一个HIV感染的动力学模型

考虑到人体免疫缺损病毒(HIV)能感染和杀每T4细胞,病毒颗粒能从感染细胞膜上发芽而出以及感染细胞能与未感染细胞融合等实验事实,建议了一个细胞水平的人体免疫缺损病毒感染的动力学模型。利用这个模型,我们对HIV感染的动力学行为进行了分析。结果表明:在潜伏期,感染细胞的溶度和病毒的溶度都渐渐地趋于一个暂态的平衡值;在表达期,病毒溶度大幅度增加,正常T4细胞溶度渐渐减少,这也许正是AIDS病致病的原因。     

HIV模型动力学分析及抗HIV感染治疗仿真

基于基本病毒感染模型,本文引入了一个包含免疫项的艾滋病病毒(HIV)感染模型.该模型有一个病毒清除平衡点和一个持续带毒平衡点.证明如果病毒感染的基本再生数R1,则病毒清除平衡点是全局渐近稳定的.该结果说明若一个HIV感染者其R1,则即使被感染大量的HIV最终仍然能自愈.基于该模型本文提出了一个抗HIV感染治疗模型.本文定理暗指若抗HIV感染治疗时,患者的R1则迟早患者体内的HIV可以清除.反之数值的仿真模拟表明患者R1时,患者体内的HIV不能被彻底清除.患者的依从性是抗HIV感染成功的重要因素之一.     

具免疫时滞的HIV感染模型动力学性质分析

讨论了一类具免疫时滞的HIV感染模型.分析了未感染平衡点的全局渐近稳定性,给出了感染无免疫平衡点及感染免疫平衡点局部渐近稳定的充分条件.数值模拟结果表明,当易感细胞生成率的取值使得基本再生数满足平衡存在的条件且低于某一临界值时,时滞对平衡点的稳定性没有影响;若大于该临界值,随着时滞增大,稳定性开关发生,平衡点不稳定,出现一系列Hopf分支,最终表现为周期波动模式.     

具有年龄结构的HIV感染模型稳定性分析

研究了一类具有年龄结构的HIV感染模型,得到了未感染平衡点、感染平衡点局部渐近稳定的充分条件.     

HIV感染的基因治疗研究进展

由于目前尚无有效的抗ＨＩＶ感染的化学药物和疫苗,从九十年代开始,人们开始日益重视探索ＨＩＶ感染的基因治疗的新途径。ＨＩＶ感染的基因治疗就是把具有治疗作用的基因转移到合适的靶细胞中,使其在表达为ＲＮＡ或蛋白质后干扰ＨＩＶ基因表达及调控,以达到防治ＨＩＶ感染的目的。ＨＩＶ的分子生物学研究的深入和体细胞基因治疗技术的发展为ＨＩＶ感染的基因治疗提供了基础。目前采用的策略主要有三大类：抗病毒的基因治疗;细胞     

HIV感染中的细胞凋亡

CD4^ T细胞的丢失在HIV感染引起免疫缺陷过程中起着重要作用。但造成CD4^ T细胞丢失的具体机制还不清楚,细胞凋亡可能是CD4^ T细胞丢失的一个重要因素,HIV感染以后,病毒蛋白的持续性产出导致免疫系统的持续性激活,引起Th1细胞的丢失,Th1细胞通过合成Ⅰ型细胞因子,抑制淋巴细胞的自发凋亡,另外,病毒蛋白或其他因素能够使CD4^ ,CD8^ T细胞和APC转化为凋亡的效应细胞,通过Fas/FasL或其他途径引起细胞凋亡,HIV感染人体后凋亡细胞不仅有CD4^ T细胞,还包括B细胞,NK细胞,粒细胞,神经细胞和单细胞,凋亡作为机体的自我防护措施,在清除感染细胞的同时,并没有抑制HIV在单细胞/巨噬细胞内的复制,反而造成大量未感染细胞的凋亡,导致对HIV复制的失控,发展为严重的免疫缺陷,引起AIDS相关的机会性感染。     

HIV感染检测技术的研究进展

ＨＩＶ感染的检测是防治艾滋病和控制其传播的重要手段。本文综述了从宿主标本中直接检测到病毒本身的ＰＣＲ技术的抗原检测,以及抗ＨＩＶ检测技术的应用情况及优缺点,并结合自己的工作实际对ＨＩＶ感染检测技术的选择使用进行评述     

HIV感染的辅助因子—融合素

ＨＩＶ感染的辅助因子——融合素黄仕和秦椿华（卫生部武汉生物制品研究所,武汉４３００６０）（同济医科大学工业毒理研究室,武汉４３００３０）关键词融合素ＨＩＶ感染１９８４年,研究者发现,ＨＩＶ感染细胞是通过细胞表面受体ＣＤ４进行的。二年后又发现,仅有ＣＤ...     

NK细胞与HIV/SIV感染相关性的研究进展

NK细胞作为天然免疫系统的重要组成部分,其在HIV/SIV感染后的免疫机制及如何发挥抗病毒作用成为近几年艾滋病研究的热点之一。研究中发现,伴随HIV/SIV的感染,NK细胞亚群比例发生改变同时伴有功能缺陷,这种变化与HIV/SIV慢性感染阶段病毒复制水平有显著相关性。并且由于归巢受体表达的改变引起NK细胞在HIV/SIV感染者体内不同组织间的重新分布。NK细胞表面的受体KIR3DL1和KIR3DS也表现出对HIV感染的抵抗作用。这些发现为我们进一步研究NK细胞的抗HIV/SIV病毒感染的免疫机制提供了新的思路和方向。     

The effect of delayed death in HIV/AIDS models

HIV-infected patients who receive treatment survive for some years after they have acquired the disease. The received treatment causes sustained reduction of viral reproduction by improving the immune function, leading to prolonged progression period to AIDS development. This prolonged progression period has created variability in survival times that affects estimates produced using mathematical models that do not include delay in disease related mortality. This paper investigates the effect of including delay in AIDS death occurrence in HIV/AIDS transmission models. A simple mathematical model with two stages of HIV progression is developed and extended to include time delay in the occurrence of AIDS deaths. Numerical simulations indicate that time delay changes the mortality curves considerably but has less effect on the proportion of infectives. The study highlights the importance of incorporating delay in models of HIV/AIDS for the production of accurate HIV/AIDS estimates.     

Impact of gene-modified T cells on HIV infection dynamics

Previous clinical trials in HIV-infected patients involving infusion of T cells protected by an antiviral gene have failed to show any therapeutic benefit. The value of such a treatment approach is thus still highly controversial. In this study, the anticipated effects of gene-modified cells on virus and T-cell kinetics are analysed by mathematical modeling. Because technically only a small fraction of all T cells in a patient can be manipulated ex vivo, therapeutic success will depend on the accumulation of gene-modified cells after infusion into the patient by in vivo selection. Our simulations predict that a significant therapeutic benefit is conferred only by antiviral genes that inhibit HIV replication before virus integration (class I genes). Genes that inhibit viral protein expression (class II, used in previous clinical trials), require a much higher inhibitory activity than class I genes to promote the regeneration of T cells and reduce the viral load. Inhibition of virus assembly and release alone (class III) confers no selective advantage to the T cell and is therefore ineffective unless combined with class I (or, possibly, class II) genes. Also crucial in determining the clinical outcome are the regenerative capacity of the gene-modified cells and the level of HIV replication in the patient. These results can be important for guiding future strategies in the field of gene therapy for HIV infection.     

Population dynamics and control of Triatoma infestans

Analysis of field populations of Triatoma infestans (Hemiptera: Reduviidae), after a 3-year study, shows that population growth rate is affected by both density-dependent and density-independent mortality. Although an equilibrium exists, apparently as a consequence of a density dependent-mechanism, population density fluctuates throughout the year because of the effect of monthly mean minimum temperature as a density-independent source of mortality. Simulation studies based on Moran curves shows that high population densities have an approximately constant extinction probability (around 0.20), independently of the season the population starts growing. However, at very low population densities, the extinction probability depends strongly on the season when the population begins to grow. Very low density populations beginning in winter or autumn have the highest extinction probability. The outcome of the simulation studies coincides with results observed in field populations affected by insecticide application at different seasons.     

Bayesian experimental design for nonlinear mixed-effects models with application to HIV dynamics

Bayesian experimental design is investigated for Bayesian analysis of nonlinear mixed-effects models. Existence of the posterior risk for parameter estimation is shown. When the same prior distribution is used for both design and inference, existence of the preposterior risk for design is also proven. If the prior distribution used in design is different from that used for inference, sufficient conditions are established for existence of the preposterior risk for design. A case study of design for an experiment in population HIV dynamics is provided.     

Mutation and control of the human immunodeficiency virus

We examine the dynamics of infection by the human immunodeficiency virus (HIV), as well as therapies that minimize viral load, restore adaptive immunity, and use minimal dosage of anti-HIV drugs. Virtual therapies for wild-type infections are demonstrated; however, the HIV infection is never cured, requiring continued treatment to keep the condition in remission. With high viral turnover and mutation rates, drug-resistant strains of HIV evolve quickly. The ability of optimal therapy to contain drug-resistant strains is shown to depend upon the relative fitness of mutant strains.     

Design of long-term HIV dynamic studies using semiparametric mixed-effects models

Studies of HIV dynamics in AIDS research are very important in understanding the pathogenesis of HIV-1 infection and also in assessing the effectiveness of antiviral therapies. There are many AIDS clinical trials on HIV dynamics currently in development worldwide, giving rise to many design issues yet to be addressed. For example, most studies are focused on short-term viral dynamics and the existing models may not be applicable to describe long-term virologic response. In this paper, we use a simulation-based approach to study the designs of long-term viral dynamics under semiparametric nonlinear mixed-effects models. These models not only can preserve the meaningful interpretation of the short-term HIV dynamics, but also characterize the long-term virologic responses to antiretroviral (ARV) treatment. We investigate a number of feasible clinical protocol designs similar to those currently used in AIDS clinical trials. In particular, we evaluate whether earlier samplings can result in more useful information about the viral response trajectory; we also evaluate the effectiveness of two strategies: more frequent samplings per subject with fewer subjects versus fewer samplings per subject with more subjects while keeping the total number of samplings constant. The results of our investigation provide quantitative guidance for designing and selecting ARV therapy.     

通风房间常见微生物颗粒蒸发特性的仿真研究

通风调节房间环境参数,影响微生物颗粒蒸发过程。分析在该过程中颗粒粒径变化规律,构建对应的Matlab/simulink仿真模型,并选择典型通风房间和常见微生物颗粒释放源,应用该模型计算它们的蒸发过程,包括:在较低、较高和典型相对湿度的室内环境中,这些颗粒的蒸发过程。     

Paradoxical suppression of poly-specific broadly neutralizing antibodies in the presence of strain-specific neutralizing antibodies following HIV infection

One of the first immunologic responses against HIV infection is the presence of neutralizing antibodies that seem able to inactivate several HIV strains. Moreover, in vitro studies have shown the existence of monoclonal antibodies that exhibit broad crossclade neutralizing potential. Yet their number is low and slow to develop in vivo. In this paper, we investigate the potential benefits of inducing poly-specific neutralizing antibodies in vivo throughout immunization. We develop a mathematical model that considers the activation of families of B lymphocytes producing poly-specific and strain-specific antibodies and use it to demonstrate that, even if such families are successful in producing neutralizing antibodies, the competition between them may limit the poly-specific response allowing the virus to escape. We modify this model to account for viral evolution under the pressure of antibody responses in natural HIV infection. The model can reproduce viral escape under certain conditions of B lymphocyte competition. Using these models we provide explanations for the observed antibody failure in controlling natural infection and predict quantitative measures that need to be satisfied for long-term control of HIV infection.     

Ethical issues associated with HIV phylogenetics in HIV transmission dynamics research: A review of the literature using the Emanuel Framework

The reduced costs of DNA sequencing and the use of such data for HIV‐1 clinical management and phylogenetic analysis have led to a massive increase of HIV‐1 sequences in the last few years. Phylogenetic analysis has shed light on the origin, spread and characteristics of HIV‐1 epidemics and outbreaks. Phylogenetic analysis is now also being used to advance our knowledge of the drivers of HIV‐1 transmission in order to design effective interventions. However, HIV phylogenetic analysis presents unique ethical challenges, which have not been fully explored. This review presents an analysis of what appear to be key ethical issues in HIV phylogenetics in the hope of stimulating further conceptual and empirical work in this rapidly emerging area. We structure the review using the Emanuel Framework, a systematic, holistic framework, which has been adapted for use in developing countries, which bear the brunt of the HIV‐1 pandemic.     

Maximum likelihood estimation in dynamical models of HIV

The study of dynamical models of HIV infection, based on a system of nonlinear ordinary differential equations (ODE), has considerably improved the knowledge of its pathogenesis. While the first models used simplified ODE systems and analyzed each patient separately, recent works dealt with inference in non-simplified models borrowing strength from the whole sample. The complexity of these models leads to great difficulties for inference and only the Bayesian approach has been attempted by now. We propose a full likelihood inference, adapting a Newton-like algorithm for these particular models. We consider a relatively complex ODE model for HIV infection and a model for the observations including the issue of detection limits. We apply this approach to the analysis of a clinical trial of antiretroviral therapy (ALBI ANRS 070) and we show that the whole algorithm works well in a simulation study.