Low-Level Anorectal HIV Shedding despite Effective Antiretroviral Therapy Is Not Driven by Mucosal Inflammation
Bibliographic record
Abstract
Although antiretroviral treatment (ART) suppresses HIV RNA in blood and prevents transmission, low-level anorectal HIV RNA shedding persists in some ART-treated men who have sex with men. We collected anorectal biopsies and swabs from 55 men who have sex with men on effective ART, hypothesizing that anorectal shedding would be linked to microbiota-driven mucosal T cell activation. Lymphocytes were assessed by flow cytometry, soluble immune factors by multiplex immunoassay, neutrophils and epithelial integrity by immunofluorescence microscopy, and the anorectal microbiome by quantitative PCR and 16S rRNA gene sequencing. Unexpectedly, we found no evidence that anorectal HIV shedding was associated with the parameters of mucosal inflammation, including T cell activation, inflammatory cytokines, the density of neutrophils, or epithelial integrity. Moreover, the anorectal bacterial load was actually lower in the shedding group, with no major differences in bacterial composition. Instead, the strongest mucosal immune correlates of HIV shedding were an increase in central memory cell frequency and Ki67 expression as well as higher concentrations of the cytokine IL-7 in anorectal secretions. Anorectal HIV RNA shedding during effective ART was not driven by local inflammation; the associations seen with local homeostatic T cell proliferation will require further confirmation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".