Human papillomavirus DNA detection in sperm using polymerase chain reaction
Bibliographic record
Abstract
OBJECTIVE: To detect human papillomavirus (HPV) in semen and find if sperm washing removes HPV DNA. METHODS: Amplification by nested polymerase chain reaction (PCR) was used to detect viral DNA sequences in semen samples from 85 volunteers. Forty-five men had historical or clinical evidence of genital HPV infection (study group) and 40 were healthy, clinically HPV-negative semen donors. RESULTS: We detected HPV DNA in the sperm cells of 24 of 45 subjects (53%) with past or current HPV infections in contrast to three of 40 healthy subjects (8%) (P <.001). Overall, PCR detected HPV in 21 of 32 subjects (66%) with identifiable lesions and six of 53 (11%) without them (P <.001). Swim-up washings of all 27 prewash sperm cells with HPV reduced cellular HPV DNA below detectable levels in only two cases. CONCLUSION: HPV is present in sperm cells from infected and apparently healthy subjects, and sperm washing does not eliminate the risk of HPV transmission to recipients. We suggest that HPV DNA testing should be done on the semen of prospective donors, and those with positive tests should be excluded from donation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".