195 research outputs found

    Robust Inverse Modeling of Growing Season Net Ecosystem Exchange in a Mountainous Peatland: Influence of Distributional Assumptions on Estimated Parameters and Total Carbon Fluxes

    Get PDF
    While boreal lowland bogs have been extensively studied using the eddy‐covariance (EC) technique, less knowledge exists on mountainous peatlands. Hence, half‐hourly CO2 fluxes of an ombrotrophic peat bog in the Harz Mountains, Germany, were measured with the EC technique during a growing season with exceptionally dry weather spells. A common biophysical process model for net ecosystem exchange was used to describe measured CO2 fluxes and to fill data gaps. Model parameters and uncertainties were estimated by robust inverse modelling in a Bayesian framework using a population‐based Markov Chain Monte Carlo sampler. The focus of this study was on the correct statistical description of error, i.e. the differences between the measured and simulated carbon fluxes, and the influence of distributional assumptions on parameter estimates, cumulative carbon fluxes, and uncertainties. We tested the Gaussian, Laplace, and Student's t distribution as error models. The t‐distribution was identified as best error model by the deviance information criterion. Its use led to markedly different parameter estimates, a reduction of parameter uncertainty by about 40%, and, most importantly, to a 5% higher estimated cumulative CO2 uptake as compared to the commonly assumed Gaussian error distribution. As open‐path measurement systems have larger measurement error at high humidity, the standard deviation of the error was modeled as a function of measured vapor pressure deficit. Overall, this paper demonstrates the importance of critically assessing the influence of distributional assumptions on estimated model parameters and cumulative carbon fluxes between the land surface and the atmosphere

    Involvement of Girdin in the Determination of Cell Polarity during Cell Migration

    Get PDF
    Cell migration is a critical cellular process that determines embryonic development and the progression of human diseases. Therefore, cell- or context-specific mechanisms by which multiple promigratory proteins differentially regulate cell migration must be analyzed in detail. Girdin (girders of actin filaments) (also termed GIV, Gα-interacting vesicle associated protein) is an actin-binding protein that regulates migration of various cells such as endothelial cells, smooth muscle cells, neuroblasts, and cancer cells. Here we show that Girdin regulates the establishment of cell polarity, the deregulation of which may result in the disruption of directional cell migration. We found that Girdin interacts with Par-3, a scaffolding protein that is a component of the Par protein complex that has an established role in determining cell polarity. RNA interference-mediated depletion of Girdin leads to impaired polarization of fibroblasts and mammary epithelial cells in a way similar to that observed in Par-3-depleted cells. Accordingly, the expression of Par-3 mutants unable to interact with Girdin abrogates cell polarization in fibroblasts. Further biochemical analysis suggests that Girdin is present in the Par protein complex that includes Par-3, Par-6, and atypical protein kinase C. Considering previous reports showing the role of Girdin in the directional migration of neuroblasts, network formation of endothelial cells, and cancer invasion, these data may provide a specific mechanism by which Girdin regulates cell movement in biological contexts that require directional cell movement

    K0S and Λ production in Pb-Pb collisions at sNN−−−−√=2.76  TeV

    Get PDF
    The ALICE measurement of K0S and Λ production at midrapidity in Pb-Pb collisions at sNN−−−√=2.76  TeV is presented. The transverse momentum (pT) spectra are shown for several collision centrality intervals and in the pT range from 0.4  GeV/c (0.6  GeV/c for Λ) to 12  GeV/c. The pT dependence of the Λ/K0S ratios exhibits maxima in the vicinity of 3  GeV/c, and the positions of the maxima shift towards higher pT with increasing collision centrality. The magnitude of these maxima increases by almost a factor of three between most peripheral and most central Pb-Pb collisions. This baryon excess at intermediate pT is not observed in pp interactions at s√=0.9  TeV and at s√=7  TeV. Qualitatively, the baryon enhancement in heavy-ion collisions is expected from radial flow. However, the measured pT spectra above 2  GeV/c progressively decouple from hydrodynamical-model calculations. For higher values of pT, models that incorporate the influence of the medium on the fragmentation and hadronization processes describe qualitatively the pT dependence of the Λ/K0S ratio

    Organization of multiprotein complexes at cell–cell junctions

    Get PDF
    The formation of stable cell–cell contacts is required for the generation of barrier-forming sheets of epithelial and endothelial cells. During various physiological processes like tissue development, wound healing or tumorigenesis, cellular junctions are reorganized to allow the release or the incorporation of individual cells. Cell–cell contact formation is regulated by multiprotein complexes which are localized at specific structures along the lateral cell junctions like the tight junctions and adherens junctions and which are targeted to these site through their association with cell adhesion molecules. Recent evidence indicates that several major protein complexes exist which have distinct functions during junction formation. However, this evidence also indicates that their composition is dynamic and subject to changes depending on the state of junction maturation. Thus, cell–cell contact formation and integrity is regulated by a complex network of protein complexes. Imbalancing this network by oncogenic proteins or pathogens results in barrier breakdown and eventually in cancer. Here, I will review the molecular organization of the major multiprotein complexes at junctions of epithelial cells and discuss their function in cell–cell contact formation and maintenance

    Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

    Get PDF
    Abstract Background Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk

    Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

    Get PDF
    Funding GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file 32: Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services.Peer reviewedPublisher PD

    Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

    Get PDF
    Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe
    corecore