Model-based cellular kinetic analysis of SARS-CoV-2 infection: different immune response modes and treatment strategies
Increasing number in global COVID-19 cases demands for mathematical model to analyze the interaction between the virus dynamics and the response of innate and adaptive immunity. Here, based on the assumption of a weak and delayed response of the innate and adaptive immunity in SARS-CoV-2 infection,...
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| creator | Zhou, Zhengqing Zhao, Zhiheng Shi, Shuyu Wu, Jianghua Li, Dianjie Li, Jianwei Zhang, Jingpeng Gui, Ke Zhang, Yu Mei, Heng Hu, Yu Ouyang, Qi Li, Fangting |
| description | Increasing number in global COVID-19 cases demands for mathematical model to
analyze the interaction between the virus dynamics and the response of innate
and adaptive immunity. Here, based on the assumption of a weak and delayed
response of the innate and adaptive immunity in SARS-CoV-2 infection, we
constructed a mathematical model to describe the dynamic processes of immune
system. Integrating theoretical results with clinical COVID-19 patients' data,
we classified the COVID-19 development processes into three typical modes of
immune responses, correlated with the clinical classification of mild &
moderate, severe and critical patients. We found that the immune efficacy (the
ability of host to clear virus and kill infected cells) and the lymphocyte
supply (the abundance and pool of na\"ive T and B cell) play important roles in
the dynamic process and determine the clinical outcome, especially for the
severe and critical patients. Furthermore, we put forward possible treatment
strategies for the three typical modes of immune response. We hope our results
can help to understand the dynamical mechanism of the immune response against
SARS-CoV-2 infection, and to be useful for the treatment strategies and vaccine
design. |
| doi_str_mv | 10.48550/arxiv.2101.04477 |
| format | Article |
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analyze the interaction between the virus dynamics and the response of innate
and adaptive immunity. Here, based on the assumption of a weak and delayed
response of the innate and adaptive immunity in SARS-CoV-2 infection, we
constructed a mathematical model to describe the dynamic processes of immune
system. Integrating theoretical results with clinical COVID-19 patients' data,
we classified the COVID-19 development processes into three typical modes of
immune responses, correlated with the clinical classification of mild &
moderate, severe and critical patients. We found that the immune efficacy (the
ability of host to clear virus and kill infected cells) and the lymphocyte
supply (the abundance and pool of na\"ive T and B cell) play important roles in
the dynamic process and determine the clinical outcome, especially for the
severe and critical patients. Furthermore, we put forward possible treatment
strategies for the three typical modes of immune response. We hope our results
can help to understand the dynamical mechanism of the immune response against
SARS-CoV-2 infection, and to be useful for the treatment strategies and vaccine
design.</description><identifier>DOI: 10.48550/arxiv.2101.04477</identifier><language>eng</language><subject>Quantitative Biology - Cell Behavior ; Quantitative Biology - Populations and Evolution</subject><creationdate>2021-01</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,776,881</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2101.04477$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2101.04477$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhou, Zhengqing</creatorcontrib><creatorcontrib>Zhao, Zhiheng</creatorcontrib><creatorcontrib>Shi, Shuyu</creatorcontrib><creatorcontrib>Wu, Jianghua</creatorcontrib><creatorcontrib>Li, Dianjie</creatorcontrib><creatorcontrib>Li, Jianwei</creatorcontrib><creatorcontrib>Zhang, Jingpeng</creatorcontrib><creatorcontrib>Gui, Ke</creatorcontrib><creatorcontrib>Zhang, Yu</creatorcontrib><creatorcontrib>Mei, Heng</creatorcontrib><creatorcontrib>Hu, Yu</creatorcontrib><creatorcontrib>Ouyang, Qi</creatorcontrib><creatorcontrib>Li, Fangting</creatorcontrib><title>Model-based cellular kinetic analysis of SARS-CoV-2 infection: different immune response modes and treatment strategies</title><description>Increasing number in global COVID-19 cases demands for mathematical model to
analyze the interaction between the virus dynamics and the response of innate
and adaptive immunity. Here, based on the assumption of a weak and delayed
response of the innate and adaptive immunity in SARS-CoV-2 infection, we
constructed a mathematical model to describe the dynamic processes of immune
system. Integrating theoretical results with clinical COVID-19 patients' data,
we classified the COVID-19 development processes into three typical modes of
immune responses, correlated with the clinical classification of mild &
moderate, severe and critical patients. We found that the immune efficacy (the
ability of host to clear virus and kill infected cells) and the lymphocyte
supply (the abundance and pool of na\"ive T and B cell) play important roles in
the dynamic process and determine the clinical outcome, especially for the
severe and critical patients. Furthermore, we put forward possible treatment
strategies for the three typical modes of immune response. We hope our results
can help to understand the dynamical mechanism of the immune response against
SARS-CoV-2 infection, and to be useful for the treatment strategies and vaccine
design.</description><subject>Quantitative Biology - Cell Behavior</subject><subject>Quantitative Biology - Populations and Evolution</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotkM1OAyEURtm4MNUHcCUvwAiUGRh3TeNf0sbENm4nF-ZiiDNMA1Tt29tWV9_my0nOIeRG8EqZuuZ3kH7CVyUFFxVXSutL8r2eehyYhYw9dTgM-wES_QwRS3AUIgyHHDKdPN0s3jZsOb0zSUP06EqY4j3tg_eYMBYaxnEfkSbMuylmpOMRnI-EnpaEUMbTJ5cEBT8C5ity4WHIeP2_M7J9fNgun9nq9elluVgxaLRmUnFtkUtpDViunWjANK7xSkinnTTGOmvQ8VbwVqGz3vRCN7VTrdUttHw-I7d_2LN5t0thhHToTgW6c4H5L3x9V_g</recordid><startdate>20210112</startdate><enddate>20210112</enddate><creator>Zhou, Zhengqing</creator><creator>Zhao, Zhiheng</creator><creator>Shi, Shuyu</creator><creator>Wu, Jianghua</creator><creator>Li, Dianjie</creator><creator>Li, Jianwei</creator><creator>Zhang, Jingpeng</creator><creator>Gui, Ke</creator><creator>Zhang, Yu</creator><creator>Mei, Heng</creator><creator>Hu, Yu</creator><creator>Ouyang, Qi</creator><creator>Li, Fangting</creator><scope>ALC</scope><scope>GOX</scope></search><sort><creationdate>20210112</creationdate><title>Model-based cellular kinetic analysis of SARS-CoV-2 infection: different immune response modes and treatment strategies</title><author>Zhou, Zhengqing ; Zhao, Zhiheng ; Shi, Shuyu ; Wu, Jianghua ; Li, Dianjie ; Li, Jianwei ; Zhang, Jingpeng ; Gui, Ke ; Zhang, Yu ; Mei, Heng ; Hu, Yu ; Ouyang, Qi ; Li, Fangting</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a677-2407be022b8ab07c16a86c6f412c7c288bcb8ec091094ecbf8d1765c49b79a903</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Quantitative Biology - Cell Behavior</topic><topic>Quantitative Biology - Populations and Evolution</topic><toplevel>online_resources</toplevel><creatorcontrib>Zhou, Zhengqing</creatorcontrib><creatorcontrib>Zhao, Zhiheng</creatorcontrib><creatorcontrib>Shi, Shuyu</creatorcontrib><creatorcontrib>Wu, Jianghua</creatorcontrib><creatorcontrib>Li, Dianjie</creatorcontrib><creatorcontrib>Li, Jianwei</creatorcontrib><creatorcontrib>Zhang, Jingpeng</creatorcontrib><creatorcontrib>Gui, Ke</creatorcontrib><creatorcontrib>Zhang, Yu</creatorcontrib><creatorcontrib>Mei, Heng</creatorcontrib><creatorcontrib>Hu, Yu</creatorcontrib><creatorcontrib>Ouyang, Qi</creatorcontrib><creatorcontrib>Li, Fangting</creatorcontrib><collection>arXiv Quantitative Biology</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Zhou, Zhengqing</au><au>Zhao, Zhiheng</au><au>Shi, Shuyu</au><au>Wu, Jianghua</au><au>Li, Dianjie</au><au>Li, Jianwei</au><au>Zhang, Jingpeng</au><au>Gui, Ke</au><au>Zhang, Yu</au><au>Mei, Heng</au><au>Hu, Yu</au><au>Ouyang, Qi</au><au>Li, Fangting</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Model-based cellular kinetic analysis of SARS-CoV-2 infection: different immune response modes and treatment strategies</atitle><date>2021-01-12</date><risdate>2021</risdate><abstract>Increasing number in global COVID-19 cases demands for mathematical model to
analyze the interaction between the virus dynamics and the response of innate
and adaptive immunity. Here, based on the assumption of a weak and delayed
response of the innate and adaptive immunity in SARS-CoV-2 infection, we
constructed a mathematical model to describe the dynamic processes of immune
system. Integrating theoretical results with clinical COVID-19 patients' data,
we classified the COVID-19 development processes into three typical modes of
immune responses, correlated with the clinical classification of mild &
moderate, severe and critical patients. We found that the immune efficacy (the
ability of host to clear virus and kill infected cells) and the lymphocyte
supply (the abundance and pool of na\"ive T and B cell) play important roles in
the dynamic process and determine the clinical outcome, especially for the
severe and critical patients. Furthermore, we put forward possible treatment
strategies for the three typical modes of immune response. We hope our results
can help to understand the dynamical mechanism of the immune response against
SARS-CoV-2 infection, and to be useful for the treatment strategies and vaccine
design.</abstract><doi>10.48550/arxiv.2101.04477</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Quantitative Biology - Cell Behavior Quantitative Biology - Populations and Evolution |
| title | Model-based cellular kinetic analysis of SARS-CoV-2 infection: different immune response modes and treatment strategies |
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