145 research outputs found

    Identifying and managing patients at risk of severe allergic reactions to food: report from two iFAAM workshops

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    Food allergy affects a small but important number of children and adults. Much of the morbidity associated with food allergy is driven by the fear of a severe reaction, and fatalities continue to occur. Foods are the commonest cause of anaphylaxis. One of the aims of the European Union funded Integrated Approaches to Food Allergen and Allergy Risk Management (iFAAM) project was to improve the identification and management of children and adults at risk of experiencing a severe reaction. A number of interconnected studies within the project have focused on quantifying the severity of allergic reactions; the impact of food matrix, immunological factors on severity of reactions; the impact of co‐factors such as medications on the severity of reactions; utilising single dose challenges to understand threshold and severity of reactions; and community studies to understand the experience of patients suffering real‐life allergic reactions to food. Associated studies have examined population thresholds, and co‐factors such as exercise and stress. This paper summarises two workshops focused on the severity of allergic reactions to food. It outlines the related studies being undertaken in the project indicating how they are likely to impact on our ability to identify individuals at risk of severe reactions and improve their management

    Measurement of the Forward-Backward Asymmetry in the B -> K(*) mu+ mu- Decay and First Observation of the Bs -> phi mu+ mu- Decay

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    We reconstruct the rare decays B+K+μ+μB^+ \to K^+\mu^+\mu^-, B0K(892)0μ+μB^0 \to K^{*}(892)^0\mu^+\mu^-, and Bs0ϕ(1020)μ+μB^0_s \to \phi(1020)\mu^+\mu^- in a data sample corresponding to 4.4fb14.4 {\rm fb^{-1}} collected in ppˉp\bar{p} collisions at s=1.96TeV\sqrt{s}=1.96 {\rm TeV} by the CDF II detector at the Fermilab Tevatron Collider. Using 121±16121 \pm 16 B+K+μ+μB^+ \to K^+\mu^+\mu^- and 101±12101 \pm 12 B0K0μ+μB^0 \to K^{*0}\mu^+\mu^- decays we report the branching ratios. In addition, we report the measurement of the differential branching ratio and the muon forward-backward asymmetry in the B+B^+ and B0B^0 decay modes, and the K0K^{*0} longitudinal polarization in the B0B^0 decay mode with respect to the squared dimuon mass. These are consistent with the theoretical prediction from the standard model, and most recent determinations from other experiments and of comparable accuracy. We also report the first observation of the Bs0ϕμ+μdecayandmeasureitsbranchingratioB^0_s \to \phi\mu^+\mu^- decay and measure its branching ratio {\mathcal{B}}(B^0_s \to \phi\mu^+\mu^-) = [1.44 \pm 0.33 \pm 0.46] \times 10^{-6}using using 27 \pm 6signalevents.Thisiscurrentlythemostrare signal events. This is currently the most rare B^0_s$ decay observed.Comment: 7 pages, 2 figures, 3 tables. Submitted to Phys. Rev. Let

    Search for a New Heavy Gauge Boson Wprime with Electron + missing ET Event Signature in ppbar collisions at sqrt(s)=1.96 TeV

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    We present a search for a new heavy charged vector boson WW^\prime decaying to an electron-neutrino pair in ppˉp\bar{p} collisions at a center-of-mass energy of 1.96\unit{TeV}. The data were collected with the CDF II detector and correspond to an integrated luminosity of 5.3\unit{fb}^{-1}. No significant excess above the standard model expectation is observed and we set upper limits on σB(Weν)\sigma\cdot{\cal B}(W^\prime\to e\nu). Assuming standard model couplings to fermions and the neutrino from the WW^\prime boson decay to be light, we exclude a WW^\prime boson with mass less than 1.12\unit{TeV/}c^2 at the 95\unit{%} confidence level.Comment: 7 pages, 2 figures Submitted to PR

    Measurements of the properties of Lambda_c(2595), Lambda_c(2625), Sigma_c(2455), and Sigma_c(2520) baryons

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    We report measurements of the resonance properties of Lambda_c(2595)+ and Lambda_c(2625)+ baryons in their decays to Lambda_c+ pi+ pi- as well as Sigma_c(2455)++,0 and Sigma_c(2520)++,0 baryons in their decays to Lambda_c+ pi+/- final states. These measurements are performed using data corresponding to 5.2/fb of integrated luminosity from ppbar collisions at sqrt(s) = 1.96 TeV, collected with the CDF II detector at the Fermilab Tevatron. Exploiting the largest available charmed baryon sample, we measure masses and decay widths with uncertainties comparable to the world averages for Sigma_c states, and significantly smaller uncertainties than the world averages for excited Lambda_c+ states.Comment: added one reference and one table, changed order of figures, 17 pages, 15 figure

    A Robust, Simple Genotyping-by-Sequencing (GBS) Approach for High Diversity Species

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    Advances in next generation technologies have driven the costs of DNA sequencing down to the point that genotyping-by-sequencing (GBS) is now feasible for high diversity, large genome species. Here, we report a procedure for constructing GBS libraries based on reducing genome complexity with restriction enzymes (REs). This approach is simple, quick, extremely specific, highly reproducible, and may reach important regions of the genome that are inaccessible to sequence capture approaches. By using methylation-sensitive REs, repetitive regions of genomes can be avoided and lower copy regions targeted with two to three fold higher efficiency. This tremendously simplifies computationally challenging alignment problems in species with high levels of genetic diversity. The GBS procedure is demonstrated with maize (IBM) and barley (Oregon Wolfe Barley) recombinant inbred populations where roughly 200,000 and 25,000 sequence tags were mapped, respectively. An advantage in species like barley that lack a complete genome sequence is that a reference map need only be developed around the restriction sites, and this can be done in the process of sample genotyping. In such cases, the consensus of the read clusters across the sequence tagged sites becomes the reference. Alternatively, for kinship analyses in the absence of a reference genome, the sequence tags can simply be treated as dominant markers. Future application of GBS to breeding, conservation, and global species and population surveys may allow plant breeders to conduct genomic selection on a novel germplasm or species without first having to develop any prior molecular tools, or conservation biologists to determine population structure without prior knowledge of the genome or diversity in the species

    What Can Causal Networks Tell Us about Metabolic Pathways?

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    Graphical models describe the linear correlation structure of data and have been used to establish causal relationships among phenotypes in genetic mapping populations. Data are typically collected at a single point in time. Biological processes on the other hand are often non-linear and display time varying dynamics. The extent to which graphical models can recapitulate the architecture of an underlying biological processes is not well understood. We consider metabolic networks with known stoichiometry to address the fundamental question: “What can causal networks tell us about metabolic pathways?”. Using data from an Arabidopsis BaySha population and simulated data from dynamic models of pathway motifs, we assess our ability to reconstruct metabolic pathways using graphical models. Our results highlight the necessity of non-genetic residual biological variation for reliable inference. Recovery of the ordering within a pathway is possible, but should not be expected. Causal inference is sensitive to subtle patterns in the correlation structure that may be driven by a variety of factors, which may not emphasize the substrate-product relationship. We illustrate the effects of metabolic pathway architecture, epistasis and stochastic variation on correlation structure and graphical model-derived networks. We conclude that graphical models should be interpreted cautiously, especially if the implied causal relationships are to be used in the design of intervention strategies

    Genetic Architecture of Aluminum Tolerance in Rice (Oryza sativa) Determined through Genome-Wide Association Analysis and QTL Mapping

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    Aluminum (Al) toxicity is a primary limitation to crop productivity on acid soils, and rice has been demonstrated to be significantly more Al tolerant than other cereal crops. However, the mechanisms of rice Al tolerance are largely unknown, and no genes underlying natural variation have been reported. We screened 383 diverse rice accessions, conducted a genome-wide association (GWA) study, and conducted QTL mapping in two bi-parental populations using three estimates of Al tolerance based on root growth. Subpopulation structure explained 57% of the phenotypic variation, and the mean Al tolerance in Japonica was twice that of Indica. Forty-eight regions associated with Al tolerance were identified by GWA analysis, most of which were subpopulation-specific. Four of these regions co-localized with a priori candidate genes, and two highly significant regions co-localized with previously identified QTLs. Three regions corresponding to induced Al-sensitive rice mutants (ART1, STAR2, Nrat1) were identified through bi-parental QTL mapping or GWA to be involved in natural variation for Al tolerance. Haplotype analysis around the Nrat1 gene identified susceptible and tolerant haplotypes explaining 40% of the Al tolerance variation within the aus subpopulation, and sequence analysis of Nrat1 identified a trio of non-synonymous mutations predictive of Al sensitivity in our diversity panel. GWA analysis discovered more phenotype–genotype associations and provided higher resolution, but QTL mapping identified critical rare and/or subpopulation-specific alleles not detected by GWA analysis. Mapping using Indica/Japonica populations identified QTLs associated with transgressive variation where alleles from a susceptible aus or indica parent enhanced Al tolerance in a tolerant Japonica background. This work supports the hypothesis that selectively introgressing alleles across subpopulations is an efficient approach for trait enhancement in plant breeding programs and demonstrates the fundamental importance of subpopulation in interpreting and manipulating the genetics of complex traits in rice
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