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Record W2737125392 · doi:10.1016/j.neuron.2017.06.044

Initiation of Behavioral Response to Antidepressants by Cholecystokinin Neurons of the Dentate Gyrus

2017· article· en· W2737125392 on OpenAlexaff
Lucian Medrihan, Yotam Sagi, Zintis Inde, Oleh Krupa, Chelsea Daniels, Adrien Peyrache, Paul Greengard

Bibliographic record

VenueNeuron · 2017
Typearticle
Languageen
FieldNeuroscience
TopicNeuropeptides and Animal Physiology
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersFondation pour la Recherche MédicaleNational Institutes of HealthDebra and Leon Black Family FoundationJPB Foundation
KeywordsDentate gyrusParvalbuminCholecystokininAntidepressantNeuroscienceInhibitory postsynaptic potentialSerotoninCholecystokinin receptorPharmacologyReceptorChemistryBiologyHippocampusBiochemistry

Abstract

fetched live from OpenAlex

Selective serotonin reuptake inhibitors (SSRIs) are the most commonly used class of antidepressant drugs, but the cellular and molecular mechanisms by which their therapeutic action is initiated are poorly understood. Here we show that serotonin 5-HT1B receptors in cholecystokinin (CCK) inhibitory interneurons of the mammalian dentate gyrus (DG) initiate the therapeutic response to antidepressants. In these neurons, 5-HT1B receptors are expressed presynaptically, and their activation inhibits GABA release. Inhibition of GABA release from CCK neurons disinhibits parvalbumin (PV) interneurons and, as a consequence, reduces the neuronal activity of the granule cells. Finally, inhibition of CCK neurons mimics the antidepressant behavioral effects of SSRIs, suggesting that these cells may represent a novel cellular target for the development of fast-acting antidepressant drugs.

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 score0.002
Threshold uncertainty score0.004

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.056
GPT teacher head0.334
Teacher spread0.278 · 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

Citations74
Published2017
Admission routes1
Has abstractno

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