Mutations in exon 11 (11.1 and 11.2) of the BRCA1 gene and risk factors for breast cancer in Burkina Faso
Bibliographic record
Abstract
Breast cancer is the leading cause of death among women in both developed and developing countries. It is multifactorial, including genetic predispositions such as oncogenic mutations on BRCA1 and 2 genes. The objectives of the present study were to identify oncogenic mutations in exon 11 of the BRCA1 gene and to determine the risk factors for breast cancer among women population in Burkina Faso. This study involved 100 women, including 50 cases of breast cancer and 50 controls (no clinical signs and no family history of breast cancer or other cancers). Mutations in the BRCA1 gene were detected by PCR using sequence primers specific for exon 11 fragments (11.1 and 11.2). In our study population, age (OR=22.40; CI: 4.33-115.82; p0.001) and obesity (OR=4.23; CI: 1.64-10.92; p=0.003) were risk factors while multiparity was a protective factor for breast cancer (OR=0.35; CI: 0.15-0.81; p=0.02). A mutation was found on both fragments 11.1 and 11.2 of the BRCA1 gene exon 11 in 04/50 (8.0 %) of patients. No mutations were observed in controls. The present study revealed high frequency of oncogenic mutations in exon 11 fragments (11.1 and 11.2) of the BRCA1 gene. These mutations on exon 11 are and involved in the occurrence of breast cancer in our population. Age and obesity were also risk factors for breast cancer among women population in Burkina Faso.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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".