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Record W4382318808 · doi:10.1016/j.cub.2023.05.065

Claustral neurons projecting to frontal cortex restrict opioid consumption

2023· article· en· W4382318808 on OpenAlexaff
Anna Terem, Yonatan Fatal, Noa Peretz‐Rivlin, Hagit Turm, Shahar Shohat Koren, Danny Kitsberg, Reut Ashwal-Fluss, Diptendu Mukherjee, Naomi Habib, Ami Citri

Bibliographic record

VenueCurrent Biology · 2023
Typearticle
Languageen
FieldNeuroscience
TopicNeurotransmitter Receptor Influence on Behavior
Canadian institutionsCanadian Institute for Advanced Research
Fundersnot available
KeywordsBiologyNeuroscienceFrontal cortexCortex (anatomy)Consumption (sociology)Anatomy

Abstract

fetched live from OpenAlex

The synthetic opioid fentanyl is a major contributor to the current opioid addiction crisis. We report that claustral neurons projecting to the frontal cortex limit oral fentanyl self-administration in mice. We found that fentanyl transcriptionally activates frontal-projecting claustrum neurons. These neurons also exhibit a unique suppression of Ca 2+ activity upon initiation of bouts of fentanyl consumption. Optogenetic stimulation of frontal-projecting claustral neurons, intervening in this suppression, decreased bouts of fentanyl consumption. In contrast, constitutive inhibition of frontal-projecting claustral neurons in the context of a novel, group-housed self-administration procedure increased fentanyl bout consumption. This same manipulation also sensitized conditioned-place preference for fentanyl and enhanced the representation of fentanyl experience in the frontal cortex. Together, our results indicate that claustrum neurons exert inhibitory control over frontal cortical neurons to restrict oral fentanyl intake. Upregulation of activity in the claustro-frontal projection may be a promising strategy for reducing human opioid addiction.

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 score0.001
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 head0.150
GPT teacher head0.396
Teacher spread0.246 · 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

Citations21
Published2023
Admission routes1
Has abstractyes

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