标题： 药物洗脱和病毒反弹：在停止抗逆转录病毒治疗期间HIV再激活的建模 显示英文标题

标题： Drug Washout and Viral Rebound: Modeling HIV Reactivation Under ART Discontinuation

摘要： 由于潜伏感染的CD4$^+$T细胞的持续存在，实现HIV-1的功能性治愈仍然是一个重大挑战，因为病毒能够逃避免疫清除，这反过来导致治疗后病毒反弹。 由于传统确定性模型假设再激活速率为常数，它们无法捕捉到受免疫扰动和ART药代动力学影响的潜伏逆转的随机性。 因此，在本研究中，通过使用一种结合激活速率波动的泊松驱动随机框架，我们研究了病毒反弹动力学。 通过一个指数衰减的药物洗脱模型，我们准确量化了ART衰减与随机再激活之间的非线性相互作用，提高了对治疗后控制的理论估计。 除了引入随机性外，我们的模型建立了一个时间依赖的病毒再激活框架，整合了激活速率中的周期性和随机扰动。 与假设均匀（时间独立）再激活的传统模型不同，我们表明潜伏逆转遵循由免疫周期、昼夜节律和短暂炎症事件调制的结构化振荡模式。 这一发现表明，病毒反弹风险是由免疫波动动态塑造的，这与再激活概率恒定的假设相反。 我们还通过引入伽马分布的等待时间来研究模型系统，以考虑再激活动力学的异质性，从而提供了对储库动力学更灵活的表征。 我们认为这些见解对HIV治愈策略具有重要的意义。 显示英文摘要

摘要： Due to the persistence of latently infected CD4$^+$ T cells, achieving a functional cure for HIV-1 remains a significant challenge since the viruses are able to evade immune clearance, which in turn enables post-treatment viral rebound. Because traditional deterministic models assume a constant reactivation rate, they fail to capture the stochastic nature of latency reversal influenced by immune perturbations and ART pharmacokinetics. Thus, in this study, by using a Poisson-driven stochastic framework that incorporates fluctuations in activation rates, we study viral rebound dynamics. Via an exponentially decreasing drug washout model, we accurately quantifies the nonlinear interplay between ART decay and stochastic reactivation, improving the theoretical estimates of post-treatment control. Beyond the introduction of stochasticity, our model establishes a time-dependent viral reactivation framework that integrates periodic and random perturbations in the activation rates. Unlike conventional models that assume uniform (temporally independent reactivation), we show that latency reversal follows structured oscillatory patterns modulated by immune cycles, circadian rhythms, and transient inflammatory episodes. This finding suggests that viral rebound risk is dynamically shaped by immune fluctuations, contrary to the assumption of a constant reactivation probability. We also study the model system by incorporating Gamma-distributed waiting times to account for heterogeneity in reactivation kinetics, which in turn provides a more flexible characterization of reservoir dynamics. We believe that these insights have critical implications for HIV cure strategies.