No abstract

An LC/MS/MS method for the rapid and simultaneous determination of low levels of eleven topical corticosteroids in creams was developed, optimized and validated. The proposed method can be used for testing of different products indicated for the treatment of atopic dermatitis, including "natural products", and "herbal creams" with "miraculous effects".

No abstract

Hydrogen evolution reaction (HER) was investigated on reduced graphene oxide (rGO)-supported Au and PdAu nanoparticles in acid solution. The graphene spread over glassy carbon (rGO/GC) was used as a support for the spontaneous deposition of Au and Pd. The resulting Au/rGO and PdAu/rGO electrodes were characterized using atomic force microscopy (AFM) and X-ray photoelectron spectroscopy (XPS) techniques. Phase AFM images have shown that the edges of the rGO sheets were active sites for the deposition of both Au and Pd. XPS analysis revealed that the atomic percentages of both Au and PdAu nanoparticles were slightly higher than 1%. The activity of the PdAu/rGO electrode for the HER was remarkably high, with the overpotential close to zero. HER activity was stable over a 3 h testing time, with a low Tafel slope of approx. −46 mV/dec achieved after prolonged hydrogen evolution at a constant potential.

The study of experimental design in conjunction with artificial neural networks for optimization of isocratic ultra performance liquid chromatography method for separation of mycophenolate mofetil and its degradation products has been reported. Experimental design showed to be suitable for selection of experimental scheme, while Kennard‐Stone algorithm was used for selection of training data set. The input variables were column temperature and composition of mobile phase including percentage of acetonitrile, concentration of ammonium acetate in buffer, and its pH value. The retention factor of the most retentive component and selectivity factors were used as the dependent variables (outputs). In this way, artificial neural network has been applied as a predictable tool in solving a method optimization problem using small number of experiments. Network architecture and training parameters were optimized to the lowest root‐mean‐square error values, and the network with 5‐4‐4‐4 topology has been selected as the most predictable one. Predicted data were in good agreement with experimental data, and regression statistics confirmed good ability of trained network to predict compounds retention. The optimal chromatographic conditions included column temperature of 40°C, flow rate of 700 µl min−1, 26% of acetonitrile and 9 mM ammonium acetate in mobile phase, and buffer pH of 5.87. The chromatographic analysis has been achieved within 5.2 min. The validation of the proposed method was also performed considering selectivity, linearity, accuracy, precision, limit of detection, and limit of quantification, and the results indicated that the method fulfilled all required criteria. The method was successfully applied to the analysis of commercial dosage form. Copyright © 2014 John Wiley & Sons, Ltd.