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Record W2072316081 · doi:10.2174/187152709789824624

The Endocannabinoid System and the Treatment of Mood and Anxiety Disorders

2009· review· en· W2072316081 on OpenAlexaff
Matthew N. Hill, Boris B. Gorzalka

Bibliographic record

VenueCNS & Neurological Disorders - Drug Targets · 2009
Typereview
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEndocannabinoid systemAnxietyAnxiolyticNeuroscience2-ArachidonoylglycerolMood disordersPsychologyCannabinoid receptorMoodAnxiogenicPanic disorderMedicineClinical psychologyPsychiatryReceptorInternal medicine

Abstract

fetched live from OpenAlex

The central endocannabinoid system is a neuroactive lipid signalling system in the brain which acts to control neurotransmitter release. The expression patterns of this system throughout limbic regions of the brain ideally situate it to exert regulatory control over emotional behaviour, mood and stress responsivity. A growing body of evidence unequivocally demonstrates that deficits in endocannabinoid signalling may result in depressive and anxiogenic behavioral responses, while pharmacological augmentation of endocannabinoid signalling can produce both antidepressive and anxiolytic behavioral responses. The aim of this review is to summarize current knowledge of the role of the endocannabinoid system in the etiology and treatment of mood and anxiety disorders, such as depression, anxiety and post-traumatic stress disorder. Collectively, both clinical and preclinical data argue that cannabinoid receptor signalling may be a realistic target in the development of a novel class of agent for the pharmacotherapy of mood and anxiety 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.286
Teacher spread0.273 · 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.

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

Citations156
Published2009
Admission routes1
Has abstractyes

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