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Record W4402201589 · doi:10.1111/nmo.14911

Endocannabinoid signaling in stress, nausea, and vomiting

2024· review· en· W4402201589 on OpenAlexafffund
Marieka V. DeVuono, Thangam Venkatesan, Cecilia J. Hillard

Bibliographic record

VenueNeurogastroenterology & Motility · 2024
Typereview
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsWestern University
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesCanadian Institutes of Health ResearchCanada First Research Excellence Fund
KeywordsNauseaVomitingEndocannabinoid systemAnxietyAnxiolyticCannabisMedicineAnesthesiaCannabinoid receptorAntiemeticCannabinoidPsychologyInternal medicinePsychiatryAgonistReceptor

Abstract

fetched live from OpenAlex

BACKGROUND: Classical antiemetics that target the serotonin system may not be effective in treating certain nausea and vomiting conditions like cyclic vomiting syndrome (CVS) and cannabinoid hyperemesis syndrome (CHS). As a result, there is a need for better therapies to manage the symptoms of these disorders, including nausea, vomiting, and anxiety. Cannabis is often used for its purported antiemetic and anxiolytic effects, given regulation of these processes by the endocannabinoid system (ECS). However, there is considerable evidence that cannabinoids can also produce nausea and vomiting and increase anxiety in certain instances, especially at higher doses. This paradoxical effect of cannabinoids on nausea, vomiting, and anxiety may be due to the dysregulation of the ECS, altering how it maintains these processes and contributing to the pathophysiology of CVS or CHS. PURPOSE: The purpose of this review is to highlight the involvement of the ECS in the regulation of stress, nausea, and vomiting. We discuss how prolonged cannabis use, such as in the case of CHS or heightened stress, can dysregulate the ECS and affect its modulation of these functions. The review also examines the evidence for the roles of ECS and stress systems' dysfunction in CVS and CHS to better understand the underlying mechanisms of these conditions.

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), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.947
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.003
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 head0.038
GPT teacher head0.362
Teacher spread0.325 · 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

Citations22
Published2024
Admission routes2
Has abstractyes

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