Differential effects of CB1 neutral antagonists and inverse agonists on gastrointestinal motility in mice
Bibliographic record
Abstract
BACKGROUND: Cannabinoid type 1 (CB(1)) receptors are involved in the regulation of gastrointestinal (GI) motility and secretion. Our aim was to characterize the roles of the CB(1) receptor on GI motility and secretion in vitro and in vivo by using different classes of CB(1) receptor antagonists. METHODS: Immunohistochemistry was used to examine the localization of CB(1) receptor in the mouse ileum and colon. Organ bath experiments on mouse ileum and in vivo motility testing comprising upper GI transit, colonic expulsion, and whole gut transit were performed to characterize the effects of the inverse agonist/antagonist AM251 and the neutral antagonist AM4113. As a marker of secretory function we measured short circuit current in vitro using Ussing chambers and stool fluid content in vivo in mouse colon. We also assessed colonic epithelial permeability in vitro using FITC-labeled inulin. KEY RESULTS: In vivo, the inverse agonist AM251 increased upper GI transit and whole gut transit, but it had no effect on colonic expulsion. By contrast, the neutral antagonist AM4113 increased upper GI transit, but unexpectedly reduced both colonic expulsion and whole gut transit at high, but not lower doses. CONCLUSIONS & INFERENCES: Cannabinoid type 1 receptors regulate small intestinal and colonic motility, but not GI secretion under physiological conditions. Cannabinoid type 1 inverse agonists and CB(1) neutral antagonists have different effects on intestinal motility. The ability of the neutral antagonist not to affect whole gut transit may be important for the future development of CB(1) receptor antagonists as therapeutic agents.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".