Cannabinoid 2 receptor agonist and L-arginine combination attenuates diabetic cardiomyopathy in rats via NF-ĸβ inhibition
Bibliographic record
Abstract
Beta-caryophyllene (BCP), a cannabinoid 2 (CB2) receptor agonist has recently been found to have cardioprotective activity as an anti-inflammatory and antioxidant molecule. L-arginine (LA), a nitric oxide (NO) donor, is a potential regulator of cardiovascular function. Considering the role of CB2 receptor activation and NO regulation in cardiovascular diseases, the combination of BCP with LA may be a possible treatment of diabetic cardiomyopathy (DCM). Hence, we investigated the efficacy of the novel combination of BCP with LA on cardiovascular inflammation and oxidative stress in diabetic rats. DCM was induced by streptozotocin (55 mg/kg) in Sprague–Dawley rats intraperitoneally. BCP, LA, and BCP with LA were administered to diabetic rats for 4 weeks. After completion of the study, hemodynamic parameters, biochemical parameters, and inflammatory cytokine levels were analyzed. Also, oxidative stress parameters, nuclear factor kappa beta (NF-ĸβ) expression, and histopathology in cardiac tissues were estimated. The combination of BCP (200 mg/kg) with LA (200 mg/kg) significantly normalized the hemodynamic parameters and decreased the glucose, cardiac markers, interleukin-6, and tumor necrosis factor-alpha levels. Treatment of BCP and LA showed a significant decrease in oxidative stress and downregulated the cardiac expression of NF-ĸβ. Thus, the combination of BCP with LA improves cardiac functions by attenuating inflammation through NF-ĸβ inhibition in DCM.
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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 | 0.001 |
| 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 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".