Gastric Bypass Increases Energy Expenditure in Rats
Bibliographic record
Abstract
BACKGROUND & AIMS: Mechanisms underlying weight loss maintenance after gastric bypass are poorly understood. Our aim was to examine the effects of gastric bypass on energy expenditure in rats. METHODS: Thirty diet-induced obese male Wistar rats underwent either gastric bypass (n = 14), sham-operation ad libitum fed (n = 8), or sham-operation body weight-matched (n = 8). Energy expenditure was measured in an open circuit calorimetry system. RESULTS: Twenty-four-hour energy expenditure was increased after gastric bypass (4.50 +/- 0.04 kcal/kg/h) compared with sham-operated, ad libitum fed (4.29 +/- 0.08 kcal/kg/h) and sham-operated, body weight-matched controls (3.98 +/- 0.10 kcal/kg/h, P < .001). Gastric bypass rats showed higher energy expenditure during the light phase than sham-operated control groups (sham-operated, ad libitum fed: 3.63 +/- 0.04 kcal/kg/h vs sham-operated, body weight-matched: 3.42 +/- 0.05 kcal/kg/h vs bypass: 4.12 +/- 0.03 kcal/kg/h, P < .001). Diet-induced thermogenesis was elevated after gastric bypass compared with sham-operated, body weight-matched controls 3 hours after a test meal (0.41% +/- 1.9% vs 10.5% +/- 2.0%, respectively, P < .05). The small bowel of gastric bypass rats was 72.1% heavier because of hypertrophy compared with sham-operated, ad libitum fed rats (P < .0001). CONCLUSIONS: Gastric bypass in rats prevented the decrease in energy expenditure after weight loss. Diet-induced thermogenesis was higher after gastric bypass compared with body weight-matched controls. Raised energy expenditure may be a mechanism explaining the physiologic basis of weight loss after gastric bypass.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".