Modulation of NMDA‐mediated excitotoxicity by protein kinase C
Bibliographic record
Abstract
Excessive activation of N-methyl-D-aspartate (NMDA) receptors leads to cell death in human embryonic kidney-293 (HEK) cells which have been transfected with recombinant NMDA receptors. To evaluate the role of protein kinase C (PKC) activation in NMDA-mediated toxicity, we have analyzed the survival of transfected HEK cells using trypan blue exclusion. We found that NMDA-mediated death of HEK cells transfected with NR1/NR2A subunits was increased by exposure to phorbol esters and reduced by inhibitors of PKC activation, or PKC down-regulation. The region of NR2A that provides the PKC-induced enhancement of cell death was localized to a discrete segment of the C-terminus. Use of isoform-specific PKC inhibitors showed that Ca(2+)- and lipid-dependent PKC isoforms (cPKCs), specifically PKCbeta1, was responsible for the increase in cell death when phorbol esters were applied prior to NMDA in these cells. PKC activity measured by an in vitro kinase assay was also increased in NR1A/NR2A-transfected HEK cells following NMDA stimulation. These results suggest that PKC acts on the C-terminus of NR2A to accentuate cell death in NR1/NR2A-transfected cells and demonstrate that this effect is mediated by cPKC isoforms. These data indicate that elevation of cellular PKC activity can increase neurotoxicity mediated by NMDA receptor activation.
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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".