Incidence and association of high-risk HPVs and EBV in patients with advanced stages of colorectal cancer from Qatar
Bibliographic record
Abstract
High-risk Human Papillomaviruses (HPVs) and Epstein – Barr virus (EBV) are present and involved in several types of human carcinomas, including cervical and, head and neck cancers. Nevertheless, their presence and association in the pathogenesis of colorectal cancer is still nascent. The current study explored the association between the high-risk HPVs and EBV and tumor phenotype in colorectal cancers (CRCs) in the Qatari population. We found that high-risk HPVs and EBV are present in 69/100 and 21/100 cases, respectively. Additionally, 17% of the cases showed a copresence of high-risk HPVs and EBV, with a significant correlation only between the HPV45 subtype and EBV (p = .004). While the copresence did not significantly associate with clinicopathological characteristics, we identified that coinfection with more than two subtypes of HPV is a strong predictor of advanced stage CRC, and the confounding effect of the copresence of EBV in such cases strengthens this association. Our results indicate that high-risk HPVs and EBV can co-present in human CRCs in the Qatari population where they could plausibly play a specific role in human colorectal carcinogenesis. However, future studies are essential to confirm their copresence and synergistic role in developing CRCs.
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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 | 0.000 | 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) | 0.002 | 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".