Modulation of Acetylcholine-Stimulated Insulin Release by Glucose and Gastric Inhibitory Polypeptide
Bibliographic record
Abstract
The interactions of glucose, acetylcholine and gastric inhibitory polypeptide in the regulation of insulin secretion were examined using the in situ perfused rat pancreas. Acetylcholine (1 x 10(-6) M) had no effect on the release of immunoreactive insulin in the presence of 2.2 x 10(-3) M glucose. However, in the presence of 4.4, 6.6 or 8.9 x 10(-3) M glucose, the same concentration of acetylcholine stimulated insulin secretion approximately fourfold. At the highest glucose concentration tested (17.8 x 10(-3) M), the stimulatory effect of acetylcholine on insulin release was less pronounced. The insulin response to acetylcholine was potentiated by the presence of gastric inhibitory polypeptide. This potentiation was most marked when the peptide was present at a concentration of 1 x 10(-9) M, whereas the effect of concomitant infusion of acetylcholine and 2 x 10(-10) M gastric inhibitory polypeptide was only slightly greater than additive. Both atropine (1 x 10(-6) M) and hexamethonium (1 x 10(-4) M) inhibited the insulin response to acetylcholine. However, neither of these cholinergic antagonists had a significant effect on glucose- or gastric inhibitory polypeptide-stimulated insulin secretion. These results demonstrate that the insulinotropic action of acetylcholine is glucose-dependent. A synergistic interaction may exist between acetylcholine and gastric inhibitory polypeptide at the beta-cell which does not involve glucose or gastric inhibitory polypeptide acting on cholinergic receptors in the pancreas. Cholinergic stimulation of insulin secretion in the perfused rat pancreas appears to be mediated by both muscarinic receptors on the beta-cell and nicotinic receptors, presumably on intrapancreatic ganglia.
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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) | 0.001 | 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".