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Record W4206199447 · doi:10.1186/s12944-021-01609-3

(Wh)olistic (E)ndocannabinoidome-Microbiome-Axis Modulation through (N)utrition (WHEN) to Curb Obesity and Related Disorders

2022· review· en· W4206199447 on OpenAlexafffund
Jyoti Sihag, Vincenzo Di Marzo

Bibliographic record

VenueLipids in Health and Disease · 2022
Typereview
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversité LavalInstitut universitaire de cardiologie et de pneumologie de QuébecCanadian Nutrition SocietyInstitut National de la Recherche Scientifique
FundersCanada Excellence Research Chairs, Government of Canada
KeywordsClinical nutritionMicrobiomeLipidologyClinical chemistryObesityMedicineInternal medicineBiologyBioinformatics

Abstract

fetched live from OpenAlex

The discovery of the endocannabinoidome (eCBome) is evolving gradually with yet to be elucidated functional lipid mediators and receptors. The diet modulates these bioactive lipids and the gut microbiome, both working in an entwined alliance. Mounting evidence suggests that, in different ways and with a certain specialisation, lipid signalling mediators such as N-acylethanolamines (NAEs), 2-monoacylglycerols (2-MAGs), and N-acyl-amino acids (NAAs), along with endocannabinoids (eCBs), can modulate physiological mechanisms underpinning appetite, food intake, macronutrient metabolism, pain sensation, blood pressure, mood, cognition, and immunity. This knowledge has been primarily utilised in pharmacology and medicine to develop many drugs targeting the fine and specific molecular pathways orchestrating eCB and eCBome activity. Conversely, the contribution of dietary NAEs, 2-MAGs and eCBs to the biological functions of these molecules has been little studied. In this review, we discuss the importance of (Wh) olistic (E)ndocannabinoidome-Microbiome-Axis Modulation through (N) utrition (WHEN), in the management of obesity and related 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)0.001
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 score0.941
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.036
GPT teacher head0.363
Teacher spread0.327 · 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

Citations33
Published2022
Admission routes2
Has abstractyes

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