HPV73 a nonvaccine type causes cervical cancer
Bibliographic record
Abstract
HPV73 is classified as possibly oncogenic. It is neither routinely evaluated in HPV screening, nor covered by any of the prophylactic vaccines. We sought to investigate the carcinogenic characteristics of HPV73. Molecular studies were performed on eight cervix cancer biopsy specimens containing HPV73 from a cross-sectional cancer cohort of 590 women referred to the National Cancer Institute in Rio de Janeiro, Brazil. Transcriptional activity of HPV73 was evaluated by detection of spliced transcripts of E6/E6* and E1^E4 in cDNA created from RNA isolated from fresh tissue. Disruption of viral E1 and E2 genes in the tumor DNA was assessed by overlapping PCR amplification. Evaluation of viral integration was performed using a customized capture panel and next-generation sequencing, and an in-house bioinformatic pipeline. HPV73 E6/E6* transcripts were found in 7/7 specimens with available RNA, and three also had HPV73 E1^E4 transcripts. Disruption of E1 and E2 genes was observed in 4/8 specimens. Integration of HPV73 sequences into the cancer cell genomes was identified in all cervix cancer tissues. These results provide evidence that HPV73 is an oncogenic virus that can cause invasive cervix cancer. With current molecular screening and HPV vaccination, not all cervix cancers will be prevented.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".