Transforming Growth Factor-Beta3 Gene Polymorphisms and Nonsyndromic Cleft Lip and Palate Risk: A Meta-Analysis
Bibliographic record
Abstract
AIMS: To investigate the association between transforming growth factor-beta3 (TGF-β3) genetic polymorphisms and nonsyndromic cleft lip and palate (NSCLP) risk. METHODS: An extensive literature search for relevant studies was conducted on PubMed, Embase, Web of Science, Cochrane Library, and CBM databases from their inception through June 1st, 2013. Case-control studies addressing the correlation between TGF-β3 gene polymorphisms and NSCLP risk. The genotype distribution of the controls should conform to Hardy-Weinberg equilibrium. The quality of the included studies was assessed independently by two authors based on the Newcastle-Ottawa scale. All analyses were calculated using the STATA 12.0 software. RESULTS: The association between TGF-β3 gene polymorphisms and NSCLP risk was assessed. Eleven case-control studies were included with a total of 1601 NSCLP cases and 1463 healthy controls. Our meta-analysis results indicated that mutant variants of the TGF-β3 gene may be associated with an increased risk of NSCLP, especially among Asian populations. Further subgroup analyses also revealed significant associations between mutant variants of the TGF-β3 gene and an increased risk of NSCLP in the population-based and polymerase chain reaction-restriction fragment length polymorphism studies. Meta-regression analyses showed that ethnicity may be a major source of heterogeneity. CONCLUSION: Our meta-analysis suggests that TGF-β3 gene polymorphisms may contribute to NSCLP susceptibility, especially among Asian populations.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".