Rescuing the Subprime Meltdown in Insulin Exocytosis in Diabetes
Bibliographic record
Abstract
Neuroendocrine pancreatic islet beta-cells secrete the hormone insulin in response to glucose stimulation and adapt efficiently to increased demand by peripheral tissues to maintain glucose homeostasis. Insulin is packed within dense-core granules, which traffic and dock onto the plasma membrane whereby a Ca(2+) stimulus evokes exocytosis by soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE), complex-mediated, membrane fusion. Recent studies have unveiled postdocking steps mediated by "priming" factors that influence SNARE complex assembly to confer fusion readiness to the docked granules. This review will summarize recent insights into the priming role for Munc13 in the exocytosis of insulin granules. We present evidence for the interaction of Munc13-1 with exocytotic substrates involved in cAMP-mediated potentiation of insulin release, the latter we show to mediate enhanced granule-to-granule fusion events underlying compound exocytosis. We thus also further review the current understanding of granule-to-granule fusion. As agents acting on cAMP signaling are clinically used to augment insulin release in diabetes, this better understanding of priming steps may reveal additional novel therapeutic strategies to increase the capacity for insulin release to improve the treatment of 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".