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https://www.selleckchem.com/products/mm3122.html ole in reflecting sepsis prognosis.A precise HPLC-DAD-based quantification together with the metabolomics statistical method was developed to distinguish and control the quality of Fallopia multiflora, a popular medicinal material in Vietnam. Multivariate statistical methods such as hierarchical clustering analysis and principal component analysis were utilized to compare and discriminate six natural and twelve commercial samples. 2,3,4',5-Tetrahydroxystilbene 2-O-β-D-glucopyranoside (THSG) (1), emodin (4), and the new compound 6-hydroxymusizin 8-O-α-D-apiofuranosyl-(1⟶6)-β-D-glucopyranoside (5) could be considered as important markers for classification of F. multiﬂora. Furthermore, seven phenolics were quantified that the variation in the contents of selected metabolites revealed the differences in the quality of natural and commercial samples. Recovery of the compounds from the analytes was more than 98%, while the limits of detection (LOD) and the limits of quantitation (LOQ) ranged from 0.5 to 6.6 μg/ml and 1.5 to 19.8 μg/ml, respectively. The linearity, LOD, LOQ, precision, and accuracy satisfied the criteria FDA guidance on bioanalytical methods. Overall, this method is a promising tool for discrimination and quality assurance of F. multiflora products.In this study, a sensitive and selective sensor is constructed to measure the melamine (MEL) using molecular imprinting polymer (MIP) technique. Chemical and electrochemical techniques are used to construct the MIP and quantitative measurements. The constructed sensor was modified with GO-Fe3O4@SiO2 nanocomposite. Screening and optimization of factors are done using statistical methods, including Plackett-Burman design (PBD) and central composite design (CCD). Under the optimized conditions, an MIP sensor showed a linear range from 5.0 × 10-7 to 1.0 × 10-5 M MEL concentration with a correlation coefficient (R2) of 0.9997. The limit of detection was obtained (0.02

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