SMARThivPack: a complexity free and cost effective "three tests" combo kit model for improving HIV patients monitoring standards in resource poor settings

We propose a second method at an implementation level with cost and complexity reductions for monitoring HIV patients in resource-limited settings. The model is SMARThivPack, a "three tests" combo kit. Cost and complexity reductions of HIV patient monitoring technologies were described in a first model (at a technology development stage) proposed earlier. In developed countries, HIV patient clinical management programs comport three laboratory tests containing CD4 count, viral load measurement and pharmaco-resistance testing. In most developing countries only CD4 count is performed without the other two tests. Cost and complexity of required technologies are the major challenges to the developing world to meeting the "three tests" standard. SMARThivPack model achieves the "three tests" standard in the developing world by optimizing technology choice as to favour cross-use of equipments, thereby reducing equipment cost at the laboratory implementation level. Equipment cross use also reduces complexity by reducing training time, promoting specialization and substantiating experience in equipment use. The second level cost and complexity reductions model sets the grounds for a third level, global coordination cost and complexity reductions model.     

SMARThivCD4mos: a complexity-free and cost effective model technology for monitoring HIV patients CD4 number in resource-poor settings

We design a "simple" and "low cost" model technology for monitoring HIV patients CD4 number in resource-poor settings: SMARThivCD4mos. Cost and complexity are the major challenges to the developing world in transferring and implementing HIV surveillance technologies. We previously proposed a "three tests" combo kit model for improving HIV patients monitoring standards in resource-poor settings. From the pool of recommended alternative CD4 counting technologies, our "three tests" combo kit model retained the Capcellia technology for its "simplicity". However, compared to other CD4 counting technologies, such as Dynabeads, the Capcellia technology is "expensive". Here, we describe a cost reduction strategy of the Capcellia technology.     

Cost-Effectiveness of HIV Drug Resistance Testing to Inform Switching to Second Line Antiretroviral Therapy in Low Income Settings

Background

To guide future need for cheap resistance tests for use in low income settings, we assessed cost-effectiveness of drug resistance testing as part of monitoring of people on first line ART - with switching from first to second line ART being conditional on NNRTI drug resistance mutations being identified.

Methods

An individual level simulation model of HIV transmission, progression and the effect of ART which accounts for adherence and resistance development was used to compare outcomes of various potential monitoring strategies in a typical low income setting in sub-Saharan Africa. Underlying monitoring strategies considered were based on clinical disease, CD4 count or viral load. Within each we considered a strategy in which no further measures are performed, one with a viral load measure to confirm failure, and one with both a viral load measure and a resistance test. Predicted outcomes were assessed over 2015–2025 in terms of viral suppression, first line failure, switching to second line regimen, death, HIV incidence, disability-adjusted-life-years averted and costs. Potential future low costs of resistance tests ($30) were used.

Results

The most effective strategy, in terms of DALYs averted, was one using viral load monitoring without confirmation. The incremental cost-effectiveness ratio for this strategy was $2113 (the same as that for viral load monitoring with confirmation). ART monitoring strategies which involved resistance testing did not emerge as being more effective or cost effective than strategies not using it. The slightly reduced ART costs resulting from use of resistance testing, due to less use of second line regimens, was of similar magnitude to the costs of resistance tests.

Conclusion

Use of resistance testing at the time of first line failure as part of the decision whether to switch to second line therapy was not cost-effective, even though the test was assumed to be very inexpensive.     

Maximum Likelihood Estimation of Long‐Term HIV Dynamic Models and Antiviral Response

Summary HIV dynamics studies, based on differential equations, have significantly improved the knowledge on HIV infection. While first studies used simplified short‐term dynamic models, recent works considered more complex long‐term models combined with a global analysis of whole patient data based on nonlinear mixed models, increasing the accuracy of the HIV dynamic analysis. However statistical issues remain, given the complexity of the problem. We proposed to use the SAEM (stochastic approximation expectation‐maximization) algorithm, a powerful maximum likelihood estimation algorithm, to analyze simultaneously the HIV viral load decrease and the CD4 increase in patients using a long‐term HIV dynamic system. We applied the proposed methodology to the prospective COPHAR2–ANRS 111 trial. Very satisfactory results were obtained with a model with latent CD4 cells defined with five differential equations. One parameter was fixed, the 10 remaining parameters (eight with between‐patient variability) of this model were well estimated. We showed that the efficacy of nelfinavir was reduced compared to indinavir and lopinavir.     

An HIV Epidemic Model Based on Viral Load Dynamics: Value in Assessing Empirical Trends in HIV Virulence and Community Viral Load

Trends in HIV virulence have been monitored since the start of the AIDS pandemic, as studying HIV virulence informs our understanding of HIV epidemiology and pathogenesis. Here, we model changes in HIV virulence as a strictly evolutionary process, using set point viral load (SPVL) as a proxy, to make inferences about empirical SPVL trends from longitudinal HIV cohorts. We develop an agent-based epidemic model based on HIV viral load dynamics. The model contains functions for viral load and transmission, SPVL and disease progression, viral load trajectories in multiple stages of infection, and the heritability of SPVL across transmissions. We find that HIV virulence evolves to an intermediate level that balances infectiousness with longer infected lifespans, resulting in an optimal SPVL∼4.75 log₁₀ viral RNA copies/mL. Adaptive viral evolution may explain observed HIV virulence trends: our model produces SPVL trends with magnitudes that are broadly similar to empirical trends. With regard to variation among studies in empirical SPVL trends, results from our model suggest that variation may be explained by the specific epidemic context, e.g. the mean SPVL of the founding lineage or the age of the epidemic; or improvements in HIV screening and diagnosis that results in sampling biases. We also use our model to examine trends in community viral load, a population-level measure of HIV viral load that is thought to reflect a population''s overall transmission potential. We find that community viral load evolves in association with SPVL, in the absence of prevention programs such as antiretroviral therapy, and that the mean community viral load is not necessarily a strong predictor of HIV incidence.     

Durable Suppression of HIV-1 after Virologic Monitoring-Based Antiretroviral Adherence Counseling in Rakai,Uganda

ObjectivesHIV viral load is recommended for monitoring antiretroviral treatment and identifying treatment failure. We assessed the durability of viral suppression after viral load-triggered adherence counseling among patients with HIV viremia 6 months after ART initiation.DesignObservational cohort enrolled in an antiretroviral treatment program in rural Uganda.MethodsParticipants who underwent routine viral load determination every 24 weeks and had at least 48 weeks of follow-up were included in this analysis. Patients with viral loads >400 copies/ml at 24 weeks of treatment were given additional adherence counseling, and all patients were followed to assess the duration of viral suppression and development of virologic failure.Results1,841 participants initiating antiretroviral therapy were enrolled in the Rakai Health Sciences Program between June 2005 and June 2011 and were followed with viral load monitoring every 24 weeks. 148 (8%) of patients did not achieve viral suppression at 24 weeks and were given additional adherence counseling. 85 (60%) of these patients had undetectable viral loads at 48 weeks, with a median duration of viral suppression of 240 weeks (IQR 193-288 weeks). Failure to achieve an undetectable viral load at 48 weeks was associated with age <30 years and 24 week viral load >2,000 copies/ml in multivariate logistic regression analysis.ConclusionsThe majority of patients with persistent viremia who were provided adherence counseling achieved robust viral suppression for a median 4.6 years. Access to virologic monitoring and adherence counseling is a priority in resource-limited settings.     

Modelling HIV immune response and validation with clinical data

A system of ordinary differential equations is formulated to describe the pathogenesis of HIV infection, wherein certain features that have been shown to be important by recent experimental research are incorporated in the model. These include the role of CD4+memory cells that serve as a major reservoir of latently infected cells, a critical role for T-helper cells in the generation of CD8 memory cells capable of efficient recall response, and stimulation by antigens other than HIV. A stability analysis illustrates the capability of this model in admitting multiple locally asymptotically stable (locally a.s.) off-treatment equilibria. We show that this more biologically detailed model can exhibit the phenomenon of transient viremia experienced by some patients on therapy with viral load levels suppressed below the detection limit. We also show that the loss of CD4+T-cell help in the generation of CD8+memory cells leads to larger peak values for the viral load during transient viremia. Censored clinical data is used to obtain parameter estimates. We demonstrate that using a reduced set of 16 free parameters, obtained by fixing some parameters at their population averages, the model provides reasonable fits to the patient data and, moreover, that it exhibits good predictive capability. We further show that parameter values obtained for most clinical patients do not admit multiple locally a.s off-treatment equilibria. This suggests that treatment to move from a high viral load equilibrium state to an equilibrium state with a lower (or zero) viral load is not possible for these patients.     

Treatment Monitoring of HIV‐Infected Patients based on Mechanistic Models

Summary For most patients, the HIV viral load can be made undetectable by highly active antiretroviral treatments highly active antiretroviral therapy: the virus, however, cannot be eradicated. Thus, the major problem is to try to reduce the side effects of the treatment that patients have to take during their life time. We tackle the problem of monitoring the treatment dose, with the aim of giving the minimum dose that yields an undetectable viral load. The approach is based on mechanistic models of the interaction between virus and the immune system. It is shown that the “activated cells model,” allows making good predictions of the effect of dose changes and, thus, could be a good basis for treatment monitoring. Then, we use the fact that in dynamical models, there is a nontrivial equilibrium point, that is with a virus load larger than zero, only if the reproductive number R₀ is larger than one. For reducing side effects, we may give a dose just above the critical dose corresponding to R₀ equal to 1. A prior distribution of the parameters of the model can be taken as the posterior arising from the analysis of previous clinical trials. Then the observations for a given patient can be used to dynamically tune the dose so that there is a high probability that the reproductive number is below one. The advantage of the approach is that it does not depend on a cost function, weighing side effects and efficiency of the drug. It is shown that it is possible to approach the critical dose if the model is correct. A sensitivity analysis assesses the robustness of the approach.     

Beneficial effect of GB virus C co-infection in Human Immunodeficiency Virus type 1-infected individuals

Several reports have documented a better prognosis for HIV‐1‐infected patients co‐infected with GBV‐C, while other reports have contradicted such findings with the result that this issue remains controversial. We attempted to clarify the complicated status of the effect of GBV‐C co‐infection on HIV‐1‐infected patients. GBV‐C RNA was detected in 37 samples in 182 HIV‐1‐infected patients (20.3%) using RT/nested PCR. Of these, 3 were determined to be GBV‐C genotype 1, 12 were genotype 2, and the remaining 22 were genotype 3. The GBV‐C viral load quantified by real‐time PCR ranged from 7.8 × 10³ to 3.3 × 10⁶ copies/ml. Weakly negative correlation was observed between GBV‐C viral load and HIV‐1 viral load in 19 HAART‐naïve patients, indicating that a higher GBV‐C viral load is associated with a greater suppression of HIV‐1 replication. A previously published in vitro study suggested that GBV‐C infection would induce up‐regulation of RANTES, leading to suppression of HIV‐1 replication. However, in our present study, the blood RANTES level was significantly lower in the GBV‐C co‐infected group than in the uninfected group (190–9,959 vs. 264–31,038 pg/ml, P=0.004). Our results suggested that a suppression of HIV‐1 replication by GBV‐C co‐infection is not mediated by up‐regulated RANTES, and thus call for another as yet unknown factor.     

Modeling the short-, middle- and long-term viral load responses for comparing estimated dynamic parameters

A virologic marker, the number of HIV RNA copies or viral load, is currently used to evaluate antiviral therapies in AIDS clinical trials. This marker can be used to assess the antiviral potency of therapies, but is easily affected by drug exposures, drug resistance and other factors during the long-term treatment evaluation process. The study of HIV dynamics is one of the most important development in recent AIDS research for understanding the pathogenesis of HIV-1 infection and antiviral treatment strategies. Although many HIV dynamic models have been proposed by AIDS researchers in the last decade, they have only been used to quantify short-term viral dynamics and do not correctly describe long-term virologic responses to antiretroviral treatment. In other words, these simple viral dynamic models can only be used to fit short-term viral load data for estimating dynamic parameters. In this paper, a mechanism-based differential equation models is introduced for characterizing the long-term viral dynamics with antiretroviral therapy. We applied this model to fit different segments of the viral load trajectory data from a simulation experiment and an AIDS clinical trial study, and found that the estimates of dynamic parameters from our modeling approach are very consistent. We may conclude that our model can not only characterize long-term viral dynamics, but can also quantify short- and middle-term viral dynamics. It suggests that if there are enough data in the early stage of the treatment, the results from our modeling based on short-term information can be used to capture the performance of long-term care with HIV-1 infected patients.     

Clinical Evaluation of an Affordable Qualitative Viral Failure Assay for HIV Using Dried Blood Spots in Uganda

Background

WHO recommends regular viral load (VL) monitoring of patients on antiretroviral therapy (ART) for timely detection of virological failure, prevention of acquired HIV drug resistance (HIVDR) and avoiding unnecessary switching to second-line ART. However, the cost and complexity of routine VL testing remains prohibitive in most resource limited settings (RLS). We evaluated a simple, low–cost, qualitative viral–failure assay (VFA) on dried blood spots (DBS) in three clinical settings in Uganda.

Methods

We conducted a cross–sectional diagnostic accuracy study in three HIV/AIDS treatment centres at the Joint Clinical Research Centre in Uganda. The VFA employs semi-quantitative detection of HIV–1 RNA amplified from the LTR gene. We used paired dry blood spot (DBS) and plasma with the COBASAmpliPrep/COBASTaqMan, Roche version 2 (VL_ref) as the reference assay. We used the VFA at two thresholds of viral load, (>5,000 or >1,000 copies/ml).

Results

496 paired VFA and VL_ref results were available for comparative analysis. Overall, VFA demonstrated 78.4% sensitivity, (95% CI: 69.7%–87.1%), 93% specificity (95% CI: 89.7%–96.4%), 89.3% accuracy (95% CI: 85%–92%) and an agreement kappa = 0.72 as compared to the VL_ref. The predictive values of positivity and negativity among patients on ART for >12 months were 72.7% and 99.3%, respectively.

Conclusions

VFA allowed 89% of correct classification of VF. Only 11% of the patients were misclassified with the potential of unnecessary or late switch to second–line ART. Our findings present an opportunity to roll out simple and affordable VL monitoring for HIV–1 treatment in RLS.     

A stochastic model of latently infected cell reactivation and viral blip generation in treated HIV patients

Motivated by viral persistence in HIV+ patients on long-term anti-retroviral treatment (ART), we present a stochastic model of HIV viral dynamics in the blood stream. We consider the hypothesis that the residual viremia in patients on ART can be explained principally by the activation of cells latently infected by HIV before the initiation of ART and that viral blips (clinically-observed short periods of detectable viral load) represent large deviations from the mean. We model the system as a continuous-time, multi-type branching process. Deriving equations for the probability generating function we use a novel numerical approach to extract the probability distributions for latent reservoir sizes and viral loads. We find that latent reservoir extinction-time distributions underscore the importance of considering reservoir dynamics beyond simply the half-life. We calculate blip amplitudes and frequencies by computing complete viral load probability distributions, and study the duration of viral blips via direct numerical simulation. We find that our model qualitatively reproduces short small-amplitude blips detected in clinical studies of treated HIV infection. Stochastic models of this type provide insight into treatment-outcome variability that cannot be found from deterministic models.     

Reliability at the Lower Limits of HIV-1 RNA Quantification in Clinical Samples: A Comparison of RT-PCR versus bDNA Assays

Introduction

To explore whether an assay change was responsible for an increasing proportion of patients with undetectable HIV viral loads at our urban HIV clinic, we selected highly stable patients, examining their viral loads before and after changing assays. We compared the proportion with detectable viremia during RT-PCR vs. bDNA periods.

Methodology/Principal Findings

We selected patients with ≥1 viral loads assessed during both RT-PCR and bDNA periods. We included patients with stable CD4 counts, excluding patients with viral loads ≥1,000 copies/ml or any significant changes in therapy. Out of 4500 clinic patients, 419 patients (1588 viral loads) were included. 39% of viral loads were reported as detectable by RT-PCR vs. 5% reported as detectable by bDNA. The mean coefficient of variation was higher before vs. after assay change. We found an odds'' ratio of 16.7 for having a viral load >75 copies/ml during the RT-PCR vs. bDNA periods.

Discussion

These data support previous reports, suggesting that bDNA may more reliably discriminate between viral suppression and low level viremia in stable patients on therapy. Low-level viremia, noted more with RT-PCR, may promote unneeded testing, while differences in viral load reliability may impact antiretroviral trial and quality assurance endpoints. Commonly used plasma separator tubes may differentially affect RT-PCR and bDNA results.     

A cheap and open HIV viral load technique applicable in routine analysis in a resource limited setting with a wide HIV genetic diversity

Background

HIV infection in Cameroon is characterized by a great viral diversity with all HIV-1 groups (M, N, O, and P) and HIV-2 in circulation. HIV group determination is very important if tailored viral load analysis and treatments are to be applied. In our laboratory, HIV viral load is carried out using two platforms; Biocentric and Abbott depending on the HIV group identified. Biocentric which quantifies HIV-1 group M is a cheap and open system useful in resource limited settings. The objective of this study was to compare the viral load analyses of serologically group-indeterminate HIV samples using the two platforms with the view of reducing cost.

Methods

Consecutive samples received between March and May 2014, and between August and September 2014 in our laboratory for HIV viral load analysis were included. All these samples were analyzed for their HIV groups using an in-house ELISA serotyping test. All HIV-1 group M samples were quantified using the Biocentric test while all other known atypical samples (HIV-1 groups N, O and P) were analyzed using the Abbott technique. HIV group-indeterminate samples (by serotyping) were quantified with both techniques.

Results

Among the 6355 plasma samples received, HIV-1 group M was identified in 6026 (94.82%) cases; HIV-1 group O, in 20 (0.31%); HIV-1 group M?+?O, in 3 (0.05%) and HIV-2, in 3 (0.05%) case. HIV-group indeterminate samples represented about 4.76% (303/6355) and only 231 of them were available for analysis by Abbott Real-Time HIV-1 and Generic HIV Viral Load techniques. Results showed that 188 (81.39%) samples had undetectable viral load in both techniques. All the detectable samples showed high viral load, with a mean of 4.5 log copies/ml (range 2.1–6.5) for Abbott Real-Time and 4.5 log copies/ml (range 2–6.4) for Generic HIV Viral Load. The mean viral load difference between the two techniques was 0.03 log₁₀ copies/ml and a good correlation was obtained (r ² ?=?0.89; P?<?0.001).

Conclusion

Our results suggest that cheaper and open techniques such as Biocentric could be useful alternatives for HIV viral load follow-up quantification in resource limited settings like Cameroon; even with its high viral diversity.

     

Sensitivity analyses comparing outcomes only existing in a subset selected post-randomization, conditional on covariates, with application to HIV vaccine trials

In many experiments, researchers would like to compare between treatments and outcome that only exists in a subset of participants selected after randomization. For example, in preventive HIV vaccine efficacy trials it is of interest to determine whether randomization to vaccine causes lower HIV viral load, a quantity that only exists in participants who acquire HIV. To make a causal comparison and account for potential selection bias we propose a sensitivity analysis following the principal stratification framework set forth by Frangakis and Rubin (2002, Biometrics58, 21-29). Our goal is to assess the average causal effect of treatment assignment on viral load at a given baseline covariate level in the always infected principal stratum (those who would have been infected whether they had been assigned to vaccine or placebo). We assume stable unit treatment values (SUTVA), randomization, and that subjects randomized to the vaccine arm who became infected would also have become infected if randomized to the placebo arm (monotonicity). It is not known which of those subjects infected in the placebo arm are in the always infected principal stratum, but this can be modeled conditional on covariates, the observed viral load, and a specified sensitivity parameter. Under parametric regression models for viral load, we obtain maximum likelihood estimates of the average causal effect conditional on covariates and the sensitivity parameter. We apply our methods to the world's first phase III HIV vaccine trial.     

Comprehensive analysis of frequency and phenotype of T regulatory cells in HIV infection: CD39 expression of FoxP3+ T regulatory cells correlates with progressive disease

There are conflicting data about the frequency and role of regulatory T cells (Tregs) during the course of HIV infection. Peripheral blood of a large cohort of HIV-infected patients (n = 131) at different stages of disease, including 15 long-term nonprogressors and 21 elite controllers, was analyzed to determine the frequency and phenotype of Tregs, defined as CD4(+), CD25(high), CD127(low), FoxP3(high) cells. A significantly increased relative frequency of Tregs within the CD4(+) compartment of HIV(+) patients compared to that of healthy controls (P < 0.0001) was observed. Additionally, the relative frequency of Tregs directly correlated with HIV viral load and inversely with CD4(+) counts. However, the absolute Treg number was reduced in HIV-infected patients versus healthy controls (P < 0.0001), with the exception of elite controllers (P > 0.05). The loss of absolute Treg numbers coincided with rising markers of immune activation (P < 0.0006). The initiation of antiviral therapy significantly increased absolute Treg numbers (P < 0.0031). We find that the expression of CD39, a newly defined ectonucleotidase with immunomodulatory functions on Tregs, correlated with progressive HIV disease, HIV viral load, and immune activation. Of note, when tested in peripheral blood mononuclear cells of healthy volunteers, the in vitro capacity to suppress T-cell proliferation was limited to CD4(+), CD25(high), CD39(+) T cells. Interestingly, Tregs of elite controllers exhibited not only the highest expression of CCR5, CTLA-4, and ICOS but also the lowest level of CD39. The data presented here reconcile the seemingly contradictory results of previous studies looking at Tregs in HIV and highlight the complexity of Treg-mediated immunoregulation during human viral infections.     

Natural variation in HIV infection: Monte Carlo estimates that include CD8 effector cells

Viral load and CD4 T-cell counts in patients infected with the human immunodeficiency virus (HIV) are commonly used to guide clinical decisions regarding drug therapy or to assess therapeutic outcomes in clinical trials. However, random fluctuations in these markers of infection can obscure clinically significant change. We employ a Monte Carlo simulation to investigate contributing factors in the expected variability in CD4 T-cell count and viral load due solely to the stochastic nature of HIV infection. The simulation includes processes that contribute to the variability in HIV infection including CD4 and CD8 T-cell population dynamics as well as T-cell activation and proliferation. The simulation results may reconcile the wide range of variabilities in viral load observed in clinical studies, by quantifying correlations between viral load measurements taken days or weeks apart. The sensitivity of variability in T-cell count and viral load to changes in the lifetimes of CD4 and CD8 T-cells is investigated, as well as the effects of drug therapy.     

HIV 10 years later-where do we stand now?

A wide variety of up-to-date results and knowledge were presented at the 10th International AIDS Meeting, Yokohama. Epidemiologically, most interest was focused on the discovery of a new HIV subtype O, which cannot be reliably detected by currently available ELISA kits. Clinically, it is gradually appreciated that one single most important parameter is the viral load; the extent of viral load can help explain many clinical observations. Another eye-catching finding was the report of a clinical follow-up of a group of long-term nonprogressors. If the underlying operative mechanism can be elucidated, we can learn the necessary elements for halting HIV infection progression. Therapeutically, the trend has shifted to combination therapy, preferentially 3-drug combination of 2 RT inhibitors and 1 protease inhibitor. For the vaccine development, many novel vectors were introduced, but their potentials are unknown at present. The successful application of single-cell in situ PCR has changed our perception of HIV infection. This powerful technique can detect a single viral genome inside cells and revealed that a large proportion of cells already harbor HIV genomes soon after the entry of HIV into the body. A direct viral effect may fully explain subsequent T cell depletion without invoking a lot of indirect mechanisms such as apoptosis.     

After 18 months of antiretroviral therapy,total HIV DNA decreases more pronouncedly in patients infected by CRF01_AE than in those infected by subtype B and CRF07_BC

Whether the amount of HIV DNA is associated with the subtype of HIV‐1 after antiretroviral therapy (ART) has not been reported. In the present study, the amount of HIV DNA and RNA and CD4+T counts in blood and semen prior to and after 18 months of ART were compared in 48 patients infected by CRF01_AE, subtype B or CRF07_BC of HIV‐1. Viral RNA was suppressed and CD4 cell count recovery achieved in all patients. The level of HIV DNA were similar before ART; however, patients with CRF01_AE had less HIV DNA after ART than those with subtype B and CRF07_BC infection. According to prediction of co‐receptor usage by Geno2Pheno and PSSM in combination, more than 35.6% of clones for CRF01_AE were predicted as CXCR4‐using before ART, whereas less than 6% of those for subtype B and CRF07_BC were predicted as CXCR4‐using. After 18 months of ART, no CXCR4‐using clones were predicted in any of the subtypes. Despite more HIV RNA and fewer CD4 + T cells in patients with CRF01_AE before therapy, no significant differences (P > 0.05) in viral RNA or CD4 cell counts were observed between the subtypes after 18 months of ART. Thus, 18 months of antiretroviral therapy was more efficient in patients with CRF01_AE. Considering that successful ART dramatically reduces the viral load in both blood and semen, risks of sexual transmission of HIV were reduced, contributing to prevention of rapid spread of HIV among men who have sex with men in the region.

     

检测HIV-1载量的荧光实时定量PCR技术的建立及其应用

准确测定HIV 1的前病毒载量和病毒载量的技术 ,在感染者预后和艾滋病患者药物治疗效果的评价以及艾滋病的其它研究方面 ,都具有十分重要的应用价值。以定量的HIV 1DNA和RNA为标准外参照 ,利用SYBRGreen荧光染料和GeneAmp5 70 0SequenceDetectionSystem (5 70 0系统 ) ,建立了测定HIV 1的前病毒载量和病毒载量的荧光实时定量PCR技术。以病毒感染细胞和培养上清为材料 ,测定了三种化合物 (AZT ,GL和WT)对细胞内的前病毒载量和培养上清中的病毒载量的抑制活性 ,并与合胞体形成抑制方法测定化合物抗病毒活性的结果进行了比较。根据病毒载量、前病毒载量和合胞体形成计算出的三种化合物的治疗指数均依次变小 ,提出以荧光实时定量PCR技术测定前病毒载量 ,会在评价药物在体内外根除或减少存在于CD4休止或记忆T淋巴细胞中的HIV 1前病毒方面有特别的价值。