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开发一种数学模型,用于对吸入有毒物质的先天免疫反应

Aamy Bakry¹, Emma Brashear², Jacob Brashear²

¹Department of Mathematics and Statistics, University of Richmond, Richmond, VA, USA.

Journal of theoretical biology

|June 8, 2025

概括

一个新的数学模型模拟了吸入有毒物质引起的肺炎. 反复暴露会导致持续的炎症,与一次性暴露不同,为慢性呼吸道疾病提供了洞察力.

科学领域:

计算生物学是一种计算生物学.
免疫学免疫学免疫学
数学建模的数学建模

背景情况:

吸入的有毒物质,如木烟,触发肺部炎症的中心呼吸系统疾病,如喘和COPD.
了解免疫系统对有毒物质的动态反应,对于开发有效的治疗方法至关重要.

研究的目的:

开发和验证在有毒剂诱导的肺炎期间免疫细胞和细胞因子相互作用的数学模型.
调查一次性或重复性毒性物质暴露对炎症反应的影响.

主要方法:

构建了一个数学模型,整合了上皮细胞,巨细胞 (M1/M2) 和细胞因子.
校准的子模型使用体外数据和免疫反应过渡的已知知识.
进行稳定性分析和模拟,以评估不同暴露场景下的模型行为.

主要成果:

该模型准确地预测了从促炎性 (I型,M1型巨细胞) 转向抗炎性/修复性 (II型,M2型巨细胞) 反应的转变.
模拟显示单次暴露导致自我限制的炎症,而重复暴露导致持续的炎症.
在重复暴露的模拟中观察到高的M2:M1巨细胞比率,与慢性肺部疾病相关.

结论:

数学模型为了解肺炎复杂的免疫动态提供了一个可处理的框架.
重复暴露于有毒物质可以导致慢性炎症状态,突出潜在的治疗点.
该模型作为虚拟组织模型的基础,用于探索炎症性肺部疾病的干预措施.

关键词:

表皮免疫相互作用炎症炎症是一种炎症.吸入性毒理学吸入性毒理学巨细胞的两极分化普通微分方程的常规微分方程

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