Dietary energy sources affect insulin sensitivity and β‐cell responsiveness of trained Arabian geldings during endurance exercise
Bibliographic record
Abstract
Adaptation to diets which replace carbohydrates with fat as an energy source have been shown to avoid insulin resistance and improve metabolic regulation during exercise. This study compared the effects of diet and moderate‐intensity exercise on glucose and insulin concentrations in 12 trained Arabian geldings. Six Arabians were adapted for 8 weeks to a feed high in sugar and starch (SS) and six were adapted to a feed rich in fat and fibre (FF). All horses were exercise‐trained prior to and throughout feed adaptation. Horses were sampled between 0900 and 1000 h at rest and during moderate‐intensity exercise on a treadmill at 57% of their lactate threshold following 25 min of warm‐up. Plasma was analysed for glucose and insulin. Basal proxies for insulin sensitivity (LRIB = log[100/basal insulin]) and pancreatic β‐cell response to circulating glucose (MIRG = log[(100·basal insulin)/(basal glucose – 50 mg/dL)]) were calculated. Basal insulin tended to be lower in FF adapted horses (p = 0.068) and was lower during exercise as compared to rest in FF horses (p = 0.013) but not SS horses (p = 0.44). Plasma glucose concentration was lower in FF horses (p < 0.001) and increased during exercise for SS adapted horses (p = 0.015) but not FF horses (p = 0.38). Insulin sensitivity as determined by LRIB was higher during exercise (p = 0.019) for all 12 horses while β‐cell response as determined by MIRG was lower (p = 0.006). Arabians adapted to the FF diet also had higher LRIB (p = 0.047) but diet had no affect on MIRG (p = 0.20). Exercise tended to increase (p = 0.11) LRIB more in FF horses (34%) than SS horses (11%). These differences indicate that horses adapted to high carbohydrate diets have lower insulin sensitivity and impaired metabolic regulation involving insulin signalling. These effects are avoided in horses adapted to the FF feed, with potential benefits to their health and endurance exercise performance.
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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) | 0.000 | 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 | 0.000 |
| 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".