944 resultados para Connectivity breakdown


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Developing a novel technique for the efficient, noninvasive clinical evaluation of bone microarchitecture remains both crucial and challenging. The trabecular bone score (TBS) is a new gray-level texture measurement that is applicable to dual-energy X-ray absorptiometry (DXA) images. Significant correlations between TBS and standard 3-dimensional (3D) parameters of bone microarchitecture have been obtained using a numerical simulation approach. The main objective of this study was to empirically evaluate such correlations in anteroposterior spine DXA images. Thirty dried human cadaver vertebrae were evaluated. Micro-computed tomography acquisitions of the bone pieces were obtained at an isotropic resolution of 93μm. Standard parameters of bone microarchitecture were evaluated in a defined region within the vertebral body, excluding cortical bone. The bone pieces were measured on a Prodigy DXA system (GE Medical-Lunar, Madison, WI), using a custom-made positioning device and experimental setup. Significant correlations were detected between TBS and 3D parameters of bone microarchitecture, mostly independent of any correlation between TBS and bone mineral density (BMD). The greatest correlation was between TBS and connectivity density, with TBS explaining roughly 67.2% of the variance. Based on multivariate linear regression modeling, we have established a model to allow for the interpretation of the relationship between TBS and 3D bone microarchitecture parameters. This model indicates that TBS adds greater value and power of differentiation between samples with similar BMDs but different bone microarchitectures. It has been shown that it is possible to estimate bone microarchitecture status derived from DXA imaging using TBS.

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Mastoparan, a basic tetradecapeptide isolated from wasp venom, is a novel mitogen for Swiss 3T3 cells. This peptide induced DNA synthesis in synergy with insulin in a concentration-dependent manner; half-maximum and maximum responses were achieved at 14 and 17 microM, respectively. Mastoparan also stimulated DNA synthesis in the presence of other growth promoting factors including bombesin, insulin-like growth factor-1, and platelet-derived growth factor. The synergistic mitogenic stimulation by mastoparan can be dissociated from activation of phospholipase C. Mastoparan did not stimulate phosphoinositide breakdown, Ca2+ mobilization or protein kinase C-mediated phosphorylation of a major cellular substrate or transmodulation of the epidermal growth factor receptor. In contrast, mastoparan stimulated arachidonic acid release, prostaglandin E2 production, and enhanced cAMP accumulation in the presence of forskolin. These responses were inhibited by prior treatment with pertussis toxin. Hence, mastoparan stimulates arachidonic acid release via a pertussis toxin-sensitive G protein in Swiss 3T3 cells. Arachidonic acid, like mastoparan, stimulated DNA synthesis in the presence of insulin. The ability of mastoparan to stimulate mitogenesis was reduced by pertussis toxin treatment. These results demonstrate, for the first time, that mastoparan stimulates reinitiation of DNA synthesis in Swiss 3T3 cells and indicate that this peptide may be a useful probe to elucidate signal transduction mechanisms in mitogenesis.

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Fluvial deposits are a challenge for modelling flow in sub-surface reservoirs. Connectivity and continuity of permeable bodies have a major impact on fluid flow in porous media. Contemporary object-based and multipoint statistics methods face a problem of robust representation of connected structures. An alternative approach to model petrophysical properties is based on machine learning algorithm ? Support Vector Regression (SVR). Semi-supervised SVR is able to establish spatial connectivity taking into account the prior knowledge on natural similarities. SVR as a learning algorithm is robust to noise and captures dependencies from all available data. Semi-supervised SVR applied to a synthetic fluvial reservoir demonstrated robust results, which are well matched to the flow performance

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In a weighted spatial network, as specified by an exchange matrix, the variances of the spatial values are inversely proportional to the size of the regions. Spatial values are no more exchangeable under independence, thus weakening the rationale for ordinary permutation and bootstrap tests of spatial autocorrelation. We propose an alternative permutation test for spatial autocorrelation, based upon exchangeable spatial modes, constructed as linear orthogonal combinations of spatial values. The coefficients obtain as eigenvectors of the standardised exchange matrix appearing in spectral clustering, and generalise to the weighted case the concept of spatial filtering for connectivity matrices. Also, two proposals aimed at transforming an acessibility matrix into a exchange matrix with with a priori fixed margins are presented. Two examples (inter-regional migratory flows and binary adjacency networks) illustrate the formalism, rooted in the theory of spectral decomposition for reversible Markov chains.

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Alzheimer's disease (AD) disrupts functional connectivity in distributed cortical networks. We analyzed changes in the S-estimator, a measure of multivariate intraregional synchronization, in electroencephalogram (EEG) source space in 15 mild AD patients versus 15 age-matched controls to evaluate its potential as a marker of AD progression. All participants underwent 2 clinical evaluations and 2 EEG recording sessions on diagnosis and after a year. The main effect of AD was hyposynchronization in the medial temporal and frontal regions and relative hypersynchronization in posterior cingulate, precuneus, cuneus, and parietotemporal cortices. However, the S-estimator did not change over time in either group. This result motivated an analysis of rapidly progressing AD versus slow-progressing patients. Rapidly progressing AD patients showed a significant reduction in synchronization with time, manifest in left frontotemporal cortex. Thus, the evolution of source EEG synchronization over time is correlated with the rate of disease progression and should be considered as a cost-effective AD biomarker.

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Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.

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Disturbances affect metapopulations directly through reductions in population size and indirectly through habitat modification. We consider how metapopulation persistence is affected by different disturbance regimes and the way in which disturbances spread, when metapopulations are compact or elongated, using a stochastic spatially explicit model which includes metapopulation and habitat dynamics. We discover that the risk of population extinction is larger for spatially aggregated disturbances than for spatially random disturbances. By changing the spatial configuration of the patches in the system--leading to different proportions of edge and interior patches--we demonstrate that the probability of metapopulation extinction is smaller when the metapopulation is more compact. Both of these results become more pronounced when colonization connectivity decreases. Our results have important management implication as edge patches, which are invariably considered to be less important, may play an important role as disturbance refugia.

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Interrill erosion occurs by the particle breakdown caused by raindrop impact, by particle transport in surface runoff, by dragging and suspension of particles disaggregated from the soil surface, thus removing organic matter and nutrients that are essential for agricultural production. Crop residues on the soil surface modify the characteristics of the runoff generated by rainfall and the consequent particle breakdown and sediment transport resulting from erosion. The objective of this study was to determine the minimum amount of mulch that must be maintained on the soil surface of a sugarcane plantation to reduce the soil, water and nutrient losses by decreasing interrill erosion. The study was conducted in Pradópolis, São Paulo State, in 0.5 x 1.0 m plots of an Oxisol, testing five treatments in four replications. The application rates were based on the crop residue production of the area of 1.4 kg m-2 (T1- no cane trash; T2-25 % of the cane trash; T3- 50 % trash; T4-75 % trash; T5-100 % sugarcane residues on the surface), and simulated rainfall was applied at an intensity of 65 mm h-1 for 60 min. Runoff samples were collected in plastic containers and soon after taken to the laboratory to quantify the losses of soil, water and nutrients. To minimize soil loss by interrill erosion, 75 % of the cane mulch must be maintained on the soil, to control water loss 50 % must be maintained and 25 % trash controls organic matter and nutrient losses. This information can contribute to optimize the use of this resource for soil conservation on the one hand and the production of clean energy in sugar and alcohol industries on the other.

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To explore the changes in resting energy expenditure (REE) and whole body protein turnover induced by malaria, 23 children aged 6 to 14 y (23.9 +/- 1.0 kg, 1.3 +/- 0.02 m) were studied on three separate days after treatment (d 1, d 2, and 15 d later). REE was assessed by indirect calorimetry (hood), whereas whole body protein turnover was estimated using a single dose of [15N]glycine administered p.o. by measuring the isotopic enrichment of [15N]ammonia in urine over 12 h. Within the first 3.5 h after treatment, the body temperature dropped from 39.8 +/- 0.1 to 37.8 +/- 0.1 degrees C (p < 0.0001), and REE followed the same pattern, decreasing rapidly from 223 +/- 6 to 187 +/- 4 kJ/kg/d (p < 0.0001). Whole body protein synthesis and breakdown were significantly higher during the 1st day (5.65 +/- 0.38 and 6.21 +/- 0.43 g/kg/d, respectively) than at d 15 (2.95 +/- 0.17 and 2.77 +/- 0.2 g/kg/d). It is concluded that Gambian children suffering from an acute episode of malaria have an increased REE averaging 37% of the control value (d 15) and that this was associated with a substantial increase (by a factor of 2) in whole body protein turnover. A rapid normalization of the hypermetabolism and protein hypercatabolism states after treatment was observed.

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Studies of soil-water dynamics using toposequences are essential to improve the understanding of soil-water-vegetation relationships. This study assessed the hydro-physical and morphological characteristics of soils of Atlantic Rainforest in the Parque Estadual de Carlos Botelho, state of São Paulo, Brazil. The study area of 10.24 ha (320 x 320 m) was covered by dense tropical rainforest (Atlantic Rainforest). Based on soil maps and topographic maps of the area, a representative transect of the soil in this plot was chosen and five soil trenches were opened to determine morphological properties. To evaluate the soil hydro-physical functioning, soil particle size distribution, bulk density (r), particle density (r s), soil water retention curves (SWRC), field saturated hydraulic conductivity (Ks), macroporosity (macro), and microporosity (micro) and total porosity (TP) were determined. Undisturbed samples were collected for micromorphometric image analysis, to determine pore size, shape, and connectivity. The soils in the study area were predominantly Inceptisols, and secondly Entisols and Epiaquic Haplustult. In the soil hydro-physical characterization of the selected transect, a change was observed in Ks between the surface and subsurface layers, from high/intermediate to intermediate/low permeability. This variation in soil-water dynamics was also observed in the SWRC, with higher water retention in the subsurface horizons. The soil hydro-physical behavior was influenced by the morphogenetic characteristics of the soils.

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A laser-based technique for printing transparent and weakly absorbing liquids is developed. Its principle of operation relies in the tight focusing of short laser pulses inside the liquid and close to its free surface, in such a way that the laser radiation is absorbed in a tiny volume around the beam waist, with practically no absorption in any other location along the beam path. If the absorbed energy overcomes the optical breakdown threshold, a cavitation bubble is generated, and its expansion results in the propulsion of a small fraction of liquid which can be collected on a substrate, leading to the printing of a microdroplet for each laser pulse. The technique does not require the preparation of the liquid in thin film form, and its forward mode of operation imposes no restriction concerning the optical properties of the substrate. These characteristics make it well suited for printing a wide variety of materials of interest in diverse applications. We demonstrate that the film-free laser forward printing technique is capable of printing microdroplets with good resolution, reproducibility and control, and analyze the influence of the main process parameter, laser pulse energy. The mechanisms of liquid printing are also investigated: time-resolved imaging provides a clear picture of the dynamics of liquid transfer which allows understanding the main features observed in the printed droplets.

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Glutathione (GSH) dysregulation at the gene, protein, and functional levels has been observed in schizophrenia patients. Together with disease-like anomalies in GSH deficit experimental models, it suggests that such redox dysregulation can play a critical role in altering neural connectivity and synchronization, and thus possibly causing schizophrenia symptoms. To determine whether increased GSH levels would modulate EEG synchronization, N-acetyl-cysteine (NAC), a glutathione precursor, was administered to patients in a randomized, double-blind, crossover protocol for 60 days, followed by placebo for another 60 days (or vice versa). We analyzed whole-head topography of the multivariate phase synchronization (MPS) for 128-channel resting-state EEGs that were recorded at the onset, at the point of crossover, and at the end of the protocol. In this proof of concept study, the treatment with NAC significantly increased MPS compared to placebo over the left parieto-temporal, the right temporal, and the bilateral prefrontal regions. These changes were robust both at the group and at the individual level. Although MPS increase was observed in the absence of clinical improvement at a group level, it correlated with individual change estimated by Liddle's disorganization scale. Therefore, significant changes in EEG synchronization induced by NAC administration may precede clinically detectable improvement, highlighting its possible utility as a biomarker of treatment efficacy. TRIAL REGISTRATION: ClinicalTrials.gov NCT01506765.

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The major processes discussed below are protein turnover (degradation and synthesis), degradation into urea, or conversion into glucose (gluconeogenesis, Figure 1). Daily protein turnover is a dynamic process characterized by a double flux of amino acids: the amino acids released by endogenous (body) protein breakdown can be reutilized and reconverted to protein synthesis, with very little loss. Daily rates of protein turnover in humans (300 to 400 g per day) are largely in excess of the level of protein intake (50 to 80 g per day). A fast growing rate, as in premature babies or in children recovering from malnutrition, leads to a high protein turnover rate and a high protein and energy requirement. Protein metabolism (synthesis and breakdown) is an energy-requiring process, dependent upon endogenous ATP supply. The contribution made by whole-body protein turnover to the resting metabolic rate is important: it represents about 20 % in adults and more in growing children. Metabolism of proteins cannot be disconnected from that of energy since energy balance influences net protein utilization, and since protein intake has an important effect on postprandial thermogenesis - more important than that of fats or carbohydrates. The metabolic need for amino acids is essentially to maintain stores of endogenous tissue proteins within an appropriate range, allowing protein homeostasis to be maintained. Thanks to a dynamic, free amino acid pool, this demand for amino acids can be continuously supplied. The size of the free amino acid pool remains limited and is regulated within narrow limits. The supply of amino acids to cover physiological needs can be derived from 3 sources: 1. Exogenous proteins that release amino acids after digestion and absorption 2. Tissue protein breakdown during protein turnover 3. De novo synthesis, including amino acids (as well as ammonia) derived from the process of urea salvage, following hydrolysis and microflora metabolism in the hind gut. When protein intake surpasses the physiological needs of amino acids, the excess amino acids are disposed of by three major processes: 1. Increased oxidation, with terminal end products such as CO₂ and ammonia 2. Enhanced ureagenesis i. e. synthesis of urea linked to protein oxidation eliminates the nitrogen radical 3. Gluconeogenesis, i. e. de novo synthesis of glucose. Most of the amino groups of the excess amino acids are converted into urea through the urea cycle, whereas their carbon skeletons are transformed into other intermediates, mostly glucose. This is one of the mechanisms, essential for life, developed by the body to maintain blood glucose within a narrow range, (i. e. glucose homeostasis). It includes the process of gluconeogenesis, i. e. de novo synthesis of glucose from non-glycogenic precursors; in particular certain specific amino acids (for example, alanine), as well as glycerol (derived from fat breakdown) and lactate (derived from muscles). The gluconeogenetic pathway progressively takes over when the supply of glucose from exogenous or endogenous sources (glycogenolysis) becomes insufficient. This process becomes vital during periods of metabolic stress, such as starvation.

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Brain connectivity can be represented by a network that enables the comparison of the different patterns of structural and functional connectivity among individuals. In the literature, two levels of statistical analysis have been considered in comparing brain connectivity across groups and subjects: 1) the global comparison where a single measure that summarizes the information of each brain is used in a statistical test; 2) the local analysis where a single test is performed either for each node/connection which implies a multiplicity correction, or for each group of nodes/connections where each subset is summarized by one single test in order to reduce the number of tests to avoid a penalizing multiplicity correction. We comment on the different levels of analysis and present some methods that have been proposed at each scale. We highlight as well the possible factors that could influence the statistical results and the questions that have to be addressed in such an analysis.

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The mammalian brain oscillates through three distinct global activity states: wakefulness, non-rapid eye movement (NREM) sleep and REM sleep. The regulation and function of these 'vigilance' or 'behavioural' states can be investigated over a broad range of temporal and spatial scales and at different levels of functional organization, i.e. from gene expression to memory, in single neurons, cortical columns or the whole brain and organism. We summarize some basic questions that have arisen from recent approaches in the quest for the functions of sleep. Whereas traditionally sleep was viewed to be regulated through top-down control mechanisms, recent approaches have emphasized that sleep is emerging locally and regulated in a use-dependent (homeostatic) manner. Traditional markers of sleep homeostasis, such as the electroencephalogram slow-wave activity, have been linked to changes in connectivity and plasticity in local neuronal networks. Thus waking experience-induced local network changes may be sensed by the sleep homeostatic process and used to mediate sleep-dependent events, benefiting network stabilization and memory consolidation. Although many questions remain unanswered, the available data suggest that sleep function will best be understood by an analysis which integrates sleep's many functional levels with its local homeostatic regulation.