The Toxicity and Metabolism Properties of<i>Herba Epimedii</i>Flavonoids on Laval and Adult Zebrafish
Bibliographic record
Abstract
Zebrafish is being increasingly used for metabolism and toxicity assessment. The drugs consumed in zebrafish metabolism studies are far less than those used in rat studies. In our study, zebrafish embryos were exposed to icariin, Baohuoside I (BI), Epimedin A (EA), Epimedin B (EB), Epimedin C (EC), Sagittatoside A (SA), Sagittatoside B (SB), and 2''-O-rhamnosylicariside II (SC), respectively, to examine the toxicity and metabolic profiles of these flavonoids. The order of toxicity was SC, SB > EC, SA > BI, icariin, EA, EB. After 24 h exposure to SB and SC, the mortality of zebrafish larvae reached 100% and yolk sac swollen was obvious. Both SC and SB caused severe hepatocellular vacuolization and liver cells degeneration in adult zebrafish after 15 consecutive days' treatment. The metabolic profiles of these flavonoids with trace amount were also monitored in larvae. BI was the common metabolite shared by icariin, EA, EB, SA, and SB, via deglycosylation. Both BI and SC remained as the prototype in the medium, suggesting that it is hard for BI and SC to cleave the rhamnose residue. EC was metabolized into SC and BI in zebrafish, inferring that SC might be responsible for the toxicity observed in EC group. The metabolites of icariin, EA, EB, EC, and BI in zebrafish larvae coincided with results from rats and intestinal flora. These data support the use of this system as a surrogate in predicting metabolites and hepatotoxicity risk, especially for TCM compound with trace amount.
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 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".