Mucosal correlates associated with natural regression of HPV-associated dysplasia
Bibliographic record
Abstract
Abstract Background Anal HPV infection and associated pre-cancerous changes, known as anal intraepithelial neoplasia (AIN), are common among men who have sex with men (MSM). While natural regression of AIN is often observed, there are currently no predictors for disease outcomes. Therefore, we assessed mucosal immune and microbiological correlates of natural AIN regression. Methods Fifty-five HIV-infected, ART-treated MSM were recruited, of whom 26 had confirmed AIN. The microbiome was defined via qPCR and 16s sequencing of anal swabs; biopsies were collected from both healthy and AIN-confirmed sites by high-resolution anoscopy, and lymphocyte populations were defined by flow cytometric analysis including CD38 and HLA-DR as activation markers. AIN regressors vs non-regressors were compared by Mann-Whitney (SPSS). Results AIN regression was observed in 15/26 (58%) participants. Regression was associated with a higher proportion of CD8+ T cells (p= 0.006), and AIN regressors had significantly higher levels of both activated CD8+ (p= 0.023; 44.5% vs 27.9%) and activated CD4+ T cells (p=0.023; 20.4% vs 9.81%) compared to non-regressors. Interestingly, AIN regressors had reduced microbiome diversity (p=0.026; 241 vs 284 OTUs) and a trend towards a lower bacterial load (p=0.059). While age was similar between groups, AIN regressors had been living with HIV for a shorter time (p=0.023). No differences were observed between groups in T cells derived from AIN-free anal mucosa. Conclusions AIN-specific immune activation was associated with subsequent regression of AIN. Given that AIN non-regressors had greater anal microbiome diversity, defining key bacterial species and their role in HPV pathogenesis may merit further investigation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".