The calculation of neutron self-shielding factors of a group of isolated resonances

The resonance neutron self-shielding factor, G _res, is required in neutron metrology and activation data analysis. In a previous paper, the authors have shown that a dimensionless variable can be introduced which converts the dependence of G _res on the physical and nuclear properties of the material samples into an universal curve, valid for the isolated resonances of any nuclide. This work presents a methodology based on the universal curve, which enables to calculate G _res for a group of isolated resonances by weighting its individual contributions. A good agreement was reached with results calculated by the MCNP code and with experimental values for Mo foils and wires. This revised version was published online in July 2006 with corrections to the Cover Date.     

Development and application of an integrated system for monitoring ethanol content of fuels

An automated flow injection analysis (FIA) system for quantifying ethanol was developed using alcohol oxidase, horseradish peroxidase, 4-aminophenazone, and phenol. A colorimetric detection method was developed using two different methods of analysis, with free and immobilized enzymes. The system with free enzymes permitted analysis of standard ethanol solution in a range of 0.05–1.0 g of ethanol/L without external dilution, a sampling frequency of 15 analyses/h, and relative SD of 3.5%. A new system was designed consisting of a microreactor with a 0.91-mL internal volume filled with alcohol oxidase immobilized on glass beads and an addition of free peroxidase, adapted in an FIA line, for continued reuse. This integrated biosensor-FIA system is being used for quality control of biofuels, gasohol, and hydrated ethanol. The FIA system integrated with the microreactor showed a calibration curve in the range of 0.05–1.5 g of ethanol/L, and good results were obtained compared with the ethanol content measured by high-performance liquid chromatography and gas chromatography standard methods.     

Prediction of retention times of proteins in hydrophobic interaction chromatography using only their amino acid composition

This paper focuses on the prediction of the dimensionless retention time of proteins (DRT) in hydrophobic interaction chromatography (HIC) by means of mathematical models based, essentially, only on aminoacidic composition. The results show that such prediction is indeed possible. Our main contribution was the design of models that predict the DRT using the minimal information concerning a protein: its aminoacidic composition. The performance is similar to that observed in models that use much more sophisticated information such as the three-dimensional structure of proteins. Three models that, in addition to the amino acid composition, use different assumptions about the amino acids tendency to be exposed to the solvent, were evaluated in 12 proteins with known experimental DRT. In all the cases analyzed, the model that obtained the best results was the one based on a linear estimation of the aminoacidic surface composition. The models were adjusted using a collection of 74 vectors of aminoacidic properties plus a set of 6388 vectors derived from these using two mathematical tools: k-means and self-organizing maps (SOM) algorithms. The best vector was generated by the SOM algorithm and was interpreted as a hydrophobicity scale based partly on the tendency of the amino acids to be hidden in proteins. The prediction error (MSE(JK)) obtained by this model was almost 35% smaller than that obtained by the model that supposes that all the amino acids are completely exposed and 40% smaller than that obtained by the model that uses a simple correction factor considering the general tendency of each amino acid to be exposed to the solvent. In fact, the performance of the best model based on the aminoacidic composition was 5% better than that observed in the model based on the three-dimensional structure of proteins.     

Rhodopsin reconstituted into a planar-supported lipid bilayer retains photoactivity after cross-linking polymerization of lipid monomers

Transmembrane proteins (TMPs), particularly ion channels and receptors, play key roles in transport and signal transduction. Many of these proteins are pharmacologically important and therefore targets for drug discovery. TMPs can be reconstituted in planar-supported lipid bilayers (PSLBs), which has led to development of TMP-based biosensors and biochips. However, PSLBs composed of natural lipids lack the high stability desired for many technological applications. One strategy is to use synthetic lipid monomers that can be polymerized to form robust bilayers. A key question is how lipid polymerization affects TMP structure and activity. In this study, we have examined the effects of UV polymerization of bis-Sorbylphosphatidylcholine (bis-SorbPC) on the photoactivation of reconstituted bovine rhodopsin (Rho), a model G-protein-coupled receptor. Plasmon-waveguide resonance spectroscopy (PWR) was used to compare the degree of Rho incorporation and activation in fluid and poly(lipid) PSLBs. The results show that reconstitution of Rho into a supported lipid bilayer composed only of bis-SorbPC, followed by photoinduced lipid cross-linking, does not measurably diminish protein function.     

Influence of samarium on the electrocatalytic activity of platinum electrodes for the hydrogenation of benzene

The hydrogenation of benzene on platinum electrodes in 0.5 M sulfuric acid as supporting electrolyte has been studied in the presence and the absence of samarium in solution. The hydrogenation overpotential of preadsorbed benzene was diminished to 90 mV with samarium in the solution and the hydrogenation current was significatively increased. These results are interpreted in terms of a synergic effect of samarium on hydrogen adsorption and, consequently, on the electrocatalytic activity of the platinum electrode for the hydrogenation of benzene.