Interaction of CCND1 genotype and smoking habit in Taiwan lung cancer patients.
Bibliographic record
Abstract
AIM: Cyclin D1 (CCND1) is critical in the transition of the cell cycle from G1 to S phase and unbalanced cell cycle regulation is a hallmark of carcinogenesis. The study aimed at investigating the association of CCND1 genotypes with lung cancer risk in Taiwan and examining the interaction between CCND1 genotype and smoking habit. PATIENTS AND METHODS: CCND1 A870G (rs9344) and C1722G (rs678653) genotypes were determined by polymerase chain reaction (PCR) and restriction fragment length polymorphism (RFLP) analysis of DNA from the blood of 358 lung cancer patients and 716 cancer-free healthy controls. RESULTS: The results showed that there were significant differences between lung cancer and control groups in the distribution of the genotypes (p=0.0003) and allelic frequency (p=0.0007) in the CCND1 rs9344 genotype. Individuals who carried AG or GG genotype had 0.59- and 0.52-fold risk, respectively, of developing lung cancer compared to those who carried the AA genotype (95% CI=0.44-0.78 and 0.35-0.79, respectively). There was also an obvious interaction of CCND1 rs9344 genotype with personal smoking habit on lung cancer risk (p=0.0009). CONCLUSION: These findings support the conclusion that cell cycle regulation may play a role in lung cancer development and that CCND1 rs9344 polymorphism together with smoking habit maybe a useful biomarker for lung cancer prediction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".