GSTT1 and CYP2E1 polymorphisms and trihalomethanes in drinking water: effect on childhood leukemia.
Bibliographic record
Abstract
The purpose of the study was to determine whether the risk of childhood acute lymphoblastic leukemia (ALL) associated with drinking water disinfection by-products was modified in the presence of variants in genes involved in the metabolism of trihalomethanes (THMs). We included a subset of cases from a population-based case-control study in a case-only study to estimate the interaction odds ratios (IORs) between prenatal and postnatal exposure to THMs and polymorphisms in the GSTT1 and CYP2E1 genes. We compared cases with and without a given variant regarding their exposure to THMs using unconditional logistic regression. The IOR for a postnatal average of total THM above the 95th percentile with GSTT1 null genotype was 9.1 [95% confidence interval (95% CI), 1.4-57.8]. With CYP2E1 (variant G-1259C, known as the allele CYP2E1*5), the effect of exposure during pregnancy for an average exposure to total THM at or above the 75th percentile was 9.7 (95% CI, 1.1-86.0). These results contrast strongly with those from our case-control analysis, in which we considered the exposure to THMs only in relation with ALL, and observed no increase in risk or very moderate ones. The present preliminary study shows suggestive but imprecise results. We found no similar results in the literature, underscoring the need for other studies as well as the potential usefulness of combining exposure and relevant genetic information in such studies.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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".