Cistatina C, PCR, Log TG/HDLc e Sindrome Metabolica estao Relacionados a Microalbuminuria na Hipertensao

Fundamento: Em pacientes com hipertensão arterial sistêmica, a microalbuminúria é um marcador de lesão endotelial e está associada a um risco aumentado de doença cardiovascular. Objetivo: O objetivo do presente estudo foi determinar os fatores que influenciam a ocorrência de microalbumiúria em pacientes hipertensos com creatinina sérica menor que 1,5 mg/dL. Métodos: Foram incluídos no estudo 133 pacientes brasileiros atendidos em um ambulatório multidisciplinar para hipertensos. Pacientes com creatinina sérica maior do que 1,5 mg/dL e aqueles com diabete mellitus foram excluídos do estudo. A pressão arterial sistólica e diastólica foi aferida. O índice de massa corporal (IMC) e a taxa de filtração glomerular estimada pela fórmula CKD-EPI foram calculados. Em um estudo transversal, creatinina, cistatina C, colesterol total, HDL colesterol, LDL colesterol, triglicerídeos, proteína C-reativa (PCR) e glicose foram mensurados em amostra de sangue. A microalbuminúria foi determinada na urina colhida em 24 horas. Os hipertensos foram classificados pela presença de um ou mais critérios para síndrome metabólica. Resultados: Em análise de regressão múltipla, os níveis séricos de cistatina C, PCR, o índice aterogênico log TG/HDLc e a presença de três ou mais critérios para síndrome metabólica foram positivamente correlacionados com a microalbuminuria (r2: 0,277; p < 0,05). Conclusão: Cistatina C, PCR, log TG/HDLc e presença de três ou mais critérios para síndrome metabólica, independentemente da creatinina sérica, foram associados com a microalbuminúria, um marcador precoce de lesão renal e de risco cardiovascular em pacientes com hipertensão arterial essencial.

Evaluation of a linear spectral mixture model and vegetation indices (NDVI and EVI) in a study of schistosomiasis mansoni and Biomphalaria glabrata distribution in the state of Minas Gerais, Brazil

This paper analyses the associations between Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) on the prevalence of schistosomiasis and the presence of Biomphalaria glabrata in the state of Minas Gerais (MG), Brazil. Additionally, vegetation, soil and shade fraction images were created using a Linear Spectral Mixture Model (LSMM) from the blue, red and infrared channels of the Moderate Resolution Imaging Spectroradiometer spaceborne sensor and the relationship between these images and the prevalence of schistosomiasis and the presence of B. glabrata was analysed. First, we found a high correlation between the vegetation fraction image and EVI and second, a high correlation between soil fraction image and NDVI. The results also indicate that there was a positive correlation between prevalence and the vegetation fraction image (July 2002), a negative correlation between prevalence and the soil fraction image (July 2002) and a positive correlation between B. glabrata and the shade fraction image (July 2002). This paper demonstrates that the LSMM variables can be used as a substitute for the standard vegetation indices (EVI and NDVI) to determine and delimit risk areas for B. glabrata and schistosomiasis in MG, which can be used to improve the allocation of resources for disease control.

Biotic factors and occurrence of Lutzomyia longipalpis in endemic area of visceral leishmaniasis, Mato Grosso do Sul, Brazil

The relationships between environmental exposure to risk agents and health conditions have been studied with the aid of remote sensing imagery, a tool particularly useful in the study of vegetation cover. This study aims to evaluate the influence of environmental variables on the spatial distribution of the abundance of Lutzomyia longipalpis and the reported canine and human visceral leishmaniasis (VL) cases at an urban area of Campo Grande, state of Mato Grosso do Sul. The sandfly captures were performed in 13 residences that were selected by raffle considering four residences or collection station for buffer. These buffers were generated from the central house with about 50, 100 and 200 m from it in an endemic area of VL. The abundance of sandflies and human and canine cases were georreferenced using the GIS software PCI Geomatica. The normalized difference vegetation index (NDVI) and percentage of land covered by vegetation were the environmental variables extracted from a remote sensing IKONOS-2 image. The average NDVI was considered as the complexity of habitat and the standard deviation as the heterogeneity of habitat. One thousand three hundred sixty-seven specimens were collected during the catch. We found a significant positive linear correlation between the abundance of sandflies and the percentage of vegetation cover and average NDVI. However, there was no significant association between habitat heterogeneity and the abundance of these flies.

Perceived self-image in adolescent idiopathic scoliosis: an integrative review of the literature

Objective: To learn about the experiences of adolescents diagnosed with idiopathic scoliosis. Method: Integrative review of the literature published within a specified time frame. Results: For both sexes, the predominant clinical symptom of this condition appears to be the negative effect that the deformity exerts on perceived self-image. Quantitative studies used numerical scores to assess perceptions of body image but did not analyse emotional aspects. Patients treated surgically were found to have a better self-image than patients treated with a brace. Quality of life was improved by a reduction in the magnitude of the curve. Conclusion: Spinal deformity exerts a psychological effect on adolescent girls.


Mineralogy of the clay fraction of Alfisols in two slope curvatures: III - spatial variability

A good knowledge of the spatial distribution of clay minerals in the landscape facilitates the understanding of the influence of relief on the content and crystallographic attributes of soil minerals such as goethite, hematite, kaolinite and gibbsite. This study aimed at describing the relationships between the mineral properties of the clay fraction and landscape shapes by determining the mineral properties of goethite, hematite, kaolinite and gibbsite, and assessing their dependence and spatial variability, in two slope curvatures. To this end, two 100 × 100 m grids were used to establish a total of 121 regularly spaced georeferenced sampling nodes 10 m apart. Samples were collected from the layer 0.0-0.2 m and analysed for iron oxides, and kaolinite and gibbsite in the clay fraction. Minerals in the clay fraction were characterized from their X-ray diffraction (XRD) patterns, which were interpreted and used to calculate the width at half height (WHH) and mean crystallite dimension (MCD) of iron oxides, kaolinite, and gibbsite, as well as aluminium substitution and specific surface area (SSA) in hematite and goethite. Additional calculations included the goethite and hematite contents, and the goethite/(goethite+hematite) [Gt/(Gt+Hm)] and kaolinite/(kaolinite+gibbsite) [Kt/(Kt+Gb)] ratios. Mineral properties were established by statistical analysis of the XRD data, and spatial dependence was assessed geostatistically. Mineralogical properties differed significantly between the convex area and concave area. The geostatistical analysis showed a greater number of mineralogical properties with spatial dependence and a higher range in the convex than in the concave area.

Mineralogy of the clay fraction of alfisols in two slope curvatures: IV - spatial correlation with physical properties

Although the influence of clay mineralogy on soil physical properties has been widely studied, spatial relationships between these features in Alfisols have rarely been examined. The purpose of this work was to relate the clay minerals and physical properties of an Alfisol of sandstone origin in two slope curvatures. The crystallographic properties such as mean crystallite size (MCS) and width at half height (WHH) of hematite, goethite, kaolinite and gibbsite; contents of hematite and goethite; aluminium substitution (AS) and specific surface area (SSA) of hematite and goethite; the goethite/(goethite+hematite) and kaolinite/(kaolinite+gibbsite) ratios; and the citrate/bicarbonate/dithionite extractable Fe (Fe d) were correlated with the soil physical properties through Pearson correlation coefficients and cross-semivariograms. The correlations found between aluminium substitution in goethite and the soil physical properties suggest that the degree of crystallinity of this mineral influences soil properties used as soil quality indicators. Thus, goethite with a high aluminium substitution resulted in large aggregate sizes and a high porosity, and also in a low bulk density and soil penetration resistance. The presence of highly crystalline gibbsite resulted in a high density and micropore content, as well as in smaller aggregates. Interpretation of the cross-semivariogram and classification of landscape compartments in terms of the spatial dependence pattern for the relief-dependent physical and mineralogical properties of the soil proved an effective supplementary method for assessing Pearson correlations between the soil physical and mineralogical properties.

Comparison between artificial neural networks and maximum likelihood classification in digital soil mapping

Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm) in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI) and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI), derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs) was greater than of the classic Maximum Likelihood Classifier (MLC). Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 %) was superior to the MLC map (57.94 %). The main errors when using the two classifiers were caused by: a) the geological heterogeneity of the area coupled with problems related to the geological map; b) the depth of lithic contact and/or rock exposure, and c) problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.

Building predictive models of soil particle-size distribution

Is it possible to build predictive models (PMs) of soil particle-size distribution (psd) in a region with complex geology and a young and unstable land-surface? The main objective of this study was to answer this question. A set of 339 soil samples from a small slope catchment in Southern Brazil was used to build PMs of psd in the surface soil layer. Multiple linear regression models were constructed using terrain attributes (elevation, slope, catchment area, convergence index, and topographic wetness index). The PMs explained more than half of the data variance. This performance is similar to (or even better than) that of the conventional soil mapping approach. For some size fractions, the PM performance can reach 70 %. Largest uncertainties were observed in geologically more complex areas. Therefore, significant improvements in the predictions can only be achieved if accurate geological data is made available. Meanwhile, PMs built on terrain attributes are efficient in predicting the particle-size distribution (psd) of soils in regions of complex geology.

Influence of field slope and coffee plantation age on the physical properties of a red-yellow Latosol

In modern agriculture, several factors cause changes in the soil physical properties. The time of establishment of a crop (plantation age) and the slope are examples of factors that moderate the impact of mechanized operations on the soil structure. The objective of this study was to analyze the effect of machinery traffic on the physical properties of a Red-Yellow Latosol under coffee plantations with different ages (2, 7, 18, and 33 years) and slope positions (3, 9 and 15 %). Samples were collected from three positions between coffee rows (lower wheel track, inter-row and upper wheel track) and at two depths (surface layer and sub-surface). Changes in the total porosity, macroporosity, microporosity, organic matter, bulk density, and aggregate stability were investigated. Our results showed that the slope influenced the organic matter content, microporosity and aggregate stability. The soil samples under the inter-row were minimally damaged in their structure, compared to those from under the lower and upper wheel track, while the structure was better preserved under the lower than the upper track. The time since the establishment of the crop, i.e., the plantation age, was the main factor determining the extent of structural degradation in the coffee plantation.

Public-domain software for root image analysis

In the search for high efficiency in root studies, computational systems have been developed to analyze digital images. ImageJ and Safira are public-domain systems that may be used for image analysis of washed roots. However, differences in root properties measured using ImageJ and Safira are supposed. This study compared values of root length and surface area obtained with public-domain systems with values obtained by a reference method. Root samples were collected in a banana plantation in an area of a shallower Typic Carbonatic Haplic Cambisol (CXk), and an area of a deeper Typic Haplic Ta Eutrophic Cambisol (CXve), at six depths in five replications. Root images were digitized and the systems ImageJ and Safira used to determine root length and surface area. The line-intersect method modified by Tennant was used as reference; values of root length and surface area measured with the different systems were analyzed by Pearson's correlation coefficient and compared by the confidence interval and t-test. Both systems ImageJ and Safira had positive correlation coefficients with the reference method for root length and surface area data in CXk and CXve. The correlation coefficient ranged from 0.54 to 0.80, with lowest value observed for ImageJ in the measurement of surface area of roots sampled in CXve. The IC (95 %) revealed that root length measurements with Safira did not differ from that with the reference method in CXk (-77.3 to 244.0 mm). Regarding surface area measurements, Safira did not differ from the reference method for samples collected in CXk (-530.6 to 565.8 mm²) as well as in CXve (-4231 to 612.1 mm²). However, measurements with ImageJ were different from those obtained by the reference method, underestimating length and surface area in samples collected in CXk and CXve. Both ImageJ and Safira allow an identification of increases or decreases in root length and surface area. However, Safira results for root length and surface area are closer to the results obtained with the reference method.

Artificial neural networks applied for soil class prediction in mountainous landscape of the Serra do Mar¹

Soil information is needed for managing the agricultural environment. The aim of this study was to apply artificial neural networks (ANNs) for the prediction of soil classes using orbital remote sensing products, terrain attributes derived from a digital elevation model and local geology information as data sources. This approach to digital soil mapping was evaluated in an area with a high degree of lithologic diversity in the Serra do Mar. The neural network simulator used in this study was JavaNNS and the backpropagation learning algorithm. For soil class prediction, different combinations of the selected discriminant variables were tested: elevation, declivity, aspect, curvature, curvature plan, curvature profile, topographic index, solar radiation, LS topographic factor, local geology information, and clay mineral indices, iron oxides and the normalized difference vegetation index (NDVI) derived from an image of a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. With the tested sets, best results were obtained when all discriminant variables were associated with geological information (overall accuracy 93.2 - 95.6 %, Kappa index 0.924 - 0.951, for set 13). Excluding the variable profile curvature (set 12), overall accuracy ranged from 93.9 to 95.4 % and the Kappa index from 0.932 to 0.948. The maps based on the neural network classifier were consistent and similar to conventional soil maps drawn for the study area, although with more spatial details. The results show the potential of ANNs for soil class prediction in mountainous areas with lithological diversity.

Avaliação do acesso a periódicos eletrônicos na web pela análise do arquivo de log de acesso

Este artigo apresenta uma abordagem sobre a avaliação do acesso a periódicos eletrônicos disponibilizados na World Wide Web por meio da análise do arquivo de log de acesso. O arquivo de log de acesso da revista Informação & Sociedade: Estudos é processado e apresentado como um exemplo de aplicação do uso de uma ferramenta automatizada de análise para arquivo de iog de acesso. As características inerentes à análise do arquivo de log de acesso são apresentadas e discutidas.

Sample size for measurement of root traits on common bean by image analysis

Evaluation of root traits may be facilitated if they are assessed on samples of the root system. The objective of this work was to determine the sample size of the root system in order to estimate root traits of common bean (Phaseolus vulgaris L.) cultivars by digital image analysis. One plant was grown per pot and harvested at pod setting, with 64 and 16 pots corresponding to two and four cultivars in the first and second experiments, respectively. Root samples were scanned up to the completeness of the root system and the root area and length were estimated. Scanning a root sample demanded 21 minutes, and scanning the entire root system demanded 4 hours and 53 minutes. In the first experiment, root area and length estimated with two samples showed, respectively, a correlation of 0.977 and 0.860, with these traits measured in the entire root. In the second experiment, the correlation was 0.889 and 0.915. The increase in the correlation with more than two samples was negligible. The two samples corresponded to 13.4% and 16.9% of total root mass (excluding taproot and nodules) in the first and second experiments. Taproot stands for a high proportion of root mass and must be deducted on root trait estimations. Samples with nearly 15% of total root mass produce reliable root trait estimates.

Spatio-temporal image correlation (STIC): nova técnica para avaliação do coração fetal

As malformações cardíacas são as mais freqüentes anomalias congênitas ao nascimento, entretanto, a sua detecção pré-natal pela ultra-sonografia convencional permanece baixa. As ultra-sonografias de terceira e quarta dimensões surgiram no início da década de 90, apresentando grandes aplicações em obstetrícia, principalmente nos casos de diagnósticos duvidosos à ultra-sonografia bidimensional. O spatio-temporal image correlation (STIC) representa grande avanço na área de ultra-som de quarta dimensão; constitui-se em um software acoplado ao aparelho Voluson 730 Expert, que permite a aquisição volumétrica do coração fetal e suas conexões vasculares. As análises volumétricas são realizadas nos modos multiplanar e de renderização, podendo-se também utilizar o Doppler. Apresenta, como grandes vantagens, a aquisição rápida e a possibilidade de análise posterior por especialistas em ecocardiografia fetal. Pode ser aplicada para a pesquisa de quaisquer cardiopatias congênitas, pois permite a aquisição de qualquer plano, diferentemente do ultra-som bidimensional. Sua principal desvantagem está relacionada aos movimentos fetais. A maior difusão do método pode permitir um aumento na detecção de malformações cardíacas, pois possibilita ao ultra-sonografista geral encaminhar, via Internet, os volumes para a análise por especialistas em ecocardiografia fetal.

Evolution of mammographic image quality in the state of Rio de Janeiro

Objective:To evaluate the evolution of mammographic image quality in the state of Rio de Janeiro on the basis of parameters measured and analyzed during health surveillance inspections in the period from 2006 to 2011.Materials and Methods:Descriptive study analyzing parameters connected with imaging quality of 52 mammography apparatuses inspected at least twice with a one-year interval.Results:Amongst the 16 analyzed parameters, 7 presented more than 70% of conformity, namely: compression paddle pressure intensity (85.1%), films development (72.7%), film response (72.7%), low contrast fine detail (92.2%), tumor mass visualization (76.5%), absence of image artifacts (94.1%), mammography-specific developers availability (88.2%). On the other hand, relevant parameters were below 50% conformity, namely: monthly image quality control testing (28.8%) and high contrast details with respect to microcalcifications visualization (47.1%).Conclusion:The analysis revealed critical situations in terms of compliance with the health surveillance standards. Priority should be given to those mammography apparatuses that remained non-compliant at the second inspection performed within the one-year interval.