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Record W2030487055 · doi:10.1371/journal.pone.0112170

FRET-FLIM Investigation of PSD95-NMDA Receptor Interaction in Dendritic Spines; Control by Calpain, CaMKII and Src Family Kinase

2014· article· en· W2030487055 on OpenAlexafffund
Kim Doré, Simon Labrecque, Christian Tardif, Paul De Koninck

Bibliographic record

VenuePLoS ONE · 2014
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsInstitut Universitaire en Santé Mentale de QuébecUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsNMDA receptorDendritic spineFörster resonance energy transferCalpainSynaptic plasticityCell biologyBiologySrc family kinaseHippocampal formationNeuroscienceKinaseReceptorProto-oncogene tyrosine-protein kinase SrcBiochemistryEnzyme

Abstract

fetched live from OpenAlex

Little is known about the changes in protein interactions inside synapses during synaptic remodeling, as their live monitoring in spines has been limited. We used a FRET-FLIM approach in developing cultured rat hippocampal neurons expressing fluorescently tagged NMDA receptor (NMDAR) and PSD95, two essential proteins in synaptic plasticity, to examine the regulation of their interaction. NMDAR stimulation caused a transient decrease in FRET between the NMDAR and PSD95 in spines of young and mature neurons. The activity of both CaMKII and calpain were essential for this effect in both developmental stages. Meanwhile, inhibition of Src family kinase (SFK) had opposing impacts on this decrease in FRET in young versus mature neurons. Our data suggest concerted roles for CaMKII, SFK and calpain activity in regulating activity-dependent separation of PSD95 from GluN2A or GluN2B. Finally, we found that calpain inhibition reduced spine growth that was caused by NMDAR activity, supporting the hypothesis that PSD95-NMDAR separation is implicated in synaptic remodeling.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.067
GPT teacher head0.293
Teacher spread0.226 · 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 source (direct Gemma or distilled Codex), 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

Citations33
Published2014
Admission routes2
Has abstractyes

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