Segmentation of the left ventricle of the heart in 3-D+t MRI data using an optimized nonrigid temporal model

Modern medical imaging modalities provide large amounts of information in both the spatial and temporal domains and the incorporation of this information in a coherent algorithmic framework is a significant challenge. In this paper, we present a novel and intuitive approach to combine 3-D spatial and temporal (3-D + time) magnetic resonance imaging (MRI) data in an integrated segmentation algorithm to extract the myocardium of the left ventricle. A novel level-set segmentation process is developed that simultaneously delineates and tracks the boundaries of the left ventricle muscle. By encoding prior knowledge about cardiac temporal evolution in a parametric framework, an expectation-maximization algorithm optimally tracks the myocardial deformation over the cardiac cycle. The expectation step deforms the level-set function while the maximization step updates the prior temporal model parameters to perform the segmentation in a nonrigid sense

A dynamic network model with persistent links and node-specific latent variables, with an application to the interbank market

We propose a dynamic network model where two mechanisms control the probability of a link between two nodes: (i) the existence or absence of this link in the past, and (ii) node-specific latent variables (dynamic fitnesses) describing the propensity of each node to create links. Assuming a Markov dynamics for both mechanisms, we propose an Expectation-Maximization algorithm for model estimation and inference of the latent variables. The estimated parameters and fitnesses can be used to forecast the presence of a link in the future. We apply our methodology to the e-MID interbank network for which the two linkage mechanisms are associated with two different trading behaviors in the process of network formation, namely preferential trading and trading driven by node-specific characteristics. The empirical results allow to recognise preferential lending in the interbank market and indicate how a method that does not account for time-varying network topologies tends to overestimate preferential linkage.Comment: 19 pages, 6 figure

The structure of Herpesvirus Fusion Glycoprotein B-Bilayer Complex reveals the protein-membrane and lateral protein-protein interaction

Glycoprotein B (gB) is a key component of the complex herpesvirus fusion machinery. We studied membrane interaction of two gB ectodomain forms and present an electron cryotomography structure of the gB-bilayer complex. The two forms differed in presence or absence of the membrane proximal region (MPR) but showed an overall similar trimeric shape. The presence of the MPR impeded interaction with liposomes. In contrast, the MPR-lacking form interacted efficiently with liposomes. Lateral interaction resulted in coat formation on the membranes. The structure revealed that interaction of gB with membranes was mediated by the fusion loops and limited to the outer membrane leaflet. The observed intrinsic propensity of gB to cluster on membranes indicates an additional role of gB in driving the fusion process forward beyond the transient fusion pore opening and subsequently leading to fusion pore expansion