Modeling oncolytic virus therapy with distributed delay and non-local diffusion
In the field of modeling the dynamics of oncolytic viruses, researchers often face the challenge of using specialized mathematical terms to explain uncertain biological phenomena. This paper introduces a basic framework for an oncolytic virus dynamics model with a general growth rate $\mathcal{F}$ a...
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creator | Wang, Zizi |
description | In the field of modeling the dynamics of oncolytic viruses, researchers often
face the challenge of using specialized mathematical terms to explain uncertain
biological phenomena. This paper introduces a basic framework for an oncolytic
virus dynamics model with a general growth rate $\mathcal{F}$ and a general
nonlinear incidence term $\mathcal{G}$. The construction and derivation of the
model explain in detail the generation process and practical significance of
the distributed time delays and non-local infection terms. The paper provides
the existence and uniqueness of solutions to the model, as well as the
existence of a global attractor. Furthermore, through two auxiliary linear
partial differential equations, the threshold parameters $\sigma_1$ are
determined for sustained tumor growth and $\lambda_1$ for successful viral
invasion of tumor cells to analyze the global dynamic behavior of the model.
Finally, we illustrate and analyze our abstract theoretical results through a
specific example. |
doi_str_mv | 10.48550/arxiv.2402.13474 |
format | Article |
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face the challenge of using specialized mathematical terms to explain uncertain
biological phenomena. This paper introduces a basic framework for an oncolytic
virus dynamics model with a general growth rate $\mathcal{F}$ and a general
nonlinear incidence term $\mathcal{G}$. The construction and derivation of the
model explain in detail the generation process and practical significance of
the distributed time delays and non-local infection terms. The paper provides
the existence and uniqueness of solutions to the model, as well as the
existence of a global attractor. Furthermore, through two auxiliary linear
partial differential equations, the threshold parameters $\sigma_1$ are
determined for sustained tumor growth and $\lambda_1$ for successful viral
invasion of tumor cells to analyze the global dynamic behavior of the model.
Finally, we illustrate and analyze our abstract theoretical results through a
specific example.</description><identifier>DOI: 10.48550/arxiv.2402.13474</identifier><language>eng</language><subject>Mathematics - Dynamical Systems</subject><creationdate>2024-02</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>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,780,885</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2402.13474$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2402.13474$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Wang, Zizi</creatorcontrib><title>Modeling oncolytic virus therapy with distributed delay and non-local diffusion</title><description>In the field of modeling the dynamics of oncolytic viruses, researchers often
face the challenge of using specialized mathematical terms to explain uncertain
biological phenomena. This paper introduces a basic framework for an oncolytic
virus dynamics model with a general growth rate $\mathcal{F}$ and a general
nonlinear incidence term $\mathcal{G}$. The construction and derivation of the
model explain in detail the generation process and practical significance of
the distributed time delays and non-local infection terms. The paper provides
the existence and uniqueness of solutions to the model, as well as the
existence of a global attractor. Furthermore, through two auxiliary linear
partial differential equations, the threshold parameters $\sigma_1$ are
determined for sustained tumor growth and $\lambda_1$ for successful viral
invasion of tumor cells to analyze the global dynamic behavior of the model.
Finally, we illustrate and analyze our abstract theoretical results through a
specific example.</description><subject>Mathematics - Dynamical Systems</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotz7tOwzAYBWAvDKjwAEz4BRJi-7fjjqjiJhV1KHv015fWkrErxynk7SmF6Qzn6EgfIXesa0FL2T1g-Q6nlkPHWyagh2uyec_WxZD2NCeT41yDoadQppHWgyt4nOlXqAdqw1hL2E3VWXre40wxWZpyamI2GM-999MYcrohVx7j6G7_c0G2z08fq9dmvXl5Wz2uG1Q9NMyD4tYpyTR3FpaGCWHZ0hjFmeLeeYOCa-2d4kaAAieY6KzUKDn0FsSC3P-9XkDDsYRPLPPwCxsuMPEDMDJJTQ</recordid><startdate>20240220</startdate><enddate>20240220</enddate><creator>Wang, Zizi</creator><scope>AKZ</scope><scope>GOX</scope></search><sort><creationdate>20240220</creationdate><title>Modeling oncolytic virus therapy with distributed delay and non-local diffusion</title><author>Wang, Zizi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a674-1f462de65182ed49c133d19cc62162fefca3288fe62c3464e3130d58a5247d43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Mathematics - Dynamical Systems</topic><toplevel>online_resources</toplevel><creatorcontrib>Wang, Zizi</creatorcontrib><collection>arXiv Mathematics</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Wang, Zizi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Modeling oncolytic virus therapy with distributed delay and non-local diffusion</atitle><date>2024-02-20</date><risdate>2024</risdate><abstract>In the field of modeling the dynamics of oncolytic viruses, researchers often
face the challenge of using specialized mathematical terms to explain uncertain
biological phenomena. This paper introduces a basic framework for an oncolytic
virus dynamics model with a general growth rate $\mathcal{F}$ and a general
nonlinear incidence term $\mathcal{G}$. The construction and derivation of the
model explain in detail the generation process and practical significance of
the distributed time delays and non-local infection terms. The paper provides
the existence and uniqueness of solutions to the model, as well as the
existence of a global attractor. Furthermore, through two auxiliary linear
partial differential equations, the threshold parameters $\sigma_1$ are
determined for sustained tumor growth and $\lambda_1$ for successful viral
invasion of tumor cells to analyze the global dynamic behavior of the model.
Finally, we illustrate and analyze our abstract theoretical results through a
specific example.</abstract><doi>10.48550/arxiv.2402.13474</doi><oa>free_for_read</oa></addata></record> |
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title | Modeling oncolytic virus therapy with distributed delay and non-local diffusion |
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