2,500 research outputs found

    A model-based multithreshold method for subgroup identification

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    Thresholding variable plays a crucial role in subgroup identification for personalizedmedicine. Most existing partitioning methods split the sample basedon one predictor variable. In this paper, we consider setting the splitting rulefrom a combination of multivariate predictors, such as the latent factors, principlecomponents, and weighted sum of predictors. Such a subgrouping methodmay lead to more meaningful partitioning of the population than using a singlevariable. In addition, our method is based on a change point regression modeland thus yields straight forward model-based prediction results. After choosinga particular thresholding variable form, we apply a two-stage multiple changepoint detection method to determine the subgroups and estimate the regressionparameters. We show that our approach can produce two or more subgroupsfrom the multiple change points and identify the true grouping with high probability.In addition, our estimation results enjoy oracle properties. We design asimulation study to compare performances of our proposed and existing methodsand apply them to analyze data sets from a Scleroderma trial and a breastcancer study

    Rapidity and Centrality Dependence of Proton and Anti-proton Production from Au+Au Collisions at sqrt(sNN) = 130GeV

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    We report on the rapidity and centrality dependence of proton and anti-proton transverse mass distributions from Au+Au collisions at sqrt(sNN) = 130GeV as measured by the STAR experiment at RHIC. Our results are from the rapidity and transverse momentum range of |y|<0.5 and 0.35 <p_t<1.00GeV/c. For both protons and anti-protons, transverse mass distributions become more convex from peripheral to central collisions demonstrating characteristics of collective expansion. The measured rapidity distributions and the mean transverse momenta versus rapidity are flat within |y|<0.5. Comparisons of our data with results from model calculations indicate that in order to obtain a consistent picture of the proton(anti-proton) yields and transverse mass distributions the possibility of pre-hadronic collective expansion may have to be taken into account.Comment: 4 pages, 3 figures, 1 table, submitted to PR

    Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm

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    Over the past five decades, k-means has become the clustering algorithm of choice in many application domains primarily due to its simplicity, time/space efficiency, and invariance to the ordering of the data points. Unfortunately, the algorithm's sensitivity to the initial selection of the cluster centers remains to be its most serious drawback. Numerous initialization methods have been proposed to address this drawback. Many of these methods, however, have time complexity superlinear in the number of data points, which makes them impractical for large data sets. On the other hand, linear methods are often random and/or sensitive to the ordering of the data points. These methods are generally unreliable in that the quality of their results is unpredictable. Therefore, it is common practice to perform multiple runs of such methods and take the output of the run that produces the best results. Such a practice, however, greatly increases the computational requirements of the otherwise highly efficient k-means algorithm. In this chapter, we investigate the empirical performance of six linear, deterministic (non-random), and order-invariant k-means initialization methods on a large and diverse collection of data sets from the UCI Machine Learning Repository. The results demonstrate that two relatively unknown hierarchical initialization methods due to Su and Dy outperform the remaining four methods with respect to two objective effectiveness criteria. In addition, a recent method due to Erisoglu et al. performs surprisingly poorly.Comment: 21 pages, 2 figures, 5 tables, Partitional Clustering Algorithms (Springer, 2014). arXiv admin note: substantial text overlap with arXiv:1304.7465, arXiv:1209.196

    Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

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    The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

    Children with cerebral malaria or severe malarial anaemia lack immunity to distinct variant surface antigen subsets

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    Abstract Variant surface antigens (VSAs) play a critical role in severe malaria pathogenesis. Defining gaps, or “lacunae”, in immunity to these Plasmodium falciparum antigens in children with severe malaria would improve our understanding of vulnerability to severe malaria and how protective immunity develops. Using a protein microarray with 179 antigen variants from three VSA families as well as more than 300 variants of three other blood stage P. falciparum antigens, reactivity was measured in sera from Malian children with cerebral malaria or severe malarial anaemia and age-matched controls. Sera from children with severe malaria recognized fewer extracellular PfEMP1 fragments and were less reactive to specific fragments compared to controls. Following recovery from severe malaria, convalescent sera had increased reactivity to certain non-CD36 binding PfEMP1s, but not other malaria antigens. Sera from children with severe malarial anaemia reacted to fewer VSAs than did sera from children with cerebral malaria, and both of these groups had lacunae in their seroreactivity profiles in common with children who had both cerebral malaria and severe malarial anaemia. This microarray-based approach may identify a subset of VSAs that could inform the development of a vaccine to prevent severe disease or a diagnostic test to predict at-risk children

    Synthesis and preliminary assessment of the anticancer and Wnt/β-catenin inhibitory activity of small amide libraries of fenamates and profens

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    As part of an ongoing program to study the anticancer activity of non-steroidal anti-inflammatory drugs (NSAIDs) through generating diversity libraries of multiple NSAID scaffolds, we synthesized a series of NSAID amide derivatives and screened these sets against three cancer cell lines (prostate, colon and breast) and Wnt/β-catenin signaling. The evaluated amide analog libraries show significant anticancer activity/cell proliferation inhibition, and specific members of the sets show inhibition of Wnt/β-catenin signaling.</p

    Gebiss: an ImageJ plugin for the specification of ground truth and the performance evaluation of 3D segmentation algorithms.

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    Background: Image segmentation is a crucial step in quantitative microscopy that helps to define regions of tissues, cells or subcellular compartments. Depending on the degree of user interactions, segmentation methods can be divided into manual, automated or semi-automated approaches. 3D image stacks usually require automated methods due to their large number of optical sections. However, certain applications benefit from manual or semi-automated approaches. Scenarios include the quantification of 3D images with poor signal-to-noise ratios or the generation of so-called ground truth segmentations that are used to evaluate the accuracy of automated segmentation methods. Results: We have developed Gebiss; an ImageJ plugin for the interactive segmentation, visualisation and quantification of 3D microscopic image stacks. We integrated a variety of existing plugins for threshold-based segmentation and volume visualisation. Conclusions: We demonstrate the application of Gebiss to the segmentation of nuclei in live Drosophila embryos and the quantification of neurodegeneration in Drosophila larval brains. Gebiss was developed as a cross-platform ImageJ plugin and is freely available on the web at http://imaging.bii.a-star.edu.sg/projects/gebiss

    A Rapid and Sensitive Method for Measuring NAcetylglucosaminidase Activity in Cultured Cells

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    A rapid and sensitive method to quantitatively assess N-acetylglucosaminidase (NAG) activity in cultured cells is highly desirable for both basic research and clinical studies. NAG activity is deficient in cells from patients with Mucopolysaccharidosis type IIIB (MPS IIIB) due to mutations in NAGLU, the gene that encodes NAG. Currently available techniques for measuring NAG activity in patient-derived cell lines include chromogenic and fluorogenic assays and provide a biochemical method for the diagnosis of MPS IIIB. However, standard protocols require large amounts of cells, cell disruption by sonication or freeze-thawing, and normalization to the cellular protein content, resulting in an error-prone procedure that is material- and time-consuming and that produces highly variable results. Here we report a new procedure for measuring NAG activity in cultured cells. This procedure is based on the use of the fluorogenic NAG substrate, 4- Methylumbelliferyl-2-acetamido-2-deoxy-alpha-D-glucopyranoside (MUG), in a one-step cell assay that does not require cell disruption or post-assay normalization and that employs a low number of cells in 96-well plate format. We show that the NAG one-step cell assay greatly discriminates between wild-type and MPS IIIB patient-derived fibroblasts, thus providing a rapid method for the detection of deficiencies in NAG activity. We also show that the assay is sensitive to changes in NAG activity due to increases in NAGLU expression achieved by either overexpressing the transcription factor EB (TFEB), a master regulator of lysosomal function, or by inducing TFEB activation chemically. Because of its small format, rapidity, sensitivity and reproducibility, the NAG one-step cell assay is suitable for multiple procedures, including the high-throughput screening of chemical libraries to identify modulators of NAG expression, folding and activity, and the investigation of candidate molecules and constructs for applications in enzyme replacement therapy, gene therapy, and combination therapies
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