Peroxisome Proliferator‐activated Receptor γ 2 and Acyl‐CoA Synthetase 5 Polymorphisms Influence Diet Response
Bibliographic record
Abstract
Peroxisome proliferator-activated receptor gamma (PPARgamma) and its response gene, Acyl CoA synthetase 5 (ACSL5), which has an important role in fatty acid metabolism, may affect weight loss in response to caloric restriction. Therefore, we aimed to determine whether these genes were involved in the interindividual response to dietary treatment. Genotypic/phenotypic comparisons were made between selected obese women from the quintiles losing the most (diet responsive, n = 74) and the quintiles losing the least (diet-resistant, n = 67) weight in the first 6 weeks of a 900-kcal formula diet. Two common PPARgamma single nucleotide polymorphisms, Pro(12)Ala and C1431T, and eight polymorphisms across the ACSL5 gene were selected for single locus and haplotypic association analyses. The PPARgamma Pro(12)Ala single nucleotide polymorphism was associated with diet resistance (odds ratio = 3.48, 95% confidence interval = 1.41 to 8.56, p = 0.03), and the rs2419621, located in the 5'untranslated region of the ACSL5 gene, displayed the strongest association with diet response (odds ratio = 3.45, 95% confidence interval = 1.61 to 7.69, p = 0.001). Skeletal muscle ACSL5 mRNA expression was significantly lower in carriers of the wildtype compared with the variant rs2419621 allele (p = 0.03). Our results suggest a link between PPARgamma2 and ACSL5 genotype and diet responsiveness.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".