Pharmacodynamic substances in Salvia miltiorrhiza for prevention and treatment of hyperlipidemia and coronary heart disease based on lipidomics technology and network pharmacology analysis.

In this study, untargeted lipidomics based on UPLC-Q/TOF-MS, network pharmacology and atomic force microscopy were used to explore the common biomarkers of hyperlipidemia and coronary heart disease, the therapeutic mechanism of the main components of Salvia miltiorrhiza as well as the action mechanism of key lipids. Firstly, the serum samples of 30 healthy people, 30 patients with coronary heart disease and 30 patients with hyperlipidemia were analyzed by using lipidomics technology to obtain biomarkers which can be used to link hyperlipidemia and coronary heart disease and to find potential targets; then, the key components and core targets of Salvia miltiorrhiza intervention in hyperlipidemia and coronary heart disease were analyzed by network pharmacology, the results were verified by atomic force microscopy. It showed that SMS2 might be the key target. And through network pharmacology and atomic force microscope analysis, it can be inferred that salvianolic acid A can combine with SMS2 to play a therapeutic role.

Analysis of biomarkers and metabolic pathways in patients with unstable angina based on ultra­high­performance liquid chromatography­quadrupole time­of­flight mass spectrometry.

Unstable angina (UA) is a coronary disease with a high mortality and morbidity worldwide. The present study aimed to use non­invasive techniques to identify urine biomarkers in patients with UA, so as to provide more information for the early diagnosis and treatment of the disease. Based on metabolomics, urine samples from 28 patients with UA and 28 healthy controls (HCs) were analyzed using ultra­high­performance liquid chromatography­quadrupole time­of­flight mass spectrometry (UPLC­Q­TOF/MS). A total of 16 significant biomarkers that could distinguish between patients with UA and HCs, including D­glucuronic acid, creatinine, succinic acid and N­acetylneuraminic acid, were identified. The major metabolic pathways associated with UA were subsequently analyzed by non­targeted metabolomics. The results demonstrated that amino acid and energy metabolism, fatty acid metabolism, purine metabolism and steroid hormone biosynthetic metabolism may serve important roles in UA. The results of the current study may provide a theoretical basis for the early diagnosis of UA and novel treatment strategies for clinicians. The trial was registered with the Chinese Clinical Trial Registration Center (registration no. ChiCTR­ROC­17013957) at Tianjin University of Traditional Chinese Medicine.

Liquiritinapioside - A mineralocorticoid-like substance from liquorice.

Surface plasmon resonance (SPR) analysis of the main components of liquorice was performed and a novel strong mineralocorticoid receptor (MR) agonist, namely liquiritinapioside (LA), whose the binding constant was 1.093 × 10-5 M, was reported. As a supplement, LA has been further demonstrated to have a strong MR binding capacity through competitive binding experiments (the enrichment factor of LA was 10.22%). This study also validated the activity of LA on H9c2 cells. The expression of collagen I and the results of Masson staining were used to determine the ability of this substance to cause H9c2 cell fibrosis. Moreover, western blotting was used to verify the mechanism of compound-induced myocardial fibrosis. Overall, the attained results showed that LA could induce the activation of the TGF-ß1/p38 MAPK signalling pathway through the MR to induce H9c2 cell fibrosis.

A Large-Scale, Multi-Center Urine Biomarkers Identification of Coronary Heart Disease in TCM Syndrome Differentiation.

Coronary heart disease (CHD) threatens human health. The discovery and assessment of potential biometabolic markers for different syndrome types of CHD may contribute to decipher pathophysiological mechanisms and identify new targets for diagnosis and treatment. On the basis of UPLC-Q-TOF/MS metabolomics technology, urine samples of 1072 participants from nine centers, including normal control, phlegm and blood stasis (PBS) syndrome and Qi and Yin deficiency (QYD) syndrome, and other syndromes of CHD, were conducted to find biomarkers. Among them, the discovery set ( n = 125) and the test set ( n = 337) were used to identify and validate biomarkers, and the validation set ( n = 610) was used for the application and evaluation of the support vector machine (SVM) prediction model. We discovered 15 CHD-PBS syndrome biomarkers and 12 CHD-QYD syndrome biomarkers, and the receiver-operator characteristic (ROC) area-under-the-curve (AUC) values of them were 0.963 and 0.990. The established SVM model has a good diagnostic ability and can well distinguish the two syndromes of CHD with a high predicted accuracy >98.0%. The discovery of biomarkers and metabolic pathways in different syndrome types of CHD provides a basis for the diagnosis and evaluation of CHD, thereby improving the accurate diagnosis and precise treatment level of Chinese medicine.