Polysaccharides from <i>Angelica</i> and <i>Astragalus</i> exert hepatoprotective effects against carbon-tetrachloride-induced intoxication in mice
Bibliographic record
Abstract
This study aimed to investigate the effects of polysaccharide from Angelica and Astragalus (AAP) on carbon tetrachloride (CCl4) induced liver damage in mice. A total of 120 Kunming mice were randomly distributed among 6 groups comprising (i) the normal control mice, (ii) the CCl4 treatment group, (iii) the bifendate treatment group, (iv) the AAP treatment group, (v) the Angelica sinensis polysaccharide (ASP) treatment group, and (vi) the Astragalus membranaceus polysaccharide (AMP) treatment group. AAP, ASP and AMP were administered to mice treated with CCl4. The activities of alanine transaminase (ALT) and aspartate transaminase (AST) in the serum, and superoxide dismutase (SOD) and malondialdehyde (MDA) in the liver tissues were quantified, as well as the liver index. Hepatic histological changes were observed by staining liver sections with hematoxylin and eosin. Our results show that bifendate, AAP, ASP, and AMP significantly decreased the activities of MDA, AST, and ALT, and enhanced the activity of SOD in CCl4-treated mice. Bifendate, AAP, ASP, and AMP consistently ameliorated the liver injuries induced with CCl4. Notably, the hepatoprotective effect of AAP was stronger than that of bifendate, ASP, or AMP. In addition, AAP alleviated liver inflammation and decreased the liver indexes of mice induced with CCl4. These effects were at least partly due to the antioxidant properties of AAP in scavenging free radicals to ameliorate oxidative stress and to inhibit lipid peroxidation.
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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".