Polymorphism in nucleotide excision repair gene <i>XPC</i> correlates with bleomycin‐induced chromosomal aberrations
Bibliographic record
Abstract
Chromosomal aberrations (CAs) are important genetic alterations in the development and progression of the majority of human cancers. The frequency with which such alterations occur depends to a large extent on polymorphisms of DNA-repair genes and in genes coding for xenobiotic metabolizing enzymes, which are involved in the processes of activation and inactivation of xenobiotics. The frequency of bleomycin (BLM)-induced CAs is an indirect measure of the effectiveness of DNA repair mechanisms, and a predictor of environment-related risk of cancer. Our study was conducted on the human peripheral blood lymphocytes of 82 healthy volunteers. The aim of the study was to elucidate whether the frequency of BLM-induced CAs is correlated with polymorphisms of selected genes involved in different mechanisms of DNA repair such as: XRCC1 [base excision repair]; XPA, XPC, XPG, XPD, XPF, ERCC1 [nucleotide excision repair], NBS1, RAD51, XRCC2, XRCC3, RAD51, and BRCA1 [homologous recombination], as well as in genes encoding xenobiotic metabolizing enzymes, such as CYP1A, CYP2E1, NAT2, GSTT1, and EPHX (mEH). Our study indicated that, of the polymorphisms studied, only XPC (exon 15 and intron 11) is associated with BLM-induced CAs, suggesting a role of the NER pathway in the repair of BLM-induced chromosomal aberrations.
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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) | 0.003 | 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".