Assessment of the mechanisms exerting glucose-lowering effects of dried peas in glucose-intolerant rats
Bibliographic record
Abstract
The present study compared the effects of feeding uncooked pea fractions (embryo v. seed coat) on glucose homeostasis in glucose-intolerant rats and examined potential mechanisms influencing glucose homeostasis. Rats were made glucose intolerant by high-fat feeding, after which diets containing both high-fat and pea fractions were fed for 4 weeks. Rats fed diets containing uncooked pea seed coats low (non-coloured seed coat; NSC) or high (coloured seed coat; CSC) in proanthocyanidins but not embryos had improved oral glucose tolerance (P < 0·05). NSC also lowered fasting and glucose-stimulated insulin secretion (P < 0·05), decreased β-cell mass by 50 % (P < 0·05) and lowered levels of malondialdehyde, a marker of oxidative stress. Furthermore, NSC decreased the mucosal thickness of the colon by 25 % (P < 0·05), which might affect fibre fermentation and other gut functions. Small but statistically significant (P < 0·05) effects consistent with enhanced glucose transport or metabolism were observed in the skeletal muscle of rats fed NSC or CSC, for example, increased levels of AMP-dependent kinase or akt. We conclude that pea seed coats are the fraction exerting beneficial effects on glucose tolerance. Most of the changes were small in amplitude, suggesting that additive effects on multiple tissues may be important. NSC content appeared to have the most beneficial effects in improving glucose homeostasis but our ability to detect the effect of flavonoids may have been limited by their low concentration in the diet.
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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 | 0.000 |
| 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 | 0.001 |
| 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".