Altered Interaction Between PSD‐95 and the NMDA Receptor Following Transient Global Ischemia
Bibliographic record
Abstract
The postsynaptic density (PSD) is a cytoskeletal specialization involved in the anchoring of neurotransmitter receptors and in regulating the response of postsynaptic neurons to synaptic stimulation. The postsynaptic protein PSD-95 binds to NMDA receptor subunits NR2A and NR2B and to signaling molecules such as neuronal nitric oxide synthase and p135synGAP. We investigated the effects of transient cerebral ischemia on protein interactions involving PSD-95 and the NMDA receptor in the rat hippocampus. Ischemia followed by reperfusion resulted in a decrease in the solubility of the NMDA receptor and PSD-95 in 1% sodium deoxycholate, the decrease being greater in the vulnerable CA1 hippocampal subfield than in the less sensitive CA3/dentate gyrus regions. Solubilization of the kainic acid receptor GluR6/7 and the PSD-95 binding proteins, neuronal nitric oxide synthase and p135synGAP, also decreased following ischemia. The association between PSD-95 and NR2A and NR2B, as indicated by coimmunoprecipitation, was less in postischemic samples than in sham-operated controls. Ischemia also resulted in a decrease in the size of protein complexes containing PSD-95, but had only a small effect on the size distribution of complexes containing the NMDA receptor. The results indicate that molecular interactions involving PSD-95 and the NMDA receptor are modified by an ischemic challenge.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".