NMDA Receptor Subunits Have Differential Roles in Mediating Excitotoxic Neuronal Death Both<i>In Vitro</i>and<i>In Vivo</i>
Bibliographic record
Abstract
Well-documented experimental evidence from both in vitro and in vivo models of stroke strongly supports the critical involvement of NMDA receptor-mediated excitotoxicity in neuronal damage after stroke. Despite this, the results of clinical trials testing NMDA receptor antagonists as neuroprotectants after stroke and brain trauma have been discouraging. Here, we report that in mature cortical cultures, activation of either synaptic or extrasynaptic NR2B-containing NMDA receptors results in excitotoxicity, increasing neuronal apoptosis. In contrast, activation of either synaptic or extrasynaptic NR2A-containing NMDA receptors promotes neuronal survival and exerts a neuroprotective action against both NMDA receptor-mediated and non-NMDA receptor-mediated neuronal damage. A similar opposing action of NR2B and NR2A in mediating cell death and cell survival was also observed in an in vivo rat model of focal ischemic stroke. Moreover, we found that blocking NR2B-mediated cell death was effective in reducing infarct volume only when the receptor antagonist was given before the onset of stroke and not 4.5 h after stroke. In great contrast, activation of NR2A-mediated cell survival signaling with administration of either glycine alone or in the presence of NR2B antagonist significantly attenuated ischemic brain damage even when delivered 4.5 h after stroke onset. Together, the present work provides a molecular basis for the dual roles of NMDA receptors in promoting neuronal survival and mediating neuronal damage and suggests that selective enhancement of NR2A-containing NMDA receptor activation with glycine may constitute a promising therapy for stroke.
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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".