65 resultados para structure based alignments


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The integration of optical detection methods in continuous flow microsystems can highly extend their range of application, as long as some negative effects derived from their scaling down can be minimized. Downsizing affects to a greater extent the sensitivity of systems based on absorbance measurements than the sensitivity of those based on emission ones. However, a careful design of the instrumental setup is needed to maintain the analytical features in both cases. In this work, we present the construction and evaluation of a simple miniaturized optical system, which integrates a novel flow cell configuration to carry out chemiluminescence (CL) measurements using a simple photodiode. It consists of a micro-mixer based on a vortex structure, which has been constructed by means of the low-temperature cofired ceramics (LTCC) technology. This mixer not only efficiently promotes the CL reaction due to the generated high turbulence but also allows the detection to be carried out in the same area, avoiding intensity signal losses. As a demonstration, a flow injection system has been designed and optimized for the detection of cobalt(H) in water samples. It shows a linear response between 2 and 20 mu M with a correlation of r > 0.993, a limit of detection of 1.1 mu M, a repeatability of RSD = 12.4 %, and an analysis time of 17 s. These results demonstrate the suitability of the proposal to the determination of compounds involved in CL reactions by means of an easily constructed versatile device based on low-cost instrumentation.

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The present work reports the thermal annealing process, the number of layer and electrochemical process effect in the optical response quality of Bragg and microcavity devices that were applied as organic solvent sensors. These devices have been obtained by using porous silicon (PS) technology. The optical characterization of the Bragg reflector, before annealing, showed a broad photonic band-gap structure with blue shifted and narrowed after annealing process. The electrochemical process used to obtain the PS-based device imposes the limit in the number of layers because of the chemical dissolution effect. The interface roughness minimizations in the devices have been achieved by using the double electrochemical cell setup. The microcavity devices showed to have a good sensibility for organic solvent detection. The thermal annealed device showed better sensibility feature and this result was attributed to passivation of the surface devices. (c) 2007 Elsevier Ltd. All rights reserved.

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Xanthomonas axonopodis pv. passiflorae causes bacterial spot in passion fruit. It attacks the purple and yellow passion fruit as well as the sweet passion fruit. The diversity of 87 isolates of pv. passiflorae collected from across 22 fruit orchards in Brazil was evaluated using molecular profiles and statistical procedures, including an unweighted pair-group method with arithmetical averages-based dendrogram, analysis of molecular variance (AMOVA), and an assigning test that provides information on genetic structure at the population level. Isolates from another eight pathovars were included in the molecular analyses and all were shown to have a distinct repetitive sequence-based polymerase chain reaction profile. Amplified fragment length polymorphism technique revealed considerable diversity among isolates of pv. passiflorae, and AMOVA showed that most of the variance (49.4%) was due to differences between localities. Cluster analysis revealed that most genotypic clusters were homogeneous and that variance was associated primarily with geographic origin. The disease adversely affects fruit production and may kill infected plants. A method for rapid diagnosis of the pathogen, even before the disease symptoms become evident, has value for producers. Here, a set of primers (Xapas) was designed by exploiting a single-nucleotide polymorphism between the sequences of the intergenic 16S-23S rRNA spacer region of the pathovars. Xapas was shown to effectively detect all pv. passiflorae isolates and is recommended for disease diagnosis in passion fruit orchards.

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The application of tannery sludge to soils is a form of recycling; however, few studies have examined the impacts of this practice on soil microbial properties. We studied effects of two applications (2006 and 2007) of tannery sludge (with a low chromium content) on the structure of the bacterial community and on the microbial activity of soils. We fertilized an agricultural area in Rolandia, Parana state, Brazil with different doses of sludge based on total N content, which ranged from 0 to 1200 kg N ha(-1). Sludge remained on the soil surface for three months before being plowed. Soils were sampled seven times during the experiment. Bacterial community structure, assessed by denaturing gradient gel electrophoresis (DGGE), was modified by the application of tannery sludge. Soon after the first application, there was clear separation between the bacterial communities in different treatments, such that each dose of sludge was associated with a specific community. These differences remained until 300 days after application and also after the second sludge application, but 666 days after the beginning of the experiment no differences were found in the bacterial communities of the lowest doses and the control. The principal response curve (PRC) analysis showed that the first sludge application strongly stimulated biological activity even 300 days after application. The second application also stimulated activity, but at a lower magnitude and for a shorter time, given that 260 days after the second application there was no difference in biological activity among treatments. PRC also showed that the properties most influenced by the application of tannery sludge were enzymatic activities related to N cycling (asparaginase and urease). The redundancy analysis (RDA) showed that tannery sludge`s influence on microbial activity is mainly related to increases in inorganic N and soil pH. Results showed that changes in the structure of the bacterial community in the studied soils were directly related to changes of their biological activity. (C) 2010 Elsevier Ltd. All rights reserved.

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By allowing the estimation of forest structural and biophysical characteristics at different temporal and spatial scales, remote sensing may contribute to our understanding and monitoring of planted forests. Here, we studied 9-year time-series of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) on a network of 16 stands in fast-growing Eucalyptus plantations in Sao Paulo State, Brazil. We aimed to examine the relationships between NDVI time-series spanning entire rotations and stand structural characteristics (volume, dominant height, mean annual increment) in these simple forest ecosystems. Our second objective was to examine spatial and temporal variations of light use efficiency for wood production, by comparing time-series of Absorbed Photosynthetically Active Radiation (APAR) with inventory data. Relationships were calibrated between the NDVI and the fractions of intercepted diffuse and direct radiation, using hemispherical photographs taken on the studied stands at two seasons. APAR was calculated from the NDVI time-series using these relationships. Stem volume and dominant height were strongly correlated with summed NDVI values between planting date and inventory date. Stand productivity was correlated with mean NDVI values. APAR during the first 2 years of growth was variable between stands and was well correlated with stem wood production (r(2) = 0.78). In contrast, APAR during the following years was less variable and not significantly correlated with stem biomass increments. Production of wood per unit of absorbed light varied with stand age and with site index. In our study, a better site index was accompanied both by increased APAR during the first 2 years of growth and by higher light use efficiency for stem wood production during the whole rotation. Implications for simple process-based modelling are discussed. (C) 2009 Elsevier B.V. All rights reserved.

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Tuberculosis (TB) is the primary cause of mortality among infectious diseases. Mycobacterium tuberculosis monophosphate kinase (TMPKmt) is essential to DNA replication. Thus, this enzyme represents a promising target for developing new drugs against TB. In the present study, the receptor-independent, RI, 4D-QSAR method has been used to develop QSAR models and corresponding 3D-pharmacophores for a set of 81 thymidine analogues, and two corresponding subsets, reported as inhibitors of TMPKmt. The resulting optimized models are not only statistically significant with r (2) ranging from 0.83 to 0.92 and q (2) from 0.78 to 0.88, but also are robustly predictive based on test set predictions. The most and the least potent inhibitors in their respective postulated active conformations, derived from each of the models, were docked in the active site of the TMPKmt crystal structure. There is a solid consistency between the 3D-pharmacophore sites defined by the QSAR models and interactions with binding site residues. Moreover, the QSAR models provide insights regarding a probable mechanism of action of the analogues.

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The Brazil consolidated itself as the largest world producer of sugarcane, sugar and ethanol. The creation of the Programa Nacional do Alcool - PROALCOOL and the growing use of cars with flexible motors were some of the factors that helped to motivate still more the production. Evolutions in the agricultural and industrial research did the Brazilian competitiveness in sugar and ethanol globally elevated, what is evidenced when comparing the amount produced at the country and the production costs, which turned a big one differential. Therefore, the administration of costs is of great relevance to the sugar and ethanol companies, for representing a significant rationalization in the production processes, with economy of resources and the reach of better earnings, besides reducing the operational risk pertinent at the fixed costs of production. Thus, the present work has for objective to analyze the costs structure of sugar and ethanol companies of the Center-south area of the country through an empiric-analytical study based in methodologies and concepts extracted of the costs accounting. It is verified that great part of the costs and operational expenses have variable behavior, a positive factor for the sector reducing the operational risk of the activity. The main restraint of this study is the sample of five years and 10% of the number of plants in Brazil that although they represent 30% of the national production, don`t allow the generalization of the model.

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Streptococcus pyogenes infections remain a health problem in several countries due to poststreptococcal sequelae. We developed a vaccine epitope (StreptInCor) composed of 55 amino acids residues of the C-terminal portion of the M protein that encompasses both T and B cell protective epitopes. The nuclear magnetic resonance (NMR) structure of the StreptInCor peptide showed that the structure was composed of two microdomains linked by an 18-residue alpha-helix. A chemical stability study of the StreptInCor folding/unfolding process using far-UV circular dichroism showed that the structure was chemically stable with respect to pH and the concentration of urea. The T cell epitope is located in the first microdomain and encompasses 11 out of the 18 alpha-helix residues, whereas the B cell epitope is in the second microdomain and showed no alpha-helical structure. The prediction of StreptInCor epitope binding to different HLA class II molecules was evaluated based on an analysis of the 55 residues and the theoretical possibilities for the processed peptides to fit into the P1, P4, P6, and P9 pockets in the groove of several HLA class II molecules. We observed 7 potential sites along the amino acid sequence of StreptInCor that were capable of recognizing HLA class II molecules (DRB1*, DRB3*, DRB4*, and DRB5*). StreptInCoroverlapping peptides induced cellular and humoral immune responses of individuals bearing different HLA class II molecules and could be considered as a universal vaccine epitope.

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The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

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Here, we examine morphological changes in cortical thickness of patients with Alzheimer`s disease (AD) using image analysis algorithms for brain structure segmentation and study automatic classification of AD patients using cortical and volumetric data. Cortical thickness of AD patients (n = 14) was measured using MRI cortical surface-based analysis and compared with healthy subjects (n = 20). Data was analyzed using an automated algorithm for tissue segmentation and classification. A Support Vector Machine (SVM) was applied over the volumetric measurements of subcortical and cortical structures to separate AD patients from controls. The group analysis showed cortical thickness reduction in the superior temporal lobe, parahippocampal gyrus, and enthorhinal cortex in both hemispheres. We also found cortical thinning in the isthmus of cingulate gyrus and middle temporal gyrus at the right hemisphere, as well as a reduction of the cortical mantle in areas previously shown to be associated with AD. We also confirmed that automatic classification algorithms (SVM) could be helpful to distinguish AD patients from healthy controls. Moreover, the same areas implicated in the pathogenesis of AD were the main parameters driving the classification algorithm. While the patient sample used in this study was relatively small, we expect that using a database of regional volumes derived from MRI scans of a large number of subjects will increase the SVM power of AD patient identification.

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Nursing diagnoses associated with alterations of urinary elimination require different interventions, Nurses, who are not specialists, require support to diagnose and manage patients with disturbances of urine elimination. The aim of this study was to present a model based on fuzzy logic for differential diagnosis of alterations in urinary elimination, considering nursing diagnosis approved by the North American Nursing Diagnosis Association, 2001-2002. Fuzzy relations and the maximum-minimum composition approach were used to develop the system. The model performance was evaluated with 195 cases from the database of a previous study, resulting in 79.0% of total concordance and 19.5% of partial concordance, when compared with the panel of experts. Total discordance was observed in only three cases (1.5%). The agreement between model and experts was excellent (kappa = 0.98, P < .0001) or substantial (kappa = 0.69, P < .0001) when considering the overestimative accordance (accordance was considered when at least one diagnosis was equal) and the underestimative discordance (discordance was considered when at least one diagnosis was different), respectively. The model herein presented showed good performance and a simple theoretical structure, therefore demanding few computational resources.

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Objective: To compare the volume of the hippocampus and parahippocampal gyrus in elderly individuals with and without depressive disorders, and to determine whether the volumes of these regions correlate with scores on memory tests. Method: Clinical and demographic differences, as well as differences in regional gray matter volumes, were assessed in 48 elderly patients with depressive disorders and 31 control subjects. Brain (structural MRI) scans were processed using statistical parametric mapping and voxel-based morphometry. Cognitive tests were administered to subjects in both groups. Results: There were no between-group gray matter volume differences in the hippocampus or parahippocampal gyrus. In the elderly depressed group only, the volume of the left parahippocampal gyrus correlated with scores on the delayed naming portion of the visual verbal learning test. There were also significant direct correlations in depressed subjects between the volumes of the left hippocampus, right and left parahippocampal gyrus and immediate recall scores on verbal episodic memory tests and visual learning tests. In the control group, there were direct correlations only between overall cognitive performance (as assessed with the MMSE) and the volume of right hippocampus, and between the total score on the visual verbal learning test and the volume of the right and left parahippocampal gyrus. Conclusions: These findings highlight different patterns of relationship between cognitive performance and volumes of medial temporal structures in depressed individuals and healthy elderly subjects. The direct correlation between delayed visual verbal memory recall scores with left parahippocampal volumes specifically in elderly depressed individuals provides support to the view that depression in elderly populations may be a risk factor for dementia. (C) 2009 Elsevier Inc. All rights reserved.

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Degenerative aortic valve disease (DAVD), a common finding in the elderly, is associated with an increased risk of death due to cardiovascular causes. Taking advantage of its longitudinal design, this study evaluates the prevalence of DAVD and its temporal associations with long-term exposure to cardiovascular risk factors in the general population. We studied 953 subjects (aged 25-74 years) from a random sample of German residents. Risk factors had been determined at a baseline investigation in 1994/95. At a follow-up investigation, 10 years later, standardized echocardiography determined aortic valve morphology and aortic valve area (AVA) as well as left ventricular geometry and function. At the follow-up study, the overall prevalence of DAVD was 28%. In logistic regression models adjusting for traditional cardiovascular risk factors at baseline age (OR 2.0 [1.7-2.3] per 10 years, P < 0.001), active smoking (OR 1.7 [1.1-2.4], P = 0.009) and elevated total cholesterol levels (OR 1.2 [1.1-1.3] per increase of 20 mg/dL, P < 0.001) were significantly related to DAVD at follow-up. Furthermore, age, baseline status of smoking, and total cholesterol level were significant predictors of a smaller AVA at follow-up study. In contrast, hypertension and obesity had no detectable relationship with long-term changes of aortic valve structure. In the general population we observed a high prevalence of DAVD that is associated with long-term exposure to elevated cholesterol levels and active smoking. These findings strengthen the notion that smoking cessation and cholesterol lowering are promising treatment targets for prevention of DAVD.

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The resin phase of dental composites is mainly composed of combinations of dimethacrylate comonomers, with final polymeric network structure defined by monomer type/reactivity and degree of conversion. This fundamental study evaluates how increasing concentrations of the flexible triethylene glycol dimethacrylate (TEGDMA) influences void formation in bisphenol A diglycidyl dimethacrylate (BisGMA) co-polymerizations and correlates this aspect of network structure with reaction kinetic parameters and macroscopic volumetric shrinkage. Photopolymerization kinetics was followed in real-time by a near-infrared (NIR) spectroscopic technique, viscosity was assessed with a viscometer, volumetric shrinkage was followed with a linometer, free volume formation was determined by positron annihilation lifetime spectroscopy (PALS) and the sol-gel composition was determined by extraction with dichloromethane followed by (1)H NMR analysis. Results show that, as expected, volumetric shrinkage increases with TEGDMA concentration and monomer conversion. Extraction/(1)H NMR studies show increasing participation of the more flexible TEGDMA towards the limiting stages of conversion/crosslinking development. As the conversion progresses, either based on longer irradiation times or greater TEGDMA concentrations, the network becomes more dense, which is evidenced by the decrease in free volume and weight loss after extraction in these situations. For the same composition (BisGMA/TEGDMA 60-40 mol%) light-cured for increasing periods of time (from 10 to 600 s), free volume decreased and volumetric shrinkage increased, in a linear relationship with conversion. However, the correlation between free volume and macroscopic volumetric shrinkage was shown to be rather complex for variable compositions exposed for the same time (600 s). The addition of TEGDMA decreases free-volume up to 40 mol% (due to increased conversion), but above that concentration, in spite of the increase in conversion/crosslinking, free volume pore size increases due to the high concentration of the more flexible monomer. In those cases, the increase in volumetric shrinkage was due to higher functional group concentration, in spite of the greater free volume. Therefore, through the application of the PALS model, this study elucidates the network formation in dimethacrylates commonly used in dental materials. (C) 2010 Elsevier Ltd. All rights reserved.

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This work explores in detail synoptic and mesoscale features of Hurricane Catarina during its life cycle from a decaying baroclinic wave to a tropical depression that underwent tropical transition (TT) and finally to a Category 2 hurricane at landfall over Santa Catarina State coast, southern Brazil. This unique system caused 11 deaths mostly off the Brazilian coast and an estimated half billion dollars in damage in a matter of a few hours on 28 March 2004. Although the closest meteorological station available was tens of kilometres away from the eye, in situ meteorological measurements provided by a work-team sent to the area where the eye made landfall unequivocally reproduces the tropical signature with category 2 strength, adding to previous analysis where this data was not available. Further analyses are based mostly on remote sensing data available at the time of the event. A classic dipole blocking set synoptic conditions for Hurricane Catarina to develop, dynamically contributing to the low wind shear observed. On the other hand, on its westward transit, large scale subsidence limited its strength and vertical development. Catarina had relatively cool SST conditions, but this was mitigated by favourable air-sea fluxes leading to latent heat release-driven processes during the mature phase. The ocean`s dynamic topography also suggested the presence of nearby warm core rings which may have facilitated the transition and post-transition intensification. Since there were no records of such a system at least in the past 30 years and given that SSTs were generally below 26 degrees C and vertical shear was usually strong, despite all satellite data available, the system was initially classified as an extratropical cyclone. Here we hypothesise that this categorization was based oil inadequate regional scale model outputs which did not account for the importance of the latent heat fluxes over the ocean. Hurricane Catarina represents a dramatic event on weather systems in South America. It has attracted attention worldwide and poses questions as whether or not it is a symptom of global warming. (C) 2009 Elsevier B.V. All rights reserved.