Regulation of PINK1 by NR2B‐containing NMDA receptors in ischemic neuronal injury
Bibliographic record
Abstract
Dysfunction of PTEN-induced kinase-1 (PINK1) is implicated in neurodegeneration. We report here that oxygen-glucose deprivation (OGD), an in vitro insult mimicking ischemic neuron injury, resulted in a significant reduction of PINK1 protein expression in cultured cortical neurons. The decrease of PINK1 expression was blocked by the antagonists of NMDA receptors. We revealed that the overactivation of NR2B-containing NMDA receptors (NR2BRs) was responsible for the OGD-induced PINK1 reduction. The overactivated NR2BRs also inhibited the phosphorylation, but not the protein expression, of the cell survival-promoting kinase Akt after OGD insult, indicating that OGD-induced reduction of PINK1 protein is specific in the injury paradigm. We further showed that enhancing the protein expression of PINK1 antagonized OGD-induced reduction of Akt phosphorylation, suggesting that Akt may be a downstream target of PINK1 in ischemic neuron injury. Importantly, we provided evidence that both NR2BR antagonist and PINK1 over-expression protected against OGD-induced neuronal death. These results suggest that the overactivation of NR2BRs may contribute to ischemic neuron death through suppressing PINK1-dependent survival signaling. Thus, selectively antagonizing NR2BR signal pathway-induced neurotoxicity may be a potential neuroprotection strategy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".