ABSTRACT
Allergic diseases, mainly mediated by T helper type 2 (Th2) immunity, have become a worldwide public health problem. Traditional Chinese medicine (TCM) has long been used in treating and preventing allergic symptoms. As the new target of anti-allergy TCM, basophils, after approximately 140 years since their discovery, are just now gaining respect as important contributors in the pathogenesis underlying allergic inflammation and disease. In addition to their role as effector cells, basophils can release early IL-4, migrate from circulatory system into draining lymph nodes, present antigen to naive CD4+ T cells, and promote the differentiation of Th2 cells. Herein, we briefly summarized the recent research advances of the essential contributions of basophils in the initiation of Th2 immune responses.
ABSTRACT
Objective: To identify and comprehensively evaluate Cynomorium songaricum from different producing areas in order to provide reference for the quality evaluation of C. songaricum and the determination of the suitability of the origin. Methods: A total of 40 samples from five provinces (regions) were collected to measure the content of gallic acid, protocatechuic acid, catechins, total polysaccharides, total flavonoids, Na, K, Ca, Mg, Fe, Zn, Mn, Co, Sr, Ni, Ag, Ba, Ti, Cu, Pb, Cr, Cd, As, and Hg. The data reflecting the quality of C. songaricum were analyzed by orthogonal partial least squares discriminant analysis (OPLS-DA) and entropy weight TOPSIS analysis. Results: The contents of Mn, Zn, Co, catechin, Pb, Cr, Ca, Ti, total flavonoids, protocatechuic acid, Mg and Cu in C. songaricum are important for distinguishing different producing areas. The quality of C. songaricum in Inner Mongolia was the best in all provinces (regions), followed by Gansu, Ningxia, Xinjiang, and Qinghai Provinces. Conclusion: The results of OPLS-DA combined with entropy weight TOPSIS analysis are reasonable, objective and effective, and can be applied to the comprehensive evaluation of multiple indicators of C. songaricum.
ABSTRACT
Objective::To establish a pre-column derivatization reverse-phase high-performance liquid chromatography (RP-HPLC) method for the simultaneous determination of 17 amino acids in Cynomorii Herba from different producing areas and conduct a multivariate statistical analysis. Method::RP-HPLC with pre-column derivatization was employed, with phenyl isothiocyanate (PITC) as derivatization reagent. Separation was performed on a WondaSil C18-WR column (4.6 mm×150 mm, 5 μm), with 0.05 mol·L-1 sodium acetate solution (pH 6.5) as mobile phase A, and acetonitrile-methanol-water (3∶1∶1) as mobile phase B for gradient elution at a flow rate of 0.8 mL·min-1. The detective wave length was set at 254 nm, and the column temperature was maintained at 35 ℃. Principal component analysis (PCA) and systematic cluster analysis (HCA) models were established for multivariate statistical analysis and quality evaluation. Result::17 Kinds of amino acid were detected in Cynomorii Herba, 7 of which were essential amino acids. The 17 amino acids showed good linearity in respective concentration range, r = 0.999 0-0.999 9.The average recoveries were between 98.03%-103.89%with RSD<3.5%. The results of PCA and HCA were basically the same, and both methods can be used to clearly distinguish Cynomorii Herba from 12 municipal producing areas into 6 regions. PCA can be used to classify Cynomorii Herba according to different municipal or provincial production areas, and HCA can be used to classify it according to provincial production areas. It showed that the amino acid contents in Cynomorii Herba from different municipal and provincial producing areas had differences, and the content distribution showed obvious geographical clustering characteristics. PCA showed that Cynomorii Herba from Gansu province and Inner Mongolia had higher amino acid contents and better quality as compared with other producing areas. Conclusion::The established method can be used for content determination of 17 amino acids in Cynomorii Herba from different producing areas, and provide a reference for its comprehensive quality evaluation.
ABSTRACT
Objective: To realize the classification and identification of Cynomorii Herba from different producing areas based on fourier transform infrared spectroscopy (FTIR) and chemometrics. Method: FTIR spectrum data of 106 batches of Cynomorii Herba from 12 cities in 5 provinces were collected by transmission method and preprocessed. The FTIR fingerprints of Cynomorii Herba were established, and spectrum analysis was performed. The FTIR similarities of Cynomorii Herba from different producing areas were calculated by correlation coefficient method. The first derivative (1D) spectrum of average FTIR of Cynomorii Herba from different producing areas were obtained. The soft independent modeling of class analog (SIMCA) model based on principal component analysis (PCA) was established by the preprocessed 1D spectrum data. The orthogonal partial least squares (OPLS) model was established by top 6 principal components. Result: The FTIR fingerprint trend and main absorption peaks of Cynomorii Herba from different producing areas were basically the same,and 16 common characteristic absorption peaks were recognized. Similarity and 1D spectrum of FTIR fingerprint of Cynomorii Herba from different producing areas showed significant and unique characteristics. The established SIMCA model can realize the classification and identification of Cynomorii Herba from different provinces,while OPLS model can realize accurate classification and identification of Cynomorii Herba in different cities. The classification and identification of Cynomorii Herba from 12 city producing areas showed obvious geographical clustering characteristics. Conclusion: The established method based on FTIR and chemometrics can realize the classification and identification of Cynomorii Herba from 12 cities.