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Record W2752685040 · doi:10.1186/s12981-017-0167-6

The biology of how circumcision reduces HIV susceptibility: broader implications for the prevention field

2017· review· en· W2752685040 on OpenAlexafffund
Jessica L. Prodger, Rupert Kaul

Bibliographic record

VenueAIDS Research and Therapy · 2017
Typereview
Languageen
FieldMedicine
TopicGenital Health and Disease
Canadian institutionsCanada Research ChairsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsForeskinMedicineImmune systemImmunologyHuman immunodeficiency virus (HIV)MicrobiomeMale circumcisionSex organBioinformaticsBiologyPopulationCell culture

Abstract

fetched live from OpenAlex

Circumcision reduces heterosexual HIV-1 acquisition in men by at least 60%. However, the biological mechanisms by which circumcision is protective remain incompletely understood. We test the hypothesis that the sub-preputial microenvironment created by the foreskin drives immune activation in adjacent foreskin tissues, facilitating HIV-1 infection through a combination of epithelial barrier disruption, enhanced dendritic cell maturation, and the recruitment/activation of neutrophils and susceptible CD4 T cell subsets such as Th17 cells. Furthermore, we provide evidence that the genital microbiome may be an important driver of this immune activation. This suggests that new modalities to reduce genital immune activation and/or alter the genital microbiome, used alone or in combination with topical microbicides, may be of significant benefit to HIV prevention.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.459
GPT teacher head0.585
Teacher spread0.125 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations56
Published2017
Admission routes2
Has abstractyes

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