LEP and LEPR Polymorphisms Influences Anthropometric Outcome in Response to 8 Weeks of Combined Training in Obese boys
Bibliographic record
Abstract
Objectives: The purpose of the present study was to investigate whether LEP19 G>A and LEPR 668 A>G polymorphisms, would influence the effect of an 8-week combined aerobic and resistance training. Methods: Thirty obese boys (BMIz>+2) aged 11-13 (12.66±0.47) were recruited from three middle schools in Quchan. The changes in body composition parameters and metabolic factors in response to 8-weeks combined aerobic and resistance training program were analyzed regarding LEP and LEPR polymorphism. DNA was extracted from cheek cells donated by the 30 participants and genotyping was carried out using PCR. Results: Our results suggest that carriers of rs2167270G allele and rs1137101A allele were characterized by a greater reduction in body mass and WHR (P< 0.05). Also, a significant decrease was observed in leptin levels in carriers of rs2167270G allele after the training program (P=0.031). Moreover, the LEP and LEPR polymorphisms were associated with changes in lipid profile in response to training. Conclusion: In response to 8 weeks of regular physical activity, obese boys with G (rs2167270) and A (rs1137101) alleles had the best likelihood of losing weight which was associated with a decrease in body mass, fat mass (%), WHR and leptin concentrations.
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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 | 0.000 |
| 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".