Mathematics Institute, University of Warwick, Coventry CV4 7AL, UK.
J Theor Biol. 2010 Jun 7;264(3):962-70. doi: 10.1016/j.jtbi.2010.03.010. Epub 2010 Mar 11.
In infectious disease as well as in cancer, the ultimate outcome of the curative response, mediated by the body itself or through drug treatment, is either successful eradication or a resurgence of the disease ("flare-up" or "relapse"), depending on random fluctuations that dominate the dynamics of the system when the number of diseased cells has become very low. The presence of a low-numbers bottle-neck in the dynamics, which is unavoidable if eradication is to take place at all, renders at least one phase of the dynamics essentially stochastic. However, the eradicating agents (e.g. immune cells, drug molecules) generally remain at high numbers during the critical bottle-neck phase, sufficiently so to warrant a deterministic treatment. This leads us to consider a hybrid stochastic-deterministic approach where the infected cells are treated stochastically whereas the eradicating agents are treated deterministically. Exploiting the fact that the number of eradicating agents typically decreases monotonically during the resolution phase of the response, we derive a set of coupled first-order differential equations that describe the probability of ultimate eradication as a function of the system's state, and we consider a number of biomedical applications.
在传染病和癌症中,由机体自身介导或通过药物治疗产生的治疗反应的最终结果,要么是成功根除,要么是疾病的复发(“爆发”或“复发”),这取决于当患病细胞数量非常低时,主导系统动态的随机波动。如果要实现根除,动态中必然存在一个低数量瓶颈,这使得动态的至少一个阶段本质上是随机的。然而,根除剂(例如免疫细胞、药物分子)在关键瓶颈阶段通常仍然保持在较高数量,足以保证确定性治疗。这导致我们考虑一种混合的随机-确定性方法,其中受感染的细胞是随机处理的,而根除剂是确定性处理的。利用根除剂数量在反应的解决阶段通常单调下降的事实,我们推导出一组耦合的一阶微分方程,将最终根除的概率描述为系统状态的函数,并考虑了一些生物医学应用。