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Spatiotemporal Dynamics of Virus Infection Spreading in Tissues
Virus spreading in tissues is determined by virus transport, virus multiplication in host cells and the virus-induced immune response. Cytotoxic T cells remove infected cells with a rate determined by the infection level. The intensity of the immune response has a bell-shaped dependence on the conce...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5173377/ https://www.ncbi.nlm.nih.gov/pubmed/27997613 http://dx.doi.org/10.1371/journal.pone.0168576 |
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author | Bocharov, Gennady Meyerhans, Andreas Bessonov, Nickolai Trofimchuk, Sergei Volpert, Vitaly |
author_facet | Bocharov, Gennady Meyerhans, Andreas Bessonov, Nickolai Trofimchuk, Sergei Volpert, Vitaly |
author_sort | Bocharov, Gennady |
collection | PubMed |
description | Virus spreading in tissues is determined by virus transport, virus multiplication in host cells and the virus-induced immune response. Cytotoxic T cells remove infected cells with a rate determined by the infection level. The intensity of the immune response has a bell-shaped dependence on the concentration of virus, i.e., it increases at low and decays at high infection levels. A combination of these effects and a time delay in the immune response determine the development of virus infection in tissues like spleen or lymph nodes. The mathematical model described in this work consists of reaction-diffusion equations with a delay. It shows that the different regimes of infection spreading like the establishment of a low level infection, a high level infection or a transition between both are determined by the initial virus load and by the intensity of the immune response. The dynamics of the model solutions include simple and composed waves, and periodic and aperiodic oscillations. The results of analytical and numerical studies of the model provide a systematic basis for a quantitative understanding and interpretation of the determinants of the infection process in target organs and tissues from the image-derived data as well as of the spatiotemporal mechanisms of viral disease pathogenesis, and have direct implications for a biopsy-based medical testing of the chronic infection processes caused by viruses, e.g. HIV, HCV and HBV. |
format | Online Article Text |
id | pubmed-5173377 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-51733772017-01-04 Spatiotemporal Dynamics of Virus Infection Spreading in Tissues Bocharov, Gennady Meyerhans, Andreas Bessonov, Nickolai Trofimchuk, Sergei Volpert, Vitaly PLoS One Research Article Virus spreading in tissues is determined by virus transport, virus multiplication in host cells and the virus-induced immune response. Cytotoxic T cells remove infected cells with a rate determined by the infection level. The intensity of the immune response has a bell-shaped dependence on the concentration of virus, i.e., it increases at low and decays at high infection levels. A combination of these effects and a time delay in the immune response determine the development of virus infection in tissues like spleen or lymph nodes. The mathematical model described in this work consists of reaction-diffusion equations with a delay. It shows that the different regimes of infection spreading like the establishment of a low level infection, a high level infection or a transition between both are determined by the initial virus load and by the intensity of the immune response. The dynamics of the model solutions include simple and composed waves, and periodic and aperiodic oscillations. The results of analytical and numerical studies of the model provide a systematic basis for a quantitative understanding and interpretation of the determinants of the infection process in target organs and tissues from the image-derived data as well as of the spatiotemporal mechanisms of viral disease pathogenesis, and have direct implications for a biopsy-based medical testing of the chronic infection processes caused by viruses, e.g. HIV, HCV and HBV. Public Library of Science 2016-12-20 /pmc/articles/PMC5173377/ /pubmed/27997613 http://dx.doi.org/10.1371/journal.pone.0168576 Text en © 2016 Bocharov et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Bocharov, Gennady Meyerhans, Andreas Bessonov, Nickolai Trofimchuk, Sergei Volpert, Vitaly Spatiotemporal Dynamics of Virus Infection Spreading in Tissues |
title | Spatiotemporal Dynamics of Virus Infection Spreading in Tissues |
title_full | Spatiotemporal Dynamics of Virus Infection Spreading in Tissues |
title_fullStr | Spatiotemporal Dynamics of Virus Infection Spreading in Tissues |
title_full_unstemmed | Spatiotemporal Dynamics of Virus Infection Spreading in Tissues |
title_short | Spatiotemporal Dynamics of Virus Infection Spreading in Tissues |
title_sort | spatiotemporal dynamics of virus infection spreading in tissues |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5173377/ https://www.ncbi.nlm.nih.gov/pubmed/27997613 http://dx.doi.org/10.1371/journal.pone.0168576 |
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