ReviewJournal of translational medicine2016
Using animal models to overcome temporal, spatial and combinatorial challenges in HIV persistence research.
Review in Journal of translational medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
12 citing papers in PubMed.
- CD169 (Siglec-1) as a Robust Human Cell Biomarker of Toll-Like Receptor 9 Agonist Immunotherapy.Frontiers in cellular and infection microbiology · 2022Article
- μ-Lat: A mouse model to evaluate human immunodeficiency virus eradication strategies.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2020Article
- Article
- HIV-2 as a model to identify a functional HIV cure.AIDS research and therapy · 2019Review
- Recent Updates on Mouse Models for Human Immunodeficiency, Influenza, and Dengue Viral Infections.Viruses · 2019Review
- Immune Activations and Viral Tissue Compartmentalization During Progressive HIV-1 Infection of Humanized Mice.Frontiers in immunology · 2019Article
- Impacts of HIV Cure Interventions on Viral Reservoirs in Tissues.Frontiers in microbiology · 2019Review
- Advanced model systems and tools for basic and translational human immunology.Genome medicine · 2018Review
- Human Immune System Mice for the Study of Human Immunodeficiency Virus-Type 1 Infection of the Central Nervous System.Frontiers in immunology · 2018Review
- HIV Persistence in Gut-Associated Lymphoid Tissues: Pharmacological Challenges and Opportunities.AIDS research and human retroviruses · 2017Review
- Humanized Mouse Models of Clinical Disease.Annual review of pathology · 2017Review
- Are T cells the only HIV-1 reservoir?Retrovirology · 2016Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Research challenges associated with understanding HIV persistence during antiretroviral therapy can be categorized as temporal, spatial and combinatorial. Temporal research challenges relate to the timing of events during establishment and maintenance of HIV persistence. Spatial research challenges regard the anatomical locations and cell subsets that harbor persistent HIV. Combinatorial research challenges pertain to the order of administration, timing of administration and specific combinations of compounds to be administered during HIV eradication therapy. Overcoming these challenges will improve our understanding of HIV persistence and move the field closer to achieving eradication of persistent HIV. Given that humanized mice and non-human primate HIV models permit rigorous control of experimental conditions, these models have been used extensively as in vivo research platforms for directly addressing these research challenges. The aim of this manuscript is to provide a comprehensive review of these recent translational advances made in animal models of HIV persistence.
Indexed as
Identifiers
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.