Stimulation of Acidic Reduction of Nitrite to Nitric Oxide by Soybean Phenolics: Possible Relevance to Gastrointestinal Host Defense

This study aimed to evaluate the potential of soybean-promoted acidic nitrite reduction and to correlate this activity with the content of phenolics and with the bactericidal activity against Escherichia coli O157:H7. Extracts of embrionary axes and cotyledons enriched in phenolics increased (center dot)NO formation at acidic pH at values that were 7.1 and 4.5 times higher, respectively, when compared to the reduction of the nonenriched extracts. Among the various phenolics accumulated in the soybean extracts, five stimulated nitrite reduction in the following decreasing order of potency: epicatechin gallate, chlorogenic acid, caffeic acid, galic acid and p-coumaric acid. Extracts of embrionary axes presented higher contents of epicatechin gallate and caffeic acid, compared to that of cotyledons, indicating a positive correlation between activity of the extracts and content of phenolics with regard to nitrite reducing activity. Soybean extracts enriched in phenolics interacted synergistically with acidified nitrite to prevent E. coli O157:H7 growth. The results suggest that soybean phenolics may interfere with the metabolism of (center dot)NO in an acidic environment by accelerating the reduction of nitrite, with a potential antimicrobial effect in the stomach.

Unraveling the Role of Sulfur Compounds in Acid Rain Formation: Experiments on a Wetted Glass pH Electrode

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The reduction of Cu(II)/neocuproine complexes by some polyphenols: Total polyphenols determination in wine samples

A new method is presented for spectrophotometric determination of total polyphenols content in wine. The procedure is a modified CUPRAC method based on the reduction of Cu(II), in hydroethanolic medium (pH 7.0) in the presence of neocuproine (2,9-dimethyl-1,10-phenanthroline), by polyphenols, yielding a Cu(I) complexes with maximum absorption peak at 450 nm. The absorbance values are linear (r = 0.998, n = 6) with tannic acid concentrations from 0.4 to 3.6 mu mol L(-1). The limit of detection obtained was 0.41 mu mol L(-1) and relative standard deviation 1.2% (1 mu mol L(-1); n = 8). Recoveries between 80% and 110% (mean value of 95%) were calculated for total polyphenols determination in 14 commercials and 2 synthetic wine samples (with and without sulphite). The proposed procedure is about 1.5 more sensitive than the official Folin-Ciocalteu method. The sensitivities of both methods were compared by the analytical responses of several polyphenols tested in each method. (C) 2010 Elsevier Ltd. All rights reserved.

Rapid method for the determination. of organic acids in wine by capillary electrophoresis with indirect UV detection

A capillary electrophoresis method for organic acids in wine was developed and validated. The optimal electrolyte consisted of 10 mmol/L 3,5-dinitrobenzoic acid (DNB) at pH 3.6 containing 0.2 mmol/L cetyltrimethylammonium bromide as flow reverser. DNB was chosen because it has an effective mobility similar to the organic acids under investigation, good buffering capacity at pH 3.6, and good chromophoric characteristics for indirect UV-absorbance detection at 254 nm. Sample preparation involved dilution and filtration. The method showed good performance characteristics: Linearity at 6 to 285 mg/L (r > 0.99); detection and quantification limits of 0.64 to 1.55 and 2.12 to 5.15 mg/L, respectively; separation time of less than 5.5 min. Coefficients of variation for ten injections were less than 5% and recoveries varied from 95% to 102%. Application to 23 samples of Brazilian wine confirmed good repeatability and demonstrated wide variation in the organic acid concentrations. (C) 2008 Elsevier Ltd. All rights reserved.

Reduction of Models in the Presence of Nuisance Parameters

In many statistical inference problems, there is interest in estimation of only some elements of the parameter vector that defines the adopted model. In general, such elements are associated to measures of location and the additional terms, known as nuisance parameters, to control the dispersion and asymmetry of the underlying distributions. To estimate all the parameters of the model and to draw inferences only on the parameters of interest. Depending on the adopted model, this procedure can be both algebraically is common and computationally very costly and thus it is convenient to reduce it, so that it depends only on the parameters of interest. This article reviews estimation methods in the presence of nuisance parameters and consider some applications in models recently discussed in the literature.

The effect of ultra-low proton concentration on the electrocatalytic reduction of nitrate over platinum

The electrocatalytic reduction of NO3- (aq) over platinum has been investigated in sulfuric acid solutions with proton concentrations between 1 mM and 50 mM. Cyclic voltammetry indicates that for [H+] < 10 mM, NO3- (aq) is reduced in two distinct regions of potential: one reduction peak occurs at approximately 0.1 V vs. RHE and one occurs at -0.13 V vs. RHE. This second reduction peak has never before been observed, and is not present for proton concentrations >10 mM, where hydrogen electroreduction prevails below 0.0 V vs. RHE. Chronoamperometry shows that the kinetics of the two reduction peaks are distinct, suggesting that the two reduction peaks may correspond to the evolution of different products. Results are discussed in the context of tuning the product selectivity of the electrocatalytic reduction of NO3- (aq). (C) 2007 Elsevier B.V. All rights reserved.

Reduction of NO by CO on Cu/ZrO(2)/Al(2)O(3) catalysts: Characterization and catalytic activities

ZrO(2), gamma-Al(2)O(3) and ZrO(2)/gamma-Al(2)O(3)-supported copper catalysts have been prepared, each with three different copper loads (1, 2 and 5 wt%), by the impregnation method. The catalysts were characterized by nitrogen adsorption (BET), X-ray diffraction (XRD), temperature programmed reduction (TPR) with H(2), Raman spectroscopy and electronic paramagnetic resonance (EPR). The reduction of NO by CO was studied in a fixed-bed reactor packed with these catalysts and fed with a mixture of 1% CO and 1% NO in helium. The catalyst with 5 wt% copper supported on the ZrO(2)/gamma-Al(2)O(3) matrix achieved 80% reduction of NO. Approximately the same rate of conversion was obtained on the catalyst with 2 wt% copper on ZrO(2). Characterization of these catalysts indicated that the active copper species for the reduction of NO are those in direct contact with the oxygen vacancies found in ZrO(2). (C) 2009 Published by Elsevier Ltd.

A neural networks study of quinone compounds with trypanocidal activity

This work investigates neural network models for predicting the trypanocidal activity of 28 quinone compounds. Artificial neural networks (ANN), such as multilayer perceptrons (MLP) and Kohonen models, were employed with the aim of modeling the nonlinear relationship between quantum and molecular descriptors and trypanocidal activity. The calculated descriptors and the principal components were used as input to train neural network models to verify the behavior of the nets. The best model for both network models (MLP and Kohonen) was obtained with four descriptors as input. The descriptors were T(5) (torsion angle), QTS1 (sum of absolute values of the atomic charges), VOLS2 (volume of the substituent at region B) and HOMO-1 (energy of the molecular orbital below HOMO). These descriptors provide information on the kind of interaction that occurs between the compounds and the biological receptor. Both neural network models used here can predict the trypanocidal activity of the quinone compounds with good agreement, with low errors in the testing set and a high correctness rate. Thanks to the nonlinear model obtained from the neural network models, we can conclude that electronic and structural properties are important factors in the interaction between quinone compounds that exhibit trypanocidal activity and their biological receptors. The final ANN models should be useful in the design of novel trypanocidal quinones having improved potency.

A combined X-ray and theoretical study of flavonoid compounds with anti-inflammatory activity

The structure of 7,4`-dimethoxy-3`-acetylflavone (tithonin-Ac) has been determined by X-ray diffraction and its geometry is compared with optimized geometrical parameters obtained by means of density functional theory at the B3LYP/6-311++G(d,p) level of calculation. in addition, vertical ionization potential (IPv) and acidity for tithonin-Ac and two derivatives have been also calculated. Calculations of spin densities were also performed for the radical formed by the electron abstraction of other flavones. The unpaired electron is located on C3 carbon atom (21-25%). (C) 2008 Elsevier B.V. All rights reserved.

Artificial Neural Networks and the Study of the Psychoactivity of Cannabinoid Compounds

Cannabinoid compounds have widely been employed because of its medicinal and psychotropic properties. These compounds are isolated from Cannabis sativa (or marijuana) and are used in several medical treatments, such as glaucoma, nausea associated to chemotherapy, pain and many other situations. More recently, its use as appetite stimulant has been indicated in patients with cachexia or AIDS. In this work, the influence of several molecular descriptors on the psychoactivity of 50 cannabinoid compounds is analyzed aiming one obtain a model able to predict the psychoactivity of new cannabinoids. For this purpose, initially, the selection of descriptors was carried out using the Fisher`s weight, the correlation matrix among the calculated variables and principal component analysis. From these analyses, the following descriptors have been considered more relevant: E(LUMO) (energy of the lowest unoccupied molecular orbital), Log P (logarithm of the partition coefficient), VC4 (volume of the substituent at the C4 position) and LP1 (Lovasz-Pelikan index, a molecular branching index). To follow, two neural network models were used to construct a more adequate model for classifying new cannabinoid compounds. The first model employed was multi-layer perceptrons, with algorithm back-propagation, and the second model used was the Kohonen network. The results obtained from both networks were compared and showed that both techniques presented a high percentage of correctness to discriminate psychoactive and psychoinactive compounds. However, the Kohonen network was superior to multi-layer perceptrons.

Characterization of organic matter from composting of different residues by physicochemical and spectroscopic methods

Chemical and spectroscopic methods were used to characterize organic matter transformations during the composting process. Four different residue mixtures were studied: P1 - garden trimmings (GT) only, P2 - GT plus fresh cattle manure, P3 - GT plus orange pomace and P4 - GT plus filter cake. The thermophilic phase was not reached in PI compost, but the P2, P3 and P4 composts showed all three typical process phases. The thermophilic phase and CEC/C ratio stabilized after 90 days, while C/N ratio and the ash content stabilized after 60 days. The increasing E(4)/E(6) ratio indicated oxidation reactions occurring during the process in the material from P2, P3 and P4. The (13)C NMR and FTIR results suggested extraction of both pectin and lignin in the HA-like fraction. The CEC/C ratio, temperature and E(4)/E(6) ratio showed that within 90 days P2, P3 and P4 composts were humified. However, material from P1 did not show characteristics of humified compost. From these data, it is apparent that C/N ratio and ash content are not reliable methods for monitoring the composting process. (C) 2009 Elsevier Ltd. All rights reserved.

Characterization by Fluorescence of Organic Matter from Oxisols under Sewage Sludge Applications

Sewage sludge from wastewater treatment contains organic matter and plant nutrients that can play an important role in agricultural production and the maintenance of soil fertility, The present study has aimed to evaluate the degree of humification following sewage sludge application of soil organic matter by laser-induced fluorescence and humic acids using ultraviolet-visible fluorescence, and including comparison with Fourier-transform infrared spectroscopy and elemental analysis. Sewage sludge applications to the soil caused a decrease in the degree of humification of the soil organic matter and humic acids for both a Typic Eutrorthox (clayey) soil and a Typic Haplorthox (sandy) soil of around 14 and 27%, respectively. This effect is probably clue to incorporation of newly formed humic substances from the sewage sludge into the characteristics of less humified material, and to the indigenous soil humic substances. The minor alterations observed in the clay soil probably occurred due to both the greater mineral association, which better stabilized the indigenous soil organic matter, and the higher microbial activity in this soil, which accelerated sewage sludge mineralization. Sewage sludge applications increased the C content for the clay and sandy soils by 7.4 and 15.4 g kg(-1), respectively, suggesting a positive effect on these two soils.

Docking and molecular dynamics simulation of quinone compounds with trypanocidal activity

In this work, two different docking programs were used, AutoDock and FlexX, which use different types of scoring functions and searching methods. The docking poses of all quinone compounds studied stayed in the same region in the trypanothione reductase. This region is a hydrophobic pocket near to Phe396, Pro398 and Leu399 amino acid residues. The compounds studied displays a higher affinity in trypanothione reductase (TR) than glutathione reductase (GR), since only two out of 28 quinone compounds presented more favorable docking energy in the site of human enzyme. The interaction of quinone compounds with the TR enzyme is in agreement with other studies, which showed different binding sites from the ones formed by cysteines 52 and 58. To verify the results obtained by docking, we carried out a molecular dynamics simulation with the compounds that presented the highest and lowest docking energies. The results showed that the root mean square deviation (RMSD) between the initial and final pose were very small. In addition, the hydrogen bond pattern was conserved along the simulation. In the parasite enzyme, the amino acid residues Leu399, Met400 and Lys402 are replaced in the human enzyme by Met406, Tyr407 and Ala409, respectively. In view of the fact that Leu399 is an amino acid of the Z site, this difference could be explored to design selective inhibitors of TR.

Effectiveness of different solid-phase microextraction fibres for differentiation of selected Madeira island fruits based on their volatile metabolite profile: identification of novel compounds

A headspace solid-phase microextraction (HS-SPME) procedure based on five commercialised fibres (85 μm polyacrylate – PA, 100 μm polydimethylsiloxane – PDMS, 65 μm polydimethylsiloxane/divinylbenzene – PDMS/DVB, 70 μm carbowax/divinylbenzene – CW/DVB and 85 μm carboxen/polydimethylsiloxane – CAR/PDMS) is presented for the characterization of the volatile metabolite profile of four selected Madeira island fruit species, lemon (Citrus limon), kiwi (Actinidia deliciosa), papaya (Carica papaya L.) and Chickasaw plum (Prunus angustifolia). The isolation of metabolites was followed by thermal desorption gas chromatography–quadrupole mass spectrometry (GC–qMS) methodology. The performance of the target fibres was evaluated and compared. The SPME fibre coated with CW/DVB afforded the highest extraction efficiency in kiwi and papaya pulps, while in lemon and plum the same was achieved with PMDS/DVB fibre. This procedure allowed for the identification of 80 compounds, 41 in kiwi, 24 in plums, 23 in papaya and 20 in lemon. Considering the best extraction conditions, the most abundant volatiles identified in kiwi were the intense aldehydes and ethyl esters such as (E)-2-hexenal and ethyl butyrate, while in Chicasaw plum predominate 2-hexenal, 2-methyl-4-pentenal, hexanal, (Z)-3-hexenol and cyclohexylene oxide. The major compounds identified in the papaya pulp were benzyl isothiocyanate, linalool oxide, furfural, hydroxypropanone, linalool and acetic acid. Finally, lemon was shown to be the most divergent of the four fruits, being its aroma profile composed almost exclusively by terpens, namely limonene, γ-terpinene, o-cymene and α-terpinolene. Thirty two volatiles were identified for the first time in the fruit or close related species analysed and 14 volatiles are reported as novel volatile metabolites in fruits. This includes 5 new compounds in kiwi (2-cyclohexene-1,4-dione, furyl hydroxymethyl ketone, 4-hydroxydihydro-2(3H)-furanone, 5-acetoxymethyl-2-furaldehyde and ethanedioic acid), 4 in plum (4-hydroxydihydro-2(3H)-furanone, 5-methyl-2-pyrazinylmethanol, cyclohexylene oxide and 1-methylcyclohexene), 4 in papaya (octaethyleneglycol, 1,2-cyclopentanedione, 3-methyl-1,2-cyclopentanedione and 2-furyl methyl ketone) and 2 in lemon (geranyl farnesate and safranal). It is noteworthy that among the 15 volatile metabolites identified in papaya, 3-methyl-1,2-cyclopentanedione was previously described as a novel PPARγ (peroxisome proliferator-activated receptor γ) agonist, having a potential to minimize inflammation.