Influence of human papillomavirus type 16 (HPV-16) E2 polymorphism on quantification of HPV-16 episomal and integrated DNA in cervicovaginal lavages from women with cervical intraepithelial neoplasia
Bibliographic record
Abstract
Integrated human papillomavirus type 16 (HPV-16) viral loads are currently estimated by quantification with real-time PCR of HPV-16 E6 (RT-E6 and HPV-16 PG) and E2 (RT-E2-1) DNA. We assessed the influence of HPV-16 E2 polymorphism on quantification of integrated HPV-16 DNA in anogenital specimens. HPV-16 E2 was sequenced from 135 isolates (123 from European and 12 from non-European lineages). An assay targeting conserved HPV-16 E2 sequences (RT-E2-2) was optimized and applied with RT-E6 and RT-E2-1 on 139 HPV-16-positive cervicovaginal lavages collected from 74 women [58 human immunodeficiency virus (HIV)-seropositive and 16 HIV-seronegative]. Ratios of HPV-16 copies measured with RT-E2-2 and RT-E2-1 obtained with African 2 (median=3.23, range=1.92-3.49) or Asian-American (median=3.78, range=1.47-37) isolates were greater than those obtained with European isolates (median=1.02, range=0.64-1.80; P<0.02 for each comparison). The distribution of HPV-16 E2 copies measured in 139 samples with RT-E2-2 (median=6150) and RT-E2-1 (median=8960) were different (P<0.0001). The risk of high-grade cervical intraepithelial neoplasia (CIN-2,3) compared with women without CIN was increased with higher HPV-16 total [odds ratio (OR)=2.17, 95 % confidence interval (CI)=1.11-4.23], episomal (OR=2.14, 95 % CI=1.09-4.19), but not for HPV-16 integrated viral load (OR=1.71, 95 % CI=0.90-3.26), after controlling for age, race, CD4 count, HIV and HPV-16 polymorphism. The proportion of samples with an E6/E2 ratio >2 in women without squamous intraepithelial lesion (7 of 35) was similar to that of women with CIN-2,3 (5 of 11, P=0.24) or CIN-1 (5 of 14, P=0.50). HPV-16 E2 polymorphism was a significant factor that influenced measures of HPV-16 integrated viral load.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".