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10.1016/j.yjmcc.2016.03.008 http://scihub22266oqcxt.onion/10.1016/j.yjmcc.2016.03.008 C4861657!4861657 !27017945     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=27017945 &cmd=llinks): Failed to open stream: HTTP request failed! 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A computational model of cardiac fibroblast signaling predicts context-dependent drivers of myofibroblast differentiation |pdf=|usr=}}{{27017945 }} gab.com Text A computational model of cardiac fibroblast signaling predicts context-dependent drivers of myofibroblast differentiation JO: J Mol Cell Cardiol http://www.kidney.de/pget.php?&tw=1&pmid=27017945 #FOAvip Cardiac fibroblasts support heart function, and aberrant fibroblast signaling can lead to fibrosis and cardiac dysfunction. Yet how signaling molecules drive myofibroblast differentiation and fibrosis in the complex signaling environment of cardiac injury remains unclear. We developed a large-scale computational model of cardiac fibroblast signaling in order to identify regulators of fibrosis under diverse signaling contexts. The model network integrates 10 signaling pathways, including 91 nodes and 134 reactions, and it correctly predicted 80% of independent previous experiments. The model predicted key fibrotic signaling regulators (e.g. reactive oxygen species, tissue growth factor ? (TGF?) receptor), whose function varied depending on the extracellular environment. We characterized how network structure relates to function, identified functional modules, and predicted cross-talk between TGF? and mechanical signaling, which was validated experimentally in adult cardiac fibroblasts. This study provides a systems framework for predicting key regulators of fibroblast signaling across diverse signaling contexts. Twit Text FOAVip A computational model of cardiac fibroblast signaling predicts context-dependent drivers of myofibroblast differentiation ????J Mol Cell Cardiol http://www.kidney.de/pget.php?&tw=1&pmid=27017945 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27017945 #FOAvip English Wikipedia <ref>{{Cite pmid|27017945 }}</ref> A computational model of cardiac fibroblast signaling predicts context-dependent drivers of myofibroblast differentiation #MMPMID27017945 Zeigler AC ; Richardson WJ ; Holmes JW ; Saucerman JJ J Mol Cell Cardiol 2016[May]; 94 (ä): 72-81 PMID27017945 show ga Cardiac fibroblasts support heart function, and aberrant fibroblast signaling can lead to fibrosis and cardiac dysfunction. Yet how signaling molecules drive myofibroblast differentiation and fibrosis in the complex signaling environment of cardiac injury remains unclear. We developed a large-scale computational model of cardiac fibroblast signaling in order to identify regulators of fibrosis under diverse signaling contexts. The model network integrates 10 signaling pathways, including 91 nodes and 134 reactions, and it correctly predicted 80% of independent previous experiments. The model predicted key fibrotic signaling regulators (e.g. reactive oxygen species, tissue growth factor ? (TGF?) receptor), whose function varied depending on the extracellular environment. We characterized how network structure relates to function, identified functional modules, and predicted cross-talk between TGF? and mechanical signaling, which was validated experimentally in adult cardiac fibroblasts. This study provides a systems framework for predicting key regulators of fibroblast signaling across diverse signaling contexts. |*Cell Differentiation [MESH] |*Computer Simulation [MESH] |*Models, Biological [MESH] |*Signal Transduction [MESH] |Animals [MESH] |Cells, Cultured [MESH] |Computational Biology/methods [MESH] |Gene Expression Profiling [MESH] |Humans [MESH] |Myofibroblasts/*cytology/*metabolism [MESH]A computational model of cardiac fibroblast signaling predicts context(epmc).pdf DeepDyve Pubget Overpricing