Saikosaponin-d attenuates the development of liver fibrosis by preventing hepatocyte injuryThis paper is one of a selection of papers in this Special Issue, entitled International Symposium on Recent Advances in Molecular, Clinical, and Social Medicine, and has undergone the Journal's usual peer-review process.
Bibliographic record
Abstract
Treatment of liver fibrosis and cirrhosis remains a challenging field. Hepatocyte injury and the activation of hepatic stellate cells are the 2 major events in the development of liver fibrosis and cirrhosis. It is known that several Chinese herbs have significant beneficial effects on the liver; therefore, the purpose of the present study was to investigate the therapeutic effect of saikosaponin-d (SSd) on liver fibrosis and cirrhosis. A rat model of liver fibrosis was established using the dimethylnitrosamine method. Liver tissue and serum were used to examine the effect of SSd on liver fibrosis. A hepatocyte culture was also used to investigate how SSd can protect hepatocytes from oxidative injury induced by carbon tetrachloride. The results showed that SSd significantly reduced collagen I deposition in the liver and alanine aminotransferase level in the serum. Moreover, SSd decreased the content of TGF-beta1 in the liver, which was significantly elevated after dimethylnitrosamine induced liver fibrosis. Furthermore, SSd was able to alleviate hepatocyte injury from oxidative stress. In conclusion, SSd could postpone the development of liver fibrosis by attenuating hepatocyte injury.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".