Recurrent focal neuropathy with liability to pressure palsies is a relatively frequent autosomal-dominant demyelinating neuropathy linked to peripheral myelin protein 22 (PMP22) gene deletions. The combination of PMP22 gene mutations with other genetic variants is known to cause a more severe phenotype than expected. We present the case of a patient with severe orthostatic hypotension since 12 years of age, who inherited a PMP22 gene deletion from his father. Genetic double trouble was suspected because of selective sympathetic autonomic disturbances.

In the last two decades, PSO (Particle Swarm Optimization) gained a lot of attention among the different derivative-free algorithms for global optimization. The simplicity of the implementation, compact memory usage and parallel structure represent some key features, largely appreciated. On the other hand, the absence of local information about the objective function slow down the algorithm when one or more constraints are violated, even if a penalty approach is applied.

Understanding the conditions ensuring the persistence of a population is an issue of primary importance in population biology. The first theoretical approach to the problem dates back to the 1950s with the Kierstead, Slobodkin, and Skellam (KiSS) model, namely a continuous reaction-diffusion equation for a population growing on a patch of finite size L surrounded by a deadly environment with infinite mortality, i.e., an oasis in a desert. The main outcome of the model is that only patches above a critical size allow for population persistence.

Background: Chip-seq experiments are becoming a standard approach for genome-wide profiling protein-DNA interactions, such as detecting transcription factor binding sites, histone modification marks and RNA Polymerase II occupancy. However, when comparing a ChIP sample versus a control sample, such as Input DNA, normalization procedures have to be applied in order to remove experimental source of biases. Despite the substantial impact that the choice of the normalization method can have on the results of a ChIP-seq data analysis, their assessment is not fully explored in the literature.

In this study, we investigated by in silico analysis the possible correlation between microRNAs (miRNAs) and Anamnia V-SINEs (a superfamily of short interspersed nuclear elements), which belong to those retroposon families that have been preserved in vertebrate genomes for millions of years and are actively transcribed because they are embedded in the 3? untranslated region (UTR) of several genes. We report the results of the analysis of the genomic distribution of these mobile elements in zebrafish (Danio rerio) and discuss their involvement in generating miRNA gene loci.

We study the Perspective Shape from Shading problem from the numerical point of view pre- senting a simple algorithm to compute its solution. The scheme is based on a semi-Lagrangian approximation of the first order Hamilton-Jacobi equation related to the problem. The scheme is converging to the weak solution (in the viscosity sense) of the equation and allows to compute accurately regular as well as non regular solutions.

Gene expression data from high-throughput assays, such as microarray, are often used to predict cancer survival. Available datasets consist of a small number of samples (n patients) and a large number of genes (p predictors). Therefore, the main challenge is to cope with the high-dimensionality. Moreover, genes are co-regulated and their expression levels are expected to be highly correlated. In order to face these two issues, network based approaches can be applied.

In this paper we propose a LWR-like model for traffic flow on networks which allows to track several groups of drivers, each of them being characterized only by their destination in the network. The path actually followed to reach the destination is not assigned a priori, and can be chosen by the drivers during the journey, taking decisions at junctions. The model is then used to describe three possible behaviors of drivers, as- sociated to three different ways to solve the route choice problem: 1. Drivers ignore the presence of the other vehicles; 2.

In this paper, multi-disciplinary optimization techniques are applied to sail design. Two different mathematical models, providing the solution of the fluid-dynamic and the structural problems governing the behaviour of a complete sailplan, are coupled in a fluid-structure interaction (FSI) scheme, in order to determine the real flying shape of the sails and the forces acting on them. A numerical optimization algorithm is then applied, optimizing the structural pattern of the sailplan in order to maximize the driving force or other significant quantities.