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Interaction of Calcineurin and Type-A GABA Receptor γ<sub>2</sub>Subunits Produces Long-Term Depression at CA1 Inhibitory Synapses

2003· article· en· W1845046061 on OpenAlexafffund
Jian Wang, Shuhong Liu, Ursula Haditsch, Weihong Tu, Kimberley Cochrane, Gholamreza Ahmadian, Linda Tran, Jadine Paw, YuTian Wang, Isabelle M. Mansuy, Michael Salter, YouMing Lu

Bibliographic record

VenueJournal of Neuroscience · 2003
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of TorontoUniversity of Calgary
FundersFondation pour la Recherche MédicaleHeart and Stroke Foundation of Canada
KeywordsInhibitory postsynaptic potentialHippocampusCalcineurinNeuroscienceNeurotransmissionReceptorLong-term depressionChemistryBiologyCell biologyBiochemistryAMPA receptorGlutamate receptorInternal medicineMedicine

Abstract

fetched live from OpenAlex

Long-term depression (LTD) is an activity-dependent weakening of synaptic efficacy at individual inhibitory synapses, a possible cellular model of learning and memory. Here, we show that the induction of LTD of inhibitory transmission recruits activated calcineurin (CaN) to dephosphorylate type-A GABA receptor (GABA(A)Rs) via the direct binding of CaN catalytic domain to the second intracellular domain of the GABA(A)R-gamma(2) subunits. Prevention of the CaN-GABA(A) receptor complex formation by expression of an autoinhibitory domain of CaN in the hippocampus of transgenic mice blocks the induction of LTD. Conversely, genetic expression of the CaN catalytic domain in the hippocampus depresses inhibitory synaptic responses, occluding LTD. Thus, an activity-dependent physical and functional interaction between CaN and GABA(A) receptors is both necessary and sufficient for inducing LTD at CA1 individual inhibitory synapses.

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)0.005
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 score0.015
Threshold uncertainty score0.755

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.062
GPT teacher head0.348
Teacher spread0.286 · 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

Citations137
Published2003
Admission routes2
Has abstractyes

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