Metabolic profiles of dioscin in rats revealed by ultra‐performance liquid chromatography quadrupole time‐of‐flight mass spectrometry

Dioscin (DIS), one of the most abundant bioactive steroidal saponins in Dioscorea sp., is used as a complementary medicine to treat coronary disease and angina pectoris in China. Although the pharmacological activities and pharmacokinetics of DIS have been well demonstrated, information regarding the final metabolic fates is very limited. This study investigated the in vivo metabolic profiles of DIS after oral administration by ultra‐performance liquid chromatography quadrupole time‐of‐flight mass spectrometry method. The structures of the metabolites were identified and tentatively characterized by means of comparing the molecular mass, retention time and fragmentation pattern of the analytes with those of the parent compound. A total of eight metabolites, including seven phase I and one phase II metabolites, were detected and tentatively identified for the first time. Oxidation, deglycosylation and glucuronidation were found to be the major metabolic processes of the compound in rats. In addition, a possible metabolic pathway on the biotransformation of DIS in vivo was proposed. This study provides valuable and new information on the metabolism of DIS, which will be helpful for further understanding its mechanism of action. Copyright © 2015 John Wiley & Sons, Ltd.     

DFT mechanistic study of the H2‐assisted chain transfer copolymerization of propylene and p‐methylstyrene catalyzed by zirconocene complex

DFT computations have been performed to investigate the mechanism of H₂‐assisted chain transfer strategy to functionalize polypropylene via Zr‐catalyzed copolymerization of propylene and p‐methylstyrene (pMS). The study unveils the following: (i) propylene prefers 1,2‐insertion over 2,1‐insertion both kinetically and thermodynamically, explaining the observed 1,2‐insertion regioselectivity for propylene insertion. (ii) The 2,1‐inserion of pMS is kinetically less favorable but thermodynamically more favorable than 1,2‐insertion. The observation of 2,1‐insertion pMS at the end of polymer chain is due to thermodynamic control and that the barrier difference between the two insertion modes become smaller as the chain length becomes longer. (iii) The pMS insertion results in much higher barriers for subsequent either propylene or pMS insertion, which causes deactivation of the catalytic system. (iv) Small H₂ can react with the deactivated [Zr]?pMS?PP_n facilely, which displace functionalized pMS?PP_n chain and regenerate [Zr]? H active catalyst to continue copolymerization. The effects of counterions are also discussed. © 2014 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2015 , 53, 576–585     

A Photoactivated Cu–CeO2 Catalyst with Cu-[O]-Ce Active Species Designed through MOF Crystal Engineering

Fully utilizing solar energy for catalysis requires the integration of conversion mechanisms and therefore delicate design of catalyst structures and active species. Herein, a MOF crystal engineering method was developed to controllably synthesize a copper–ceria catalyst with well-dispersed photoactive Cu-[O]-Ce species. Using the preferential oxidation of CO as a model reaction, the catalyst showed remarkably efficient and stable photoactivated catalysis, which found practical application in feed gas treatment for fuel cell gas supply. The coexistence of photochemistry and thermochemistry effects contributes to the high efficiency. Our results demonstrate a catalyst design approach with atomic or molecular precision and a combinatorial photoactivation strategy for solar energy conversion.     

Origins of Boosted Charge Storage on Heteroatom-Doped Carbons

Although tremendous efforts have been devoted to understanding the origin of boosted charge storage on heteroatom-doped carbons, none of the present studies has shown a whole landscape. Herein, by both experimental evidence and theoretical simulation, it is demonstrated that heteroatom doping not only results in a broadened operating voltage, but also successfully promotes the specific capacitance in aqueous supercapacitors. In particular, the electrolyte cations adsorbed on heteroatom-doped carbon can effectively inhibit hydrogen evolution reaction, a key step of water decomposition during the charging process, which broadens the voltage window of aqueous electrolytes even beyond the thermodynamic limit of water (1.23 V). Furthermore, the reduced adsorption energy of heteroatom-doped carbon consequently leads to more stored cations on the heteroatom-doped carbon surface, thus yielding a boosted charge storage performance.     

An Improved Composite Multiscale Fuzzy Entropy for Feature Extraction of MI-EEG

Motor Imagery Electroencephalography (MI-EEG) has shown good prospects in neurorehabilitation, and the entropy-based nonlinear dynamic methods have been successfully applied to feature extraction of MI-EEG. Especially based on Multiscale Fuzzy Entropy (MFE), the fuzzy entropies of the τ coarse-grained sequences in τ scale are calculated and averaged to develop the Composite MFE (CMFE) with more feature information. However, the coarse-grained process fails to match the nonstationary characteristic of MI-EEG by a mean filtering algorithm. In this paper, CMFE is improved by assigning the different weight factors to the different sample points in the coarse-grained process, i.e., using the weighted mean filters instead of the original mean filters, which is conductive to signal filtering and feature extraction, and the resulting personalized Weighted CMFE (WCMFE) is more suitable to represent the nonstationary MI-EEG for different subjects. All the WCMFEs of multi-channel MI-EEG are fused in serial to construct the feature vector, which is evaluated by a back-propagation neural network. Based on a public dataset, extensive experiments are conducted, yielding a relatively higher classification accuracy by WCMFE, and the statistical significance is examined by two-sample t-test. The results suggest that WCMFE is superior to the other entropy-based and traditional feature extraction methods.