Study of the Mechanism of Action of Guanxin Shutong Capsules in the Treatment of Coronary Heart Disease Based on Metabolomics
Bibliographic record
Abstract
Background: Guan-Xin-Shu-Tong capsule (GXSTC) is a traditional Chinese medicine (TCM) that has been used to treat coronary heart disease (CHD) for many years in China. However, the holistic mechanism of GXSTC against CHD is still unclear. Therefore, the purpose of this paper was to systematically explore the mechanism of action GXSTC in the treatment of CHD rats using a metabolomics strategy. Methods: A CHD model was induced by ligation of the left anterior descending coronary artery (LAD). In each group, echocardiography was performed; the contents of creatine kinase (CK), lactate dehydrogenase (LDH) and aspartate transaminase (AST) in serum were determined; and the myocardial infarct size was measured. The metabolites in plasma were analyzed by UHPLC-MS/MS-based untargeted metabolomics. Then, multivariate statistical analysis was performed to screen potential biomarkers associated with the GXSTC treatment in the LAD-induced rat CHD model. Finally, the MetaboAnalyst 4.0 platform was used for metabolic pathway enrichment analysis. Results: GXSTC was able to regulate the contents of CK, LDH and AST; restore impaired cardiac function; and significantly reduce the myocardial infarction area in model rats. Twenty-two biomarkers and nine metabolic pathways of GXSTC in the treatment of CHD were identified through UHPLC-MS/MS-based untargeted metabolomics analysis. Conclusion: GXSTC regulates metabolic disorders of endogenous components in LAD-induced CHD rats. The anti-CHD mechanism of GXSTC is mainly related to the regulation of amino acid, lipid and hormonal metabolism. This study provides an overall view of the mechanism underlying the action of GXSTC against CHD.
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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".