Metabolic and Hormonal Response to a Feed-challenge Test in Lean and Overweight Dogs
Bibliographic record
Abstract
BACKGROUND: Obese dogs risk poor life quality, creating a need for increased knowledge of metabolism in overweight dogs. OBJECTIVES: Investigate postprandial metabolic and hormonal responses to a high-fat mixed-meal in dogs and responses of lean versus overweight dogs. ANIMALS: Twenty-eight healthy intact male Labrador Retrievers were included. METHODS: Prospective observational study. Twelve dogs were grouped as lean (body condition score (BCS 4-5), 10 as slightly overweight (BCS 6), and 6 as overweight (BCS 6.5-8) on a 9-point scale. After an overnight fast, urine and blood samples were collected. Dogs were then fed a high-fat mixed-meal, and blood was collected hourly for 4 hours and urine after 3 hours. RESULTS: Postprandial concentrations of insulin and glucagon were increased at 1 hour (both P < 0.0001), triglycerides at 2 hours (P < 0.0001), and glucose at 3 hours (P = 0.004); and all remained increased throughout the feed-challenge in all dogs. Postprandial urine cortisol/creatinine ratio was higher than fasting values (P = 0.001). Comparing between groups, there was an overall higher triglyceride response in overweight compared to lean (P = 0.001) and slightly overweight (P = 0.015) dogs. Overweight dogs also had higher fasting cortisol/creatinine ratio compared to lean dogs (P = 0.024). CONCLUSIONS AND CLINICAL IMPORTANCE: Postprandial responses of dogs to a high-fat mixed-meal were similar to those previously reported in people. The higher postprandial triglyceride response and fasting cortisol/creatinine ratio in the overweight dogs could be early signs of metabolic imbalance. Thus, although overweight dogs often appear healthy, metabolic alterations might be present.
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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 | 0.001 | 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".