Depolarization Induces NR2A Tyrosine Phosphorylation and Neuronal Apoptosis
Bibliographic record
Abstract
BACKGROUND: Cytosol Ca2+ overload plays a vital role in ischemic neuronal damage, which is largely contributed by the Ca2+ influx through L-type voltage-gated calcium channels (L-VGCCs) and N-methyl-D-aspartate (NMDA) type glutamate receptors. In this article, L-VGCCs were activated by depolarization to investigate the cross-talk between NMDA receptors and L-VGCCs. METHODS: Depolarization was induced by 20 minutes incubation of 75 mM KCl in cultured rat cortical neuron. Apoptosis-like neuronal death was detected by DAPI staining. Tyrosine phosphorylation of NMDA receptor subunit 2A (NR2A), interactions of Src and NR2A were detected by immunoblot and immunoprecipitation. RESULTS: Depolarization induced cortical neuron apoptosis-like cell death after 24 hours of restoration. The apoptosis was partially inhibited by 5 mM EGTA, 100 μM Cd2+, 10 μM nimodipine, 100 μM genistein, 20 μM MK-801, 2 μM PP2 and combined treatment of nimodipine and MK-801. NR2A tyrosine phosphorylation increased after depolarization, and the increase was inhibited by the drugs listed above. Moreover, non-receptor tyrosine kinase Src bound with NR2A after depolarization and restoration. The binding was also inhibited by the drugs listed above. CONCLUSIONS: The results indicated that depolarization-induced neuronal death might be due to extracellular Ca2+ influx through L-VGCCs and subsequently Src activationmediated NR2A tyrosine phosphorylation.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".