Calpain-Regulated p35/cdk5 Plays a Central Role in Dopaminergic Neuron Death through Modulation of the Transcription Factor Myocyte Enhancer Factor 2
Bibliographic record
Abstract
The mechanisms underlying dopamine neuron loss in Parkinson's disease (PD) are not clearly defined. Here, we delineate a pathway by which dopaminergic loss induced by 1-methyl-4-phenyl 1,2,3,6 tetrahydropyridine (MPTP) is controlled in vivo. We reported previously that calpains play a central required role in dopamine loss after MPTP treatment. Here, we provide evidence that the downstream effector pathway of calpains is through cyclin-dependent kinase 5 (cdk5)-mediated modulation of the transcription factor myocyte enhancer factor 2 (MEF2). We show that MPTP-induced conversion of the cdk5 activator p35 to a pathogenic p25 form is dependent on calpain activity in vivo. In addition, p35 deficiency attenuates MPTP-induced dopamine neuron loss and behavioral outcome. Moreover, MEF2 is phosphorylated on Ser444, an inactivating site, after MPTP treatment. This phosphorylation is dependent on both calpain and p35 activity, consistent with the model that calpain-mediated activation of cdk5 results in phosphorylation of MEF2 in vivo. Finally, we provide evidence that MEF2 is critical for dopaminergic loss because "cdk5 phosphorylation site mutant" of MEF2D provides neuroprotection in an MPTP mouse model of PD. Together, these data indicate that calpain-p35-p25/cdk5-mediated inactivation of MEF2 plays a critical role in dopaminergic loss in vivo.
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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 | 0.000 |
| 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".