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Record W3200459505 · doi:10.3390/brainsci11091199

Sex Differences in Dopamine Receptors and Relevance to Neuropsychiatric Disorders

2021· review· en· W3200459505 on OpenAlexafffund
Olivia O. F. Williams, Madeleine Coppolino, Susan R. George, Melissa L. Perreault

Bibliographic record

VenueBrain Sciences · 2021
Typereview
Languageen
FieldNeuroscience
TopicNeurotransmitter Receptor Influence on Behavior
Canadian institutionsUniversity of TorontoUniversity of Guelph
FundersNational Institute on Drug AbuseNational Research Council Canada
KeywordsDopamineDopaminergicSchizophrenia (object-oriented programming)Dopamine receptorAddictionPsychologyNeuroscienceDopamine receptor D3Dopamine hypothesis of schizophreniaAnxietyDopamine receptor D2PsychiatryMedicine

Abstract

fetched live from OpenAlex

Dopamine is an important neurotransmitter that plays a key role in neuropsychiatric illness. Sex differences in dopaminergic signaling have been acknowledged for decades and have been linked to sex-specific heterogeneity in both dopamine-related behaviours as well as in various neuropsychiatric disorders. However, the overall number of studies that have evaluated sex differences in dopamine signaling, both in health and in these disorders, is low. This review will bring together what is known regarding sex differences in innate dopamine receptor expression and function, as well as highlight the known sex-specific roles of dopamine in addiction, depression, anxiety, schizophrenia, and attention deficit hyperactivity disorder. Due to differences in prognosis, diagnosis, and symptomatology between male and female subjects in disorders that involve dopamine signaling, or in responses that utilize pharmacological interventions that target dopamine receptors, understanding the fundamental sex differences in dopamine receptors is of vital importance for the personalization of therapeutic treatment strategies.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.076
GPT teacher head0.353
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 designNot applicable
Domainnot available
GenreReview

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

Citations103
Published2021
Admission routes2
Has abstractyes

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