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Record W4205523133 · doi:10.1172/jci136227

The multifaceted nature of HIV latency

2020· review· en· W4205523133 on OpenAlexafffund
Caroline Dufour, Pierre Gantner, Rémi Fromentin, Nicolas Chomont

Bibliographic record

VenueJournal of Clinical Investigation · 2020
Typereview
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsCentre Hospitalier de l’Université de Montréal
FundersFonds de Recherche du Québec - SantéNational Institute of Allergy and Infectious DiseasesCanadian Institutes of Health ResearchStyrelsen för Internationellt Utvecklingssamarbete
KeywordsVirus latencyVirologyBiologyViral replicationHuman immunodeficiency virus (HIV)Latency (audio)Latent VirusVirusGenomeAntiretroviral therapyImmunologyViral loadGeneticsGeneComputer science

Abstract

fetched live from OpenAlex

Although antiretroviral therapies (ARTs) potently inhibit HIV replication, they do not eradicate the virus. HIV persists in cellular and anatomical reservoirs that show minimal decay during ART. A large number of studies conducted during the past 20 years have shown that HIV persists in a small pool of cells harboring integrated and replication-competent viral genomes. The majority of these cells do not produce viral particles and constitute what is referred to as the latent reservoir of HIV infection. Therefore, although HIV is not considered as a typical latent virus, it can establish a state of nonproductive infection under rare circumstances, particularly in memory CD4+ T cells, which represent the main barrier to HIV eradication. While it was originally thought that the pool of latently infected cells was largely composed of cells harboring transcriptionally silent genomes, recent evidence indicates that several blocks contribute to the nonproductive state of these cells. Here, we describe the virological and immunological factors that play a role in the establishment and persistence of the pool of latently infected cells and review the current approaches aimed at eliminating the latent HIV reservoir.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.981
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.122
GPT teacher head0.442
Teacher spread0.319 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations95
Published2020
Admission routes2
Has abstractyes

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