Polymorphism of fucosyltransferase 3 gene is associated with inflammatory bowel disease: a systematic review
Bibliographic record
Abstract
Abstract Background Inflammatory bowel disease (IBD) is a condition with an unclear genetic basis. Fucosyltransferase 3 (FUT3) could potentially be linked to IBD susceptibility. Objective To investigate the association between FUT3 gene polymorphisms and IBD. Methods Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 checklist and Population, Intervention, Comparison, Outcomes, and Study (PICOS) guidelines, case-control studies published until April 30, 2020 was searched. Two independent reviewers conducted screening, data extraction, and quality assessment using the Newcastle-Ottawa Scale. Meta-analysis, sensitivity analysis, and Egger tests were performed using RevMan and Stata12.0. Results The review included 5 articles and 12 case-control studies involving 1712 IBD patients and 1903 controls. The meta-analysis revealed the following combined odds ratios [95% confidence intervals]: rs3745635 genotype ( GA+AA vs GG ) 0.84 (0.72–0.97), ( GG+GA vs AA ) 1.93 (1.23–3.05), ( GG vs AA ) 2.38 (1.52–3.74), ( A vs G ) 0.84 (0.73–0.96); rs3894326 genotype ( TA+AA vs TT ) 1.03 (0.87–1.23), ( TT+TA vs AA ) 1.19 (0.56–2.51), ( TT vs AA ) 1.19 (0.56–2.51), ( A vs T ) 1.02 (0.86–1.20); rs28362459 genotype ( TG+GG vs TT ) 0.98 (0.85–1.12), ( TT+TG vs GG ) 1.20 (0.90–1.61), ( TT vs GG ) 1.21 (0.90–1.62), ( G vs T ) 0.96 (0.86–1.07). Sensitivity analysis indicated the stability of the results, and Egger analysis showed no significant publication bias. Conclusions The rs3745635 gene polymorphism may be associated with IBD susceptibility, whereas the rs3894326 and rs28362459 gene polymorphisms may not be associated with IBD.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.013 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".