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Record W2166632802 · doi:10.1186/1756-6606-2-17

Hook-up of GluA2, GRIP and liprin-α for cholinergic muscarinic receptor-dependent LTD in the hippocampus

2009· letter· en· W2166632802 on OpenAlexafffund
Long‐Jun Wu, Min Zhuo

Bibliographic record

VenueMolecular Brain · 2009
Typeletter
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsUniversity of British ColumbiaCanada Research ChairsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsAMPA receptorMuscarinic acetylcholine receptorCholinergicNeuroscienceAcetylcholine receptorCell biologyScaffold proteinBiologyReceptorChemistrySignal transductionGlutamate receptorBiochemistry

Abstract

fetched live from OpenAlex

The molecular mechanism underlying muscarinic acetylcholine receptor-dependent LTD (mAChR-LTD) in the hippocampus is less studied. In a recent study, a novel mechanism is described. The induction of mAChR-LTD required the activation of protein tyrosine phosphatase (PTP), and the expression was mediated by AMPA receptor endocytosis via interactions between GluA2, GRIP and liprin-alpha. The hook-up of these proteins may result in the recruitment of leukocyte common antigen-related receptor (LAR), a PTP that is known to be involved in AMPA receptor trafficking. Interestingly, the similar molecular interaction cannot be applied to mGluR-LTD, despite the fact that the same G-protein involved in LTD is activated by both mAChR and mGluR. This discovery provides key molecular insights for cholinergic dependent cognitive function, and mAChR-LTD can serve as a useful cellular model for studying the roles of cholinergic mechanism in learning and memory.

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)0.001
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0100.006
Insufficient payload (model declined to judge)0.0060.006

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 head0.039
GPT teacher head0.331
Teacher spread0.291 · 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

Citations6
Published2009
Admission routes2
Has abstractyes

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