Leptin Levels, Leptin Receptor Gene Polymorphisms, and Energy Metabolism in Women
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: Resting metabolic rate (RMR) is mainly determined by fat-free mass and additionally by age, sex, hormones, and possibly genetic differences. We evaluated whether leptin levels and polymorphisms in the leptin receptor (LEPR) gene were associated with energy expenditure phenotypes. METHODS: RMR, body composition, and leptin levels were measured in 125 overweight and obese women. Three LEPR polymorphisms, Lys109Arg, Gln223Arg, and Lys656Asn, were typed on genomic DNA of another group of 192 women in whom RMR was measured. Fat, protein, and carbohydrate oxidation were calculated for 103 of these subjects. In 38 subjects, glucose-induced thermogenesis was measured over 3 hours. RESULTS: In the first study group, a negative correlation between RMR and leptin levels was found after controlling for fat and fat-free mass. In multiple regression analysis, leptin contributed significantly to RMR, independent of body composition. In the second study group, RMR was not associated with LEPR polymorphisms. Differences in substrate oxidation rates were found among genotypes at the Lys656Asn site. In fasting conditions, Lys656Lys showed a trend to oxidize more carbohydrates and less fat than Asn656 carriers, a trend which became significant after the glucose load when carbohydrate oxidation rate in Lys656Lys was 15% higher than in Asn656 carriers (p = 0.04), and fat oxidation rate was 44% lower (p = 0.02). DISCUSSION: These results suggest that DNA sequence variations in the LEPR gene could affect substrate oxidation. We hypothesize that this might be caused by differences in glucose levels, leading to differences in glucose oxidation rates.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 it