192 resultados para Network Visualization


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Cancer genomes frequently contain somatic copy number alterations (SCNA) that can significantly perturb the expression level of affected genes and thus disrupt pathways controlling normal growth. In melanoma, many studies have focussed on the copy number and gene expression levels of the BRAF, PTEN and MITF genes, but little has been done to identify new genes using these parameters at the genome-wide scale. Using karyotyping, SNP and CGH arrays, and RNA-seq, we have identified SCNA affecting gene expression ('SCNA-genes') in seven human metastatic melanoma cell lines. We showed that the combination of these techniques is useful to identify candidate genes potentially involved in tumorigenesis. Since few of these alterations were recurrent across our samples, we used a protein network-guided approach to determine whether any pathways were enriched in SCNA-genes in one or more samples. From this unbiased genome-wide analysis, we identified 28 significantly enriched pathway modules. Comparison with two large, independent melanoma SCNA datasets showed less than 10% overlap at the individual gene level, but network-guided analysis revealed 66% shared pathways, including all but three of the pathways identified in our data. Frequently altered pathways included WNT, cadherin signalling, angiogenesis and melanogenesis. Additionally, our results emphasize the potential of the EPHA3 and FRS2 gene products, involved in angiogenesis and migration, as possible therapeutic targets in melanoma. Our study demonstrates the utility of network-guided approaches, for both large and small datasets, to identify pathways recurrently perturbed in cancer.

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For self-pollinating plants to reproduce, male and female organ development must be coordinated as flowers mature. The Arabidopsis transcription factors AUXIN RESPONSE FACTOR 6 (ARF6) and ARF8 regulate this complex process by promoting petal expansion, stamen filament elongation, anther dehiscence, and gynoecium maturation, thereby ensuring that pollen released from the anthers is deposited on the stigma of a receptive gynoecium. ARF6 and ARF8 induce jasmonate production, which in turn triggers expression of MYB21 and MYB24, encoding R2R3 MYB transcription factors that promote petal and stamen growth. To understand the dynamics of this flower maturation regulatory network, we have characterized morphological, chemical, and global gene expression phenotypes of arf, myb, and jasmonate pathway mutant flowers. We found that MYB21 and MYB24 promoted not only petal and stamen development but also gynoecium growth. As well as regulating reproductive competence, both the ARF and MYB factors promoted nectary development or function and volatile sesquiterpene production, which may attract insect pollinators and/or repel pathogens. Mutants lacking jasmonate synthesis or response had decreased MYB21 expression and stamen and petal growth at the stage when flowers normally open, but had increased MYB21 expression in petals of older flowers, resulting in renewed and persistent petal expansion at later stages. Both auxin response and jasmonate synthesis promoted positive feedbacks that may ensure rapid petal and stamen growth as flowers open. MYB21 also fed back negatively on expression of jasmonate biosynthesis pathway genes to decrease flower jasmonate level, which correlated with termination of growth after flowers have opened. These dynamic feedbacks may promote timely, coordinated, and transient growth of flower organs.

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OBJECTIVES: The goal was to test 2 hypotheses: first, that coronary endothelial function can be measured noninvasively and abnormal function detected using clinical 3.0-T magnetic resonance imaging (MRI); and second, that the extent of local coronary artery disease (CAD), in a given patient, is related to the degree of local abnormal coronary endothelial function. BACKGROUND: Abnormal endothelial function mediates the initiation and progression of atherosclerosis and predicts cardiovascular events. However, direct measures of coronary endothelial function have required invasive assessment. METHODS: The MRI was performed in 20 healthy adults and 17 patients with CAD. Cross-sectional coronary area and blood flow were quantified before and during isometric handgrip exercise, an endothelial-dependent stressor. In 10 severe, single-vessel CAD patients, paired endothelial function was measured in the artery with severe stenosis and the contralateral artery with minimal disease. RESULTS: In healthy adults, coronary arteries dilated and flow increased with stress. In CAD patients, coronary artery area and blood flow decreased with stress (both p </= 0.02). In the paired study, coronary artery area and blood flow failed to increase during exercise in the mildly diseased vessel, but both area (p = 0.01) and blood flow (p = 0.02) decreased significantly in the severely diseased, contralateral artery. CONCLUSIONS: Endothelial-dependent coronary artery dilation and increased blood flow in healthy subjects, and their absence in CAD patients, can now be directly visualized and quantified noninvasively. Local coronary endothelial function differs between severely and mildly diseased arteries in a given CAD patient. This novel, safe method may offer new insights regarding the importance of local coronary endothelial function and improved risk stratification in patients at risk for and with known CAD.

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PURPOSE: To investigate magnetization transfer (MT) effects as a new source of contrast for imaging and tracking of peripheral foot nerves. MATERIALS AND METHODS: Two sets of 3D spoiled gradient-echo images acquired with and without a saturation pulse were used to generate MT ratio (MTR) maps of 260 μm in-plane resolution for eight volunteers at 3T. Scan parameters were adjusted to minimize signal loss due to T2 dephasing, and a dedicated coil was used to improve the inherently low signal-to-noise ratio of small voxels. Resulting MTR values in foot nerves were compared with those in surrounding muscle tissue. RESULTS: Average MTR values for muscle (45.5 ± 1.4%) and nerve (21.4 ± 3.1%) were significantly different (P < 0.0001). In general, the difference in MTR values was sufficiently large to allow for intensity-based segmentation and tracking of foot nerves in individual subjects. This procedure was termed MT-based 3D visualization. CONCLUSION: The MTR serves as a new source of contrast for imaging of peripheral foot nerves and provides a means for high spatial resolution tracking of these structures. The proposed methodology is directly applicable on standard clinical MR scanners and could be applied to systemic pathologies, such as diabetes.

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This paper deals with the problem of spatial data mapping. A new method based on wavelet interpolation and geostatistical prediction (kriging) is proposed. The method - wavelet analysis residual kriging (WARK) - is developed in order to assess the problems rising for highly variable data in presence of spatial trends. In these cases stationary prediction models have very limited application. Wavelet analysis is used to model large-scale structures and kriging of the remaining residuals focuses on small-scale peculiarities. WARK is able to model spatial pattern which features multiscale structure. In the present work WARK is applied to the rainfall data and the results of validation are compared with the ones obtained from neural network residual kriging (NNRK). NNRK is also a residual-based method, which uses artificial neural network to model large-scale non-linear trends. The comparison of the results demonstrates the high quality performance of WARK in predicting hot spots, reproducing global statistical characteristics of the distribution and spatial correlation structure.

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Abstract Sitting between your past and your future doesn't mean you are in the present. Dakota Skye Complex systems science is an interdisciplinary field grouping under the same umbrella dynamical phenomena from social, natural or mathematical sciences. The emergence of a higher order organization or behavior, transcending that expected of the linear addition of the parts, is a key factor shared by all these systems. Most complex systems can be modeled as networks that represent the interactions amongst the system's components. In addition to the actual nature of the part's interactions, the intrinsic topological structure of underlying network is believed to play a crucial role in the remarkable emergent behaviors exhibited by the systems. Moreover, the topology is also a key a factor to explain the extraordinary flexibility and resilience to perturbations when applied to transmission and diffusion phenomena. In this work, we study the effect of different network structures on the performance and on the fault tolerance of systems in two different contexts. In the first part, we study cellular automata, which are a simple paradigm for distributed computation. Cellular automata are made of basic Boolean computational units, the cells; relying on simple rules and information from- the surrounding cells to perform a global task. The limited visibility of the cells can be modeled as a network, where interactions amongst cells are governed by an underlying structure, usually a regular one. In order to increase the performance of cellular automata, we chose to change its topology. We applied computational principles inspired by Darwinian evolution, called evolutionary algorithms, to alter the system's topological structure starting from either a regular or a random one. The outcome is remarkable, as the resulting topologies find themselves sharing properties of both regular and random network, and display similitudes Watts-Strogtz's small-world network found in social systems. Moreover, the performance and tolerance to probabilistic faults of our small-world like cellular automata surpasses that of regular ones. In the second part, we use the context of biological genetic regulatory networks and, in particular, Kauffman's random Boolean networks model. In some ways, this model is close to cellular automata, although is not expected to perform any task. Instead, it simulates the time-evolution of genetic regulation within living organisms under strict conditions. The original model, though very attractive by it's simplicity, suffered from important shortcomings unveiled by the recent advances in genetics and biology. We propose to use these new discoveries to improve the original model. Firstly, we have used artificial topologies believed to be closer to that of gene regulatory networks. We have also studied actual biological organisms, and used parts of their genetic regulatory networks in our models. Secondly, we have addressed the improbable full synchronicity of the event taking place on. Boolean networks and proposed a more biologically plausible cascading scheme. Finally, we tackled the actual Boolean functions of the model, i.e. the specifics of how genes activate according to the activity of upstream genes, and presented a new update function that takes into account the actual promoting and repressing effects of one gene on another. Our improved models demonstrate the expected, biologically sound, behavior of previous GRN model, yet with superior resistance to perturbations. We believe they are one step closer to the biological reality.

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The regulation of the immune system is controlled by many cell surface receptors. A prominent representative is the 'molecular switch' HVEM (herpes virus entry mediator) that can activate either proinflammatory or inhibitory signaling pathways. HVEM ligands belong to two distinct families: the TNF-related cytokines LIGHT and lymphotoxin-α, and the Ig-related membrane proteins BTLA and CD160. HVEM and its ligands have been involved in the pathogenesis of various autoimmune and inflammatory diseases, but recent reports indicate that this network may also be involved in tumor progression and resistance to immune response. Here we summarize the recent advances made regarding the knowledge on HVEM and its ligands in cancer cells, and their potential roles in tumor progression and escape to immune responses. Blockade or enhancement of these pathways may help improving cancer therapy.

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Substance user adolescents were asked to report on each contact they had had with any type of care providers since they had begun to use alcohol or illegal drugs regularly. Primary care doctors and social workers represent the main access to the care network. In one out of two contacts substance use was not discussed.

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AIMS: We sought to evaluate the utility of contrast-enhanced coronary magnetic resonance imaging (CE-MRI) for selective visualization and non-invasive differentiation of atherosclerotic coronary plaque in humans. METHODS AND RESULTS: Nine patients with coronary artery disease (CAD) as confirmed by X-ray angiography and multidetector computed tomography (MDCT) were studied by T1-weighted black blood inversion recovery coronary MRI before (N-IR) and after administration of Gd-DTPA (CE-IR). Plaques were categorized as calcified, non-calcified, and mixed based on their Hounsfield number derived from MDCT. With MDCT, a total of 29 plaques were identified, including calcified (n=6), non-calcified (n=6), and mixed calcified/non-calcified (n=17). On N-IR MRI, 26 plaques (90%) were dark, whereas three plaques (two non-calcified and one mixed) appeared bright. On CE-MRI, 13/29 (45%) plaques, 11 of which were mixed, one non-calcified, and one calcified showed contrast uptake. All others remained dark. CONCLUSION: In this preliminary study, we demonstrate the potential utility of CE-IR MRI for selective plaque visualization and differentiation of plaque types. The observed contrast uptake may be associated with endothelial dysfunction, neovascularization, inflammation, and/or fibrosis.

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Inhibitory control refers to the ability to suppress planned or ongoing cognitive or motor processes. Electrophysiological indices of inhibitory control failure have been found to manifest even before the presentation of the stimuli triggering the inhibition, suggesting that pre-stimulus brain-states modulate inhibition performance. However, previous electrophysiological investigations on the state-dependency of inhibitory control were based on averaged event-related potentials (ERPs), a method eliminating the variability in the ongoing brain activity not time-locked to the event of interest. These studies thus left unresolved whether spontaneous variations in the brain-state immediately preceding unpredictable inhibition-triggering stimuli also influence inhibitory control performance. To address this question, we applied single-trial EEG topographic analyses on the time interval immediately preceding NoGo stimuli in conditions where the responses to NoGo trials were correctly inhibited [correct rejection (CR)] vs. committed [false alarms (FAs)] during an auditory spatial Go/NoGo task. We found a specific configuration of the EEG voltage field manifesting more frequently before correctly inhibited responses to NoGo stimuli than before FAs. There was no evidence for an EEG topography occurring more frequently before FAs than before CR. The visualization of distributed electrical source estimations of the EEG topography preceding successful response inhibition suggested that it resulted from the activity of a right fronto-parietal brain network. Our results suggest that the fluctuations in the ongoing brain activity immediately preceding stimulus presentation contribute to the behavioral outcomes during an inhibitory control task. Our results further suggest that the state-dependency of sensory-cognitive processing might not only concern perceptual processes, but also high-order, top-down inhibitory control mechanisms.

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In this paper we analyse the decline of the Swiss corporate network between 1980 and 2000. We address the theoretical and methodological challenge of this transformation by the use of a combination of network analysis and multiple correspondence analysis (MCA). Based on a sample of top managers of the 110 largest Swiss companies in 1980 and 2000 we show that, beyond an adjustment to structural pressure, an explanation of the decline of the network has to include the strategies of the fractions of the business elites. We reveal that three factors contribute crucially to the decline of the Swiss corporate network: the managerialization of industrial leaders, the marginalization of law degree holders and the influx of hardly connected foreign managers.

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The aim of this study was to describe the clinical and PSG characteristics of narcolepsy with cataplexy and their genetic predisposition by using the retrospective patient database of the European Narcolepsy Network (EU-NN). We have analysed retrospective data of 1099 patients with narcolepsy diagnosed according to International Classification of Sleep Disorders-2. Demographic and clinical characteristics, polysomnography and multiple sleep latency test data, hypocretin-1 levels, and genome-wide genotypes were available. We found a significantly lower age at sleepiness onset (men versus women: 23.74 ± 12.43 versus 21.49 ± 11.83, P = 0.003) and longer diagnostic delay in women (men versus women: 13.82 ± 13.79 versus 15.62 ± 14.94, P = 0.044). The mean diagnostic delay was 14.63 ± 14.31 years, and longer delay was associated with higher body mass index. The best predictors of short diagnostic delay were young age at diagnosis, cataplexy as the first symptom and higher frequency of cataplexy attacks. The mean multiple sleep latency negatively correlated with Epworth Sleepiness Scale (ESS) and with the number of sleep-onset rapid eye movement periods (SOREMPs), but none of the polysomnographic variables was associated with subjective or objective measures of sleepiness. Variant rs2859998 in UBXN2B gene showed a strong association (P = 1.28E-07) with the age at onset of excessive daytime sleepiness, and rs12425451 near the transcription factor TEAD4 (P = 1.97E-07) with the age at onset of cataplexy. Altogether, our results indicate that the diagnostic delay remains extremely long, age and gender substantially affect symptoms, and that a genetic predisposition affects the age at onset of symptoms.