Upregulation of inducible NO synthase by exogenous adenosine in vascular smooth muscle cells activated by inflammatory stimuli in experimental diabetes

BACKGROUND: Adenosine has been shown to induce nitric oxide (NO) production via inducible NO synthase (iNOS) activation in vascular smooth muscle cells (VSMCs). Although this is interpreted as a beneficial vasodilating pathway in vaso-occlusive disorders, iNOS is also involved in diabetic vascular dysfunction. Because the turnover of and the potential to modulate iNOS by adenosine in experimental diabetes have not been explored, we hypothesized that both the adenosine system and control of iNOS function are impaired in VSMCs from streptozotocin-diabetic rats. METHODS: Male Sprague-Dawley rats were injected with streptozotocin once to induce diabetes. Aortic VSMCs from diabetic and nondiabetic rats were isolated, cultured and exposed to lipopolysaccharide (LPS) plus a cytokine mix for 24 h in the presence or absence of (1) exogenous adenosine and related compounds, and/or (2) pharmacological agents affecting adenosine turnover. iNOS functional expression was determined by immunoblotting and NO metabolite assays. Concentrations of adenosine, related compounds and metabolites thereof were assayed by HPLC. Vasomotor responses to adenosine were determined in endothelium-deprived aortic rings. RESULTS: Treatment with adenosine-degrading enzymes or receptor antagonists increased iNOS formation in activated VSMCs from nondiabetic and diabetic rats. Following treatment with the adenosine transport inhibitor NBTI, iNOS levels increased in nondiabetic but decreased in diabetic VSMCs. The amount of secreted NO metabolites was uncoupled from iNOS levels in diabetic VSMCs. Addition of high concentrations of adenosine and its precursors or analogues enhanced iNOS formation solely in diabetic VSMCs. Exogenous adenosine and AMP were completely removed from the culture medium and converted into metabolites. A tendency towards elevated inosine generation was observed in diabetic VSMCs, which were also less sensitive to CD73 inhibition, but inosine supplementation did not affect iNOS levels. Pharmacological inhibition of NOS abolished adenosine-induced vasorelaxation in aortic tissues from diabetic but not nondiabetic animals. CONCLUSIONS: Endogenous adenosine prevented cytokine- and LPS-induced iNOS activation in VSMCs. By contrast, supplementation with adenosine and its precursors or analogues enhanced iNOS levels in diabetic VSMCs. This effect was associated with alterations in exogenous adenosine turnover. Thus, overactivation of the adenosine system may foster iNOS-mediated diabetic vascular dysfunction

Estrogen, angiogenesis, immunity and cell metabolism: Solving the puzzle

Estrogen plays an important role in the regulation of cardiovascular physiology and the immune system by inducing direct effects on multiple cell types including immune and vascular cells. Sex steroid hormones are implicated in cardiovascular protection, including endothelial healing in case of arterial injury and collateral vessel formation in ischemic tissue. Estrogen can exert potent modulation effects at all levels of the innate and adaptive immune systems. Their action is mediated by interaction with classical estrogen receptors (ERs), ER\u3b1 and ER\u3b2, as well as the more recently identified G-protein coupled receptor 30/G-protein estrogen receptor 1 (GPER1), via both genomic and non-genomic mechanisms. Emerging data from the literature suggest that estrogen deficiency in menopause is associated with an increased potential for an unresolved inflammatory status. In this review, we provide an overview through the puzzle pieces of how 17\u3b2-estradiol can influence the cardiovascular and immune systems

Spectral and time-frequency domains features for quantitative lower-limb rehabilitation monitoring via wearable inertial sensors

Inertial data represent a rich source of clinically relevant information which can provide details on motor assessment in subjects involved in a rehabilitation process. Thus, a number of metrics in the spectral and time-frequency domain has been considered to be reliable for measuring and quantifying patient progress and has been applied on the 3D accelerometer and angular rate signals collected on one impaired subject with knee injury through a wearable wireless inertial sensing system developed at the Tyndall National Institute. The subject has performed different activities evaluated across several sessions over time. Data show that most of the studied features can provide a quantitative analysis of the improvement of the subject along rehabilitation, and differentiate between impaired and unimpaired limb motor performance. The work proves that the studied features can be taken into account by clinicians and sport scientists to study the overall patients' condition and provide accurate clinical feedback as to their rehabilitative progress. The work is ongoing and additional clinical trials are currently being planned with an enhanced number of injured subjects to provide a more robust statistical analysis of the data in the study

GEOBIA, TREE DECISION AND HIERARCHICAL CLASSIFICATION FOR MAPPING GULLY EROSION

The gullies provoke environmental, social and financial damages. The application of corrective and preventive measures needs gullies mapping and monitoring. In this scope, this study proposes a methodology for gullies delimitation using object-oriented image analysis. For such, there were used high spatial resolution imagery and ALS data applied for two study areas, one in Uberlandia-Minas Gerais (Brazil) and another one in Queensland (Australia). The objects were generated by multiresolution segmentation. The most important attributes on the delimitation of the gullies were selected using decision tree induction algorithms, being them: spectral, altimetric and texture. Classifications by decision trees and hierarchical were carried out. The use of decision tree allowed the selection of attributes and the establishment of preliminary decision rules. However, since this procedure did not use fuzzy logic, mixtures between classes could not be evidenced in the rule base. Moreover, the classification was performed by a factor of scale only, which did not allow the identification of all the constituent features of the gully. In hierarchical classification, the procedure is performed on different scales, allowing the use of fuzzy logic to describe different degrees of membership in each class, which makes it a very attractive method for cases such as this study, where there is mixing of classes. The classification obtained with hierarchical classification it was more reliable with the field truth, by allowing the use of different scales, uncertainty insert and integration of knowledge, compared to the automatic classification by decision tree

Delimitação de voçoroca com imagens de alta resolução e ALS por meio de árvore de decisão e GEOBIA

Orientadores : Prof. Dr. Alzir Felippe Buffara AntunesTese (doutorado) - Universidade Federal do Paraná, Setor de Ciências da Terra, Programa de Pós-Graduação em Ciências Geodésicas. Defesa: Curitiba, 30/07/2015Inclui referências : f. 167-179Resumo: As voçorocas representam os processos erosivos responsáveis pelos maiores prejuízos ambientais, sociais e financeiros. A aplicação de medidas corretivas e preventivas necessita do mapeamento das voçorocas, bem como do monitoramento de sua evolução. No âmbito do sensoriamento remoto, dentre as características das voçorocas, podem-se citar: heterogeneidade espectral (mistura de solo, vegetação, sombra e água), heterogeneidade espacial (existência de feições como cabeceira, canais e dígitos, com formas irregulares e dimensões variáveis) e variação altimétrica (com alta declividade nas bordas). Em função destas especificidades, este estudo propôs uma metodologia para delimitação de voçorocas, em procedimentos de classificação de imagens baseados em análise orientada a objeto. Para tal, foram usadas imagem e ortofoto de alta resolução espacial e dados altimétricos ALS. Duas áreas de estudo foram selecionadas: uma localizada em Uberlândia-MG e outra localizada em Queensland-Austrália. Os objetos foram gerados por segmentação multirresolução (método FNEA-Fractal Net Evolution Approach). Foram selecionados os atributos mais relevantes na delimitação das voçorocas, usando algoritmos de indução de árvores de decisão (CART - Classification And Regression Trees), sendo estes atributos espectrais, altimétricos e de textura. Foram realizadas classificações por árvores de decisão e por classificação hierárquica. O uso da árvore de decisão permitiu a seleção de atributos e o estabelecimento de uma base de regras de decisão preliminar para a delimitação da voçoroca. Entretanto, como esse tipo de procedimento não faz uso de lógica fuzzy, as misturas entre as classes não pode ser evidenciada na base de regras de decisão. Além disso, a classificação é realizada apenas para um fator de escala, não permitindo identificar todas as feições constituintes do sistema voçoroca (como canais e dígitos). Na classificação hierárquica, o procedimento é realizado em escalas diferentes, permitindo o uso da lógica fuzzy para descrever diferentes graus de pertinência a cada classe, o que torna o método bastante atraente para casos como o deste estudo, onde há mistura de classes. Assim, a classificação obtida com o método semiautomático, de classificação hierárquica, mostrou-se mais fidedigna à realidade de campo, por permitir o uso de escalas diferentes, inserção de incerteza (pela lógica fuzzy) e inserção de conhecimento (pela base de regras estabelecida), quando comparada à classificação automática por árvore de decisão. Palavras-chave: voçoroca, análise orientada a objeto, segmentação multirresolução, classificação hierárquica, árvores de decisão.Abstract: The gullies represent the erosive processes responsible for major ambient, social and financial damages. The application of corrective and preventive measures needs to map gullies, as well as the monitoring of its evolution. Under remote sensing, the characteristics of the gullies can be mentioned: spectral heterogeneity (soil, vegetation, shade and water mix), spatial heterogeneity (existence of features as head, canals and digits with irregular forms and variable dimensions) and altimetry variation (with high declivity on the borders). Due to these specificities, this study proposed a methodology for delimitation of gullies on image classification procedures based on object-oriented image analysis. For such, there were used high spatial resolution image and orthophoto and ALS altimetry data. Two study areas were selected: one located in Uberlandia, Minas Gerais and another located in Queensland, Australia. The objects were generated by multiresolution segmentation (FNEA-Fractal Net Evolution Approach method). The most important attributes in the definition of gullies were selected using decision tree induction algorithms (CART - Classification and Regression Trees), being these attributes spectral, altimetry and texture. Classifications by decision trees and hierarchical were carried out. The use of decision tree allowed the selection of attributes and the establishment of preliminary decision rules as a basis for the delimitation of the gully. However, since this procedure does not use fuzzy logic, mixtures between classes cannot be evidenced in the rule base. Moreover, the classification is performed only by a factor of scale, allowing the identification of all the constituent features of the gully system (such as channels and digits). In hierarchical classification, the procedure is performed at different scales, allowing the use of fuzzy logic to describe different degrees of membership in each class, which makes it a very attractive method for cases such as this study, where there is mixing of classes. Thus, the classification obtained with the semi-automatic method of hierarchical classification, proved the field of reality more reliable, by allowing the use of different scales, uncertainty insert (by fuzzy logic) and integration of knowledge (the established rule base) compared to the automatic classification by decision tree. Keywords: gully erosion, object based image analysis, multirresolution segmentation, hierarchical classification, tree decision

Estimativa de profundidades utilizando imagens de alta resolução apoiadas por dados de levantamento batimétrico /

Orientadora: Cláudia Pereira KruegerOrientador: Jorge Antonio Silva CentenoDissertação (mestrado) - Universidade Federal do Paraná, Setor de Ciencias da Terra, Programa de Pós-Graduação em Ciencias Geodésicas. Defesa: Curitiba, 2003Inclui bibliografi

ESTIMATIVA DE PROFUNDIDADES UTILIZANDO IMAGENS DE ALTA RESOLUÇÃO APOIADAS POR DADOS DE LEVANTAMENTO BATIMÉTRICO

As imagens de satélite vêm sendo amplamente utilizadas para as mais diversas finalidades. São empregadas, por exemplo, em estudos geológicos, na cartografia, no planejamento e desenvolvimento urbanístico, nas definições de projetos de engenharia, na agricultura e em hidrologia. Quanto às aplicações em hidrologia, pode-se citar o uso das imagens para mapeamento e delineamento de corpos d'água, verificação e controle da qualidade física da água, avaliação da quantidade de sedimentos em suspensão e verificação de turbidez. Além disso, estudos já foram realizados com imagens Landsat e SPOT com o intuito de extrair profundidades a partir das mesmas, com base nos valores de reflectância. Para países como o Brasil, com extenso litoral e grande quantidade de rios navegáveis, que utilizam estes tanto para o transporte de pessoas e cargas quanto para o lazer e turismo, cartas de navegação confiáveis e constantemente atualizadas são requeridas. No entanto os sistemas hídricos são muito dinâmicos, sofrendo processos de erosão e deposição que provocam variações no relevo submarino, tornando as cartas náuticas desatualizadas rapidamente. Em função disso, este trabalho propõe um método alternativo para estimativa de profundidades e, conseqüentemente, para atualização e complementação de mapas batimétricos, através da integração de dados espectrais provenientes de imagens IKONOS e dados batimétricos. Experimentos foram realizados para a região do canal localizado entre as ilhas Sepultura e do Capinzal, na Baía de Guaratuba, litoral paranaense. Dados de profundidade foram coletados em junho de 2002, através de levantamento batimétrico utilizando-se ecobatímetro de feixe único e posicionamento horizontal através do DGPS. Com base nestes dados, analisou-se o comportamento dos valores digitais na imagem em função da profundidade e elaborou-se um modelo matemático para estimativa de profundidades em função de valores digitais. O modelo foi então aplicado à imagem e avaliações da precisão alcançada foram realizadas, mostrando a validade do modelo e viabilidade do método proposto. Extracting Depths from Images Upon of High Resolution Based on Reflectance Values Abstract The satellite images have been used with many purposes, for example in geological studies, cartography, urban planning and development, engineering projects definitions, agriculture and hydrology. In hydrology, satellite images can be used in body water mapping and delineation, water physical quality verification and control, suspended sediment quantity evaluation and turbidity verification. Besides, investigations were performed with Landsat TM and SPOT images to extract depths from images based on reflectance values. For countries like Brazil that has an extensive coast and a lot of navigable rivers, which are used to transport cargo and people, for business, leisure and tourism, reliable and updated nautical charts are required. However, the aquatic systems are very dynamic, suffering erosion and deposition processes that cause variations on submarine relief, turning nautical charts quickly out of date. This essay proposes an alternative method to estimate sub aquatic depths and consequently complementation and updating nautical charts, through IKONOS image and bathymetric data integration. Experiments were performed in the stream located between Sepultura and Capinzal islands, Guaratuba Bay, Paraná coast. Depth data were collected in June 2002, through bathymetric survey using single beam echo sounder and horizontal positioning by DGPS. With these data the digital numbers of the image were analysed in function of depth and a mathematic model were elaborated to estimate depth through digital numbers. The model was so applied to image and precision evaluations were accomplished, showing the model validity and proposed method viability

Wearable inertial sensors as a tool for quantitative assessment of progress during rehabilitation

Biomechanics analysis is frequently used in both clinical and sporting practice in order to assess human motion and performance of defined tasks. Whilst camera-based motion systems have long been regarded as the ‘Goldstandard’ for quantitative movement-based analysis, their application is not without limitations as regards potential sources of variability in measurements, high costs, and practicality of use for larger patient/subject groups. Another more practical approach, which presents itself as a viable solution to biomechanical motion capture and monitoring in sporting and patient groups, is through the use of small-size low-cost wearable Micro-ElectroMechanical Systems (MEMs)- based inertial sensors. The clinical aim of the present work is to evaluate gait during rehabilitation following knee injuries and to identify gait abnormalities through a wireless inertial sensing system. This system was developed at the Tyndall National Institute to meet clinician-defined needs, and is able to provide a complete biomechanics assessment without the constraints of a motion capture laboratory. The derived motion parameter outcomes can be analyzed by clinicians and sport scientists to study the overall patients’ condition and provide accurate medical feedback as to their rehabilitative progress. Detection of atypical movement characteristics is possible by comparing the performance and variability in motion characteristics in the patient’s affected and unaffected lower-limbs. The work is ongoing, and to date the system has been tested on only one impaired subject, additional clinical trials are currently being planned with an enhanced number of injured subjects. This will provide a more robust statistical analysis of the data in the study. The present feasibility study proved that inertial sensors can be used for a quantitative assessment of knee joint mobility, and gait mechanics during the rehabilitation program of injured subjects and can provide valuable information to clinical experts as regards patient rehabilitation

Water use and water saving in Italian hospitals. A preliminary investigation

Aim. The aim of this work is to investigate about water use, wastage, saving and reuse in hospitals. Methods. An anonymous ad hoc questionnaire was tested in a sample of 36 public hospitals of Lombardy Region (21% of total public hospitals). Daily water consumption reported is on average equal to 481 m3, ranging from 30 to 2280 m3. There is a strong correlation between water consumption and number of hospital beds (p < 0.005). In 33 hospitals (92%) water consumption is measured and, among them, in about 48% more than one flow meter is installed; 86% consider “important” the reduction of water consumption and about 55% recognize that wastewater could be minimized within the structures. Discussion. There is consensus about the need to train health personnel and to implement technical measures to improve the water resources management, but initiatives to raise knowledge and awareness of health personnel have been promoted only in 10% of hospitals. Results. Results show not only a lack of awareness regarding water use and saving among the personnel in general, but also among heads of the hospitas’ technical office and energy managers as well. For this reason, it will be of interest to carry out this investigation at national level and also to develop recommendations to support and promote a safe reuse of water in all the hospitals

Inertial sensors-based lower-limb rehabilitation assessment: A comprehensive evaluation of gait, kinematic and statistical metrics

Analysis of biomechanics is frequently used in both clinical and sporting practice in order to assess human motion and their performance of defined tasks. Whilst camera-based motion capture systems have long been regarded as the ‘Gold-standard’ for quantitative movement-based analysis, their application is not without limitations as regards potential sources of variability in measurements, high cost, and practicality of use for larger patient/subject groups. Another more practical approach, which presents itself as a viable solution to biomechanical motion capture and monitoring in sporting and patient groups, is through the use of small-size low-cost wearable Micro-ElectroMechanical Systems (MEMs)-based inertial sensors. The clinical aim of the present work is to evaluate rehabilitation progress following knee injuries, identifying a number of metrics measured via a wireless inertial sensing system. Several metrics in the time-domain have been considered to be reliable for measuring and quantifying patient progress across multiple exercises in different activities. This system was developed at the Tyndall National Institute and is able to provide a complete and accurate biomechanics assessment without the constraints of a motion capture laboratory. The results show that inertial sensors can be used for a quantitative assessment of knee joint mobility, providing valuable information to clinical experts as regards the trend of patient progress over the course of rehabilitation