P.; Veras, C.A.G.; Carvalho, J.A. Jr.

    1999-10-01

    The use of oxygen to enrich the oxidizer can be an attractive alternate to increase incineration rates of a combustion chamber originally designed to operate with air. For a certain fuel flow rate, if some incineration parameters are held constant (as combustion chamber temperature, turbulence level, and residence time), an increase of incineration rates becomes possible with injection of oxygen. This work presents a theoretical evaluation of combustion air enrichment in a combustion chamber designed to incinerate aqueous residues using methane as fuel and air as oxidizer. Detailed chemistry was employed to predict pollutants formation. The overall process was investigated using the PSR routine from the CHEMKIN library.

  14. Cluster analysis of word frequency dynamics

    NASA Astrophysics Data System (ADS)

    Maslennikova, Yu S.; Bochkarev, V. V.; Belashova, I. A.

    2015-01-01

    This paper describes the analysis and modelling of word usage frequency time series. During one of previous studies, an assumption was put forward that all word usage frequencies have uniform dynamics approaching the shape of a Gaussian function. This assumption can be checked using the frequency dictionaries of the Google Books Ngram database. This database includes 5.2 million books published between 1500 and 2008. The corpus contains over 500 billion words in American English, British English, French, German, Spanish, Russian, Hebrew, and Chinese. We clustered time series of word usage frequencies using a Kohonen neural network. The similarity between input vectors was estimated using several algorithms. As a result of the neural network training procedure, more than ten different forms of time series were found. They describe the dynamics of word usage frequencies from birth to death of individual words. Different groups of word forms were found to have different dynamics of word usage frequency variations.

  15. LOW-RESOLUTION SPECTROSCOPY FOR THE GLOBULAR CLUSTERS WITH SIGNS OF SUPERNOVA ENRICHMENT: M22, NGC 1851, AND NGC 288

    SciTech Connect

    Lim, Dongwook; Han, Sang-Il; Lee, Young-Wook; Roh, Dong-Goo; Sohn, Young-Jong; Chun, Sang-Hyun; Lee, Jae-Woo; Johnson, Christian I.

    2015-01-01

    There is increasing evidence for the presence of multiple red giant branches (RGBs) in the color-magnitude diagrams of massive globular clusters (GCs). In order to investigate the origin of this split on the RGB, we have performed new narrow-band Ca photometry and low-resolution spectroscopy for M22, NGC 1851, and NGC 288. We find significant differences (more than 4σ) in calcium abundance from the spectroscopic HK' index for M22 and NGC 1851. We also find more than 8σ differences in CN-band strength between the Ca-strong and Ca-weak subpopulations for these GCs. For NGC 288, however, a large difference is detected only in the CN strength. The calcium abundances of RGB stars in this GC are identical to within the errors. This is consistent with the conclusion from our new Ca photometry where the RGB splits are confirmed in M22 and NGC 1851, but not in NGC 288. We also find interesting differences in the CN-CH correlations among these GCs. While CN and CH are anti-correlated in NGC 288, they show a positive correlation in M22. NGC 1851, however, shows no difference in CH between the two groups of stars with different CN strengths. We suggest that all of these systematic differences would be best explained by how strongly Type II supernovae enrichment has contributed to the chemical evolution of these GCs.

  16. Failure Mode Identification Through Clustering Analysis

    NASA Technical Reports Server (NTRS)

    Arunajadai, Srikesh G.; Stone, Robert B.; Tumer, Irem Y.; Clancy, Daniel (Technical Monitor)

    2002-01-01

    Research has shown that nearly 80% of the costs and problems are created in product development and that cost and quality are essentially designed into products in the conceptual stage. Currently, failure identification procedures (such as FMEA (Failure Modes and Effects Analysis), FMECA (Failure Modes, Effects and Criticality Analysis) and FTA (Fault Tree Analysis)) and design of experiments are being used for quality control and for the detection of potential failure modes during the detail design stage or post-product launch. Though all of these methods have their own advantages, they do not give information as to what are the predominant failures that a designer should focus on while designing a product. This work uses a functional approach to identify failure modes, which hypothesizes that similarities exist between different failure modes based on the functionality of the product/component. In this paper, a statistical clustering procedure is proposed to retrieve information on the set of predominant failures that a function experiences. The various stages of the methodology are illustrated using a hypothetical design example.

  17. A hybrid monkey search algorithm for clustering analysis.

    PubMed

    Chen, Xin; Zhou, Yongquan; Luo, Qifang

    2014-01-01

    Clustering is a popular data analysis and data mining technique. The k-means clustering algorithm is one of the most commonly used methods. However, it highly depends on the initial solution and is easy to fall into local optimum solution. In view of the disadvantages of the k-means method, this paper proposed a hybrid monkey algorithm based on search operator of artificial bee colony algorithm for clustering analysis and experiment on synthetic and real life datasets to show that the algorithm has a good performance than that of the basic monkey algorithm for clustering analysis.

  18. Simultaneous Two-Way Clustering of Multiple Correspondence Analysis

    ERIC Educational Resources Information Center

    Hwang, Heungsun; Dillon, William R.

    2010-01-01

    A 2-way clustering approach to multiple correspondence analysis is proposed to account for cluster-level heterogeneity of both respondents and variable categories in multivariate categorical data. Specifically, in the proposed method, multiple correspondence analysis is combined with k-means in a unified framework in which "k"-means is applied…

  19. A Survey of Popular R Packages for Cluster Analysis

    ERIC Educational Resources Information Center

    Flynt, Abby; Dean, Nema

    2016-01-01

    Cluster analysis is a set of statistical methods for discovering new group/class structure when exploring data sets. This article reviews the following popular libraries/commands in the R software language for applying different types of cluster analysis: from the stats library, the kmeans, and hclust functions; the mclust library; the poLCA…

  20. Using Cluster Analysis for Data Mining in Educational Technology Research

    ERIC Educational Resources Information Center

    Antonenko, Pavlo D.; Toy, Serkan; Niederhauser, Dale S.

    2012-01-01

    Cluster analysis is a group of statistical methods that has great potential for analyzing the vast amounts of web server-log data to understand student learning from hyperlinked information resources. In this methodological paper we provide an introduction to cluster analysis for educational technology researchers and illustrate its use through…

  1. Early Hemostatic Responses to Trauma Identified Using Hierarchical Clustering Analysis

    PubMed Central

    White, N.J.; Contaifer, D.; Martin, E.J.; Newton, J.C.; Mohammed, B.M.; Bostic, J.L.; Brophy, G.M.; Spiess, B.D.; Pusateri, A.E.; Ward, K.R.; Brophy, D.F.

    2015-01-01

    Background Trauma-induced coagulopathy is a complex multifactorial hemostatic response that is poorly understood. Objectives Identify distinct hemostatic responses to trauma and identify key components of the hemostatic system that vary between responses. Patients/Methods Cross-sectional observational study of adult trauma patients at an urban Level I trauma center Emergency Department. Hierarchical clustering analysis was used to identify distinct clusters of similar subjects using vital signs, injury/shock severity, and by comprehensive assessment of coagulation, clot formation, platelet function, and thrombin generation. Results Of 84 total trauma patients included in the model, three distinct trauma clusters were identified. Cluster 1 (N=57) displayed platelet activation, preserved peak thrombin generation, plasma coagulation dysfunction, moderately decreased fibrinogen concentration, and normal clot formation relative to healthy controls. Cluster 2 (N=18) displayed platelet activation, preserved peak thrombin generation, and preserved fibrinogen concentration with normal clot formation. Cluster 3 (N=9) was the most severely injured and shocked and displayed a strong inflammatory and bleeding phenotype. Platelet dysfunction, thrombin inhibition, plasma coagulation dysfunction, and decreased fibrinogen concentration were present in this cluster. Fibrinolytic activation was present in all clusters, but increased more so in Cluster 3. Trauma clusters were different most noticeably in their relative fibrinogen concentration, peak thrombin generation, and platelet-induced clot contraction. Conclusions Hierarchical clustering analysis identified 3 distinct hemostatic responses to trauma. Further insight into the underlying hemostatic mechanisms responsible for these responses is needed. PMID:25816845

  2. Photometric analysis of Collinder Cluster 223

    NASA Astrophysics Data System (ADS)

    Duplancic Videla, M. F.; Molina, S.; González, J. F.

    We present photometric observations of the open-cluster Collinder 223 (RA= 10h 30m 38s , dec =-60° 06' 39'' ), obtained from observation with the HSH telescope in CASLEO. This cluster has not been studied extensively, there is only one photoelectric photometric UBV study, done by Clariá and Lapasset (1991). A later study, done by Tadross (2004), reanalyzed the data, however, no other photometric measurements have been carried out until present. We observed seven fields in the cluster which were chosen prioritizing the zones of major stellar concentration. We obtained color-magnitude diagrams of the cluster, reaching stars two magnitudes weaker than those previously obtained by Clariá and Lapasset. The cluster sequence shows well in accordance with the isochrone corresponding to the age of 3.5 10E7 yr.

  3. Star formation in the first galaxies - III. Formation, evolution, and characteristics of the first metal-enriched stellar cluster

    NASA Astrophysics Data System (ADS)

    Safranek-Shrader, Chalence; Montgomery, Michael H.; Milosavljević, Miloš; Bromm, Volker

    2016-01-01

    We simulate the formation of a low-metallicity (10-2 Z⊙) stellar cluster at redshift z ˜ 14. Beginning with cosmological initial conditions, the simulation utilizes adaptive mesh refinement and sink particles to follow the collapse and evolution of gas past the opacity limit for fragmentation, thus resolving the formation of individual protostellar cores. A time- and location-dependent protostellar radiation field, which heats the gas by absorption on dust, is computed by integration of protostellar evolutionary tracks. The simulation also includes a robust non-equilibrium chemical network that self-consistently treats gas thermodynamics and dust-gas coupling. The system is evolved for 18 kyr after the first protostellar source has formed. In this time span, 30 sink particles representing protostellar cores form with a total mass of 81 M⊙. Their masses range from ˜0.1 to 14.4 M⊙ with a median mass ˜0.5-1 M⊙. Massive protostars grow by competitive accretion while lower mass protostars are stunted in growth by close encounters and many-body ejections. In the regime explored here, the characteristic mass scale is determined by the cosmic microwave background temperature floor and the onset of efficient dust-gas coupling. It seems unlikely that host galaxies of the first bursts of metal-enriched star formation will be detectable with the James Webb Space Telescope or other next-generation infrared observatories. Instead, the most promising access route to the dawn of cosmic star formation may lie in the scrutiny of metal-poor, ancient stellar populations in the Galactic neighbourhood. The observable targets corresponding to the system simulated here are ultra-faint dwarf satellite galaxies such as Boötes II and Willman I.

  4. Enrichment/isolation of phosphorylated peptides on hafnium oxide prior to mass spectrometric analysis.

    PubMed

    Rivera, José G; Choi, Yong Seok; Vujcic, Stefan; Wood, Troy D; Colón, Luis A

    2009-01-01

    Hafnium oxide (hafnia) exhibits unique enrichment properties towards phosphorylated peptides that are complementary to those of titanium oxide (titania) and zirconium oxide (zirconia) for use with mass spectrometric analysis in the field of proteomics.

  5. eSNPO: An eQTL-based SNP Ontology and SNP functional enrichment analysis platform

    PubMed Central

    Li, Jin; Wang, Limei; Jiang, Tao; Wang, Jizhe; Li, Xue; Liu, Xiaoyan; Wang, Chunyu; Teng, Zhixia; Zhang, Ruijie; Lv, Hongchao; Guo, Maozu

    2016-01-01

    Genome-wide association studies (GWASs) have mined many common genetic variants associated with human complex traits like diseases. After that, the functional annotation and enrichment analysis of significant SNPs are important tasks. Classic methods are always based on physical positions of SNPs and genes. Expression quantitative trait loci (eQTLs) are genomic loci that contribute to variation in gene expression levels and have been proven efficient to connect SNPs and genes. In this work, we integrated the eQTL data and Gene Ontology (GO), constructed associations between SNPs and GO terms, then performed functional enrichment analysis. Finally, we constructed an eQTL-based SNP Ontology and SNP functional enrichment analysis platform. Taking Parkinson Disease (PD) as an example, the proposed platform and method are efficient. We believe eSNPO will be a useful resource for SNP functional annotation and enrichment analysis after we have got significant disease related SNPs. PMID:27470167

  6. eSNPO: An eQTL-based SNP Ontology and SNP functional enrichment analysis platform.

    PubMed

    Li, Jin; Wang, Limei; Jiang, Tao; Wang, Jizhe; Li, Xue; Liu, Xiaoyan; Wang, Chunyu; Teng, Zhixia; Zhang, Ruijie; Lv, Hongchao; Guo, Maozu

    2016-01-01

    Genome-wide association studies (GWASs) have mined many common genetic variants associated with human complex traits like diseases. After that, the functional annotation and enrichment analysis of significant SNPs are important tasks. Classic methods are always based on physical positions of SNPs and genes. Expression quantitative trait loci (eQTLs) are genomic loci that contribute to variation in gene expression levels and have been proven efficient to connect SNPs and genes. In this work, we integrated the eQTL data and Gene Ontology (GO), constructed associations between SNPs and GO terms, then performed functional enrichment analysis. Finally, we constructed an eQTL-based SNP Ontology and SNP functional enrichment analysis platform. Taking Parkinson Disease (PD) as an example, the proposed platform and method are efficient. We believe eSNPO will be a useful resource for SNP functional annotation and enrichment analysis after we have got significant disease related SNPs. PMID:27470167

  7. Analysis of Network Clustering Algorithms and Cluster Quality Metrics at Scale

    PubMed Central

    Kobourov, Stephen; Gallant, Mike; Börner, Katy

    2016-01-01

    Overview Notions of community quality underlie the clustering of networks. While studies surrounding network clustering are increasingly common, a precise understanding of the realtionship between different cluster quality metrics is unknown. In this paper, we examine the relationship between stand-alone cluster quality metrics and information recovery metrics through a rigorous analysis of four widely-used network clustering algorithms—Louvain, Infomap, label propagation, and smart local moving. We consider the stand-alone quality metrics of modularity, conductance, and coverage, and we consider the information recovery metrics of adjusted Rand score, normalized mutual information, and a variant of normalized mutual information used in previous work. Our study includes both synthetic graphs and empirical data sets of sizes varying from 1,000 to 1,000,000 nodes. Cluster Quality Metrics We find significant differences among the results of the different cluster quality metrics. For example, clustering algorithms can return a value of 0.4 out of 1 on modularity but score 0 out of 1 on information recovery. We find conductance, though imperfect, to be the stand-alone quality metric that best indicates performance on the information recovery metrics. Additionally, our study shows that the variant of normalized mutual information used in previous work cannot be assumed to differ only slightly from traditional normalized mutual information. Network Clustering Algorithms Smart local moving is the overall best performing algorithm in our study, but discrepancies between cluster evaluation metrics prevent us from declaring it an absolutely superior algorithm. Interestingly, Louvain performed better than Infomap in nearly all the tests in our study, contradicting the results of previous work in which Infomap was superior to Louvain. We find that although label propagation performs poorly when clusters are less clearly defined, it scales efficiently and accurately to large

  8. Spectral Analysis of Cluster Induced Turbulence

    NASA Astrophysics Data System (ADS)

    Patel, Ravi; Ireland, Peter; Capecelatro, Jesse; Fox, Rodney; Desjardins, Olivier

    2015-11-01

    Particle laden turbulent flows are an important feature of many industrial processes such as fluidized bed reactors. The study of cluster-induced turbulence (CIT), wherein particles falling under gravity generate turbulence in the carrier gas via fluctuations in particle concentration, may lead to better models for these processes. We present a spectral analysis of a database of statistically stationary CIT simulations. These simulations were previously performed using a two way coupled Eulerian-Lagrangian approach for various mass loadings and particle-scale Reynolds numbers. The Lagrangian particle data is carefully filtered to obtain Eulerian fields for particle phase volume fraction, velocity, and granular temperature. We perform a spectral decomposition of the particle and fluid turbulent kinetic energy budget. We investigate the contributions to the particle and fluid turbulent kinetic energy by pressure strain, viscous dissipation, drag exchange, viscous exchange, and pressure exchange over the range of wavenumbers. Results from this study may help develop closure models for large eddy simulation of particle laden turbulent flows.

  9. A deep Chandra observation of the poor cluster AWM 4 - II. The role of the radio jets in enriching the intracluster medium

    NASA Astrophysics Data System (ADS)

    O'Sullivan, Ewan; Giacintucci, Simona; David, Laurence P.; Vrtilek, Jan M.; Raychaudhury, Somak

    2011-03-01

    We use a Chandra observation of the poor cluster AWM 4 to map the temperature and abundance of the intracluster medium, so as to examine the influence of the central radio galaxy on its environment. While the cluster core is generally enriched to near-solar abundances, we find evidence of supersolar abundances correlated with the radio jets, extending ˜35 kpc from the core of the central dominant galaxy NGC 6051 along its minor-axis. We conclude that the enriched gas has been transported out of the central galaxy through the action of the radio source. We estimate the excess mass of iron in the entrained gas to be ˜1.4 × 106 M⊙ and find that this can be produced in the core of NGC 6051 within the time-scale of the active galactic nucleus (AGN) outburst. The energy required to transport this gas to its current location is ˜4.5 × 1057 erg, a significant fraction of the estimated total mechanical energy output of the AGN, though this estimate is dependent on the degree of enrichment of the uplifted gas. The larger near-solar abundance region is also compatible with enrichment by metals mixed outwards from NGC 6051 over a much longer time-scale.

  10. A UNIFORM CONTRIBUTION OF CORE-COLLAPSE AND TYPE Ia SUPERNOVAE TO THE CHEMICAL ENRICHMENT PATTERN IN THE OUTSKIRTS OF THE VIRGO CLUSTER

    SciTech Connect

    Simionescu, A.; Ichinohe, Y.; Werner, N.; Urban, O.; Allen, S. W.; Zhuravleva, I.

    2015-10-01

    We present the first measurements of the abundances of α-elements (Mg, Si, and S) extending out beyond the virial radius of a cluster of galaxies. Our results, based on Suzaku Key Project observations of the Virgo Cluster, show that the chemical composition of the intracluster medium is consistent with being constant on large scales, with a flat distribution of the Si/Fe, S/Fe, and Mg/Fe ratios as a function of radius and azimuth out to 1.4 Mpc (1.3 r{sub 200}). Chemical enrichment of the intergalactic medium due solely to core-collapse supernovae (SNcc) is excluded with very high significance; instead, the measured metal abundance ratios are generally consistent with the solar value. The uniform metal abundance ratios observed today are likely the result of an early phase of enrichment and mixing, with both SNcc and SNe Ia contributing to the metal budget during the period of peak star formation activity at redshifts of 2–3. We estimate the ratio between the number of SNe Ia and the total number of supernovae enriching the intergalactic medium to be between 12% and 37%, broadly consistent with the metal abundance patterns in our own Galaxy or with the SN Ia contribution estimated for the cluster cores.

  11. A uniform contribution of core-collapse and type Ia supernovae to the chemical enrichment pattern in the outskirts of the Virgo Cluster

    DOE PAGES

    Simionescu, A.; Werner, N.; Urban, O.; Allen, S. W.; Ichinohe, Y.; Zhuravleva, I.

    2015-09-24

    We present the first measurements of the abundances of α-elements (Mg, Si, and S) extending out beyond the virial radius of a cluster of galaxies. Our results, based on Suzaku Key Project observations of the Virgo Cluster, show that the chemical composition of the intracluster medium is consistent with being constant on large scales, with a flat distribution of the Si/Fe, S/Fe, and Mg/Fe ratios as a function of radius and azimuth out to 1.4 Mpc (1.3 r200). Chemical enrichment of the intergalactic medium due solely to core-collapse supernovae (SNcc) is excluded with very high significance; instead, the measured metalmore » abundance ratios are generally consistent with the solar value. The uniform metal abundance ratios observed today are likely the result of an early phase of enrichment and mixing, with both SNcc and SNe Ia contributing to the metal budget during the period of peak star formation activity at redshifts of 2–3. Furthermore, we estimate the ratio between the number of SNe Ia and the total number of supernovae enriching the intergalactic medium to be between 12% and 37%, broadly consistent with the metal abundance patterns in our own Galaxy or with the SN Ia contribution estimated for the cluster cores.« less

  12. A uniform contribution of core-collapse and type Ia supernovae to the chemical enrichment pattern in the outskirts of the Virgo Cluster

    SciTech Connect

    Simionescu, A.; Werner, N.; Urban, O.; Allen, S. W.; Ichinohe, Y.; Zhuravleva, I.

    2015-09-24

    We present the first measurements of the abundances of α-elements (Mg, Si, and S) extending out beyond the virial radius of a cluster of galaxies. Our results, based on Suzaku Key Project observations of the Virgo Cluster, show that the chemical composition of the intracluster medium is consistent with being constant on large scales, with a flat distribution of the Si/Fe, S/Fe, and Mg/Fe ratios as a function of radius and azimuth out to 1.4 Mpc (1.3 r200). Chemical enrichment of the intergalactic medium due solely to core-collapse supernovae (SNcc) is excluded with very high significance; instead, the measured metal abundance ratios are generally consistent with the solar value. The uniform metal abundance ratios observed today are likely the result of an early phase of enrichment and mixing, with both SNcc and SNe Ia contributing to the metal budget during the period of peak star formation activity at redshifts of 2–3. Furthermore, we estimate the ratio between the number of SNe Ia and the total number of supernovae enriching the intergalactic medium to be between 12% and 37%, broadly consistent with the metal abundance patterns in our own Galaxy or with the SN Ia contribution estimated for the cluster cores.

  13. MASSCLEAN: MASSive CLuster Evolution and ANalysis package -- A new tool for stellar clusters

    NASA Astrophysics Data System (ADS)

    Popescu, Bogdan

    2010-11-01

    Stellar clusters are laboratories for stellar evolution. Their stellar content have an uniform age and chemical composition, but span a large mass interval. The majority of stars are born in clusters and end up in the general field population. An accurate characterization of stellar clusters could be used to built better models, from stellar evolution to the evolution of an entire galaxy. Regardless of the fact that they are so close, for many Milky Way clusters it is difficult to be observed because they are obscured by the dust in the disk of our Galaxy. The clusters from the Local Group and beyond are too distant, so only their integrated properties could be used most of the time. There is one way to analyze the observational data, to search for clusters, and to describe them: simulations. MASSCLEAN (MASSive CLuster Evolution and ANalysis) package was developed to provide a better characterization of Galactic clusters, to derive selection effects of current surveys, and to provide information about the extra-galactic clusters. Simulations of known Galactic clusters are used to get better constraints on their parameters, like mass, age, extinction, chemical composition and distance. This is the traditional way to describe the Galactic clusters, fitting the data using the available models. The difference is that MASSCLEAN simulations provide a consistent set of parameters. The majority of extra-galactic clusters are known only from their integrated properties, integrated magnitudes and colors. The current models for stellar populations are available only in the infinite mass limit. But the real clusters have a finite mass, and their integrated colors show a large dispersion (stochastic fluctuations). The description of the variation of integrated colors as a function of mass and age lead to the creation of MASSCLEANcolors database, based on 70 million Monte Carlo simulations. Since the entries in the database form a consistent set of integrated colors, integrated

  14. Transcriptomic analysis of a marine bacterial community enriched with dimethylsulfoniopropionate.

    PubMed

    Vila-Costa, Maria; Rinta-Kanto, Johanna M; Sun, Shulei; Sharma, Shalabh; Poretsky, Rachel; Moran, Mary Ann

    2010-11-01

    Dimethylsulfoniopropionate (DMSP) is an important source of reduced sulfur and carbon for marine microbial communities, as well as the precursor of the climate-active gas dimethylsulfide (DMS). In this study, we used metatranscriptomic sequencing to analyze gene expression profiles of a bacterial assemblage from surface waters at the Bermuda Atlantic Time-series Study (BATS) station with and without a short-term enrichment of DMSP (25 nM for 30 min). An average of 303 143 reads were obtained per treatment using 454 pyrosequencing technology, of which 51% were potential protein-encoding sequences. Transcripts from Gammaproteobacteria and Bacteroidetes increased in relative abundance on DMSP addition, yet there was little change in the contribution of two bacterioplankton groups whose cultured members harbor known DMSP degradation genes, Roseobacter and SAR11. The DMSP addition led to an enrichment of transcripts supporting heterotrophic activity, and a depletion of those encoding light-related energy generation. Genes for the degradation of C3 compounds were significantly overrepresented after DMSP addition, likely reflecting the metabolism of the C3 component of DMSP. Mapping these transcripts to known biochemical pathways indicated that both acetyl-CoA and succinyl-CoA may be common entry points of this moiety into the tricarboxylic acid cycle. In a short time frame (30 min) in the extremely oligotrophic Sargasso Sea, different gene expression patterns suggest the use of DMSP by a diversity of marine bacterioplankton as both carbon and sulfur sources. PMID:20463763

  15. Preparation of Mitochondrial Enriched Fractions for Metabolic Analysis in Drosophila

    PubMed Central

    Villa-Cuesta, Eugenia; Rand, David M.

    2015-01-01

    Since mitochondria play roles in amino acid metabolism, carbohydrate metabolism and fatty acid oxidation, defects in mitochondrial function often compromise the lives of those who suffer from these complex diseases. Detecting mitochondrial metabolic changes is vital to the understanding of mitochondrial disorders and mitochondrial responses to pharmacological agents. Although mitochondrial metabolism is at the core of metabolic regulation, the detection of subtle changes in mitochondrial metabolism may be hindered by the overrepresentation of other cytosolic metabolites obtained using whole organism or whole tissue extractions. Here we describe an isolation method that detected pronounced mitochondrial metabolic changes in Drosophila that were distinct between whole-fly and mitochondrial enriched preparations. To illustrate the sensitivity of this method, we used a set of Drosophila harboring genetically diverse mitochondrial DNAs (mtDNA) and exposed them to the drug rapamycin. Using this method we showed that rapamycin modifies mitochondrial metabolism in a mitochondrial-genotype-dependent manner. However, these changes are much more distinct in metabolomics studies when metabolites were extracted from mitochondrial enriched fractions. In contrast, whole tissue extracts only detected metabolic changes mediated by the drug rapamycin independently of mtDNAs. PMID:26485391

  16. Phytotoxicity and Plant Productivity Analysis of Tar-Enriched Biochars

    NASA Astrophysics Data System (ADS)

    Keller, M. L.; Masiello, C. A.; Dugan, B.; Rudgers, J. A.; Capareda, S. C.

    2008-12-01

    Biochar is one of the three by-products obtained by the pyrolysis of organic material, the other two being syngas and bio-oil. The pyrolysis of biomass has generated a great amount of interest in recent years as all three by-products can be put toward beneficial uses. As part of a larger project designed to evaluate the hydrologic impact of biochar soil amendment, we generated a biochar through fast pyrolysis (less than 2 minutes) of sorghum stock at 600°C. In the initial biochar production run, the char bin was not purged with nitrogen. This inadvertent change in pyrolysis conditions produced a fast-pyrolysis biochar enriched with tars. We chose not to discard this batch, however, and instead used it to test the impact of tar-enriched biochars on plants. A suite of phytotoxicity tests were run to assess the effects of tar-rich biochar on plant germination and plant productivity. We designed the experiment to test for negative effects, using an organic carbon and nutrient-rich, greenhouse- optimized potting medium instead of soil. We used Black Seeded Simpson lettuce (Lactuca sativa) as the test organism. We found that even when tars are present within biochar, biochar amendment up to 10% by weight caused increased lettuce germination rates and increased biomass productivity. In this presentation, we will report the statistical significance of our germination and biomass data, as well as present preliminary data on how biochar amendment affects soil hydrologic properties.

  17. Transcriptomic analysis of a marine bacterial community enriched with dimethylsulfoniopropionate.

    PubMed

    Vila-Costa, Maria; Rinta-Kanto, Johanna M; Sun, Shulei; Sharma, Shalabh; Poretsky, Rachel; Moran, Mary Ann

    2010-11-01

    Dimethylsulfoniopropionate (DMSP) is an important source of reduced sulfur and carbon for marine microbial communities, as well as the precursor of the climate-active gas dimethylsulfide (DMS). In this study, we used metatranscriptomic sequencing to analyze gene expression profiles of a bacterial assemblage from surface waters at the Bermuda Atlantic Time-series Study (BATS) station with and without a short-term enrichment of DMSP (25 nM for 30 min). An average of 303 143 reads were obtained per treatment using 454 pyrosequencing technology, of which 51% were potential protein-encoding sequences. Transcripts from Gammaproteobacteria and Bacteroidetes increased in relative abundance on DMSP addition, yet there was little change in the contribution of two bacterioplankton groups whose cultured members harbor known DMSP degradation genes, Roseobacter and SAR11. The DMSP addition led to an enrichment of transcripts supporting heterotrophic activity, and a depletion of those encoding light-related energy generation. Genes for the degradation of C3 compounds were significantly overrepresented after DMSP addition, likely reflecting the metabolism of the C3 component of DMSP. Mapping these transcripts to known biochemical pathways indicated that both acetyl-CoA and succinyl-CoA may be common entry points of this moiety into the tricarboxylic acid cycle. In a short time frame (30 min) in the extremely oligotrophic Sargasso Sea, different gene expression patterns suggest the use of DMSP by a diversity of marine bacterioplankton as both carbon and sulfur sources.

  18. The REFLEX II Galaxy Cluster sample: mock catalogues and clustering analysis

    NASA Astrophysics Data System (ADS)

    Balaguera-Antolinez, Andres; Sanchez, Ariel G.; Bohringer, Hans

    2012-09-01

    We present results of the analysis of abundance and clustering from the new ROSAT-ESO Flux-Limited X-Ray (REFLEX) II galaxy cluster catalogue. To model the covariance matrix of the different statistics, we have created a set of 100 mock galaxy cluster catalogues built from a suite large volume LambdaCDM N-Body simulations (L-BASICC and calibrated with the X-ray luminosity function. We discuss the calibration scheme and some implications regarding the cluster scaling relations, particularly, the link between mass and luminosity. Similarly we show the behavior of the clustering signal as a function of the X-ray luminosity and some cosmological implications.

  19. Visual cluster analysis and pattern recognition methods

    DOEpatents

    Osbourn, Gordon Cecil; Martinez, Rubel Francisco

    2001-01-01

    A method of clustering using a novel template to define a region of influence. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques.

  20. Glycemic index and microstructure analysis of a newly developed fiber enriched cookie.

    PubMed

    Schuchardt, Jan Philipp; Wonik, Jasmin; Bindrich, Ute; Heinemann, Michaela; Kohrs, Heike; Schneider, Inga; Möller, Katharina; Hahn, Andreas

    2016-01-01

    A diet with a high glycemic index (GI) is associated with an elevated risk for obesity or type 2 diabetes. We investigated the GI of a newly-developed fiber enriched cookie and characterized the microstructure of ingredients used. In a study with 26 non-diabetic healthy volunteers it was shown that the fiber enriched cookie has a GI of 58.9 in relation to white bread as reference. Using a conversion factor of 1.4, the GI of the fiber enriched cookie in relation to a glucose-solution is 42.0 and can be classified as a low-GI food. Postprandial insulin concentration was significantly lower after consumption of fiber enriched cookies compared to white bread. Glucose release after in vitro digestion was significantly lower from fiber enriched cookies compared to other cookies tested. In addition to its high percentage of fiber, the cookies' low GI can be attributed to the limited gelatinization potential of the starch granules found in the ingredients used. Using confocal laser scanning microscopy it is shown that starch granule surface area of whole grain barley flour, spelt flour and oat flakes bears cluster-shaped protein-NSPS complexes that preferentially absorb water in conditions of water shortage and thereby prevent starch gelatinization.

  1. Glycemic index and microstructure analysis of a newly developed fiber enriched cookie.

    PubMed

    Schuchardt, Jan Philipp; Wonik, Jasmin; Bindrich, Ute; Heinemann, Michaela; Kohrs, Heike; Schneider, Inga; Möller, Katharina; Hahn, Andreas

    2016-01-01

    A diet with a high glycemic index (GI) is associated with an elevated risk for obesity or type 2 diabetes. We investigated the GI of a newly-developed fiber enriched cookie and characterized the microstructure of ingredients used. In a study with 26 non-diabetic healthy volunteers it was shown that the fiber enriched cookie has a GI of 58.9 in relation to white bread as reference. Using a conversion factor of 1.4, the GI of the fiber enriched cookie in relation to a glucose-solution is 42.0 and can be classified as a low-GI food. Postprandial insulin concentration was significantly lower after consumption of fiber enriched cookies compared to white bread. Glucose release after in vitro digestion was significantly lower from fiber enriched cookies compared to other cookies tested. In addition to its high percentage of fiber, the cookies' low GI can be attributed to the limited gelatinization potential of the starch granules found in the ingredients used. Using confocal laser scanning microscopy it is shown that starch granule surface area of whole grain barley flour, spelt flour and oat flakes bears cluster-shaped protein-NSPS complexes that preferentially absorb water in conditions of water shortage and thereby prevent starch gelatinization. PMID:26514289

  2. Using Cluster Analysis To Facilitate the Standard Setting Process.

    ERIC Educational Resources Information Center

    Sireci, Stephen G.; Robin, Frederic; Patelis, Thanos

    The most popular methods for setting passing scores and other standards on educational tests rely heavily on subjective judgment. This paper presents and evaluates a new procedure for setting and evaluating standards on tests based on cluster analysis of test data. The clustering procedure was applied to a statewide mathematics proficiency test…

  3. A Note on Cluster Effects in Latent Class Analysis

    ERIC Educational Resources Information Center

    Kaplan, David; Keller, Bryan

    2011-01-01

    This article examines the effects of clustering in latent class analysis. A comprehensive simulation study is conducted, which begins by specifying a true multilevel latent class model with varying within- and between-cluster sample sizes, varying latent class proportions, and varying intraclass correlations. These models are then estimated under…

  4. Hierarchical spike clustering analysis for investigation of interneuron heterogeneity.

    PubMed

    Boehlen, Anne; Heinemann, Uwe; Henneberger, Christian

    2016-04-21

    Action potentials represent the output of a neuron. Especially interneurons display a variety of discharge patterns ranging from regular action potential firing to prominent spike clustering or stuttering. The mechanisms underlying this heterogeneity remain incompletely understood. We established hierarchical cluster analysis of spike trains as a measure of spike clustering. A clustering index was calculated from action potential trains recorded in the whole-cell patch clamp configuration from hippocampal (CA1, stratum radiatum) and entorhinal (medial entorhinal cortex, layer 2) interneurons in acute slices and simulated data. Prominent, region-dependent, but also variable spike clustering was detected using this measure. Further analysis revealed a strong positive correlation between spike clustering and membrane potentials oscillations but an inverse correlation with neuronal resonance. Furthermore, clustering was more pronounced when the balance between fast-activating K(+) currents, assessed by the spike repolarisation time, and hyperpolarization-activated currents, gauged by the size of the sag potential, was shifted in favour of fast K(+) currents. Simulations of spike clustering confirmed that variable ratios of fast K(+) and hyperpolarization-activated currents could underlie different degrees of spike clustering and could thus be crucial for temporally structuring interneuron spike output. PMID:26987719

  5. Effective Enrichment and Mass Spectrometry Analysis of Phosphopeptides Using Mesoporous Metal Oxide Nanomaterials

    PubMed Central

    Nelson, Cory A.; Szczech, Jeannine R.; Dooley, Chad J.; Xu, Qingge; Lawrence, Matthew J.; Zhu, Haoyue; Jin, Song; Ge, Ying

    2010-01-01

    Mass spectrometry (MS)-based phosphoproteomics remains challenging due to the low abundance of phosphoproteins and substoichiometric phosphorylation. This demands better methods to effectively enrich phosphoproteins/peptides prior to MS analysis. We have previously communicated the first use of mesoporous zirconium oxide (ZrO2) nanomaterials for effective phosphopeptide enrichment. Here we present the full report including the synthesis, characterization, and application of mesoporous titanium dioxide (TiO2), ZrO2, and hafnium oxide (HfO2) in phosphopeptide enrichment and MS analysis. Mesoporous ZrO2 and HfO2 are demonstrated to be superior to TiO2 for phosphopeptide enrichment from a complex mixture with high specificity (>99%), which could almost be considered as “a purification”, mainly because of the extremely large active surface area of mesoporous nanomaterials. A single enrichment and Fourier transform MS analysis of phosphopeptides digested from a complex mixture containing 7% of α-casein identified 21 out of 22 phosphorylation sites for α-casein. Moreover, the mesoporous ZrO2 and HfO2 can be reused after a simple solution regeneration procedure with comparable enrichment performance to that of fresh materials. Mesoporous ZrO2 and HfO2 nanomaterials hold great promise for applications in MS-based phosphoproteomics. PMID:20704311

  6. Effective enrichment and mass spectrometry analysis of phosphopeptides using mesoporous metal oxide nanomaterials.

    PubMed

    Nelson, Cory A; Szczech, Jeannine R; Dooley, Chad J; Xu, Qingge; Lawrence, Matthew J; Zhu, Haoyue; Jin, Song; Ge, Ying

    2010-09-01

    Mass spectrometry (MS)-based phosphoproteomics remains challenging due to the low abundance of phosphoproteins and substoichiometric phosphorylation. This demands better methods to effectively enrich phosphoproteins/peptides prior to MS analysis. We have previously communicated the first use of mesoporous zirconium dioxide (ZrO(2)) nanomaterials for effective phosphopeptide enrichment. Here, we present the full report including the synthesis, characterization, and application of mesoporous titanium dioxide (TiO(2)), ZrO(2), and hafnium dioxide (HfO(2)) in phosphopeptide enrichment and MS analysis. Mesoporous ZrO(2) and HfO(2) are demonstrated to be superior to TiO(2) for phosphopeptide enrichment from a complex mixture with high specificity (>99%), which could almost be considered as a "purification", mainly because of the extremely large active surface area of mesoporous nanomaterials. A single enrichment and Fourier transform MS analysis of phosphopeptides digested from a complex mixture containing 7% of alpha-casein identified 21 out of 22 phosphorylation sites for alpha-casein. Moreover, the mesoporous ZrO(2) and HfO(2) can be reused after a simple solution regeneration procedure with comparable enrichment performance to that of fresh materials. Mesoporous ZrO(2) and HfO(2) nanomaterials hold great promise for applications in MS-based phosphoproteomics.

  7. Obstructive Sleep Apnea: A Cluster Analysis at Time of Diagnosis

    PubMed Central

    Grillet, Yves; Richard, Philippe; Stach, Bruno; Vivodtzev, Isabelle; Timsit, Jean-Francois; Lévy, Patrick; Tamisier, Renaud; Pépin, Jean-Louis

    2016-01-01

    Background The classification of obstructive sleep apnea is on the basis of sleep study criteria that may not adequately capture disease heterogeneity. Improved phenotyping may improve prognosis prediction and help select therapeutic strategies. Objectives: This study used cluster analysis to investigate the clinical clusters of obstructive sleep apnea. Methods An ascending hierarchical cluster analysis was performed on baseline symptoms, physical examination, risk factor exposure and co-morbidities from 18,263 participants in the OSFP (French national registry of sleep apnea). The probability for criteria to be associated with a given cluster was assessed using odds ratios, determined by univariate logistic regression. Results: Six clusters were identified, in which patients varied considerably in age, sex, symptoms, obesity, co-morbidities and environmental risk factors. The main significant differences between clusters were minimally symptomatic versus sleepy obstructive sleep apnea patients, lean versus obese, and among obese patients different combinations of co-morbidities and environmental risk factors. Conclusions Our cluster analysis identified six distinct clusters of obstructive sleep apnea. Our findings underscore the high degree of heterogeneity that exists within obstructive sleep apnea patients regarding clinical presentation, risk factors and consequences. This may help in both research and clinical practice for validating new prevention programs, in diagnosis and in decisions regarding therapeutic strategies. PMID:27314230

  8. FunRich: An open access standalone functional enrichment and interaction network analysis tool.

    PubMed

    Pathan, Mohashin; Keerthikumar, Shivakumar; Ang, Ching-Seng; Gangoda, Lahiru; Quek, Camelia Y J; Williamson, Nicholas A; Mouradov, Dmitri; Sieber, Oliver M; Simpson, Richard J; Salim, Agus; Bacic, Antony; Hill, Andrew F; Stroud, David A; Ryan, Michael T; Agbinya, Johnson I; Mariadason, John M; Burgess, Antony W; Mathivanan, Suresh

    2015-08-01

    As high-throughput techniques including proteomics become more accessible to individual laboratories, there is an urgent need for a user-friendly bioinformatics analysis system. Here, we describe FunRich, an open access, standalone functional enrichment and network analysis tool. FunRich is designed to be used by biologists with minimal or no support from computational and database experts. Using FunRich, users can perform functional enrichment analysis on background databases that are integrated from heterogeneous genomic and proteomic resources (>1.5 million annotations). Besides default human specific FunRich database, users can download data from the UniProt database, which currently supports 20 different taxonomies against which enrichment analysis can be performed. Moreover, the users can build their own custom databases and perform the enrichment analysis irrespective of organism. In addition to proteomics datasets, the custom database allows for the tool to be used for genomics, lipidomics and metabolomics datasets. Thus, FunRich allows for complete database customization and thereby permits for the tool to be exploited as a skeleton for enrichment analysis irrespective of the data type or organism used. FunRich (http://www.funrich.org) is user-friendly and provides graphical representation (Venn, pie charts, bar graphs, column, heatmap and doughnuts) of the data with customizable font, scale and color (publication quality).

  9. Visual verification and analysis of cluster detection for molecular dynamics.

    PubMed

    Grottel, Sebastian; Reina, Guido; Vrabec, Jadran; Ertl, Thomas

    2007-01-01

    A current research topic in molecular thermodynamics is the condensation of vapor to liquid and the investigation of this process at the molecular level. Condensation is found in many physical phenomena, e.g. the formation of atmospheric clouds or the processes inside steam turbines, where a detailed knowledge of the dynamics of condensation processes will help to optimize energy efficiency and avoid problems with droplets of macroscopic size. The key properties of these processes are the nucleation rate and the critical cluster size. For the calculation of these properties it is essential to make use of a meaningful definition of molecular clusters, which currently is a not completely resolved issue. In this paper a framework capable of interactively visualizing molecular datasets of such nucleation simulations is presented, with an emphasis on the detected molecular clusters. To check the quality of the results of the cluster detection, our framework introduces the concept of flow groups to highlight potential cluster evolution over time which is not detected by the employed algorithm. To confirm the findings of the visual analysis, we coupled the rendering view with a schematic view of the clusters' evolution. This allows to rapidly assess the quality of the molecular cluster detection algorithm and to identify locations in the simulation data in space as well as in time where the cluster detection fails. Thus, thermodynamics researchers can eliminate weaknesses in their cluster detection algorithms. Several examples for the effective and efficient usage of our tool are presented. PMID:17968118

  10. Visual verification and analysis of cluster detection for molecular dynamics.

    PubMed

    Grottel, Sebastian; Reina, Guido; Vrabec, Jadran; Ertl, Thomas

    2007-01-01

    A current research topic in molecular thermodynamics is the condensation of vapor to liquid and the investigation of this process at the molecular level. Condensation is found in many physical phenomena, e.g. the formation of atmospheric clouds or the processes inside steam turbines, where a detailed knowledge of the dynamics of condensation processes will help to optimize energy efficiency and avoid problems with droplets of macroscopic size. The key properties of these processes are the nucleation rate and the critical cluster size. For the calculation of these properties it is essential to make use of a meaningful definition of molecular clusters, which currently is a not completely resolved issue. In this paper a framework capable of interactively visualizing molecular datasets of such nucleation simulations is presented, with an emphasis on the detected molecular clusters. To check the quality of the results of the cluster detection, our framework introduces the concept of flow groups to highlight potential cluster evolution over time which is not detected by the employed algorithm. To confirm the findings of the visual analysis, we coupled the rendering view with a schematic view of the clusters' evolution. This allows to rapidly assess the quality of the molecular cluster detection algorithm and to identify locations in the simulation data in space as well as in time where the cluster detection fails. Thus, thermodynamics researchers can eliminate weaknesses in their cluster detection algorithms. Several examples for the effective and efficient usage of our tool are presented.

  11. A Flocking Based algorithm for Document Clustering Analysis

    SciTech Connect

    Cui, Xiaohui; Gao, Jinzhu; Potok, Thomas E

    2006-01-01

    Social animals or insects in nature often exhibit a form of emergent collective behavior known as flocking. In this paper, we present a novel Flocking based approach for document clustering analysis. Our Flocking clustering algorithm uses stochastic and heuristic principles discovered from observing bird flocks or fish schools. Unlike other partition clustering algorithm such as K-means, the Flocking based algorithm does not require initial partitional seeds. The algorithm generates a clustering of a given set of data through the embedding of the high-dimensional data items on a two-dimensional grid for easy clustering result retrieval and visualization. Inspired by the self-organized behavior of bird flocks, we represent each document object with a flock boid. The simple local rules followed by each flock boid result in the entire document flock generating complex global behaviors, which eventually result in a clustering of the documents. We evaluate the efficiency of our algorithm with both a synthetic dataset and a real document collection that includes 100 news articles collected from the Internet. Our results show that the Flocking clustering algorithm achieves better performance compared to the K- means and the Ant clustering algorithm for real document clustering.

  12. Revealing gene clusters associated with the development of cholangiocarcinoma, based on a time series analysis.

    PubMed

    Wu, Jianyu; Xiao, Zhifu; Zhao, Xiulei; Wu, Xiangsong

    2015-05-01

    Cholangiocarcinoma (CC) is a rapidly lethal malignancy and currently is considered to be incurable. Biomarkers related to the development of CC remain unclear. The present study aimed to identify differentially expressed genes (DEGs) between normal tissue and intrahepatic CC, as well as specific gene expression patterns that changed together with the development of CC. By using a two‑way analysis of variance test, the biomarkers that could distinguish between normal tissue and intrahepatic CC dissected from different days were identified. A k‑means cluster method was used to identify gene clusters associated with the development of CC according to their changing expression pattern. Functional enrichment analysis was used to infer the function of each of the gene sets. A time series analysis was constructed to reveal gene signatures that were associated with the development of CC based on gene expression profile changes. Genes related to CC were shown to be involved in 'mitochondrion' and 'focal adhesion'. Three interesting gene groups were identified by the k‑means cluster method. Gene clusters with a unique expression pattern are related with the development of CC. The data of this study will facilitate novel discoveries regarding the genetic study of CC by further work.

  13. Automated analysis of organic particles using cluster SIMS

    NASA Astrophysics Data System (ADS)

    Gillen, Greg; Zeissler, Cindy; Mahoney, Christine; Lindstrom, Abigail; Fletcher, Robert; Chi, Peter; Verkouteren, Jennifer; Bright, David; Lareau, Richard T.; Boldman, Mike

    2004-06-01

    Cluster primary ion bombardment combined with secondary ion imaging is used on an ion microscope secondary ion mass spectrometer for the spatially resolved analysis of organic particles on various surfaces. Compared to the use of monoatomic primary ion beam bombardment, the use of a cluster primary ion beam (SF 5+ or C 8-) provides significant improvement in molecular ion yields and a reduction in beam-induced degradation of the analyte molecules. These characteristics of cluster bombardment, along with automated sample stage control and custom image analysis software are utilized to rapidly characterize the spatial distribution of trace explosive particles, narcotics and inkjet-printed microarrays on a variety of surfaces.

  14. Logistics Enterprise Evaluation Model Based On Fuzzy Clustering Analysis

    NASA Astrophysics Data System (ADS)

    Fu, Pei-hua; Yin, Hong-bo

    In this thesis, we introduced an evaluation model based on fuzzy cluster algorithm of logistics enterprises. First of all,we present the evaluation index system which contains basic information, management level, technical strength, transport capacity,informatization level, market competition and customer service. We decided the index weight according to the grades, and evaluated integrate ability of the logistics enterprises using fuzzy cluster analysis method. In this thesis, we introduced the system evaluation module and cluster analysis module in detail and described how we achieved these two modules. At last, we gave the result of the system.

  15. Identification of chronic rhinosinusitis phenotypes using cluster analysis

    PubMed Central

    Soler, Zachary M.; Hyer, J. Madison; Ramakrishnan, Viswanathan; Smith, Timothy L.; Mace, Jess; Rudmik, Luke; Schlosser, Rodney J.

    2015-01-01

    Introduction Current clinical classifications of chronic rhinosinusitis (CRS) have been largely defined based upon preconceived notions of factors thought to be important, such as polyp or eosinophil status. Unfortunately, these classification systems have little correlation with symptom severity or treatment outcomes. Unsupervised clustering can be used to identify phenotypic subgroups of CRS patients, describe clinical differences in these clusters and define simple algorithms for classification. Methods A multi-institutional, prospective study of 382 patients with CRS who had failed initial medical therapy completed the SinoNasal Outcome Test (SNOT-22), Rhinosinusitis Disability Index (RSDI), Short Form-12 (SF-12), Pittsburgh Sleep Quality Index (PSQI), and Patient Health Questionnaire (PHQ-2). Objective measures of CRS severity included Brief Smell Identification Test (B-SIT), CT and endoscopy scoring. All variables were reduced and unsupervised hierarchical clustering was performed. After clusters were defined, variations in medication usage were analyzed. Discriminant analysis was performed to develop a simplified, clinically useful algorithm for clustering. Results Clustering was largely determined by age, severity of patient reported outcome measures, depression and fibromyalgia. CT and endoscopy varied somewhat among clusters. Traditional clinical measures including polyp/atopic status, prior surgery, B-SIT and asthma did not vary among clusters. A simplified algorithm based upon productivity loss, SNOT-22 score and age predicted clustering with 89% accuracy. Medication usage among clusters did vary significantly. Discussion A simplified algorithm based upon hierarchical clustering is able to classify CRS patients and predict medication usage. Further studies are warranted to determine if such clustering predicts treatment outcomes. PMID:25694390

  16. Effects of Group Size and Lack of Sphericity on the Recovery of Clusters in K-Means Cluster Analysis

    ERIC Educational Resources Information Center

    de Craen, Saskia; Commandeur, Jacques J. F.; Frank, Laurence E.; Heiser, Willem J.

    2006-01-01

    K-means cluster analysis is known for its tendency to produce spherical and equally sized clusters. To assess the magnitude of these effects, a simulation study was conducted, in which populations were created with varying departures from sphericity and group sizes. An analysis of the recovery of clusters in the samples taken from these…

  17. Following tetraploidy in an Arabidopsis ancestor, genes were removed preferentially from one homeolog leaving clusters enriched in dose-sensitive genes.

    PubMed

    Thomas, Brian C; Pedersen, Brent; Freeling, Michael

    2006-07-01

    Approximately 90% of Arabidopsis' unique gene content is found in syntenic blocks that were formed during the most recent whole-genome duplication. Within these blocks, 28.6% of the genes have a retained pair; the remaining genes have been lost from one of the homeologs. We create a minimized genome by condensing local duplications to one gene, removing transposons, and including only genes within blocks defined by retained pairs. We use a moving average of retained and non-retained genes to find clusters of retention and then identify the types of genes that appear in clusters at frequencies above expectations. Significant clusters of retention exist for almost all chromosomal segments. Detailed alignments show that, for 85% of the genome, one homeolog was preferentially (1.6x) targeted for fractionation. This homeolog fractionation bias suggests an epigenetic mechanism. We find that islands of retention contain "connected genes," those genes predicted-by the gene balance hypothesis-to be resistant to removal because the products they encode interact with other products in a dose-sensitive manner, creating a web of dependency. Gene families that are overrepresented in clusters include those encoding components of the proteasome/protein modification complexes, signal transduction machinery, ribosomes, and transcription factor complexes. Gene pair fractionation following polyploidy or segmental duplication leaves a genome enriched for "connected" genes. These clusters of duplicate genes may help explain the evolutionary origin of coregulated chromosomal regions and new functional modules. PMID:16760422

  18. Following tetraploidy in an Arabidopsis ancestor, genes were removed preferentially from one homeolog leaving clusters enriched in dose-sensitive genes.

    PubMed

    Thomas, Brian C; Pedersen, Brent; Freeling, Michael

    2006-07-01

    Approximately 90% of Arabidopsis' unique gene content is found in syntenic blocks that were formed during the most recent whole-genome duplication. Within these blocks, 28.6% of the genes have a retained pair; the remaining genes have been lost from one of the homeologs. We create a minimized genome by condensing local duplications to one gene, removing transposons, and including only genes within blocks defined by retained pairs. We use a moving average of retained and non-retained genes to find clusters of retention and then identify the types of genes that appear in clusters at frequencies above expectations. Significant clusters of retention exist for almost all chromosomal segments. Detailed alignments show that, for 85% of the genome, one homeolog was preferentially (1.6x) targeted for fractionation. This homeolog fractionation bias suggests an epigenetic mechanism. We find that islands of retention contain "connected genes," those genes predicted-by the gene balance hypothesis-to be resistant to removal because the products they encode interact with other products in a dose-sensitive manner, creating a web of dependency. Gene families that are overrepresented in clusters include those encoding components of the proteasome/protein modification complexes, signal transduction machinery, ribosomes, and transcription factor complexes. Gene pair fractionation following polyploidy or segmental duplication leaves a genome enriched for "connected" genes. These clusters of duplicate genes may help explain the evolutionary origin of coregulated chromosomal regions and new functional modules.

  19. Using cluster analysis to organize and explore regional GPS velocities

    USGS Publications Warehouse

    Simpson, Robert W.; Thatcher, Wayne; Savage, James C.

    2012-01-01

    Cluster analysis offers a simple visual exploratory tool for the initial investigation of regional Global Positioning System (GPS) velocity observations, which are providing increasingly precise mappings of actively deforming continental lithosphere. The deformation fields from dense regional GPS networks can often be concisely described in terms of relatively coherent blocks bounded by active faults, although the choice of blocks, their number and size, can be subjective and is often guided by the distribution of known faults. To illustrate our method, we apply cluster analysis to GPS velocities from the San Francisco Bay Region, California, to search for spatially coherent patterns of deformation, including evidence of block-like behavior. The clustering process identifies four robust groupings of velocities that we identify with four crustal blocks. Although the analysis uses no prior geologic information other than the GPS velocities, the cluster/block boundaries track three major faults, both locked and creeping.

  20. Comparative analysis of genomic signal processing for microarray data clustering.

    PubMed

    Istepanian, Robert S H; Sungoor, Ala; Nebel, Jean-Christophe

    2011-12-01

    Genomic signal processing is a new area of research that combines advanced digital signal processing methodologies for enhanced genetic data analysis. It has many promising applications in bioinformatics and next generation of healthcare systems, in particular, in the field of microarray data clustering. In this paper we present a comparative performance analysis of enhanced digital spectral analysis methods for robust clustering of gene expression across multiple microarray data samples. Three digital signal processing methods: linear predictive coding, wavelet decomposition, and fractal dimension are studied to provide a comparative evaluation of the clustering performance of these methods on several microarray datasets. The results of this study show that the fractal approach provides the best clustering accuracy compared to other digital signal processing and well known statistical methods.

  1. Genome wide analysis of Silurana (Xenopus) tropicalis development reveals dynamic expression using network enrichment analysis.

    PubMed

    Langlois, Valérie S; Martyniuk, Christopher J

    2013-01-01

    Development involves precise timing of gene expression and coordinated pathways for organogenesis and morphogenesis. Functional and sub-network enrichment analysis provides an integrated approach for identifying networks underlying development. The objectives of this study were to characterize early gene regulatory networks over Silurana tropicalis development from NF stage 2 to 46 using a custom Agilent 4×44K microarray. There were >8000 unique gene probes that were differentially expressed between Nieuwkoop-Faber (NF) stage 2 and stage 16, and >2000 gene probes differentially expressed between NF 34 and 46. Gene ontology revealed that genes involved in nucleosome assembly, cell division, pattern specification, neurotransmission, and general metabolism were increasingly regulated throughout development, consistent with active development. Sub-network enrichment analysis revealed that processes such as membrane hyperpolarisation, retinoic acid, cholesterol, and dopamine metabolic gene networks were activated/inhibited over time. This study identifies RNA transcripts that are potentially maternally inherited in an anuran species, provides evidence that the expression of genes involved in retinoic acid receptor signaling may increase prior to those involved in thyroid receptor signaling, and characterizes novel gene expression networks preceding organogenesis which increases understanding of the spatiotemporal embryonic development in frogs.

  2. Automated classification of visible and infrared spectra using cluster analysis

    NASA Astrophysics Data System (ADS)

    Marzo, G. A.; Roush, T. L.; Hogan, R. C.

    2009-08-01

    Planetary space experiments collect large volumes of data whose scientific content requires understanding. Marzo et al. (2006) presented an unsupervised cluster analysis scheme that is able to reduce a spectral data set to a few clusters, allowing for more focused and rapid evaluation of their scientific meaning. Here, we extend the original approach to account for the measurement uncertainty and build a classification scheme. We apply the clustering technique to the ASTER and RELAB libraries of visible and infrared spectral reflectance. These spectral libraries are documented, allowing assignment of a label to each spectrum reflecting its physical and chemical properties. We assess the ability of the original and extended approaches to identify natural clusters of the library spectra and estimate associated uncertainties of the results. We evaluate the scientific meaning of the derived clusters based on the labels contained within each cluster. Once the cluster meanings are defined, we test our classification scheme using a training-testing approach and evaluate the accuracy of assigning the unknown spectra to the correct cluster.

  3. A Distributed Flocking Approach for Information Stream Clustering Analysis

    SciTech Connect

    Cui, Xiaohui; Potok, Thomas E

    2006-01-01

    Intelligence analysts are currently overwhelmed with the amount of information streams generated everyday. There is a lack of comprehensive tool that can real-time analyze the information streams. Document clustering analysis plays an important role in improving the accuracy of information retrieval. However, most clustering technologies can only be applied for analyzing the static document collection because they normally require a large amount of computation resource and long time to get accurate result. It is very difficult to cluster a dynamic changed text information streams on an individual computer. Our early research has resulted in a dynamic reactive flock clustering algorithm which can continually refine the clustering result and quickly react to the change of document contents. This character makes the algorithm suitable for cluster analyzing dynamic changed document information, such as text information stream. Because of the decentralized character of this algorithm, a distributed approach is a very natural way to increase the clustering speed of the algorithm. In this paper, we present a distributed multi-agent flocking approach for the text information stream clustering and discuss the decentralized architectures and communication schemes for load balance and status information synchronization in this approach.

  4. Meta-analysis of pathway enrichment: combining independent and dependent omics data sets.

    PubMed

    Kaever, Alexander; Landesfeind, Manuel; Feussner, Kirstin; Morgenstern, Burkhard; Feussner, Ivo; Meinicke, Peter

    2014-01-01

    A major challenge in current systems biology is the combination and integrative analysis of large data sets obtained from different high-throughput omics platforms, such as mass spectrometry based Metabolomics and Proteomics or DNA microarray or RNA-seq-based Transcriptomics. Especially in the case of non-targeted Metabolomics experiments, where it is often impossible to unambiguously map ion features from mass spectrometry analysis to metabolites, the integration of more reliable omics technologies is highly desirable. A popular method for the knowledge-based interpretation of single data sets is the (Gene) Set Enrichment Analysis. In order to combine the results from different analyses, we introduce a methodical framework for the meta-analysis of p-values obtained from Pathway Enrichment Analysis (Set Enrichment Analysis based on pathways) of multiple dependent or independent data sets from different omics platforms. For dependent data sets, e.g. obtained from the same biological samples, the framework utilizes a covariance estimation procedure based on the nonsignificant pathways in single data set enrichment analysis. The framework is evaluated and applied in the joint analysis of Metabolomics mass spectrometry and Transcriptomics DNA microarray data in the context of plant wounding. In extensive studies of simulated data set dependence, the introduced correlation could be fully reconstructed by means of the covariance estimation based on pathway enrichment. By restricting the range of p-values of pathways considered in the estimation, the overestimation of correlation, which is introduced by the significant pathways, could be reduced. When applying the proposed methods to the real data sets, the meta-analysis was shown not only to be a powerful tool to investigate the correlation between different data sets and summarize the results of multiple analyses but also to distinguish experiment-specific key pathways.

  5. An Economical Method for Static Headspace Enrichment for Arson Analysis

    ERIC Educational Resources Information Center

    Olesen, Bjorn

    2010-01-01

    Static headspace analysis of accelerants from suspected arsons is accomplished by placing an arson sample in a sealed container with a carbon strip suspended above the sample. The sample is heated, cooled to room temperature, and then the organic components are extracted from the carbon strip with carbon disulfide followed by gas chromatography…

  6. Cluster analysis of Southeastern U.S. climate stations

    NASA Astrophysics Data System (ADS)

    Stooksbury, D. E.; Michaels, P. J.

    1991-09-01

    A two-step cluster analysis of 449 Southeastern climate stations is used to objectively determine general climate clusters (groups of climate stations) for eight southeastern states. The purpose is objectively to define regions of climatic homogeneity that should perform more robustly in subsequent climatic impact models. This type of analysis has been successfully used in many related climate research problems including the determination of corn/climate districts in Iowa (Ortiz-Valdez, 1985) and the classification of synoptic climate types (Davis, 1988). These general climate clusters may be more appropriate for climate research than the standard climate divisions (CD) groupings of climate stations, which are modifications of the agro-economic United States Department of Agriculture crop reporting districts. Unlike the CD's, these objectively determined climate clusters are not restricted by state borders and thus have reduced multicollinearity which makes them more appropriate for the study of the impact of climate and climatic change.

  7. GE-Miner: integration of cluster ensemble and text mining for comprehensive gene expression analysis.

    PubMed

    Hu, Xiaohua

    2006-01-01

    Generating high quality gene clusters and identifying the underlying biological mechanism of the gene clusters are the important goals of clustering gene expression analysis. Based on this consideration, we design and develop a unified system Gene Expression Miner (GE-Miner) by integrating cluster ensemble, text clustering and multidocument summarisation and provide an environment for comprehensive gene expression data analysis. Experimental results demonstrate that our systems can obtain high quality clusters and provide concise and informative textual summary for the gene clusters.

  8. A meta-analysis of the effects of nutrient enrichment on litter decomposition in streams.

    PubMed

    Ferreira, Verónica; Castagneyrol, Bastien; Koricheva, Julia; Gulis, Vladislav; Chauvet, Eric; Graça, Manuel A S

    2015-08-01

    The trophic state of many streams is likely to deteriorate in the future due to the continuing increase in human-induced nutrient availability. Therefore, it is of fundamental importance to understand how nutrient enrichment affects plant litter decomposition, a key ecosystem-level process in forest streams. Here, we present a meta-analysis of 99 studies published between 1970 and 2012 that reported the effects of nutrient enrichment on litter decomposition in running waters. When considering the entire database, which consisted of 840 case studies, nutrient enrichment stimulated litter decomposition rate by approximately 50%. The stimulation was higher when the background nutrient concentrations were low and the magnitude of the nutrient enrichment was high, suggesting that oligotrophic streams are most vulnerable to nutrient enrichment. The magnitude of the nutrient-enrichment effect on litter decomposition was higher in the laboratory than in the field experiments, suggesting that laboratory experiments overestimate the effect and their results should be interpreted with caution. Among field experiments, effects of nutrient enrichment were smaller in the correlative than in the manipulative experiments since in the former the effects of nutrient enrichment on litter decomposition were likely confounded by other environmental factors, e.g. pollutants other than nutrients commonly found in streams impacted by human activity. However, primary studies addressing the effect of multiple stressors on litter decomposition are still few and thus it was not possible to consider the interaction between factors in this review. In field manipulative experiments, the effect of nutrient enrichment on litter decomposition depended on the scale at which the nutrients were added: stream reach > streamside channel > litter bag. This may have resulted from a more uniform and continuous exposure of microbes and detritivores to nutrient enrichment at the stream-reach scale. By

  9. Chemical analysis of giant stars in the young open cluster NGC 3114

    NASA Astrophysics Data System (ADS)

    Santrich, O. J. Katime; Pereira, C. B.; Drake, N. A.

    2013-06-01

    Context. Open clusters are very useful targets for examining possible trends in galactocentric distance and age, especially when young and old open clusters are compared. Aims: We carried out a detailed spectroscopic analysis to derive the chemical composition of seven red giants in the young open cluster NGC 3114. Abundances of C, N, O, Li, Na, Mg, Al, Ca, Si, Ti, Ni, Cr, Y, Zr, La, Ce, and Nd were obtained, as well as the carbon isotopic ratio. Methods: The atmospheric parameters of the studied stars and their chemical abundances were determined using high-resolution optical spectroscopy. We employed the local-thermodynamic-equilibrium model atmospheres of Kurucz and the spectral analysis code MOOG. The abundances of the light elements were derived using the spectral synthesis technique. Results: We found that NGC 3114 has a mean metallicity of [Fe/H] = -0.01 ± 0.03. The isochrone fit yielded a turn-off mass of 4.2 M⊙. The [N/C] ratio is in good agreement with the models predicted by first dredge-up. We found that two stars, HD 87479 and HD 304864, have high rotational velocities of 15.0 km s-1 and 11.0 km s-1; HD 87526 is a halo star and is not a member of NGC 3114. Conclusions: The carbon and nitrogen abundance in NGC 3114 agree with the field and cluster giants. The oxygen abundance in NGC 3114 is lower compared to the field giants. The [O/Fe] ratio is similar to the giants in young clusters. We detected sodium enrichment in the analyzed cluster giants. As far as the other elements are concerned, their [X/Fe] ratios follow the same trend seen in giants with the same metallicity. Based on observations made with the 2.2 m telescope at the European Southern Observatory (La Silla, Chile).Tables 2 and 5 are available in electronic form at http://www.aanda.org

  10. Analysis of the effectiveness of gas centrifuge enrichment plants advanced safeguards

    SciTech Connect

    Boyer, Brian David; Erpenbeck, Heather H; Miller, Karen A; Swinjoe, Martyn T; Ianakiev, Kiril D; Marlow, Johnna B

    2010-01-01

    Current safeguards approaches used by the International Atomic Energy Agency (IAEA) at gas centrifuge enrichment plants (GCEPs) need enhancement in order to verify declared low-enriched uranium (LEU) production, detect undeclared LEU production and detect highly enriched uranium (HEU) production with adequate detection probability using non destructive assay (NDA) techniques. At present inspectors use attended systems, systems needing the presence of an inspector for operation, during inspections to verify the mass and 235U enrichment of declared UF6 containers used in the process of enrichment at GCEPs. This paper contains an analysis of possible improvements in unattended and attended NDA systems including process monitoring and possible on-site destructive assay (DA) of samples that could reduce the uncertainty of the inspector's measurements. These improvements could reduce the difference between the operator's and inspector's measurements providing more effective and efficient IAEA GCEPs safeguards. We also explore how a few advanced safeguards systems could be assembled for unattended operation. The analysis will focus on how unannounced inspections (UIs), and the concept of information-driven inspections (IDS) can affect probability of detection of the diversion of nuclear materials when coupled to new GCEPs safeguards regimes augmented with unattended systems.

  11. The Enhanced Hoshen-Kopelman Algorithm for Cluster Analysis

    NASA Astrophysics Data System (ADS)

    Hoshen, Joseph

    1997-08-01

    In 1976 Hoshen and Kopelman(J. Hoshen and R. Kopelman, Phys. Rev. B, 14, 3438 (1976).) introduced a breakthrough algorithm, known today as the Hoshen-Kopelman algorithm, for cluster analysis. This algorithm revolutionized Monte Carlo cluster calculations in percolation theory as it enables analysis of very large lattices containing 10^11 or more sites. Initially the HK algorithm primary use was in the domain of pure and basic sciences. Later it began finding applications in diverse fields of technology and applied sciences. Example of such applications are two and three dimensional image analysis, composite material modeling, polymers, remote sensing, brain modeling and food processing. While the original HK algorithm provides only cluster size data for only one class of sites, the Enhanced HK (EHK) algorithm, presented in this paper, enables calculations of cluster spatial moments -- characteristics of cluster shapes -- for multiple classes of sites. These enhancements preserve the time and space complexities of the original HK algorithm, such that very large lattices could be still analyzed simultaneously in a single pass through the lattice for cluster sizes, classes and shapes.

  12. Application of Subspace Clustering in DNA Sequence Analysis.

    PubMed

    Wallace, Tim; Sekmen, Ali; Wang, Xiaofei

    2015-10-01

    Identification and clustering of orthologous genes plays an important role in developing evolutionary models such as validating convergent and divergent phylogeny and predicting functional proteins in newly sequenced species of unverified nucleotide protein mappings. Here, we introduce an application of subspace clustering as applied to orthologous gene sequences and discuss the initial results. The working hypothesis is based upon the concept that genetic changes between nucleotide sequences coding for proteins among selected species and groups may lie within a union of subspaces for clusters of the orthologous groups. Estimates for the subspace dimensions were computed for a small population sample. A series of experiments was performed to cluster randomly selected sequences. The experimental design allows for both false positives and false negatives, and estimates for the statistical significance are provided. The clustering results are consistent with the main hypothesis. A simple random mutation binary tree model is used to simulate speciation events that show the interdependence of the subspace rank versus time and mutation rates. The simple mutation model is found to be largely consistent with the observed subspace clustering singular value results. Our study indicates that the subspace clustering method may be applied in orthology analysis. PMID:26162018

  13. Systematic enrichment analysis of gene expression profiling studies identifies consensus pathways implicated in colorectal cancer development

    PubMed Central

    Lascorz, Jesús; Hemminki, Kari; Försti, Asta

    2011-01-01

    Background: A large number of gene expression profiling (GEP) studies on colorectal carcinogenesis have been performed but no reliable gene signature has been identified so far due to the lack of reproducibility in the reported genes. There is growing evidence that functionally related genes, rather than individual genes, contribute to the etiology of complex traits. We used, as a novel approach, pathway enrichment tools to define functionally related genes that are consistently up- or down-regulated in colorectal carcinogenesis. Materials and Methods: We started the analysis with 242 unique annotated genes that had been reported by any of three recent meta-analyses covering GEP studies on genes differentially expressed in carcinoma vs normal mucosa. Most of these genes (218, 91.9%) had been reported in at least three GEP studies. These 242 genes were submitted to bioinformatic analysis using a total of nine tools to detect enrichment of Gene Ontology (GO) categories or Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. As a final consistency criterion the pathway categories had to be enriched by several tools to be taken into consideration. Results: Our pathway-based enrichment analysis identified the categories of ribosomal protein constituents, extracellular matrix receptor interaction, carbonic anhydrase isozymes, and a general category related to inflammation and cellular response as significantly and consistently overrepresented entities. Conclusions: We triaged the genes covered by the published GEP literature on colorectal carcinogenesis and subjected them to multiple enrichment tools in order to identify the consistently enriched gene categories. These turned out to have known functional relationships to cancer development and thus deserve further investigation. PMID:21483658

  14. CLASH-VLT: Strangulation of cluster galaxies in MACS J0416.1-2403 as seen from their chemical enrichment

    NASA Astrophysics Data System (ADS)

    Maier, C.; Kuchner, U.; Ziegler, B. L.; Verdugo, M.; Balestra, I.; Girardi, M.; Mercurio, A.; Rosati, P.; Fritz, A.; Grillo, C.; Nonino, M.; Sartoris, B.

    2016-05-01

    Aims: Environmental effects gain importance as large scale structures in the Universe develop with time and have become the dominant mechanism for quenching galaxies of intermediate and low stellar masses at lower redshifts. Therefore, clusters of galaxies at z< 0.5 are the sites where environmental effects are expected to be more pronounced and more easily observed with present-day large telescopes. Methods: We explore the Frontier Fields cluster MACS J0416.1-2403 at z = 0.3972 with VIMOS/VLT spectroscopy from the CLASH-VLT survey covering a region that corresponds to almost three virial radii. We measure fluxes of Hβ, [O III]λ 5007, Hα, and [N II]λ 6584 emission lines of cluster members enabling us to unambiguously derive O/H gas metallicities, and also star formation rates from extinction-corrected Hα fluxes. We compare our cluster galaxy sample with a field sample at z ~ 0.4 drawn from zCOSMOS. Results: The 76 galaxies of our cluster sample follow the star-forming metallicity sequence in a diagnostic diagram disentangling ionizing sources. For intermediate masses we find a similar distribution of cluster and field galaxies in the mass vs. metallicity and mass vs. sSFR diagrams. An in-depth investigation furthermore reveals that bulge-dominated cluster galaxies have on average lower sSFRs and higher O/Hs than their disk-dominated counterparts. We use the location of galaxies in the projected velocity vs. position phase-space to separate our cluster sample into a region of objects accreted longer ago and a region of recently accreted and infalling galaxies. We find a higher fraction of accreted metal-rich galaxies (63%) compared to the fraction of 28% of metal-rich galaxies in the infalling regions. Intermediate-mass galaxies (9.2 < log (M/M⊙) < 10.2) falling into the cluster for the first time are found to be in agreement with predictions of the fundamental metallicity relation. In contrast, for already accreted star-forming galaxies of similar masses, we

  15. Open-box spectral clustering: applications to medical image analysis.

    PubMed

    Schultz, Thomas; Kindlmann, Gordon L

    2013-12-01

    Spectral clustering is a powerful and versatile technique, whose broad range of applications includes 3D image analysis. However, its practical use often involves a tedious and time-consuming process of tuning parameters and making application-specific choices. In the absence of training data with labeled clusters, help from a human analyst is required to decide the number of clusters, to determine whether hierarchical clustering is needed, and to define the appropriate distance measures, parameters of the underlying graph, and type of graph Laplacian. We propose to simplify this process via an open-box approach, in which an interactive system visualizes the involved mathematical quantities, suggests parameter values, and provides immediate feedback to support the required decisions. Our framework focuses on applications in 3D image analysis, and links the abstract high-dimensional feature space used in spectral clustering to the three-dimensional data space. This provides a better understanding of the technique, and helps the analyst predict how well specific parameter settings will generalize to similar tasks. In addition, our system supports filtering outliers and labeling the final clusters in such a way that user actions can be recorded and transferred to different data in which the same structures are to be found. Our system supports a wide range of inputs, including triangular meshes, regular grids, and point clouds. We use our system to develop segmentation protocols in chest CT and brain MRI that are then successfully applied to other datasets in an automated manner.

  16. An Enriched Radial Point Interpolation Method (e-RPIM) for the Analysis of Crack Tip

    NASA Astrophysics Data System (ADS)

    Gu, Y. T.; Wang, W. L.; Fu, Q.

    2010-05-01

    In this paper, an enriched radial point interpolation method (e-RPIM) is developed for the determination of crack tip fields. The conventional RBF interpolation is novelly augmented by the suitable trigonometric basis functions to reflect the properties of stresses for the crack tip fields. The performance of the enriched meshfree RBF shape functions is firstly investigated using the surface fitting. The surface fitting results have proven that, comparing with the conventional RBF, the enriched RBF interpolation has: 1) a similar accuracy to fit a polynomial surface; and 2) a much better accuracy to fit a trigonometric surface then the conventional RBF interpolation. It has proven that the enriched RBF shape function will not only possess all advantages of conventional RBF interpolation, but also can accurately reflect the properties of stresses for the crack tip fields. The system of equations for the crack analysis is then derived based on the enriched RBF shape function and the meshfree weak-form. Crack problems are simulated using this newly developed e-RPIM method. It has been demonstrated that the present e-RPIM is very accurate and stable, and it has very good potential to develop a practical simulation tool for fracture mechanics problems.

  17. A mathematical analysis of the selective enrichment of NECEEM-based non-SELEX.

    PubMed

    Yu, Xinliang; Yu, Yixiong

    2014-08-01

    Non-Systematic Evolution of Ligands by EXponential enrichment (SELEX)selection of aptamers, a novel technology for aptamer selection from libraries of random DNA (or RNA) sequences, involves repetitive steps of partitioning without polymerase chain reaction (PCR) amplification between them. This selection is based on non-equilibrium capillary electrophoresis of equilibrium mixtures (NECEEM) and has exceptionally high efficiency. In this paper, a mathematical analysis was carried out to predict the levels of enrichment of non-SELEX selection under different conditions such as different protein concentrations and different efficiencies of partitioning. Investigated results suggest that the magnitude of the bulk affinity (k d) being 10(4) or 10(5) μM for the initial pool has no obvious effect on selective enrichment and that the first, second, and third rounds of non-SELEX selection have different optimum protein concentration values [T f] that give maximum enrichment levels when [T f] ranges from 0.0005 to 0.5 μM. The significance of analyzing selective enrichment of NECEEM-based non-SELEX with the efficiency of partitioning target-bound ligands from free ligands has been demonstrated.

  18. The vacancy mechanism of high oxygen solubility and nucleation of stable oxygen-enriched clusters in Fe

    SciTech Connect

    Fu, Chong Long; Krcmar, Maja; Painter, Gayle S; Chen, Xingqiu

    2007-01-01

    First-principles studies have identified the atomic-level mechanism that underlies the unusually high solubility of O and nucleation of self-assembled stable O-enriched nanoclusters in defect-containing Fe. Oxygen is confined as an interstitial in Fe such that it shows an exceptionally high affinity for vacancies (an effect that is augmented by density expansion due to spin-polarization), leading to the formation of very stable O-vacancy (O:V) pairs. If vacancies pre-exist, the formation energy of an O:V pair essentially vanishes, allowing the O concentration to become as high as that of the vacancies. This vacancy mechanism based upon O-confinement enables the nucleation of O-enriched nanoclusters, that also contain solutes (Ti and Y) with high O-affinities. Fe-based alloys strengthened by these stable nanoclusters exhibit superior mechanical properties.

  19. A Method for Selective Enrichment and Analysis of Nitrotyrosine-Containing Peptides in Complex Proteome Samples

    SciTech Connect

    Zhang, Qibin; Qian, Weijun; Knyushko, Tanya V.; Clauss, Therese RW; Purvine, Samuel O.; Moore, Ronald J.; Sacksteder, Colette A.; Chin, Mark H.; Smith, Desmond J.; Camp, David G.; Bigelow, Diana J.; Smith, Richard D.

    2007-06-01

    Elevated levels of protein tyrosine nitration have been found in various neurodegenerative diseases and aging related pathologies; however, the lack of an efficient enrichment method has prevented the analysis of this important low level protein modification. We have developed an efficient method for specific enrichment of nitrotyrosine containing peptides that permits nitrotyrosine peptides and specific nitration sites to be unambiguously identified with LC-MS/MS. The method is based on the derivatization of nitrotyrosine into free sulfhydryl groups followed by high efficiency enrichment of sulfhydryl-containing peptides with thiopropyl sepharose beads. The derivatization process starts with acetylation with acetic anhydride to block all primary amines, followed by reduction of nitrotyrosine to aminotyrosine, then derivatization of aminotyrosine with N-Succinimidyl S-Acetylthioacetate (SATA), and finally deprotecting of S-acetyl on SATA to form free sulfhydryl groups. This method was evaluated using nitrotyrosine containing peptides, in-vitro nitrated human histone 1.2, and bovine serum albumin (BSA). 91% and 62% of the identified peptides from enriched histone and BSA samples were nitrotyrosine derivatized peptides, respectively, suggesting relative high specificity of the enrichment method. The application of this method to in-vitro nitrated mouse brain homogenate resulted in 35% of identified peptides containing nitrotyrosine (compared to only 5.9% observed from the global analysis of unenriched sample), and a total of 150 unique nitrated peptides covering 102 proteins were identified with a false discovery rate estimated at 3.3% from duplicate LC-MS/MS analyses of a single enriched sample.

  20. [Meta-analysis of stable carbon and nitrogen isotopic enrichment factors for aquatic animals].

    PubMed

    Guo, Liang; Sun, Cui-ping; Ren, Wei-zheng; Zhang, Jian; Tang, Jian-iun; Hu, Liana-liang; Chen, Xin

    2016-02-01

    Isotopic enrichment factor (Δ, the difference between the δ value of food and a consumer tissue) is an important parameter in using stable isotope analysis (SIA) to reconstruct diets, characterize trophic relationships, elucidate patterns of resource allocation, and construct food webs. Isotopic enrichment factor has been considered as a constancy value across a broad range of animals. However, recent studies showed that the isotopic enrichment factor differed among various types of animals although the magnitude of variation was not clear. Here, we conducted a meta-analysis to synthesize and compare Δ13C and Δ15N among four types of aquatic animals (teleosts, crustaceans, reptiles and molluscs). We searched for papers published before 2014 on Web of Science and CNKI using the key words "stable isotope or isotopic fractionation or fractionation factor or isotopic enrichment or trophic enrichment". Forty-two publications that contain 140 studies on Δ13C and 159 studies on Δ15N were obtained. We conducted three parallel meta-analyses by using three types of weights (the reciprocal of variance as weights, the sample size as weights, and equal weights). The results showed that no significant difference in Δ13C among different animal types (teleosts 1.0 per thousand, crustaceans 1.3 per thousand, reptiles 0.5 per thousand, and molluscs 1.5 per thousand), while Δ15N values were significantly different (teleosts 2.4 per thousand, crustaceans 3.6 per thousand, reptiles 1.0 per thousand and molluscs 2.5 per thousand). Our results suggested that the overall mean of Δ13C could be used as a general enrichment factor, but Δ15N should be chosen according to the type of aquatic animals in using SIA to analyze trophic relationships, patterns of resource allocation and food webs. PMID:27396136

  1. [Meta-analysis of stable carbon and nitrogen isotopic enrichment factors for aquatic animals].

    PubMed

    Guo, Liang; Sun, Cui-ping; Ren, Wei-zheng; Zhang, Jian; Tang, Jian-iun; Hu, Liana-liang; Chen, Xin

    2016-02-01

    Isotopic enrichment factor (Δ, the difference between the δ value of food and a consumer tissue) is an important parameter in using stable isotope analysis (SIA) to reconstruct diets, characterize trophic relationships, elucidate patterns of resource allocation, and construct food webs. Isotopic enrichment factor has been considered as a constancy value across a broad range of animals. However, recent studies showed that the isotopic enrichment factor differed among various types of animals although the magnitude of variation was not clear. Here, we conducted a meta-analysis to synthesize and compare Δ13C and Δ15N among four types of aquatic animals (teleosts, crustaceans, reptiles and molluscs). We searched for papers published before 2014 on Web of Science and CNKI using the key words "stable isotope or isotopic fractionation or fractionation factor or isotopic enrichment or trophic enrichment". Forty-two publications that contain 140 studies on Δ13C and 159 studies on Δ15N were obtained. We conducted three parallel meta-analyses by using three types of weights (the reciprocal of variance as weights, the sample size as weights, and equal weights). The results showed that no significant difference in Δ13C among different animal types (teleosts 1.0 per thousand, crustaceans 1.3 per thousand, reptiles 0.5 per thousand, and molluscs 1.5 per thousand), while Δ15N values were significantly different (teleosts 2.4 per thousand, crustaceans 3.6 per thousand, reptiles 1.0 per thousand and molluscs 2.5 per thousand). Our results suggested that the overall mean of Δ13C could be used as a general enrichment factor, but Δ15N should be chosen according to the type of aquatic animals in using SIA to analyze trophic relationships, patterns of resource allocation and food webs.

  2. Effect of rosemary polyphenols on human colon cancer cells: transcriptomic profiling and functional enrichment analysis.

    PubMed

    Valdés, Alberto; García-Cañas, Virginia; Rocamora-Reverte, Lourdes; Gómez-Martínez, Angeles; Ferragut, José Antonio; Cifuentes, Alejandro

    2013-01-01

    In this work, the effect of rosemary extracts rich on polyphenols obtained using pressurized fluids was investigated on the gene expression of human SW480 and HT29 colon cancer cells. The application of transcriptomic profiling and functional enrichment analysis was done via two computational approaches, Ingenuity Pathway Analysis and Gene Set Enrichment Analysis. These two approaches were used for functional enrichment analysis as a previous step for a reliable interpretation of the data obtained from microarray analysis. Reverse transcription quantitative-PCR was used to confirm relative changes in mRNA levels of selected genes from microarrays. The selection of genes was based on their expression change, adjusted p value, and known biological function. According to genome-wide transcriptomics analysis, rosemary polyphenols altered the expression of ~4 % of the genes covered by the Affymetrix Human Gene 1.0ST chip in both colon cancer cells. However, only ~18 % of the differentially expressed genes were common to both cell lines, indicating markedly different expression profiles in response to the treatment. Differences in induction of G2/M arrest observed by rosemary polyphenols in the two colon adenocarcinoma cell lines suggest that the extract may be differentially effective against tumors with specific mutational pattern. From our results, it is also concluded that rosemary polyphenols induced a low degree of apoptosis indicating that other multiple signaling pathways may contribute to colon cancer cell death.

  3. Network analysis identifies protein clusters of functional importance in juvenile idiopathic arthritis

    PubMed Central

    2014-01-01

    Introduction Our objective was to utilise network analysis to identify protein clusters of greatest potential functional relevance in the pathogenesis of oligoarticular and rheumatoid factor negative (RF-ve) polyarticular juvenile idiopathic arthritis (JIA). Methods JIA genetic association data were used to build an interactome network model in BioGRID 3.2.99. The top 10% of this protein:protein JIA Interactome was used to generate a minimal essential network (MEN). Reactome FI Cytoscape 2.83 Plugin and the Disease Association Protein-Protein Link Evaluator (Dapple) algorithm were used to assess the functionality of the biological pathways within the MEN and to statistically rank the proteins. JIA gene expression data were integrated with the MEN and clusters of functionally important proteins derived using MCODE. Results A JIA interactome of 2,479 proteins was built from 348 JIA associated genes. The MEN, representing the most functionally related components of the network, comprised of seven clusters, with distinct functional characteristics. Four gene expression datasets from peripheral blood mononuclear cells (PBMC), neutrophils and synovial fluid monocytes, were mapped onto the MEN and a list of genes enriched for functional significance identified. This analysis revealed the genes of greatest potential functional importance to be PTPN2 and STAT1 for oligoarticular JIA and KSR1 for RF-ve polyarticular JIA. Clusters of 23 and 14 related proteins were derived for oligoarticular and RF-ve polyarticular JIA respectively. Conclusions This first report of the application of network biology to JIA, integrating genetic association findings and gene expression data, has prioritised protein clusters for functional validation and identified new pathways for targeted pharmacological intervention. PMID:24886659

  4. Design of an Unattended Environmental Aerosol Sampling and Analysis System for Gaseous Centrifuge Enrichment Plants

    SciTech Connect

    Anheier, Norman C.; Munley, John T.; Alexander, M. L.

    2011-07-19

    The resources of the IAEA continue to be challenged by the rapid, worldwide expansion of nuclear energy production. Gaseous centrifuge enrichment plants (GCEPs) represent an especially formidable dilemma to the application of safeguard measures, as the size and enrichment capacity of GCEPs continue to escalate. During the early part of the 1990's, the IAEA began to lay the foundation to strengthen and make cost-effective its future safeguard regime. Measures under Part II of 'Programme 93+2' specifically sanctioned access to nuclear fuel production facilities and environmental sampling by IAEA inspectors. Today, the Additional Protocol grants inspection and environmental sample collection authority to IAEA inspectors at GCEPs during announced and low frequency unannounced (LFUA) inspections. During inspections, IAEA inspectors collect environmental swipe samples that are then shipped offsite to an analytical laboratory for enrichment assay. This approach has proven to be an effective deterrence to GCEP misuse, but this method has never achieved the timeliness of detection goals set forth by IAEA. Furthermore it is questionable whether the IAEA will have the resources to even maintain pace with the expansive production capacity of the modern GCEP, let alone improve the timeliness in reaching current safeguards conclusions. New safeguards propositions, outside of familiar mainstream safeguard measures, may therefore be required that counteract the changing landscape of nuclear energy fuel production. A new concept is proposed that offers rapid, cost effective GCEP misuse detection, without increasing LFUA inspection access or introducing intrusive access demands on GCEP operations. Our approach is based on continuous onsite aerosol collection and laser enrichment analysis. This approach mitigates many of the constraints imposed by the LFUA protocol, reduces the demand for onsite sample collection and offsite analysis, and overcomes current limitations associated with

  5. Bayesian Analysis of Two Stellar Populations in Galactic Globular Clusters III: Analysis of 30 Clusters

    NASA Astrophysics Data System (ADS)

    Wagner-Kaiser, R.; Stenning, D. C.; Sarajedini, A.; von Hippel, T.; van Dyk, D. A.; Robinson, E.; Stein, N.; Jefferys, W. H.

    2016-09-01

    We use Cycle 21 Hubble Space Telescope (HST) observations and HST archival ACS Treasury observations of 30 Galactic Globular Clusters to characterize two distinct stellar populations. A sophisticated Bayesian technique is employed to simultaneously sample the joint posterior distribution of age, distance, and extinction for each cluster, as well as unique helium values for two populations within each cluster and the relative proportion of those populations. We find the helium differences among the two populations in the clusters fall in the range of ˜0.04 to 0.11. Because adequate models varying in CNO are not presently available, we view these spreads as upper limits and present them with statistical rather than observational uncertainties. Evidence supports previous studies suggesting an increase in helium content concurrent with increasing mass of the cluster and also find that the proportion of the first population of stars increases with mass as well. Our results are examined in the context of proposed globular cluster formation scenarios. Additionally, we leverage our Bayesian technique to shed light on inconsistencies between the theoretical models and the observed data.

  6. Cluster Analysis of Clinical Data Identifies Fibromyalgia Subgroups

    PubMed Central

    Docampo, Elisa; Collado, Antonio; Escaramís, Geòrgia; Carbonell, Jordi; Rivera, Javier; Vidal, Javier; Alegre, José

    2013-01-01

    Introduction Fibromyalgia (FM) is mainly characterized by widespread pain and multiple accompanying symptoms, which hinder FM assessment and management. In order to reduce FM heterogeneity we classified clinical data into simplified dimensions that were used to define FM subgroups. Material and Methods 48 variables were evaluated in 1,446 Spanish FM cases fulfilling 1990 ACR FM criteria. A partitioning analysis was performed to find groups of variables similar to each other. Similarities between variables were identified and the variables were grouped into dimensions. This was performed in a subset of 559 patients, and cross-validated in the remaining 887 patients. For each sample and dimension, a composite index was obtained based on the weights of the variables included in the dimension. Finally, a clustering procedure was applied to the indexes, resulting in FM subgroups. Results Variables clustered into three independent dimensions: “symptomatology”, “comorbidities” and “clinical scales”. Only the two first dimensions were considered for the construction of FM subgroups. Resulting scores classified FM samples into three subgroups: low symptomatology and comorbidities (Cluster 1), high symptomatology and comorbidities (Cluster 2), and high symptomatology but low comorbidities (Cluster 3), showing differences in measures of disease severity. Conclusions We have identified three subgroups of FM samples in a large cohort of FM by clustering clinical data. Our analysis stresses the importance of family and personal history of FM comorbidities. Also, the resulting patient clusters could indicate different forms of the disease, relevant to future research, and might have an impact on clinical assessment. PMID:24098674

  7. Mokken Scale Analysis Using Hierarchical Clustering Procedures

    ERIC Educational Resources Information Center

    van Abswoude, Alexandra A. H.; Vermunt, Jeroen K.; Hemker, Bas T.; van der Ark, L. Andries

    2004-01-01

    Mokken scale analysis (MSA) can be used to assess and build unidimensional scales from an item pool that is sensitive to multiple dimensions. These scales satisfy a set of scaling conditions, one of which follows from the model of monotone homogeneity. An important drawback of the MSA program is that the sequential item selection and scale…

  8. Unsupervised feature relevance analysis applied to improve ECG heartbeat clustering.

    PubMed

    Rodríguez-Sotelo, J L; Peluffo-Ordoñez, D; Cuesta-Frau, D; Castellanos-Domínguez, G

    2012-10-01

    The computer-assisted analysis of biomedical records has become an essential tool in clinical settings. However, current devices provide a growing amount of data that often exceeds the processing capacity of normal computers. As this amount of information rises, new demands for more efficient data extracting methods appear. This paper addresses the task of data mining in physiological records using a feature selection scheme. An unsupervised method based on relevance analysis is described. This scheme uses a least-squares optimization of the input feature matrix in a single iteration. The output of the algorithm is a feature weighting vector. The performance of the method was assessed using a heartbeat clustering test on real ECG records. The quantitative cluster validity measures yielded a correctly classified heartbeat rate of 98.69% (specificity), 85.88% (sensitivity) and 95.04% (general clustering performance), which is even higher than the performance achieved by other similar ECG clustering studies. The number of features was reduced on average from 100 to 18, and the temporal cost was a 43% lower than in previous ECG clustering schemes. PMID:22672933

  9. Kinematic gait patterns in healthy runners: A hierarchical cluster analysis.

    PubMed

    Phinyomark, Angkoon; Osis, Sean; Hettinga, Blayne A; Ferber, Reed

    2015-11-01

    Previous studies have demonstrated distinct clusters of gait patterns in both healthy and pathological groups, suggesting that different movement strategies may be represented. However, these studies have used discrete time point variables and usually focused on only one specific joint and plane of motion. Therefore, the first purpose of this study was to determine if running gait patterns for healthy subjects could be classified into homogeneous subgroups using three-dimensional kinematic data from the ankle, knee, and hip joints. The second purpose was to identify differences in joint kinematics between these groups. The third purpose was to investigate the practical implications of clustering healthy subjects by comparing these kinematics with runners experiencing patellofemoral pain (PFP). A principal component analysis (PCA) was used to reduce the dimensionality of the entire gait waveform data and then a hierarchical cluster analysis (HCA) determined group sets of similar gait patterns and homogeneous clusters. The results show two distinct running gait patterns were found with the main between-group differences occurring in frontal and sagittal plane knee angles (P<0.001), independent of age, height, weight, and running speed. When these two groups were compared to PFP runners, one cluster exhibited greater while the other exhibited reduced peak knee abduction angles (P<0.05). The variability observed in running patterns across this sample could be the result of different gait strategies. These results suggest care must be taken when selecting samples of subjects in order to investigate the pathomechanics of injured runners.

  10. Unsupervised feature relevance analysis applied to improve ECG heartbeat clustering.

    PubMed

    Rodríguez-Sotelo, J L; Peluffo-Ordoñez, D; Cuesta-Frau, D; Castellanos-Domínguez, G

    2012-10-01

    The computer-assisted analysis of biomedical records has become an essential tool in clinical settings. However, current devices provide a growing amount of data that often exceeds the processing capacity of normal computers. As this amount of information rises, new demands for more efficient data extracting methods appear. This paper addresses the task of data mining in physiological records using a feature selection scheme. An unsupervised method based on relevance analysis is described. This scheme uses a least-squares optimization of the input feature matrix in a single iteration. The output of the algorithm is a feature weighting vector. The performance of the method was assessed using a heartbeat clustering test on real ECG records. The quantitative cluster validity measures yielded a correctly classified heartbeat rate of 98.69% (specificity), 85.88% (sensitivity) and 95.04% (general clustering performance), which is even higher than the performance achieved by other similar ECG clustering studies. The number of features was reduced on average from 100 to 18, and the temporal cost was a 43% lower than in previous ECG clustering schemes.

  11. Phage cluster relationships identified through single gene analysis

    PubMed Central

    2013-01-01

    Background Phylogenetic comparison of bacteriophages requires whole genome approaches such as dotplot analysis, genome pairwise maps, and gene content analysis. Currently mycobacteriophages, a highly studied phage group, are categorized into related clusters based on the comparative analysis of whole genome sequences. With the recent explosion of phage isolation, a simple method for phage cluster prediction would facilitate analysis of crude or complex samples without whole genome isolation and sequencing. The hypothesis of this study was that mycobacteriophage-cluster prediction is possible using comparison of a single, ubiquitous, semi-conserved gene. Tape Measure Protein (TMP) was selected to test the hypothesis because it is typically the longest gene in mycobacteriophage genomes and because regions within the TMP gene are conserved. Results A single gene, TMP, identified the known Mycobacteriophage clusters and subclusters using a Gepard dotplot comparison or a phylogenetic tree constructed from global alignment and maximum likelihood comparisons. Gepard analysis of 247 mycobacteriophage TMP sequences appropriately recovered 98.8% of the subcluster assignments that were made by whole-genome comparison. Subcluster-specific primers within TMP allow for PCR determination of the mycobacteriophage subcluster from DNA samples. Using the single-gene comparison approach for siphovirus coliphages, phage groupings by TMP comparison reflected relationships observed in a whole genome dotplot comparison and confirm the potential utility of this approach to another widely studied group of phages. Conclusions TMP sequence comparison and PCR results support the hypothesis that a single gene can be used for distinguishing phage cluster and subcluster assignments. TMP single-gene analysis can quickly and accurately aid in mycobacteriophage classification. PMID:23777341

  12. A Cluster Analysis of Personality Style in Adults with ADHD

    ERIC Educational Resources Information Center

    Robin, Arthur L.; Tzelepis, Angela; Bedway, Marquita

    2008-01-01

    Objective: The purpose of this study was to use hierarchical linear cluster analysis to examine the normative personality styles of adults with ADHD. Method: A total of 311 adults with ADHD completed the Millon Index of Personality Styles, which consists of 24 scales assessing motivating aims, cognitive modes, and interpersonal behaviors. Results:…

  13. Influence of Scholarships on STEM Teachers: Cluster Analysis and Characteristics

    ERIC Educational Resources Information Center

    Liou, Pey-Yan; Desjardins, Christopher David; Lawrenz, Frances

    2010-01-01

    Science, technology, engineering, and mathematics (STEM) teachers' perceptions about the influence of scholarship on their decision to teach and to teach in a high-needs school were examined using cluster analysis. Three hundred and four STEM scholars, who were currently teaching, and who received funding from 45 institutions located throughout…

  14. Language Learner Motivational Types: A Cluster Analysis Study

    ERIC Educational Resources Information Center

    Papi, Mostafa; Teimouri, Yasser

    2014-01-01

    The study aimed to identify different second language (L2) learner motivational types drawing on the framework of the L2 motivational self system. A total of 1,278 secondary school students learning English in Iran completed a questionnaire survey. Cluster analysis yielded five different groups based on the strength of different variables within…

  15. Key genes and pathways in thyroid cancer based on gene set enrichment analysis.

    PubMed

    He, Wenwu; Qi, Bin; Zhou, Qiuxi; Lu, Chuansen; Huang, Qi; Xian, Lei; Chen, Mingwu

    2013-09-01

    The incidence of thyroid cancer and its associated morbidity has shown the most rapid increase among all cancers since 1982, but the mechanisms involved in thyroid cancer, particularly significant key genes induced in thyroid cancer, remain undefined. In many studies, gene probes have been used to search for key genes involved in causing and facilitating thyroid cancer. As a result, many possible virulence genes and pathways have been identified. However, these studies lack a case contrast for selecting the most possible virulence genes and pathways, as well as conclusive results with which to clarify the mechanisms of cancer development. In the present study, we used gene set enrichment and meta-analysis to select key genes and pathways. Based on gene set enrichment, we identified 5 downregulated and 4 upregulated mixed pathways in 6 tissue datasets. Based on the meta-analysis, there were 17 common pathways in the tissue datasets. One pathway, the p53 signaling pathway, which includes 13 genes, was identified by both the gene set enrichment analysis and meta-analysis. Genes are important elements that form key pathways. These pathways can induce the development of thyroid cancer later in life. The key pathways and genes identified in the present study can be used in the next stage of research, which will involve gene elimination and other methods of experimentation.

  16. K-means cluster analysis and seismicity partitioning for Pakistan

    NASA Astrophysics Data System (ADS)

    Rehman, Khaista; Burton, Paul W.; Weatherill, Graeme A.

    2014-07-01

    Pakistan and the western Himalaya is a region of high seismic activity located at the triple junction between the Arabian, Eurasian and Indian plates. Four devastating earthquakes have resulted in significant numbers of fatalities in Pakistan and the surrounding region in the past century (Quetta, 1935; Makran, 1945; Pattan, 1974 and the recent 2005 Kashmir earthquake). It is therefore necessary to develop an understanding of the spatial distribution of seismicity and the potential seismogenic sources across the region. This forms an important basis for the calculation of seismic hazard; a crucial input in seismic design codes needed to begin to effectively mitigate the high earthquake risk in Pakistan. The development of seismogenic source zones for seismic hazard analysis is driven by both geological and seismotectonic inputs. Despite the many developments in seismic hazard in recent decades, the manner in which seismotectonic information feeds the definition of the seismic source can, in many parts of the world including Pakistan and the surrounding regions, remain a subjective process driven primarily by expert judgment. Whilst much research is ongoing to map and characterise active faults in Pakistan, knowledge of the seismogenic properties of the active faults is still incomplete in much of the region. Consequently, seismicity, both historical and instrumental, remains a primary guide to the seismogenic sources of Pakistan. This study utilises a cluster analysis approach for the purposes of identifying spatial differences in seismicity, which can be utilised to form a basis for delineating seismogenic source regions. An effort is made to examine seismicity partitioning for Pakistan with respect to earthquake database, seismic cluster analysis and seismic partitions in a seismic hazard context. A magnitude homogenous earthquake catalogue has been compiled using various available earthquake data. The earthquake catalogue covers a time span from 1930 to 2007 and

  17. Structural cluster analysis of chemical reactions in solution

    NASA Astrophysics Data System (ADS)

    Gallet, Grégoire A.; Pietrucci, Fabio

    2013-08-01

    We introduce a simple and general approach to the problem of clustering structures from atomic trajectories of chemical reactions in solution. By considering distance metrics which are invariant under permutation of identical atoms or molecules, we demonstrate that it is possible to automatically resolve as distinct structural clusters the configurations corresponding to reactants, products, and transition states, even in presence of atom-exchanges and of hundreds of solvent molecules. Our approach strongly simplifies the analysis of large trajectories and it opens the way to the construction of kinetic network models of activated processes in solution employing the available efficient schemes developed for proteins conformational ensembles.

  18. Cluster analysis of movement patterns in multiarticular actions: a tutorial.

    PubMed

    Rein, Robert; Button, Chris; Davids, Keith; Summers, Jeffery

    2010-04-01

    The present paper proposes a technical analysis method for extracting information about movement patterning in studies of motor control, based on a cluster analysis of movement kinematics. In a tutorial fashion, data from three different experiments are presented to exemplify and validate the technical method. When applied to three different basketball-shooting techniques, the method clearly distinguished between the different patterns. When applied to a cyclical wrist supination-pronation task, the cluster analysis provided the same results as an analysis using the conventional discrete relative phase measure. Finally, when analyzing throwing performance constrained by distance to target, the method grouped movement patterns together according to throwing distance. In conclusion, the proposed technical method provides a valuable tool to improve understanding of coordination and control in different movement models, including multiarticular actions.

  19. LA-ICP-MS analysis of isolated phosphatic grains indicates selective rare earth element enrichment during reworking and transport processes

    NASA Astrophysics Data System (ADS)

    Auer, Gerald; Reuter, Markus; Hauzenberger, Christoph A.; Piller, Werner E.

    2016-04-01

    water chemistry under certain well constrained circumstances of primary authigenesis. Are these conditions not met, REE patterns are more likely to reflect complex enrichment processes that likely already started to occur during reworking over geologically relatively short time frames. Similarities in the REE patterns of clearly detrital and biogenic phosphate further suggest that the often observed 'hat-shaped' pattern in biogenic phosphates can easily result from increased middle REE (Neodymium to Holmium) scavenging during taphonomic processes prior to final deposition. Finally, cluster analysis coupled with sedimentological considerations proved a valuable tool for the characterization of REE patterns of phosphates in terms of their formation conditions and depositional history, such as the distinction of phosphates formed in situ from reworked and transported phosphate grains.

  20. Constraints on the Parental Melts of Enriched Shergottites from Image Analysis and High Pressure Experiments

    NASA Technical Reports Server (NTRS)

    Collinet, M.; Medard, E.; Devouard, B.; Peslier, A.

    2012-01-01

    Martian basalts can be classified in at least two geochemically different families: enriched and depleted shergottites. Enriched shergottites are characterized by higher incompatible element concentrations and initial Sr-87/Sr-86 and lower initial Nd-143/Nd-144 and Hf-176/Hf-177 than depleted shergottites [e.g. 1, 2]. It is now generally admitted that shergottites result from the melting of at least two distinct mantle reservoirs [e.g. 2, 3]. Some of the olivine-phyric shergottites (either depleted or enriched), the most magnesian Martian basalts, could represent primitive melts, which are of considerable interest to constrain mantle sources. Two depleted olivine-phyric shergottites, Yamato (Y) 980459 and Northwest Africa (NWA) 5789, are in equilibrium with their most magnesian olivine (Fig. 1) and their bulk rock compositions are inferred to represent primitive melts [4, 5]. Larkman Nunatak (LAR) 06319 [3, 6, 7] and NWA 1068 [8], the most magnesian enriched basalts, have bulk Mg# that are too high to be in equilibrium with their olivine megacryst cores. Parental melt compositions have been estimated by subtracting the most magnesian olivine from the bulk rock composition, assuming that olivine megacrysts have partially accumulated [3, 9]. However, because this technique does not account for the actual petrography of these meteorites, we used image analysis to study these rocks history, reconstruct their parent magma and understand the nature of olivine megacrysts.

  1. Outcome-Driven Cluster Analysis with Application to Microarray Data.

    PubMed

    Hsu, Jessie J; Finkelstein, Dianne M; Schoenfeld, David A

    2015-01-01

    One goal of cluster analysis is to sort characteristics into groups (clusters) so that those in the same group are more highly correlated to each other than they are to those in other groups. An example is the search for groups of genes whose expression of RNA is correlated in a population of patients. These genes would be of greater interest if their common level of RNA expression were additionally predictive of the clinical outcome. This issue arose in the context of a study of trauma patients on whom RNA samples were available. The question of interest was whether there were groups of genes that were behaving similarly, and whether each gene in the cluster would have a similar effect on who would recover. For this, we develop an algorithm to simultaneously assign characteristics (genes) into groups of highly correlated genes that have the same effect on the outcome (recovery). We propose a random effects model where the genes within each group (cluster) equal the sum of a random effect, specific to the observation and cluster, and an independent error term. The outcome variable is a linear combination of the random effects of each cluster. To fit the model, we implement a Markov chain Monte Carlo algorithm based on the likelihood of the observed data. We evaluate the effect of including outcome in the model through simulation studies and describe a strategy for prediction. These methods are applied to trauma data from the Inflammation and Host Response to Injury research program, revealing a clustering of the genes that are informed by the recovery outcome. PMID:26562156

  2. Outcome-Driven Cluster Analysis with Application to Microarray Data

    PubMed Central

    Hsu, Jessie J.; Finkelstein, Dianne M.; Schoenfeld, David A.

    2015-01-01

    One goal of cluster analysis is to sort characteristics into groups (clusters) so that those in the same group are more highly correlated to each other than they are to those in other groups. An example is the search for groups of genes whose expression of RNA is correlated in a population of patients. These genes would be of greater interest if their common level of RNA expression were additionally predictive of the clinical outcome. This issue arose in the context of a study of trauma patients on whom RNA samples were available. The question of interest was whether there were groups of genes that were behaving similarly, and whether each gene in the cluster would have a similar effect on who would recover. For this, we develop an algorithm to simultaneously assign characteristics (genes) into groups of highly correlated genes that have the same effect on the outcome (recovery). We propose a random effects model where the genes within each group (cluster) equal the sum of a random effect, specific to the observation and cluster, and an independent error term. The outcome variable is a linear combination of the random effects of each cluster. To fit the model, we implement a Markov chain Monte Carlo algorithm based on the likelihood of the observed data. We evaluate the effect of including outcome in the model through simulation studies and describe a strategy for prediction. These methods are applied to trauma data from the Inflammation and Host Response to Injury research program, revealing a clustering of the genes that are informed by the recovery outcome. PMID:26562156

  3. Cluster coarsening during polymer collapse: Finite-size scaling analysis

    NASA Astrophysics Data System (ADS)

    Majumder, Suman; Janke, Wolfhard

    2015-06-01

    We study the kinetics of the collapse of a single flexible polymer when it is quenched from a good solvent to a poor solvent. Results obtained from Monte Carlo simulations show that the collapse occurs through a sequence of events with the formation, growth and subsequent coalescence of clusters of monomers to a single compact globule. Particular emphasis is given in this work to the cluster growth during the collapse, analyzed via the application of finite-size scaling techniques. The growth exponent obtained in our analysis is suggestive of the universal Lifshitz-Slyozov mechanism of cluster growth. The methods used in this work could be of more general validity and applicable to other phenomena such as protein folding.

  4. GeneCodis3: a non-redundant and modular enrichment analysis tool for functional genomics.

    PubMed

    Tabas-Madrid, Daniel; Nogales-Cadenas, Ruben; Pascual-Montano, Alberto

    2012-07-01

    Since its first release in 2007, GeneCodis has become a valuable tool to functionally interpret results from experimental techniques in genomics. This web-based application integrates different sources of information to finding groups of genes with similar biological meaning. This process, known as enrichment analysis, is essential in the interpretation of high-throughput experiments. The frequent feedbacks and the natural evolution of genomics and bioinformatics have allowed the growth of the tool and the development of this third release. In this version, a special effort has been made to remove noisy and redundant output from the enrichment results with the inclusion of a recently reported algorithm that summarizes significantly enriched terms and generates functionally coherent modules of genes and terms. A new comparative analysis has been added to allow the differential analysis of gene sets. To expand the scope of the application, new sources of biological information have been included, such as genetic diseases, drugs-genes interactions and Pubmed information among others. Finally, the graphic section has been renewed with the inclusion of new interactive graphics and filtering options. The application is freely available at http://genecodis.cnb.csic.es.

  5. A novel titanium dioxide-polydimethylsiloxane plate for phosphopeptide enrichment and mass spectrometry analysis.

    PubMed

    Chen, Chao-Jung; Lai, Chien-Chen; Tseng, Mei-Chun; Liu, Yu-Ching; Liu, Yu-Huei; Chiou, Liang-Wei; Tsai, Fuu-Jen

    2014-02-17

    The phosphorylation of proteins is a major post-translational modification that is required for the regulation of many cellular processes and activities. Mass spectrometry signals of low-abundance phosphorylated peptides are commonly suppressed by the presence of abundant non-phosphorylated peptides. Therefore, one of the major challenges in the detection of low-abundance phosphopeptides is their enrichment from complex peptide mixtures. Titanium dioxide (TiO2) has been proven to be a highly efficient approach for phosphopeptide enrichment and is widely applied. In this study, a novel TiO2 plate was developed by coating TiO2 particles onto polydimethylsiloxane (PDMS)-coated MALDI plates, glass, or plastic substrates. The TiO2-PDMS plate (TP plate) could be used for on-target MALDI-TOF analysis, or as a purification plate on which phosphopeptides were eluted out and subjected to MALDI-TOF or nanoLC-MS/MS analysis. The detection limit of the TP plate was ∼10-folds lower than that of a TiO2-packed tip approach. The capacity of the ∼2.5 mm diameter TiO2 spots was estimated to be ∼10 μg of β-casein. Following TiO2 plate enrichment of SCC4 cell lysate digests and nanoLC-MS/MS analysis, ∼82% of the detected proteins were phosphorylated, illustrating the sensitivity and effectiveness of the TP plate for phosphoproteomic study.

  6. Network expansion and pathway enrichment analysis towards biologically significant findings from microarrays.

    PubMed

    Wu, Xiaogang; Huang, Hui; Wei, Tao; Pandey, Ragini; Reinhard, Christoph; Li, Shuyu D; Chen, Jake Y

    2012-01-01

    In many cases, crucial genes show relatively slight changes between groups of samples (e.g. normal vs. disease), and many genes selected from microarray differential analysis by measuring the expression level statistically are also poorly annotated and lack of biological significance. In this paper, we present an innovative approach - network expansion and pathway enrichment analysis (NEPEA) for integrative microarray analysis. We assume that organized knowledge will help microarray data analysis in significant ways, and the organized knowledge could be represented as molecular interaction networks or biological pathways. Based on this hypothesis, we develop the NEPEA framework based on network expansion from the human annotated and predicted protein interaction (HAPPI) database, and pathway enrichment from the human pathway database (HPD). We use a recently-published microarray dataset (GSE24215) related to insulin resistance and type 2 diabetes (T2D) as case study, since this study provided a thorough experimental validation for both genes and pathways identified computationally from classical microarray analysis and pathway analysis. We perform our NEPEA analysis for this dataset based on the results from the classical microarray analysis to identify biologically significant genes and pathways. Our findings are not only consistent with the original findings mostly, but also obtained more supports from other literatures.

  7. REGIONAL-SCALE WIND FIELD CLASSIFICATION EMPLOYING CLUSTER ANALYSIS

    SciTech Connect

    Glascoe, L G; Glaser, R E; Chin, H S; Loosmore, G A

    2004-06-17

    The classification of time-varying multivariate regional-scale wind fields at a specific location can assist event planning as well as consequence and risk analysis. Further, wind field classification involves data transformation and inference techniques that effectively characterize stochastic wind field variation. Such a classification scheme is potentially useful for addressing overall atmospheric transport uncertainty and meteorological parameter sensitivity issues. Different methods to classify wind fields over a location include the principal component analysis of wind data (e.g., Hardy and Walton, 1978) and the use of cluster analysis for wind data (e.g., Green et al., 1992; Kaufmann and Weber, 1996). The goal of this study is to use a clustering method to classify the winds of a gridded data set, i.e, from meteorological simulations generated by a forecast model.

  8. Full text clustering and relationship network analysis of biomedical publications.

    PubMed

    Guan, Renchu; Yang, Chen; Marchese, Maurizio; Liang, Yanchun; Shi, Xiaohu

    2014-01-01

    Rapid developments in the biomedical sciences have increased the demand for automatic clustering of biomedical publications. In contrast to current approaches to text clustering, which focus exclusively on the contents of abstracts, a novel method is proposed for clustering and analysis of complete biomedical article texts. To reduce dimensionality, Cosine Coefficient is used on a sub-space of only two vectors, instead of computing the Euclidean distance within the space of all vectors. Then a strategy and algorithm is introduced for Semi-supervised Affinity Propagation (SSAP) to improve analysis efficiency, using biomedical journal names as an evaluation background. Experimental results show that by avoiding high-dimensional sparse matrix computations, SSAP outperforms conventional k-means methods and improves upon the standard Affinity Propagation algorithm. In constructing a directed relationship network and distribution matrix for the clustering results, it can be noted that overlaps in scope and interests among BioMed publications can be easily identified, providing a valuable analytical tool for editors, authors and readers.

  9. The Productivity Analysis of Chennai Automotive Industry Cluster

    NASA Astrophysics Data System (ADS)

    Bhaskaran, E.

    2014-07-01

    Chennai, also called the Detroit of India, is India's second fastest growing auto market and exports auto components and vehicles to US, Germany, Japan and Brazil. For inclusive growth and sustainable development, 250 auto component industries in Ambattur, Thirumalisai and Thirumudivakkam Industrial Estates located in Chennai have adopted the Cluster Development Approach called Automotive Component Cluster. The objective is to study the Value Chain, Correlation and Data Envelopment Analysis by determining technical efficiency, peer weights, input and output slacks of 100 auto component industries in three estates. The methodology adopted is using Data Envelopment Analysis of Output Oriented Banker Charnes Cooper model by taking net worth, fixed assets, employment as inputs and gross output as outputs. The non-zero represents the weights for efficient clusters. The higher slack obtained reveals the excess net worth, fixed assets, employment and shortage in gross output. To conclude, the variables are highly correlated and the inefficient industries should increase their gross output or decrease the fixed assets or employment. Moreover for sustainable development, the cluster should strengthen infrastructure, technology, procurement, production and marketing interrelationships to decrease costs and to increase productivity and efficiency to compete in the indigenous and export market.

  10. Full text clustering and relationship network analysis of biomedical publications.

    PubMed

    Guan, Renchu; Yang, Chen; Marchese, Maurizio; Liang, Yanchun; Shi, Xiaohu

    2014-01-01

    Rapid developments in the biomedical sciences have increased the demand for automatic clustering of biomedical publications. In contrast to current approaches to text clustering, which focus exclusively on the contents of abstracts, a novel method is proposed for clustering and analysis of complete biomedical article texts. To reduce dimensionality, Cosine Coefficient is used on a sub-space of only two vectors, instead of computing the Euclidean distance within the space of all vectors. Then a strategy and algorithm is introduced for Semi-supervised Affinity Propagation (SSAP) to improve analysis efficiency, using biomedical journal names as an evaluation background. Experimental results show that by avoiding high-dimensional sparse matrix computations, SSAP outperforms conventional k-means methods and improves upon the standard Affinity Propagation algorithm. In constructing a directed relationship network and distribution matrix for the clustering results, it can be noted that overlaps in scope and interests among BioMed publications can be easily identified, providing a valuable analytical tool for editors, authors and readers. PMID:25250864

  11. Transcriptional analysis of exopolysaccharides biosynthesis gene clusters in Lactobacillus plantarum.

    PubMed

    Vastano, Valeria; Perrone, Filomena; Marasco, Rosangela; Sacco, Margherita; Muscariello, Lidia

    2016-04-01

    Exopolysaccharides (EPS) from lactic acid bacteria contribute to specific rheology and texture of fermented milk products and find applications also in non-dairy foods and in therapeutics. Recently, four clusters of genes (cps) associated with surface polysaccharide production have been identified in Lactobacillus plantarum WCFS1, a probiotic and food-associated lactobacillus. These clusters are involved in cell surface architecture and probably in release and/or exposure of immunomodulating bacterial molecules. Here we show a transcriptional analysis of these clusters. Indeed, RT-PCR experiments revealed that the cps loci are organized in five operons. Moreover, by reverse transcription-qPCR analysis performed on L. plantarum WCFS1 (wild type) and WCFS1-2 (ΔccpA), we demonstrated that expression of three cps clusters is under the control of the global regulator CcpA. These results, together with the identification of putative CcpA target sequences (catabolite responsive element CRE) in the regulatory region of four out of five transcriptional units, strongly suggest for the first time a role of the master regulator CcpA in EPS gene transcription among lactobacilli.

  12. The Quantitative Analysis of Chennai Automotive Industry Cluster

    NASA Astrophysics Data System (ADS)

    Bhaskaran, Ethirajan

    2016-07-01

    Chennai, also called as Detroit of India due to presence of Automotive Industry producing over 40 % of the India's vehicle and components. During 2001-2002, the Automotive Component Industries (ACI) in Ambattur, Thirumalizai and Thirumudivakkam Industrial Estate, Chennai has faced problems on infrastructure, technology, procurement, production and marketing. The objective is to study the Quantitative Performance of Chennai Automotive Industry Cluster before (2001-2002) and after the CDA (2008-2009). The methodology adopted is collection of primary data from 100 ACI using quantitative questionnaire and analyzing using Correlation Analysis (CA), Regression Analysis (RA), Friedman Test (FMT), and Kruskall Wallis Test (KWT).The CA computed for the different set of variables reveals that there is high degree of relationship between the variables studied. The RA models constructed establish the strong relationship between the dependent variable and a host of independent variables. The models proposed here reveal the approximate relationship in a closer form. KWT proves, there is no significant difference between three locations clusters with respect to: Net Profit, Production Cost, Marketing Costs, Procurement Costs and Gross Output. This supports that each location has contributed for development of automobile component cluster uniformly. The FMT proves, there is no significant difference between industrial units in respect of cost like Production, Infrastructure, Technology, Marketing and Net Profit. To conclude, the Automotive Industries have fully utilized the Physical Infrastructure and Centralised Facilities by adopting CDA and now exporting their products to North America, South America, Europe, Australia, Africa and Asia. The value chain analysis models have been implemented in all the cluster units. This Cluster Development Approach (CDA) model can be implemented in industries of under developed and developing countries for cost reduction and productivity

  13. Bacterial community analysis of cypermethrin enrichment cultures and bioremediation of cypermethrin contaminated soils.

    PubMed

    Akbar, Shamsa; Sultan, Sikander; Kertesz, Michael

    2015-07-01

    Cypermethrin is widely used for insect control; however, its toxicity toward aquatic life requires its complete removal from contaminated areas where the natural degradation ability of microbes can be utilized. Agricultural soil with extensive history of CM application was used to prepare enrichment cultures using cypermethrin as sole carbon source for isolation of cypermethrin degrading bacteria and bacterial community analysis using PCR-DGGE of 16 S rRNA gene. DGGE analysis revealed that dominant members of CM enrichment culture were associated with α-proteobacteria followed by γ-proteobacteria, Firmicutes, and Actinobacteria. Three potential CM-degrading isolates identified as Ochrobactrum anthropi JCm1, Bacillus megaterium JCm2, and Rhodococcus sp. JCm5 degraded 86-100% of CM (100 mg L(-1) ) within 10 days. These isolates were also able to degrade other pyrethroids, carbofuran, and cypermethrin degradation products. Enzyme activity assays revealed that enzymes involved in CM-degradation were inducible and showed activity when strains were grown on cypermethrin. Degradation kinetics of cypermethrin (200 mg kg(-1)) in soils inoculated with isolates JCm1, JCm2, and JCm5 suggested time-dependent disappearance of cypermethrin with rate constants of 0.0516, 0.0425, and 0.0807 d(-1), respectively, following first order rate kinetics. The isolated bacterial strains were among dominant genera selected under CM enriched conditions and represent valuable candidates for in situ bioremediation of contaminated soils and waters.

  14. DChIPRep, an R/Bioconductor package for differential enrichment analysis in chromatin studies

    PubMed Central

    Chabbert, Christophe D.; Steinmetz, Lars M.

    2016-01-01

    The genome-wide study of epigenetic states requires the integrative analysis of histone modification ChIP-seq data. Here, we introduce an easy-to-use analytic framework to compare profiles of enrichment in histone modifications around classes of genomic elements, e.g. transcription start sites (TSS). Our framework is available via the user-friendly R/Bioconductor package DChIPRep. DChIPRep uses biological replicate information as well as chromatin Input data to allow for a rigorous assessment of differential enrichment. DChIPRep is available for download through the Bioconductor project at http://bioconductor.org/packages/DChIPRep. Contact. DChIPRep@gmail.com. PMID:27168989

  15. Applying cluster analysis to physics education research data

    NASA Astrophysics Data System (ADS)

    Springuel, R. Padraic

    One major thrust of Physics Education Research (PER) is the identification of student ideas about specific physics concepts, both correct ideas and those that differ from the expert consensus. Typically the research process of eliciting the spectrum of student ideas involves the administration of specially designed questions to students. One major analysis task in PER is the sorting of these student responses into thematically coherent groups. This process is one which has previously been done by eye in PER. This thesis explores the possibility of using cluster analysis to perform the task in a more rigorous and less time-intensive fashion while making fewer assumptions about what the students are doing. Since this technique has not previously been used in PER, a summary of the various kinds of cluster analysis is included as well as a discussion of which might be appropriate for the task of sorting student responses into groups. Two example data sets (one based on the Force and Motion Conceptual Evaluation (DICE) the other looking at acceleration in two-dimensions (A2D) are examined in depth to demonstrate how cluster analysis can be applied to PER data and the various considerations which must be taken into account when doing so. In both cases, the techniques described in this thesis found 5 groups which contained about 90% of the students in the data set. The results of this application are compared to previous research on the topics covered by the two examples to demonstrate that cluster analysis can effectively uncover the same patterns in student responses that have already been identified.

  16. Multilayer interparticle linking hybrid MOF-199 for noninvasive enrichment and analysis of plant hormone ethylene.

    PubMed

    Zhang, Zhuomin; Huang, Yichun; Ding, Weiwei; Li, Gongke

    2014-04-01

    Ethylene, an important plant hormone, is of utmost importance during many developmental processes of plants. However, the efficient enrichment and analysis of trace ethylene still remains a challenge. A simple and mild multilayer interparticle linking strategy was proposed to fabricate a novel hybrid MOF-199 enrichment coating. Strong chemical interparticle linkages throughout the coating improved the durability and reproducibility of hybrid MOF-199 coating dramatically. This coating performed a significant extraction superiority of ethylene over commonly used commercial coatings, attributed to the multiple interactions including "molecular sieving effect", hydrogen bonding, open metal site interaction, and π-π affinity. The hybridization of multiwalled carbon nanotubes (MWCNTs) with MOF-199 further improved the enrichment capability and also acted as a hydrophobic "shield" to prevent the open metal sites of MOF-199 from being occupied by water molecules, which effectively improved the moisture-resistant property of MOF-199/CNTs coating. Finally, this novel enrichment method was successfully applied for the noninvasive analysis of trace ethylene, methanol, and ethanol from fruit samples with relatively high humidity. The low detection limit was 0.016 μg/L for ethylene. It was satisfactory that trace ethylene could be actually detected from fruit samples by this noninvasive method. Good recoveries of spiked grape, wampee, blueberry, and durian husk samples were obtained in the range of 90.0-114%, 79.4-88.6%, 78.5-86.8%, and 85.2-105% with the corresponding relative standard deviations of 4.8-9.8%, 6.9-8.9%, 3.8-8.1%, and 9.3-10.5% (n = 3), respectively.

  17. Applications of cluster analysis to the creation of perfectionism profiles: a comparison of two clustering approaches

    PubMed Central

    Bolin, Jocelyn H.; Edwards, Julianne M.; Finch, W. Holmes; Cassady, Jerrell C.

    2014-01-01

    Although traditional clustering methods (e.g., K-means) have been shown to be useful in the social sciences it is often difficult for such methods to handle situations where clusters in the population overlap or are ambiguous. Fuzzy clustering, a method already recognized in many disciplines, provides a more flexible alternative to these traditional clustering methods. Fuzzy clustering differs from other traditional clustering methods in that it allows for a case to belong to multiple clusters simultaneously. Unfortunately, fuzzy clustering techniques remain relatively unused in the social and behavioral sciences. The purpose of this paper is to introduce fuzzy clustering to these audiences who are currently relatively unfamiliar with the technique. In order to demonstrate the advantages associated with this method, cluster solutions of a common perfectionism measure were created using both fuzzy clustering and K-means clustering, and the results compared. Results of these analyses reveal that different cluster solutions are found by the two methods, and the similarity between the different clustering solutions depends on the amount of cluster overlap allowed for in fuzzy clustering. PMID:24795683

  18. Volatile trace elements in and cluster analysis of Martian meteorites

    NASA Astrophysics Data System (ADS)

    Wang, Ming-Sheng; Mokos, Jennifer A.; Lipschutz, Michael E.

    1998-07-01

    We report data for 15 mainly volatile trace elements (Ag, Au, Bi, Cd, Co, Cs, Ga, In, Rb, Sb, Se, Te, Tl, U, Zn) by radiochemical neutron activation analysis (RNAA) in whole-rock samples of 5 martian meteorites which, with 7 others studied earlier, completes the 12-member martian meteorite suite. Nearly all of these elements exhibit highly variable compositional continua and are richer in the martian suite compared with other basaltic meteorites. From cluster analysis, we find that the clustering of subtypes based on these elements is virtually identical to that based on contents of major refractory elements and mineralogic/petrographic characteristics, implying that each source region on Mars was closed to volatile transport. Martian meteorite data can be used to infer volatile element contents in that planet.

  19. Segment clustering methodology for unsupervised Holter recordings analysis

    NASA Astrophysics Data System (ADS)

    Rodríguez-Sotelo, Jose Luis; Peluffo-Ordoñez, Diego; Castellanos Dominguez, German

    2015-01-01

    Cardiac arrhythmia analysis on Holter recordings is an important issue in clinical settings, however such issue implicitly involves attending other problems related to the large amount of unlabelled data which means a high computational cost. In this work an unsupervised methodology based in a segment framework is presented, which consists of dividing the raw data into a balanced number of segments in order to identify fiducial points, characterize and cluster the heartbeats in each segment separately. The resulting clusters are merged or split according to an assumed criterion of homogeneity. This framework compensates the high computational cost employed in Holter analysis, being possible its implementation for further real time applications. The performance of the method is measure over the records from the MIT/BIH arrhythmia database and achieves high values of sensibility and specificity, taking advantage of database labels, for a broad kind of heartbeats types recommended by the AAMI.

  20. Finite element adaptive mesh analysis using a cluster of workstations

    NASA Astrophysics Data System (ADS)

    Wang, K. P.; Bruch, J. C., Jr.

    1998-01-01

    Parallel computation on clusters of workstations is becoming one of the major trends in the study of parallel computations, because of their high computing speed, cost effectiveness and scalability. This paper presents studies of using a cluster of workstations for the finite element adaptive mesh analysis of a free surface seepage problem. A parallel algorithm proven to be simple to implement and efficient is used to perform the analysis. A network of workstations is used as the hardware of a parallel system. Two parallel software packages, P4 and PVM (parallel virtual machine), are used to handle communications among networked workstations. Computational issues to be discussed are domain decomposition, load balancing, and communication time.

  1. A New Analysis of s-process Enrichments in Planetary Nebulae

    NASA Astrophysics Data System (ADS)

    Sterling, Nicholas C.; Porter, Ryan; Dinerstein, Harriet L.

    2015-01-01

    We present a new analysis of selenium and krypton enrichments in planetary nebulae (PNe), using recently determined atomic data for these elements. Se and Kr are the two most widely-detected neutron-capture elements in PNe, and can be enriched by s-process nucleosynthesis in PN progenitor stars. With the photoionization code Cloudy (Ferland et al. 2013, RMxA&A, 49, 1), we computed grids of models that span the range of physical conditions in most PNe to investigate the ionization balance of Se and Kr. The new atomic data were tested by modeling 15 PNe that exhibit emission from multiple Kr ions. We found systematic discrepancies between the modeled and observed Kr lines, which could not be satisfactorily explained by observational uncertainties or approximations in the models. The observed ionization balance is reproduced more accurately by empirically adjusting the photoionization cross sections of Kr+—Kr3+ within their cited uncertainties, and the dielectronic recombination rate coefficients by slightly larger amounts. We present new analytical ionization correction factors for Se and Kr, based on correlations between the ionic fractions of detected Se and Kr ions and those of routinely observed O, Ar, and S ions. The correction factors are applied to the K band survey of Sterling & Dinerstein (2008, ApJS, 174, 158) to derive improved Se and Kr abundances in 120 PNe. The revised abundances are 0.1—0.3 dex lower than the previous values in most PNe, reducing the estimated fraction of enriched objects from 52% to 37%. However, this figure depends on the assumed initial abundances of Se and Kr in the progenitor stars, which may be subsolar in some cases and may differ for objects belonging to different stellar populations. We find that the primary conclusions of Sterling & Dinerstein still hold: Kr is more strongly enriched than Se in PNe, in accordance with nucleosynthetic predictions; PNe with more massive progenitors show little if any s-process enrichment

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

    PubMed

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

    2015-01-01

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

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

    PubMed Central

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

    2015-01-01

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

  4. Coupled two-way clustering analysis of gene microarray data

    NASA Astrophysics Data System (ADS)

    Getz, Gad; Levine, Erel; Domany, Eytan

    2000-10-01

    We present a coupled two-way clustering approach to gene microarray data analysis. The main idea is to identify subsets of the genes and samples, such that when one of these is used to cluster the other, stable and significant partitions emerge. The search for such subsets is a computationally complex task. We present an algorithm, based on iterative clustering, that performs such a search. This analysis is especially suitable for gene microarray data, where the contributions of a variety of biological mechanisms to the gene expression levels are entangled in a large body of experimental data. The method was applied to two gene microarray data sets, on colon cancer and leukemia. By identifying relevant subsets of the data and focusing on them we were able to discover partitions and correlations that were masked and hidden when the full dataset was used in the analysis. Some of these partitions have clear biological interpretation; others can serve to identify possible directions for future research.

  5. Psychosocial Costs of Racism to Whites: Exploring Patterns through Cluster Analysis

    ERIC Educational Resources Information Center

    Spanierman, Lisa B.; Poteat, V. Paul; Beer, Amanda M.; Armstrong, Patrick Ian

    2006-01-01

    Participants (230 White college students) completed the Psychosocial Costs of Racism to Whites (PCRW) Scale. Using cluster analysis, we identified 5 distinct cluster groups on the basis of PCRW subscale scores: the unempathic and unaware cluster contained the lowest empathy scores; the insensitive and afraid cluster consisted of low empathy and…

  6. Enrichment of Extracellular Matrix Proteins from Tissues and Digestion into Peptides for Mass Spectrometry Analysis.

    PubMed

    Naba, Alexandra; Clauser, Karl R; Hynes, Richard O

    2015-07-23

    The extracellular matrix (ECM) is a complex meshwork of cross-linked proteins that provides biophysical and biochemical cues that are major regulators of cell proliferation, survival, migration, etc. The ECM plays important roles in development and in diverse pathologies including cardio-vascular and musculo-skeletal diseases, fibrosis, and cancer. Thus, characterizing the composition of ECMs of normal and diseased tissues could lead to the identification of novel prognostic and diagnostic biomarkers and potential novel therapeutic targets. However, the very nature of ECM proteins (large in size, cross-linked and covalently bound, heavily glycosylated) has rendered biochemical analyses of ECMs challenging. To overcome this challenge, we developed a method to enrich ECMs from fresh or frozen tissues and tumors that takes advantage of the insolubility of ECM proteins. We describe here in detail the decellularization procedure that consists of sequential incubations in buffers of different pH and salt and detergent concentrations and that results in 1) the extraction of intracellular (cytosolic, nuclear, membrane and cytoskeletal) proteins and 2) the enrichment of ECM proteins. We then describe how to deglycosylate and digest ECM-enriched protein preparations into peptides for subsequent analysis by mass spectrometry.

  7. Enrichment Analysis Identifies Functional MicroRNA-Disease Associations in Humans.

    PubMed

    Yuan, Dandan; Cui, Xiaomeng; Wang, Yang; Zhao, Yilei; Li, Huiying; Hu, Suangjiu; Chu, Xiaodan; Li, Yan; Li, Qiang; Liu, Qian; Zhu, Wenliang

    2015-01-01

    Substantial evidence has shown that microRNAs (miRNAs) may be causally linked to the occurrence and progression of human diseases. Herein, we conducted an enrichment analysis to identify potential functional miRNA-disease associations (MDAs) in humans by integrating currently known biological data: miRNA-target interactions (MTIs), protein-protein interactions, and gene-disease associations. Two contributing factors to functional miRNA-disease associations were quantitatively considered: the direct effects of miRNA that target disease-related genes, and indirect effects triggered by protein-protein interactions. Ninety-nine miRNAs were scanned for possible functional association with 2223 MeSH-defined human diseases. Each miRNA was experimentally validated to target ≥ 10 mRNA genes. Putative MDAs were identified when at least one MTI was confidently validated for a disease. Overall, 19648 putative MDAs were found, of which 10.0% was experimentally validated. Further results suggest that filtering for miRNAs that target a greater number of disease-related genes (n ≥ 8) can significantly enrich for true MDAs from the set of putative associations (enrichment rate = 60.7%, adjusted hypergeometric p = 2.41×10-91). Considering the indirect effects of miRNAs further elevated the enrichment rate to 72.6%. By using this method, a novel MDA between miR-24 and ovarian cancer was found. Compared with scramble miRNA overexpression of miR-24 was validated to remarkably induce ovarian cancer cells apoptosis. Our study provides novel insight into factors contributing to functional MDAs by integrating large quantities of previously generated biological data, and establishes a feasible method to identify plausible associations with high confidence. PMID:26296081

  8. ESEA: Discovering the Dysregulated Pathways based on Edge Set Enrichment Analysis

    PubMed Central

    Han, Junwei; Shi, Xinrui; Zhang, Yunpeng; Xu, Yanjun; Jiang, Ying; Zhang, Chunlong; Feng, Li; Yang, Haixiu; Shang, Desi; Sun, Zeguo; Su, Fei; Li, Chunquan; Li, Xia

    2015-01-01

    Pathway analyses are playing an increasingly important role in understanding biological mechanism, cellular function and disease states. Current pathway-identification methods generally focus on only the changes of gene expression levels; however, the biological relationships among genes are also the fundamental components of pathways, and the dysregulated relationships may also alter the pathway activities. We propose a powerful computational method, Edge Set Enrichment Analysis (ESEA), for the identification of dysregulated pathways. This provides a novel way of pathway analysis by investigating the changes of biological relationships of pathways in the context of gene expression data. Simulation studies illustrate the power and performance of ESEA under various simulated conditions. Using real datasets from p53 mutation, Type 2 diabetes and lung cancer, we validate effectiveness of ESEA in identifying dysregulated pathways. We further compare our results with five other pathway enrichment analysis methods. With these analyses, we show that ESEA is able to help uncover dysregulated biological pathways underlying complex traits and human diseases via specific use of the dysregulated biological relationships. We develop a freely available R-based tool of ESEA. Currently, ESEA can support pathway analysis of the seven public databases (KEGG; Reactome; Biocarta; NCI; SPIKE; HumanCyc; Panther). PMID:26267116

  9. Multifaceted enrichment analysis of RNA–RNA crosstalk reveals cooperating micro-societies in human colorectal cancer

    PubMed Central

    Mazza, Tommaso; Mazzoccoli, Gianluigi; Fusilli, Caterina; Capocefalo, Daniele; Panza, Anna; Biagini, Tommaso; Castellana, Stefano; Gentile, Annamaria; De Cata, Angelo; Palumbo, Orazio; Stallone, Raffaella; Rubino, Rosa; Carella, Massimo; Piepoli, Ada

    2016-01-01

    Alterations in the balance of mRNA and microRNA (miRNA) expression profiles contribute to the onset and development of colorectal cancer. The regulatory functions of individual miRNA-gene pairs are widely acknowledged, but group effects are largely unexplored. We performed an integrative analysis of mRNA–miRNA and miRNA–miRNA interactions using high-throughput mRNA and miRNA expression profiles obtained from matched specimens of human colorectal cancer tissue and adjacent non-tumorous mucosa. This investigation resulted in a hypernetwork-based model, whose functional backbone was fulfilled by tight micro-societies of miRNAs. These proved to modulate several genes that are known to control a set of significantly enriched cancer-enhancer and cancer-protection biological processes, and that an array of upstream regulatory analyses demonstrated to be dependent on miR-145, a cell cycle and MAPK signaling cascade master regulator. In conclusion, we reveal miRNA-gene clusters and gene families with close functional relationships and highlight the role of miR-145 as potent upstream regulator of a complex RNA–RNA crosstalk, which mechanistically modulates several signaling pathways and regulatory circuits that when deranged are relevant to the changes occurring in colorectal carcinogenesis. PMID:27067546

  10. Systematic enrichment analysis of microRNA expression profiling studies in endometriosis

    PubMed Central

    Wei, Shiyang; Xu, Hong; Kuang, Yan

    2015-01-01

    Objective(s): The purpose of this study was to conduct a meta-analysis on human microRNAs (miRNAs) expression data of endometriosis tissue profiles versus those of normal controls and to identify novel putative diagnostic markers. Materials and Methods: PubMed, Embase, Web of Science, Ovid Medline were used to search for endometriosis miRNA expression profiling studies of endometriosis. The miRNAs expression data were extracted, and study quality of each article was assessed. The frequently reported miRNAs with consistent regulation were screened out by a meta-profiling algorithm. The putative targets of consistently expressed miRNAs were predicted by using four target prediction tools (TargetScan, PicTar, miRanda, miRDB), and gene ontology pathway enrichment analysis (KEGG and Panther pathways) of the miRNA targets were carried out with GeneCodis web tool. Results: A total of 194 related literatures were retrieved in four databases. One hundred and thirty four differentially expressed miRNAs were found in the 12 microRNA expression profiling studies that compared endometriosis tissues with normal tissues, with 28 miRNAs reported in at least two studies, and 9882 candidate genes retrieved for 13 consistently expressed miRNAs. Kyoto encyclopedia of genes and genomes (KEGG) and Panther pathways enrichment analysis showed that endometriosis related differently expressed miRNA targets were mainly enriched in cancer, endocytosis, Wnt signalling pathway, and angiogenesis. It showed that these differently expressed miRNAs and gene are potential biomarkers of endometriosis. Conclusion: miRNAs appear to be potent regulators of gene expression in endometriosis and its associated reproductive disorders, raising the prospect of using miRNAs as biomarkers and therapeutic agent in endometriosis. PMID:26124927

  11. Cluster Analysis and Fuzzy Query in Ship Maintenance and Design

    NASA Astrophysics Data System (ADS)

    Che, Jianhua; He, Qinming; Zhao, Yinggang; Qian, Feng; Chen, Qi

    Cluster analysis and fuzzy query win wide-spread applications in modern intelligent information processing. In allusion to the features of ship maintenance data, a variant of hypergraph-based clustering algorithm, i.e., Correlation Coefficient-based Minimal Spanning Tree(CC-MST), is proposed to analyze the bulky data rooting in ship maintenance process, discovery the unknown rules and help ship maintainers make a decision on various device fault causes. At the same time, revising or renewing an existed design of ship or device maybe necessary to eliminate those device faults. For the sake of offering ship designers some valuable hints, a fuzzy query mechanism is designed to retrieve the useful information from large-scale complicated and reluctant ship technical and testing data. Finally, two experiments based on a real ship device fault statistical dataset validate the flexibility and efficiency of the CC-MST algorithm. A fuzzy query prototype demonstrates the usability of our fuzzy query mechanism.

  12. Accident patterns for construction-related workers: a cluster analysis

    NASA Astrophysics Data System (ADS)

    Liao, Chia-Wen; Tyan, Yaw-Yauan

    2012-01-01

    The construction industry has been identified as one of the most hazardous industries. The risk of constructionrelated workers is far greater than that in a manufacturing based industry. However, some steps can be taken to reduce worker risk through effective injury prevention strategies. In this article, k-means clustering methodology is employed in specifying the factors related to different worker types and in identifying the patterns of industrial occupational accidents. Accident reports during the period 1998 to 2008 are extracted from case reports of the Northern Region Inspection Office of the Council of Labor Affairs of Taiwan. The results show that the cluster analysis can indicate some patterns of occupational injuries in the construction industry. Inspection plans should be proposed according to the type of construction-related workers. The findings provide a direction for more effective inspection strategies and injury prevention programs.

  13. Accident patterns for construction-related workers: a cluster analysis

    NASA Astrophysics Data System (ADS)

    Liao, Chia-Wen; Tyan, Yaw-Yauan

    2011-12-01

    The construction industry has been identified as one of the most hazardous industries. The risk of constructionrelated workers is far greater than that in a manufacturing based industry. However, some steps can be taken to reduce worker risk through effective injury prevention strategies. In this article, k-means clustering methodology is employed in specifying the factors related to different worker types and in identifying the patterns of industrial occupational accidents. Accident reports during the period 1998 to 2008 are extracted from case reports of the Northern Region Inspection Office of the Council of Labor Affairs of Taiwan. The results show that the cluster analysis can indicate some patterns of occupational injuries in the construction industry. Inspection plans should be proposed according to the type of construction-related workers. The findings provide a direction for more effective inspection strategies and injury prevention programs.

  14. Cluster: Mission Overview and End-of-Life Analysis

    NASA Technical Reports Server (NTRS)

    Pallaschke, S.; Munoz, I.; Rodriquez-Canabal, J.; Sieg, D.; Yde, J. J.

    2007-01-01

    The Cluster mission is part of the scientific programme of the European Space Agency (ESA) and its purpose is the analysis of the Earth's magnetosphere. The Cluster project consists of four satellites. The selected polar orbit has a shape of 4.0 and 19.2 Re which is required for performing measurements near the cusp and the tail of the magnetosphere. When crossing these regions the satellites form a constellation which in most of the cases so far has been a regular tetrahedron. The satellite operations are carried out by the European Space Operations Centre (ESOC) at Darmstadt, Germany. The paper outlines the future orbit evolution and the envisaged operations from a Flight Dynamics point of view. In addition a brief summary of the LEOP and routine operations is included beforehand.

  15. Analysis of civilian processing programs in reduction of excess separated plutonium and high-enriched uranium

    SciTech Connect

    Persiani, P.J.

    1995-12-31

    The purpose of this preliminary investigation is to explore alternatives and strategies aimed at the gradual reduction of the excess inventories of separated plutonium and high-enriched uranium (HEU) in the civilian nuclear power industry. The study attempts to establish a technical and economic basis to assist in the formation of alternative approaches consistent with nonproliferation and safeguards concerns. The analysis addresses several options in reducing the excess separated plutonium and HEU, and the consequences on nonproliferation and safeguards policy assessments resulting from the interacting synergistic effects between fuel cycle processes and isotopic signatures of nuclear materials.

  16. Characterization of Protein N-Glycosylation by Analysis of ZIC-HILIC-Enriched Intact Proteolytic Glycopeptides.

    PubMed

    Pohlentz, Gottfried; Marx, Kristina; Mormann, Michael

    2016-01-01

    Zwitterionic hydrophilic interaction chromatography (ZIC-HILIC) solid-phase extraction (SPE) combined with direct-infusion nanoESI mass spectrometry (MS) and tandem MS/MS is a well-suited method for the analysis of protein N-glycosylation. A site-specific characterization of N-glycopeptides is achieved by the combination of proteolytic digestions employing unspecific proteases, glycopeptide enrichment by use of ZIC-HILIC SPE, and subsequent mass spectrometric analysis. The use of thermolysin or a mixture of trypsin and chymotrypsin leads per se to a mass-based separation, that is, small nonglycosylated peptides and almost exclusively glycopeptides at higher m/z values. As a result of their higher hydrophilicity N-glycopeptides comprising short peptide backbones are preferably accumulated by the ZIC-HILIC-based separation procedure. By employing this approach complications associated with low ionization efficiencies of N-glycopeptides resulting from signal suppression in the presence of highly abundant nonglycosylated peptides can be largely reduced. Here, we describe a simple protocol aimed at the enrichment of N-glycopeptides derived from in-solution and in-gel digestions of SDS-PAGE-separated glycoproteins preceding mass spectrometric analysis.

  17. Associations between DNA methylation and schizophrenia-related intermediate phenotypes - a gene set enrichment analysis.

    PubMed

    Hass, Johanna; Walton, Esther; Wright, Carrie; Beyer, Andreas; Scholz, Markus; Turner, Jessica; Liu, Jingyu; Smolka, Michael N; Roessner, Veit; Sponheim, Scott R; Gollub, Randy L; Calhoun, Vince D; Ehrlich, Stefan

    2015-06-01

    Multiple genetic approaches have identified microRNAs as key effectors in psychiatric disorders as they post-transcriptionally regulate expression of thousands of target genes. However, their role in specific psychiatric diseases remains poorly understood. In addition, epigenetic mechanisms such as DNA methylation, which affect the expression of both microRNAs and coding genes, are critical for our understanding of molecular mechanisms in schizophrenia. Using clinical, imaging, genetic, and epigenetic data of 103 patients with schizophrenia and 111 healthy controls of the Mind Clinical Imaging Consortium (MCIC) study of schizophrenia, we conducted gene set enrichment analysis to identify markers for schizophrenia-associated intermediate phenotypes. Genes were ranked based on the correlation between DNA methylation patterns and each phenotype, and then searched for enrichment in 221 predicted microRNA target gene sets. We found the predicted hsa-miR-219a-5p target gene set to be significantly enriched for genes (EPHA4, PKNOX1, ESR1, among others) whose methylation status is correlated with hippocampal volume independent of disease status. Our results were strengthened by significant associations between hsa-miR-219a-5p target gene methylation patterns and hippocampus-related neuropsychological variables. IPA pathway analysis of the respective predicted hsa-miR-219a-5p target genes revealed associated network functions in behavior and developmental disorders. Altered methylation patterns of predicted hsa-miR-219a-5p target genes are associated with a structural aberration of the brain that has been proposed as a possible biomarker for schizophrenia. The (dys)regulation of microRNA target genes by epigenetic mechanisms may confer additional risk for developing psychiatric symptoms. Further study is needed to understand possible interactions between microRNAs and epigenetic changes and their impact on risk for brain-based disorders such as schizophrenia. PMID:25598502

  18. Associations between DNA methylation and schizophrenia-related intermediate phenotypes - a gene set enrichment analysis.

    PubMed

    Hass, Johanna; Walton, Esther; Wright, Carrie; Beyer, Andreas; Scholz, Markus; Turner, Jessica; Liu, Jingyu; Smolka, Michael N; Roessner, Veit; Sponheim, Scott R; Gollub, Randy L; Calhoun, Vince D; Ehrlich, Stefan

    2015-06-01

    Multiple genetic approaches have identified microRNAs as key effectors in psychiatric disorders as they post-transcriptionally regulate expression of thousands of target genes. However, their role in specific psychiatric diseases remains poorly understood. In addition, epigenetic mechanisms such as DNA methylation, which affect the expression of both microRNAs and coding genes, are critical for our understanding of molecular mechanisms in schizophrenia. Using clinical, imaging, genetic, and epigenetic data of 103 patients with schizophrenia and 111 healthy controls of the Mind Clinical Imaging Consortium (MCIC) study of schizophrenia, we conducted gene set enrichment analysis to identify markers for schizophrenia-associated intermediate phenotypes. Genes were ranked based on the correlation between DNA methylation patterns and each phenotype, and then searched for enrichment in 221 predicted microRNA target gene sets. We found the predicted hsa-miR-219a-5p target gene set to be significantly enriched for genes (EPHA4, PKNOX1, ESR1, among others) whose methylation status is correlated with hippocampal volume independent of disease status. Our results were strengthened by significant associations between hsa-miR-219a-5p target gene methylation patterns and hippocampus-related neuropsychological variables. IPA pathway analysis of the respective predicted hsa-miR-219a-5p target genes revealed associated network functions in behavior and developmental disorders. Altered methylation patterns of predicted hsa-miR-219a-5p target genes are associated with a structural aberration of the brain that has been proposed as a possible biomarker for schizophrenia. The (dys)regulation of microRNA target genes by epigenetic mechanisms may confer additional risk for developing psychiatric symptoms. Further study is needed to understand possible interactions between microRNAs and epigenetic changes and their impact on risk for brain-based disorders such as schizophrenia.

  19. Clustered Numerical Data Analysis Using Markov Lie Monoid Based Networks

    NASA Astrophysics Data System (ADS)

    Johnson, Joseph

    2016-03-01

    We have designed and build an optimal numerical standardization algorithm that links numerical values with their associated units, error level, and defining metadata thus supporting automated data exchange and new levels of artificial intelligence (AI). The software manages all dimensional and error analysis and computational tracing. Tables of entities verses properties of these generalized numbers (called ``metanumbers'') support a transformation of each table into a network among the entities and another network among their properties where the network connection matrix is based upon a proximity metric between the two items. We previously proved that every network is isomorphic to the Lie algebra that generates continuous Markov transformations. We have also shown that the eigenvectors of these Markov matrices provide an agnostic clustering of the underlying patterns. We will present this methodology and show how our new work on conversion of scientific numerical data through this process can reveal underlying information clusters ordered by the eigenvalues. We will also show how the linking of clusters from different tables can be used to form a ``supernet'' of all numerical information supporting new initiatives in AI.

  20. Covariance analysis of differential drag-based satellite cluster flight

    NASA Astrophysics Data System (ADS)

    Ben-Yaacov, Ohad; Ivantsov, Anatoly; Gurfil, Pini

    2016-06-01

    One possibility for satellite cluster flight is to control relative distances using differential drag. The idea is to increase or decrease the drag acceleration on each satellite by changing its attitude, and use the resulting small differential acceleration as a controller. The most significant advantage of the differential drag concept is that it enables cluster flight without consuming fuel. However, any drag-based control algorithm must cope with significant aerodynamical and mechanical uncertainties. The goal of the current paper is to develop a method for examination of the differential drag-based cluster flight performance in the presence of noise and uncertainties. In particular, the differential drag control law is examined under measurement noise, drag uncertainties, and initial condition-related uncertainties. The method used for uncertainty quantification is the Linear Covariance Analysis, which enables us to propagate the augmented state and filter covariance without propagating the state itself. Validation using a Monte-Carlo simulation is provided. The results show that all uncertainties have relatively small effect on the inter-satellite distance, even in the long term, which validates the robustness of the used differential drag controller.

  1. GRAF1a is a brain-specific protein that promotes lipid droplet clustering and growth, and is enriched at lipid droplet junctions

    PubMed Central

    Lucken-Ardjomande Häsler, Safa; Vallis, Yvonne; Jolin, Helen E.; McKenzie, Andrew N.; McMahon, Harvey T.

    2014-01-01

    ABSTRACT Lipid droplets are found in all cell types. Normally present at low levels in the brain, they accumulate in tumours and are associated with neurodegenerative diseases. However, little is known about the mechanisms controlling their homeostasis in the brain. We found that GRAF1a, the longest GRAF1 isoform (GRAF1 is also known as ARHGAP26), was enriched in the brains of neonates. Endogenous GRAF1a was found on lipid droplets in oleic-acid-fed primary glial cells. Exclusive localization required a GRAF1a-specific hydrophobic segment and two membrane-binding regions, a BAR and a PH domain. Overexpression of GRAF1a promoted lipid droplet clustering, inhibited droplet mobility and severely perturbed lipolysis following the chase of cells overloaded with fatty acids. Under these conditions, GRAF1a concentrated at the interface between lipid droplets. Although GRAF1-knockout mice did not show any gross abnormal phenotype, the total lipid droplet volume that accumulated in GRAF1−/− primary glia upon incubation with fatty acids was reduced compared to GRAF1+/+ cells. These results provide additional insights into the mechanisms contributing to lipid droplet growth in non-adipocyte cells, and suggest that proteins with membrane sculpting BAR domains play a role in droplet homeostasis. PMID:25189622

  2. Partial Safety Analysis for a Reduced Uranium Enrichment Core for the High Flux Isotope Reactor

    SciTech Connect

    Primm, Trent; Gehin, Jess C

    2009-04-01

    A computational model of the reactor core of the High Flux Isotope Rector (HFIR) was developed in order to analyze non-destructive accidents caused by transients during reactor operation. The reactor model was built for the latest version of the nuclear analysis software package called Program for the Analysis of Reactor Transients (PARET). Analyses performed with the model constructed were compared with previous data obtained with other tools in order to benchmark the code. Finally, the model was used to analyze the behavior of the reactor under transients using a different nuclear fuel with lower enrichment of uranium (LEU) than the fuel currently used, which has a high enrichment of uranium (HEU). The study shows that the presence of fertile isotopes in LEU fuel, which increases the neutron resonance absorption, reduces the impact of transients on the fuel and enhances the negative reactivity feedback, thus, within the limitations of this study, making LEU fuel appear to be a safe alternative fuel for the reactor core.

  3. Length bias correction in gene ontology enrichment analysis using logistic regression.

    PubMed

    Mi, Gu; Di, Yanming; Emerson, Sarah; Cumbie, Jason S; Chang, Jeff H

    2012-01-01

    When assessing differential gene expression from RNA sequencing data, commonly used statistical tests tend to have greater power to detect differential expression of genes encoding longer transcripts. This phenomenon, called "length bias", will influence subsequent analyses such as Gene Ontology enrichment analysis. In the presence of length bias, Gene Ontology categories that include longer genes are more likely to be identified as enriched. These categories, however, are not necessarily biologically more relevant. We show that one can effectively adjust for length bias in Gene Ontology analysis by including transcript length as a covariate in a logistic regression model. The logistic regression model makes the statistical issue underlying length bias more transparent: transcript length becomes a confounding factor when it correlates with both the Gene Ontology membership and the significance of the differential expression test. The inclusion of the transcript length as a covariate allows one to investigate the direct correlation between the Gene Ontology membership and the significance of testing differential expression, conditional on the transcript length. We present both real and simulated data examples to show that the logistic regression approach is simple, effective, and flexible. PMID:23056249

  4. The REFLEX II galaxy cluster survey: power spectrum analysis

    NASA Astrophysics Data System (ADS)

    Balaguera-Antolínez, A.; Sánchez, Ariel G.; Böhringer, H.; Collins, C.; Guzzo, L.; Phleps, S.

    2011-05-01

    We present the power spectrum of galaxy clusters measured from the new ROSAT-ESO Flux-Limited X-Ray (REFLEX II) galaxy cluster catalogue. This new sample extends the flux limit of the original REFLEX catalogue to 1.8 × 10-12 erg s-1 cm-2, yielding a total of 911 clusters with ≥94 per cent completeness in redshift follow-up. The analysis of the data is improved by creating a set of 100 REFLEX II-catalogue-like mock galaxy cluster catalogues built from a suite of large-volume Λ cold dark matter (ΛCDM) N-body simulations (L-BASICC II). The measured power spectrum is in agreement with the predictions from a ΛCDM cosmological model. The measurements show the expected increase in the amplitude of the power spectrum with increasing X-ray luminosity. On large scales, we show that the shape of the measured power spectrum is compatible with a scale-independent bias and provide a model for the amplitude that allows us to connect our measurements with a cosmological model. By implementing a luminosity-dependent power-spectrum estimator, we observe that the power spectrum measured from the REFLEX II sample is weakly affected by flux-selection effects. The shape of the measured power spectrum is compatible with a featureless power spectrum on scales k > 0.01 h Mpc-1 and hence no statistically significant signal of baryonic acoustic oscillations can be detected. We show that the measured REFLEX II power spectrum displays signatures of non-linear evolution.

  5. Proteomics Analysis Reveals Overlapping Functions of Clustered Protocadherins*

    PubMed Central

    Han, Meng-Hsuan; Lin, Chengyi; Meng, Shuxia; Wang, Xiaozhong

    2010-01-01

    The three tandem-arrayed protocadherin (Pcdh) gene clusters, namely Pcdh-α, Pcdh-β, and Pcdh-γ, play important roles in the development of the vertebrate central nervous system. To gain insight into the molecular action of PCDHs, we performed a systematic proteomics analysis of PCDH-γ-associated protein complexes. We identified a list of 154 non-redundant proteins in the PCDH-γ complexes. This list includes nearly 30 members of clustered Pcdh-α, -β, and -γ families as core components of the complexes and additionally over 120 putative PCDH-associated proteins. We validated a selected subset of PCDH-γ-associated proteins using specific antibodies. Analysis of the identities of PCDH-associated proteins showed that the majority of them overlap with the proteomic profile of postsynaptic density preparations. Further analysis of membrane protein complexes revealed that several validated PCDH-γ-associated proteins exhibit reduced levels in Pcdh-γ-deficient brain tissues. Therefore, PCDH-γs are required for the integrity of the complexes. However, the size of the overall complexes and the abundance of many other proteins remained unchanged, raising a possibility that PCDH-αs and PCDH-βs might compensate for PCDH-γ function in complex formation. As a test of this idea, RNA interference knockdown of both PCDH-αs and PCDH-γs showed that PCDHs have redundant functions in regulating neuronal survival in the chicken spinal cord. Taken together, our data provide evidence that clustered PCDHs coexist in large protein complexes and have overlapping functions during vertebrate neural development. PMID:19843561

  6. [Dermatoglyphics parameters and cluster analysis of seven minority nationalities].

    PubMed

    Zhang, H G; Shen, R C; Su, Y B; Chen, R B; Feng, B; Ding, M; Huang, M L; Wang, Y P; Jiao, Y P; Peng, L

    1989-01-01

    This paper reports the normal values of dermatoglyphics parameters of seven minority nationalities in Yunnan Province which are Bai, Blang, Yi, Hui, Lisu, Nu and Jinuo. The test of difference signification and cluster analysis show different parameters in several nationalities and the greatest most remarkable difference between Jinou and other nationalities. Han is very different from several nationalities. In each nationality, the symmetry pattern of same name finger or area is highly unanimous, the symmetry between left and right does not show random combination.

  7. Nonuniqueness in traveltime tomography: Ensemble inference and cluster analysis

    SciTech Connect

    Vasco, D.W.; Peterson, J.E. Jr.; Majer, E.L.

    1996-07-01

    The authors examine the nonlinear aspects of seismic traveltime tomography. This is accomplished by completing an extensive set of conjugate gradient inversions on a parallel virtual machine, with each initiated by a different starting model. The goal is an exploratory analysis of a set of conjugate gradient solutions to the traveltime tomography problem. The authors find that distinct local minima are generated when prior constraints are imposed on traveltime tomographic inverse problems. Methods from cluster analysis determine the number and location of the isolated solutions to the traveltime tomography problem. They apply the cluster analysis techniques to a cross-borehole traveltime data set gathered at the Gypsy Pilot Site in Pawnee County, Oklahoma. They find that the 1075 final models, satisfying the traveltime data and a model norm penalty, form up to 61 separate solutions. All solutions appear to contain a central low velocity zone bounded above and below by higher velocity layers. Such a structure agrees with well-logs, hydrological well tests, and a previous seismic inversion.

  8. [Clustering analysis applied to near-infrared spectroscopy analysis of Chinese traditional medicine].

    PubMed

    Liu, Mu-qing; Zhou, De-cheng; Xu, Xin-yuan; Sun, Yao-jie; Zhou, Xiao-li; Han, Lei

    2007-10-01

    The present article discusses the clustering analysis used in the near-infrared (NIR) spectroscopy analysis of Chinese traditional medicines, which provides a new method for the classification of Chinese traditional medicines. Samples selected purposely in the authors' research to measure their absorption spectra in seconds by a multi-channel NIR spectrometer developed in the authors' lab were safrole, eucalypt oil, laurel oil, turpentine, clove oil and three samples of costmary oil from different suppliers. The spectra in the range of 0.70-1.7 microm were measured with air as background and the results indicated that they are quite distinct. Qualitative mathematical model was set up and cluster analysis based on the spectra was carried out through different clustering methods for optimization, and came out the cluster correlation coefficient of 0.9742 in the authors' research. This indicated that cluster analysis of the group of samples is practicable. Also it is reasonable to get the result that the calculated classification of 8 samples was quite accorded with their characteristics, especially the three samples of costmary oil were in the closest classification of the clustering analysis. PMID:18306778

  9. Transcriptomic Analysis of the Effects of a Fish Oil Enriched Diet on Murine Brains

    PubMed Central

    Gautam, Aarti; Miller, Stacy-Ann; Muhie, Seid; Meyerhoff, James; Jett, Marti

    2014-01-01

    The health benefits of fish oil enriched with high omega-3 polyunsaturated fatty acids (n-3 PUFA) are widely documented. Fish oil as dietary supplements, however, show moderate clinical efficacy, highlighting an immediate scope of systematic in vitro feedback. Our transcriptomic study was designed to investigate the genomic shift of murine brains fed on fish oil enriched diets. A customized fish oil enriched diet (FD) and standard lab diet (SD) were separately administered to two randomly chosen populations of C57BL/6J mice from their weaning age until late adolescence. Statistical analysis mined 1,142 genes of interest (GOI) differentially altered in the hemibrains collected from the FD- and SD-fed mice at the age of five months. The majority of identified GOI (∼40%) encodes proteins located in the plasma membrane, suggesting that fish oil primarily facilitated the membrane-oriented biofunctions. FD potentially augmented the nervous system's development and functions by selectively stimulating the Src-mediated calcium-induced growth cascade and the downstream PI3K-AKT-PKC pathways. FD reduced the amyloidal burden, attenuated oxidative stress, and assisted in somatostatin activation—the signatures of attenuation of Alzheimer's disease, Parkinson's disease, and affective disorder. FD induced elevation of FKBP5 and suppression of BDNF, which are often linked with the improvement of anxiety disorder, depression, and post-traumatic stress disorder. Hence we anticipate efficacy of FD in treating illnesses such as depression that are typically triggered by the hypoactivities of dopaminergic, adrenergic, cholinergic, and GABAergic networks. Contrastingly, FD's efficacy could be compromised in treating illnesses such as bipolar disorder and schizophrenia, which are triggered by hyperactivities of the same set of neuromodulators. A more comprehensive investigation is recommended to elucidate the implications of fish oil on disease pathomechanisms, and the result

  10. Transcriptomic analysis of the effects of a fish oil enriched diet on murine brains.

    PubMed

    Hammamieh, Rasha; Chakraborty, Nabarun; Gautam, Aarti; Miller, Stacy-Ann; Muhie, Seid; Meyerhoff, James; Jett, Marti

    2014-01-01

    The health benefits of fish oil enriched with high omega-3 polyunsaturated fatty acids (n-3 PUFA) are widely documented. Fish oil as dietary supplements, however, show moderate clinical efficacy, highlighting an immediate scope of systematic in vitro feedback. Our transcriptomic study was designed to investigate the genomic shift of murine brains fed on fish oil enriched diets. A customized fish oil enriched diet (FD) and standard lab diet (SD) were separately administered to two randomly chosen populations of C57BL/6J mice from their weaning age until late adolescence. Statistical analysis mined 1,142 genes of interest (GOI) differentially altered in the hemibrains collected from the FD- and SD-fed mice at the age of five months. The majority of identified GOI (∼ 40%) encodes proteins located in the plasma membrane, suggesting that fish oil primarily facilitated the membrane-oriented biofunctions. FD potentially augmented the nervous system's development and functions by selectively stimulating the Src-mediated calcium-induced growth cascade and the downstream PI3K-AKT-PKC pathways. FD reduced the amyloidal burden, attenuated oxidative stress, and assisted in somatostatin activation-the signatures of attenuation of Alzheimer's disease, Parkinson's disease, and affective disorder. FD induced elevation of FKBP5 and suppression of BDNF, which are often linked with the improvement of anxiety disorder, depression, and post-traumatic stress disorder. Hence we anticipate efficacy of FD in treating illnesses such as depression that are typically triggered by the hypoactivities of dopaminergic, adrenergic, cholinergic, and GABAergic networks. Contrastingly, FD's efficacy could be compromised in treating illnesses such as bipolar disorder and schizophrenia, which are triggered by hyperactivities of the same set of neuromodulators. A more comprehensive investigation is recommended to elucidate the implications of fish oil on disease pathomechanisms, and the result

  11. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update

    PubMed Central

    Kuleshov, Maxim V.; Jones, Matthew R.; Rouillard, Andrew D.; Fernandez, Nicolas F.; Duan, Qiaonan; Wang, Zichen; Koplev, Simon; Jenkins, Sherry L.; Jagodnik, Kathleen M.; Lachmann, Alexander; McDermott, Michael G.; Monteiro, Caroline D.; Gundersen, Gregory W.; Ma'ayan, Avi

    2016-01-01

    Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gene set libraries available for analysis and download. In total, Enrichr currently contains 180 184 annotated gene sets from 102 gene set libraries. New features have been added to Enrichr including the ability to submit fuzzy sets, upload BED files, improved application programming interface and visualization of the results as clustergrams. Overall, Enrichr is a comprehensive resource for curated gene sets and a search engine that accumulates biological knowledge for further biological discoveries. Enrichr is freely available at: http://amp.pharm.mssm.edu/Enrichr. PMID:27141961

  12. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update.

    PubMed

    Kuleshov, Maxim V; Jones, Matthew R; Rouillard, Andrew D; Fernandez, Nicolas F; Duan, Qiaonan; Wang, Zichen; Koplev, Simon; Jenkins, Sherry L; Jagodnik, Kathleen M; Lachmann, Alexander; McDermott, Michael G; Monteiro, Caroline D; Gundersen, Gregory W; Ma'ayan, Avi

    2016-07-01

    Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gene set libraries available for analysis and download. In total, Enrichr currently contains 180 184 annotated gene sets from 102 gene set libraries. New features have been added to Enrichr including the ability to submit fuzzy sets, upload BED files, improved application programming interface and visualization of the results as clustergrams. Overall, Enrichr is a comprehensive resource for curated gene sets and a search engine that accumulates biological knowledge for further biological discoveries. Enrichr is freely available at: http://amp.pharm.mssm.edu/Enrichr. PMID:27141961

  13. Multivariate cluster analysis of forest fire events in Portugal

    NASA Astrophysics Data System (ADS)

    Tonini, Marj; Pereira, Mario; Vega Orozco, Carmen; Parente, Joana

    2015-04-01

    Portugal is one of the major fire-prone European countries, mainly due to its favourable climatic, topographic and vegetation conditions. Compared to the other Mediterranean countries, the number of events registered here from 1980 up to nowadays is the highest one; likewise, with respect to the burnt area, Portugal is the third most affected country. Portuguese mapped burnt areas are available from the website of the Institute for the Conservation of Nature and Forests (ICNF). This official geodatabase is the result of satellite measurements starting from the year 1990. The spatial information, delivered in shapefile format, provides a detailed description of the shape and the size of area burnt by each fire, while the date/time information relate to the ignition fire is restricted to the year of occurrence. In terms of a statistical formalism wildfires can be associated to a stochastic point process, where events are analysed as a set of geographical coordinates corresponding, for example, to the centroid of each burnt area. The spatio/temporal pattern of stochastic point processes, including the cluster analysis, is a basic procedure to discover predisposing factorsas well as for prevention and forecasting purposes. These kinds of studies are primarily focused on investigating the spatial cluster behaviour of environmental data sequences and/or mapping their distribution at different times. To include both the two dimensions (space and time) a comprehensive spatio-temporal analysis is needful. In the present study authors attempt to verify if, in the case of wildfires in Portugal, space and time act independently or if, conversely, neighbouring events are also closer in time. We present an application of the spatio-temporal K-function to a long dataset (1990-2012) of mapped burnt areas. Moreover, the multivariate K-function allowed checking for an eventual different distribution between small and large fires. The final objective is to elaborate a 3D

  14. A Monte Carlo Analysis of Gas Centrifuge Enrichment Plant Process Load Cell Data

    SciTech Connect

    Garner, James R; Whitaker, J Michael

    2013-01-01

    As uranium enrichment plants increase in number, capacity, and types of separative technology deployed (e.g., gas centrifuge, laser, etc.), more automated safeguards measures are needed to enable the IAEA to maintain safeguards effectiveness in a fiscally constrained environment. Monitoring load cell data can significantly increase the IAEA s ability to efficiently achieve the fundamental safeguards objective of confirming operations as declared (i.e., no undeclared activities), but care must be taken to fully protect the operator s proprietary and classified information related to operations. Staff at ORNL, LANL, JRC/ISPRA, and University of Glasgow are investigating monitoring the process load cells at feed and withdrawal (F/W) stations to improve international safeguards at enrichment plants. A key question that must be resolved is what is the necessary frequency of recording data from the process F/W stations? Several studies have analyzed data collected at a fixed frequency. This paper contributes to load cell process monitoring research by presenting an analysis of Monte Carlo simulations to determine the expected errors caused by low frequency sampling and its impact on material balance calculations.

  15. Multivariate analysis of the heterogeneous geochemical processes controlling arsenic enrichment in a shallow groundwater system.

    PubMed

    Huang, Shuangbing; Liu, Changrong; Wang, Yanxin; Zhan, Hongbin

    2014-01-01

    The effects of various geochemical processes on arsenic enrichment in a high-arsenic aquifer at Jianghan Plain in Central China were investigated using multivariate models developed from combined adaptive neuro-fuzzy inference system (ANFIS) and multiple linear regression (MLR). The results indicated that the optimum variable group for the AFNIS model consisted of bicarbonate, ammonium, phosphorus, iron, manganese, fluorescence index, pH, and siderite saturation. These data suggest that reductive dissolution of iron/manganese oxides, phosphate-competitive adsorption, pH-dependent desorption, and siderite precipitation could integrally affect arsenic concentration. Analysis of the MLR models indicated that reductive dissolution of iron(III) was primarily responsible for arsenic mobilization in groundwaters with low arsenic concentration. By contrast, for groundwaters with high arsenic concentration (i.e., > 170 μg/L), reductive dissolution of iron oxides approached a dynamic equilibrium. The desorption effects from phosphate-competitive adsorption and the increase in pH exhibited arsenic enrichment superior to that caused by iron(III) reductive dissolution as the groundwater chemistry evolved. The inhibition effect of siderite precipitation on arsenic mobilization was expected to exist in groundwater that was highly saturated with siderite. The results suggest an evolutionary dominance of specific geochemical process over other factors controlling arsenic concentration, which presented a heterogeneous distribution in aquifers. Supplemental materials are available for this article. Go to the publisher's online edition of the Journal of Environmental Science and Health, Part A, to view the supplemental file. PMID:24345245

  16. Phylogenetic analysis of anaerobic psychrophilic enrichment cultures obtained from a greenland glacier ice core

    NASA Technical Reports Server (NTRS)

    Sheridan, Peter P.; Miteva, Vanya I.; Brenchley, Jean E.

    2003-01-01

    The examination of microorganisms in glacial ice cores allows the phylogenetic relationships of organisms frozen for thousands of years to be compared with those of current isolates. We developed a method for aseptically sampling a sediment-containing portion of a Greenland ice core that had remained at -9 degrees C for over 100,000 years. Epifluorescence microscopy and flow cytometry results showed that the ice sample contained over 6 x 10(7) cells/ml. Anaerobic enrichment cultures inoculated with melted ice were grown and maintained at -2 degrees C. Genomic DNA extracted from these enrichments was used for the PCR amplification of 16S rRNA genes with bacterial and archaeal primers and the preparation of clone libraries. Approximately 60 bacterial inserts were screened by restriction endonuclease analysis and grouped into 27 unique restriction fragment length polymorphism types, and 24 representative sequences were compared phylogenetically. Diverse sequences representing major phylogenetic groups including alpha, beta, and gamma Proteobacteria as well as relatives of the Thermus, Bacteroides, Eubacterium, and Clostridium groups were found. Sixteen clone sequences were closely related to those from known organisms, with four possibly representing new species. Seven sequences may reflect new genera and were most closely related to sequences obtained only by PCR amplification. One sequence was over 12% distant from its closest relative and may represent a novel order or family. These results show that phylogenetically diverse microorganisms have remained viable within the Greenland ice core for at least 100,000 years.

  17. An enhanced cluster analysis program with bootstrap significance testing for ecological community analysis

    USGS Publications Warehouse

    McKenna, J.E.

    2003-01-01

    The biosphere is filled with complex living patterns and important questions about biodiversity and community and ecosystem ecology are concerned with structure and function of multispecies systems that are responsible for those patterns. Cluster analysis identifies discrete groups within multivariate data and is an effective method of coping with these complexities, but often suffers from subjective identification of groups. The bootstrap testing method greatly improves objective significance determination for cluster analysis. The BOOTCLUS program makes cluster analysis that reliably identifies real patterns within a data set more accessible and easier to use than previously available programs. A variety of analysis options and rapid re-analysis provide a means to quickly evaluate several aspects of a data set. Interpretation is influenced by sampling design and a priori designation of samples into replicate groups, and ultimately relies on the researcher's knowledge of the organisms and their environment. However, the BOOTCLUS program provides reliable, objectively determined groupings of multivariate data.

  18. Time series clustering analysis of health-promoting behavior

    NASA Astrophysics Data System (ADS)

    Yang, Chi-Ta; Hung, Yu-Shiang; Deng, Guang-Feng

    2013-10-01

    Health promotion must be emphasized to achieve the World Health Organization goal of health for all. Since the global population is aging rapidly, ComCare elder health-promoting service was developed by the Taiwan Institute for Information Industry in 2011. Based on the Pender health promotion model, ComCare service offers five categories of health-promoting functions to address the everyday needs of seniors: nutrition management, social support, exercise management, health responsibility, stress management. To assess the overall ComCare service and to improve understanding of the health-promoting behavior of elders, this study analyzed health-promoting behavioral data automatically collected by the ComCare monitoring system. In the 30638 session records collected for 249 elders from January, 2012 to March, 2013, behavior patterns were identified by fuzzy c-mean time series clustering algorithm combined with autocorrelation-based representation schemes. The analysis showed that time series data for elder health-promoting behavior can be classified into four different clusters. Each type reveals different health-promoting needs, frequencies, function numbers and behaviors. The data analysis result can assist policymakers, health-care providers, and experts in medicine, public health, nursing and psychology and has been provided to Taiwan National Health Insurance Administration to assess the elder health-promoting behavior.

  19. Clustering Financial Time Series by Network Community Analysis

    NASA Astrophysics Data System (ADS)

    Piccardi, Carlo; Calatroni, Lisa; Bertoni, Fabio

    In this paper, we describe a method for clustering financial time series which is based on community analysis, a recently developed approach for partitioning the nodes of a network (graph). A network with N nodes is associated to the set of N time series. The weight of the link (i, j), which quantifies the similarity between the two corresponding time series, is defined according to a metric based on symbolic time series analysis, which has recently proved effective in the context of financial time series. Then, searching for network communities allows one to identify groups of nodes (and then time series) with strong similarity. A quantitative assessment of the significance of the obtained partition is also provided. The method is applied to two distinct case-studies concerning the US and Italy Stock Exchange, respectively. In the US case, the stability of the partitions over time is also thoroughly investigated. The results favorably compare with those obtained with the standard tools typically used for clustering financial time series, such as the minimal spanning tree and the hierarchical tree.

  20. Systematic analysis of a novel human renal glomerulus-enriched gene expression dataset.

    PubMed

    Lindenmeyer, Maja T; Eichinger, Felix; Sen, Kontheari; Anders, Hans-Joachim; Edenhofer, Ilka; Mattinzoli, Deborah; Kretzler, Matthias; Rastaldi, Maria P; Cohen, Clemens D

    2010-01-01

    Glomerular diseases account for the majority of cases with chronic renal failure. Several genes have been identified with key relevance for glomerular function. Quite a few of these genes show a specific or preferential mRNA expression in the renal glomerulus. To identify additional candidate genes involved in glomerular function in humans we generated a human renal glomerulus-enriched gene expression dataset (REGGED) by comparing gene expression profiles from human glomeruli and tubulointerstitium obtained from six transplant living donors using Affymetrix HG-U133A arrays. This analysis resulted in 677 genes with prominent overrepresentation in the glomerulus. Genes with 'a priori' known prominent glomerular expression served for validation and were all found in the novel dataset (e.g. CDKN1, DAG1, DDN, EHD3, MYH9, NES, NPHS1, NPHS2, PDPN, PLA2R1, PLCE1, PODXL, PTPRO, SYNPO, TCF21, TJP1, WT1). The mRNA expression of several novel glomerulus-enriched genes in REGGED was validated by qRT-PCR. Gene ontology and pathway analysis identified biological processes previously not reported to be of relevance in glomeruli of healthy human adult kidneys including among others axon guidance. This finding was further validated by assessing the expression of the axon guidance molecules neuritin (NRN1) and roundabout receptor ROBO1 and -2. In diabetic nephropathy, a prevalent glomerulopathy, differential regulation of glomerular ROBO2 mRNA was found.In summary, novel transcripts with predominant expression in the human glomerulus could be identified using a comparative strategy on microdissected nephrons. A systematic analysis of this glomerulus-specific gene expression dataset allows the detection of target molecules and biological processes involved in glomerular biology and renal disease. PMID:20634963

  1. Discovering Biology in Periodic Data through Phase Set Enrichment Analysis (PSEA).

    PubMed

    Zhang, Ray; Podtelezhnikov, Alexei A; Hogenesch, John B; Anafi, Ron C

    2016-06-01

    Several tools use prior biological knowledge to interpret gene expression data. However, existing enrichment tools assume that variables are monotonic and incorrectly measure the distance between periodic phases. As a result, these tools are poorly suited for the analysis of the cell cycle, circadian clock, or other periodic systems. Here, we develop Phase Set Enrichment Analysis (PSEA) to incorporate prior knowledge into the analysis of periodic data. PSEA identifies biologically related gene sets showing temporally coordinated expression. Using synthetic gene sets of various sizes generated from von Mises (circular normal) distributions, we benchmarked PSEA alongside existing methods. PSEA offered enhanced sensitivity over a broad range of von Mises distributions and gene set sizes. Importantly, and unlike existing tools, the sensitivity of PSEA is independent of the mean expression phase of the set. We applied PSEA to 4 published datasets. Application of PSEA to the mouse circadian atlas revealed that several pathways, including those regulating immune and cell-cycle function, demonstrate temporal orchestration across multiple tissues. We then applied PSEA to the phase shifts following a restricted feeding paradigm. We found that this perturbation disrupts intraorgan metabolic synchrony in the liver, altering the timing between anabolic and catabolic pathways. Reanalysis of expression data using custom gene sets derived from recent ChIP-seq results revealed circadian transcriptional targets bound exclusively by CLOCK, independently of BMAL1, differ from other exclusive circadian output genes and have well-synchronized phases. Finally, we used PSEA to compare 2 cell-cycle datasets. PSEA increased the apparent biological overlap while also revealing evidence of cell-cycle dysregulation in these cancer cells. To encourage its use by the community, we have implemented PSEA as a Java application. In sum, PSEA offers a powerful new tool to investigate large

  2. Analysis of clustered data in community psychology: with an example from a worksite smoking cessation project.

    PubMed

    Hedeker, D; McMahon, S D; Jason, L A; Salina, D

    1994-10-01

    Although it is common in community psychology research to have data at both the community, or cluster, and individual level, the analysis of such clustered data often presents difficulties for many researchers. Since the individuals within the cluster cannot be assumed to be independent, the use of many traditional statistical techniques that assumes independence of observations is problematic. Further, there is often interest in assessing the degree of dependence in the data resulting from the clustering of individuals within communities. In this paper, a random-effects regression model is described for analysis of clustered data. Unlike ordinary regression analysis of clustered data, random-effects regression models do not assume that each observation is independent, but do assume data within clusters are dependent to some degree. The degree of this dependency is estimated along with estimates of the usual model parameters, thus adjusting these effects for the dependency resulting from the clustering of the data. Models are described for both continuous and dichotomous outcome variables, and available statistical software for these models is discussed. An analysis of a data set where individuals are clustered within firms is used to illustrate features of random-effects regression analysis, relative to both individual-level analysis which ignores the clustering of the data, and cluster-level analysis which aggregates the individual data. PMID:7755003

  3. Cluster Analysis of Tumor Suppressor Genes in Canine Leukocytes Identifies Activation State

    PubMed Central

    Daly, Julie-Anne; Mortlock, Sally-Anne; Taylor, Rosanne M.; Williamson, Peter

    2015-01-01

    Cells of the immune system undergo activation and subsequent proliferation in the normal course of an immune response. Infrequently, the molecular and cellular events that underlie the mechanisms of proliferation are dysregulated and may lead to oncogenesis, leading to tumor formation. The most common forms of immunological cancers are lymphomas, which in dogs account for 8%–20% of all cancers, affecting up to 1.2% of the dog population. Key genes involved in negatively regulating proliferation of lymphocytes include a group classified as tumor suppressor genes (TSGs). These genes are also known to be associated with progression of lymphoma in humans, mice, and dogs and are potential candidates for pathological grading and diagnosis. The aim of the present study was to analyze TSG profiles in stimulated leukocytes from dogs to identify genes that discriminate an activated phenotype. A total of 554 TSGs and three gene set collections were analyzed from microarray data. Cluster analysis of three subsets of genes discriminated between stimulated and unstimulated cells. These included 20 most upregulated and downregulated TSGs, TSG in hallmark gene sets significantly enriched in active cells, and a selection of candidate TSGs, p15 (CDKN2B), p18 (CDKN2C), p19 (CDKN1A), p21 (CDKN2A), p27 (CDKN1B), and p53 (TP53) in the third set. Analysis of two subsets suggested that these genes or a subset of these genes may be used as a specialized PCR set for additional analysis. PMID:27478369

  4. The composite sequential clustering technique for analysis of multispectral scanner data

    NASA Technical Reports Server (NTRS)

    Su, M. Y.

    1972-01-01

    The clustering technique consists of two parts: (1) a sequential statistical clustering which is essentially a sequential variance analysis, and (2) a generalized K-means clustering. In this composite clustering technique, the output of (1) is a set of initial clusters which are input to (2) for further improvement by an iterative scheme. This unsupervised composite technique was employed for automatic classification of two sets of remote multispectral earth resource observations. The classification accuracy by the unsupervised technique is found to be comparable to that by traditional supervised maximum likelihood classification techniques. The mathematical algorithms for the composite sequential clustering program and a detailed computer program description with job setup are given.

  5. Global analysis of asymmetric RNA enrichment in oocytes reveals low conservation between closely related Xenopus species.

    PubMed

    Claußen, Maike; Lingner, Thomas; Pommerenke, Claudia; Opitz, Lennart; Salinas, Gabriela; Pieler, Tomas

    2015-11-01

    RNAs that localize to the vegetal cortex during Xenopus laevis oogenesis have been reported to function in germ layer patterning, axis determination, and development of the primordial germ cells. Here we report on the genome-wide, comparative analysis of differentially localizing RNAs in Xenopus laevis and Xenopus tropicalis oocytes, revealing a surprisingly weak degree of conservation in respect to the identity of animally as well as vegetally enriched transcripts in these closely related species. Heterologous RNA injections and protein binding studies indicate that the different RNA localization patterns in these two species are due to gain/loss of cis-acting localization signals rather than to differences in the RNA-localizing machinery.

  6. Sequence element enrichment analysis to determine the genetic basis of bacterial phenotypes

    PubMed Central

    Lees, John A.; Vehkala, Minna; Välimäki, Niko; Harris, Simon R.; Chewapreecha, Claire; Croucher, Nicholas J.; Marttinen, Pekka; Davies, Mark R.; Steer, Andrew C.; Tong, Steven Y. C.; Honkela, Antti; Parkhill, Julian; Bentley, Stephen D.; Corander, Jukka

    2016-01-01

    Bacterial genomes vary extensively in terms of both gene content and gene sequence. This plasticity hampers the use of traditional SNP-based methods for identifying all genetic associations with phenotypic variation. Here we introduce a computationally scalable and widely applicable statistical method (SEER) for the identification of sequence elements that are significantly enriched in a phenotype of interest. SEER is applicable to tens of thousands of genomes by counting variable-length k-mers using a distributed string-mining algorithm. Robust options are provided for association analysis that also correct for the clonal population structure of bacteria. Using large collections of genomes of the major human pathogens Streptococcus pneumoniae and Streptococcus pyogenes, SEER identifies relevant previously characterized resistance determinants for several antibiotics and discovers potential novel factors related to the invasiveness of S. pyogenes. We thus demonstrate that our method can answer important biologically and medically relevant questions. PMID:27633831

  7. Sequence element enrichment analysis to determine the genetic basis of bacterial phenotypes.

    PubMed

    Lees, John A; Vehkala, Minna; Välimäki, Niko; Harris, Simon R; Chewapreecha, Claire; Croucher, Nicholas J; Marttinen, Pekka; Davies, Mark R; Steer, Andrew C; Tong, Steven Y C; Honkela, Antti; Parkhill, Julian; Bentley, Stephen D; Corander, Jukka

    2016-01-01

    Bacterial genomes vary extensively in terms of both gene content and gene sequence. This plasticity hampers the use of traditional SNP-based methods for identifying all genetic associations with phenotypic variation. Here we introduce a computationally scalable and widely applicable statistical method (SEER) for the identification of sequence elements that are significantly enriched in a phenotype of interest. SEER is applicable to tens of thousands of genomes by counting variable-length k-mers using a distributed string-mining algorithm. Robust options are provided for association analysis that also correct for the clonal population structure of bacteria. Using large collections of genomes of the major human pathogens Streptococcus pneumoniae and Streptococcus pyogenes, SEER identifies relevant previously characterized resistance determinants for several antibiotics and discovers potential novel factors related to the invasiveness of S. pyogenes. We thus demonstrate that our method can answer important biologically and medically relevant questions. PMID:27633831

  8. Enrichments for phototrophic bacteria and characterization by morphology and pigment analysis

    NASA Technical Reports Server (NTRS)

    Brune, D.

    1985-01-01

    The purpose of this investigation was to examine several sulfide containing environments for the presence of phototrophic bacteria and to obtain enriched cultures of some of the bacteria present. The field sites were Alum Rock State Park, the Palo Alto salt marsh, the bay area salt ponds, and Big Soda Lake (near Fallon, Nevada). Bacteria from these sites were characterized by microscopic examination, measurement of in vitro absorption spectra, and analysis of carotenoid pigments. Field observations at one of the bay area salt ponds, in which the salt concentration was saturating (about 30 percent NaCl) and the sediments along the shore of the pond covered with a gypsum crust, revealed a layer of purple photosynthetic bacteria under a green layer in the gypsum crust. Samples of this gypsum crust were taken to the laboratory to measure light transmission through the crust and to try to identify the purple photosynthetic bacteria present in this extremely saline environment.

  9. Program Process, Costs and Consequences: A Comparative Analysis of YCCIP Enrichment, and a Guidebook for the Enrichment of Labor-Intensive Work Projects.

    ERIC Educational Resources Information Center

    Osoro and Associates, Bellingham, WA.

    This document contains (1) a monograph investigating and describing conditions under which it is cost-beneficial to operate an enriched YCCIP (Youth Community Conservation and Improvement Project) design and (2) a guidebook to work project enrichment. The first sections of the monograph focus on the attributes of an enriched YCCIP activity in…

  10. Subgroups of physically abusive parents based on cluster analysis of parenting behavior and affect.

    PubMed

    Haskett, Mary E; Scott, Susan Smith; Ward, Caryn Sabourin

    2004-10-01

    Cluster analysis of observed parenting and self-reported discipline was used to categorize 83 abusive parents into subgroups. A 2-cluster solution received support for validity. Cluster 1 parents were relatively warm, positive, sensitive, and engaged during interactions with their children, whereas Cluster 2 parents were relatively negative, disengaged or intrusive, and insensitive. Further, clusters differed in emotional health, parenting stress, perceptions of children, and problem solving. Children of parents in the 2 clusters differed on several indexes of social adjustment. Cluster 1 parents were similar to nonabusive parents (n = 66) on parenting and related constructs, but Cluster 2 parents differed from nonabusive parents on all clustering variables and many validation variables. Results highlight clinically relevant diversity in parenting practices and functioning among abusive parents.

  11. Highlights of the Merging Cluster Collaboration's Analysis of 26 Radio Relic Galaxy Cluster Mergers

    NASA Astrophysics Data System (ADS)

    Dawson, William; Golovich, Nathan; Wittman, David M.; Bradac, Marusa; Brüggen, Marcus; Bullock, James; Elbert, Oliver; Jee, James; Kaplinghat, Manoj; Kim, Stacy; Mahdavi, Andisheh; Merten, Julian; Ng, Karen; Annika, Peter; Rocha, Miguel E.; Sobral, David; Stroe, Andra; Van Weeren, Reinout J.; Merging Cluster Collaboration

    2016-01-01

    Merging galaxy clusters are now recognized as multifaceted probes providing unique insight into the properties of dark matter, the environmental impact of plasma shocks on galaxy evolution, and the physics of high energy particle acceleration. The Merging Cluster Collaboration has used the diffuse radio emission associated with the synchrotron radiation of relativistic particles accelerated by shocks generated during major cluster mergers (i.e. radio relics) to identify a homogenous sample of 26 galaxy cluster mergers. We have confirmed theoretical expectations that radio relics are predominantly associated with mergers occurring near the plane of the sky and at a relatively common merger phase; making them ideal probes of self-interacting dark matter, and eliminating much of the dominant uncertainty when relating the observed star formation rates to the event of the major cluster merger. We will highlight a number of the discovered common traits of this sample as well as detailed measurements of individual mergers.

  12. Comparative analysis of metagenomes from three methanogenic hydrocarbon-degrading enrichment cultures with 41 environmental samples

    PubMed Central

    Tan, Boonfei; Jane Fowler, S; Laban, Nidal Abu; Dong, Xiaoli; Sensen, Christoph W; Foght, Julia; Gieg, Lisa M

    2015-01-01

    Methanogenic hydrocarbon metabolism is a key process in subsurface oil reservoirs and hydrocarbon-contaminated environments and thus warrants greater understanding to improve current technologies for fossil fuel extraction and bioremediation. In this study, three hydrocarbon-degrading methanogenic cultures established from two geographically distinct environments and incubated with different hydrocarbon substrates (added as single hydrocarbons or as mixtures) were subjected to metagenomic and 16S rRNA gene pyrosequencing to test whether these differences affect the genetic potential and composition of the communities. Enrichment of different putative hydrocarbon-degrading bacteria in each culture appeared to be substrate dependent, though all cultures contained both acetate- and H2-utilizing methanogens. Despite differing hydrocarbon substrates and inoculum sources, all three cultures harbored genes for hydrocarbon activation by fumarate addition (bssA, assA, nmsA) and carboxylation (abcA, ancA), along with those for associated downstream pathways (bbs, bcr, bam), though the cultures incubated with hydrocarbon mixtures contained a broader diversity of fumarate addition genes. A comparative metagenomic analysis of the three cultures showed that they were functionally redundant despite their enrichment backgrounds, sharing multiple features associated with syntrophic hydrocarbon conversion to methane. In addition, a comparative analysis of the culture metagenomes with those of 41 environmental samples (containing varying proportions of methanogens) showed that the three cultures were functionally most similar to each other but distinct from other environments, including hydrocarbon-impacted environments (for example, oil sands tailings ponds and oil-affected marine sediments). This study provides a basis for understanding key functions and environmental selection in methanogenic hydrocarbon-associated communities. PMID:25734684

  13. Comparative analysis of metagenomes from three methanogenic hydrocarbon-degrading enrichment cultures with 41 environmental samples.

    PubMed

    Tan, Boonfei; Fowler, S Jane; Abu Laban, Nidal; Dong, Xiaoli; Sensen, Christoph W; Foght, Julia; Gieg, Lisa M

    2015-09-01

    Methanogenic hydrocarbon metabolism is a key process in subsurface oil reservoirs and hydrocarbon-contaminated environments and thus warrants greater understanding to improve current technologies for fossil fuel extraction and bioremediation. In this study, three hydrocarbon-degrading methanogenic cultures established from two geographically distinct environments and incubated with different hydrocarbon substrates (added as single hydrocarbons or as mixtures) were subjected to metagenomic and 16S rRNA gene pyrosequencing to test whether these differences affect the genetic potential and composition of the communities. Enrichment of different putative hydrocarbon-degrading bacteria in each culture appeared to be substrate dependent, though all cultures contained both acetate- and H2-utilizing methanogens. Despite differing hydrocarbon substrates and inoculum sources, all three cultures harbored genes for hydrocarbon activation by fumarate addition (bssA, assA, nmsA) and carboxylation (abcA, ancA), along with those for associated downstream pathways (bbs, bcr, bam), though the cultures incubated with hydrocarbon mixtures contained a broader diversity of fumarate addition genes. A comparative metagenomic analysis of the three cultures showed that they were functionally redundant despite their enrichment backgrounds, sharing multiple features associated with syntrophic hydrocarbon conversion to methane. In addition, a comparative analysis of the culture metagenomes with those of 41 environmental samples (containing varying proportions of methanogens) showed that the three cultures were functionally most similar to each other but distinct from other environments, including hydrocarbon-impacted environments (for example, oil sands tailings ponds and oil-affected marine sediments). This study provides a basis for understanding key functions and environmental selection in methanogenic hydrocarbon-associated communities.

  14. Characterization of the Mouse Brain Proteome Using Global Proteomic Analysis Complemented with Cysteinyl-Peptide Enrichment

    PubMed Central

    Wang, Haixing; Qian, Wei-Jun; Chin, Mark H.; Petyuk, Vladislav A.; Barry, Richard C.; Liu, Tao; Gritsenko, Marina A.; Mottaz, Heather M.; Moore, Ronald J.; Camp, David G.; Khan, Arshad H.; Smith, Desmond J.; Smith, Richard D.

    2007-01-01

    Given the growing interest in applying genomic and proteomic approaches for studying the mammalian brain using mouse models, we hereby present a global proteomic approach for analyzing brain tissue and for the first time a comprehensive characterization of the whole mouse brain proteome. Preparation of the whole brain sample incorporated a highly efficient cysteinyl-peptide enrichment (CPE) technique to complement a global enzymatic digestion method. Both the global and the cysteinyl-enriched peptide samples were analyzed by SCX fractionation coupled with reversed phase LC-MS/MS analysis. A total of 48,328 different peptides were confidently identified (>98% confidence level), covering 7792 non-redundant proteins (∼34% of the predicted mouse proteome). 1564 and 1859 proteins were identified exclusively from the cysteinyl-peptide and the global peptide samples, respectively, corresponding to 25% and 31% improvements in proteome coverage compared to analysis of only the global peptide or cysteinyl-peptide samples. The identified proteins provide a broad representation of the mouse proteome with little bias evident due to protein pI, molecular weight, and/or cellular localization. Approximately 26% of the identified proteins with gene ontology (GO) annotations were membrane proteins, with 1447 proteins predicted to have transmembrane domains, and many of the membrane proteins were found to be involved in transport and cell signaling. The MS/MS spectrum count information for the identified proteins was used to provide a measure of relative protein abundances. The mouse brain peptide/protein database generated from this study represents the most comprehensive proteome coverage for the mammalian brain to date, and the basis for future quantitative brain proteomic studies using mouse models. The proteomic approach presented here may have broad applications for rapid proteomic analyses of various mouse models of human brain diseases. PMID:16457602

  15. Symbolic clustering

    SciTech Connect

    Reinke, R.E.

    1991-01-01

    Clustering is the problem of finding a good organization for data. Because there are many kinds of clustering problems, and because there are many possible clusterings for any data set, clustering programs use knowledge and assumptions about individual problems to make clustering tractable. Cluster-analysis techniques allow knowledge to be expressed in the choice of a pairwise distance measure and in the choice of clustering algorithm. Conceptual clustering adds knowledge and preferences about cluster descriptions. In this study the author describes symbolic clustering, which adds representation choice to the set of ways a data analyst can use problem-specific knowledge. He develops an informal model for symbolic clustering, and uses it to suggest where and how knowledge can be expressed in clustering. A language for creating symbolic clusters, based on the model, was developed and tested on three real clustering problems. The study concludes with a discussion of the implications of the model and the results for clustering in general.

  16. Investigating Faculty Familiarity with Assessment Terminology by Applying Cluster Analysis to Interpret Survey Data

    ERIC Educational Resources Information Center

    Raker, Jeffrey R.; Holme, Thomas A.

    2014-01-01

    A cluster analysis was conducted with a set of survey data on chemistry faculty familiarity with 13 assessment terms. Cluster groupings suggest a high, middle, and low overall familiarity with the terminology and an independent high and low familiarity with terms related to fundamental statistics. The six resultant clusters were found to be…

  17. Cluster analysis of rural, urban, and curbside atmospheric particle size data.

    PubMed

    Beddows, David C S; Dall'Osto, Manuel; Harrison, Roy M

    2009-07-01

    Particle size is a key determinant of the hazard posed by airborne particles. Continuous multivariate particle size data have been collected using aerosol particle size spectrometers sited at four locations within the UK: Harwell (Oxfordshire); Regents Park (London); British Telecom Tower (London); and Marylebone Road (London). These data have been analyzed using k-means cluster analysis, deduced to be the preferred cluster analysis technique, selected from an option of four partitional cluster packages, namelythe following: Fuzzy; k-means; k-median; and Model-Based clustering. Using cluster validation indices k-means clustering was shown to produce clusters with the smallest size, furthest separation, and importantly the highest degree of similarity between the elements within each partition. Using k-means clustering, the complexity of the data set is reduced allowing characterization of the data according to the temporal and spatial trends of the clusters. At Harwell, the rural background measurement site, the cluster analysis showed that the spectra may be differentiated by their modal-diameters and average temporal trends showing either high counts during the day-time or night-time hours. Likewise for the urban sites, the cluster analysis differentiated the spectra into a small number of size distributions according their modal-diameter, the location of the measurement site, and time of day. The responsible aerosol emission, formation, and dynamic processes can be inferred according to the cluster characteristics and correlation to concurrently measured meteorological, gas phase, and particle phase measurements.

  18. The XMM Cluster Survey: optical analysis methodology and the first data release

    NASA Astrophysics Data System (ADS)

    Mehrtens, Nicola; Romer, A. Kathy; Hilton, Matt; Lloyd-Davies, E. J.; Miller, Christopher J.; Stanford, S. A.; Hosmer, Mark; Hoyle, Ben; Collins, Chris A.; Liddle, Andrew R.; Viana, Pedro T. P.; Nichol, Robert C.; Stott, John P.; Dubois, E. Naomi; Kay, Scott T.; Sahlén, Martin; Young, Owain; Short, C. J.; Christodoulou, L.; Watson, William A.; Davidson, Michael; Harrison, Craig D.; Baruah, Leon; Smith, Mathew; Burke, Claire; Mayers, Julian A.; Deadman, Paul-James; Rooney, Philip J.; Edmondson, Edward M.; West, Michael; Campbell, Heather C.; Edge, Alastair C.; Mann, Robert G.; Sabirli, Kivanc; Wake, David; Benoist, Christophe; da Costa, Luiz; Maia, Marcio A. G.; Ogando, Ricardo

    2012-06-01

    The XMM Cluster Survey (XCS) is a serendipitous search for galaxy clusters using all publicly available data in the XMM-Newton Science Archive. Its main aims are to measure cosmological parameters and trace the evolution of X-ray scaling relations. In this paper we present the first data release from the XMM Cluster Survey (XCS-DR1). This consists of 503 optically confirmed, serendipitously detected, X-ray clusters. Of these clusters, 256 are new to the literature and 357 are new X-ray discoveries. We present 463 clusters with a redshift estimate (0.06 < z < 1.46), including 261 clusters with spectroscopic redshifts. The remainder have photometric redshifts. In addition, we have measured X-ray temperatures (TX) for 401 clusters (0.4 < TX < 14.7 keV). We highlight seven interesting subsamples of XCS-DR1 clusters: (i) 10 clusters at high redshift (z > 1.0, including a new spectroscopically confirmed cluster at z= 1.01); (ii) 66 clusters with high TX (>5 keV) (iii) 130 clusters/groups with low TX (<2 keV) (iv) 27 clusters with measured TX values in the Sloan Digital Sky Survey (SDSS) ‘Stripe 82’ co-add region; (v) 77 clusters with measured TX values in the Dark Energy Survey region; (vi) 40 clusters detected with sufficient counts to permit mass measurements (under the assumption of hydrostatic equilibrium); (vii) 104 clusters that can be used for applications such as the derivation of cosmological parameters and the measurement of cluster scaling relations. The X-ray analysis methodology used to construct and analyse the XCS-DR1 cluster sample has been presented in a companion paper, Lloyd-Davies et al.

  19. A tripartite clustering analysis on microRNA, gene and disease model.

    PubMed

    Shen, Chengcheng; Liu, Ying

    2012-02-01

    Alteration of gene expression in response to regulatory molecules or mutations could lead to different diseases. MicroRNAs (miRNAs) have been discovered to be involved in regulation of gene expression and a wide variety of diseases. In a tripartite biological network of human miRNAs, their predicted target genes and the diseases caused by altered expressions of these genes, valuable knowledge about the pathogenicity of miRNAs, involved genes and related disease classes can be revealed by co-clustering miRNAs, target genes and diseases simultaneously. Tripartite co-clustering can lead to more informative results than traditional co-clustering with only two kinds of members and pass the hidden relational information along the relation chain by considering multi-type members. Here we report a spectral co-clustering algorithm for k-partite graph to find clusters with heterogeneous members. We use the method to explore the potential relationships among miRNAs, genes and diseases. The clusters obtained from the algorithm have significantly higher density than randomly selected clusters, which means members in the same cluster are more likely to have common connections. Results also show that miRNAs in the same family based on the hairpin sequences tend to belong to the same cluster. We also validate the clustering results by checking the correlation of enriched gene functions and disease classes in the same cluster. Finally, widely studied miR-17-92 and its paralogs are analyzed as a case study to reveal that genes and diseases co-clustered with the miRNAs are in accordance with current research findings. PMID:22809308

  20. A tripartite clustering analysis on microRNA, gene and disease model.

    PubMed

    Shen, Chengcheng; Liu, Ying

    2012-02-01

    Alteration of gene expression in response to regulatory molecules or mutations could lead to different diseases. MicroRNAs (miRNAs) have been discovered to be involved in regulation of gene expression and a wide variety of diseases. In a tripartite biological network of human miRNAs, their predicted target genes and the diseases caused by altered expressions of these genes, valuable knowledge about the pathogenicity of miRNAs, involved genes and related disease classes can be revealed by co-clustering miRNAs, target genes and diseases simultaneously. Tripartite co-clustering can lead to more informative results than traditional co-clustering with only two kinds of members and pass the hidden relational information along the relation chain by considering multi-type members. Here we report a spectral co-clustering algorithm for k-partite graph to find clusters with heterogeneous members. We use the method to explore the potential relationships among miRNAs, genes and diseases. The clusters obtained from the algorithm have significantly higher density than randomly selected clusters, which means members in the same cluster are more likely to have common connections. Results also show that miRNAs in the same family based on the hairpin sequences tend to belong to the same cluster. We also validate the clustering results by checking the correlation of enriched gene functions and disease classes in the same cluster. Finally, widely studied miR-17-92 and its paralogs are analyzed as a case study to reveal that genes and diseases co-clustered with the miRNAs are in accordance with current research findings.

  1. ToppGene Suite for gene list enrichment analysis and candidate gene prioritization

    PubMed Central

    Chen, Jing; Bardes, Eric E.; Aronow, Bruce J.; Jegga, Anil G.

    2009-01-01

    ToppGene Suite (http://toppgene.cchmc.org; this web site is free and open to all users and does not require a login to access) is a one-stop portal for (i) gene list functional enrichment, (ii) candidate gene prioritization using either functional annotations or network analysis and (iii) identification and prioritization of novel disease candidate genes in the interactome. Functional annotation-based disease candidate gene prioritization uses a fuzzy-based similarity measure to compute the similarity between any two genes based on semantic annotations. The similarity scores from individual features are combined into an overall score using statistical meta-analysis. A P-value of each annotation of a test gene is derived by random sampling of the whole genome. The protein–protein interaction network (PPIN)-based disease candidate gene prioritization uses social and Web networks analysis algorithms (extended versions of the PageRank and HITS algorithms, and the K-Step Markov method). We demonstrate the utility of ToppGene Suite using 20 recently reported GWAS-based gene–disease associations (including novel disease genes) representing five diseases. ToppGene ranked 19 of 20 (95%) candidate genes within the top 20%, while ToppNet ranked 12 of 16 (75%) candidate genes among the top 20%. PMID:19465376

  2. CAGEd-oPOSSUM: motif enrichment analysis from CAGE-derived TSSs

    PubMed Central

    Arenillas, David J.; Forrest, Alistair R. R.; Kawaji, Hideya; Lassmann, Timo; Wasserman, Wyeth W.; Mathelier, Anthony

    2016-01-01

    With the emergence of large-scale Cap Analysis of Gene Expression (CAGE) datasets from individual labs and the FANTOM consortium, one can now analyze the cis-regulatory regions associated with gene transcription at an unprecedented level of refinement. By coupling transcription factor binding site (TFBS) enrichment analysis with CAGE-derived genomic regions, CAGEd-oPOSSUM can identify TFs that act as key regulators of genes involved in specific mammalian cell and tissue types. The webtool allows for the analysis of CAGE-derived transcription start sites (TSSs) either provided by the user or selected from ∼1300 mammalian samples from the FANTOM5 project with pre-computed TFBS predicted with JASPAR TF binding profiles. The tool helps power insights into the regulation of genes through the study of the specific usage of TSSs within specific cell types and/or under specific conditions. Availability and Implementation: The CAGEd-oPOSUM web tool is implemented in Perl, MySQL and Apache and is available at http://cagedop.cmmt.ubc.ca/CAGEd_oPOSSUM. Contacts: anthony.mathelier@ncmm.uio.no or wyeth@cmmt.ubc.ca Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27334471

  3. Analysis of phytosterols and phytostanols in enriched dairy products by Fast gas chromatography with mass spectrometry.

    PubMed

    Inchingolo, Raffaella; Cardenia, Vladimiro; Rodriguez-Estrada, Maria Teresa

    2014-10-01

    A Fast gas chromatography and mass spectrometry method for plant sterols/stanols analysis was developed, using a short capillary gas chromatography column (10 m × 0.1 mm internal diameter × 0.1 μm film thickness) coated with 5% diphenyl-polysiloxane. A silylated mixture of the main plant sterols/stanols standards (β-sitosterol, campesterol, stigmasterol, campestanol, sitostanol) was well separated in 1.5 min, with a good peak resolution (>1.4, determined on a critical chromatographic peak pair (β-sitosterol and sitostanol)), repeatability (<13%), and sensitivity (<0.017 ng/mL). The suitability of this Fast chromatography method was tested on plant sterols/stanols-enriched dairy products (yogurt and milk), which were subjected to lipid extraction, cold saponification, and silylation prior to injection. The analytical performance (sensitivity < 0.256 ng/mL and repeatability < 10.36%) and significant reduction of the analysis time and consumables demonstrate that Fast gas chromatography-mass spectrometry method could be also employed for the plant sterols/stanols analysis in functional dairy products.

  4. Genome-wide enrichment analysis between endometriosis and obesity-related traits reveals novel susceptibility loci

    PubMed Central

    Rahmioglu, Nilufer; Macgregor, Stuart; Drong, Alexander W.; Hedman, Åsa K.; Harris, Holly R.; Randall, Joshua C.; Prokopenko, Inga; Nyholt, Dale R.; Morris, Andrew P.; Montgomery, Grant W.; Missmer, Stacey A.; Lindgren, Cecilia M.; Zondervan, Krina T.

    2015-01-01

    Endometriosis is a chronic inflammatory condition in women that results in pelvic pain and subfertility, and has been associated with decreased body mass index (BMI). Genetic variants contributing to the heritable component have started to emerge from genome-wide association studies (GWAS), although the majority remain unknown. Unexpectedly, we observed an intergenic locus on 7p15.2 that was genome-wide significantly associated with both endometriosis and fat distribution (waist-to-hip ratio adjusted for BMI; WHRadjBMI) in an independent meta-GWAS of European ancestry individuals. This led us to investigate the potential overlap in genetic variants underlying the aetiology of endometriosis, WHRadjBMI and BMI using GWAS data. Our analyses demonstrated significant enrichment of common variants between fat distribution and endometriosis (P = 3.7 × 10−3), which was stronger when we restricted the investigation to more severe (Stage B) cases (P = 4.5 × 10−4). However, no genetic enrichment was observed between endometriosis and BMI (P = 0.79). In addition to 7p15.2, we identify four more variants with statistically significant evidence of involvement in both endometriosis and WHRadjBMI (in/near KIFAP3, CAB39L, WNT4, GRB14); two of these, KIFAP3 and CAB39L, are novel associations for both traits. KIFAP3, WNT4 and 7p15.2 are associated with the WNT signalling pathway; formal pathway analysis confirmed a statistically significant (P = 6.41 × 10−4) overrepresentation of shared associations in developmental processes/WNT signalling between the two traits. Our results demonstrate an example of potential biological pleiotropy that was hitherto unknown, and represent an opportunity for functional follow-up of loci and further cross-phenotype comparisons to assess how fat distribution and endometriosis pathogenesis research fields can inform each other. PMID:25296917

  5. Outlier Identification in Model-Based Cluster Analysis

    PubMed Central

    Evans, Katie; Love, Tanzy; Thurston, Sally W.

    2015-01-01

    In model-based clustering based on normal-mixture models, a few outlying observations can influence the cluster structure and number. This paper develops a method to identify these, however it does not attempt to identify clusters amidst a large field of noisy observations. We identify outliers as those observations in a cluster with minimal membership proportion or for which the cluster-specific variance with and without the observation is very different. Results from a simulation study demonstrate the ability of our method to detect true outliers without falsely identifying many non-outliers and improved performance over other approaches, under most scenarios. We use the contributed R package MCLUST for model-based clustering, but propose a modified prior for the cluster-specific variance which avoids degeneracies in estimation procedures. We also compare results from our outlier method to published results on National Hockey League data. PMID:26806993

  6. Microarray Cluster Analysis of Irradiated Growth Plate Zones Following Laser Microdissection

    SciTech Connect

    Damron, Timothy A. Zhang Mingliang; Pritchard, Meredith R.; Middleton, Frank A.; Horton, Jason A.; Margulies, Bryan M.; Strauss, Judith A.; Farnum, Cornelia E.; Spadaro, Joseph A.

    2009-07-01

    Purpose: Genes and pathways involved in early growth plate chondrocyte recovery after fractionated irradiation were sought as potential targets for selective radiorecovery modulation. Materials and Methods: Three groups of six 5-week male Sprague-Dawley rats underwent fractionated irradiation to the right tibiae over 5 days, totaling 17.5 Gy, and then were killed at 7, 11, and 16 days after the first radiotherapy fraction. The growth plates were collected from the proximal tibiae bilaterally and subsequently underwent laser microdissection to separate reserve, perichondral, proliferative, and hypertrophic zones. Differential gene expression was analyzed between irradiated right and nonirradiated left tibia using RAE230 2.0 GeneChip microarray, compared between zones and time points and subjected to functional pathway cluster analysis with real-time polymerase chain reaction to confirm selected results. Results: Each zone had a number of pathways showing enrichment after the pattern of hypothesized importance to growth plate recovery, yet few met the strictest criteria. The proliferative and hypertrophic zones showed both the greatest number of genes with a 10-fold right/left change at 7 days after initiation of irradiation and enrichment of the most functional pathways involved in bone, cartilage, matrix, or skeletal development. Six genes confirmed by real-time polymerase chain reaction to have early upregulation included insulin-like growth factor 2, procollagen type I alpha 2, matrix metallopeptidase 9, parathyroid hormone receptor 1, fibromodulin, and aggrecan 1. Conclusions: Nine overlapping pathways in the proliferative and hypertrophic zones (skeletal development, ossification, bone remodeling, cartilage development, extracellular matrix structural constituent, proteinaceous extracellular matrix, collagen, extracellular matrix, and extracellular matrix part) may play key roles in early growth plate radiorecovery.

  7. Phenotypes of comorbidity in OSAS patients: combining categorical principal component analysis with cluster analysis.

    PubMed

    Vavougios, George D; George D, George; Pastaka, Chaido; Zarogiannis, Sotirios G; Gourgoulianis, Konstantinos I

    2016-02-01

    Phenotyping obstructive sleep apnea syndrome's comorbidity has been attempted for the first time only recently. The aim of our study was to determine phenotypes of comorbidity in obstructive sleep apnea syndrome patients employing a data-driven approach. Data from 1472 consecutive patient records were recovered from our hospital's database. Categorical principal component analysis and two-step clustering were employed to detect distinct clusters in the data. Univariate comparisons between clusters included one-way analysis of variance with Bonferroni correction and chi-square tests. Predictors of pairwise cluster membership were determined via a binary logistic regression model. The analyses revealed six distinct clusters: A, 'healthy, reporting sleeping related symptoms'; B, 'mild obstructive sleep apnea syndrome without significant comorbidities'; C1: 'moderate obstructive sleep apnea syndrome, obesity, without significant comorbidities'; C2: 'moderate obstructive sleep apnea syndrome with severe comorbidity, obesity and the exclusive inclusion of stroke'; D1: 'severe obstructive sleep apnea syndrome and obesity without comorbidity and a 33.8% prevalence of hypertension'; and D2: 'severe obstructive sleep apnea syndrome with severe comorbidities, along with the highest Epworth Sleepiness Scale score and highest body mass index'. Clusters differed significantly in apnea-hypopnea index, oxygen desaturation index; arousal index; age, body mass index, minimum oxygen saturation and daytime oxygen saturation (one-way analysis of variance P < 0.0001). Binary logistic regression indicated that older age, greater body mass index, lower daytime oxygen saturation and hypertension were associated independently with an increased risk of belonging in a comorbid cluster. Six distinct phenotypes of obstructive sleep apnea syndrome and its comorbidities were identified. Mapping the heterogeneity of the obstructive sleep apnea syndrome may help the early identification of at

  8. Cluster analysis application in research on pork quality determinants

    NASA Astrophysics Data System (ADS)

    Przybylski, W.; Wasiewicz, P.; Zieliński, P.; Gromadzka-Ostrowska, J.; Olczak, E.; Jaworska, D.; Niemyjski, S.; Santé-Lhoutellier, V.

    2010-09-01

    In this paper data mining methods were applied to investigate features determining high quality pork meat. The aim of the study was analysis of conditionality of the pork meat quality defined in coherence with HDL and LDL cholesterol concentration, plasma leptin, triglycerides, plasma glucose and serum. The research was carried out on 54 pigs. originated from crossbreeding of Naima sows with P76-PenArLan boars hybrids line. Meat quality parameters were evaluated in samples derived from the Longissimus (LD) muscle taken behind the last rib on the basis: the pH value, meat colour, drip loss, the RTN, intramuscular fat and glycolytic potential. The results of this study were elaborated by using R environment and show that cluster and regression analysis can be a useful tool for in-depth analysis of the determinants of the quality of pig meat in homogeneous populations of pigs. However, the question of determinants of the level of glycogen and fat in meat requires further research.

  9. Gene set enrichment analysis and ingenuity pathway analysis of metastatic clear cell renal cell carcinoma cell line.

    PubMed

    Khan, Mohammed I; Dębski, Konrad J; Dabrowski, Michał; Czarnecka, Anna M; Szczylik, Cezary

    2016-08-01

    In recent years, genome-wide RNA expression analysis has become a routine tool that offers a great opportunity to study and understand the key role of genes that contribute to carcinogenesis. Various microarray platforms and statistical approaches can be used to identify genes that might serve as prognostic biomarkers and be developed as antitumor therapies in the future. Metastatic renal cell carcinoma (mRCC) is a serious, life-threatening disease, and there are few treatment options for patients. In this study, we performed one-color microarray gene expression (4×44K) analysis of the mRCC cell line Caki-1 and the healthy kidney cell line ASE-5063. A total of 1,921 genes were differentially expressed in the Caki-1 cell line (1,023 upregulated and 898 downregulated). Gene Set Enrichment Analysis (GSEA) and Ingenuity Pathway Analysis (IPA) approaches were used to analyze the differential-expression data. The objective of this research was to identify complex biological changes that occur during metastatic development using Caki-1 as a model mRCC cell line. Our data suggest that there are multiple deregulated pathways associated with metastatic clear cell renal cell carcinoma (mccRCC), including integrin-linked kinase (ILK) signaling, leukocyte extravasation signaling, IGF-I signaling, CXCR4 signaling, and phosphoinositol 3-kinase/AKT/mammalian target of rapamycin signaling. The IPA upstream analysis predicted top transcriptional regulators that are either activated or inhibited, such as estrogen receptors, TP53, KDM5B, SPDEF, and CDKN1A. The GSEA approach was used to further confirm enriched pathway data following IPA.

  10. A Meta-Analysis of the Effects of Enrichment Programs on Gifted Students

    ERIC Educational Resources Information Center

    Kim, Mihyeon

    2016-01-01

    Although descriptions of enrichment programs are valuable for practitioners, practices, and services for gifted students, they must be backed by evidence, derived through a synthesis of research. This study examined research on enrichment programs serving gifted students and synthesized the current studies between 1985 and 2014 on the effects of…

  11. Defining the optimal animal model for translational research using gene set enrichment analysis.

    PubMed

    Weidner, Christopher; Steinfath, Matthias; Opitz, Elisa; Oelgeschläger, Michael; Schönfelder, Gilbert

    2016-01-01

    The mouse is the main model organism used to study the functions of human genes because most biological processes in the mouse are highly conserved in humans. Recent reports that compared identical transcriptomic datasets of human inflammatory diseases with datasets from mouse models using traditional gene-to-gene comparison techniques resulted in contradictory conclusions regarding the relevance of animal models for translational research. To reduce susceptibility to biased interpretation, all genes of interest for the biological question under investigation should be considered. Thus, standardized approaches for systematic data analysis are needed. We analyzed the same datasets using gene set enrichment analysis focusing on pathways assigned to inflammatory processes in either humans or mice. The analyses revealed a moderate overlap between all human and mouse datasets, with average positive and negative predictive values of 48 and 57% significant correlations. Subgroups of the septic mouse models (i.e., Staphylococcus aureus injection) correlated very well with most human studies. These findings support the applicability of targeted strategies to identify the optimal animal model and protocol to improve the success of translational research. PMID:27311961

  12. Enrichment of Root Endophytic Bacteria from Populus deltoides and Single-Cell-Genomics Analysis

    DOE PAGES

    Utturkar, Sagar M.; Cude, W. Nathan; Robeson, Jr., Michael S.; Yang, Zamin Koo; Klingeman, Dawn Marie; Land, Miriam L.; Allman, Steve L.; Lu, Tse-Yuan S.; Brown, Steven D.; Schadt, Christopher Warren; et al

    2016-07-15

    Bacterial endophytes that colonize Populus trees contribute to nutrient acquisition, prime immunity responses, and directly or indirectly increase both above- and below-ground biomasses. Endophytes are embedded within plant material, so physical separation and isolation are difficult tasks. Application of culture-independent methods, such as metagenome or bacterial transcriptome sequencing, has been limited due to the predominance of DNA from the plant biomass. In this paper, we present a modified differential and density gradient centrifugation-based protocol for the separation of endophytic bacteria from Populus roots. This protocol achieved substantial reduction in contaminating plant DNA, allowed enrichment of endophytic bacteria away from themore » plant material, and enabled single-cell genomics analysis. Four single-cell genomes were selected for whole-genome amplification based on their rarity in the microbiome (potentially uncultured taxa) as well as their inferred abilities to form associations with plants. Bioinformatics analyses, including assembly, contamination removal, and completeness estimation, were performed to obtain single-amplified genomes (SAGs) of organisms from the phyla Armatimonadetes, Verrucomicrobia, and Planctomycetes, which were unrepresented in our previous cultivation efforts. Finally, comparative genomic analysis revealed unique characteristics of each SAG that could facilitate future cultivation efforts for these bacteria.« less

  13. AVES: A Computer Cluster System approach for INTEGRAL Scientific Analysis

    NASA Astrophysics Data System (ADS)

    Federici, M.; Martino, B. L.; Natalucci, L.; Umbertini, P.

    The AVES computing system, based on an "Cluster" architecture is a fully integrated, low cost computing facility dedicated to the archiving and analysis of the INTEGRAL data. AVES is a modular system that uses the software resource manager (SLURM) and allows almost unlimited expandibility (65,536 nodes and hundreds of thousands of processors); actually is composed by 30 Personal Computers with Quad-Cores CPU able to reach the computing power of 300 Giga Flops (300x10{9} Floating point Operations Per Second), with 120 GB of RAM and 7.5 Tera Bytes (TB) of storage memory in UFS configuration plus 6 TB for users area. AVES was designed and built to solve growing problems raised from the analysis of the large data amount accumulated by the INTEGRAL mission (actually about 9 TB) and due to increase every year. The used analysis software is the OSA package, distributed by the ISDC in Geneva. This is a very complex package consisting of dozens of programs that can not be converted to parallel computing. To overcome this limitation we developed a series of programs to distribute the workload analysis on the various nodes making AVES automatically divide the analysis in N jobs sent to N cores. This solution thus produces a result similar to that obtained by the parallel computing configuration. In support of this we have developed tools that allow a flexible use of the scientific software and quality control of on-line data storing. The AVES software package is constituted by about 50 specific programs. Thus the whole computing time, compared to that provided by a Personal Computer with single processor, has been enhanced up to a factor 70.

  14. A Laser-Based Method for On-Site Analysis of UF6 at Enrichment Plants

    SciTech Connect

    Anheier, Norman C.; Cannon, Bret D.; Martinez, Alonzo; Barrett, Christopher A.; Taubman, Matthew S.; Anderson, Kevin K.; Smith, Leon E.

    2014-11-23

    The International Atomic Energy Agency’s (IAEA’s) long-term research and development plan calls for more cost-effective and efficient safeguard methods to detect and deter misuse of gaseous centrifuge enrichment plants (GCEPs). The IAEA’s current safeguards approaches at GCEPs are based on a combination of routine and random inspections that include environmental sampling and destructive assay (DA) sample collection from UF6 in-process material and selected cylinders. Samples are then shipped offsite for subsequent laboratory analysis. In this paper, a new DA sample collection and onsite analysis approach that could help to meet challenges in transportation and chain of custody for UF6 DA samples is introduced. This approach uses a handheld sampler concept and a Laser Ablation, Laser Absorbance Spectrometry (LAARS) analysis instrument, both currently under development at the Pacific Northwest National Laboratory. A LAARS analysis instrument could be temporarily or permanently deployed in the IAEA control room of the facility, in the IAEA data acquisition cabinet, for example. The handheld PNNL DA sampler design collects and stabilizes a much smaller DA sample mass compared to current sampling methods. The significantly lower uranium mass reduces the sample radioactivity and the stabilization approach diminishes the risk of uranium and hydrogen fluoride release. These attributes enable safe sample handling needed during onsite LAARS assay and may help ease shipping challenges for samples to be processed at the IAEA’s offsite laboratory. The LAARS and DA sampler implementation concepts will be described and preliminary technical viability results presented.

  15. Combined clustering models for the analysis of gene expression

    SciTech Connect

    Angelova, M. Ellman, J.

    2010-02-15

    Clustering has become one of the fundamental tools for analyzing gene expression and producing gene classifications. Clustering models enable finding patterns of similarity in order to understand gene function, gene regulation, cellular processes and sub-types of cells. The clustering results however have to be combined with sequence data or knowledge about gene functionality in order to make biologically meaningful conclusions. In this work, we explore a new model that integrates gene expression with sequence or text information.

  16. miR2Gene: pattern discovery of single gene, multiple genes, and pathways by enrichment analysis of their microRNA regulators

    PubMed Central

    2011-01-01

    Background In recent years, a number of tools have been developed to explore microRNAs (miRNAs) by analyzing their target genes. However, a reverse problem, that is, inferring patterns of protein-coding genes through their miRNA regulators, has not been explored. As various miRNA annotation data become available, exploring gene patterns by analyzing the prior knowledge of their miRNA regulators is becoming more feasible. Results In this study, we developed a tool, miR2Gene, for this purpose. Various sets of miRNAs, according to prior rules such as function, associated disease, tissue specificity, family, and cluster, were integrated with miR2Gene. For given genes, miR2Gene evaluates the enrichment of the predicted miRNAs that regulate them in each miRNA set. This tool can be used for single genes, multiple genes, and KEGG pathways. For the KEGG pathway, genes with enriched miRNA sets are highlighted according to various rules. We confirmed the usefulness of miR2Gene through case studies. Conclusions miR2Gene represents a novel and useful tool that integrates miRNA knowledge for protein-coding gene analysis. miR2Gene is freely available at http://cmbi.hsc.pku.edu.cn/mir2gene. PMID:22784580

  17. Fuzzy and hard clustering analysis for thyroid disease.

    PubMed

    Azar, Ahmad Taher; El-Said, Shaimaa Ahmed; Hassanien, Aboul Ella

    2013-07-01

    Thyroid hormones produced by the thyroid gland help regulation of the body's metabolism. A variety of methods have been proposed in the literature for thyroid disease classification. As far as we know, clustering techniques have not been used in thyroid diseases data set so far. This paper proposes a comparison between hard and fuzzy clustering algorithms for thyroid diseases data set in order to find the optimal number of clusters. Different scalar validity measures are used in comparing the performances of the proposed clustering systems. To demonstrate the performance of each algorithm, the feature values that represent thyroid disease are used as input for the system. Several runs are carried out and recorded with a different number of clusters being specified for each run (between 2 and 11), so as to establish the optimum number of clusters. To find the optimal number of clusters, the so-called elbow criterion is applied. The experimental results revealed that for all algorithms, the elbow was located at c=3. The clustering results for all algorithms are then visualized by the Sammon mapping method to find a low-dimensional (normally 2D or 3D) representation of a set of points distributed in a high dimensional pattern space. At the end of this study, some recommendations are formulated to improve determining the actual number of clusters present in the data set. PMID:23357404

  18. Study on Cluster Analysis Used with Laser-Induced Breakdown Spectroscopy

    NASA Astrophysics Data System (ADS)

    He, Li'ao; Wang, Qianqian; Zhao, Yu; Liu, Li; Peng, Zhong

    2016-06-01

    Supervised learning methods (eg. PLS-DA, SVM, etc.) have been widely used with laser-induced breakdown spectroscopy (LIBS) to classify materials; however, it may induce a low correct classification rate if a test sample type is not included in the training dataset. Unsupervised cluster analysis methods (hierarchical clustering analysis, K-means clustering analysis, and iterative self-organizing data analysis technique) are investigated in plastics classification based on the line intensities of LIBS emission in this paper. The results of hierarchical clustering analysis using four different similarity measuring methods (single linkage, complete linkage, unweighted pair-group average, and weighted pair-group average) are compared. In K-means clustering analysis, four kinds of choosing initial centers methods are applied in our case and their results are compared. The classification results of hierarchical clustering analysis, K-means clustering analysis, and ISODATA are analyzed. The experiment results demonstrated cluster analysis methods can be applied to plastics discrimination with LIBS. supported by Beijing Natural Science Foundation of China (No. 4132063)

  19. Transmutation Analysis of Enriched Uranium and Deep Burn High Temperature Reactors

    SciTech Connect

    Michael A. Pope

    2012-07-01

    High temperature reactors (HTRs) have been under consideration for production of electricity, process heat, and for destruction of transuranics for decades. As part of the transmutation analysis efforts within the Fuel Cycle Research and Development (FCR&D) campaign, a need was identified for detailed discharge isotopics from HTRs for use in the VISION code. A conventional HTR using enriched uranium in UCO fuel was modeled having discharge burnup of 120 GWd/MTiHM. Also, a deep burn HTR (DB-HTR) was modeled burning transuranic (TRU)-only TRU-O2 fuel to a discharge burnup of 648 GWd/MTiHM. For each of these cases, unit cell depletion calculations were performed with SCALE/TRITON. Unit cells were used to perform this analysis using SCALE 6.1. Because of the long mean free paths (and migration lengths) of neutrons in HTRs, using a unit cell to represent a whole core can be non-trivial. The sizes of these cells were first set by using Serpent calculations to match a spectral index between unit cell and whole core domains. In the case of the DB-HTR, the unit cell which was arrived at in this way conserved the ratio of fuel to moderator found in a single block of fuel. In the conventional HTR case, a larger moderator-to-fuel ratio than that of a single block was needed to simulate the whole core spectrum. Discharge isotopics (for 500 nuclides) and one-group cross-sections (for 1022 nuclides) were delivered to the transmutation analysis team. This report provides documentation for these calculations. In addition to the discharge isotopics, one-group cross-sections were provided for the full list of 1022 nuclides tracked in the transmutation library.

  20. Tracking Difference in Gene Expression in a Time-Course Experiment Using Gene Set Enrichment Analysis

    PubMed Central

    Wong, Pui Shan; Tanaka, Michihiro; Sunaga, Yoshihiko; Tanaka, Masayoshi; Taniguchi, Takeaki; Yoshino, Tomoko; Tanaka, Tsuyoshi; Fujibuchi, Wataru; Aburatani, Sachiyo

    2014-01-01

    Fistulifera sp. strain JPCC DA0580 is a newly sequenced pennate diatom that is capable of simultaneously growing and accumulating lipids. This is a unique trait, not found in other related microalgae so far. It is able to accumulate between 40 to 60% of its cell weight in lipids, making it a strong candidate for the production of biofuel. To investigate this characteristic, we used RNA-Seq data gathered at four different times while Fistulifera sp. strain JPCC DA0580 was grown in oil accumulating and non-oil accumulating conditions. We then adapted gene set enrichment analysis (GSEA) to investigate the relationship between the difference in gene expression of 7,822 genes and metabolic functions in our data. We utilized information in the KEGG pathway database to create the gene sets and changed GSEA to use re-sampling so that data from the different time points could be included in the analysis. Our GSEA method identified photosynthesis, lipid synthesis and amino acid synthesis related pathways as processes that play a significant role in oil production and growth in Fistulifera sp. strain JPCC DA0580. In addition to GSEA, we visualized the results by creating a network of compounds and reactions, and plotted the expression data on top of the network. This made existing graph algorithms available to us which we then used to calculate a path that metabolizes glucose into triacylglycerol (TAG) in the smallest number of steps. By visualizing the data this way, we observed a separate up-regulation of genes at different times instead of a concerted response. We also identified two metabolic paths that used less reactions than the one shown in KEGG and showed that the reactions were up-regulated during the experiment. The combination of analysis and visualization methods successfully analyzed time-course data, identified important metabolic pathways and provided new hypotheses for further research. PMID:25268590

  1. Towards Effective Clustering Techniques for the Analysis of Electric Power Grids

    SciTech Connect

    Hogan, Emilie A.; Cotilla Sanchez, Jose E.; Halappanavar, Mahantesh; Wang, Shaobu; Mackey, Patrick S.; Hines, Paul; Huang, Zhenyu

    2013-11-30

    Clustering is an important data analysis technique with numerous applications in the analysis of electric power grids. Standard clustering techniques are oblivious to the rich structural and dynamic information available for power grids. Therefore, by exploiting the inherent topological and electrical structure in the power grid data, we propose new methods for clustering with applications to model reduction, locational marginal pricing, phasor measurement unit (PMU or synchrophasor) placement, and power system protection. We focus our attention on model reduction for analysis based on time-series information from synchrophasor measurement devices, and spectral techniques for clustering. By comparing different clustering techniques on two instances of realistic power grids we show that the solutions are related and therefore one could leverage that relationship for a computational advantage. Thus, by contrasting different clustering techniques we make a case for exploiting structure inherent in the data with implications for several domains including power systems.

  2. Multidimensional cluster stability analysis from a Brazilian Bradyrhizobium sp. RFLP/PCR data set

    NASA Astrophysics Data System (ADS)

    Milagre, S. T.; Maciel, C. D.; Shinoda, A. A.; Hungria, M.; Almeida, J. R. B.

    2009-05-01

    The taxonomy of the N2-fixing bacteria belonging to the genus Bradyrhizobium is still poorly refined, mainly due to conflicting results obtained by the analysis of the phenotypic and genotypic properties. This paper presents an application of a method aiming at the identification of possible new clusters within a Brazilian collection of 119 Bradyrhizobium strains showing phenotypic characteristics of B. japonicum and B. elkanii. The stability was studied as a function of the number of restriction enzymes used in the RFLP-PCR analysis of three ribosomal regions with three restriction enzymes per region. The method proposed here uses clustering algorithms with distances calculated by average-linkage clustering. Introducing perturbations using sub-sampling techniques makes the stability analysis. The method showed efficacy in the grouping of the species B. japonicum and B. elkanii. Furthermore, two new clusters were clearly defined, indicating possible new species, and sub-clusters within each detected cluster.

  3. Investigating Regional Disparities of China's Human Development with Cluster Analysis: A Historical Perspective

    ERIC Educational Resources Information Center

    Yang, Yongheng; Hu, Angang

    2008-01-01

    This paper adopts both one-dimensional and multi-dimensional cluster analysis to analyze China's HDI data for 1982, 1995, 1999, and 2003, and to classify China's provinces into four tiers based on the three basic developmental aspects embedded in HDI. The classifications by cluster analysis depends on the observations' similarities with respect to…

  4. Tracking Undergraduate Student Achievement in a First-Year Physiology Course Using a Cluster Analysis Approach

    ERIC Educational Resources Information Center

    Brown, S. J.; White, S.; Power, N.

    2015-01-01

    A cluster analysis data classification technique was used on assessment scores from 157 undergraduate nursing students who passed 2 successive compulsory courses in human anatomy and physiology. Student scores in five summative assessment tasks, taken in each of the courses, were used as inputs for a cluster analysis procedure. We aimed to group…

  5. An enriched 1D finite element for the buckling analysis of sandwich beam-columns

    NASA Astrophysics Data System (ADS)

    Sad Saoud, Kahina; Le Grognec, Philippe

    2016-06-01

    Sandwich constructions have been widely used during the last few decades in various practical applications, especially thanks to the attractive compromise between a lightweight and high mechanical properties. Nevertheless, despite the advances achieved to date, buckling still remains a major failure mode for sandwich materials which often fatally leads to collapse. Recently, one of the authors derived closed-form analytical solutions for the buckling analysis of sandwich beam-columns under compression or pure bending. These solutions are based on a specific hybrid formulation where the faces are represented by Euler-Bernoulli beams and the core layer is described as a 2D continuous medium. When considering more complex loadings or non-trivial boundary conditions, closed-form solutions are no more available and one must resort to numerical models. Instead of using a 2D computationally expensive model, the present paper aims at developing an original enriched beam finite element. It is based on the previous analytical formulation, insofar as the skin layers are modeled by Timoshenko beams whereas the displacement fields in the core layer are described by means of hyperbolic functions, in accordance with the modal displacement fields obtained analytically. By using this 1D finite element, linearized buckling analyses are performed for various loading cases, whose results are confronted to either analytical or numerical reference solutions, for validation purposes.

  6. Weighted Kolmogorov Smirnov testing: an alternative for Gene Set Enrichment Analysis.

    PubMed

    Charmpi, Konstantina; Ycart, Bernard

    2015-06-01

    Gene Set Enrichment Analysis (GSEA) is a basic tool for genomic data treatment. Its test statistic is based on a cumulated weight function, and its distribution under the null hypothesis is evaluated by Monte-Carlo simulation. Here, it is proposed to subtract to the cumulated weight function its asymptotic expectation, then scale it. Under the null hypothesis, the convergence in distribution of the new test statistic is proved, using the theory of empirical processes. The limiting distribution needs to be computed only once, and can then be used for many different gene sets. This results in large savings in computing time. The test defined in this way has been called Weighted Kolmogorov Smirnov (WKS) test. Using expression data from the GEO repository, tested against the MSig Database C2, a comparison between the classical GSEA test and the new procedure has been conducted. Our conclusion is that, beyond its mathematical and algorithmic advantages, the WKS test could be more informative in many cases, than the classical GSEA test.

  7. Proteomic analysis of ethene-enriched groundwater microcosms from a vinyl chloride-contaminated site.

    PubMed

    Chuang, Adina S; Jin, Yang Oh; Schmidt, Laura S; Li, Yalan; Fogel, Samuel; Smoler, Donna; Mattes, Timothy E

    2010-03-01

    Contamination of groundwater with vinyl chloride (VC), a known human carcinogen, is a common environmental problem at plastics manufacturing, dry cleaning, and military sites. At many sites, there is the potential to cleanup VC groundwater plumes with aerobic VC-oxidizing microorganisms (e.g., methanotrophs, etheneotrophs, and VC-assimilating bacteria). Environmental biotechnologies that reveal the presence and activity of VC-oxidizing bacteria in contaminated groundwater samples would provide valuable lines of evidence that bioremediation of VC is occurring at a site. We applied targeted shotgun mass spectrometry-based proteomic methods to ethene-enriched groundwater microcosms from a VC-contaminated site. Polypeptides from the enzymes alkene monooxygenase (EtnC) and epoxyalkane:CoM transferase (EtnE), both of which are expressed by aerobic etheneotrophs and VC-assimilating bacteria, were identified in 7 of the 14 samples analyzed. Bioinformatic analysis revealed that 2 EtnC and 5 EtnE peptides were unique to deduced EtnC and EtnE sequences from two different cultivated strains. In addition, several partial EtnE genes sequenced from microcosms matched with observed EtnE peptides. Our results have revealed broader etheneotroph functional gene diversity and demonstrate the feasibility, speed, and accuracy of applying a targeted metaproteomics approach to identifying protein biomarkers from etheneotrophs in complex environmental samples.

  8. Multilevel Analysis Methods for Partially Nested Cluster Randomized Trials

    ERIC Educational Resources Information Center

    Sanders, Elizabeth A.

    2011-01-01

    This paper explores multilevel modeling approaches for 2-group randomized experiments in which a treatment condition involving clusters of individuals is compared to a control condition involving only ungrouped individuals, otherwise known as partially nested cluster randomized designs (PNCRTs). Strategies for comparing groups from a PNCRT in the…

  9. Alternatives to Multilevel Modeling for the Analysis of Clustered Data

    ERIC Educational Resources Information Center

    Huang, Francis L.

    2016-01-01

    Multilevel modeling has grown in use over the years as a way to deal with the nonindependent nature of observations found in clustered data. However, other alternatives to multilevel modeling are available that can account for observations nested within clusters, including the use of Taylor series linearization for variance estimation, the design…

  10. Detecting Hotspots from Taxi Trajectory Data Using Spatial Cluster Analysis

    NASA Astrophysics Data System (ADS)

    Zhao, P. X.; Qin, K.; Zhou, Q.; Liu, C. K.; Chen, Y. X.

    2015-07-01

    A method of trajectory clustering based on decision graph and data field is proposed in this paper. The method utilizes data field to describe spatial distribution of trajectory points, and uses decision graph to discover cluster centres. It can automatically determine cluster parameters and is suitable to trajectory clustering. The method is applied to trajectory clustering on taxi trajectory data, which are on the holiday (May 1st, 2014), weekday (Wednesday, May 7th, 2014) and weekend (Saturday, May 10th, 2014) respectively, in Wuhan City, China. The hotspots in four hours (8:00-9:00, 12:00-13:00, 18:00-19:00 and 23:00-24:00) for three days are discovered and visualized in heat maps. In the future, we will further research the spatiotemporal distribution and laws of these hotspots, and use more data to carry out the experiments.

  11. Two worlds collide: Image analysis methods for quantifying structural variation in cluster molecular dynamics

    SciTech Connect

    Steenbergen, K. G.; Gaston, N.

    2014-02-14

    Inspired by methods of remote sensing image analysis, we analyze structural variation in cluster molecular dynamics (MD) simulations through a unique application of the principal component analysis (PCA) and Pearson Correlation Coefficient (PCC). The PCA analysis characterizes the geometric shape of the cluster structure at each time step, yielding a detailed and quantitative measure of structural stability and variation at finite temperature. Our PCC analysis captures bond structure variation in MD, which can be used to both supplement the PCA analysis as well as compare bond patterns between different cluster sizes. Relying only on atomic position data, without requirement for a priori structural input, PCA and PCC can be used to analyze both classical and ab initio MD simulations for any cluster composition or electronic configuration. Taken together, these statistical tools represent powerful new techniques for quantitative structural characterization and isomer identification in cluster MD.

  12. Enrichment of amino acid-oxidizing, acetate-reducing bacteria.

    PubMed

    Ato, Makoto; Ishii, Masaharu; Igarashi, Yasuo

    2014-08-01

    In anaerobic condition, amino acids are oxidatively deaminated, and decarboxylated, resulting in the production of volatile fatty acids. In this process, excess electrons are produced and their consumption is necessary for the accomplishment of amino acid degradation. In this study, we anaerobically constructed leucine-degrading enrichment cultures from three different environmental samples (compost, excess sludge, and rice field soil) in order to investigate the diversity of electron-consuming reaction coupled to amino acid oxidation. Constructed enrichment cultures oxidized leucine to isovalerate and their activities were strongly dependent on acetate. Analysis of volatile fatty acids (VFAs) profiles and community structure analysis during batch culture of each enrichment indicated that Clostridium cluster I coupled leucine oxidation to acetate reduction in the enrichment from the compost and the rice field soil. In these cases, acetate was reduced to butyrate. On the other hand, Clostridium cluster XIVb coupled leucine oxidation to acetate reduction in the enrichment from the excess sludge. In this case, acetate was reduced to propionate. To our surprise, the enrichment from rice field soil oxidized leucine even in the absence of acetate and produced butyrate. The enrichment would couple leucine oxidation to reductive butyrate synthesis from CO2. The coupling reaction would be achieved based on trophic link between hydrogenotrophic acetogenic bacteria and acetate-reducing bacteria by sequential reduction of CO2 and acetate. Our study suggests anaerobic degradation of amino acids is achieved yet-to-be described reactions. PMID:24630616

  13. Enrichment of Root Endophytic Bacteria from Populus deltoides and Single-Cell-Genomics Analysis

    PubMed Central

    Utturkar, Sagar M.; Cude, W. Nathan; Robeson, Michael S.; Yang, Zamin K.; Klingeman, Dawn M.; Land, Miriam L.; Allman, Steve L.; Lu, Tse-Yuan S.; Brown, Steven D.; Schadt, Christopher W.; Podar, Mircea; Doktycz, Mitchel J.

    2016-01-01

    ABSTRACT Bacterial endophytes that colonize Populus trees contribute to nutrient acquisition, prime immunity responses, and directly or indirectly increase both above- and below-ground biomasses. Endophytes are embedded within plant material, so physical separation and isolation are difficult tasks. Application of culture-independent methods, such as metagenome or bacterial transcriptome sequencing, has been limited due to the predominance of DNA from the plant biomass. Here, we describe a modified differential and density gradient centrifugation-based protocol for the separation of endophytic bacteria from Populus roots. This protocol achieved substantial reduction in contaminating plant DNA, allowed enrichment of endophytic bacteria away from the plant material, and enabled single-cell genomics analysis. Four single-cell genomes were selected for whole-genome amplification based on their rarity in the microbiome (potentially uncultured taxa) as well as their inferred abilities to form associations with plants. Bioinformatics analyses, including assembly, contamination removal, and completeness estimation, were performed to obtain single-amplified genomes (SAGs) of organisms from the phyla Armatimonadetes, Verrucomicrobia, and Planctomycetes, which were unrepresented in our previous cultivation efforts. Comparative genomic analysis revealed unique characteristics of each SAG that could facilitate future cultivation efforts for these bacteria. IMPORTANCE Plant roots harbor a diverse collection of microbes that live within host tissues. To gain a comprehensive understanding of microbial adaptations to this endophytic lifestyle from strains that cannot be cultivated, it is necessary to separate bacterial cells from the predominance of plant tissue. This study provides a valuable approach for the separation and isolation of endophytic bacteria from plant root tissue. Isolated live bacteria provide material for microbiome sequencing, single-cell genomics, and analyses

  14. Visual Cluster Analysis in Support of Clinical Decision Intelligence

    PubMed Central

    Gotz, David; Sun, Jimeng; Cao, Nan; Ebadollahi, Shahram

    2011-01-01

    Electronic health records (EHRs) contain a wealth of information about patients. In addition to providing efficient and accurate records for individual patients, large databases of EHRs contain valuable information about overall patient populations. While statistical insights describing an overall population are beneficial, they are often not specific enough to use as the basis for individualized patient-centric decisions. To address this challenge, we describe an approach based on patient similarity which analyzes an EHR database to extract a cohort of patient records most similar to a specific target patient. Clusters of similar patients are then visualized to allow interactive visual refinement by human experts. Statistics are then extracted from the refined patient clusters and displayed to users. The statistical insights taken from these refined clusters provide personalized guidance for complex decisions. This paper focuses on the cluster refinement stage where an expert user must interactively (a) judge the quality and contents of automatically generated similar patient clusters, and (b) refine the clusters based on his/her expertise. We describe the DICON visualization tool which allows users to interactively view and refine multidimensional similar patient clusters. We also present results from a preliminary evaluation where two medical doctors provided feedback on our approach. PMID:22195102

  15. Topological Analysis of Emerging Bipole Clusters Producing Violent Solar Events

    NASA Astrophysics Data System (ADS)

    Mandrini, C. H.; Schmieder, B.; Démoulin, P.; Guo, Y.; Cristiani, G. D.

    2014-06-01

    During the rising phase of Solar Cycle 24 tremendous activity occurred on the Sun with rapid and compact emergence of magnetic flux leading to bursts of flares (C to M and even X-class). We investigate the violent events occurring in the cluster of two active regions (ARs), NOAA numbers 11121 and 11123, observed in November 2010 with instruments onboard the Solar Dynamics Observatory and from Earth. Within one day the total magnetic flux increased by 70 % with the emergence of new groups of bipoles in AR 11123. From all the events on 11 November, we study, in particular, the ones starting at around 07:16 UT in GOES soft X-ray data and the brightenings preceding them. A magnetic-field topological analysis indicates the presence of null points, associated separatrices, and quasi-separatrix layers (QSLs) where magnetic reconnection is prone to occur. The presence of null points is confirmed by a linear and a non-linear force-free magnetic-field model. Their locations and general characteristics are similar in both modelling approaches, which supports their robustness. However, in order to explain the full extension of the analysed event brightenings, which are not restricted to the photospheric traces of the null separatrices, we compute the locations of QSLs. Based on this more complete topological analysis, we propose a scenario to explain the origin of a low-energy event preceding a filament eruption, which is accompanied by a two-ribbon flare, and a consecutive confined flare in AR 11123. The results of our topology computation can also explain the locations of flare ribbons in two other events, one preceding and one following the ones at 07:16 UT. Finally, this study provides further examples where flare-ribbon locations can be explained when compared to QSLs and only, partially, when using separatrices.

  16. Selecting representative climate simulations for impact studies using cluster analysis

    NASA Astrophysics Data System (ADS)

    Mendlik, Thomas; Gobiet, Andreas

    2013-04-01

    In climate change impact research it is crucial to carefully select the climatic input in order to realistically represent the uncertainty in climate scenarios. Usually, the selection of a few simulations as input for the impact investigation is mostly based on subjective expert judgment. However, a more sophisticated objective approach should consider the fact that these climate simulations stem from an ensemble of opportunity, which might inherit model inter-dependencies and biases. Such objective methods for sub-sampling climate simulations from a larger ensemble receive relatively small attention in scientific literature. This study represents one possible framework to aid selecting representative climate simulations for specific climate impact studies. By doing so, model interdependence is taken into account, leading to a more reliable ensemble. Multivariate statistical methods are used to describe model dependence based on the spatial patterns of their climate change signals. Several meteorological parameters important for impact models are therefor considered simultaneously. After using dimension reduction techniques, like principal component analysis, similar behavior of climate simulations is detected using cluster analysis. From each grouping found, one representative simulation will be selected, leading to a more independent sub-sample while conserving the main climate change characteristics of the original ensemble. This method can be applied using standard statistical software and is easily adoptable to various sets of meteorological variables and regions. We present an application of this method to select representative simulations from the ENSEMBLES regional multi-model ensemble for a variety of climate impact studies spread over the whole European continent in the EU-FP7 project IMPACT2C.

  17. Analysis of radial velocities in the Antlia cluster

    NASA Astrophysics Data System (ADS)

    Faifer, F. R.; Smith Castelli, A. V.; Calderón, J. P.; Caso, J. P.; Bassino, L. P.; Cellone, S. A.; Richtler, T.

    We present preliminary results of a radial velocity survey in the central re- gion of the Antlia cluster. These velocities have been measured on spec- tra obtained, in the 2008A and 2009A semesters, with GMOS (GEMINI South). In this way, several dwarf galaxies that had no previous radial ve- locities, have been confirmed as cluster members. Our work is based on the Ferguson & Sandage (1990) catalogue, in which originally only 6% of the catalogued galaxies (375) had radial velocities. Thanks to the newly determined radial velocities we are able to begin to disentangle the cluster internal structure. FULL TEXT IN SPANISH

  18. Cluster Analysis in Patients with GOLD 1 Chronic Obstructive Pulmonary Disease

    PubMed Central

    Gagnon, Philippe; Casaburi, Richard; Saey, Didier; Porszasz, Janos; Provencher, Steeve; Milot, Julie; Bourbeau, Jean; O’Donnell, Denis E.; Maltais, François

    2015-01-01

    Background We hypothesized that heterogeneity exists within the Global Initiative for Chronic Obstructive Lung Disease (GOLD) 1 spirometric category and that different subgroups could be identified within this GOLD category. Methods Pre-randomization study participants from two clinical trials were symptomatic/asymptomatic GOLD 1 chronic obstructive pulmonary disease (COPD) patients and healthy controls. A hierarchical cluster analysis used pre-randomization demographics, symptom scores, lung function, peak exercise response and daily physical activity levels to derive population subgroups. Results Considerable heterogeneity existed for clinical variables among patients with GOLD 1 COPD. All parameters, except forced expiratory volume in 1 second (FEV1)/forced vital capacity (FVC), had considerable overlap between GOLD 1 COPD and controls. Three-clusters were identified: cluster I (18 [15%] COPD patients; 105 [85%] controls); cluster II (45 [80%] COPD patients; 11 [20%] controls); and cluster III (22 [92%] COPD patients; 2 [8%] controls). Apart from reduced diffusion capacity and lower baseline dyspnea index versus controls, cluster I COPD patients had otherwise preserved lung volumes, exercise capacity and physical activity levels. Cluster II COPD patients had a higher smoking history and greater hyperinflation versus cluster I COPD patients. Cluster III COPD patients had reduced physical activity versus controls and clusters I and II COPD patients, and lower FEV1/FVC versus clusters I and II COPD patients. Conclusions The results emphasize heterogeneity within GOLD 1 COPD, supporting an individualized therapeutic approach to patients. Trial registration www.clinicaltrials.gov. NCT01360788 and NCT01072396. PMID:25906326

  19. Cluster analysis of spontaneous preterm birth phenotypes identifies potential associations among preterm birth mechanisms

    PubMed Central

    Esplin, M Sean; Manuck, Tracy A.; Varner, Michael W.; Christensen, Bryce; Biggio, Joseph; Bukowski, Radek; Parry, Samuel; Zhang, Heping; Huang, Hao; Andrews, William; Saade, George; Sadovsky, Yoel; Reddy, Uma M.; Ilekis, John

    2015-01-01

    Objective We sought to employ an innovative tool based on common biological pathways to identify specific phenotypes among women with spontaneous preterm birth (SPTB), in order to enhance investigators' ability to identify to highlight common mechanisms and underlying genetic factors responsible for SPTB. Study Design A secondary analysis of a prospective case-control multicenter study of SPTB. All cases delivered a preterm singleton at SPTB ≤34.0 weeks gestation. Each woman was assessed for the presence of underlying SPTB etiologies. A hierarchical cluster analysis was used to identify groups of women with homogeneous phenotypic profiles. One of the phenotypic clusters was selected for candidate gene association analysis using VEGAS software. Results 1028 women with SPTB were assigned phenotypes. Hierarchical clustering of the phenotypes revealed five major clusters. Cluster 1 (N=445) was characterized by maternal stress, cluster 2 (N=294) by premature membrane rupture, cluster 3 (N=120) by familial factors, and cluster 4 (N=63) by maternal comorbidities. Cluster 5 (N=106) was multifactorial, characterized by infection (INF), decidual hemorrhage (DH) and placental dysfunction (PD). These three phenotypes were highly correlated by Chi-square analysis [PD and DH (p<2.2e-6); PD and INF (p=6.2e-10); INF and DH (p=0.0036)]. Gene-based testing identified the INS (insulin) gene as significantly associated with cluster 3 of SPTB. Conclusion We identified 5 major clusters of SPTB based on a phenotype tool and hierarchal clustering. There was significant correlation between several of the phenotypes. The INS gene was associated with familial factors underlying SPTB. PMID:26070700

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

    PubMed Central

    2014-01-01

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

  1. Visual cluster analysis and pattern recognition template and methods

    SciTech Connect

    Osbourn, G.C.; Martinez, R.F.

    1993-12-31

    This invention is comprised of a method of clustering using a novel template to define a region of influence. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques.

  2. Visual cluster analysis and pattern recognition template and methods

    DOEpatents

    Osbourn, Gordon Cecil; Martinez, Rubel Francisco

    1999-01-01

    A method of clustering using a novel template to define a region of influence. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques.

  3. Visual cluster analysis and pattern recognition template and methods

    DOEpatents

    Osbourn, G.C.; Martinez, R.F.

    1999-05-04

    A method of clustering using a novel template to define a region of influence is disclosed. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques. 30 figs.

  4. Development and optimization of SPECT gated blood pool cluster analysis for the prediction of CRT outcome

    SciTech Connect

    Lalonde, Michel Wassenaar, Richard; Wells, R. Glenn; Birnie, David; Ruddy, Terrence D.

    2014-07-15

    Purpose: Phase analysis of single photon emission computed tomography (SPECT) radionuclide angiography (RNA) has been investigated for its potential to predict the outcome of cardiac resynchronization therapy (CRT). However, phase analysis may be limited in its potential at predicting CRT outcome as valuable information may be lost by assuming that time-activity curves (TAC) follow a simple sinusoidal shape. A new method, cluster analysis, is proposed which directly evaluates the TACs and may lead to a better understanding of dyssynchrony patterns and CRT outcome. Cluster analysis algorithms were developed and optimized to maximize their ability to predict CRT response. Methods: About 49 patients (N = 27 ischemic etiology) received a SPECT RNA scan as well as positron emission tomography (PET) perfusion and viability scans prior to undergoing CRT. A semiautomated algorithm sampled the left ventricle wall to produce 568 TACs from SPECT RNA data. The TACs were then subjected to two different cluster analysis techniques, K-means, and normal average, where several input metrics were also varied to determine the optimal settings for the prediction of CRT outcome. Each TAC was assigned to a cluster group based on the comparison criteria and global and segmental cluster size and scores were used as measures of dyssynchrony and used to predict response to CRT. A repeated random twofold cross-validation technique was used to train and validate the cluster algorithm. Receiver operating characteristic (ROC) analysis was used to calculate the area under the curve (AUC) and compare results to those obtained for SPECT RNA phase analysis and PET scar size analysis methods. Results: Using the normal average cluster analysis approach, the septal wall produced statistically significant results for predicting CRT results in the ischemic population (ROC AUC = 0.73;p < 0.05 vs. equal chance ROC AUC = 0.50) with an optimal operating point of 71% sensitivity and 60% specificity. Cluster

  5. MtDNA analysis reveals enriched pathogenic mutations in Tibetan highlanders.

    PubMed

    Kang, Longli; Zheng, Hong-Xiang; Zhang, Menghan; Yan, Shi; Li, Lei; Liu, Lijun; Liu, Kai; Hu, Kang; Chen, Feng; Ma, Lifeng; Qin, Zhendong; Wang, Yi; Wang, Xiaofeng; Jin, Li

    2016-01-01

    Tibetan highlanders, including Tibetans, Monpas, Lhobas, Dengs and Sherpas, are considered highly adaptive to severe hypoxic environments. Mitochondrial DNA (mtDNA) might be important in hypoxia adaptation given its role in coding core subunits of oxidative phosphorylation. In this study, we employed 549 complete highlander mtDNA sequences (including 432 random samples) to obtain a comprehensive view of highlander mtDNA profile. In the phylogeny of a total of 36,914 sequences, we identified 21 major haplogroups representing founding events of highlanders, most of which were coalesced in 10 kya. Through founder analysis, we proposed a three-phase model of colonizing the plateau, i.e., pre-LGM Time (30 kya, 4.68%), post-LGM Paleolithic Time (16.8 kya, 29.31%) and Neolithic Time (after 8 kya, 66.01% in total). We observed that pathogenic mutations occurred far more frequently in 22 highlander-specific lineages (five lineages carrying two pathogenic mutations and six carrying one) than in the 6,857 haplogroups of all the 36,914 sequences (P = 4.87 × 10(-8)). Furthermore, the number of possible pathogenic mutations carried by highlanders (in average 3.18 ± 1.27) were significantly higher than that in controls (2.82 ± 1.40) (P = 1.89 × 10(-4)). Considering that function-altering and pathogenic mutations are enriched in highlanders, we therefore hypothesize that they may have played a role in hypoxia adaptation. PMID:27498855

  6. MtDNA analysis reveals enriched pathogenic mutations in Tibetan highlanders

    PubMed Central

    Kang, Longli; Zheng, Hong-Xiang; Zhang, Menghan; Yan, Shi; Li, Lei; Liu, Lijun; Liu, Kai; Hu, Kang; Chen, Feng; Ma, Lifeng; Qin, Zhendong; Wang, Yi; Wang, Xiaofeng; Jin, Li

    2016-01-01

    Tibetan highlanders, including Tibetans, Monpas, Lhobas, Dengs and Sherpas, are considered highly adaptive to severe hypoxic environments. Mitochondrial DNA (mtDNA) might be important in hypoxia adaptation given its role in coding core subunits of oxidative phosphorylation. In this study, we employed 549 complete highlander mtDNA sequences (including 432 random samples) to obtain a comprehensive view of highlander mtDNA profile. In the phylogeny of a total of 36,914 sequences, we identified 21 major haplogroups representing founding events of highlanders, most of which were coalesced in 10 kya. Through founder analysis, we proposed a three-phase model of colonizing the plateau, i.e., pre-LGM Time (30 kya, 4.68%), post-LGM Paleolithic Time (16.8 kya, 29.31%) and Neolithic Time (after 8 kya, 66.01% in total). We observed that pathogenic mutations occurred far more frequently in 22 highlander-specific lineages (five lineages carrying two pathogenic mutations and six carrying one) than in the 6,857 haplogroups of all the 36,914 sequences (P = 4.87 × 10−8). Furthermore, the number of possible pathogenic mutations carried by highlanders (in average 3.18 ± 1.27) were significantly higher than that in controls (2.82 ± 1.40) (P = 1.89 × 10−4). Considering that function-altering and pathogenic mutations are enriched in highlanders, we therefore hypothesize that they may have played a role in hypoxia adaptation. PMID:27498855

  7. Combining Quantitative Genetic Footprinting and Trait Enrichment Analysis to Identify Fitness Determinants of a Bacterial Pathogen

    PubMed Central

    Wiles, Travis J.; Norton, J. Paul; Russell, Colin W.; Dalley, Brian K.; Fischer, Kael F.; Mulvey, Matthew A.

    2013-01-01

    Strains of Extraintestinal Pathogenic Escherichia c oli (ExPEC) exhibit an array of virulence strategies and are a major cause of urinary tract infections, sepsis and meningitis. Efforts to understand ExPEC pathogenesis are challenged by the high degree of genetic and phenotypic variation that exists among isolates. Determining which virulence traits are widespread and which are strain-specific will greatly benefit the design of more effective therapies. Towards this goal, we utilized a quantitative genetic footprinting technique known as transposon insertion sequencing (Tn-seq) in conjunction with comparative pathogenomics to functionally dissect the genetic repertoire of a reference ExPEC isolate. Using Tn-seq and high-throughput zebrafish infection models, we tracked changes in the abundance of ExPEC variants within saturated transposon mutant libraries following selection within distinct host niches. Nine hundred and seventy bacterial genes (18% of the genome) were found to promote pathogen fitness in either a niche-dependent or independent manner. To identify genes with the highest therapeutic and diagnostic potential, a novel Trait Enrichment Analysis (TEA) algorithm was developed to ascertain the phylogenetic distribution of candidate genes. TEA revealed that a significant portion of the 970 genes identified by Tn-seq have homologues more often contained within the genomes of ExPEC and other known pathogens, which, as suggested by the first axiom of molecular Koch's postulates, is considered to be a key feature of true virulence determinants. Three of these Tn-seq-derived pathogen-associated genes—a transcriptional repressor, a putative metalloendopeptidase toxin and a hypothetical DNA binding protein—were deleted and shown to independently affect ExPEC fitness in zebrafish and mouse models of infection. Together, the approaches and observations reported herein provide a resource for future pathogenomics-based research and highlight the diversity of

  8. The role of voluntary exercise in enriched rearing: a behavioral analysis.

    PubMed

    Pietropaolo, Susanna; Feldon, Joram; Alleva, Enrico; Cirulli, Francesca; Yee, Benjamin K

    2006-08-01

    The effects of postweaning enriched rearing and home cage voluntary wheel-running exercise in adulthood were contrasted on a comprehensive battery of tests designed to assess mnemonic, attentional, emotional, and motor functions. In a 2 x 2 factorial design, female C57BL/6 mice were housed in groups in either standard or enriched cages, which were equipped with either a running or a locked wheel. They were maintained in the corresponding housing conditions for 2 months postweaning prior to, and throughout, testing. Enriched rearing was associated with anxiogenesis, hypolocomotor activity, enhanced motor skills, retarded extinction of conditioned responding, and improved water maze performance. Exercise as such enhanced motor coordination and facilitated extinction of contextual conditioning. Evidence for an interaction between enrichment and exercise was apparent in the open field test, conditioned freezing to a tone stimulus, prepulse inhibition, and acquisition of water maze reference memory. Hence, care should be taken to control for the unique contribution of wheel-running exercise when it is included as an integral component of the enrichment procedure.

  9. Work-family enrichment, work-family conflict, and marital satisfaction: a dyadic analysis.

    PubMed

    van Steenbergen, Elianne F; Kluwer, Esther S; Karney, Benjamin R

    2014-04-01

    This study was designed to examine whether spouses' work-to-family (WF) enrichment experiences account for their own and their partner's marital satisfaction, beyond the effects of WF conflict. Data were collected from both partners of 215 dual-earner couples with children. As hypothesized, structural equation modeling revealed that WF enrichment experiences accounted for variance in individuals' marital satisfaction, over and above WF conflict. In line with our predictions, this positive link between individuals' WF enrichment and their marital satisfaction was mediated by more positive marital behavior, and more positive perceptions of the partner's behavior. Furthermore, evidence for crossover was found. Husbands who experienced more WF enrichment were found to show more marital positivity (according to their wives), which related to increased marital satisfaction in their wives. No evidence of such a crossover effect from wives to husbands was found. The current findings not only highlight the added value of studying positive spillover and crossover effects of work into the marriage, but also suggest that positive spillover and crossover effects on marital satisfaction might be stronger than negative spillover and crossover are. These results imply that organizational initiatives of increasing job enrichment may make employees' marital life happier and can contribute to a happy, healthy, and high-performing workforce.

  10. Work-family enrichment, work-family conflict, and marital satisfaction: a dyadic analysis.

    PubMed

    van Steenbergen, Elianne F; Kluwer, Esther S; Karney, Benjamin R

    2014-04-01

    This study was designed to examine whether spouses' work-to-family (WF) enrichment experiences account for their own and their partner's marital satisfaction, beyond the effects of WF conflict. Data were collected from both partners of 215 dual-earner couples with children. As hypothesized, structural equation modeling revealed that WF enrichment experiences accounted for variance in individuals' marital satisfaction, over and above WF conflict. In line with our predictions, this positive link between individuals' WF enrichment and their marital satisfaction was mediated by more positive marital behavior, and more positive perceptions of the partner's behavior. Furthermore, evidence for crossover was found. Husbands who experienced more WF enrichment were found to show more marital positivity (according to their wives), which related to increased marital satisfaction in their wives. No evidence of such a crossover effect from wives to husbands was found. The current findings not only highlight the added value of studying positive spillover and crossover effects of work into the marriage, but also suggest that positive spillover and crossover effects on marital satisfaction might be stronger than negative spillover and crossover are. These results imply that organizational initiatives of increasing job enrichment may make employees' marital life happier and can contribute to a happy, healthy, and high-performing workforce. PMID:24730427

  11. Marketing Mix Formulation for Higher Education: An Integrated Analysis Employing Analytic Hierarchy Process, Cluster Analysis and Correspondence Analysis

    ERIC Educational Resources Information Center

    Ho, Hsuan-Fu; Hung, Chia-Chi

    2008-01-01

    Purpose: The purpose of this paper is to examine how a graduate institute at National Chiayi University (NCYU), by using a model that integrates analytic hierarchy process, cluster analysis and correspondence analysis, can develop effective marketing strategies. Design/methodology/approach: This is primarily a quantitative study aimed at…

  12. Is Omega-3 Fatty Acids Enriched Nutrition Support Safe for Critical Ill Patients? A Systematic Review and Meta-Analysis

    PubMed Central

    Chen, Wei; Jiang, Hua; Zhou, Zhi-Yuan; Tao, Ye-Xuan; Cai, Bin; Liu, Jie; Yang, Hao; Lu, Charles Damien; Zeng, Jun

    2014-01-01

    Objective: To systematically review the effects of omega-3 poly unsaturated fatty acids (FA) enriched nutrition support on the mortality of critically illness patients. Methods: Databases of Medline, ISI, Cochrane Library, and Chinese Biomedicine Database were searched and randomized controlled trials (RCTs) were identified. We enrolled RCTs that compared fish oil enriched nutrition support and standard nutrition support. Major outcome is mortality. Methodological quality assessment was conducted based on Modified Jadad’s score scale. For control heterogeneity, we developed a method that integrated I2 test, nutritional support route subgroup analysis and clinical condition of severity. RevMan 5.0 software (The Nordic Cochrane Centre, Copenhagen, Denmark) was used for meta-analysis. Results: Twelve trials involving 1208 patients that met all the inclusion criteria. Heterogeneity existed between the trials. A random model was used, there was no significant effect on mortality RR, 0.82, 95% confidence interval (CI) (0.62, 1.09), p = 0.18. Knowing that the route of fish oil administration may affect heterogeneity, we categorized the trials into two sub-groups: parenteral administration (PN) of omega-3 and enteral administration (EN) of omega-3. Six trials administered omega-3 FA through PN. Pooled results indicated that omega-3 FA had no significant effect on mortality, RR 0.76, 95% CI (0.52, 1.10), p = 0.15. Six trials used omega-3 fatty acids enriched EN. After excluded one trial that was identified as source of heterogeneity, pooled data indicated omega-3 FA enriched EN significant reduce mortality, RR=0.69, 95% CI [0.53, 0.91] (p = 0.007). Conclusion: Omega-3 FA enriched nutrition support is safe. Due to the limited sample size of the included trials, further large-scale RCTs are needed. PMID:24886987

  13. Bacterial community analysis in chlorpyrifos enrichment cultures via DGGE and use of bacterial consortium for CP biodegradation.

    PubMed

    Akbar, Shamsa; Sultan, Sikander; Kertesz, Michael

    2014-10-01

    The organophosphate pesticide chlorpyrifos (CP) has been used extensively since the 1960s for insect control. However, its toxic effects on mammals and persistence in environment necessitate its removal from contaminated sites, biodegradation studies of CP-degrading microbes are therefore of immense importance. Samples from a Pakistani agricultural soil with an extensive history of CP application were used to prepare enrichment cultures using CP as sole carbon source for bacterial community analysis and isolation of CP metabolizing bacteria. Bacterial community analysis (denaturing gradient gel electrophoresis) revealed that the dominant genera enriched under these conditions were Pseudomonas, Acinetobacter and Stenotrophomonas, along with lower numbers of Sphingomonas, Agrobacterium and Burkholderia. Furthermore, it revealed that members of Bacteroidetes, Firmicutes, α- and γ-Proteobacteria and Actinobacteria were present at initial steps of enrichment whereas β-Proteobacteria appeared in later steps and only Proteobacteria were selected by enrichment culturing. However, when CP-degrading strains were isolated from this enrichment culture, the most active organisms were strains of Acinetobacter calcoaceticus, Pseudomonas mendocina and Pseudomonas aeruginosa. These strains degraded 6-7.4 mg L(-1) day(-1) of CP when cultivated in mineral medium, while the consortium of all four strains degraded 9.2 mg L(-1) day(-1) of CP (100 mg L(-1)). Addition of glucose as an additional C source increased the degradation capacity by 8-14 %. After inoculation of contaminated soil with CP (200 mg kg(-1)) disappearance rates were 3.83-4.30 mg kg(-1) day(-1) for individual strains and 4.76 mg kg(-1) day(-1) for the consortium. These results indicate that these organisms are involved in the degradation of CP in soil and represent valuable candidates for in situ bioremediation of contaminated soils and waters.

  14. Evidence-Based Clustering of Reads and Taxonomic Analysis of Metagenomic Data

    NASA Astrophysics Data System (ADS)

    Folino, Gianluigi; Gori, Fabio; Jetten, Mike S. M.; Marchiori, Elena

    The rapidly emerging field of metagenomics seeks to examine the genomic content of communities of organisms to understand their roles and interactions in an ecosystem. In this paper we focus on clustering methods and their application to taxonomic analysis of metagenomic data. Clustering analysis for metagenomics amounts to group similar partial sequences, such as raw sequence reads, into clusters in order to discover information about the internal structure of the considered dataset, or the relative abundance of protein families. Different methods for clustering analysis of metagenomic datasets have been proposed. Here we focus on evidence-based methods for clustering that employ knowledge extracted from proteins identified by a BLASTx search (proxygenes). We consider two clustering algorithms introduced in previous works and a new one. We discuss advantages and drawbacks of the algorithms, and use them to perform taxonomic analysis of metagenomic data. To this aim, three real-life benchmark datasets used in previous work on metagenomic data analysis are used. Comparison of the results indicates satisfactory coherence of the taxonomies output by the three algorithms, with respect to phylogenetic content at the class level and taxonomic distribution at phylum level. In general, the experimental comparative analysis substantiates the effectiveness of evidence-based clustering methods for taxonomic analysis of metagenomic data.

  15. Mass spectrometric analysis with cluster projectiles and coincidence counting

    SciTech Connect

    Cox, B.D.

    1992-01-01

    Methods for maximizing the amount of secondary ion information, per primary projectile, are described. The method is based on time-of-flight mass spectrometry and event-by-event coincidence counting. The information obtained from coincidence counting time-of-flight mass spectrometry includes: (a) surface composition, (b) relative concentrations, and (c) degree of intermolecular mixing. The technique was applied to the study of an important new class of polymers: polymer blends. Secondary ion mass spectrometry, when applied to the analysis of synthetic polymers, induces backbone fragmentation which is characteristic of the homopolymer. The characteristic fingerprint peaks from polystyrene and poly(vinyl methyl ether) were used to identify the presence of these two polymers in a polymer blend. The percent coincidence between the characteristic secondary ions from each component of the blend were used to determine both the relative concentration and the degree of molecular mixing. Results indicate molecular segregation of the two polymers on the film surface. The largest degree of segregation was determined for the phase separated blends. The performance of this technique depends on the desorption efficiency of the primary projectiles. In practice one seeks primary ions which are surface sensitive, have controllable parameters such as size, velocity, and charge state, and generate high secondary ion yields. Focus was placed on the use of keV organic cluster projectiles to meet these criteria. Of interest to this study were C[sub 18] (chrysene), C[sub 24] (coronene), and C[sub 60] (buckminster-fulleren). Results indicate enhanced secondary ion yields for C[sub 60]. For example, when CsI is bombarded with 30 keV C[sub 60], the yields for I[sup [minus

  16. Alternative Computational Analysis Shows No Evidence for Nucleosome Enrichment at Repetitive Sequences in Mammalian Spermatozoa.

    PubMed

    Royo, Hélène; Stadler, Michael Beda; Peters, Antoine Hendrik Felix Marie

    2016-04-01

    Samans et al. (2014) reported the enrichment of nucleosomes in human and bovine spermatozoa at centromere repeats and retrotransposon sequences such as LINE-1 and SINE. We demonstrate here that nucleosomal enrichments at repetitive sequences as reported result from bioinformatic analyses that make redundant use of sequencing reads that map to multiple locations in the genome. To illustrate that this computational approach is flawed, we observed comparable artificial enrichments at repetitive sequences when aligning control genomic DNA or simulated reads of uniform genome coverage. These results imply that the main conclusions of the article by Samans et al. (2014) are confounded by an inappropriate computational methodology used to analyze the primary data. PMID:27046835

  17. Batch methods for enriching trace impurities in hydrogen gas for their further analysis

    DOEpatents

    Ahmed, Shabbir; Lee, Sheldon H.D.; Kumar, Romesh; Papdias, Dionissios D.

    2014-07-15

    Provided herein are batch methods and devices for enriching trace quantities of impurities in gaseous mixtures, such as hydrogen fuel. The methods and devices rely on concentrating impurities using hydrogen transport membranes wherein the time period for concentrating the sample is calculated on the basis of optimized membrane characteristics, comprising its thickness and permeance, with optimization of temperature, and wherein the enrichment of trace impurities is proportional to the pressure ratio P.sub.hi/P.sub.lo and the volume ratio V.sub.1/V.sub.2, with following detection of the impurities using commonly-available detection methods.

  18. Strategies for Distributing Time When Studying Text: An Exploratory Cluster-Analysis Approach.

    ERIC Educational Resources Information Center

    Freebody, Peter; And Others

    1986-01-01

    Indicates that membership in pausing and skimming clusters appears to relate to text comprehension, grade level, and rated academic ability, but that these relationships are not all simple or direct. Finds that the cluster-analytic approach provides a useful empirical adjunct to current theoretical perspectives on text analysis and reading…

  19. Identifying At-Risk Students in General Chemistry via Cluster Analysis of Affective Characteristics

    ERIC Educational Resources Information Center

    Chan, Julia Y. K.; Bauer, Christopher F.

    2014-01-01

    The purpose of this study is to identify academically at-risk students in first-semester general chemistry using affective characteristics via cluster analysis. Through the clustering of six preselected affective variables, three distinct affective groups were identified: low (at-risk), medium, and high. Students in the low affective group…

  20. Social Learning Network Analysis Model to Identify Learning Patterns Using Ontology Clustering Techniques and Meaningful Learning

    ERIC Educational Resources Information Center

    Firdausiah Mansur, Andi Besse; Yusof, Norazah

    2013-01-01

    Clustering on Social Learning Network still not explored widely, especially when the network focuses on e-learning system. Any conventional methods are not really suitable for the e-learning data. SNA requires content analysis, which involves human intervention and need to be carried out manually. Some of the previous clustering techniques need…

  1. On the Partitioning of Squared Euclidean Distance and Its Applications in Cluster Analysis.

    ERIC Educational Resources Information Center

    Carter, Randy L.; And Others

    1989-01-01

    The partitioning of squared Euclidean--E(sup 2)--distance between two vectors in M-dimensional space into the sum of squared lengths of vectors in mutually orthogonal subspaces is discussed. Applications to specific cluster analysis problems are provided (i.e., to design Monte Carlo studies for performance comparisons of several clustering methods…

  2. Applying Clustering to Statistical Analysis of Student Reasoning about Two-Dimensional Kinematics

    ERIC Educational Resources Information Center

    Springuel, R. Padraic; Wittman, Michael C.; Thompson, John R.

    2007-01-01

    We use clustering, an analysis method not presently common to the physics education research community, to group and characterize student responses to written questions about two-dimensional kinematics. Previously, clustering has been used to analyze multiple-choice data; we analyze free-response data that includes both sketches of vectors and…

  3. Isotope Enrichment Detection by Laser Ablation - Laser Absorption Spectrometry: Automated Environmental Sampling and Laser-Based Analysis for HEU Detection

    SciTech Connect

    Anheier, Norman C.; Bushaw, Bruce A.

    2010-01-01

    The global expansion of nuclear power, and consequently the uranium enrichment industry, requires the development of new safeguards technology to mitigate proliferation risks. Current enrichment monitoring instruments exist that provide only yes/no detection of highly enriched uranium (HEU) production. More accurate accountancy measurements are typically restricted to gamma-ray and weight measurements taken in cylinder storage yards. Analysis of environmental and cylinder content samples have much higher effectiveness, but this approach requires onsite sampling, shipping, and time-consuming laboratory analysis and reporting. Given that large modern gaseous centrifuge enrichment plants (GCEPs) can quickly produce a significant quantity (SQ ) of HEU, these limitations in verification suggest the need for more timely detection of potential facility misuse. The Pacific Northwest National Laboratory (PNNL) is developing an unattended safeguards instrument concept, combining continuous aerosol particulate collection with uranium isotope assay, to provide timely analysis of enrichment levels within low enriched uranium facilities. This approach is based on laser vaporization of aerosol particulate samples, followed by wavelength tuned laser diode spectroscopy to characterize the uranium isotopic ratio through subtle differences in atomic absorption wavelengths. Environmental sampling (ES) media from an integrated aerosol collector is introduced into a small, reduced pressure chamber, where a focused pulsed laser vaporizes material from a 10 to 20-µm diameter spot of the surface of the sampling media. The plume of ejected material begins as high-temperature plasma that yields ions and atoms, as well as molecules and molecular ions. We concentrate on the plume of atomic vapor that remains after the plasma has expanded and then cooled by the surrounding cover gas. Tunable diode lasers are directed through this plume and each isotope is detected by monitoring absorbance

  4. Quantitative Methylation Analysis of the PCDHB Gene Cluster.

    PubMed

    Banelli, Barbara; Romani, Massimo

    2015-01-01

    Long Range Epigenetic Silencing (LRES) is a repressed chromatin state of large chromosomal regions caused by DNA hypermethylation and histone modifications and is commonly observed in cancer. At 5q31 a LRES region of 800 kb includes three multi-gene clusters (PCDHA@, PCDHB@, and PCDHG@, respectively). Multiple experimental evidences have led to consider the PCDHB cluster as a DNA methylation marker of aggressiveness in neuroblastoma, second most common solid tumor in childhood. Because of its potential involvement not only in neuroblastoma but also in other malignancies, an easy and fast assay to screen the DNA methylation content of the PCDHB cluster might be useful for the precise stratification of the patients into risk groups and hence for choosing the most appropriate therapeutic protocol. Accordingly, we have developed a simple and cost-effective Pyrosequencing(®) assay to evaluate the methylation level of 17 genes in the protocadherin B cluster (PCDHB@). The rationale behind this Pyrosequencing assay can in principle be applied to analyze the DNA methylation level of any gene cluster with high homologies for screening purposes. PMID:26103900

  5. A Bayesian Analysis of the Ages of Four Open Clusters

    NASA Astrophysics Data System (ADS)

    Jeffery, Elizabeth J.; von Hippel, Ted; van Dyk, David A.; Stenning, David C.; Robinson, Elliot; Stein, Nathan; Jefferys, William H.

    2016-09-01

    In this paper we apply a Bayesian technique to determine the best fit of stellar evolution models to find the main sequence turn-off age and other cluster parameters of four intermediate-age open clusters: NGC 2360, NGC 2477, NGC 2660, and NGC 3960. Our algorithm utilizes a Markov chain Monte Carlo technique to fit these various parameters, objectively finding the best-fit isochrone for each cluster. The result is a high-precision isochrone fit. We compare these results with the those of traditional “by-eye” isochrone fitting methods. By applying this Bayesian technique to NGC 2360, NGC 2477, NGC 2660, and NGC 3960, we determine the ages of these clusters to be 1.35 ± 0.05, 1.02 ± 0.02, 1.64 ± 0.04, and 0.860 ± 0.04 Gyr, respectively. The results of this paper continue our effort to determine cluster ages to a higher precision than that offered by these traditional methods of isochrone fitting.

  6. Robust growing neural gas algorithm with application in cluster analysis.

    PubMed

    Qin, A K; Suganthan, P N

    2004-01-01

    We propose a novel robust clustering algorithm within the Growing Neural Gas (GNG) framework, called Robust Growing Neural Gas (RGNG) network.The Matlab codes are available from . By incorporating several robust strategies, such as outlier resistant scheme, adaptive modulation of learning rates and cluster repulsion method into the traditional GNG framework, the proposed RGNG network possesses better robustness properties. The RGNG is insensitive to initialization, input sequence ordering and the presence of outliers. Furthermore, the RGNG network can automatically determine the optimal number of clusters by seeking the extreme value of the Minimum Description Length (MDL) measure during network growing process. The resulting center positions of the optimal number of clusters represented by prototype vectors are close to the actual ones irrespective of the existence of outliers. Topology relationships among these prototypes can also be established. Experimental results have shown the superior performance of our proposed method over the original GNG incorporating MDL method, called GNG-M, in static data clustering tasks on both artificial and UCI data sets. PMID:15555857

  7. Deconstruction and analysis of multiphonic clusters in the modern flute

    NASA Astrophysics Data System (ADS)

    Barravecchio, Shauna

    The modern flute has been acoustically analyzed in great detail by many, but only from the point of view of traditional playing techniques. Very little research exists to date on more modem, "extended" technique performance. This paper explores the production of multiphonic note clusters as played on the modern flute. Several clusters as notated in James Pellerite's book on flute fingerings are recorded and analyzed for frequency content. Each one is then compared to the expected frequency content based on John Backus' 1978 paper on woodwind multiphonics. Using this information, the fingering configuration of each cluster can be deconstructed and each component pitch explained in terms of the root frequencies, overtone series, and sideband frequencies.

  8. Functional clustering algorithm for the analysis of dynamic network data

    NASA Astrophysics Data System (ADS)

    Feldt, S.; Waddell, J.; Hetrick, V. L.; Berke, J. D.; Żochowski, M.

    2009-05-01

    We formulate a technique for the detection of functional clusters in discrete event data. The advantage of this algorithm is that no prior knowledge of the number of functional groups is needed, as our procedure progressively combines data traces and derives the optimal clustering cutoff in a simple and intuitive manner through the use of surrogate data sets. In order to demonstrate the power of this algorithm to detect changes in network dynamics and connectivity, we apply it to both simulated neural spike train data and real neural data obtained from the mouse hippocampus during exploration and slow-wave sleep. Using the simulated data, we show that our algorithm performs better than existing methods. In the experimental data, we observe state-dependent clustering patterns consistent with known neurophysiological processes involved in memory consolidation.

  9. Connectionist approach for clustering with applications in image analysis

    SciTech Connect

    Vinod, V.V.; Chaudhury, S.; Mukherjee, J.; Ghose, S.

    1994-03-01

    A new neural network strategy for clustering is presented. The network works on the histogram and the process is similar to mode separation. The number of clusters are autonomously detected by the network and it overcomes some major difficulties encountered by mode separation techniques. Clustering is done by first selecting the prototypes and then assigning patterns to one of the prototypes based on its distance from the prototype and the distribution of data. The network does not employ weight learning and is therefore faster than existing unsupervised learning networks. The network was applied to a wide class of problems including gray level image reduction, color segmentation and remotely sensed image segmentation. The experimental results obtained are promising. 26 refs.

  10. Molecular-dynamics analysis of mobile helium cluster reactions near surfaces of plasma-exposed tungsten

    SciTech Connect

    Hu, Lin; Maroudas, Dimitrios; Hammond, Karl D.; Wirth, Brian D.

    2015-10-28

    We report the results of a systematic atomic-scale analysis of the reactions of small mobile helium clusters (He{sub n}, 4 ≤ n ≤ 7) near low-Miller-index tungsten (W) surfaces, aiming at a fundamental understanding of the near-surface dynamics of helium-carrying species in plasma-exposed tungsten. These small mobile helium clusters are attracted to the surface and migrate to the surface by Fickian diffusion and drift due to the thermodynamic driving force for surface segregation. As the clusters migrate toward the surface, trap mutation (TM) and cluster dissociation reactions are activated at rates higher than in the bulk. TM produces W adatoms and immobile complexes of helium clusters surrounding W vacancies located within the lattice planes at a short distance from the surface. These reactions are identified and characterized in detail based on the analysis of a large number of molecular-dynamics trajectories for each such mobile cluster near W(100), W(110), and W(111) surfaces. TM is found to be the dominant cluster reaction for all cluster and surface combinations, except for the He{sub 4} and He{sub 5} clusters near W(100) where cluster partial dissociation following TM dominates. We find that there exists a critical cluster size, n = 4 near W(100) and W(111) and n = 5 near W(110), beyond which the formation of multiple W adatoms and vacancies in the TM reactions is observed. The identified cluster reactions are responsible for important structural, morphological, and compositional features in the plasma-exposed tungsten, including surface adatom populations, near-surface immobile helium-vacancy complexes, and retained helium content, which are expected to influence the amount of hydrogen re-cycling and tritium retention in fusion tokamaks.

  11. Comparative proteomics analysis of selenium responses in selenium-enriched rice grains.

    PubMed

    Wang, Yu-Dong; Wang, Xu; Ngai, Sai-ming; Wong, Yum-shing

    2013-02-01

    By foliar fortification with selenite, selenium (Se)-enriched rice with a higher Se content and grain yield has been generated. However, the regulatory mechanisms of Se response in rice grains remain unknown; therefore, we carried out a comparative proteomics study in Se-enriched rice grains by using two approaches including two-dimensional gel electrophoresis (2-DE)-coupled MALDI-TOF/TOF MS and 1-DE/LC-FTICR-MS-coupled label-free quantification. By comparison between Se treatment and control, 62 and 250 abundance changed proteins were identified from 2-DE and 1-DE, respectively. By functional classification, proteins involved in metabolism, cell redox regulation, and seed nutritional storage were the most highly affected by Se accumulation. The up-regulation of late embryogenesis abundant proteins as well as proteins involved in sucrose synthesis and other metabolism pathways may contribute to the earlier maturation and higher yield of the Se-enriched rice. In addition, there have been six proteins identified to contain selenoamino acid modification, which is the first identification of selenoproteins in higher plants. In conclusion, our study provided novel insights into Se response in rice grains at the proteome level, which are expected to be highly useful for dissecting the Se response pathways in rice and for the production of Se-enriched rice in the future.

  12. twzPEA: A Topology and Working Zone Based Pathway Enrichment Analysis Framework

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Sensitive detection of involvement and adaptation of key signaling, regulatory, and metabolic pathways holds the key to deciphering molecular mechanisms such as those in the biomass-to-biofuel conversion process in yeast. Typical gene set enrichment analyses often do not use topology information in...

  13. X-ray analysis of filaments in galaxy clusters

    NASA Astrophysics Data System (ADS)

    Walker, S. A.; Kosec, P.; Fabian, A. C.; Sanders, J. S.

    2015-11-01

    We perform a detailed X-ray study of the filaments surrounding the brightest cluster galaxies in a sample of nearby galaxy clusters using deep Chandra observations, namely the Perseus, Centaurus and Virgo clusters, and Abell 1795. We compare the X-ray properties and spectra of the filaments in all of these systems, and find that their Chandra X-ray spectra are all broadly consistent with an absorbed two-temperature thermal model, with temperature components at 0.75 and 1.7 keV. We find that it is also possible to model the Chandra ACIS filament spectra with a charge exchange model provided a thermal component is also present, and the abundance of oxygen is suppressed relative to the abundance of Fe. In this model, charge exchange provides the dominant contribution to the spectrum in the 0.5-1.0 keV band. However, when we study the high spectral resolution RGS spectrum of the filamentary plume seen in X-rays in Centaurus, the opposite appears to be the case. The properties of the filaments in our sample of clusters are also compared to the X-ray tails of galaxies in the Coma cluster and Abell 3627. In the Perseus cluster, we search for signs of absorption by a prominent region of molecular gas in the filamentary structure around NGC 1275. We do find a decrement in the X-ray spectrum below 2 keV, indicative of absorption. However, the spectral shape is inconsistent with this decrement being caused by simply adding an additional absorbing component. We find that the spectrum can be well fit (with physically sensible parameters) with a model that includes both absorption by molecular gas and X-ray emission from the filament, which partially counteracts the absorption.

  14. MASSCLEAN - MASSive CLuster Evolution and ANalysis Package - Description and Tests

    NASA Astrophysics Data System (ADS)

    Hanson, Margaret M.; Popescu, B.

    2009-05-01

    We present MASSCLEAN, a new, sophisticated and robust stellar cluster image and photometry simulation package. This package is able to create color-magnitude diagrams and standard FITS images in any of the traditional optical and near-infrared bands based on cluster characteristics input by the user, including but not limited to distance, age, mass, radius and extinction. At the limit of very distant, unresolved clusters, we have checked the integrated colors created in MASSCLEAN against those from other simple stellar population models with consistent results. We have also tested models which provide a reasonable estimate of the field star contamination in images and color-magnitude diagrams. We demonstrate the package by simulating images and color-magnitude diagrams of well known massive Milky Way clusters and compare their appearance to real data. Because the algorithm populates the cluster with a discrete number of tenable stars, it can be used as part of a Monte Carlo Method to derive the probabilistic range of characteristics (integrated colors, for example) consistent with a given cluster mass and age. The discrete nature of our code is demonstrated in the realistic stochastic variation seen in the predicted V-K integrated colors as compared to the unrealistically smooth color from other SSP codes. Our simulation package is available to download and will run on any standard desktop running UNIX/Linux. Full documentation on installation and its use is also available. Finally, a web-based version of MASSCLEAN which can be immediately used and is sufficiently adaptable for most applications is available through a web interface.

  15. Behavioral analysis of Wistar rats fed with a flaxseed based diet added to an environmental enrichment.

    PubMed

    Azevedo de Meneses, J; Junqueira Lopes, C A; Coca Velarde, L G; Teles Boaventura, G

    2011-01-01

    Flaxseed has a high content of n-3 fatty acids and its intake associated with an environmental enrichment may promote distinct behavioral results upon habituation and animal behavior. This work aimed to evaluating animal behavior under the use of these two tools in the Open Field Test. Thirty-six male Wistar rats were divided into 6 groups (n = 6): FEEG, receiving chow made up of flaxseed and kept in enriched environment; FSEG, receiving flaxseed based diet and kept in a standard environment; CEEG, receiving casein based diet and kept in enriched environment; CSEG, receiving casein based chow and kept in standard environment; MCEEG, receiving chow made up of casein but modified so as to provide the same content of fibers and lipids found in flaxseed diet and kept in enriched environment; MCSEG, receiving modified casein based diet and kept in standard environment. All animals were kept under controlled temperature, collective cages and dark/light cycle, receiving chow and water ad libitum, except for MCEEG and MCSEG, which were pair fed with FEEG and FSEG, respectively. Chow intake and animal body weight were evaluated twice in a week. Animals were maintained in these groups from the first until the second month of life, by the time when 3 day tests in Open Field Test began. Finishing the tests, animals were sacrificed and their brains were obtained in order to calculate the relative brain weight. Our results show an interplay between flaxseed and environmental enrichment in habituation to a new environment, making the animals more manageable and less stressed.

  16. Microbial community structure analysis of a benzoate-degrading halophilic archaeal enrichment.

    PubMed

    Dalvi, Sonal; Youssef, Noha H; Fathepure, Babu Z

    2016-05-01

    A benzoate-degrading archaeal enrichment was developed using sediment samples from Rozel Point at Great Salt Lake, UT. The enrichment degraded benzoate as the sole carbon source at salinity ranging from 2.0 to 5.0 M NaCl with highest rate of degradation observed at 4.0 M. The enrichment was also tested for its ability to grow on other aromatic compounds such as 4-hydroxybenzoic acid (4-HBA), gentisic acid, protocatechuic acid (PCA), catechol, benzene and toluene as the sole sources of carbon and energy. Of these, the culture only utilized 4-HBA as the carbon source. To determine the initial steps in benzoate degradation pathway, a survey of ring-oxidizing and ring-cleaving genes was performed using degenerate PCR primers. Results showed the presence of 4-hydroxybenzoate 3-monooxygenase (4-HBMO) and protocatechuate 3, 4-dioxygenase (3,4-PCA) genes suggesting that the archaeal enrichment might degrade benzoate to 4-HBA that is further converted to PCA by 4-HBMO and, thus, formed PCA would undergo ring-cleavage by 3,4-PCA to form intermediates that enter the Krebs cycle. Small subunit rRNA gene-based diversity survey revealed that the enrichment consisted entirely of class Halobacteria members belonging to the genera Halopenitus, Halosarcina, Natronomonas, Halosimplex, Halorubrum, Salinarchaeum and Haloterrigena. Of these, Halopenitus was the dominant group accounting for almost 91 % of the total sequences suggesting their potential role in degrading oxygenated aromatic compounds at extreme salinity. PMID:26995683

  17. An analysis of spatial clustering and implications for wildlife management: a burrowing owl example.

    PubMed

    Fisher, Joshua B; Trulio, Lynne A; Biging, Gregory S; Chromczak, Debra

    2007-03-01

    Analysis tools that combine large spatial and temporal scales are necessary for efficient management of wildlife species, such as the burrowing owl (Athene cunicularia). We assessed the ability of Ripley's K-function analysis integrated into a geographic information system (GIS) to determine changes in burrowing owl nest clustering over two years at NASA Ames Research Center. Specifically, we used these tools to detect changes in spatial and temporal nest clustering before, during, and after conducting management by mowing to maintain low vegetation height at nest burrows. We found that the scale and timing of owl nest clustering matched the scale and timing of our conservation management actions over a short time frame. While this study could not determine a causal link between mowing and nest clustering, we did find that Ripley's K and GIS were effective in detecting owl nest clustering and show promise for future conservation uses. PMID:17253092

  18. An Analysis of Spatial Clustering and Implications for Wildlife Management: A Burrowing Owl Example

    NASA Astrophysics Data System (ADS)

    Fisher, Joshua B.; Trulio, Lynne A.; Biging, Gregory S.; Chromczak, Debra

    2007-03-01

    Analysis tools that combine large spatial and temporal scales are necessary for efficient management of wildlife species, such as the burrowing owl ( Athene cunicularia). We assessed the ability of Ripley’s K-function analysis integrated into a geographic information system (GIS) to determine changes in burrowing owl nest clustering over two years at NASA Ames Research Center. Specifically, we used these tools to detect changes in spatial and temporal nest clustering before, during, and after conducting management by mowing to maintain low vegetation height at nest burrows. We found that the scale and timing of owl nest clustering matched the scale and timing of our conservation management actions over a short time frame. While this study could not determine a causal link between mowing and nest clustering, we did find that Ripley’s K and GIS were effective in detecting owl nest clustering and show promise for future conservation uses.

  19. An analysis of spatial clustering and implications for wildlife management: a burrowing owl example.

    PubMed

    Fisher, Joshua B; Trulio, Lynne A; Biging, Gregory S; Chromczak, Debra

    2007-03-01

    Analysis tools that combine large spatial and temporal scales are necessary for efficient management of wildlife species, such as the burrowing owl (Athene cunicularia). We assessed the ability of Ripley's K-function analysis integrated into a geographic information system (GIS) to determine changes in burrowing owl nest clustering over two years at NASA Ames Research Center. Specifically, we used these tools to detect changes in spatial and temporal nest clustering before, during, and after conducting management by mowing to maintain low vegetation height at nest burrows. We found that the scale and timing of owl nest clustering matched the scale and timing of our conservation management actions over a short time frame. While this study could not determine a causal link between mowing and nest clustering, we did find that Ripley's K and GIS were effective in detecting owl nest clustering and show promise for future conservation uses.

  20. An Empirical Comparison of Variable Standardization Methods in Cluster Analysis.

    ERIC Educational Resources Information Center

    Schaffer, Catherine M.; Green, Paul E.

    1996-01-01

    The common marketing research practice of standardizing the columns of a persons-by-variables data matrix prior to clustering the entities corresponding to the rows was evaluated with 10 large-scale data sets. Results indicate that the column standardization practice may be problematic for some kinds of data that marketing researchers used for…

  1. Functional Analysis of a Mosquito Short Chain Dehydrogenase Cluster

    PubMed Central

    Mayoral, Jaime G.; Leonard, Kate T.; Defelipe, Lucas A.; Turjansksi, Adrian G.; Nouzova, Marcela; Noriegal, Fernando G.

    2013-01-01

    The short chain dehydrogenases (SDR) constitute one the oldest and largest families of enzymes with over 46,000 members in sequence databases. About 25% of all known dehydrogenases belong to the SDR family. SDR enzymes have critical roles in lipid, amino acid, carbohydrate, hormone and xenobiotic metabolism as well as in redox sensor mechanisms. This family is present in archaea, bacteria, and eukaryota, emphasizing their versatility and fundamental importance for metabolic processes. We identified a cluster of eight SDRs in the mosquito Aedes aegypti (AaSDRs). Members of the cluster differ in tissue specificity and developmental expression. Heterologous expression produced recombinant proteins that had diverse substrate specificities, but distinct from the conventional insect alcohol (ethanol) dehydrogenases. They are all NADP+-dependent and they have S-enantioselectivity and preference for secondary alcohols with 8–15 carbons. Homology modeling was used to build the structure of AaSDR1 and two additional cluster members. The computational study helped explain the selectivity towards the (10S)-isomers as well as the reduced activity of AaSDR4 and AaSDR9 for longer isoprenoid substrates. Similar clusters of SDRs are present in other species of insects, suggesting similar selection mechanisms causing duplication and diversification of this family of enzymes. PMID:23238893

  2. A SPECTROSCOPIC ANALYSIS OF THE GALACTIC GLOBULAR CLUSTER NGC 6273 (M19)

    SciTech Connect

    Johnson, Christian I.; Caldwell, Nelson; Rich, R. Michael; Pilachowski, Catherine A.; Mateo, Mario; Bailey, John I. III; Crane, Jeffrey D. E-mail: ncaldwell@cfa.harvard.edu E-mail: catyp@astro.indiana.edu E-mail: baileyji@umich.edu

    2015-08-15

    A combined effort utilizing spectroscopy and photometry has revealed the existence of a new globular cluster class. These “anomalous” clusters, which we refer to as “iron-complex” clusters, are differentiated from normal clusters by exhibiting large (≳0.10 dex) intrinsic metallicity dispersions, complex sub-giant branches, and correlated [Fe/H] and s-process enhancements. In order to further investigate this phenomenon, we have measured radial velocities and chemical abundances for red giant branch stars in the massive, but scarcely studied, globular cluster NGC 6273. The velocities and abundances were determined using high resolution (R ∼ 27,000) spectra obtained with the Michigan/Magellan Fiber System (M2FS) and MSpec spectrograph on the Magellan–Clay 6.5 m telescope at Las Campanas Observatory. We find that NGC 6273 has an average heliocentric radial velocity of +144.49 km s{sup −1} (σ = 9.64 km s{sup −1}) and an extended metallicity distribution ([Fe/H] = −1.80 to −1.30) composed of at least two distinct stellar populations. Although the two dominant populations have similar [Na/Fe], [Al/Fe], and [α/Fe] abundance patterns, the more metal-rich stars exhibit significant [La/Fe] enhancements. The [La/Eu] data indicate that the increase in [La/Fe] is due to almost pure s-process enrichment. A third more metal-rich population with low [X/Fe] ratios may also be present. Therefore, NGC 6273 joins clusters such as ω Centauri, M2, M22, and NGC 5286 as a new class of iron-complex clusters exhibiting complicated star formation histories.

  3. Representation in GIS of the Results Obtained by Cluster Analysis in Territorial Profile

    NASA Astrophysics Data System (ADS)

    Dârdalą, Marian; Furtuną, Titus Felix; Reveiu, Adriana

    2010-05-01

    Cluster analysis involves grouping characteristics analyzed by the values of grouping parameters. The statistical cluster analysis uses the method of minimum dispersion of hierarchical tree method, in order to obtain the information necessary to group the administrative units. Territorial profile economic analyses can use the cluster analysis in order to make hierarchical classifications, according to performance, strategies. The hierarchical tree methods consist in identifying certain hierarchies used to take into consideration the units. According to their organization mode, clusters can be: vertically integrated, horizontally integrated, emerging clusters. With GIS, spatial data clustering can be applied to spatial data to represent the territorial analysis performed. In terms of viewing the results of cluster analysis by GIS, a usual way is to generate cartograms. In this case, a cartogram supposes defining a colors ramp, having a number of colors equal with the number of groups that divide the collectivity. The parameters used as the basis of the clustering process may exist as independent data or can be stored in the database of an informatic system. As a case study we implemented an ArcMap extension to analyze the clusters by selecting the grouping parameters and by setting the number of groups that will divide the collectivity. Cartograma can be defined taking into consideration multi-level administrative division of the territory. For example, Romania uses the split on villages, counties, regions and macro-regions. Analysis can be applied on different levels of administrative organization by aggregating the values of parameters. For example, the value of a parameter for a county can be obtained by aggregating all parameter values, for all villages, belonging to the county.

  4. Dynamical analysis of the cluster pair: A3407 + A3408

    NASA Astrophysics Data System (ADS)

    Nascimento, R. S.; Ribeiro, A. L. B.; Trevisan, M.; Carrasco, E. R.; Plana, H.; Dupke, R.

    2016-08-01

    We carried out a dynamical study of the galaxy cluster pair A3407 and A3408 based on a spectroscopic survey obtained with the 4 metre Blanco telescope at the Cerro Tololo Interamerican Observatory, plus 6dF data, and ROSAT All-Sky Survey. The sample consists of 122 member galaxies brighter than mR = 20. Our main goal is to probe the galaxy dynamics in this field and verify if the sample constitutes a single galaxy system or corresponds to an ongoing merging process. Statistical tests were applied to clusters members showing that both the composite system A3407 + A3408 as well as each individual cluster have Gaussian velocity distribution. A velocity gradient of ˜847 ± 114 km s- 1 was identified around the principal axis of the projected distribution of galaxies, indicating that the global field may be rotating. Applying the KMM algorithm to the distribution of galaxies, we found that the solution with two clusters is better than the single unit solution at the 99 per cent cl. This is consistent with the X-ray distribution around this field, which shows no common X-ray halo involving A3407 and A3408. We also estimated virial masses and applied a two-body model to probe the dynamics of the pair. The more likely scenario is that in which the pair is gravitationally bound and probably experiences a collapse phase, with the cluster cores crossing in less than ˜1 h-1 Gyr, a pre-merger scenario. The complex X-ray morphology, the gas temperature, and some signs of galaxy evolution in A3408 suggest a post-merger scenario, with cores having crossed each other ˜1.65 h-1 Gyr ago, as an alternative solution.

  5. Galaxy cluster mass estimation from stacked spectroscopic analysis

    NASA Astrophysics Data System (ADS)

    Farahi, Arya; Evrard, August E.; Rozo, Eduardo; Rykoff, Eli S.; Wechsler, Risa H.

    2016-08-01

    We use simulated galaxy surveys to study: (i) how galaxy membership in redMaPPer clusters maps to the underlying halo population, and (ii) the accuracy of a mean dynamical cluster mass, Mσ(λ), derived from stacked pairwise spectroscopy of clusters with richness λ. Using ˜130 000 galaxy pairs patterned after the Sloan Digital Sky Survey (SDSS) redMaPPer cluster sample study of Rozo et al., we show that the pairwise velocity probability density function of central-satellite pairs with mi < 19 in the simulation matches the form seen in Rozo et al. Through joint membership matching, we deconstruct the main Gaussian velocity component into its halo contributions, finding that the top-ranked halo contributes ˜60 per cent of the stacked signal. The halo mass scale inferred by applying the virial scaling of Evrard et al. to the velocity normalization matches, to within a few per cent, the log-mean halo mass derived through galaxy membership matching. We apply this approach, along with miscentring and galaxy velocity bias corrections, to estimate the log-mean matched halo mass at z = 0.2 of SDSS redMaPPer clusters. Employing the velocity bias constraints of Guo et al., we find = ln (M30) + αm ln (λ/30) with M30 = 1.56 ± 0.35 × 1014 M⊙ and αm = 1.31 ± 0.06stat ± 0.13sys. Systematic uncertainty in the velocity bias of satellite galaxies overwhelmingly dominates the error budget.

  6. (30)Si mole fraction of a silicon material highly enriched in (28)Si determined by instrumental neutron activation analysis.

    PubMed

    D'Agostino, Giancarlo; Di Luzio, Marco; Mana, Giovanni; Oddone, Massimo; Pramann, Axel; Prata, Michele

    2015-06-01

    The latest determination of the Avogadro constant, carried out by counting the atoms in a pure silicon crystal highly enriched in (28)Si, reached the target 2 × 10(-8) relative uncertainty required for the redefinition of the kilogram based on the Planck constant. The knowledge of the isotopic composition of the enriched silicon material is central; it is measured by isotope dilution mass spectrometry. In this work, an independent estimate of the (30)Si mole fraction was obtained by applying a relative measurement protocol based on Instrumental Neutron Activation Analysis. The amount of (30)Si isotope was determined by counting the 1266.1 keV γ-photons emitted during the radioactive decay of the radioisotope (31)Si produced via the neutron capture reaction (30)Si(n,γ)(31)Si. The x((30)Si) = 1.043(19) × 10(-6) mol mol(-1) is consistent with the value currently adopted by the International Avogadro Coordination.

  7. NeAT: a toolbox for the analysis of biological networks, clusters, classes and pathways.

    PubMed

    Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Sand, Olivier; Janky, Rekin's; Vanderstocken, Gilles; Deville, Yves; van Helden, Jacques

    2008-07-01

    The network analysis tools (NeAT) (http://rsat.ulb.ac.be/neat/) provide a user-friendly web access to a collection of modular tools for the analysis of networks (graphs) and clusters (e.g. microarray clusters, functional classes, etc.). A first set of tools supports basic operations on graphs (comparison between two graphs, neighborhood of a set of input nodes, path finding and graph randomization). Another set of programs makes the connection between networks and clusters (graph-based clustering, cliques discovery and mapping of clusters onto a network). The toolbox also includes programs for detecting significant intersections between clusters/classes (e.g. clusters of co-expression versus functional classes of genes). NeAT are designed to cope with large datasets and provide a flexible toolbox for analyzing biological networks stored in various databases (protein interactions, regulation and metabolism) or obtained from high-throughput experiments (two-hybrid, mass-spectrometry and microarrays). The web interface interconnects the programs in predefined analysis flows, enabling to address a series of questions about networks of interest. Each tool can also be used separately by entering custom data for a specific analysis. NeAT can also be used as web services (SOAP/WSDL interface), in order to design programmatic workflows and integrate them with other available resources.

  8. Groundwater source contamination mechanisms: physicochemical profile clustering, risk factor analysis and multivariate modelling.

    PubMed

    Hynds, Paul; Misstear, Bruce D; Gill, Laurence W; Murphy, Heather M

    2014-04-01

    An integrated domestic well sampling and "susceptibility assessment" programme was undertaken in the Republic of Ireland from April 2008 to November 2010. Overall, 211 domestic wells were sampled, assessed and collated with local climate data. Based upon groundwater physicochemical profile, three clusters have been identified and characterised by source type (borehole or hand-dug well) and local geological setting. Statistical analysis indicates that cluster membership is significantly associated with the prevalence of bacteria (p=0.001), with mean Escherichia coli presence within clusters ranging from 15.4% (Cluster-1) to 47.6% (Cluster-3). Bivariate risk factor analysis shows that on-site septic tank presence was the only risk factor significantly associated (p<0.05) with bacterial presence within all clusters. Point agriculture adjacency was significantly associated with both borehole-related clusters. Well design criteria were associated with hand-dug wells and boreholes in areas characterised by high permeability subsoils, while local geological setting was significant for hand-dug wells and boreholes in areas dominated by low/moderate permeability subsoils. Multivariate susceptibility models were developed for all clusters, with predictive accuracies of 84% (Cluster-1) to 91% (Cluster-2) achieved. Septic tank setback was a common variable within all multivariate models, while agricultural sources were also significant, albeit to a lesser degree. Furthermore, well liner clearance was a significant factor in all models, indicating that direct surface ingress is a significant well contamination mechanism. Identification and elucidation of cluster-specific contamination mechanisms may be used to develop improved overall risk management and wellhead protection strategies, while also informing future remediation and maintenance efforts.

  9. A Conserved BDNF, Glutamate- and GABA-Enriched Gene Module Related to Human Depression Identified by Coexpression Meta-Analysis and DNA Variant Genome-Wide Association Studies

    PubMed Central

    Chang, Lun-Ching; Jamain, Stephane; Lin, Chien-Wei; Rujescu, Dan; Tseng, George C.; Sibille, Etienne

    2014-01-01

    Large scale gene expression (transcriptome) analysis and genome-wide association studies (GWAS) for single nucleotide polymorphisms have generated a considerable amount of gene- and disease-related information, but heterogeneity and various sources of noise have limited the discovery of disease mechanisms. As systematic dataset integration is becoming essential, we developed methods and performed meta-clustering of gene coexpression links in 11 transcriptome studies from postmortem brains of human subjects with major depressive disorder (MDD) and non-psychiatric control subjects. We next sought enrichment in the top 50 meta-analyzed coexpression modules for genes otherwise identified by GWAS for various sets of disorders. One coexpression module of 88 genes was consistently and significantly associated with GWAS for MDD, other neuropsychiatric disorders and brain functions, and for medical illnesses with elevated clinical risk of depression, but not for other diseases. In support of the superior discriminative power of this novel approach, we observed no significant enrichment for GWAS-related genes in coexpression modules extracted from single studies or in meta-modules using gene expression data from non-psychiatric control subjects. Genes in the identified module encode proteins implicated in neuronal signaling and structure, including glutamate metabotropic receptors (GRM1, GRM7), GABA receptors (GABRA2, GABRA4), and neurotrophic and development-related proteins [BDNF, reelin (RELN), Ephrin receptors (EPHA3, EPHA5)]. These results are consistent with the current understanding of molecular mechanisms of MDD and provide a set of putative interacting molecular partners, potentially reflecting components of a functional module across cells and biological pathways that are synchronously recruited in MDD, other brain disorders and MDD-related illnesses. Collectively, this study demonstrates the importance of integrating transcriptome data, gene coexpression modules

  10. A Unified Framework for Clustering and Quantitative Analysis of White Matter Fiber Tracts

    PubMed Central

    Maddah, Mahnaz; Grimson, W. Eric L.; Warfield, Simon K.; Wells, William M.

    2008-01-01

    We present a novel approach for joint clustering and point-by-point mapping of white matter fiber pathways. Knowledge of the point correspondence along the fiber pathways is not only necessary for accurate clustering of the trajectories into fiber bundles, but also crucial for any tract-oriented quantitative analysis. We employ an expectation-maximization (EM) algorithm to cluster the trajectories in a Gamma mixture model context. The result of clustering is the probabilistic assignment of the fiber trajectories to each cluster, an estimate of the cluster parameters, i.e. spatial mean and variance, and point correspondences. The fiber bundles are modeled by the mean trajectory and its spatial variation. Point-by-point correspondence of the trajectories within a bundle is obtained by constructing a distance map and a label map from each cluster center at every iteration of the EM algorithm. This offers a time-efficient alternative to pairwise curve matching of all trajectories with respect to each cluster center. The proposed method has the potential to benefit from an anatomical atlas of fiber tracts by incorporating it as prior information in the EM algorithm. The algorithm is also capable of handling outliers in a principled way. The presented results confirm the efficiency and effectiveness of the proposed framework for quantitative analysis of diffusion tensor MRI. PMID:18180197

  11. Comprehensive Meta-analysis of Ontology Annotated 16S rRNA Profiles Identifies Beta Diversity Clusters of Environmental Bacterial Communities

    PubMed Central

    Henschel, Andreas; Anwar, Muhammad Zohaib; Manohar, Vimitha

    2015-01-01

    Comprehensive mapping of environmental microbiomes in terms of their compositional features remains a great challenge in understanding the microbial biosphere of the Earth. It bears promise to identify the driving forces behind the observed community patterns and whether community assembly happens deterministically. Advances in Next Generation Sequencing allow large community profiling studies, exceeding sequencing data output of conventional methods in scale by orders of magnitude. However, appropriate collection systems are still in a nascent state. We here present a database of 20,427 diverse environmental 16S rRNA profiles from 2,426 independent studies, which forms the foundation of our meta-analysis. We conducted a sample size adaptive all-against-all beta diversity comparison while also respecting phylogenetic relationships of Operational Taxonomic Units(OTUs). After conventional hierarchical clustering we systematically test for enrichment of Environmental Ontology terms and their abstractions in all possible clusters. This post-hoc algorithm provides a novel formalism that quantifies to what extend compositional and semantic similarity of microbial community samples coincide. We automatically visualize significantly enriched subclusters on a comprehensive dendrogram of microbial communities. As a result we obtain the hitherto most differentiated and comprehensive view on global patterns of microbial community diversity. We observe strong clusterability of microbial communities in ecosystems such as human/mammal-associated, geothermal, fresh water, plant-associated, soils and rhizosphere microbiomes, whereas hypersaline and anthropogenic samples are less homogeneous. Moreover, saline samples appear less cohesive in terms of compositional properties than previously reported. PMID:26458130

  12. Transcriptome outlier analysis implicates schizophrenia susceptibility genes and enriches putatively functional rare genetic variants

    PubMed Central

    Duan, Jubao; Sanders, Alan R.; Moy, Winton; Drigalenko, Eugene I.; Brown, Eric C.; Freda, Jessica; Leites, Catherine; Göring, Harald H. H.; Gejman, Pablo V.

    2015-01-01

    We searched a gene expression dataset comprised of 634 schizophrenia (SZ) cases and 713 controls for expression outliers (i.e., extreme tails of the distribution of transcript expression values) with SZ cases overrepresented compared with controls. These outlier genes were enriched for brain expression and for genes known to be associated with neurodevelopmental disorders. SZ cases showed higher outlier burden (i.e., total outlier events per subject) than controls for genes within copy number variants (CNVs) associated with SZ or neurodevelopmental disorders. Outlier genes were enriched for CNVs and for rare putative regulatory variants, but this only explained a small proportion of the outlier subjects, highlighting the underlying presence of additional genetic and potentially, epigenetic mechanisms. PMID:26022996

  13. Analysis of Density Changes in Plutonium Observed from Accelerated Aging Using Pu-238 Enrichment

    SciTech Connect

    Chung, B W; Saw, C K; Thompson, S R; Quick, T M; Woods, C H; Hopkins, D J; Ebbinghaus, B B

    2006-07-11

    We present dimensional and density changes in an aging plutonium alloy enriched with 7.3 at.% of {sup 238}Pu and reference alloys of various ages. After 45 equivalent years of aging, the enriched alloys at 35 C have swelled in volume by 0.14 to 0.16% and now exhibit a near linear volume increase, without void swelling. Based on X-ray diffraction measurements, the lattice expansion by self-irradiation appears to be the primary cause for dimensional changes during the initial 2-3 years of aging. Following the initial transient, the density change is primarily cause by a constant helium in-growth rate as a result of {alpha}-particle decay.

  14. Transcriptome outlier analysis implicates schizophrenia susceptibility genes and enriches putatively functional rare genetic variants.

    PubMed

    Duan, Jubao; Sanders, Alan R; Moy, Winton; Drigalenko, Eugene I; Brown, Eric C; Freda, Jessica; Leites, Catherine; Göring, Harald H H; Gejman, Pablo V

    2015-08-15

    We searched a gene expression dataset comprised of 634 schizophrenia (SZ) cases and 713 controls for expression outliers (i.e., extreme tails of the distribution of transcript expression values) with SZ cases overrepresented compared with controls. These outlier genes were enriched for brain expression and for genes known to be associated with neurodevelopmental disorders. SZ cases showed higher outlier burden (i.e., total outlier events per subject) than controls for genes within copy number variants (CNVs) associated with SZ or neurodevelopmental disorders. Outlier genes were enriched for CNVs and for rare putative regulatory variants, but this only explained a small proportion of the outlier subjects, highlighting the underlying presence of additional genetic and potentially, epigenetic mechanisms.

  15. Underwater Explosion Analysis of Hexogen-Enriched Novel Hydrogen Storage Alloy

    NASA Astrophysics Data System (ADS)

    Chen, Yuan; Chen, Xiang; Wu, Dejun; Xu, Sen; Liu, Dabin; Xu, Minxiao

    2016-01-01

    A novel hydrogen storage alloy was used in hexogen-based thermobaric explosive (RDX-based TBE). Two types of fashioned explosive charges with mass of 160 g and 500 g were used in this work. The energy of TBE was tested by underwater explosion. The results indicate hexogen-enriched novel hydrogen storage alloy can produce higher bubble energy than that enriched aluminum. The total useful energy was 4.7 % (160 g) and 6.4 % (500 g) higher than an explosive with the same aluminum content, and Trotyl (TNT) equivalent of 2.1 times. The heat of explosion test shows the similar result that the novel hydrogen storage alloy can improve the total energy, about 7.9 % higher than the aluminized.

  16. Refined phosphopeptide enrichment by phosphate additive and the analysis of human brain phosphoproteome.

    PubMed

    Tan, Haiyan; Wu, Zhiping; Wang, Hong; Bai, Bing; Li, Yuxin; Wang, Xusheng; Zhai, Bo; Beach, Thomas G; Peng, Junmin

    2015-01-01

    Alzheimer's disease (AD) is the most common form of dementia, characterized by progressive loss of cognitive function. One of the pathological hallmarks of AD is the formation of neurofibrillary tangles composed of abnormally hyperphosphorylated tau protein, but global deregulation of protein phosphorylation in AD is not well analyzed. Here, we report a pilot investigation of AD phosphoproteome by titanium dioxide enrichment coupled with high resolution LC-MS/MS. During the optimization of the enrichment method, we found that phosphate ion at a low concentration (e.g. 1 mM) worked efficiently as a nonphosphopeptide competitor to reduce background. The procedure was further tuned with respect to peptide-to-bead ratio, phosphopeptide recovery, and purity. Using this refined method and 9 h LC-MS/MS, we analyzed phosphoproteome in one milligram of digested AD brain lysate, identifying 5243 phosphopeptides containing 3715 nonredundant phosphosites on 1455 proteins, including 31 phosphosites on the tau protein. This modified enrichment method is simple and highly efficient. The AD case study demonstrates its feasibility of dissecting phosphoproteome in a limited amount of postmortem human brain. All MS data have been deposited in the ProteomeXchange with identifier PXD001180 (http://proteomecentral.proteomexchange.org/dataset/PXD001180). PMID:25307156

  17. Analysis of expressed sequence tags generated from full-length enriched cDNA libraries of melon

    PubMed Central

    2011-01-01

    Background Melon (Cucumis melo), an economically important vegetable crop, belongs to the Cucurbitaceae family which includes several other important crops such as watermelon, cucumber, and pumpkin. It has served as a model system for sex determination and vascular biology studies. However, genomic resources currently available for melon are limited. Result We constructed eleven full-length enriched and four standard cDNA libraries from fruits, flowers, leaves, roots, cotyledons, and calluses of four different melon genotypes, and generated 71,577 and 22,179 ESTs from full-length enriched and standard cDNA libraries, respectively. These ESTs, together with ~35,000 ESTs available in public domains, were assembled into 24,444 unigenes, which were extensively annotated by comparing their sequences to different protein and functional domain databases, assigning them Gene Ontology (GO) terms, and mapping them onto metabolic pathways. Comparative analysis of melon unigenes and other plant genomes revealed that 75% to 85% of melon unigenes had homologs in other dicot plants, while approximately 70% had homologs in monocot plants. The analysis also identified 6,972 gene families that were conserved across dicot and monocot plants, and 181, 1,192, and 220 gene families specific to fleshy fruit-bearing plants, the Cucurbitaceae family, and melon, respectively. Digital expression analysis identified a total of 175 tissue-specific genes, which provides a valuable gene sequence resource for future genomics and functional studies. Furthermore, we identified 4,068 simple sequence repeats (SSRs) and 3,073 single nucleotide polymorphisms (SNPs) in the melon EST collection. Finally, we obtained a total of 1,382 melon full-length transcripts through the analysis of full-length enriched cDNA clones that were sequenced from both ends. Analysis of these full-length transcripts indicated that sizes of melon 5' and 3' UTRs were similar to those of tomato, but longer than many other dicot

  18. Development of microsatellite markers from an enriched genomic library for genetic analysis of melon (Cucumis melo L.)

    PubMed Central

    Ritschel, Patricia Silva; Lins, Tulio Cesar de Lima; Tristan, Rodrigo Lourenço; Buso, Gláucia Salles Cortopassi; Buso, José Amauri; Ferreira, Márcio Elias

    2004-01-01

    Background Despite the great advances in genomic technology observed in several crop species, the availability of molecular tools such as microsatellite markers has been limited in melon (Cucumis melo L.) and cucurbit species. The development of microsatellite markers will have a major impact on genetic analysis and breeding of melon, especially on the generation of marker saturated genetic maps and implementation of marker assisted breeding programs. Genomic microsatellite enriched libraries can be an efficient alternative for marker development in such species. Results Seven hundred clones containing microsatellite sequences from a Tsp-AG/TC microsatellite enriched library were identified and one-hundred and forty-four primer pairs designed and synthesized. When 67 microsatellite markers were tested on a panel of melon and other cucurbit accessions, 65 revealed DNA polymorphisms among the melon accessions. For some cucurbit species, such as Cucumis sativus, up to 50% of the melon microsatellite markers could be readily used for DNA polymophism assessment, representing a significant reduction of marker development costs. A random sample of 25 microsatellite markers was extracted from the new microsatellite marker set and characterized on 40 accessions of melon, generating an allelic frequency database for the species. The average expected heterozygosity was 0.52, varying from 0.45 to 0.70, indicating that a small set of selected markers should be sufficient to solve questions regarding genotype identity and variety protection. Genetic distances based on microsatellite polymorphism were congruent with data obtained from RAPD marker analysis. Mapping analysis was initiated with 55 newly developed markers and most primers showed segregation according to Mendelian expectations. Linkage analysis detected linkage between 56% of the markers, distributed in nine linkage groups. Conclusions Genomic library microsatellite enrichment is an efficient procedure for marker

  19. Analysis of Cluster spacecraft potential during active control

    NASA Astrophysics Data System (ADS)

    Torkar, K.; Fehringer, M.; Escoubet, C. P.; André, M.; Pedersen, A.; Svenes, K. R.; Décréau, P. M. E.

    The floating potential of a spacecraft is determined by an equilibrium between photo-electron emission from the sunlit spacecraft surfaces and the plasma electron current, while other currents play a secondary role. On the Cluster spacecraft, the presence of the experiment ASPOC to control the potential by an ion beam with currents up to several tens of microamperes and energies of several keV provides an opportunity to study the interaction between the spacecraft and the ambient plasma with the current of the artificial ion beam as an additional parameter. The effect of active control on the Cluster spacecraft potential in the various plasma environments is presented in an overall statistics. Changes of the potential resulting from switching the ion beam current to different levels serve to calibrate the density-potential relationship.

  20. SU-E-J-98: Radiogenomics: Correspondence Between Imaging and Genetic Features Based On Clustering Analysis

    SciTech Connect

    Harmon, S; Wendelberger, B; Jeraj, R

    2014-06-01

    Purpose: Radiogenomics aims to establish relationships between patient genotypes and imaging phenotypes. An open question remains on how best to integrate information from these distinct datasets. This work investigates if similarities in genetic features across patients correspond to similarities in PET-imaging features, assessed with various clustering algorithms. Methods: [{sup 18}F]FDG PET data was obtained for 26 NSCLC patients from a public database (TCIA). Tumors were contoured using an in-house segmentation algorithm combining gradient and region-growing techniques; resulting ROIs were used to extract 54 PET-based features. Corresponding genetic microarray data containing 48,778 elements were also obtained for each tumor. Given mismatch in feature sizes, two dimension reduction techniques were also applied to the genetic data: principle component analysis (PCA) and selective filtering of 25 NSCLC-associated genes-ofinterest (GOI). Gene datasets (full, PCA, and GOI) and PET feature datasets were independently clustered using K-means and hierarchical clustering using variable number of clusters (K). Jaccard Index (JI) was used to score similarity of cluster assignments across different datasets. Results: Patient clusters from imaging data showed poor similarity to clusters from gene datasets, regardless of clustering algorithms or number of clusters (JI{sub mean}= 0.3429±0.1623). Notably, we found clustering algorithms had different sensitivities to data reduction techniques. Using hierarchical clustering, the PCA dataset showed perfect cluster agreement to the full-gene set (JI =1) for all values of K, and the agreement between the GOI set and the full-gene set decreased as number of clusters increased (JI=0.9231 and 0.5769 for K=2 and 5, respectively). K-means clustering assignments were highly sensitive to data reduction and showed poor stability for different values of K (JI{sub range}: 0.2301–1). Conclusion: Using commonly-used clustering algorithms

  1. Insights into quasar UV spectra using unsupervised clustering analysis

    NASA Astrophysics Data System (ADS)

    Tammour, A.; Gallagher, S. C.; Daley, M.; Richards, G. T.

    2016-06-01

    Machine learning techniques can provide powerful tools to detect patterns in multidimensional parameter space. We use K-means - a simple yet powerful unsupervised clustering algorithm which picks out structure in unlabelled data - to study a sample of quasar UV spectra from the Quasar Catalog of the 10th Data Release of the Sloan Digital Sky Survey (SDSS-DR10) of Paris et al. Detecting patterns in large data sets helps us gain insights into the physical conditions and processes giving rise to the observed properties of quasars. We use K-means to find clusters in the parameter space of the equivalent width (EW), the blue- and red-half-width at half-maximum (HWHM) of the Mg II 2800 Å line, the C IV 1549 Å line, and the C III] 1908 Å blend in samples of broad absorption line (BAL) and non-BAL quasars at redshift 1.6-2.1. Using this method, we successfully recover correlations well-known in the UV regime such as the anti-correlation between the EW and blueshift of the C IV emission line and the shape of the ionizing spectra energy distribution (SED) probed by the strength of He II and the Si III]/C III] ratio. We find this to be particularly evident when the properties of C III] are used to find the clusters, while those of Mg II proved to be less strongly correlated with the properties of the other lines in the spectra such as the width of C IV or the Si III]/C III] ratio. We conclude that unsupervised clustering methods (such as K-means) are powerful methods for finding `natural' binning boundaries in multidimensional data sets and discuss caveats and future work.

  2. Photometric analysis of Galactic Stellar Clusters in VVV Survey

    NASA Astrophysics Data System (ADS)

    Mauro, F.; Moni Bidin, C.; Cohen, R. E.; Geisler, D.; Villanova, S.; Chené, A. N.

    2014-10-01

    We show the preliminary results of the study of the structure of the Horizontal Branch of Liller 1 and some results from the Calcium Triplet method using Ks magnitude applied to several Galactic Globular clusters using data from the VISTA Variables in the Via Lactea Survey (Minniti et al. 2010) and obtained with GeMS/GSAOI. The data are extracted with the new automatic VVV-SkZ_pipeline photometric pipeline (Mauro et al. 2013).

  3. Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data

    SciTech Connect

    Data Analysis and Visualization and the Department of Computer Science, University of California, Davis, One Shields Avenue, Davis CA 95616, USA,; nternational Research Training Group ``Visualization of Large and Unstructured Data Sets,'' University of Kaiserslautern, Germany; Computational Research Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA; Genomics Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley CA 94720, USA; Life Sciences Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley CA 94720, USA,; Computer Science Division,University of California, Berkeley, CA, USA,; Computer Science Department, University of California, Irvine, CA, USA,; All authors are with the Berkeley Drosophila Transcription Network Project, Lawrence Berkeley National Laboratory,; Rubel, Oliver; Weber, Gunther H.; Huang, Min-Yu; Bethel, E. Wes; Biggin, Mark D.; Fowlkes, Charless C.; Hendriks, Cris L. Luengo; Keranen, Soile V. E.; Eisen, Michael B.; Knowles, David W.; Malik, Jitendra; Hagen, Hans; Hamann, Bernd

    2008-05-12

    The recent development of methods for extracting precise measurements of spatial gene expression patterns from three-dimensional (3D) image data opens the way for new analyses of the complex gene regulatory networks controlling animal development. We present an integrated visualization and analysis framework that supports user-guided data clustering to aid exploration of these new complex datasets. The interplay of data visualization and clustering-based data classification leads to improved visualization and enables a more detailed analysis than previously possible. We discuss (i) integration of data clustering and visualization into one framework; (ii) application of data clustering to 3D gene expression data; (iii) evaluation of the number of clusters k in the context of 3D gene expression clustering; and (iv) improvement of overall analysis quality via dedicated post-processing of clustering results based on visualization. We discuss the use of this framework to objectively define spatial pattern boundaries and temporal profiles of genes and to analyze how mRNA patterns are controlled by their regulatory transcription factors.

  4. Analysis of Cluster spacecraft potential during active control

    NASA Astrophysics Data System (ADS)

    Torkar, K.; Fehringer, M.; Escoubet, C.; Andre, M.; Pedersen, A.; Svenes, K.; Décréau, P.

    The floating potential of a spacecraft is determined by an equilibrium between photo-electron emission from the sunlit spacecraft surfaces, plasma electron current, and secondary effects. Without spacecraft potential control, the result largely reflects the density and temperature of the ambient plasma. On the Cluster spacecraft, the presence of the experiment ASPOC to control the potential by an ion beam with currents up to several tens of microamperes and energies of several keV provides an opportunity to study the interaction between the spacecraft and the ambient plasma with the current of the artificial ion beam as an additional parameter. Changes of the potential resulting from switching the ion beam current to different levels serve to calibrate the density-potential relationship. Wave data are used to obtain independent information on plasma density. The measurements onboard Cluster are compared with models and data from other spacecraft. After describing the principle of the interaction and showing some events out of the first 1.5 years of operation, an overall statistic is presented, describing the effect of active control on the Cluster spacecraft potential in the various plasma environments.

  5. Variability in body size and shape of UK offshore workers: A cluster analysis approach.

    PubMed

    Stewart, Arthur; Ledingham, Robert; Williams, Hector

    2017-01-01

    Male UK offshore workers have enlarged dimensions compared with UK norms and knowledge of specific sizes and shapes typifying their physiques will assist a range of functions related to health and ergonomics. A representative sample of the UK offshore workforce (n = 588) underwent 3D photonic scanning, from which 19 extracted dimensional measures were used in k-means cluster analysis to characterise physique groups. Of the 11 resulting clusters four somatotype groups were expressed: one cluster was muscular and lean, four had greater muscularity than adiposity, three had equal adiposity and muscularity and three had greater adiposity than muscularity. Some clusters appeared constitutionally similar to others, differing only in absolute size. These cluster centroids represent an evidence-base for future designs in apparel and other applications where body size and proportions affect functional performance. They also constitute phenotypic evidence providing insight into the 'offshore culture' which may underpin the enlarged dimensions of offshore workers. PMID:27633221

  6. Facile synthesis of titania nanoparticles coated carbon nanotubes for selective enrichment of phosphopeptides for mass spectrometry analysis.

    PubMed

    Yan, Yinghua; Lu, Jin; Deng, Chunhui; Zhang, Xiangmin

    2013-03-30

    In this work, titania nanoparticles coated carbon nanotubes (denoted as CNTs/TiO2 composites) were synthesized through a facile but effective solvothermal reaction using titanium isopropoxide as the titania source, isopropyl alcohol as the solvent and as the basic catalyst in the presence of hydrophilic carbon nanotubes. Characterizations using scanning electron microscopy (SEM) and transmission electron microscopy (TEM) indicate that the CNTs/TiO2 composites consist of CNT core and a rough outer layer formed by titania nanoparticles (5-10nm). Measurements using wide angle X-ray diffraction (WAXRD), zeta potential and N2 sorption reveal that the titania shell is formed by anatase titania nanoparticles, and the composites have a high specific surface area of about 104 m(2)/g. By using their high surface area and affinity to phosphopeptides, the CNTs/TiO2 composites were applied to selectively enrich phosphopeptides for mass spectrometry analysis. The high selectivity and capacity of the CNTs/TiO2 composites have been demonstrated by effective enrichment of phosphopeptides from digests of phosphoprotein, protein mixtures of β-casein and bovine serum albumin, human serum and rat brain samples. These results foresee a promising application of the novel CNTs/TiO2 composites in the selective enrichment of phosphopeptides.

  7. How Teachers Use and Manage Their Blogs? A Cluster Analysis of Teachers' Blogs in Taiwan

    ERIC Educational Resources Information Center

    Liu, Eric Zhi-Feng; Hou, Huei-Tse

    2013-01-01

    The development of Web 2.0 has ushered in a new set of web-based tools, including blogs. This study focused on how teachers use and manage their blogs. A sample of 165 teachers' blogs in Taiwan was analyzed by factor analysis, cluster analysis and qualitative content analysis. First, the teachers' blogs were analyzed according to six criteria…

  8. Abundance analysis of an extended sample of open clusters: A search for chemical inhomogeneities

    NASA Astrophysics Data System (ADS)

    Reddy, Arumalla B. S.; Giridhar, Sunetra; Lambert, David L.

    We have initiated a program to explore the presence of chemical inhomogeneities in the Galactic disk using the open clusters as ideal probes. We have analyzed high-dispersion echelle spectra (R ≥ 55,000) of red giant members for eleven open clusters to derive abundances for many elements. The membership to the cluster has been confirmed through their radial velocities and proper motions. The spread in temperatures and gravities being very small among the red giants, nearly the same stellar lines were employed thereby reducing the random errors. The errors of average abundance for the cluster were generally in 0.02 to 0.07 dex range. Our present sample covers galactocentric distances of 8.3 to 11.3 kpc and an age range of 0.2 to 4.3 Gyrs. Our earlier analysis of four open clusters (Reddy A.B.S. et al., 2012, MNRAS, 419,1350) indicate that abundances relative to Fe for elements from Na to Eu are equal within measurement uncertainties to published abundances for thin disk giants in the field. This supports the view that field stars come from disrupted open clusters. In the enlarged sample of eleven open clusters we find cluster to cluster abundance variations for some s- and r- process elements, with certain elements such as Zr and Ba showing large variation. These differences mark the signatures that these clusters had formed under different environmental conditions (Type II SN, Type Ia SN, AGB stars or a mixture of any of these) unique to the time and site of formation. These eleven clusters support the widely held impression that there is an abundance gradient such that the metallicity [Fe/H] at the solar galactocentric distance decreases outwards at about -0.1 dex per kpc.

  9. The CERN analysis facility—a PROOF cluster for day-one physics analysis

    NASA Astrophysics Data System (ADS)

    G-Oetringhaus, J. F.

    2008-07-01

    ALICE (A Large Ion Collider Experiment) at the LHC plans to use a PROOF cluster at CERN (CAF - CERN Analysis Facility) for analysis. The system is especially aimed at the prototyping phase of analyses that need a high number of development iterations and thus require a short response time. Typical examples are the tuning of cuts during the development of an analysis as well as calibration and alignment. Furthermore, the use of an interactive system with very fast response will allow ALICE to extract physics observables out of first data quickly. An additional use case is fast event simulation and reconstruction. A test setup consisting of 40 machines is used for evaluation since May 2006. The PROOF system enables the parallel processing and xrootd the access to files distributed on the test cluster. An automatic staging system for files either catalogued in the ALICE file catalog or stored in the CASTOR mass storage system has been developed. The current setup and ongoing development towards disk quotas and CPU fairshare are described. Furthermore, the integration of PROOF into ALICE's software framework (AliRoot) is discussed.

  10. Effect of Glutamine Enriched Nutrition Support on Surgical Patients with Gastrointestinal Tumor: A Meta-Analysis of Randomized Controlled Trials

    PubMed Central

    Kang, Kai; Shu, Xiao-Liang; Zhang, Yong-Sheng; Liu, Xian-Li; Zhao, Jian

    2015-01-01

    Background: Associations between glutamine (Gln) enriched nutrition support and surgical patients with gastrointestinal (GI) tumor remain controversy. The purpose of this meta-analysis was to assess the effect of Gln enriched nutrition support on surgical patients with GI tumor in term of relevant biochemical indices, immune indices, and clinical outcomes. Methods: Six databases were systematically searched to find eligible randomized controlled trials (RCTs) from 1966 to May 2014. When estimated the analysis indexes, the relative risk (RR) was used as the effect size of the categorical variable, while the weighted mean difference (MD) was used as the effect size of a continuous variable. Meta-analysis was conducted with Rev Man 5.2. Results: Thirteen RCTs, involving 1034 patients, were included in the meta-analysis. The analysis showed that Gln enriched nutrition support was more effective in increasing serum albumin (MD: 0.10; 95% confidence interval [CI]: 0.02–0.18; P < 0.05), serum prealbumin (MD: 1.98; 95% CI: 1.40–2.55; P < 0.05) and serum transferring (MD: 0.35; 95% CI: 0.12–0.57; P < 0.05), concentration of IgG (MD: 1.26; 95% CI: 0.90–1.63; P < 0.05), IgM (MD: 0.18; 95% CI: 0.11–0.25; P < 0.05), IgA (MD: 0.22; 95% CI: 0.10–0.33; P < 0.05), CD3+ (MD: 3.71; 95% CI: 2.57–4.85; P < 0.05) and CD4/CD8 ratio (MD: 0.27; 95% CI: 0.12–0.42; P < 0.05). Meanwhile, it was more significant in decreasing the incidence of infectious complications (RR: 0.67; 95% CI: 0.50–0.90; P < 0.05) and shortening the length of hospital stay (MD: −1.72; 95% CI: −3.31–−0.13; P < 0.05). Conclusions: Glutamine enriched nutrition support was superior in improving immune function, reducing the incidence of infectious complications and shortening the length of hospital stay, playing an important role in the rehabilitation of surgical GI cancer patients. PMID:25591570

  11. Cluster analysis of particulate matter (PM10) and black carbon (BC) concentrations

    NASA Astrophysics Data System (ADS)

    Žibert, Janez; Pražnikar, Jure

    2012-09-01

    The monitoring of air-pollution constituents like particulate matter (PM10) and black carbon (BC) can provide information about air quality and the dynamics of emissions. Air quality depends on natural and anthropogenic sources of emissions as well as the weather conditions. For a one-year period the diurnal concentrations of PM10 and BC in the Port of Koper were analysed by clustering days into similar groups according to the similarity of the BC and PM10 hourly derived day-profiles without any prior assumptions about working and non-working days, weather conditions or hot and cold seasons. The analysis was performed by using k-means clustering with the squared Euclidean distance as the similarity measure. The analysis showed that 10 clusters in the BC case produced 3 clusters with just one member day and 7 clusters that encompasses more than one day with similar BC profiles. Similar results were found in the PM10 case, where one cluster has a single-member day, while 7 clusters contain several member days. The clustering analysis revealed that the clusters with less pronounced bimodal patterns and low hourly and average daily concentrations for both types of measurements include the most days in the one-year analysis. A typical day profile of the BC measurements includes a bimodal pattern with morning and evening peaks, while the PM10 measurements reveal a less pronounced bimodality. There are also clusters with single-peak day-profiles. The BC data in such cases exhibit morning peaks, while the PM10 data consist of noon or afternoon single peaks. Single pronounced peaks can be explained by appropriate cluster wind speed profiles. The analysis also revealed some special day-profiles. The BC cluster with a high midnight peak at 30/04/2010 and the PM10 cluster with the highest observed concentration of PM10 at 01/05/2010 (208.0 μg m-3) coincide with 1 May, which is a national holiday in Slovenia and has very strong tradition of bonfire parties. The clustering of

  12. Age determination of highly enriched uranium: separation and analysis of 231Pa.

    PubMed

    Morgenstern, A; Apostolidis, C; Mayer, K

    2002-11-01

    An analytical procedure has been developed for the age determination of highly enriched uranium samples exploiting the mother/daughter pair 235U/231Pa. Protactinium is separated from bulk uranium through highly selective sorption to silica gel and is subsequently quantified using alpha-spectrometry. The method has been validated using uranium standard reference materials of known ages. It affords decontamination factors exceeding 2.5 x 10(7), overall recoveries in the range of 80-85%, and a combined uncertainty below 5%.

  13. Age determination of highly enriched uranium: separation and analysis of 231Pa.

    PubMed

    Morgenstern, A; Apostolidis, C; Mayer, K

    2002-11-01

    An analytical procedure has been developed for the age determination of highly enriched uranium samples exploiting the mother/daughter pair 235U/231Pa. Protactinium is separated from bulk uranium through highly selective sorption to silica gel and is subsequently quantified using alpha-spectrometry. The method has been validated using uranium standard reference materials of known ages. It affords decontamination factors exceeding 2.5 x 10(7), overall recoveries in the range of 80-85%, and a combined uncertainty below 5%. PMID:12433081

  14. MMPI-2: Cluster Analysis of Personality Profiles in Perinatal Depression—Preliminary Evidence

    PubMed Central

    Grillo, Alessandra; Lauriola, Marco; Giacchetti, Nicoletta

    2014-01-01

    Background. To assess personality characteristics of women who develop perinatal depression. Methods. The study started with a screening of a sample of 453 women in their third trimester of pregnancy, to which was administered a survey data form, the Edinburgh Postnatal Depression Scale (EPDS) and the Minnesota Multiphasic Personality Inventory 2 (MMPI-2). A clinical group of subjects with perinatal depression (PND, 55 subjects) was selected; clinical and validity scales of MMPI-2 were used as predictors in hierarchical cluster analysis carried out. Results. The analysis identified three clusters of personality profile: two “clinical” clusters (1 and 3) and an “apparently common” one (cluster 2). The first cluster (39.5%) collects structures of personality with prevalent obsessive or dependent functioning tending to develop a “psychasthenic” depression; the third cluster (13.95%) includes women with prevalent borderline functioning tending to develop “dysphoric” depression; the second cluster (46.5%) shows a normal profile with a “defensive” attitude, probably due to the presence of defense mechanisms or to the fear of stigma. Conclusion. Characteristics of personality have a key role in clinical manifestations of perinatal depression; it is important to detect them to identify mothers at risk and to plan targeted therapeutic interventions. PMID:25574499

  15. Mitochondrial capture enriches mito-DNA 100 fold, enabling PCR-free mitogenomics biodiversity analysis.

    PubMed

    Liu, Shanlin; Wang, Xin; Xie, Lin; Tan, Meihua; Li, Zhenyu; Su, Xu; Zhang, Hao; Misof, Bernhard; Kjer, Karl M; Tang, Min; Niehuis, Oliver; Jiang, Hui; Zhou, Xin

    2016-03-01

    Biodiversity analyses based on next-generation sequencing (NGS) platforms have developed by leaps and bounds in recent years. A PCR-free strategy, which can alleviate taxonomic bias, was considered as a promising approach to delivering reliable species compositions of targeted environments. The major impediment of such a method is the lack of appropriate mitochondrial DNA enrichment ways. Because mitochondrial genomes (mitogenomes) make up only a small proportion of total DNA, PCR-free methods will inevitably result in a huge excess of data (>99%). Furthermore, the massive volume of sequence data is highly demanding on computing resources. Here, we present a mitogenome enrichment pipeline via a gene capture chip that was designed by virtue of the mitogenome sequences of the 1000 Insect Transcriptome Evolution project (1KITE, www.1kite.org). A mock sample containing 49 species was used to evaluate the efficiency of the mitogenome capture method. We demonstrate that the proportion of mitochondrial DNA can be increased by approximately 100-fold (from the original 0.47% to 42.52%). Variation in phylogenetic distances of target taxa to the probe set could in principle result in bias in abundance. However, the frequencies of input taxa were largely maintained after capture (R(2) = 0.81). We suggest that our mitogenome capture approach coupled with PCR-free shotgun sequencing could provide ecological researchers an efficient NGS method to deliver reliable biodiversity assessment.

  16. A Metaproteomic Analysis of the Response of a Freshwater Microbial Community under Nutrient Enrichment

    PubMed Central

    Russo, David A.; Couto, Narciso; Beckerman, Andrew P.; Pandhal, Jagroop

    2016-01-01

    Eutrophication can lead to an uncontrollable increase in algal biomass, which has repercussions for the entire microbial and pelagic community. Studies have shown how nutrient enrichment affects microbial species succession, however details regarding the impact on community functionality are rare. Here, we applied a metaproteomic approach to investigate the functional changes to algal and bacterial communities, over time, in oligotrophic and eutrophic conditions, in freshwater microcosms. Samples were taken early during algal and cyanobacterial dominance and later under bacterial dominance. 1048 proteins, from the two treatments and two timepoints, were identified and quantified by their exponentially modified protein abundance index. In oligotrophic conditions, Bacteroidetes express extracellular hydrolases and Ton-B dependent receptors to degrade and transport high molecular weight compounds captured while attached to the phycosphere. Alpha- and Beta-proteobacteria were found to capture different substrates from algal exudate (carbohydrates and amino acids, respectively) suggesting resource partitioning to avoid direct competition. In eutrophic conditions, environmental adaptation proteins from cyanobacteria suggested better resilience compared to algae in a low carbon nutrient enriched environment. This study provides insight into differences in functional microbial processes between oligo- and eutrophic conditions at different timepoints and highlights how primary producers control bacterial resources in freshwater environments. The data have been deposited to the ProteomeXchange with identifier PXD004592. PMID:27536273

  17. A Metaproteomic Analysis of the Response of a Freshwater Microbial Community under Nutrient Enrichment.

    PubMed

    Russo, David A; Couto, Narciso; Beckerman, Andrew P; Pandhal, Jagroop

    2016-01-01

    Eutrophication can lead to an uncontrollable increase in algal biomass, which has repercussions for the entire microbial and pelagic community. Studies have shown how nutrient enrichment affects microbial species succession, however details regarding the impact on community functionality are rare. Here, we applied a metaproteomic approach to investigate the functional changes to algal and bacterial communities, over time, in oligotrophic and eutrophic conditions, in freshwater microcosms. Samples were taken early during algal and cyanobacterial dominance and later under bacterial dominance. 1048 proteins, from the two treatments and two timepoints, were identified and quantified by their exponentially modified protein abundance index. In oligotrophic conditions, Bacteroidetes express extracellular hydrolases and Ton-B dependent receptors to degrade and transport high molecular weight compounds captured while attached to the phycosphere. Alpha- and Beta-proteobacteria were found to capture different substrates from algal exudate (carbohydrates and amino acids, respectively) suggesting resource partitioning to avoid direct competition. In eutrophic conditions, environmental adaptation proteins from cyanobacteria suggested better resilience compared to algae in a low carbon nutrient enriched environment. This study provides insight into differences in functional microbial processes between oligo- and eutrophic conditions at different timepoints and highlights how primary producers control bacterial resources in freshwater environments. The data have been deposited to the ProteomeXchange with identifier PXD004592. PMID:27536273

  18. Proteomic analysis of mouse liver plasma membrane: use of differential extraction to enrich hydrophobic membrane proteins.

    PubMed

    Zhang, Lijun; Xie, Jinyun; Wang, Xi'e; Liu, Xiaohui; Tang, Xinke; Cao, Rui; Hu, Weijun; Nie, Song; Fan, Chunming; Liang, Songping

    2005-11-01

    To comprehensively identify proteins of liver plasma membrane (PM), we isolated PMs from mouse liver by sucrose density gradient centrifugation. An optimized extraction method for whole PM proteins and several methods of differential extraction expected to enrich hydrophobic membrane proteins were tested. The extracted PM proteins were separated by 2-DE, and were identified by MALDI-TOF-MS, and ESI-quadrupole-TOF MS. As the complementary method, 1-DE-MS/MS was also used to identify PM proteins. The optimized lysis buffer containing urea, thiourea, CHAPS and NP-40 was able to extract more PM proteins, and treatment of PM samples with chloroform/methanol and sodium carbonate led to enrichment of more hydrophobic PM proteins. From the mouse liver PM fraction, 175 non-redundant gene products were identified, of which 88 (about 50%) were integral membrane proteins with one to seven transmembrane domains. The remaining products were probably membrane-associated and cytosolic proteins. The function distribution of all the identified liver PM proteins was analyzed; 40% represented enzymes, 12% receptors and 9% proteins with unknown function.

  19. PSEA-Quant: a protein set enrichment analysis on label-free and label-based protein quantification data.

    PubMed

    Lavallée-Adam, Mathieu; Rauniyar, Navin; McClatchy, Daniel B; Yates, John R

    2014-12-01

    The majority of large-scale proteomics quantification methods yield long lists of quantified proteins that are often difficult to interpret and poorly reproduced. Computational approaches are required to analyze such intricate quantitative proteomics data sets. We propose a statistical approach to computationally identify protein sets (e.g., Gene Ontology (GO) terms) that are significantly enriched with abundant proteins with reproducible quantification measurements across a set of replicates. To this end, we developed PSEA-Quant, a protein set enrichment analysis algorithm for label-free and label-based protein quantification data sets. It offers an alternative approach to classic GO analyses, models protein annotation biases, and allows the analysis of samples originating from a single condition, unlike analogous approaches such as GSEA and PSEA. We demonstrate that PSEA-Quant produces results complementary to GO analyses. We also show that PSEA-Quant provides valuable information about the biological processes involved in cystic fibrosis using label-free protein quantification of a cell line expressing a CFTR mutant. Finally, PSEA-Quant highlights the differences in the mechanisms taking place in the human, rat, and mouse brain frontal cortices based on tandem mass tag quantification. Our approach, which is available online, will thus improve the analysis of proteomics quantification data sets by providing meaningful biological insights. PMID:25177766

  20. Weighing the Giants - I. Weak-lensing masses for 51 massive galaxy clusters: project overview, data analysis methods and cluster images

    NASA Astrophysics Data System (ADS)

    von der Linden, Anja; Allen, Mark T.; Applegate, Douglas E.; Kelly, Patrick L.; Allen, Steven W.; Ebeling, Harald; Burchat, Patricia R.; Burke, David L.; Donovan, David; Morris, R. Glenn; Blandford, Roger; Erben, Thomas; Mantz, Adam

    2014-03-01

    This is the first in a series of papers in which we measure accurate weak-lensing masses for 51 of the most X-ray luminous galaxy clusters known at redshifts 0.15 ≲ zCl ≲ 0.7, in order to calibrate X-ray and other mass proxies for cosmological cluster experiments. The primary aim is to improve the absolute mass calibration of cluster observables, currently the dominant systematic uncertainty for cluster count experiments. Key elements of this work are the rigorous quantification of systematic uncertainties, high-quality data reduction and photometric calibration, and the `blind' nature of the analysis to avoid confirmation bias. Our target clusters are drawn from X-ray catalogues based on the ROSAT All-Sky Survey, and provide a versatile calibration sample for many aspects of cluster cosmology. We have acquired wide-field, high-quality imaging using the Subaru Telescope and Canada-France-Hawaii Telescope for all 51 clusters, in at least three bands per cluster. For a subset of 27 clusters, we have data in at least five bands, allowing accurate photometric redshift estimates of lensed galaxies. In this paper, we describe the cluster sample and observations, and detail the processing of the SuprimeCam data to yield high-quality images suitable for robust weak-lensing shape measurements and precision photometry. For each cluster, we present wide-field three-colour optical images and maps of the weak-lensing mass distribution, the optical light distribution and the X-ray emission. These provide insights into the large-scale structure in which the clusters are embedded. We measure the offsets between X-ray flux centroids and the brightest cluster galaxies in the clusters, finding these to be small in general, with a median of 20 kpc. For offsets ≲100 kpc, weak-lensing mass measurements centred on the brightest cluster galaxies agree well with values determined relative to the X-ray centroids; miscentring is therefore not a significant source of systematic

  1. Transcriptome Analysis of Aspergillus flavus Reveals veA-Dependent Regulation of Secondary Metabolite Gene Clusters, Including the Novel Aflavarin Cluster

    PubMed Central

    Cary, J. W.; Han, Z.; Yin, Y.; Lohmar, J. M.; Shantappa, S.; Harris-Coward, P. Y.; Mack, B.; Ehrlich, K. C.; Wei, Q.; Arroyo-Manzanares, N.; Uka, V.; Vanhaecke, L.; Bhatnagar, D.; Yu, J.; Nierman, W. C.; Johns, M. A.; Sorensen, D.; Shen, H.; De Saeger, S.; Diana Di Mavungu, J.

    2015-01-01

    The global regulatory veA gene governs development and secondary metabolism in numerous fungal species, including Aspergillus flavus. This is especially relevant since A. flavus infects crops of agricultural importance worldwide, contaminating them with potent mycotoxins. The most well-known are aflatoxins, which are cytotoxic and carcinogenic polyketide compounds. The production of aflatoxins and the expression of genes implicated in the production of these mycotoxins are veA dependent. The genes responsible for the synthesis of aflatoxins are clustered, a signature common for genes involved in fungal secondary metabolism. Studies of the A. flavus genome revealed many gene clusters possibly connected to the synthesis of secondary metabolites. Many of these metabolites are still unknown, or the association between a known metabolite and a particular gene cluster has not yet been established. In the present transcriptome study, we show that veA is necessary for the expression of a large number of genes. Twenty-eight out of the predicted 56 secondary metabolite gene clusters include at least one gene that is differentially expressed depending on presence or absence of veA. One of the clusters under the influence of veA is cluster 39. The absence of veA results in a downregulation of the five genes found within this cluster. Interestingly, our results indicate that the cluster is expressed mainly in sclerotia. Chemical analysis of sclerotial extracts revealed that cluster 39 is responsible for the production of aflavarin. PMID:26209694

  2. Somatosensory nociceptive characteristics differentiate subgroups in people with chronic low back pain: a cluster analysis.

    PubMed

    Rabey, Martin; Slater, Helen; OʼSullivan, Peter; Beales, Darren; Smith, Anne

    2015-10-01

    The objectives of this study were to explore the existence of subgroups in a cohort with chronic low back pain (n = 294) based on the results of multimodal sensory testing and profile subgroups on demographic, psychological, lifestyle, and general health factors. Bedside (2-point discrimination, brush, vibration and pinprick perception, temporal summation on repeated monofilament stimulation) and laboratory (mechanical detection threshold, pressure, heat and cold pain thresholds, conditioned pain modulation) sensory testing were examined at wrist and lumbar sites. Data were entered into principal component analysis, and 5 component scores were entered into latent class analysis. Three clusters, with different sensory characteristics, were derived. Cluster 1 (31.9%) was characterised by average to high temperature and pressure pain sensitivity. Cluster 2 (52.0%) was characterised by average to high pressure pain sensitivity. Cluster 3 (16.0%) was characterised by low temperature and pressure pain sensitivity. Temporal summation occurred significantly more frequently in cluster 1. Subgroups were profiled on pain intensity, disability, depression, anxiety, stress, life events, fear avoidance, catastrophizing, perception of the low back region, comorbidities, body mass index, multiple pain sites, sleep, and activity levels. Clusters 1 and 2 had a significantly greater proportion of female participants and higher depression and sleep disturbance scores than cluster 3. The proportion of participants undertaking <300 minutes per week of moderate activity was significantly greater in cluster 1 than in clusters 2 and 3. Low back pain, therefore, does not appear to be homogeneous. Pain mechanisms relating to presentations of each subgroup were postulated. Future research may investigate prognoses and interventions tailored towards these subgroups. PMID:26020225

  3. Somatosensory nociceptive characteristics differentiate subgroups in people with chronic low back pain: a cluster analysis.

    PubMed

    Rabey, Martin; Slater, Helen; OʼSullivan, Peter; Beales, Darren; Smith, Anne

    2015-10-01

    The objectives of this study were to explore the existence of subgroups in a cohort with chronic low back pain (n = 294) based on the results of multimodal sensory testing and profile subgroups on demographic, psychological, lifestyle, and general health factors. Bedside (2-point discrimination, brush, vibration and pinprick perception, temporal summation on repeated monofilament stimulation) and laboratory (mechanical detection threshold, pressure, heat and cold pain thresholds, conditioned pain modulation) sensory testing were examined at wrist and lumbar sites. Data were entered into principal component analysis, and 5 component scores were entered into latent class analysis. Three clusters, with different sensory characteristics, were derived. Cluster 1 (31.9%) was characterised by average to high temperature and pressure pain sensitivity. Cluster 2 (52.0%) was characterised by average to high pressure pain sensitivity. Cluster 3 (16.0%) was characterised by low temperature and pressure pain sensitivity. Temporal summation occurred significantly more frequently in cluster 1. Subgroups were profiled on pain intensity, disability, depression, anxiety, stress, life events, fear avoidance, catastrophizing, perception of the low back region, comorbidities, body mass index, multiple pain sites, sleep, and activity levels. Clusters 1 and 2 had a significantly greater proportion of female participants and higher depression and sleep disturbance scores than cluster 3. The proportion of participants undertaking <300 minutes per week of moderate activity was significantly greater in cluster 1 than in clusters 2 and 3. Low back pain, therefore, does not appear to be homogeneous. Pain mechanisms relating to presentations of each subgroup were postulated. Future research may investigate prognoses and interventions tailored towards these subgroups.

  4. The application of cluster analysis in the intercomparison of loop structures in RNA.

    PubMed

    Huang, Hung-Chung; Nagaswamy, Uma; Fox, George E

    2005-04-01

    We have developed a computational approach for the comparison and classification of RNA loop structures. Hairpin or interior loops identified in atomic resolution RNA structures were intercompared by conformational matching. The root-mean-square deviation (RMSD) values between all pairs of RNA fragments of interest, even if from different molecules, are calculated. Subsequently, cluster analysis is performed on the resulting matrix of RMSD distances using the unweighted pair group method with arithmetic mean (UPGMA). The cluster analysis objectively reveals groups of folds that resemble one another. To demonstrate the utility of the approach, a comprehensive analysis of all the terminal hairpin tetraloops that have been observed in 15 RNA structures that have been determined by X-ray crystallography was undertaken. The method found major clusters corresponding to the well-known GNRA and UNCG types. In addition, two tetraloops with the unusual primary sequence UMAC (M is A or C) were successfully assigned to the GNRA cluster. Larger loop structures were also examined and the clustering results confirmed the occurrence of variations of the GNRA and UNCG tetraloops in these loops and provided a systematic means for locating them. Nineteen examples of larger loops that closely resemble either the GNRA or UNCG tetraloop were found in the large ribosomal RNAs. When the clustering approach was extended to include all structures in the SCOR database, novel relationships were detected including one between the ANYA motif and a less common folding of the GAAA tetraloop sequence.

  5. Analysis of cluster explosive synchronization in complex networks

    NASA Astrophysics Data System (ADS)

    Ji, Peng; Peron, Thomas K. DM.; Rodrigues, Francisco A.; Kurths, Jürgen

    2014-12-01

    Correlations between intrinsic dynamics and local topology have become a new trend in the study of synchronization in complex networks. In this paper, we investigate the influence of topology on the dynamics of networks made up of second-order Kuramoto oscillators. In particular, based on mean-field calculations, we provide a detailed investigation of cluster explosive synchronization (CES) [Phys. Rev. Lett. 110, 218701 (2013), 10.1103/PhysRevLett.110.218701] in scale-free networks as a function of several topological properties. Moreover, we investigate the robustness of discontinuous transitions by including an additional quenched disorder, and we show that the phase coherence decreases with increasing strength of the quenched disorder. These results complement the previous findings regarding CES and also fundamentally deepen the understanding of the interplay between topology and dynamics under the constraint of correlating natural frequencies and local structure.

  6. A landscape-based cluster analysis using recursive search instead of a threshold parameter.

    PubMed

    Gladwin, Thomas E; Vink, Matthijs; Mars, Roger B

    2016-01-01

    Cluster-based analysis methods in neuroimaging provide control of whole-brain false positive rates without the need to conservatively correct for the number of voxels and the associated false negative results. The current method defines clusters based purely on shapes in the landscape of activation, instead of requiring the choice of a statistical threshold that may strongly affect results. Statistical significance is determined using permutation testing, combining both size and height of activation. A method is proposed for dealing with relatively small local peaks. Simulations confirm the method controls the false positive rate and correctly identifies regions of activation. The method is also illustrated using real data. •A landscape-based method to define clusters in neuroimaging data avoids the need to pre-specify a threshold to define clusters.•The implementation of the method works as expected, based on simulated and real data.•The recursive method used for defining clusters, the method used for combining clusters, and the definition of the "value" of a cluster may be of interest for future variations.

  7. Cluster analysis for the probability of DSB site induced by electron tracks

    NASA Astrophysics Data System (ADS)

    Yoshii, Y.; Sasaki, K.; Matsuya, Y.; Date, H.

    2015-05-01

    To clarify the influence of bio-cells exposed to ionizing radiations, the densely populated pattern of the ionization in the cell nucleus is of importance because it governs the extent of DNA damage which may lead to cell lethality. In this study, we have conducted a cluster analysis of ionization and excitation events to estimate the number of double-strand breaks (DSBs) induced by electron tracks. A Monte Carlo simulation for electrons in liquid water was performed to determine the spatial location of the ionization and excitation events. The events were divided into clusters by using the density-based spatial clustering of applications with noise (DBSCAN) algorithm. The algorithm enables us to sort out the events into the groups (clusters) in which a minimum number of neighboring events are contained within a given radius. For evaluating the number of DSBs in the extracted clusters, we have introduced an aggregation index (AI). The computational results show that a sub-keV electron produces DSBs in a dense formation more effectively than higher energy electrons. The root-mean square radius (RMSR) of the cluster size is below 5 nm, which is smaller than the chromatin fiber thickness. It was found that this size of clustering events has a high possibility to cause lesions in DNA within the chromatin fiber site.

  8. A landscape-based cluster analysis using recursive search instead of a threshold parameter.

    PubMed

    Gladwin, Thomas E; Vink, Matthijs; Mars, Roger B

    2016-01-01

    Cluster-based analysis methods in neuroimaging provide control of whole-brain false positive rates without the need to conservatively correct for the number of voxels and the associated false negative results. The current method defines clusters based purely on shapes in the landscape of activation, instead of requiring the choice of a statistical threshold that may strongly affect results. Statistical significance is determined using permutation testing, combining both size and height of activation. A method is proposed for dealing with relatively small local peaks. Simulations confirm the method controls the false positive rate and correctly identifies regions of activation. The method is also illustrated using real data. •A landscape-based method to define clusters in neuroimaging data avoids the need to pre-specify a threshold to define clusters.•The implementation of the method works as expected, based on simulated and real data.•The recursive method used for defining clusters, the method used for combining clusters, and the definition of the "value" of a cluster may be of interest for future variations. PMID:27489780

  9. Concomitant formation of different nature clusters and hardening in reactor pressure vessel steels irradiated by heavy ions

    NASA Astrophysics Data System (ADS)

    Fujii, K.; Fukuya, K.; Hojo, T.

    2013-11-01

    Specimens of A533B steels containing 0.04, 0.09 and 0.21 wt%Cu were irradiated at 290 °C to 3 dpa with 3 MeV Fe ions and subjected to atom probe analyses, transmission electron microscopy observations and hardness measurements. The atom probe analysis results showed that two types of solute clusters were formed: Cu-enriched clusters containing Mn, Ni and Si atoms as irradiation-enhanced solute atom clusters and Mn/Ni/Si-enriched clusters as irradiation-induced solute atom clusters. Both cluster types occurred in the highest Cu-content steel and the ratio of Mn/Ni/Si-enriched clusters to Cu-enriched clusters increased with irradiation doses. It was confirmed that the cluster formation was a key factor in the microstructure evolution until the high dose irradiation was reached even in the low Cu content steels though the dislocation loops with much lower density than that of the clusters were observed as matrix damage. The difference in the hardening efficiency due to the difference in the nature of the clusters was small. The irradiation-induced clustering of undersized Si atoms suggested that a clustering driving force other than vacancy-driven diffusion, probably an interstitial mechanism, may become important at higher dose rates.

  10. Task Analysis for Health Occupations. Cluster: Nursing. Occupation: Home Health Aide. Education for Employment Task Lists.

    ERIC Educational Resources Information Center

    Lake County Area Vocational Center, Grayslake, IL.

    This document contains a task analysis for health occupations (home health aid) in the nursing cluster. For each task listed, occupation, duty area, performance standard, steps, knowledge, attitudes, safety, equipment/supplies, source of analysis, and Illinois state goals for learning are listed. For the duty area of "providing therapeutic…

  11. Task Analysis for Health Occupations. Cluster: Dental Assisting. Occupation: Dental Assistant. Education for Employment Task Lists.

    ERIC Educational Resources Information Center

    Lathrop, Janice

    This document contains a task analysis for health occupations (dental assistant) in the dental assisting cluster. For each task listed, occupation, duty area, performance standard, steps, knowledge, attitudes, safety, equipment/supplies, source of analysis, and Illinois state goals for learning are listed. For the duty area of "providing…

  12. Standardized Effect Size Measures for Mediation Analysis in Cluster-Randomized Trials

    ERIC Educational Resources Information Center

    Stapleton, Laura M.; Pituch, Keenan A.; Dion, Eric

    2015-01-01

    This article presents 3 standardized effect size measures to use when sharing results of an analysis of mediation of treatment effects for cluster-randomized trials. The authors discuss 3 examples of mediation analysis (upper-level mediation, cross-level mediation, and cross-level mediation with a contextual effect) with demonstration of the…

  13. Prediction of lithology types at the Hanford 300 Area using a clustering analysis

    NASA Astrophysics Data System (ADS)

    Thai, J.; Rockhold, M. L.; Vermeul, V.; Johnson, T. E.; Zachara, J. M.; Rubin, Y.

    2011-12-01

    The purpose of this study is to find an optimal method for mapping the three-dimensional distribution of lithology at the Hanford IFRC site 300 Area based on surrogate measurements. We considered 6 types of measurements for this analysis: gamma ray, concentration of U-238 (609), K-40, U-238 (1764), Th-232, and the hydraulic conductivity. To decide which combinations of variables are best suited for determining lithology type, we trained our classification method using training sets that included several wells with lithological information. A clustering analysis was applied to each training set and the lithology types for each cluster of the training set were fitted with a probability distribution function. The lithology type at each point in the testing set was selected to be the one linked with the mode of the distribution at the corresponding cluster. The predictions were then checked against the data of the testing set. This process was applied repeatedly using different numbers of clusters. In addition, many different configurations of training sets and testing sets were used to establish confidence in the predictive ability of the clustering and classification methods. Our best success rates as measured by matching predictions with observations were obtained for 2 or 3 clusters, and the following measurements: concentration of U-238 (609), K-40, U-238 (1764), and Th-232, and were consistently around 80%.

  14. Insights into secondary metabolism from a global analysis of prokaryotic biosynthetic gene clusters

    PubMed Central

    Cimermancic, Peter; Medema, Marnix H.; Claesen, Jan; Kurita, Kenji; Wieland Brown, Laura C.; Mavrommatis, Konstantinos; Pati, Amrita; Godfrey, Paul A.; Koehrsen, Michael; Clardy, Jon; Birren, Bruce W.; Takano, Eriko; Sali, Andrej; Linington, Roger G.; Fischbach, Michael A.

    2014-01-01

    Summary Although biosynthetic gene clusters (BGCs) have been discovered for hundreds of bacterial metabolites, our knowledge of their diversity remains limited. Here, we used a novel algorithm to systematically identify BGCs in the extensive extant microbial sequencing data. Network analysis of the predicted BGCs revealed large gene cluster families, the vast majority uncharacterized. We experimentally characterized the most prominent family, consisting of two subfamilies of hundreds of BGCs distributed throughout the Proteobacteria; their products are aryl polyenes, lipids with an aryl head group conjugated to a polyene tail. We identified a distant relationship to a third subfamily of aryl polyene BGCs, and together the three subfamilies represent the largest known family of biosynthetic gene clusters, with more than 1,000 members. Although these clusters are widely divergent in sequence, their small molecule products are remarkably conserved, indicating for the first time the important roles these compounds play in Gram-negative cell biology. PMID:25036635

  15. 3D Plasma Clusters: Analysis of dynamical evolution and individual particle interaction

    SciTech Connect

    Antonova, T.; Thomas, H. M.; Morfill, G. E.; Annaratone, B. M.

    2008-09-07

    3D plasma clusters (up to 100 particles) have been built inside small (32 mm{sup 3}) plasma volume in gravity. It has been estimated that the external confinement has a negligible influence on the processes inside the clusters. At such conditions the analysis of dynamical evolution and individual particle interactions have shown that the binary interaction among particles in addition to the repelling Coulomb force exhibits also an attractive part. The tendency of the systems to approach the state with minimum energy by rearranging particles inside has been detected. The measured 63 particles' cluster vibrations are in close agreement with vibrations of a drop with surface tension. This indicates that even a 63 particle cluster already exhibits properties normally associated with the cooperative regime.

  16. 3D Plasma Clusters: Analysis of dynamical evolution and individual particle interaction

    NASA Astrophysics Data System (ADS)

    Antonova, T.; Annaratone, B. M.; Thomas, H. M.; Morfill, G. E.

    2008-09-01

    3D plasma clusters (up to 100 particles) have been built inside small (32 mm3) plasma volume in gravity. It has been estimated that the external confinement has a negligible influence on the processes inside the clusters. At such conditions the analysis of dynamical evolution and individual particle interactions have shown that the binary interaction among particles in addition to the repelling Coulomb force exhibits also an attractive part. The tendency of the systems to approach the state with minimum energy by rearranging particles inside has been detected. The measured 63 particles' cluster vibrations are in close agreement with vibrations of a drop with surface tension. This indicates that even a 63 particle cluster already exhibits properties normally associated with the cooperative regime.

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

    SciTech Connect

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

    2010-04-15

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

  18. Cluster Analysis of Longidorus Species (Nematoda: Longidoridae), a New Approach in Species Identification

    PubMed Central

    Ye, Weimin; Robbins, R. T.

    2004-01-01

    Hierarchical cluster analysis based on female morphometric character means including body length, distance from vulva opening to anterior end, head width, odontostyle length, esophagus length, body width, tail length, and tail width were used to examine the morphometric relationships and create dendrograms for (i) 62 populations belonging to 9 Longidorus species from Arkansas, (ii) 137 published Longidorus species, and (iii) 137 published Longidorus species plus 86 populations of 16 Longidorus species from Arkansas and various other locations by using JMP 4.02 software (SAS Institute, Cary, NC). Cluster analysis dendograms visually illustrated the grouping and morphometric relationships of the species and populations. It provided a computerized statistical approach to assist by helping to identify and distinguish species, by indicating morphometric relationships among species, and by assisting with new species diagnosis. The preliminary species identification can be accomplished by running cluster analysis for unknown species together with the data matrix of known published Longidorus species. PMID:19262809

  19. RNA Enrichment Method for Quantitative Transcriptional Analysis of Pathogens In Vivo Applied to the Fungus Candida albicans

    PubMed Central

    Amorim-Vaz, Sara; Tran, Van Du T.; Pradervand, Sylvain; Pagni, Marco; Coste, Alix T.

    2015-01-01

    ABSTRACT In vivo transcriptional analyses of microbial pathogens are often hampered by low proportions of pathogen biomass in host organs, hindering the coverage of full pathogen transcriptome. We aimed to address the transcriptome profiles of Candida albicans, the most prevalent fungal pathogen in systemically infected immunocompromised patients, during systemic infection in different hosts. We developed a strategy for high-resolution quantitative analysis of the C. albicans transcriptome directly from early and late stages of systemic infection in two different host models, mouse and the insect Galleria mellonella. Our results show that transcriptome sequencing (RNA-seq) libraries were enriched for fungal transcripts up to 1,600-fold using biotinylated bait probes to capture C. albicans sequences. This enrichment biased the read counts of only ~3% of the genes, which can be identified and removed based on a priori criteria. This allowed an unprecedented resolution of C. albicans transcriptome in vivo, with detection of over 86% of its genes. The transcriptional response of the fungus was surprisingly similar during infection of the two hosts and at the two time points, although some host- and time point-specific genes could be identified. Genes that were highly induced during infection were involved, for instance, in stress response, adhesion, iron acquisition, and biofilm formation. Of the in vivo-regulated genes, 10% are still of unknown function, and their future study will be of great interest. The fungal RNA enrichment procedure used here will help a better characterization of the C. albicans response in infected hosts and may be applied to other microbial pathogens. PMID:26396240

  20. Fuzzy C-means clustering for chromatographic fingerprints analysis: A gas chromatography-mass spectrometry case study.

    PubMed

    Parastar, Hadi; Bazrafshan, Alisina

    2016-03-18

    Fuzzy C-means clustering (FCM) is proposed as a promising method for the clustering of chromatographic fingerprints of complex samples, such as essential oils. As an example, secondary metabolites of 14 citrus leaves samples are extracted and analyzed by gas chromatography-mass spectrometry (GC-MS). The obtained chromatographic fingerprints are divided to desired number of chromatographic regions. Owing to the fact that chromatographic problems, such as elution time shift and peak overlap can significantly affect the clustering results, therefore, each chromatographic region is analyzed using multivariate curve resolution-alternating least squares (MCR-ALS) to address these problems. Then, the resolved elution profiles are used to make a new data matrix based on peak areas of pure components to cluster by FCM. The FCM clustering parameters (i.e., fuzziness coefficient and number of cluster) are optimized by two different methods of partial least squares (PLS) as a conventional method and minimization of FCM objective function as our new idea. The results showed that minimization of FCM objective function is an easier and better way to optimize FCM clustering parameters. Then, the optimized FCM clustering algorithm is used to cluster samples and variables to figure out the similarities and dissimilarities among samples and to find discriminant secondary metabolites in each cluster (chemotype). Finally, the FCM clustering results are compared with those of principal component analysis (PCA), hierarchical cluster analysis (HCA) and Kohonon maps. The results confirmed the outperformance of FCM over the frequently used clustering algorithms.

  1. Analysis of cardiac tissue by gold cluster ion bombardment

    NASA Astrophysics Data System (ADS)

    Aranyosiova, M.; Chorvatova, A.; Chorvat, D.; Biro, Cs.; Velic, D.

    2006-07-01

    Specific molecules in cardiac tissue of spontaneously hypertensive rats are studied by using time-of-flight secondary ion mass spectrometry (TOF-SIMS). The investigation determines phospholipids, cholesterol, fatty acids and their fragments in the cardiac tissue, with special focus on cardiolipin. Cardiolipin is a unique phospholipid typical for cardiomyocyte mitochondrial membrane and its decrease is involved in pathologic conditions. In the positive polarity, the fragments of phosphatydilcholine are observed in the mass region of 700-850 u. Peaks over mass 1400 u correspond to intact and cationized molecules of cardiolipin. In animal tissue, cardiolipin contains of almost exclusively 18 carbon fatty acids, mostly linoleic acid. Linoleic acid at 279 u, other fatty acids, and phosphatidylglycerol fragments, as precursors of cardiolipin synthesis, are identified in the negative polarity. These data demonstrate that SIMS technique along with Au 3+ cluster primary ion beam is a good tool for detection of higher mass biomolecules providing approximately 10 times higher yield in comparison with Au +.

  2. Differentiating Procrastinators from Each Other: A Cluster Analysis.

    PubMed

    Rozental, Alexander; Forsell, Erik; Svensson, Andreas; Forsström, David; Andersson, Gerhard; Carlbring, Per

    2015-01-01

    Procrastination refers to the tendency to postpone the initiation and completion of a given course of action. Approximately one-fifth of the adult population and half of the student population perceive themselves as being severe and chronic procrastinators. Albeit not a psychiatric diagnosis, procrastination has been shown to be associated with increased stress and anxiety, exacerbation of illness, and poorer performance in school and work. However, despite being severely debilitating, little is known about the population of procrastinators in terms of possible subgroups, and previous research has mainly investigated procrastination among university students. The current study examined data from a screening process recruiting participants to a randomized controlled trial of Internet-based cognitive behavior therapy for procrastination (Rozental et al., in press). In total, 710 treatment-seeking individuals completed self-report measures of procrastination, depression, anxiety, and quality of life. The results suggest that there might exist five separate subgroups, or clusters, of procrastinators: "Mild procrastinators" (24.93%), "Average procrastinators" (27.89%), "Well-adjusted procrastinators" (13.94%), "Severe procrastinators" (21.69%), and "Primarily depressed" (11.55%). Hence, there seems to be marked differences among procrastinators in terms of levels of severity, as well as a possible subgroup for which procrastinatory problems are primarily related to depression. Tailoring the treatment interventions to the specific procrastination profile of the individual could thus become important, as well as screening for comorbid psychiatric diagnoses in order to target difficulties associated with, for instance, depression. PMID:26178164

  3. Differentiating Procrastinators from Each Other: A Cluster Analysis.

    PubMed

    Rozental, Alexander; Forsell, Erik; Svensson, Andreas; Forsström, David; Andersson, Gerhard; Carlbring, Per

    2015-01-01

    Procrastination refers to the tendency to postpone the initiation and completion of a given course of action. Approximately one-fifth of the adult population and half of the student population perceive themselves as being severe and chronic procrastinators. Albeit not a psychiatric diagnosis, procrastination has been shown to be associated with increased stress and anxiety, exacerbation of illness, and poorer performance in school and work. However, despite being severely debilitating, little is known about the population of procrastinators in terms of possible subgroups, and previous research has mainly investigated procrastination among university students. The current study examined data from a screening process recruiting participants to a randomized controlled trial of Internet-based cognitive behavior therapy for procrastination (Rozental et al., in press). In total, 710 treatment-seeking individuals completed self-report measures of procrastination, depression, anxiety, and quality of life. The results suggest that there might exist five separate subgroups, or clusters, of procrastinators: "Mild procrastinators" (24.93%), "Average procrastinators" (27.89%), "Well-adjusted procrastinators" (13.94%), "Severe procrastinators" (21.69%), and "Primarily depressed" (11.55%). Hence, there seems to be marked differences among procrastinators in terms of levels of severity, as well as a possible subgroup for which procrastinatory problems are primarily related to depression. Tailoring the treatment interventions to the specific procrastination profile of the individual could thus become important, as well as screening for comorbid psychiatric diagnoses in order to target difficulties associated with, for instance, depression.

  4. Weak lensing analysis of the galaxy cluster RXJ1117.4+0743 ([VMF98]097)

    NASA Astrophysics Data System (ADS)

    Gonzalez, E. J.; Domínguez, M.; García Lambas, D.; Moreschi, O.; Foex, G.; Nilo Castellon, J. L.; Alonso, M. V.

    We present a weak lensing analysis of the galaxy cluster RXJ1117.4+0743 ([VMF98]097) at ; based on data collected with Gemini South Telescope. The cluster was formerly analyzed by Carrasco et al. (2007; ApJ; 664; 777); and they found a large discrepancy between the mass estimated from X-ray observations and lensing estimates; exceeding the lensing mass by more than a factor three. Our result for the mass from the weak lensing analysis is lower than the mass obtained by Carrasco et al. and closer to the X-ray mass.

  5. Cluster analysis and relative relocation of mining-induced seismicity using HAMNET data

    NASA Astrophysics Data System (ADS)

    Wehling-Benatelli, S.; Becker, D.; Bischoff, M.; Friederich, W.; Meier, T.

    2012-04-01

    Longwall mining activity in the Ruhr-coal mining district leads to mining-induced seismicity. For detailed studies seismicity of the single longwall panel S 109 beneath Hamm-Herringen in the eastern Ruhr area was monitored between June 2006 and July 2007. More than 7000 seismic events with magnitudes -1.7 ≤ ML ≤ 2.0 are localized in this period. 70% of the events occur in the vicinity of the moving longwall face. Moreover, the seismicity pattern shows spatial clustering of events in distances up to 500 m from the panel which is related to remnant pillars of old workings and tectonic features. Two sources with common location and rock failure mechanism are expected to show identical waveforms. Hence, similar waveforms suggest similarity of source properties. Waveform similarity can be quantified by cross-correlation. Similarity matrices have been established and build the basis of a cluster analysis presented here. We compare two approaches for cluster definition: a single-linkage approach and excerpting clusters by visual inspection of the sorted similarity matrices. Clusters are found as areas of high inter-event similarity in the depicted matrix. In contrast, the single-linkage approach assigns an event to the cluster if the similarity threshold v sl = 0.9 is exceeded to at least one other member. This method is more restrictive and, in general, leads to clusters with less members than visual inspection. Both methods exhibit clusters which show the same properties. The largest clusters are built by low-magnitude events (around ML ≈-0.6) directly at the longwall face at the mining level. Other clusters include events with magnitudes as large as ML,max = 1.8. Their locations tend to lie above or below the mining level in load-bearing sandstone layers. Mining accompanying events show face-parallel near vertical fault planes whereas more distant clusters have typical solutions of remnant pillar failure with a medium dip angle. Relative relocation of the events

  6. Analysis of 13C labeling enrichment in microbial culture applying metabolic tracer experiments using gas chromatography-combustion-isotope ratio mass spectrometry.

    PubMed

    Heinzle, Elmar; Yuan, Yongbo; Kumar, Sathish; Wittmann, Christoph; Gehre, Matthias; Richnow, Hans-Herrmann; Wehrung, Patrick; Adam, Pierre; Albrecht, Pierre

    2008-09-15

    The applicability of gas chromatography-combustion-isotope ratio mass spectrometry (GC-C-IRMS) for the quantification of 13C enrichment of proteinogenic amino acids in metabolic tracer experiments was evaluated. Measurement of the 13C enrichment of proteinogenic amino acids from cell hydrolyzates of Corynebacterium glutamicum growing on different mixtures containing between 0.5 and 10% [1-13C]glucose shows the significance of kinetic isotope effects in metabolic flux studies at low degree of labeling. We developed a method to calculate the 13C enrichment. The approach to correct for these effects in metabolic flux studies using delta13C measurement by GC-C-IRMS uses two parallel experiments applying substrate with natural abundance and 13C-enriched tracer substrate, respectively. The fractional enrichment obtained in natural substrate is subtracted from that of the enriched one. Tracer studies with C. glutamicum resulted in a statistically identical relative fractional enrichment of 13C in proteinogenic amino acids over the whole range of applied concentrations of [1-13C]glucose. The current findings indicate a great potential of GC-C-IRMS for labeling quantification in 13C metabolic flux analysis with low labeling degree of tracer substrate directly in larger scale bioreactors.

  7. Earthquake Cluster Analysis for Turkey and its Application for Seismic Hazard Assessment

    NASA Astrophysics Data System (ADS)

    Schaefer, Andreas; Daniell, James; Wenzel, Friedemann

    2015-04-01

    Earthquake clusters are an important element in general seismology and also for the application in seismic hazard assessment. In probabilistic seismic hazard assessment, the occurrence of earthquakes is often linked to an independent Monte Carlo process, following a stationary Poisson model. But earthquakes are dependent and constrained, especially in terms of earthquake swarms, fore- and aftershocks or even larger sequences as observed for the Landers sequence in California or the Darfield-Christchurch sequence in New Zealand. For earthquake catalogues, the element of declustering is an important step to capture earthquake frequencies by avoiding a bias towards small magnitudes due to aftershocks. On the other hand, declustered catalogues for independent probabilistic seismic activity will underestimate the total number of earthquakes by neglecting dependent seismicity. In this study, the effect of clusters on probabilistic seismic hazard assessment is investigated in detail. To capture the features of earthquake clusters, a uniform framework for earthquake cluster analysis is introduced using methodologies of geostatistics and machine learning. These features represent important cluster characteristics like cluster b-values, temporal decay, rupture orientations and many more. Cluster parameters are mapped in space using kriging. Furthermore, a detailed data analysis is undertaken to provide magnitude-dependent relations for various cluster parameters. The acquired features are used to introduce dependent seismicity within stochastic earthquake catalogues. In addition, the development of smooth seismicity maps based on historic databases is in general biased to the more complete recent decades. A filling methodology is introduced which will add dependent seismicity in catalogues where none has been recorded to avoid the above mentioned bias. As a case study, Turkey has been chosen due to its inherent seismic activity and well-recorded data coverage. Clustering

  8. Global Analysis Reveals Families of Chemical Motifs Enriched for hERG Inhibitors

    PubMed Central

    Du, Fang; Babcock, Joseph J.; Yu, Haibo; Zou, Beiyan; Li, Min

    2015-01-01

    Promiscuous inhibition of the human ether-à-go-go-related gene (hERG) potassium channel by drugs poses a major risk for life threatening arrhythmia and costly drug withdrawals. Current knowledge of this phenomenon is derived from a limited number of known drugs and tool compounds. However, in a diverse, naïve chemical library, it remains unclear which and to what degree chemical motifs or scaffolds might be enriched for hERG inhibition. Here we report electrophysiology measurements of hERG inhibition and computational analyses of >300,000 diverse small molecules. We identify chemical ‘communities’ with high hERG liability, containing both canonical scaffolds and structurally distinctive molecules. These data enable the development of more effective classifiers to computationally assess hERG risk. The resultant predictive models now accurately classify naïve compound libraries for tendency of hERG inhibition. Together these results provide a more complete reference map of characteristic chemical motifs for hERG liability and advance a systematic approach to rank chemical collections for cardiotoxicity risk. PMID:25700001

  9. Drug-set enrichment analysis: a novel tool to investigate drug mode of action

    PubMed Central

    Napolitano, Francesco; Sirci, Francesco; Carrella, Diego; di Bernardo, Diego

    2016-01-01

    Motivation: Automated screening approaches are able to rapidly identify a set of small molecules inducing a desired phenotype from large small-molecule libraries. However, the resulting set of candidate molecules is usually very diverse pharmacologically, thus little insight on the shared mechanism of action (MoA) underlying their efficacy can be gained. Results: We introduce a computational method (Drug-Set Enrichment Analysis—DSEA) based on drug-induced gene expression profiles, which is able to identify the molecular pathways that are targeted by most of the drugs in the set. By diluting drug-specific effects unrelated to the phenotype of interest, DSEA is able to highlight phenotype-specific pathways, thus helping to formulate hypotheses on the MoA shared by the drugs in the set. We validated the method by analysing five different drug-sets related to well-known pharmacological classes. We then applied DSEA to identify the MoA shared by drugs known to be partially effective in rescuing mutant cystic fibrosis transmembrane conductance regulator (CFTR) gene function in Cystic Fibrosis. Availability and implementation: The method is implemented as an online web tool publicly available at http://dsea.tigem.it. Contact: dibernardo@tigem.it Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26415724

  10. i-cisTarget 2015 update: generalized cis-regulatory enrichment analysis in human, mouse and fly

    PubMed Central

    Imrichová, Hana; Hulselmans, Gert; Kalender Atak, Zeynep; Potier, Delphine; Aerts, Stein

    2015-01-01

    i-cisTarget is a web tool to predict regulators of a set of genomic regions, such as ChIP-seq peaks or co-regulated/similar enhancers. i-cisTarget can also be used to identify upstream regulators and their target enhancers starting from a set of co-expressed genes. Whereas the original version of i-cisTarget was focused on Drosophila data, the 2015 update also provides support for human and mouse data. i-cisTarget detects transcription factor motifs (position weight matrices) and experimental data tracks (e.g. from ENCODE, Roadmap Epigenomics) that are enriched in the input set of regions. As experimental data tracks we include transcription factor ChIP-seq data, histone modification ChIP-seq data and open chromatin data. The underlying processing method is based on a ranking-and-recovery procedure, allowing accurate determination of enrichment across heterogeneous datasets, while also discriminating direct from indirect target regions through a ‘leading edge’ analysis. We illustrate i-cisTarget on various Ewing sarcoma datasets to identify EWS-FLI1 targets starting from ChIP-seq, differential ATAC-seq, differential H3K27ac and differential gene expression data. Use of i-cisTarget is free and open to all, and there is no login requirement. Address: http://gbiomed.kuleuven.be/apps/lcb/i-cisTarget. PMID:25925574

  11. i-cisTarget 2015 update: generalized cis-regulatory enrichment analysis in human, mouse and fly.

    PubMed

    Imrichová, Hana; Hulselmans, Gert; Atak, Zeynep Kalender; Potier, Delphine; Aerts, Stein

    2015-07-01

    i-cisTarget is a web tool to predict regulators of a set of genomic regions, such as ChIP-seq peaks or co-regulated/similar enhancers. i-cisTarget can also be used to identify upstream regulators and their target enhancers starting from a set of co-expressed genes. Whereas the original version of i-cisTarget was focused on Drosophila data, the 2015 update also provides support for human and mouse data. i-cisTarget detects transcription factor motifs (position weight matrices) and experimental data tracks (e.g. from ENCODE, Roadmap Epigenomics) that are enriched in the input set of regions. As experimental data tracks we include transcription factor ChIP-seq data, histone modification ChIP-seq data and open chromatin data. The underlying processing method is based on a ranking-and-recovery procedure, allowing accurate determination of enrichment across heterogeneous datasets, while also discriminating direct from indirect target regions through a 'leading edge' analysis. We illustrate i-cisTarget on various Ewing sarcoma datasets to identify EWS-FLI1 targets starting from ChIP-seq, differential ATAC-seq, differential H3K27ac and differential gene expression data. Use of i-cisTarget is free and open to all, and there is no login requirement. Address: http://gbiomed.kuleuven.be/apps/lcb/i-cisTarget.

  12. Variant allele frequency enrichment analysis in vitro reveals sonic hedgehog pathway to impede sustained temozolomide response in GBM

    PubMed Central

    Biswas, Nidhan K.; Chandra, Vikas; Sarkar-Roy, Neeta; Das, Tapojyoti; Bhattacharya, Rabindra N.; Tripathy, Laxmi N.; Basu, Sunandan K.; Kumar, Shantanu; Das, Subrata; Chatterjee, Ankita; Mukherjee, Ankur; Basu, Pryiadarshi; Maitra, Arindam; Chattopadhyay, Ansuman; Basu, Analabha; Dhara, Surajit

    2015-01-01

    Neoplastic cells of Glioblastoma multiforme (GBM) may or may not show sustained response to temozolomide (TMZ) chemotherapy. We hypothesize that TMZ chemotherapy response in GBM is predetermined in its neoplastic clones via a specific set of mutations that alter relevant pathways. We describe exome-wide enrichment of variant allele frequencies (VAFs) in neurospheres displaying contrasting phenotypes of sustained versus reversible TMZ-responses in vitro. Enrichment of VAFs was found on genes ST5, RP6KA1 and PRKDC in cells showing sustained TMZ-effect whereas on genes FREM2, AASDH and STK36, in cells showing reversible TMZ-effect. Ingenuity pathway analysis (IPA) revealed that these genes alter cell-cycle, G2/M-checkpoint-regulation and NHEJ pathways in sustained TMZ-effect cells whereas the lysine-II&V/phenylalanine degradation and sonic hedgehog (Hh) pathways in reversible TMZ-effect cells. Next, we validated the likely involvement of the Hh-pathway in TMZ-response on additional GBM neurospheres as well as on GBM patients, by extracting RNA-sequencing-based gene expression data from the TCGA-GBM database. Finally, we demonstrated TMZ-sensitization of a TMZ non-responder neurosphere in vitro by treating them with the FDA-approved pharmacological Hh-pathway inhibitor vismodegib. Altogether, our results indicate that the Hh-pathway impedes sustained TMZ-response in GBM and could be a potential therapeutic target to enhance TMZ-response in this malignancy. PMID:25604826

  13. Comprehensive Behavioral Analysis of Cluster of Differentiation 47 Knockout Mice

    PubMed Central

    Koshimizu, Hisatsugu; Takao, Keizo; Matozaki, Takashi; Ohnishi, Hiroshi; Miyakawa, Tsuyoshi

    2014-01-01

    Cluster of differentiation 47 (CD47) is a member of the immunoglobulin superfamily which functions as a ligand for the extracellular region of signal regulatory protein α (SIRPα), a protein which is abundantly expressed in the brain. Previous studies, including ours, have demonstrated that both CD47 and SIRPα fulfill various functions in the central nervous system (CNS), such as the modulation of synaptic transmission and neuronal cell survival. We previously reported that CD47 is involved in the regulation of depression-like behavior of mice in the forced swim test through its modulation of tyrosine phosphorylation of SIRPα. However, other potential behavioral functions of CD47 remain largely unknown. In this study, in an effort to further investigate functional roles of CD47 in the CNS, CD47 knockout (KO) mice and their wild-type littermates were subjected to a battery of behavioral tests. CD47 KO mice displayed decreased prepulse inhibition, while the startle response did not differ between genotypes. The mutants exhibited slightly but significantly decreased sociability and social novelty preference in Crawley’s three-chamber social approach test, whereas in social interaction tests in which experimental and stimulus mice have direct contact with each other in a freely moving setting in a novel environment or home cage, there were no significant differences between the genotypes. While previous studies suggested that CD47 regulates fear memory in the inhibitory avoidance test in rodents, our CD47 KO mice exhibited normal fear and spatial memory in the fear conditioning and the Barnes maze tests, respectively. These findings suggest that CD47 is potentially involved in the regulation of sensorimotor gating and social behavior in mice. PMID:24586890

  14. Functional analysis of the upstream regulatory region of chicken miR-17-92 cluster.

    PubMed

    Min, Cheng; Wenjian, Zhang; Tianyu, Xing; Xiaohong, Yan; Yumao, Li; Hui, Li; Ning, Wang

    2016-08-01

    miR-17-92 cluster plays important roles in cell proliferation, differentiation, apoptosis, animal development and tumorigenesis. The transcriptional regulation of miR-17-92 cluster has been extensively studied in mammals, but not in birds. To date, avian miR-17-92 cluster genomic structure has not been fully determined. The promoter location and sequence of miR-17-92 cluster have not been determined, due to the existence of a genomic gap sequence upstream of miR-17-92 cluster in all the birds whose genomes have been sequenced. In this study, genome walking was used to close the genomic gap upstream of chicken miR-17-92 cluster. In addition, bioinformatics analysis, reporter gene assay and truncation mutagenesis were used to investigate functional role of the genomic gap sequence. Genome walking analysis showed that the gap region was 1704 bp long, and its GC content was 80.11%. Bioinformatics analysis showed that in the gap region, there was a 200 bp conserved sequence among the tested 10 species (Gallus gallus, Homo sapiens, Pan troglodytes, Bos taurus, Sus scrofa, Rattus norvegicus, Mus musculus, Possum, Danio rerio, Rana nigromaculata), which is core promoter region of mammalian miR-17-92 host gene (MIR17HG). Promoter luciferase reporter gene vector of the gap region was constructed and reporter assay was performed. The result showed that the promoter activity of pGL3-cMIR17HG (-4228/-2506) was 417 times than that of negative control (empty pGL3 basic vector), suggesting that chicken miR-17-92 cluster promoter exists in the gap region. To further gain insight into the promoter structure, two different truncations for the cloned gap sequence were generated by PCR. One had a truncation of 448 bp at the 5'-end and the other had a truncation of 894 bp at the 3'-end. Further reporter analysis showed that compared with the promoter activity of pGL3-cMIR17HG (-4228/-2506), the reporter activities of the 5'-end truncation and the 3'-end truncation were reduced by 19

  15. Cluster Analysis of Velocity Field Derived from Dense GNSS Network of Japan

    NASA Astrophysics Data System (ADS)

    Takahashi, A.; Hashimoto, M.

    2015-12-01

    Dense GNSS networks have been widely used to observe crustal deformation. Simpson et al. (2012) and Savage and Simpson (2013) have conducted cluster analyses of GNSS velocity field in the San Francisco Bay Area and Mojave Desert, respectively. They have successfully found velocity discontinuities. They also showed an advantage of cluster analysis for classifying GNSS velocity field. Since in western United States, strike-slip events are dominant, geometry is simple. However, the Japanese Islands are tectonically complicated due to subduction of oceanic plates. There are many types of crustal deformation such as slow slip event and large postseismic deformation. We propose a modified clustering method of GNSS velocity field in Japan to separate time variant and static crustal deformation. Our modification is performing cluster analysis every several months or years, then qualifying cluster member similarity. If a GNSS station moved differently from its neighboring GNSS stations, the station will not belong to in the cluster which includes its surrounding stations. With this method, time variant phenomena were distinguished. We applied our method to GNSS data of Japan from 1996 to 2015. According to the analyses, following conclusions were derived. The first is the clusters boundaries are consistent with known active faults. For examples, the Arima-Takatsuki-Hanaore fault system and the Shimane-Tottori segment proposed by Nishimura (2015) are recognized, though without using prior information. The second is improving detectability of time variable phenomena, such as a slow slip event in northern part of Hokkaido region detected by Ohzono et al. (2015). The last one is the classification of postseismic deformation caused by large earthquakes. The result suggested velocity discontinuities in postseismic deformation of the Tohoku-oki earthquake. This result implies that postseismic deformation is not continuously decaying proportional to distance from its epicenter.

  16. A population-based analysis of clustering identifies a strong genetic contribution to lethal prostate cancer

    PubMed Central

    Nelson, Quentin; Agarwal, Neeraj; Stephenson, Robert; Cannon-Albright, Lisa A.

    2013-01-01

    Background: Prostate cancer is a common and often deadly cancer. Decades of study have yet to identify genes that explain much familial prostate cancer. Traditional linkage analysis of pedigrees has yielded results that are rarely validated. We hypothesize that there are rare segregating variants responsible for high-risk prostate cancer pedigrees, but recognize that within-pedigree heterogeneity is responsible for significant noise that overwhelms signal. Here we introduce a method to identify homogeneous subsets of prostate cancer, based on cancer characteristics, which show the best evidence for an inherited contribution. Methods: We have modified an existing method, the Genealogical Index of Familiality (GIF) used to show evidence for significant familial clustering. The modification allows a test for excess familial clustering of a subset of prostate cancer cases when compared to all prostate cancer cases. Results: Consideration of the familial clustering of eight clinical subsets of prostate cancer cases compared to the expected familial clustering of all prostate cancer cases identified three subsets of prostate cancer cases with evidence for familial clustering significantly in excess of expected. These subsets include prostate cancer cases diagnosed before age 50 years, prostate cancer cases with body mass index (BMI) greater than or equal to 30, and prostate cancer cases for whom prostate cancer contributed to death. Conclusions: This analysis identified several subsets of prostate cancer cases that cluster significantly more than expected when compared to all prostate cancer familial clustering. A focus on high-risk prostate cancer cases or pedigrees with these characteristics will reduce noise and could allow identification of the rare predisposition genes or variants responsible. PMID:23970893

  17. Indentifying the major air pollutants base on factor and cluster analysis, a case study in 74 Chinese cities

    NASA Astrophysics Data System (ADS)

    Zhang, Jing; Zhang, Lan-yue; Du, Ming; Zhang, Wei; Huang, Xin; Zhang, Ya-qi; Yang, Yue-yi; Zhang, Jian-min; Deng, Shi-huai; Shen, Fei; Li, Yuan-wei; Xiao, Hong

    2016-11-01

    This article investigated the major air pollutants and its spatial and seasonal distribution in 74 Chinese cities. Factor analysis and Cluster analysis are employed to indentify major factors of air pollutants. The following results are obtained (1) major factors are obtained in spring, summer, autumn, and winter. The first factor in spring includes NO2, PM10, CO, and PM2.5; the first factor in summer and autumn includes PM10, PM2.5, CO and SO2; in winter, the first factor includes NO2, PM10, PM2.5, and SO2. (2) In spring, cities of cluster 5 are the severest polluted by emission sources of SO2, CO, PM10, and PM2.5; the emission sources of O3 would significantly influence the air quality in cities of cluster 2; the emission sources of NO2 could significantly influence the air quality in cities of cluster 3 and cluster 5. (3) In summer, cities of cluster 5 are the severest polluted by automotive emissions and coal flue gas. Cities of cluster 1 are the lightest polluted. Cities of cluster 3 and cluster 2 are polluted by emission sources of SO2 and O3. (4) In Autumn, cities of cluster 3 and 4 are the severest polluted by the emission sources of SO2, CO, PM10, and PM2.5; the emission sources of NO2 would significantly influence the air quality in cities of cluster 5; the emission sources of O3 could significantly influence the air quality in cities of cluster 1 and cluster 4. (5) In winter, cities of cluster 5 are the severest polluted by the emission sources of SO2, CO, PM10, PM2.5, and CO; the emission sources of O3 could significantly influence the air quality in cities of cluster 1 and cluster 5.

  18. Cluster analysis of European surface ozone observations and MACC reanalysis data

    NASA Astrophysics Data System (ADS)

    Lyapina, Olga; Schultz, Martin; Hense, Andreas; Waychal, Snehal; Schröder, Sabine

    2013-04-01

    Europe has a high density of surface ozone monitoring sites, thus the comparison of measured ozone data with coarse-scale models requires special techniques. We have used Cluster Analysis (CA) to divide stations from the European air quality database (Airbase) into several groups and compare these groups with the results from a similar analysis performed on the output from the MOZART model in the Monitoring Atmospheric Composition and Climate (MACC) project. As initial set of variables the monthly averaged diurnal variations of the individual ozone time series were calculated. CA is an appropriate method for classification of a large number of monitoring sites, in order to find similar ozone behavior and representative station inside each group. Therefore CA opens new possibilities for the comparison between measured and modeled data. Airbase provides ozone data for all countries from the European Union. After applying filter criteria that 2/3 of data must be present in each month during the period 2007-2010, around 1500 stations were chosen from the Airbase. The modeled data were interpolated to the geographical site locations. Clusters from the measurements were compared with corresponding clusters obtained from the MACC model data. CA results are shown, characteristics of separate clusters are described, and seasonal-diurnal variations of clusters from monitored and modeled data are compared and discussed.

  19. Molecular analysis of enrichment cultures of ammonia oxidizers from the Salar de Huasco, a high altitude saline wetland in northern Chile.

    PubMed

    Dorador, Cristina; Busekow, Annika; Vila, Irma; Imhoff, Johannes F; Witzel, Karl-Paul

    2008-05-01

    We analyzed enrichment cultures of ammonia-oxidizing bacteria (AOB) collected from different areas of Salar de Huasco, a high altitude, saline, pH-neutral water body in the Chilean Altiplano. Samples were inoculated into mineral media with 10 mM NH4+ at five different salt concentrations (10, 200, 400, 800 and 1,400 mM NaCl). Low diversity (up to three phylotypes per enrichment) of beta-AOB was detected using 16S rDNA and amoA clone libraries. Growth of beta-AOB was only recorded in a few enrichment cultures and varied according to site or media salinity. In total, five 16S rDNA and amoA phylotypes were found which were related to Nitrosomonas europaea/Nitrosococcus mobilis, N. marina and N. communis clusters. Phylotype 1-16S was 97% similar with N. halophila, previously isolated from Mongolian soda lakes, and phylotypes from amoA sequences were similar with yet uncultured beta-AOB from different biofilms. Sequences related to N. halophila were frequently found at all salinities. Neither gamma-AOB nor ammonia-oxidizing Archaea were recorded in these enrichment cultures. PMID:18305895

  20. Universal screening test based on analysis of circulating organ-enriched microRNAs: a novel approach to diagnostic screening.

    PubMed

    Sheinerman, Kira S; Umansky, Samuil

    2015-03-01

    Early disease detection leads to more effective and cost-efficient treatment. It is especially important for cancer and neurodegenerative diseases, because progression of these pathologies leads to significant and frequently irreversible changes in underlying pathophysiological processes. At the same time, the development of specific screening tests for detection of each of the hundreds of human pathologies in asymptomatic stage may be impractical. Here, we discuss a recently proposed concept: the development of minimally invasive Universal Screening Test (UST) based on analysis of organ-enriched microRNAs in plasma and other bodily fluids. The UST is designed to detect the presence of a pathology in particular organ systems, organs, tissues or cell types without diagnosing a specific disease. Once the pathology is detected, more specific, and if necessary invasive and expensive, tests can be administered to precisely define the nature of the disease. Here, we discuss recent studies and analyze the data supporting the UST approach.

  1. Graphene based soft nanoreactors for facile "one-step" glycan enrichment and derivatization for MALDI-TOF-MS analysis.

    PubMed

    Bai, Haihong; Pan, Yiting; Tong, Wei; Zhang, Wanjun; Ren, Xiaojun; Tian, Fang; Peng, Bo; Wang, Xin; Zhang, Yangjun; Deng, Yulin; Qin, Weijie; Qian, Xiaohong

    2013-12-15

    Protein glycosylation is involved in the control of many important biological processes and structural alterations of the N-linked glycans are correlated with various kinds of disease. High-throughput N-glycan profiling is a key technique for elucidating the functions of glycans in biological process and disease development as well as discovering new diagnostic biomarkers. However, the low abundance of glycans existing in living organism, the competition/suppression effect of other highly abundant biological molecules and the inherent lack of alkalinity and hydrophobicity of glycans leads to particularly poor detection sensitivity in MS analysis. Here, we demonstrated the first "one-step" approach for highly efficient glycan enrichment and derivatization using reduced graphene oxide as nanoreactors and 1-pyrenebutyric hydrazide for glycan capture and derivatization, which resulted in a 33-fold increase in the glycan detection sensitivity in MALDI-TOF-MS and the identification of 48N-glycoforms from human plasma.

  2. Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

    NASA Astrophysics Data System (ADS)

    Crawford, I.; Ruske, S.; Topping, D. O.; Gallagher, M. W.

    2015-11-01

    In this paper we present improved methods for discriminating and quantifying primary biological aerosol particles (PBAPs) by applying hierarchical agglomerative cluster analysis to multi-parameter ultraviolet-light-induced fluorescence (UV-LIF) spectrometer data. The methods employed in this study can be applied to data sets in excess of 1 × 106 points on a desktop computer, allowing for each fluorescent particle in a data set to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient data set. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4) where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best-performing methods were applied to the BEACHON-RoMBAS (Bio-hydro-atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics and Nitrogen-Rocky Mountain Biogenic Aerosol Study) ambient data set, where it was found that the z-score and range normalisation methods yield similar results, with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP) where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the underestimation of

  3. Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

    NASA Astrophysics Data System (ADS)

    Crawford, I.; Ruske, S.; Topping, D. O.; Gallagher, M. W.

    2015-07-01

    In this paper we present improved methods for discriminating and quantifying Primary Biological Aerosol Particles (PBAP) by applying hierarchical agglomerative cluster analysis to multi-parameter ultra violet-light induced fluorescence (UV-LIF) spectrometer data. The methods employed in this study can be applied to data sets in excess of 1×106 points on a desktop computer, allowing for each fluorescent particle in a dataset to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient dataset. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4) where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best performing methods were applied to the BEACHON-RoMBAS ambient dataset where it was found that the z-score and range normalisation methods yield similar results with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP) where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the underestimation of bacterial aerosol concentration by a factor of 5. We suggest that this likely due to errors arising from misatrribution due to poor

  4. An expressed sequence tag database of T-cell-enriched activated chicken splenocytes: sequence analysis of 5251 clones.

    PubMed

    Tirunagaru, V G; Sofer, L; Cui, J; Burnside, J

    2000-06-01

    The cDNA and gene sequences of many mammalian cytokines and their receptors are known. However, corresponding information on avian cytokines is limited due to the lack of cross-species activity at the functional level or strong homology at the molecular level. To improve the efficiency of identifying cytokines and novel chicken genes, a directionally cloned cDNA library from T-cell-enriched activated chicken splenocytes was constructed, and the partial sequence of 5251 clones was obtained. Sequence clustering indicates that 2357 (42%) of the clones are present as a single copy, and 2961 are distinct clones, demonstrating the high level of complexity of this library. Comparisons of the sequence data with known DNA sequences in GenBank indicate that approximately 25% of the clones match known chicken genes, 39% have similarity to known genes in other species, and 11% had no match to any sequence in the database. Several previously uncharacterized chicken cytokines and their receptors were present in our library. This collection provides a useful database for cataloging genes expressed in T cells and a valuable resource for future investigations of gene expression in avian immunology. A chicken EST Web site (http://udgenome. ags.udel. edu/chickest/chick.htm) has been created to provide access to the data, and a set of unique sequences has been deposited with GenBank (Accession Nos. AI979741-AI982511). Our new Web site (http://www. chickest.udel.edu) will be active as of March 3, 2000, and will also provide keyword-searching capabilities for BLASTX and BLASTN hits of all our clones. PMID:10860659

  5. Exploring the Relationship between Autism Spectrum Disorder and Epilepsy Using Latent Class Cluster Analysis

    ERIC Educational Resources Information Center

    Cuccaro, Michael L.; Tuchman, Roberto F.; Hamilton, Kara L.; Wright, Harry H.; Abramson, Ruth K.; Haines, Jonathan L.; Gilbert, John R.; Pericak-Vance, Margaret

    2012-01-01

    Epilepsy co-occurs frequently in autism spectrum disorders (ASD). Understanding this co-occurrence requires a better understanding of the ASD-epilepsy phenotype (or phenotypes). To address this, we conducted latent class cluster analysis (LCCA) on an ASD dataset (N = 577) which included 64 individuals with epilepsy. We identified a 5-cluster…

  6. [Current service invention patents and growth pathways on basis of cluster analysis].

    PubMed

    Yang, Xu-jie; Xiao, Shi-ying

    2012-09-01

    This study aims for enhancing quantity and quality of patents of traditional Chinese medicine compounds of traditional Chinese medicine enterprises, traditional Chinese medicine colleges and relevant institutions while building an efficient pathway for patent protection using simple statistics and cluster analysis, with service invention patent holders of traditional Chinese medicine compounds as the study object.

  7. Clustered Stomates in "Begonia": An Exercise in Data Collection & Statistical Analysis of Biological Space

    ERIC Educational Resources Information Center

    Lau, Joann M.; Korn, Robert W.

    2007-01-01

    In this article, the authors present a laboratory exercise in data collection and statistical analysis in biological space using clustered stomates on leaves of "Begonia" plants. The exercise can be done in middle school classes by students making their own slides and seeing imprints of cells, or at the high school level through collecting data of…

  8. Student Motivational Profiles in an Introductory MIS Course: An Exploratory Cluster Analysis

    ERIC Educational Resources Information Center

    Nelson, Klara

    2014-01-01

    This study profiles students in an introductory MIS course according to a variety of variables associated with choice of academic major. The data were collected through a survey administered to 12 sections of the course. A two-step cluster analysis was performed with gender as a categorical variable and students' perceptions of task value…

  9. Profiles of More and Less Successful L2 Learners: A Cluster Analysis Study

    ERIC Educational Resources Information Center

    Sparks, Richard L.; Patton, Jon; Ganschow, Leonore

    2012-01-01

    This retrospective study examined L1 achievement, intelligence, L2 aptitude, and L2 proficiency profiles of 208 students completing two years of high school L2 courses. A cluster analysis was performed to determine whether distinct cognitive and achievement profiles of more and less successful L2 learners would emerge. The results of…

  10. A Cluster Analysis of the Circumstances of Death in Suicides in Hong Kong

    ERIC Educational Resources Information Center

    Chen, Eric Y. H.; Chan, Wincy S. C.; Chan, Sandra S. M.; Liu, Ka Y.; Chan, Cecilia L. W.; Wong, Paul W. C.; Law, Y. W.; Yip, Paul S. F.

    2007-01-01

    Classification of suicides is essential for clinicians to better identify self-harm patients with future suicidal risks. This study examined potential subtypes of suicide in a psychological autopsy sample (N = 148) in Hong Kong. Hierarchical cluster analysis extracted two subgroups of subjects in terms of expressed deliberation assessed by the…

  11. Cluster Analysis of Assessment in Anatomy and Physiology for Health Science Undergraduates

    ERIC Educational Resources Information Center

    Brown, Stephen; White, Sue; Power, Nicola

    2016-01-01

    Academic content common to health science programs is often taught to a mixed group of students; however, content assessment may be consistent for each discipline. This study used a retrospective cluster analysis on such a group, first to identify high and low achieving students, and second, to determine the distribution of students within…

  12. Student Motivation and Learning in Mathematics and Science: A Cluster Analysis

    ERIC Educational Resources Information Center

    Ng, Betsy L. L.; Liu, W. C.; Wang, John C. K.

    2016-01-01

    The present study focused on an in-depth understanding of student motivation and self-regulated learning in mathematics and science through cluster analysis. It examined the different learning profiles of motivational beliefs and self-regulatory strategies in relation to perceived teacher autonomy support, basic psychological needs (i.e. autonomy,…

  13. An algol program for dissimilarity analysis: a divisive-omnithetic clustering technique

    USGS Publications Warehouse

    Tipper, J.C.

    1979-01-01

    Clustering techniques are used properly to generate hypotheses about patterns in data. Of the hierarchical techniques, those which are divisive and omnithetic possess many theoretically optimal properties. One such method, dissimilarity analysis, is implemented here in ALGOL 60, and determined to be competitive computationally with most other methods. ?? 1979.

  14. Fuzzy Clustering Analysis in Environmental Impact Assessment--A Complement Tool to Environmental Quality Index.

    ERIC Educational Resources Information Center

    Kung, Hsiang-Te; And Others

    1993-01-01

    In spite of rapid progress achieved in the methodological research underlying environmental impact assessment (EIA), the problem of weighting various parameters has not yet been solved. This paper presents a new approach, fuzzy clustering analysis, which is illustrated with an EIA case study on Baoshan-Wusong District in Shanghai, China. (Author)

  15. Multiscale deep drawing analysis of dual-phase steels using grain cluster-based RGC scheme

    NASA Astrophysics Data System (ADS)

    Tjahjanto, D. D.; Eisenlohr, P.; Roters, F.

    2015-06-01

    Multiscale modelling and simulation play an important role in sheet metal forming analysis, since the overall material responses at macroscopic engineering scales, e.g. formability and anisotropy, are strongly influenced by microstructural properties, such as grain size and crystal orientations (texture). In the present report, multiscale analysis on deep drawing of dual-phase steels is performed using an efficient grain cluster-based homogenization scheme. The homogenization scheme, called relaxed grain cluster (RGC), is based on a generalization of the grain cluster concept, where a (representative) volume element consists of p  ×  q  ×  r (hexahedral) grains. In this scheme, variation of the strain or deformation of individual grains is taken into account through the, so-called, interface relaxation, which is formulated within an energy minimization framework. An interfacial penalty term is introduced into the energy minimization framework in order to account for the effects of grain boundaries. The grain cluster-based homogenization scheme has been implemented and incorporated into the advanced material simulation platform DAMASK, which purposes to bridge the macroscale boundary value problems associated with deep drawing analysis to the micromechanical constitutive law, e.g. crystal plasticity model. Standard Lankford anisotropy tests are performed to validate the model parameters prior to the deep drawing analysis. Model predictions for the deep drawing simulations are analyzed and compared to the corresponding experimental data. The result shows that the predictions of the model are in a very good agreement with the experimental measurement.

  16. Insulin-positive, Glut2-low cells present within mouse pancreas exhibit lineage plasticity and are enriched within extra-islet endocrine cell clusters.

    PubMed

    Beamish, Christine A; Strutt, Brenda J; Arany, Edith J; Hill, David J

    2016-04-18

    Regeneration of insulin-producing β-cells from resident pancreas progenitors requires an understanding of both progenitor identity and lineage plasticity. One model suggested that a rare β-cell sub-population within islets demonstrated multi-lineage plasticity. We hypothesized that β-cells from young mice (postnatal day 7, P7) exhibit such plasticity and used a model of islet dedifferentiation toward a ductal epithelial-cell phenotype to test this theory. RIPCre;Z/AP(+/+) mice were used to lineage trace the fate of β-cells during dedifferentiation culture by a human placental alkaline phosphatase (HPAP) reporter. There was a significant loss of HPAP-expressing β-cells in culture, but remaining HPAP(+) cells lost insulin expression while gaining expression of the epithelial duct cell marker cytokeratin-19 (Ck19). Flow cytometry and recovery of β-cell subpopulations from whole pancreas vs. islets suggest that the HPAP(+)Ck19(+) cells had derived from insulin-positive, glucose-transporter-2-low (Ins(+)Glut2(LO)) cells, representing 3.5% of all insulin-expressing cells. The majority of these cells were found outside of islets within clusters of <5 β-cells. These insulin(+)Glut2(LO) cells demonstrated a greater proliferation rate in vivo and in vitro as compared to insulin(+)Glut2(+) cells at P7, were retained into adulthood, and a subset differentiated into endocrine, ductal, and neural lineages, illustrating substantial plasticity. Results were confirmed using RIPCre;ROSA- eYFP mice. Quantitative PCR data indicated these cells possess an immature β-cell phenotype. These Ins(+)Glut2(LO) cells may represent a resident population of cells capable of forming new, functional β-cells, and which may be potentially exploited for regenerative therapies in the future.

  17. Insulin-positive, Glut2-low cells present within mouse pancreas exhibit lineage plasticity and are enriched within extra-islet endocrine cell clusters.

    PubMed

    Beamish, Christine A; Strutt, Brenda J; Arany, Edith J; Hill, David J

    2016-04-18

    Regeneration of insulin-producing β-cells from resident pancreas progenitors requires an understanding of both progenitor identity and lineage plasticity. One model suggested that a rare β-cell sub-population within islets demonstrated multi-lineage plasticity. We hypothesized that β-cells from young mice (postnatal day 7, P7) exhibit such plasticity and used a model of islet dedifferentiation toward a ductal epithelial-cell phenotype to test this theory. RIPCre;Z/AP(+/+) mice were used to lineage trace the fate of β-cells during dedifferentiation culture by a human placental alkaline phosphatase (HPAP) reporter. There was a significant loss of HPAP-expressing β-cells in culture, but remaining HPAP(+) cells lost insulin expression while gaining expression of the epithelial duct cell marker cytokeratin-19 (Ck19). Flow cytometry and recovery of β-cell subpopulations from whole pancreas vs. islets suggest that the HPAP(+)Ck19(+) cells had derived from insulin-positive, glucose-transporter-2-low (Ins(+)Glut2(LO)) cells, representing 3.5% of all insulin-expressing cells. The majority of these cells were found outside of islets within clusters of <5 β-cells. These insulin(+)Glut2(LO) cells demonstrated a greater proliferation rate in vivo and in vitro as compared to insulin(+)Glut2(+) cells at P7, were retained into adulthood, and a subset differentiated into endocrine, ductal, and neural lineages, illustrating substantial plasticity. Results were confirmed using RIPCre;ROSA- eYFP mice. Quantitative PCR data indicated these cells possess an immature β-cell phenotype. These Ins(+)Glut2(LO) cells may represent a resident population of cells capable of forming new, functional β-cells, and which may be potentially exploited for regenerative therapies in the future. PMID:27010375

  18. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS.

    PubMed

    Lorkiewicz, Pawel; Higashi, Richard M; Lane, Andrew N; Fan, Teresa W-M

    2012-01-01

    Fourier transform-ion cyclotron resonance-mass spectrometry (FTICR-MS) is capable of acquiring unmatched quality of isotopologue data for stable isotope resolved metabolomics (SIRM). This capability drives the need for a continuous ion introduction for obtaining optimal isotope ratios. Here we report the simultaneous analysis of mono and dinucleotides from crude polar extracts by FTICR-MS by adapting an ion-pairing sample preparation method for LC-MS analysis. This involves a rapid cleanup of extracted nucleotides on pipet tips containing a C(18) stationary phase, which enabled global analysis of nucleotides and their (13)C isotopologues at nanomolar concentrations by direct infusion nanoelectrospray FTICR-MS with 5 minutes of data acquisition. The resolution and mass accuracy enabled computer-assisted unambiguous assignment of most nucleotide species, including all phosphorylated forms of the adenine, guanine, uracil and cytosine nucleotides, NAD(+), NADH, NADP(+), NADPH, cyclic nucleotides, several UDP-hexoses, and all their (13)C isotopologues. The method was applied to a SIRM study on human lung adenocarcinoma A549 cells grown in [U-(13)C] glucose with or without the anti-cancer agent methylseleninic acid. At m/z resolving power of 400,000, (13)C-isotopologues of nucleotides were fully resolved from all other elemental isotopologues, thus allowing their (13)C fractional enrichment to be accurately determined. The method achieves both high sample and high information throughput analysis of nucleotides for metabolic pathway reconstruction in SIRM investigations.

  19. Gene Co-Expression Network Analysis for Identifying Modules and Functionally Enriched Pathways in Type 1 Diabetes

    PubMed Central

    Riquelme Medina, Ignacio; Lubovac-Pilav, Zelmina

    2016-01-01

    Type 1 diabetes (T1D) is a complex disease, caused by the autoimmune destruction of the insulin producing pancreatic beta cells, resulting in the body’s inability to produce insulin. While great efforts have been put into understanding the genetic and environmental factors that contribute to the etiology of the disease, the exact molecular mechanisms are still largely unknown. T1D is a heterogeneous disease, and previous research in this field is mainly focused on the analysis of single genes, or using traditional gene expression profiling, which generally does not reveal the functional context of a gene associated with a complex disorder. However, network-based analysis does take into account the interactions between the diabetes specific genes or proteins and contributes to new knowledge about disease modules, which in turn can be used for identification of potential new biomarkers for T1D. In this study, we analyzed public microarray data of T1D patients and healthy controls by applying a systems biology approach that combines network-based Weighted Gene Co-Expression Network Analysis (WGCNA) with functional enrichment analysis. Novel co-expression gene network modules associated with T1D were elucidated, which in turn provided a basis for the identification of potential pathways and biomarker genes that may be involved in development of T1D. PMID:27257970

  20. Gene Co-Expression Network Analysis for Identifying Modules and Functionally Enriched Pathways in Type 1 Diabetes.

    PubMed

    Riquelme Medina, Ignacio; Lubovac-Pilav, Zelmina

    2016-01-01

    Type 1 diabetes (T1D) is a complex disease, caused by the autoimmune destruction of the insulin producing pancreatic beta cells, resulting in the body's inability to produce insulin. While great efforts have been put into understanding the genetic and environmental factors that contribute to the etiology of the disease, the exact molecular mechanisms are still largely unknown. T1D is a heterogeneous disease, and previous research in this field is mainly focused on the analysis of single genes, or using traditional gene expression profiling, which generally does not reveal the functional context of a gene associated with a complex disorder. However, network-based analysis does take into account the interactions between the diabetes specific genes or proteins and contributes to new knowledge about disease modules, which in turn can be used for identification of potential new biomarkers for T1D. In this study, we analyzed public microarray data of T1D patients and healthy controls by applying a systems biology approach that combines network-based Weighted Gene Co-Expression Network Analysis (WGCNA) with functional enrichment analysis. Novel co-expression gene network modules associated with T1D were elucidated, which in turn provided a basis for the identification of potential pathways and biomarker genes that may be involved in development of T1D. PMID:27257970

  1. Unraveling the dha cluster in Citrobacter werkmanii: comparative genomic analysis of bacterial 1,3-propanediol biosynthesis clusters.

    PubMed

    Maervoet, Veerle E T; De Maeseneire, Sofie L; Soetaert, Wim K; De Mey, Marjan

    2014-04-01

    In natural 1,3-propanediol (PDO) producing microorganisms such as Klebsiella pneumoniae, Citrobacter freundii and Clostridium sp., the genes coding for PDO producing enzymes are grouped in a dha cluster. This article describes the dha cluster of a novel candidate for PDO production, Citrobacter werkmanii DSM17579 and compares the cluster to the currently known PDO clusters of Enterobacteriaceae and Clostridiaceae. Moreover, we attribute a putative function to two previously unannotated ORFs, OrfW and OrfY, both in C. freundii and in C. werkmanii: both proteins might form a complex and support the glycerol dehydratase by converting cob(I)alamin to the glycerol dehydratase cofactor coenzyme B12. Unraveling this biosynthesis cluster revealed high homology between the deduced amino acid sequence of the open reading frames of C. werkmanii DSM17579 and those of C. freundii DSM30040 and K. pneumoniae MGH78578, i.e., 96 and 87.5 % identity, respectively. On the other hand, major differences between the clusters have also been discovered. For example, only one dihydroxyacetone kinase (DHAK) is present in the dha cluster of C. werkmanii DSM17579, while two DHAK enzymes are present in the cluster of K. pneumoniae MGH78578 and Clostridium butyricum VPI1718.

  2. N-glycoproteome Analysis of the Secretome of Human Metastatic Hepatocellular Carcinoma Cell Lines Combining Hydrazide Chemistry, HILIC Enrichment and Mass Spectrometry

    PubMed Central

    Li, Xianyu; Jiang, Jing; Zhao, Xinyuan; Wang, Jifeng; Han, Huanhuan; Zhao, Yan; Peng, Bo; Zhong, Rugang; Ying, Wantao; Qian, Xiaohong

    2013-01-01

    Cancer cell metastasis is a major cause of cancer death. Unfortunately, the underlying molecular mechanisms remain unknown, which results in the lack of efficient diagnosis, therapy and prevention approaches. Nevertheless, the dysregulation of the cancer cell secretome is known to play key roles in tumor transformation and progression. The majority of proteins in the secretome are secretory proteins and membrane-released proteins, and, mostly, the glycosylated proteins. Until recently, few studies have explored protein N-glycosylation changes in the secretome, although protein glycosylation has received increasing attention in the study of tumor development processes. Here, the N-glycoproteins in the secretome of two human hepatocellular carcinoma (HCC) cell lines with low (MHCC97L) or high (HCCLM3) metastatic potential were investigated with a in-depth characterization of the N-glycosites by combining two general glycopeptide enrichment approaches, hydrazide chemistry and zwitterionic hydrophilic interaction chromatography (zic-HILIC), with mass spectrometry analysis. A total of 1,213 unique N-glycosites from 611 N-glycoproteins were confidently identified. These N-glycoproteins were primarily localized to the extracellular space and plasma membrane, supporting the important role of N-glycosylation in the secretory pathway. Coupling label-free quantification with a hierarchical clustering strategy, we determined the differential regulation of several N-glycoproteins that are related to metastasis, among which AFP, DKK1, FN1, CD151 and TGFβ2 were up-regulated in HCCLM3 cells. The inclusion of the well-known metastasis-related proteins AFP and DKK1 in this list provides solid supports for our study. Further western blotting experiments detecting FN1 and FAT1 confirmed our discovery. The glycoproteome strategy in this study provides an effective means to explore potential cancer biomarkers. PMID:24324730

  3. A New Classification of Diabetic Gait Pattern Based on Cluster Analysis of Biomechanical Data

    PubMed Central

    Sawacha, Zimi; Guarneri, Gabriella; Avogaro, Angelo; Cobelli, Claudio

    2010-01-01

    Background The diabetic foot, one of the most serious complications of diabetes mellitus and a major risk factor for plantar ulceration, is determined mainly by peripheral neuropathy. Neuropathic patients exhibit decreased stability while standing as well as during dynamic conditions. A new methodology for diabetic gait pattern classification based on cluster analysis has been proposed that aims to identify groups of subjects with similar patterns of gait and verify if three-dimensional gait data are able to distinguish diabetic gait patterns from one of the control subjects. Method The gait of 20 nondiabetic individuals and 46 diabetes patients with and without peripheral neuropathy was analyzed [mean age 59.0 (2.9) and 61.1(4.4) years, mean body mass index (BMI) 24.0 (2.8), and 26.3 (2.0)]. K-means cluster analysis was applied to classify the subjects' gait patterns through the analysis of their ground reaction forces, joints and segments (trunk, hip, knee, ankle) angles, and moments. Results Cluster analysis classification led to definition of four well-separated clusters: one aggregating just neuropathic subjects, one aggregating both neuropathics and non-neuropathics, one including only diabetes patients, and one including either controls or diabetic and neuropathic subjects. Conclusions Cluster analysis was useful in grouping subjects with similar gait patterns and provided evidence that there were subgroups that might otherwise not be observed if a group ensemble was presented for any specific variable. In particular, we observed the presence of neuropathic subjects with a gait similar to the controls and diabetes patients with a long disease duration with a gait as altered as the neuropathic one. PMID:20920432

  4. The Feasibility of Using Cluster Analysis to Examine Log Data from Educational Video Games. CRESST Report 790

    ERIC Educational Resources Information Center

    Kerr, Deirdre; Chung, Gregory K. W. K.; Iseli, Markus R.

    2011-01-01

    Analyzing log data from educational video games has proven to be a challenging endeavor. In this paper, we examine the feasibility of using cluster analysis to extract information from the log files that is interpretable in both the context of the game and the context of the subject area. If cluster analysis can be used to identify patterns of…

  5. Market segmentation for multiple option healthcare delivery systems--an application of cluster analysis.

    PubMed

    Jarboe, G R; Gates, R H; McDaniel, C D

    1990-01-01

    Healthcare providers of multiple option plans may be confronted with special market segmentation problems. This study demonstrates how cluster analysis may be used for discovering distinct patterns of preference for multiple option plans. The availability of metric, as opposed to categorical or ordinal, data provides the ability to use sophisticated analysis techniques which may be superior to frequency distributions and cross-tabulations in revealing preference patterns.

  6. NPP Saturation, Soil Acidification, and Phosphorus Limitation Caused by Nitrogen Enrichment-Meta Analysis of Manipulative Experiments

    NASA Astrophysics Data System (ADS)

    Niu, S.; Tian, D.; Li, Y.

    2015-12-01

    Increased reactive nitrogen (N) deposition is traditionally expected to increase net primary production (NPP), but continued retention of N deposition may saturate the ecosystem capacity to store N and cause some dark side effects on ecosystems, like soil acidification and the limitation of other nutrient. However, those dark side effects of nitrogen deposition have not been well quantified based on experimental evidences. We synthesized nitrogen deposition experiments in the world and conducted three meta-analysis studies. By compiling a dataset from 44 studies with at least three levels of N addition treatment, we found an universal saturation response of NPP to N addition gradient in terrestrial ecosystems. The N saturation threshold for NPP was at the N addition rates of 4-5 g m-2 yr-1 on average across all the ecosystems. However, ecosystem types and environmental factors largely impacted the saturation response patterns and the N thresholds. By synthesizing 106 studies that monitored soil pH and base cations under N enrichment, we quantified global soil acidification caused by N addition. On average, N addition significantly reduced soil pH by 0.26, but the magnitude varied with ecosystem types, N addition rate, N fertilization forms, and experimental durations. Environmental factors such as initial soil pH, soil carbon and nitrogen content, precipitation, and temperature all influenced the N responses of soil pH. Global soils are now at a buffering transition from base cations (Ca2+, Mg2+ and K+) to non-base cations (Mn2+ and Al3+). This calls our attention to care about the limitation of base cations and the toxic impact of non-base cations for terrestrial ecosystems with N deposition. By comparing the phosphorus limitation on biomass productions between the ambient and elevated N conditions, we found a stronger P limitation induced by N enrichment. Overall, the results indicate that the beneficial effect of N deposition on ecosystem productivity will

  7. Chemical preparation of an isotopically enriched superoxide dismutase and its characterization as a standard for species-specific isotope dilution analysis.

    PubMed

    Deitrich, Christian L; Raab, Andrea; Pioselli, Barbara; Thomas-Oates, Jane E; Feldmann, Jörg

    2007-11-01

    The development of methods to analyze accurately and precisely individual metalloproteins is of increasing importance. Here we describe for the first time the chemical preparation and characterization of an isotopically enriched metalloenzyme containing two different metal isotopes. Its evaluation as a standard in species-specific isotope dilution analysis by HPLC coupled to inductively coupled plasma mass spectrometry is carefully evaluated. Our model enzyme bovine superoxide dismutase (SOD) contains both Cu and Zn and is remarkably stable at high temperatures and even under denaturing conditions. The enzyme's metal cofactors were removed under a range of different conditions and replaced with isotopically enriched 65Cu and 68Zn. Depending on the conditions, various isotopic ratios differing from the natural Cu and Zn abundances were obtained for the reconstituted enzyme. Both the wild type and isotopically enriched enzyme had the same migration pattern on native 1D-PAGE. Using an enzyme activity test, we showed that the incorporated 65Cu was bound to the right SOD-binding site, since the measured activity correlated directly with the amount of Cu incorporated. Mixing the native and the isotopically enriched enzyme standard with free enriched 65Cu and 68Zn or a metal chelator did not result in any exchange or loss of the metals from the enzyme at neutral pH. This verifies the stability of the enzyme metal center under the chosen conditions. The isotopically enriched enzyme standard was spiked into a wild type SOD solution to evaluate its use for species-specific isotope dilution experiments. To our knowledge, this is the first report of the chemical preparation of a metalloenzyme containing two different isotopically enriched metals. We provide evidence that the incorporated isotopically enriched metals are bound to the right binding site of SOD using an specific enzymatic activity assay.

  8. Alteration mapping at Goldfield, Nevada, by cluster and discriminant analysis of LANDSAT digital data

    NASA Technical Reports Server (NTRS)

    Ballew, G.

    1977-01-01

    The ability of Landsat multispectral digital data to differentiate among 62 combinations of rock and alteration types at the Goldfield mining district of Western Nevada was investigated by using statistical techniques of cluster and discriminant analysis. Multivariate discriminant analysis was not effective in classifying each of the 62 groups, with classification results essentially the same whether data of four channels alone or combined with six ratios of channels were used. Bivariate plots of group means revealed a cluster of three groups including mill tailings, basalt and all other rock and alteration types. Automatic hierarchical clustering based on the fourth dimensional Mahalanobis distance between group means of 30 groups having five or more samples was performed. The results of the cluster analysis revealed hierarchies of mill tailings vs. natural materials, basalt vs. non-basalt, highly reflectant rocks vs. other rocks and exclusively unaltered rocks vs. predominantly altered rocks. The hierarchies were used to determine the order in which sets of multiple discriminant analyses were to be performed and the resulting discriminant functions were used to produce a map of geology and alteration which has an overall accuracy of 70 percent for discriminating exclusively altered rocks from predominantly altered rocks.

  9. Fault Reactivation Analysis Using Microearthquake Clustering Based on Signal-to-Noise Weighted Waveform Similarity

    NASA Astrophysics Data System (ADS)

    Grund, Michael; Groos, Jörn C.; Ritter, Joachim R. R.

    2016-07-01

    The cluster formation of about 2000 induced microearthquakes (mostly M L < 2) is studied using a waveform similarity technique based on cross-correlation and a subsequent equivalence class approach. All events were detected within two separated but neighbouring seismic volumes close to the geothermal powerplants near Landau and Insheim in the Upper Rhine Graben, SW Germany between 2006 and 2013. Besides different sensors, sampling rates and individual data gaps, mainly low signal-to-noise ratios (SNR) of the recordings at most station sites provide a complication for the determination of a precise waveform similarity analysis of the microseismic events in this area. To include a large number of events for such an analysis, a newly developed weighting approach was implemented in the waveform similarity analysis which directly considers the individual SNRs across the whole seismic network. The application to both seismic volumes leads to event clusters with high waveform similarities within short (seconds to hours) and long (months to years) time periods covering two magnitude ranges. The estimated relative hypocenter locations are spatially concentrated for each single cluster and mirror the orientations of mapped faults as well as interpreted rupture planes determined from fault plane solutions. Depending on the waveform cross-correlation coefficient threshold, clusters can be resolved in space to as little as one dominant wavelength. The interpretation of these observations implies recurring fault reactivations by fluid injection with very similar faulting mechanisms during different time periods between 2006 and 2013.

  10. Clustering analysis of western North Pacific Tropical Cyclone tracks using the Self Organizing Map

    NASA Astrophysics Data System (ADS)

    Kim, H.; Seo, K.

    2013-12-01

    A cluster analysis using Self Organizing Map (SOM) is used to characterize tropical cyclone (TC) tracks over the western North Pacific. A False Discovery Rate (FDR) method is used to objectively determine an optimum cluster number. For 620 TC tracks over the WNP from June-October during 1979-2010, the five clusters for TC tracks are selected. These can further be categorized into three major patterns: straight-moving track, recurving track, and quasi-random pattern. Each pattern is characterized by land falling regions: near South and East China, East Asia, and off-shore of Japan. In addition, each pattern shows distinctive properties in its traveling distance, lifetime, intensity (mean minimum sea level pressure), and genesis location. It is revealed that these three patterns are associated with the large-scale dynamics such as variability of the western Pacific subtropical high and the Madden-Julian Oscillation. The impacts of El Nino and NAO will be discussed.

  11. [Investigation of fuzzy-clustering in octane number prediction model based on detailed hydrocarbon analysis data].

    PubMed

    Liu, Yingrong; Xu, Yupeng; Yang, Haiying

    2004-09-01

    A method to establish octane number prediction model based on detailed hydrocarbon analysis (DHA) data is presented. The techniques of fuzzy-clustering and the Euclidian distance are employed to select the samples needed in pattern establishment. One hundred and fifty gasoline samples and an amount of 140 characteristic components in the DHA chromatogram of each sample are used for the fuzzy-clustering research. It is found that the 3 - 10 samples, which have the nearest Euclidian distance ( < 1.5) to the prediction sample in the same cluster, are enough to build the octane number prediction model. The experimental results proved that the model obtained according to the above method has more predictable accuracy, wider application range and higher data resource utility compared with the current prediction method.

  12. Assessing antibiotic resistance in fecal Escherichia coli in young calves using cluster analysis techniques.

    PubMed

    Berge, A C B; Atwill, E R; Sischo, W M

    2003-10-15

    This study uses cluster analysis techniques to describe the antibiotic susceptibility patterns seen in calf fecal Escherichia coli (E. coli). Cohorts of 30 dairy calves at six farms were sampled at 2-week intervals during the pre-weaning period. At each sampling occasion five fecal E. coli isolates per calf were analyzed for antibiotic susceptibility to 12 antibiotics using the disk diffusion method. All isolates had a profile consisting of the aggregate measured inhibition zone size for each of the evaluated antibiotics. Several cluster analytic algorithms were assessed to partition the E. coli isolates. For our data, Ward's minimum variance method met the objectives of the study. Relative to the number of possible combinations of resistance clusters, a parsimonious set of 14 patterns was developed. This set of E. coli isolates exhibited a limited set of resistance patterns to the different antibiotics indicating that certain resistance genes may be linked.

  13. Cluster Method Analysis of K. S. C. Image

    NASA Technical Reports Server (NTRS)

    Rodriguez, Joe, Jr.; Desai, M.

    1997-01-01

    Information obtained from satellite-based systems has moved to the forefront as a method in the identification of many land cover types. Identification of different land features through remote sensing is an effective tool for regional and global assessment of geometric characteristics. Classification data acquired from remote sensing images have a wide variety of applications. In particular, analysis of remote sensing images have special applications in the classification of various types of vegetation. Results obtained from classification studies of a particular area or region serve towards a greater understanding of what parameters (ecological, temporal, etc.) affect the region being analyzed. In this paper, we make a distinction between both types of classification approaches although, focus is given to the unsupervised classification method using 1987 Thematic Mapped (TM) images of Kennedy Space Center.

  14. Automation of Large-scale Computer Cluster Monitoring Information Analysis

    NASA Astrophysics Data System (ADS)

    Magradze, Erekle; Nadal, Jordi; Quadt, Arnulf; Kawamura, Gen; Musheghyan, Haykuhi

    2015-12-01

    High-throughput computing platforms consist of a complex infrastructure and provide a number of services apt to failures. To mitigate the impact of failures on the quality of the provided services, a constant monitoring and in time reaction is required, which is impossible without automation of the system administration processes. This paper introduces a way of automation of the process of monitoring information analysis to provide the long and short term predictions of the service response time (SRT) for a mass storage and batch systems and to identify the status of a service at a given time. The approach for the SRT predictions is based on Adaptive Neuro Fuzzy Inference System (ANFIS). An evaluation of the approaches is performed on real monitoring data from the WLCG Tier 2 center GoeGrid. Ten fold cross validation results demonstrate high efficiency of both approaches in comparison to known methods.

  15. Sensory analysis of rainbow trout, oncorhynchus mykiss, fed enriched black soldier fly prepupae, hermetia illucens

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A growth trial and fillet sensory analysis were conducted to examine the effects of replacing dietary fish meal with black soldier fly (BSF) prepupae, Hermetia illucens, in rainbow trout, Oncorhynchus mykiss. A practical-type trout diet was formulated to contain 45% protein; four test diets were dev...

  16. Symmetry analysis in the investigation of clusters in complex metallic alloys

    NASA Astrophysics Data System (ADS)

    Sikora, W.; Malinowski, J.; Kuna, A.; Pytlik, L.

    2008-03-01

    In the complex metallic alloys (CMA) it is often found that some parts of the unit cell form well-defined nanoscale building blocks, called clusters, which are characterized by a specific local symmetry and separated from the 'matrix' crystal lattice by a partially disordered interface zone. The interior of the cluster is usually a close packed structure, the structure of which is not always exactly known, because of the partial disorder in the outer coordination shells. In many CMA's the clusters form a high-symmetry superlattice structure, what usually leads to a giant cubic or pseudo cubic unit cell. The present paper shows a possibility to analyze the changes in local symmetry of the clusters (objects decorating the superlattice nodes) during transformations of the global crystal symmetry. The symmetry analysis method applied to tensor objects, attributed to the clusters, provides information about the symmetry relations between the objects located in different nodes as well as the local symmetry of individual objects (local principal axes, local anisotropy etc.)

  17. Links between patterns of racial socialization and discrimination experiences and psychological adjustment: a cluster analysis.

    PubMed

    Ajayi, Alex A; Syed, Moin

    2014-10-01

    This study used a person-oriented analytic approach to identify meaningful patterns of barriers-focused racial socialization and perceived racial discrimination experiences in a sample of 295 late adolescents. Using cluster analysis, three distinct groups were identified: Low Barrier Socialization-Low Discrimination, High Barrier Socialization-Low Discrimination, and High Barrier Socialization-High Discrimination clusters. These groups were substantively unique in terms of the frequency of racial socialization messages about bias preparation and out-group mistrust its members received and their actual perceived discrimination experiences. Further, individuals in the High Barrier Socialization-High Discrimination cluster reported significantly higher depressive symptoms than those in the Low Barrier Socialization-Low Discrimination and High Barrier Socialization-Low Discrimination clusters. However, no differences in adjustment were observed between the Low Barrier Socialization-Low Discrimination and High Barrier Socialization-Low Discrimination clusters. Overall, the findings highlight important individual differences in how young people of color experience their race and how these differences have significant implications on psychological adjustment.

  18. A clustering analysis of eddies' spatial distribution in the South China Sea

    NASA Astrophysics Data System (ADS)

    Yi, J.; Du, Y.; Wang, X.; He, Z.; Zhou, C.

    2013-02-01

    Spatial variation is important for studying the mesoscale eddies in the South China Sea (SCS). To investigate such spatial variations, this study made a clustering analysis on eddies' distribution using the K-means approach. Results showed that clustering tendency of anticyclonic eddies (AEs) and cyclonic eddies (CEs) were weak but not random, and the number of clusters were proved greater than four. Finer clustering results showed 10 regions where AEs densely populated and 6 regions for CEs in the SCS. Previous studies confirmed these partitions and possible generation mechanisms were related. Comparisons between AEs and CEs revealed that patterns of AE are relatively more aggregated than those of CE, and specific distinctions were summarized: (1) to the southwest of Luzon Island, AEs and CEs are generated spatially apart; AEs are likely located north of 14° N and closer to shore, while CEs are to the south and further offshore. (2) The central SCS and Nansha Trough are mostly dominated by AEs. (3) Along 112° E, clusters of AEs and CEs are located sequentially apart, and the pairs off Vietnam represent the dipole structures. (4) To the southwest of the Dongsha Islands, AEs are concentrated to the east of CEs. Overlaps of AEs and CEs in the northeastern and southern SCS were further examined considering seasonal variations. The northeastern overlap represented near-concentric distributions while the southern one was a mixed effect of seasonal variations, complex circulations and topography influences.

  19. Links between patterns of racial socialization and discrimination experiences and psychological adjustment: a cluster analysis.

    PubMed

    Ajayi, Alex A; Syed, Moin

    2014-10-01

    This study used a person-oriented analytic approach to identify meaningful patterns of barriers-focused racial socialization and perceived racial discrimination experiences in a sample of 295 late adolescents. Using cluster analysis, three distinct groups were identified: Low Barrier Socialization-Low Discrimination, High Barrier Socialization-Low Discrimination, and High Barrier Socialization-High Discrimination clusters. These groups were substantively unique in terms of the frequency of racial socialization messages about bias preparation and out-group mistrust its members received and their actual perceived discrimination experiences. Further, individuals in the High Barrier Socialization-High Discrimination cluster reported significantly higher depressive symptoms than those in the Low Barrier Socialization-Low Discrimination and High Barrier Socialization-Low Discrimination clusters. However, no differences in adjustment were observed between the Low Barrier Socialization-Low Discrimination and High Barrier Socialization-Low Discrimination clusters. Overall, the findings highlight important individual differences in how young people of color experience their race and how these differences have significant implications on psychological adjustment. PMID:25124381

  20. Cluster Analysis and Web-Based 3-D Visualization of Large-scale Geophysical Data

    NASA Astrophysics Data System (ADS)

    Kadlec, B. J.; Yuen, D. A.; Bollig, E. F.; Dzwinel, W.; da Silva, C. R.

    2004-05-01

    We present a problem-solving environment WEB-IS (Web-based Data Interrogative System), which we have developed for remote analysis and visualization of geophysical data [Garbow et. al., 2003]. WEB-IS employs agglomerative clustering methods intended for feature extraction and studying the predictions of large magnitude earthquake events. Data-mining is accomplished using a mutual nearest meighbor (MNN) algorithm for extracting event clusters of different density and shapes based on a hierarchical proximity measure. Clustering schemes used in molecular dynamics [Da Silva et. al., 2002] are also considered for increasing computational efficiency using a linked cell algorithm for creating a Verlet neighbor list (VNL) and extracting different cluster structures by applying a canonical backtracking search on the VNL. Space and time correlations between the events are visualized dynamically in 3-D through a filter by showing clusters at different timescales according to defined units of time ranging from days to years. This WEB-IS functionality was tested both on synthetic [Eneva and Ben-Zion, 1997] and actual earthquake catalogs of Japanese earthquakes and can be applied to the soft-computing data mining methods used in hydrology and geoinformatics. Da Silva, C.R.S., Justo, J.F., Fazzio, A., Phys Rev B, vol., 65, 2002. Eneva, M., Ben-Zion, Y.,J. Geophys. Res., 102, 17785-17795, 1997. Garbow, Z.A., Yuen, D.A., Erlebacher, G., Bollig, E.F., Kadlec, B.J., Vis. Geosci., 2003.

  1. A cluster analysis of the neurons of the rat interpeduncular nucleus.

    PubMed Central

    Gioia, M; Vizzotto, L; Bianchi, R

    1994-01-01

    The morphometric characteristics of the neurons of the interpeduncular nucleus (IPN) in the rat were investigated by cluster analysis in order to identify neuronal groups which are morphometrically homogeneous, and to define their position and density in the IPN subnuclei. Two clusters of cells were detected. Cluster 1 neurons had a larger perikaryal size with a mean cross-sectional area of 170 microns2 and a high nuclear/cytoplasmic ratio. They were located mainly in the pars dorsalis (37%) and pars medialis (34%) rather than in the pars lateralis (29%). Cluster 1 neurons were also more frequent at the rostral (31%) and caudal (57%) poles than in the central part of the IPN. Cluster 2 cells showed a smaller mean perikaryal area (110 microns2), a small nucleus and abundant cytoplasm. They were equally distributed throughout the whole IPN. These findings suggest the existence of a magnocellular region at the rostral pole of the IPN which has not been described previously. The presence of IPN regions endowed with specific cytoarchitectural characteristics is discussed with respect to the complex neurochemical organisation of the nucleus. Images Fig. 1 Fig. 2 Fig. 4 PMID:7649781

  2. Descriptive characteristics and cluster analysis of male veteran hazardous drinkers in an alcohol moderation intervention.

    PubMed

    Walker, Robrina; Hunt, Yvonne M; Olivier, Jake; Grothe, Karen B; Dubbert, Patricia M; Burke, Randy S; Cushman, William C

    2012-01-01

    Current efforts underway to develop the fifth edition of the Diagnostic and Statistical Manual (DSM-5) have reignited discussions for classifying the substance use disorders. This study's aim was to contribute to the understanding of abusive alcohol use and its validity as a diagnosis. Cluster analysis was used to identify relatively homogeneous groups of hazardous, nondependent drinkers by using data collected from the Prevention and Treatment of Hypertension Study (PATHS), a multisite trial that examined the ability of a cognitive-behavioral-based alcohol reduction intervention, compared to a control condition, to reduce alcohol use. Participants for this study (N = 511) were male military veterans. Variables theoretically associated with alcohol use (eg, demographic, tobacco use, and mental health) were used to create the clusters and a priori, empirically based external criteria were used to assess discriminant validity. Bivariate correlations among cluster variables were generally consistent with previous findings in the literature. Analyses of internal and discriminant validity of the identified clusters were largely nonsignificant, suggesting meaningful differences between clusters could not be identified. Although the typology literature has contributed supportive validity for the alcohol dependence diagnosis, this study's results do not lend supportive validity for the construct of alcohol abuse. PMID:22691012

  3. Exploring the application of latent class cluster analysis for investigating pedestrian crash injury severities in Switzerland.

    PubMed

    Sasidharan, Lekshmi; Wu, Kun-Feng; Menendez, Monica

    2015-12-01

    One of the major challenges in traffic safety analyses is the heterogeneous nature of safety data, due to the sundry factors involved in it. This heterogeneity often leads to difficulties in interpreting results and conclusions due to unrevealed relationships. Understanding the underlying relationship between injury severities and influential factors is critical for the selection of appropriate safety countermeasures. A method commonly employed to address systematic heterogeneity is to focus on any subgroup of data based on the research purpose. However, this need not ensure homogeneity in the data. In this paper, latent class cluster analysis is applied to identify homogenous subgroups for a specific crash type-pedestrian crashes. The manuscript employs data from police reported pedestrian (2009-2012) crashes in Switzerland. The analyses demonstrate that dividing pedestrian severity data into seven clusters helps in reducing the systematic heterogeneity of the data and to understand the hidden relationships between crash severity levels and socio-demographic, environmental, vehicle, temporal, traffic factors, and main reason for the crash. The pedestrian crash injury severity models were developed for the whole data and individual clusters, and were compared using receiver operating characteristics curve, for which results favored clustering. Overall, the study suggests that latent class clustered regression approach is suitable for reducing heterogeneity and revealing important hidden relationships in traffic safety analyses.

  4. Cluster analysis of the DrugBank chemical space using molecular quantum numbers.

    PubMed

    Awale, Mahendra; Reymond, Jean-Louis

    2012-09-15

    DrugBank (>6000 approved and experimental drugs) was analyzed using molecular quantum numbers (MQNs), which are 42 integer value descriptors of molecular structure counting atoms, bonds, polar groups and topological features. Principal component analysis of MQN-space showed that drugs differ mostly by size (PC1, 67% variance) and structural rigidity and polarity (PC2, 18% variance). Twenty-eight groups of target specific drugs were recovered by proximity sorting in MQN-space as efficiently as by substructure fingerprint (SF) similarity, but in different order allowing for lead-hopping relationships not seen in SF similarity. Clustering by MQN- or SF-similarity produced very different types of clusters. Each of the 28 drug groups spread over different clusters in both MQN- and SF-clustering, and most clusters contained drugs from different target specific groups, showing that structure-based classifications only partially overlap with bioactivity. An MQN-browsable version of DrugBank is available at www.gdb.unibe.ch. PMID:22465859

  5. Cluster-based analysis for personalized stress evaluation using physiological signals.

    PubMed

    Xu, Qianli; Nwe, Tin Lay; Guan, Cuntai

    2015-01-01

    Technology development in wearable sensors and biosignal processing has made it possible to detect human stress from the physiological features. However, the intersubject difference in stress responses presents a major challenge for reliable and accurate stress estimation. This research proposes a novel cluster-based analysis method to measure perceived stress using physiological signals, which accounts for the intersubject differences. The physiological data are collected when human subjects undergo a series of task-rest cycles, incurring varying levels of stress that is indicated by an index of the State Trait Anxiety Inventory. Next, a quantitative measurement of stress is developed by analyzing the physiological features in two steps: 1) a k -means clustering process to divide subjects into different categories (clusters), and 2) cluster-wise stress evaluation using the general regression neural network. Experimental results show a significant improvement in evaluation accuracy as compared to traditional methods without clustering. The proposed method is useful in developing intelligent, personalized products for human stress management. PMID:25561450

  6. Meiofaunal community analysis by high-throughput sequencing: comparison of extraction, quality filtering, and clustering methods.

    PubMed

    Brannock, Pamela M; Halanych, Kenneth M

    2015-10-01

    Using molecular tools to examine community composition of meiofauna, animals 45μm to 1mm in size living between sediment grains in aquatic environments, is relatively new in comparison to bacterial and archaeal microbial studies. Although high-throughput molecular approaches are starting to be applied to these ccommunities, effectiveness of different approaches for nucleic acid extraction from meiofauna is poorly known and bioinformatic pipelines vary between studies. Given this situation, there is a need for protocols to be developed that promote consistency in sample collection and processing, sequence quality filtering, and Operational Taxonomic Unit (OTU) clustering methods. Herein, we assess different approaches used for DNA extraction (DNA extracted directly from sediment versus elutriated material retained on a 45μm sieve) as well as how different quality filtering methods of sequences and OTU clustering algorithms impact genetic assessment of meiofauna community composition. DNA extracted directly from sediment resulted in higher presence of non-metazoan eukaryotic taxa; in contrast, an elutriation (resuspension with decanting) approach increased meiofauna abundance and enriched metazoan OTUs. In regards to bioinformatics analyses, the number of overall OTUs varied by clustering algorithm, primarily due to the applied method of sequence quality filtering. However, alpha and beta diversity analyses showed similar trends regardless of bioinformatics pipeline utilized. Based on our results, we recommend studies of meiofauna communities first elutriate samples prior to DNA extraction and include multiple biological replicates to account for variation in community-level composition. The quality filtering method should be carefully considered as this step accounted for large discrepancy in the number of OTUs inferred.

  7. Spatiotemporal Clustering Analysis and Risk Assessments of Human Cutaneous Anthrax in China, 2005–2012

    PubMed Central

    Qian, Quan; Haque, Ubydul; Soares Magalhaes, Ricardo J.; Li, Shen-Long; Tong, Shi-Lu; Li, Cheng-Yi; Sun, Hai-Long; Sun, Yan-Song

    2015-01-01

    Objective To investigate the epidemic characteristics of human cutaneous anthrax (CA) in China, detect the spatiotemporal clusters at the county level for preemptive public health interventions, and evaluate the differences in the epidemiological characteristics within and outside clusters. Methods CA cases reported during 2005–2012 from the national surveillance system were evaluated at the county level using space-time scan statistic. Comparative analysis of the epidemic characteristics within and outside identified clusters was performed using using the χ2 test or Kruskal-Wallis test. Results The group of 30–39 years had the highest incidence of CA, and the fatality rate increased with age, with persons ≥70 years showing a fatality rate of 4.04%. Seasonality analysis showed that most of CA cases occurred between May/June and September/October of each year. The primary spatiotemporal cluster contained 19 counties from June 2006 to May 2010, and it was mainly located straddling the borders of Sichuan, Gansu, and Qinghai provinces. In these high-risk areas, CA cases were predominantly found among younger, local, males, shepherds, who were living on agriculture and stockbreeding and characterized with high morbidity, low mortality and a shorter period from illness onset to diagnosis. Conclusion CA was geographically and persistently clustered in the Southwestern China during 2005–2012, with notable differences in the epidemic characteristics within and outside spatiotemporal clusters; this demonstrates the necessity for CA interventions such as enhanced surveillance, health education, mandatory and standard decontamination or disinfection procedures to be geographically targeted to the areas identified in this study. PMID:26208355

  8. Phenotype Clustering of Breast Epithelial Cells in Confocal Imagesbased on Nuclear Protein Distribution Analysis

    SciTech Connect

    Long, Fuhui; Peng, Hanchuan; Sudar, Damir; Levievre, Sophie A.; Knowles, David W.

    2006-09-05

    Background: The distribution of the chromatin-associatedproteins plays a key role in directing nuclear function. Previously, wedeveloped an image-based method to quantify the nuclear distributions ofproteins and showed that these distributions depended on the phenotype ofhuman mammary epithelial cells. Here we describe a method that creates ahierarchical tree of the given cell phenotypes and calculates thestatistical significance between them, based on the clustering analysisof nuclear protein distributions. Results: Nuclear distributions ofnuclear mitotic apparatus protein were previously obtained fornon-neoplastic S1 and malignant T4-2 human mammary epithelial cellscultured for up to 12 days. Cell phenotype was defined as S1 or T4-2 andthe number of days in cultured. A probabilistic ensemble approach wasused to define a set of consensus clusters from the results of multipletraditional cluster analysis techniques applied to the nucleardistribution data. Cluster histograms were constructed to show how cellsin any one phenotype were distributed across the consensus clusters.Grouping various phenotypes allowed us to build phenotype trees andcalculate the statistical difference between each group. The resultsshowed that non-neoplastic S1 cells could be distinguished from malignantT4-2 cells with 94.19 percent accuracy; that proliferating S1 cells couldbe distinguished from differentiated S1 cells with 92.86 percentaccuracy; and showed no significant difference between the variousphenotypes of T4-2 cells corresponding to increasing tumor sizes.Conclusion: This work presents a cluster analysis method that canidentify significant cell phenotypes, based on the nuclear distributionof specific proteins, with high accuracy.

  9. Validation of hierarchical cluster analysis for identification of bacterial species using 42 bacterial isolates

    NASA Astrophysics Data System (ADS)

    Ghebremedhin, Meron; Yesupriya, Shubha; Luka, Janos; Crane, Nicole J.

    2015-03-01

    Recent studies have demonstrated the potential advantages of the use of Raman spectroscopy in the biomedical field due to its rapidity and noninvasive nature. In this study, Raman spectroscopy is applied as a method for differentiating between bacteria isolates for Gram status and Genus species. We created models for identifying 28 bacterial isolates using spectra collected with a 785 nm laser excitation Raman spectroscopic system. In order to investigate the groupings of these samples, partial least squares discriminant analysis (PLSDA) and hierarchical cluster analysis (HCA) was implemented. In addition, cluster analyses of the isolates were performed using various data types consisting of, biochemical tests, gene sequence alignment, high resolution melt (HRM) analysis and antimicrobial susceptibility tests of minimum inhibitory concentration (MIC) and degree of antimicrobial resistance (SIR). In order to evaluate the ability of these models to correctly classify bacterial isolates using solely Raman spectroscopic data, a set of 14 validation samples were tested using the PLSDA models and consequently the HCA models. External cluster evaluation criteria of purity and Rand index were calculated at different taxonomic levels to compare the performance of clustering using Raman spectra as well as the other datasets. Results showed that Raman spectra performed comparably, and in some cases better than, the other data types with Rand index and purity values up to 0.933 and 0.947, respectively. This study clearly demonstrates that the discrimination of bacterial species using Raman spectroscopic data and hierarchical cluster analysis is possible and has the potential to be a powerful point-of-care tool in clinical settings.

  10. An assessment of climatological synoptic typing by principal component analysis and kmeans clustering

    NASA Astrophysics Data System (ADS)

    Cuell, Charles; Bonsal, Barrie

    2009-10-01

    A common method of automated synoptic typing for climatological investigations involves data reduction by principal component analysis followed by the application of a clustering method. The number of eigenvectors kept in the principal component analysis is usually determined by a threshold value of relative variance retained, typically 85% to 95%, under the implicit assumption that varying this relative variance will not affect the resultant synoptic catalogue. This assumption is tested using daily 500-mb geopotential heights over northwest Canada during the winter period (December to February) from 1948 to 2006. Results show that the synoptic catalogue and associated surface climatological characteristics undergo changes for values of relative variance retained over 99%, indicating the typical thresholds are too low and calling into question the validity of performing principal component analysis prior to objective clustering.

  11. Clustering Analysis of OFFICER'S Behaviours in London Police Foot Patrol Activities

    NASA Astrophysics Data System (ADS)

    Shen, J.; Cheng, T.

    2015-07-01

    In this small paper we aim at presenting a framework of conceptual representation and clustering analysis of police officers' patrol pattern obtained from mining their raw movement trajectory data. This have been achieved by a model developed to accounts for the spatio-temporal dynamics human movements by incorporating both the behaviour features of the travellers and the semantic meaning of the environment they are moving in. Hence, the similarity metric of traveller behaviours is jointly defined according to the stay time allocation in each Spatio-temporal region of interests (ST-ROI) to support clustering analysis of patrol behaviours. The proposed framework enables the analysis of behaviour and preferences on higher level based on raw moment trajectories. The model is firstly applied to police patrol data provided by the Metropolitan Police and will be tested by other type of dataset afterwards.

  12. Cluster analysis of European surface ozone observations for evaluation of MACC reanalysis data

    NASA Astrophysics Data System (ADS)

    Lyapina, Olga; Schultz, Martin G.; Hense, Andreas

    2016-06-01

    The high density of European surface ozone monitoring sites provides unique opportunities for the investigation of regional ozone representativeness and for the evaluation of chemistry climate models. The regional representativeness of European ozone measurements is examined through a cluster analysis (CA) of 4 years of 3-hourly ozone data from 1492 European surface monitoring stations in the Airbase database; the time resolution corresponds to the output frequency of the model that is compared to the data in this study. K-means clustering is implemented for seasonal-diurnal variations (i) in absolute mixing ratio units and (ii) normalized by the overall mean ozone mixing ratio at each site. Statistical tests suggest that each CA can distinguish between four and five different ozone pollution regimes. The individual clusters reveal differences in seasonal-diurnal cycles, showing typical patterns of the ozone behavior for more polluted stations or more rural background. The robustness of the clustering was tested with a series of k-means runs decreasing randomly the size of the initial data set or lengths of the time series. Except for the Po Valley, the clustering does not provide a regional differentiation, as the member stations within each cluster are generally distributed all over Europe. The typical seasonal, diurnal, and weekly cycles of each cluster are compared to the output of the multi-year global reanalysis produced within the Monitoring of Atmospheric Composition and Climate (MACC) project. While the MACC reanalysis generally captures the shape of the diurnal cycles and the diurnal amplitudes, it is not able to reproduce the seasonal cycles very well and it exhibits a high bias up to 12 nmol mol-1. The bias decreases from more polluted clusters to cleaner ones. Also, the seasonal and weekly cycles and frequency distributions of ozone mixing ratios are better described for clusters with relatively clean signatures. Due to relative sparsity of CO and NOx

  13. Metal Oxide-Based Selective Enrichment Combined with Stable Isotope Labeling-Mass Spectrometry Analysis for Profiling of Ribose Conjugates.

    PubMed

    Chu, Jie-Mei; Qi, Chu-Bo; Huang, Yun-Qing; Jiang, Han-Peng; Hao, Yan-Hong; Yuan, Bi-Feng; Feng, Yu-Qi

    2015-07-21

    Some modified ribonucleosides in biological fluids have been evaluated as cancer-related metabolites. Detection of endogenous modified ribonucleosides in biological fluids may serve as a noninvasive cancers diagnostic method. However, determination of modified ribonucleosides is still challenging because of their low abundance and serious matrix interferences in biological fluids. Here, we developed a novel strategy for comprehensive profiling of ribose conjugates from biological fluids using metal oxide-based dispersive solid-phase extraction (DSPE) followed with in vitro stable isotope labeling and double neutral loss scan-mass spectrometry analysis (DSPE-SIL-LC-DNLS-MS). Cerium dioxide (CeO2) was used to selectively recognize and capture ribose conjugates from complex biological samples under basic environment. The enriched ribose conjugates were subsequently labeled with a pair of isotope labeling reagents (acetone and acetone-d6). The glucosidic bond of acetone labeled ribose conjugates is readily ruptured, and the generated ribose that carries an isotope tag can be lost as a neutral fragment under collision induced dissociation (CID). Since the light (acetone) and heavy (acetone-d6) labeled compounds have the same chemical structures and can generate different neutral loss fragments (NL 172 and 178 Da), it is therefore highly convenient to profile ribose conjugates by double neutral loss scan mode in mass spectrometry analysis. In this respect, the light and heavy labeled compounds were ionized at the same condition but recorded separately on MS spectra, which can significantly improve the detection specificity and facilitate the identification of ribose conjugates. Using the developed DSPE-SIL-LC-DNLS-MS strategy, we profiled the ribose conjugates in human urine, and 49 ribose conjugates were readily identified, among which 7 ribose conjugates exhibited significant contents change between healthy controls and lymphoma patients. The DSPE

  14. Expanded Natural Product Diversity Revealed by Analysis of Lanthipeptide-Like Gene Clusters in Actinobacteria

    PubMed Central

    Zhang, Qi; Doroghazi, James R.; Zhao, Xiling; Walker, Mark C.

    2015-01-01

    Lanthionine-containing peptides (lanthipeptides) are a rapidly growing family of polycyclic peptide natural products belonging to the large class of ribosomally synthesized and posttranslationally modified peptides (RiPPs). Lanthipeptides are widely distributed in taxonomically distant species, and their currently known biosynthetic systems and biological activities are diverse. Building on the recent natural product gene cluster family (GCF) project, we report here large-scale analysis of lanthipeptide-like biosynthetic gene clusters from Actinobacteria. Our analysis suggests that lanthipeptide biosynthetic pathways, and by extrapolation the natural products themselves, are much more diverse than currently appreciated and contain many different posttranslational modifications. Furthermore, lanthionine synthetases are much more diverse in sequence and domain topology than currently characterized systems, and they are used by the biosynthetic machineries for natural products other than lanthipeptides. The gene cluster families described here significantly expand the chemical diversity and biosynthetic repertoire of lanthionine-related natural products. Biosynthesis of these novel natural products likely involves unusual and unprecedented biochemistries, as illustrated by several examples discussed in this study. In addition, class IV lanthipeptide gene clusters are shown not to be silent, setting the stage to investigate their biological activities. PMID:25888176

  15. Joint Analysis of Cluster Observations. II. Chandra/XMM-Newton X-Ray and Weak Lensing Scaling Relations for a Sample of 50 Rich Clusters of Galaxies

    NASA Astrophysics Data System (ADS)

    Mahdavi, Andisheh; Hoekstra, Henk; Babul, Arif; Bildfell, Chris; Jeltema, Tesla; Henry, J. Patrick

    2013-04-01

    We present a study of multiwavelength X-ray and weak lensing scaling relations for a sample of 50 clusters of galaxies. Our analysis combines Chandra and XMM-Newton data using an energy-dependent cross-calibration. After considering a number of scaling relations, we find that gas mass is the most robust estimator of weak lensing mass, yielding 15% ± 6% intrinsic scatter at r500WL (the pseudo-pressure YX yields a consistent scatter of 22% ± 5%). The scatter does not change when measured within a fixed physical radius of 1 Mpc. Clusters with small brightest cluster galaxy (BCG) to X-ray peak offsets constitute a very regular population whose members have the same gas mass fractions and whose even smaller (<10%) deviations from regularity can be ascribed to line of sight geometrical effects alone. Cool-core clusters, while a somewhat different population, also show the same (<10%) scatter in the gas mass-lensing mass relation. There is a good correlation and a hint of bimodality in the plane defined by BCG offset and central entropy (or central cooling time). The pseudo-pressure YX does not discriminate between the more relaxed and less relaxed populations, making it perhaps the more even-handed mass proxy for surveys. Overall, hydrostatic masses underestimate weak lensing masses by 10% on the average at r500WL; but cool-core clusters are consistent with no bias, while non-cool-core clusters have a large and constant 15%-20% bias between r2500WL and r500WL, in agreement with N-body simulations incorporating unthermalized gas. For non-cool-core clusters, the bias correlates well with BCG ellipticity. We also examine centroid shift variance and power ratios to quantify substructure; these quantities do not correlate with residuals in the scaling relations. Individual clusters have for the most part forgotten the source of their departures from self-similarity.

  16. Bayesian Analysis of Two Stellar Populations in Galactic Globular Clusters. II. NGC 5024, NGC 5272, and NGC 6352

    NASA Astrophysics Data System (ADS)

    Wagner-Kaiser, R.; Stenning, D. C.; Robinson, E.; von Hippel, T.; Sarajedini, A.; van Dyk, D. A.; Stein, N.; Jefferys, W. H.

    2016-07-01

    We use Cycle 21 Hubble Space Telescope (HST) observations and HST archival Advanced Camera for Surveys Treasury observations of Galactic Globular Clusters to find and characterize two stellar populations in NGC 5024 (M53), NGC 5272 (M3), and NGC 6352. For these three clusters, both single and double-population analyses are used to determine a best fit isochrone(s). We employ a sophisticated Bayesian analysis technique to simultaneously fit the cluster parameters (age, distance, absorption, and metallicity) that characterize each cluster. For the two-population analysis, unique population level helium values are also fit to each distinct population of the cluster and the relative proportions of the populations are determined. We find differences in helium ranging from ˜0.05 to 0.11 for these three clusters. Model grids with solar α-element abundances ([α/Fe] = 0.0) and enhanced α-elements ([α/Fe] = 0.4) are adopted.

  17. Microarray analysis reveals the actual specificity of enrichment media used for food safety assessment.

    PubMed

    Kostić, Tanja; Stessl, Beatrix; Wagner, Martin; Sessitsch, Angela

    2011-06-01

    Microbial diagnostic microarrays are tools for simultaneous detection and identification of microorganisms in food, clinical, and environmental samples. In comparison to classic methods, microarray-based systems have the potential for high throughput, parallelism, and miniaturization. High specificity and high sensitivity of detection have been demonstrated. A microbial diagnostic microarray for the detection of the most relevant bacterial food- and waterborne pathogens and indicator organisms was developed and thoroughly validated. The microarray platform based on sequence-specific end labeling of oligonucleotides and the phylogenetically robust gyrB marker gene allowed a highly specific (resolution on genus and/or species level) and sensitive (0.1% relative and 10(4) CFU absolute sensitivity) detection of the target pathogens. In initial challenge studies of the applicability of microarray-based food analysis, we obtained results demonstrating the questionable specificity of standardized culture-dependent microbiological detection methods. Taking into consideration the importance of reliable food safety assessment methods, comprehensive performance assessment is essential. Results demonstrate the potential of this new pathogen diagnostic microarray to evaluate culture-based standard methods in microbiological food analysis.

  18. Shotgun proteomic analysis of a chromatophore-enriched preparation from the purple phototrophic bacterium Rhodopseudomonas palustris.

    PubMed

    Fejes, Anthony P; Yi, Eugene C; Goodlett, David R; Beatty, J Thomas

    2003-01-01

    A proteomics approach was evaluated for analysis of photosyntheis-related proteins that are characteristic of chromatophores, particles derived from purple phototrophic bacterial intracytoplasmic membranes. Proteins of purified chromatophores from Rhodopseudomonas palustris were solubilized and digested with trypsin, to create a collection of peptides that were fractionated by liquid chromatography. Peptide sequences were determined and assigned to specific proteins by analysis of tandem mass spectra of peptides, and comparison to a library derived from the recently determined R. palustris genome sequence. A total of 300 proteins were detected with a probability value >/=0.9, and the number of proteins detected increased to 345 when the minimum probability value was reduced to 0.5. Membrane-integral proteins of the reaction center, cytochrome b/c (1), light-harvesting and ATPase complexes were used as controls to assess how well this approach performs with hydrophobic proteins. New genes were identified, and tentatively designated as encoding photosynthesis-related proteins. We conclude that this approach is a powerful method to evaluate the possible existence of new photosynthesis-related proteins (and genes), although alternative methods are needed to evaluate the exact functions of newly discovered genes.

  19. Amine Chemistry Method for Selective Enrichment of N-Linked Glycopeptides for Glycoproteomics Analysis.

    PubMed

    Zhang, Zhang; Sun, Deguang; Cong, Yuting; Mao, Jiawei; Huang, Junfeng; Qin, Hongqiang; Liu, Jing; Huang, Guang; Wang, Liming; Ye, Mingliang; Zou, Hanfa

    2015-09-01

    An amine chemistry method was developed for the extraction of N-glycopeptides using amine-functionalized beads for glycoproteomics analysis. Two reductive amination reactions between primary amine and aldehyde were employed in this approach. The first one was to block the primary amines in the peptides by addition of formaldehyde and sodium cyanoborohydride into the peptide sample, and the second one was to couple the glycopeptides onto solid phase beads by incubating the glycopeptides containing aldehyde groups (oxidized by periodate) with the amine-functionalized beads in the presence of sodium cyanoborohydride. It was demonstrated that the blocking of primary amines in the peptides by the first reductive amination reaction prior to the periodate oxidation made the amine chemistry method very efficient and sensitive. This new method was validated by analysis of glycoprotein standards as well as proteome samples. It was found that this new method led to significant increase in the identification of N-glycosites compared with the conventional hydrazide chemistry method.

  20. Effect of Model Sorptive Phases on Phenanthrene Biodegradation: Molecular Analysis of Enrichments and Isolates Suggests Selection Based on Bioavailability

    PubMed Central

    Friedrich, M.; Grosser, R. J.; Kern, E. A.; Inskeep, W. P.; Ward, D. M.

    2000-01-01

    Reduced bioavailability of nonpolar contaminants due to sorption to natural organic matter is an important factor controlling biodegradation of pollutants in the environment. We established enrichment cultures in which solid organic phases were used to reduce phenanthrene bioavailability to different degrees (R. J. Grosser, M. Friedrich, D. M. Ward, and W. P. Inskeep, Appl. Environ. Microbiol. 66:2695–2702, 2000). Bacteria enriched and isolated from contaminated soils under these conditions were analyzed by denaturing gradient gel electrophoresis (DGGE) and sequencing of PCR-amplified 16S ribosomal DNA segments. Compared to DGGE patterns obtained with enrichment cultures containing sand or no sorptive solid phase, different DGGE patterns were obtained with enrichment cultures containing phenanthrene sorbed to beads of Amberlite IRC-50 (AMB), a weak cation-exchange resin, and especially Biobead SM7 (SM7), a polyacrylic resin that sorbed phenanthrene more strongly. SM7 enrichments selected for mycobacterial phenanthrene mineralizers, whereas AMB enrichments selected for a Burkholderia sp. that degrades phenanthrene. Identical mycobacterial and Burkholderia 16S rRNA sequence segments were found in SM7 and AMB enrichment cultures inoculated with contaminated soil from two geographically distant sites. Other closely related Burkholderia sp. populations, some of which utilized phenanthrene, were detected in sand and control enrichment cultures. Our results are consistent with the hypothesis that different phenanthrene-utilizing bacteria inhabiting the same soils may be adapted to different phenanthrene bioavailabilities. PMID:10877758

  1. Spatial cluster analysis of nanoscopically mapped serotonin receptors for classification of fixed brain tissue

    NASA Astrophysics Data System (ADS)

    Sams, Michael; Silye, Rene; Göhring, Janett; Muresan, Leila; Schilcher, Kurt; Jacak, Jaroslaw

    2014-01-01

    We present a cluster spatial analysis method using nanoscopic dSTORM images to determine changes in protein cluster distributions within brain tissue. Such methods are suitable to investigate human brain tissue and will help to achieve a deeper understanding of brain disease along with aiding drug development. Human brain tissue samples are usually treated postmortem via standard fixation protocols, which are established in clinical laboratories. Therefore, our localization microscopy-based method was adapted to characterize protein density and protein cluster localization in samples fixed using different protocols followed by common fluorescent immunohistochemistry techniques. The localization microscopy allows nanoscopic mapping of serotonin 5-HT1A receptor groups within a two-dimensional image of a brain tissue slice. These nanoscopically mapped proteins can be confined to clusters by applying the proposed statistical spatial analysis. Selected features of such clusters were subsequently used to characterize and classify the tissue. Samples were obtained from different types of patients, fixed with different preparation methods, and finally stored in a human tissue bank. To verify the proposed method, samples of a cryopreserved healthy brain have been compared with epitope-retrieved and paraffin-fixed tissues. Furthermore, samples of healthy brain tissues were compared with data obtained from patients suffering from mental illnesses (e.g., major depressive disorder). Our work demonstrates the applicability of localization microscopy and image analysis methods for comparison and classification of human brain tissues at a nanoscopic level. Furthermore, the presented workflow marks a unique technological advance in the characterization of protein distributions in brain tissue sections.

  2. Stable-isotope analysis of a deep-sea benthic-fish assemblage: evidence of an enriched benthic food web.

    PubMed

    Boyle, M D; Ebert, D A; Cailliet, G M

    2012-04-01

    In this study, fishes and invertebrates collected from the continental slope (1000 m) of the eastern North Pacific Ocean were analysed using stable-isotope analysis (SIA). Resulting trophic positions (T(P) ) were compared to known diets and habitats from the literature. Dual isotope plots indicated that most species groups (invertebrates and fishes) sorted as expected along the carbon and nitrogen axes, with less intraspecific variability than interspecific variability. Results also indicated an isotopically distinct benthic and pelagic food web, as the benthic food web was more enriched in both nitrogen and carbon isotopes. Trophic positions from SIA supported this finding, resulting in the assignment of fishes to different trophic positions from those expected based on published dietary information. These differences can be explained largely by the habitat of the prey and the percentage of the diet that was scavenged. A mixing model estimated dietary contributions of prey similar to those of the known diet of Bathyraja trachura from stomach-content analysis (SCA). Linear regressions indicated that trophic positions calculated from SIA and SCA, when plotted against B. trachura total length for 32 individuals, exhibited similar variation and patterns. Only the T(P) from SCA yielded significant results (stomach content: P < 0·05, stable isotope: P > 0·05). PMID:22497394

  3. Stable-isotope analysis of a deep-sea benthic-fish assemblage: evidence of an enriched benthic food web.

    PubMed

    Boyle, M D; Ebert, D A; Cailliet, G M

    2012-04-01

    In this study, fishes and invertebrates collected from the continental slope (1000 m) of the eastern North Pacific Ocean were analysed using stable-isotope analysis (SIA). Resulting trophic positions (T(P) ) were compared to known diets and habitats from the literature. Dual isotope plots indicated that most species groups (invertebrates and fishes) sorted as expected along the carbon and nitrogen axes, with less intraspecific variability than interspecific variability. Results also indicated an isotopically distinct benthic and pelagic food web, as the benthic food web was more enriched in both nitrogen and carbon isotopes. Trophic positions from SIA supported this finding, resulting in the assignment of fishes to different trophic positions from those expected based on published dietary information. These differences can be explained largely by the habitat of the prey and the percentage of the diet that was scavenged. A mixing model estimated dietary contributions of prey similar to those of the known diet of Bathyraja trachura from stomach-content analysis (SCA). Linear regressions indicated that trophic positions calculated from SIA and SCA, when plotted against B. trachura total length for 32 individuals, exhibited similar variation and patterns. Only the T(P) from SCA yielded significant results (stomach content: P < 0·05, stable isotope: P > 0·05).

  4. Selenium-Enriched Foods Are More Effective at Increasing Glutathione Peroxidase (GPx) Activity Compared with Selenomethionine: A Meta-Analysis

    PubMed Central

    Bermingham, Emma N.; Hesketh, John E.; Sinclair, Bruce R.; Koolaard, John P.; Roy, Nicole C.

    2014-01-01

    Selenium may play a beneficial role in multi-factorial illnesses with genetic and environmental linkages via epigenetic regulation in part via glutathione peroxidase (GPx) activity. A meta-analysis was undertaken to quantify the effects of dietary selenium supplementation on the activity of overall GPx activity in different tissues and animal species and to compare the effectiveness of different forms of dietary selenium. GPx activity response was affected by both the dose and form of selenium (p < 0.001). There were differences between tissues on the effects of selenium supplementation on GPx activity (p < 0.001); however, there was no evidence in the data of differences between animal species (p = 0.95). The interactions between dose and tissue, animal species and form were significant (p < 0.001). Tissues particularly sensitive to changes in selenium supply include red blood cells, kidney and muscle. The meta-analysis identified that for animal species selenium-enriched foods were more effective than selenomethionine at increasing GPx activity. PMID:25268836

  5. Analysis of local bond-orientational order for liquid gallium at ambient pressure: Two types of cluster structures.

    PubMed

    Chen, Lin-Yuan; Tang, Ping-Han; Wu, Ten-Ming

    2016-07-14

    In terms of the local bond-orientational order (LBOO) parameters, a cluster approach to analyze local structures of simple liquids was developed. In this approach, a cluster is defined as a combination of neighboring seeds having at least nb local-orientational bonds and their nearest neighbors, and a cluster ensemble is a collection of clusters with a specified nb and number of seeds ns. This cluster analysis was applied to investigate the microscopic structures of liquid Ga at ambient pressure (AP). The liquid structures studied were generated through ab initio molecular dynamics simulations. By scrutinizing the static structure factors (SSFs) of cluster ensembles with different combinations of nb and ns, we found that liquid Ga at AP contained two types of cluster structures, one characterized by sixfold orientational symmetry and the other showing fourfold orientational symmetry. The SSFs of cluster structures with sixfold orientational symmetry were akin to the SSF of a hard-sphere fluid. On the contrary, the SSFs of cluster structures showing fourfold orientational symmetry behaved similarly as the anomalous SSF of liquid Ga at AP, which is well known for exhibiting a high-q shoulder. The local structures of a highly LBOO cluster whose SSF displayed a high-q shoulder were found to be more similar to the structure of β-Ga than those of other solid phases of Ga. More generally, the cluster structures showing fourfold orientational symmetry have an inclination to resemble more to β-Ga.

  6. Analysis of local bond-orientational order for liquid gallium at ambient pressure: Two types of cluster structures.

    PubMed

    Chen, Lin-Yuan; Tang, Ping-Han; Wu, Ten-Ming

    2016-07-14

    In terms of the local bond-orientational order (LBOO) parameters, a cluster approach to analyze local structures of simple liquids was developed. In this approach, a cluster is defined as a combination of neighboring seeds having at least nb local-orientational bonds and their nearest neighbors, and a cluster ensemble is a collection of clusters with a specified nb and number of seeds ns. This cluster analysis was applied to investigate the microscopic structures of liquid Ga at ambient pressure (AP). The liquid structures studied were generated through ab initio molecular dynamics simulations. By scrutinizing the static structure factors (SSFs) of cluster ensembles with different combinations of nb and ns, we found that liquid Ga at AP contained two types of cluster structures, one characterized by sixfold orientational symmetry and the other showing fourfold orientational symmetry. The SSFs of cluster structures with sixfold orientational symmetry were akin to the SSF of a hard-sphere fluid. On the contrary, the SSFs of cluster structures showing fourfold orientational symmetry behaved similarly as the anomalous SSF of liquid Ga at AP, which is well known for exhibiting a high-q shoulder. The local structures of a highly LBOO cluster whose SSF displayed a high-q shoulder were found to be more similar to the structure of β-Ga than those of other solid phases of Ga. More generally, the cluster structures showing fourfold orientational symmetry have an inclination to resemble more to β-Ga. PMID:27421419

  7. Analysis of local bond-orientational order for liquid gallium at ambient pressure: Two types of cluster structures

    NASA Astrophysics Data System (ADS)

    Chen, Lin-Yuan; Tang, Ping-Han; Wu, Ten-Ming

    2016-07-01

    In terms of the local bond-orientational order (LBOO) parameters, a cluster approach to analyze local structures of simple liquids was developed. In this approach, a cluster is defined as a combination of neighboring seeds having at least nb local-orientational bonds and their nearest neighbors, and a cluster ensemble is a collection of clusters with a specified nb and number of seeds ns. This cluster analysis was applied to investigate the microscopic structures of liquid Ga at ambient pressure (AP). The liquid structures studied were generated through ab initio molecular dynamics simulations. By scrutinizing the static structure factors (SSFs) of cluster ensembles with different combinations of nb and ns, we found that liquid Ga at AP contained two types of cluster structures, one characterized by sixfold orientational symmetry and the other showing fourfold orientational symmetry. The SSFs of cluster structures with sixfold orientational symmetry were akin to the SSF of a hard-sphere fluid. On the contrary, the SSFs of cluster structures showing fourfold orientational symmetry behaved similarly as the anomalous SSF of liquid Ga at AP, which is well known for exhibiting a high-q shoulder. The local structures of a highly LBOO cluster whose SSF displayed a high-q shoulder were found to be more similar to the structure of β-Ga than those of other solid phases of Ga. More generally, the cluster structures showing fourfold orientational symmetry have an inclination to resemble more to β-Ga.

  8. Ultrasonic enrichment of microspheres for ultrasensitive biomedical analysis in confocal laser-scanning fluorescence detection

    NASA Astrophysics Data System (ADS)

    Wiklund, M.; Toivonen, J.; Tirri, M.; Hänninen, P.; Hertz, H. M.

    2004-07-01

    An ultrasonic particle concentrator based on a standing-wave hemispherical resonator is combined with confocal laser-scanning fluorescence detection. The goal is to perform ultrasensitive biomedical analysis by concentration of biologically active microspheres. The standing-wave resonator consists of a 4 MHz focusing ultrasonic transducer combined with the optically transparent plastic bottom of a disposable 96-well microplate platform. The ultrasonic particle concentrator collects suspended microspheres into dense, single-layer aggregates at well-defined positions in the sample vessel of the microplate, and the fluorescence from the aggregates is detected by the confocal laser-scanning system. The biochemical properties of the system are investigated using a microsphere-based human thyroid stimulating hormone assay.

  9. Constrained Ordination Analysis with Enrichment of Bell-Shaped Response Functions

    PubMed Central

    Zhang, Yingjie; Thas, Olivier

    2016-01-01

    Constrained ordination methods aims at finding an environmental gradient along which the species abundances are maximally separated. The species response functions, which describe the expected abundance as a function of the environmental score, are according to the ecological fundamental niche theory only meaningful if they are bell-shaped. Many classical model-based ordination methods, however, use quadratic regression models without imposing the bell-shape and thus allowing for meaningless U-shaped response functions. The analysis output (e.g. a biplot) may therefore be potentially misleading and the conclusions are prone to errors. In this paper we present a log-likelihood ratio criterion with a penalisation term to enforce more bell-shaped response shapes. We report the results of a simulation study and apply our method to metagenomics data from microbial ecology. PMID:27100464