New insights into the molecular mechanisms of priming of insulin exocytosis
Bibliographic record
Abstract
Exocytosis of insulin vesicles in the pancreatic beta-cell involves a sequence of regulated events, whose normal function and efficient adaptation to increased demand are essential for the maintenance of glucose homeostasis. These exocytotic events comprise the trafficking and docking of vesicles to the plasma membrane, followed by fusion triggered by Ca(2+). Recent studies have unravelled post-docking steps mediated by novel factors, which, by their interactions with soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE)- and SNARE-associated proteins, confer the docked vesicles fusion competence. These priming steps define the releasable pool of insulin vesicles, which accounts for the first phase of insulin secretion, and controls the rate at which vesicles are replenished for the second phase of secretion. This article aims to summarize what is currently known about the mechanisms that underlie the priming activity of these proteins, focusing on Munc13, a topic to which we have made some recent contributions. Abnormal glucose homeostasis in type 2 diabetes is because of the failure of islet beta-cells to augment insulin secretion sufficiently to compensate for reduced insulin sensitivity. A better understanding of the priming steps may help develop novel approaches to increase insulin secretory capacity and thereby prevent the progression to type 2 diabetes.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".