University of Virginia

About: University of Virginia is a education organization based out in Charlottesville, Virginia, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 52543 authors who have published 113268 publications receiving 5220506 citations. The organization is also known as: U of V & UVa.

Pervasive sharing of genetic effects in autoimmune disease.

Abstract: Genome-wide association (GWA) studies have identified numerous, replicable, genetic associations between common single nucleotide polymorphisms (SNPs) and risk of common autoimmune and inflammatory (immune-mediated) diseases, some of which are shared between two diseases. Along with epidemiological and clinical evidence, this suggests that some genetic risk factors may be shared across diseases-as is the case with alleles in the Major Histocompatibility Locus. In this work we evaluate the extent of this sharing for 107 immune disease-risk SNPs in seven diseases: celiac disease, Crohn's disease, multiple sclerosis, psoriasis, rheumatoid arthritis, systemic lupus erythematosus, and type 1 diabetes. We have developed a novel statistic for Cross Phenotype Meta-Analysis (CPMA) which detects association of a SNP to multiple, but not necessarily all, phenotypes. With it, we find evidence that 47/107 (44%) immune-mediated disease risk SNPs are associated to multiple-but not all-immune-mediated diseases (SNP-wise P(CPMA)<0.01). We also show that distinct groups of interacting proteins are encoded near SNPs which predispose to the same subsets of diseases; we propose these as the mechanistic basis of shared disease risk. We are thus able to leverage genetic data across diseases to construct biological hypotheses about the underlying mechanism of pathogenesis.

A systematic study of automated program repair: fixing 55 out of 105 bugs for $8 each

Abstract: There are more bugs in real-world programs than human programmers can realistically address. This paper evaluates two research questions: ``What fraction of bugs can be repaired automatically?'' and ``How much does it cost to repair a bug automatically?'' In previous work, we presented GenProg, which uses genetic programming to repair defects in off-the-shelf C programs. To answer these questions, we: (1) propose novel algorithmic improvements to GenProg that allow it to scale to large programs and find repairs 68% more often, (2) exploit GenProg's inherent parallelism using cloud computing resources to provide grounded, human-competitive cost measurements, and (3) generate a large, indicative benchmark set to use for systematic evaluations. We evaluate GenProg on 105 defects from 8 open-source programs totaling 5.1 million lines of code and involving 10,193 test cases. GenProg automatically repairs 55 of those 105 defects. To our knowledge, this evaluation is the largest available of its kind, and is often two orders of magnitude larger than previous work in terms of code or test suite size or defect count. Public cloud computing prices allow our 105 runs to be reproduced for $403; a successful repair completes in 96 minutes and costs $7.32, on average.

Complete reversal of acid-induced acute lung injury by blocking of platelet-neutrophil aggregation

Abstract: Acute lung injury (ALI) causes high mortality, but its molecular mechanisms are poorly understood. Acid aspiration is a frequent cause of ALI, leading to neutrophil sequestration, increased permeability, and deterioration of gas exchange. We investigated the role of platelet-neutrophil interactions in a murine model of acid-induced ALI. Acid aspiration induced P-selectin–dependent platelet-neutrophil interactions in blood and in lung capillaries. Reducing circulating platelets or blocking P-selectin halted the development of ALI. Bone marrow chimeras showed that platelet, not endothelial, P-selectin was responsible for the injury. The interaction of platelets with neutrophils and endothelia was associated with TXA2 formation, with detrimental effects on permeability and tissue function. Activated platelets induced endothelial expression of ICAM-1 and increased neutrophil adhesion. Inhibition of platelet-neutrophil aggregation improved gas exchange, reduced neutrophil recruitment and permeability, and prolonged survival. The key findings were confirmed in a sepsis-induced model of ALI. These findings may translate into improved clinical treatments for ALI.

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

Abstract: The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta)<2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.

Copy number variation detection and genotyping from exome sequence data

Abstract: While exome sequencing is readily amenable to single-nucleotide variant discovery, the sparse and nonuniform nature of the exome capture reaction has hindered exome-based detection and characterization of genic copy number variation. We developed a novel method using singular value decomposition (SVD) normalization to discover rare genic copy number variants (CNVs) as well as genotype copy number polymorphic (CNP) loci with high sensitivity and specificity from exome sequencing data. We estimate the precision of our algorithm using 122 trios (366 exomes) and show that this method can be used to reliably predict (94% overall precision) both de novo and inherited rare CNVs involving three or more consecutive exons. We demonstrate that exome-based genotyping of CNPs strongly correlates with whole-genome data (median r(2) = 0.91), especially for loci with fewer than eight copies, and can estimate the absolute copy number of multi-allelic genes with high accuracy (78% call level). The resulting user-friendly computational pipeline, CoNIFER (copy number inference from exome reads), can reliably be used to discover disruptive genic CNVs missed by standard approaches and should have broad application in human genetic studies of disease.