Conditional Disruption of Calpain in the CNS Alters Dendrite Morphology, Impairs LTP, and Promotes Neuronal Survival following Injury
Bibliographic record
Abstract
Ubiquitous classical (typical) calpains, calpain-1 and calpain-2, are Ca(+2)-dependent cysteine proteases, which have been associated with numerous physiological and pathological cellular functions. However, a clear understanding of the role of calpains in the CNS has been hampered by the lack of appropriate deletion paradigms in the brain. In this study, we describe a unique model of conditional deletion of both calpain-1 and calpain-2 activities in mouse brain, which more definitively assesses the role of these ubiquitous proteases in brain development/function and pathology. Surprisingly, we show that these calpains are not critical for gross CNS development. However, calpain-1/calpain-2 loss leads to reduced dendritic branching complexity and spine density deficits associated with major deterioration in hippocampal long-term potentiation and spatial memory. Moreover, calpain-1/calpain-2-deficient neurons were significantly resistant to injury induced by excitotoxic stress or mitochondrial toxicity. Examination of downstream target showed that the conversion of the Cdk5 activator, p35, to pathogenic p25 form, occurred only in the presence of calpain and that it played a major role in calpain-mediated neuronal death. These findings unequivocally establish two central roles of calpain-1/calpain-2 in CNS function in plasticity and neuronal death.
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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 | 0.001 |
| 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".