Genotyping of Human Papillomavirus DNA in Anal Biopsies and Anal Swabs Collected From HIV-Seropositive Men With Anal Dysplasia
Bibliographic record
Abstract
BACKGROUND: Human papillomavirus (HPV) causes anal intraepithelial neoplasia (AIN) in HIV-seropositive men. The detection of HPV genotypes in anal biopsies and swabs was compared. METHODS: HPV DNA was detected in anal swabs and biopsies obtained concurrently from 154 HIV-seropositive men [31 without AIN, 60 low-grade AIN (AIN-1), 62 high-grade AIN (AIN-2,3), and 1 indeterminate AIN] under or eligible to highly active antiretroviral therapy. RESULTS: HPV DNA was detected in 24.2% of normal biopsies compared with 93.5% with AIN-2,3 (P < 0.001) and 88.3% with AIN-1 (P < 0.001). The proportion of biopsies containing multiple genotypes was greater in AIN-1 (n = 21, 35.0%; P = 0.002) and AIN-2,3 (n = 38, 58%; P < 0.001) than in normal biopsies (n = 2, 6.5%). The most frequent genotypes in order of frequency were in AIN-2,3 biopsies HPV-16, 18, 58, and 45 and were in AIN-1 biopsies HPV-6, 11, 16, and 39. Controlling for age, CD4 count, and smoking, the presence of high-risk HPV DNA in biopsies [odds ratio (OR) = 50.8, 95% confidence interval (CI): 13.0 to 199.5] but not in swabs (OR = 2.0, 95% CI: 0.6 to 7.0) was associated with AIN-2,3. CONCLUSIONS: AIN-2,3 was associated with high-risk HPV infection detected in biopsies but not in swabs in men under or starting highly active antiretroviral therapy, possibly due to the presence of HPV foci outside of the neoplastic lesion.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".