Determination of the β-Glucosidase Activity in Different Soils by Pre Capillary Enzyme Assay Using Capillary Electrophoresis with Laser-Induced Fluorescence Detection

Enzyme activities can provide indication for quantitative changes in soil organic matter (SOM). It is known that the activities of most enzymes increase as native SOM content reflecting larger microbial communities and stabilization of enzymes on humic materials. β-Gucosidase (β-Glu) activities have been frequently used as indicators of changes in quantity and quality of SOM. In this study we propose a simple and very sensitive method, which has lower limit of detection compared with classic spectrophotometric method with the aim of determinate the β-Glu activity in soil samples using Fluorescein mono-β-D-glucopyranoside (FMGlc) as a substrate. The fluorescein released by the enzymatic reaction was quantified by capillary electrophoresis-laser induced fluorescence (CE-LIF) method. The background electrolyte (BGE) consisted in 40 mM phosphate buffer, pH 6. The LOD and LOQ for fluorescein were 1.3 10⁻⁷ mg mL⁻¹ and 6.4 10⁻⁶ mg mL⁻¹, respectively. This work deals with the minimization of the mixture for the enzymatic reaction and with the optimization conditions of CE separation. To the best of our knowledge, this is the first time that an enzymatic activity was detected in soil using CE-LIF system.     

Entropy factor in the hopping frequency for ionic conduction in oxide glasses induced by energetic clustering

The contribution of configurational entropy to the effective hopping frequency of ionic transport in amorphous systems is discussed. The effective rate of ion hopping has been extracted from the onset frequency of the ac conductivity measured in ionically conducting silicate glasses. Both the onset frequency and the dc conductivity exhibit Arrhenius-type thermal activation with similar values for the activation energy, DeltaEa=0.65+/-0.3 eV. The prefactor of the onset frequency results in nu0'=(1.05+/-0.05)x10(11) Hz, which is much lower than characteristic vibrational frequencies (10(13) Hz). Following standard hopping percolation theory, the long-range motion is dominated by a fraction of high-energy barriers that connect clusters of faster sites. The multiplicity of equivalent sites for ion hop entails a retardation of the effective jumping time with respect to the elementary hop. This effect can be assimilated into a negative activation entropy term in the frequency prefactor of the ion hopping rate, which depends on the features of energy clustering and accounts for the wide dispersion of nu0' reported for many conducting glasses. The model implies an effective percolation length of Lc approximately 7 nm, in good agreement with previous works.     

Is ammonia a better solvent than water for contact ion pairs?

The existence of a charge-transfer-to-solvent process when a KI contact ion pair (CIP) dissolved in supercritical water (SCW) is excited by UV light was confirmed by use of electronic structure calculations applied to molecular dynamics trajectories. We observed similar behavior with fluid density as that found for the KI-CIP in supercritical ammonia (SCA); nevertheless, there are some distinct features in the two supercritical solvents. First, the effect of the solvent field due to the molecules lying beyond the first solvation shell is very different in SCW compared with that observed in SCA; in SCW it actually has a destabilizing effect over the ground and excited states. Second, our results for the thermodynamic behavior of the CIP indicate that SCA is better solvent than SCW for this species. The differences found can be attributed to the solvent molecules surrounding the CIP and bridging the two ions; they shield more efficiently the ion pair from long-range solvent effects in SCA. The different behavior is partially attributed to a stronger solvent-solvent interaction in SCW than in SCA.     

Online immunoaffinity assay-CE using magnetic nanobeads for the determination of anti-Helicobacter pylori IgG in human serum

About two-thirds of the world's population is infected with Helicobacter pylori (H. pylori). This Gram-negative bacterium is the most important etiological agent of chronic active type B gastritis and peptic ulcer diseases. Conventional methods such as gastric biopsy, ELISA and culture, require a long time for the determination of H. pylori infections. Moreover, the antibodies in human serum sample are capable to react immunologically with the purified H. pylori antigens immobilized on different kinds of support like magnetic nanobeads. In this study, we have developed an online immunoaffinity assay-CE to determine the concentration of anti-H. pylori IgG using magnetic nanobeads as a support of the immunological affinity ligands and an LIF as a detector. The separation was performed in 0.1 M glycine-HCl, pH 2, as the background electrolyte. The linear calibration curve to predict the concentration of H. pylori-specific immunoglobulin G antibodies in serum was produced within the range of 0.12-100 U/mL. The linear regression equation was i = 492.86+96.03 × C(anti-H. pylori), with the linear regression coefficient r(2) = 0.999. The LOD calculated by fluorescence detection procedure was of 0.06 U/mL. The whole assay was done in no more than 35 min and it was entirely automatized. The development of immunoaffinity assay-CE in this study demonstrates that there is a large possibility to introduce nanotechnology in several fields with significant advantages over the classic methodologies. Our proposition comprises the diagnosis and screening field.     

Interfacial energy and the law of corresponding states 2: associated fluids

A mesoscopic model for the liquid/vapor interface previously developed for nonpolar fluids [J. Phys. Chem. A 2003, 107, 875; 2003, 107, 883] is extended to the case of polar associated compounds. The interfacial energy is factorized in two terms: one corresponding to association depending on the hydrogen bonds density, the other corresponding to the nonpolar contribution. This last term is treated in the framework of the corresponding states formalism similar to the one used in the case of nonpolar fluids [J. Phys. Chem. B 2004, 108, 5951]. The model yields a generalized behavior of the association factor as a function of the dielectric constant for the treated fluids. The calculated surface tension shows a mean error of about 1% for seven compounds having different multivalent H-bond characters.     

On number system constructions

We investigate various number system constructions. After summarizing earlier results we prove that for a given lattice Λ and expansive matrix M: Λ → Λ if ρ(M ⁻¹) < 1/2 then there always exists a suitable digit set D for which (Λ, M, D) is a number system. Here ρ means the spectral radius of M ⁻¹. We shall prove further that if the polynomial f(x) = c ₀ + c ₁ x + ··· + c _k x ^k ∈ Z[x], c _k = 1 satisfies the condition |c ₀| > 2 Σ _i=1 ^k |c _i | then there is a suitable digit set D for which (Z ^k , M, D) is a number system, where M is the companion matrix of f(x). The research was supported by OTKA-T043657 and Bolyai Fellowship Committee.     

Wildland fire growth prediction method based on Multiple Overlapping Solution

Several Data-Driven Methods have been developed to try to solve the input parameters uncertainty when considering problems like Wildfires Prediction. In general, these methods operate over a large number of input parameters, and consider the most recent known behavior of wildfires. The purpose of the methods is to find the parameter set that best describes the real situation under consideration. Therefore, it is presumed that the same set of values could be used to predict the immediate future.However, because this kind of prediction is based on a single set of parameters, for those parameters that present a dynamic behavior (e.g. wind direction and speed), the new optimized values are not adequate to make a prediction.In this paper we propose an alternative method developed in a new branch of Data-Driven Prediction, which we called Multiple Overlapping Solution. This method combines statistical concepts and HPC (High Performance Computing) to obtain a higher quality prediction.