Significant association of Ku80 single nucleotide polymorphisms with colorectal cancer susceptibility in Central Taiwan.
Bibliographic record
Abstract
AIM: To evaluate the association between the polymorphisms of the Ku80 gene and the risk of colorectal cancer in Central Taiwan. MATERIALS AND METHODS: In this hospital-based case-control study, the association of Ku80 G-1401T rs828907, Ku80 C-319T rs11685387 and Ku80 intron 19 rs9288518 polymorphisms with colorectal cancer risk in a central Taiwanese population was investigated. In total, 362 patients with colorectal cancer and 362 age- and gender-matched healthy controls recruited from the China Medical Hospital in central Taiwan were genotyped. RESULTS: A significantly different distribution was found in the frequency of the Ku80 G-1401T genotype, but not the Ku80 C-319T or intron 19 genotypes, between the colorectal cancer and control groups. The T allele Ku80 G-1401T conferred a significantly (p=0.0069) increased risk of colorectal cancer. As for Ku80 C-319T and intron 19 polymorphisms, there was no difference in distribution between the colorectal cancer and control groups. Gene interactions with smoking, but not with alcohol consumption, were significant for Ku80 G-1401T polymorphism. The Ku80 G-1401T GT and TT genotype in association with smoking conferred an increased risk of 2.537 (95% confidence interval=1.398-4.601) for colorectal cancer. CONCLUSION: These results provide the first evidence that the T allele of the Ku80 G-1401T may be associated with the development of colorectal cancer and may be a novel useful marker for primary prevention and anticancer intervention.
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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".