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Myasthenia gravis is an autoimmune disease affecting neuromuscular transmission and causing skeletal muscle weakness. Additionally, systemic inflammation, cognitive deficits and autonomic dysfunction have been described.
However, little is known about myasthenia gravis-related reorganization of the brain. In this study, we thus investigated the structural and functional brain changes in myasthenia gravis patients.
Eleven myasthenia gravis patients (age: 70.64 +/- 9.27; 11 males) were compared to age-, sex- and education-matched healthy controls (age: 70.18 +/- 8.98; 11 males). Most of the patients (n = 10, 0.91%) received cholinesterase inhibitors.
Structural brain changes were determined by applying voxel-based morphometry using high-resolution T-1-weighted sequences. Functional brain changes were assessed with a neuropsychological test battery (including attention, memory and executive functions), a spatial orientation task and brain-derived neurotrophic factor blood levels.
Myasthenia gravis patients showed significant grey matter volume reductions in the cingulate gyrus, in the inferior parietal lobe and in the fusiform gyrus. Furthermore, myasthenia gravis patients showed significantly lower performance in executive functions, working memory (Spatial Span, P = 0.034, d = 1.466), verbal episodic memory (P = 0.003, d = 1.468) and somatosensory-related spatial orientation (Triangle Completion Test, P = 0.003, d = 1.200).
Additionally, serum brain-derived neurotrophic factor levels were significantly higher in myasthenia gravis patients (P = 0.001, d = 2.040). Our results indicate that myasthenia gravis is associated with structural and functional brain alterations. Especially the grey matter volume changes in the cingulate gyrus and the inferior parietal lobe could be associated with cognitive deficits in memory and executive functions.
Furthermore, deficits in somatosensory-related spatial orientation could be associated with the lower volumes in the inferior parietal lobe. Future research is needed to replicate these findings independently in a larger sample and to investigate the underlying mechanisms in more detail.
Klaus et al. compared myasthenia gravis patients to matched healthy control subjects and identified functional alterations in memory functions as well as structural alterations in the cingulate gyrus, in the inferior parietal lobe and in the fusiform gyrus.
Die Tagungsreihe zur Hochschuldidaktik der Informatik HDI wird vom Fachbereich Informatik und Ausbildung / Didaktik der Informatik (IAD) in der Gesellschaft für Informatik e. V. (GI) organisiert. Sie dient den Lehrenden der Informatik in Studiengängen an Hochschulen als Forum der Information und des Austauschs über neue didaktische Ansätze und bildungspolitische Themen im Bereich der Hochschulausbildung aus der fachlichen Perspektive der Informatik. Diese fünfte HDI 2012 wurde an der Universität Hamburg organisiert. Für sie wurde das spezielle Motto „Informatik für eine nachhaltige Zukunft“ gewählt, um insbesondere Fragen der Bildungsrelevanz informatischer Inhalte, der Kompetenzen für Studierende informatisch geprägter Studiengänge und der Rolle der Informatik in der Hochschulentwicklung zu diskutieren.
1. For managed temperate forests, conservationists and policymakers favour fine-grained uneven-aged (UEA) management over more traditional coarse-grained even-aged (EA) management, based on the assumption that within-stand habitat heterogeneity enhances biodiversity. There is, however, little empirical evidence to support this assumption. We investigated for the first time how differently grained forest management systems affect the biodiversity of multiple above- and below-ground taxa across spatial scales. 2. We sampled 15 taxa of animals, plants, fungi and bacteria within the largest contiguous beech forest landscape of Germany and classified them into functional groups. Selected forest stands have been managed for more than a century at different spatial grains. The EA (coarse-grained management) and UEA (fine-grained) forests are comparable in spatial arrangement, climate and soil conditions. These were compared to forests of a nearby national park that have been unmanaged for at least 20years. We used diversity accumulation curves to compare -diversity for Hill numbers D-0 (species richness), D-1 (Shannon diversity) and D-2 (Simpson diversity) between the management systems. Beta diversity was quantified as multiple-site dissimilarity. 3. Gamma diversity was higher in EA than in UEA forests for at least one of the three Hill numbers for six taxa (up to 77%), while eight showed no difference. Only bacteria showed the opposite pattern. Higher -diversity in EA forests was also found for forest specialists and saproxylic beetles. 4. Between-stand -diversity was higher in EA than in UEA forests for one-third (all species) and half (forest specialists) of all taxa, driven by environmental heterogeneity between age-classes, while -diversity showed no directional response across taxa or for forest specialists. 5. Synthesis and applications. Comparing EA and uneven-aged forest management in Central European beech forests, our results show that a mosaic of different age-classes is more important for regional biodiversity than high within-stand heterogeneity. We suggest reconsidering the current trend of replacing even-aged management in temperate forests. Instead, the variability of stages and stand structures should be increased to promote landscape-scale biodiversity.
Incremental Support Vector Machines (SVM) are instrumental in practical applications of online learning. This work focuses on the design and analysis of efficient incremental SVM learning, with the aim of providing a fast, numerically stable and robust implementation. A detailed analysis of convergence and of algorithmic complexity of incremental SVM learning is carried out. Based on this analysis, a new design of storage and numerical operations is proposed, which speeds up the training of an incremental SVM by a factor of 5 to 20. The performance of the new algorithm is demonstrated in two scenarios: learning with limited resources and active learning. Various applications of the algorithm, such as in drug discovery, online monitoring of industrial devices and and surveillance of network traffic, can be foreseen.
Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.
This paper proposes a new independent component analysis (ICA) method which is able to unmix overcomplete mixtures of sparce or structured signals like speech, music or images. Furthermore, the method is designed to be robust against outliers, which is a favorable feature for ICA algorithms since most of them are extremely sensitive to outliers. Our approach is based on a simple outlier index. However, instead of robustifying an existing algorithm by some outlier rejection technique we show how this index can be used directly to solve the ICA problem for super-Gaussian sources. The resulting inlier-based ICA (IBICA) is outlier-robust by construction and can be used for standard ICA as well as for overcomplete ICA (i.e. more source signals than observed signals). (c) 2005 Wiley Periodicals, Inc
Usually, noise is considered to be destructive. We present a new method that constructively injects noise to assess the reliability and the grouping structure of empirical ICA component estimates. Our method can be viewed as a Monte-Carlo-style approximation of the curvature of some performance measure at the solution. Simulations show that the true root-mean-squared angle distances between the real sources and the source estimates can be approximated well by our method. In a toy experiment, we see that we are also able to reveal the underlying grouping structure of the extracted ICA components. Furthermore, an experiment with fetal ECG data demonstrates that our approach is useful for exploratory data analysis of real-world data. (C) 2003 Elsevier B.V. All rights reserved
The Cassini-Huygens Cosmic Dust Analyzer (CDA) is intended to provide direct observations of dust grains with masses between 10(-19) and 10(-9) kg in interplanetary space and in the jovian and saturnian systems, to investigate their physical, chemical and dynamical properties as functions of the distances to the Sun, to Jupiter and to Saturn and its satellites and rings, to study their interaction with the saturnian rings, satellites and magnetosphere. Chemical composition of interplanetary meteoroids will be compared with asteroidal and cometary dust, as well as with Saturn dust, ejecta from rings and satellites. Ring and satellites phenomena which might be effects of meteoroid impacts will be compared with the interplanetary dust environment. Electrical charges of particulate matter in the magnetosphere and its consequences will be studied, e.g. the effects of the ambient plasma and the magnetic held on the trajectories of dust particles as well as fragmentation of particles due to electrostatic disruption. The investigation will be performed with an instrument that measures the mass, composition, electric charge, speed, and flight direction of individual dust particles. It is a highly reliable and versatile instrument with a mass sensitivity 106 times higher than that of the Pioneer 10 and I I dust detectors which measured dust in the saturnian system. The Cosmic Dust Analyzer has significant inheritance from former space instrumentation developed for the VEGA, Giotto, Galileo, and Ulysses missions. It will reliably measure impacts from as low as I impact per month up to 104 impacts per second. The instrument weighs 17 kg and consumes 12 W, the integrated time-of-flight mass spectrometer has a mass resolution of up to 50. The nominal data transmission rate is 524 bits/s and varies between 50 and 4192 bps
Aus der Einleitung: Die derzeitige Situation in der Elektrizitätswirtschaft ist gekennzeichnet durch eine große Zahl anstehender Netzübernahmen infolge auslaufender Konzessionsverträge oder Arrondierungsmaßnahmen und einer Reihe dabei anhängiger Rechtsstreite, in denen insbesondere der "angemessene" Übernahmepreis strittig ist. Die in der Vergangenheit getätigten Netzübernahmen liefern zu der Frage nach dem "angemessenen" bzw. "rechtlich richtigen" Übernahmepreis keine Antwort, da die letztendlich gezahlten Preise i.d.R. das Ergebnis eines Verhandlungsprozesses waren und die damit verbundenen rechtlichen Streitfragen weiterhin offen sind. Die vorliegende Untersuchung greift die Frage nach dem "angemessenen" Übernahmepreis auf und versucht, eine aus ökonomischen Argumenten abgeleitete sowie mit den rechtlichen Rahmenbedingungen zu vereinbarende Antwort zu liefern.