1000 resultados para Brain oscillations
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AIMS: The plasma levels of either brain natriuretic peptide (BNP) or the N-terminal fragment of the prohormone (NT-proBNP) have recently gained extreme importance as markers of myocardial dysfunction. Patients with type 2 diabetes are at high risk of developing cardiovascular complications. This study was aimed to assess whether plasma NT-proBNP levels are at similar levels in type 2 diabetics with or without overt cardiovascular diseases. METHODS: We assayed plasma NT-proBNP in 54 type 2 diabetics, 27 of whom had no overt macro- and/or microvascular complications, while the remaining ones had either or both. The same assay was carried out in 38 healthy control subjects age and sex matched as a group with the diabetics. RESULTS: Plasma NT-proBNP was higher in diabetics (median 121 pg/ml, interquartile range 50-240 pg/ml, ) than in those without complications (37 pg/ml, 21-54 pg/ml, P<0.01). Compared with the controls (55 pg/ml, 40-79 pg/ml), only diabetics with vascular complications had significantly increased plasma NT-proBNP levels (P<0.001). In the diabetics, coronary heart disease and nephropathy (defined according to urinary excretion of albumin) were each independently associated with elevated values of plasma NT-proBNP. CONCLUSIONS: In type 2 diabetes mellitus, patients with macro- and/or micro-vascular complications exhibit an elevation of plasma NT-proBNP levels compared to corresponding patients with no evidence of vascular disease. The excessive secretion of this peptide is independently associated with coronary artery disease and overt nephropathy. The measurement of circulating NT-proBNP concentration may therefore be useful to screen for the presence of macro- and/or microvascular disease.
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Background: Maturation of amplitude-integrated electroencephalogram (aEEG) activity is influenced by both gestational age (GA) and postmenstrual age. It is not fully known how this process is influenced by cerebral lesions. Objective: To compare early aEEG developmental changes between preterm newborns with different degrees of cerebral lesions on cranial ultrasound (cUS). Methods: Prospective cohort study on preterm newborns with GA <32.0 weeks, undergoing continuous aEEG recording during the first 84 h after birth. aEEG characteristics were qualitatively and quantitatively evaluated using pre-established criteria. Based on cUS findings three groups were formed: normal (n = 78), mild (n = 20), and severe cerebral lesions (n = 6). Linear mixed models for repeated measures were used to analyze aEEG maturational trajectories. Results: 104 newborns with a mean GA (range) 29.5 (24.4-31.7) weeks, and birth weight 1,220 (580-2,020) g were recruited. Newborns with severe brain lesions started with similar aEEG scores and tendentially lower aEEG amplitudes than newborns without brain lesions, and showed a slower development of the cyclic activity (p < 0.001), but a more rapid increase of the maximum and minimum aEEG amplitudes (p = 0.002 and p = 0.04). Conclusions: Preterm infants with severe cerebral lesions manifest a maturational delay in the aEEG cyclic activity already early after birth, but show a catch-up of aEEG amplitudes to that of newborns without cerebral lesions. Changes in the maturational aEEG pattern may be a marker of severe neurological lesions in the preterm infant.
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In vivo 13C NMR spectroscopy has the unique capability to measure metabolic fluxes noninvasively in the brain. Quantitative measurements of metabolic fluxes require analysis of the 13C labeling time courses obtained experimentally with a metabolic model. The present work reviews the ingredients necessary for a dynamic metabolic modeling study, with particular emphasis on practical issues.
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PURPOSE OF REVIEW: Energy metabolism is increasingly recognized as a key factor in the pathogenesis of acute brain injury (ABI). We review the role of cerebral lactate metabolism and summarize evidence showing that lactate may act as supplemental fuel after ABI. RECENT FINDINGS: The role of cerebral lactate has shifted from a waste product to a potentially preferential fuel and signaling molecule. According to the astrocyte-neuron lactate shuttle model, glycolytic lactate might act as glucose-sparing substrate. Lactate also is emerging as a key signal to regulate cerebral blood flow (CBF) and a neuroprotective agent after experimental ABI. Clinical investigation using cerebral microdialysis shows the existence of two main lactate patterns, ischemic - from anaerobic metabolism - and nonischemic, from activated glycolysis, whereby lactate can be used as supplemental energy fuel. Preliminary clinical data suggests hypertonic lactate solutions improve cerebral energy metabolism and are an effective treatment for elevated intracranial pressure (ICP) after ABI. SUMMARY: Lactate can be a supplemental fuel for the injured brain and is important to regulate glucose metabolism and CBF. Exogenous lactate supplementation may be neuroprotective after experimental ABI. Recent clinical data from ABI patients suggest hypertonic lactate solutions may be a valid therapeutic option for secondary energy dysfunction and elevated ICP.
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Brain spectrin, a membrane-related cytoskeletal protein, exists as two isoforms. Brain spectrin 240/235 is localized preferentially in the perikaryon and axon of neuronal cells and brain spectrin 240/235E is found essentially in the neuronal soma and dendrites and in glia (Riederer et al., 1986, J. Cell Biol., 102, 2088 - 2097). The sensory neurons in dorsal root ganglia, devoid of any dendrites, make a good tool to investigate such differential expression of spectrin isoforms. In this study expression and localization of both brain spectrin isoforms were analysed during early chicken dorsal root ganglia development in vivo and in culture. Both isoforms appeared at embryonic day 6. Brain spectrin 240/235 exhibited a transient increase during embryonic development and was first expressed in ventrolateral neurons. In ganglion cells in situ and in culture this spectrin type showed a somato - axonal distribution pattern. In contrast, brain spectrin 240/235E slightly increased between E6 and E15 and remained practically unchanged. It was localized mainly in smaller neurons of the mediodorsal area as punctate staining in the cytoplasm, was restricted exclusively to the ganglion cell perikarya and was absent from axons both in situ and in culture. This study suggests that brain spectrin 240/235 may contribute towards outgrowth, elongation and maintenance of axonal processes and that brain spectrin 240/235E seems to be exclusively involved in the stabilization of the cytoarchitecture of cell bodies in a selected population of ganglion cells.
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Subplate neurons are among the earliest born cells of the neocortex and play a fundamental role in cortical development, in particular in the formation of thalamocortical connections. Subplate abnormalities have been described in several neuropathological disorders including schizophrenia, autism and periventricular eukomalacia (Eastwood and Harrison, Schizophr Res, 79, 2005; McQuillen and Ferriero, Brain Pathol, 15, 2005). We have identified and confirmed a range of specific markers for murine subplate using a microarray based approach and found that different subplate subpopulations are characterized by distinct expression patterns of these genes (Hoerder-Suabedissen et al., Cereb Cortex, 19, 2009). In this current study, we are making use of these markers to investigate neuropathological changes of the subplate after cerebral hypoxia-ischemia (HI) in the neonatal rat. First, we characterized the expression of a number of murine subplate markers in the postnatal rat using immunohistochemistry and in situ hybridization. While several genes (Nurr1, Cplx3, Ctgf and Tmem163) presented very similar expression patterns as in the mouse, others (Ddc, MoxD1 and TRH) were completely absent in the rat cortex. This finding suggests important differences in the subplate populations of these two rodent species. In a neonatal rat model of HI, selective vulnerability of subplate has been suggested using BrdU birthdating methods (McQuillen et al., J Neurosci, 15, 2003). We hypothesized that certain subplate subpopulations could be more susceptible than others and analyzed the above subplate markers in a similar yet slightly milder HI model. Two-day old male rat pups underwent permanent occlusion of the right common carotid artery followed by a period of hypoxia (6% O2, 1.5h or 2h) and were analyzed six days later. Preliminary counts on three subplate subpopulations (Nurr1+, Cplx3+ and Ctgf+ cells, respectively) showed similar reductions in cell numbers for all three groups. In addition, we found that the majority of cases which show changes in the subplate also exhibit lesions in the deep cortical layers VI (identified by FoxP2 expression) and sometimes even layer V (revealed by Er81 immunoreactivity), which questions the selective susceptibility of subplate over other cortical layers under the conditions we used in our model. Supported by MRC, FMO holds a Berrow Scholarship, Lincoln College, Oxford.
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Background: Conventional magnetic resonance imaging (MRI) techniques are highly sensitive to detect multiple sclerosis (MS) plaques, enabling a quantitative assessment of inflammatory activity and lesion load. In quantitative analyses of focal lesions, manual or semi-automated segmentations have been widely used to compute the total number of lesions and the total lesion volume. These techniques, however, are both challenging and time-consuming, being also prone to intra-observer and inter-observer variability.Aim: To develop an automated approach to segment brain tissues and MS lesions from brain MRI images. The goal is to reduce the user interaction and to provide an objective tool that eliminates the inter- and intra-observer variability.Methods: Based on the recent methods developed by Souplet et al. and de Boer et al., we propose a novel pipeline which includes the following steps: bias correction, skull stripping, atlas registration, tissue classification, and lesion segmentation. After the initial pre-processing steps, a MRI scan is automatically segmented into 4 classes: white matter (WM), grey matter (GM), cerebrospinal fluid (CSF) and partial volume. An expectation maximisation method which fits a multivariate Gaussian mixture model to T1-w, T2-w and PD-w images is used for this purpose. Based on the obtained tissue masks and using the estimated GM mean and variance, we apply an intensity threshold to the FLAIR image, which provides the lesion segmentation. With the aim of improving this initial result, spatial information coming from the neighbouring tissue labels is used to refine the final lesion segmentation.Results:The experimental evaluation was performed using real data sets of 1.5T and the corresponding ground truth annotations provided by expert radiologists. The following values were obtained: 64% of true positive (TP) fraction, 80% of false positive (FP) fraction, and an average surface distance of 7.89 mm. The results of our approach were quantitatively compared to our implementations of the works of Souplet et al. and de Boer et al., obtaining higher TP and lower FP values.Conclusion: Promising MS lesion segmentation results have been obtained in terms of TP. However, the high number of FP which is still a well-known problem of all the automated MS lesion segmentation approaches has to be improved in order to use them for the standard clinical practice. Our future work will focus on tackling this issue.
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BACKGROUND: In 2005, findings of the first "cost of disorders of the brain in Europe" study of the European Brain Council (EBC) showed that these costs cause a substantial economic burden to the Swiss society. In 2010 an improved update with a broader range of disorders has been analysed. This report shows the new findings for Switzerland and discusses changes. METHODS: Data are derived from the EBC 2010 census study that estimates 12-month prevalence of 12 groups of disorders of the brain and calculates costs (direct health-care costs, direct non-medical costs and indirect costs) by combining top-down and bottom up cost approaches using existing data. RESULTS: The most frequent disorder was headache (2.3 million). Anxiety disorders were found in 1 million persons and sleep disorders in 700,000 persons. Annual costs for all assessed disorders total to 14.5 billion Euro corresponding to about 1,900 EUR per inhabitant per year. Mood, psychotic disorders and dementias (appr. 2 billion EUR each) were most costly. Costs per person were highest for neurological/neurosurgery-relevant disorders, e.g. neuromuscular disorders, brain tumour and multiple sclerosis (38,000 to 24,000 EUR). CONCLUSION: The estimates of the EBC 2010 study for Switzerland provide a basis for health care planning. Increase in size and costs compared to 2005 are mostly due to the inclusion of new disorders (e.g., sleep disorders), or the re-definition of others (e.g., headache) and to an increase in younger cohorts. We suggest coordinated research and preventive measures coordinated between governmental bodies, private health-care and pharmaceutical companies.
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G protein-coupled receptors (GPCRs) play critical roles in cellular processes and signaling and have been shown to form heteromers with diverge biochemical and/or pharmacological activities that are different from those of the corresponding monomers or homomers. However, despite extensive experimental results supporting the formation of GPCR heteromers in heterologous systems, the existence of such receptor heterocomplexes in the brain remains largely unknown, mostly because of the lack of appropriate methodology. Herein, we describe the in situ proximity ligation assay procedure underlining its high selectivity and sensitivity to image GPCR heteromers with confocal microscopy in brain sections. We describe here how the assay is performed and discuss advantages and disadvantages of this method compared with other available techniques.
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Extrasynaptic neurotransmission is an important short distance form of volume transmission (VT) and describes the extracellular diffusion of transmitters and modulators after synaptic spillover or extrasynaptic release in the local circuit regions binding to and activating mainly extrasynaptic neuronal and glial receptors in the neuroglial networks of the brain. Receptor-receptor interactions in G protein-coupled receptor (GPCR) heteromers play a major role, on dendritic spines and nerve terminals including glutamate synapses, in the integrative processes of the extrasynaptic signaling. Heteromeric complexes between GPCR and ion-channel receptors play a special role in the integration of the synaptic and extrasynaptic signals. Changes in extracellular concentrations of the classical synaptic neurotransmitters glutamate and GABA found with microdialysis is likely an expression of the activity of the neuron-astrocyte unit of the brain and can be used as an index of VT-mediated actions of these two neurotransmitters in the brain. Thus, the activity of neurons may be functionally linked to the activity of astrocytes, which may release glutamate and GABA to the extracellular space where extrasynaptic glutamate and GABA receptors do exist. Wiring transmission (WT) and VT are fundamental properties of all neurons of the CNS but the balance between WT and VT varies from one nerve cell population to the other. The focus is on the striatal cellular networks, and the WT and VT and their integration via receptor heteromers are described in the GABA projection neurons, the glutamate, dopamine, 5-hydroxytryptamine (5-HT) and histamine striatal afferents, the cholinergic interneurons, and different types of GABA interneurons. In addition, the role in these networks of VT signaling of the energy-dependent modulator adenosine and of endocannabinoids mainly formed in the striatal projection neurons will be underlined to understand the communication in the striatal cellular networks
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Normal and abnormal brains can be segmented by registering the target image with an atlas. Here, an atlas is defined as the combination of an intensity image (template) and its segmented image (the atlas labels). After registering the atlas template and the target image, the atlas labels are propagated to the target image. We define this process as atlas-based segmentation. In recent years, researchers have investigated registration algorithms to match atlases to query subjects and also strategies for atlas construction. In this paper we present a review of the automated approaches for atlas-based segmentation of magnetic resonance brain images. We aim to point out the strengths and weaknesses of atlas-based methods and suggest new research directions. We use two different criteria to present the methods. First, we refer to the algorithms according to their atlas-based strategy: label propagation, multi-atlas methods, and probabilistic techniques. Subsequently, we classify the methods according to their medical target: the brain and its internal structures, tissue segmentation in healthy subjects, tissue segmentation in fetus, neonates and elderly subjects, and segmentation of damaged brains. A quantitative comparison of the results reported in the literature is also presented.