Hepatoprotective Effect of Floccularia luteovirens (Agaricomycetes) Polysaccharides on Alcohol-Induced Acute Liver Injury in Mice
Bibliographic record
Abstract
Floccularia luteovirens mushroom polysaccharides (FLPs) have anti-inflammatory and antioxidant effects in many inflammatory diseases. However, its protective effect on alcoholic liver injury has not been studied. This study investigated the protective effects of FLPs on acute alcoholic liver injury in mice. After administering FLPs at doses of 200, 400, and 800 mg/kg for 14 days, it was found that FLPs could inhibit the levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), and γ-glutamyl transpeptidase (γ-GT) in the serum. FLPs also significantly reduced the levels of four inflammatory factors, interleukin (IL)-1α, IL-1β, IL-33, and tumor necrosis factor-α (TNF-α) in the serum. All dose groups of FLPs could significantly inhibit the levels of reactive oxygen species (ROS) and malondialdehyde (MDA) in liver tissues. At the same time, they could significantly increase the levels of catalase (CAT) and glutathione peroxidase (GSH-Px), enhancing the antioxidant capacity of the body, which confirmed the protective therapeutic effects of FLPs against oxidative stress and inflammation in alcoholic liver injury. The Western blot assay investigated the effect of FLPs on the NF-κB/NLRP3 signaling pathway in the liver tissues of mice with alcoholic liver injury, indicating that its mechanism of action may be to inhibit the expression of inflammatory factors such as IL-1β and suppress the NF-κB/NLRP3 inflammasome signaling pathway to achieve antioxidant and anti-inflammatory effects.
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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) | 0.000 | 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".