176 research outputs found

    DbarN interaction in a color-confining chiral quark model

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    We investigate the low-energy elastic DbarN interaction using a quark model that confines color and realizes dynamical chiral symmetry breaking. The model is defined by a microscopic Hamiltonian inspired in the QCD Hamiltonian in Coulomb gauge. Constituent quark masses are obtained by solving a gap equation and baryon and meson bound-state wave functions are obtained using a variational method. We derive a low energy meson-nucleon potential from a quark-interchange mechanism whose ingredients are the quark-quark and quark-antiquark interactions and baryon and meson wave functions, all derived from the same microscopic Hamiltonian. The model is supplemented with (sigma,rho,omega,a0) single-meson exchanges to describe the long-range part of the interaction. Cross-sections and phase shifts are obtained by iterating the quark-interchange plus meson-exchange potentials in a Lippmann-Schwinger equation. Once model parameters in meson exchange potential are fixed to describe the low-energy experimental phase shifts of the K+N and K0N reactions, predictions for Dbar0N and D-N reactions are obtained without introducing new parameters.Comment: 13 latex pages, 7 figure

    Community Structure Characterization

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    This entry discusses the problem of describing some communities identified in a complex network of interest, in a way allowing to interpret them. We suppose the community structure has already been detected through one of the many methods proposed in the literature. The question is then to know how to extract valuable information from this first result, in order to allow human interpretation. This requires subsequent processing, which we describe in the rest of this entry

    A graph-theoretical approach in brain functional networks. Possible implications in EEG studies

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    Abstract\ud \ud \ud \ud Background\ud \ud Recently, it was realized that the functional connectivity networks estimated from actual brain-imaging technologies (MEG, fMRI and EEG) can be analyzed by means of the graph theory, that is a mathematical representation of a network, which is essentially reduced to nodes and connections between them.\ud \ud \ud \ud Methods\ud \ud We used high-resolution EEG technology to enhance the poor spatial information of the EEG activity on the scalp and it gives a measure of the electrical activity on the cortical surface. Afterwards, we used the Directed Transfer Function (DTF) that is a multivariate spectral measure for the estimation of the directional influences between any given pair of channels in a multivariate dataset. Finally, a graph theoretical approach was used to model the brain networks as graphs. These methods were used to analyze the structure of cortical connectivity during the attempt to move a paralyzed limb in a group (N=5) of spinal cord injured patients and during the movement execution in a group (N=5) of healthy subjects.\ud \ud \ud \ud Results\ud \ud Analysis performed on the cortical networks estimated from the group of normal and SCI patients revealed that both groups present few nodes with a high out-degree value (i.e. outgoing links). This property is valid in the networks estimated for all the frequency bands investigated. In particular, cingulate motor areas (CMAs) ROIs act as ‘‘hubs’’ for the outflow of information in both groups, SCI and healthy. Results also suggest that spinal cord injuries affect the functional architecture of the cortical network sub-serving the volition of motor acts mainly in its local feature property.\ud In particular, a higher local efficiency El can be observed in the SCI patients for three frequency bands, theta (3-6 Hz), alpha (7-12 Hz) and beta (13-29 Hz).\ud By taking into account all the possible pathways between different ROI couples, we were able to separate clearly the network properties of the SCI group from the CTRL group. In particular, we report a sort of compensatory mechanism in the SCI patients for the Theta (3-6 Hz) frequency band, indicating a higher level of “activation” Ω within the cortical network during the motor task. The activation index is directly related to diffusion, a type of dynamics that underlies several biological systems including possible spreading of neuronal activation across several cortical regions.\ud \ud \ud \ud Conclusions\ud \ud The present study aims at demonstrating the possible applications of graph theoretical approaches in the analyses of brain functional connectivity from EEG signals. In particular, the methodological aspects of the i) cortical activity from scalp EEG signals, ii) functional connectivity estimations iii) graph theoretical indexes are emphasized in the present paper to show their impact in a real application.This study was performed with support of the European Union, through the COST program NEUROMATH (BM0601). This paper only reflects the authors’ views and funding agency is not liable for any use that may be made of the information contained herein.This study was performed with support of the European Union, through the COST program NEUROMATH (BM0601). This paper only reflects the authors’ views and funding agency is not liable for any use that may be made of the information contained herein.This article has been published as part of Nonlinear Biomedical Physics Volume 4 Supplement 1, 2010: Consciousness and its Measures: Joint Workshop for COST Actions Neuromath and Consciousness. The full contents of the supplement are available online at http://www.nonlinearbiomedphys.com/supplements/4/S1.This article has been published as part of Nonlinear Biomedical Physics Volume 4 Supplement 1, 2010: Consciousness and its Measures: Joint Workshop for COST Actions Neuromath and Consciousness. The full contents of the supplement are available online at http://www.nonlinearbiomedphys.com/supplements/4/S1

    Nogo-Receptors NgR1 and NgR2 Do Not Mediate Regulation of CD4 T Helper Responses and CNS Repair in Experimental Autoimmune Encephalomyelitis

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    Myelin-associated inhibition of axonal regrowth after injury is considered one important factor that contributes to regeneration failure in the adult central nervous system (CNS). Blocking strategies targeting this pathway have been successfully applied in several nerve injury models, including experimental autoimmune encephalomyelitis (EAE), suggesting myelin-associated inhibitors (MAIs) and functionally related molecules as targets to enhance regeneration in multiple sclerosis. NgR1 and NgR2 were identified as interaction partners for the myelin proteins Nogo-A, MAG and OMgp and are probably mediating their growth-inhibitory effects on axons, although the in vivo relevance of this pathway is currently under debate. Recently, alternative functions of MAIs and NgRs in the regulation of immune cell migration and T cell differentiation have been described. Whether and to what extent NgR1 and NgR2 are contributing to Nogo and MAG-related inhibition of neuroregeneration or immunomodulation during EAE is currently unknown. Here we show that genetic deletion of both receptors does not promote functional recovery during EAE and that NgR1 and NgR2-mediated signals play a minor role in the development of CNS inflammation. Induction of EAE in Ngr1/2-double mutant mice resulted in indifferent disease course and tissue damage when compared to WT controls. Further, the development of encephalitogenic CD4+ Th1 and Th17 responses was unchanged. However, we observed a slightly increased leukocyte infiltration into the CNS in the absence of NgR1 and NgR2, indicating that NgRs might be involved in the regulation of immune cell migration in the CNS. Our study demonstrates the urgent need for a more detailed knowledge on the multifunctional roles of ligands and receptors involved in CNS regeneration failure

    Nicotinic acid adenine dinucleotide phosphate-mediated calcium signalling in effector T cells regulates autoimmunity of the central nervous system

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    Nicotinic acid adenine dinucleotide phosphate represents a newly identified second messenger in T cells involved in antigen receptor-mediated calcium signalling. Its function in vivo is, however, unknown due to the lack of biocompatible inhibitors. Using a recently developed inhibitor, we explored the role of nicotinic acid adenine dinucleotide phosphate in autoreactive effector T cells during experimental autoimmune encephalomyelitis, the animal model for multiple sclerosis. We provide in vitro and in vivo evidence that calcium signalling controlled by nicotinic acid adenine dinucleotide phosphate is relevant for the pathogenic potential of autoimmune effector T cells. Live two photon imaging and molecular analyses revealed that nicotinic acid adenine dinucleotide phosphate signalling regulates T cell motility and re-activation upon arrival in the nervous tissues. Treatment with the nicotinic acid adenine dinucleotide phosphate inhibitor significantly reduced both the number of stable arrests of effector T cells and their invasive capacity. The levels of pro-inflammatory cytokines interferon-gamma and interleukin-17 were strongly diminished. Consecutively, the clinical symptoms of experimental autoimmune encephalomyelitis were ameliorated. In vitro, antigen-triggered T cell proliferation and cytokine production were evenly suppressed. These inhibitory effects were reversible: after wash-out of the nicotinic acid adenine dinucleotide phosphate antagonist, the effector T cells fully regained their functions. The nicotinic acid derivative BZ194 induced this transient state of non-responsiveness specifically in post-activated effector T cells. Naïve and long-lived memory T cells, which express lower levels of the putative nicotinic acid adenine dinucleotide phosphate receptor, type 1 ryanodine receptor, were not targeted. T cell priming and recall responses in vivo were not reduced. These data indicate that the nicotinic acid adenine dinucleotide phosphate/calcium signalling pathway is essential for the recruitment and the activation of autoaggressive effector T cells within their target organ. Interference with this signalling pathway suppresses the formation of autoimmune inflammatory lesions and thus might qualify as a novel strategy for the treatment of T cell mediated autoimmune diseases

    Analyzing and Modeling Real-World Phenomena with Complex Networks: A Survey of Applications

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    The success of new scientific areas can be assessed by their potential for contributing to new theoretical approaches and in applications to real-world problems. Complex networks have fared extremely well in both of these aspects, with their sound theoretical basis developed over the years and with a variety of applications. In this survey, we analyze the applications of complex networks to real-world problems and data, with emphasis in representation, analysis and modeling, after an introduction to the main concepts and models. A diversity of phenomena are surveyed, which may be classified into no less than 22 areas, providing a clear indication of the impact of the field of complex networks.Comment: 103 pages, 3 figures and 7 tables. A working manuscript, suggestions are welcome
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