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HIV 潜伏数学模型。

Mathematical Models of HIV Latency.

机构信息

Program for Evolutionary Dynamics, Harvard University, Cambridge, MA, 02138, USA.

出版信息

Curr Top Microbiol Immunol. 2018;417:131-156. doi: 10.1007/82_2017_77.

Abstract

Viral latency is a major barrier to curing HIV infection with antiretroviral therapy, and consequently, for eliminating the disease globally. The establishment, maintenance, and potential clearance of latent infection are complex dynamic processes and can be best understood and described with the help of mathematical models. Here we review the use of viral dynamics models for HIV, with a focus on applications to the latent reservoir. Such models have been used to explain the multiphasic decay of viral load during antiretroviral therapy, the early seeding of the latent reservoir during acute infection and the limited inflow during treatment, the dynamics of viral blips, and the phenomenon of posttreatment control. In addition, mathematical models have been used to predict the efficacy of potential HIV cure strategies, such as latency-reversing agents, early treatment initiation, or gene therapies, and to provide guidance for designing trials of these novel interventions.

摘要

病毒潜伏是利用抗逆转录病毒疗法治愈 HIV 感染的主要障碍,因此也是在全球消除该疾病的主要障碍。潜伏感染的建立、维持和潜在清除是复杂的动态过程,借助数学模型可以最好地理解和描述这些过程。在这里,我们综述了 HIV 病毒动力学模型的应用,重点是对潜伏库的应用。此类模型已被用于解释抗逆转录病毒治疗期间病毒载量的多相衰减、急性感染期间潜伏库的早期定植以及治疗期间有限的流入、病毒爆发的动力学以及治疗后控制现象。此外,数学模型还被用于预测潜在的 HIV 治愈策略(如潜伏逆转剂、早期治疗开始或基因治疗)的疗效,并为这些新干预措施的试验设计提供指导。

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