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Record W3026337320 · doi:10.1128/jvi.00415-20

HIV RNA Rebound in Seminal Plasma after Antiretroviral Treatment Interruption

2020· article· en· W3026337320 on OpenAlexaff
Sara Gianella, Antoine Chaillon, Tae‐Wook Chun, Michael C. Sneller, Caroline Ignacio, Milenka Vargas-Meneses, Gemma Caballero, Ronald J. Ellis, Colin Kovacs, Erika Benko, Sanja Huibner, Rupert Kaul

Bibliographic record

VenueJournal of Virology · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsMaple Leaf Medical ClinicUniversity of Toronto
FundersCommon FundNational Center for Advancing Translational SciencesEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute on Drug AbuseNational Institute of Mental HealthNational Institutes of HealthNational Institute of Allergy and Infectious DiseasesU.S. Department of Veterans Affairs
KeywordsBiologySemenViral loadVirologyPopulationRNAViral evolutionLentivirusImmunologyHuman immunodeficiency virus (HIV)Internal medicinePhysiologyViral diseaseGeneticsMedicine

Abstract

fetched live from OpenAlex

To cure HIV, we likely need to target the reservoirs in all anatomic compartments. Here, we used sophisticated statistical and phylogenetic methods to analyze blood and semen samples collected from 12 persons with HIV who began antiretroviral therapy (ART) during very early HIV infection and who interrupted their ART as part of a clinical trial. First, we found that HIV RNA rebound in semen occurred significantly later and reached lower levels than in blood. Second, we found that the virus in semen was genetically different in some participants compared to that in blood. Finally, we found increased HIV RNA molecular diversity in semen compared to that in blood in almost all study participants. These data suggest that the HIV RNA populations emerging from the genital compartment after ART interruption might not be the same as those emerging from blood plasma. Future research should evaluate whether the genital compartment might contribute to viral rebound in some people with HIV (PWH) interrupting 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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.028
GPT teacher head0.290
Teacher spread0.262 · 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 designObservational
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

Citations7
Published2020
Admission routes1
Has abstractyes

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