Guo Yin

New phenanthrene derivatives with nitric oxide inhibitory and radical-scavenging activities from Pholidota imbricata Hook.

One new phenanthrene derivative phoimbrtol A (1) with seven known compounds, loddigesiinol B (2), shanciol B (3), (–)-medioresinol (4), (–)-pinoresinol (5), quercetin 3-O-β-l-arabinofuranoside (6), luteolin 7-O-β-glucoside (7) and platycaryanin D (8) have been isolated from the ethyl acetate extract of the air-dried whole plant of Pholidota imbricata Hook. Their inhibitory effects on nitric oxide (NO) production and 1,1-diphenyl-2-picrylhydrazil (DPPH) radical scavenging activity were examined. Among these compounds, 8 exhibited the most potent activity at NO production inhibitory assay and DPPH radical scavenging assay, stronger than those of the familiar antioxidative agents, quercetin and resveratrol.

Metabonomic Study of Biochemical Changes in Human Hair of Heroin Abusers by Liquid Chromatography Coupled with Ion Trap-Time of Flight Mass Spectrometry.

Hair analysis is with the advantage of non-invasive collection and long surveillance window. The present study employed a sensitive and reliable liquid chromatography coupled with ion trap-time of flight mass spectrometry method to study the metabonomic characters in the hair of 58 heroin abusers and 72 non-heroin abusers. Results indicated that certain endogenous metabolites, such as sorbitol and cortisol, were accelerated, and the level of arachidonic acid, glutathione, linoleic acid, and myristic acid was decreased in hair of heroin abusers. The metabonomic study is helpful for further understanding of heroin addiction and clinical diagnosis.

Identification of Salvia species using HPLC combined with chemical pattern recognition analysis

Salvia miltiorrhiza, also known as Danshen, is a widely used traditional Chinese medicine for the treatment of cardiovascular diseases and hematological abnormalities. The root and rhizome of Salvia przewalskii and Salvia yunnanensis have been found as substitutes for Salvia miltiorrhiza in the market. In this study, the chemical information of 14 major compounds in Salvia miltiorrhiza and its substitutes were determined using a high-performance liquid chromatography method. Stepwise discriminant analysis was adopted to select the characteristic variables. Partial least squares discriminant and hierarchical cluster analysis were performed to classify Salvia miltiorrhiza and its substitutes. The results showed that all of the samples were correctly classified both in partial least squares discriminant analysis and hierarchical cluster analysis based on the four compounds (caffeic acid, rosmarinic acid, salvianolic acid B, and salvianolic acid A). This method can not only distinguish Salvia miltiorrhiza and its substitutes, but also classify Salvia przewalskii and Salvia yunnanensis. The method can be applied for the quality assessment of Salvia miltiorrhiza and identification of unknown samples.

Potential of near infrared spectroscopy and pattern recognition for rapid discrimination and quantification of Gleditsia sinensis thorn powder with adulterants

HIGHLIGHTSFT‐NIR spectroscopy coupled with chemometric techniques was applied to quality control of Gleditsia Sinensis Thorn (GST).Three spectral regions combined with five pre‐processing methods were used to improve performance of classification models.BPNN classification model with 6500–5500cm−1 showed 100% identification accuracy among authentic and adulterated GST samples.In the quantitative study, PLS regression gives good predicted ability of the adulterants content in GST samples. ABSTRACT The Gleditsia sinensis Lam thorn (GST) is a classical traditional Chinese medical herb, which is of high medical and economic value. GST could be easily adulterated with branch of Rosa multiflora thunb (BRM) and Rosa rugosa thumb (BRR), because of their similar appearances and much lower cost for these adulterants. In this study Fourier transform near‐infrared spectroscopy (FT‐NIR) combined with chemical pattern recognition techniques was explored for the first time to discriminate and quantify of cheaper materials (BRM and BRR) in GST. The Savitzkye‐Golay (SG) smoothing, vector normalization (VN), min max normalization (MMN), first derivative (1st D) and second derivative (2nd D) methods were used to pre‐process the raw FT‐NIR spectra. Successive projections algorithm was adopted to select the characteristic variables and linear discriminate analysis (LDA), support vector machine (SVM), as while as back propagation neural network (BPNN) algorithms were applied to construct the identification models. Results showed that BPNN models performance best compared with LDA and SVM models for it could reach 100% accuracy for identifying authentic GST, and GST adulterated with BRM and BRR based on the spectral region of 6500–5500 cm−1 combined with 1st D pre‐processing. In addition, the BRM and BRR content in adulterated GST were determined by partial least squares (PLS) regression. The correlation coefficient of prediction (rp), root mean square error of prediction (RMSEP) and bias for the prediction by PLS regression model were 0.9972, 1.969% and 0.3198 for BRM, 0.9972, 1.879% and 0.05408 for BRR, respectively. These results suggest that the combination of NIR spectroscopy and chemometric methods offers a simple, fast and reliable method for classification and quantification in the quality control of the tradition Chinese medicine herb of GST.