2,372 research outputs found

    Matrix stiffness controls lymphatic vessel formation through regulation of a GATA2-dependent transcriptional program.

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    Tissue and vessel wall stiffening alters endothelial cell properties and contributes to vascular dysfunction. However, whether extracellular matrix (ECM) stiffness impacts vascular development is not known. Here we show that matrix stiffness controls lymphatic vascular morphogenesis. Atomic force microscopy measurements in mouse embryos reveal that venous lymphatic endothelial cell (LEC) progenitors experience a decrease in substrate stiffness upon migration out of the cardinal vein, which induces a GATA2-dependent transcriptional program required to form the first lymphatic vessels. Transcriptome analysis shows that LECs grown on a soft matrix exhibit increased GATA2 expression and a GATA2-dependent upregulation of genes involved in cell migration and lymphangiogenesis, including VEGFR3. Analyses of mouse models demonstrate a cell-autonomous function of GATA2 in regulating LEC responsiveness to VEGF-C and in controlling LEC migration and sprouting in vivo. Our study thus uncovers a mechanism by which ECM stiffness dictates the migratory behavior of LECs during early lymphatic development

    Pitfalls of using the risk ratio in meta‐analysis

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    For meta-analysis of studies that report outcomes as binomial proportions, the most popular measure of effect is the odds ratio (OR), usually analyzed as log(OR). Many meta-analyses use the risk ratio (RR) and its logarithm, because of its simpler interpretation. Although log(OR) and log(RR) are both unbounded, use of log(RR) must ensure that estimates are compatible with study-level event rates in the interval (0, 1). These complications pose a particular challenge for random-effects models, both in applications and in generating data for simulations. As background we review the conventional random-effects model and then binomial generalized linear mixed models (GLMMs) with the logit link function, which do not have these complications. We then focus on log-binomial models and explore implications of using them; theoretical calculations and simulation show evidence of biases. The main competitors to the binomial GLMMs use the beta-binomial (BB) distribution, either in BB regression or by maximizing a BB likelihood; a simulation produces mixed results. Two examples and an examination of Cochrane meta-analyses that used RR suggest bias in the results from the conventional inverse-variance-weighted approach. Finally, we comment on other measures of effect that have range restrictions, including risk difference, and outline further research

    Chern-Simons black holes: scalar perturbations, mass and area spectrum and greybody factors

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    We study the Chern-Simons black holes in d-dimensions and we calculate analytically the quasi-normal modes of the scalar perturbations and we show that they depend on the highest power of curvature present in the Chern-Simons theory. We obtain the mass and area spectrum of these black holes and we show that they have a strong dependence on the topology of the transverse space and they are not evenly spaced. We also calculate analytically the reflection and transmission coefficients and the absorption cross section and we show that at low frequency limit there is a range of modes which contributes to the absorption cross section.Comment: 19 pages, 18 figures, the title has been changed to reflect the addition of an another section on the reflection, transmission coefficients and absorption cross sections of the Chern-Simons black holes. Version to be published in JHE

    Common Variants at 10 Genomic Loci Influence Hemoglobin A(1C) Levels via Glycemic and Nonglycemic Pathways

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    OBJECTIVE Glycated hemoglobin (HbA1c), used to monitor and diagnose diabetes, is influenced by average glycemia over a 2- to 3-month period. Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin could also be associated with increased levels of HbA1c. We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA1c levels. RESEARCH DESIGN AND METHODS We studied associations with HbA1c in up to 46,368 nondiabetic adults of European descent from 23 genome-wide association studies (GWAS) and 8 cohorts with de novo genotyped single nucleotide polymorphisms (SNPs). We combined studies using inverse-variance meta-analysis and tested mediation by glycemia using conditional analyses. We estimated the global effect of HbA1c loci using a multilocus risk score, and used net reclassification to estimate genetic effects on diabetes screening. RESULTS Ten loci reached genome-wide significant association with HbA1c, including six new loci near FN3K (lead SNP/P value, rs1046896/P = 1.6 × 10−26), HFE (rs1800562/P = 2.6 × 10−20), TMPRSS6 (rs855791/P = 2.7 × 10−14), ANK1 (rs4737009/P = 6.1 × 10−12), SPTA1 (rs2779116/P = 2.8 × 10−9) and ATP11A/TUBGCP3 (rs7998202/P = 5.2 × 10−9), and four known HbA1c loci: HK1 (rs16926246/P = 3.1 × 10−54), MTNR1B (rs1387153/P = 4.0 × 10−11), GCK (rs1799884/P = 1.5 × 10−20) and G6PC2/ABCB11 (rs552976/P = 8.2 × 10−18). We show that associations with HbA1c are partly a function of hyperglycemia associated with 3 of the 10 loci (GCK, G6PC2 and MTNR1B). The seven nonglycemic loci accounted for a 0.19 (% HbA1c) difference between the extreme 10% tails of the risk score, and would reclassify ∼2% of a general white population screened for diabetes with HbA1c. CONCLUSIONS GWAS identified 10 genetic loci reproducibly associated with HbA1c. Six are novel and seven map to loci where rarer variants cause hereditary anemias and iron storage disorders. Common variants at these loci likely influence HbA1c levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA1c

    TRY plant trait database - enhanced coverage and open access

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    Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

    Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

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    Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

    Search for direct pair production of the top squark in all-hadronic final states in proton-proton collisions at s√=8 TeV with the ATLAS detector

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    The results of a search for direct pair production of the scalar partner to the top quark using an integrated luminosity of 20.1fb−1 of proton–proton collision data at √s = 8 TeV recorded with the ATLAS detector at the LHC are reported. The top squark is assumed to decay via t˜→tχ˜01 or t˜→ bχ˜±1 →bW(∗)χ˜01 , where χ˜01 (χ˜±1 ) denotes the lightest neutralino (chargino) in supersymmetric models. The search targets a fully-hadronic final state in events with four or more jets and large missing transverse momentum. No significant excess over the Standard Model background prediction is observed, and exclusion limits are reported in terms of the top squark and neutralino masses and as a function of the branching fraction of t˜ → tχ˜01 . For a branching fraction of 100%, top squark masses in the range 270–645 GeV are excluded for χ˜01 masses below 30 GeV. For a branching fraction of 50% to either t˜ → tχ˜01 or t˜ → bχ˜±1 , and assuming the χ˜±1 mass to be twice the χ˜01 mass, top squark masses in the range 250–550 GeV are excluded for χ˜01 masses below 60 GeV

    Discontinuous properties of current-induced magnetic domain wall depinning

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    The current-induced motion of magnetic domain walls (DWs) confined to nanostructures is of great interest for fundamental studies as well as for technological applications in spintronic devices. Here, we present magnetic images showing the depinning properties of pulse-current-driven domain walls in well-shaped Permalloy nanowires obtained using photoemission electron microscopy combined with X-ray magnetic circular dichroism. In the vicinity of the threshold current density (J th = 4.2 × 10 11 â.A.m-2) for the DW motion, discontinuous DW depinning and motion have been observed as a sequence of "Barkhausen jumps". A one-dimensional analytical model with a piecewise parabolic pinning potential has been introduced to reproduce the DW hopping between two nearest neighbour sites, which reveals the dynamical nature of the current-driven DW motion in the depinning regime

    Does the diurnal cycle of cortisol explain the relationship between physical performance and cognitive function in older adults?

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    Background Regular physical activity is a promising strategy to treat and prevent cognitive decline. The mechanisms that mediate these benefits are not fully clear but physical activity is thought to attenuate the harmful effects of chronic psychological stress and hypercortisolism on cognition. However, the circadian pattern of cortisol secretion is complex and it is not known which aspects are most closely associated with increased cognitive function and better physical performance. This is the first study to simultaneously measure cognitive function, the diurnal cycle of salivary cortisol and physical performance in older adults, without cognitive impairment (n = 30) and with amnestic Mild Cognitive Impairment (aMCI) (n = 30). Results Regression analysis showed that better cognitive function was associated with better physical performance. A greater variance in cortisol levels across the day from morning to evening was associated with better cognitive function and physical performance. Conclusions The results support the idea that a more dynamic cortisol secretion pattern is associated with better cognitive function and physical performance even in the presence of cognitive impairment, but our results could not confirm a mediating role in this relationship
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