Update on the role of antipsychotics in the treatment of Tourette syndrome

Tourette syndrome (TS) is a neuropsychiatric disorder with typical onset in childhood and characterized by chronic occurrence of motor and vocal tics. The disorder can lead to serious impairments of both quality of life and psychosocial functioning, particularly for those individuals displaying complex tics. In such patients, drug treatment is recommended. The pathophysiology of TS is thought to involve a dysfunction of basal ganglia-related circuits and hyperactive dopaminergic innervations. Congruently, dopamine receptor antagonism of neuroleptics appears to be the most efficacious approach for pharmacological intervention. To assess the efficacy of the different neuroleptics available, a systematic, keyword-related search in PubMed (National Library of Medicine, Washington, DC) was undertaken. Much information on the use of antipsychotics in the treatment of TS is based on older data. Our objective was to give an update and therefore we focused on papers published in the last decade (between 2001 and 2011). Accordingly, the present review aims to summarize the current and evidence-based knowledge on the risk-benefit ratio of both first and second generation neuroleptics in TS

Auxetic orthotropic materials: Numerical determination of a phenomenological spline-based stored density energy and its implementation for finite element analysis

Abstract Auxetic materials, which have negative Poisson’s ratio, show potential to be used in many interesting applications. Finite element analysis (FEA) is an important phase in implementing auxetic materials, but may become computationally expensive because simulation often needs microscale details and a fine mesh. It is also necessary to check that topological aspects of the microscale reflects not only micro but macromechanical behavior. This work presents a phenomenological approach to the problem using data-driven spline-based techniques to properly characterize orthotropic auxetic material requiring neither analytical constraints nor micromechanics, expanding on previous methods for isotropic materials. Hyperelastic energies of auxetic orthotropic material are determined from experimental data by solving the equilibrium differential functional equations directly, so no fitting or analytical estimation is necessary. This offers two advantages; (i) it allows the FEA study of orthotropic auxetic materials without requiring micromechanics considerations, reducing modeling and computational time costs by two to three orders of magnitude; (ii) it adapts the hyperelastic energies to the nature of the material with precision, which could be critical in scenarios where accuracy is essential (e.g. robotic surgery)

Memory prosthesis: is it time for a deep neuromimetic approach?

Memory loss, one of the most dreaded afflictions of the human condition, presents considerable burden on the world’s health care system and it is recognized as a major challenge in the elderly. There are only a few neuro-modulation treatments for memory dysfunctions. Open loop deep brain stimulation is such a treatment for memory improvement, but with limited success and conflicting results. In recent years closed-loop neuropros-thesis systems able to simultaneously record signals during behavioural tasks and generate with the use of inter-nal neural factors the precise timing of stimulation patterns are presented as attractive alternatives and show promise in memory enhancement and restoration. A few such strides have already been made in both animals and humans, but with limited insights into their mechanisms of action. Here, I discuss why a deep neuromimetic computing approach linking multiple levels of description, mimicking the dynamics of brain circuits, interfaced with recording and stimulating electrodes could enhance the performance of current memory prosthesis systems, shed light into the neurobiology of learning and memory and accelerate the progress of memory prosthesis research. I propose what the necessary components (nodes, structure, connectivity, learning rules, and physi-ological responses) of such a deep neuromimetic model should be and what type of data are required to train/ test its performance, so it can be used as a true substitute of damaged brain areas capable of restoring/enhancing their missing memory formation capabilities. Considerations to neural circuit targeting, tissue interfacing, elec-trode placement/implantation and multi-network interactions in complex cognition are also provided

Verbesserung lokaler Spaltbruchmodelle unter Berücksichtigung mikromechanischer Vorgänge

Das Ziel der Arbeit ist die Ableitung, Implementierung und Validierung eines mikromechanisch basierten lokalen probabilistischen Spaltbruchmodells zur Bewertung der Bruchwahrscheinlichkeit von Bauteilen aus ferritischen Werkstoffen unter Berücksichtigung komplexer mehraxialer Spannungszustände. Mit dem so definierten Spaltbruchmodell steht ein universell einsetzbares Berechnungswerkzeug zur Integritätsbewertung unter Berücksichtigung der lokalen Belastungssituation zur Verfügung

Numerical analysis of uncertainties in the effective material behaviour of disordered structural foams

The present contribution is concerned with a numerical analysis of the uncertainties in the structural response of three-dimensional structural foams with partially open cells. The effective thermo mechanical material response is determined by means of an energy based homogenization procedure. Stochastic effects in the geometry and topology of the microstructure are treated by means of a repeated analysis of small-scale representative volume elements with prescribed relative density and prescribed cell size distribution. The results are evaluated by stochastic methods