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Record W4296551121 · doi:10.1016/j.bcp.2022.115261

Biosynthesis and metabolism of endocannabinoids and their congeners from the monoacylglycerol and N-acyl-ethanolamine families

2022· review· en· W4296551121 on OpenAlexafffund
Mélissa Simard, Anne‐Sophie Archambault, Jean-Philippe C. Lavoie, Élizabeth Dumais, Vincenzo Di Marzo, Nicolas Flamand

Bibliographic record

VenueBiochemical Pharmacology · 2022
Typereview
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsImpactUniversité LavalInstitut universitaire de cardiologie et de pneumologie de Québec
FundersNatural Sciences and Engineering Research Council of CanadaCanada Excellence Research Chairs, Government of CanadaUniversité Laval
KeywordsEndocannabinoid systemMonoacylglycerol lipaseCannabinoid receptorBiochemistryMetabolismEthanolamineCannabinoidAnandamideReceptorBiologyEicosanoidChemistryBiosynthesisArachidonic acidEnzymeAntagonist

Abstract

fetched live from OpenAlex

The endocannabinoids 2-arachidonoyl-glycerol (2-AG) and N-arachidonoyl-ethanolamine (AEA) are eicosanoids implicated in numerous physiological processes like appetite, adipogenesis, inflammatory pain and inflammation. They mediate most of their physiological effects by activating the cannabinoid (CB) receptors 1 and 2. Other than directly binding to the CB receptors, 2-AG and AEA are also metabolized by most eicosanoid biosynthetic enzymes, yielding many metabolites that are part of the oxyendocannabinoidome. Some of these metabolites have been found in vivo, have the ability to modulate specific receptors and thus potentially influence physiological processes. In this review, we discuss the biosynthesis and metabolism of 2-AG and AEA, as well as their congeners from the monoacyl-glycerol and N-acyl-ethanolamine families, with a special focus on the metabolism by oxygenases involved in arachidonic acid metabolism. We highlight the knowledge gaps in our understanding of the regulation and roles the oxyendocannabinoidome mediators.

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 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 score0.839
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.040
GPT teacher head0.336
Teacher spread0.295 · 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

Citations54
Published2022
Admission routes2
Has abstractyes

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