107 resultados para VIRAL LOAD
Resumo:
Cardiac failure occurs when the heart fails to adapt to chronic stresses. Reactive oxygen species (ROS)-dependent signaling is implicated in cardiac stress responses but the role of different ROS sources remains unclear. Here, we report that NADPH oxidase-4 (Nox4) facilitates cardiac adaptation to chronic stress. Unlike other Nox proteins, Nox4 activity is regulated mainly by its expression level which increased in cardiomyocytes during stresses such as pressure overload or hypoxia. To investigate the functional role of Nox4 during the cardiac response to stress, we generated mice with a genetic deletion of Nox4 or a cardiomyocyte-targeted overexpression of Nox4. Basal cardiac function was normal in both models but Nox4-null animals developed exaggerated contractile dysfunction, hypertrophy and cardiac dilatation during exposure to chronic overload whereas Nox4-transgenic mice were protected. Investigation of mechanisms underlying this protective effect revealed a significant Nox4-dependent preservation of myocardial capillary density after pressure overload. Nox4 enhanced stress-induced activation of cardiomyocyte Hif1 and the release of VEGF, resulting in an increased paracrine angiogenic activity. These data indicate that cardiomyocyte Nox4 is a novel inducible regulator of myocardial angiogenesis, a key determinant of cardiac adaptation to overload stress. Our results also have wider relevance to the use of non-specific antioxidant approaches in cardiac disease and may provide an explanation for the failure of such strategies in many settings.
Resumo:
Artificial neural networks (ANNs) can be easily applied to short-term load forecasting (STLF) models for electric power distribution applications. However, they are not typically used in medium and long term load forecasting (MLTLF) electric power models because of the difficulties associated with collecting and processing the necessary data. Virtual instrument (VI) techniques can be applied to electric power load forecasting but this is rarely reported in the literature. In this paper, we investigate the modelling and design of a VI for short, medium and long term load forecasting using ANNs. Three ANN models were built for STLF of electric power. These networks were trained using historical load data and also considering weather data which is known to have a significant affect of the use of electric power (such as wind speed, precipitation, atmospheric pressure, temperature and humidity). In order to do this a V-shape temperature processing model is proposed. With regards MLTLF, a model was developed using radial basis function neural networks (RBFNN). Results indicate that the forecasting model based on the RBFNN has a high accuracy and stability. Finally, a virtual load forecaster which integrates the VI and the RBFNN is presented.
Resumo:
Aim: The aim of this study was to determine if asthmatic children have viruses more commonly detected in lower airways during asymptomatic periods than normal children. Methods: Fifty-five asymptomatic children attending elective surgical procedures (14 with stable asthma, 41 normal controls) underwent non-bronchoscopic bronchoalveolar lavage. Differential cell count and PCR for 13 common viruses were performed. Results: Nineteen (35%) children were positive for at least one virus, with adenovirus being most common. No differences in the proportion of viruses detected were seen between asthmatic and normal ‘control’ children. Viruses other than adenovirus were associated with higher neutrophil counts, suggesting that they caused an inflammatory response in both asthmatics and controls (median BAL neutrophil count, 6.9% for virus detected vs. 1.5% for virus not detected, p = 0.03). Conclusions: Over one-third of asymptomatic children have a detectable virus (most commonly adenovirus) in the lower airway; however, this was not more common in asthmatics. Viruses other than adenovirus were associated with elevated neutrophils suggesting that viral infection can be present during relatively asymptomatic periods in asthmatic children.