Prevalence of selective inhibition of HPV‐16 DNA amplification in cervicovaginal lavages
Bibliographic record
Abstract
HPV-16 viral load has been assessed with real-time PCR assays by measuring HPV-16 DNA and a human gene in genital samples. HPV-16 viral load measurements are thus based on the inference that inhibitors contained in samples will equally impede amplification of DNA sequences from HPV-16 and human DNA. We have previously shown that sample lysates can inhibit amplification of HPV-16 but not beta-globin DNA. In the current study, cervicovaginal lavages lysates considered adequate for PCR analysis by a qualitative beta-globin PCR test, were screened for the presence of inhibitors using internal controls (IC) for HPV-16 DNA and beta-globin in real-time PCR assays. Of 150 lysates screened with both ICs, 12 (8%) contained inhibitors. Inhibition of amplification of both ICs was demonstrated in four of these specimens. In eight lysates, amplification of HPV-16 IC only was impeded. Six (50%) of these 12 lysates tested positive for HPV-16 DNA despite the presence of PCR inhibitors. The HPV-16 viral load increased significantly after dilution of 11 of 12 lysates, demonstrating the presence of inhibitors in the undiluted lysate. Nine (90%) of 10 samples with inhibitors that were tested after dilution did not demonstrate inhibitory activity. The use of internal controls in real-time PCR is clearly essential to determine HPV viral loads since the effect of inhibitors on primer-driven genomic amplification is variable.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".