Glycogen Synthase Kinase 3β Is a Negative Regulator of Growth Factor-induced Activation of the c-Jun N-terminal Kinase
Bibliographic record
Abstract
The c-Jun N-terminal kinase (JNK)/stress activated protein kinase is preferentially activated by stress stimuli. Growth factors, particularly ligands for G protein-coupled receptors, usually induce only modest JNK activation, although they may trigger marked activation of the related extracellular signal-regulated kinase. In the present study, we demonstrated that homozygous disruption of glycogen synthase kinase 3beta (GSK-3beta) dramatically sensitized mouse embryonic fibroblasts (MEFs) to JNK activation induced by lysophosphatidic acid (LPA) and sphingosine-1-phosphate, two prototype ligands for G protein-coupled receptors. To a lesser degree, a lack of GSK-3beta also potentiated JNK activation in response to epidermal growth factor. In contrast, the absence of GSK-3beta decreased UV light-induced JNK activation. The increased JNK activation induced by LPA in GSK-3beta null MEFs was insufficient to trigger apoptotic cell death or growth inhibition. Instead, the increased JNK activation observed in GSK-3beta-/- MEFs was associated with an increased proliferative response to LPA, which was reduced by the inhibition of JNK. Ectopic expression of GSK-3beta in GSK-3beta-negative MEFs restrained LPA-triggered JNK phosphorylation and induced a concomitant decrease in the mitogenic response to LPA compatible with GSK-3beta through the inhibition of JNK activation, thus limiting LPA-induced cell proliferation. Mutation analysis indicated that GSK-3beta kinase activity was required for GSK-3beta to optimally inhibit LPA-stimulated JNK activation. Thus GSK-3beta serves as a physiological switch to specifically repress JNK activation in response to LPA, sphingosine-1-phosphate, or the epidermal growth factor. These results reveal a novel role for GSK-3beta in signal transduction and cellular responses to growth factors.
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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) | 0.001 | 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 | 0.000 |
| 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".