Models of cytokine dynamics in the inflammatory response of viral zoonotic infectious diseases.

IF 0.8 4区 数学 Q4 BIOLOGY
Wenjing Zhang, Sophia Jang, Colleen B Jonsson, Linda J S Allen
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引用次数: 0

Abstract

Inflammatory responses to an infection from a zoonotic pathogen, such as avian influenza viruses, hantaviruses and some coronaviruses, are distinctly different in their natural reservoir versus human host. While not as well studied in the natural reservoirs, the pro-inflammatory response and viral replication appear controlled and show no obvious pathology. In contrast, infection in humans results in an initial high viral load marked by an aggressive pro-inflammatory response known as a cytokine storm. The key difference in the course of the infection between the reservoir and human host is the inflammatory response. In this investigation, we apply a simple two-component differential equation model for pro-inflammatory and anti-inflammatory responses and a detailed mathematical analysis to identify specific regions in parameter space for single stable endemic equilibrium, bistability or periodic solutions. The extensions of the deterministic model to two stochastic models account for variability in responses seen at the cell (local) or tissue (global) levels. Numerical solutions of the stochastic models exhibit outcomes that are typical of a chronic infection in the natural reservoir or a cytokine storm in human infection. In the chronic infection, occasional flare-ups between high and low responses occur when model parameters are in a region of bistability or periodic solutions. The cytokine storm with a vigorous pro-inflammatory response and less vigorous anti-inflammatory response occurs in the parameter region for a single stable endemic equilibrium with a strong pro-inflammatory response. The results of the model analyses and the simulations are interpreted in terms of the functional role of the cytokines and the inflammatory responses seen in infection of the natural reservoir or of the human host.

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病毒性人畜共患传染病炎症反应中的细胞因子动态模型。
人畜共患病病原体(如禽流感病毒、汉坦病毒和某些冠状病毒)感染后产生的炎症反应在其自然储库和人类宿主中截然不同。虽然对自然储库的研究并不深入,但其促炎反应和病毒复制似乎受到控制,没有明显的病理表现。与此相反,人类感染会导致最初的高病毒载量,并伴有被称为细胞因子风暴的侵袭性促炎症反应。储库宿主和人类宿主在感染过程中的关键区别在于炎症反应。在这项研究中,我们采用了一个简单的双分量微分方程模型来描述促炎和抗炎反应,并进行了详细的数学分析,以确定参数空间中单一稳定流行平衡、双稳态或周期解的特定区域。将确定性模型扩展为两个随机模型,可解释细胞(局部)或组织(整体)层面的反应变化。随机模型的数值解显示了自然储库中慢性感染或人类感染中细胞因子风暴的典型结果。在慢性感染中,当模型参数处于双稳态或周期解区域时,偶尔会出现高反应和低反应之间的爆发。细胞因子风暴具有强烈的促炎反应和较弱的抗炎反应,发生在具有强烈促炎反应的单一稳定流行平衡的参数区域。模型分析和模拟结果从细胞因子的功能作用和自然储库或人类宿主感染时的炎症反应角度进行了解释。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.20
自引率
0.00%
发文量
15
审稿时长
>12 weeks
期刊介绍: Formerly the IMA Journal of Mathematics Applied in Medicine and Biology. Mathematical Medicine and Biology publishes original articles with a significant mathematical content addressing topics in medicine and biology. Papers exploiting modern developments in applied mathematics are particularly welcome. The biomedical relevance of mathematical models should be demonstrated clearly and validation by comparison against experiment is strongly encouraged. The journal welcomes contributions relevant to any area of the life sciences including: -biomechanics- biophysics- cell biology- developmental biology- ecology and the environment- epidemiology- immunology- infectious diseases- neuroscience- pharmacology- physiology- population biology
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