University of Luxembourg

About: University of Luxembourg is a education organization based out in Luxembourg, Luxembourg. It is known for research contribution in the topics: Population & European union. The organization has 4744 authors who have published 22175 publications receiving 381824 citations.

DICKKOPF-4 is induced by TCF/β-catenin and upregulated in human colon cancer, promotes tumour cell invasion and angiogenesis and is repressed by 1α,25-dihydroxyvitamin D3

Abstract: Aberrant activation of the Wnt/β-catenin signaling pathway is a hallmark of colon cancer. We show that the Wnt antagonist DICKKOPF-4 (DKK-4) gene is repressed by 1α,25-dihydroxyvitamin D3 (1,25(OH)2D3) in human colon cancer cells. This effect correlated with the inhibition of the DKK-4 promoter. Chromatin immunoprecipitation assays revealed that 1,25(OH)2D3 induces early and transient binding of the vitamin D receptor (VDR) and the SMRT corepressor to the region adjacent to the transcription start site of DKK-4. Additionally, we demonstrate that the DKK-4 gene is a new downstream target of TCF/β-catenin. Remarkably, expression of DKK-4 messenger RNA (mRNA) was not detected in a series of 29 human normal (N) colon biopsies but expression was upregulated in all the matched tumour (T) tissues. An inverse correlation existed between the expression of DKK-4 and VDR RNA in the Ts. Ectopic DKK-4 expression increased the migration and invasion properties of colon cancer cells and conditioned media (CM) from DKK-4-expressing cells enhanced the capacity to migrate and form capillary-like tubules of human primary microvascular endothelial cells. In conclusion, DKK-4 is upregulated in colon cancer and is associated with the acquisition of malignant properties by neoplastic cells. DKK-4 downregulation is a novel effect of 1,25(OH)2D3 that may contribute to its anticancer action.

Magnetic small-angle neutron scattering

Abstract: Deutsche Forschungsgemeinschaft (Project No. BE 2464/10-3), the EU-FP7 project “NANOPYME” (310516), and the EU Horizon-2020 project “AMPHIBIAN” (720853). M. R. E. was supported by the U.S. Department of Energy, Office of Basic Energy Sciences, under Award No. DE-SC0005051. F. B. thanks Andreas Ulbricht for fruitful discussions over the many years. C. L. was funded by the U.S. Department of Energy through the University of Minnesota Center for Quantum Materials under DE-FG02-06ER46275 and DESC-0016371. S. D. acknowledges financial support from the German Research Foundation (DFG Emmy Noether Grant No. DI 1788/2-1).

Physical Layer Security in Multibeam Satellite Systems

Abstract: Security threats introduced due to the vulnerability of the transmission medium may hinder the proliferation of Ka band multibeam satellite systems for civil and military data applications. This paper sets the analytical framework and then studies physical layer security techniques for fixed legitimate receivers dispersed throughout multiple beams, each possibly surrounded by multiple (passive) eavesdroppers. The design objective is to minimize via transmit beamforming the costly total transmit power on board the satellite, while satisfying individual intended users' secrecy rate constraints. Assuming state-of-the-art satellite channel models, when perfect channel state information (CSI) about the eavesdroppers is available at the satellite, a partial zero-forcing approach is proposed for obtaining a low-complexity sub-optimal solution. For the optimal solution, an iterative algorithm combining semi-definite programming relaxation and the gradient-based method is devised by studying the convexity of the problem. Furthermore, the use of artificial noise as an additional degree-of-freedom for protection against eavesdroppers is explored. When only partial CSI about the eavesdroppers is available, we study the problem of minimizing the eavesdroppers' received signal to interference-plus-noise ratios. Simulation results demonstrate substantial performance improvements over existing approaches.

Non-covalent interactions across organic and biological subsets of chemical space: Physics-based potentials parametrized from machine learning

Abstract: Classical intermolecular potentials typically require an extensive parametrization procedure for any new compound considered. To do away with prior parametrization, we propose a combination of physics-based potentials with machine learning (ML), coined IPML, which is transferable across small neutral organic and biologically relevant molecules. ML models provide on-the-fly predictions for environment-dependent local atomic properties: electrostatic multipole coefficients (significant error reduction compared to previously reported), the population and decay rate of valence atomic densities, and polarizabilities across conformations and chemical compositions of H, C, N, and O atoms. These parameters enable accurate calculations of intermolecular contributions—electrostatics, charge penetration, repulsion, induction/polarization, and many-body dispersion. Unlike other potentials, this model is transferable in its ability to handle new molecules and conformations without explicit prior parametrization: All l...