Cell Cycle Regulatory CCND1 G870A Gene Polymorphism and Periodontitis-Induced Oral Cancer: A Risk Analysis
Bibliographic record
Abstract
Abstract Strong association has been recently observed between periodontitis/gingivitis and Oral squamous cell carcinoma (OSCC). A high incidence of oral cancer has been reported in the case of chronic periodontitis. Recently Cell cycle regulatory /Senescence genes have been associated with Gingivitis/ Periodontitis susceptibility. Cyclin D1 is one such cell cycle regulatory gene. Several findings have reported that Cyclin D1 (CCND1) G870A Single nucleotide polymorphism is associated with oral cancer (OC) risk, but yielded inconsistent data across different studies. This meta-analysis explores the precise relationship between CCND1 G870A polymorphism and OC risk. PubMed (Medline), EMBASE, & Google Scholar databases were searched for eligible studies and pooled odds ratios (ORs) and 95% confidence intervals (CI) were calculated. Newcastle-Ottawa analysis was done for selected articles quality assessment, bias in publication (if any) was estimated through Funnel plots and Egger’s test. Pooled analysis from eleven eligible studies suggests that CCND1 G870A polymorphism is not significantly associated with OC risk. Sub-group analysis by ethnicity failed to show any association. Sequential single study omission was performed to determine the credibility and resilience of the inferences drawn.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.014 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".