897 resultados para Stochastic Resonance


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The relevance of the relationship between cardiac disease and depressive symptoms is well established. White matter hyperintensity, a bright signal area in the brain on T2-weighted magnetic resonance imaging scans, has been separately associated with cardiovascular risk factors, cardiac disease and late-life depression. However, no study has directly investigated the association between heart failure, major depressive symptoms and the presence of hyperintensities. Using a visual assessment scale, we have investigated the frequency and severity of white matter hyperintensities identified by magnetic resonance imaging in eight patients with late-life depression and heart failure, ten patients with heart failure without depression, and fourteen healthy elderly volunteers. Since the frontal lobe has been the proposed site for the preferential location of white matter hyperintensities in patients with late-life depression, we focused our investigation specifically on this brain region. Although there were no significant group differences in white matter hyperintensities in the frontal region, a significant direct correlation emerged between the severity of frontal periventricular white matter hyperintensity and scores on the Hamilton scale for depression in the group with heart failure and depression (P = 0.016, controlled for the confounding influence of age). There were no significant findings in any other areas of the brain. This pattern of results adds support to a relationship between cardiovascular risk factors and depressive symptoms, and provides preliminary evidence that the presence of white matter hyperintensities specifically in frontal regions may contribute to the severity of depressive symptoms in cardiac disease.

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The aim of the present study was to evaluate the role of magnetic resonance imaging (MRI) for the non-invasive detection of coronary abnormalities and specifically the remodeling process in patients with coronary artery disease (CAD). MRI was performed in 10 control healthy subjects and 26 patients with angiographically proven CAD of the right coronary (RCA) or left anterior descending (LAD) artery; 23 patients were within two months of acute coronary syndromes, and 3 had stable angina with a positive test for ischemia. Wall thickness (WT), vessel wall area (VWA), total vessel area (TVA), and luminal area (LA) were measured. There were significant increases in WT (mean ± SEM, RCA: 2.62 ± 0.75 vs 0.53 ± 0.15 mm; LAD: 2.21 ± 0.69 vs 0.62 ± 0.24 mm) and in VWA (RCA: 30.96 ± 17.57 vs 2.1 ± 1.2 mm²; LAD: 19.53 ± 7.25 vs 3.6 ± 2.0 mm²) patients compared to controls (P < 0.001 for each variable). TVA values were also greater in patients compared to controls (RCA: 44.56 ± 21.87 vs 12.3 ± 4.2 mm²; LAD: 31.89 ± 11.31 vs 17.0 ± 6.2 mm²; P < 0.001). In contrast, the LA did not differ between patients and controls for RCA or LAD. When the LA was adjusted for vessel size using the LA/TVA ratio, a significant difference was found: 0.33 ± 0.16 in patients vs 0.82 ± 0.09 in controls (RCA) and 0.38 ± 0.13 vs 0.78 ± 0.06 (LAD) (P < 0.001). As opposed to normal controls, positive remodeling was present in all patients with CAD, as indicated by larger VWA. We conclude that MRI detected vessel wall abnormalities and was an effective tool for the noninvasive evaluation of the atherosclerotic process and coronary vessel wall modifications, including positive remodeling that frequently occurs in patients with acute coronary syndromes.

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COSY proton nuclear magnetic resonance was used to measure the exchange rates of amide protons of hen egg white lysozyme (HEWL) in the pressure-assisted cold-denatured state and in the heat-denatured state. After dissolving lysozyme in deuterium oxide buffer, labile protons exchange for deuterons in such a way that exposed protons are substituted rapidly, whereas "protected" protons within structured parts of the protein are substituted slowly. The exchange rates k obs were determined for HEWL under heat treatment (80ºC) and under high pressure conditions at low temperature (3.75 kbar, -13ºC). Moreover, the influence of co-solvents (sorbitol, urea) on the exchange rate was examined under pressure-assisted cold denaturation conditions, and the corresponding protection factors, P, were determined. The exchange kinetics upon heat treatment was found to be a two-step process with initial slow exchange followed by a fast one, showing residual protection in the slow-exchange state and P-factors in the random-coil-like range for the final temperature-denatured state. Addition of sorbitol (500 mM) led to an increase of P-factors for the pressure-assisted cold denatured state, but not for the heat-denatured state. The presence of 2 M urea resulted in a drastic decrease of the P-factors of the pressure-assisted cold denatured state. For both types of co-solvents, the effect they exert appears to be cooperative, i.e., no particular regions within the protein can be identified with significantly diverse changes of P-factors.

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The aim of the present study was to determine whether specific subgroups of schizophrenic patients, grouped according to electrodermal characteristics, show differences in the N-acetylaspartate/creatine plus choline (NAA / (Cr + Cho)) ratios in the frontal, cingulate and perirolandic cortices. Skin conductance levels (SCL) and skin conductance responses to auditory stimulation were measured in 38 patients with schizophrenia and in the same number of matched healthy volunteers (control). All subjects were submitted to multivoxel proton magnetic resonance spectroscopic imaging. When compared to the control group, patients presented significantly lower NAA / (Cr + Cho) ratios in the right dorsolateral prefrontal cortex (schizophrenia = 0.95 ± 0.03; control = 1.12 ± 0.04) and in the right (schizophrenia = 0.88 ± 0.02; control = 0.94 ± 0.03) and left (schizophrenia = 0.84 ± 0.03; control = 0.94 ± 0.03) cingulates. These ratios did not differ between electrodermally responsive and non-responsive patients. When patients were divided into two groups: lower SCL (less than the mean SCL of the control group minus two standard deviations) and normal SCL (similar to the control group), the subgroup with a lower level of SCL showed a lower NAA / (Cr + Cho) ratio in the left cingulate (0.78 ± 0.05) than the controls (0.95 ± 0.02, P < 0.05) and the subgroup with normal SCL (0.88 ± 0.03, P < 0.05). There was a negative correlation between the NAA / (Cr + Cho) ratio in the left cingulate of patients with schizophrenia and the duration of the disease and years under medication. These data suggest the existence of a schizophrenic subgroup characterized by low SCL that could be a consequence of the lower neuronal viability observed in the left cingulate of these patients.

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The loss of brain volume has been used as a marker of tissue destruction and can be used as an index of the progression of neurodegenerative diseases, such as multiple sclerosis. In the present study, we tested a new method for tissue segmentation based on pixel intensity threshold using generalized Tsallis entropy to determine a statistical segmentation parameter for each single class of brain tissue. We compared the performance of this method using a range of different q parameters and found a different optimal q parameter for white matter, gray matter, and cerebrospinal fluid. Our results support the conclusion that the differences in structural correlations and scale invariant similarities present in each tissue class can be accessed by generalized Tsallis entropy, obtaining the intensity limits for these tissue class separations. In order to test this method, we used it for analysis of brain magnetic resonance images of 43 patients and 10 healthy controls matched for gender and age. The values found for the entropic q index were 0.2 for cerebrospinal fluid, 0.1 for white matter and 1.5 for gray matter. With this algorithm, we could detect an annual loss of 0.98% for the patients, in agreement with literature data. Thus, we can conclude that the entropy of Tsallis adds advantages to the process of automatic target segmentation of tissue classes, which had not been demonstrated previously.

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Electron paramagnetic resonance (EPR) spectroscopy of spin labels was used to monitor membrane dynamic changes in erythrocytes subjected to oxidative stress with hydrogen peroxide (H2O2). The lipid spin label, 5-doxyl stearic acid, responded to dramatic reductions in membrane fluidity, which was correlated with increases in the protein content of the membrane. Membrane rigidity, associated with the binding of hemoglobin (Hb) to the erythrocyte membrane, was also indicated by a spin-labeled maleimide, 5-MSL, covalently bound to the sulfhydryl groups of membrane proteins. At 2% hematocrit, these alterations in membrane occurred at very low concentrations of H2O2 (50 µM) after only 5 min of incubation at 37°C in azide phosphate buffer, pH 7.4. Lipid peroxidation, suggested by oxidative hemolysis and malondialdehyde formation, started at 300 µM H2O2 (for incubation of 3 h), which is a concentration about six times higher than those detected with the probes. Ascorbic acid and α-tocopherol protected the membrane against lipoperoxidation, but did not prevent the binding of proteins to the erythrocyte membrane. Moreover, the antioxidant (+)-catechin, which also failed to prevent the cross-linking of cytoskeletal proteins with Hb, was very effective in protecting erythrocyte ghosts from lipid peroxidation induced by the Fenton reaction. This study also showed that EPR spectroscopy can be useful to assess the molecular dynamics of red blood cell membranes in both the lipid and protein domains and examine oxidation processes in a system that is so vulnerable to oxidation.

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Huntington's disease (HD) is a neurologic disorder that is not completely understood; its fundamental physiological mechanisms and chemical effects remain somewhat unclear. Among these uncertainties, we can highlight information about the concentrations of brain metabolites, which have been widely discussed. Concentration differences in affected, compared to healthy, individuals could lead to the development of useful tools for evaluating the progression of disease, or to the advance of investigations of different/alternative treatments. The aim of this study was to compare the thalamic concentration of metabolites in HD patients and healthy individuals using magnetic resonance spectroscopy. We used a 2.0-Tesla magnetic field, repetition time of 1500 ms, and echo time of 135 ms. Spectra from 40 adult HD patients and 26 control subjects were compared. Quantitative analysis was performed using the LCModel method. There were statistically significant differences between HD patients and controls in the concentrations ofN-acetylaspartate+N-acetylaspartylglutamate (NAA+NAAG; t-test, P<0.001), and glycerophosphocholine+phosphocholine (GPC+PCh;t-test, P=0.001) relative to creatine+phosphocreatine (Cr+PCr). The NAA+NAAG/Cr+PCr ratio was decreased by 9% and GPC+PCh/Cr+PCr increased by 17% in patients compared with controls. There were no correlations between the concentration ratios and clinical features. Although these results could be caused by T1 and T2 changes, rather than variations in metabolite concentrations given the short repetition time and long echo time values used, our findings point to thalamic dysfunction, corroborating prior evidence.

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Maintenance of thermal homeostasis in rats fed a high-fat diet (HFD) is associated with changes in their thermal balance. The thermodynamic relationship between heat dissipation and energy storage is altered by the ingestion of high-energy diet content. Observation of thermal registers of core temperature behavior, in humans and rodents, permits identification of some characteristics of time series, such as autoreference and stationarity that fit adequately to a stochastic analysis. To identify this change, we used, for the first time, a stochastic autoregressive model, the concepts of which match those associated with physiological systems involved and applied in male HFD rats compared with their appropriate standard food intake age-matched male controls (n=7 per group). By analyzing a recorded temperature time series, we were able to identify when thermal homeostasis would be affected by a new diet. The autoregressive time series model (AR model) was used to predict the occurrence of thermal homeostasis, and this model proved to be very effective in distinguishing such a physiological disorder. Thus, we infer from the results of our study that maximum entropy distribution as a means for stochastic characterization of temperature time series registers may be established as an important and early tool to aid in the diagnosis and prevention of metabolic diseases due to their ability to detect small variations in thermal profile.

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Radiotherapy is one of the main approaches to cure prostate cancer, and its success depends on the accuracy of dose planning. A complicating factor is the presence of a metallic prosthesis in the femur and pelvis, which is becoming more common in elderly populations. The goal of this work was to perform dose measurements to check the accuracy of radiotherapy treatment planning under these complicated conditions. To accomplish this, a scale phantom of an adult pelvic region was used with alanine dosimeters inserted in the prostate region. This phantom was irradiated according to the planned treatment under the following three conditions: with two metallic prostheses in the region of the femur head, with only one prosthesis, and without any prostheses. The combined relative standard uncertainty of dose measurement by electron spin resonance (ESR)/alanine was 5.05%, whereas the combined relative standard uncertainty of the applied dose was 3.35%, resulting in a combined relative standard uncertainty of the whole process of 6.06%. The ESR dosimetry indicated that there was no difference (P>0.05, ANOVA) in dosage between the planned dose and treatments. The results are in the range of the planned dose, within the combined relative uncertainty, demonstrating that the treatment-planning system compensates for the effects caused by the presence of femur and hip metal prostheses.

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Different axioms underlie efficient market theory and Keynes's liquidity preference theory. Efficient market theory assumes the ergodic axiom. Consequently, today's decision makers can calculate with actuarial precision the future value of all possible outcomes resulting from today's decisions. Since in an efficient market world decision makers "know" their intertemporal budget constraints, decision makers never default on a loan, i.e., systemic defaults, insolvencies, and bankruptcies are impossible. Keynes liquidity preference theory rejects the ergodic axiom. The future is ontologically uncertain. Accordingly systemic defaults and insolvencies can occur but can never be predicted in advance.

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Since its discovery, chaos has been a very interesting and challenging topic of research. Many great minds spent their entire lives trying to give some rules to it. Nowadays, thanks to the research of last century and the advent of computers, it is possible to predict chaotic phenomena of nature for a certain limited amount of time. The aim of this study is to present a recently discovered method for the parameter estimation of the chaotic dynamical system models via the correlation integral likelihood, and give some hints for a more optimized use of it, together with a possible application to the industry. The main part of our study concerned two chaotic attractors whose general behaviour is diff erent, in order to capture eventual di fferences in the results. In the various simulations that we performed, the initial conditions have been changed in a quite exhaustive way. The results obtained show that, under certain conditions, this method works very well in all the case. In particular, it came out that the most important aspect is to be very careful while creating the training set and the empirical likelihood, since a lack of information in this part of the procedure leads to low quality results.

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The aim of this study is to propose a stochastic model for commodity markets linked with the Burgers equation from fluid dynamics. We construct a stochastic particles method for commodity markets, in which particles represent market participants. A discontinuity in the model is included through an interacting kernel equal to the Heaviside function and its link with the Burgers equation is given. The Burgers equation and the connection of this model with stochastic differential equations are also studied. Further, based on the law of large numbers, we prove the convergence, for large N, of a system of stochastic differential equations describing the evolution of the prices of N traders to a deterministic partial differential equation of Burgers type. Numerical experiments highlight the success of the new proposal in modeling some commodity markets, and this is confirmed by the ability of the model to reproduce price spikes when their effects occur in a sufficiently long period of time.