Evaluation of Hepatoprotective Activity of Berberis Aristata Root Extract against Chemical-induced Acute Hepatotoxicity in Rats
Bibliographic record
Abstract
Biotransformation of free radical derivatives, increased lipid peroxidation, and excessive cell death are all important factors causing liver damage induced by CCL4. The pharmacological properties of "berberine chloride," a root extract from Berberis aristata, include antimicrobial, antiviral, anti-inflammatory, cholesterol-lowering, anticancer, and antioxidant effects. The present study aimed to explore the preventive and curative effects of Berberine on liver tissue injury, liver enzymes, total bilirubin and liver weight. The study was conducted at the Department of Pharmacology in collaboration with the Department of Pathology and Biochemistry, MM Institute of Medical Sciences &Research, Mullana, India. Adult wistar rats aged 7 -9 weeks were injected with 50% CCl4 intraperitoneally as a 1:1 mixture in liquid paraffin. Berberine was administered intraperitoneally before or after CCl4 treatment in various groups. Twenty-four hours after CCl4 injection, levels of liver enzymes (serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP)), bilirubin and liver weight were measured. Histological changes in the liver were also examined with microscopy. The serum levels of liver enzymes and bilirubin were significantly increased (p<0.01) in CCl4-treated group 2 rats. In comparison, group 3-5 rats treated with CCl4 followed by berberine chloride at doses of 5, 10 and 20 mg/kg, respectively, showed a significant decrease (p<0.05) in levels. The effects of Berberine were dose-dependent in both pre-and post-treatment groups. Histological examination also showed decreased liver damage in berberine-treated groups. The current study demonstrates that Berberine has both preventive and curative hepatoprotective effects against CCl4-induced hepatotoxicity. Berberine has the potential to design new treatments against drug-induced hepatotoxicity.
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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 | 0.000 |
| 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) | 0.002 | 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".