961 resultados para Functional Capability Framework


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Linking the structural connectivity of brain circuits to their cooperative dynamics and emergent functions is a central aim of neuroscience research. Graph theory has recently been applied to study the structure-function relationship of networks, where dynamical similarity of different nodes has been turned into a "static" functional connection. However, the capability of the brain to adapt, learn and process external stimuli requires a constant dynamical functional rewiring between circuitries and cell assemblies. Hence, we must capture the changes of network functional connectivity over time. Multi-electrode array data present a unique challenge within this framework. We study the dynamics of gamma oscillations in acute slices of the somatosensory cortex from juvenile mice recorded by planar multi-electrode arrays. Bursts of gamma oscillatory activity lasting a few hundred milliseconds could be initiated only by brief trains of electrical stimulations applied at the deepest cortical layers and simultaneously delivered at multiple locations. Local field potentials were used to study the spatio-temporal properties and the instantaneous synchronization profile of the gamma oscillatory activity, combined with current source density (CSD) analysis. Pair-wise differences in the oscillation phase were used to determine the presence of instantaneous synchronization between the different sites of the circuitry during the oscillatory period. Despite variation in the duration of the oscillatory response over successive trials, they showed a constant average power, suggesting that the rate of expenditure of energy during the gamma bursts is consistent across repeated stimulations. Within each gamma burst, the functional connectivity map reflected the columnar organization of the neocortex. Over successive trials, an apparently random rearrangement of the functional connectivity was observed, with a more stable columnar than horizontal organization. This work reveals new features of evoked gamma oscillations in developing cortex.

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Aquaporin-1 (AQP1) is a water channel that is highly expressed in tissues with rapid O(2) transport. It has been reported that this protein contributes to gas permeation (CO(2), NO and O(2)) through the plasma membrane. We show that hypoxia increases Aqp1 mRNA and protein levels in tissues, namely mouse brain and lung, and in cultured cells, the 9L glioma cell line. Stopped-flow light-scattering experiments confirmed an increase in the water permeability of 9L cells exposed to hypoxia, supporting the view that hypoxic Aqp1 up-regulation has a functional role. To investigate the molecular mechanisms underlying this regulatory process, transcriptional regulation was studied by transient transfections of mouse endothelial cells with a 1297 bp 5' proximal Aqp1 promoter-luciferase construct. Incubation in hypoxia produced a dose- and time-dependent induction of luciferase activity that was also obtained after treatments with hypoxia mimetics (DMOG and CoCl(2)) and by overexpressing stabilized mutated forms of HIF-1α. Single mutations or full deletions of the three putative HIF binding domains present in the Aqp1 promoter partially reduced its responsiveness to hypoxia, and transfection with Hif-1α siRNA decreased the in vitro hypoxia induction of Aqp1 mRNA and protein levels. Our results indicate that HIF-1α participates in the hypoxic induction of AQP1. However, we also demonstrate that the activation of Aqp1 promoter by hypoxia is complex and multifactorial and suggest that besides HIF-1α other transcription factors might contribute to this regulatory process. These data provide a conceptual framework to support future research on the involvement of AQP1 in a range of pathophysiological conditions, including edema, tumor growth, and respiratory diseases.

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CD6 has recently been identified and validated as risk gene for multiple sclerosis (MS), based on the association of a single nucleotide polymorphism (SNP), rs17824933, located in intron 1. CD6 is a cell surface scavenger receptor involved in T-cell activation and proliferation, as well as in thymocyte differentiation. In this study, we performed a haptag SNP screen of the CD6 gene locus using a total of thirteen tagging SNPs, of which three were non-synonymous SNPs, and replicated the recently reported GWAS SNP rs650258 in a Spanish-Basque collection of 814 controls and 823 cases. Validation of the six most strongly associated SNPs was performed in an independent collection of 2265 MS patients and 2600 healthy controls. We identified association of haplotypes composed of two non-synonymous SNPs [rs11230563 (R225W) and rs2074225 (A257V)] in the 2(nd) SRCR domain with susceptibility to MS (P max(T) permutation = 1×10(-4)). The effect of these haplotypes on CD6 surface expression and cytokine secretion was also tested. The analysis showed significantly different CD6 expression patterns in the distinct cell subsets, i.e. - CD4(+) naïve cells, P = 0.0001; CD8(+) naïve cells, P<0.0001; CD4(+) and CD8(+) central memory cells, P = 0.01 and 0.05, respectively; and natural killer T (NKT) cells, P = 0.02; with the protective haplotype (RA) showing higher expression of CD6. However, no significant changes were observed in natural killer (NK) cells, effector memory and terminally differentiated effector memory T cells. Our findings reveal that this new MS-associated CD6 risk haplotype significantly modifies expression of CD6 on CD4(+) and CD8(+) T cells.

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Fungalysins are secreted fungal peptidases with the ability to degrade the extracellular matrix proteins elastin and collagen and are thought to act as virulence factors in diseases caused by fungi. Fungalysins constitute a unique family among zinc-dependent peptidases that bears low sequence similarity to known bacterial peptidases of the thermolysin family. The crystal structure of the archetype of the fungalysin family, Aspergillus fumigatus metalloprotease (AfuMep), has been obtained for the first time. The 1.8 Å resolution structure of AfuMep corresponds to that of an autoproteolyzed proenzyme with separate polypeptide chains corresponding to the N-terminal prodomain in a binary complex with the C-terminal zinc-bound catalytic domain. The prodomain consists of a tandem of cystatin-like folds whose C-terminal end is buried into the active-site cleft of the catalytic domain. The catalytic domain harbouring the key catalytic zinc ion and its ligands, two histidines and one glutamic acid, undergoes a conspicuous rearrangement of its N-terminal end during maturation. One key positively charged amino-acid residue and the C-terminal disulfide bridge appear to contribute to its structural-functional properties. Thus, structural, biophysical and biochemical analysis were combined to provide a deeper comprehension of the underlying properties of A. fumigatus fungalysin, serving as a framework for the as yet poorly known metallopeptidases from pathogenic fungi.

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In this paper, we propose a new paradigm to carry outthe registration task with a dense deformation fieldderived from the optical flow model and the activecontour method. The proposed framework merges differenttasks such as segmentation, regularization, incorporationof prior knowledge and registration into a singleframework. The active contour model is at the core of ourframework even if it is used in a different way than thestandard approaches. Indeed, active contours are awell-known technique for image segmentation. Thistechnique consists in finding the curve which minimizesan energy functional designed to be minimal when thecurve has reached the object contours. That way, we getaccurate and smooth segmentation results. So far, theactive contour model has been used to segment objectslying in images from boundary-based, region-based orshape-based information. Our registration technique willprofit of all these families of active contours todetermine a dense deformation field defined on the wholeimage. A well-suited application of our model is theatlas registration in medical imaging which consists inautomatically delineating anatomical structures. Wepresent results on 2D synthetic images to show theperformances of our non rigid deformation field based ona natural registration term. We also present registrationresults on real 3D medical data with a large spaceoccupying tumor substantially deforming surroundingstructures, which constitutes a high challenging problem.

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Mutations of the Ectodysplasin-A (EDA) gene are generally associated with the syndrome hypohidrotic ectodermal dysplasia (MIM 305100), but they can also manifest as selective, non-syndromic tooth agenesis (MIM300606). We have performed an in vitro functional analysis of six selective tooth agenesis-causing EDA mutations (one novel and five known) that are located in the C-terminal tumor necrosis factor homology domain of the protein. Our study reveals that expression, receptor binding or signaling capability of the mutant EDA1 proteins is only impaired in contrast to syndrome-causing mutations, which we have previously shown to abolish EDA1 expression, receptor binding or signaling. Our results support a model in which the development of the human dentition, especially of anterior teeth, requires the highest level of EDA-receptor signaling, whereas other ectodermal appendages, including posterior teeth, have less stringent requirements and form normally in response to EDA mutations with reduced activity.

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A set of connections among several nuclear and electronic indexes of reactivity in the framework of the conceptual Density Functional Theory by using an expansion ofthe energy functional in terms of the total number of electrons and the normal coordinates within a canonical ensemble was derived. The relations obtained provided explicit links between important quantities related to the chemical reactivity of a system. This paper particularly demonstrates that the derivative of the electronic energy with respect to the external potential of a system in its equilibrium geometry was equal to the negative of the nuclear repulsion derivative with respect to the external potential

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A conceptually new approach is introduced for the decomposition of the molecular energy calculated at the density functional theory level of theory into sum of one- and two-atomic energy components, and is realized in the "fuzzy atoms" framework. (Fuzzy atoms mean that the three-dimensional physical space is divided into atomic regions having no sharp boundaries but exhibiting a continuous transition from one to another.) The new scheme uses the new concept of "bond order density" to calculate the diatomic exchange energy components and gives them unexpectedly close to the values calculated by the exact (Hartree-Fock) exchange for the same Kohn-Sham orbitals

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Genetic and functional data indicate that variation in the expression of the neurotrophin-3 receptor gene (NTRK3) may have an impact on neuronal plasticity, suggesting a role for NTRK3 in the pathophysiology of anxiety disorders. MicroRNA (miRNA) posttranscriptional gene regulators act by base-pairing to specific sequence sites, usually at the 3'UTR of the target mRNA. Variants at these sites might result in gene expression changes contributing to disease susceptibility. We investigated genetic variation in two different isoforms of NTRK3 as candidate susceptibility factors for anxiety by resequencing their 3'UTRs in patients with panic disorder (PD), obsessive-compulsive disorder (OCD), and in controls. We have found the C allele of rs28521337, located in a functional target site for miR-485-3p in the truncated isoform of NTRK3, to be significantly associated with the hoarding phenotype of OCD. We have also identified two new rare variants in the 3'UTR of NTRK3, ss102661458 and ss102661460, each present only in one chromosome of a patient with PD. The ss102661458 variant is located in a functional target site for miR-765, and the ss102661460 in functional target sites for two miRNAs, miR-509 and miR-128, the latter being a brain-enriched miRNA involved in neuronal differentiation and synaptic processing. Interestingly, these two variants significantly alter the miRNA-mediated regulation of NTRK3, resulting in recovery of gene expression. These data implicate miRNAs as key posttranscriptional regulators of NTRK3 and provide a framework for allele-specific miRNA regulation of NTRK3 in anxiety disorders.

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Background: Single nucleotide polymorphisms (SNPs) are the most frequent type of sequence variation between individuals, and represent a promising tool for finding genetic determinants of complex diseases and understanding the differences in drug response. In this regard, it is of particular interest to study the effect of non-synonymous SNPs in the context of biological networks such as cell signalling pathways. UniProt provides curated information about the functional and phenotypic effects of sequence variation, including SNPs, as well as on mutations of protein sequences. However, no strategy has been developed to integrate this information with biological networks, with the ultimate goal of studying the impact of the functional effect of SNPs in the structure and dynamics of biological networks. Results: First, we identified the different challenges posed by the integration of the phenotypic effect of sequence variants and mutations with biological networks. Second, we developed a strategy for the combination of data extracted from public resources, such as UniProt, NCBI dbSNP, Reactome and BioModels. We generated attribute files containing phenotypic and genotypic annotations to the nodes of biological networks, which can be imported into network visualization tools such as Cytoscape. These resources allow the mapping and visualization of mutations and natural variations of human proteins and their phenotypic effect on biological networks (e.g. signalling pathways, protein-protein interaction networks, dynamic models). Finally, an example on the use of the sequence variation data in the dynamics of a network model is presented. Conclusion: In this paper we present a general strategy for the integration of pathway and sequence variation data for visualization, analysis and modelling purposes, including the study of the functional impact of protein sequence variations on the dynamics of signalling pathways. This is of particular interest when the SNP or mutation is known to be associated to disease. We expect that this approach will help in the study of the functional impact of disease-associated SNPs on the behaviour of cell signalling pathways, which ultimately will lead to a better understanding of the mechanisms underlying complex diseases.

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In a biophysical approach to the study of swimming performance (blending biomechanics and bioenergetics), inter-limb coordination is typically considered and analysed to improve propulsion and propelling efficiency. In this approach, 'opposition' or 'continuous' patterns of inter-limb coordination, where continuity between propulsive actions occurs, are promoted in the acquisition of expertise. Indeed a 'continuous' pattern theoretically minimizes intra-cyclic speed variations of the centre of mass. Consequently, it may also minimize the energy cost of locomotion. However, in skilled swimming performance there is a need to strike a delicate balance between inter-limb coordination pattern stability and variability, suggesting the absence of an 'ideal' pattern of coordination toward which all swimmers must converge or seek to imitate. Instead, an ecological dynamics framework advocates that there is an intertwined relationship between the specific intentions, perceptions and actions of individual swimmers, which constrains this relationship between coordination pattern stability and variability. This perspective explains how behaviours emerge from a set of interacting constraints, which each swimmer has to satisfy in order to achieve specific task performance goals and produce particular task outcomes. This overview updates understanding on inter-limb coordination in swimming to analyse the relationship between coordination variability and stability in relation to interacting constraints (related to task, environment and organism) that swimmers may encounter during training and performance.

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High-speed running accounts for the majority of hamstring strains in many sports. The terminal swing phase is believed to be the most hazardous as the hamstrings are undergoing an active lengthening contraction in a long muscle length position. Prevention-based strength training mainly focuses on eccentric exercises. However, it appears crucial to integrate other parameters than the contraction type. Therefore, the aim of this study is to present a conceptual framework based on six key parameters (contraction type, load, range of motion, angular velocity, uni-/bilateral exercises, kinetic chain) for the hamstring's strength exercise for strain prevention. Based on the biomechanical parameters of sprinting, it is proposed to use high-load eccentric contractions. The movement should be performed at a slow to moderate angular velocity and focused at the knee joint, while the hip is kept in a large flexion position in order to reach a greater elongation stress of the hamstrings than in the terminal swing phase. In this way, we believe that, during sprinting, athletes would be better trained to brake the knee extension effectively in the whole range of motion without overstretch of the hamstrings. Finally, based on its functional application, unilateral open kinetic chain should be preferred.

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In this paper we propose a generalization of the density functional theory. The theory leads to single-particle equations of motion with a quasilocal mean-field operator, which contains a quasiparticle position-dependent effective mass and a spin-orbit potential. The energy density functional is constructed using the extended Thomas-Fermi approximation and the ground-state properties of doubly magic nuclei are considered within the framework of this approach. Calculations were performed using the finite-range Gogny D1S forces and the results are compared with the exact Hartree-Fock calculations

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Brain fluctuations at rest are not random but are structured in spatial patterns of correlated activity across different brain areas. The question of how resting-state functional connectivity (FC) emerges from the brain's anatomical connections has motivated several experimental and computational studies to understand structure-function relationships. However, the mechanistic origin of resting state is obscured by large-scale models' complexity, and a close structure-function relation is still an open problem. Thus, a realistic but simple enough description of relevant brain dynamics is needed. Here, we derived a dynamic mean field model that consistently summarizes the realistic dynamics of a detailed spiking and conductance-based synaptic large-scale network, in which connectivity is constrained by diffusion imaging data from human subjects. The dynamic mean field approximates the ensemble dynamics, whose temporal evolution is dominated by the longest time scale of the system. With this reduction, we demonstrated that FC emerges as structured linear fluctuations around a stable low firing activity state close to destabilization. Moreover, the model can be further and crucially simplified into a set of motion equations for statistical moments, providing a direct analytical link between anatomical structure, neural network dynamics, and FC. Our study suggests that FC arises from noise propagation and dynamical slowing down of fluctuations in an anatomically constrained dynamical system. Altogether, the reduction from spiking models to statistical moments presented here provides a new framework to explicitly understand the building up of FC through neuronal dynamics underpinned by anatomical connections and to drive hypotheses in task-evoked studies and for clinical applications.

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The electronic and magnetic structures of the LaMnO3 compound have been studied by means of periodic calculations within the framework of spin polarized hybrid density-functional theory. In order to quantify the role of approximations to electronic exchange and correlation three different hybrid functionals have been used which mix nonlocal Fock and local Dirac-Slater exchange. Periodic Hartree-Fock results are also reported for comparative purposes. The A-antiferromagnetic ground state is properly predicted by all methods including Hartree-Fock exchange. In general, the different hybrid methods provide a rather accurate description of the band gap and of the two magnetic coupling constants, strongly suggesting that the corresponding description of the electronic structure is also accurate. An important conclusion emerging from this study is that the nature of the occupied states near the Fermi level is intermediate between the Hartree-Fock and local density approximation descriptions with a comparable participation of both Mn and O states.