miR-608 rs4919510 C>G POLYMORPHISM DECREASED THE RISK OF BREAST CANCER IN AN IRANIAN SUBPOPULATION
Bibliographic record
Abstract
AIM: MicroRNAs (miRNAs) are small noncoding RNAs that function as oncogene or tumor suppressors. The single nucleotide polymorphisms in miRNAs potentially can alter miRNA-binding sites on target genes as well as affecting miRNAs expression. The present study aimed to evaluate the impact of miR-608 rs4919510 C>G variant on breast cancer (BC) risk. MATERIALS AND METHODS: This case-control study conducted on 160 women with BC and 192 age-matched healthy women. Genotyping of miR-608 rs4919510 was done using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. RESULTS: Our findings showed that GC genotype significantly decreased the risk of BC (odds ratio (OR) = 0.49, 95% confidence interval (CI) 0.28-0.88, p = 0.018) compared to CC genotype. Furthermore the G allele decreased the risk of BC (OR = 0.53, 95%CI 0.30-0.92, p = 0.024). No significant association was found between miR-609 genotypes and clinicopathological characteristics of BC patients (p >0.05). CONCLUSION: Our findings indicate that miR-608 polymorphism might be associated with decreased risk of BC in an Iranian subpopulation. Further large-scale studies with different ethnicities are needed to verify our findings.
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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 | 0.000 | 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) | 0.002 | 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".