21 research outputs found

    Oxidant-NO dependent gene regulation in dogs with type I diabetes: impact on cardiac function and metabolism

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    <p>Abstract</p> <p>Background</p> <p>The mechanisms responsible for the cardiovascular mortality in type I diabetes (DM) have not been defined completely. We have shown in conscious dogs with DM that: <it>1</it>) baseline coronary blood flow (CBF) was significantly decreased, <it>2</it>) endothelium-dependent (ACh) coronary vasodilation was impaired, and <it>3</it>) reflex cholinergic NO-dependent coronary vasodilation was selectively depressed. The most likely mechanism responsible for the depressed reflex cholinergic NO-dependent coronary vasodilation was the decreased bioactivity of NO from the vascular endothelium. The goal of this study was to investigate changes in cardiac gene expression in a canine model of alloxan-induced type 1 diabetes.</p> <p>Methods</p> <p>Mongrel dogs were chronically instrumented and the dogs were divided into two groups: one normal and the other diabetic. In the diabetic group, the dogs were injected with alloxan monohydrate (40-60 mg/kg iv) over 1 min. The global changes in cardiac gene expression in dogs with alloxan-induced diabetes were studied using Affymetrix Canine Array. Cardiac RNA was extracted from the control and DM (n = 4).</p> <p>Results</p> <p>The array data revealed that 797 genes were differentially expressed (P < 0.01; fold change of at least ±2). 150 genes were expressed at significantly greater levels in diabetic dogs and 647 were significantly reduced. There was no change in eNOS mRNA. There was up regulation of some components of the NADPH oxidase subunits (gp91 by 2.2 fold, P < 0.03), and down-regulation of SOD1 (3 fold, P < 0.001) and decrease (4 - 40 fold) in a large number of genes encoding mitochondrial enzymes. In addition, there was down-regulation of Ca<sup>2+ </sup>cycling genes (ryanodine receptor; SERCA2 Calcium ATPase), structural proteins (actin alpha). Of particular interests are genes involved in glutathione metabolism (glutathione peroxidase 1, glutathione reductase and glutathione S-transferase), which were markedly down regulated.</p> <p>Conclusion</p> <p>our findings suggest that type I diabetes might have a direct effect on the heart by impairing NO bioavailability through oxidative stress and perhaps lipid peroxidases.</p

    Entropy and Complexity Analyses in Alzheimer’s Disease: An MEG Study

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    Alzheimer’s disease (AD) is one of the most frequent disorders among elderly population and it is considered the main cause of dementia in western countries. This irreversible brain disorder is characterized by neural loss and the appearance of neurofibrillary tangles and senile plaques. The aim of the present study was the analysis of the magnetoencephalogram (MEG) background activity from AD patients and elderly control subjects. MEG recordings from 36 AD patients and 26 controls were analyzed by means of six entropy and complexity measures: Shannon spectral entropy (SSE), approximate entropy (ApEn), sample entropy (SampEn), Higuchi’s fractal dimension (HFD), Maragos and Sun’s fractal dimension (MSFD), and Lempel-Ziv complexity (LZC). SSE is an irregularity estimator in terms of the flatness of the spectrum, whereas ApEn and SampEn are embbeding entropies that quantify the signal regularity. The complexity measures HFD and MSFD were applied to MEG signals to estimate their fractal dimension. Finally, LZC measures the number of different substrings and the rate of their recurrence along the original time series. Our results show that MEG recordings are less complex and more regular in AD patients than in control subjects. Significant differences between both groups were found in several brain regions using all these methods, with the exception of MSFD (p-value < 0.05, Welch’s t-test with Bonferroni’s correction). Using receiver operating characteristic curves with a leave-one-out cross-validation procedure, the highest accuracy was achieved with SSE: 77.42%. We conclude that entropy and complexity analyses from MEG background activity could be useful to help in AD diagnosis
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