A nonlinear drift which leads to κ\kappa-generalized distributions

We consider a system described by a Fokker-Planck equation with a new type of momentum-dependent drift coefficient which asymptotically decreases as $-1/p$ for a large momentum $p$. It is shown that the steady-state of this system is a $\kappa$-generalized Gaussian distribution, which is a non-Gaussian distribution with a power-law tail.Comment: Submitted to EPJB. 8 pages, 2 figures, dedicated to the proceedings of APFA

Dynamic stereo microscopy for studying particle sedimentation

We demonstrate a new method for measuring the sedimentation of a single colloidal bead by using a combination of optical tweezers and a stereo microscope based on a spatial light modulator. We use optical tweezers to raise a micron-sized silica bead to a fixed height and then release it to observe its 3D motion while it sediments under gravity. This experimental procedure provides two independent measurements of bead diameter and a measure of Faxén’s correction, where the motion changes due to presence of the boundary

Structure preserving schemes for mean-field equations of collective behavior

In this paper we consider the development of numerical schemes for mean-field equations describing the collective behavior of a large group of interacting agents. The schemes are based on a generalization of the classical Chang-Cooper approach and are capable to preserve the main structural properties of the systems, namely nonnegativity of the solution, physical conservation laws, entropy dissipation and stationary solutions. In particular, the methods here derived are second order accurate in transient regimes whereas they can reach arbitrary accuracy asymptotically for large times. Several examples are reported to show the generality of the approach.Comment: Proceedings of the XVI International Conference on Hyperbolic Problem

Superior efficacy of a human immunodeficiency virus vaccine combined with antiretroviral prevention in simian-human immunodeficiency virus-challenged nonhuman primates

International audienc

Correlation functions quantify super-resolution images and estimate apparent clustering due to over-counting

We present an analytical method to quantify clustering in super-resolution localization images of static surfaces in two dimensions. The method also describes how over-counting of labeled molecules contributes to apparent self-clustering and how the effective lateral resolution of an image can be determined. This treatment applies to clustering of proteins and lipids in membranes, where there is significant interest in using super-resolution localization techniques to probe membrane heterogeneity. When images are quantified using pair correlation functions, the magnitude of apparent clustering due to over-counting will vary inversely with the surface density of labeled molecules and does not depend on the number of times an average molecule is counted. Over-counting does not yield apparent co-clustering in double label experiments when pair cross-correlation functions are measured. We apply our analytical method to quantify the distribution of the IgE receptor (Fc{\epsilon}RI) on the plasma membranes of chemically fixed RBL-2H3 mast cells from images acquired using stochastic optical reconstruction microscopy (STORM) and scanning electron microscopy (SEM). We find that apparent clustering of labeled IgE bound to Fc{\epsilon}RI detected with both methods arises from over-counting of individual complexes. Thus our results indicate that these receptors are randomly distributed within the resolution and sensitivity limits of these experiments.Comment: 22 pages, 5 figure

A Lagrangian scheme for the solution of nonlinear diffusion equations using moving simplex meshes

A Lagrangian numerical scheme for solving nonlinear degenerate Fokker{Planck equations in space dimensions d>2 is presented. It applies to a large class of nonlinear diffusion equations, whose dynamics are driven by internal energies and given external potentials, e.g. the porous medium equation and the fast diffusion equation. The key ingredient in our approach is the gradient ow structure of the dynamics. For discretization of the Lagrangian map, we use a finite subspace of linear maps in space and a variational form of the implicit Euler method in time. Thanks to that time discretisation, the fully discrete solution inherits energy estimates from the original gradient ow, and these lead to weak compactness of the trajectories in the continuous limit. Consistency is analyzed in the planar situation, d = 2. A variety of numerical experiments for the porous medium equation indicates that the scheme is well-adapted to track the growth of the solution's support

ADI splitting schemes for a fourth-order nonlinear partial differential equation from image processing

We present directional operator splitting schemes for the numerical solution of a fourth-order, nonlinear partial differential evolution equation which arises in image processing. This equation constitutes the H−1-gradient flow of the total variation and represents a prototype of higher-order equations of similar type which are popular in imaging for denoising, deblurring and inpainting problems. The efficient numerical solution of this equation is very challenging due to the stiffness of most numerical schemes. We show that the combination of directional splitting schemes with implicit time-stepping provides a stable and computationally cheap numerical realisation of the equation

DC-SCRIPT is a novel regulator of the tumor suppressor gene CDKN2B and induces cell cycle arrest in ERα-positive breast cancer cells

Breast cancer is one of the most common causes of cancer-related deaths in women. The estrogen receptor (ERα) is well known for having growth promoting effects in breast cancer. Recently, we have identified DC-SCRIPT (ZNF366) as a co-suppressor of ERα and as a strong and independent prognostic marker in ESR1 (ERα gene)-positive breast cancer patients. In this study, we further investigated the molecular mechanism on how DC-SCRIPT inhibits breast cancer cell growth. DC-SCRIPT mRNA levels from 190 primary ESR1-positive breast tumors were related to global gene expression, followed by gene ontology and pathway analysis. The effect of DC-SCRIPT on breast cancer cell growth and cell cycle arrest was investigated using novel DC-SCRIPT-inducible MCF7 breast cancer cell lines. Genome-wide expression profiling of DC-SCRIPT-expressing MCF7 cells was performed to investigate the effect of DC-SCRIPT on cell cycle-related gene expression. Findings were validated by real-time PCR in a cohort of 1,132 ESR1-positive breast cancer patients. In the primary ESR1-positive breast tumors, DC-SCRIPT expression negatively correlated with several cell cycle gene ontologies and pathways. DC-SCRIPT expression strongly reduced breast cancer cell growth in vitro, breast tumor growth in vivo, and induced cell cycle arrest. In addition, in the presence of DC-SCRIPT, multiple cell cycles related genes were differentially expressed including the tumor suppressor gene CDKN2B. Moreover, in 1,132 primary ESR1-positive breast tumors, DC-SCRIPT expression also correlated with CDKN2B expression. Collectively, these data show that DC-SCRIPT acts as a novel regulator of CDKN2B and induces cell cycle arrest in ESR1-positive breast cancer cells