Graft polymerization of vinyl monomers inside macroporous polyacrylamide gel,cryogel, in aqueous and aqueous‐organic media initiated by diperiodatocuprate(III) complexes

Graft polymerization initiated by diperiodatocuprate(III) complex (Cu(III)) initiator was found to be an effective and convenient method for graft polymerization of vinyl monomers onto macroporous polyacrylamide gels, the so‐called cryogels (pAAm‐cryogels). The effect of time, temperature, monomer and initiator concentration during the graft polymerization in aqueous and aqueous‐organic media was studied. The graft polymerization of water‐soluble monomers as [2‐(methacryloyloxy)ethyl]‐trimethylammonium chloride, 2‐hydroxyethyl methacrylate, N‐isopropylacrylamide, and N,N‐dimethylacrylamide proceeds with higher grafting yield in aqueous medium, as compared with that in aqueous‐organic media. Graft polymerization in aqueous‐organic media such as water–DMSO solutions allows grafting of water‐insoluble monomers such as glycidyl methacrylate and N‐tert‐butylacrylamide with high grafting degrees of 100 and 410%, respectively. It was found that the deposition of initiator on the pore surface of cryogels promoted graft polymerization by facilitating the formation of the redox couple Cu(III)‐acrylamide group. © 2006 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 44: 1952–1963, 2006     

Application of associative neural networks for prediction of lipophilicity in ALOGPS 2.1 program

This article provides a systematic study of several important parameters of the Associative Neural Network (ASNN), such as the number of networks in the ensemble, distance measures, neighbor functions, selection of smoothing parameters, and strategies for the user-training feature of the algorithm. The performance of the different methods is assessed with several training/test sets used to predict lipophilicity of chemical compounds. The Spearman rank-order correlation coefficient and Parzen-window regression methods provide the best performance of the algorithm. If additional user data is available, an improved prediction of lipophilicity of chemicals up to 2-5 times can be calculated when the appropriate smoothing parameters for the neural network are selected. The detected best combinations of parameters and strategies are implemented in the ALOGPS 2.1 program that is publicly available at http://www.vcclab.org/lab/alogps.     

Rational Krylov methods for fractional diffusion problems on graphs

BIT Numerical Mathematics - In this paper we propose a method to compute the solution to the fractional diffusion equation on directed networks, which can be expressed in terms of the graph...     

Feasibility of atmospheric pressure desorption/ionization on silicon mass spectrometry in analysis of drugs

The feasibility of atmospheric pressure desorption/ionization on silicon mass spectrometry (AP-DIOS-MS) for drug analysis was investigated. It was observed that only compounds with relative high proton affinity are efficiently ionized under AP-DIOS conditions. The limits of detection (LODs) achieved in MS mode with midazolam, propranolol, and angiotensin II were 80 fmol, 20 pmol, and 1 pmol, respectively. In MS/MS mode the LODs for midazolam and propranolol were 10 fmol and 5 pmol, respectively. The good linearity (r(2) > 0.991), linear dynamic range of 3 orders of magnitude, and reasonable repeatability showed that the method is suitable for quantitative analysis.     

Monitoring of ethanol during fermentation using a microbial biosensor with enhanced selectivity

The present study is concerning the construction of ferricyanide-mediated Gluconobacter oxydans cell ethanol biosensor. The size exclusion effect of a cellulose acetate membrane was used for elimination of glucose interferences during ethanol assays in real samples. A typical response time of the biosensor was 13 s with a high sensitivity of 3.5 microA mM(-1). The microbial biosensor exhibits a very low detection limit of 0.85 microM and a wide linear range from 2 to 270 microM. The operational stability was excellent. During 8.5 h of repetitive ethanol assays, no decrease in the sensor sensitivity was observed. The biosensor was successfully used in the off-line monitoring of ethanol fermentation with a good agreement with HPLC measurements (R(2)=0.998).