Role of the M <sub>3</sub> muscarinic acetylcholine receptor in β‐cell function and glucose homeostasis
Bibliographic record
Abstract
The release of insufficient amounts of insulin in the presence of elevated blood glucose levels is one of the key features of type 2 diabetes. Various lines of evidence indicate that acetylcholine (ACh), the major neurotransmitter of the parasympathetic nervous system, can enhance glucose-stimulated insulin secretion from pancreatic beta-cells. Studies with isolated islets prepared from whole body M(3) muscarinic ACh receptor knockout mice showed that cholinergic amplification of glucose-dependent insulin secretion is exclusively mediated by the M(3) muscarinic receptor subtype. To investigate the physiological relevance of this muscarinic pathway, we used Cre/loxP technology to generate mutant mice that lack M(3) receptors only in pancreatic beta-cells. These mutant mice displayed impaired glucose tolerance and significantly reduced insulin secretion. In contrast, transgenic mice overexpressing M(3) receptors in pancreatic beta-cells showed a pronounced increase in glucose tolerance and insulin secretion and were resistant to diet-induced glucose intolerance and hyperglycaemia. These findings indicate that beta-cell M(3) muscarinic receptors are essential for maintaining proper insulin secretion and glucose homeostasis. Moreover, our data suggest that enhancing signalling through beta-cell M(3) muscarinic receptors may represent a new avenue in the treatment of glucose intolerance and type 2 diabetes.
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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".