Dietary Tryptophan Restriction Dose-Dependently Modulates Energy Balance, Gut Hormones, and Microbiota in Obesity-Prone Rats.
Bibliographic record
Abstract
Objective To determine the effects of graded dietary restriction of tryptophan on food intake, energy expenditure, body composition, gut hormones, and select fecal bacterial populations in obesity-prone rats. Methods Obesity-prone rats were randomized to isocaloric diets with varying degrees of tryptophan restriction: control (100% requirements), 70% tryptophan (70TRP), 40% tryptophan (40TRP), or 10% tryptophan (10TRP) for 21 days. The sympathetic system was challenged with a subcutaneous injection of propranolol on days 15 to 17. Measurements included food intake, energy expenditure, body composition, metabolic hormones, and fecal concentrations of select bacteria. Results Moderate tryptophan restriction (70TRP) induced thermogenesis without altering body composition, whereas severe degrees of restriction (40TRP, 10TRP) produced profound hypophagia and decreased energy expenditure and body weight. The thermogenic effects of moderate tryptophan restriction were sympathetically mediated. Severe tryptophan restriction decreased fasting circulating concentrations of glucose, insulin, C-peptide, and leptin, but increased glucagon, pancreatic polypeptide, and glucagon-like peptide-1. Severe tryptophan restriction decreased fecal concentrations of Enterobacteriaceae, Lactobacillus, Bacteroides, and Clostridium coccoides while increasing Roseburia groups. Conclusions Our findings demonstrate that dietary tryptophan restriction dose-dependently modulates energy balance, with severe restriction causing hypophagia and weight loss and moderate restriction promoting sympathetically driven thermogenesis as well as concurrent changes in gut microbiota and hormones.
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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) | 0.001 | 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 | 0.001 |
| 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".