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Record W3135669933 · doi:10.1093/infdis/jiab121

Gag p24 Is a Marker of Human Immunodeficiency Virus Expression in Tissues and Correlates With Immune Response

2021· article· en· W3135669933 on OpenAlexaff
Guoxin Wu, Paul Zuck, Shih Lin Goh, Jeffrey M. Milush, Poonam Vohra, Joseph K. Wong, Ma Somsouk, Steven A. Yukl, Barbara L. Shacklett, Nicolas Chomont, Ashley T. Haase, Hiroyu Hatano, Timothy W. Schacker, Steven G. Deeks, Daria J. Hazuda, Peter W. Hunt, Bonnie J. Howell

Bibliographic record

VenueThe Journal of Infectious Diseases · 2021
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsCentre Hospitalier de l’Université de Montréal
FundersNational Center for Research ResourcesCenter for AIDS Prevention Studies, University of California, San FranciscoNational Institute of Neurological Disorders and StrokeamfAR, The Foundation for AIDS ResearchNational Cancer InstituteUniversity of California, San FranciscoCenter for AIDS Research, University of WashingtonCalifornia HIV/AIDS Research ProgramNational Institute of Allergy and Infectious DiseasesDelaney AIDS Research EnterpriseNational Institute of Diabetes and Digestive and Kidney DiseasesGilead SciencesNational Institute of Mental HealthU.S. Department of Veterans Affairs
KeywordsImmune systemImmunologyCD14BiologyVirusCD8Lymph nodeVirologyHuman immunodeficiency virus (HIV)Group-specific antigenAntiretroviral therapyViral load

Abstract

fetched live from OpenAlex

We demonstrate that human immunodeficiency virus (HIV) gag p24 protein is more readily detected in gut and lymph node tissues than in blood CD4+ T cells and correlates better with CD4 count during antiretroviral therapy (ART). Gut p24 levels also measurably decline with ART in natural controllers. During ART, gut p24 expression is more strongly associated both with HIV-specific CD8+ T-cell frequency and plasma soluble CD14 levels than gut HIV RNA expression. This study supports using gag p24 as a marker of HIV expression in HIV+ tissues to study effects of viral persistence and to monitor efficacy of treatment in HIV-based clearance studies.

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: Observational · Consensus signal: none
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
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.262
Teacher spread0.255 · 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

Citations29
Published2021
Admission routes1
Has abstractyes

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