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Record W1811771892 · doi:10.1096/fj.14-269746

Allosteric modulation of metabotropic glutamate receptors by chloride ions

2015· article· en· W1811771892 on OpenAlexafffund
Amélie S. Tora, Xavier Rovira, Ibrahima Dione, Hugues‐Olivier Bertrand, Isabelle Brabet, Yves De Koninck, Nicolas Doyon, Jean‐Philippe Pin, Francine Acher, Cyril Goudet

Bibliographic record

VenueThe FASEB Journal · 2015
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsUniversité LavalInstitut Universitaire en Santé Mentale de Québec
FundersCanadian Institutes of Health ResearchLaboratoire d'Excellence EpiGenMedCentre National de la Recherche ScientifiqueAgence Nationale de la Recherche
KeywordsMetabotropic glutamate receptorMetabotropic glutamate receptor 2Allosteric regulationMetabotropic glutamate receptor 5ChemistryGlutamate receptorMetabotropic glutamate receptor 1Metabotropic glutamate receptor 7Metabotropic receptorAllosteric modulatorMetabotropic glutamate receptor 3BiophysicsBiochemistryReceptorBiology

Abstract

fetched live from OpenAlex

Metabotropic glutamate receptors (mGluRs) play key roles in the modulation of many synapses. Chloride (Cl(-)) is known to directly bind and regulate the function of different actors of neuronal activity, and several studies have pointed to the possible modulation of mGluRs by Cl(-). Herein, we demonstrate that Cl(-) behaves as a positive allosteric modulator of mGluRs. For example, whereas glutamate potency was 3.08 ± 0.33 μM on metabotropic glutamate (mGlu) 4 receptors in high-Cl(-) buffer, signaling activity was almost abolished in low Cl(-) in cell-based assays. Cl(-) potency was 78.6 ± 3.5 mM. Cl(-) possesses a high positive cooperativity with glutamate (Hill slope ≈6 on mGlu4), meaning that small variations in [Cl(-)] lead to large variations in glutamate action. Using molecular modeling and mutagenesis, we have identified 2 well-conserved Cl(-) binding pockets in the extracellular domain of mGluRs. Moreover, modeling of activity-dependent Cl(-) variations at GABAergic synapses suggests that these variations may be compatible with a dynamic modulation of the most sensitive mGluRs present in these synapses. Taken together, these data reveal a necessary role of Cl(-) for the glutamate activation of many mGluRs. Exploiting Cl(-) binding pockets may yield to the development of innovative regulators of mGluR activity.

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)0.000
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 score0.002
Threshold uncertainty score0.263

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.090
GPT teacher head0.334
Teacher spread0.245 · 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

Citations41
Published2015
Admission routes2
Has abstractyes

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