Comparison of Glucose and Satiety Hormone Response to Oral Glucose vs. Two Mixed-Nutrient Meals in Rats
Bibliographic record
Abstract
The obesity epidemic is driving interest in identifying strategies that enhance appetite control by altering the secretion of hormones that regulate satiety and food intake. An appropriate nutrient stimulus, such as a meal or oral nutrient solution, is needed to elicit the secretion of satiety hormones in order to evaluate the impact of dietary and other interventions. Our objective was to compare the effects of oral glucose versus mixed nutrients on plasma concentrations of glucose and appetite-regulating hormones to determine the most appropriate oral nutrient challenge to trigger robust hormone secretion. A 120min oral glucose tolerance test (OGTT) was compared with two meal tolerance tests (MTT) of differing formulation to evaluate glucose and satiety hormone responses. Following overnight feed deprivation, male Sprague-Dawley rats were given one of three oral gavages with equal carbohydrate content (2g CHO/kg) in the form of: 1) Dextrose, 2) Ensure®, or 3) Mixed Meal. A fourth group was given saline as a control. Blood was collected via tail snip and analyzed for glucose, insulin, GLP-1, GIP, PYY, amylin, leptin and ghrelin. Dextrose resulted in the highest blood glucose at T15 (P=0.014), while the mixed meal was significantly higher than saline from T30-T120 (P<0.05). Insulin was higher at T15 with dextrose compared to saline (P=0.031) and Ensure® (P=0.033). GLP-1 tAUC was significantly higher with dextrose compared to mixed meal (P=0.04) while GIP tAUC was higher with dextrose and mixed meal compared to saline (P<0.05). Changes in tAUC for insulin, amylin, leptin, ghrelin and PYY did not reach significance. Based on these findings, dextrose appears to provide a robust acute glycemic and hormone response and is therefore likely an appropriate oral solution to reproducibly test the impact of various dietary, surgical or pharmacological interventions on glucose and satiety hormone response.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".