ABSTRACT
Objective: To establish an HPLC-ELSD method for simultaneous determination of astragaloside IV, ferulic acid, paeoniflorin, glycyrrhizic acid, vaccarin, naringin, neohesperidin, and platycodin D in Buxue Shengru Granules (BSG). Methods: The analysis of methanol extract of this drug was performed on a Diamonsil C18 (250 mm × 4.6 mm, 5 μm) with the mobile phase comprising of 0.1% formic acid aqueous solution-acetonitrile. Flow rate was 1 mL/min and column temperature was 30 ℃. The samples were tested on Evaporative Light-scattering Detector with drift tube temperature of 40 oC. Results: The analysis permitted very good separation of eight constituents within 52 min. The linearity ranges of the eight constituents were 62.5-1 250.0 μg/mL (r > 0.995 0). The average recoveries of eight constituents in the samples were in the range of 95.51%-99.47%, and the RSD ranged from 0.31% to 3.70%. Intraday and interday precisions RSD of the peak areas of the eight components were less than 3%; The repeatability RSD of each component ranged from 0.94% to 2.11%; Eight components had good stability within 18 h, and the concentration RSD of each component ranged from 0.98% to 2.86%. The content of vaccarin, paeoniflorin, ferulic acid, naringin, neohesperidin, platycodin D, astragaloside IV, and glycyrrhizic acid were 0.550 7-0.584 3, 19.657 9-19.952 1, 0.350 5-0.384 7, 18.794 7-19.557 3, 12.124 7-12.414 2, 0.610 7-0.631 3, 0.238 8-0.274 3, and 2.750 4-2.852 2 mg/g, respectively. Conclusion: This simple and accurate method can be used for the rapid quality control of BSG.
ABSTRACT
The mechanism of leukocyte elevation activity of Lvjiao Buxue granules was studied by establishing the active components-targets network and protein interactions network and analyzing the functions and pathways of targets. The main active ingredients of Lvjiao Buxue granules were obtained by TCMSP and literature excavation. Based on the DRAR-CPI, GeneCards and CoolGeN, the active components of Lvjiao Buxue granules were predicted and screened. Cytoscape software was used to construct the drug-active components-target network, and a protein database was constructed by using String database and Cytoscape software. The relation of the main active ingredients and targets were validated by Systems Dock Web Site. The GO and KEGG pathways involved in the targets were analyzed by DAVID databases. Using DisGeNET database to attribute the type of targets. The results showed that 49 active components and 89 targets of Lvjiao Buxue granules were involved. The network results showed that the composition of purine ribonucleosides, the regulation of cell death, especially the biological processes such as neutrophil and oxidative stress were mainly involved in the regulation of metabolic, cancer, tuberculosis, PI3K-Akt signaling and many other pathways to play its elevating leukocytes effect. This study reflects the characteristics of multi-components-multi-targets and multi-pathways of Lvjiao Buxue granules, which laid the foundation for further research into the mechanism of leukocyte elevation activity of Lvjiao Buxue granules.
ABSTRACT
Hemolytic anemia is a common clinical disease with diverse pathogenesis. In recent years, the incidence of hemolytic anemia is increasing dramatically. The present clinical treatment of immunosuppressive agents or splenectomy is effective to some extent; however, the accompanied clinical adverse reactions are also significant. Traditional Chinese medicine (TCM) has beneficial therapeutic effect on hemolytic anemia, with the obvious advantages including curative effect, less adverse reactions, and low price. The pathogenesis of hemolytic anemia as well as the pharmacological effects and mechanisms of the compound, single herb, and monomer composition of TCM in the treatment of hemolytic anemia were reviewed, aiming to provide the basis for the clinical treatment of hemolytic anemia and the modern research on the mechanism of TCM.
ABSTRACT
A novel method was developed for the rapid determination of multi-indicators in corni fructus by means of near infrared (NIR) spectroscopy. Particle swarm optimization (PSO) based least squares support vector machine was investigated to increase the levels of quality control. The calibration models of moisture, extractum, morroniside and loganin were established using the PSO-LS-SVM algorithm. The performance of PSO-LS-SVM models was compared with partial least squares regression (PLSR) and back propagation artificial neural network (BP-ANN). The calibration and validation results of PSO-LS-SVM were superior to both PLS and BP-ANN. For PSO-LS-SVM models, the correlation coefficients (r) of calibrations were all above 0.942. The optimal prediction results were also achieved by PSO-LS-SVM models with the RMSEP (root mean square error of prediction) and RSEP (relative standard errors of prediction) less than 1.176 and 15.5% respectively. The results suggest that PSO-LS-SVM algorithm has a good model performance and high prediction accuracy. NIR has a potential value for rapid determination of multi-indicators in Corni Fructus.