309 resultados para Multiple datasets
Resumo:
INTRODUCTION: Malignant variant is a rare subtype of multiple sclerosis (MS) that is rapidly progressive and may lead to significant disability or even death. No consensus exists on best management of this disorder, although corticosteroids and plasmapheresis are commonly used in the acute phase, followed either by MS-specific disease-modifying therapy or an immunosuppressant. CASE REPORT: The patient is a 30-year-old man with relapsing-remitting MS previously well controlled with natalizumab, who has developed fulminant disease activity upon natalizumab cessation. In the acute phase, patient had a suboptimal response to multiple corticosteroid treatments but responded very well to plasmapheresis. Patient continued to have worsening disease activity despite fingolimod treatment. Disease control has been eventually achieved by switching to rituximab. CONCLUSION: Rituximab treatment should be considered for a patient with fulminant MS who responded well to plasmapheresis.
Accelerated Microstructure Imaging via Convex Optimisation for regions with multiple fibres (AMICOx)
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This paper reviews and extends our previous work to enable fast axonal diameter mapping from diffusion MRI data in the presence of multiple fibre populations within a voxel. Most of the existing mi-crostructure imaging techniques use non-linear algorithms to fit their data models and consequently, they are computationally expensive and usually slow. Moreover, most of them assume a single axon orientation while numerous regions of the brain actually present more complex configurations, e.g. fiber crossing. We present a flexible framework, based on convex optimisation, that enables fast and accurate reconstructions of the microstructure organisation, not limited to areas where the white matter is coherently oriented. We show through numerical simulations the ability of our method to correctly estimate the microstructure features (mean axon diameter and intra-cellular volume fraction) in crossing regions.
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Background Virtual reality (VR) simulation is increasingly used in surgical disciplines. Since VR simulators measure multiple outcomes, standardized reporting is needed. Methods We present an algorithm for combining multiple VR outcomes into dimension summary measures, which are then integrated into a meaningful total score. We reanalyzed the data of two VR studies applying the algorithm. Results The proposed algorithm was successfully applied to both VR studies. Conclusions The algorithm contributes to standardized and transparent reporting in VR-related research.
Resumo:
Food allergies are believed to be on the rise and currently management relies on the avoidance of the food. Hen's egg allergy is after cow's milk allergy the most common food allergy; eggs are used in many food products and thus difficult to avoid. A technological process using a combination of enzymatic hydrolysis and heat treatment was designed to produce modified hen's egg with reduced allergenic potential. Biochemical (SDS-PAGE, Size exclusion chromatography and LC-MS/MS) and immunological (ELISA, immunoblot, RBL-assays, animal model) analysis showed a clear decrease in intact proteins as well as a strong decrease of allergenicity. In a clinical study, 22 of the 24 patients with a confirmed egg allergy who underwent a double blind food challenge with the hydrolysed egg remained completely free of symptoms. Hydrolysed egg products may be beneficial as low allergenic foods for egg allergic patients to extent their diet. This article is protected by copyright. All rights reserved.