Anti‐inflammatory effects of cannabinoid CB<sub>2</sub> receptor activation in endotoxin‐induced uveitis
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Cannabinoid CB2 receptors mediate immunomodulation. Here, we investigated the effects of CB2 receptor ligands on leukocyte-endothelial adhesion and inflammatory mediator release in experimental endotoxin-induced uveitis (EIU). EXPERIMENTAL APPROACH: EIU was induced by intraocular injection of lipopolysaccharide (LPS, 20 ng·μL(-1) ). Effects of the CB2 receptor agonist, HU308 (1.5% topical), the CB2 receptor antagonist, AM630 (2.5 mg·kg(-1) i.v.), or a combination of both compounds on leukocyte-endothelial interactions were measured hourly for 6 h in rat iridial vasculature using intravital microscopy. Anti-inflammatory actions of HU308 were compared with those of clinical treatments for uveitis - dexamethasone, prednisolone and nepafenac. Transcription factors (NF-κB, AP-1) and inflammatory mediators (cytokines, chemokines and adhesion molecules) were measured in iris and ciliary body tissue. KEY RESULTS: Leukocyte-endothelium adherence was increased in iridial microvasculature between 4-6 h after LPS. HU308 reduced this effect after LPS injection and decreased pro-inflammatory mediators: TNF-α, IL-1β, IL-6, CCL5 and CXCL2. AM630 blocked the actions of HU-308, and increased leukocyte-endothelium adhesion. HU-308 decreased levels of the transcription factors NF-κB and AP-1, while AM630 increased levels of NF-κB. Topical treatments with dexamethasone, prednisolone or nepafenac, failed to alter leukocyte adhesion or mitigate LPS-induced increases in inflammatory mediators during the 6 h of EIU. CONCLUSION AND IMPLICATIONS: Activation of CB2 receptors was anti-inflammatory in a model of acute EIU and involved a reduction in NF-κB, AP-1 and inflammatory mediators. CB2 receptors may be promising drug targets for the development of novel ocular anti-inflammatory agents. LINKED ARTICLES: This article is part of a themed section on Cannabinoids 2013. To view the other articles in this section visit http://dx.doi.org/10.1111/bph.2014.171.issue-6.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".