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Record W2032329981 · doi:10.1097/qai.0b013e318189a7ca

Bacterial Vaginosis in HIV-Infected Women Induces Reversible Alterations in the Cervical Immune Environment

2008· article· en· W2032329981 on OpenAlexaff
Anuradha Rebbapragada, Kathryn L. Howe, Charles Wachihi, Christopher Pettengell, Sherzana Sunderji, Sanja Huibner, T. Blake Ball, Francis A. Plummer, Walter Jaoko, Rupert Kaul

Bibliographic record

VenueJAIDS Journal of Acquired Immune Deficiency Syndromes · 2008
Typearticle
Languageen
FieldImmunology and Microbiology
TopicReproductive tract infections research
Canadian institutionsUniversity of ManitobaUniversity of Toronto
Fundersnot available
KeywordsBacterial vaginosisImmune systemChemokineImmunologyCytokineVaginaVaginal floraInterleukinBiologyMedicineMicrobiology

Abstract

fetched live from OpenAlex

BACKGROUND: Bacterial vaginosis (BV) has been associated with increased HIV cervicovaginal shedding. We hypothesized that this might relate to BV-associated increases in mucosal activated CD4 T cells, which could enhance local HIV replication. METHODS: Vaginal flora, cytokine/chemokine levels, and mucosal immune cell populations collected by cervical cytobrush were analyzed in 15 HIV-infected Kenyan female sex workers, before and after BV therapy with oral metronidazole. RESULTS: Therapy reduced the Nugent score in all but 1 participant, and BV elimination was associated with reduced genital levels of interleukin 1beta(IL1beta), interleukin 8 (IL-8), and Regulated Upon Activation Normal T-cell Expressed and Secreted (RANTES). In addition, BV elimination reduced the total number of cervical CD4 T cells, including those expressing the HIV coreceptor CCR5 and the activation marker CD69. CONCLUSIONS: BV induces significant and reversible alterations in cervical immune cell populations and local inflammatory cytokines that would be expected to enhance local HIV replication.

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)0.001
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.025
GPT teacher head0.259
Teacher spread0.235 · 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

Citations60
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueJAIDS Journal of Acquired Immune Deficiency SyndromesSame topicReproductive tract infections researchFrench-language works237,207