Department of Mathematics and Computer Science, Hobart and Williams Smith Colleges, 300 Pulteney St., Geneva, NY 14456, USA.
Bull Math Biol. 2012 Jul;74(7):1651-72. doi: 10.1007/s11538-012-9729-x. Epub 2012 May 5.
While antiretroviral drugs can drive HIV to undetectably low levels in the blood, eradication is hindered by the persistence of long-lived, latently infected memory CD4 T cells. Immune activation therapy aims to eliminate this latent reservoir by reactivating these memory cells, exposing them to removal by the immune system and the cytotoxic effects of active infection. In this paper, we develop a mathematical model that investigates the use of immune activation strategies while limiting virus and latent class rebound. Our model considers infection of two memory classes, central and transitional CD4 T cells and the role that general immune activation therapy has on their elimination. Further, we incorporate ways to control viral rebound by blocking activated cell proliferation through anti proliferation therapy. Using the model, we provide insight into the control of latent infection and subsequently into the long term control of HIV infection.
虽然抗逆转录病毒药物可以将 HIV 血液中的病毒载量降低到无法检测的水平,但长期潜伏感染的记忆 CD4 T 细胞的存在阻碍了 HIV 的彻底清除。免疫激活疗法旨在通过激活这些记忆细胞,使其暴露于免疫系统的清除和活跃感染的细胞毒性作用下,从而消除这种潜伏储库。在本文中,我们开发了一个数学模型,研究了在限制病毒和潜伏细胞反弹的情况下使用免疫激活策略的问题。我们的模型考虑了两种记忆细胞类别的感染,即中央记忆和过渡性 CD4 T 细胞,以及一般免疫激活疗法对它们消除的作用。此外,我们还通过抗增殖治疗来抑制激活细胞的增殖,从而控制病毒反弹。利用该模型,我们深入了解了潜伏感染的控制,进而了解了 HIV 感染的长期控制。