Increased phosphorylation and redistribution of NMDA receptors between synaptic lipid rafts and post‐synaptic densities following transient global ischemia in the rat brain
Bibliographic record
Abstract
Ischemia results in increased phosphorylation of NMDA receptors. To investigate the possible role of lipid rafts in this increase, lipid rafts and post-synaptic densities (PSDs) were isolated by the extraction of rat brain synaptosomes with Triton X-100 followed by sucrose density gradient centrifugation. Lipid rafts accounted for the majority of PSD-95, whereas SAP102 was predominantly located in PSDs. Between 50 and 60% of NMDA receptors were associated with lipid rafts. Greater than 85-90% of Src and Fyn were present in lipid rafts, whereas Pyk2 was mainly associated with PSDs. Lipid rafts and PSDs were isolated from animals subjected to 15 min of global ischemia followed by 6 h of recovery. Ischemia did not affect the yield, density, flotillin-1 or cholesterol content of lipid rafts. Following ischemia, the phosphorylation of NR1 by protein kinase C and tyrosine phosphorylation of NR2A and NR2B was increased in both lipid rafts and PSDs, with a greater increase in tyrosine phosphorylation occurring in the raft fraction. Following ischemia, NR1, NR2A and NR2B levels were elevated in PSDs and reduced in lipid rafts. The findings are consistent with a model involving close interaction between lipid rafts and PSDs and a role for lipid rafts in ischemia-induced signaling pathways.
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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) | 0.001 | 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".