Genetic polymorphisms in TLR1, TLR2, TLR4, and TLR10 of Helicobacter pylori-associated gastritis: a prospective cross-sectional study in Thailand
Bibliographic record
Abstract
The toll-like receptors (TLRs) mediate the recognition of Helicobacter pylori and initiate the innate immune response to infection. We hypothesized those genetic polymorphisms in the TLR1, TLR2, TLR4, and TLR10 influence bacterial infection, affecting susceptibility H. pylori to disease outcomes. Genomic DNA was extracted and genotypes of TLR1 (rs4833095), TLR2 (rs3804099 and rs3804100), TLR4 (rs10759932), and TLR10 (rs10004195) polymorphism were detected by the TagMan single-nucleotide epolymorphisms genotyping assay using the real-time PCR hybridization probe method. The TLR1 (rs4833095), C allele and the TLR10 (rs10004195), A allele frequency was significantly increased risk in the H. pylori infection group (odds ratio=1.76, 95% confidence interval=1.84-2.15, P=0.01 and odds ratio=1.81, 95% confidence interval=1.18-3.26, P=0.04, respectively). The TLR1 (rs4833095), C allele and TLR10 (rs10004195), A allele are susceptible TLRs polymorphisms in the Thai population. These findings suggest that TLR1 rs4833095 and TLR10 rs10004195 may play crucial roles in H. pylori susceptibility and gastric pathogenesis.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".