Experimental Cannabinoid 2 Receptor-Mediated Immune Modulation in Sepsis
Bibliographic record
Abstract
Sepsis is a complex condition that results from a dysregulated immune system in response to a systemic infection. Current treatments lack effectiveness in reducing the incidence and mortality associated with this disease. The endocannabinoid system offers great promise in managing sepsis pathogenesis due to its unique characteristics. The present study explored the effect of modulating the CB2 receptor pathway in an acute sepsis mouse model. Endotoxemia was induced by intravenous injection of lipopolysaccharide (LPS) in mice and intestinal microcirculation was assessed through intravital microscopy. We found that HU308 (CB2 receptor agonist) reduced the number of adherent leukocytes in submucosal venules but did not restore muscular and mucosal villi FCD in endotoxemic mice. AM630 (CB2 receptor antagonist) maintained the level of adherent leukocytes induced by LPS but further reduced muscular and mucosal villi FCD. URB597 (FAAH inhibitor) and JZL184 (MAGL inhibitor) both reduced the number of adherent leukocytes in submucosal venules but did not restore the mucosal villi FCD. Using various compounds we have shown different mechanisms of activating CB2 receptors to reduce leukocyte endothelial interactions in order to prevent further inflammatory damage during sepsis.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".