Effect of an extruded pea or rice diet on postprandial insulin and cardiovascular responses in dogs
Bibliographic record
Abstract
Peas are increasing in popularity as a source of carbohydrate, protein and fibre in extruded canine diets. The aim of this study was to test the health effects of two canine diets with identical macronutrient profiles, but containing either yellow field peas or white rice as the carbohydrate source on metabolism, cardiovascular outcomes and adiposity. First, the acute glycemic, insulinemic and cardiovascular responses to the pea- or rice-based diets were determined in normal weight beagles (n = 7 dogs). The glycemic index did not differ between the pea diet (56 ± 12) and rice diet (63 ± 9). Next, obese beagles (n = 9) were fed the yellow field pea diet or white rice diet ad libitum for 12 weeks in a crossover study. Adiposity (measured using computed tomography), metabolic (oral glucose tolerance test, plasma leptin, adiponectin, C-reactive protein) and cardiovascular assessments (echocardiography and blood pressure) were performed before and after each crossover study period. After 12 weeks on each diet, peak insulin (p = 0.05) and area under the curve (AUC) for insulin after a 10 g oral glucose tolerance test (p = 0.05) were lower with the pea than the rice diet. Diet did not show a significant effect on body weight, fat distribution, cardiovascular variables, adiponectin or leptin. In conclusion, a diet containing yellow field peas reduced the postprandial insulin response after glucose challenge in dogs despite continued obesity, indicating improved metabolic health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".