Cannabidiol protects against high glucose‐induced oxidative stress and cytotoxicity in cardiac voltage‐gated sodium channels
Bibliographic record
Abstract
Background and Purpose Cardiovascular complications are the major cause of mortality in diabetic patients. However, the molecular mechanisms underlying diabetes‐associated arrhythmias are unclear. We hypothesized that high glucose could adversely affect Nav1.5, the major cardiac sodium channel isoform of the heart, at least partially via oxidative stress. We further hypothesized that cannabidiol (CBD), one of the main constituents of Cannabis sativa, through its effects on Nav1.5, could protect against high glucose‐elicited oxidative stress and cytotoxicity. Experimental Approach To test these ideas, we used CHO cells transiently co‐transfected with cDNA encoding human Nav1.5 α‐subunit under control and high glucose conditions (50 or 100 mM for 24 hr). Several experimental and computational techniques were used, including voltage clamp of heterologous expression systems, cell viability assays, fluorescence assays and action potential modelling. Key Results High glucose evoked cell death associated with elevation in reactive oxygen species (ROS) right shifted the voltage dependence of conductance and steady‐state fast inactivation, and increased persistent current leading to computational prolongation of action potential (hyperexcitability) which could result in long QT3 arrhythmia. CBD mitigated all the deleterious effects provoked by high glucose. Perfusion with lidocaine (a well‐known sodium channel inhibitor with antioxidant effects) or co‐incubation of Tempol (a well‐known antioxidant) elicited protection, comparable to CBD, against the deleterious effects of high glucose. Conclusion and Implications These findings suggest that, through its favourable antioxidant and sodium channel inhibitory effects, CBD may protect against high glucose‐induced arrhythmia and cytotoxicity.
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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 | 0.000 |
| 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".