A new HPLC-DAD-MS/MS method for the simultaneous determination of major compounds in the crude extract of Lychnophora salicifolia Mart. (Brazilian arnicao) leaves: Application to chemical variability evaluation

Lychnophora salicifolia Mart., which occurs in the Brazilian Cerrado in the states of Bahia and Minas Gerais as well as in the southeast of the state of Goias, is the most widely distributed and also the most polymorphic species of the genus. This plant is popularly known to have anti-inflammatory and analgesic activities. In this work, we have studied the variation in terms of polar metabolites of ninety-three Lychnophora salicifolia Mart, specimens collected from different regions of the Brazilian Cerrado. Identification of the constituents of this mixture was carried out by analysis of the UV spectra and MS data after chromatographic separation. Twenty substances were identified, including chlorogenic acid derivatives, a flavonoid C-glucoside, and other sesquiterpenes. The analytical method was validated, and the reliability and credibility of the results was ensured for the purposes of this study. The concentration range required for analysis of content variability within the analyzed group of specimens was covered with appropriate values of limits of detection and quantitation, as well as satisfactory precision and recovery. A quantitative variability was observed among specimens collected from the same location, but on average they were similar from a chemical viewpoint. In relation to the study involving specimens from different locations, there were both qualitative and quantitative differences among plants collected from different regions of Brazil. Statistical analysis revealed that there is a correlation between geographical localization and polar metabolites profile for specimens collected from different locations. This is evidence that the pattern of metabolites concentration depends on the geographical distribution of the specimens. (C) 2012 Elsevier B.V. All rights reserved.

Riverbed: A Novel User-Steered Image Segmentation Method Based on Optimum Boundary Tracking

This paper presents an optimum user-steered boundary tracking approach for image segmentation, which simulates the behavior of water flowing through a riverbed. The riverbed approach was devised using the image foresting transform with a never-exploited connectivity function. We analyze its properties in the derived image graphs and discuss its theoretical relation with other popular methods such as live wire and graph cuts. Several experiments show that riverbed can significantly reduce the number of user interactions (anchor points), as compared to live wire for objects with complex shapes. This paper also includes a discussion about how to combine different methods in order to take advantage of their complementary strengths.

A NEW METHOD TO QUANTIFY X-RAY SUBSTRUCTURES IN CLUSTERS OF GALAXIES

We present a new method to quantify substructures in clusters of galaxies, based on the analysis of the intensity of structures. This analysis is done in a residual image that is the result of the subtraction of a surface brightness model, obtained by fitting a two-dimensional analytical model (beta-model or Sersic profile) with elliptical symmetry, from the X-ray image. Our method is applied to 34 clusters observed by the Chandra Space Telescope that are in the redshift range z is an element of [0.02, 0.2] and have a signal-to-noise ratio (S/N) greater than 100. We present the calibration of the method and the relations between the substructure level with physical quantities, such as the mass, X-ray luminosity, temperature, and cluster redshift. We use our method to separate the clusters in two sub-samples of high-and low-substructure levels. We conclude, using Monte Carlo simulations, that the method recuperates very well the true amount of substructure for small angular core radii clusters (with respect to the whole image size) and good S/N observations. We find no evidence of correlation between the substructure level and physical properties of the clusters such as gas temperature, X-ray luminosity, and redshift; however, analysis suggest a trend between the substructure level and cluster mass. The scaling relations for the two sub-samples (high-and low-substructure level clusters) are different (they present an offset, i. e., given a fixed mass or temperature, low-substructure clusters tend to be more X-ray luminous), which is an important result for cosmological tests using the mass-luminosity relation to obtain the cluster mass function, since they rely on the assumption that clusters do not present different scaling relations according to their dynamical state.

Antioxidant Activity of Brazilian Vegetables and Its Relation with Phenolic Composition

Vegetables are widely consumed in Brazil and exported to several countries. This study was performed to evaluate the phenolic content and antioxidant activity of vegetables commonly consumed in Brazil using five different methods, namely DPPH and ABTS free radical, beta-carotene bleaching, reduction of Fe3+ (FRAP), oxidative stability in Rancimat, and the chemical composition using gas chromatography-mass spectrometry (GC-MS). The content of phenolic compounds ranged from 1.2 mg GA/g (carrot) to 16.9 mg GA/g (lettuce). Vegetables presenting the highest antioxidant activity were lettuce (77.2 mu mol Trolox/g DPPH center dot; 447.1 mu mol F2+/g FRAP), turmeric (118.6 mu mol Trolox/g ABTS(center dot+); 92.8% beta-carotene), watercress and broccoli (protective factor 1.29-Rancimat method). Artichoke, spinach, broccoli, and asparagus also showed considerable antioxidant activity. The most frequent phenolic compounds identified by GC-MS were ferulic, caffeic, p-coumaric, 2-dihydroxybenzoic, 2,5-dihydroxybenzoic acids, and quercetin. We observed antioxidant activity in several vegetables and our results point out their importance in the diet.

Treatment of rice straw hemicellulosic hydrolysates with advanced oxidative processes: a new and promising detoxification method to improve the bioconversion process

Abstract Background The use of lignocellulosic constituents in biotechnological processes requires a selective separation of the main fractions (cellulose, hemicellulose and lignin). During diluted acid hydrolysis for hemicellulose extraction, several toxic compounds are formed by the degradation of sugars and lignin, which have ability to inhibit microbial metabolism. Thus, the use of a detoxification step represents an important aspect to be considered for the improvement of fermentation processes from hydrolysates. In this paper, we evaluated the application of Advanced Oxidative Processes (AOPs) for the detoxification of rice straw hemicellulosic hydrolysate with the goal of improving ethanol bioproduction by Pichia stipitis yeast. Aiming to reduce the toxicity of the hemicellulosic hydrolysate, different treatment conditions were analyzed. The treatments were carried out according to a Taguchi L16 orthogonal array to evaluate the influence of Fe+2, H2O2, UV, O3 and pH on the concentration of aromatic compounds and the fermentative process. Results The results showed that the AOPs were able to remove aromatic compounds (furan and phenolic compounds derived from lignin) without affecting the sugar concentration in the hydrolysate. Ozonation in alkaline medium (pH 8) in the presence of H2O2 (treatment A3) or UV radiation (treatment A5) were the most effective for hydrolysate detoxification and had a positive effect on increasing the yeast fermentability of rice straw hemicellulose hydrolysate. Under these conditions, the higher removal of total phenols (above 40%), low molecular weight phenolic compounds (above 95%) and furans (above 52%) were observed. In addition, the ethanol volumetric productivity by P. stipitis was increased in approximately twice in relation the untreated hydrolysate. Conclusion These results demonstrate that AOPs are a promising methods to reduce toxicity and improve the fermentability of lignocellulosic hydrolysates.

Estimation of transpiration of the 'Valencia' orange young plant using thermal dissipation probe method

Most studies on measures of transpiration of plants, especially woody fruit, relies on methods of heat supply in the trunk. This study aimed to calibrate the Thermal Dissipation Probe Method (TDP) to estimate the transpiration, study the effects of natural thermal gradients and determine the relation between outside diameter and area of xylem in 'Valencia' orange young plants. TDP were installed in 40 orange plants of 15 months old, planted in boxes of 500 L, in a greenhouse. It was tested the correction of the natural thermal differences (DTN) for the estimation based on two unheated probes. The area of the conductive section was related to the outside diameter of the stem by means of polynomial regression. The equation for estimation of sap flow was calibrated having as standard lysimeter measures of a representative plant. The angular coefficient of the equation for estimating sap flow was adjusted by minimizing the absolute deviation between the sap flow and daily transpiration measured by lysimeter. Based on these results, it was concluded that the method of TDP, adjusting the original calibration and correction of the DTN, was effective in transpiration assessment.