A systematic evaluation of the influence of macrophage phenotype descriptions on inflammatory dynamics

Suliman Almansour, Joanne L Dunster, Jonathan J Crofts, Martin R Nelson
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Abstract

Macrophages play a wide range of roles in resolving the inflammatory damage that underlies many medical conditions, and have the ability to adopt different phenotypes in response to different environmental stimuli. Categorising macrophage phenotypes exactly is a difficult task, and there is disparity in the literature around the optimal nomenclature to describe these phenotypes; however, what is clear is that macrophages can exhibit both pro- and anti-inflammatory behaviours dependent upon their phenotype, rendering mathematical models of the inflammatory response potentially sensitive to their description of the macrophage populations that they incorporate. Many previous models of inflammation include a single macrophage population with both pro- and anti-inflammatory functions. Here, we build upon these existing models to include explicit descriptions of distinct macrophage phenotypes and examine the extent to which this influences the inflammatory dynamics that the models emit. We analyse our models via numerical simulation in Matlab and dynamical systems analysis in XPPAUT, and show that models that account for distinct macrophage phenotypes separately can offer more realistic steady state solutions than precursor models do (better capturing the anti-inflammatory activity of tissue resident macrophages), as well as oscillatory dynamics not previously observed. Finally, we reflect on the conclusions of our analysis in the context of the ongoing hunt for potential new therapies for inflammatory conditions, highlighting manipulation of macrophage polarisation states as a potential therapeutic target.
系统评估巨噬细胞表型描述对炎症动态的影响
巨噬细胞在解决许多疾病的炎症损伤方面发挥着广泛的作用,并能对不同的环境刺激做出不同的表型反应。对巨噬细胞表型进行准确分类是一项艰巨的任务,文献中对描述这些表型的最佳术语也存在分歧;但显而易见的是,巨噬细胞可根据其表型表现出促炎症和抗炎症行为,这使得炎症反应数学模型可能对其所包含的巨噬细胞群的描述非常敏感。以前的许多炎症模型都包含一个同时具有促炎和抗炎功能的巨噬细胞群。在此,我们在这些现有模型的基础上,明确描述了不同的巨噬细胞表型,并研究了这在多大程度上影响了模型发出的炎症动态。我们通过 Matlab 中的数值模拟和 XPPAUT 中的动力系统分析来分析我们的模型,结果表明,与前体模型相比,分别考虑不同巨噬细胞表型的模型能提供更真实的稳态解(更好地捕捉组织常驻巨噬细胞的抗炎活性),以及以前未观察到的振荡动力学。最后,我们结合正在寻找治疗炎症的潜在新疗法的工作,对我们的分析结论进行了反思,并强调操纵巨噬细胞极化状态是一个潜在的治疗目标。
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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