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Record W2952808508 · doi:10.1093/cercor/bhy261

High Sensitivity Mapping of Cortical Dopamine D2 Receptor Expressing Neurons

2018· article· en· W2952808508 on OpenAlexafffund
Jivan Khlghatyan, Clémentine Quintana, Martin Parent, Jean‐Martin Beaulieu

Bibliographic record

VenueCerebral Cortex · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReceptor Mechanisms and Signaling
Canadian institutionsUniversité LavalUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsNeuroscienceBiologyParvalbuminDopamine receptor D2Context (archaeology)Dopamine

Abstract

fetched live from OpenAlex

Cortical D2 dopamine receptor (Drd2) have mostly been examined in the context of cognitive function regulation and neurotransmission modulation of medial prefrontal cortex by principal neurons and parvalbumin positive, fast-spiking, interneurons in schizophrenia. Early studies suggested the presence of D2 receptors in several cortical areas, albeit with major technical limitations. We used combinations of transgenic reporter systems, recombinase activated viral vectors, quantitative translatome analysis, and high sensitivity in situ hybridization to identify D2 receptor expressing cells and establish a map of their respective projections. Our results identified previously uncharacterized clusters of D2 expressing neurons in limbic and sensory regions of the adult mouse brain cortex. Characterization of these clusters by translatome analysis and cell type specific labeling revealed highly heterogeneous expression of D2 receptors in principal neurons and various populations of interneurons across cortical areas. Transcript enrichment analysis also demonstrated variable levels of D2 receptor expression and several orphan G-protein-coupled receptors coexpression in different neuronal clusters, thus suggesting strategies for genetic and therapeutic targeting of D2 expressing neurons in specific cortical areas. These results pave the way for a thorough re-examination of cortical D2 receptor functions, which could provide information about neuronal circuits involved in psychotic and mood disorders.

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)0.000
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 score0.014
Threshold uncertainty score0.606

Codex and Gemma teacher scores by category

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 integrity0.0000.000
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 head0.015
GPT teacher head0.238
Teacher spread0.224 · 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
Published2018
Admission routes2
Has abstractyes

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