Serologic Response to Human Papillomavirus Genotypes Among Unvaccinated Women: Findings From the HITCH Cohort Study
Bibliographic record
Abstract
BACKGROUND: Humoral immune responses may be critical for preventing, controlling, and/or eliminating human papillomavirus (HPV) infection. We analyzed humoral response to natural HPV infection considering phylogenetic relatedness among unvaccinated women. METHODS: We included 399 young women attending university/college in Montreal, Canada who were participants of the HITCH cohort. Participants provided blood samples at baseline and 5 follow-up visits. Antibody response to bacterially expressed L1 and E6 glutathione S-transferase (GST) fusion proteins, and virus-like particles (VLP-L1) of Alphapapillomavirus types were measured using multiplex serology. We assessed correlations and associations between HPV types at baseline using Pearson correlation coefficients (r) and univariable linear regressions. RESULTS: At baseline, > 40% were seropositive for GST-L1 antibodies of at least 1 HPV type. Strong correlations between GST-L1 were observed for α9 HPV types: 58-52 (r = 0.86), 58-33 (r = 0.75), 33-52 (r = 0.72), and between GST-E6: 52-11 (r = 0.84), 52-18 (r = 0.79), 58-33 (r = 0.78), 35-11 (r = 0.76). HPV16 VLP-L1 moderately explained variability in HPV16 GST-L1 (regression coefficient [b] = 0.38, R2 = 43.1%), and HPV45 GST-L1 in HPV18 GST-L1 (b = 0.68, R2 = 42.8%). GST-E6 antibodies accounted for a low to moderate proportion of variability in HPV16 and HPV18 GST-E6 (R2 = 6.4%-62.2%). CONCLUSIONS: Associations between naturally induced HPV-specific antibodies depend on phylogenetic relatedness.
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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 | 0.002 |
| 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 | 0.000 | 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".