The autonomic nervous system regulates pancreatic β-cell proliferation in adult male rats
Bibliographic record
Abstract
The pancreatic β-cell responds to changes in the nutrient environment to maintain glucose homeostasis by adapting its function and mass. Nutrients can act directly on the β-cell and also indirectly through the brain via autonomic nerves innervating islets. Despite the importance of the brain-islet axis in insulin secretion, relatively little is known regarding its involvement in β-cell proliferation. We previously demonstrated that prolonged infusions of nutrients in rats provoke a dramatic increase in β-cell proliferation in part because of the direct action of nutrients. Here, we addressed the contribution of the autonomic nervous system. In isolated islets, muscarinic stimulation increased, whereas adrenergic stimulation decreased, glucose-induced β-cell proliferation. Blocking α-adrenergic receptors reversed the effect of epinephrine on glucose + nonesterified fatty acids (NEFA)-induced β-cell proliferation, whereas activation of β-adrenergic receptors was without effect. Infusion of glucose + NEFA toward the brain stimulated β-cell proliferation, and this effect was abrogated following celiac vagotomy. The increase in β-cell proliferation following peripheral infusions of glucose + NEFA was not inhibited by vagotomy or atropine treatment but was blocked by coinfusion of epinephrine. We conclude that β-cell proliferation is stimulated by parasympathetic and inhibited by sympathetic signals. Whereas glucose + NEFA in the brain stimulates β-cell proliferation through the vagus nerve, β-cell proliferation in response to systemic nutrient excess does not involve parasympathetic signals but may be associated with decreased sympathetic tone.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.002 | 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".