174 resultados para Portacaval anastomosis (PCA)


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Uncaria tomentosa (cat's claw) is a vine widely distributed throughout the South-American rainforest. Many studies investigating the chemical composition of cat's claw have focused on the pentacyclic (POA) and tetracyclic oxindole alkaloids (TOA), quinovic acid glycosides (QAG), and polyphenols (PPH). Nevertheless, it is still uncertain how environmental factors affect chemical groups. The aim of this work was to better understand the influence of environmental factors (geographic origin, altitude, and season) on cat's claw chemical composition. Stem bark, branches and leaf samples were extracted and analyzed by HPLC-PDA. The data obtained were explored by multivariate analysis (HCA and PCA). Higher amounts of oxindole alkaloids and PPH were found in leaves, followed by stem bark and branches. No clear relationship was verified among geographic origin or altitude and chemical composition, which remained unchanged regardless of season (dry or rainy). However, three oxindole alkaloid chemotypes were clearly recognized: chemotype I (POA with cis D/E ring junction); chemotype II (POA with trans D/E ring junction); and chemotype III (TOA). Thus, environmental factors appear to have only a minor influence on the chemical heterogeneity of the cat's claw wild population. Nevertheless, the occurrence of different chemotypes based on alkaloid profiles seems to be clear.

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The objective of this work was to develop a free access exploratory data analysis software application for academic use that is easy to install and can be handled without user-level programming due to extensive use of chemometrics and its association with applications that require purchased licenses or routines. The developed software, called Chemostat, employs Hierarchical Cluster Analysis (HCA), Principal Component Analysis (PCA), intervals Principal Component Analysis (iPCA), as well as correction methods, data transformation and outlier detection. The data can be imported from the clipboard, text files, ASCII or FT-IR Perkin-Elmer “.sp” files. It generates a variety of charts and tables that allow the analysis of results that can be exported in several formats. The main features of the software were tested using midinfrared and near-infrared spectra in vegetable oils and digital images obtained from different types of commercial diesel. In order to validate the software results, the same sets of data were analyzed using Matlab© and the results in both applications matched in various combinations. In addition to the desktop version, the reuse of algorithms allowed an online version to be provided that offers a unique experience on the web. Both applications are available in English.

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AbstractThe purpose of this study was to evaluate the best operating conditions of ICP OES for the determination of Na, Ca, Mg, Sr and Fe in aqueous extract of crude oil obtained after hot extraction with organic solvents (ASTM D 6470-99 modified). Thus, the full factorial design and central composite design were used to optimize the best conditions for the flow of nebulization gas, the flow of auxiliary gas, and radio frequency power. After optimization of variables, a study to obtain correct classification of the 18 samples of aqueous extract of crude oils (E1 to E18) from three production and refining fields was carried out. Exploratory analysis of these extracts was performed by principal component analysis (PCA), hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA), using the original variables as the concentration of the metals Na, Ca, Mg, Sr and Fe determined by ICP OES.

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The calyxes of Hibiscus sabdariffa are used in traditional medicine around the world. However, quality assurance protocols and chemical variability have not been previously analyzed. In the present study, chemical characterization of a set of samples of H. sabdariffa calyxes commercialized in Colombia was accomplished with the aim to explore the chemical variability among them. Chemometrics-based analyses on the data obtained from the HPLC-UV-DAD-derived profiles were then performed. Thus, the pre-processed single-wavelength data were subjected to principal component analysis (PCA). The PCA-derived results evidenced different groups which were well-correlated to the corresponding total phenolic and total anthocyanin contents. Multi-wavelength chromatographic (HPLC-UV-DAD surfaces) data were additionally examined via parallel factor analysis (PARAFAC) as data reduction method and the obtained loadings were subsequently submitted to PCA and orthogonal partial least squares discriminant analysis (OPLS-DA). Results were thus consistent with those from single-wavelength data. PCA loadings were employed to determine those chemical components responsible for the data variance and OPLS-DA model, constructed from PARAFAC loadings, and indicated differentiation according total anthocyanin contents among samples. The present chemometric analysis therefore demonstrated to be an excellent tool for differentiation of H. sabdariffacalyxes according to their chemical composition.

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Principal component analysis (PCA) is a chemometric method that allows for the extraction of chemical information that would otherwise be impossible to determine. Teaching chemometrics to undergraduates can contribute to the overall professional development and training of new teachers, whose profiles have been gaining attention due to the current demand for data interpretation. In this study, a didactic experiment involving PCA is proposed. Spectrophotometry was used in the ultraviolet-visible (UV-Vis) region to assess the behavior of anthocyanins extracted from red cabbage at different pH values. The results suggest the possible separation of anthocyanin structures into three distinct groups, according to their chemical characteristics displayed in acid, neutral, and basic media. The objective is to develop educational materials targeted to undergraduate courses, which encompass a larger number of concepts and introduce instrumental techniques currently being employed in both academic research and the industrial sector. Specifically, the proposed experiment introduces concepts related to spectrophotometry in the UV-Vis range and the PCA chemometric method. The materials used are easily accessible, and UV-Vis spectroscopy equipment is less expensive in comparison with other spectroscopy methods.

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The objective of this work is to demonstrate the efficient utilization of the Principal Components Analysis (PCA) as a method to pre-process the original multivariate data, that is rewrite in a new matrix with principal components sorted by it's accumulated variance. The Artificial Neural Network (ANN) with backpropagation algorithm is trained, using this pre-processed data set derived from the PCA method, representing 90.02% of accumulated variance of the original data, as input. The training goal is modeling Dissolved Oxygen using information of other physical and chemical parameters. The water samples used in the experiments are gathered from the Paraíba do Sul River in São Paulo State, Brazil. The smallest Mean Square Errors (MSE) is used to compare the results of the different architectures and choose the best. The utilization of this method allowed the reduction of more than 20% of the input data, which contributed directly for the shorting time and computational effort in the ANN training.

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The aim of this study was to identify isolates of Rhizoctonia solani causing hypocotyl rot and foliar blight in soybean (Glycine max) in Brazil by the nucleotide sequences of ITS-5.8S regions of rDNA. The 5.8S rDNA gene sequence (155 bp) was highly conserved among all isolates but differences in length and nucleotide sequence of the ITS1 and ITS2 regions were observed between soybean isolates and AG testers. The similarity of the nucleotide sequence among AG-1 IA isolates, causing foliar blight, was 95.1-100% and 98.5-100% in the ITS1 and ITS2 regions, respectively. The nucleotide sequence similarity among subgroups IA, IB and IC ranged from 84.3 to 89% in ITS1 and from 93.3 to 95.6% in ITS2. Nucleotide sequence similarity of 99.1% and 99.3-100% for ITS1 and ITS2, respectively, was observed between AG-4 soybean isolates causing hypocotyl rots and the AG-4 HGI tester. The similarity of the nucleotide sequence of the ITS-5.8S rDNA region confirmed that the R. solani Brazilian isolates causing foliar blight are AG-1 IA and isolates causing hypocotyl rot symptoms are AG-4 HGI. The ITS-5.8S rDNA sequence was not determinant for the identification of the AG-2-2 IIIB R. solani soybean isolate.

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Okra pods with unusual brown lesions and rot were collected in a local supermarket in Brasília DF. The objective of this paper was to characterize the causal agent, to fulfill Koch's postulates and to determine some conditions conducive to disease. The pathogen was identified as Rhizoctonia solani based on morphological characteristics which fitted the fungus description, such as pale to brown hyphae, with nearly right-angled side branches constricted at the base, hyphal cells 6-10 µm wide with a septum near the base. Five isolates were obtained from infected pods and identified as AG 1-IB anastomosis group. Wounded or unwounded okra pods cv. Santa Cruz 47 were inoculated with mycelium disks of R. solani and kept in humid chambers at 12 ºC or 25 ºC. After seven days at 25 ºC, both wounded and unwounded pods were completely rotted and brown, while those kept at 12 ºC showed small lesions ranging from 0.6 to 1.0 mm only in wounded pods. The pathogen was able to grow in different materials used for assembling crates and packs of horticultural products, such as pinewood, corrugated carton, plastic, Styrofoam and newspaper sheets when kept in humid chambers (24 ºC, 96 % RH). The disease occurrence can be related to careless handling practices and to the transmission of R. solani propagules by infected plant debris or soil particles. This is the first report of Rhizoctonia solani causing postharvest rot in okra pods in Brazil.

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Os teores de Ca, Cu, K, Mg, Na, P e S foram determinados simultaneamente em sucos e refrigerantes de uva utilizando espectrometria de emissão ótica com plasma de argônio induzido (ICP-OES) como técnica analítica. Os dados obtidos foram submetidos a dois métodos de análise exploratória: análise de componentes principais (PCA) e análise hierárquica de agrupamentos (HCA). Os resultados mostraram que o Na foi o principal elemento para discriminação entre as amostras, diferenciando principalmente sucos e refrigerantes. A adição de conservantes e o teor de sais minerais também foram aspectos relevantes para a discriminação dos grupos. A análise exploratória mostrou-se útil para o tratamento dos dados em questão, produzindo informações que dificilmente seriam visualizadas diretamente na matriz de dados.

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O objetivo deste trabalho foi empregar a análise exploratória de dados, no caso, a técnica de análise de componentes principais (PCA) como ferramenta na avaliação de modificadores químicos na determinação direta e simultânea de Al, As, Cu, Fe, Mn e Ni em álcool etílico combustível por espectrometria de absorção atômica em forno de grafite (GFAAS). Os modificadores químicos avaliados foram: Pd(NO3)2 + Mg(NO3)2; W/Rh; W+ co-injeção de Pd(NO3)2 + Mg(NO3)2 e para cada modificador foram utilizadas trintas amostras de álcool etílico combustível. Como dados experimentais foram utilizados os resultados dos testes de adição e recuperação dos analitos frente aos diferentes modificadores químicos estudados. O emprego da técnica de PCA possibilitou a separação dos tipos de modificadores em função do intervalo de recuperação do analito. Dentre os modificadores avaliados, W+ co-injeção de Pd(NO3)2 + Mg(NO3)2 apresentou-se como a espécie de maior correlação positiva, pois apresenta os maiores teores de recuperação, e sendo assim, foi o escolhido para o desenvolvimento de metodologia para determinação direta e simultânea de Al, As, Cu, Fe, Mn e Ni em álcool etílico combustível por GFAAS.

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Two series of alkanediyl-a,w-bis (dimethylalkylammonium bromide (n-2-n and n-6-n; n=8, 10,12, and 16) have been synthesized and their micelles properties studied in aqueous solution using pyrene, pyrenecarboxaldehyde (PCA) and 1,8 anilinonaphtalene sulfonic acid sodium salt (ANS) as fluorescent probes. The micelles from these surfactants have been characterized on the basis of the information provided by micelle-solubilized fluorescent probes. The obtained results indicated that the surfactant concentration at which a marked decrease in l max parameter of pyrenecarboxaldehyde (PCA) occurs corresponds to the CMC determined by conductimetric measurements. Changes in the emission spectra of ANS and PCA observed in the submicellar range for both surfactants series (n-2-n and n-6-n) were interpreted as formation of pre-aggregates. It was found that the dimeric surfactants with long spacer (s= 6) form more hydrated aggregates when compared with those formed by the n-2-n and CnTAB surfactants series. This was attributed to a more difficult packing of n-6-n surfactant molecules to form micelles.

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Foram analisadas amostras de quiabo dos municípios de Caruaru e Vitória de Santo Antão, em Pernambuco, assim como nos municípios de Ceará-Mirim, Macaíba e Extremoz no estado do Rio Grande do Norte. A aplicação de dois métodos de análise exploratória de dados: Análise de Componentes principais - PCA e Análise de Agrupamentos Hierárquicos - HCA permitiu a discriminação geográfica do quiabo proveniente dos dois estados.

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The characterization of different ecological groups in a forest formation/succession is unclear. To better define the different successional classes, we have to consider ecophysiological aspects, such as the capacity to use or dissipate the light energy available. The main objective of this work was to assess the chlorophyll fluorescence emission of tropical tree species growing in a gap of a semi-deciduous forest. Three species of different ecological groups were selected: Croton floribundus Spreng. (pioneer, P), Astronium graveolens Jacq. (early secondary, Si), and Esenbeckia febrifuga A. Juss. (late secondary, St). The potential (Fv/Fm) and effective (deltaF/Fm') quantum efficiency of photosystem II, apparent electron transport rate (ETR), non-photochemical (qN) and photochemical (qP) quenching of fluorescence were evaluated, using a modulated fluorometer, between 7:30 and 11:00 h. Values of Fv/Fm remained constant in St, decreasing in P and Si after 9:30 h, indicating the occurrence of photoinhibition. Concerning the measurements taken under light conditions (deltaF/Fm', ETR, qP and qN), P and Si showed better photochemical performance, i.e., values of deltaF/Fm', ETR and qP were higher than St when light intensity was increased. Values of qN indicated that P and Si had an increasing tendency of dissipating the excess of energy absorbed by the leaf, whereas the opposite was found for St. The principal component analysis (PCA), considering all evaluated parameters, showed a clear distinction between St, P and Si, with P and Si being closer. The PCA results suggest that chlorophyll fluorescence may be a potential tool to differentiate tree species from distinct successional groups.

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A busca por novas tecnologias que garantam a uniformidade da qualidade dos produtos tem se tornado constante, assim este trabalho teve como objetivo estudar a potencialidade de medidas espectroscópicas combinadas a ferramentas estatísticas para classificação de lâminas de madeiras de Pinus spp. contaminadas por fungos manchadores. As amostras foram coletadas em processo industrial, e observou-se que algumas lâminas estavam contaminadas por fungos manchadores. Assim, utilizou-se este material para investigar a influência dessa mancha azul em metodologias espectroscópicas e a possibilidade de discriminação dessa contaminação. Desse material contaminado foram capturados os espectros, na faixa de 400 a 1000 nm. Com esses dados, realizou-se uma análise exploratória por Componentes Principais (PCA) e classificação via SIMCA, em que se verificou a discriminação eficiente em dois grupos, madeiras sadias e contaminadas. Observou-se que a técnica de espectroscopia óptica preenche os requisitos necessários para uma possível aplicação na classificação de lâminas no processo produtivo.

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The aim of this study was to identify, by multivariate statistical technique, the physic, chemical and biological variables that best characterize the quality of surface waters in two small rural catchments with different land uses (eucalyptus silviculture (SC) vs. pasture and extensive livestock (LC)) located in Rosário do Sul, RS - Brazil. Monitoring was conducted during the months of August 2011 to August 2012 and the following parameters were analyzed: Ca2+, Mg2+, K+, SO42-, Cl-, pH, electrical conductivity, turbidity, alkalinity, suspended and dissolved solids, biochemical oxygen demand , total coliforms, Escherichia coli and temperature, flow and rainfall. Through the use of FA/PCA, it was found that the model best fit to express water quality of in LC that was composed of five factors which account for 83.5% of the total variance, while for SC, four factors accounted for 85.12% of the variance. In LC, the five main factors were, respectively, soluble salts, diffuse pollution, solid, and both anthropogenic and organic factors. In SC, the four factors were namely: soluble salts, mineral, nutritional and diffuse pollution factors. The results of this study showed that by replacing the traditional soil usage (pasture and livestock) with planted forest, diffuse pollution was attenuated but, however, it did not result in major changes in the physical-chemical and biological characteristics of the water. Another point to note is that factorial analysis did not result in a large reduction in the number of variables, once the best model fit occurred with the addition of 15 of 18 analyzed variables (LC) and 17 of 18 analyzed variables (SC).