The threshold of stochastic tumor-immune model with regime switching

Chen, Xing; Li, Xiaoyue; Ma, Yuting; Yuan, Chenggui

doi:10.1016/j.jmaa.2022.126956

Journal article 509 views 19 downloads

The threshold of stochastic tumor-immune model with regime switching

Xing Chen, Xiaoyue Li, Yuting Ma, Chenggui Yuan

Journal of Mathematical Analysis and Applications, Volume: 522, Issue: 1, Start page: 126956

Swansea University Author: Chenggui Yuan

PDF | Accepted Manuscript

©2022 All rights reserved. All article content, except where otherwise noted, is licensed under a Creative Commons Attribution Non-Commercial No Derivatives License (CC-BY-NC-ND)
Download (2.92MB)

Check full text

DOI (Published version): 10.1016/j.jmaa.2022.126956

Abstract

In response to the pressing needs for comprehending the cancer biology, this paper focuses on dynamical behaviors of a class of stochastic tumor-immune models in random environment modulated by Markov chains. A sufficient and nearly necessary threshold-type criterion is investigated, which shows the...

Full description

Published in:	Journal of Mathematical Analysis and Applications
ISSN:	0022-247X
Published:	Elsevier BV 2023
Online Access:	Check full text
URI:	https://cronfa.swan.ac.uk/Record/cronfa62241
Tags:	Add Tag No Tags, Be the first to tag this record!

first_indexed	2023-01-03T11:44:23Z
last_indexed	2023-02-04T04:13:25Z
id	cronfa62241
recordtype	SURis
fullrecord	<?xml version="1.0" encoding="utf-8"?><rfc1807 xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"><bib-version>v2</bib-version><id>62241</id><entry>2023-01-03</entry><title>The threshold of stochastic tumor-immune model with regime switching</title><swanseaauthors><author><sid>22b571d1cba717a58e526805bd9abea0</sid><ORCID>0000-0003-0486-5450</ORCID><firstname>Chenggui</firstname><surname>Yuan</surname><name>Chenggui Yuan</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2023-01-03</date><deptcode>MACS</deptcode><abstract>In response to the pressing needs for comprehending the cancer biology, this paper focuses on dynamical behaviors of a class of stochastic tumor-immune models in random environment modulated by Markov chains. A sufficient and nearly necessary threshold-type criterion is investigated, which shows the long-time behavior of the system can be classified by a real-value parameter λ. Precisely, if , tumor cells die out. If , the system exists a unique invariant probability measure, and the transition probability of the solution process converges to this invariant measure. Moreover, we also estimate the expectations with respect to the invariant measure under some conditions. Two numerical examples are provided to illustrate our results.</abstract><type>Journal Article</type><journal>Journal of Mathematical Analysis and Applications</journal><volume>522</volume><journalNumber>1</journalNumber><paginationStart>126956</paginationStart><paginationEnd/><publisher>Elsevier BV</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>0022-247X</issnPrint><issnElectronic/><keywords>Markov chain; Stochastic tumor-immune systems; Invariant measure; Ergodicity; Permanence; Extinction</keywords><publishedDay>1</publishedDay><publishedMonth>6</publishedMonth><publishedYear>2023</publishedYear><publishedDate>2023-06-01</publishedDate><doi>10.1016/j.jmaa.2022.126956</doi><url/><notes/><college>COLLEGE NANME</college><department>Mathematics and Computer Science School</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>MACS</DepartmentCode><institution>Swansea University</institution><apcterm/><funders/><projectreference/><lastEdited>2024-07-25T15:54:15.2017634</lastEdited><Created>2023-01-03T11:42:39.0289688</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Mathematics and Computer Science - Mathematics</level></path><authors><author><firstname>Xing</firstname><surname>Chen</surname><order>1</order></author><author><firstname>Xiaoyue</firstname><surname>Li</surname><order>2</order></author><author><firstname>Yuting</firstname><surname>Ma</surname><order>3</order></author><author><firstname>Chenggui</firstname><surname>Yuan</surname><orcid>0000-0003-0486-5450</orcid><order>4</order></author></authors><documents><document><filename>62241__26169__df08f0b0ca5340ed9c104e157dc0f1b9.pdf</filename><originalFilename>62241.pdf</originalFilename><uploaded>2023-01-03T11:44:07.3145249</uploaded><type>Output</type><contentLength>3064840</contentLength><contentType>application/pdf</contentType><version>Accepted Manuscript</version><cronfaStatus>true</cronfaStatus><embargoDate>2023-12-28T00:00:00.0000000</embargoDate><documentNotes>©2022 All rights reserved. All article content, except where otherwise noted, is licensed under a Creative Commons Attribution Non-Commercial No Derivatives License (CC-BY-NC-ND)</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>https://creativecommons.org/licenses/by-nc-nd/4.0/</licence></document></documents><OutputDurs/></rfc1807>
spelling	v2 62241 2023-01-03 The threshold of stochastic tumor-immune model with regime switching 22b571d1cba717a58e526805bd9abea0 0000-0003-0486-5450 Chenggui Yuan Chenggui Yuan true false 2023-01-03 MACS In response to the pressing needs for comprehending the cancer biology, this paper focuses on dynamical behaviors of a class of stochastic tumor-immune models in random environment modulated by Markov chains. A sufficient and nearly necessary threshold-type criterion is investigated, which shows the long-time behavior of the system can be classified by a real-value parameter λ. Precisely, if , tumor cells die out. If , the system exists a unique invariant probability measure, and the transition probability of the solution process converges to this invariant measure. Moreover, we also estimate the expectations with respect to the invariant measure under some conditions. Two numerical examples are provided to illustrate our results. Journal Article Journal of Mathematical Analysis and Applications 522 1 126956 Elsevier BV 0022-247X Markov chain; Stochastic tumor-immune systems; Invariant measure; Ergodicity; Permanence; Extinction 1 6 2023 2023-06-01 10.1016/j.jmaa.2022.126956 COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University 2024-07-25T15:54:15.2017634 2023-01-03T11:42:39.0289688 Faculty of Science and Engineering School of Mathematics and Computer Science - Mathematics Xing Chen 1 Xiaoyue Li 2 Yuting Ma 3 Chenggui Yuan 0000-0003-0486-5450 4 62241__26169__df08f0b0ca5340ed9c104e157dc0f1b9.pdf 62241.pdf 2023-01-03T11:44:07.3145249 Output 3064840 application/pdf Accepted Manuscript true 2023-12-28T00:00:00.0000000 ©2022 All rights reserved. All article content, except where otherwise noted, is licensed under a Creative Commons Attribution Non-Commercial No Derivatives License (CC-BY-NC-ND) true eng https://creativecommons.org/licenses/by-nc-nd/4.0/
title	The threshold of stochastic tumor-immune model with regime switching
spellingShingle	The threshold of stochastic tumor-immune model with regime switching Chenggui Yuan
title_short	The threshold of stochastic tumor-immune model with regime switching
title_full	The threshold of stochastic tumor-immune model with regime switching
title_fullStr	The threshold of stochastic tumor-immune model with regime switching
title_full_unstemmed	The threshold of stochastic tumor-immune model with regime switching
title_sort	The threshold of stochastic tumor-immune model with regime switching
author_id_str_mv	22b571d1cba717a58e526805bd9abea0
author_id_fullname_str_mv	22b571d1cba717a58e526805bd9abea0_***_Chenggui Yuan
author	Chenggui Yuan
author2	Xing Chen Xiaoyue Li Yuting Ma Chenggui Yuan
format	Journal article
container_title	Journal of Mathematical Analysis and Applications
container_volume	522
container_issue	1
container_start_page	126956
publishDate	2023
institution	Swansea University
issn	0022-247X
doi_str_mv	10.1016/j.jmaa.2022.126956
publisher	Elsevier BV
college_str	Faculty of Science and Engineering
hierarchytype
hierarchy_top_id	facultyofscienceandengineering
hierarchy_top_title	Faculty of Science and Engineering
hierarchy_parent_id	facultyofscienceandengineering
hierarchy_parent_title	Faculty of Science and Engineering
department_str	School of Mathematics and Computer Science - Mathematics{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Mathematics
document_store_str	1
active_str	0
description	In response to the pressing needs for comprehending the cancer biology, this paper focuses on dynamical behaviors of a class of stochastic tumor-immune models in random environment modulated by Markov chains. A sufficient and nearly necessary threshold-type criterion is investigated, which shows the long-time behavior of the system can be classified by a real-value parameter λ. Precisely, if , tumor cells die out. If , the system exists a unique invariant probability measure, and the transition probability of the solution process converges to this invariant measure. Moreover, we also estimate the expectations with respect to the invariant measure under some conditions. Two numerical examples are provided to illustrate our results.
published_date	2023-06-01T15:54:14Z
_version_	1805563204084957184
score	11.036706

The threshold of stochastic tumor-immune model with regime switching

Similar Items