Role of Phosphatidylinositol 3-Kinaseγ in the β-Cell: Interactions with Glucagon-Like Peptide-1
Bibliographic record
Abstract
Glucagon-like peptide-1 (GLP-1) increases beta-cell function and growth through protein kinase A- and phosphatidylinositol-3-kinase (PI3-K)/protein kinase B, respectively. GLP-1 acts via a G protein-coupled receptor, and PI3-Kgamma is known to be activated by G(betagamma.) Therefore, the role of PI3-Kgamma in the chronic effects of GLP-1 on the beta-cell was investigated using PI3-Kgamma knockout (KO) mice treated with the GLP-1 receptor agonist, exendin-4 (Ex4; 1 nmol/kg sc every 24 h for 14 d). In vivo, glucose and insulin responses were similar in PBS- and Ex4-treated KO and wild-type (WT) mice. However, glucose-stimulated insulin secretion was markedly impaired in islets from PBS-KO mice (P < 0.05), and this was partially normalized by chronic Ex4 treatment (P < 0.05). In contrast, insulin content was increased in PBS-KO islets, and this was paradoxically decreased by Ex4 treatment, compared with the stimulatory effect of Ex4 on WT islets (P < 0.05-0.01). Transfection of INS-1E beta-cells with small interfering RNA for PI3-Kgamma similarly decreased glucose-stimulated insulin secretion (P < 0.01) and increased insulin content. Basal values for beta-cell mass, islet number and proliferation, glucose transporter 2, glucokinase, and insulin receptor substrate-2 were increased in PBS-KO mice (P < 0.05-0.001) and, although they were increased by Ex4 treatment of WT animals (P < 0.05), they were decreased in Ex4-KO mice (P < 0.05-0.01). These findings indicate that PI3-Kgamma deficiency impairs insulin secretion, resulting in compensatory islet growth to maintain normoglycemia. Chronic Ex4 treatment normalizes the secretory defect, thereby relieving the pressure for expansion of beta-cell mass. These studies reveal a new role for PI3-Kgamma as a positive regulator of insulin secretion, and reinforce the importance of GLP-1 for the maintenance of normal beta-cell function.
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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 | 0.000 |
| 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) | 0.001 | 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".