Benefits from early treatment of HIV-1 infection

Encouraging results in the treatment of HIV-1 infection have been achieved in the last few years, after introduction of the triple therapy approach. The initial hope that the immune system might control the infection after highly active antiviral therapy (HAART) has however not been fulfilled, as the reappearance of virus has been observed after discontinuation of HAART. The early phase of the infection determines the ultimate outcome, as it is this period when immune cells that are able to control the infection start to proliferate. Unfortunately, HIV-1 replicates more efficiently in proliferating CD4 T cells, resulting in the self-elimination of the immune cells capable of dealing with the virus within the first months of infection.     

Advance in treatment strategy and immune reconstruction against HIV-1 infection

HIV-1 can be considered an infection of the immune system, resulting in progressive and ultimately profound immune suppression. The availability of highly active antiretroviral therapy (HAART) has resulted in dramatic changes in the disease course in persons fortunate enough to have access to these medications, but long-term therapy is limited by the development of resistance as well as toxicities of the potent medication regimens. Emerging data indicate that individuals who have non-progressive clinical course control HIV-1 immunologically. This has bolstered hope that the immune response might be effectively augmented in persons with HIV infection. Recent data indicating that immediate treatment of acute infection leads to augmentation of antiviral immune responses have provided evidence that the immune system might be enhanced in certain situations. Therefore, investigation in the reconstitution of anti-HIV immune response in patients under HAART should provide encouragement for continuing to explore methods to obtain meaningful and durable immune enhancement as an adjunct to HAART in HIV-1 infection.     

Stochastic optimal therapy for enhanced immune response

Therapeutic enhancement of humoral immune response to microbial attack is addressed as the stochastic optimal control of a dynamic system. Without therapy, the modeled immune response depends upon the initial concentration of pathogens in a simulated attack. Immune response can be augmented by agents that kill the pathogen directly, that stimulate the production of plasma cells or antibodies, or that enhance organ health. Using a generic mathematical model of immune response to the infection (i.e., of the dynamic state of the system), previous papers demonstrated optimal (open-loop) and neighboring-optimal (closed-loop) control solutions that defeat the pathogen and preserve organ health, given initial conditions that otherwise would be lethal [Optimal Contr. Appl. Methods 23 (2002) 91, Bioinformatics 18 (2002) 1227]. Therapies based on separate and combined application of the agents were derived by minimizing a quadratic cost function that weighted both system response and drug usage, providing implicit control over harmful side effects. Here, we focus on the effects that corrupted or incomplete measurements of the dynamic state may have on neighboring-optimal feedback control. Imperfect measurements degrade the precision of feedback adjustments to therapy; however, optimal state estimation allows the feedback strategy to be implemented with incomplete measurements and minimizes the expected effects of measurement error. Complete observability of the perturbed state for this four state example is provided by measurement of four of the six possible pairs of two variables, either set of three variables, or all four variables. The inclusion of state estimation extends the applicability of optimal control theory for developing new therapeutic protocols to enhance immune response.     

Reconstitution of EBV latent but not lytic antigen-specific CD4+ and CD8+ T cells after HIV treatment with highly active antiretroviral therapy

The incidence of (EBV-related) malignancies in HIV-infected subjects has declined since the introduction of highly active antiretroviral therapy (HAART). To investigate the effect of HAART on EBV infection, we performed a longitudinal analysis of the T cell response to both a latent and a lytic Ag and EBV viral load in 10 subjects from early in HIV infection up to 5 years after HAART. All individuals responded to HAART by a decline in HIV viral load, a restoration of total CD4+ T cell numbers, and a decline in T cell immune activation. Despite this, EBV load remained unaltered, even after 5 years of therapy, although a decline in both CD4+ and CD8+ T cells specific for the lytic EBV protein BZLF1 suggested a decreased EBV reactivation rate. In contrast, latent EBV Ag EBNA1-specific CD4+ and CD8+ T cell responses were restored after 5 years of treatment to levels comparable to healthy individuals. In two individuals who were treated by HAART late during HIV progression, a lymphoma developed shortly after initiation of HAART, despite restoration of EBV-specific CD4+ and CD8+ T cells. In conclusion, long-term HAART does not alter the EBV DNA load, but does lead to a restoration of EBNA1-specific T cell responses, which might allow better control of EBV-infected cells when applied early enough during HIV infection.     

Optimal vaccine allocation for COVID-19 in the Netherlands: A data-driven prioritization

For the control of COVID-19, vaccination programmes provide a long-term solution. The amount of available vaccines is often limited, and thus it is crucial to determine the allocation strategy. While mathematical modelling approaches have been used to find an optimal distribution of vaccines, there is an excessively large number of possible allocation schemes to be simulated. Here, we propose an algorithm to find a near-optimal allocation scheme given an intervention objective such as minimization of new infections, hospitalizations, or deaths, where multiple vaccines are available. The proposed principle for allocating vaccines is to target subgroups with the largest reduction in the outcome of interest. We use an approximation method to reconstruct the age-specific transmission intensity (the next generation matrix), and express the expected impact of vaccinating each subgroup in terms of the observed incidence of infection and force of infection. The proposed approach is firstly evaluated with a simulated epidemic and then applied to the epidemiological data on COVID-19 in the Netherlands. Our results reveal how the optimal allocation depends on the objective of infection control. In the case of COVID-19, if we wish to minimize deaths, the optimal allocation strategy is not efficient for minimizing other outcomes, such as infections. In simulated epidemics, an allocation strategy optimized for an outcome outperforms other strategies such as the allocation from young to old, from old to young, and at random. Our simulations clarify that the current policy in the Netherlands (i.e., allocation from old to young) was concordant with the allocation scheme that minimizes deaths. The proposed method provides an optimal allocation scheme, given routine surveillance data that reflect ongoing transmissions. This approach to allocation is useful for providing plausible simulation scenarios for complex models, which give a more robust basis to determine intervention strategies.     

Cutting edge: Rapid recovery of NKT cells upon institution of highly active antiretroviral therapy for HIV-1 infection

CD1d-restricted NKT cells play important regulatory roles in various immune responses and are rapidly and selectively depleted upon infection with HIV-1. The cause of this selective depletion is incompletely understood, although it is in part due to the high susceptibility of CD4+ NKT cells to direct infection and subsequent cell death by HIV-1. Here, we demonstrate that highly active antiretroviral therapy (HAART) results in the rapid recovery of predominantly CD4(-) NKT cells with kinetics that are strikingly similar to those of mainstream T cells. As it is well known that the early recovery of mainstream T cells in response to HAART is due to their redistribution from tissues to the circulation, our data suggest that the selective depletion of circulating NKT cells is likely due to a combination of cell death and tissue sequestration and indicates that HAART can improve immune functions by reconstituting both conventional T cells and immunoregulatory NKT cells.     

Cyclosporin A in combination with HAART in primary HIV-1 infection

HAART is the cornerstone of HIV therapy, and has significantly reduced morbidity and mortality associated with HIV disease. The institution of HAART during the primary HIV-1 infection has a more profound influence on the ultimate pattern and rate of disease progression than therapy commenced later on. However, it also well demonstrated that HAART alone is not able to eradicate the virus, unless over a life-long period of time. There is therefore the need to develop alternative strategies aimed at modulating the immune responses in order to achieve the long-term control of HIV even once HAART is discontinued. Among immunomodulant agents, cyclosporin A in combination with HAART might play a role in the treatment of people with primary HIV-1 infection.     

A model predictive control based scheduling method for HIV therapy

Recently developed models of the interaction of the human immune system and the human immunodeficiency virus (HIV) suggest the possibility of using interruptions of highly active anti-retroviral therapy (HAART) to simulate a therapeutic vaccine and induce cytotoxic lymphocyte (CTL) mediated control of HIV infection. We have developed a model predictive control (MPC) based method for determining optimal treatment interruption schedules for this purpose. This method provides a clinically implementable framework for calculating interruption schedules that are robust to errors due to measurement and patient variations. In this paper, we discuss the medical motivation for this work, introduce the MPC-based method, show simulation results, and discuss future work necessary to implement the method.     

基于RNA的抗HIV-1基因治疗方法研究进展

艾滋病自发现以来在全球范围内迅速蔓延,危害性极高,目前广泛采用的高效抗逆转录病毒疗法(HAART)虽能够显著提高HIV-1感染者生活质量,但存在着价格昂贵,耐药和副作用的问题经常会导致HAART治疗的中断。要获得长期持续的抗病毒治疗效果还有待于研发新的抗病毒药物和治疗方法。近年来随着分子生物技术、干细胞研究、纳米技术等相关技术的发展,关于抗HIV-1基因治疗方法的研究受到了广泛关注。主要针对基于RNA的抗HIV-1基因治疗方法,包括反义RNA、核酶、RNA诱饵以及RNA干扰技术在抗HIV-1基因治疗方面进行综述。研究表明,以RNA为基础的抗HIV-1基因治疗方法有望成为传统治疗方法的一种有效辅助手段。     

Dynamic optimization of host defense, immune memory, and post-infection pathogen levels in mammals

When attacked by pathogens, higher vertebrates produce specific immune cells that fight against them. We here studied the host's optimal schedule of specific immune cell production. The damage caused by the pathogen increases with the pathogen amount in the host integrated over time. On the other hand, there is also a cost incurred by the production of specific immune cells, not only in terms of the energy needed to produce and maintain the cells, but also with respect to damages sustained by the host's body as a result of immune activity. The optimal strategy of the host is the one that minimizes the total cost, defined as a weighted sum of the damage caused by pathogens and the costs caused by the specific immune cells. The problem is solved by using Pontryagin's maximum principle and dynamic programming. The optimal defense schedule is typically as follows: In the initial phase after infection, immune cells are produced at the fastest possible rate. The amount of pathogen increases temporarily but is eventually suppressed. When the pathogen amount is suppressed to a sufficiently low level, the immune cell number decreases and converges to a low steady level, which is maintained by alternately switching between fastest production and no production. We examine the effect of time delay required to have fully active immune cells by comparing cases with different number of rate limiting steps before producing immune cells. We examine the effect of the duration of time (time delay) required before full-scale production of active immune cells by comparing cases with different numbers of rate-limiting steps before immune-cell production. We also discuss the role of immune memory based on the results of the optimal immune reaction.     

The merits of a parallel genetic algorithm in solving hard optimization problems

A parallel genetic algorithm for optimization is outlined, and its performance on both mathematical and biomechanical optimization problems is compared to a sequential quadratic programming algorithm, a downhill simplex algorithm and a simulated annealing algorithm. When high-dimensional non-smooth or discontinuous problems with numerous local optima are considered, only the simulated annealing and the genetic algorithm, which are both characterized by a weak search heuristic, are successful in finding the optimal region in parameter space. The key advantage of the genetic algorithm is that it can easily be parallelized at negligible overhead.     

Neutralizing antibodies associated with viremia control in a subset of individuals after treatment of acute human immunodeficiency virus type 1 infection

Immediate treatment of acute human immunodeficiency virus type 1 (HIV-1) infection has been associated with subsequent control of viremia in a subset of patients after therapy cessation, but the immune responses contributing to control have not been fully defined. Here we examined neutralizing antibodies as a correlate of viremia control following treatment interruption in HIV-1-infected individuals in whom highly active antiretriviral therapy (HAART) was initiated during early seroconversion and who remained on therapy for 1 to 3 years. Immediately following treatment interruption, neutralizing antibodies were undetectable with T-cell-line adapted strains and the autologous primary HIV-1 isolate in seven of nine subjects. Env- and Gag-specific antibodies as measured by enzyme-linked immunosorbent assay were also low or undetectable at this time. Despite this apparent poor maturation of the virus-specific B-cell response during HAART, autologous neutralizing antibodies emerged rapidly and correlated with a spontaneous downregulation in rebound viremia following treatment interruption in three subjects. Control of rebound viremia was seen in other subjects in the absence of detectable neutralizing antibodies. The results indicate that virus-specific B-cell priming occurs despite the early institution of HAART, allowing rapid secondary neutralizing-antibody production following treatment interruption in a subset of individuals. Since early HAART limits viral diversification, we hypothesize that potent neutralizing-antibody responses to autologous virus are able to mature and that in some persons these responses contribute to the control of plasma viremia after treatment cessation.     

Association of Y chromosome haplogroup I with HIV progression, and HAART outcome

The host genetic basis of differential outcomes in HIV infection, progression, viral load set point and highly active retroviral therapy (HAART) responses was examined for the common Y haplogroups in European Americans and African Americans. Accelerated progression to acquired immune deficiency syndrome (AIDS) and related death in European Americans among Y chromosome haplogroup I (Y-I) subjects was discovered. Additionally, Y-I haplogroup subjects on HAART took a longer time to HIV-1 viral suppression and were more likely to fail HAART. Both the accelerated progression and longer time to viral suppression results observed in haplogroup Y-I were significant after false-discovery-rate corrections. A higher frequency of AIDS-defining illnesses was also observed in haplogroup Y-I. These effects were independent of the previously identified autosomal AIDS restriction genes. When the Y-I haplogroup subjects were further subdivided into six I subhaplogroups, no one subhaplogroup accounted for the effects on HIV progression, viral load or HAART response. Adjustment of the analyses for population stratification found significant and concordant haplogroup Y-I results. The Y chromosome haplogroup analyses of HIV infection and progression in African Americans were not significant. Our results suggest that one or more loci on the Y chromosome found on haplogroup Y-I have an effect on AIDS progression and treatment responses in European Americans. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Genetic Algorithm Based Scheduling of Meta-Tasks with Stochastic Execution Times in Heterogeneous Computing Systemst1

In this study, we address the meta-task scheduling problem in heterogeneous computing (HC) systems, which is to find a task assignment that minimizes the schedule length of a meta-task composed of several independent tasks with no data dependencies. The fact that the meta-task scheduling problem in HC systems is NP-hard has motivated the development of many heuristic scheduling algorithms. These heuristic algorithms, however, neglect the stochastic nature of task execution times in an attempt to minimize a deterministic objective function, which is the maximum of the expected values of machine loads. Contrary to existing heuristics, we account for this stochastic nature by modeling task execution times as random variables. We, then, formulate a stochastic scheduling problem where the objective is to minimize the expected value of the maximum of machine loads. We prove that this new objective is underestimated by the deterministic objective function and that an optimal task assignment obtained with respect to the deterministic objective function could be inefficient in a real computing platform. In order to solve the stochastic scheduling problem posed, we develop a genetic algorithm based scheduling heuristic. Our extensive simulation studies show that the proposed genetic algorithm can produce better task assignments as compared to existing heuristics. Specifically, we observe a performance improvement on the relative cost heuristic (M.-Y. Wu and W. Shu, A high-performance mapping algorithm for heterogeneous computing systems, in: Int. Parallel and Distributed Processing Symposium, San Francisco, CA, April 2001) by up to 61%.     

Anti-human immunodeficiency virus type 1 humoral immune response and highly active antiretroviral treatment

Highly active antiretroviral treatment (HAART) of human immunodeficiency type 1 (HIV-1) infection is very effective in controlling infection, but elimination of viral infection has not been achieved as yet, and upon treatment interruption an immediate rebound of viremia is observed. A combination of HAART with an immune stimulation might allow treatment interruption without this rebounding viremia, as the very low viremias observed with successful HAART may be insufficient to permit maintenance of a specific anti-HIV-1 immune response. The objective of this study was to compare the humoral immune response of individuals undergoing successful HAART (NF=no failure) with that of individuals with evidence of failure of therapy (FT) and to verify if the viremia peaks observed in individuals with therapy failure would act as a specific stimulus for the humoral anti-HIV-1 immune response. Antibodies binding to gp120 V3 genotype consensus peptides were more frequently observed for FT, mainly against peptides corresponding to sequences of genotypes prevalent in the Rio de Janeiro city area, B and F. HIV-1 neutralization of HIV-1 IIIB and of four primary isolates from Rio de Janeiro was less frequently observed for plasma from the NF than the FT group, but this difference was more expressive when plasma from individuals with detectable viremia were compared to that of individuals with undetectable viral loads in the year before sample collection. Although statistically significant differences were observed only in some specific comparisons, the study indicates that presence of detectable viremia may contribute to the maintenance of a specific anti-HIV-1 humoral immune response.     

Optimal vaccination schedules using simulated annealing

SUMMARY: Since few years the problem of finding optimal solutions for drug or vaccine protocols have been tackled using system biology modeling. These approaches are usually computationally expensive. Our previous experiences in optimizing vaccine or drug protocols using genetic algorithms required the use of a high performance computing infrastructure for a couple of days. In the present article we show that by an appropriate use of a different optimization algorithm, the simulated annealing, we have been able to downsize the computational effort by a factor 10(2). The new algorithm requires computational effort that can be achieved by current generation personal computers. AVAILABILITY: Software and additional data can be found at http://www.immunomics.eu/SA/     

Comparison of epigenetic profiles of human oral epithelial cells from HIV-positive (on HAART) and HIV-negative subjects

HIV-infected subjects on highly active antiretroviral therapy (HAART) are susceptible to comorbid microbial infections in the oral cavity. We observed that primary oral epithelial cells (POECs) isolated from HIV+ subjects on HAART grow more slowly and are less innate immune responsive to microbial challenge when compared with POECs from normal subjects. These aberrant cells also demonstrate epigenetic differences that include reduction in histone deacetylase 1 (HDAC-1) levels and reduced total DNA methyltransferase (DNMT) activity specific to enzymes DNMT1 and DNMT3A. The DNMT activity correlates well with global DNA methylation, indicating that aberrant DNMT activity in HIV+ (on HAART) POECs leads to an aberrantly methylated epithelial cell phenotype. Overall, our results lead us to hypothesize that, in patients with chronic HIV infection on HAART, epigenetic changes in key genes result in increased vulnerability to microbial infection in the oral cavity.     

Potential role of immune modulation in the effective long-term control of HIV-1 infection

Recent advances in HIV-1 pathogenesis, and in defining virological and immunological responses to highly active antiretroviral therapy (HAART), along with the identification of the numerous drawbacks of HAART, have clearly demonstrated that the eradication of the virus is not a feasible therapeutic goal, and that there is an urgent need to develop other approaches to fight HIV-1 infection. Novel therapeutic approaches of immune modulation have recently been evaluated in pilot clinical trials. First, treating primary HIV-1 infection with cyclosporin A (CsA) coupled with HAART to target massive immune activation extends the benefits achieved with HAART during primary HIV-1 infection and might contribute to the establishment of a more favourable immunological set-point affecting the ultimate pattern and rate of disease progression. Second, treating chronic HIV-1 infection in patients with long-term suppression of virus replication induced by HAART, with the addition of mycophenolate mofetil (MMF) reduces the pool of activated CD4+ T lymphocytes able to support productive HIV-1 infection, and might have an indirect impact on the pool of resting, latently infected CD4+ T cells, contributing to its depletion in vivo. The important question is clearly whether these results will have an impact on the clinical management of patients with HIV-1 infection, determining the precise therapeutic function of drugs like CsA and MMF, thus investigating the effects of these drugs on residual viral replication and the decay of the latent reservoir, on long-term immunological benefit, and, ultimately, on clinical benefit.     

Switching neuronal state: optimal stimuli revealed using a stochastically-seeded gradient algorithm

Inducing a switch in neuronal state using energy optimal stimuli is relevant to a variety of problems in neuroscience. Analytical techniques from optimal control theory can identify such stimuli; however, solutions to the optimization problem using indirect variational approaches can be elusive in models that describe neuronal behavior. Here we develop and apply a direct gradient-based optimization algorithm to find stimulus waveforms that elicit a change in neuronal state while minimizing energy usage. We analyze standard models of neuronal behavior, the Hodgkin-Huxley and FitzHugh-Nagumo models, to show that the gradient-based algorithm: 1) enables automated exploration of a wide solution space, using stochastically generated initial waveforms that converge to multiple locally optimal solutions; and 2) finds optimal stimulus waveforms that achieve a physiological outcome condition, without a priori knowledge of the optimal terminal condition of all state variables. Analysis of biological systems using stochastically-seeded gradient methods can reveal salient dynamical mechanisms underlying the optimal control of system behavior. The gradient algorithm may also have practical applications in future work, for example, finding energy optimal waveforms for therapeutic neural stimulation that minimizes power usage and diminishes off-target effects and damage to neighboring tissue.