931 resultados para Recent Structural Models


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Epileptic seizures of focal origin are classically considered to arise from a focal epileptogenic zone and then spread to other brain regions. This is a key concept for semiological electro-clinical correlations, localization of relevant structural lesions, and selection of patients for epilepsy surgery. Recent development in neuro-imaging and electro-physiology and combinations, thereof, have been validated as contributory tools for focus localization. In parallel, these techniques have revealed that widespread networks of brain regions, rather than a single epileptogenic region, are implicated in focal epileptic activity. Sophisticated multimodal imaging and analysis strategies of brain connectivity patterns have been developed to characterize the spatio-temporal relationships within these networks by combining the strength of both techniques to optimize spatial and temporal resolution with whole-brain coverage and directional connectivity. In this paper, we review the potential clinical contribution of these functional mapping techniques as well as invasive electrophysiology in human beings and animal models for characterizing network connectivity.

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Intervertebral disc (IVD) degeneration is a major cause of pain and disability; yet therapeutic options are limited and treatment often remains unsatisfactory. In recent years, research activities have intensified in tissue engineering and regenerative medicine, and pre-clinical studies have demonstrated encouraging results. Nonetheless, the translation of new biological therapies into clinical practice faces substantial barriers. During the symposium "Where Science meets Clinics", sponsored by the AO Foundation and held in Davos, Switzerland, from September 5-7, 2013, hurdles for translation were outlined, and ways to overcome them were discussed. With respect to cell therapy for IVD repair, it is obvious that regenerative treatment is indicated at early stages of disc degeneration, before structural changes have occurred. It is envisaged that in the near future, screening techniques and non-invasive imaging methods will be available to detect early degenerative changes. The promises of cell therapy include a sustained effect on matrix synthesis, inflammation control, and prevention of angio- and neuro-genesis. Discogenic pain, originating from "black discs" or annular injury, prevention of adjacent segment disease, and prevention of post-discectomy syndrome were identified as prospective indications for cell therapy. Before such therapy can safely and effectively be introduced into clinics, the identification of the patient population and proper standardisation of diagnostic parameters and outcome measurements are indispensable. Furthermore, open questions regarding the optimal cell type and delivery method need to be resolved in order to overcome the safety concerns implied with certain procedures. Finally, appropriate large animal models and well-designed clinical studies will be required, particularly addressing safety aspects.

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Pre-clinical studies using murine models are critical for understanding the pathophysiological mechanisms underlying immune-mediated disorders such as Eosinophilic esophagitis (EoE). In this study, an optical coherence tomography (OCT) system capable of providing three-dimensional images with axial and transverse resolutions of 5 µm and 10 µm, respectively, was utilized to obtain esophageal images from a murine model of EoE-like disease ex vivo. Structural changes in the esophagus of wild-type (Tslpr(+/+) ) and mutant (Tslpr(-/-) ) mice with EoE-like disease were quantitatively evaluated and food impaction sites in the esophagus of diseased mice were monitored using OCT. Here, the capability of OCT as a label-free imaging tool devoid of tissue-processing artifacts to effectively characterize murine EoE-like disease models has been demonstrated.

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The brain is a complex neural network with a hierarchical organization and the mapping of its elements and connections is an important step towards the understanding of its function. Recent developments in diffusion-weighted imaging have provided the opportunity to reconstruct the whole-brain structural network in-vivo at a large scale level and to study the brain structural substrate in a framework that is close to the current understanding of brain function. However, methods to construct the connectome are still under development and they should be carefully evaluated. To this end, the first two studies included in my thesis aimed at improving the analytical tools specific to the methodology of brain structural networks. The first of these papers assessed the repeatability of the most common global and local network metrics used in literature to characterize the connectome, while in the second paper the validity of further metrics based on the concept of communicability was evaluated. Communicability is a broader measure of connectivity which accounts also for parallel and indirect connections. These additional paths may be important for reorganizational mechanisms in the presence of lesions as well as to enhance integration in the network. These studies showed good to excellent repeatability of global network metrics when the same methodological pipeline was applied, but more variability was detected when considering local network metrics or when using different thresholding strategies. In addition, communicability metrics have been found to add some insight into the integration properties of the network by detecting subsets of nodes that were highly interconnected or vulnerable to lesions. The other two studies used methods based on diffusion-weighted imaging to obtain knowledge concerning the relationship between functional and structural connectivity and about the etiology of schizophrenia. The third study integrated functional oscillations measured using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) as well as diffusion-weighted imaging data. The multimodal approach that was applied revealed a positive relationship between individual fluctuations of the EEG alpha-frequency and diffusion properties of specific connections of two resting-state networks. Finally, in the fourth study diffusion-weighted imaging was used to probe for a relationship between the underlying white matter tissue structure and season of birth in schizophrenia patients. The results are in line with the neurodevelopmental hypothesis of early pathological mechanisms as the origin of schizophrenia. The different analytical approaches selected in these studies also provide arguments for discussion of the current limitations in the analysis of brain structural networks. To sum up, the first studies presented in this thesis illustrated the potential of brain structural network analysis to provide useful information on features of brain functional segregation and integration using reliable network metrics. In the other two studies alternative approaches were presented. The common discussion of the four studies enabled us to highlight the benefits and possibilities for the analysis of the connectome as well as some current limitations.

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Antisense oligonucleotides (AONs) hold promise for therapeutic correction of many genetic diseases via exon skipping, and the first AON-based drugs have entered clinical trials for neuromuscular disorders1, 2. However, despite advances in AON chemistry and design, systemic use of AONs is limited because of poor tissue uptake, and recent clinical reports confirm that sufficient therapeutic efficacy has not yet been achieved. Here we present a new class of AONs made of tricyclo-DNA (tcDNA), which displays unique pharmacological properties and unprecedented uptake by many tissues after systemic administration. We demonstrate these properties in two mouse models of Duchenne muscular dystrophy (DMD), a neurogenetic disease typically caused by frame-shifting deletions or nonsense mutations in the gene encoding dystrophin3, 4 and characterized by progressive muscle weakness, cardiomyopathy, respiratory failure5 and neurocognitive impairment6. Although current naked AONs do not enter the heart or cross the blood-brain barrier to any substantial extent, we show that systemic delivery of tcDNA-AONs promotes a high degree of rescue of dystrophin expression in skeletal muscles, the heart and, to a lesser extent, the brain. Our results demonstrate for the first time a physiological improvement of cardio-respiratory functions and a correction of behavioral features in DMD model mice. This makes tcDNA-AON chemistry particularly attractive as a potential future therapy for patients with DMD and other neuromuscular disorders or with other diseases that are eligible for exon-skipping approaches requiring whole-body treatment.

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The central assumption in the literature on collaborative networks and policy networks is that political outcomes are affected by a variety of state and nonstate actors. Some of these actors are more powerful than others and can therefore have a considerable effect on decision making. In this article, we seek to provide a structural and institutional explanation for these power differentials in policy networks and support the explanation with empirical evidence. We use a dyadic measure of influence reputation as a proxy for power, and posit that influence reputation over the political outcome is related to vertical integration into the political system by means of formal decision-making authority, and to horizontal integration by means of being well embedded into the policy network. Hence, we argue that actors are perceived as influential because of two complementary factors: (a) their institutional roles and (b) their structural positions in the policy network. Based on temporal and cross-sectional exponential random graph models, we compare five cases about climate, telecommunications, flood prevention, and toxic chemicals politics in Switzerland and Germany. The five networks cover national and local networks at different stages of the policy cycle. The results confirm that institutional and structural drivers seem to have a crucial impact on how an actor is perceived in decision making and implementation and, therefore, their ability to significantly shape outputs and service delivery.

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Prospective Memory (PM), executive functions (EF) and metacognition (MC) are relevant cognitive abilities for everyday functioning. They all seem to develop gradually in childhood and appear to be theoretically closely related; however, their empirical links remain unclear, especially in children. As a recent study revealed significant cross-sectional links between PM and EF, and a weaker but close link between PM and MC in 2nd graders (Spiess, Meier, & Roebers, submitted), this study focused on their short-term relationships and on their development. 119 children (MT1 =95 months, SDT1, = 4.8 months) completed the same tasks (one PM, three EF, one MC task) twice with a time-lag of 7 months. T-tests showed significant improvements in all tasks, except in the updating task. Different structural equation models were contrasted (AMOS); the best fitting model revealed that PMT2 was similarly predicted by PMT1 (r = .33) and EFT1 (r = .34). Additionally, EFT1 predicted MCT2 (r = .44), chi2(118, 119) = 128.91, p = .23, TLI = .968, CFI = .978, RMSEA = .028. Results show that PM, EF, and MC develop during childhood and also demonstrate that they are linked not only cross-sectionally, but longitudinally. Findings are discussed in a broader developmental framework.

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Species adapted to cold-climatic mountain environments are expected to face a high risk of range contractions, if not local extinctions under climate change. Yet, the populations of many endothermic species may not be primarily affected by physiological constraints, but indirectly by climate-induced changes of habitat characteristics. In mountain forests, where vertebrate species largely depend on vegetation composition and structure, deteriorating habitat suitability may thus be mitigated or even compensated by habitat management aiming at compositional and structural enhancement. We tested this possibility using four cold-adapted bird species with complementary habitat requirements as model organisms. Based on species data and environmental information collected in 300 1-km2 grid cells distributed across four mountain ranges in central Europe, we investigated (1) how species’ occurrence is explained by climate, landscape, and vegetation, (2) to what extent climate change and climate-induced vegetation changes will affect habitat suitability, and (3) whether these changes could be compensated by adaptive habitat management. Species presence was modelled as a function of climate, landscape and vegetation variables under current climate; moreover, vegetation-climate relationships were assessed. The models were extrapolated to the climatic conditions of 2050, assuming the moderate IPCC-scenario A1B, and changes in species’ occurrence probability were quantified. Finally, we assessed the maximum increase in occurrence probability that could be achieved by modifying one or multiple vegetation variables under altered climate conditions. Climate variables contributed significantly to explaining species occurrence, and expected climatic changes, as well as climate-induced vegetation trends, decreased the occurrence probability of all four species, particularly at the low-altitudinal margins of their distribution. These effects could be partly compensated by modifying single vegetation factors, but full compensation would only be achieved if several factors were changed in concert. The results illustrate the possibilities and limitations of adaptive species conservation management under climate change.

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This article addresses factors that infl uence member commitment in sport clubs. Based on the theory of social action and the economic behaviour theory, it focuses not only on individual characteristics of club members but also on the corresponding structural conditions of sport clubs. Accordingly, a multilevel framework is developed for explaining member commitment in sport clubs. Different multilevel models were estimated in order to analyse the infl uences of both the individual and corresponding context Level in a sample of n = 1,699 members of 42 Swiss and German sport clubs. The multilevel analysis permitted an adequate handling of hierarchically structured data. Results of These multilevel analyses indicated that the commitment of members is not just an outcome of individual characteristics such as strong identifi cation with their club, positively perceived (collective) solidarity, satisfaction with their sport club, or voluntary engagement. It is also determined by club-specific structural conditions: commitment proves to be more probable in rural sport clubs and clubs that explicitly support sociability. Furthermore, cross-level effects in relation to member commitment were also found between the context variable sociability and the individual variable identification.

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Progress toward elucidating the 3D structures of eukaryotic membrane proteins has been hampered by the lack of appropriate expression systems. Recent work using the Xenopus oocyte as a novel expression system for structural analysis demonstrates the capability of providing not only the significant amount of protein yields required for structural work but also the expression of eukaryotic membrane proteins in a more native and functional conformation. There is a long history using the oocyte expression system as an efficient tool for membrane transporter and channel expression in direct functional analysis, but improvements in robotic injection systems and protein yield optimization allow the rapid scalability of expressed proteins to be purified and characterized in physiologically relevant structural states. Traditional overexpression systems (yeast, bacteria, and insect cells) by comparison require chaotropic conditions over several steps for extraction, solubilization, and purification. By contrast, overexpressing within the oocyte system for subsequent negative-staining transmission electron microscopy studies provides a single system that can functionally assess and purify eukaryotic membrane proteins in fewer steps maintaining the physiological properties of the membrane protein.

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The geologic structures and metamorphic zonation of the northwestern Indian Himalaya contrast significantly with those in the central and eastern parts of the range, where the high-grade metamorphic rocks of the High Himalayan Crystalline (HHC) thrust southward over the weakly metamorphosed sediments of the Lesser Himalaya along the Main Central Thrust (MCT). Indeed, the hanging wall of the MCT in the NW Himalaya mainly consists of the greenschist facies metasediments of the Chamba zone, whereas HHC high-grade rocks are exposed more internally in the range as a large-scale dome called the Gianbul dome. This Gianbul dome is bounded by two oppositely directed shear zones, the NE-dipping Zanskar Shear Zone (ZSZ) on the northern flank and the SW-dipping Miyar Shear Zone (MSZ) on the southern limb. Current models for the emplacement of the HHC in NW India as a dome structure differ mainly in terms of the roles played by both the ZSZ and the MSZ during the tectonothermal evolution of the HHC. In both the channel flow model and wedge extrusion model, the ZSZ acts as a backstop normal fault along which the high-grade metamorphic rocks of the HHC of Zanskar are exhumed. In contrast, the recently proposed tectonic wedging model argues that the ZSZ and the MSZ correspond to one single detachment system that operates as a subhorizontal backthrust off of the MCT. Thus, the kinematic evolution of the two shear zones, the ZSZ and the MSZ, and their structural, metamorphic and chronological relations appear to be diagnostic features for discriminating the different models. In this paper, structural, metamorphic and geochronological data demonstrate that the MSZ and the ZSZ experienced two distinct kinematic evolutions. As such, the data presented in this paper rule out the hypothesis that the MSZ and the ZSZ constitute one single detachment system, as postulated by the tectonic wedging model. Structural, metamorphic and geochronological data are used to present an alternative tectonic model for the large-scale doming in the NW Indian Himalaya involving early NE-directed tectonics, weakness in the upper crust, reduced erosion at the orogenic front and rapid exhumation along both the ZSZ and the MSZ.

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High-resolution, ground-based and independent observations including co-located wind radiometer, lidar stations, and infrasound instruments are used to evaluate the accuracy of general circulation models and data-constrained assimilation systems in the middle atmosphere at northern hemisphere midlatitudes. Systematic comparisons between observations, the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analyses including the recent Integrated Forecast System cycles 38r1 and 38r2, the NASA’s Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalyses, and the free-running climate Max Planck Institute–Earth System Model–Low Resolution (MPI-ESM-LR) are carried out in both temporal and spectral dom ains. We find that ECMWF and MERRA are broadly consistent with lidar and wind radiometer measurements up to ~40 km. For both temperature and horizontal wind components, deviations increase with altitude as the assimilated observations become sparser. Between 40 and 60 km altitude, the standard deviation of the mean difference exceeds 5 K for the temperature and 20 m/s for the zonal wind. The largest deviations are observed in winter when the variability from large-scale planetary waves dominates. Between lidar data and MPI-ESM-LR, there is an overall agreement in spectral amplitude down to 15–20 days. At shorter time scales, the variability is lacking in the model by ~10 dB. Infrasound observations indicate a general good agreement with ECWMF wind and temperature products. As such, this study demonstrates the potential of the infrastructure of the Atmospheric Dynamics Research Infrastructure in Europe project that integrates various measurements and provides a quantitative understanding of stratosphere-troposphere dynamical coupling for numerical weather prediction applications.

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Two-dimensional (2D) crystallisation of Membrane proteins reconstitutes them into their native environment, the lipid bilayer. Electron crystallography allows the structural analysis of these regular protein–lipid arrays up to atomic resolution. The crystal quality depends on the protein purity, ist stability and on the crystallisation conditions. The basics of 2D crystallisation and different recent advances are reviewed and electron crystallography approaches summarised. Progress in 2D crystallisation, sample preparation, image detectors and automation of the data acquisition and processing pipeline makes 2D electron crystallography particularly attractive for the structural analysis of membrane proteins that are too small for single-particle analyses and too unstable to form three-dimensional (3D) crystals.

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OBJECTIVES To test the applicability, accuracy, precision, and reproducibility of various 3D superimposition techniques for radiographic data, transformed to triangulated surface data. METHODS Five superimposition techniques (3P: three-point registration; AC: anterior cranial base; AC + F: anterior cranial base + foramen magnum; BZ: both zygomatic arches; 1Z: one zygomatic arch) were tested using eight pairs of pre-existing CT data (pre- and post-treatment). These were obtained from non-growing orthodontic patients treated with rapid maxillary expansion. All datasets were superimposed by three operators independently, who repeated the whole procedure one month later. Accuracy was assessed by the distance (D) between superimposed datasets on three form-stable anatomical areas, located on the anterior cranial base and the foramen magnum. Precision and reproducibility were assessed using the distances between models at four specific landmarks. Non parametric multivariate models and Bland-Altman difference plots were used for analyses. RESULTS There was no difference among operators or between time points on the accuracy of each superimposition technique (p>0.05). The AC + F technique was the most accurate (D<0.17 mm), as expected, followed by AC and BZ superimpositions that presented similar level of accuracy (D<0.5 mm). 3P and 1Z were the least accurate superimpositions (0.790.05), the detected structural changes differed significantly between different techniques (p<0.05). Bland-Altman difference plots showed that BZ superimposition was comparable to AC, though it presented slightly higher random error. CONCLUSIONS Superimposition of 3D datasets using surface models created from voxel data can provide accurate, precise, and reproducible results, offering also high efficiency and increased post-processing capabilities. In the present study population, the BZ superimposition was comparable to AC, with the added advantage of being applicable to scans with a smaller field of view.

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Vestibular cognition has recently gained attention. Despite numerous experimental and clinical demonstrations, it is not yet clear what vestibular cognition really is. For future research in vestibular cognition, adopting a computational approach will make it easier to explore the underlying mech- anisms. Indeed, most modeling approaches in vestibular science include a top-down or a priori component. We review recent Bayesian optimal observer models, and discuss in detail the conceptual value of prior assumptions, likelihood and posterior estimates for research in vestibular cognition. We then consider forward models in vestibular processing, which are required in order to distinguish between sensory input that is induced by active self-motion, and sensory input that is due to passive self-motion. We suggest that forward models are used not only in the service of estimating sensory states but they can also be drawn upon in an offline mode (e.g., spatial perspective transformations), in which interaction with sensory input is not desired. A computational approach to vestibular cogni- tion will help to discover connections across studies, and it will provide a more coherent framework for investigating vestibular cognition.