Theoretical approach to evaluate thermodiffusion in aqueous alkanol solutions

Flow due to thermodiffusion may change direction in fluid mixtures with the variation of composition and temperature. This occurrence remains an unraveled phenomenon in petroleum research. Using a modified theoretical approach, this paper evaluates the thermal diffusion factor in alkanol water mixtures, including methanol, ethanol, and isopropanol aqueous mixtures. By combining this approach with an equation of state perturbed chain statistical associating fluid theory and using two adjustable parameters calculated from experimental data, the present approach provides a good agreement for the prediction of thermal diffusion in alkanol water mixtures when compared with the available experimental data. This work reveals that the thermodiffusion in infinite dilutions may play an important role in understanding the thermodiffusion phenomena.     

New Disulfiram Derivatives as MAGL-Selective Inhibitors

Monoacylglycerol lipase (MAGL) is a key enzyme in the human endocannabinoid system. It is also the main enzyme responsible for the conversion of 2-arachidonoyl glycerol (2-AG) to arachidonic acid (AA), a precursor of prostaglandin synthesis. The inhibition of MAGL activity would be beneficial for the treatment of a wide range of diseases, such as inflammation, neurodegeneration, metabolic disorders and cancer. Here, the author reports the pharmacological evaluation of new disulfiram derivatives as potent inhibitors of MAGL. These analogues displayed high inhibition selectivity over fatty acid amide hydrolase (FAAH), another endocannabinoid-hydrolyzing enzyme. In particular, compound 2i inhibited MAGL in the low micromolar range. However, it did not show any inhibitory activity against FAAH.     

Electric impedance study of elastic alternating propylene-carbon monoxide copolymer (PCO-200)

The electrical properties of elastic alternating propylene-carbon monoxide copolymer (PCO-200) were investigated using the impedance spectroscopy technique. The results revealed a phase transition at about 70 °C where the material transforms from its insulating phase of conductivity in the order of 6×10⁻⁹ to about 9×10⁻⁵ (Ω m)⁻¹, The second phase is characterized by temperature dependent electrical relaxation phenomena. The plot of the complex electric modulus and the complex impedance yields semicircles in the temperature range 70 up to 110 °C and a decreasing radius with increasing temperature. The activation energy was found to be in the order of 0.8 eV.     

Solvent and conformation dependence of amide I vibrations in peptides and proteins containing proline

We present a mixed quantum-classical model for studying the amide I vibrational dynamics (predominantly CO stretching) in peptides and proteins containing proline. There are existing models developed for determining frequencies of and couplings between the secondary amide units. However, these are not applicable to proline because this amino acid has a tertiary amide unit. Therefore, a new parametrization is required for infrared-spectroscopic studies of proteins that contain proline, such as collagen, the most abundant protein in humans and animals. Here, we construct the electrostatic and dihedral maps accounting for solvent and conformation effects on frequency and coupling for the proline unit. We examine the quality and the applicability of these maps by carrying out spectral simulations of a number of peptides with proline in D(2)O and compare with experimental observations.     

Mixed ligand monolithic columns for reversed-phase capillary electrochromatography via hydrophobic and π interactions

Novel mixed ligand monoliths (MLM) for capillary electrochromatography (CEC) of a wide range of solutes differing in both polarity and size were introduced. The MLM capillary columns were based on the different compositions of octadecyl acrylate (ODA) and 2-naphthyl methacrylate (NAPM) monomers in the presence of trimethylolpropane trimethacrylate (TRIM) crosslinker and a ternary porogenic solvent made up of cyclohexanol, ethylene glycol, and water. As expected, the magnitude of the electroosmotic flow (EOF) changed with the composition of the MLM. As the percent of the monomer ODA in the polymerization mixture was increased, the EOF increased to a maximum at 50-mol% ODA and then leveled off at 75-mol% and 100-mol% ODA, an indication that the ODA ligand in general exhibited a higher binding for the mobile-phase ions than the NAPM ligand. This is due to the fact that the ODA is an acrylate-based monomer, whereas the NAPM is a methacrylate-based monomer. While ODA provided solely nonpolar interactions, NAPM exhibited both nonpolar and π interactions with certain solutes. It was found out that columns with a given composition of both ligands yielded a unique selectivity for a given set of solutes that was not matched by columns made by either ODA or NAPM alone. Several test mixtures were used in the evaluation of the MLM columns including polycyclic aromatic hydrocarbons, alkyl phenyl ketones, nitroalkanes, alkylbenzenes, toluene derivatives, peptides, and proteins. Peptide mapping of the tryptic digest of the standard lysozyme protein was also studied.     

Organic monoliths for hydrophilic interaction electrochromatography/chromatography and immunoaffinity chromatography

This article is aimed at providing a review of the progress made over the past decade in the preparation of polar monoliths for hydrophilic interaction LC (HILIC)/capillary electrochromatography (HI-CEC) and in the design of immuno-monoliths for immunoaffinity chromatography that are based on some of the polar monolith precursors used in HILIC/HI-CEC. In addition, this review article discusses some of the applications of polar monoliths by HILIC and HI-CEC, and the applications of immuno-monoliths. This article is by no means an exhaustive review of the literature; it is rather a survey of the recent progress made in the field with 83 references published in the past decade on the topics of HILIC and immunoaffinity chromatography monoliths.     

Modeling of thermotransport phenomenon in metal alloys using artificial neural networks

Thermodiffusion in molten metals, also known as thermotransport, a phenomenon in which constituent elements of an alloy separate under the influence of non-uniform temperature field, is of significance in several applications. However, due to the complex inter-particle interactions, there is no theoretical formulation that can model this phenomenon with adequate accuracy. Keeping in mind the severe deficiencies of the present day thermotransport models and an urgent need of a reliable method in several engineering applications ranging from crystal growth to integrated circuit design to nuclear reactor designs, an engineering approach has been taken in which neurocomputing principles have been employed to develop artificial neural network models to study and quantify the thermotransport phenomenon in binary metal alloys. Unlike any other thermotransport model for molten metals, the neural network approach has been validated for several types of binary alloys, viz., concentrated, dilute, isotopic and non-isotopic metals. Additionally, to establish the soundness of the model and to highlight its potential as a unified computational analysis tool, it ability to capture several thermotransport trends has been shown. Comparison with other models from the literature has also been made indicating a superior performance of this technique with respect to several other well established thermotransport models.