Cross-Talk between Phosphatidylinositol 3-Kinase/AKT and c-Jun NH2-Terminal Kinase Mediates Survival of Isolated Human Islets
Bibliographic record
Abstract
Therapeutic strategies aimed at the inhibition of specific cell death mechanisms may increase islet yield and improve cell viability and function after routine isolation. The aim of the current study was to explore the possibility of AKT-JNK cross-talk in islets after isolation and the relevance of c-jun NH2-terminal kinases (JNK) suppression on islet survival. After routine isolation, increased AKT activity correlated with suppression of JNK activation, suggesting that they may be related events. Indeed, the increase in AKT activation after isolation correlated with suppression of apoptosis signal-regulating kinase 1 (ASK1), a kinase acting upstream of JNK, by phosphorylation at Ser83. We therefore examined whether modulators of phosphatidylinositol 3-kinase (PI3K)/AKT signaling affected JNK activation. PI3K inhibition led to increased JNK phosphorylation and islet cell death, which could be reversed by the specific JNK inhibitor SP600125. In addition, IGF-I suppressed cytokine-mediated JNK activation in a PI3K-dependent manner. We also demonstrate that inhibition of PI3K rendered islets more susceptible to cytokine-mediated cell death. SP600125 transiently protected islets from cytokine-mediated cell death, suggesting that JNK may not be necessary for cytokine-induced cell death. When administered immediately after isolation, SP600125 improved islet survival and function, even 48 h after removal of SP600125, suggesting that JNK inhibition by SP600125 may be a viable strategy for improving isolated islet survival. Taken together, these results demonstrate that PI3K/AKT suppresses the JNK pathway in islets, and this cross-talk represents an important antiapoptotic consequence of PI3K/AKT activation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".