Toll-like receptor 6 expression, sequence variants, and their association with colorectal cancer risk
Bibliographic record
Abstract
This is the first study to examine the potential correlation of the rs3796508 and rs5743810 SNPs of the TLR6 gene in patients with colorectal cancer (CRC) in a subset of the Saudi population. TLR6 gene expression was studied by real-time PCR assaysin 10 matching normal and cancer colon tissues. TLR6 expression at the protein level was determined by immunohistochemistry. A case-control search was conductedon 115 case patients and 102 controls. All samples were genotyped with the TaqMan assay for the TLR6 gene. Odds ratios and 95% confidence interval were computed from logistic regression models after adjusting for age, sex, and tumor localization. Our findings showed a decrease in TLR6 expression (p <0.001) in colon cancer tissues when compared to normal colon tissues. Global analysis revealed no significant association between the TLR6 rs3796508 and rs5743810 and CRC in this population. However, the Val/Met genotype of rs3796508 had a significantly higher frequency in the control group than in the cases for the male group (OR= 0.095, and p= 0.03385) or the volunteers aged more than 57 years OR= 0.152; and p= 0.04069, respectively). Two non-synonymous single nucleotide polymorphisms (SNP; S249P and V327M) were common in a few patients and were predicted as damaging by SIFT and Polyphen and were further analyzed for their protein stability and function using advanced bioinformatics tools. The results suggest that TLR6 rs3796508 has a crucial role as a protective factor against colorectal cancer in the older Saudi male 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 | 0.000 | 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) | 0.001 | 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".