(Wh)olistic (E)ndocannabinoidome-Microbiome-Axis Modulation through (N)utrition (WHEN) to Curb Obesity and Related Disorders
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".