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Record W2797584216 · doi:10.1128/jvi.02225-17

The Pathway To Establishing HIV Latency Is Critical to How Latency Is Maintained and Reversed

2018· article· en· W2797584216 on OpenAlexfundno aff
Simin D. Rezaei, Hao Lu, Judy Chang, Ajantha Rhodes, Sharon R. Lewin, Paul Cameron

Bibliographic record

VenueJournal of Virology · 2018
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsnot available
FundersInstitute of Infection and ImmunityNational Institute of Allergy and Infectious DiseasesNational Health and Medical Research Council
KeywordsBiologyVirus latencyLatency (audio)VirologyCytotoxic T cellCell biologyGreen fluorescent proteinVirusImmunologyViral replicationIn vitro

Abstract

fetched live from OpenAlex

ABSTRACT HIV infection requires lifelong antiretroviral therapy because of the persistence of latently infected CD4 + T cells. The induction of virus expression from latently infected cells occurs following T cell receptor (TCR) activation, but not all latently infected cells respond to TCR stimulation. We compared two models of latently infected cells using an enhanced green fluorescent protein (EGFP) reporter virus to infect CCL19-treated resting CD4 + (rCD4 + ) T cells (preactivation latency) or activated CD4 + T cells that returned to a resting state (postactivation latency). We isolated latently infected cells by sorting for EGFP-negative (EGFP − ) cells after infection. These cells were cultured with antivirals and stimulated with anti-CD3/anti-CD28, mitogens, and latency-reversing agents (LRAs) and cocultured with monocytes and anti-CD3. Spontaneous EGFP expression was more frequent in postactivation than in preactivation latency. Stimulation of latently infected cells with monocytes/anti-CD3 resulted in an increase in EGFP expression compared to that for unstimulated controls using the preactivation latency model but led to a reduction in EGFP expression in the postactivation latency model. The reduced EGFP expression was not associated with reductions in the levels of viral DNA or T cell proliferation but depended on direct contact between monocytes and T cells. Monocytes added to the postactivation latency model during the establishment of latency reduced spontaneous virus expression, suggesting that monocyte-T cell interactions at an early time point postinfection can maintain HIV latency. This direct comparison of pre- and postactivation latency suggests that effective strategies needed to reverse latency will depend on how latency is established. IMPORTANCE One strategy being evaluated to eliminate latently infected cells that persist in HIV-infected individuals on antiretroviral therapy (ART) is to activate HIV expression or production with the goal of inducing virus-mediated cytolysis or immune-mediated clearance of infected cells. The gold standard for the activation of latent virus is T cell receptor stimulation with anti-CD3/anti-CD28. However, this stimulus activates only a small proportion of latently infected cells. We show clear differences in the responses of latently infected cells to activating stimuli based on how latent infection is established, an observation that may potentially explain the persistence of noninduced intact proviruses in HIV-infected individuals on ART.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.014
GPT teacher head0.281
Teacher spread0.267 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations32
Published2018
Admission routes1
Has abstractyes

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