Department of Mathematics, 301 Thackeray Hall, University of Pittsburgh, Pittsburgh, PA 15260, United States.
Department of Mathematics, 301 Thackeray Hall, University of Pittsburgh, Pittsburgh, PA 15260, United States.
J Theor Biol. 2019 Jan 7;460:101-114. doi: 10.1016/j.jtbi.2018.08.033. Epub 2018 Aug 25.
When a pathogen invades the body, an acute inflammatory response is activated to eliminate the intruder. In some patients, runaway activation of the immune system may lead to collateral tissue damage and, in the extreme, organ failure and death. Experimental studies have found an association between severe infections and depletion in levels of adenosine triphosphate (ATP), increase in nitric oxide production, and accumulation of lactate, suggesting that tissue energetics is compromised. In this work we present a differential equations model that incorporates the dynamics of ATP, nitric oxide, and lactate accompanying an acute inflammatory response and employ this model to explore their roles in shaping this response. The bifurcation diagram of the model system with respect to the pathogen growth rate reveals three equilibrium states characterizing the health, aseptic and septic conditions. We explore the domains of attraction of these states to inform the instantiation of heterogeneous virtual patient populations utilized in a survival analysis. We then apply the model to study alterations in the inflammatory response and survival outcomes in metabolically altered conditions such as hypoglycemia, hyperglycemia, and hypoxia.
当病原体侵入人体时,会激活急性炎症反应以消灭入侵物。在某些患者中,免疫系统的失控激活可能导致附带的组织损伤,甚至导致器官衰竭和死亡。实验研究发现,严重感染与三磷酸腺苷 (ATP) 水平降低、一氧化氮生成增加和乳酸积累之间存在关联,表明组织能量学受到损害。在这项工作中,我们提出了一个微分方程模型,该模型包含伴随急性炎症反应的 ATP、一氧化氮和乳酸的动力学,并利用该模型探索它们在塑造这种反应中的作用。模型系统相对于病原体增长率的分岔图揭示了三个平衡状态,分别代表健康、无菌和感染状态。我们探索了这些状态的吸引域,以告知用于生存分析的异构虚拟患者群体的实例化。然后,我们将模型应用于研究代谢改变条件(如低血糖、高血糖和缺氧)下炎症反应和生存结果的改变。