Human papillomavirus type 52 polymorphism and high‐grade lesions of the uterine cervix
Bibliographic record
Abstract
The association between polymorphism of human papillomavirus type 52 (HPV52) and high-grade cervical intraepithelial neoplasia (CIN2,3) was investigated in Canadian women. HPV-52-positive endocervical specimens collected from 216 women selected from a total of 3,614 participants recruited in two case-control and two cohort studies conducted in Canada, were further analyzed by PCR-sequencing of the LCR and E6 gene. Overall, the HPV52 LCR prototype was detected more frequently in Caucasian women (69 of 132, 52.3%, 95% confidence interval (CI): 43.8%-60.6%) than in non-Caucasian women (15 of 48, 31.3%, 95% CI 19.9%-45.4%). In two cohort studies, HPV52 prototype was detected in seven of 15 (46.7%, 95% CI 24.8-69.9) HPV52 persistent infections and 14 of 35 (40.0%, 95% CI 25.5-56.5) transient infections (p = 0.76). In two case-control studies, 30 participants did not have CIN, 18 had low-grade CIN (CIN1), 64 had CIN2,3, seven had cervical cancer and the diagnosis was undefined for 27 women. Variant MTL-52-LCR-02 was detected more frequently in women with cancer (28.6%, 95% CI 7.6%-64.8%) than in women without cancer or CIN2,3 (0%, 95% CI 0.0%-9.2%; p = 0.015). CIN2,3 risk was significantly associated with a deletion at nucleotide position 7695 in the LCR (OR 4.9, 95% CI 1.2-20.8), the T7744C variation in the LCR (OR 5.7, 95% CI 1.1-32.0), and the K93R variation in E6 (OR 6.9, 95% CI 1.3-36.8), after adjusting for age, detection of HPV16 or 18 and study site. These findings indicate that HPV52 polymorphism influences risk of CIN-2,3 and possibly invasive cancer.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".