Bibliographic record
Abstract
Cannabis has been used for its medicinal purposes since ancient times. Its consumption leads to the activation of Cannabis receptors CB1 and CB2 that, through specific mechanisms can lead to modulation and progression of inflammation or repair. The novel findings are linked to the medical use of Cannabis in gastrointestinal (GI) system. PURPOSE: The objective of the present paper is to elucidate the role of Cannabis consumption in GI system. An additional aim is to review the information on the function of Cannabis in non-alcoholic fatty liver disease (NAFLD). METHODS AND RESULTS: This review summarizes the recent findings on the role of cannabinoid receptors, their synthetic or natural ligands, as well as their metabolizing enzymes in normal GI function and its disorders, including irritable bowel syndrome (IBS), inflammatory bowel disease (IBD) and possible adverse events. The synergism or antagonism between Cannabis' active ingredients and the "entourage" plays a role in the efficacy of various strains. Some elements of Cannabis may alter disease severity as over-activation of Cannabis receptors CB1 and CB2 can lead to changes of the commensal gut flora. The endocannabinoid system (ECS) contributes to gut homeostasis. The ability of ECS to modulate inflammatory responses demonstrates the capacity of ECS to preserve gastrointestinal (GI) function. Alterations of the ECS may predispose patients to pathologic disorders, including IBD. Clinical studies in IBD demonstrate that subjects benefit from Cannabis consumption as seen through a reduction of the IBD-inflammation, as well as through a decreased need for other medication. NAFLD is characterized by fat accumulation in the liver. The occurrence of inflammation in NAFLD leads to non-alcoholic-steatohepatitis (NASH). The use of Cannabis might reduce liver inflammation. CONCLUSIONS: With limited evidence of efficacy and safety of Cannabis in IBD, IBS, and NAFLD, randomized controlled studies are required to examine its therapeutic efficacy. Moreover, since long term use of the plant leads to drug use disorders the patients should be followed continuously.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".