Review article: endocannabinoids and their receptors in the enteric nervous system
Bibliographic record
Abstract
The therapeutic actions of cannabinoids have been known for centuries. In the last 25 years this area of research has grown exponentially with the discovery of specific cannabinoid receptors and endogenous ligands. In the enteric nervous system of gastrointestinal tract, cannabinoid receptors are located on enteric nerve terminals where they exert inhibitory actions on neurotransmission to reduce motility and secretion. Endogenous cannabinoids are present in the enteric nervous system, as are the degradative enzymes necessary to inhibit their action. The cellular mechanism of action of endocannabinoids has not been established in the enteric nervous system. Endocannabinoids not only act at cannabinoid receptors, but potentially also at vanilloid and 5-HT3 receptors, both of which are expressed in the gastrointestinal tract. The interactions between endocannabinoids and these other important receptor systems have not been extensively investigated. A greater understanding of the endocannabinoid system in the enteric nervous system could lead to advances with important therapeutic potential in the treatment of gastrointestinal disorders such as irritable bowel syndrome, inflammatory bowel disease, secretory diarrhoea and gastro-oesophageal reflux disease.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".