Meal patterns, satiety, and food choice in a rat model of Roux-en-Y gastric bypass surgery
Bibliographic record
Abstract
Gastric bypass surgery efficiently and lastingly reduces excess body weight and reverses type 2 diabetes in obese patients. Although increased energy expenditure may also play a role, decreased energy intake is thought to be the main reason for weight loss, but the mechanisms involved are poorly understood. Therefore, the aim of this study was to characterize the changes in ingestive behavior in a rat model of Roux-en-Y gastric bypass surgery (RYGB). Obese (24% body fat compared with 18% in chow-fed controls), male Sprague-Dawley rats maintained for 15 wk before and 4 mo after RYGB or sham-surgery on a two-choice low-fat/high-fat diet, were subjected to a series of tests assessing energy intake, meal patterning, and food choice. Although sham-operated rats gained an additional 100 g body wt during the postoperative period, RYGB rats lost approximately 100 g. Intake of a nutritionally complete and palatable liquid diet (Ensure) was significantly reduced by approximately 50% during the first 2 wk after RYGB compared with sham surgery. Decreased intake was the result of greatly reduced meal size with only partial compensation by meal frequency, and a corresponding increase in the satiety ratio. Similar results were obtained with solid food (regular or high-fat chow) 6 wk after surgery. In 12- to 24-h two-choice liquid or solid diet paradigms with nutritionally complete low- and high-fat diets, RYGB rats preferred the low-fat choice (solid) or showed decreased acceptance for the high-fat choice (liquid), whereas sham-operated rats preferred the high-fat choices. A separate group of rats offered chow only before surgery completely avoided the solid high-fat diet in a choice paradigm. The results confirm anecdotal reports of "nibbling" behavior and fat avoidance in RYGB patients and provide a basis for more mechanistic studies in this rat model.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".