Role of Endothelium in Abnormal Cannabidiol-Induced Vasoactivity in Retinal Arterioles
Bibliographic record
Abstract
PURPOSE: Cannabinoids have been reported to mediate changes in vascular resistance through endothelial receptor targets. We examined involvement of the endothelium in cannabinoid-mediated vasoactive responses in resistance arterioles of the retina. METHODS: Vascular responses to both intraluminal (IL) and extraluminal (EL) administration of the atypical cannabinoid, abnormal cannabidiol (abn-CBD), a prototypical agonist at the non-CB1/CB2 endothelial cannabinoid receptor (CBeR), were studied in endothelial intact and endothelial denuded, isolated perfused porcine retinal arterioles with and without endothelin-1 (ET-1) precontraction. The effects of AM251, a CB1 receptor antagonist, and O-1918, an analog of CBD reported to antagonize CBeR, were also studied. RESULTS: Dose-dependent vasocontractile responses were induced by both IL and EL administration of abn-CBD in the absence of precontraction. Significantly greater vasoconstriction was induced by IL administration of abn-CBD than with EL administration. In contrast, only vasodilation to abn-CBD was observed in ET-1 precontracted retinal arterioles. Endothelium removal significantly reduced abn-CBD-induced vasoactivity when abn-CBD was used IL but not when applied EL. IL abn-CBD-induced vasoactivity was antagonized by O-1918 and AM251. CONCLUSIONS: Cannabinoids show complex vasoactive actions in isolated perfused retinal arterioles. The fact that abn-CBD-mediated vasorelaxation was seen only in precontracted retinal vessels indicates that the abn-CBD-induced vasoactive response is highly dependent on vascular tone. Furthermore, IL and EL administration produced differential responses, and removal of endothelium blunted abn-CBD vasoactivity, highlighting the critical role of endothelium in abn-CBD vasoactivity. AM251 and O-1918 inhibition of abn-CBD-induced vasoactivity suggests the possibility of modulating abn-CBD-induced vasoactivity.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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 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".