Evaluation of the Effect of Virgin Rice Bran Oil (VRBO) on Doxorubicininduced Cardiotoxicity in Wistar Rats
Bibliographic record
Abstract
INTRODUCTION: The usage of doxorubicin (DOX), an antineoplastic drug that is frequently used for the cure of cancer, is restricted to maximal doses due to its cardiac toxicity. Reactive oxygen species produced by DOX result in lipid peroxidation and organ failure, ultimately resulting in cardiomyopathy. Due to its high polyphenol content, virgin rice bran oil (VRBO) is a diet nutritional supplement with a strong antioxidant. This study aimed to assess the potential defense of VRBO against DOX-induced cardiotoxicity. METHODS: VRBO and DOX injections were administered to thirty male Wistar rats for 42 days after being randomly assigned to five groups. RESULTS: The study demonstrated the cardioprotective effects of VRBO against doxorubicin (DOX)-induced cardiotoxicity. VRBO (0.71 and 1.42 ml/kg) significantly improved the heart-tobody weight ratio, reduced elevated serum CK-MB and LDH levels by 18.4% and 52.7%, respectively, and increased HDL by 43.1%. ECG parameters also improved, with reductions in QT interval (19%), ST interval (28%), and QRS complex (15%). VRBO enhanced systolic blood pressure (up to 21%) and heart rate (7.1%). Antioxidant markers showed notable recovery, with MDA levels reduced by 66.1%, while GSH, SOD, and catalase levels increased by 129.4%, 158.2%, and 84.8%, respectively. CONCLUSION: A cardioprotective benefit was found at middle and higher VRBO dosages. In order to demonstrate the effectiveness of VRBO as a cardioprotective medication, further research on dosage response and bioavailability is required.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".