Coinfection of HPVs Is Associated with Advanced Stage in Colorectal Cancer Patients from Qatar
Bibliographic record
Abstract
High-risk human papillomaviruses (HPVs) are considered risk factors in the origin of several human malignancies, such as breast, cervical, head and neck, as well as colorectal cancers. However, there are no data reported on the HPV status in colorectal cancer in the State of Qatar. Therefore, we herein examined the presence of high-risk HPVs (16, 18, 31, 33, 35, 45, 51, 52, and 59), using polymerase chain reaction (PCR) in a cohort of 100 Qatari colorectal cancer patients, and their association with tumor phenotype. We found that high-risk HPV types 16, 18, 31, 35, 45, 51, 52, and 59 were present in 4, 36, 14, 5, 14, 6, 41, and 17% of our samples, respectively. Overall, 69 (69%) of the 100 samples were HPV positive; among these, 34/100 (34%) were positive for single HPV subtypes, while 35/100 (35%) of the samples were positive for two or more HPV subtypes. No significant association was noted between the presence of HPV and tumor grade, stage, or location. However, the presence of coinfection of HPV subtypes strongly correlated with advanced stage (stage 3 and 4) colorectal cancer, indicating that the copresence of more than one HPV subtype can significantly worsen the prognosis of colorectal cancer. The results from this study imply that coinfection with high-risk HPV subtypes is associated with the development of colorectal cancer in the Qatari population.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".