Activation of caspase‐6 and cleavage of caspase‐6 substrates is an early event in NMDA receptor–mediated excitotoxicity
Bibliographic record
Abstract
Excitotoxicity, due to overstimulation of N-methyl D-aspartate receptors (NMDARs), has a pivotal role in many neurological disorders. However, NMDAR antagonists often cause side effects, and identifying more druggable therapeutic targets for NMDAR excitotoxicity is an important goal. Activation of caspases is a downstream effect of excitotoxicity that may be critically involved in NMDAR-mediated cell death. Caspase-6 (casp6) in particular has been shown to play a key role in the pathogenesis of stroke, Huntington disease, and Alzheimer disease. Using N-methyl D-aspartate (NMDA)-induced excitotoxic injuries of primary rat neurons, we demonstrate that there is an early increase in caspase profiles after an excitotoxic event at the level of mRNA, protein, and activity. Casp6 is elevated and activated first, followed by caspase-8 and caspase-3. Similarly, known casp6 substrates huntingtin, as well as novel casp6 substrates serine/threonine kinase 3 and death domain-associated protein, are cleaved in similar temporal patterns post NMDA. On the basis of these data, we propose that casp6 may be an initiator caspase in apoptotic cascades leading to neuronal death after an excitotoxic event and suggest casp6 as a potential therapeutic target for neurological disorders where NMDAR-mediated excitotoxicity has been shown to play a role.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".