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Record W2128089251 · doi:10.1093/infdis/jis544

Impaired Hepatitis C Virus (HCV)–Specific Interferon-γ Responses in Individuals With HIV Who Acquire HCV Infection: Correlation With CD4+ T-Cell Counts

2012· article· en· W2128089251 on OpenAlexaff
Jacqueline K. Flynn, Gregory J. Dore, Gail Matthews, Margaret Hellard, Barbara Yeung, William D. Rawlinson, Peter A. White, John Kaldor, Andrew R. Lloyd, Rosemary Ffrench

Bibliographic record

VenueThe Journal of Infectious Diseases · 2012
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsInstitute of Infection and Immunity
FundersNational Health and Medical Research CouncilU.S. Public Health ServiceNational Institutes of Health
KeywordsCoinfectionHepatitis C virusELISPOTImmunologyHepatitis CViremiaVirologyMedicineCytokineHepacivirusInterferonImmune systemVirusT cell

Abstract

fetched live from OpenAlex

Studies examining the effect of coinfection with human immunodeficiency virus (HIV) and hepatitis C virus (HCV) on the HCV-specific immune response in acute HCV infection are limited. This study directly compared acute HCV-specific T-cell responses and cytokine profiles between 20 HIV/HCV-coinfected and 20 HCV-monoinfected subjects, enrolled in the Australian Trial in Acute Hepatitis C (ATAHC), using HCV peptide enzyme-linked immunospot (ELISPOT) and multiplex in vitro cytokine production assays. HIV/HCV coinfection had a detrimental effect on the HCV-specific cytokine production in acute HCV infection, particularly on HCV-specific interferon γ (IFN-γ) production (magnitude P = .004; breadth P = .046), which correlated with peripheral CD4(+) T-cell counts (ρ = 0.605; P = .005) but not with detectable HIV viremia (ρ = 0.152; P = .534).

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)0.003
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.281
Teacher spread0.263 · 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

Citations21
Published2012
Admission routes1
Has abstractyes

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Same venueThe Journal of Infectious DiseasesSame topicHepatitis C virus researchFrench-language works237,207