School of Science & Technology, Nottingham Trent University, Nottingham, NG11 8NS, UK.
Institute for Cardiovascular and Metabolic Research, University of Reading, Reading, RG6 6AS, UK.
Math Med Biol. 2024 Jun 15;41(2):81-109. doi: 10.1093/imammb/dqae004.
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.
巨噬细胞在解决许多医学病症所涉及的炎症损伤方面发挥着广泛的作用，并且能够针对不同的环境刺激来采用不同的表型。准确地对巨噬细胞表型进行分类是一项艰巨的任务，并且在描述这些表型的最佳命名法方面存在文献差异；然而，很明显的是，巨噬细胞可以根据其表型表现出促炎和抗炎行为，这使得炎症反应的数学模型对其包含的巨噬细胞群体的描述变得敏感。许多以前的炎症模型都包含具有促炎和抗炎功能的单一巨噬细胞群体。在这里，我们在这些现有模型的基础上加入了对不同巨噬细胞表型的明确描述，并研究了这种描述对模型发出的炎症动态的影响程度。我们通过在 MATLAB 中的数值模拟和在 XPPAUT 中的动力系统分析来分析我们的模型，并表明，与前体模型相比，分别考虑不同巨噬细胞表型的模型可以提供更现实的稳态解（更好地捕捉组织驻留巨噬细胞的抗炎活性），以及以前未观察到的振荡动态。最后，我们在寻求炎症病症潜在新疗法的背景下反思我们分析的结论，强调巨噬细胞极化状态的操纵作为潜在的治疗靶点。
