The relationship between dietary branched-chain and aromatic amino acids with the regulation of leptin and FTO genes in adipose tissue of patients undergoing abdominal surgery
Bibliographic record
Abstract
Recent studies have suggested that the interaction between diet and an individual’s genetic predisposition can determine the likelihood of obesity and various metabolic disorders. The current study aimed to examine the association of dietary branched-chain amino acids(BCAAs) and aromatic amino acids(AAAs) with the expression of the leptin and FTO genes in the visceral and subcutaneous adipose tissues of individuals undergoing surgery. This cross-sectional study was conducted on 136 Iranian adults, both men and women, aged ≥18 years. The samples were selected from patients admitted for abdominal surgeries. The dietary intake of BCAAs and AAAs was determined using a valid and reliable 168-item food frequency questionnaire. Using the quantitative PCR method, leptin and FTO mRNA expression was measured in both visceral and subcutaneous fat tissues. The mean age of the participants was 39.8 ± 12.7 years, and the mean intake of BCAAs and AAAs was 17.7 ± 0.9 and 9.3 ± 0.3% of protein per day, respectively. In overweight-obese patients(body mass index = 25–34.9 kg/m 2 ), the intake of BCAAs(β:-0.75,95%CI:-1.47,-0.03), valine(β:-0.78,95%CI:-1.51,-0.05), and tyrosine(β:-0.81,95%CI:-1.55,-0.06) was inversely associated with FTO gene expression in subcutaneous fat tissue in adjusted model. In morbidly obese patients(body mass index ≥ 35 kg/m 2 ), a higher intake of total BCAAs(β:1.10,95%CI:0.07–2.13), leucine(β:1.07,95%CI:0.03–2.13), and isoleucine(β:1.49,95%CI:0.46–2.52) was associated with an increase of leptin gene expression in subcutaneous fat tissue. Our findings suggest that dietary BCAA may associated with gene expression in adipose tissues, potentially influencing obesity-related metabolic pathways. Further prospective studies are warranted to validate results and elucidate the potential for dietary interventions targeting amino acids intake in obesity management.
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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) | 0.001 | 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".