ReviewViruses2023
Mathematical Models of HIV-1 Dynamics, Transcription, and Latency.
Review in Viruses, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 14 citations in OpenAlex.
- Is the molecular microenvironment of the latent HIV reservoir predictable using deep learning approaches?Journal of virology · 2026Review
- Forecasting monthly AIDS incidence in China via LSTM-CNN parallel fusion: a comparative study of 10 predictive models.Frontiers in public health · 2026Article
- A mathematical framework of HIV and TB co-infection dynamics.Scientific reports · 2025Article
- Study on the prediction performance of AIDS monthly incidence in Xinjiang based on time series and deep learning models.BMC public health · 2025Article
- The HIV-1 Transcriptional Program: From Initiation to Elongation Control.Journal of molecular biology · 2025Review
- Distinguishable topology of the task-evoked functional genome networks in HIV-1 reservoirs.iScience · 2024Article
- QuickFit: A High-Throughput RT-qPCR-Based Assay to Quantify Viral Growth and Fitness In Vitro.Viruses · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
HIV-1 latency is a major barrier to curing infections with antiretroviral therapy and, consequently, to eliminating the disease globally. The establishment, maintenance, and potential clearance of latent infection are complex dynamic processes and can be best described with the help of mathematical models followed by experimental validation. Here, we review the use of viral dynamics models for HIV-1, with a focus on applications to the latent reservoir. Such models have been used to explain the multi-phasic decay of viral load during antiretroviral therapy, the early seeding of the latent reservoir during acute infection and the limited inflow during treatment, the dynamics of viral blips, and the phenomenon of post-treatment control. Finally, we discuss that mathematical models have been used to predict the efficacy of potential HIV-1 cure strategies, such as latency-reversing agents, early treatment initiation, or gene therapies, and to provide guidance for designing trials of these novel interventions.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.