480 resultados para Ultradian rhythms


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The suprachiasmatic nucleus, an essential diencephalic component of the circadian timing system, plays a role in the generation and modulation of behavioral and neuroendocrine rhythms in mammals. Its cytoarchitecture, neurochemical and hodological characteristics have been investigated in various mammalian species, particularly in rodents. In most species, two subdivisions, based on these aspects and considered to reflect functional specialization within the nucleus, can be recognized. Many studies reveal a typical dense innervation by serotonergic fibers in this nucleus, mainly in the ventromedial area, overlapping the retinal afferents. However, a different pattern occurs in certain animals, which lead us to investigate the distribution of serotonergic afferents in the suprachiasmatic nucleus of the Capuchin monkey, Cebus apella, compared to the marmoset, Callithrix jacchus, and two Rattus norvegicus lines (Long Evans and Wistar), and to reported findings for other mammalian species. Our morphometric data show the volume and length of the suprachiasmatic nucleus along the rostrocaudal axis to be greatest in C. apella > C. jacchus > Long Evans ≥ Wistar rats, in agreement with their body sizes. In C. apella, however, the serotonergic terminals occupy only some 10% of the nucleus' area, less than the 25% seen in the marmoset and rats. The distribution of the serotonergic fibers in C. apella does not follow the characteristic ventral organization pattern seen in the rodents. These findings raise questions concerning the intrinsic organization of the nucleus, as well as regarding the functional relationship between serotonergic input and retinal afferents in this diurnal species. © 2007 Elsevier B.V. All rights reserved.

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Background and Purpose: The circadian rhythm of melatonin in saliva or plasma, or of the melatonin metabolite 6-sulfatoxymelatonin (a6MTs) in urine, is a defining feature of suprachiasmatic nucleus (SCN) function, the body's endogenous oscillatory pacemaker. The primary objective of this review is to ascertain the clinical benefits and limitations of current methodologies employed for detection and quantification of melatonin in biological fluids and tissues. Data Identification: A search of the English-language literature (Medline) and a systematic review of published articles were carried out. Study Selection: Articles that specified both the methodology for quantifying melatonin and indicated the clinical purpose were chosen for inclusion in the review. Data Extraction: The authors critically evaluated the methodological issues associated with various tools and techniques (e.g. standards, protocols, and procedures). Results of Data Synthesis: Melatonin measurements are useful for evaluating problems related to the onset or offset of sleep and for assessing phase delays or advances of rhythms in entrained individuals. They have also become an important tool for psychiatric diagnosis, their use being recommended for phase typing in patients suffering from sleep and mood disorders. Additionally, there has been a continuous interest in the use of melatonin as a marker for neoplasms of the pineal region. Melatonin decreases such as found with aging are or post pinealectomy can cause alterations in the sleep/wake cycle. The development of sensitive and selective methods for the precise detection of melatonin in tissues and fluids has increasingly been shown to have direct relevance for clinical decision making. Conclusions: Due to melatonin's low concentration, as well as the coexistence of numerous other compounds in the blood, the routine determination of melatonin has been an analytical challenge. The available evidence indicates however that these challenges can be overcome and consequently that evaluation of melatonin's presence and activity can be an accessible and useful tool for clinical diagnosis. © Springer-Verlag 2010.

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An important tool for the heart disease diagnosis is the analysis of electrocardiogram (ECG) signals, since the non-invasive nature and simplicity of the ECG exam. According to the application, ECG data analysis consists of steps such as preprocessing, segmentation, feature extraction and classification aiming to detect cardiac arrhythmias (i.e.; cardiac rhythm abnormalities). Aiming to made a fast and accurate cardiac arrhythmia signal classification process, we apply and analyze a recent and robust supervised graph-based pattern recognition technique, the optimum-path forest (OPF) classifier. To the best of our knowledge, it is the first time that OPF classifier is used to the ECG heartbeat signal classification task. We then compare the performance (in terms of training and testing time, accuracy, specificity, and sensitivity) of the OPF classifier to the ones of other three well-known expert system classifiers, i.e.; support vector machine (SVM), Bayesian and multilayer artificial neural network (MLP), using features extracted from six main approaches considered in literature for ECG arrhythmia analysis. In our experiments, we use the MIT-BIH Arrhythmia Database and the evaluation protocol recommended by The Association for the Advancement of Medical Instrumentation. A discussion on the obtained results shows that OPF classifier presents a robust performance, i.e.; there is no need for parameter setup, as well as a high accuracy at an extremely low computational cost. Moreover, in average, the OPF classifier yielded greater performance than the MLP and SVM classifiers in terms of classification time and accuracy, and to produce quite similar performance to the Bayesian classifier, showing to be a promising technique for ECG signal analysis. © 2012 Elsevier Ltd. All rights reserved.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Ciências Sociais - FFC

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Pós-graduação em Geografia - FCT

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Pós-graduação em Geografia - FCT

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)