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

    PubMed

    Wu, Lingxiang; Chen, Xiujie; Zhang, Denan; Zhang, Wubing; 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.

  3. The self-enrichment of globular clusters

    NASA Astrophysics Data System (ADS)

    Morgan, Siobahn; Lake, George

    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 suprernova detonation. If this is the case, the minimum mass of a globular cluster is about 10 to the 4.6th solar mass.

  4. 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

  5. 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…

  6. 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.

  7. 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.…

  8. 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.

  9. A Detailed Study of Chemical Enrichment History of Galaxy Clusters out to Virial Radius

    NASA Astrophysics Data System (ADS)

    Loewenstein, Michael

    The origin of the metal enrichment of the intracluster medium (ICM) represents a fundamental problem in extragalactic astrophysics, with implications for our understanding of how stars and galaxies form, the nature of Type Ia supernova (SNIa) progenitors, and the thermal history of the ICM. These heavy elements are ultimately synthesized by supernova (SN) explosions; however, the details of the sites of metal production and mechanisms that transport metals to the ICM remain unclear. To make progress, accurate abundance profiles for multiple elements extending from the cluster core out to the virial radius (r180) are required for a significant cluster sample. We propose an X-ray spectroscopic study of a carefully-chosen sample of archival Suzaku and XMM-Newton observations of 23 clusters: XMM-Newton data probe the cluster temperature and abundances out to (0.5-1)r500, while Suzaku data probe the cluster outskirts. A method devised by our team to utilize all elements with emission lines in the X-ray bandpass to measure the relative contributions of supernova explosions by direct modeling of their X-ray spectra will be applied in order to constrain the demographics of the enriching supernova population. In addition we will conduct a stacking analysis of our already existing Suzaku and XMM-Newton cluster spectra to search for weak emssion lines that are important SN diagnostics, and to look for trends with cluster mass and redshift. The funding we propose here will also support the data analysis of our recent Suzaku observations of the archetypal cluster A3112 (200 ks each on the core and outskirts). Our data analysis, intepreted using theoretical models we have developed, will enable us to constrain the star formation history, SN demographics, and nature of SNIa progenitors associated with galaxy cluster stellar populations - and, hence, directly addresess NASA s Strategic Objective 2.4.2 in Astrophysics that aims to improve the understanding of how the Universe works

  10. 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}.

  11. 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…

  12. Uranium enrichment management review: summary of analysis

    SciTech Connect

    Not Available

    1981-01-01

    In May 1980, the Assistant Secretary for Resource Applications within the Department of Energy requested that a group of experienced business executives be assembled to review the operation, financing, and management of the uranium enrichment enterprise as a basis for advising the Secretary of Energy. After extensive investigation, analysis, and discussion, the review group presented its findings and recommendations in a report on December 2, 1980. The following pages contain background material on which that final report was based. This report is arranged in chapters that parallel those of the uranium enrichment management review final report - chapters that contain summaries of the review group's discussion and analyses in six areas: management of operations and construction; long-range planning; marketing of enrichment services; financial management; research and development; and general management. Further information, in-depth analysis, and discussion of suggested alternative management practices are provided in five appendices.

  13. Supernova enrichment of planetary systems in low-mass star clusters

    NASA Astrophysics Data System (ADS)

    Nicholson, Rhana B.; Parker, Richard J.

    2017-02-01

    The presence and abundance of short-lived radioisotopes 26Al and 60Fe in chondritic meteorites implies that the Sun formed in the vicinity of one or more massive stars that exploded as supernovae (SNe). Massive stars are more likely to form in massive star clusters (>1000 M⊙) than lower mass clusters. However, photoevaporation of protoplanetary discs from massive stars and dynamical interactions with passing stars can inhibit planet formation in clusters with radii of ˜1 pc. We investigate whether low-mass (50-200 M⊙) star clusters containing one or two massive stars are a more likely avenue for early Solar system enrichment as they are more dynamically quiescent. We analyse N-body simulations of the evolution of these low-mass clusters and find that a similar fraction of stars experience SN enrichment than in high-mass clusters, despite their lower densities. This is due to two-body relaxation, which causes a significant expansion before the first SN even in clusters with relatively low (100 stars pc-3) initial densities. However, because of the high number of low-mass clusters containing one or two massive stars, the absolute number of enriched stars is the same, if not higher than for more populous clusters. Our results show that direct enrichment of protoplanetary discs from SNe occurs as frequently in low-mass clusters containing one or two massive stars (>20 M⊙) as in more populous star clusters (1000 M⊙). This relaxes the constraints on the direct enrichment scenario and therefore the birth environment of the Solar system.

  14. Preparation of magnetic hydroxyapatite clusters and their application in the enrichment of phosphopeptides.

    PubMed

    Yu, Qiao; Li, Xiao-Shui; Yuan, Bi-Feng; Feng, Yu-Qi

    2014-03-01

    A novel strategy for the effective enrichment of phosphopeptides based on magnetic hydro-xyapatite (HAp) clusters was developed in the current study. The structure of HAp ensures its probable separation capability, including cation exchange with P-sites (negatively charged pairs of crystal phosphates), calcium coordination, anion exchange with C-sites (positively charged pairs of crystal calcium ions). The prepared magnetic HAp clusters showed good performance on the efficient enrichment of phosphopeptides from the digestion mixture of β-casein and BSA. Compared to commercial HAp particles, the magnetic HAp clusters exhibited better selectivity toward phosphopeptides. In addition, the use of magnetic material greatly simplified the enrichment procedure, which avoided the tedious centrifugation steps in a typical phosphopeptides enrichment protocol. Finally, the material was successfully applied in the enrichment of phosphopeptides from human serum. Taken together, the efficient enrichment of the phosphopeptides by the easily prepared magnetic HAp clusters demonstrated a rapid and convenient strategy for the purification of phosphopeptides from complex samples, which may facilitate protein phosphorylation studies.

  15. 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.

  16. 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

  17. Globular clusters in the far-ultraviolet: evidence for He-enriched second populations in extragalactic globular clusters?

    NASA Astrophysics Data System (ADS)

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

    2017-01-01

    We investigate the integrated far-ultraviolet (FUV) emission from globular clusters. We present new FUV photometry of M87's clusters based on archival Hubble Space Telescope (HST) Wide Field Planetary Camera 2 F170W observations. We use these data to test the reliability of published photometry based on HST space telescope imaging spectrograph 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, M31, M81 and M87 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 M31, M81 and M87 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 M31, M81 and M87 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 extragalactic globular clusters.

  18. 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

  19. 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

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

    DOE PAGES

    Johnson, Timothy A.; Stedtfeld, Robert D.; Wang, Qiong; ...

    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

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

    SciTech Connect

    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 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.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

  2. Principal Angle Enrichment Analysis (PAEA): Dimensionally Reduced Multivariate Gene Set Enrichment Analysis Tool.

    PubMed

    Clark, Neil R; Szymkiewicz, Maciej; Wang, Zichen; Monteiro, Caroline D; Jones, Matthew R; Ma'ayan, Avi

    2015-11-01

    Gene set analysis of differential expression, which identifies collectively differentially expressed gene sets, has become an important tool for biology. The power of this approach lies in its reduction of the dimensionality of the statistical problem and its incorporation of biological interpretation by construction. Many approaches to gene set analysis have been proposed, but benchmarking their performance in the setting of real biological data is difficult due to the lack of a gold standard. In a previously published work we proposed a geometrical approach to differential expression which performed highly in benchmarking tests and compared well to the most popular methods of differential gene expression. As reported, this approach has a natural extension to gene set analysis which we call Principal Angle Enrichment Analysis (PAEA). PAEA employs dimensionality reduction and a multivariate approach for gene set enrichment analysis. However, the performance of this method has not been assessed nor its implementation as a web-based tool. Here we describe new benchmarking protocols for gene set analysis methods and find that PAEA performs highly. The PAEA method is implemented as a user-friendly web-based tool, which contains 70 gene set libraries and is freely available to the community.

  3. 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.

  4. FLUORINE VARIATIONS IN THE GLOBULAR CLUSTER NGC 6656 (M22): IMPLICATIONS FOR INTERNAL ENRICHMENT TIMESCALES

    SciTech Connect

    D'Orazi, Valentina; Lucatello, Sara; Gratton, Raffaele G.; Lugaro, Maria; Angelou, George; Bragaglia, Angela; Carretta, Eugenio; Alves-Brito, Alan; Ivans, Inese I.; Masseron, Thomas; Mucciarelli, Alessio

    2013-01-20

    Observed chemical (anti)correlations in proton-capture elements among globular cluster stars are presently recognized as the signature of self-enrichment from now extinct, previous generations of stars. This defines the multiple population scenario. Since fluorine is also affected by proton captures, determining its abundance in globular clusters provides new and complementary clues regarding the nature of these previous generations and supplies strong observational constraints to the chemical enrichment timescales. In this paper, we present our results on near-infrared CRIRES spectroscopic observations of six cool giant stars in NGC 6656 (M22): the main objective is to derive the F content and its internal variation in this peculiar cluster, which exhibits significant changes in both light- and heavy-element abundances. Across our sample, we detected F variations beyond the measurement uncertainties and found that the F abundances are positively correlated with O and anticorrelated with Na, as expected according to the multiple population framework. Furthermore, our observations reveal an increase in the F content between the two different sub-groups, s-process rich and s-process poor, hosted within M22. The comparison with theoretical models suggests that asymptotic giant stars with masses between 4 and 5 M {sub Sun} are responsible for the observed chemical pattern, confirming evidence from previous works: the difference in age between the two sub-components in M22 must be not larger than a few hundred Myr.

  5. Fluorine Variations in the Globular Cluster NGC 6656 (M22): Implications for Internal Enrichment Timescales

    NASA Astrophysics Data System (ADS)

    D'Orazi, Valentina; Lucatello, Sara; Lugaro, Maria; Gratton, Raffaele G.; Angelou, George; Bragaglia, Angela; Carretta, Eugenio; Alves-Brito, Alan; Ivans, Inese I.; Masseron, Thomas; Mucciarelli, Alessio

    2013-01-01

    Observed chemical (anti)correlations in proton-capture elements among globular cluster stars are presently recognized as the signature of self-enrichment from now extinct, previous generations of stars. This defines the multiple population scenario. Since fluorine is also affected by proton captures, determining its abundance in globular clusters provides new and complementary clues regarding the nature of these previous generations and supplies strong observational constraints to the chemical enrichment timescales. In this paper, we present our results on near-infrared CRIRES spectroscopic observations of six cool giant stars in NGC 6656 (M22): the main objective is to derive the F content and its internal variation in this peculiar cluster, which exhibits significant changes in both light- and heavy-element abundances. Across our sample, we detected F variations beyond the measurement uncertainties and found that the F abundances are positively correlated with O and anticorrelated with Na, as expected according to the multiple population framework. Furthermore, our observations reveal an increase in the F content between the two different sub-groups, s-process rich and s-process poor, hosted within M22. The comparison with theoretical models suggests that asymptotic giant stars with masses between 4 and 5 M ⊙ are responsible for the observed chemical pattern, confirming evidence from previous works: the difference in age between the two sub-components in M22 must be not larger than a few hundred Myr. Based on observations taken with ESO telescopes under program 087.0319(A).

  6. 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.

  7. ALMA Reveals Potential Localized Dust Enrichment from Massive Star Clusters in II Zw 40

    NASA Astrophysics Data System (ADS)

    Consiglio, S. Michelle; Turner, Jean L.; Beck, Sara; Meier, David S.

    2016-12-01

    We present subarcsecond images of submillimeter CO and continuum emission from a local galaxy forming massive star clusters: the blue compact dwarf galaxy II Zw 40. At ˜0.″4 resolution (20 pc), the CO(3-2), CO(1-0), 3 mm, and 870 μm continuum maps illustrate star formation on the scales of individual molecular clouds. Dust contributes about one-third of the 870 μm continuum emission, with free-free accounting for the rest. On these scales, there is not a good correspondence between gas, dust, and free-free emission. Dust continuum is enhanced toward the star-forming region as compared to the CO emission. We suggest that an unexpectedly low and spatially variable gas-to-dust ratio is the result of rapid and localized dust enrichment of clouds by the massive clusters of the starburst.

  8. 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.

  9. 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.

  10. 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

  11. Overview on techniques in cluster analysis.

    PubMed

    Frades, Itziar; Matthiesen, Rune

    2010-01-01

    Clustering is the unsupervised, semisupervised, and supervised classification of patterns into groups. The clustering problem has been addressed in many contexts and disciplines. Cluster analysis encompasses different methods and algorithms for grouping objects of similar kinds into respective categories. In this chapter, we describe a number of methods and algorithms for cluster analysis in a stepwise framework. The steps of a typical clustering analysis process include sequentially pattern representation, the choice of the similarity measure, the choice of the clustering algorithm, the assessment of the output, and the representation of the clusters.

  12. 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.

  13. 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

  14. 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

  15. 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.

  16. DICON: interactive visual analysis of multidimensional clusters.

    PubMed

    Cao, Nan; Gotz, David; Sun, Jimeng; Qu, Huamin

    2011-12-01

    Clustering as a fundamental data analysis technique has been widely used in many analytic applications. However, it is often difficult for users to understand and evaluate multidimensional clustering results, especially the quality of clusters and their semantics. For large and complex data, high-level statistical information about the clusters is often needed for users to evaluate cluster quality while a detailed display of multidimensional attributes of the data is necessary to understand the meaning of clusters. In this paper, we introduce DICON, an icon-based cluster visualization that embeds statistical information into a multi-attribute display to facilitate cluster interpretation, evaluation, and comparison. We design a treemap-like icon to represent a multidimensional cluster, and the quality of the cluster can be conveniently evaluated with the embedded statistical information. We further develop a novel layout algorithm which can generate similar icons for similar clusters, making comparisons of clusters easier. User interaction and clutter reduction are integrated into the system to help users more effectively analyze and refine clustering results for large datasets. We demonstrate the power of DICON through a user study and a case study in the healthcare domain. Our evaluation shows the benefits of the technique, especially in support of complex multidimensional cluster analysis.

  17. Enabling Enrichment Analysis with the Human Disease Ontology

    PubMed Central

    LePendu, Paea; Musen, Mark A.; Shah, Nigam H.

    2012-01-01

    Advanced statistical methods used to analyze high-throughput data such as gene-expression assays result in long lists of “significant genes.” One way to gain insight into the significance of altered expression levels is to determine whether Gene Ontology (GO) terms associated with a particular biological process, molecular function, or cellular component are over- or under-represented in the set of genes deemed significant. This process, referred to as enrichment analysis, profiles a gene-set, and is widely used to make sense of the results of high-throughput experiments. Our goal is to develop and apply general enrichment analysis methods to profile other sets of interest, such as patient cohorts from the electronic medical record, using a variety of ontologies including SNOMED CT, MedDRA, RxNorm, and others. Although it is possible to perform enrichment analysis using ontologies other than the GO, a key pre-requisite is the availability of a background set of annotations to enable the enrichment calculation. In the case of the GO, this background set is provided by the Gene Ontology Annotations. In the current work, we describe: (i) a general method that uses hand-curated GO annotations as a starting point for creating background datasets for enrichment analysis using other ontologies; and (ii) a gene–disease background annotation set—that enables disease-based enrichment—to demonstrate feasibility of our method. PMID:21550421

  18. 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.

  19. ProbCD: enrichment analysis accounting for categorization uncertainty

    PubMed Central

    Vêncio, Ricardo ZN; Shmulevich, Ilya

    2007-01-01

    Background As in many other areas of science, systems biology makes extensive use of statistical association and significance estimates in contingency tables, a type of categorical data analysis known in this field as enrichment (also over-representation or enhancement) analysis. In spite of efforts to create probabilistic annotations, especially in the Gene Ontology context, or to deal with uncertainty in high throughput-based datasets, current enrichment methods largely ignore this probabilistic information since they are mainly based on variants of the Fisher Exact Test. Results We developed an open-source R-based software to deal with probabilistic categorical data analysis, ProbCD, that does not require a static contingency table. The contingency table for the enrichment problem is built using the expectation of a Bernoulli Scheme stochastic process given the categorization probabilities. An on-line interface was created to allow usage by non-programmers and is available at: . Conclusion We present an analysis framework and software tools to address the issue of uncertainty in categorical data analysis. In particular, concerning the enrichment analysis, ProbCD can accommodate: (i) the stochastic nature of the high-throughput experimental techniques and (ii) probabilistic gene annotation. PMID:17935624

  20. 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.

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

    PubMed

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

    2014-03-06

    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.

  2. 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.

  3. 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.

  4. Anaerobic central metabolic pathways active during polyhydroxyalkanoate production in uncultured cluster 1 Defluviicoccus enriched in activated sludge communities.

    PubMed

    Burow, Luke C; Mabbett, Amanda N; Borrás, Luis; Blackall, Linda L

    2009-09-01

    A glycogen nonpolyphosphate-accumulating organism (GAO) enrichment culture dominated by the Alphaproteobacteria cluster 1 Defluviicoccus was investigated to determine the metabolic pathways involved in the anaerobic formation of polyhydroxyalkanoates, carbon storage polymers important for the proliferation of microorganisms in enhanced biological phosphorus removal processes. FISH-microautoradiography and post-FISH fluorescent chemical staining confirmed acetate assimilation as polyhydroxyalkanoates in cluster 1 Defluviicoccus under anaerobic conditions. Chemical inhibition of glycolysis using iodoacetate, and of isocitrate lyase by 3-nitropropionate and itaconate, indicated that carbon is likely to be channelled through both glycolysis and the glyoxylate cycle in cluster 1 Defluviicoccus. The effect of metabolic inhibitors of aconitase (monofluoroacetate) and succinate dehydrogenase (malonate) suggested that aconitase, but not succinate dehydrogenase, was active, providing further support for the role of the glyoxylate cycle in these GAOs. Metabolic inhibition of fumarate reductase using oxantel decreased polyhydroxyalkanoate production. This indicated reduction of fumarate to succinate and the operation of the reductive branch of the tricarboxylic acid cycle, which is possibly important in the production of the polyhydroxyvalerate component of polyhydroxyalkanoates observed in cluster 1 Defluviicoccus enrichment cultures. These findings were integrated with previous metabolic models for GAOs and enabled an anaerobic central metabolic pathway model for polyhydroxyalkanoate formation in cluster 1 Defluviicoccus to be proposed.

  5. 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.

  6. FDR-FET: an optimizing gene set enrichment analysis method

    PubMed Central

    Ji, Rui-Ru; Ott, Karl-Heinz; Yordanova, Roumyana; Bruccoleri, Robert E

    2011-01-01

    Gene set enrichment analysis for analyzing large profiling and screening experiments can reveal unifying biological schemes based on previously accumulated knowledge represented as “gene sets”. Most of the existing implementations use a fixed fold-change or P value cutoff to generate regulated gene lists. However, the threshold selection in most cases is arbitrary, and has a significant effect on the test outcome and interpretation of the experiment. We developed a new gene set enrichment analysis method, ie, FDR-FET, which dynamically optimizes the threshold choice and improves the sensitivity and selectivity of gene set enrichment analysis. The procedure translates experimental results into a series of regulated gene lists at multiple false discovery rate (FDR) cutoffs, and computes the P value of the overrepresentation of a gene set using a Fisher’s exact test (FET) in each of these gene lists. The lowest P value is retained to represent the significance of the gene set. We also implemented improved methods to define a more relevant global reference set for the FET. We demonstrate the validity of the method using a published microarray study of three protease inhibitors of the human immunodeficiency virus and compare the results with those from other popular gene set enrichment analysis algorithms. Our results show that combining FDR with multiple cutoffs allows us to control the error while retaining genes that increase information content. We conclude that FDR-FET can selectively identify significant affected biological processes. Our method can be used for any user-generated gene list in the area of transcriptome, proteome, and other biological and scientific applications. PMID:21918636

  7. FDR-FET: an optimizing gene set enrichment analysis method.

    PubMed

    Ji, Rui-Ru; Ott, Karl-Heinz; Yordanova, Roumyana; Bruccoleri, Robert E

    2011-01-01

    Gene set enrichment analysis for analyzing large profiling and screening experiments can reveal unifying biological schemes based on previously accumulated knowledge represented as "gene sets". Most of the existing implementations use a fixed fold-change or P value cutoff to generate regulated gene lists. However, the threshold selection in most cases is arbitrary, and has a significant effect on the test outcome and interpretation of the experiment. We developed a new gene set enrichment analysis method, ie, FDR-FET, which dynamically optimizes the threshold choice and improves the sensitivity and selectivity of gene set enrichment analysis. The procedure translates experimental results into a series of regulated gene lists at multiple false discovery rate (FDR) cutoffs, and computes the P value of the overrepresentation of a gene set using a Fisher's exact test (FET) in each of these gene lists. The lowest P value is retained to represent the significance of the gene set. We also implemented improved methods to define a more relevant global reference set for the FET. We demonstrate the validity of the method using a published microarray study of three protease inhibitors of the human immunodeficiency virus and compare the results with those from other popular gene set enrichment analysis algorithms. Our results show that combining FDR with multiple cutoffs allows us to control the error while retaining genes that increase information content. We conclude that FDR-FET can selectively identify significant affected biological processes. Our method can be used for any user-generated gene list in the area of transcriptome, proteome, and other biological and scientific applications.

  8. Nursing home care quality: a cluster analysis.

    PubMed

    Grøndahl, Vigdis Abrahamsen; Fagerli, Liv Berit

    2017-02-13

    Purpose The purpose of this paper is to explore potential differences in how nursing home residents rate care quality and to explore cluster characteristics. Design/methodology/approach A cross-sectional design was used, with one questionnaire including questions from quality from patients' perspective and Big Five personality traits, together with questions related to socio-demographic aspects and health condition. Residents ( n=103) from four Norwegian nursing homes participated (74.1 per cent response rate). Hierarchical cluster analysis identified clusters with respect to care quality perceptions. χ(2) tests and one-way between-groups ANOVA were performed to characterise the clusters ( p<0.05). Findings Two clusters were identified; Cluster 1 residents (28.2 per cent) had the best care quality perceptions and Cluster 2 (67.0 per cent) had the worst perceptions. The clusters were statistically significant and characterised by personal-related conditions: gender, psychological well-being, preferences, admission, satisfaction with staying in the nursing home, emotional stability and agreeableness, and by external objective care conditions: healthcare personnel and registered nurses. Research limitations/implications Residents assessed as having no cognitive impairments were included, thus excluding the largest group. By choosing questionnaire design and structured interviews, the number able to participate may increase. Practical implications Findings may provide healthcare personnel and managers with increased knowledge on which to develop strategies to improve specific care quality perceptions. Originality/value Cluster analysis can be an effective tool for differentiating between nursing homes residents' care quality perceptions.

  9. 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

  10. Evidence for a chemical enrichment coupling of globular clusters and field stars in the Fornax dSph

    NASA Astrophysics Data System (ADS)

    Hendricks, Benjamin; Boeche, Corrado; Johnson, Christian I.; Frank, Matthias J.; Koch, Andreas; Mateo, Mario; Bailey, John I.

    2016-01-01

    The globular cluster H4, located in the center of the Fornax dwarf spheroidal galaxy, is crucial for understanding the formation and chemical evolution of star clusters in low-mass galactic environments. H4 is peculiar because the cluster is significantly more metal-rich than the galaxy's other clusters, is located near the galaxy center, and may also be the youngest cluster in the galaxy. In this study, we present detailed chemical abundances derived from high-resolution (R ~ 28 000) spectroscopy of an isolated H4 member star for comparison with a sample of 22 nearby Fornax field stars. We find the H4 member to be depleted in the alpha-elements Si, Ca, and Ti with [Si/Fe] = -0.35 ± 0.34, [Ca/Fe] = + 0.05 ± 0.08, and [Ti/Fe] = -0.27 ± 0.23, resulting in an average [α/Fe] = -0.19 ± 0.14. If this result is representative of the average cluster properties, H4 is the only known system with a low [α/Fe] ratio and a moderately low metallicity embedded in an intact birth environment. For the field stars we find a clear sequence, seen as an early depletion in [α/Fe] at low metallicities, in good agreement with previous measurements. H4 falls on top of the observed field star [α/Fe] sequence and clearly disagrees with the properties of Milky Way halo stars. We therefore conclude that within a galaxy, the chemical enrichment of globular clusters may be closely linked to the enrichment pattern of the field star population. The low [α/Fe] ratios of H4 and similar metallicity field stars in Fornax give evidence that slow chemical enrichment environments, such as dwarf galaxies, may be the original hosts of alpha-depleted clusters in the halos of the Milky Way and M31. This article includes data gathered with the 6.5 m Magellan Telescopes located at Las Campanas Observatory, Chile.

  11. Constraints on mass loss and self-enrichment scenarios for the globular clusters of the Fornax dSph

    NASA Astrophysics Data System (ADS)

    Larsen, S. S.; Strader, J.; Brodie, J. P.

    2012-08-01

    Recently, high-dispersion spectroscopy has demonstrated conclusively that four of the five globular clusters (GCs) in the Fornax dwarf spheroidal galaxy are very metal-poor with [Fe/H] < -2. The remaining cluster, Fornax 4, has [Fe/H] = -1.4. This is in stark contrast to the field star metallicity distribution which shows a broad peak around [Fe/H] ≈ -1 with only a few percent of the stars having [Fe/H] < -2. If we only consider stars and clusters with [Fe/H] < -2 we thus find an extremely high GC specific frequency, SN ≈ 400, implying by far the highest ratio of GCs to field stars known anywhere. We estimate that about 1/5-1/4 of all stars in the Fornax dSph with [Fe/H] < -2 belong to the four most metal-poor GCs. These GCs could, therefore, at most have been a factor of 4-5 more massive initially. Yet, the Fornax GCs appear to share the same anomalous chemical abundance patterns known from Milky Way GCs, commonly attributed to the presence of multiple stellar generations within the clusters. The extreme ratio of metal-poor GC- versus field stars in the Fornax dSph is difficult to reconcile with scenarios for self-enrichment and early evolution of GCs in which a large fraction (90%-95%) of the first-generation stars have been lost. It also suggests that the GCs may not have formed as part of a larger population of now disrupted clusters with an initial power-law mass distribution. The Fornax dSph may be a rosetta stone for constraining theories of the formation, self-enrichment and early dynamical evolution of star clusters. Based on observations made with ESO Telescopes at the La Silla Paranal Observatory under programme ID 078.B-0631(A).

  12. Interactive Maximum Reliability Cluster Analysis.

    ERIC Educational Resources Information Center

    Mays, Robert

    1978-01-01

    A FORTRAN program for clustering variables using the alpha coefficient of reliability is described. For batch operation, a rule for stopping the agglomerative precedure is available. The conversational version of the program allows the user to intervene in the process in order to test the final solution for sensitivity to changes. (Author/JKS)

  13. [Cluster analysis and its application].

    PubMed

    Půlpán, Zdenĕk

    2002-01-01

    The study exploits knowledge-oriented and context-based modification of well-known algorithms of (fuzzy) clustering. The role of fuzzy sets is inherently inclined towards coping with linguistic domain knowledge also. We try hard to obtain from rich diverse data and knowledge new information about enviroment that is being explored.

  14. 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…

  15. 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.

  16. Simple enrichment and analysis of plasma lysophosphatidic acids.

    PubMed

    Wang, Jialu; Sibrian-Vazquez, Martha; Escobedo, Jorge O; Lowry, Mark; Wang, Lei; Chu, Yu-Hsuan; Moore, Richard G; Strongin, Robert M

    2013-11-21

    A simple and highly efficient technique for the analysis of lysophosphatidic acid (LPA) subspecies in human plasma is described. The streamlined sample preparation protocol furnishes the five major LPA subspecies with excellent recoveries. Extensive analysis of the enriched sample reveals only trace levels of other phospholipids. This level of purity not only improves MS analyses, but enables HPLC post-column detection in the visible region with a commercially available fluorescent phospholipids probe. Human plasma samples from different donors were analyzed using the above method and validated by LC-ESI/MS/MS.

  17. Using cluster analysis to explore survey data.

    PubMed

    Spencer, Llinos; Roberts, Gwerfyl; Irvine, Fiona; Jones, Peter; Baker, Colin

    2007-01-01

    Llinos Haf Spencer reports on the use of the cluster analysis statistical technique in nursing research and uses data from the Welsh Language Awareness in Healthcare Provision in Wales survey as an exemplar She concludes that cluster analysis is a valuable tool to tease out patterns in data that are not initially evident in bivariate analyses and thus should be considered as a viable option for nursing research.

  18. Digital image analysis of haematopoietic clusters.

    PubMed

    Benzinou, A; Hojeij, Y; Roudot, A-C

    2005-02-01

    Counting and differentiating cell clusters is a tedious task when performed with a light microscope. Moreover, biased counts and interpretation are difficult to avoid because of the difficulties to evaluate the limits between different types of clusters. Presented here, is a computer-based application able to solve these problems. The image analysis system is entirely automatic, from the stage screening, to the statistical analysis of the results of each experimental plate. Good correlations are found with measurements made by a specialised technician.

  19. 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.

  20. Cluster Analysis and Clinical Asthma Phenotypes

    PubMed Central

    Shaw, Dominic E.; Berry, Michael A.; Thomas, Michael; Brightling, Christopher E.; Wardlaw, Andrew J.

    2014-01-01

    Rationale Heterogeneity in asthma expression is multidimensional, including variability in clinical, physiologic, and pathologic parameters. Classification requires consideration of these disparate domains in a unified model. Objectives To explore the application of a multivariate mathematical technique, k-means cluster analysis, for identifying distinct phenotypic groups. Methods We performed k-means cluster analysis in three independent asthma populations. Clusters of a population managed in primary care (n = 184) with predominantly mild to moderate disease, were compared with a refractory asthma population managed in secondary care (n = 187). We then compared differences in asthma outcomes (exacerbation frequency and change in corticosteroid dose at 12 mo) between clusters in a third population of 68 subjects with predominantly refractory asthma, clustered at entry into a randomized trial comparing a strategy of minimizing eosinophilic inflammation (inflammation-guided strategy) with standard care. Measurements and Main Results Two clusters (early-onset atopic and obese, noneosinophilic) were common to both asthma populations. Two clusters characterized by marked discordance between symptom expression and eosinophilic airway inflammation (early-onset symptom predominant and late-onset inflammation predominant) were specific to refractory asthma. Inflammation-guided management was superior for both discordant subgroups leading to a reduction in exacerbation frequency in the inflammation-predominant cluster (3.53 [SD, 1.18] vs. 0.38 [SD, 0.13] exacerbation/patient/yr, P = 0.002) and a dose reduction of inhaled corticosteroid in the symptom-predominant cluster (mean difference, 1,829 μg beclomethasone equivalent/d [95% confidence interval, 307–3,349 μg]; P = 0.02). Conclusions Cluster analysis offers a novel multidimensional approach for identifying asthma phenotypes that exhibit differences in clinical response to treatment algorithms. PMID:18480428

  1. Origin of central abundances in the hot intra-cluster medium. II. Chemical enrichment and supernova yield models

    NASA Astrophysics Data System (ADS)

    Mernier, F.; de Plaa, J.; Pinto, C.; Kaastra, J. S.; Kosec, P.; Zhang, Y.-Y.; Mao, J.; Werner, N.; Pols, O. R.; Vink, J.

    2016-11-01

    The hot intra-cluster medium (ICM) is rich in metals, which are synthesised by supernovae (SNe) and accumulate over time into the deep gravitational potential well of clusters of galaxies. Since most of the elements visible in X-rays are formed by type Ia (SNIa) and/or core-collapse (SNcc) supernovae, measuring their abundances gives us direct information on the nucleosynthesis products of billions of SNe since the epoch of the star formation peak (z 2-3). In this study, we compare the most accurate average X/Fe abundance ratios (compiled in a previous work from XMM-Newton EPIC and RGS observations of 44 galaxy clusters, groups, and ellipticals), representative of the chemical enrichment in the nearby ICM, to various SNIa and SNcc nucleosynthesis models found in the literature. The use of a SNcc model combined to any favoured standard SNIa model (deflagration or delayed-detonation) fails to reproduce our abundance pattern. In particular, the Ca/Fe and Ni/Fe ratios are significantly underestimated by the models. We show that the Ca/Fe ratio can be reproduced better, either by taking a SNIa delayed-detonation model that matches the observations of the Tycho supernova remnant, or by adding a contribution from the "Ca-rich gap transient" SNe, whose material should easily mix into the hot ICM. On the other hand, the Ni/Fe ratio can be reproduced better by assuming that both deflagration and delayed-detonation SNIa contribute in similar proportions to the ICM enrichment. In either case, the fraction of SNIa over the total number of SNe (SNIa+SNcc) contributing to the ICM enrichment ranges within 29-45%. This fraction is found to be systematically higher than the corresponding SNIa/(SNIa+SNcc) fraction contributing to the enrichment of the proto-solar environnement (15-25%). We also discuss and quantify two useful constraints on both SNIa (i.e. the initial metallicity on SNIa progenitors and the fraction of low-mass stars that result in SNIa) and SNcc (i.e. the effect of

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

    DOE PAGES

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

    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

  3. 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.

  4. 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.

  5. 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.

  6. 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,…

  7. 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...

  8. 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.

  9. [Bacterial diversity analysis of moderately thermophilic microflora enriched by different energy sources].

    PubMed

    Liu, Fei-fei; Zhou, Hong-bo; Fu, Bo; Qiu, Guan-zhou

    2007-06-01

    Bacterial biodiversities of three moderately thermophilic bioleaching microfloras grown at 50 degrees C on media with pyrite, chalcopyrite, and pure ferrous iron supplemented with sulfur as energy sources were investigated respectively. The 16S rRNA genes of the microorganisms in the cultures flasks were PCR amplified and cloned to identify the bacterial species by comparative sequence analysis, the structural differences of microfloras enriched by different energy sources were compared. A total of 303 clones were recovered and evaluated by restriction fragment length polymorphism (RFLP) analysis. Cluster analysis identified 29 unique RFLP patterns, and the inserted 16S rRNA genes sequences were determined and for phylogenetic analysis. Most of sequences obtained were similar (89.1%-99.7%) to the 16S rRNA gene sequences of the reported bioleaching microorganisms. The species identified from the flasks during bioleaching of pyrite, pure ferrous iron supplemented with sulfur, and chalcopyrite were closely related to Acidithiobacillus caldus, Sulfobacillus thermotolerans, Sulfobacillus thermosulfidooxidans, Leptospirillum ferriphilum, two uncultured forest soil bacterium clones and one uncultured proteobacterium clone. Among these bacteria, Acidithiobacillus caldus, Sulfobacillus thermotolerans and Leptospirillum ferriphilum were the dominant bacterial species. L. ferriphilum was the most dominant species in microfloras enriched in media with pyrite and ferrous iron supplemented with sulfur as energy sources, the abundance were 53.8% and 45.9% respectively. In the culture with chalcopyrite as energy sources, S. thermotolerans had the highest abundance of 70.1%.

  10. Globular Cluster Formation at High Density: A Model for Elemental Enrichment with Fast Recycling of Massive-star Debris

    NASA Astrophysics Data System (ADS)

    Elmegreen, Bruce G.

    2017-02-01

    The self-enrichment of massive star clusters by p-processed elements is shown to increase significantly with increasing gas density as a result of enhanced star formation rates and stellar scatterings compared to the lifetime of a massive star. Considering the type of cloud core where a globular cluster (GC) might have formed, we follow the evolution and enrichment of the gas and the time dependence of stellar mass. A key assumption is that interactions between massive stars are important at high density, including interactions between massive stars and massive-star binaries that can shred stellar envelopes. Massive-star interactions should also scatter low-mass stars out of the cluster. Reasonable agreement with the observations is obtained for a cloud-core mass of ∼4 × 106 M ⊙ and a density of ∼2 × 106 cm‑3. The results depend primarily on a few dimensionless parameters, including, most importantly, the ratio of the gas consumption time to the lifetime of a massive star, which has to be low, ∼10%, and the efficiency of scattering low-mass stars per unit dynamical time, which has to be relatively large, such as a few percent. Also for these conditions, the velocity dispersions of embedded GCs should be comparable to the high gas dispersions of galaxies at that time, so that stellar ejection by multistar interactions could cause low-mass stars to leave a dwarf galaxy host altogether. This could solve the problem of missing first-generation stars in the halos of Fornax and WLM.

  11. 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.

  12. 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.

  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. 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.

  15. Electrical Load Profile Analysis Using Clustering Techniques

    NASA Astrophysics Data System (ADS)

    Damayanti, R.; Abdullah, A. G.; Purnama, W.; Nandiyanto, A. B. D.

    2017-03-01

    Data mining is one of the data processing techniques to collect information from a set of stored data. Every day the consumption of electricity load is recorded by Electrical Company, usually at intervals of 15 or 30 minutes. This paper uses a clustering technique, which is one of data mining techniques to analyse the electrical load profiles during 2014. The three methods of clustering techniques were compared, namely K-Means (KM), Fuzzy C-Means (FCM), and K-Means Harmonics (KHM). The result shows that KHM is the most appropriate method to classify the electrical load profile. The optimum number of clusters is determined using the Davies-Bouldin Index. By grouping the load profile, the demand of variation analysis and estimation of energy loss from the group of load profile with similar pattern can be done. From the group of electric load profile, it can be known cluster load factor and a range of cluster loss factor that can help to find the range of values of coefficients for the estimated loss of energy without performing load flow studies.

  16. THE SUPERNOVA DELAY TIME DISTRIBUTION IN GALAXY CLUSTERS AND IMPLICATIONS FOR TYPE-Ia PROGENITORS AND METAL ENRICHMENT

    SciTech Connect

    Maoz, Dan; Sharon, Keren; Avishay Gal-Yam

    2010-10-20

    Knowledge of the supernova (SN) delay time distribution (DTD)-the SN rate versus time that would follow a hypothetical brief burst of star formation-can shed light on SN progenitors and physics, as well as on the timescales of chemical enrichment in different environments. We compile recent measurements of the Type-Ia SN (SN Ia) rate in galaxy clusters at redshifts from z = 0 out to z = 1.45, just 2 Gyr after cluster star formation at z {approx} 3. We review the plausible range for the observed total iron-to-stellar mass ratio in clusters, based on the latest data and analyses, and use it to constrain the time-integrated number of SN Ia events in clusters. With these data, we recover the DTD of SNe Ia in cluster environments. The DTD is sharply peaked at the shortest time-delay interval we probe, 0Gyr < t < 2.2 Gyr, with a low tail out to delays of {approx}10 Gyr, and is remarkably consistent with several recent DTD reconstructions based on different methods, applied to different environments. We test DTD models from the literature, requiring that they simultaneously reproduce the observed cluster SN rates and the observed iron-to-stellar mass ratios. A parameterized power-law DTD of the form t {sup -1.2{+-}0.3} from t = 400 Myr to a Hubble time can satisfy both constraints. Shallower power laws such as t {sup -1/2} cannot, assuming a single DTD, and a single star formation burst (either brief or extended) at high z. This implies that 50%-85% of SNe Ia explode within 1 Gyr of star formation. DTDs from double-degenerate (DD) models, which generically have {approx}t {sup -1} shapes over a wide range of timescales, match the data, but only if their predictions are scaled up by factors of 5-10. Single-degenerate (SD) DTDs always give poor fits to the data, due to a lack of delayed SNe and overall low numbers of SNe. The observations can also be reproduced with a combination of two SN Ia populations-a prompt SD population of SNe Ia that explodes within a few Gyr of star

  17. 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.

  18. Enrichment Analysis - A Technique for Encouraging Better Planning and Better Use of Resources.

    ERIC Educational Resources Information Center

    Andrew, Loyd D.

    The University of Utah in building a planning, programming, and budgeting system has developed an analytical measurement called enrichment analysis that has proved useful in focusing faculty and administration attention during budget setting on long-range planning, objectives and outputs. Enrichment analysis shows not only the rate of increase in…

  19. 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.

  20. 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.

  1. 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.

  2. The isotopic composition of enriched Si: a data analysis

    NASA Astrophysics Data System (ADS)

    Bulska, E.; Drozdov, M. N.; Mana, G.; Pramann, A.; Rienitz, O.; Sennikov, P.; Valkiers, S.

    2011-04-01

    To determine the Avogadro constant by counting the atoms in quasi-perfect spheres made of a silicon crystal highly enriched with 28Si, the isotopic composition of the crystal was measured in different laboratories by different measurement methods. This paper examines the consistency of the measurement results.

  3. 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.

  4. Genome editing using FACS enrichment of nuclease-expressing cells and indel detection by amplicon analysis.

    PubMed

    Lonowski, Lindsey A; Narimatsu, Yoshiki; Riaz, Anjum; Delay, Catherine E; Yang, Zhang; Niola, Francesco; Duda, Katarzyna; Ober, Elke A; Clausen, Henrik; Wandall, Hans H; Hansen, Steen H; Bennett, Eric P; Frödin, Morten

    2017-03-01

    This protocol describes methods for increasing and evaluating the efficiency of genome editing based on the CRISPR-Cas9 (clustered regularly interspaced short palindromic repeats-CRISPR-associated 9) system, transcription activator-like effector nucleases (TALENs) or zinc-finger nucleases (ZFNs). First, Indel Detection by Amplicon Analysis (IDAA) determines the size and frequency of insertions and deletions elicited by nucleases in cells, tissues or embryos through analysis of fluorophore-labeled PCR amplicons covering the nuclease target site by capillary electrophoresis in a sequenator. Second, FACS enrichment of cells expressing nucleases linked to fluorescent proteins can be used to maximize knockout or knock-in editing efficiencies or to balance editing efficiency and toxic/off-target effects. The two methods can be combined to form a pipeline for cell-line editing that facilitates the testing of new nuclease reagents and the generation of edited cell pools or clonal cell lines, reducing the number of clones that need to be generated and increasing the ease with which they are screened. The pipeline shortens the time line, but it most prominently reduces the workload of cell-line editing, which may be completed within 4 weeks.

  5. Accelerating DNA analysis applications on GPU clusters

    SciTech Connect

    Tumeo, Antonino; Villa, Oreste

    2010-06-13

    DNA analysis is an emerging application of high performance bioinformatic. Modern sequencing machinery are able to provide, in few hours, large input streams of data which needs to be matched against exponentially growing databases known fragments. The ability to recognize these patterns effectively and fastly may allow extending the scale and the reach of the investigations performed by biology scientists. Aho-Corasick is an exact, multiple pattern matching algorithm often at the base of this application. High performance systems are a promising platform to accelerate this algorithm, which is computationally intensive but also inherently parallel. Nowadays, high performance systems also include heterogeneous processing elements, such as Graphic Processing Units (GPUs), to further accelerate parallel algorithms. Unfortunately, the Aho-Corasick algorithm exhibits large performance variabilities, depending on the size of the input streams, on the number of patterns to search and on the number of matches, and poses significant challenges on current high performance software and hardware implementations. An adequate mapping of the algorithm on the target architecture, coping with the limit of the underlining hardware, is required to reach the desired high throughputs. Load balancing also plays a crucial role when considering the limited bandwidth among the nodes of these systems. In this paper we present an efficient implementation of the Aho-Corasick algorithm for high performance clusters accelerated with GPUs. We discuss how we partitioned and adapted the algorithm to fit the Tesla C1060 GPU and then present a MPI based implementation for a heterogeneous high performance cluster. We compare this implementation to MPI and MPI with pthreads based implementations for a homogeneous cluster of x86 processors, discussing the stability vs. the performance and the scaling of the solutions, taking into consideration aspects such as the bandwidth among the different nodes.

  6. Cluster analysis applied to multiparameter geophysical dataset

    NASA Astrophysics Data System (ADS)

    Di Giuseppe, M. G.; Troiano, A.; Troise, C.; De Natale, G.

    2012-04-01

    Multi-parameter acquisition is a common geophysical field practice nowadays. Regularly seismic velocity and attenuation, gravity and electromagnetic dataset are acquired in a certain area, to obtain a complete characterization of the some investigate feature of the subsoil. Such a richness of information is often underestimated, although an integration of the analysis could provide a notable improving in the imaging of the investigated structures, mostly because the handling of distinct parameters and their joint inversion still presents several and severe problems. Post-inversion statistical techniques represent a promising approach to these questions, providing a quick, simple and elegant way to obtain this advantageous but complex integration. We present an approach based on the partition of the analyzed multi parameter dataset in a number of different classes, identified as localized regions of high correlation. These classes, or 'Cluster', are structured in such a way that the observations pertaining to a certain group are more similar to each other than the observations belonging to a different one, according to an optimal logical criterion. Regions of the subsoil sharing the same physical characteristic are so identified, without a-priori or empirical relationship linking the distinct measured parameters. The retrieved imaging results highly affordable in a statistical sense, specifically due to this lack of external hypothesis that are, instead, indispensable in a full joint inversion, were works, as matter of fact, just a real constrain for the inversion process, not seldom of relative consistence. We apply our procedure to a certain number of experimental dataset, related to several structures at very different scales presents in the Campanian district (southern Italy). These structures goes from the shallows evidence of the active fault zone originating the M 7.9 Irpinia earthquake to the main feature characterizing the Campi Flegrei Caldera and the Mt

  7. 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.

  8. 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.

  9. Solid-phase enrichment and analysis of electrophilic natural products

    PubMed Central

    Wesche, Frank; He, Yue

    2017-01-01

    In search for new natural products, which may lead to the development of new drugs for all kind of applications, novel methods are needed. Here we describe the identification of electrophilic natural products in crude extracts via their reactivity against azide as a nucleophile followed by their subsequent enrichment using a cleavable azide-reactive resin (CARR). Using this approach, natural products carrying epoxides and α,β-unsaturated enones as well as several unknown compounds were identified in crude extracts from entomopathogenic Photorhabdus bacteria. PMID:28382178

  10. The limitations of simple gene set enrichment analysis assuming gene independence.

    PubMed

    Tamayo, Pablo; Steinhardt, George; Liberzon, Arthur; Mesirov, Jill P

    2016-02-01

    Since its first publication in 2003, the Gene Set Enrichment Analysis method, based on the Kolmogorov-Smirnov statistic, has been heavily used, modified, and also questioned. Recently a simplified approach using a one-sample t-test score to assess enrichment and ignoring gene-gene correlations was proposed by Irizarry et al. 2009 as a serious contender. The argument criticizes Gene Set Enrichment Analysis's nonparametric nature and its use of an empirical null distribution as unnecessary and hard to compute. We refute these claims by careful consideration of the assumptions of the simplified method and its results, including a comparison with Gene Set Enrichment Analysis's on a large benchmark set of 50 datasets. Our results provide strong empirical evidence that gene-gene correlations cannot be ignored due to the significant variance inflation they produced on the enrichment scores and should be taken into account when estimating gene set enrichment significance. In addition, we discuss the challenges that the complex correlation structure and multi-modality of gene sets pose more generally for gene set enrichment methods.

  11. 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.

  12. 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

  13. 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.

  14. 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.; ...

    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

  15. 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.

  16. 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.

  17. Somatotyping using 3D anthropometry: a cluster analysis.

    PubMed

    Olds, Tim; Daniell, Nathan; Petkov, John; David Stewart, Arthur

    2013-01-01

    Somatotyping is the quantification of human body shape, independent of body size. Hitherto, somatotyping (including the most popular method, the Heath-Carter system) has been based on subjective visual ratings, sometimes supported by surface anthropometry. This study used data derived from three-dimensional (3D) whole-body scans as inputs for cluster analysis to objectively derive clusters of similar body shapes. Twenty-nine dimensions normalised for body size were measured on a purposive sample of 301 adults aged 17-56 years who had been scanned using a Vitus Smart laser scanner. K-means Cluster Analysis with v-fold cross-validation was used to determine shape clusters. Three male and three female clusters emerged, and were visualised using those scans closest to the cluster centroid and a caricature defined by doubling the difference between the average scan and the cluster centroid. The male clusters were decidedly endomorphic (high fatness), ectomorphic (high linearity), and endo-mesomorphic (a mixture of fatness and muscularity). The female clusters were clearly endomorphic, ectomorphic, and the ecto-mesomorphic (a mixture of linearity and muscularity). An objective shape quantification procedure combining 3D scanning and cluster analysis yielded shape clusters strikingly similar to traditional somatotyping.

  18. 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.

  19. Instantaneous normal mode analysis of melting of finite dust clusters.

    PubMed

    Melzer, André; Schella, André; Schablinski, Jan; Block, Dietmar; Piel, Alexander

    2012-06-01

    The experimental melting transition of finite two-dimensional dust clusters in a dusty plasma is analyzed using the method of instantaneous normal modes. In the experiment, dust clusters are heated in a thermodynamic equilibrium from a solid to a liquid state using a four-axis laser manipulation system. The fluid properties of the dust cluster, such as the diffusion constant, are measured from the instantaneous normal mode analysis. Thereby, the phase transition of these finite clusters is approached from the liquid phase. From the diffusion constants, unique melting temperatures have been assigned to dust clusters of various sizes that very well reflect their dynamical stability properties.

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

    PubMed

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

    2015-10-20

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

  1. 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…

  2. 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…

  3. 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…

  4. The Psychology of Yoga Practitioners: A Cluster Analysis.

    PubMed

    Genovese, Jeremy E C; Fondran, Kristine M

    2017-03-30

    Yoga practitioners (N = 261) completed the revised Expression of Spirituality Inventory (ESI) and the Multidimensional Body-Self Relations Questionnaire. Cluster analysis revealed three clusters: Cluster A scored high on all four spiritual constructs. They had high positive evaluations of their appearance, but a lower orientation towards their appearance. They tended to have a high evaluation of their fitness and health, and higher body satisfaction. Cluster B showed lower scores on the spiritual constructs. Like Cluster A, members of Cluster B tended to show high positive evaluations of appearance and fitness. They also had higher body satisfaction. Members of Cluster B had a higher fitness orientation and a higher appearance orientation than members of Cluster A. Members of Cluster C had low scores for all spiritual constructs. They had a low evaluation of, and unhappiness with, their appearance. They were unhappy with the size and appearance of their bodies. They tended to see themselves as overweight. There was a significant difference in years of practice between the three groups (Kruskall-Wallis, p = .0041). Members of Cluster A have the most years of yoga experience and members of Cluster B have more yoga experience than members of Cluster C. These results suggest the possible existence of a developmental trajectory for yoga practitioners. Such a developmental sequence may have important implications for yoga practice and instruction.

  5. 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

  6. Characterization of population exposure to organochlorines: a cluster analysis application.

    PubMed

    Guimarães, Raphael Mendonça; Asmus, Carmen Ildes Rodrigues Fróes; Burdorf, Alex

    2013-06-01

    This study aimed to show the results from a cluster analysis application in the characterization of population exposure to organochlorines through variables related to time and exposure dose. Characteristics of 354 subjects in a population exposed to organochlorine pesticides residues related to time and exposure dose were subjected to cluster analysis to separate them into subgroups. We performed hierarchical cluster analysis. To evaluate the classification accuracy, compared to intra-group and inter-group variability by ANOVA for each dimension. The aggregation strategy was accomplished by the method of Ward. It was, for the creation of clusters, variables associated with exposure and routes of contamination. The information on the estimated intake doses of compound were used to weight the values of exposure time at each of the routes, so as to obtain values proxy exposure intensity. The results showed three clusters: cluster 1 (n = 45), characteristics of greatest exposure, the cluster 2 (n = 103), intermediate exposure, and cluster 3 (n = 206), less exposure. The bivariate analyzes performed with groups that are groups showed a statistically significant difference. This study demonstrated the applicability of cluster analysis to categorize populations exposed to organochlorines and also points to the relevance of typological studies that may contribute to a better classification of subjects exposed to chemical agents, which is typical of environmental epidemiology studies to a wider understanding of etiological, preventive and therapeutic contamination.

  7. Investigating Subtypes of Child Development: A Comparison of Cluster Analysis and Latent Class Cluster Analysis in Typology Creation

    ERIC Educational Resources Information Center

    DiStefano, Christine; Kamphaus, R. W.

    2006-01-01

    Two classification methods, latent class cluster analysis and cluster analysis, are used to identify groups of child behavioral adjustment underlying a sample of elementary school children aged 6 to 11 years. Behavioral rating information across 14 subscales was obtained from classroom teachers and used as input for analyses. Both the procedures…

  8. 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

  9. Two-Way Regularized Fuzzy Clustering of Multiple Correspondence Analysis.

    PubMed

    Kim, Sunmee; Choi, Ji Yeh; Hwang, Heungsun

    2017-01-01

    Multiple correspondence analysis (MCA) is a useful tool for investigating the interrelationships among dummy-coded categorical variables. MCA has been combined with clustering methods to examine whether there exist heterogeneous subclusters of a population, which exhibit cluster-level heterogeneity. These combined approaches aim to classify either observations only (one-way clustering of MCA) or both observations and variable categories (two-way clustering of MCA). The latter approach is favored because its solutions are easier to interpret by providing explicitly which subgroup of observations is associated with which subset of variable categories. Nonetheless, the two-way approach has been built on hard classification that assumes observations and/or variable categories to belong to only one cluster. To relax this assumption, we propose two-way fuzzy clustering of MCA. Specifically, we combine MCA with fuzzy k-means simultaneously to classify a subgroup of observations and a subset of variable categories into a common cluster, while allowing both observations and variable categories to belong partially to multiple clusters. Importantly, we adopt regularized fuzzy k-means, thereby enabling us to decide the degree of fuzziness in cluster memberships automatically. We evaluate the performance of the proposed approach through the analysis of simulated and real data, in comparison with existing two-way clustering approaches.

  10. Promoter analysis of intestinal genes induced during iron-deprivation reveals enrichment of conserved SP1-like binding sites

    PubMed Central

    Collins, James F; Hu, Zihua

    2007-01-01

    Background Iron-deficiency leads to the induction of genes related to intestinal iron absorption and homeostasis. By analyzing a large GeneChip® dataset from the rat intestine, we identified a large cluster of 228 genes that was induced by iron-deprivation. Only 2 of these genes contained 3' iron-response elements, suggesting that other regulation including transcriptional may be involved. We therefore utilized computational methods to test the hypothesis that some of the genes within this large up-regulated cluster are co-ordinately regulated by common transcriptional mechanisms. We thus identified promoters from the up-regulated gene cluster from rat, mouse and human, and performed enrichment analyses with the Clover program and the TRANSFAC database. Results Surprisingly, we found a strong statistical enrichment for SP1 binding sites in our experimental promoters as compared to background sequences. As the TRANSFAC database cannot distinguish among SP/KLF family members, many of which bind similar GC-rich DNA sequences, we surmise that SP1 or an SP1-like factor could be involved in this response. In fact, we detected induction of SP6/KLF14 in the GeneChip® studies, and confirmed it by real-time PCR. Additional computational analyses suggested that an SP1-like factor may function synergistically with a FOX TF to regulate a subset of these genes. Furthermore, analysis of promoter sequences identified many genes with multiple, conserved SP1 and FOX binding sites, the relative location of which within orthologous promoters was highly conserved. Conclusion SP1 or a closely related factor may play a primary role in the genetic response to iron-deficiency in the mammalian intestine. PMID:18005439

  11. 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.

  12. The smart cluster method - Adaptive earthquake cluster identification and analysis in strong seismic regions

    NASA Astrophysics Data System (ADS)

    Schaefer, Andreas M.; Daniell, James E.; Wenzel, Friedemann

    2017-03-01

    Earthquake clustering is an essential part of almost any statistical analysis of spatial and temporal properties of seismic activity. 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 for probabilistic seismic hazard assessment. This study introduces the Smart Cluster Method (SCM), a new methodology to identify earthquake clusters, which uses an adaptive point process for spatio-temporal cluster identification. It utilises the magnitude-dependent spatio-temporal earthquake density to adjust the search properties, subsequently analyses the identified clusters to determine directional variation 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 sequence, a reclassification procedure is applied to disassemble subsequent ruptures using near-field searches, nearest neighbour classification and temporal splitting. The method is capable of identifying and classifying earthquake clusters in space and time. It has been tested and validated using earthquake data from California and New Zealand. A total of more than 1500 clusters have been found in both regions since 1980 with M m i n = 2.0. Utilising the knowledge of cluster classification, the method has been adjusted to provide an earthquake declustering algorithm, which has been compared to existing methods. Its performance is comparable to established methodologies. The analysis of earthquake clustering statistics lead to various new and updated correlation functions, e.g. for ratios between mainshock and strongest aftershock and general aftershock activity metrics.

  13. Distinct clinical phenotypes of airways disease defined by cluster analysis.

    PubMed

    Weatherall, M; Travers, J; Shirtcliffe, P M; Marsh, S E; Williams, M V; Nowitz, M R; Aldington, S; Beasley, R

    2009-10-01

    Airways disease is currently classified using diagnostic labels such as asthma, chronic bronchitis and emphysema. The current definitions of these classifications may not reflect the phenotypes of airways disease in the community, which may have differing disease processes, clinical features or responses to treatment. The aim of the present study was to use cluster analysis to explore clinical phenotypes in a community population with airways disease. A random population sample of 25-75-yr-old adults underwent detailed investigation, including a clinical questionnaire, pulmonary function tests, nitric oxide measurements, blood tests and chest computed tomography. Cluster analysis was performed on the subgroup with current respiratory symptoms or obstructive spirometric results. Subjects with a complete dataset (n = 175) were included in the cluster analysis. Five clusters were identified with the following characteristics: cluster 1: severe and markedly variable airflow obstruction with features of atopic asthma, chronic bronchitis and emphysema; cluster 2: features of emphysema alone; cluster 3: atopic asthma with eosinophilic airways inflammation; cluster 4: mild airflow obstruction without other dominant phenotypic features; and cluster 5: chronic bronchitis in nonsmokers. Five distinct clinical phenotypes of airflow obstruction were identified. If confirmed in other populations, these findings may form the basis of a modified taxonomy for the disorders of airways obstruction.

  14. Two-dimensional enrichment analysis for mining high-level imaging genetic associations.

    PubMed

    Yao, Xiaohui; Yan, Jingwen; Kim, Sungeun; Nho, Kwangsik; Risacher, Shannon L; Inlow, Mark; Moore, Jason H; Saykin, Andrew J; Shen, Li

    2017-03-01

    Enrichment analysis has been widely applied in the genome-wide association studies, where gene sets corresponding to biological pathways are examined for significant associations with a phenotype to help increase statistical power and improve biological interpretation. In this work, we expand the scope of enrichment analysis into brain imaging genetics, an emerging field that studies how genetic variation influences brain structure and function measured by neuroimaging quantitative traits (QT). Given the high dimensionality of both imaging and genetic data, we propose to study Imaging Genetic Enrichment Analysis (IGEA), a new enrichment analysis paradigm that jointly considers meaningful gene sets (GS) and brain circuits (BC) and examines whether any given GS-BC pair is enriched in a list of gene-QT findings. Using gene expression data from Allen Human Brain Atlas and imaging genetics data from Alzheimer's Disease Neuroimaging Initiative as test beds, we present an IGEA framework and conduct a proof-of-concept study. This empirical study identifies 25 significant high-level two-dimensional imaging genetics modules. Many of these modules are relevant to a variety of neurobiological pathways or neurodegenerative diseases, showing the promise of the proposal framework for providing insight into the mechanism of complex diseases.

  15. Correlation analysis of objectively defined galaxy and cluster catalogues

    NASA Astrophysics Data System (ADS)

    Stevenson, P. R. F.; Fong, R.; Shanks, T.

    1988-10-01

    The authors present further galaxy clustering results from the objective COSMOS/UKST galaxy catalogue of Stevenson et al. They first re-examine the results of SSFM for the galaxy correlation function, wgg(θ), testing the stability of the result against possible systematic effects and extending the analysis to larger angular scales. They then use the method of Turner & Gott to automatically detect groups and clusters in these catalogues. The authors next present the cluster-galaxy cross-correlation function wcg. Finally, the above correlation analyses are carried out on simulated galaxy and cluster catalogues.

  16. 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.

  17. Reactome Pathway Analysis to Enrich Biological Discovery in Proteomics Datasets

    PubMed Central

    Haw, Robin; Hermjakob, Henning; D’Eustachio, Peter; Stein, Lincoln

    2012-01-01

    Reactome (http://www.reactome.org) is an open source, expert-authored, peer-reviewed, manually curated database of reactions, pathways and biological processes. We provide an intuitive web-based user interface to pathway knowledge and a suite of data analysis tools. The Pathway Browser is a Systems Biology Graphical Notation (SBGN)-like visualization system that supports manual navigation of pathways by zooming, scrolling and event highlighting, and that exploits PSI Common Query Interface (PSIQUIC) web services to overlay pathways with molecular interaction data from the Reactome Functional Interaction (FI) Network and interaction databases such as IntAct, ChEMBL, and BioGRID. Pathway and Expression Analysis tools employ web services to provide ID mapping, pathway assignment and over-representation analysis of user-supplied datasets. By applying Ensembl Compara to curated human proteins and reactions, Reactome generates pathway inferences for 20 other species. The Species Comparison tool provides a summary of results for each of these species as a table showing numbers of orthologous proteins found by pathway from which users can navigate to inferred details for specific proteins and reactions. Reactome’s diverse pathway knowledge and suite of data analysis tools provide a platform for data mining, modeling and the analysis of large-scale proteomics datasets. PMID:21751369

  18. First CCD UBVI photometric analysis of six open cluster candidates

    NASA Astrophysics Data System (ADS)

    Piatti, A. E.; Clariá, J. J.; Ahumada, A. V.

    2011-04-01

    We have obtained CCD UBVIKC photometry down to V ˜ 22 for the open cluster candidates Haffner 3, Haffner 5, NGC 2368, Haffner 25, Hogg 3 and Hogg 4 and their surrounding fields. None of these objects have been photometrically studied so far. Our analysis shows that these stellar groups are not genuine open clusters since no clear main sequences or other meaningful features can be seen in their colour-magnitude and colour-colour diagrams. We checked for possible differential reddening across the studied fields that could be hiding the characteristics of real open clusters. However, the dust in the directions to these objects appears to be uniformly distributed. Moreover, star counts carried out within and outside the open cluster candidate fields do not support the hypothesis that these objects are real open clusters or even open cluster remnants.

  19. 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…

  20. 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

  1. 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

  2. The enrichment ratio of atomic contacts in crystals, an indicator derived from the Hirshfeld surface analysis.

    PubMed

    Jelsch, Christian; Ejsmont, Krzysztof; Huder, Loïc

    2014-03-01

    The partitioning of space with Hirshfeld surfaces enables the analysis of fingerprint molecular interactions in crystalline environments. This study uses the decomposition of the crystal contact surface between pairs of interacting chemical species to derive an enrichment ratio. This quantity enables the analysis of the propensity of chemical species to form intermolecular interactions with themselves and other species. The enrichment ratio is obtained by comparing the actual contacts in the crystal with those computed as if all types of contacts had the same probability to form. The enrichments and contact tendencies were analyzed in several families of compounds, based on chemical composition and aromatic character. As expected, the polar contacts of the type H⋯N, H⋯O and H⋯S, which are generally hydrogen bonds, show enrichment values larger than unity. O⋯O and N⋯N contacts are impoverished while H⋯H interactions display enrichment ratios which are generally close to unity or slightly lower. In aromatic compounds, C⋯C contacts can display large enrichment ratios due to extensive π⋯π stacking in the crystal packings of heterocyclic compounds. C⋯C contacts are, however, less enriched in pure (C,H) hydrocarbons as π⋯π stacking is not so favourable from the electrostatic point of view compared with heterocycles. C⋯H contacts are favoured in (C,H) aromatics, but these interactions occur less in compounds containing O, N or S as some H atoms are then involved in hydrogen bonds. The study also highlights the fact that hydrogen is a prefered interaction partner for fluorine.

  3. 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.

  4. Mission analysis of clusters of satellites

    NASA Astrophysics Data System (ADS)

    Frayssinhes, Eric; Lansard, Erick

    1996-09-01

    An innovative satellite system that provides high precision localisation of beacon positions consists of a cluster of satellites, i.e. a group of satellites that maintain assigned positions at relatively short distances from each other. Compared to a single satellite, the interest of such a cluster lies in its ability to synthesise antenna bases much longer than those who can be physically mounted on one satellite. Each satellite of the cluster measures the time-of-arrival of the signal transmitted by the beacon. The derived time-differences-of-arrival (TDOA) are processed to estimate the beacon position. At first, this paper summarises the investigations performed on the localisation accuracy that have yielded the optimal cluster geometry. In a previous paper [E. Frayssinhes and E. Lansard, AAS paper 95-334 (1995)], Alcatel Espace has proposed a mathematical formulation relying on a strong analogy with GPS geometrical characterisation of navigation performances. The effects of geometry are expressed by geometric dilution of precision (GDOP) parameters. Such parameters are obtained by solving the TDOA measurement equations for the beacon position using an iterated-least-squares procedure. Then, the paper focuses at the system level on the peculiar problems that arise when such a satellite cluster system is dealt with, and more particularly the launch and early operations phases, the station-keeping strategies of manoeuvres, and the relative localisation and clock synchronisation of the satellites. In particular, it is shown that even with the "civil" C/A GPS measurements, differential techniques can yield respective accuracies better than 5 m r.m.s. and 15 ns r.m.s.

  5. 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.

  6. 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.

  7. Atlas-Guided Cluster Analysis of Large Tractography Datasets

    PubMed Central

    Ros, Christian; Güllmar, Daniel; Stenzel, Martin; Mentzel, Hans-Joachim; Reichenbach, Jürgen Rainer

    2013-01-01

    Diffusion Tensor Imaging (DTI) and fiber tractography are important tools to map the cerebral white matter microstructure in vivo and to model the underlying axonal pathways in the brain with three-dimensional fiber tracts. As the fast and consistent extraction of anatomically correct fiber bundles for multiple datasets is still challenging, we present a novel atlas-guided clustering framework for exploratory data analysis of large tractography datasets. The framework uses an hierarchical cluster analysis approach that exploits the inherent redundancy in large datasets to time-efficiently group fiber tracts. Structural information of a white matter atlas can be incorporated into the clustering to achieve an anatomically correct and reproducible grouping of fiber tracts. This approach facilitates not only the identification of the bundles corresponding to the classes of the atlas; it also enables the extraction of bundles that are not present in the atlas. The new technique was applied to cluster datasets of 46 healthy subjects. Prospects of automatic and anatomically correct as well as reproducible clustering are explored. Reconstructed clusters were well separated and showed good correspondence to anatomical bundles. Using the atlas-guided cluster approach, we observed consistent results across subjects with high reproducibility. In order to investigate the outlier elimination performance of the clustering algorithm, scenarios with varying amounts of noise were simulated and clustered with three different outlier elimination strategies. By exploiting the multithreading capabilities of modern multiprocessor systems in combination with novel algorithms, our toolkit clusters large datasets in a couple of minutes. Experiments were conducted to investigate the achievable speedup and to demonstrate the high performance of the clustering framework in a multiprocessing environment. PMID:24386292

  8. Evaluating the Efficacy of Using Predifferentiated and Enriched Mathematics Curricula for Grade 3 Students: A Multisite Cluster-Randomized Trial

    ERIC Educational Resources Information Center

    McCoach, D. Betsy; Gubbins, E. Jean; Foreman, Jennifer; Rubenstein, Lisa DaVia; Rambo-Hernandez, Karen E.

    2014-01-01

    Despite the potential of differentiated curricula to enhance learning, limited research exists that documents their impact on Grade 3 students of all ability levels. To determine if there was a difference in achievement between students involved in 16 weeks of predifferentiated, enriched mathematics curricula and students using their district's…

  9. Construction of gene/protein interaction networks for primary myelofibrosis and KEGG pathway-enrichment analysis of molecular compounds.

    PubMed

    Sun, C G; Cao, X J; Zhou, C; Liu, L J; Feng, F B; Liu, R J; Zhuang, J; Li, Y J

    2015-12-08

    The objective of this study was the development of a gene/protein interaction network for primary myelofibrosis based on gene expression, and the enrichment analysis of KEGG pathways underlying the molecular complexes in this network. To achieve this, genes involved in primary myelofibrosis were selected from the OMIM database. A gene/protein interaction network for primary myelofibrosis was obtained through Cytoscape with the literature mining performed using the Agilent Literature Search plugin. The molecular complexes in the network were detected by ClusterViz plugin and KEGG pathway enrichment of molecular complexes was performed using DAVID online. We found 75 genes associated with primary myelofibrosis in the OMIM database. The gene/protein interaction network of primary myelofibrosis contained 608 nodes, 2086 edges, and 4 molecular complexes with a correlation integral value greater than 4. Molecular complexes involved in KEGG pathways are related to cytokine regulation, immune function regulation, ECM-receptor interaction, focal adhesion, actin cytoskeleton regulation, cell adhesion molecules, and other biological behavior of tumors, which can provide a reliable direction for the treatment of primary myelofibrosis and the bioinformatic foundation for further understanding the molecular mechanisms of this disease.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. Clustering rainfall pattern in Malaysia using functional data analysis

    NASA Astrophysics Data System (ADS)

    Hamdan, Muhammad Fauzee; Suhaila, Jamaludin; Jemain, Abdul Aziz

    2015-02-01

    Understanding rainfall pattern is important for planning and prediction in hydrology, meteorology, water planning and agriculture. There are two important features of rainfall: the rainfall amount and the probability of rainfall occurrence. The discrete raw data of rainfall precipitation was reconstructed into rainfall amount curves by using functional data analysis method. Hierarchical clustering method with complete-linkage method was used to search for natural similar groupings of rainfall amount curves. The functional clustering illustrated the four dominant patterns for rainfall amount curves. In additional, adaptive Neyman test showed that each clusters are significantly different with from each others.

  15. 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.

  16. 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.

  17. 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.

  18. IDAS: a Windows based software package for cluster analysis

    NASA Astrophysics Data System (ADS)

    Bondarenko, Igor; Treiger, Boris; Van Grieken, René; Van Espen, Pierre

    1996-03-01

    This article is an electronic publication in Spectrochimica Acta Electronica (SAE), the electronic section of Spectrochimica Acta Part B (SAB). The hardcopy text, comprising the main article and one appendix, is accompanied by two installation diskettes with the software package and data files. The main article discusses the chemometric aspects of the package and explains its purpose. The IDAS software package combines three cluster analysis methods (hierarchical, non-hierarchical and fuzzy) and runs under MS Windows. Modified algorithms for non-hierarchical and fuzzy clusterings are described. The interpretation of the clustering results is facilitated by the extensive use of different types of graph. New approaches to the graphical representation of the results of fuzzy clustering are proposed. Two data sets, the Iris data by Fisher and a data set on the chemical composition of tea, are used to demonstrate the capabilities of the software.

  19. Characterizing Suicide in Toronto: An Observational Study and Cluster Analysis

    PubMed Central

    Sinyor, Mark; Schaffer, Ayal; Streiner, David L

    2014-01-01

    Objective: To determine whether people who have died from suicide in a large epidemiologic sample form clusters based on demographic, clinical, and psychosocial factors. Method: We conducted a coroner’s chart review for 2886 people who died in Toronto, Ontario, from 1998 to 2010, and whose death was ruled as suicide by the Office of the Chief Coroner of Ontario. A cluster analysis using known suicide risk factors was performed to determine whether suicide deaths separate into distinct groups. Clusters were compared according to person- and suicide-specific factors. Results: Five clusters emerged. Cluster 1 had the highest proportion of females and nonviolent methods, and all had depression and a past suicide attempt. Cluster 2 had the highest proportion of people with a recent stressor and violent suicide methods, and all were married. Cluster 3 had mostly males between the ages of 20 and 64, and all had either experienced recent stressors, suffered from mental illness, or had a history of substance abuse. Cluster 4 had the youngest people and the highest proportion of deaths by jumping from height, few were married, and nearly one-half had bipolar disorder or schizophrenia. Cluster 5 had all unmarried people with no prior suicide attempts, and were the least likely to have an identified mental illness and most likely to leave a suicide note. Conclusions: People who die from suicide assort into different patterns of demographic, clinical, and death-specific characteristics. Identifying and studying subgroups of suicides may advance our understanding of the heterogeneous nature of suicide and help to inform development of more targeted suicide prevention strategies. PMID:24444321

  20. An Empirical Analysis of Rough Set Categorical Clustering Techniques

    PubMed Central

    2017-01-01

    Clustering a set of objects into homogeneous groups is a fundamental operation in data mining. Recently, many attentions have been put on categorical data clustering, where data objects are made up of non-numerical attributes. For categorical data clustering the rough set based approaches such as Maximum Dependency Attribute (MDA) and Maximum Significance Attribute (MSA) has outperformed their predecessor approaches like Bi-Clustering (BC), Total Roughness (TR) and Min-Min Roughness(MMR). This paper presents the limitations and issues of MDA and MSA techniques on special type of data sets where both techniques fails to select or faces difficulty in selecting their best clustering attribute. Therefore, this analysis motivates the need to come up with better and more generalize rough set theory approach that can cope the issues with MDA and MSA. Hence, an alternative technique named Maximum Indiscernible Attribute (MIA) for clustering categorical data using rough set indiscernible relations is proposed. The novelty of the proposed approach is that, unlike other rough set theory techniques, it uses the domain knowledge of the data set. It is based on the concept of indiscernibility relation combined with a number of clusters. To show the significance of proposed approach, the effect of number of clusters on rough accuracy, purity and entropy are described in the form of propositions. Moreover, ten different data sets from previously utilized research cases and UCI repository are used for experiments. The results produced in tabular and graphical forms shows that the proposed MIA technique provides better performance in selecting the clustering attribute in terms of purity, entropy, iterations, time, accuracy and rough accuracy. PMID:28068344

  1. Mapping DNA-protein interactions in large genomes by sequence tag analysis of genomic enrichment.

    PubMed

    Kim, Jonghwan; Bhinge, Akshay A; Morgan, Xochitl C; Iyer, Vishwanath R

    2005-01-01

    Identifying the chromosomal targets of transcription factors is important for reconstructing the transcriptional regulatory networks underlying global gene expression programs. We have developed an unbiased genomic method called sequence tag analysis of genomic enrichment (STAGE) to identify the direct binding targets of transcription factors in vivo. STAGE is based on high-throughput sequencing of concatemerized tags derived from target DNA enriched by chromatin immunoprecipitation. We first used STAGE in yeast to confirm that RNA polymerase III genes are the most prominent targets of the TATA-box binding protein. We optimized the STAGE protocol and developed analysis methods to allow the identification of transcription factor targets in human cells. We used STAGE to identify several previously unknown binding targets of human transcription factor E2F4 that we independently validated by promoter-specific PCR and microarray hybridization. STAGE provides a means of identifying the chromosomal targets of DNA-associated proteins in any sequenced genome.

  2. 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.

  3. CN and CH Abundance Analysis in a Sample of Eight Galactic Globular Clusters

    NASA Astrophysics Data System (ADS)

    Smolinski, Jason P.; Lee, Y.; Beers, T. C.; Martell, S. L.; An, D.; Sivarani, T.

    2011-01-01

    Galactic globular clusters exhibit star-to-star variations in their light element abundances that are not predicted by formation and evolution models involving single stellar generations. Recently it has been suggested that internal pollution from early supernovae and AGB winds may have played important roles in forming a second generation of enriched stars. We present updated results of a CN and CH abundance analysis of stars from the base to the tip of the red giant branch, and in some cases down onto the main sequence, for eight globular clusters with available photometric and spectroscopic data from SDSS-I and SDSS-II/SEGUE. These results include a discussion of the radial distribution of CN enrichment and how this may impact the current paradigm. Funding for SDSS-I and SDSS-II has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation, the U.S. Department of Energy, the National Aeronautics and Space Administration, the Japanese Monbukagakusho, the Max Planck Society, and the Higher Education Funding Council for England. The SDSS Web Site is http://www.sdss.org/. This work was supported in part by grants PHY 02-16783 and PHY 08-22648: Physics Frontiers Center/Joint Institute for Nuclear Astrophysics (JINA), awarded by the U.S. National Science Foundation.

  4. Integrated proteomic analysis of post-translational modifications by serial enrichment

    PubMed Central

    Mertins, Philipp; Qiao, Jana W; Patel, Jinal; Udeshi, Namrata D; Clauser, Karl R; Mani, D R; Burgess, Michael W; Gillette, Michael A; Jaffe, Jacob D; Carr, Steven A

    2014-01-01

    We report a mass spectrometry–based method for the integrated analysis of protein expression, phosphorylation, ubiquitination and acetylation by serial enrichments of different post-translational modifications (SEPTM) from the same biological sample. this technology enabled quantitative analysis of nearly 8,000 proteins and more than 20,000 phosphorylation, 15,000 ubiquitination and 3,000 acetylation sites per experiment, generating a holistic view of cellular signal transduction pathways as exemplified by analysis of bortezomib-treated human leukemia cells. PMID:23749302

  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. Sun Protection Belief Clusters: Analysis of Amazon Mechanical Turk Data.

    PubMed

    Santiago-Rivas, Marimer; Schnur, Julie B; Jandorf, Lina

    2016-12-01

    This study aimed (i) to determine whether people could be differentiated on the basis of their sun protection belief profiles and individual characteristics and (ii) explore the use of a crowdsourcing web service for the assessment of sun protection beliefs. A sample of 500 adults completed an online survey of sun protection belief items using Amazon Mechanical Turk. A two-phased cluster analysis (i.e., hierarchical and non-hierarchical K-means) was utilized to determine clusters of sun protection barriers and facilitators. Results yielded three distinct clusters of sun protection barriers and three distinct clusters of sun protection facilitators. Significant associations between gender, age, sun sensitivity, and cluster membership were identified. Results also showed an association between barrier and facilitator cluster membership. The results of this study provided a potential alternative approach to developing future sun protection promotion initiatives in the population. Findings add to our knowledge regarding individuals who support, oppose, or are ambivalent toward sun protection and inform intervention research by identifying distinct subtypes that may best benefit from (or have a higher need for) skin cancer prevention efforts.

  7. 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.

    2016-12-01

    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 carbon, nitrogen, and oxygen 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 we 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 the inconsistencies between the theoretical models and the observed data.

  8. BayGO: Bayesian analysis of ontology term enrichment in microarray data

    PubMed Central

    Vêncio, Ricardo ZN; Koide, Tie; Gomes, Suely L; de B Pereira, Carlos A

    2006-01-01

    Background The search for enriched (aka over-represented or enhanced) ontology terms in a list of genes obtained from microarray experiments is becoming a standard procedure for a system-level analysis. This procedure tries to summarize the information focussing on classification designs such as Gene Ontology, KEGG pathways, and so on, instead of focussing on individual genes. Although it is well known in statistics that association and significance are distinct concepts, only the former approach has been used to deal with the ontology term enrichment problem. Results BayGO implements a Bayesian approach to search for enriched terms from microarray data. The R source-code is freely available at in three versions: Linux, which can be easily incorporated into pre-existent pipelines; Windows, to be controlled interactively; and as a web-tool. The software was validated using a bacterial heat shock response dataset, since this stress triggers known system-level responses. Conclusion The Bayesian model accounts for the fact that, eventually, not all the genes from a given category are observable in microarray data due to low intensity signal, quality filters, genes that were not spotted and so on. Moreover, BayGO allows one to measure the statistical association between generic ontology terms and differential expression, instead of working only with the common significance analysis. PMID:16504085

  9. 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.

  10. 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

  11. 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…

  12. Learning From Hidden Traits: Joint Factor Analysis and Latent Clustering

    NASA Astrophysics Data System (ADS)

    Yang, Bo; Fu, Xiao; Sidiropoulos, Nicholas D.

    2017-01-01

    Dimensionality reduction techniques play an essential role in data analytics, signal processing and machine learning. Dimensionality reduction is usually performed in a preprocessing stage that is separate from subsequent data analysis, such as clustering or classification. Finding reduced-dimension representations that are well-suited for the intended task is more appealing. This paper proposes a joint factor analysis and latent clustering framework, which aims at learning cluster-aware low-dimensional representations of matrix and tensor data. The proposed approach leverages matrix and tensor factorization models that produce essentially unique latent representations of the data to unravel latent cluster structure -- which is otherwise obscured because of the freedom to apply an oblique transformation in latent space. At the same time, latent cluster structure is used as prior information to enhance the performance of factorization. Specific contributions include several custom-built problem formulations, corresponding algorithms, and discussion of associated convergence properties. Besides extensive simulations, real-world datasets such as Reuters document data and MNIST image data are also employed to showcase the effectiveness of the proposed approaches.

  13. 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.

  14. 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.

  15. 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

  16. 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…

  17. Cluster analysis as a prediction tool for pregnancy outcomes.

    PubMed

    Banjari, Ines; Kenjerić, Daniela; Šolić, Krešimir; Mandić, Milena L

    2015-03-01

    Considering specific physiology changes during gestation and thinking of pregnancy as a "critical window", classification of pregnant women at early pregnancy can be considered as crucial. The paper demonstrates the use of a method based on an approach from intelligent data mining, cluster analysis. Cluster analysis method is a statistical method which makes possible to group individuals based on sets of identifying variables. The method was chosen in order to determine possibility for classification of pregnant women at early pregnancy to analyze unknown correlations between different variables so that the certain outcomes could be predicted. 222 pregnant women from two general obstetric offices' were recruited. The main orient was set on characteristics of these pregnant women: their age, pre-pregnancy body mass index (BMI) and haemoglobin value. Cluster analysis gained a 94.1% classification accuracy rate with three branch- es or groups of pregnant women showing statistically significant correlations with pregnancy outcomes. The results are showing that pregnant women both of older age and higher pre-pregnancy BMI have a significantly higher incidence of delivering baby of higher birth weight but they gain significantly less weight during pregnancy. Their babies are also longer, and these women have significantly higher probability for complications during pregnancy (gestosis) and higher probability of induced or caesarean delivery. We can conclude that the cluster analysis method can appropriately classify pregnant women at early pregnancy to predict certain outcomes.

  18. Making Sense of Cluster Analysis: Revelations from Pakistani Science Classes

    ERIC Educational Resources Information Center

    Pell, Tony; Hargreaves, Linda

    2011-01-01

    Cluster analysis has been applied to quantitative data in educational research over several decades and has been a feature of the Maurice Galton's research in primary and secondary classrooms. It has offered potentially useful insights for teaching yet its implications for practice are rarely implemented. It has been subject also to negative…

  19. Quantitative site-specific analysis of protein glycosylation by LC-MS using different glycopeptide-enrichment strategies.

    PubMed

    Wohlgemuth, Jessica; Karas, Michael; Eichhorn, Thomas; Hendriks, Robertus; Andrecht, Sven

    2009-12-15

    A common technique for analysis of protein glycosylation is HPLC coupled to mass spectrometry (LC-MS). However, analysis is challenging due to a low abundance of glycopeptides in complex protein digests, microheterogeneity at the glycosylation site, ion suppression effects, and competition for ionization by coeluting peptides. Specific sample preparation is necessary for a comprehensive and site-specific glycosylation analysis by MS. In this study we qualitatively compared hydrophilic interaction chromatography (HILIC) and hydrazine chemistry for the enrichment of all N-linked glycopeptides and titanium dioxide for capturing sialylated glycopeptides from a complex peptide mixture. Bare silica, microcrystalline cellulose, amino-, amide- (TSKgel Amide-80), and sulfobetaine-(ZIC-HILIC) bonded phases were evaluated for HILIC enrichment. The experiments revealed that ZIC-HILIC and TSKgel Amide-80 are very specific for capturing glycopeptides under optimized conditions. Quantitative analysis of N-glycosidase F-released and 2-aminobenzamide-labeled glycans of a ZIC-HILIC-enriched monoclonal antibody demonstrated that glycopeptides could be enriched without bias for particular glycan structures and without significant losses. Sialylated glycopeptides could be efficiently enriched by titanium dioxide and in addition to HILIC both methods enable a comprehensive analysis of protein glycosylation by MS. Enrichment of N-linked glycopeptides by hydrazine chemistry resulted in lower peptide recovery using a more complex enrichment scheme.

  20. Large-Scale Graph Processing Analysis using Supercomputer Cluster

    NASA Astrophysics Data System (ADS)

    Vildario, Alfrido; Fitriyani; Nugraha Nurkahfi, Galih

    2017-01-01

    Graph implementation is widely use in various sector such as automotive, traffic, image processing and many more. They produce graph in large-scale dimension, cause the processing need long computational time and high specification resources. This research addressed the analysis of implementation large-scale graph using supercomputer cluster. We impelemented graph processing by using Breadth-First Search (BFS) algorithm with single destination shortest path problem. Parallel BFS implementation with Message Passing Interface (MPI) used supercomputer cluster at High Performance Computing Laboratory Computational Science Telkom University and Stanford Large Network Dataset Collection. The result showed that the implementation give the speed up averages more than 30 times and eficiency almost 90%.

  1. 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

  2. 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.

  3. Analysis of microbial community and nitrogen transition with enriched nitrifying soil microbes for organic hydroponics.

    PubMed

    Saijai, Sakuntala; Ando, Akinori; Inukai, Ryuya; Shinohara, Makoto; Ogawa, Jun

    2016-06-27

    Nitrifying microbial consortia were enriched from bark compost in a water system by regulating the amounts of organic nitrogen compounds and by controlling the aeration conditions with addition of CaCO3 for maintaining suitable pH. Repeated enrichment showed reproducible mineralization of organic nitrogen via the conversion of ammonium ions ([Formula: see text]) and nitrite ions ([Formula: see text]) into nitrate ions ([Formula: see text]). The change in microbial composition during the enrichment was investigated by PCR-DGGE analysis with a focus on prokaryote, ammonia-oxidizing bacteria, nitrite-oxidizing bacteria, and eukaryote cell types. The microbial transition had a simple profile and showed clear relation to nitrogen ions transition. Nitrosomonas and Nitrobacter were mainly detected during [Formula: see text] and [Formula: see text] oxidation, respectively. These results revealing representative microorganisms acting in each ammonification and nitrification stages will be valuable for the development of artificial simple microbial consortia for organic hydroponics that consisted of identified heterotrophs and autotrophic nitrifying bacteria.

  4. Potentially novel copper resistance genes in copper-enriched activated sludge revealed by metagenomic analysis.

    PubMed

    Li, Li-Guan; Cai, Lin; Zhang, Xu-Xiang; Zhang, Tong

    2014-12-01

    In this study, we utilized the Illumina high-throughput metagenomic approach to investigate diversity and abundance of both microbial community and copper resistance genes (CuRGs) in activated sludge (AS) which was enriched under copper selective stress up to 800 mg/L. The raw datasets (~3.5 Gb for each sample, i.e., the copper-enriched AS and the control AS) were merged and normalized for the BLAST analyses against the SILVA SSU rRNA gene database and self-constructed copper resistance protein database (CuRD). Also, the raw metagenomic sequences were assembled into contigs and analyzed based on Open Reading Frames (ORFs) to identify potentially novel copper resistance genes. Among the different resistance systems for copper detoxification under the high copper stress condition, the Cus system was the most enriched system. The results also indicated that genes encoding multi-copper oxidase played a more important role than those encoding efflux proteins. More significantly, several potentially novel copper resistance ORFs were identified by Pfam search and phylogenic analysis. This study demonstrated a new understanding of microbial-mediated copper resistance under high copper stress using high-throughput shotgun sequencing technique.

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

    PubMed Central

    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

  6. Seismicity monitoring by cluster analysis of moment tensors

    NASA Astrophysics Data System (ADS)

    Cesca, Simone; Şen, Ali Tolga; Dahm, Torsten

    2014-03-01

    We suggest a new clustering approach to classify focal mechanisms from large moment tensor catalogues, with the purpose of automatically identify families of earthquakes with similar source geometry, recognize the orientation of most active faults, and detect temporal variations of the rupture processes. The approach differs in comparison to waveform similarity methods since clusters are detected even if they occur in large spatial distances. This approach is particularly helpful to analyse large moment tensor catalogues, as in microseismicity applications, where a manual analysis and classification is not feasible. A flexible algorithm is here proposed: it can handle different metrics, norms, and focal mechanism representations. In particular, the method can handle full moment tensor or constrained source model catalogues, for which different metrics are suggested. The method can account for variable uncertainties of different moment tensor components. We verify the method with synthetic catalogues. An application to real data from mining induced seismicity illustrates possible applications of the method and demonstrate the cluster detection and event classification performance with different moment tensor catalogues. Results proof that main earthquake source types occur on spatially separated faults, and that temporal changes in the number and characterization of focal mechanism clusters are detected. We suggest that moment tensor clustering can help assessing time dependent hazard in mines.

  7. Improving Gene-Set Enrichment Analysis of RNA-Seq Data with Small Replicates.

    PubMed

    Yoon, Sora; Kim, Seon-Young; Nam, Dougu

    2016-01-01

    Deregulated pathways identified from transcriptome data of two sample groups have played a key role in many genomic studies. Gene-set enrichment analysis (GSEA) has been commonly used for pathway or functional analysis of microarray data, and it is also being applied to RNA-seq data. However, most RNA-seq data so far have only small replicates. This enforces to apply the gene-permuting GSEA method (or preranked GSEA) which results in a great number of false positives due to the inter-gene correlation in each gene-set. We demonstrate that incorporating the absolute gene statistic in one-tailed GSEA considerably improves the false-positive control and the overall discriminatory ability of the gene-permuting GSEA methods for RNA-seq data. To test the performance, a simulation method to generate correlated read counts within a gene-set was newly developed, and a dozen of currently available RNA-seq enrichment analysis methods were compared, where the proposed methods outperformed others that do not account for the inter-gene correlation. Analysis of real RNA-seq data also supported the proposed methods in terms of false positive control, ranks of true positives and biological relevance. An efficient R package (AbsFilterGSEA) coded with C++ (Rcpp) is available from CRAN.

  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. Cluster analysis of Plasmodium RNA-seq time-course data identifies stage-specific co-regulated biological processes and regulatory elements

    PubMed Central

    Oyelade, Jelili; Adebiyi, Ezekiel

    2016-01-01

    In this study, we interpreted RNA-seq time-course data of three developmental stages of Plasmodium species by clustering genes based on similarities in their expression profile without prior knowledge of the gene function. Functional enrichment of clusters of upregulated genes at specific time-points reveals potential targetable biological processes with information on their timings. We identified common consensus sequences that these clusters shared as potential points of coordinated transcriptional control. Five cluster groups showed upregulated profile patterns of biological interest. This included two clusters from the Intraerythrocytic Developmental Cycle (cluster 4 = 16 genes, and cluster 9 = 32 genes), one from the sexual development stage (cluster 2 = 851 genes), and two from the gamete-fertilization stage in the mosquito host (cluster 4 = 153 genes, and cluster 9 = 258 genes). The IDC expressed the least numbers of genes with only 1448 genes showing any significant activity of the 5020 genes (~29%) in the experiment. Gene ontology (GO) enrichment analysis of these clusters revealed a total of 671 uncharacterized genes implicated in 14 biological processes and components associated with these stages, some of which are currently being investigated as drug targets in on-going research. Five putative transcription regulatory binding motifs shared by members of each cluster were also identified, one of which was also identified in a previous study by separate researchers. Our study shows stage-specific genes and biological processes that may be important in antimalarial drug research efforts. In addition, timed-coordinated control of separate processes may explain the paucity of factors in parasites. PMID:27990252

  10. 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.

  11. Nonproliferation analysis of the reduction of excess separated plutonium and high-enriched uranium

    SciTech Connect

    Persiani, P.J.

    1995-08-01

    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.

  12. 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.

  13. 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

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

    PubMed

    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

    2016-05-19

    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.

  15. 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.

  16. 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.

  17. Full Text Clustering and Relationship Network Analysis of Biomedical Publications

    PubMed Central

    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

  18. Criticality Expermints with Subcritical Clusters of 2.35 Wt% and 4.31 Wt% 2.35U Enriched UO2 Rods in Water at a Water-to-Fuel Volume Ratio of 1.6

    SciTech Connect

    SR Bierman; ED Clayton

    1980-07-01

    The fourth in a series of Nuclear Regulatory Commission funded criticality experiments have provided data for 2.35 wt% and 4.31 wt% {sup 235}U enriched U0{sub 2} rods at a water-to-fuel volume ratio of 1.6. The results from some 147 critical experiments are presented. They include for each enrichment: {sm_bullet}The critical size of single lattices or clusters of fuel {sm_bullet}The critical separation between sub-critical clusters of fuel {sm_bullet}The critical separation between sub-critical clusters of fuel having fixed neutron absorbers between the fuel clusters {sm_bullet}The isolation distance between fuel clusters {sm_bullet}The critical size of fuel clusters containing water holes and voids {sm_bullet}The critical size of fuel clusters separated by flux traps The fixed neutron absorbers for which data were obtained include 304-L steel, borated 304-L steel, copper, copper containing 1 wt% cadmium, cadmium, aluminium, zirconium and two trade name materials containing boron (Boral and Borofl ex).

  19. 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

  20. Specific on-plate enrichment of phosphorylated peptides for direct MALDI-TOF MS analysis.

    PubMed

    Qiao, Liang; Roussel, Christophe; Wan, Jingjing; Yang, Pengyuan; Girault, Hubert H; Liu, Baohong

    2007-12-01

    An on-plate specific enrichment method is presented for the direct analysis of peptides phosphorylation. An array of sintered TiO 2 nanoparticle spots was prepared on a stainless steel plate to provide porous substrate with a very large specific surface and durable functions. These spots were used to selectively capture phosphorylated peptides from peptide mixtures, and the immobilized phosphopeptides could then be analyzed directly by MALDI MS after washing away the nonphosphorylated peptides. beta-Casein and protein mixtures were employed as model samples to investigate the selection efficiency. In this strategy, the steps of phosphopeptide capture, purification, and subsequent mass spectrometry analysis are all successfully accomplished on a single target plate, which greatly reduces sample loss and simplifies analytical procedures. The low detection limit, small sample size, and rapid selective entrapment show that this on-plate strategy is promising for online enrichment of phosphopeptides, which is essential for the analysis of minute amount of samples in high-throughput proteome research.

  1. Enrichment and Molecular Analysis of Breast Cancer Disseminated Tumor Cells from Bone Marrow Using Microfiltration

    PubMed Central

    Siddappa, Chidananda M.; Adams, Daniel L.; Li, Shuhong; Makarova, Olga V.; Amstutz, Pete; Nunley, Ryan; Tang, Cha-Mei; Watson, Mark A.; Aft, Rebecca L.

    2017-01-01

    Purpose Molecular characterization of disseminated tumor cells (DTCs) in the bone marrow (BM) of breast cancer (BC) patients has been hindered by their rarity. To enrich for these cells using an antigen-independent methodology, we have evaluated a size-based microfiltration device in combination with several downstream biomarker assays. Methods BM aspirates were collected from healthy volunteers or BC patients. Healthy BM was mixed with a specified number of BC cells to calculate recovery and fold enrichment by microfiltration. Specimens were pre-filtered using a 70 μm mesh sieve and the effluent filtered through CellSieve microfilters. Captured cells were analyzed by immunocytochemistry (ICC), FISH for HER-2/neu gene amplification status, and RNA in situ hybridization (RISH). Cells eluted from the filter were used for RNA isolation and subsequent qRT-PCR analysis for DTC biomarker gene expression. Results Filtering an average of 14×106 nucleated BM cells yielded approximately 17–21×103 residual BM cells. In the BC cell spiking experiments, an average of 87% (range 84–92%) of tumor cells were recovered with approximately 170- to 400-fold enrichment. Captured BC cells from patients co-stained for cytokeratin and EpCAM, but not CD45 by ICC. RNA yields from 4 ml of patient BM after filtration averaged 135ng per 10 million BM cells filtered with an average RNA Integrity Number (RIN) of 5.3. DTC-associated gene expression was detected by both qRT-PCR and RISH in filtered spiked or BC patient specimens but, not in control filtered normal BM. Conclusions We have tested a microfiltration technique for enrichment of BM DTCs. DTC capture efficiency was shown to range from 84.3% to 92.1% with up to 400-fold enrichment using model BC cell lines. In patients, recovered DTCs can be identified and distinguished from normal BM cells using multiple antibody-, DNA-, and RNA-based biomarker assays. PMID:28129357

  2. 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

    2015-06-03

    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.

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

    PubMed

    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.

  4. An Interpretation of the Boshier-Collins Cluster Analysis Testing Houle's Typology.

    ERIC Educational Resources Information Center

    Furst, Edward J.

    1986-01-01

    This article speculates on an underlying order obscured by the details of the Boshier-Collins cluster analysis and the mapping of Houle's types onto it. A table illustrates an interpretation of cluster analysis on Boshier's Education Participation Scale. (CT)

  5. Analysis of data separation and recovery problems using clustered sparsity

    NASA Astrophysics Data System (ADS)

    King, Emily J.; Kutyniok, Gitta; Zhuang, Xiaosheng

    2011-09-01

    Data often have two or more fundamental components, like cartoon-like and textured elements in images; point, filament, and sheet clusters in astronomical data; and tonal and transient layers in audio signals. For many applications, separating these components is of interest. Another issue in data analysis is that of incomplete data, for example a photograph with scratches or seismic data collected with fewer than necessary sensors. There exists a unified approach to solving these problems which is minimizing the l1 norm of the analysis coefficients with respect to particular frame(s). This approach using the concept of clustered sparsity leads to similar theoretical bounds and results, which are presented here. Furthermore, necessary conditions for the frames to lead to sufficiently good solutions are also shown.

  6. 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.

  7. Proteomic analysis of the mouse brain following protein enrichment by preparative electrophoresis.

    PubMed

    Xixi, Elena; Dimitraki, Ploumisti; Vougas, Kostantinos; Kossida, Sofia; Lubec, Gert; Fountoulakis, Michael

    2006-04-01

    Proteomics is a powerful technology to study the identity and levels of brain proteins. Changes of protein levels as well as modifications that occur in neurological disorders may be informative for the pathogenesis of these disorders and could result in the identification of potential drug targets and disease markers. To increase the capability of characterizing complex protein profiles, protein mixtures should be separated into simpler fractions, thus increasing the likelihood of detecting low-abundance proteins. Considering that low-abundance proteins are thought to be involved in important biological processes, identification of those low-copy-number gene products appears to be a scientific challenge. In the present study, proteomic analysis of adult mouse brain tissue was performed following enrichment by preparative electrophoresis. This was performed using the PrepCell apparatus in the presence of 0.1% lithium dodecyl sulfate. Samples were electrophoresed in a cylindrical polyacrylamide gel and the proteins of the fractions collected were first analyzed by 1-D and then by 2-DE. Protein identification was performed by MALDI-TOF-MS. The present analysis resulted in the identification of 360 different gene products. Among those were transport proteins, transcription activators, signal transduction molecules as well as proteins with a number of other functions. Preparative electrophoresis is an efficient method for the enrichment of proteins of low molecular mass and may be useful in the investigation of disorders of the central nervous system.

  8. 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.

  9. Assessing intraplate volcano compositional similarities with cluster analysis

    NASA Astrophysics Data System (ADS)

    Konter, J. G.

    2012-12-01

    The compositional variation in intraplate volcanoes is commonly assessed as a function of end-members that were recognized as extrema in a 3D space, defined by radiogenic isotope ratios. The specific isotope ratios used are the principle components in the intraplate volcano compositional data set, and by reducing the dimensionality of the data set to 3, groupings and trends in the data can be visually identified. Such groupings can then be used to compare to other geochemical or geophysical data sets (e.g. correlations with seismic models). A complementary approach in examining groupings and trends in a data set is the use of cluster analysis, which can be used to recognize groups of similar intraplate volcanic systems. Since it is not known a priori how many clusters may exist, hierarchical cluster analysis can be used to examine the relationships between individual intraplate volcanic systems. The technique compares the Euclidian distance between the data available at the different locations, and this data can have a large number of dimensions. The results can be visualized as a dendrogram, where individual locations are represented by different branches (or leafs) that join at different distances. We use Matlab to examine the data extracted from pre-compiled GEOROC database files, including location, major elements, large ion lithophile elements, high field strength elements, rare earth elements and radiogenic isotopes. These data do not vary over the same range in values and are therefore first normalized by the total range in the data set for each particular element or isotope ratio. Since multiple samples have been analyzed for most intraplate volcanic systems, we assess the results for the average, the maximum, and the minimum values for each element. In addition, we investigate the robustness of the outcome by removing one element at a time from the data set and recalculating a new dendrogram. One of the outcomes is that the resulting clusters seem to

  10. 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…

  11. 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

  12. 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

  13. 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

    2016-07-08

    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.

  14. ACPA: automated cluster plot analysis of genotype data.

    PubMed

    Schillert, Arne; Schwarz, Daniel F; Vens, Maren; Szymczak, Silke; König, Inke R; Ziegler, Andreas

    2009-12-15

    Genome-wide association studies have become standard in genetic epidemiology. Analyzing hundreds of thousands of markers simultaneously imposes some challenges for statisticians. One issue is the problem of multiplicity, which has been compared with the search for the needle in a haystack. To reduce the number of false-positive findings, a number of quality filters such as exclusion of single-nucleotide polymorphisms (SNPs) with a high missing fraction are employed. Another filter is exclusion of SNPs for which the calling algorithm had difficulties in assigning the genotypes. The only way to do this is the visual inspection of the cluster plots, also termed signal intensity plots, but this approach is often neglected. We developed an algorithm ACPA (automated cluster plot analysis), which performs this task automatically for autosomal SNPs. It is based on counting samples that lie too close to the cluster of a different genotype; SNPs are excluded when a certain threshold is exceeded. We evaluated ACPA using 1,000 randomly selected quality controlled SNPs from the Framingham Heart Study data that were provided for the Genetic Analysis Workshop 16. We compared the decision of ACPA with the decision made by two independent readers. We achieved a sensitivity of 88% (95% CI: 81%-93%) and a specificity of 86% (95% CI: 83%-89%). In a screening setting in which one aims at not losing any good SNP, we achieved 99% (95% CI: 98%-100%) specificity and still detected every second low-quality SNP.

  15. 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.

  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. Phylogenetic Analysis of Anaerobic Psychrophilic Enrichment Cultures Obtained from a Greenland Glacier Ice Core

    PubMed Central

    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°C for over 100,000 years. Epifluorescence microscopy and flow cytometry results showed that the ice sample contained over 6 × 107 cells/ml. Anaerobic enrichment cultures inoculated with melted ice were grown and maintained at −2°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. PMID:12676695

  18. 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.

  19. 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.

  20. 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.

  1. Clustering Analysis of Fast-ion Driven Instabilities

    NASA Astrophysics Data System (ADS)

    Gresl, J.; Heidbrink, W. W.; Haskey, S.; Blackwell, B. D.

    2016-10-01

    Beam ions often drive Alfvén eigenmodes and other instabilities unstable in DIII-D. Many of these modes have been unambigously identified but some frequently occurring features have been neglected. In this work, datamining analysis techniques that successfully analyzed magnetics data from the H-1NF heliac are applied to arrays of magnetic and electron cyclotron emission (ECE) data from DIII-D. The techniques group instabilities with similar magnetic or ECE features into clusters. Once the clusters are found, a database of plasma parameters will facilitate mode identification. Work supported by the US Department of Energy under DE-FC02-04ER54698, DE-FG03-94ER54271, DE-AC02-09CH11466.

  2. 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…

  3. 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

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

    PubMed Central

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

    2015-01-01

    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. PMID:26337391

  5. 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.

  6. 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

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. Common and Cluster-Specific Simultaneous Component Analysis

    PubMed Central

    De Roover, Kim; Timmerman, Marieke E.; Mesquita, Batja; Ceulemans, Eva

    2013-01-01

    In many fields of research, so-called ‘multiblock’ data are collected, i.e., data containing multivariate observations that are nested within higher-level research units (e.g., inhabitants of different countries). Each higher-level unit (e.g., country) then corresponds to a ‘data block’. For such data, it may be interesting to investigate the extent to which the correlation structure of the variables differs between the data blocks. More specifically, when capturing the correlation structure by means of component analysis, one may want to explore which components are common across all data blocks and which components differ across the data blocks. This paper presents a common and cluster-specific simultaneous component method which clusters the data blocks according to their correlation structure and allows for common and cluster-specific components. Model estimation and model selection procedures are described and simulation results validate their performance. Also, the method is applied to data from cross-cultural values research to illustrate its empirical value. PMID:23667463

  12. 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.

  13. OSAnalyzer: A Bioinformatics Tool for the Analysis of Gene Polymorphisms Enriched with Clinical Outcomes

    PubMed Central

    Agapito, Giuseppe; Botta, Cirino; Guzzi, Pietro Hiram; Arbitrio, Mariamena; Di Martino, Maria Teresa; Tassone, Pierfrancesco; Tagliaferri, Pierosandro; Cannataro, Mario

    2016-01-01

    Background: The identification of biomarkers for the estimation of cancer patients’ survival is a crucial problem in modern oncology. Recently, the Affymetrix DMET (Drug Metabolizing Enzymes and Transporters) microarray platform has offered the possibility to determine the ADME (absorption, distribution, metabolism, and excretion) gene variants of a patient and to correlate them with drug-dependent adverse events. Therefore, the analysis of survival distribution of patients starting from their profile obtained using DMET data may reveal important information to clinicians about possible correlations among drug response, survival rate, and gene variants. Methods: In order to provide support to this analysis we developed OSAnalyzer, a software tool able to compute the overall survival (OS) and progression-free survival (PFS) of cancer patients and evaluate their association with ADME gene variants. Results: The tool is able to perform an automatic analysis of DMET data enriched with survival events. Moreover, results are ranked according to statistical significance obtained by comparing the area under the curves that is computed by using the log-rank test, allowing a quick and easy analysis and visualization of high-throughput data. Conclusions: Finally, we present a case study to highlight the usefulness of OSAnalyzer when analyzing a large cohort of patients. PMID:27669316

  14. Cluster analysis in systems of magnetic spheres and cubes

    NASA Astrophysics Data System (ADS)

    Pyanzina, E. S.; Gudkova, A. V.; Donaldson, J. G.; Kantorovich, S. S.

    2017-06-01

    In the present work we use molecular dynamics simulations and graph-theory based cluster analysis to compare self-assembly in systems of magnetic spheres, and cubes where the dipole moment is oriented along the side of the cube in the [001] crystallographic direction. We show that under the same conditions cubes aggregate far less than their spherical counterparts. This difference can be explained in terms of the volume of phase space in which the formation of the bond is thermodynamically advantageous. It follows that this volume is much larger for a dipolar sphere than for a dipolar cube.

  15. 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.

  16. Evaluation of tetraglyme for the enrichment and analysis of volatile organic compounds in air.

    PubMed

    Huybrechts, T; Dewulf, J; Van Craeynest, K; Van Langenhove, H

    2001-07-13

    A recently developed method for the sampling and analysis of volatile organic compounds in air has been evaluated. The system is based on the enrichment of analytes in tetraethylene glycol dimethyl ether or tetraglyme, a water-soluble organic liquid. The subsequent analysis consists of dispersion of a sample aliquot in water followed by purge-and-trap and gas chromatographic separation. Physico-chemical data were investigated for 10 volatile organic compounds, providing information on the possibilities and limitations of the tetraglyme method. The target analytes included chlorinated alkanes and alkenes, and monocyclic aromatic hydrocarbons. Air/tetraglyme partition coefficients Kat were determined over an environmental relevant temperature range of 2-25 degrees C to evaluate sorption efficiencies and estimate breakthrough volumes at the sampling stage. At 2 degrees C breakthrough volumes (allowing 5% of breakthrough) ranged from 5.8 (1,1-dichloroethane) to 312 l (1,1,2-trichloroethane) for 20 ml of tetraglyme. With regard to the desorption stage, the effect of tetraglyme on the air/water partition of organic compounds was investigated through the measurement of air/tetraglyme-water partition coefficients Kat-w for 2-31% (v/v) tetraglyme in water. Finally a clean-up procedure for tetraglyme was evaluated. Analysis of a blank tetraglyme-water (17:83, v:v) mixture by gas chromatography-flame ionization detection/mass spectrometry showed minor background signals. None of the target compounds were detected.

  17. 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

  18. Transcriptome analysis identifies genes with enriched expression in the mouse central Extended Amygdala

    PubMed Central

    Becker, Jérôme A. J.; Befort, Katia; Blad, Clara; Filliol, Dominique; Ghate, Aditee; Dembele, Doulaye; Thibault, Christelle; Koch, Muriel; Muller, Jean; Lardenois, Aurélie; Poch, Olivier; Kieffer, Brigitte L.

    2008-01-01

    The central Extended Amygdala (EAc) is an ensemble of highly interconnected limbic structures of the anterior brain, and forms a cellular continuum including the Bed Nucleus of the Stria Terminalis (BNST), the central nucleus of the Amygdala (CeA) and the Nucleus Accumbens shell (AcbSh). This neural network is a key site for interactions between brain reward and stress systems, and has been implicated in several aspects of drug abuse. In order to increase our understanding of EAc function at the molecular level, we undertook a genome-wide screen (Affymetrix) to identify genes whose expression is enriched in the EAc. We focused on the less-well known BNST-CeA areas of the EAc, and identified 121 genes that exhibit more than 2-fold higher expression level in the EAc compared to whole brain. Among these, forty-three genes have never been described to be expressed in the EAc. We mapped these genes throughout the brain, using non-radioactive in situ hybridization, and identified eight genes with a unique and distinct rostro-caudal expression pattern along AcbSh, BNST and CeA. Q-PCR analysis performed in brain and peripheral organ tissues indicated that, with the exception of one (Spata13), all these genes are predominantly expressed in brain. These genes encode signaling proteins (Adora2, GPR88, Arpp21 and Rem2), a transcription factor (Limh6) or proteins of unknown function (Rik130, Spata13 and Wfs1). The identification of genes with enriched expression expands our knowledge of EAc at a molecular level, and provides useful information to towards genetic manipulations within the EAc. PMID:18786617

  19. 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

  20. High resolution spectroscopic analysis of seven giants in the bulge globular cluster NGC 6723

    NASA Astrophysics Data System (ADS)

    Rojas-Arriagada, A.; Zoccali, M.; Vásquez, S.; Ripepi, V.; Musella, I.; Marconi, M.; Grado, A.; Limatola, L.

    2016-03-01

    Context. Globular clusters associated with the Galactic bulge are important tracers of stellar populations in the inner Galaxy. High resolution analysis of stars in these clusters allows us to characterize them in terms of kinematics, metallicity, and individual abundances, and to compare these fingerprints with those characterizing field populations. Aims: We present iron and element ratios for seven red giant stars in the globular cluster NGC 6723, based on high resolution spectroscopy. Methods: High resolution spectra (R ~ 48 000) of seven K giants belonging to NGC 6723 were obtained with the FEROS spectrograph at the MPG/ESO 2.2 m telescope. Photospheric parameters were derived from ~130 Fe i and Fe ii transitions. Abundance ratios were obtained from line-to-line spectrum synthesis calculations on clean selected features. Results: An intermediate metallicity of [Fe/H] = -0.98 ± 0.08 dex and a heliocentric radial velocity of vhel = -96.6 ± 1.3 km s-1 were found for NGC 6723. Alpha-element abundances present enhancements of [O/Fe] = 0.29 ± 0.18 dex, [Mg/Fe] = 0.23 ± 0.10 dex, [Si/Fe] = 0.36 ± 0.05 dex, and [Ca/Fe] = 0.30 ± 0.07 dex. Similar overabundance is found for the iron-peak Ti with [Ti/Fe] = 0.24 ± 0.09 dex. Odd-Z elements Na and Al present abundances of [Na/Fe] = 0.00 ± 0.21 dex and [Al/Fe] = 0.31 ± 0.21 dex, respectively. Finally, the s-element Ba is also enhanced by [Ba/Fe] = 0.22 ± 0.21 dex. Conclusions: The enhancement levels of NGC 6723 are comparable to those of other metal-intermediate bulge globular clusters. In turn, these enhancement levels are compatible with the abundance profiles displayed by bulge field stars at that metallicity. This hints at a possible similar chemical evolution with globular clusters and the metal-poor of the bulge going through an early prompt chemical enrichment.

  1. Year clustering analysis for modelling olive flowering phenology.

    PubMed

    Oteros, J; García-Mozo, H; Hervás-Martínez, C; Galán, C

    2013-07-01

    It is now widely accepted that weather conditions occurring several months prior to the onset of flowering have a major influence on various aspects of olive reproductive phenology, including flowering intensity. Given the variable characteristics of the Mediterranean climate, we analyse its influence on the registered variations in olive flowering intensity in southern Spain, and relate them to previous climatic parameters using a year-clustering approach, as a first step towards an olive flowering phenology model adapted to different year categories. Phenological data from Cordoba province (Southern Spain) for a 30-year period (1982-2011) were analysed. Meteorological and phenological data were first subjected to both hierarchical and "K-means" clustering analysis, which yielded four year-categories. For this classification purpose, three different models were tested: (1) discriminant analysis; (2) decision-tree analysis; and (3) neural network analysis. Comparison of the results showed that the neural-networks model was the most effective, classifying four different year categories with clearly distinct weather features. Flowering-intensity models were constructed for each year category using the partial least squares regression method. These category-specific models proved to be more effective than general models. They are better suited to the variability of the Mediterranean climate, due to the different response of plants to the same environmental stimuli depending on the previous weather conditions in any given year. The present detailed analysis of the influence of weather patterns of different years on olive phenology will help us to understand the short-term effects of climate change on olive crop in the Mediterranean area that is highly affected by it.

  2. Integrated microscale analysis system for targeted liquid chromatography mass spectrometry proteomics on limited amounts of enriched cell populations.

    PubMed

    Martin, Jeffrey G; Rejtar, Tomas; Martin, Stephen A

    2013-11-19

    Limited samples, such as those that are in vivo sourced via biopsy, are closely representative of biological systems and contain valuable information for drug discovery. However, these precious samples are often heterogeneous and require cellular prefractionation prior to proteomic analysis to isolate specific subpopulations of interest. Enriched cells from in vivo samples are often very limited (<10(4) cells) and pose a significant challenge to proteomic nanoliquid chromatography mass spectrometry (nanoLCMS) sample preparation. To enable the streamlined analysis of these limited samples, we have developed an online cell enrichment, microscale sample preparation, nanoLCMS proteomics workflow by integrating fluorescence activated cell sorting (FACS), focused ultrasonication, microfluidics, immobilized trypsin digestion, and nanoLCMS. To assess the performance of the online FACS-Chip-LCMS workflow, 5000 fluorescent labeled cells were enriched from a 5% heterogeneous cell population and processed for LCMS proteomics in less than 2 h. Within these 5000 enriched cells, 30 peptides corresponding to 17 proteins spanning more than 4 orders of magnitude of cellular abundance were quantified using a QExactive MS. The results from the online FACS-Chip-LCMS workflow starting from 5000 enriched cells were directly compared to results from a traditional macroscale sample preparation workflow starting from 2.0 × 10(6) cells. The microscale FACS-Chip-LCMS workflow demonstrated high cellular enrichment efficiency and high peptide recovery across the wide dynamic range of targeted peptides. Overall the microscale FACS-Chip-LCMS workflow has shown effectiveness in efficiently preparing limited amounts of FACS enriched cells in an online manner for proteomic LCMS.

  3. Analysis and Implementation of Graph Clustering for Digital News Using Star Clustering Algorithm

    NASA Astrophysics Data System (ADS)

    Ahdi, A. B.; SW, K. R.; Herdiani, A.

    2017-01-01

    Since Web 2.0 notion emerged and is used extensively by many services in the Internet, we see an unprecedented proliferation of digital news. Those digital news is very rich in term of content and link to other news/sources but lack of category information. This make the user could not easily identify or grouping all the news that they read into set of groups. Naturally, digital news are linked data because every digital new has relation/connection with other digital news/resources. The most appropriate model for linked data is graph model. Graph model is suitable for this purpose due its flexibility in describing relation and its easy-to-understand visualization. To handle the grouping issue, we use graph clustering approach. There are many graph clustering algorithm available, such as MST Clustering, Chameleon, Makarov Clustering and Star Clustering. From all of these options, we choose Star Clustering because this algorithm is more easy-to-understand, more accurate, efficient and guarantee the quality of clusters results. In this research, we investigate the accuracy of the cluster results by comparing it with expert judgement. We got quite high accuracy level, which is 80.98% and for the cluster quality, we got promising result which is 62.87%.

  4. 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.

  5. 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

  6. IPC two-color analysis of x ray galaxy clusters

    NASA Technical Reports Server (NTRS)

    White, Raymond E., III

    1990-01-01

    The mass distributions were determined of several clusters of galaxies by using X ray surface brightness data from the Einstein Observatory Imaging Proportional Counter (IPC). Determining cluster mass distributions is important for constraining the nature of the dark matter which dominates the mass of galaxies, galaxy clusters, and the Universe. Galaxy clusters are permeated with hot gas in hydrostatic equilibrium with the gravitational potentials of the clusters. Cluster mass distributions can be determined from x ray observations of cluster gas by using the equation of hydrostatic equilibrium and knowledge of the density and temperature structure of the gas. The x ray surface brightness at some distance from the cluster is the result of the volume x ray emissivity being integrated along the line of sight in the cluster.

  7. 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…

  8. A lectin-based isolation/enrichment strategy for improved coverage of N-glycan analysis.

    PubMed

    Guan, Feng; Tan, Zengqi; Li, Xiang; Pang, Xingchen; Zhu, Yunlin; Li, Dongliang; Yang, Ganglong

    2015-10-30

    Glycomics provides an increasingly useful research tool as the genomes and proteomes of more and more animal species are elucidated. In view of the general complexity and heterogeneity of glycans, improved depth-of-coverage and sensitivity are required for glycosylation analysis. In this study, we established the lectin-based isolation/enrichment strategy for total glycomic information. Specific lectins are added onto the filter to capture corresponding glycans prior to release of N-glycans by peptide N-glycosidase F (PNGase F). Non-bound glycans and bound glycans are released and analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS), respectively. Application of the strategy to chicken ovalbumin, normal mouse mammary epithelial cells (NMuMG), and human serum resulted in detection of 5, 6, and 11 additional N-glycan structures, respectively. The strategy facilitates identification of intact N-glycans in biological samples, and can be extended to detailed analysis of O-glycome or glycoproteome.

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

    SciTech Connect

    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; Podar, Mircea; Doktycz, Mitchel J.; Pelletier, Dale A.

    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 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. Finally, comparative genomic analysis revealed unique characteristics of each SAG that could facilitate future cultivation efforts for these bacteria.

  10. 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.; ...

    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

  11. Metatranscriptomic array analysis of 'Candidatus Accumulibacter phosphatis'-enriched enhanced biological phosphorus removal sludge.

    PubMed

    He, Shaomei; Kunin, Victor; Haynes, Matthew; Martin, Hector Garcia; Ivanova, Natalia; Rohwer, Forest; Hugenholtz, Philip; McMahon, Katherine D

    2010-05-01

    Here we report the first metatranscriptomic analysis of gene expression and regulation of 'Candidatus Accumulibacter'-enriched lab-scale sludge during enhanced biological phosphorus removal (EBPR). Medium density oligonucleotide microarrays were generated with probes targeting most predicted genes hypothesized to be important for the EBPR phenotype. RNA samples were collected at the early stage of anaerobic and aerobic phases (15 min after acetate addition and switching to aeration respectively). We detected the expression of a number of genes involved in the carbon and phosphate metabolisms, as proposed by EBPR models (e.g. polyhydroxyalkanoate synthesis, a split TCA cycle through methylmalonyl-CoA pathway, and polyphosphate formation), as well as novel genes discovered through metagenomic analysis. The comparison between the early stage anaerobic and aerobic gene expression profiles showed that expression levels of most genes were not significantly different between the two stages. The majority of upregulated genes in the aerobic sample are predicted to encode functions such as transcription, translation and protein translocation, reflecting the rapid growth phase of Accumulibacter shortly after being switched to aerobic conditions. Components of the TCA cycle and machinery involved in ATP synthesis were also upregulated during the early aerobic phase. These findings support the predictions of EBPR metabolic models that the oxidation of intracellularly stored carbon polymers through the TCA cycle provides ATP for cell growth when oxygen becomes available. Nitrous oxide reductase was among the very few Accumulibacter genes upregulated in the anaerobic sample, suggesting that its expression is likely induced by the deprivation of oxygen.

  12. 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.

  13. 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.

  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. Principal Component Analysis and Cluster Analysis in Profile of Electrical System

    NASA Astrophysics Data System (ADS)

    Iswan; Garniwa, I.

    2017-03-01

    This paper propose to present approach for profile of electrical system, presented approach is combination algorithm, namely principal component analysis (PCA) and cluster analysis. Based on relevant data of gross domestic regional product and electric power and energy use. This profile is set up to show the condition of electrical system of the region, that will be used as a policy in the electrical system of spatial development in the future. This paper consider 24 region in South Sulawesi province as profile center points and use principal component analysis (PCA) to asses the regional profile for development. Cluster analysis is used to group these region into few cluster according to the new variable be produced PCA. The general planning of electrical system of South Sulawesi province can provide support for policy making of electrical system development. The future research can be added several variable into existing variable.

  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 Use of Cluster Analysis in Typological Research on Community College Students

    ERIC Educational Resources Information Center

    Bahr, Peter Riley; Bielby, Rob; House, Emily

    2011-01-01

    One useful and increasingly popular method of classifying students is known commonly as cluster analysis. The variety of techniques that comprise the cluster analytic family are intended to sort observations (for example, students) within a data set into subsets (clusters) that share similar characteristics and differ in meaningful ways from other…

  19. [Clustering Analysis of Hydatid Disease in Gansu Province].

    PubMed

    Yu, Da-wei; Ding, Guo-wu; Hou, Yan-dong; Feng, Yu; Li, Fan

    2015-08-01

    The prevalence of hydatid disease in human population and livestock, and the positive rate of echinococcal antigen in canine feces were analyzed with sample clustering method, according to the survey on hydatid disease in 72 counties in Gansu province in the database of the National Survey on Prevalence of Echinococcosis in 2012. The prevalence of hydatid disease in huma and livestock, and the positive rate of echinococcal antigen in canine feces were 0-1.59%, 0-15.22%, and 0-16.87% respectively. Clustering analysis revealed four types of prevalence in the 72 counties. The first type existed only in Dunhuang city, with the three indicators being 0.27%, 15.22% and 16.87%; the second in four counties, with the three indicators being 0.43%, 6.57% and 1.83%; the third in 22 counties, with the three indicators being 0.22%, 1.15% and 1035%; and the fourth in 45 counties, with the three indicators being 0.16%, 0.58% and 1.69%.

  20. The methodology of multi-viewpoint clustering analysis

    NASA Technical Reports Server (NTRS)

    Mehrotra, Mala; Wild, Chris

    1993-01-01

    One of the greatest challenges facing the software engineering community is the ability to produce large and complex computer systems, such as ground support systems for unmanned scientific missions, that are reliable and cost effective. In order to build and maintain these systems, it is important that the knowledge in the system be suitably abstracted, structured, and otherwise clustered in a manner which facilitates its understanding, manipulation, testing, and utilization. Development of complex mission-critical systems will require the ability to abstract overall concepts in the system at various levels of detail and to consider the system from different points of view. Multi-ViewPoint - Clustering Analysis MVP-CA methodology has been developed to provide multiple views of large, complicated systems. MVP-CA provides an ability to discover significant structures by providing an automated mechanism to structure both hierarchically (from detail to abstract) and orthogonally (from different perspectives). We propose to integrate MVP/CA into an overall software engineering life cycle to support the development and evolution of complex mission critical systems.

  1. Using n-gram analysis to cluster heartbeat signals

    PubMed Central

    2012-01-01

    Background Biological signals may carry specific characteristics that reflect basic dynamics of the body. In particular, heart beat signals carry specific signatures that are related to human physiologic mechanisms. In recent years, many researchers have shown that representations which used non-linear symbolic sequences can often reveal much hidden dynamic information. This kind of symbolization proved to be useful for predicting life-threatening cardiac diseases. Methods This paper presents an improved method called the “Adaptive Interbeat Interval Analysis (AIIA) method”. The AIIA method uses the Simple K-Means algorithm for symbolization, which offers a new way to represent subtle variations between two interbeat intervals without human intervention. After symbolization, it uses the n-gram algorithm to generate different kinds of symbolic sequences. Each symbolic sequence stands for a variation phase. Finally, the symbolic sequences are categorized by classic classifiers. Results In the experiments presented in this paper, AIIA method achieved 91% (3-gram, 26 clusters) accuracy in successfully classifying between the patients with Atrial Fibrillation (AF), Congestive Heart Failure (CHF) and healthy people. It also achieved 87% (3-gram, 26 clusters) accuracy in classifying the patients with apnea. Conclusions The two experiments presented in this paper demonstrate that AIIA method can categorize different heart diseases. Both experiments acquired the best category results when using the Bayesian Network. For future work, the concept of the AIIA method can be extended to the categorization of other physiological signals. More features can be added to improve the accuracy. PMID:22769567

  2. Fuel handling accident analysis for the University of Missouri Research Reactor's High Enriched Uranium to Low Enriched Uranium fuel conversion initiative

    NASA Astrophysics Data System (ADS)

    Rickman, Benjamin

    In accordance with the 1986 amendment concerning licenses for research and test reactors, the MU Research Reactor (MURR) is planning to convert from using High-Enriched Uranium (HEU) fuel to the use of Low-Enriched Uranium (LEU) fuel. Since the approval of a new LEU fuel that could meet the MURR's performance demands, the next phase of action for the fuel conversion process is to create a new Safety Analysis Report (SAR) with respect to the LEU fuel. A component of the SAR includes the Maximum Hypothetical Accident (MHA) and accidents that qualify under the class of Fuel Handling Accidents (FHA). In this work, the dose to occupational staff at the MURR is calculated for the FHAs. The radionuclide inventory for the proposed LEU fuel was calculated using the ORIGEN2 point-depletion code linked to the MURR neutron spectrum. The MURR spectrum was generated from a Monte Carlo Neutron transPort (MCNP) simulation. The coupling of these codes create MONTEBURNS, a time-dependent burnup code. The release fraction from each FHA within this analysis was established by the methodology of the 2006 HEU SAR, which was accepted by the NRC. The actual dose methodology was not recorded in the HEU SAR, so a conservative path was chosen. In compliance to NUREG 1537, when new methodology is used in a HEU to LEU analysis, it is necessary to re-evaluate the HEU accident. The Total Effective Dose Equivalent (TEDE) values were calculated in addition to the whole body dose and thyroid dose to operation personnel. The LEU FHA occupational TEDE dose was 349 mrem which is under the NRC regulatory occupational dose limit of 5 rem TEDE, and under the LEU MHA limit of 403 mrem. The re-evaluated HEU FHA occupational TEDE dose was 235 mrem, which is above the HEU MHA TEDE dose of 132 mrem. Since the new methodology produces a dose that is larger than the HEU MHA, we can safely assume that it is more conservative than the previous, unspecified dose.

  3. A Hierarchical Bayesian Procedure for Two-Mode Cluster Analysis

    ERIC Educational Resources Information Center

    DeSarbo, Wayne S.; Fong, Duncan K. H.; Liechty, John; Saxton, M. Kim

    2004-01-01

    This manuscript introduces a new Bayesian finite mixture methodology for the joint clustering of row and column stimuli/objects associated with two-mode asymmetric proximity, dominance, or profile data. That is, common clusters are derived which partition both the row and column stimuli/objects simultaneously into the same derived set of clusters.…

  4. 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.

  5. Cluster randomized clinical trials in orthodontics: design, analysis and reporting issues.

    PubMed

    Pandis, Nikolaos; Walsh, Tanya; Polychronopoulou, Argy; Eliades, Theodore

    2013-10-01

    Cluster randomized trials (CRTs) use as the unit of randomization clusters, which are usually defined as a collection of individuals sharing some common characteristics. Common examples of clusters include entire dental practices, hospitals, schools, school classes, villages, and towns. Additionally, several measurements (repeated measurements) taken on the same individual at different time points are also considered to be clusters. In dentistry, CRTs are applicable as patients may be treated as clusters containing several individual teeth. CRTs require certain methodological procedures during sample calculation, randomization, data analysis, and reporting, which are often ignored in dental research publications. In general, due to similarity of the observations within clusters, each individual within a cluster provides less information compared with an individual in a non-clustered trial. Therefore, clustered designs require larger sample sizes compared with non-clustered randomized designs, and special statistical analyses that account for the fact that observations within clusters are correlated. It is the purpose of this article to highlight with relevant examples the important methodological characteristics of cluster randomized designs as they may be applied in orthodontics and to explain the problems that may arise if clustered observations are erroneously treated and analysed as independent (non-clustered).

  6. High-resolution synchrotron X-ray analysis of bioglass-enriched hydrogels.

    PubMed

    Gorodzha, Svetlana; Douglas, Timothy E L; Samal, Sangram K; Detsch, Rainer; Cholewa-Kowalska, Katarzyna; Braeckmans, Kevin; Boccaccini, Aldo R; Skirtach, Andre G; Weinhardt, Venera; Baumbach, Tilo; Surmeneva, Maria A; Surmenev, Roman A

    2016-05-01

    Enrichment of hydrogels with inorganic particles improves their suitability for bone regeneration by enhancing their mechanical properties, mineralizability, and bioactivity as well as adhesion, proliferation, and differentiation of bone-forming cells, while maintaining injectability. Low aggregation and homogeneous distribution maximize particle surface area, promoting mineralization, cell-particle interactions, and homogenous tissue regeneration. Hence, determination of the size and distribution of particles/particle agglomerates in the hydrogel is desirable. Commonly used techniques have drawbacks. High-resolution techniques (e.g., SEM) require drying. Distribution in the dry state is not representative of the wet state. Techniques in the wet state (histology, µCT) are of lower resolution. Here, self-gelling, injectable composites of Gellan Gum (GG) hydrogel and two different types of sol-gel-derived bioactive glass (bioglass) particles were analyzed in the wet state using Synchrotron X-ray radiation, enabling high-resolution determination of particle size and spatial distribution. The lower detection limit volume was 9 × 10(-5) mm(3) . Bioglass particle suspensions were also studied using zeta potential measurements and Coulter analysis. Aggregation of bioglass particles in the GG hydrogels occurred and aggregate distribution was inhomogeneous. Bioglass promoted attachment of rat mesenchymal stem cells (rMSC) and mineralization.

  7. 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.

  8. 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.

  9. Independent Component Analysis to Detect Clustered Microcalcification Breast Cancers

    PubMed Central

    Gallardo-Caballero, R.; García-Orellana, C. J.; García-Manso, A.; González-Velasco, H. M.; Macías-Macías, M.

    2012-01-01

    The presence of clustered microcalcifications is one of the earliest signs in breast cancer detection. Although there exist many studies broaching this problem, most of them are nonreproducible due to the use of proprietary image datasets. We use a known subset of the currently largest publicly available mammography database, the Digital Database for Screening Mammography (DDSM), to develop a computer-aided detection system that outperforms the current reproducible studies on the same mammogram set. This proposal is mainly based on the use of extracted image features obtained by independent component analysis, but we also study the inclusion of the patient's age as a nonimage feature which requires no human expertise. Our system achieves an average of 2.55 false positives per image at a sensitivity of 81.8% and 4.45 at a sensitivity of 91.8% in diagnosing the BCRP_CALC_1 subset of DDSM. PMID:22654626

  10. Ultrafast dynamics in atomic clusters: Analysis and control

    PubMed Central

    Bonačić-Koutecký, Vlasta; Mitrić, Roland; Werner, Ute; Wöste, Ludger; Berry, R. Stephen

    2006-01-01

    We present a study of dynamics and ultrafast observables in the frame of pump–probe negative-to-neutral-to-positive ion (NeNePo) spectroscopy illustrated by the examples of bimetallic trimers Ag2Au−/Ag2Au/Ag2Au+ and silver oxides Ag3O2−/Ag3O2/Ag3O2+ in the context of cluster reactivity. First principle multistate adiabatic dynamics allows us to determine time scales of different ultrafast processes and conditions under which these processes can be experimentally observed. Furthermore, we present a strategy for optimal pump–dump control in complex systems based on the ab initio Wigner distribution approach and apply it to tailor laser fields for selective control of the isomerization process in Na3F2. The shapes of pulses can be assigned to underlying processes, and therefore control can be used as a tool for analysis. PMID:16740664

  11. Archetypal TRMM Radar Profiles Identified Through Cluster Analysis

    NASA Technical Reports Server (NTRS)

    Boccippio, Dennis J.

    2003-01-01

    It is widely held that identifiable 'convective regimes' exist in nature, although precise definitions of these are elusive. Examples include land / Ocean distinctions, break / monsoon beahvior, seasonal differences in the Amazon (SON vs DJF), etc. These regimes are often described by differences in the realized local convective spectra, and measured by various metrics of convective intensity, depth, areal coverage and rainfall amount. Objective regime identification may be valuable in several ways: regimes may serve as natural 'branch points' in satellite retrieval algorithms or data assimilation efforts; one example might be objective identification of regions that 'should' share a similar 2-R relationship. Similarly, objectively defined regimes may provide guidance on optimal siting of ground validation efforts. Objectively defined regimes could also serve as natural (rather than arbitrary geographic) domain 'controls' in studies of convective response to environmental forcing. Quantification of convective vertical structure has traditionally involved parametric study of prescribed quantities thought to be important to convective dynamics: maximum radar reflectivity, cloud top height, 30-35 dBZ echo top height, rain rate, etc. Individually, these parameters are somewhat deficient as their interpretation is often nonunique (the same metric value may signify different physics in different storm realizations). Individual metrics also fail to capture the coherence and interrelationships between vertical levels available in full 3-D radar datasets. An alternative approach is discovery of natural partitions of vertical structure in a globally representative dataset, or 'archetypal' reflectivity profiles. In this study, this is accomplished through cluster analysis of a very large sample (0[107) of TRMM-PR reflectivity columns. Once achieved, the rainconditional and unconditional 'mix' of archetypal profile types in a given location and/or season provides a description

  12. Genomic-Bioinformatic Analysis of Transcripts Enriched in the Third-Stage Larva of the Parasitic Nematode Ascaris suum

    PubMed Central

    Huang, Cui-Qin; Gasser, Robin B.; Cantacessi, Cinzia; Nisbet, Alasdair J.; Zhong, Weiwei; Sternberg, Paul W.; Loukas, Alex; Mulvenna, Jason; Lin, Rui-Qing; Chen, Ning; Zhu, Xing-Quan

    2008-01-01

    Differential transcription in Ascaris suum was investigated using a genomic-bioinformatic approach. A cDNA archive enriched for molecules in the infective third-stage larva (L3) of A. suum was constructed by suppressive-subtractive hybridization (SSH), and a subset of cDNAs from 3075 clones subjected to microarray analysis using cDNA probes derived from RNA from different developmental stages of A. suum. The cDNAs (n = 498) shown by microarray analysis to be enriched in the L3 were sequenced and subjected to bioinformatic analyses using a semi-automated pipeline (ESTExplorer). Using gene ontology (GO), 235 of these molecules were assigned to ‘biological process’ (n = 68), ‘cellular component’ (n = 50), or ‘molecular function’ (n = 117). Of the 91 clusters assembled, 56 molecules (61.5%) had homologues/orthologues in the free-living nematodes Caenorhabditis elegans and C. briggsae and/or other organisms, whereas 35 (38.5%) had no significant similarity to any sequences available in current gene databases. Transcripts encoding protein kinases, protein phosphatases (and their precursors), and enolases were abundantly represented in the L3 of A. suum, as were molecules involved in cellular processes, such as ubiquitination and proteasome function, gene transcription, protein–protein interactions, and function. In silico analyses inferred the C. elegans orthologues/homologues (n = 50) to be involved in apoptosis and insulin signaling (2%), ATP synthesis (2%), carbon metabolism (6%), fatty acid biosynthesis (2%), gap junction (2%), glucose metabolism (6%), or porphyrin metabolism (2%), although 34 (68%) of them could not be mapped to a specific metabolic pathway. Small numbers of these 50 molecules were predicted to be secreted (10%), anchored (2%), and/or transmembrane (12%) proteins. Functionally, 17 (34%) of them were predicted to be associated with (non-wild-type) RNAi phenotypes in C. elegans, the majority being embryonic lethality

  13. 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

  14. 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

  15. Heavy metal enrichment in the seagrasses of Lakshadweep group of islands--a multivariate statistical analysis.

    PubMed

    Thangaradjou, T; Raja, S; Subhashini, Pon; Nobi, E P; Dilipan, E

    2013-01-01

    An assessment on heavy metal (Al, Cd, Co, Cr, Cu, Fe, Mg, Mn, Ni, Pb and Zn) accumulation by seven seagrass species of Lakshadweep group of islands was carried out using multivariate statistical tools like principal component analysis (PCA) and cluster analysis (CA). Among all the metals, Mg and Al were determined in higher concentration in all the seagrasses, and their values varied with respect to different seagrass species. The concentration of the four toxic heavy metals (Cd, Pb, Zn and Cu) was found higher in all the seagrasses when compared with the background values of seagrasses from Flores Sea, Indonesia. The contamination factor of these four heavy metals ranged as Cd (1.97-12.5), Cu (0.73-4.40), Pb (2.3-8.89) and Zn (1.27-2.787). In general, the Pollution Load Index (PLI) calculated was found to be maximum for Halophila decipiens (58.2). Results revealed that Halophila decipiens is a strong accumulator of heavy metals, followed by Halodule uninervis and Halodule pinifolia, among all the tested seagrasses. Interestingly, the small-leaved seagrasses were found to be efficient in heavy metal accumulation than the large-leaved seagrass species. Thus, seagrasses can better be used for biomonitoring, and seagrasses can be used as the heavy metal sink as the biomass take usually long term to get remineralize in nature.

  16. 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.

  17. A combined multidimensional scaling and hierarchical clustering view for the exploratory analysis of multidimensional data

    NASA Astrophysics Data System (ADS)

    Craig, Paul; Roa-Seïler, Néna

    2013-01-01

    This paper describes a novel information visualization technique that combines multidimensional scaling and hierarchical clustering to support the exploratory analysis of multidimensional data. The technique displays the results of multidimensional scaling using a scatter plot where the proximity of any two items' representations is approximate to their similarity according to a Euclidean distance metric. The results of hierarchical clustering are overlaid onto this view by drawing smoothed outlines around each nested cluster. The difference in similarity between successive cluster combinations is used to colour code clusters and make stronger natural clusters more prominent in the display. When a cluster or group of items is selected, multidimensional scaling and hierarchical clustering are re-applied to a filtered subset of the data, and animation is used to smooth the transition between successive filtered views. As a case study we demonstrate the technique being used to analyse survey data relating to the appropriateness of different phrases to different emotionally charged situations.

  18. Surface Analysis of Stratospheric Particles with TOF-SIMS: Bromine Enrichments Due to Contamination

    NASA Astrophysics Data System (ADS)

    Stephan, T.; Rost, D.; Jessberger, E. K.

    1995-09-01

    Volatile element enrichments compared to CI abundances in stratospheric interplanetary dust particles especially for Br have been interpreted as due to atmospheric contamination processes [1] or, less substantiated, as being indicative for a new type of chondritic material [2, 3]. Although only little is known about the actual Br concentration in the stratosphere, it is well accepted that halogens play an important role in stratospheric chemistry and therefore contamination processes have to be excluded before a Br-rich chondritic parent body can be speculated on. The analysis of the lateral distribution of halogens in IDPs with high-resolution imaging TOF-SIMS (time-of-flight secondary-ion-mass-spectrometry) [4] may help to solve the controversy about the ubiquity of Br in stratospheric IDPs. Besides controversially discussed theoretical models which try to test correlations between Br-content and stratospheric residence time or surface areas [5, 6, 7], first observational hints for halogen contamination of at least two chondritic IDPs were found for W7029E5, where Br- salt nanocrystals of presumably atmospheric origin were observed [5], and for L2006G1, which showed a halogen-rich exterior rim [8]. TOF-SIMS with its extremely high surface sensitivity -- the information depth is in the order of a few atomic monolayers -- seems to be suitable for a systematic search for surface correlated halogens in IDPs. Although, in general, plane surfaces are required for TOF-SIMS measurements, particle analysis is possible with this technique [9], though quantification is highly complicated due to topographic effects on secondary ion production and detection probability. We analyzed five stratospheric particles from small area collector U2071 which were previously investigated with SEM-EDX [10]. Silicone oil on the surfaces of some particles could still be detected with TOF-SIMS, even after extensive hexane rinsing. In three cases (chondritic particles U2071B7a, F3, and H1a

  19. Cluster analysis of indermediate deep events in the southeastern Aegean

    NASA Astrophysics Data System (ADS)

    Ruscic, Marija; Becker, Dirk; Brüstle, Andrea; Meier, Thomas

    2015-04-01

    The Hellenic subduction zone (HSZ) is the seismically most active region in Europe where the oceanic African litosphere is subducting beneath the continental Aegean plate. Although there are numerous studies of seismicity in the HSZ, very few focus on the eastern HSZ and the Wadati-Benioff-Zone of the subducting slab in that part of the HSZ. In order to gain a better understanding of the geodynamic processes in the region a dense local seismic network is required. From September 2005 to March 2007, the temporary seismic network EGELADOS has been deployed covering the entire HSZ. It consisted of 56 onshore and 23 offshore broadband stations with addition of 19 stations from GEOFON, NOA and MedNet to complete the network. Here, we focus on a cluster of intermediate deep seismicity recorded by the EGELADOS network within the subducting African slab in the region of the Nysiros volcano. The cluster consists of 159 events at 80 to 190 km depth with magnitudes between 0.2 and 4.1 that were located using nonlinear location tool NonLinLoc. A double-difference earthquake relocation using the HypoDD software is performed with both manual readings of onset times and differential traveltimes obtained by separate cross correlation of P- and S-waveforms. Single event locations are compared to relative relocations. The event hypocenters fall into a thin zone close to the top of the slab defining its geometry with an accuracy of a few kilometers. At intermediate depth the slab is dipping towards the NW at an angle of about 30°. That means it is dipping steeper than in the western part of the HSZ. The edge of the slab is clearly defined by an abrupt disappearance of intermediate depths seismicity towards the NE. It is found approximately beneath the Turkish coastline. Furthermore, results of a cluster analysis based on the cross correlation of three-component waveforms are shown as a function of frequency and the spatio-temporal migration of the seismic activity is analysed.

  20. 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.

  1. Adapting Spectral Co-clustering to Documents and Terms Using Latent Semantic Analysis

    NASA Astrophysics Data System (ADS)

    Park, Laurence A. F.; Leckie, Christopher A.; Ramamohanarao, Kotagiri; Bezdek, James C.

    Spectral co-clustering is a generic method of computing co-clusters of relational data, such as sets of documents and their terms. Latent semantic analysis is a method of document and term smoothing that can assist in the information retrieval process. In this article we examine the process behind spectral clustering for documents and terms, and compare it to Latent Semantic Analysis. We show that both spectral co-clustering and LSA follow the same process, using different normalisation schemes and metrics. By combining the properties of the two co-clustering methods, we obtain an improved co-clustering method for document-term relational data that provides an increase in the cluster quality of 33.0%.

  2. Cluster analysis of long time-series medical datasets

    NASA Astrophysics Data System (ADS)

    Hirano, Shoji; Tsumoto, Shusaku

    2004-04-01

    This paper presents a comparative study about the characteristics of clustering methods for inhomogeneous time-series medical datasets. Using various combinations of comparison methods and grouping methods, we performed clustering experiments of the hepatitis data set and evaluated validity of the results. The results suggested that (1) complete-linkage (CL) criterion in agglomerative hierarchical clustering (AHC) outperformed average-linkage (AL) criterion in terms of the interpretability of a dendrogram and clustering results, (2) combination of dynamic time warping (DTW) and CL-AHC constantly produced interpretable results, (3) combination of DTW and rough clustering (RC) would be used to find the core sequences of the clusters, (4) multiscale matching may suffer from the treatment of 'no-match' pairs, however, the problem may be eluded by using RC as a subsequent grouping method.

  3. 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.

  4. 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

  5. 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

  6. 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.

  7. 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)

  8. 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.

  9. Leukaemia clusters in childhood: geographical analysis in Britain.

    PubMed Central

    Knox, E G

    1994-01-01

    STUDY OBJECTIVE--To validate previously demonstrated spatial clustering of childhood leukaemias by showing relative proximities of selected map features to cluster locations, compared with control locations. If clusters are real, then they are likely to be close to a determining hazard. DESIGN--Cluster postcode loci and partially matched control postcodes were compared in terms of distances to railways, main roads, churches, surface water, woodland areas, and railside industrial installations. Further supporting comparisons between non-clustered cases and random postcode controls with those map features representable as single grid points were made. SETTING--England, Wales, and Scotland 1966-83. SUBJECTS--Grid referenced registrations of 9406 childhood leukaemias and non-Hodgkin's lymphomas, including 264 pairs (or more) separated by < 150 m, and grid references of random postcodes in equal numbers. MAIN RESULTS--The 264 clusters showed relative proximities (or the inverse) to several map features, of which the most powerful was an association with railways. The non-railway associations seemed to be statistically indirect. Some railside industrial installations, identified from a railway atlas, also showed relative proximities to leukaemia clusters, as well as to non-clustered cases, but did not "explain" the railway effect. These installations, with seemingly independent geographical associations, included oil refineries, petrochemical plants, oil storage and oil distribution depots, power stations, and steelworks. CONCLUSIONS--The previously shown childhood leukaemia clusters are confirmed to be non-random through their systematic associations with certain map features when compared with the control locations. The common patterns of close association of clustered and non-clustered cases imply a common aetiological component arising from a common environmental hazard--namely the use of fossil fuels, especially petroleum. PMID:7964336

  10. PAPE (Prefractionation-Assisted Phosphoprotein Enrichment): A Novel Approach for Phosphoproteomic Analysis of Green Tissues from Plants

    PubMed Central

    Lassowskat, Ines; Naumann, Kai; Lee, Justin; Scheel, Dierk

    2013-01-01

    Phosphorylation is an important post-translational protein modification with regulatory roles in diverse cellular signaling pathways. Despite recent advances in mass spectrometry, the detection of phosphoproteins involved in signaling is still challenging, as protein phosphorylation is typically transient and/or occurs at low levels. In green plant tissues, the presence of highly abundant proteins, such as the subunits of the RuBisCO complex, further complicates phosphoprotein analysis. Here, we describe a simple, but powerful, method, which we named prefractionation-assisted phosphoprotein enrichment (PAPE), to increase the yield of phosphoproteins from Arabidopsis thaliana leaf material. The first step, a prefractionation via ammonium sulfate precipitation, not only depleted RuBisCO almost completely, but, serendipitously, also served as an efficient phosphoprotein enrichment step. When coupled with a subsequent metal oxide affinity chromatography (MOAC) step, the phosphoprotein content was highly enriched. The reproducibility and efficiency of phosphoprotein enrichment was verified by phospho-specific staining and, further, by mass spectrometry, where it could be shown that the final PAPE fraction contained a significant number of known and additionally novel (potential) phosphoproteins. Hence, this facile two-step procedure is a good prerequisite to probe the phosphoproteome and gain deeper insight into plant phosphorylation-based signaling events. PMID:28250405

  11. Segmenting Business Students Using Cluster Analysis Applied to Student Satisfaction Survey Results

    ERIC Educational Resources Information Center

    Gibson, Allen

    2009-01-01

    This paper demonstrates a new application of cluster analysis to segment business school students according to their degree of satisfaction with various aspects of the academic program. The resulting clusters provide additional insight into drivers of student satisfaction that are not evident from analysis of the responses of the student body as a…

  12. Cluster Analysis of the Luria-Nebraska Neuropsychological Battery with Learning Disabled Adults.

    ERIC Educational Resources Information Center

    McCue, Michael; And Others

    The study reports a cluster analysis of Luria-Nebraska Neuropsychological Battery sources of 25 learning disabled adults. The cluster analysis suggested the presence of three subgroups within this sample, one having high elevations on the Rhythm, Writing, Reading, and Arithmetic Rhythm scales, the second having an extremely high evelation on the…

  13. Cluster Analysis as a Method of Recovering Types of Intraindividual Growth Trajectories: A Monte Carlo Study.

    ERIC Educational Resources Information Center

    Dumenci, Levent; Windle, Michael

    2001-01-01

    Used Monte Carlo methods to evaluate the adequacy of cluster analysis to recover group membership based on simulated latent growth curve (LCG) models. Cluster analysis failed to recover growth subtypes adequately when the difference between growth curves was shape only. Discusses circumstances under which it was more successful. (SLD)

  14. 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…

  15. 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…

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

    SciTech Connect

    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.

  17. 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…

  18. 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…

  19. 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.

  20. Boundaries, links and clusters: a new paradigm in spatial analysis?

    PubMed Central

    Jacquez, Geoff M.; Kaufmann, Andy; Goovaerts, Pierre

    2008-01-01

    This paper develops and applies new techniques for the simultaneous detection of boundaries and clusters within a probabilistic framework. The new statistic “little b” (written bij) evaluates boundaries between adjacent areas with different values, as well as links between adjacent areas with similar values. Clusters of high values (hotspots) and low values (coldspots) are then constructed by joining areas abutting locations that are significantly high (e.g., an unusually high disease rate) and that are connected through a “link” such that the values in the adjoining areas are not significantly different. Two techniques are proposed and evaluated for accomplishing cluster construction: “big B” and the “ladder” approach. We compare the statistical power and empirical Type I and Type II error of these approaches to those of wombling and the local Moran test. Significance may be evaluated using distribution theory based on the product of two continuous (e.g., non-discrete) variables. We also provide a “distribution free” algorithm based on resampling of the observed values. The methods are applied to simulated data for which the locations of boundaries and clusters is known, and compared and contrasted with clusters found using the local Moran statistic and with polygon Womble boundaries. The little b approach to boundary detection is comparable to polygon wombling in terms of Type I error, Type II error and empirical statistical power. For cluster detection, both the big B and ladder approaches have lower Type I and Type II error and are more powerful than the local Moran statistic. The new methods are not constrained to find clusters of a pre-specified shape, such as circles, ellipses and donuts, and yield a more accurate description of geographic variation than alternative cluster tests that presuppose a specific cluster shape. We recommend these techniques over existing cluster and boundary detection methods that do not provide such a

  1. Boundaries, links and clusters: a new paradigm in spatial analysis?

    PubMed

    Jacquez, Geoff M; Kaufmann, Andy; Goovaerts, Pierre

    2008-12-01

    This paper develops and applies new techniques for the simultaneous detection of boundaries and clusters within a probabilistic framework. The new statistic "little b" (written b(ij)) evaluates boundaries between adjacent areas with different values, as well as links between adjacent areas with similar values. Clusters of high values (hotspots) and low values (coldspots) are then constructed by joining areas abutting locations that are significantly high (e.g., an unusually high disease rate) and that are connected through a "link" such that the values in the adjoining areas are not significantly different. Two techniques are proposed and evaluated for accomplishing cluster construction: "big B" and the "ladder" approach. We compare the statistical power and empirical Type I and Type II error of these approaches to those of wombling and the local Moran test. Significance may be evaluated using distribution theory based on the product of two continuous (e.g., non-discrete) variables. We also provide a "distribution free" algorithm based on resampling of the observed values. The methods are applied to simulated data for which the locations of boundaries and clusters is known, and compared and contrasted with clusters found using the local Moran statistic and with polygon Womble boundaries. The little b approach to boundary detection is comparable to polygon wombling in terms of Type I error, Type II error and empirical statistical power. For cluster detection, both the big B and ladder approaches have lower Type I and Type II error and are more powerful than the local Moran statistic. The new methods are not constrained to find clusters of a pre-specified shape, such as circles, ellipses and donuts, and yield a more accurate description of geographic variation than alternative cluster tests that presuppose a specific cluster shape. We recommend these techniques over existing cluster and boundary detection methods that do not provide such a comprehensive description

  2. Integrating molecular QTL data into genome-wide genetic association analysis: Probabilistic assessment of enrichment and colocalization

    PubMed Central

    2017-01-01

    We propose a novel statistical framework for integrating the result from molecular quantitative trait loci (QTL) mapping into genome-wide genetic association analysis of complex traits, with the primary objectives of quantitatively assessing the enrichment of the molecular QTLs in complex trait-associated genetic variants and the colocalizations of the two types of association signals. We introduce a natural Bayesian hierarchical model that treats the latent association status of molecular QTLs as SNP-level annotations for candidate SNPs of complex traits. We detail a computational procedure to seamlessly perform enrichment, fine-mapping and colocalization analyses, which is a distinct feature compared to the existing colocalization analysis procedures in the literature. The proposed approach is computationally efficient and requires only summary-level statistics. We evaluate and demonstrate the proposed computational approach through extensive simulation studies and analyses of blood lipid data and the whole blood eQTL data from the GTEx project. In addition, a useful utility from our proposed method enables the computation of expected colocalization signals using simple characteristics of the association data. Using this utility, we further illustrate the importance of enrichment analysis on the ability to discover colocalized signals and the potential limitations of currently available molecular QTL data. The software pipeline that implements the proposed computation procedures, enloc, is freely available at https://github.com/xqwen/integrative. PMID:28278150

  3. 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...

  4. Spectral cathodoluminescence analysis of hymenopteran mandibles with different levels of zinc enrichment in their teeth.

    PubMed

    Jorge, Alberto; Polidori, Carlo; Garcia-Guinea, Javier; Nieves-Aldrey, José Luis

    2017-01-01

    The inclusion of Zn in insect mandibles affects their hardness and is functional to their use during feeding or reproducing. However, little is known on the chemical/structural base of Zn enrichment. Here, we found that cathodoluminescence (CL) technique revealed two different types of CL spectra in the mandibles of Hymenoptera, depending on the Zn enrichment level assessed by Energy Dispersive X-ray Spectroscopy (EDS). Individuals having negligible traces to low % of Zn in their mandible teeth (≤3 wt%) presented a wide band of luminescence in the visible range which resembled those observed in the CC structures of graphite. This spectrum is probably characteristic for un-enriched cuticle, since it did not differ from those obtained from the Zn-lacking inner part of mandibles. Individuals with moderate to high % of Zn in their mandible teeth (≥7 wt%), instead, presented additional CL peaks in the ultraviolet range. Comparisons with different minerals of Zn suggest that these peaks could be related with OZnO bonds, with hydroxyl groups and with zinc-chlorine links (in agreement with Cl high levels detected by the EDS). Being a non-destructive technique, CL allows large comparative studies of the chemistry of metal-enriched insect cuticle even using unique specimens, such as those deposited in Natural History Museums.

  5. Fully Automated Operational Modal Analysis using multi-stage clustering

    NASA Astrophysics Data System (ADS)

    Neu, Eugen; Janser, Frank; Khatibi, Akbar A.; Orifici, Adrian C.

    2017-02-01

    The interest for robust automatic modal parameter extraction techniques has increased significantly over the last years, together with the rising demand for continuous health monitoring of critical infrastructure like bridges, buildings and wind turbine blades. In this study a novel, multi-stage clustering approach for Automated Operational Modal Analysis (AOMA) is introduced. In contrast to existing approaches, the procedure works without any user-provided thresholds, is applicable within large system order ranges, can be used with very small sensor numbers and does not place any limitations on the damping ratio or the complexity of the system under investigation. The approach works with any parametric system identification algorithm that uses the system order n as sole parameter. Here a data-driven Stochastic Subspace Identification (SSI) method is used. Measurements from a wind tunnel investigation with a composite cantilever equipped with Fiber Bragg Grating Sensors (FBGSs) and piezoelectric sensors are used to assess the performance of the algorithm with a highly damped structure and low signal to noise ratio conditions. The proposed method was able to identify all physical system modes in the investigated frequency range from over 1000 individual datasets using FBGSs under challenging signal to noise ratio conditions and under better signal conditions but from only two sensors.

  6. Subsets in psoriatic arthritis formed by cluster analysis.

    PubMed

    Koó, T; Nagy, Z; Seszták, M; Ujfalussy, I; Merétey, K; Böhm, U; Forgács, S; Szilágyi, M; Czirják, L; Farkas, V

    2001-01-01

    The aim of the study was to create subgroups among psoriatic arthritis patients on the basis of dermatological features, clinical pattern of arthritis, and laboratory, immunological and radiological findings. Data on 100 patients were expressed in a standardised form and entered into hierarchical cluster analysis according to Ward's method. Seven subgroups were created. Fifty-six patients with mild psoriasis were sorted into a 'polyarticular group'. Two 'RA-like groups' were formed, differing from each other serologically and in axial involvement. In an 'oligoarticular group' (18 patients) serious skin disease and female gender predominancy were found to be characteristic. Eight patients with polyarticular arthritis were assigned to an 'erythrodermal group', in which polyarticular arthritis, mutilating, severe arthritis and a history of erythroderma were characteristic. Close to this group on the dendrogram eight women were sorted into a 'distal form'. Sausage fingers were frequent, and nail dystrophy was present in every case. In a 'pustular group' (three patients) the different type of skin involvement was considered and nail dystrophy was common. In the newly created subgroups not only the arthritic status, but also the type of the skin disease, played a determining role.

  7. Cluster analysis of Scedosporium boydii infections in a single hospital.

    PubMed

    Bernhardt, Anne; Seibold, Michael; Rickerts, Volker; Tintelnot, Kathrin

    2015-10-01

    Scedosporiosis is a rare, but often fatal mycotic infection occurring in immunosuppressed as well as in immunocompetent patients. Over a period of 14 months, Scedosporium boydii isolates were sent to our reference laboratory from six immunocompetent patients treated at a single hospital in Germany. In analogy to the EORTC/MSG criteria, four patients were classified as proven invasive scedosporiosis cases, and two patients as probable or possible cases. Of note, in five patients scedosporiosis was diagnosed between 1 and 14 months (median 5.0 months) after cardiac surgery. Despite antimycotic treatment two patients died, and three were lost for long-term follow-up. All clinical S. boydii isolates were characterized by molecular analysis using multilocus sequence typing (MLST). An identical MLST type was found in five patients who had been treated in the surgery unit, suggesting a link between these infections. The source of S. boydii has not been identified. Within an observation period of 2 years before and after this cluster of infections no further cases of scedosporiosis were reported from this hospital.

  8. Publication Bias Currently Makes an Accurate Estimate of the Benefits of Enrichment Programs Difficult: A Postmortem of Two Meta-Analyses Using Statistical Power Analysis

    ERIC Educational Resources Information Center

    Warne, Russell T.

    2016-01-01

    Recently Kim (2016) published a meta-analysis on the effects of enrichment programs for gifted students. She found that these programs produced substantial effects for academic achievement (g = 0.96) and socioemotional outcomes (g = 0.55). However, given current theory and empirical research these estimates of the benefits of enrichment programs…

  9. 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.

  10. Modest validity and fair reproducibility of dietary patterns derived by cluster analysis.

    PubMed

    Funtikova, Anna N; Benítez-Arciniega, Alejandra A; Fitó, Montserrat; Schröder, Helmut

    2015-03-01

    Cluster analysis is widely used to analyze dietary patterns. We aimed to analyze the validity and reproducibility of the dietary patterns defined by cluster analysis derived from a food frequency questionnaire (FFQ). We hypothesized that the dietary patterns derived by cluster analysis have fair to modest reproducibility and validity. Dietary data were collected from 107 individuals from population-based survey, by an FFQ at baseline (FFQ1) and after 1 year (FFQ2), and by twelve 24-hour dietary recalls (24-HDR). Repeatability and validity were measured by comparing clusters obtained by the FFQ1 and FFQ2 and by the FFQ2 and 24-HDR (reference method), respectively. Cluster analysis identified a "fruits & vegetables" and a "meat" pattern in each dietary data source. Cluster membership was concordant for 66.7% of participants in FFQ1 and FFQ2 (reproducibility), and for 67.0% in FFQ2 and 24-HDR (validity). Spearman correlation analysis showed reasonable reproducibility, especially in the "fruits & vegetables" pattern, and lower validity also especially in the "fruits & vegetables" pattern. κ statistic revealed a fair validity and reproducibility of clusters. Our findings indicate a reasonable reproducibility and fair to modest validity of dietary patterns derived by cluster analysis.

  11. Poisson approach to clustering analysis of regulatory sequences.

    PubMed

    Wang, Haiying; Zheng, Huiru; Hu, Jinglu

    2008-01-01

    The presence of similar patterns in regulatory sequences may aid users in identifying co-regulated genes or inferring regulatory modules. By modelling pattern occurrences in regulatory regions with Poisson statistics, this paper presents a log likelihood ratio statistics-based distance measure to calculate pair-wise similarities between regulatory sequences. We employed it within three clustering algorithms: hierarchical clustering, Self-Organising Map, and a self-adaptive neural network. The results indicate that, in comparison to traditional clustering algorithms, the incorporation of the log likelihood ratio statistics-based distance into the learning process may offer considerable improvements in the process of regulatory sequence-based classification of genes.

  12. "Follow the leader": a centrality guided clustering and its application to social network analysis.

    PubMed

    Wu, Qin; Qi, Xingqin; Fuller, Eddie; Zhang, Cun-Quan

    2013-01-01

    Within graph theory and network analysis, centrality of a vertex measures the relative importance of a vertex within a graph. The centrality plays key role in network analysis and has been widely studied using different methods. Inspired by the idea of vertex centrality, a novel centrality guided clustering (CGC) is proposed in this paper. Different from traditional clustering methods which usually choose the initial center of a cluster randomly, the CGC clustering algorithm starts from a "LEADER"--a vertex with the highest centrality score--and a new "member" is added into the same cluster as the "LEADER" when some criterion is satisfied. The CGC algorithm also supports overlapping membership. Experiments on three benchmark social network data sets are presented and the results indicate that the proposed CGC algorithm works well in social network clustering.

  13. [Principal component analysis and cluster analysis of inorganic elements in sea cucumber Apostichopus japonicus].

    PubMed

    Liu, Xiao-Fang; Xue, Chang-Hu; Wang, Yu-Ming; Li, Zhao-Jie; Xue, Yong; Xu, Jie

    2011-11-01

    The present study is to investigate the feasibility of multi-elements analysis in determination of the geographical origin of sea cucumber Apostichopus japonicus, and to make choice of the effective tracers in sea cucumber Apostichopus japonicus geographical origin assessment. The content of the elements such as Al, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Mo, Cd, Hg and Pb in sea cucumber Apostichopus japonicus samples from seven places of geographical origin were determined by means of ICP-MS. The results were used for the development of elements database. Cluster analysis(CA) and principal component analysis (PCA) were applied to differentiate the sea cucumber Apostichopus japonicus geographical origin. Three principal components which accounted for over 89% of the total variance were extracted from the standardized data. The results of Q-type cluster analysis showed that the 26 samples could be clustered reasonably into five groups, the classification results were significantly associated with the marine distribution of the sea cucumber Apostichopus japonicus samples. The CA and PCA were the effective methods for elements analysis of sea cucumber Apostichopus japonicus samples. The content of the mineral elements in sea cucumber Apostichopus japonicus samples was good chemical descriptors for differentiating their geographical origins.

  14. Quality assessment of cortex cinnamomi by HPLC chemical fingerprint, principle component analysis and cluster analysis.

    PubMed

    Yang, Jie; Chen, Li-Hong; Zhang, Qin; Lai, Mao-Xiang; Wang, Qiang

    2007-06-01

    HPLC fingerprint analysis, principle component analysis (PCA), and cluster analysis were introduced for quality assessment of Cortex cinnamomi (CC). The fingerprint of CC was developed and validated by analyzing 30 samples of CC from different species and geographic locations. Seventeen chromatographic peaks were selected as characteristic peaks and their relative peak areas (RPA) were calculated for quantitative expression of the HPLC fingerprints. The correlation coefficients of similarity in chromatograms were higher than 0.95 for the same species while much lower than 0.6 for different species. Besides, two principal components (PCs) have been extracted by PCA. PC1 separated Cinnamomum cassia from other species, capturing 56.75% of variance while PC2 contributed for their further separation, capturing 19.08% variance. The scores of the samples showed that the samples could be clustered reasonably into different groups corresponding to different species and different regions. The scores and loading plots together revealed different chemical properties of each group clearly. The cluster analysis confirmed the results of PCA analysis. Therefore, HPLC fingerprint in combination with chemometric techniques provide a very flexible and reliable method for quality assessment of traditional Chinese medicines.

  15. Critical clusters in interdependent economic sectors. A data-driven spectral clustering analysis

    NASA Astrophysics Data System (ADS)

    Oliva, Gabriele; Setola, Roberto; Panzieri, Stefano

    2016-10-01

    In this paper we develop a data-driven hierarchical clustering methodology to group the economic sectors of a country in order to highlight strongly coupled groups that are weakly coupled with other groups. Specifically, we consider an input-output representation of the coupling among the sectors and we interpret the relation among sectors as a directed graph; then we recursively apply the spectral clustering methodology over the graph, without a priori information on the number of groups that have to be obtained. In order to do this, we resort to the eigengap criterion, where a suitable number of groups is selected automatically based on the intensity and structure of the coupling among the sectors. We validate the proposed methodology considering a case study for Italy, inspecting how the coupling among clusters and sectors changes from the year 1995 to 2011, showing that in the years the Italian structure underwent deep changes, becoming more and more interdependent, i.e., a large part of the economy has become tightly coupled.

  16. Bivariate Mixed Effects Analysis of Clustered Data with Large Cluster Sizes.

    PubMed

    Zhang, Daowen; Sun, Jie Lena; Pieper, Karen

    2016-10-01

    Linear mixed effects models are widely used to analyze a clustered response variable. Motivated by a recent study to examine and compare the hospital length of stay (LOS) between patients undertaking percutaneous coronary intervention (PCI) and coronary artery bypass graft (CABG) from several international clinical trials, we proposed a bivariate linear mixed effects model for the joint modeling of clustered PCI and CABG LOS's where each clinical trial is considered a cluster. Due to the large number of patients in some trials, commonly used commercial statistical software for fitting (bivariate) linear mixed models failed to run since it could not allocate enough memory to invert large dimensional matrices during the optimization process. We consider ways to circumvent the computational problem in the maximum likelihood (ML) inference and restricted maximum likelihood (REML) inference. Particularly, we developed an expected and maximization (EM) algorithm for the REML inference and presented an ML implementation using existing software. The new REML EM algorithm is easy to implement and computationally stable and efficient. With this REML EM algorithm, we could analyze the LOS data and obtained meaningful results.

  17. Clinical Significance of Asthma Clusters by Longitudinal Analysis in Korean Asthma Cohort

    PubMed Central

    Kim, Sujeong; Yoon, Sun-young; Kwon, Hyouk-Soo; Chang, Yoon-Seok; Cho, You Sook; Jang, An-Soo; Park, Jung Won; Nahm, Dong-Ho; Yoon, Ho-Joo; Cho, Sang-Heon; Cho, Young-Joo; Choi, ByoungWhui; Moon, Hee-Bom; Kim, Tae-Bum

    2013-01-01

    Background We have previously identified four distinct groups of asthma patients in Korean cohorts using cluster analysis: (A) smoking asthma, (B) severe obstructive asthma, (C) early-onset atopic asthma, and (D) late-onset mild asthma. Methods and Results A longitudinal analysis of each cluster in a Korean adult asthma cohort was performed to investigate the clinical significance of asthma clusters over 12 months. Cluster A showed relatively high asthma control test (ACT) scores but relatively low FEV1 scores, despite a high percentage of systemic corticosteroid use. Cluster B had the lowest mean FEV1, ACT, and the quality of life questionnaire for adult Korean asthmatics (QLQAKA) scores throughout the year, even though the percentage of systemic corticosteroid use was the highest among the four clusters. Cluster C was ranked second in terms of FEV1, with the second lowest percentage of systemic corticosteroid use, and showed a marked improvement in subjective symptoms over time. Cluster D consistently showed the highest FEV1, the lowest systemic corticosteroid use, and had high ACT and QLQAKA scores. Conclusion Our asthma clusters had clinical significance with consistency among clusters over 12 months. These distinctive phenotypes may be useful in classifying asthma in real practice. PMID:24391784

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. (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

    2015-06-02

    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.

  3. 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

  4. 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

  5. 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.

  6. 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.

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

    DTIC Science & Technology

    2014-03-14

    of the genetics of cocaine, opioid, and alcohol dependence, and controls; N = 1146 European Americans (EAs) and 1284 African Americans (AAs) AA...0.0001) enriched by more than 50 candidates from the 1,142 genes of interest (GOI). Biofunction Categories p-values Number of Molecules Genetic Disorder...2011) Reducing the genetic risk of age-related macular degeneration with dietary antioxidants, zinc, and omega-3 fatty acids: the Rotterdam study. Arch

  8. 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…

  9. 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).

  10. Abundance analysis of the outer halo globular cluster Palomar 14

    NASA Astrophysics Data System (ADS)

    Çalışkan, Ş.; Christlieb, N.; Grebel, E. K.

    2012-01-01

    We determine the elemental abundances of nine red giant stars belonging to Palomar 14 (Pal 14). Pal 14 is an outer halo globular cluster (GC) at a distance of ~70 kpc. Our abundance analysis is based on high-resolution spectra and one-dimensional stellar model atmospheres. We derived the abundances for the iron peak elements Sc, V, Cr, Mn, Co, Ni, the α-elements O, Mg, Si, Ca, Ti, the light odd element Na, and the neutron-capture elements Y, Zr, Ba, La, Ce, Nd, Eu, Dy, and Cu. Our data do not permit us to investigate light element (i.e., O to Mg) abundance variations. The neutron-capture elements show an r-process signature. We compare our measurements with the abundance ratios of inner and other outer halo GCs, halo field stars, GCs of recognized extragalactic origin, and stars in dwarf spheroidal galaxies (dSphs). The abundance pattern of Pal 14 is almost identical to those of Pal 3 and Pal 4, the next distant members of the outer halo GC population after Pal 14. The abundance pattern of Pal 14 is also similar to those of the inner halo GCs, halo field stars, and GCs of recognized extragalactic origin, but differs from what is customarily found in dSphs field stars. The abundance properties of Pal 14, as well as those of the other outer halo GCs, are thus compatible with an accretion origin from dSphs. Whether or not GC accretion played a role, it seems that the formation conditions of outer halo GCs and GCs in dSphs were similar. Based on observations collected at the European Southern Observatory, Chile (Program IDs 077.B-0769).Tables A.1 and A.2 are only available at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/537/A83

  11. Global Myeloma Research Clusters, Output, and Citations: A Bibliometric Mapping and Clustering Analysis

    PubMed Central

    Andersen, Jens Peter; Bøgsted, Martin; Dybkær, Karen; Mellqvist, Ulf-Henrik; Morgan, Gareth J.; Goldschmidt, Hartmut; Dimopoulos, Meletios A.; Einsele, Hermann; San Miguel, Jesús; Palumbo, Antonio; Sonneveld, Pieter; Johnsen, Hans Erik

    2015-01-01

    Background International collaborative research is a mechanism for improving the development of disease-specific therapies and for improving health at the population level. However, limited data are available to assess the trends in research output related to orphan diseases. Methods and Findings We used bibliometric mapping and clustering methods to illustrate the level of fragmentation in myeloma research and the development of collaborative efforts. Publication data from Thomson Reuters Web of Science were retrieved for 2005–2009 and followed until 2013. We created a database of multiple myeloma publications, and we analysed impact and co-authorship density to identify scientific collaborations, developments, and international key players over time. The global annual publication volume for studies on multiple myeloma increased from 1,144 in 2005 to 1,628 in 2009, which represents a 43% increase. This increase is high compared to the 24% and 14% increases observed for lymphoma and leukaemia. The major proportion (>90% of publications) was from the US and EU over the study period. The output and impact in terms of citations, identified several successful groups with a large number of intra-cluster collaborations in the US and EU. The US-based myeloma clusters clearly stand out as the most productive and highly cited, and the European Myeloma Network members exhibited a doubling of collaborative publications from 2005 to 2009, still increasing up to 2013. Conclusion and Perspective Multiple myeloma research output has increased substantially in the past decade. The fragmented European myeloma research activities based on national or regional groups are progressing, but they require a broad range of targeted research investments to improve multiple myeloma health care. PMID:25629620

  12. 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

  13. Differences Between Ward's and UPGMA Methods of Cluster Analysis: Implications for School Psychology.

    ERIC Educational Resources Information Center

    Hale, Robert L.; Dougherty, Donna

    1988-01-01

    Compared the efficacy of two methods of cluster analysis, the unweighted pair-groups method using arithmetic averages (UPGMA) and Ward's method, for students grouped on intelligence, achievement, and social adjustment by both clustering methods. Found UPGMA more efficacious based on output, on cophenetic correlation coefficients generated by each…

  14. Application of Cluster Analysis to the Study of Piagetian Stages of Intellectual Development.

    ERIC Educational Resources Information Center

    DeLuca, Frederick P.

    1981-01-01

    Reexamined Piagetian stages of males (N=182) and females (N=176), ages nine to eighteen, using cluster analysis, and sought information concerning occurrence of stages and influence of different tasks and gender on cluster patterns. Findings, among others, indicate that deviation from Piagetian stages was influenced by gender and type of task.…

  15. 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…

  16. A method of using cluster analysis to study statistical dependence in multivariate data

    NASA Technical Reports Server (NTRS)

    Borucki, W. J.; Card, D. H.; Lyle, G. C.

    1975-01-01

    A technique is presented that uses both cluster analysis and a Monte Carlo significance test of clusters to discover associations between variables in multidimensional data. The method is applied to an example of a noisy function in three-dimensional space, to a sample from a mixture of three bivariate normal distributions, and to the well-known Fisher's Iris data.

  17. 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…

  18. Hierarchical clustering analysis of flexible GBR 12909 dialkyl piperazine and piperidine analogs

    NASA Astrophysics Data System (ADS)

    Gilbert, Kathleen M.; Venanzi, Carol A.

    2006-04-01

    Pharmacophore modeling of large, drug-like molecules, such as the dopamine reuptake inhibitor GBR 12909, is complicated by their flexibility. A comprehensive hierarchical clustering study of two GBR 12909 analogs was performed to identify representative conformers for input to three-dimensional quantitative structure-activity relationship studies of closely-related analogs. Two data sets of more than 700 conformers each produced by random search conformational analysis of a piperazine and a piperidine GBR 12909 analog were studied. Several clustering studies were carried out based on different feature sets that include the important pharmacophore elements. The distance maps, the plot of the effective number of clusters versus actual number of clusters, and the novel derived clustering statistic, percentage change in the effective number of clusters, were shown to be useful in determining the appropriate clustering level. Six clusters were chosen for each analog, each representing a different region of the torsional angle space that determines the relative orientation of the pharmacophore elements. Conformers of each cluster that are representative of these regions were identified and compared for each analog. This study illustrates the utility of using hierarchical clustering for the classification of conformers of highly flexible molecules in terms of the three-dimensional spatial orientation of key pharmacophore elements.

  19. The identification of credit card encoders by hierarchical cluster analysis of the jitters of magnetic stripes.

    PubMed

    Leung, S C; Fung, W K; Wong, K H

    1999-01-01

    The relative bit density variation graphs of 207 specimen credit cards processed by 12 encoding machines were examined first visually, and then classified by means of hierarchical cluster analysis. Twenty-nine credit cards being treated as 'questioned' samples were tested by way of cluster analysis against 'controls' derived from known encoders. It was found that hierarchical cluster analysis provided a high accuracy of identification with all 29 'questioned' samples classified correctly. On the other hand, although visual comparison of jitter graphs was less discriminating, it was nevertheless capable of giving a reasonably accurate result.

  20. 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.

  1. Nucleotide sequence and transcriptional analysis of the type A2 neurotoxin gene cluster in Clostridium botulinum.

    PubMed

    Dineen, Sean S; Bradshaw, Marite; Karasek, Charles E; Johnson, Eric A

    2004-06-01

    The nucleotide sequences of the upstream regions of the botulinum neurotoxin type A1 (BoNT/A1) cluster of Clostridium botulinum strain NCTC 2916 and the BoNT/A2 cluster of strain Kyoto-F were determined. A novel gene, designated orfx3, was identified following the orfx2 gene in both clusters. ORF-X2 and ORF-X3 exhibit similarity to the BoNT cluster associated P-47 protein. The BoNT/A1 and BoNT/A2 clusters share a similar gene arrangement, but exhibit differences in the spacing between certain genes. Sequences with similarity to transposases were identified in these intergenic regions, suggesting that these differences arose from an ancestral insertion event. Transcriptional analysis of the BoNT/A2 cluster revealed that the genes of the cluster are primarily synthesized as three polycistronic transcripts. Two divergent polycistronic transcripts, one encoding the orfx1, orfx2, and orfx3 genes, the second encoding the p47, ntnh, and bont/a2 genes, are transcribed from conserved BoNT cluster promoters. The third polycistronic transcript, expressed at low levels, encodes the positive regulatory botR gene and the orfx genes. This is the first complete analysis of a botulinum toxin A2 cluster.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. HPOSim: An R Package for Phenotypic Similarity Measure and Enrichment Analysis Based on the Human Phenotype Ontology

    PubMed Central

    Deng, Yue; Gao, Lin; Wang, Bingbo; Guo, Xingli

    2015-01-01

    Background Phenotypic features associated with genes and diseases play an important role in disease-related studies and most of the available methods focus solely on the Online Mendelian Inheritance in Man (OMIM) database without considering the controlled vocabulary. The Human Phenotype Ontology (HPO) provides a standardized and controlled vocabulary covering phenotypic abnormalities in human diseases, and becomes a comprehensive resource for computational analysis of human disease phenotypes. Most of the existing HPO-based software tools cannot be used offline and provide only few similarity measures. Therefore, there is a critical need for developing a comprehensive and offline software for phenotypic features similarity based on HPO. Results HPOSim is an R package for analyzing phenotypic similarity for genes and diseases based on HPO data. Seven commonly used semantic similarity measures are implemented in HPOSim. Enrichment analysis of gene sets and disease sets are also implemented, including hypergeometric enrichment analysis and network ontology analysis (NOA). Conclusions HPOSim can be used to predict disease genes and explore disease-related function of gene modules. HPOSim is open source and freely available at SourceForge (https://sourceforge.net/p/hposim/). PMID:25664462

  7. Photocatalytically patterned TiO2 arrays for on-plate selective enrichment of phosphopeptides and direct MALDI MS analysis.

    PubMed

    Wang, Hui; Duan, Jicheng; Cheng, Quan

    2011-03-01

    We report the development of photocatalytically patterned TiO(2) arrays for selective on-plate enrichment and direct matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) analysis of phosphopeptides. A thin TiO(2) nanofilm with controlled porosity is prepared on gold-covered glass slides by a layer-by-layer (LbL) deposition/calcination process. The highly porous and rough nanostructure offers high surface area for selective binding of phosphorylated species. The patterned arrays are generated using an octadecyltrichlorosilane (OTS) coating in combination of UV irradiation with a photomask, followed by NaOH etching. The resulting hydrophilic TiO(2) spots are thus surrounded by a hydrophobic OTS layer, which can facilitate the enrichment of low-abundance components by confining a large volume sample into a small area. The TiO(2) arrays exhibit high specificity toward phosphopeptides in complex samples including phosphoprotein digests and human serum, and the detection can be made in the fmole range. Additional advantages of the arrays include excellent stability, reusability/reproducibility, and low cost. This method has been successfully applied to the analysis of phosphopeptides in nonfat milk. The patterned TiO(2) arrays provide an attractive interface for performing on-plate reactions, including selective capture of target species for MALDI-MS analysis, and can serve as a versatile lab-on-a-chip platform for high throughput analysis in phosphoproteome research.

  8. Genomic Contributors to Rhythm Outcome of Atrial Fibrillation Catheter Ablation – Pathway Enrichment Analysis of GWAS Data

    PubMed Central

    Ueberham, Laura; Dinov, Borislav; Sommer, Philipp; Arya, Arash; Hindricks, Gerhard; Bollmann, Andreas

    2016-01-01

    Background Left atrial enlargement and persistent atrial fibrillation (AF) are well-known predictors for arrhythmia recurrence after AF catheter ablation (LRAF). In this study, by using pathway enrichment analysis of GWAS data, we tested the hypothesis that genetic pathways associated with these phenotypes are also associated with LRAF. Methods Samples from 660 patients with paroxysmal (n = 370) or persistent AF (n = 290) undergoing de-novo AF catheter ablation were genotyped for ~1,000,000 SNPs. SNPs found to be significantly associated with left atrial diameter (LAD) or AF type were used for gene-based association tests in a systematic biological Knowledge-based mining system for Genome-wide Genetic studies (KGG). Associated genes were tested for pathway enrichment using WEB-based Gene SeT AnaLysis Toolkit (WebGestalt), the Gene Annotation Tool to Help Explain Relationships (GATHER) and the databases provided by Kyoto Encyclopedia of Genes and Genomes (KEGG). In a second step, the association of consistently enriched pathways and LRAF was tested. Results By using sequential 7-day Holter ECGs, LRAF between 3 and 12 months was observed in 48% and was associated with LAD (B = 1.801, 95% CI 0.760–2.841, p = 1.0E-3) and persistent AF (OR = 2.1; 95% CI 1.567–2.931, p = 2.0E-6). WebGestalt (adj. p = 2.7E-22) and GATHER (adj. p = 5.2E-3) identified the calcium signaling pathway (hsa04020) as the only consistently enriched pathway for LAD, while the extracellular matrix (ECM) -receptor interaction pathway (hsa04512) was the only consistently enriched pathway for AF type (adj. p = 2.1E-15 in WebGestalt; adj. p = 9.3E-4 in GATHER). Both calcium signaling (adj. p = 2.2E-17 in WebGestalt; adj. p = 2.9E-2 in GATHER) and ECM-receptor interaction (adj. p = 1.2E-10 in WebGestalt; adj. p = 2.9E-2 in GATHER) were significantly associated with LRAF. Conclusions Calcium signaling and ECM-receptor interaction pathways are associated with LAD and AF type and, in turn, with LRAF

  9. 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%.

  10. Exosome enrichment of human serum using multiple cycles of centrifugation.

    PubMed

    Kim, Jeongkwon; Tan, Zhijing; Lubman, David M

    2015-09-01

    In this work, we compared the use of repeated cycles of centrifugation at conventional speeds for enrichment of exosomes from human serum compared to the use of ultracentrifugation (UC). After removal of cells and cell debris, a speed of 110 000 × g or 40 000 × g was used for the UC or centrifugation enrichment process, respectively. The enriched exosomes were analyzed using the bicinchoninic acid assay, 1D gel separation, transmission electron microscopy, Western blotting, and high-resolution LC-MS/MS analysis. It was found that a five-cycle repetition of UC or centrifugation is necessary for successful removal of nonexosomal proteins in the enrichment of exosomes from human serum. More significantly, 5× centrifugation enrichment was found to provide similar or better performance than 5× UC enrichment in terms of enriched exosome protein amount, Western blot band intensity for detection of CD-63, and numbers of identified exosome-related proteins and cluster of differentiation (CD) proteins. A total of 478 proteins were identified in the LC-MS/MS analyses of exosome proteins obtained from 5× UCs and 5× centrifugations including many important CD membrane proteins. The presence of previously reported exosome-related proteins including key exosome protein markers demonstrates the utility of this method for analysis of proteins in human serum.

  11. Cluster Analysis of Symptoms Among Patients with Upper Extremity Musculoskeletal Disorders

    PubMed Central

    Piligian, George; Glutting, Joseph J.; Hanlon, Alexandra; Frings-Dresen, Monique H. W.; Sluiter, Judith K.

    2010-01-01

    Introduction Some musculoskeletal disorders of the upper extremity are not readily classified. The study objective was to determine if there were symptom patterns in self-identified repetitive strain injury (RSI) patients. Methods Members (n = 700) of the Dutch RSI Patients Association filled out a detailed symptom questionnaire. Factor analysis followed by cluster analysis grouped correlated symptoms. Results Eight clusters, based largely on symptom severity and quality were formulated. All but one cluster showed diffuse symptoms; the exception was characterized by bilateral symptoms of stiffness and aching pain in the shoulder/neck. Conclusions Case definitions which localize upper extremity musculoskeletal disorders to a specific anatomical area may be incomplete. Future clustering studies should rely on both signs and symptoms. Data could be collected from health care providers prospectively to determine the possible prognostic value of the identified clusters with respect to natural history, chronicity, and return to work. PMID:20414797

  12. Tobacco, Marijuana, and Alcohol Use in University Students: A Cluster Analysis

    PubMed Central

    Primack, Brian A.; Kim, Kevin H.; Shensa, Ariel; Sidani, Jaime E.; Barnett, Tracey E.; Switzer, Galen E.

    2012-01-01

    Objective Segmentation of populations may facilitate development of targeted substance abuse prevention programs. We aimed to partition a national sample of university students according to profiles based on substance use. Participants We used 2008–2009 data from the National College Health Assessment from the American College Health Association. Our sample consisted of 111,245 individuals from 158 institutions. Method We partitioned the sample using cluster analysis according to current substance use behaviors. We examined the association of cluster membership with individual and institutional characteristics. Results Cluster analysis yielded six distinct clusters. Three individual factors—gender, year in school, and fraternity/sorority membership—were the most strongly associated with cluster membership. Conclusions In a large sample of university students, we were able to identify six distinct patterns of substance abuse. It may be valuable to target specific populations of college-aged substance users based on individual factors. However, comprehensive intervention will require a multifaceted approach. PMID:22686360

  13. 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.

  14. A Spectroscopic Analysis of the Galactic Globular Cluster NGC 6273 (M19)

    NASA Astrophysics Data System (ADS)

    Johnson, Christian I.; Rich, R. Michael; Pilachowski, Catherine A.; Caldwell, Nelson; Mateo, Mario; Bailey, John I., III; Crane, Jeffrey D.

    2015-08-01

    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-1 (σ = 9.64 km s-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. This paper includes data gathered with the 6.5 m Magellan Telescopes located at Las Campanas Observatory, Chile.

  15. 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…

  16. 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

  17. The Therapist Personal Reaction Questionnaire: A Cluster Analysis.

    ERIC Educational Resources Information Center

    Tryon, Georgiana Shick

    1989-01-01

    Analyzed Therapist Personal Reaction Questionnaire. Participants consisted of 6 practicum trainee graduate students and 208 undergraduate clients. Found two clusters--one related to counselor feelings toward client, one related to counselor feelings toward interview. Results indicated that more attractive clients were seen more frequently and for…

  18. The Validity of the Inverse Scree Test for Cluster Analysis.

    ERIC Educational Resources Information Center

    Lathrop, Richard G.; Williams, Janice E.

    1990-01-01

    A Monte Carlo study of the validity of the Inverse Scree Test under conditions where true group membership is known was conducted. Fifty cluster analyses of each distribution involving 2 to 5 true groups of 3,000 simulated subjects were made. Implications for the data analyst are discussed. (SLD)

  19. The Complementary Use of Cluster and Factor Analysis Methods.

    ERIC Educational Resources Information Center

    Gorman, Bernard S.; Primavera, Louis H.

    1983-01-01

    Factor and cluster analyses are distinctly different multivariate procedures with different goals. However, when used in a complementary fashion, each set of methods can be used to enhance the interpretation of results found in the other set of methods. Simple examples illustrating the joint use of the methods are provided. (Author)

  20. First photometric analysis of six open cluster candidates

    NASA Astrophysics Data System (ADS)

    Piatti, A. E.; Clariá, J. J.; Ahumada, A. V.

    2011-10-01

    In this study we try to clarify the nature of six catalogued open cluster (OC) candidates using CCD UBVI_{KC} photometry down to V = 22. The objects are Haffner 3, Haffner 5, NGC 2368, Haffner 25, Hogg 3 and Hogg 4. None of them was found to be a real OC.

  1. 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

  2. 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

  3. 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.

  4. NeAT: a toolbox for the analysis of biological networks, clusters, classes and pathways

    PubMed Central

    Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Sand, Olivier; Janky, Rekin's; Vanderstocken, Gilles; Deville, Yves; van Helden, Jacques

    2008-01-01

    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. PMID:18524799

  5. Choosing appropriate analysis methods for cluster randomised cross-over trials with a binary outcome.

    PubMed

    Morgan, Katy E; Forbes, Andrew B; Keogh, Ruth H; Jairath, Vipul; Kahan, Brennan C

    2017-01-30

    In cluster randomised cross-over (CRXO) trials, clusters receive multiple treatments in a randomised sequence over time. In such trials, there is usual correlation between patients in the same cluster. In addition, within a cluster, patients in the same period may be more similar to each other than to patients in other periods. We demonstrate that it is necessary to account for these correlations in the analysis to obtain correct Type I error rates. We then use simulation to compare different methods of analysing a binary outcome from a two-period CRXO design. Our simulations demonstrated that hierarchical models without random effects for period-within-cluster, which do not account for any extra within-period correlation, performed poorly with greatly inflated Type I errors in many scenarios. In scenarios where extra within-period correlation was present, a hierarchical model with random effects for cluster and period-within-cluster only had correct Type I errors when there were large numbers of clusters; with small numbers of clusters, the error rate was inflated. We also found that generalised estimating equations did not give correct error rates in any scenarios considered. An unweighted cluster-level summary regression performed best overall, maintaining an error rate close to 5% for all scenarios, although it lost power when extra within-period correlation was present, especially for small numbers of clusters. Results from our simulation study show that it is important to model both levels of clustering in CRXO trials, and that any extra within-period correlation should be accounted for. Copyright © 2016 John Wiley & Sons, Ltd.

  6. Groundwater source contamination mechanisms: Physicochemical profile clustering, risk factor analysis and multivariate modelling

    NASA Astrophysics Data System (ADS)

    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.

  7. 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.

  8. Does published orthodontic research account for clustering effects during statistical data analysis?

    PubMed

    Koletsi, Despina; Pandis, Nikolaos; Polychronopoulou, Argy; Eliades, Theodore

    2012-06-01

    In orthodontics, multiple site observations within patients or multiple observations collected at consecutive time points are often encountered. Clustered designs require larger sample sizes compared to individual randomized trials and special statistical analyses that account for the fact that observations within clusters are correlated. It is the purpose of this study to assess to what degree clustering effects are considered during design and data analysis in the three major orthodontic journals. The contents of the most recent 24 issues of the American Journal of Orthodontics and Dentofacial Orthopedics (AJODO), Angle Orthodontist (AO), and European Journal of Orthodontics (EJO) from December 2010 backwards were hand searched. Articles with clustering effects and whether the authors accounted for clustering effects were identified. Additionally, information was collected on: involvement of a statistician, single or multicenter study, number of authors in the publication, geographical area, and statistical significance. From the 1584 articles, after exclusions, 1062 were assessed for clustering effects from which 250 (23.5 per cent) were considered to have clustering effects in the design (kappa = 0.92, 95 per cent CI: 0.67-0.99 for inter rater agreement). From the studies with clustering effects only, 63 (25.20 per cent) had indicated accounting for clustering effects. There was evidence that the studies published in the AO have higher odds of accounting for clustering effects [AO versus AJODO: odds ratio (OR) = 2.17, 95 per cent confidence interval (CI): 1.06-4.43, P = 0.03; EJO versus AJODO: OR = 1.90, 95 per cent CI: 0.84-4.24, non-significant; and EJO versus AO: OR = 1.15, 95 per cent CI: 0.57-2.33, non-significant). The results of this study indicate that only about a quarter of the studies with clustering effects account for this in statistical data analysis.

  9. The different clinical faces of obstructive sleep apnoea: a cluster analysis.

    PubMed

    Ye, Lichuan; Pien, Grace W; Ratcliffe, Sarah J; Björnsdottir, Erla; Arnardottir, Erna Sif; Pack, Allan I; Benediktsdottir, Bryndis; Gislason, Thorarinn

    2014-12-01

    Although commonly observed in clinical practice, the heterogeneity of obstructive sleep apnoea (OSA) clinical presentation has not been formally characterised. This study was the first to apply cluster analysis to identify subtypes of patients with OSA who experience distinct combinations of symptoms and comorbidities. An analysis of baseline data from the Icelandic Sleep Apnoea Cohort (822 patients with newly diagnosed moderate-to-severe OSA) was performed. Three distinct clusters were identified. They were classified as the "disturbed sleep group" (cluster 1), "minimally symptomatic group" (cluster 2) and "excessive daytime sleepiness group" (cluster 3), consisting of 32.7%, 24.7% and 42.6% of the entire cohort, respectively. The probabilities of having comorbid hypertension and cardiovascular disease were highest in cluster 2 but lowest in cluster 3. The clusters did not differ significantly in terms of sex, body mass index or apnoea-hypopnoea index. Patients with OSA have different patterns of clinical presentation, which need to be communicated to both the lay public and the professional community with the goal of facilitating care-seeking and early identification of OSA. Identifying distinct clinical profiles of OSA creates a foundation for offering more personalised therapies in the future.

  10. Genome-wide association analysis and pathways enrichment for lactation persistency in Canadian Holstein cattle.

    PubMed

    Do, D N; Bissonnette, N; Lacasse, P; Miglior, F; Sargolzaei, M; Zhao, X; Ibeagha-Awemu, E M

    2017-03-01

    Lactation persistency (LP), defined as the rate of declining milk yield after milk peak, is an economically important trait for dairy cattle. Improving LP is considered a good alternative method for increasing overall milk production because it does not cause the negative energy balance and other health issues that cows experience during peak milk production. However, little is known about the biology of LP. A genome-wide association study (GWAS) and pathway enrichment were used to explore the genetic mechanisms underlying LP. The GWAS was performed using a univariate regression mixed linear model on LP data of 3,796 cows and 44,100 single nucleotide polymorphisms (SNP). Eight and 47 SNP were significantly and suggestively associated with LP, respectively. The 2 most important quantitative trait loci regions for LP were (1) a region from 106 to 108 Mb on Bos taurus autosome (BTA) 5, where the most significant SNP (ARS-BFGL-NGS-2399) was located and also formed a linkage disequilibrium block with 3 other SNP; and (2) a region from 29.3 to 31.3 Mb on BTA 20, which contained 3 significant SNP. Based on physical positions, MAN1C1, MAP3K5, HCN1, TSPAN9, MRPS30, TEX14, and CCL28 are potential candidate genes for LP because the significant SNP were located in their intronic regions. Enrichment analyses of a list of 536 genes in 0.5-Mb flanking regions of significant and suggestive SNP indicates that synthesis of milk components, regulation of cell apoptosis processes and insulin, and prolactin signaling pathways are important for LP. Upstream regulators relevant for LP positional candidate genes were prolactin (PRL), peroxisome proliferator-activated receptor gamma (PPARG), and Erb-B2 receptor tyrosine kinase 2 (ERBB2). Several networks related to cellular development, proliferation and death were significantly enriched for LP positional candidate genes. In conclusion, this study detected several SNP, genes, and interesting regions for fine mapping and validation of

  11. Project ENRICH.

    ERIC Educational Resources Information Center

    Gwaley, Elizabeth; And Others

    Project ENRICH was conceived in Beaver County, Pennsylvania, to: (1) identify preschool children with learning disabilities, and (2) to develop a program geared to the remediation of the learning disabilities within a school year, while allowing the child to be enrolled in a regular class situation for the following school year. Through…

  12. Selective Chemoprecipitation to Enrich Nitropeptides from Complex Proteomes for Mass Spectrometric Analysis

    PubMed Central

    Prokai, Laszlo; Guo, Jia; Prokai-Tatrai, Katalin

    2015-01-01

    Posttranslational protein nitration has attracted interest due to its involvement in cellular signaling, effects on protein function, and as a potential biomarker of nitroxidative stress. We describe a procedure for enriching nitropeptides for mass spectrometry-based proteomics that is a simple and reliable alternative to immunoaffinity-based methods. The starting material for this procedure is a proteolytic digest. The peptides are reacted with formaldehyde and sodium cyanoborohydride to dimethylate all the N-terminal and side-chain amino groups. Sodium dithionite is added subsequently to reduce the nitro groups to amines; in theory, the only amino groups present will have originally been nitro groups. The peptide sample is then applied to a solid-phase active ester reagent, and those peptides with amino groups will be selectively and covalently captured. Release of the peptides on hydrolysis with trifluoroacetic acid results in peptides that have a 4-formyl-benzamido group where the nitro group used to be. In qualitative setups, the procedure can be used to identify proteins modified by reactive nitrogen species and to determine the specific sites of their nitration. Quantitative measurements can be performed by stable-isotope labeling of the peptides in the reductive dimethylation step. Preparation of the solid-phase active ester reagent takes about 1 day. Enrichment of nitropeptides requires about 2 days, and sample preparations need 1 to 30 h varying based on experimental design. LC–MS/MS assays take from 4 h to several days and data processing can be done 1 to 7 days. PMID:24651500

  13. Coal analysis by diffuse reflectance near-infrared spectroscopy: Hierarchical cluster and linear discriminant analysis.

    PubMed

    Bona, M T; Andrés, J M

    2007-06-15

    An extensive study was carried out in coal samples coming from several origins trying to establish a relationship between nine coal properties (moisture (%), ash (%), volatile matter (%), fixed carbon (%), heating value (kcal/kg), carbon (%), hydrogen (%), nitrogen (%) and sulphur (%)) and the corresponding near-infrared spectral data. This research was developed by applying both quantitative (partial least squares regression, PLS) and qualitative multivariate analysis techniques (hierarchical cluster analysis, HCA; linear discriminant analysis, LDA), to determine a methodology able to estimate property values for a new coal sample. For that, it was necessary to define homogeneous clusters, whose calibration equations could be obtained with accuracy and precision levels comparable to those provided by commercial online analysers and, study the discrimination level between these groups of samples attending only to the instrumental variables. These two steps were performed in three different situations depending on the variables used for the pattern recognition: property values, spectral data (principal component analysis, PCA) or a combination of both. The results indicated that it was the last situation what offered the best results in both two steps previously described, with the added benefit of outlier detection and removal.

  14. 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

  15. The DANCE Project: Dynamical Analysis of Nearby Clusters

    NASA Astrophysics Data System (ADS)

    Bouy, H.; Bertin, E.; Cuillandre, J. C.; Moraux, E.; Bouvier, J.; Arevalo Sánchez, M.; Barrado Y Navascués, D.

    We present the results of the DANCE project, a ground-based survey meant to prepare and complement Gaia i) down to the planetary mass regime; ii) in regions of high extinction. The DANCE project takes advantage of archival wide-field surveys to derive precise astrometry, and in particular proper motions, for millions of stars in young nearby associations. We present the first preliminary results obtained for the Pleiades cluster, as well as our immediate objectives for other associations.

  16. 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.

  17. Hierarchical cluster analysis of matrix effects on 110 pesticide residues in 28 tea matrixes.

    PubMed

    Li, Yan; Pang, Guo-Fang; Fan, Chun-Lin; Chen, Xi

    2013-01-01

    Matrix effects on 110 pesticides in 28 tea matrixes of different varieties and origins by LC/MS/MS were studied, and most of the pesticides exhibited soft and medium signal suppression. To better understand the influence of the tea varieties and the physicochemical characteristics of pesticides on the matrix effects, the multivariate analysis tool called hierarchical cluster analysis was applied. Tea matrixes were grouped into three clusters: unfermented, fermented, and post-fermented teas. Any type of tea can be chosen from each cluster as a corresponding representative matrix within that cluster to make matrix-matched solutions, which could simplify analysis while guaranteeing its accuracy. Matrix effects on most pesticides were similar despite the physicochemical diversities of the pesticides.

  18. 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.

  19. Designed synthesis of MOF-derived magnetic nanoporous carbon materials for selective enrichment of glycans for glycomics analysis

    NASA Astrophysics Data System (ADS)

    Sun, Nianrong; Zhang, Xiangmin; Deng, Chunhui

    2015-04-01

    In this work, magnetic nanoporous carbon (NPC) materials were synthesized by choosing a MOF as a sacrificial template and a carbon precursor. The obtained Co-ZIF-67 materials showed strong magnetic response, high surface area, a uniform size of mesopores and high carbon content. The Co-ZIF-67 materials were successfully applied to glycomics analysis by enriching N-linked glycans in bio-samples with high selectivity and efficiency.In this work, magnetic nanoporous carbon (NPC) materials were synthesized by choosing a MOF as a sacrificial template and a carbon precursor. The obtained Co-ZIF-67 materials showed strong magnetic response, high surface area, a uniform size of mesopores and high carbon content. The Co-ZIF-67 materials were successfully applied to glycomics analysis by enriching N-linked glycans in bio-samples with high selectivity and efficiency. Electronic supplementary information (ESI) available: Experimental section, characterization results and additional MALDI-TOF MS spectra. See DOI: 10.1039/c5nr00244c

  20. 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.

  1. Galaxy Cluster Pressure Profiles as Determined by Sunyaev Zel’dovich Effect Observations with MUSTANG and Bolocam. II. Joint Analysis of 14 Clusters

    NASA Astrophysics Data System (ADS)

    Romero, Charles E.; Mason, Brian S.; Sayers, Jack; Mroczkowski, Tony; Sarazin, Craig; Donahue, Megan; Baldi, Alessandro; Clarke, Tracy E.; Young, Alexander H.; Sievers, Jonathan; Dicker, Simon R.; Reese, Erik D.; Czakon, Nicole; Devlin, Mark; Korngut, Phillip M.; Golwala, Sunil

    2017-04-01

    We present pressure profiles of galaxy clusters determined from high-resolution Sunyaev–Zel’dovich (SZ) effect observations of 14 clusters, which span the redshift range of 0.25< z< 0.89. The procedure simultaneously fits spherical cluster models to MUSTANG and Bolocam data. In this analysis, we adopt the generalized NFW parameterization of pressure profiles to produce our models. Our constraints on ensemble-average pressure profile parameters, in this study γ, C 500, and P 0, are consistent with those in previous studies, but for individual clusters we find discrepancies with the X-ray derived pressure profiles from the ACCEPT2 database. We investigate potential sources of these discrepancies, especially cluster geometry, electron temperature of the intracluster medium, and substructure. We find that the ensemble mean profile for all clusters in our sample is described by the parameters [γ ,{C}500,{P}0]=[{0.3}-0.1+0.1,{1.3}-0.1+0.1,{8.6}-2.4+2.4], cool core clusters are described by [γ ,{C}500,{P}0] =[{0.6}-0.1+0.1,{0.9}-0.1+0.1,{3.6}-1.5+1.5], and disturbed clusters are described by [γ ,{C}500,{P}0]=[{0.0}-0.0+0.1,{1.5}-0.2+0.1,{13.8}-1.6+1.6]. Of the 14 clusters, 4 have clear substructure in our SZ observations, while an additional 2 clusters exhibit potential substructure.

  2. A weak-lensing analysis of the Abell 383 cluster

    NASA Astrophysics Data System (ADS)

    Huang, Z.; Radovich, M.; Grado, A.; Puddu, E.; Romano, A.; Limatola, L.; Fu, L.

    2011-05-01

    Aims: We use deep CFHT and SUBARU uBVRIz archival images of the Abell 383 cluster (z = 0.187) to estimate its mass by weak-lensing. Methods: To this end, we first use simulated images to check the accuracy provided by our Kaiser-Squires-Broadhurst (KSB) pipeline. These simulations include shear testing programme (STEP) 1 and 2 simulations, as well as more realistic simulations of the distortion of galaxy shapes by a cluster with a Navarro-Frenk-White (NFW) profile. From these simulations we estimate the effect of noise on shear measurement and derive the correction terms. The R-band image is used to derive the mass by fitting the observed tangential shear profile with an NFW mass profile. Photometric redshifts are computed from the uBVRIz catalogs. Different methods for the foreground/background galaxy selection are implemented, namely selection by magnitude, color, and photometric redshifts, and the results are compared. In particular, we developed a semi-automatic algorithm to select the foreground galaxies in the color-color diagram, based on the observed colors. Results: Using color selection or photometric redshifts improves the correction of dilution from foreground galaxies: this leads to higher signals in the inner parts of the cluster. We obtain a cluster mass Mvir = 7.5+2.7_{-1.9 × 1014} M⊙: this value is 20% higher than previous estimates and is more consistent the mass expected from X-ray data. The R-band luminosity function of the cluster is computed and gives a total luminosity Ltot = (2.14 ± 0.5) × 1012 L⊙ and a mass-to-luminosity ratio M/L 300 M⊙/L⊙. Based on: data collected with the Subaru Telescope (University of Tokyo) and obtained from the SMOKA, which is operated by the Astronomy Data Center, National Astronomical Observatory of Japan; observations obtained with MegaPrime/MegaCam, a joint project of CFHT and CEA/DAPNIA, at the Canada-France-Hawaii Telescope (CFHT), which is operated by the National Research Council (NRC) of Canada

  3. Toxicity mechanisms identification via gene set enrichment analysis of time-series toxicogenomics data: impact of time and concentration.

    PubMed

    Gao, Ce; Weisman, David; Lan, Jiaqi; Gou, Na; Gu, April Z

    2015-04-07

    The advance in high-throughput "toxicogenomics" technologies, which allows for concurrent monitoring of cellular responses globally upon exposure to chemical toxicants, presents promises for next-generation toxicity assessment. It is recognized that cellular responses to toxicants have a highly dynamic nature, and exhibit both temporal complexity and dose-response shifts. Most current gene enrichment or pathway analysis lack the recognition of the inherent correlation within time series data, and may potentially miss important pathways or yield biased and inconsistent results that ignore dynamic patterns and time-sensitivity. In this study, we investigated the application of two score metrics for GSEA (gene set enrichment analysis) to rank the genes that consider the temporal gene expression profile. One applies a novel time series CPCA (common principal components analysis) to generate scores for genes based on their contributions to the common temporal variation among treatments for a given chemical at different concentrations. Another one employs an integrated altered gene expression quantifier-TELI (transcriptional effect level index) that integrates altered gene expression magnitude over the exposure time. By comparing the GSEA results using two different ranking metrics for examining the dynamic responses of reporter cells treated with various dose levels of three model toxicants, mitomycin C, hydrogen peroxide, and lead nitrate, the analysis identified and revealed different toxicity mechanisms of these chemicals that exhibit chemical-specific, as well as time-aware and dose-sensitive nature. The ability, advantages, and disadvantages of varying ranking metrics were discussed. These findings support the notion that toxicity bioassays should account for the cells' complex dynamic responses, thereby implying that both data acquisition and data analysis should look beyond simple traditional end point responses.

  4. 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…

  5. Systematic Identification and Evolutionary Analysis of Catalytically Versatile Cytochrome P450 Monooxygenase Families Enriched in Model Basidiomycete Fungi

    PubMed Central

    Syed, Khajamohiddin; Shale, Karabo; Pagadala, Nataraj Sekhar; Tuszynski, Jack

    2014-01-01

    Genome sequencing of basidiomycetes, a group of fungi capable of degrading/mineralizing plant material, revealed the presence of numerous cytochrome P450 monooxygenases (P450s) in their genomes, with some exceptions. Considering the large repertoire of P450s found in fungi, it is difficult to identify P450s that play an important role in fungal metabolism and the adaptation of fungi to diverse ecological niches. In this study, we followed Sir Charles Darwin’s theory of natural selection to identify such P450s in model basidiomycete fungi showing a preference for different types of plant components degradation. Any P450 family comprising a large number of member P450s compared to other P450 families indicates its natural selection over other P450 families by its important role in fungal physiology. Genome-wide comparative P450 analysis in the basidiomycete species, Phanerochaete chrysosporium, Phanerochaete carnosa, Agaricus bisporus, Postia placenta, Ganoderma sp. and Serpula lacrymans, revealed enrichment of 11 P450 families (out of 68 P450 families), CYP63, CYP512, CYP5035, CYP5037, CYP5136, CYP5141, CYP5144, CYP5146, CYP5150, CYP5348 and CYP5359. Phylogenetic analysis of the P450 family showed species-specific alignment of P450s across the P450 families with the exception of P450s of Phanerochaete chrysosporium and Phanerochaete carnosa, suggesting paralogous evolution of P450s in model basidiomycetes. P450 gene-structure analysis revealed high conservation in the size of exons and the location of introns. P450s with the same gene structure were found tandemly arranged in the genomes of selected fungi. This clearly suggests that extensive gene duplications, particularly tandem gene duplications, led to the enrichment of selective P450 families in basidiomycetes. Functional analysis and gene expression profiling data suggest that members of the P450 families are catalytically versatile and possibly involved in fungal colonization of plant material. To our

  6. 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

  7. TaqMan probes as blocking agents for enriched PCR amplification and DNA melting analysis of mutant genes.

    PubMed

    Botezatu, Irina V; Panchuk, Irina O; Stroganova, Anna M; Senderovich, Anastasia I; Kondratova, Valentina N; Shelepov, Valery P; Lichtenstein, Anatoly V

    2017-02-01

    Asymmetric PCR and DNA melting analysis with TaqMan probes applied for mutation detection is effectively used in clinical diagnostics. The method is simple, cost-effective, and carried out in a closed-tube format, minimizing time, labor, and risk of sample cross-contamination. Although DNA melting analysis is more sensitive than Sanger sequencing (mutation detection thresholds are ~5% and 15%-20%, respectively), it is less sensitive than more labor-intensive and expensive techniques such as pyrosequencing and droplet digital PCR. Here, we demonstrate that, under specially selected conditions of asymmetric PCR, TaqMan probes can play the role of blocking agents. Preferential blocking of the wild-type allele brings about enriched amplification of mutant alleles. As a result, an ~10-fold increase in the detection sensitivity for mutant BRAF and NRAS genes was achieved.

  8. Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient

    PubMed Central

    Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J

    2008-01-01

    Background Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. Results In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. Conclusion This study shows that SCC is

  9. 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

  10. On the association of young star clusters and their parental clouds: a statistical fractal analysis

    NASA Astrophysics Data System (ADS)

    Hetem, A.; Gregorio-Hetem, J.; Fernandes, B.; Santos-Silva, T.

    2014-10-01

    We present a study of 21 young star clusters aiming to characterize their association to dense clouds. The structure of the clouds was evaluated by means of the Q statistical fractal analysis, designed to compare their geometric structure with the spatial distribution of the cluster members. The sample was selected from the study by Santos-Silva and Gregorio-Hetem (2012, A&A, 547, A107) that evaluated the radial density profile of the stellar superficial distribution of the young clusters. The fractal dimension and other statistical parameters of most of the sample indicate that there is a good cloud-cluster correlation, when compared to other works based on an artificial distribution of points (Lomax et al. 2011, MNRAS, 412, 627). As presented in a previous work (Fernandes et al. 2012, A&A, 541, A95 ), the cluster NGC 6530 is the only object of our sample that presents anomalous statistical behaviour. The fractal analysis shows that this cluster has a centrally concentrated distribution of stars that differs from the substructures found in the density distribution of the cloud projected in the A_{V} map, suggesting that the original cloud geometry was changed by the cluster formation.

  11. Student academic performance analysis using fuzzy C-means clustering

    NASA Astrophysics Data System (ADS)

    Rosadi, R.; Akamal; Sudrajat, R.; Kharismawan, B.; Hambali, Y. A.

    2017-01-01

    Grade Point Average (GPA) is commonly used as an indicator of academic performance. Academic performance evaluations is a basic way to evaluate the progression of student performance, when evaluating student’s academic performance, there are occasion where the student data is grouped especially when the amounts of data is large. Thus, the pattern of data relationship within and among groups can be revealed. Grouping data can be done by using clustering method, where one of the methods is the Fuzzy C-Means algorithm. Furthermore, this algorithm is then applied to a set of student data form the Faculty of Mathematics and Natural Sciences, Padjadjaran University.

  12. Chaotic Artificial Bee Colony Used for Cluster Analysis

    NASA Astrophysics Data System (ADS)

    Zhang, Yudong; Wu, Lenan; Wang, Shuihua; Huo, Yuankai

    A new approach based on artificial bee colony (ABC) with chaotic theory was proposed to solve the partitional clustering problem. We first investigate the optimization model including both the encoding strategy and the variance ratio criterion (VRC). Second, a chaotic ABC algorithm was developed based on the Rossler attractor. Experiments on three types of artificial data of different degrees of overlapping all demonstrate the CABC is superior to both genetic algorithm (GA) and combinatorial particle swarm optimization (CPSO) in terms of robustness and computation time.

  13. Cluster analysis based on dimensional information with applications to feature selection and classification

    NASA Technical Reports Server (NTRS)

    Eigen, D. J.; Fromm, F. R.; Northouse, R. A.

    1974-01-01

    A new clustering algorithm is presented that is based on dimensional information. The algorithm includes an inherent feature selection criterion, which is discussed. Further, a heuristic method for choosing the proper number of intervals for a frequency distribution histogram, a feature necessary for the algorithm, is presented. The algorithm, although usable as a stand-alone clustering technique, is then utilized as a global approximator. Local clustering techniques and configuration of a global-local scheme are discussed, and finally the complete global-local and feature selector configuration is shown in application to a real-time adaptive classification scheme for the analysis of remote sensed multispectral scanner data.

  14. Characterization and expression analysis of the exopolysaccharide gene cluster in Lactobacillus fermentum TDS030603.

    PubMed

    Dan, Tong; Fukuda, Kenji; Sugai-Bannai, Michiko; Takakuwa, Naoya; Motoshima, Hidemasa; Urashima, Tadasu

    2009-12-01

    Part of the exopolysaccharide gene cluster of Lactobacillus fermentum TDS030603 was characterized. It consists of 11,890 base pairs and is located in the chromosomal DNA, 13 open reading frames of which were encoded. Out of the 13 open reading frames, six were found to be involved in exopolysaccharide synthesis; however, five were similar to transposase genes of other lactobacilli, and two were functionally unrelated. Expression analysis revealed that the exopolysaccharide synthesis-related genes were expressed during cultivation. Southern analysis using specific primers for the exopolysaccharide genes indicated that duplication of the gene cluster did not occur. The plasmid-cured strain maintained its capacity for exopolysaccharide production, confirming that the exopolysaccharide gene cluster of this strain is located in the chromosomal DNA, similarly to thermophilic lactic acid bacteria. Our results indicate that this exopolysaccharide gene cluster is likely to be functional, although extensive gene rearrangement occurs.

  15. [FTIR study of the influence of leaf senescence on magnoliaceae cluster analysis].

    PubMed

    Li, Lun; Liu, Gang; Ou, Quan-hong; Zhang, Li; Liu, Jian-hong; Sun, Shi-zhong

    2013-09-01

    Fourier transform infrared (FTIR) spectroscopy combined with hierarchical cluster analysis was used to study the influence of leaf senescence on magnoliaceae cluster. FTIR spectra of young, mature and old yellow leaves were obtained from 14 species trees belonging to the three magnoliaceae subtribes. Results showed that the infrared spectra of the three subtribes plant leaves were similar, only with minor differences in the absorption intensity of several peaks. Hierarchical cluster analysis was performed on the second derivative infrared spectra in the range 1800-700 cm(-1). The HCA results showed that the cluster based on mature leaves is better than that based on young and old yellow leaves. Our study suggests that it should be cautious to select leaf sample while using leaf spectra for classification.

  16. Quantitative Secretome Analysis of Activated Jurkat Cells Using Click Chemistry-Based Enrichment of Secreted Glycoproteins.

    PubMed

    Witzke, Kathrin E; Rosowski, Kristin; Müller, Christian; Ahrens, Maike; Eisenacher, Martin; Megger, Dominik A; Knobloch, Jürgen; Koch, Andrea; Bracht, Thilo; Sitek, Barbara

    2017-01-06

    Quantitative secretome analyses are a high-performance tool for the discovery of physiological and pathophysiological changes in cellular processes. However, serum supplements in cell culture media limit secretome analyses, but serum depletion often leads to cell starvation and consequently biased results. To overcome these limiting factors, we investigated a model of T cell activation (Jurkat cells) and performed an approach for the selective enrichment of secreted proteins from conditioned medium utilizing metabolic marking of newly synthesized glycoproteins. Marked glycoproteins were labeled via bioorthogonal click chemistry and isolated by affinity purification. We assessed two labeling compounds conjugated with either biotin or desthiobiotin and the respective secretome fractions. 356 proteins were quantified using the biotin probe and 463 using desthiobiotin. 59 proteins were found differentially abundant (adjusted p-value ≤0.05, absolute fold change ≥1.5) between inactive and activated T cells using the biotin method and 86 using the desthiobiotin approach, with 31 mutual proteins cross-verified by independent experiments. Moreover, we analyzed the cellular proteome of the same model to demonstrate the benefit of secretome analyses and provide comprehensive data sets of both. 336 proteins (61.3%) were quantified exclusively in the secretome. Data are available via ProteomeXchange with identifier PXD004280.

  17. 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

  18. Mass spectrometric analysis of the glycosphingolipid-enriched microdomains of rat natural killer cells.

    PubMed

    Man, Petr; Novák, Petr; Cebecauer, Marek; Horváth, Ondrej; Fiserová, Anna; Havlícek, Vladimír; Bezouska, Karel

    2005-01-01

    Glycosphingolipid-enriched microdomains (GEM) are membrane entities that concentrate glycosylphosphatiolylinositol(GPI)-anchored, acylated and membrane proteins important for immune receptor signaling. Using rat leukemic cell line RNK-16 we have initiated proteomic studies of microdomains in natural killer (NK) cells. Isolated plasma membranes were treated with Brij 58, or Nonidet-P40, or sodium carbonate. Extracts were separated by sucrose density gradient centrifugation into very light membrane, medium light membrane and heavy fractions, and a complete protein profile was analyzed by tandem mass spectrometry. Up to 250 proteins were unambiguously identified in each analyzed fraction. The first study of the proteome of NK cell GEM revealed several new aspects including identification of molecules not expected to be expressed in rat NK cells (e.g., NAP-22) or associated with GEM (e.g., NKR-P1, CD45, CD2). Moreover, it provided clear data consolidating controversial views concerning the occurrence of major histcompatibility complex glycoproteins and RT6.1/CD73/CD38 complex in NK cells. Our results also identified a large number of receptors as candidates for future functional studies.

  19. 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.

  20. Salient concerns in using analgesia for cancer pain among outpatients: A cluster analysis study

    PubMed Central

    Meghani, Salimah H; Knafl, George J

    2017-01-01

    AIM To identify unique clusters of patients based on their concerns in using analgesia for cancer pain and predictors of the cluster membership. METHODS This was a 3-mo prospective observational study (n = 207). Patients were included if they were adults (≥ 18 years), diagnosed with solid tumors or multiple myelomas, and had at least one prescription of around-the-clock pain medication for cancer or cancer-treatment-related pain. Patients were recruited from two outpatient medical oncology clinics within a large health system in Philadelphia. A choice-based conjoint (CBC) analysis experiment was used to elicit analgesic treatment preferences (utilities). Patients employed trade-offs based on five analgesic attributes (percent relief from analgesics, type of analgesic, type of side-effects, severity of side-effects, out of pocket cost). Patients were clustered based on CBC utilities using novel adaptive statistical methods. Multiple logistic regression was used to identify predictors of cluster membership. RESULTS The analyses found 4 unique clusters: Most patients made trade-offs based on the expectation of pain relief (cluster 1, 41%). For a subset, the main underlying concern was type of analgesic prescribed, i.e., opioid vs non-opioid (cluster 2, 11%) and type of analgesic side effects (cluster 4, 21%), respectively. About one in four made trade-offs based on multiple concerns simultaneously including pain relief, type of side effects, and severity of side effects (cluster 3, 28%). In multivariable analysis, to identify predictors of cluster membership, clinical and socioeconomic factors (education, health literacy, income, social support) rather than analgesic attitudes and beliefs were found important; only the belief, i.e., pain medications can mask changes in health or keep you from knowing what is going on in your body was found significant in predicting two of the four clusters [cluster 1 (-); cluster 4 (+)]. CONCLUSION Most patients appear to be driven

  1. Advantages and Limitations of Cluster Analysis in Interpreting Regional GPS Velocity Fields in California and Elsewhere

    NASA Astrophysics Data System (ADS)

    Thatcher, W. R.; Savage, J. C.; Simpson, R.

    2012-12-01

    Regional Global Positioning System (GPS) velocity observations are providing increasingly precise mappings of actively deforming continental lithosphere. Cluster analysis, a venerable data analysis method, offers a simple, visual exploratory tool for the initial organization and investigation of GPS velocities (Simpson et al., 2012 GRL). Here we describe the application of cluster analysis to GPS velocities from three regions, the Mojave Desert and the San Francisco Bay regions in California, and the Aegean in the eastern Mediterranean. Our goal is to illustrate the strengths and shortcomings of the method in searching for spatially coherent patterns of deformation, including evidence for and against block-like behavior in these 3 regions. 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, is subjective and usually guided by the distribution of known faults. Cluster analysis applied to GPS velocities provides a completely objective method for identifying groups of observations ranging in size from 10s to 100s of km in characteristic dimension based solely on the similarities of their velocity vectors. In the three regions we have studied, statistically significant clusters are almost invariably spatially coherent, fault bounded, and coincide with elastic, geologically identified structural blocks. Often, higher order clusters that are not statistically significant are also spatially coherent, suggesting the existence of additional blocks, or defining regions of other tectonic importance (e.g. zones of localized elastic strain accumulation near locked faults). These results can be used to both formulate tentative tectonic models with testable consequences and to suggest focused new measurements in under-sampled regions. Cluster analysis applied to GPS velocities has several potential limitations, aside from the

  2. 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

  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. Comparison of polymerase chain reaction methods and plating for analysis of enriched cultures of Listeria monocytogenes when using the ISO11290-1 method.

    PubMed

    Dalmasso, Marion; Bolocan, Andrei Sorin; Hernandez, Marta; Kapetanakou, Anastasia E; Kuchta, Tomáš; Manios, Stavros G; Melero, Beatriz; Minarovičová, Jana; Muhterem, Meryem; Nicolau, Anca Ioana; Rovira, Jordi; Skandamis, Panagiotis N; Stessl, Beatrix; Wagner, Martin; Jordan, Kieran; Rodríguez-Lázaro, David

    2014-03-01

    Analysis for Listeria monocytogenes by ISO11290-1 is time-consuming, entailing two enrichment steps and subsequent plating on agar plates, taking five days without isolate confirmation. The aim of this study was to determine if a polymerase chain reaction (PCR) assay could be used for analysis of the first and second enrichment broths, saving four or two days, respectively. In a comprehensive approach involving six European laboratories, PCR and traditional plating of both enrichment broths from the ISO11290-1 method were compared for the detection of L. monocytogenes in 872 food, raw material and processing environment samples from 13 different dairy and meat food chains. After the first and second enrichments, total DNA was extracted from the enriched cultures and analysed for the presence of L. monocytogenes DNA by PCR. DNA extraction by chaotropic solid-phase extraction (spin column-based silica) combined with real-time PCR (RTi-PCR) was required as it was shown that crude DNA extraction applying sonication lysis and boiling followed by traditional gel-based PCR resulted in fewer positive results than plating. The RTi-PCR results were compared to plating, as defined by the ISO11290-1 method. For first and second enrichments, 90% of the samples gave the same results by RTi-PCR and plating, whatever the RTi-PCR method used. For the samples that gave different results, plating was significantly more accurate for detection of positive samples than RTi-PCR from the first enrichment, but RTi-PCR detected a greater number of positive samples than plating from the second enrichment, regardless of the RTi-PCR method used. RTi-PCR was more accurate for non-food contact surface and food contact surface samples than for food and raw material samples especially from the first enrichment, probably because of sample matrix interference. Even though RTi-PCR analysis of the first enrichment showed less positive results than plating, in outbreak scenarios where a rapid result is

  5. Heating Two Types of Enriched Margarine: Complementary Analysis of Phytosteryl/Phytostanyl Fatty Acid Esters and Phytosterol/Phytostanol Oxidation Products.

    PubMed

    Scholz, Birgit; Menzel, Nicole; Lander, Vera; Engel, Karl-Heinz

    2016-04-06

    Two phytosteryl and/or phytostanyl fatty acid ester-enriched margarines were subjected to common heating procedures. UHPLC-APCI-MS analysis resulted for the first time in comprehensive quantitative data on the decreases of individual phytosteryl/-stanyl fatty acid esters upon heating of enriched foods. These data were complemented by determining the concurrently formed phytosterol/-stanol oxidation products (POPs) via online LC-GC. Microwave-heating led to the least decreases of esters of approximately 5% in both margarines. Oven-heating of the margarine in a casserole caused the greatest decreases, with 68 and 86% esters remaining, respectively; the impact on individual esters was more pronounced with increasing degree of unsaturation of the esterified fatty acids. In the phytosteryl/-stanyl ester-enriched margarine, approximately 20% of the ester losses could be explained by the formation of POPs; in the phytostanyl ester-enriched margarine, the POPs accounted for <1% of the observed ester decreases.

  6. Analysis of the histone cluster in Senegalese sole (Solea senegalensis): evidence for a divergent evolution of two canonical histone clusters.

    PubMed

    Merlo, Manuel Alejandro; Iziga, Roger; Portela, Silvia; Cross, Ismael; Kosyakova, Nadezda; Liehr, Thomas; Manchado, Manuel; Rebordinos, Laureana

    2016-12-10

    The Senegalese sole (Solea senegalensis) is commercially very important, and is a priority species for aquaculture product diversification. The main histone cluster was found in two BAC clones. However, two replacement histones (H1.0 and H3.3) were found in another BAC clone. Different types of canonical H2A and H2B have been found in one species for the first time. Phylogenetic analysis demonstrated that the different H1, H2A and H2B types were all more similar to each other than to canonical histones from other species. The canonical H3 of S. senegalensis differs from subtypes H3.1 and H3.2 in humans in the residue 96, in which a serine residue is found instead of an alanine. This same polymorphism has been found only in Danio rerio. The S. senegalensis karyotype comprises 21 pairs of chromosomes, distributed in 3 metacentric pairs, 2 submetacentric pairs, 4 subtelocentric pairs and 12 acrocentric pairs. The two BAC clones that contain the clusters of canonical histones have both been mapped in the largest metacentric pair, and mFISH confirmed the co-location with the dmrt1 gene in that pair. Three chromosome markers have been identified, which in addition to those previously described, account for 18 chromosome pairs with markers in S. senegalensis.

  7. Cluster analysis of passive air sampling data based on the relative composition of persistent organic pollutants.

    PubMed

    Liu, Xiande; Wania, Frank

    2014-03-01

    The development of passive air samplers has allowed the measurement of time-integrated concentrations of persistent organic pollutants (POPs) within spatial networks on a variety of scales. Cluster analysis of POP composition may enhance the interpretation of such spatial data. Several methodological aspects of the application of cluster analysis are discussed, including the influence of a dominant pollutant, the role of PAS duplication, and comparison of regional studies. Relying on data from six regional studies in North and South America, Africa, and Asia, we illustrate here how cluster analysis can be used to extract information and gain insights into POP sources and atmospheric transport contributions. Cluster analysis allows classification of PAS samples into those with significant local source contributions and those that represent regional fingerprints. Local emissions, atmospheric transport, and seasonal cycles are identified as being among the major factors determining the variation in POP composition at many sites. By complementing cluster analysis with meteorological data such as air mass back-trajectories, terrain, as well as geographical and socio-economic aspects, a comprehensive picture of the atmospheric contamination of a region by POPs emerges.

  8. Analysis of cluster explosive synchronization in complex networks.

    PubMed

    Ji, Peng; Peron, Thomas K D M; 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)] 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.

  9. DEFOG: Discrete Enrichment of Functionally Organized Genes†

    PubMed Central

    Wittkop, Tobias; Berman, Ari E.; Fleisch, K. Mathew; Mooney, Sean D.

    2012-01-01

    High-throughput biological experiments commonly result in a list of genes or proteins of interest. In order to understand the observed changes of the genes and to generate new hypotheses, one needs to understand the functions and roles of the genes and how those functions relate to the experimental conditions. Typically, statistical tests are performed in order to detect enriched Gene Ontology categories or Pathways, i.e. the categories are observed in the genes of interest more often than is expected by chance. Depending on the number of genes and the complexity and quantity of functions in which they are involved, such an analysis can easily result in hundreds of enriched terms. To this end we developed DEFOG, a web-based application that facilitates the functional analysis of gene sets by hierarchically organizing the genes into functionally related modules. Our computational pipeline utilizes three powerful tools to achieve this goal: (1) GeneMANIA creates a functional consensus network of the genes of interest based on gene-list-specific data fusion of hundreds of genomic networks from publicly available sources; (2) Transitivity Clustering organizes those genes into a clear hierarchy of functionally related groups, and (3) Ontologizer performs a Gene Ontology enrichment analysis on the resulting gene clusters. DEFOG integrates this computational pipeline within an easy-to-use web interface, thus allowing for a novel visual analysis of gene sets that aids in the discovery of potentially important biological mechanisms and facilitates the creation of new hypotheses. DEFOG is available at http://www.mooneygroup.org/defog. PMID:22706384

  10. Variable number of tandem repeats and pulsed-field gel electrophoresis cluster analysis of enterohemorrhagic Escherichia coli serovar O157 strains.

    PubMed

    Yokoyama, Eiji; Uchimura, Masako

    2007-11-01

    Ninety-five enterohemorrhagic Escherichia coli serovar O157 strains, including 30 strains isolated from 13 intrafamily outbreaks and 14 strains isolated from 3 mass outbreaks, were studied by pulsed-field gel electrophoresis (PFGE) and variable number of tandem repeats (VNTR) typing, and the resulting data were subjected to cluster analysis. Cluster analysis of the VNTR typing data revealed that 57 (60.0%) of 95 strains, including all epidemiologically linked strains, formed clusters with at least 95% similarity. Cluster analysis of the PFGE patterns revealed that 67 (70.5%) of 95 strains, including all but 1 of the epidemiologically linked strains, formed clusters with 90% similarity. The number of epidemiologically unlinked strains forming clusters was significantly less by VNTR cluster analysis than by PFGE cluster analysis. The congruence value between PFGE and VNTR cluster analysis was low and did not show an obvious correlation. With two-step cluster analysis, the number of clustered epidemiologically unlinked strains by PFGE cluster analysis that were divided by subsequent VNTR cluster analysis was significantly higher than the number by VNTR cluster analysis that were divided by subsequent PFGE cluster analysis. These results indicate that VNTR cluster analysis is more efficient than PFGE cluster analysis as an epidemiological tool to trace the transmission of enterohemorrhagic E. coli O157.

  11. Analysis of the Tribolium homeotic complex: insights into mechanisms constraining insect Hox clusters

    PubMed Central

    Ronshaugen, Matthew; Cande, Jessica; He, JianPing; Beeman, Richard W.; Levine, Michael; Brown, Susan J.; Denell, Robin E.

    2008-01-01

    The remarkable conservation of Hox clusters is an accepted but little understood principle of biology. Some organizational constraints have been identified for vertebrate Hox clusters, but most of these are thought to be recent innovations that may not apply to other organisms. Ironically, many model organisms have disrupted Hox clusters and may not be well-suited for studies of structural constraints. In contrast, the red flour beetle, Tribolium castaneum, which has a long history in Hox gene research, is thought to have a more ancestral-type Hox cluster organization. Here, we demonstrate that the Tribolium homeotic complex (HOMC) is indeed intact, with the individual Hox genes in the expected colinear arrangement and transcribed from the same strand. There is no evidence that the cluster has been invaded by non-Hox protein-coding genes, although expressed sequence tag and genome tiling data suggest that noncoding transcripts are prevalent. Finally, our analysis of several mutations affecting the Tribolium HOMC suggests that intermingling of enhancer elements with neighboring transcription units may constrain the structure of at least one region of the Tribolium cluster. This work lays a foundation for future studies of the Tribolium HOMC that may provide insights into the reasons for Hox cluster conservation. PMID:18392875

  12. 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.

  13. Profiling nurses' job satisfaction, acculturation, work environment, stress, cultural values and coping abilities: A cluster analysis.

    PubMed

    Goh, Yong-Shian; Lee, Alice; Chan, Sally Wai-Chi; Chan, Moon Fai

    2015-08-01

    This study aimed to determine whether definable profiles existed in a cohort of nursing staff with regard to demographic characteristics, job satisfaction, acculturation, work environment, stress, cultural values and coping abilities. A survey was conducted in one hospital in Singapore from June to July 2012, and 814 full-time staff nurses completed a self-report questionnaire (89% response rate). Demographic characteristics, job satisfaction, acculturation, work environment, perceived stress, cultural values, ways of coping and intention to leave current workplace were assessed as outcomes. The two-step cluster analysis revealed three clusters. Nurses in cluster 1 (n = 222) had lower acculturation scores than nurses in cluster 3. Cluster 2 (n = 362) was a group of younger nurses who reported higher intention to leave (22.4%), stress level and job dissatisfaction than the other two clusters. Nurses in cluster 3 (n = 230) were mostly Singaporean and reported the lowest intention to leave (13.0%). Resources should be allocated to specifically address the needs of younger nurses and hopefully retain them in the profession. Management should focus their retention strategies on junior nurses and provide a work environment that helps to strengthen their intention to remain in nursing by increasing their job satisfaction.

  14. 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.

  15. The distinction of 'psychosomatogenic family types' based on parents' self reported questionnaire information: a cluster analysis.

    PubMed

    Rousseau, Sofie; Grietens, Hans; Vanderfaeillie, Johan; Ceulemans, Eva; Hoppenbrouwers, Karel; Desoete, Annemie; Van Leeuwen, Karla

    2014-06-01

    The theory of 'psychosomatogenic family types' is often used in treatment of somatizing adolescents. This study investigated the validity of distinguishing 'psychosomatogenic family types' based on parents' self-reported family features. The study included a Flemish general population sample of 12-year olds (n = 1428). We performed cluster analysis on 3 variables concerning parents' self-reported problems in family functioning. The distinguished clusters were examined for differences in marital problems, parental emotional problems, professional help for family members, demographics, and adolescents' somatization. Results showed the existence of 5 family types: 'chaotic family functioning,' 'average amount of family functioning problems,' 'few family functioning problems,' 'high amount of support and communication problems,' and 'high amount of sense of security problems' clusters. Membership of the 'chaotic family functioning' and 'average amount of family functioning problems' cluster was significantly associated with higher levels of somatization, compared with 'few family functioning problems' cluster membership. Among additional variables, only marital and parental emotional problems distinguished somatization relevant from non relevant clusters: parents in 'average amount of family functioning problems' and 'chaotic family functioning' clusters reported higher problems. The data showed that 'apparently perfect' or 'enmeshed' patterns of family functioning may not be assessed by means of parent report as adopted in this study. In addition, not only adolescents from 'extreme' types of family functioning may suffer from somatization. Further, professionals should be careful assuming that families in which parents report average to high amounts of family functioning problems also show different demographic characteristics.

  16. Structural Parameters of M81 Globular Clusters: Analysis of their Intensity Profile

    NASA Astrophysics Data System (ADS)

    Santiago-Cortés, M.; Mayya, Y. D.; Rosa-González, D.

    2014-09-01

    We present here an analysis of the surface brightness profiles on the Hubble Space Telescope (HST) F435W and F814W images for 110 Globular Clusters (GCs) in M81. The structural parameters for each of these clusters were obtained by fitting a King model to the observed profiles. The profiles are well-fitted by the King model in the majority of the GCs. We used these structural parameters to classify the GCs based on their halo and core properties. Based on the physical extent of the halo, measured as the isophotal radius at μ_I = 24 mag/arcsec^2 , we divided the clusters into two groups — compact and classical. By analyzing the core properties, we found 7 cuspy clusters, with properties similar to the cuspy clusters found in the Milky Way. In addition, we found 2 clusters that have a blue excess in the core, similar to the brightest GC in M81. We show that all clusters at galactocentric distance less than 4 kpc are tidally limited in M81.

  17. 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…

  18. 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…

  19. 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…

  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. On-plate selective enrichment and self-desalting of peptides/proteins for direct MALDI MS analysis.

    PubMed

    Zeng, Zhoufang; Wang, Yandong; Shi, Shoulei; Wang, Lifeng; Guo, Xinhua; Lu, Nan

    2012-03-06

    In this paper, a new technique has been proposed to achieve simultaneous peptides/proteins enrichment and wash-free self-desalting on a novel sample support with a circle hydrophobic-hydrophilic-hydrophobic pattern. Upon deposition, the sample solution is first concentrated in a small area by repulsion of the hydrophobic outer layer, and then, the peptides/proteins and coexisting salt contaminants are selectively captured in different regions of the pattern through strong hydrophobic and hydrophilic attractions, respectively. As a result, the detection sensitivity is improved by 2 orders of magnitude better than the use of the traditional MALDI plate, and high-quality mass spectra are obtained even in the presence of NaCl (1 M), NH(4)HCO(3) (100 mM), or urea (1 M). The practical application of this method is further demonstrated by the successful analysis of myoglobin digests with high sequence coverage, demonstrating the great potential in proteomic research.

  2. Importance of Viral Sequence Length and Number of Variable and Informative Sites in Analysis of HIV Clustering.

    PubMed

    Novitsky, Vlad; Moyo, Sikhulile; Lei, Quanhong; DeGruttola, Victor; Essex, M

    2015-05-01

    To improve the methodology of HIV cluster analysis, we addressed how analysis of HIV clustering is associated with parameters that can affect the outcome of viral clustering. The extent of HIV clustering and tree certainty was compared between 401 HIV-1C near full-length genome sequences and subgenomic regions retrieved from the LANL HIV Database. Sliding window analysis was based on 99 windows of 1,000 bp and 45 windows of 2,000 bp. Potential associations between the extent of HIV clustering and sequence length and the number of variable and informative sites were evaluated. The near full-length genome HIV sequences showed the highest extent of HIV clustering and the highest tree certainty. At the bootstrap threshold of 0.80 in maximum likelihood (ML) analysis, 58.9% of near full-length HIV-1C sequences but only 15.5% of partial pol sequences (ViroSeq) were found in clusters. Among HIV-1 structural genes, pol showed the highest extent of clustering (38.9% at a bootstrap threshold of 0.80), although it was significantly lower than in the near full-length genome sequences. The extent of HIV clustering was significantly higher for sliding windows of 2,000 bp than 1,000 bp. We found a strong association between the sequence length and proportion of HIV sequences in clusters, and a moderate association between the number of variable and informative sites and the proportion of HIV sequences in clusters. In HIV cluster analysis, the extent of detectable HIV clustering is directly associated with the length of viral sequences used, as well as the number of variable and informative sites. Near full-length genome sequences could provide the most informative HIV cluster analysis. Selected subgenomic regions with a high extent of HIV clustering and high tree certainty could also be considered as a second choice.

  3. 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.

  4. 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

  5. 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

  6. 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.

  7. Use of multiple cluster analysis methods to explore the validity of a community outcomes concept map.

    PubMed

    Orsi, Rebecca

    2017-02-01

    Concept mapping is now a commonly-used technique for articulating and evaluating programmatic outcomes. However, research regarding validity of knowledge and outcomes produced with concept mapping is sparse. The current study describes quantitative validity analyses using a concept mapping dataset. We sought to increase the validity of concept mapping evaluation results by running multiple cluster analysis methods and then using several metrics to choose from among solutions. We present four different clustering methods based on analyses using the R statistical software package: partitioning around medoids (PAM), fuzzy analysis (FANNY), agglomerative nesting (AGNES) and divisive analysis (DIANA). We then used the Dunn and Davies-Bouldin indices to assist in choosing a valid cluster solution for a concept mapping outcomes evaluation. We conclude that the validity of the outcomes map is high, based on the analyses described. Finally, we discuss areas for further concept mapping methods research.

  8. Preliminary Cluster Analysis For Several Representatives Of Genus Kerivoula (Chiroptera: Vespertilionidae) in Borneo

    NASA Astrophysics Data System (ADS)

    Hasan, Noor Haliza; Abdullah, M. T.

    2008-01-01

    The aim of the study is to use cluster analysis on morphometric parameters within the genus Kerivoula to produce a dendrogram and to determine the suitability of this method to describe the relationship among species within this genus. A total of 15 adult male individuals from genus Kerivoula taken from sampling trips around Borneo and specimens kept at the zoological museum of Universiti Malaysia Sarawak were examined. A total of 27 characters using dental, skull and external body measurements were recorded. Clustering analysis illustrated the grouping and morphometric relationships between the species of this genus. It has clearly separated each species from each other despite the overlapping of measurements of some species within the genus. Cluster analysis provides an alternative approach to make a preliminary identification of a species.

  9. 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.

  10. Dual mode use requirements analysis for the institutional cluster.

    SciTech Connect

    Leland, Robert W.

    2003-09-01

    This paper analyzes what additional costs would be incurred in supporting dual-mode, i.e. both classified and unclassified use of the Institutional Computing (IC) hardware. The following five options are considered: periods processing in which a fraction of the system alternates in time between classified and unclassified modes, static split in which the system is constructed as a set of smaller clusters which remain in one mode or the other, re-configurable split in which the system is constructed in a split fashion but a mechanism is provided to reconfigure it very infrequently, red/black switching in which a mechanism is provided to switch sections of the system between modes frequently, and complementary operation in which parts of the system are operated entirely in one mode at one geographical site and entirely in the other mode at the other geographical site and other systems are repartitioned to balance work load. These options are evaluated against eleven criteria such as disk storage costs, distance computing costs, reductions in capability and capacity as a result of various factors etc. The evaluation is both qualitative and quantitative, and is captured in various summary tables.

  11. 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 +.

  12. 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.

  13. 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

  14. Enrichment 2.0 Gifted and Talented Education for the 21st Century

    ERIC Educational Resources Information Center

    Eckstein, Michelle

    2009-01-01

    Enrichment clusters, a component of the Schoolwide Enrichment Model, are multigrade investigative groups based on constructivist learning methodology. Enrichment clusters are organized around major disciplines, interdisciplinary themes, or cross-disciplinary topics. Within clusters, students are grouped across grade levels by interests and focused…

  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. Moving beyond Citation Analysis: How Surveys and Interviews Enhance, Enrich, and Expand Your Research Findings

    ERIC Educational Resources Information Center

    deVries, Susann; Kelly, Robert; Storm, Paula M.

    2010-01-01

    A traditional mixed methods research model of citation analysis, a survey, and interviews was selected to determine if the Bruce T. Halle Library at Eastern Michigan University owned the content that faculty cited in their research, if the collection was being utilized, and what library services the faculty used. The combination of objective data…

  17. Clustering of ant communities and indicator species analysis using self-organizing maps.

    PubMed

    Park, Sang-Hyun; Hosoishi, Shingo; Ogata, Kazuo; Kuboki, Yuzuru

    2014-09-01

    To understand the complex relationships that exist between ant assemblages and their habitats, we performed a self-organizing map (SOM) analysis to clarify the interactions among ant diversity, spatial distribution, and land use types in Fukuoka City, Japan. A total of 52 species from 12 study sites with nine land use types were collected from 1998 to 2012. A SOM was used to classify the collected data into three clusters based on the similarities between the ant communities. Consequently, each cluster reflected both the species composition and habitat characteristics in the study area. A detrended correspondence analysis (DCA) corroborated these findings, but removal of unique and duplicate species from the dataset in order to avoid sampling errors had a marked effect on the results; specifically, the clusters produced by DCA before and after the exclusion of specific data points were very different, while the clusters produced by the SOM were consistent. In addition, while the indicator value associated with SOMs clearly illustrated the importance of individual species in each cluster, the DCA scatterplot generated for species was not clear. The results suggested that SOM analysis was better suited for understanding the relationships between ant communities and species and habitat characteristics.

  18. Tracking undergraduate student achievement in a first-year physiology course using a cluster analysis approach.

    PubMed

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

    2015-12-01

    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 students into high-achieving (HA) and low-achieving (LA) clusters and to determine the ability of each summative assessment task to discriminate between HA and LA students. The two clusters identified in each semester were described as HA (n = 42) and LA (n = 115) in semester 1 (HA1 and LA1, respectively) and HA (n = 91) and LA (n = 42) in semester 2 (HA2 and LA2, respectively). In both semesters, HA and LA means for all inputs were different (all P < 0.001). Nineteen students moved from the HA1 group into the LA2 group, whereas 68 students moved from the LA1 group into the HA2 group. The overall order of importance of inputs that determined group membership was different in semester 1 compared with semester 2; in addition, the within-cluster order of importance in LA groups was different compared with HA groups. This method of analysis may 1) identify students who need extra instruction, 2) identify which assessment is more effective in discriminating between HA and LA students, and 3) provide quantitative evidence to track student achievement.

  19. Comprehensive behavioral analysis of cluster of differentiation 47 knockout mice.

    PubMed

    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.

  20. Coffee-ring effect-based simultaneous SERS substrate fabrication and analyte enrichment for trace analysis

    NASA Astrophysics Data System (ADS)

    Wang, Weidong; Yin, Yongguang; Tan, Zhiqiang; Liu, Jingfu

    2014-07-01

    Based on the ``coffee-ring effect'', we developed a highly efficient SERS platform which integrates the fabrication of SERS-active substrates and the preconcentration of analytes into one step. The high sensitivity, robustness, reproducibility and simplicity make this platform ideal for on-site analysis of small volume samples at low concentrations in complex matrices.Based on the ``coffee-ring effect'', we developed a highly efficient SERS platform which integrates the fabrication of SERS-active substrates and the preconcentration of analytes into one step. The high sensitivity, robustness, reproducibility and simplicity make this platform ideal for on-site analysis of small volume samples at low concentrations in complex matrices. Electronic supplementary information (ESI) available. See DOI: 10.1039/c4nr03198a

  1. A cluster analysis to investigating nurses' knowledge, attitudes, and skills regarding the clinical management system.

    PubMed

    Chan, M F

    2007-01-01

    Nurses' knowledge, attitudes, and skills regarding the Clinical Management System are explored by identifying profiles of nurses working in Hong Kong. A total of 282 nurses from four hospitals completed a self-reported questionnaire during the period from December 2004 to May 2005. Two-step cluster analysis yielded two clusters. The first cluster (n = 159, 56.4%) was labeled "negative attitudes, less skillful, and average knowledge" group. The second cluster (n = 123, 43.6%) was labeled "positive attitudes, good knowledge, but less skillful." There was a positive correlation in cluster 1 for nurses' knowledge and attitudes (rs = 0.28) and in cluster 2 for nurses' skills and attitudes (rs = 0.25) toward computerization. The study showed that senior and more highly educated nurses generally held more positive attitudes to computerization, whereas the attitudes among younger and less well educated nurses generally were more negative. Such findings should be used to formulate strategies to encourage nurses to resolve actual problems following computer training and to increase the depth and breadth of nurses' computer knowledge and skills and improve their attitudes toward computerization.

  2. Comparative genomic analysis of sixty mycobacteriophage genomes: Genome clustering, gene acquisition and gene size

    PubMed Central

    Hatfull, Graham F.; Jacobs-Sera, Deborah; Lawrence, Jeffrey G.; Pope, Welkin H.; Russell, Daniel A.; Ko, Ching-Chung; Weber, Rebecca J.; Patel, Manisha C.; Germane, Katherine L.; Edgar, Robert H.; Hoyte, Natasha N.; Bowman, Charles A.; Tantoco, Anthony T.; Paladin, Elizabeth C.; Myers, Marlana S.; Smith, Alexis L.; Grace, Molly S.; Pham, Thuy T.; O'Brien, Matthew B.; Vogelsberger, Amy M.; Hryckowian, Andrew J.; Wynalek, Jessica L.; Donis-Keller, Helen; Bogel, Matt W.; Peebles, Craig L.; Cresawn, Steve G.; Hendrix, Roger W.

    2010-01-01

    Mycobacteriophages are viruses that infect mycobacterial hosts. Expansion of a collection of sequenced phage genomes to a total of sixty – all infecting a common bacterial host – provides further insight into their diversity and evolution. Of the sixty phage genomes, 55 can be grouped into nine clusters according to their nucleotide sequence similarities, five of which can be further divided into subclusters; five genomes do not cluster with other phages. The sequence diversity between genomes within a cluster varies greatly; for example, the six genomes in cluster D share more than 97.5% average nucleotide similarity with each other. In contrast, similarity between the two genomes in Cluster I is barely detectable by diagonal plot analysis. The total of 6,858 predicted ORFs have been grouped into 1523 phamilies (phams) of related sequences, 46% of which possess only a single member. Only 18.8% of the phams have sequence similarity to non-mycobacteriophage database entries and fewer than 10% of all phams can be assigned functions based on database searching or synteny. Genome clustering facilitates the identification of genes that are in greatest genetic flux and are more likely to have been exchanged horizontally in relatively recent evolutionary time. Although mycobacteriophage genes exhibit smaller average size than genes of their host (205 residues compared to 315), phage genes in higher flux average only ∼100 amino acids, suggesting that the primary units of genetic exchange correspond to single protein domains. PMID:20064525

  3. Adults' Physical Activity Patterns across Life Domains: Cluster Analysis with Replication

    PubMed Central

    Rovniak, Liza S.; Sallis, James F.; Saelens, Brian E.; Frank, Lawrence D.; Marshall, Simon J.; Norman, Gregory J.; Conway, Terry L.; Cain, Kelli L.; Hovell, Melbourne F.

    2010-01-01

    Objective Identifying adults' physical activity patterns across multiple life domains could inform the design of interventions and policies. Design Cluster analysis was conducted with adults in two US regions (Baltimore-Washington DC, n = 702; Seattle-King County, n = 987) to identify different physical activity patterns based on adults' reported physical activity across four life domains: leisure, occupation, transport, and home. Objectively measured physical activity, and psychosocial and built (physical) environment characteristics of activity patterns were examined. Main Outcome Measures Accelerometer-measured activity, reported domain-specific activity, psychosocial characteristics, built environment, body mass index (BMI). Results Three clusters replicated (kappa = .90-.93) across both regions: Low Activity, Active Leisure, and Active Job. The Low Activity and Active Leisure adults were demographically similar, but Active Leisure adults had the highest psychosocial and built environment support for activity, highest accelerometer-measured activity, and lowest BMI. Compared to the other clusters, the Active Job cluster had lower socioeconomic status and intermediate accelerometer-measured activity. Conclusion Adults can be clustered into groups based on their patterns of accumulating physical activity across life domains. Differences in psychosocial and built environment support between the identified clusters suggest that tailored interventions for different subgroups may be beneficial. PMID:20836604

  4. Enrichment of low molecular weight serum proteins using acetonitrile precipitation for mass spectrometry based proteomic analysis.

    PubMed

    Kay, Richard; Barton, Chris; Ratcliffe, Lucy; Matharoo-Ball, Balwir; Brown, Pamela; Roberts, Jane; Teale, Phil; Creaser, Colin

    2008-10-01

    A rapid acetonitrile (ACN)-based extraction method has been developed that reproducibly depletes high abundance and high molecular weight proteins from serum prior to mass spectrometric analysis. A nanoflow liquid chromatography/tandem mass spectrometry (nano-LC/MS/MS) multiple reaction monitoring (MRM) method for 57 high to medium abundance serum proteins was used to characterise the ACN-depleted fraction after tryptic digestion. Of the 57 targeted proteins 29 were detected and albumin, the most abundant protein in serum and plasma, was identified as the 20th most abundant protein in the extract. The combination of ACN depletion and one-dimensional nano-LC/MS/MS enabled the detection of the low abundance serum protein, insulin-like growth factor-I (IGF-I), which has a serum concentration in the region of 100 ng/mL. One-dimensional sodium dodecyl sulfate/polyacrylamide gel electrophoresis (SDS-PAGE) analysis of the depleted serum showed no bands corresponding to proteins of molecular mass over 75 kDa after extraction, demonstrating the efficiency of the method for the depletion of high molecular weight proteins. Total protein analysis of the ACN extracts showed that approximately 99.6% of all protein is removed from the serum. The ACN-depletion strategy offers a viable alternative to the immunochemistry-based protein-depletion techniques commonly used for removing high abundance proteins from serum prior to MS-based proteomic analyses.

  5. 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

  6. 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.

  7. Cluster Analysis of Indonesian Province Based on Household Primary Cooking Fuel Using K-Means

    NASA Astrophysics Data System (ADS)

    Huda, S. N.

    2017-03-01

    Each household definitely provides installations for cooking. Kerosene, which is refined from petroleum products once dominated types of primary fuel for cooking in Indonesia, whereas kerosene has an expensive cost and small efficiency. Other household use LPG as their primary cooking fuel. However, LPG supply is also limited. In addition, with a very diverse environments and cultures in Indonesia led to diversity of the installation type of cooking, such as wood-burning stove brazier. The government is also promoting alternative fuels, such as charcoal briquettes, and fuel from biomass. The use of other fuels is part of the diversification of energy that is expected to reduce community dependence on petroleum-based fuels. The use of various fuels in cooking that vary from one region to another reflects the distribution of fuel basic use by household. By knowing the characteristics of each province, the government can take appropriate policies to each province according each character. Therefore, it would be very good if there exist a cluster analysis of all provinces in Indonesia based on the type of primary cooking fuel in household. Cluster analysis is done using K-Means method with K ranging from 2-5. Cluster results are validated using Silhouette Coefficient (SC). The results show that the highest SC achieved from K = 2 with SC value 0.39135818388151. Two clusters reflect provinces in Indonesia, one is a cluster of more traditional provinces and the other is a cluster of more modern provinces. The cluster results are then shown in a map using Google Map API.

  8. Pathways enrichment analysis for differentially expressed genes in squamous lung cancer.

    PubMed

    Qian, Liqiang; Luo, Qingquan; Zhao, Xiaojing; Huang, Jia

    2014-01-01

    Squamous lung cancer (SQLC) is a common type of lung cancer, but its oncogenesis mechanism is not so clear. The aim of this study was to screen the potential pathways changed in SQLC and elucidate the mechanism of it. Published microarray data of GSE3268 series was downloaded from Gene Expression Omnibus (GEO). Significance analysis of microarrays was performed using software R, and differentially expressed genes (DEGs) were harvested. The functions and pathways of DEGs were mapped in Gene Otology and KEGG pathway database, respectively. A total of 2961 genes were filtered as DEGs between normal and SQLC cells. Cell cycle and metabolism were the mainly changed functions of SQLC cells. Meanwhile genes such as MCM, RFC, FEN1, and POLD may induce SQLC through DNA replication pathway, and genes such as PTTG1, CCNB1, CDC6, and PCNA may be involved in SQLC through cell cycle pathway. It is demonstrated that pathway analysis is useful in the identification of target genes in SQLC.

  9. 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.

  10. Field of Study Choice: Using Conjoint Analysis and Clustering

    ERIC Educational Resources Information Center

    Shtudiner, Ze'ev; Zwilling, Moti; Kantor, Jeffrey

    2017-01-01

    Purpose: The purpose of this paper is to measure student's preferences regarding various attributes that affect their decision process while choosing a higher education area of study. Design/ Methodology/Approach: The paper exhibits two different models which shed light on the perceived value of each examined area of study: conjoint analysis and…

  11. Analysis of traffic accidents on rural highways using Latent Class Clustering and Bayesian Networks.

    PubMed

    de Oña, Juan; López, Griselda; Mujalli, Randa; Calvo, Francisco J

    2013-03-01

    One of the principal objectives of traffic accident analyses is to identify key factors that affect the severity of an accident. However, with the presence of heterogeneity in the raw data used, the analysis of traffic accidents becomes difficult. In this paper, Latent Class Cluster (LCC) is used as a preliminary tool for segmentation of 3229 accidents on rural highways in Granada (Spain) between 2005 and 2008. Next, Bayesian Networks (BNs) are used to identify the main factors involved in accident severity for both, the entire database (EDB) and the clusters previously obtained by LCC. The results of these cluster-based analyses are compared with the results of a full-data analysis. The results show that the combined use of both techniques is very interesting as it reveals further information that would not have been obtained without prior segmentation of the data. BN inference is used to obtain the variables that best identify accidents with killed or seriously injured. Accident type and sight distance have been identify in all the cases analysed; other variables such as time, occupant involved or age are identified in EDB and only in one cluster; whereas variables vehicles involved, number of injuries, atmospheric factors, pavement markings and pavement width are identified only in one cluster.

  12. Gene microarray data analysis using parallel point-symmetry-based clustering.

    PubMed

    Sarkar, Anasua; Maulik, Ujjwal

    2015-01-01

    Identification of co-expressed genes is the central goal in microarray gene expression analysis. Point-symmetry-based clustering is an important unsupervised learning technique for recognising symmetrical convex- or non-convex-shaped clusters. To enable fast clustering of large microarray data, we propose a distributed time-efficient scalable approach for point-symmetry-based K-Means algorithm. A natural basis for analysing gene expression data using symmetry-based algorithm is to group together genes with similar symmetrical expression patterns. This new parallel implementation also satisfies linear speedup in timing without sacrificing the quality of clustering solution on large microarray data sets. The parallel point-symmetry-based K-Means algorithm is compared with another new parallel symmetry-based K-Means and existing parallel K-Means over eight artificial and benchmark microarray data sets, to demonstrate its superiority, in both timing and validity. The statistical analysis is also performed to establish the significance of this message-passing-interface based point-symmetry K-Means implementation. We also analysed the biological relevance of clustering solutions.

  13. Hierarchical cluster analysis for exposure assessment of workers in the Semiconductor Health Study.

    PubMed

    Hines, C J; Selvin, S; Samuels, S J; Hammond, S K; Woskie, S R; Hallock, M F; Schenker, M B

    1995-12-01

    The fabrication of integrated circuits in the semiconductor industry involves worker exposures to multiple chemical and physical agents. The potential for a high degree of correlation among exposure variables was of concern in the Semiconductor Health Study. Hierarchical cluster analysis was used to identify groups or "clusters" of correlated variables. Several variations of hierarchical cluster analysis were performed on 14 chemical and physical agents, using exposure data on 882 subjects from the historical cohort of the epidemiological studies. Similarity between agent pairs was determined by calculating two metrics of dissimilarity, and hierarchical trees were constructed using three clustering methods. Among subjects exposed to ethylene-based glycol ethers (EGE), xylene, or n-butyl acetate (nBA), 83% were exposed to EGE and xylene, 86% to EGE and nBA, and 94% to xylene and nBA, suggesting that exposures to EGE, xylene, and nBA were highly correlated. A high correlation was also found for subjects exposed to boron and phosphorus (80%). The trees also revealed cluster groups containing agents associated with work-group exposure categories developed for the epidemiologic analyses.

  14. 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

  15. 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).

  16. Analysis of the clustering of inertial particles in turbulent flows

    NASA Astrophysics Data System (ADS)

    Esmaily-Moghadam, Mahdi; Mani, Ali

    2016-12-01

    An asymptotic solution is derived for the motion of inertial particles exposed to Stokes drag in an unsteady random flow. This solution provides an estimate for the sum of Lyapunov exponents as a function of the Stokes number and Lagrangian strain- and rotation-rate autocovariance functions. The sum of exponents in a Lagrangian framework is the rate of contraction of clouds of particles, and in an Eulerian framework, it is the concentration-weighted divergence of the particle velocity field. Previous literature offers an estimate of the divergence of the particle velocity field, which is applicable only in the limit of small Stokes numbers [Robinson, Comm. Pure Appl. Math. 9, 69 (1956), 10.1002/cpa.3160090105 and Maxey, J. Fluid Mech. 174, 441 (1987), 10.1017/S0022112087000193] (R-M). In addition to reproducing R-M at this limit, our analysis provides a first-order correction to R-M at larger Stokes numbers. Our analysis is validated by a directly computed rate of contraction of clouds of particles from simulations of particles in homogeneous isotropic turbulence over a broad range of Stokes numbers. Our analysis and R-M predictions agree well with the direct computations at the limit of small Stokes numbers. At large Stokes numbers, in contrast to R-M, our model predictions remain bounded. In spite of an improvement over R-M, our analysis fails to predict the expansion of high Stokes clouds observed in the direct computations. Consistent with the general trend of particle segregation versus Stokes number, our analysis shows a maximum rate of contraction at an intermediate Stokes number of O (1 ) and minimal rates of contraction at small and large Stokes numbers.

  17. Constrained Ordination Analysis with Enrichment of Bell-Shaped Response Functions.

    PubMed

    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.

  18. 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.

  19. 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,…

  20. Spectral analysis of A and F dwarf members of the open cluster M6: preliminary results

    NASA Astrophysics Data System (ADS)

    Kılıçoǧlu, T.; Monier, R.; Fossati, L.

    2010-12-01

    We present the first abundance analysis of CD-32 13109 (NGC 6405 47), member of the M6 open cluster. The photospheric abundances of 14 chemical elements were determined by comparing synthetic spectra and observed spectra of the star. Findings show that this star should be an Am star.

  1. Comparative Evaluation of Two Superior Stopping Rules for Hierarchical Cluster Analysis.

    ERIC Educational Resources Information Center

    Atlas, Robert S.; Overall, John E.

    1994-01-01

    A split-sample replication stopping rule for hierarchical cluster analysis is compared with the internal criterion previously found superior by Milligan and Cooper (1985) in their comparison of 30 different procedures. Situations under which the methods are equivalent or not equally useful are discussed. (SLD)

  2. Posterior AD-Type Pathology: Cognitive Subtypes Emerging from a Cluster Analysis

    PubMed Central

    Cappa, Antonella; Ciccarelli, Nicoletta; Silveri, Maria Caterina

    2014-01-01

    Background. “Posterior shift” of the neuropathological changes of Alzheimer's disease (AD) produces a syndrome (posterior cortical atrophy) (PCA) dominated by high-level visual deficits. Objective. To explore in patients with AD-type pathology whether a data-driven analysis (cluster analysis) based on neuropsychological findings resulted in the emergence of different subgroups of patients; in particular to find out whether it was possible to identify patients with visuospatial deficits consistent with the hypothesis that PCA is a “dorsal stream” syndrome or, rather, whether there were subgroups of patients with different types of impairment within the high-level visual domain. Methods. 23 PCA and 16 DAT patients were studied. By a principal component analysis performed on a wide range of neuropsychological tasks, 15 variables were obtained that loaded onto five main factors (memory, language, perceptual, visuospatial, and calculation) which entered a hierarchical cluster analysis. Results. Four clusters of cognitive impairment emerged: visuospatial/perceptual, memory, perceptual/calculation, and language. Only in the first cluster a visuospatial deficit clearly emerged. Conclusions. AD pathology produces not only variants dominated by memory (DAT) and, to a lesser extent, visuospatial deficit (PCA), but also other distinct syndromic subtypes with disorders in visual perception and language which reflect a different vulnerability of specific functional networks. PMID:24994944

  3. [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.

  4. 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…

  5. Structure of Hierarchic Clusterings: Implications for Information Retrieval and for Multivariate Data Analysis.

    ERIC Educational Resources Information Center

    Murtagh, F.

    1984-01-01

    Using examples of data from the areas of information retrieval and of multivariate data analysis, six hierarchic clustering algorithms (single link, median, centroid, group average, complete link, Wards's) are examined and evaluated by using three proposed coefficients of hierarchic structure. Nine references are cited. (EJS)

  6. 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…

  7. 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…

  8. 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.

  9. 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…

  10. 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…

  11. 2 x 2 Achievement Goals and Achievement Emotions: A Cluster Analysis of Students' Motivation

    ERIC Educational Resources Information Center

    Jang, Leong Yeok; Liu, Woon Chia

    2012-01-01

    This study sought to better understand the adoption of multiple achievement goals at an intra-individual level, and its links to emotional well-being, learning, and academic achievement. Participants were 480 Secondary Two students (aged between 13 and 14 years) from two coeducational government schools. Hierarchical cluster analysis revealed the…

  12. Enrichment analysis of Alu elements with different spatial chromatin proximity in the human genome.

    PubMed

    Gu, Zhuoya; Jin, Ke; Crabbe, M James C; Zhang, Yang; Liu, Xiaolin; Huang, Yanyan; Hua, Mengyi; Nan, Peng; Zhang, Zhaolei; Zhong, Yang

    2016-04-01

    Transposable elements (TEs) have no longer been totally considered as "junk DNA" for quite a time since the continual discoveries of their multifunctional roles in eukaryote genomes. As one of the most important and abundant TEs that still active in human genome, Alu, a SINE family, has demonstrated its indispensable regulatory functions at sequence level, but its spatial roles are still unclear. Technologies based on 3C (chromosome conformation capture) have revealed the mysterious three-dimensional structure of chromatin, and make it possible to study the distal chromatin interaction in the genome. To find the role TE playing in distal regulation in human genome, we compiled the new released Hi-C data, TE annotation, histone marker annotations, and the genome-wide methylation data to operate correlation analysis, and found that the density of Alu elements showed a strong positive correlation with the level of chromatin interactions (hESC: r = 0.9, P < 2.2 × 10(16); IMR90 fibroblasts: r = 0.94, P < 2.2 × 10(16)) and also have a significant positive correlation with some remote functional DNA elements like enhancers and promoters (Enhancer: hESC: r = 0.997, P = 2.3 × 10(-4); IMR90: r = 0.934, P = 2 × 10(-2); Promoter: hESC: r = 0.995, P = 3.8 × 10(-4); IMR90: r = 0.996, P = 3.2 × 10(-4)). Further investigation involving GC content and methylation status showed the GC content of Alu covered sequences shared a similar pattern with that of the overall sequence, suggesting that Alu elements also function as the GC nucleotide and CpG site provider. In all, our results suggest that the Alu elements may act as an alternative parameter to evaluate the Hi-C data, which is confirmed by the correlation analysis of Alu elements and histone markers. Moreover, the GC-rich Alu sequence can bring high GC content and methylation flexibility to the regions with more distal chromatin contact, regulating the transcription of tissue-specific genes.

  13. Identification of Salmonella Typhimurium deubiquitinase SseL substrates by immunoaffinity enrichment and quantitative proteomic analysis

    DOE PAGES

    Nakayasu, Ernesto S.; Sydor, Michael A.; Brown, Roslyn N.; ...

    2015-07-06

    Ubiquitination is a key protein post-translational modification that regulates many important cellular pathways and whose levels are regulated by equilibrium between the activities of ubiquitin ligases and deubiquitinases. Here we present a method to identify specific deubiquitinase substrates based on treatment of cell lysates with recombinant enzymes, immunoaffinity purification and global quantitative proteomic analysis. As model system to identify substrates, we used a virulence-related deubiquitinase secreted by Salmonella enterica serovar Typhimurium into the host cells, SseL. By using this approach two SseL substrates were identified in RAW 264.7 murine macrophage-like cell line, S100A6 and het-erogeneous nuclear ribonuclear protein K, inmore » addition to the previously reported K63-linked ubiquitin chains. These substrates were further validated by a combination of enzymatic and binding assays. Finally, this method can be used for the systematic identification of substrates of deubiquitinases from other organisms and applied to study their functions in physiology and disease.« less

  14. Identification of Salmonella Typhimurium deubiquitinase SseL substrates by immunoaffinity enrichment and quantitative proteomic analysis

    SciTech Connect

    Nakayasu, Ernesto S.; Sydor, Michael A.; Brown, Roslyn N.; Sontag, Ryan L.; Sobreira, Tiago; Slysz, Gordon W.; Humphrys, Daniel R.; Skarina, Tatiana; Onoprienko, Olena; Di Leo, Rosa; Kaiser, Brooke L. Deatherage; Li, Jie; Ansong, Charles; Cambronne, Eric; Smith, Richard D.; Savchenko, Alexei; Adkins, Joshua N.

    2015-07-06

    Ubiquitination is a key protein post-translational modification that regulates many important cellular pathways and whose levels are regulated by equilibrium between the activities of ubiquitin ligases and deubiquitinases. Here we present a method to identify specific deubiquitinase substrates based on treatment of cell lysates with recombinant enzymes, immunoaffinity purification and global quantitative proteomic analysis. As model system to identify substrates, we used a virulence-related deubiquitinase secreted by Salmonella enterica serovar Typhimurium into the host cells, SseL. By using this approach two SseL substrates were identified in RAW 264.7 murine macrophage-like cell line, S100A6 and het-erogeneous nuclear ribonuclear protein K, in addition to the previously reported K63-linked ubiquitin chains. These substrates were further validated by a combination of enzymatic and binding assays. Finally, this method can be used for the systematic identification of substrates of deubiquitinases from other organisms and applied to study their functions in physiology and disease.

  15. Microfluidic enrichment for the single cell analysis of circulating tumor cells

    PubMed Central

    Yeo, Trifanny; Tan, Swee Jin; Lim, Chew Leng; Lau, Dawn Ping Xi; Chua, Yong Wei; Krisna, Sai Sakktee; Iyer, Gopal; Tan, Gek San; Lim, Tony Kiat Hon; Tan, Daniel S.W.; Lim, Wan-Teck; Lim, Chwee Teck

    2016-01-01

    Resistance to drug therapy is a major concern in cancer treatment. To probe clones resistant to chemotherapy, the current approach is to conduct pooled cell analysis. However, this can yield false negative outcomes, especially when we are analyzing a rare number of circulating tumor cells (CTCs) among an abundance of other cell types. Here, we develop a microfluidic device that is able to perform high throughput, selective picking and isolation of single CTC to 100% purity from a larger population of other cells. This microfluidic device can effectively separate the very rare CTCs from blood samples from as few as 1 in 20,000 white blood cells. We first demonstrate isolation of pure tumor cells from a mixed population and track variations of acquired T790M mutations before and after drug treatment using a model PC9 cell line. With clinical CTC samples, we then show that the isolated single CTCs are representative of dominant EGFR mutations such as T790M and L858R found in the primary tumor. With this single cell recovery device, we can potentially implement personalized treatment not only through detecting genetic aberrations at the single cell level, but also through tracking such changes during an anticancer therapy. PMID:26924553

  16. Performance evaluation and bacteria analysis of AFB-MFC enriched with high-strength synthetic wastewater.

    PubMed

    Huang, Jian-sheng; Guo, Yong; Yang, Ping; Li, Chong-ming; Gao, Hui; Feng, Li; Zhang, Yun

    2014-01-01

    In order to study the performance and bacterial communities of an anaerobic fluidized bed microbial fuel cell (AFB-MFC) system, the 16S rDNA gene sequencing was applied, and high-strength synthetic wastewater was treated by the AFB-MFC system. The high-strength synthetic wastewater, in which the concentrations of chemical oxygen demand (COD), nitrite nitrogen, and nitrate nitrogen were above 19,000, 2,516-3,871 and 927-1,427 mg/L, was treated by the AFB-MFC system. The removal efficiency of COD, nitrite nitrogen, and nitrate nitrogen reached 70-89, 98 and 98%, while the maximum voltage was 394 mV. The bacteria analysis revealed the presence of Alistipes putredinis, Carnobacterium sp., Victivallis vadensis, Klebsiella pneumoniae, Thauera sp., Parabacteroides merdae, Parvimonas micra, Parabacteroides sp., and Desulfomicrobium baculatum in the anode chamber. In addition, the Klebsiella pneumoniae was observed to have the capability of organic degradation and electricity generation, while the Thauera sp. has the capability of denitrification.

  17. Quantification, 2DE analysis and identification of enriched glycosylated proteins from mouse muscles: Difficulties and alternatives.

    PubMed

    de Fátima MenegociEugênio, Patrícia; Assunção, Nilson Antonio; Sciandra, Francesca; Aquino, Adriano; Brancaccio, Andrea; Carrilho, Emanuel

    2016-01-01

    One of the problems with 2DE is that proteins present in low amounts in a sample are usually not detected, since their signals are masked by the predominant proteins. The elimination of these abundant proteins is not a guaranteed solution to achieve the desired results. The main objective of this study was the comparison of common and simple methodologies employed for 2DE analysis followed by MS identification, focusing on a pre-purified sample using a wheat germ agglutinin (WGA) column. Adult male C57Black/Crj6 (C57BL/6) mice were chosen as the model animal in this study; the gastrocnemius muscles were collected and processed for the experiments. The initial fractionation with succinylated WGA was successful for the elimination of the most abundant proteins. Two quantification methods were employed for the purified samples, and bicinchoninic acid (BCA) was proven to be most reliable for the quantification of glycoproteins. The gel staining method, however, was found to be decisive for the detection of specific proteins, since their structures affect the interaction of the dye with the peptide backbone. The Coomassie Blue R-250 dye very weakly stained the gel with the WGA purified sample. When the same gel was stained with silver nitrate, however, MS could positively assign 12 new spots. The structure of the referred proteins was not found to be prone to interaction with Coomassie blue.

  18. 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.

  19. Cluster analysis of resting-state fMRI time series.

    PubMed

    Mezer, Aviv; Yovel, Yossi; Pasternak, Ofer; Gorfine, Tali; Assaf, Yaniv

    2009-05-01

    Functional MRI (fMRI) has become one of the leading methods for brain mapping in neuroscience. Recent advances in fMRI analysis were used to define the default state of brain activity, functional connectivity and basal activity. Basal activity measured with fMRI raised tremendous interest among neuroscientists since synchronized brain activity pattern could be retrieved while the subject rests (resting state fMRI). During recent years, a few signal processing schemes have been suggested to analyze the resting state blood oxygenation level dependent (BOLD) signal from simple correlations to spectral decomposition. In most of these analysis schemes, the question asked was which brain areas "behave" in the time domain similarly to a pre-specified ROI. In this work we applied short time frequency analysis and clustering to study the spatial signal characteristics of resting state fMRI time series. Such analysis revealed that clusters of similar BOLD fluctuations are found in the cortex but also in the white matter and sub-cortical gray matter regions (thalamus). We found high similarities between the BOLD clusters and the neuro-anatomical appearance of brain regions. Additional analysis of the BOLD time series revealed a strong correlation between head movements and clustering quality. Experiments performed with T1-weighted time series also provided similar quality of clustering. These observations led us to the conclusion that non-functional contributions to the BOLD time series can also account for symmetric appearance of signal fluctuations. These contributions may include head motions, the underling microvasculature anatomy and cellular morphology.

  20. Module Cluster: IFE - 001.00 (GSC) Basic Terminology and Analysis of Writings Concerned with Educational Issues.

    ERIC Educational Resources Information Center

    Zahn, R. D.

    This document is one of the module clusters developed for the Camden Teacher Corps project. The purpose of this module cluster is to enable students to define and use basic terminology in the discussion and analysis of educational issues, to use various approaches in studying an issue, and to apply critical analysis skills to written and spoken…

  1. 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…

  2. Investigating nurses' knowledge, attitudes, and skills patterns towards clinical management system: results of a cluster analysis.

    PubMed

    Chan, M F

    2006-09-01

    To determine whether definable subtypes exist within a cohort of Hong Kong nurses as related to the clinical management system use in their clinical practices based on their knowledge, attitudes, skills, and background factors. Data were collected using a structured questionnaire. The sample of 242 registered nurses was recruited from three hospitals in Hong Kong. The study employs personal and demographic variables, knowledge, attitudes, and skills scale. A cluster analysis yielded two clusters. Each cluster represents a different profile of Hong Kong nurses on the clinical management system use in their clinical practices. The first group (Cluster 1) was labeled 'lower attitudes, less skilful and average knowledge' group, and represented 55.4% of the total respondents. The second group (Cluster 2) was labeled as 'positive attitudes, good knowledge but less skilful'. They comprised almost 44.6% of this nursing sample. Cluster 2 had more older nurses, the majority were educated to the baccalaureate or above level, with more than 10 years working experience, and they held a more senior ranking then Cluster 1. A clear profile of Hong Kong nurses may benefit healthcare professionals in making appropriate education or assistance to prompt the use of the clinical management system by nurses an officially recognized profession. The findings were useful in determining nurse-users' specific needs and their preferences for modification of the clinical management system. Such findings should be used to formulate strategies to encourage nurses to resolve actual problems following computer training and to increase the depth and breadth of nurses' knowledge, attitudes, and skills toward such system.

  3. Neutron activation analysis of the 30Si content of highly enriched 28Si: proof of concept and estimation of the achievable uncertainty

    NASA Astrophysics Data System (ADS)

    D'Agostino, G.; Mana, G.; Oddone, M.; Prata, M.; Bergamaschi, L.; Giordani, L.

    2014-06-01

    We investigated the use of neutron activation to estimate the 30Si mole fraction of the ultra-pure silicon material highly enriched in 28Si for the measurement of the Avogadro constant. Specifically, we developed a relative method based on instrumental neutron activation analysis and using a natural-Si sample as a standard. To evaluate the achievable uncertainty, we irradiated a 6 g sample of a natural-Si material and modelled experimentally the signal that would be produced by a sample of the 28Si-enriched material of similar mass and subjected to the same measurement conditions. The extrapolation of the expected uncertainty from the experimental data indicates that a measurement of the 30Si mole fraction of the 28Si-enriched material might reach a 4% relative combined standard uncertainty.

  4. 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.

  5. Bacterial antibiotic resistance studies using in vitro dynamic models: Population analysis vs. susceptibility testing as endpoints of mutant enrichment.

    PubMed

    Firsov, Alexander A; Strukova, Elena N; Portnoy, Yury A; Shlykova, Darya S; Zinner, Stephen H

    2015-09-01

    Emergence of bacterial antibiotic resistance is usually characterised either by population analysis or susceptibility testing. To compare these endpoints in their ability to demonstrate clear relationships with the ratio of 24-h area under the concentration-time curve (AUC24) to the minimum inhibitory concentration (MIC), enrichment of ciprofloxacin-resistant mutants of four clinical isolates of Pseudomonas aeruginosa was studied in an in vitro dynamic model that simulates mono-exponential pharmacokinetics of ciprofloxacin over a wide range of the AUC24/MIC ratios. Each organism was exposed to twice-daily ciprofloxacin for 3 days. Amplification of resistant mutants was monitored by plating on media with 2×, 4×, 8× and 16× MIC of ciprofloxacin. Population analysis data were expressed by the area under the bacterial mutant concentration-time curve (AUBCM). Changes in P. aeruginosa susceptibility were examined by daily MIC determinations. To account for the different susceptibilities of P. aeruginosa strains, post-exposure MICs (MICfinal) were related to the MICs determined with the starting inoculum (MICinitial). For each organism, AUC24/MIC relationships both with AUBCM and MICfinal/MICinitial were bell-shaped, but the latter were more strain-specific than the former. Using combined data on all four isolates, AUBCM showed a better correlation than MICfinal/MICinitial (r(2)=0.75 vs. r(2)=0.53). The shift of MICfinal/MICinitial relative to AUBCM vs. AUC24/MIC curves resulted in a weak correlation between AUBCM and MICfinal/MICinitial (r(2)=0.41). These data suggest that population analysis is preferable to susceptibility testing in bacterial resistance studies and that these endpoints should not be considered interchangeable.

  6. 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.

  7. 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.

  8. Analysis of a continuous-variable quadripartite cluster state from a single optical parametric oscillator

    SciTech Connect

    Midgley, S. L. W.; Olsen, M. K.; Bradley, A. S.; Pfister, O.

    2010-11-15

    We examine the feasibility of generating continuous-variable multipartite entanglement in an intracavity concurrent downconversion scheme that has been proposed for the generation of cluster states by Menicucci et al. [Phys. Rev. Lett. 101, 130501 (2008)]. By calculating optimized versions of the van Loock-Furusawa correlations we demonstrate genuine quadripartite entanglement and investigate the degree of entanglement present. Above the oscillation threshold the basic cluster state geometry under consideration suffers from phase diffusion. We alleviate this problem by incorporating a small injected signal into our analysis. Finally, we investigate squeezed joint operators. While the squeezed joint operators approach zero in the undepleted regime, we find that this is not the case when we consider the full interaction Hamiltonian and the presence of a cavity. In fact, we find that the decay of these operators is minimal in a cavity, and even depletion alone inhibits cluster state formation.

  9. [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.

  10. 3D Building Models Segmentation Based on K-Means++ Cluster Analysis

    NASA Astrophysics Data System (ADS)

    Zhang, C.; Mao, B.

    2016-10-01

    3D mesh model segmentation is drawing increasing attentions from digital geometry processing field in recent years. The original 3D mesh model need to be divided into separate meaningful parts or surface patches based on certain standards to support reconstruction, compressing, texture mapping, model retrieval and etc. Therefore, segmentation is a key problem for 3D mesh model segmentation. In this paper, we propose a method to segment Collada (a type of mesh model) 3D building models into meaningful parts using cluster analysis. Common clustering methods segment 3D mesh models by K-means, whose performance heavily depends on randomized initial seed points (i.e., centroid) and different randomized centroid can get quite different results. Therefore, we improved the existing method and used K-means++ clustering algorithm to solve this problem. Our experiments show that K-means++ improves both the speed and the accuracy of K-means, and achieve good and meaningful results.

  11. 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.

  12. 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.

  13. Proteomic Analysis of Protein-Protein Interactions within the CSD Fe-S Cluster Biogenesis System

    PubMed Central

    Bolstad, Heather M.; Botelho, Danielle J.; Wood, Matthew J.

    2010-01-01

    Fe-S cluster biogenesis is of interest to many fields, including bioenergetics and gene regulation. The CSD system is one of three Fe-S cluster biogenesis systems in E. coli and is comprised of the cysteine desulfurase CsdA, the sulfur acceptor protein CsdE, and the E1-like protein CsdL. The biological role, biochemical mechanism, and protein targets of the system remain uncharacterized. Here we present that the active site CsdE C61 has a lowered pKa value of 6.5, which is nearly identical to that of C51 in the homologous SufE protein and which is likely critical for its function. We observed that CsdE forms disulfide bonds with multiple proteins and identified the proteins that copurify with CsdE. The identification of Fe-S proteins and both putative and established Fe-S cluster assembly (ErpA, glutaredoxin-3, glutaredoxin-4) and sulfur trafficking (CsdL, YchN) proteins supports the two-pathway model, in which the CSD system is hypothesized to synthesize both Fe-S clusters and other sulfur-containing cofactors. We suggest that the identified Fe-S cluster assembly proteins may be the scaffold and/or shuttle proteins for the CSD system. By comparison with previous analysis of SufE, we demonstrate that there is some overlap in the CsdE and SufE interactomes. PMID:20734996

  14. 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.

  15. 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.

  16. A cluster analysis of neuronal activity in the dorsal premotor cortical area for neuroprosthetic control.

    PubMed

    Ye, N; Roontiva, A; He, J

    2008-01-01

    With the use of the neuronal data acquisition technology, millisecond-level multi-electrode data from several regions of the premotor area were obtained from two rhesus monkeys trained to perform arm-reach tasks with visual cues in virtual reality. In each trial, animals were required to select and perform one of the four possible arm reaching movements to the target on the top-left or top-right of the virtual reality space. They were also required to decide whether they would move their arms straight to the target or curve them in order to avoid the obstacle that was presented. After the acquired neuronal signals were processed, unsupervised Hierarchical clustering and K-means clustering were performed to uncover the similarity and difference in the average firing rate of spike train data between neurons and phases for each experiment condition. The clustering results indicate the similarity of neuronal data in the movement planning and actual movement phases, and the difference of such data from the data in information processing phases. Furthermore, the clustering results show that when the target location is on the right, the move planning started earlier. The analysis of variance (ANOVA) on the neuronal data confirms the results from the hierarchical clustering.

  17. Integrated simultaneous analysis of different biomedical data types with exact weighted bi-cluster editing.

    PubMed

    Sun, Peng; Guo, Jiong; Baumbach, Jan

    2012-07-17

    The explosion of biological data has largely influenced the focus of today’s biology research. Integrating and analysing large quantity of data to provide meaningful insights has become the main challenge to biologists and bioinformaticians. One major problem is the combined data analysis of data from different types, such as phenotypes and genotypes. This data is modelled as bi-partite graphs where nodes correspond to the different data points, mutations and diseases for instance, and weighted edges relate to associations between them. Bi-clustering is a special case of clustering designed for partitioning two different types of data simultaneously. We present a bi-clustering approach that solves the NP-hard weighted bi-cluster editing problem by transforming a given bi-partite graph into a disjoint union of bi-cliques. Here we contribute with an exact algorithm that is based on fixed-parameter tractability. We evaluated its performance on artificial graphs first. Afterwards we exemplarily applied our Java implementation to data of genome-wide association studies (GWAS) data aiming for discovering new, previously unobserved geno-to-pheno associations. We believe that our results will serve as guidelines for further wet lab investigations. Generally our software can be applied to any kind of data that can be modelled as bi-partite graphs. To our knowledge it is the fastest exact method for weighted bi-cluster editing problem.

  18. 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

  19. The heterogeneity of headache patients who self-medicate: a cluster analysis approach.

    PubMed

    Mehuys, Els; Paemeleire, Koen; Crombez, Geert; Adriaens, Els; Van Hees, Thierry; Demarche, Sophie; Christiaens, Thierry; Van Bortel, Luc; Van Tongelen, Inge; Remon, Jean-Paul; Boussery, Koen

    2016-07-01

    Patients with headache often self-treat their condition with over-the-counter analgesics. However, overuse of analgesics can cause medication-overuse headache. The present study aimed to identify subgroups of individuals with headache who self-medicate, as this could be helpful to tailor intervention strategies for prevention of medication-overuse headache. Patients (n = 1021) were recruited from 202 community pharmacies and completed a self-administered questionnaire. A hierarchical cluster analysis was used to group patients as a function of sociodemographics, pain, disability, and medication use for pain. Three patient clusters were identified. Cluster 1 (n = 498, 48.8%) consisted of relatively young individuals, and most of them suffered from migraine. They reported the least number of other pain complaints and the lowest prevalence of medication overuse (MO; 16%). Cluster 2 (n = 301, 29.5%) included older persons with mainly non-migraine headache, a low disability, and on average pain in 2 other locations. Prevalence of MO was 40%. Cluster 3 (n = 222, 21.7%) mostly consisted of patients with migraine who also report pain in many other locations. These patients reported a high disability and a severe limitation of activities. They also showed the highest rates of MO (73%).

  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. Development of magnetic graphene @hydrophilic polydopamine for the enrichment and analysis of phthalates in environmental water samples.

    PubMed

    Wang, Xianying; Song, Guoxin; Deng, Chunhui

    2015-01-01

    Magnetic graphene @hydrophilic polydopamine composites were successfully fabricated via a simple solvothermal reaction and self-polymerization of dopamine. Benefit from the excellent characteristics of strong magnetic responsivity, super-hydrophilicity and abundant π-electron system, the prepared material showed great potential as a magnetic solid phase extraction (MSPE) sorbent. In this work, six kinds of phthalates (PAEs) were selected as the target analytes to evaluate the extraction ability of the adsorbents combined with MSPE-GC-MS. And various extraction parameters were optimized by selecting the pH value of samples, the amount of sorbents, adsorption and desorption time, the type and volume of eluting solution. Meanwhile, the whole extraction process could be finished in 30 min. Under the optimized conditions, validations of the method were evaluated as well. And the results presented excellent linearity with a wide range of 50-20,000 μg/L (R(2)>0.9991). The detection of limits were in the range from 0.05-5 μg/L (S/N=3). Therefore, the novel magnetic graphene@polydopamine composites were successfully used as the sorbents for the enrichment and analysis of PAEs in real water samples. This proposed method provided a simple, efficient and sensitive approach for the determination of aromatic compounds in real environmental samples.

  2. Functional connectivity decreases in autism in emotion, self, and face circuits identified by Knowledge-based Enrichment Analysis.

    PubMed

    Cheng, Wei; Rolls, Edmund T; Zhang, Jie; Sheng, Wenbo; Ma, Liang; Wan, Lin; Luo, Qiang; Feng, Jianfeng

    2017-03-01

    A powerful new method is described called Knowledge based functional connectivity Enrichment Analysis (KEA) for interpreting resting state functional connectivity, using circuits that are functionally identified using search terms with the Neurosynth database. The method derives its power by focusing on neural circuits, sets of brain regions that share a common biological function, instead of trying to interpret single functional connectivity links. This provides a novel way of investigating how task- or function-related networks have resting state functional connectivity differences in different psychiatric states, provides a new way to bridge the gap between task and resting-state functional networks, and potentially helps to identify brain networks that might be treated. The method was applied to interpreting functional connectivity differences in autism. Functional connectivity decreases at the network circuit level in 394 patients with autism compared with 473 controls were found in networks involving the orbitofrontal cortex, anterior cingulate cortex, middle temporal gyrus cortex, and the precuneus, in networks that are implicated in the sense of self, face processing, and theory of mind. The decreases were correlated with symptom severity.

  3. Replacements of rare herbs and simplifications of traditional chinese medicine formulae based on attribute similarities and pathway enrichment analysis.

    PubMed

    Fang, Zhao; Zhang, Meixia; Yi, Zhenghui; Wen, Chengping; Qian, Min; Shi, Tieliu

    2013-01-01

    A Traditional Chinese Medicine (TCM) formula is a collection of several herbs. TCM formulae have been used to treat various diseases for several thousand years. However, wide usage of TCM formulae has results in rapid decline of some rare herbs. So it is urgent to find common available replacements for those rare herbs with the similar effects. In addition, a formula can be simplified by reducing herbs with unchanged effects. Based on this consideration, we propose a method, called "formula pair," to replace the rare herbs and simplify TCM formulae. We show its reasonableness from a perspective of pathway enrichment analysis. Both the replacements of rare herbs and simplifications of formulae provide new approaches for a new formula discovery. We demonstrate our approach by replacing a rare herb "Forsythia suspensa" in the f