Pharmacokinetics Comparison, Intestinal Absorption and Acute Toxicity Assessment of a Novel Water-Soluble Astragaloside IV Derivative (Astragalosidic Acid, LS-102).

BACKGROUND AND OBJECTIVES: Astragaloside IV (AGS IV) is the most important bioactive constituent of Radix Astragali. However, its disappointing clinical application is mainly caused by its very low solubility in biologic fluids, resulting in poor bioavailability after oral administration. We recently obtained a novel water-soluble derivative of AGS IV (astragalosidic acid, LS-102) that displayed significant cardioprotective potential against hypoxia-induced injury. The objective of this study was to investigate the intestinal absorption, main pharmacokinetic parameters and acute toxicity of LS-102 in rodents compared with AGS IV. METHODS: An oral dose of LS-102 and AGS IV (20 mg/kg) was administered to Sprague-Dawley (SD) rats, and blood samples were collected at predetermined time points. The plasma concentrations were detected by a validated UHPLC-MS/MS method, and pharmacokinetic parameters were calculated using a compartmental model. In the intestinal permeability study, the transport of LS-102 across Caco-2 cell monolayers was investigated at six concentrations from 6.25 to 250 µM. Moreover, the acute toxicity of LS-102 (40-5000 mg/kg) via a single oral administration was investigated in BALB/c mice. RESULTS: LS-102 was rapidly absorbed, attaining a maximum concentration of 248.7 ± 22.0 ng/ml at 1.0 ± 0.5 h after oral administration. The relative bioavailability of LS-102 was twice that of AGS IV. LS-102 had a Papp (mean) of 15.72-25.50 × 10-6 cm/s, which was almost 500-fold higher than that of AGS IV, showing that LS-102 had better transepithelial permeability and could be better absorbed in the intestinal tract. The acute toxicity study showed no abnormal changes or mortality in mice treated with LS-102 even at the single high dose of 5000 mg/kg body weight. CONCLUSIONS: Oral LS-102 produced a pharmacokinetic profile different from AGS IV with higher bioavailability, while the toxic tolerance was similar to previous estimates. Thus, we speculated that LS-102 might provide better clinical efficacy and be a potential candidate for the new drug development of Radix Astragali.

Discovery of markers for discriminating the age of cultivated ginseng by using UHPLC-QTOF/MS coupled with OPLS-DA.

BACKGROUND: Ginseng (Ginseng Radix et Rhizoma, Panax ginseng C.A. Meyer) is gaining more publicity in modern society due to its health benefit and huge value in market. In the practice of grading and pricing of ginseng, the age is one of the major factor influencing the price and grade of ginseng. Therefore, the age discrimination is an important task for the quality control of ginseng. However, the traditional morphological methods are too subjective to be reproductive in discrimination. PURPOSE: To establish a method that can discriminate the ginseng samples with different cultivation years. STUDY DESIGN: To analyze the correlation between chemical compositions and cultivation years of cultivated ginseng samples of different age and thus discover potential quality marker (Q-marker) for discriminating the age of cultivated ginseng. METHODS: In the present study, the ultra-high performance liquid chromatography coupled with the quadrupole-time of flight mass spectrometry (UHPLC-QTOF/MS) were utilized for the age discrimination and marker discovery. A statistical data processing procedure was established to screen markers and reduce the false positive rate. RESULTS: The results showed that the ginseng samples from 2- to 6-year-old could be well separated in the orthogonal projections on the latent structure - discrimination analysis (OPLS-DA) using the markers screened by the established statistical procedure, which could reduce approximately 20% of the insignificant markers and false positive discoveries. Ultimately, more than 50 compounds contributing to the age discrimination were identified including one new compound (malonylginsenoside). One negative marker (1038.4825@8.98) was discovered for the 2-year-old ginseng, and an equation was established to effectively predict the age of 3- to 6-year-old of ginseng. CONCLUSION: The constructed method can discriminate the ginseng samples with different cultivation years and is a complement to the traditional discrimination method of ginseng age.

An integrated strategy for rapid discovery and identification of quality markers in Guanxin Kangtai preparation using UHPLC-TOF/MS and multivariate statistical analysis.

BACKGROUND: Guanxin Kangtai preparation (GXKT), consisting of Panax ginseng, Panax notoginseng and Ilex pubescens, is a new proprietary Chinese medicines under development for treating coronary heart disease. Like other Chinese medicines, the components of GXKT were complex and the bioactive compounds remained unclear. PURPOSE: To discover bioactive compounds as quality markers (Q-markers) for better quality control of GXKT. STUDY DESIGN: Chinese medicines was separated into fractions. The correlation between chemical information and bioactivity of these fractions were analyzed with multivariate statistical methods to discover bioactive compounds responsible for the actions of Chinese medicine. METHOD: GXKT was separated into fractions by using high-performance liquid chromatography (HPLC). Ultra HPLC coupled with time-of-flight mass spectrometer (UHPLC-TOF/MS) was applied to detect compound information from these fractions to form a chemical database. The bioactivity of these fractions in protecting cardiomyocytes from ischemia/reperfusion injury was examined in H9c2 cells that were exposed to hypoxia followed by reoxygenation (H/R). Then, partial least square model and orthogonal projections to latent structures discriminant analysis were employed to discover bioactive compounds from the chemical database that were positively correlated with the bioactivity of GXKT fractions. Finally, the bioactivity of these compounds was confirmed by bioassay in H9c2 cells. RESULTS: The chemical information of 120 fractions separated from GXKT was detected and extracted by UHPLC-TOF/MS, and a chemical database including 61 high abundance compounds were formed from all fractions. These fractions produced different extent of protective effect to H9c2 cell underwent H/R treatment with cell viability ranging from 33.43% to 74.91%, demonstrating the separation of bioactive compounds among different fractions. The multivariate analysis discovered 16 compounds from GXKT positively correlated with the bioactivity of GXKT. Of these compounds, 6 compounds, i.e.: ginsenoside Rg1, Rb1, Rh1, Rc, ilexsaponin A1, and chikusetsusaponin IVa were chemical identified and also confirmed for their responsibility to the action of GXKT by bioassay. CONCLUSION: Ginsenoside Rg1, Rb1, Rh1, Rc, ilexsaponin A1, and chikusetsusaponin IVa were bioactive compounds and qualified as Q-markers for quality control of GXKT. This research provided a useful reference for the quality research of Chinese medicines.

Suppressing mPGES-1 expression by sinomenine ameliorates inflammation and arthritis.

Recently, microsomal prostaglandin E synthase 1 (mPGES-1) has attracted much attention from pharmacologists as a promising strategy and an attractive target for treating various types of diseases including rheumatoid arthritis (RA), which could preserve the anti-inflammatory effect while reducing the adverse effects often occur during administration of non-steroidal anti-inflammatory drugs (NSAIDs). Here, we report that sinomenine (SIN) decreased prostaglandin (PG)E2 levels without affecting prostacyclin (PG)I2 and thromboxane (TX)A2 synthesis via selective inhibiting mPGES-1 expression, a possible reason of low risk of cardiovascular event compared with NSAIDs. In addition, mPGES-1 protein expression was down-regulated by SIN treatment in the inflamed paw tissues both in carrageenan-induced edema model in rats and the collagen-II induced arthritis (CIA) model in DBA mice. More interestingly, SIN suppressed the last step of mPGES-1 gene expression by decreasing the DNA binding ability of NF-κB, paving a new way for drug discovery.

Purity assessment of ginsenoside Rg1 using quantitative 1H nuclear magnetic resonance.

Ginseng herbs comprise a group of the most popular herbs, including Panax ginseng, P. notoginseng and P. quinquefolius (Family Araliaceae), which are used as traditional Chinese medicine (TCM) and are some of the best-selling natural products in the world. The accurate quantification of ginsenoside Rg1 is one of the major aspects of its quality control. However, the purity of the commercial Rg1 chemical reference substance (CRS) is often measured with high-performance chromatography coupled with an ultraviolet detector (HPLC-UV), which is a selective detector with unequal responses to different compounds; thus, this detector introduces probable error to purity assessments. In the present study, quantitative nuclear magnetic resonance (qNMR), due to its absolute quantification ability, was applied to accurately assess the purity of Rg1 CRS. Phenylmethyl phthalate was used as the internal standard (IS) to calibrate the purity of Rg1 CRS. The proton signal of Rg1 CRS in methanol-d4 at 4.37ppm was selected to avoid interfering signals, enabling accurate quantitative analysis. The relaxation delay, number of scans, and NMR windowing were optimized for data acquisition. For post-processing, the Lorentz/Gauss deconvolution method was employed to increase the signal accuracy by separating the impurities and noise in the integrated region of the quantitative proton. The method validation showed that the developed method has acceptable sensitivity, linearity, precision, and accuracy. The purity of the commercial Rg1 CRS examined with the method developed in this research was 90.34±0.21%, which was obviously lower than that reported by the manufacturer (>98.0%, HPLC-UV). The cross-method validation shows that the commonly used HPLC-UV, HPLC-ELSD (evaporative light scattering detector) and even LC-MS (mass spectrometry) methods provide significantly higher purity values of Rg1 CRS compared with the qNMR method, and the accuracy of these LC-based methods largely depend on the amount of the sample that was loaded and the properties of the impurities.