Polymorphisms in the major histocompatibility complex and cervical human papillomavirus infection in a cohort of Montreal university students
Bibliographic record
Abstract
Only a minority of women with a human papillomavirus (HPV) infection eventually develop cervical cancer. This suggests a role for immune mechanisms in viral acquisition and clearance, most notably presentation of HPV antigens as mediated by gene products of the human leukocyte antigen (HLA) complex. A longitudinal cohort investigation of cervical HPV infections was utilized to examine the role of selected HLA class I and II alleles in determining risk of HPV positivity and persistence for students attending McGill and Concordia universities in Montreal. HPV positivity was measured at baseline and then once every six months for a period of two years. Five hundred and fifty-nine women were identified for analysis. Five HLA alleles: B*07, DQB1*03, DQB1*0602, DRB1*13, and DRB1*1501 were typed using DNA extracted from cervical specimens sampled at enrollment. In multivariate logistic regression analyses DRB1*13 (odds ratio [OR]: 2.0; 95% confidence interval [CI]: 1.0-4.0) and DRB1*1501 (OR: 2.1; CI: 1.1-4.1) were associated with HPV 16 positivity. Women with DRB1*13 were also more likely to be positive for high-risk (HR) HPV infections (OR: 1.7; CI: 1.0-2.9), or H PV infection of any type (OR: 1.7; CI: 1.0-2.8). Most associations became stronger in the subset of women restricted on the basis of high likelihood to prior HPV exposure. These results support the hypothesis that certain HLA class II polymorphisms mediate genetic susceptibility to HPV infection in young women.
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 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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
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".