Opposing effects on regulated insulin secretion of acute vs chronic stimulation of AMP-activated protein kinase
Bibliographic record
Abstract
AIMS/HYPOTHESIS: Although targeted in extrapancreatic tissues by several drugs used to treat type 2 diabetes, the role of AMP-activated protein kinase (AMPK) in the control of insulin secretion is still debatable. Previous studies have used pharmacological activators of limited selectivity and specificity, and none has examined in primary pancreatic beta cells the actions of the latest generation of highly potent and specific activators that act via the allosteric drug and metabolite (ADaM) site. METHODS: AMPK was activated acutely in islets isolated from C57BL6/J mice, and in an EndoC-βH3 cell line, using three structurally distinct ADaM site activators (991, PF-06409577 and RA089), with varying selectivity for β1- vs β2-containing complexes. Mouse lines expressing a gain-of-function mutation in the γ1 AMPK subunit (D316a) were generated to examine the effects of chronic AMPK stimulation in the whole body, or selectively in the beta cell. RESULTS: dynamics in response to 991 (AUC, p<0.05) and to RA089 at the highest dose (25 μmol/l) at 5.59 min (p<0.05). Although abolished in the absence of AMPK, the effects of 991 were observed in the absence of the upstream kinase, liver kinase B1, further implicating 'amplifying' pathways. In marked contrast, chronic activation of AMPK, either globally or selectively in the beta cell, achieved using a gain-of-function mutant, impaired insulin release in vivo (p<0.05 at 15 min following i.p. injection of 3 mmol/l glucose) and in vitro (p<0.01 following incubation of islets with 17 mmol/l glucose), and lowered glucose tolerance (p<0.001). CONCLUSIONS/INTERPRETATION: AMPK activation exerts complex, time-dependent effects on insulin secretion. These observations should inform the design and future clinical use of AMPK modulators.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".