TLR4 polymorphism and periodontitis susceptibility
Bibliographic record
Abstract
BACKGROUND: Many primary and secondary studies reported the association between Toll-like receptor 4 (TLR4) polymorphism and periodontitis susceptibility, which mainly focused on TLR4-299A>G or TLR4-399C>T of Caucasian, however, these studies had different conclusions. The aim of this study was to reassess relative studies about TLR4 polymorphism and periodontitis susceptibility, and update meta-analysis. METHODS: We searched the electronic database including CNKI (Chinese National Knowledge Infrastructure), PubMed, Embase, and hand searched relative studies until January 4, 2016. Two authors selected studies according to inclusion and exclusion criteria, assessed studies using Newcastle-Ottawa Scale case control study (NOS), and calculated the combined effect size using STATA software, version 12.0. RESULTS: This meta-analysis included 18 studies, containing 2453 healthy participants and 2987 patients with chronic periodontitis (CP) and 462 patients with aggressive periodontitis (AP). There was a significance between TLR4C>G (rs7873784) allele and CP in Asian, and its recessive model was also significant (for C vs G: odds ratio [OR] = 0.72, 95% confidence interval [CI] = 0.54-0.95, I = 0%; for CC + CG vs GG: OR = 0.66, 95% CI = 0.49-0.89, I = 0%). However, we did not detect any significant relevance between other TLR4 polymorphism and periodontitis susceptibility in overall and subgroup analyses. The sensitive analysis showed that dropping any single studies did not affect the pooled-analysis results. Publication bias was not detected. CONCLUSIONS: The meta-analysis found association between TLR4C>G (rs7873784) allele and CP in Asian and it may passed on to offsprings in the form of recessiveness. However, further studies about the association between TLR4C>G (rs7873784) and CP is warranted to confirm.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.009 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".