PI3 kinases p110α and PI3K-C2β negatively regulate cAMP via PDE3/8 to control insulin secretion in mouse and human islets
Bibliographic record
Abstract
OBJECTIVES: Phosphatidylinositol-3-OH kinase (PI3K) signalling in the endocrine pancreas contributes to glycaemic control. However, the mechanism by which PI3K modulates insulin secretion from the pancreatic beta cell is poorly understood. Thus, our objective was two-fold; to determine the signalling pathway by which acute PI3K inhibition enhances glucose-stimulated insulin secretion (GSIS) and to examine the role of this pathway in islets from type-2 diabetic (T2D) donors. METHODS: Isolated islets from mice and non-diabetic or T2D human donors, or INS 832/13 cells, were treated with inhibitors of PI3K and/or phosphodiesterases (PDEs). The expression of PI3K-C2β was knocked down using siRNA. We measured insulin release, single-cell exocytosis, intracellular Ca(2+) responses ([Ca(2+)]i) and Ca(2+) channel currents, intracellular cAMP concentrations ([cAMP]i), and activation of cAMP-dependent protein kinase A (PKA) and protein kinase B (PKB/AKT). RESULTS: The non-specific PI3K inhibitor wortmannin amplifies GSIS, raises [cAMP]i and activates PKA, but is without effect in T2D islets. Direct inhibition of specific PDE isoforms demonstrates a role for PDE3 (in humans and mice) and PDE8 (in mice) downstream of PI3K, and restores glucose-responsiveness of T2D islets. We implicate a role for the Class II PI3K catalytic isoform PI3K-C2β in this effect by limiting beta cell exocytosis. CONCLUSIONS: PI3K limits GSIS via PDE3 in human islets. While inhibition of p110α or PIK-C2β signalling per se, may promote nutrient-stimulated insulin release, we now suggest that this signalling pathway is perturbed in islets from T2D donors.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".