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T-Cell Receptor Activation Decreases Excitability of Cortical Interneurons by Inhibiting α7 Nicotinic Receptors

2013· article· en· W2007222696 on OpenAlexafffund
Pragya Komal, Geoff Gudavicius, Christopher J. Nelson, Raad Nashmi

Bibliographic record

VenueJournal of Neuroscience · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNicotinic Acetylcholine Receptors Study
Canadian institutionsUniversity of Victoria
FundersBritish Columbia Knowledge Development FundNational Alliance for Research on Schizophrenia and DepressionNatural Sciences and Engineering Research Council of CanadaHeart and Stroke Foundation of Canada
KeywordsCell biologyNicotinic agonistFYNT-cell receptorTyrosine kinaseTyrosine phosphorylationT cellNeuroscienceBiologyReceptorAcetylcholine receptorProto-oncogene tyrosine-protein kinase SrcChemistryPhosphorylationSignal transductionImmune systemBiochemistryImmunology

Abstract

fetched live from OpenAlex

Many proteins in the immune system are also expressed in the brain. One such class of immune proteins are T-cell receptors (TCRs), whose functions in T lymphocytes in adaptive immunity are well characterized. In the brain, TCRs are confined to neocortical neurons, but their functional role has not been determined. In mouse layer 1 neocortical neurons, TCR activation inhibited α7 nicotinic currents. TCRs modulated α7 currents via tyrosine phosphorylation of α7 nicotinic receptors (nAChRs) through src tyrosine kinases because eliminating lck kinase expression, coexpressing fyn kinase dead, or mutating tyrosine to alanine in α7 blocked the effect of TCR activation. We found that TCR stimulation decreased surface α7 nAChRs and reduced single-channel conductance. These results reveal that TCRs play a major role in the modulation of cholinergic neurotransmission in the brain mediated by α7 nAChRs and that this has a profound effect on regulating neuronal excitability.

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)0.003
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 score0.009
Threshold uncertainty score0.563

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
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 integrity0.0000.000
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 head0.012
GPT teacher head0.260
Teacher spread0.248 · 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

Citations23
Published2013
Admission routes2
Has abstractyes

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