Mathematics, Ohio University, Athens, OH 45701, USA.
Math Biosci. 2012 Feb;235(2):189-200. doi: 10.1016/j.mbs.2011.12.004. Epub 2012 Jan 4.
In order to gain a deeper understanding of the onset and progression of pulmonary infections we present and analyze a low dimensional, phenomenological model of infection and the innate immune response in the lungs. Because pulmonary innate immunity has features unique to itself, general mathematical models of the immune system may not be appropriate. The differential equations model that we propose is based on current knowledge of the biology of pulmonary innate immunity and accurately reproduces known features of the initial phase of the dynamics of pulmonary innate system as exhibited in recent experiments. Further, we propose to use the model as a starting point for interrogation with clinical data from a new noninvasive technique for sampling alveolar lining fluid.
为了更深入地了解肺部感染的发病机制和进展，我们提出并分析了一个肺部感染和先天免疫反应的低维、唯象模型。由于肺部先天免疫具有自身独特的特征，一般的免疫系统数学模型可能并不适用。我们提出的微分方程模型基于目前对肺部先天免疫生物学的认识，并准确再现了最近实验中展示的肺部先天系统动力学初始阶段的已知特征。此外，我们还提出利用该模型作为起点，结合一种新的非侵入性肺泡衬液取样技术的临床数据进行研究。
