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Na,K-ATPase Activity Regulates AMPA Receptor Turnover through Proteasome-Mediated Proteolysis

2009· article· en· W2110405052 on OpenAlexaff
Dawei Zhang, Qingming Hou, Min Wang, Amy Lin, Larissa A. Jarzylo, Allison Navis, Aram Raissi, Fang Liu, Heng‐Ye Man

Bibliographic record

VenueJournal of Neuroscience · 2009
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersNational Institute of Mental HealthNational Institutes of Health
KeywordsAMPA receptorIonotropic effectCell biologyGlutamate receptorNeurotransmissionChemistrySynapseGlutamatergicSilent synapseReceptorLong-term depressionNeuroscienceBiologyBiochemistry

Abstract

fetched live from OpenAlex

Neuronal activity largely depends on two key components on the membrane: the Na,K-ATPase (NKA) that maintains the ion gradients and sets the foundation of excitability, and the ionotropic glutamatergic AMPA receptors (AMPARs) through which sodium influx forms the driving force for excitation. Because the frequent sodium transients from glutamate receptor activity need to be efficiently extruded, a functional coupling between NKA and AMPARs should be a necessary cellular device for synapse physiology. We show that NKA is enriched at synapses and associates with AMPARs. NKA dysfunction induces a rapid reduction in AMPAR cell-surface expression as well as total protein abundance, leading to a long-lasting depression in synaptic transmission. AMPAR proteolysis requires sodium influx, proteasomal activity and receptor internalization. These data elucidate a novel mechanism by which NKA regulates AMPAR turnover and thereby synaptic strength and brain function.

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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.060
GPT teacher head0.349
Teacher spread0.289 · 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

Citations120
Published2009
Admission routes1
Has abstractyes

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