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Record W2979782115 · doi:10.1128/jvi.01174-19

Infrequent HIV Infection of Circulating Monocytes during Antiretroviral Therapy

2019· article· en· W2979782115 on OpenAlexafffund
Marta Massanella, Wendy Bakeman, Pasiri Sithinamsuwan, James L. K. Fletcher, Nitiya Chomchey, Somporn Tipsuk, Thep Chalermchai, Jean‐Pierre Routy, Jintanat Ananworanich, Victor Valcour, Nicolas Chomont

Bibliographic record

VenueJournal of Virology · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsMcGill University Health CentreUniversité de MontréalCentre Hospitalier de l’Université de Montréal
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchGovernment of CanadaCanadian HIV Trials Network, Canadian Institutes of Health ResearchNational Institute of Neurological Disorders and StrokeamfAR, The Foundation for AIDS Research
KeywordsCD14MonocyteFlow cytometryBiologyImmunologyCell sortingPopulationLentivirusT cellVirologyHuman immunodeficiency virus (HIV)Viral diseaseImmune systemMedicine

Abstract

fetched live from OpenAlex

The role of circulating monocytes as persistent HIV reservoirs during ART is still controversial. Several studies have reported persistent infection of monocytes in virally suppressed individuals; however, others failed to detect HIV in this subset. These discrepancies are likely explained by the diversity of the methods used to isolate monocytes and to detect HIV infection. In this study, we show that only flow cytometry cell sorting yields a highly pure population of monocytes largely devoid of CD4 contaminants. Using this approach in a longitudinal cohort of HIV-infected individuals before and during ART, we demonstrate that HIV is rarely found in monocytes from untreated and treated HIV-infected individuals. This study highlights the importance of using methods that yield highly pure populations of cells as flow cytometry cell sorting to minimize and control for CD4 + T-cell contamination.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.262
Teacher spread0.248 · 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

Citations36
Published2019
Admission routes2
Has abstractyes

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