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10.1371/journal.pcbi.1008874 http://scihub22266oqcxt.onion/10.1371/journal.pcbi.1008874 34695114!8608315!34695114     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=34695114&cmd=llinks): Failed to open stream: HTTP request failed! 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Multicellular spatial model of RNA virus replication and interferon responses reveals factors controlling plaque growth dynamics |pdf=|usr=}}{{34695114}} gab.com Text Multicellular spatial model of RNA virus replication and interferon responses reveals factors controlling plaque growth dynamics JO: PLoS Comput Biol http://www.kidney.de/pget.php?&tw=1&pmid=34695114 #FOAvip Respiratory viruses present major public health challenges, as evidenced by the 1918 Spanish Flu, the 1957 H2N2, 1968 H3N2, and 2009 H1N1 influenza pandemics, and the ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Severe RNA virus respiratory infections often correlate with high viral load and excessive inflammation. Understanding the dynamics of the innate immune response and its manifestations at the cell and tissue levels is vital to understanding the mechanisms of immunopathology and to developing strain-independent treatments. Here, we present a novel spatialized multicellular computational model of RNA virus infection and the type-I interferon-mediated antiviral response that it induces within lung epithelial cells. The model is built using the CompuCell3D multicellular simulation environment and is parameterized using data from influenza virus-infected cell cultures. Consistent with experimental observations, it exhibits either linear radial growth of viral plaques or arrested plaque growth depending on the local concentration of type I interferons. The model suggests that modifying the activity of signaling molecules in the JAK/STAT pathway or altering the ratio of the diffusion lengths of interferon and virus in the cell culture could lead to plaque growth arrest. The dependence of plaque growth arrest on diffusion lengths highlights the importance of developing validated spatial models of cytokine signaling and the need for in vitro measurement of these diffusion coefficients. Sensitivity analyses under conditions leading to continuous or arrested plaque growth found that plaque growth is more sensitive to variations of most parameters and more likely to have identifiable model parameters when conditions lead to plaque arrest. This result suggests that cytokine assay measurements may be most informative under conditions leading to arrested plaque growth. The model is easy to extend to include SARS-CoV-2-specific mechanisms or to use as a component in models linking epithelial cell signaling to systemic immune models. Twit Text FOAVip Multicellular spatial model of RNA virus replication and interferon responses reveals factors controlling plaque growth dynamics ????PLoS Comput Biol http://www.kidney.de/pget.php?&tw=1&pmid=34695114 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34695114 #FOAvip English Wikipedia <ref>{{Cite pmid|34695114}}</ref> Multicellular spatial model of RNA virus replication and interferon responses reveals factors controlling plaque growth dynamics #MMPMID34695114 Aponte-Serrano JO; Weaver JJA; Sego TJ; Glazier JA; Shoemaker JE PLoS Comput Biol 2021[Oct]; 17 (10): e1008874 PMID34695114show ga Respiratory viruses present major public health challenges, as evidenced by the 1918 Spanish Flu, the 1957 H2N2, 1968 H3N2, and 2009 H1N1 influenza pandemics, and the ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Severe RNA virus respiratory infections often correlate with high viral load and excessive inflammation. Understanding the dynamics of the innate immune response and its manifestations at the cell and tissue levels is vital to understanding the mechanisms of immunopathology and to developing strain-independent treatments. Here, we present a novel spatialized multicellular computational model of RNA virus infection and the type-I interferon-mediated antiviral response that it induces within lung epithelial cells. The model is built using the CompuCell3D multicellular simulation environment and is parameterized using data from influenza virus-infected cell cultures. Consistent with experimental observations, it exhibits either linear radial growth of viral plaques or arrested plaque growth depending on the local concentration of type I interferons. The model suggests that modifying the activity of signaling molecules in the JAK/STAT pathway or altering the ratio of the diffusion lengths of interferon and virus in the cell culture could lead to plaque growth arrest. The dependence of plaque growth arrest on diffusion lengths highlights the importance of developing validated spatial models of cytokine signaling and the need for in vitro measurement of these diffusion coefficients. Sensitivity analyses under conditions leading to continuous or arrested plaque growth found that plaque growth is more sensitive to variations of most parameters and more likely to have identifiable model parameters when conditions lead to plaque arrest. This result suggests that cytokine assay measurements may be most informative under conditions leading to arrested plaque growth. The model is easy to extend to include SARS-CoV-2-specific mechanisms or to use as a component in models linking epithelial cell signaling to systemic immune models. |*Interferons/immunology/metabolism[MESH] |*RNA Virus Infections/immunology/virology[MESH] |*RNA Viruses/immunology/physiology[MESH] |*Virus Replication/immunology/physiology[MESH] |Cells, Cultured[MESH] |Computational Biology[MESH] |Epithelial Cells/immunology[MESH] |Host-Pathogen Interactions/*immunology[MESH] |Humans[MESH] |Immunity, Innate/immunology[MESH] |Lung/cytology/immunology[MESH]Multicellular spatial model of RNA virus replication and interferon re(epmc).pdf DeepDyve Pubget Overpricing