Muscarinic Receptors Control Glucagon-Like Peptide 1 Secretion by Human Endocrine L Cells
Bibliographic record
Abstract
Glucagon-like peptide 1 (GLP-1) released from distal intestinal endocrine L cells after food intake is a potent glucose-dependent stimulant of insulin secretion. Plasma levels of GLP-1 rise rapidly after nutrient ingestion through an indirect mechanism triggered from the proximal intestine and involving the vagus nerve. Our previous studies showed the involvement of M1 muscarinic receptors expressed by the L cells in the regulation of postprandial GLP-1 secretion in rats. The goal of this study was to explore the involvement of muscarinic receptors in the regulation of GLP-1 secretion by human L cells using a newly described human L cell line (NCI-H716). Phorbol 12-myristate 13-acetate (positive control) stimulated GLP-1 secretion to 252 +/- 38% of the control (P < 0.001). Bethanechol, a nonselective muscarinic agonist, significantly stimulated GLP-1 secretion to 187 +/- 20% of the control (P < 0.01, n = 8). Pirenzepine (M1 antagonist; 10-1000 microM) and gallamine (M2 antagonist; 10-1000 microM) completely inhibited bethanechol-induced GLP-1 secretion, whereas 4-diphenylacetoxy-N-methylpiperidine (M3 antagonist) had no effect on bethanechol-stimulated GLP-1 secretion. McN-A-343 (M1 muscarinic agonist) dose dependently stimulated GLP-1 secretion (to 252 +/- 50% of control at 1000 microM; P < 0.01), whereas oxotremorine (M3 agonist) had no effect. M1, M2, and M3 muscarinic receptors were shown to be expressed in NCI-H716 cells by Western blot, immunohystochemistry, and RT-PCR. Expression of the M1, M2, and M3 muscarinic receptor subtypes was also confirmed in paraffin-embedded human small intestine sections by double immunofluorescent staining. These results demonstrate the role of M1 and M2 muscarinic receptors expressed by human L cells in the control of GLP-1 secretion.
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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 | 0.001 |
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".