Toxicity of Tetradium ruticarpum: Subacute Toxicity Assessment and Metabolomic Identification of Relevant Biomarkers
Bibliographic record
Abstract
(TR) is widely used in Asia to treat gastrointestinal disorders and pain. Stir-frying with licorice aqueous extract is a traditional processing procedure of TR formed in a long-term practice and performed before clinical application, and believed to reduce TR's toxicity. However, its toxicity and possible toxicity attenuation approach are yet to be well investigated. Subacute toxicity and metabolomics studies were conducted to help understand the toxicity of TR. The subacute toxicity assessment indicated that 3 fold of the recommended therapeutic dose of TR did not show obvious subacute toxicity in rats. Although an extremely high dose (i.e., 60 fold of the recommended dose) may cause toxicity in rats, it reversed to normal after 2 weeks of recovery. Hepatocellular injury was the major toxic phenotype of TR-induced liver damage, indicating as aspartate aminotransferase (AST) and liver index increasing, with histopathologic findings as local hepatocyte necrosis, focal inflammatory cell infiltration, slightly bile duct hyperplasia, and partial hepatocyte vacuolation. Moreover, we evaluated the impact of processing in toxicity. TR processed with licorice could effectively reduce drug-induced toxicity, which is a valuable step in TR pretreatment before clinical application. Metabolomics profiling revealed that primary bile acid biosynthesis, steroid biosynthesis, and arachidonic acid metabolism were mainly involved in profiling the toxicity metabolic regulatory network. The processing procedure could back-regulate these three pathways, and may be in an Aryl hydrocarbon Receptor (AhR) dependent manner to alleviate the metabolic perturbations induced by TR. 7α-hydroxycholesterol, calcitriol, and taurocholic acid were screened and validated as the toxicity biomarkers of TR for potential clinical translation. Overall, the extensive subacute toxicity evaluation and metabolomic analysis would not only expand knowledge of the toxicity mechanisms of TR, but also provide scientific insight of traditional processing theory, and support clinical rational use of TR.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".