Resistant starch intake at breakfast affects postprandial responses in type 2 diabetics and enhances the glucose-dependent insulinotropic polypeptide – insulin relationship following a second meal
Bibliographic record
Abstract
Resistant starch (RS) consumption can modulate postprandial metabolic responses, but its effects on carbohydrate (CHO) handling in type 2 diabetics (T2D) are unclear. It was hypothesized that a bagel high in RS would improve glucose and insulin homeostasis following the 1st meal, regardless of the amount of available CHO, and that in association with incretins, the effects would carry over to a 2nd meal. Using a randomized crossover design, 12 T2D ingested four different bagel treatments (their 1st meal) determined by available CHO and the weight or amount of bagel consumed: treatment A, without RS (50 g of available CHO); treatment B, with RS (same total CHO as in A); treatment C, with RS (same available CHO as in A); and treatment D, with the same RS as in B and available CHO as in A and C. A standard 2nd meal was ingested 3 h later. Following the first meal, B elicited a lower glucose incremental area under the curve (iAUC) than C (P < 0.05), D (P < 0.05), and A (trend; P = 0.07), lower insulin iAUC than A (P < 0.05) and C (P < 0.05), and lower glucose-dependent insulinotropic polypeptide (GIP) iAUC than A (P < 0.05). There was a positive correlation (P < 0.05) between GIP and insulin iAUCs after the 2nd meal, and C had a 3 times greater slope than the other treatments (r = 0.91, P < 0.001), yet lacked a significant concomitant improvement in glucose disposal. These results show that for the 1st meal, RS was effective when it replaced a portion of the available CHO, while ingesting more RS influenced the GIP-insulin axis following the 2nd meal.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".