864 research outputs found

    Labor Law

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    Profiling allele-specific gene expression in brains from individuals with autism spectrum disorder reveals preferential minor allele usage.

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    One fundamental but understudied mechanism of gene regulation in disease is allele-specific expression (ASE), the preferential expression of one allele. We leveraged RNA-sequencing data from human brain to assess ASE in autism spectrum disorder (ASD). When ASE is observed in ASD, the allele with lower population frequency (minor allele) is preferentially more highly expressed than the major allele, opposite to the canonical pattern. Importantly, genes showing ASE in ASD are enriched in those downregulated in ASD postmortem brains and in genes harboring de novo mutations in ASD. Two regions, 14q32 and 15q11, containing all known orphan C/D box small nucleolar RNAs (snoRNAs), are particularly enriched in shifts to higher minor allele expression. We demonstrate that this allele shifting enhances snoRNA-targeted splicing changes in ASD-related target genes in idiopathic ASD and 15q11-q13 duplication syndrome. Together, these results implicate allelic imbalance and dysregulation of orphan C/D box snoRNAs in ASD pathogenesis

    Crystal Structure of a Charge Engineered Human Lysozyme Having Enhanced Bactericidal Activity

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    Human lysozyme is a key component of the innate immune system, and recombinant forms of the enzyme represent promising leads in the search for therapeutic agents able to treat drug-resistant infections. The wild type protein, however, fails to participate effectively in clearance of certain infections due to inherent functional limitations. For example, wild type lysozymes are subject to electrostatic sequestration and inactivation by anionic biopolymers in the infected airway. A charge engineered variant of human lysozyme has recently been shown to possess improved antibacterial activity in the presence of disease associated inhibitory molecules. Here, the 2.04 Å crystal structure of this variant is presented along with an analysis that provides molecular level insights into the origins of the protein's enhanced performance. The charge engineered variant's two mutated amino acids exhibit stabilizing interactions with adjacent native residues, and from a global perspective, the mutations cause no gross structural perturbations or loss of stability. Importantly, the two substitutions dramatically expand the negative electrostatic potential that, in the wild type enzyme, is restricted to a small region near the catalytic residues. The net result is a reduction in the overall strength of the engineered enzyme's electrostatic potential field, and it appears that the specific nature of this remodeled field underlies the variant's reduced susceptibility to inhibition by anionic biopolymers

    Fitting the integrated Spectral Energy Distributions of Galaxies

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    Fitting the spectral energy distributions (SEDs) of galaxies is an almost universally used technique that has matured significantly in the last decade. Model predictions and fitting procedures have improved significantly over this time, attempting to keep up with the vastly increased volume and quality of available data. We review here the field of SED fitting, describing the modelling of ultraviolet to infrared galaxy SEDs, the creation of multiwavelength data sets, and the methods used to fit model SEDs to observed galaxy data sets. We touch upon the achievements and challenges in the major ingredients of SED fitting, with a special emphasis on describing the interplay between the quality of the available data, the quality of the available models, and the best fitting technique to use in order to obtain a realistic measurement as well as realistic uncertainties. We conclude that SED fitting can be used effectively to derive a range of physical properties of galaxies, such as redshift, stellar masses, star formation rates, dust masses, and metallicities, with care taken not to over-interpret the available data. Yet there still exist many issues such as estimating the age of the oldest stars in a galaxy, finer details ofdust properties and dust-star geometry, and the influences of poorly understood, luminous stellar types and phases. The challenge for the coming years will be to improve both the models and the observational data sets to resolve these uncertainties. The present review will be made available on an interactive, moderated web page (sedfitting.org), where the community can access and change the text. The intention is to expand the text and keep it up to date over the coming years.Comment: 54 pages, 26 figures, Accepted for publication in Astrophysics & Space Scienc

    Eight common genetic variants associated with serum dheas levels suggest a key role in ageing mechanisms

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    Dehydroepiandrosterone sulphate (DHEAS) is the most abundant circulating steroid secreted by adrenal glands-yet its function is unknown. Its serum concentration declines significantly with increasing age, which has led to speculation that a relative DHEAS deficiency may contribute to the development of common age-related diseases or diminished longevity. We conducted a meta-analysis of genome-wide association data with 14,846 individuals and identified eight independent common SNPs associated with serum DHEAS concentrations. Genes at or near the identified loci include ZKSCAN5 (rs11761528; p = 3.15×10-36), SULT2A1 (rs2637125; p = 2.61×10-19), ARPC1A (rs740160; p = 1.56×10-16), TRIM4 (rs17277546; p = 4.50×10-11), BMF (rs7181230; p = 5.44×10-11), HHEX (rs2497306; p = 4.64×10-9), BCL2L11 (rs6738028; p = 1.72×10-8), and CYP2C9 (rs2185570; p = 2.29×10-8). These genes are associated with type 2 diabetes, lymphoma, actin filament assembly, drug and xenobiotic metabolism, and zinc finger proteins. Several SNPs were associated with changes in gene expression levels, and the related genes are connected to biological pathways linking DHEAS with ageing. This study provides much needed insight into the function of DHEAS

    Epistatic Roles for Pseudomonas aeruginosa MutS and DinB (DNA Pol IV) in Coping with Reactive Oxygen Species-Induced DNA Damage

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    Pseudomonas aeruginosa is especially adept at colonizing the airways of individuals afflicted with the autosomal recessive disease cystic fibrosis (CF). CF patients suffer from chronic airway inflammation, which contributes to lung deterioration. Once established in the airways, P. aeruginosa continuously adapts to the changing environment, in part through acquisition of beneficial mutations via a process termed pathoadaptation. MutS and DinB are proposed to play opposing roles in P. aeruginosa pathoadaptation: MutS acts in replication-coupled mismatch repair, which acts to limit spontaneous mutations; in contrast, DinB (DNA polymerase IV) catalyzes error-prone bypass of DNA lesions, contributing to mutations. As part of an ongoing effort to understand mechanisms underlying P. aeruginosa pathoadaptation, we characterized hydrogen peroxide (H2O2)-induced phenotypes of isogenic P. aeruginosa strains bearing different combinations of mutS and dinB alleles. Our results demonstrate an unexpected epistatic relationship between mutS and dinB with respect to H2O2-induced cell killing involving error-prone repair and/or tolerance of oxidized DNA lesions. In striking contrast to these error-prone roles, both MutS and DinB played largely accurate roles in coping with DNA lesions induced by ultraviolet light, mitomycin C, or 4-nitroquinilone 1-oxide. Models discussing roles for MutS and DinB functionality in DNA damage-induced mutagenesis, particularly during CF airway colonization and subsequent P. aeruginosa pathoadaptation are discussed

    Search for supersymmetry in events with b-quark jets and missing transverse energy in pp collisions at 7 TeV

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    Results are presented from a search for physics beyond the standard model based on events with large missing transverse energy, at least three jets, and at least one, two, or three b-quark jets. The study is performed using a sample of proton-proton collision data collected at sqrt(s) = 7 TeV with the CMS detector at the LHC in 2011. The integrated luminosity of the sample is 4.98 inverse femtobarns. The observed number of events is found to be consistent with the standard model expectation, which is evaluated using control samples in the data. The results are used to constrain cross sections for the production of supersymmetric particles decaying to b-quark-enriched final states in the context of simplified model spectra.Comment: Submitted to Physical Review

    Performance of the CMS Cathode Strip Chambers with Cosmic Rays

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    The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

    Coefficient shifts in geographical ecology: an empirical evaluation of spatial and non-spatial regression

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    Copyright © 2009 The Authors. Copyright © ECOGRAPHY 2009.A major focus of geographical ecology and macro ecology is to understand the causes of spatially structured ecological patterns. However, achieving this understanding can be complicated when using multiple regressions, because the relative importance of explanatory variables, as measured by regression coefficients, can shift depending on whether spatially explicit or non-spatial modelling is used. However, the extent to which coefficients may shift and why shifts occur are unclear. Here, we analyze the relationship between environmental predictors and the geographical distribution of species richness, body size, range size and abundance in 97 multi-factorial data sets. Our goal was to compare standardized partial regression coefficients of non-spatial ordinary least squares regressions (i.e. models fitted using ordinary least squares without taking autocorrelation into account; “OLS models” hereafter) and eight spatial methods to evaluate the frequency of coefficient shifts and identify characteristics of data that might predict when shifts are likely. We generated three metrics of coefficient shifts and eight characteristics of the data sets as predictors of shifts. Typical of ecological data, spatial autocorrelation in the residuals of OLS models was found in most data sets. The spatial models varied in the extent to which they minimized residual spatial autocorrelation. Patterns of coefficient shifts also varied among methods and datasets, although the magnitudes of shifts tended to be small in all cases. We were unable to identify strong predictors of shifts, including the levels of autocorrelation in either explanatory variables or model residuals. Thus, changes in coefficients between spatial and non-spatial methods depend on the method used and are largely idiosyncratic, making it difficult to predict when or why shifts occur. We conclude that the ecological importance of regression coefficients cannot be evaluated with confidence irrespective of whether spatially explicit modelling is used or not. Researchers may have little choice but to be more explicit about the uncertainty of models and more cautious in their interpretation
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