Toward modulation of the endocannabinoid system for treatment of gastrointestinal disease: <scp>FAAH</scp>ster but not “higher”
Bibliographic record
Abstract
Cannabis has been used to treat various afflictions throughout the centuries, including nausea, vomiting, and pain. It has also been used recreationally for its psychotropic properties, which can include a pleasurable 'high' feeling and a decrease in anxiety and tension; however, other may experience dysphoria. Changes in cognition and psychomotor performance are also well-known with cannabis use. In recent years, our understanding of the endocannabinoid system (ECS) has progressed dramatically; the objective of identifying agents which may allow modulation of the ECS without significant psychotropic side effects may be possible. Inhibition of fatty acid amide hydrolase (FAAH), an important enzyme for the degradation of anandamide and other endogenous cannabinoids, is a promising target to achieve this goal. In this issue of Neurogastroenterology and Motility, Fichna and colleagues report on a novel selective FAAH inhibitor, PF-3845, with potent antinociceptive and antidiarrheal effects in a mouse model. In this context, we briefly review the components of the ECS, discuss pharmacologic targets for indirect cannabinoid receptor stimulation, and describe recent research with cannabinoids for gut 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.020 | 0.017 |
| Insufficient payload (model declined to judge) | 0.004 | 0.006 |
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".