Inhibitory Phosphorylation of GSK-3 by CaMKII Couples Depolarization to Neuronal Survival
Bibliographic record
Abstract
Glycogen synthase kinase-3 (GSK-3) plays a critical role in neuronal apoptosis. The two mammalian isoforms of the kinase, GSK-3α and GSK-3β, are inhibited by phosphorylation at Ser-21 and Ser-9, respectively. Depolarization, which is vital for neuronal survival, causes both an increase in Ser-21/9 phosphorylation and an inhibition of GSK-3α/β. However, the role of GSK-3 phosphorylation in depolarization-dependent neuron survival and the signaling pathway contributing to GSK-3 phosphorylation during depolarization remain largely unknown. Using several approaches, we showed that both isoforms of GSK-3 are important for mediating neuronal apoptosis. Nonphosphorylatable GSK-3α/β mutants (S21A/S9A) promoted apoptosis, whereas a peptide encompassing Ser-9 of GSK-3β protected neurons in a phosphorylation-dependent manner; these results indicate a critical role for Ser-21/9 phosphorylation on depolarization-dependent neuron survival. We found that Ser-21/9 phosphorylation of GSK-3 was mediated by Ca(2+)/calmodulin-dependent protein kinase II (CaMKII) but not by Akt/PKB, PKA, or p90(RSK). CaMKII associated with and phosphorylated GSK-3α/β. Furthermore, the pro-survival effect of CaMKII was mediated by GSK-3 phosphorylation and inactivation. These findings identify a novel Ca(2+)/calmodulin/CaMKII/GSK-3 pathway that couples depolarization to neuronal survival.
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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) | 0.001 | 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".