Cannabinoid CB<sub>2</sub> receptors in the enteric nervous system modulate gastrointestinal contractility in lipopolysaccharide-treated rats
Bibliographic record
Abstract
Enhanced intestinal transit due to lipopolysaccharide (LPS) is reversed by cannabinoid (CB)2 receptor agonists in vivo, but the site and mechanism of action are unknown. We have tested the hypothesis that CB2 receptors are expressed in the enteric nervous system and are activated in pathophysiological conditions. Tissues from either saline- or LPS-treated (2 h; 65 microg/kg ip) rats were processed for RT-PCR, Western blotting, and immunohistochemistry or were mounted in organ baths where electrical field stimulation was applied in the presence or absence of CB receptor agonists. Whereas the CB2 receptor agonist JWH133 did not affect the electrically evoked twitch response of the ileum under basal conditions, in the LPS-treated tissues JWH133 was able to reduce the enhanced contractile response in a concentration-dependent manner. Rat ileum expressed CB2 receptor mRNA and protein under physiological conditions, and this expression was not affected by LPS treatment. In the myenteric plexus, CB2 receptors were expressed on the majority of neurons, although not on those expressing nitric oxide synthase. LPS did not alter the distribution of CB2 receptor expression in the myenteric plexus. In vivo LPS treatment significantly increased Fos expression in both enteric glia and neurons. This enhanced expression was significantly attenuated by JWH133, whose action was reversed by the CB2 receptor antagonist AM630. Taking these facts together, we conclude that activation of CB2 receptors in the enteric nervous system of the gastrointestinal tract dampens endotoxin-induced enhanced intestinal contractility.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".