Chromatographic fingerprinting and quantitative analysis for the quality evaluation of Xinfeng capsule

A simple, accurate and sensitive method of high performance liquid chromatography (HPLC) with diode array detector was established to identify Xinfeng capsules and systematically evaluated its quality, based on chromatographic fingerprint integrated with the similarity analysis, hierarchical cluster analysis and the quantitative analysis of multi-components by single marker (QAMS). In this study, 18 peaks were selected as the common peaks to evaluate the similarities among different batches (S1–S10) of Xinfeng capsules samples, which were manufactured in the First Affiliated Hospital of Anhui University of Chinese Medicine with a three-year span. Compared to control fingerprint, the similarities values for 10 batches of samples were more than 0.90. Moreover, by analyzing the reference of astragalus, the chromatogram of astragalus was developed, and 10 common peaks of astragalus were identified. More importantly, simultaneous quantification of three markers in Xinfeng capsule, including Calycosin-7-glucoside, calycosin and Formononetinaldehyde was performed, the three constituents showed good regression (R > 0.999) within linear ranges, and their recoveries were within the range of 97.6–101.5%. The validation results showed that the developed method was specific, accurate, precise and robust. This study demonstrated that the developed method offers an efficient, reliable and practical approach for systematic quality evaluation of Xinfeng capsule.

Mechanism of Xinfeng Capsule on Adjuvant-Induced Arthritis via Analysis of Urinary Metabolomic Profiles

We aimed to explore the potential effects of Xinfeng capsule (XFC) on urine metabolic profiling in adjuvant-induced arthritis (AA) rats by using gas chromatography time-of-flight mass spectrometry (GC-TOF/MS). GC-TOF/MS technology was combined with multivariate statistical approaches, such as principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal projections to latent structures discriminant analysis (OPLS-DA). These methods were used to distinguish the healthy group, untreated group, and XFC treated group and elucidate potential biomarkers. Nine potential biomarkers such as hippuric acid, adenine, and L-dopa were identified as potential biomarkers, indicating that purine metabolism, fat metabolism, amino acid metabolism, and energy metabolism were disturbed in AA rats. This study demonstrated that XFC is efficacious for RA and explained its potential metabolomics mechanism.