A Zinc Sulphate-Resistant Acrodermatitis Enteropathica Patient With A Novel Mutation In Slc39A4 Gene

Acrodermatitis enteropathica (AE) is a rare autosomal recessive disorder of zinc deficiency due to an abnormal intestinal zinc transporter. It is characterized by the triad of acral dermatitis, alopecia, and diarrhoea. Once AE is correctly diagnosed, patients are treated with orally administered zinc sulphate. En some patients, relapses occur during adolescence, despite the regular treatment. Here, we discuss the clinical and molecular features of a 13-year-old adolescent girl with acrodermatitis enteropathica who was resistant to high-dose zinc sulphate therapy. We successfully treated the patient with zinc gluconate and vitamin C, and we detected a novel homozygous c.541_551dup (p.Leu186fsX38) mutation in the exon 3 of her SLC39A4 gene.Wo

Semi-supervised echo state networks for audio classification

Echo state networks (ESNs), belonging to the wider family of reservoir computing methods, are a powerful tool for the analysis of dynamic data. In an ESN, the input signal is fed to a fixed (possibly large) pool of interconnected neurons, whose state is then read by an adaptable layer to provide the output. This last layer is generally trained via a regularized linear least-squares procedure. In this paper, we consider the more complex problem of training an ESN for classification problems in a semi-supervised setting, wherein only a part of the input sequences are effectively labeled with the desired response. To solve the problem, we combine the standard ESN with a semi-supervised support vector machine (S3VM) for training its adaptable connections. Additionally, we propose a novel algorithm for solving the resulting non-convex optimization problem, hinging on a series of successive approximations of the original problem. The resulting procedure is highly customizable and also admits a principled way of parallelizing training over multiple processors/computers. An extensive set of experimental evaluations on audio classification tasks supports the presented semi-supervised ESN as a practical tool for dynamic problems requiring the analysis of partially labeled data

Signs of Timing in Motor Cortex During Movement Preparation and Cue Anticipation

International audienceThe capacity to accurately anticipate the timing of predictable events is essential for sensorimotor behavior. Motor cortex holds an established role in movement preparation and execution. In this chapter we review the different ways in which motor cortical activity is modulated by event timing in sensorimotor delay tasks. During movement preparation, both single neuron and population responses reflect the temporal constraints of the task. Anticipatory modulations prior to sensory cues are also observed in motor cortex when the cue timing is predictable. We propose that the motor cortical activity during cue anticipation and movement preparation is embedded in a timing network that facilitates sensorimotor processing. In this context, the pre-cue and post-cue activity may reflect a presetting mechanism, complementing processing during movement execution, while prohibiting premature responses in situations requiring delayed motor output