A within-host model on the interactions of sensitive and resistant Helicobacter pylori to antibiotic therapy considering immune response.

IF 2.6 4区 工程技术 Q1 Mathematics Mathematical Biosciences and Engineering Pub Date : 2025-01-20 DOI:10.3934/mbe.2025009
Edgar Alberto Vega Noguera, Simeón Casanova Trujillo, Eduardo Ibargüen-Mondragón
{"title":"A within-host model on the interactions of sensitive and resistant <i>Helicobacter pylori</i> to antibiotic therapy considering immune response.","authors":"Edgar Alberto Vega Noguera, Simeón Casanova Trujillo, Eduardo Ibargüen-Mondragón","doi":"10.3934/mbe.2025009","DOIUrl":null,"url":null,"abstract":"<p><p>In this work, we formulated a mathematical model to describe growth, acquisition of bacterial resistance, and immune response for Helicobacter pylori (<i>H. pylori</i>). The qualitative analysis revealed the existence of five equilibrium solutions: (ⅰ) An infection-free state, in which the bacterial population and immune cells are suppressed, (ⅱ) an endemic state only with resistant bacteria without immune cells, (ⅲ) an endemic state only with resistant bacteria and immune cells, (ⅳ) an endemic state of bacterial coexistence without immune cells, and (ⅴ) an endemic coexistence state with immune response. The stability analysis showed that the equilibrium solutions (ⅰ) and (ⅳ) are locally asymptotically stable, whereas the equilibria (ⅱ) and (ⅲ) are unstable. We found four threshold conditions that establish the existence and stability of equilibria, which determine when the populations of sensitive <i>H. pylori</i> and resistant <i>H. pylori</i> are controlled or eliminated, or when the infection progresses only with resistant bacteria or with both bacterial populations. The numerical simulations corroborated the qualitative analysis, and provided information on the emergence of a limit cycle that breaks the stability of the coexistence equilibrium. The results revealed that the key to controlling bacterial progression is to keep bacterial growth thresholds below 1; this can be achieved by applying an appropriate combination of antibiotics and correct stimulation of the immune response. Otherwise, when bacterial growth thresholds exceed 1, the bacterial persistence scenarios mentioned above occur.</p>","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":"22 1","pages":"185-224"},"PeriodicalIF":2.6000,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mathematical Biosciences and Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.3934/mbe.2025009","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 0

Abstract

In this work, we formulated a mathematical model to describe growth, acquisition of bacterial resistance, and immune response for Helicobacter pylori (H. pylori). The qualitative analysis revealed the existence of five equilibrium solutions: (ⅰ) An infection-free state, in which the bacterial population and immune cells are suppressed, (ⅱ) an endemic state only with resistant bacteria without immune cells, (ⅲ) an endemic state only with resistant bacteria and immune cells, (ⅳ) an endemic state of bacterial coexistence without immune cells, and (ⅴ) an endemic coexistence state with immune response. The stability analysis showed that the equilibrium solutions (ⅰ) and (ⅳ) are locally asymptotically stable, whereas the equilibria (ⅱ) and (ⅲ) are unstable. We found four threshold conditions that establish the existence and stability of equilibria, which determine when the populations of sensitive H. pylori and resistant H. pylori are controlled or eliminated, or when the infection progresses only with resistant bacteria or with both bacterial populations. The numerical simulations corroborated the qualitative analysis, and provided information on the emergence of a limit cycle that breaks the stability of the coexistence equilibrium. The results revealed that the key to controlling bacterial progression is to keep bacterial growth thresholds below 1; this can be achieved by applying an appropriate combination of antibiotics and correct stimulation of the immune response. Otherwise, when bacterial growth thresholds exceed 1, the bacterial persistence scenarios mentioned above occur.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
在这项研究中,我们建立了一个数学模型来描述幽门螺杆菌(H. pylori)的生长、细菌抗药性的获得和免疫反应。定性分析显示存在五种平衡解:(ⅰ)细菌种群和免疫细胞均受到抑制的无感染状态;(ⅱ)仅有抗性细菌而无免疫细胞的流行状态;(ⅲ)仅有抗性细菌和免疫细胞的流行状态;(ⅳ)无免疫细胞的细菌共存流行状态;(ⅴ)有免疫反应的细菌共存流行状态。稳定性分析表明,平衡解(ⅰ)和(ⅳ)是局部渐近稳定的,而平衡解(ⅱ)和(ⅲ)是不稳定的。我们发现了四个阈值条件,这些条件确定了平衡态的存在和稳定性,它们决定了敏感幽门螺杆菌种群和抗性幽门螺杆菌种群何时被控制或消除,或感染何时只在抗性细菌或两种细菌种群中进行。数值模拟证实了定性分析,并提供了有关打破共存平衡稳定性的极限循环出现的信息。结果表明,控制细菌繁殖的关键是将细菌生长阈值保持在 1 以下;这可以通过适当组合使用抗生素和正确刺激免疫反应来实现。否则,当细菌生长阈值超过 1 时,就会出现上述细菌持续存在的情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Mathematical Biosciences and Engineering
Mathematical Biosciences and Engineering 工程技术-数学跨学科应用
CiteScore
3.90
自引率
7.70%
发文量
586
审稿时长
>12 weeks
期刊介绍: Mathematical Biosciences and Engineering (MBE) is an interdisciplinary Open Access journal promoting cutting-edge research, technology transfer and knowledge translation about complex data and information processing. MBE publishes Research articles (long and original research); Communications (short and novel research); Expository papers; Technology Transfer and Knowledge Translation reports (description of new technologies and products); Announcements and Industrial Progress and News (announcements and even advertisement, including major conferences).
期刊最新文献
A within-host model on the interactions of sensitive and resistant Helicobacter pylori to antibiotic therapy considering immune response. Traveling waves in a free boundary problem for the spread of ecosystem engineers. A fully automated U-net based ROIs localization and bone age assessment method. Computational physics and imaging in medicine. Robust control and data reconstruction for nonlinear epidemiological models using feedback linearization and state estimation.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1