Inhibition of endocannabinoid degradation in experimental endotoxemia reduces leukocyte adhesion and improves capillary perfusion in the gut
Bibliographic record
Abstract
BACKGROUND: Changes in leukocyte-endothelial and microvascular perfusion are hallmark events in inflammation. Thus, protection of the intestinal microcirculation represents a pivotal therapeutic target in systemic inflammation and sepsis. The endocannabinoid system (ECS) modulates a number of critical homeostatic functions and has been associated with anti-inflammatory responses. Our study aimed to examine intestinal leukocyte adhesion and capillary perfusion following selective inhibition of the endocannabinoid degradation enzyme, fatty acid amide hydrolase (FAAH), in experimental sepsis (endotoxemia). METHODS: Five groups of rats were used: controls, endotoxemia [lipopolysaccharide (LPS)], FAAH inhibitor URB597 (0.3 mg/kg)+LPS, URB597 (0.6 mg/kg)+LPS, and URB597 (0.6 mg/kg)+cannabinoid 2 receptor (CB2R) antagonist (AM630)+LPS. After 2 h, intravital microscopy was performed to quantify intestinal leukocyte recruitment and functional capillary density (FCD), as well as macrohemodynamic monitoring and histological examinations. RESULTS: LPS induced a significant increase in leukocyte adhesion in collecting and postcapillary submucosal venules and a decrease in intestinal FCD. URB597 pretreatment prevented the LPS-induced increase in leukocyte adhesion in intestinal venules and a decrease in intestinal FCD. The administration of the CB2R inhibitor, AM630, with URB597 reversed the protective effects of URB597 on the LPS-induced increase in leukocyte adhesion in intestinal venules, but not URB597's effect on the intestinal FCD. CONCLUSIONS: FAAH inhibition prevents the LPS-induced increase in leukocyte adhesion and improves the capillary perfusion of the gut. This might be mediated in part by CB2R activation. Our study encourages further investigation into the therapeutic potential of drugs targeting the ECS in 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 | 0.000 | 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".