Thanks to innovative sample-preparation and sequencing technologies, gene expression in individual cells can now be measured for thousands of cells in a single experiment. Since its introduction, single-cell RNA sequencing (scRNA-seq) approaches have revolutionized the genomics field as they created unprecedented opportunities for resolving cell heterogeneity by exploring gene expression profiles at a single-cell resolution. However, the rapidly evolving field of scRNA-seq invoked the emergence of various analytics approaches aimed to maximize the full potential of this novel strategy.

MagnetoEncephaloGraphy (MEG) and ElectroEncephaloGraphy (EEG) are the most common non-invasive brain imaging techniques for monitoring the electrical brain activity with millisecond resolution. Due to their high, millisecond, temporal resolution, these techniques are also the most suitable for studying the dynamic interplay of between brain regions during information processing. In clinical settings, MEG and EEG are valuable methods for the pre-surgical evaluation of patients with pharmaco-resistant epilepsy.

Purpose: This study aimed to describe a multisystemic disorder featuring cardiovascular, facial, musculoskeletal, and cutaneous anomalies caused by heterozygous loss-of-function variants in TAB2. Methods: Affected individuals were analyzed by next-generation technologies and genomic array. The presumed loss-of-function effect of identified variants was assessed by luciferase assay in cells transiently expressing TAB2 deleterious alleles. In available patients' fibroblasts, variant pathogenicity was further explored by immunoblot and osteoblast differentiation assays.

We present mesoscale numerical simulations of Rayleigh-Bénard (RB) convection in a two-dimensional model emulsion. The systems under study are constituted of finite-size droplets, whose concentration is systematically varied from small (Newtonian emulsions) to large values (non-Newtonian emulsions). We focus on the characterisation of the heat transfer properties close to the transition from conductive to convective states, where it is well known that a homogeneous Newtonian system exhibits a steady flow and a time-independent heat flux.

A full ODE model for the transmission of cholera is investigated, includ- ing both direct and indirect transmission and a nonlinear growth for pathogens. The direct problem is preliminarily studied and characterized in terms of reproduction number, endemic and disease free equilibria. The inverse problem is then discussed in view of parameter estimation and model identification via a Least Squares Approximation approach. The procedure is applied to real data coming from the recent Yemen cholera outbreak of 2017-2018.

Starting from recent experimental observations of starlings and jackdaws, we propose a minimal agent-based mathematical model for bird flocks based on a system of second-order delayed stochastic differential equations with discontinuous (both in space and time) right-hand side. The model is specifically designed to reproduce self-organized spontaneous sudden changes of direction, not caused by external stimuli like predator's attacks. The main novelty of the model is that every bird is a potential turn initiator, thus leadership is formed in a group of indistinguishable agents.

In this paper we establish the boundedness and the higher differentiability of solutions to the {div(A(x,Du))+b(x)|u(x)|u(x)=fin ?u=0on ?? under a Sobolev assumption on the partial map x->A(x,?). The novelty here is that we deal with degenerate elliptic operator A(x,?) with p-growth, p>=2, with respect to the gradient variable, in presence of lower order terms. The interplay between b(x) and f(x), introduced in ([1]), gives a regularizing effect also in the degenerate elliptic setting.

We consider 2D discrete systems, described by scalar functions and governed by periodic interaction potentials. We focus on anisotropic nearest neighbors interactions in the hexagonal lattice and on isotropic long range interactions in the square lattice. In both these cases, we perform a complete Gamma-convergence analysis of the energy induced by a configuration of discrete topological singularities. This analysis allows to prove the existence of many metastable configurations of singularities in the hexagonal lattice.

Electrical source imaging (ESI) aims at reconstructing the electrical brain activity from measurements of the electric field on the scalp. ESI is a key element in the analysis of EEG data, in both research and clinical settings. In the last twenty years several algorithms have been applied for solving the ill- posed EEG inverse problem.