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Increased phosphorylation and redistribution of NMDA receptors between synaptic lipid rafts and post‐synaptic densities following transient global ischemia in the rat brain

2005· article· en· W2062416537 on OpenAlexafffund
Shintaro Besshoh, Damanpreet Bawa, Lucy Teves, M. Christopher Wallace, James W. Gurd

Bibliographic record

VenueJournal of Neurochemistry · 2005
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsToronto Western HospitalThe Scarborough HospitalUniversity of Toronto
FundersCanadian Stroke NetworkHeart and Stroke Foundation of Canada
KeywordsLipid raftPhosphorylationTyrosine phosphorylationCell biologyNMDA receptorBiologyBiophysicsChemistryBiochemistryReceptorSignal transduction

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.516

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.297
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations131
Published2005
Admission routes2
Has abstractyes

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