Pathogenesis and treatment of HIV infection: the cellular, the immune system and the neuroendocrine systems perspective

Comprehensive insights into herbal P-glycoprotein inhibitors and nanoformulations for improving anti-retroviral therapy efficacy

The worldwide HIV cases were 39.0 million (33.1-45.7 million) in 2022. Due to genetic variations, HIV-1 is more easily transmitted than HIV-2 and favours CD4 + T cells and macrophages, producing AIDS. Conventional HIV drug therapy has many drawbacks, including adherence issues leading to resistance, side effects that lower life quality, drug interactions, high costs limiting global access, inability to eliminate viral reservoirs, chronicity requiring lifelong treatment, emerging toxicities, and a focus on managing infections. Conventional dosage forms have bioavailability issues due to intestinal P-glycoprotein (P-gp) efflux, which can reduce anti-retroviral drug efficacy and lead to resistance. Use of phyto-constituents with P-gp regulating actions has great benefits for semi-synthetic modification to create formulations with greater bioavailability and reduced toxicity, which improves drug effectiveness. Lipid-based nanocarriers, solid lipid nanoparticles, nanostructured lipid carriers, polymer-based nanocarriers, and inorganic nanoparticles may inhibit P-gp efflux. Employing potent P-gp inhibitors within nanocarriers as a Trojan horse approach can enhance the intracellular accumulation of anti-retroviral drugs (ARDs), which are substrates for efflux transporters. This technique increases oral bioavailability and offers lower-dose options, boosting HIV patient compliance and lowering costs. Molecular docking of the inhibitor with P-gp may anticipate optimum binding and function, allowing drug efflux to be minimised.

Biologically grounded scientific methods: The challenges ahead for combating epidemics

The protracted COVID 19 pandemic may indicate failures of scientific methodologies. Hoping to facilitate the evaluation and/or update of methods relevant in Biomedicine, several aspects of scientific processes are here explored. First, the background is reviewed. In particular, eight topics are analyzed: (i) the history of Higher Education models in reference to the pursuit of science and the type of student cognition pursued, (ii) whether explanatory or actionable knowledge is emphasized depending on the well- or ill-defined nature of problems, (iii) the role of complexity and dynamics, (iv) how differences between Biology and other fields influence methodologies, (v) whether theory, hypotheses or data drive scientific research, (vi) whether Biology is reducible to one or a few factors, (vii) the fact that data, to become actionable knowledge, require structuring, and (viii) the need of inter-/trans-disciplinary knowledge integration. To illustrate how these topics interact, a second section describes four temporal stages of scientific methods: conceptualization, operationalization, validation and evaluation. They refer to the transition from abstract (non-measurable) concepts (such as 'health') to the selection of concrete (measurable) operations (such as 'quantification of ́anti-virus specific antibody titers'). Conceptualization is the process that selects concepts worth investigating, which continues as operationalization when data-producing variables viewed to reflect critical features of the concepts are chosen. Because the operations selected are not necessarily valid, informative, and may fail to solve problems, validations and evaluations are critical stages, which require inter/trans-disciplinary knowledge integration. It is suggested that data structuring can substantially improve scientific methodologies applicable in Biology, provided that other aspects here mentioned are also considered. The creation of independent bodies meant to evaluate biologically oriented scientific methods is recommended.

Markov Chain-Based Stochastic Modelling of HIV-1 Life Cycle in a CD4 T Cell

Replication of Human Immunodeficiency Virus type 1 (HIV) in infected CD4+ T cells represents a key driver of HIV infection. The HIV life cycle is characterised by the heterogeneity of infected cells with respect to multiplicity of infection and the variability in viral progeny. This heterogeneity can result from the phenotypic diversity of infected cells as well as from random effects and fluctuations in the kinetics of biochemical reactions underlying the virus replication cycle. To quantify the contribution of stochastic effects to the variability of HIV life cycle kinetics, we propose a high-resolution mathematical model formulated as a Markov chain jump process. The model is applied to generate the statistical characteristics of the (i) cell infection multiplicity, (ii) cooperative nature of viral replication, and (iii) variability in virus secretion by phenotypically identical cells. We show that the infection with a fixed number of viruses per CD4+ T cell leads to some heterogeneity of infected cells with respect to the number of integrated proviral genomes. The bottleneck factors in the virus production are identified, including the Gag-Pol proteins. Sensitivity analysis enables ranking of the model parameters with respect to the strength of their impact on the size of viral progeny. The first three globally influential parameters are the transport of genomic mRNA to membrane, the tolerance of transcription activation to Tat-mediated regulation, and the degradation of free and mature virions. These can be considered as potential therapeutical targets.

Modeling of the HIV-1 Life Cycle in Productively Infected Cells to Predict Novel Therapeutic Targets

There are many studies that model the within-host population dynamics of Human Immunodeficiency Virus Type 1 (HIV-1) infection. However, the within-infected-cell replication of HIV-1 remains to be not comprehensively addressed. There exist rather few quantitative models describing the regulation of the HIV-1 life cycle at the intracellular level. In treatment of HIV-1 infection, there remain issues related to side-effects and drug-resistance that require further search "...for new and better drugs, ideally targeting multiple independent steps in the HIV-1 replication cycle" (as highlighted recently by Teldury et al., The Future of HIV-1 Therapeutics, 2015). High-resolution mathematical models of HIV-1 growth in infected cells provide an additional analytical tool in identifying novel drug targets. We formulate a high-dimensional model describing the biochemical reactions underlying the replication of HIV-1 in target cells. The model considers a nonlinear regulation of the transcription of HIV-1 mediated by Tat and the Rev-dependent transport of fully spliced and singly spliced transcripts from the nucleus to the cytoplasm. The model is calibrated using available information on the kinetics of various stages of HIV-1 replication. The sensitivity analysis of the model is performed to rank the biochemical processes of HIV-1 replication with respect to their impact on the net production of virions by one actively infected cell. The ranking of the sensitivity factors provides a quantitative basis for identifying novel targets for antiviral therapy. Our analysis suggests that HIV-1 assembly depending on Gag and Tat-Rev regulation of transcription and mRNA distribution present two most critical stages in HIV-1 replication that can be targeted to effectively control virus production. These processes are not covered by current antiretroviral treatments.

Cancer immunotherapy of patients with HIV infection

Cancer immunotherapy with antibodies against immune checkpoints has made impressive advances in the last several years. The most relevant drugs target programmed cell death 1 (PD-1) expressed on T cells or its ligand, the programmed cell death ligand 1 (PD-L1), expressed on cancer cells, and cytotoxic T lymphocyte-associated protein 4 (CTLA-4). Unfortunately, cancer patients with HIV infection are usually excluded from cancer clinical trials, because there are concerns about the safety and the anti-tumoral activity of these novel therapies in patients with HIV infection. Several retrospective studies and some case reports now support the notion that antibodies against immune checkpoints are safe and active in cancer patients with HIV infection, but prospective data in these patients are lacking. In addition, signs of antiviral activity with increase in CD4 T cell counts, plasma viremia reduction or decrease in the viral reservoir have been reported in some of the patients treated, although no patient achieved a complete clearance of the viral reservoir. Here we briefly summarize all clinical cases reported in the literature, as well as ongoing clinical trials testing novel immunotherapy drugs in cancer patients with HIV infection.