The role of two DNA repair polymorphisms XRCC1-R399Q and XRCCC3-T241M in breast cancer risk
Bibliographic record
Abstract
The objective of this thesis was to determine the potential role of two single nucleotide polymorphisrns in DNA repair genes, XRCC1 and XRCC3, as susceptibility alleles for breast cancer. XRCC1 and XRCC3 are involved in base excision repair and double strand break repair respectively. A polymorphism in XRCC1 results in an arginine (R) to glutamine (Q) change at codon 399 within a BRCT domain and PARP binding site. Another polymorphism in XRCC3 results in a threonine (T) to methionine (M) change at codon 241 located in a RecA protein domain. Both amino acid substitutions result in radical changes in conserved sites of their respective proteins. Furthermore, these polymorphisms have been linked with DNA damage phenotypes in human tissues and associated with cancer susceptibility in previous case-control studies. This study combines the systematically-collected data in the Ontario Familial Breast Cancer Registry (OFBCR) and existing high throughput technology to conduct a case-control study to investigate the roles of two SNPs in DNA repair genes, XRCC1-R399Q and XRCC3-T241 M, in breast cancer. We hypothesize that these SNPs may be low-penetrant breast cancer susceptibility alleles. (Abstract shortened by UMI.)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.004 | 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".