The cannabinoid‐1 receptor inverse agonist taranabant reduces abdominal pain and increases intestinal transit in mice
Bibliographic record
Abstract
BACKGROUND: Constipation-predominant irritable bowel syndrome (IBS-C) is a common functional gastrointestinal (GI) disorder with abdominal pain and decreased motility. Current treatments of IBS-C are insufficient. The aim of this study was to evaluate the potential application of taranabant, a cannabinoid type 1 (CB1) inverse agonist using mouse models mimicking the symptoms of IBS-C. METHODS: Changes in intestinal contractile activity were studied in vitro, using isolated mouse ileum and colon and intracellular recordings. In vivo, whole gastrointestinal transit (WGT) and fecal pellet output (FPO) were measured under standard conditions and with pharmacologically delayed GI transit. The antinociceptive effect was evaluated in mustard oil- and acetic acid-induced models of visceral pain. Forced swimming and tail suspension tests were performed and locomotor activity was measured to evaluate potential central side effects. KEY RESULTS: In vitro, taranabant (10(-10) -10(-7) mol L(-1)) increased contractile responses in mouse ileum and blocked the effect of the CB agonist WIN 55,212-2. Taranabant had no effect on the amplitude of electrical field stimulation (EFS)-evoked junction potentials. In vivo, taranabant (0.1-3 mg kg(-1), i.p. and 3 mg kg(-1), p.o.) increased WGT and FPO in mice and reversed experimental constipation. The effect of taranabant was absent in CB1(-/-) mice. Taranabant significantly decreased the number of pain-related behaviors in animal models. At the doses tested, taranabant did not display mood-related adverse side effects typical for CB1 receptor inverse agonists. CONCLUSIONS & INFERENCES: Taranabant improved symptoms related to slow GI motility and abdominal pain and may become an attractive template in the development of novel therapeutics targeting IBS-C.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".