Signaling Pathways Involved in the Cardioprotective Effects of Cannabinoids
Bibliographic record
Abstract
The aim of the present article is to review the cardioprotective properties of cannabinoids, with an emphasis on the signaling pathways involved. Cannabinoids have been reported to protect against ischemia in rat isolated hearts, as well as in rats and mice in vivo. Although these effects have been observed mostly with a pre-treatment of a cannabinoid, we report that the selective CB(2)-receptor agonist JWH133 is able to reduce infarct size when administered either before ischemia, during the entire ischemic period, or just upon reperfusion. Little is known about the signaling pathways involved in these cardioprotective effects. Likely candidates include protein kinase C (PKC) and mitogen-activated protein kinases (MAPK) since they are activated during ischemia-reperfusion and contribute to the protective effect ischemic preconditioning. The use of pharmacological inhibitors suggests that PKC, p38 MAPK, and p42/p44 MAPK (ERK1/2) contribute to the protective effect of cannabinoids. In addition, perfusion with JWH133 in healthy hearts caused an increase in both p38 MAPK phosphorylation level and activity, whereas the CB(1)-receptor agonist ACEA was associated with an increase in the phosphorylation status of both ERK1 and ERK2 without any change in activity. During ischemia, both agonists doubled p38 MAPK activity, whereas ERK1/2 phosphorylation level and activity during reperfusion were enhanced only by the CB(1)-receptor agonist. Finally, although nitric oxide (NO) was shown to exert both pro and anti-apoptotic effects on cardiomyocytes, with an apparently controversial effect on myocardial survival, our data suggest that NO may contribute to the cardioprotective effect of some cannabinoids.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".