159 research outputs found

    Health-related quality of life in adolescents and young adults with high functioning autism-spectrum disorder

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    Aim: Over the last years, health-related quality of life (HRQOL) has emerged as an important measure not only in somatic medicine but also in psychiatry. To date, there are only few reports on HRQOL in patients with autism-spectrum disorder (ASD). This study aimed at studying HRQOL in ASD patients with an IQ >70, using a self-report HRQOL questionnaire with cross-cultural validity

    How Do Adults with Autism Spectrum Disorder Participate in the Labor Market? A German Multi-center Survey

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    International studies show disadvantages for adults with autism spectrum disorder (ASD) in the labor market. Data about their participation in the German labor market are scarce. The aim of this study was to examine the integration of adults with ASD in the German labor market in terms of education, employment and type of occupation by means of a cross-sectional-study, using a postal questionnaire. Findings show above average levels of education for adults with ASD compared to the general population of Germany and simultaneously, below average rates of employment and high rates of financial dependency. That indicates a poor integration of adults with ASD in the German labor market and emphasizes the need for vocational support policies for adults with ASD

    Luminescent silver nanoclusters decorated on ZnO tetrapods: a detailed understanding of their role in photoluminescence features

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    Optical spectroscopic measurements are conducted on luminescent silver nanocluster (AgNC) decorated ZnO tetrapods (ZnO Tp), AgNC@ZnO Tp, synthesized via a colloidal route. Their properties are compared with those of the corresponding AgNC and ZnO Tp to understand their impact on the photoluminescence (PL). Raman spectroscopy reveals the high structural integrity of the ZnO structure in the AgNC@ZnO Tp. PL analysis of the ZnO Tp shows a well-resolved near band edge emission and a green band comprised by the overlapping of at least three emitting optical centres. The addition of AgNC to ZnO Tp in the hybrid material enhances the emission from ZnO surface states. The recombination of the AgNC in water solution is dominated by a red emission band peaking at ∼1.9 eV and the PL excitation spectra monitored at the band maximum reveal that the red PL of AgNC is preferentially populated by well-defined excitation bands corresponding to discrete electronic transitions of the NCs. Yet, a shift to lower energies of the AgNC emission occurs in the AgNC@ZnO Tp hybrid when excited with energies below the ZnO bandgap, while for energies above this value no emission from the AgNC was observed, with the ZnO-related recombination dominating the spectra. A gradual loss in the PL intensity of the AgNC is observed in the hybrid with increasing time, which is consistent with their coalescence to transform into larger Ag nanoparticles (NPs) on the tetrapod surface, as revealed by confocal microscopy.publishe

    Understanding B-type Supergiants in the Low Metallicity Environment of the SMC

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    Spectroscopic analyses of 7 SMC B-type supergiants and 1 giant have been undertaken using high resolution optical data obtained on the VLT with UVES. FASTWIND, a non-LTE, spherical,line-blanketed model atmosphere code was used to derive atmospheric and wind parameters of these stars as well as their absolute abundances. The implications of these results for stellar evolution and line driven wind theory are discussed.Comment: 19 pages, 6 tables, 10 figures, accepted for publication in Astronomy and Astrophysics (5/12/2003

    Dysfunctions in brain networks supporting empathy: An fMRI study in adults with autism spectrum disorders

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    The present study aimed at identifying dysfunctions in brain networks that may underlie disturbed empathic behavior in autism spectrum disorders (ASD). During functional magnetic resonance imaging, subjects were asked to identify the emotional state observed in a facial stimulus (other-task) or to evaluate their own emotional response (self-task). Behaviorally, ASD subjects performed equally to the control group during the other-task, but showed less emotionally congruent responses in the self-task. Activations in brain regions related to theory of mind were observed in both groups. Activations of the medial prefrontal cortex (MPFC) were located in dorsal subregions in ASD subjects and in ventral areas in control subjects. During the self-task, ASD subjects activated an additional network of frontal and inferior temporal areas. Frontal areas previously associated with the human mirror system were activated in both tasks in control subjects, while ASD subjects recruited these areas during the self-task only. Activations in the ventral MPFC may provide the basis for one's “emotional bond” with other persons’ emotions. Such atypical patterns of activation may underlie disturbed empathy in individuals with ASD. Subjects with ASD may use an atypical cognitive strategy to gain access to their own emotional state in response to other people's emotions

    The Systems Biology Research Tool: evolvable open-source software

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    BACKGROUND: Research in the field of systems biology requires software for a variety of purposes. Software must be used to store, retrieve, analyze, and sometimes even to collect the data obtained from system-level (often high-throughput) experiments. Software must also be used to implement mathematical models and algorithms required for simulation and theoretical predictions on the system-level. RESULTS: We introduce a free, easy-to-use, open-source, integrated software platform called the Systems Biology Research Tool (SBRT) to facilitate the computational aspects of systems biology. The SBRT currently performs 35 methods for analyzing stoichiometric networks and 16 methods from fields such as graph theory, geometry, algebra, and combinatorics. New computational techniques can be added to the SBRT via process plug-ins, providing a high degree of evolvability and a unifying framework for software development in systems biology. CONCLUSION: The Systems Biology Research Tool represents a technological advance for systems biology. This software can be used to make sophisticated computational techniques accessible to everyone (including those with no programming ability), to facilitate cooperation among researchers, and to expedite progress in the field of systems biology

    Refining Kidney Survival in 383 Genetically Characterized Patients With Nephronophthisis

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    Introduction: Nephronophthisis (NPH) comprises a group of rare disorders accounting for up to 10% of end-stage kidney disease (ESKD) in children. Prediction of kidney prognosis poses a major challenge. We assessed differences in kidney survival, impact of variant type, and the association of clinical characteristics with declining kidney function. Methods: Data was obtained from 3 independent sources, namely the network for early onset cystic kidney diseases clinical registry (n = 105), an online survey sent out to the European Reference Network for Rare Kidney Diseases (n = 60), and a literature search (n = 218). Results: A total of 383 individuals were available for analysis: 116 NPHP1, 101 NPHP3, 81 NPHP4 and 85 NPHP11/TMEM67 patients. Kidney survival differed between the 4 cohorts with a highly variable median age at onset of ESKD as follows: NPHP3, 4.0 years (interquartile range 0.3–12.0); NPHP1, 13.5 years (interquartile range 10.5–16.5); NPHP4, 16.0 years (interquartile range 11.0–25.0); and NPHP11/TMEM67, 19.0 years (interquartile range 8.7–28.0). Kidney survival was significantly associated with the underlying variant type for NPHP1, NPHP3, and NPHP4. Multivariate analysis for the NPHP1 cohort revealed growth retardation (hazard ratio 3.5) and angiotensin-converting enzyme inhibitor (ACEI) treatment (hazard ratio 2.8) as 2 independent factors associated with an earlier onset of ESKD, whereas arterial hypertension was linked to an accelerated glomerular filtration rate (GFR) decline. Conclusion: The presented data will enable clinicians to better estimate kidney prognosis of distinct patients with NPH and thereby allow personalized counseling

    Can we predict real-time fMRI neurofeedback learning success from pretraining brain activity?

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    Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large inter-individual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pretraining functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pretraining activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning

    FASIMU: flexible software for flux-balance computation series in large metabolic networks

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    <p>Abstract</p> <p>Background</p> <p>Flux-balance analysis based on linear optimization is widely used to compute metabolic fluxes in large metabolic networks and gains increasingly importance in network curation and structural analysis. Thus, a computational tool flexible enough to realize a wide variety of FBA algorithms and able to handle batch series of flux-balance optimizations is of great benefit.</p> <p>Results</p> <p>We present FASIMU, a command line oriented software for the computation of flux distributions using a variety of the most common FBA algorithms, including the first available implementation of (i) weighted flux minimization, (ii) fitness maximization for partially inhibited enzymes, and (iii) of the concentration-based thermodynamic feasibility constraint. It allows batch computation with varying objectives and constraints suited for network pruning, leak analysis, flux-variability analysis, and systematic probing of metabolic objectives for network curation. Input and output supports SBML. FASIMU can work with free (lp_solve and GLPK) or commercial solvers (CPLEX, LINDO). A new plugin (faBiNA) for BiNA allows to conveniently visualize calculated flux distributions. The platform-independent program is an open-source project, freely available under GNU public license at <url>http://www.bioinformatics.org/fasimu</url> including manual, tutorial, and plugins.</p> <p>Conclusions</p> <p>We present a flux-balance optimization program whose main merits are the implementation of thermodynamics as a constraint, batch series of computations, free availability of sources, choice on various external solvers, and the flexibility on metabolic objectives and constraints.</p

    OptFlux: an open-source software platform for in silico metabolic engineering

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    <p>Abstract</p> <p>Background</p> <p>Over the last few years a number of methods have been proposed for the phenotype simulation of microorganisms under different environmental and genetic conditions. These have been used as the basis to support the discovery of successful genetic modifications of the microbial metabolism to address industrial goals. However, the use of these methods has been restricted to bioinformaticians or other expert researchers. The main aim of this work is, therefore, to provide a user-friendly computational tool for Metabolic Engineering applications.</p> <p>Results</p> <p><it>OptFlux </it>is an open-source and modular software aimed at being the reference computational application in the field. It is the first tool to incorporate strain optimization tasks, i.e., the identification of Metabolic Engineering targets, using Evolutionary Algorithms/Simulated Annealing metaheuristics or the previously proposed OptKnock algorithm. It also allows the use of stoichiometric metabolic models for (i) phenotype simulation of both wild-type and mutant organisms, using the methods of Flux Balance Analysis, Minimization of Metabolic Adjustment or Regulatory on/off Minimization of Metabolic flux changes, (ii) Metabolic Flux Analysis, computing the admissible flux space given a set of measured fluxes, and (iii) pathway analysis through the calculation of Elementary Flux Modes.</p> <p><it>OptFlux </it>also contemplates several methods for model simplification and other pre-processing operations aimed at reducing the search space for optimization algorithms.</p> <p>The software supports importing/exporting to several flat file formats and it is compatible with the SBML standard. <it>OptFlux </it>has a visualization module that allows the analysis of the model structure that is compatible with the layout information of <it>Cell Designer</it>, allowing the superimposition of simulation results with the model graph.</p> <p>Conclusions</p> <p>The <it>OptFlux </it>software is freely available, together with documentation and other resources, thus bridging the gap from research in strain optimization algorithms and the final users. It is a valuable platform for researchers in the field that have available a number of useful tools. Its open-source nature invites contributions by all those interested in making their methods available for the community.</p> <p>Given its plug-in based architecture it can be extended with new functionalities. Currently, several plug-ins are being developed, including network topology analysis tools and the integration with Boolean network based regulatory models.</p
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