Adiponectin-induced ERK and Akt Phosphorylation Protects against Pancreatic Beta Cell Apoptosis and Increases Insulin Gene Expression and Secretion*
Bibliographic record
Abstract
The functional impact of adiponectin on pancreatic beta cells is so far poorly understood. Although adiponectin receptors (AdipoR1/2) were identified, their involvement in adiponectin-induced signaling and other molecules involved is not clearly defined. Therefore, we investigated the role of adiponectin in beta cells and the signaling mediators involved. MIN6 beta cells and mouse islets were stimulated with globular (2.5 μg/ml) or full-length (5 μg/ml) adiponectin under serum starvation, and cell viability, proliferation, apoptosis, insulin gene expression, and secretion were measured. Lysates were subjected to Western blot analysis to determine phosphorylation of AMP-activated protein kinase (AMPK), Akt, or ERK. Functional significance of signaling was confirmed using dominant negative mutants or pharmacological inhibitors. Participation of AdipoRs was assessed by overexpression or siRNA. Adiponectin failed to activate AMPK after 10 min or 1- and 24-h stimulation. ERK was significantly phosphorylated after 24-h treatment with adiponectin, whereas Akt was activated at all time points examined. 24-h stimulation with adiponectin significantly increased cell viability by decreasing cellular apoptosis, and this was prevented by dominant negative Akt, wortmannin (PI3K inhibitor), and U0126 (MEK inhibitor). Moreover, adiponectin regulated insulin gene expression and glucose-stimulated insulin secretion, which was also prevented by wortmannin and U0126 treatment. Interestingly, the data also suggest adiponectin-induced changes in Akt and ERK phosphorylation and caspase-3 may occur independent of the level of AdipoR expression. This study demonstrates a lack of AMPK involvement and implicates Akt and ERK in adiponectin signaling, leading to protection against apoptosis and stimulation of insulin gene expression and secretion in pancreatic beta cells.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".