Hepatoprotective activity of the ethanolic extract of Morus indica roots from Indian Bodo tribes
Bibliographic record
Abstract
Abstract The roots of Morus species are well described in the Pharmacopoeia of the People's Republic of China (ChP) for its traditional use in treating liver fibrosis due to its hepatoprotective property. However, little is known about the hepatoprotective effect of the roots of Morus indica L. (RoMi), and the pharmacological mechanism(s) are uncertain due to its intricacy. Therefore, this study evaluates the hepatoprotective activity of the ethanolic extract of RoMi (eRoMi) against the CCl4-induced in-vivo animal model at different dosages (100 and 200 mg/kg BW) in comparison with silymarin as a positive control. The hepatoprotective activity of eRoMi was evaluated by measuring the levels of serum biomarkers, hepatic antioxidant enzymes and was verified by histological studies. Interestingly, 1,2-bis(trimethylsilyl) benzene, 1,4-phenylenebis (trimethylsilane), 2,4,6-cycloheptatriene-1-one, 3,5-bis-trimethylsilyl and α-amyrin were the active components found in eRoMi as detected by GC–MS. Oral administration of eRoMi (200 mg/kg BW) to rats significantly protected serum biochemical parameters (increased ALT, AST, LDH, bilirubin and GGT as well as depletion of antioxidant enzymes and hepatic GSH) and elevation in hepatic lipid peroxidation as compared to CCl4-treated rats. The hematological indices such as erythrocytes, hemoglobin, monocytes and lymphocytes were also normal in eRoMi-treated rats. The histopathological evaluation indicated a significant restoration of liver structure as compared to silymarin. This study is the first scientific validation for the traditional use of eRoMi to understand its hepatoprotective activity.
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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 | 0.001 | 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 | 0.000 |
| 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".