The Y-box factor ZONAB/DbpA associates with GEF-H1/Lfc and mediates Rho-stimulated transcription

Epithelial tight junctions recruit different types of signalling proteins that regulate cell proliferation and differentiation. Little is known about how such proteins interact functionally and biochemically with each other. Here, we focus on the Y-box transcription factor ZONAB (zonula occludens 1-associated nucleic-acid-binding protein)/DbpA (DNA-binding protein A) and the Rho GTPase activator guanine nucleotide exchange factor (GEF)-H1/Lbc's first cousin, which are two tight-junction-associated signalling proteins that regulate proliferation. Our data show that the two proteins interact and that ZONAB activity is Rho-dependent. Overexpression of GEF-H1 induces accumulation of ZONAB in the nucleus and activates transcription. Microtubule-affinity regulating kinase/partition-defective-1, another type of GEF-H1-associated signalling protein, remains in the cytoplasm and partially co-localizes with the exchange factor. GEF-H1 and ZONAB are required for expression of endogenous cyclin D1, a crucial RhoA signalling target gene, and GEF-H1-stimulated cyclin D1 promoter activity requires ZONAB. Our data thus indicate that GEF-H1 and ZONAB form a signalling module that mediates Rho-regulated cyclin D1 promoter activation and expression

Unsupervised Feature Selection with Adaptive Structure Learning

The problem of feature selection has raised considerable interests in the past decade. Traditional unsupervised methods select the features which can faithfully preserve the intrinsic structures of data, where the intrinsic structures are estimated using all the input features of data. However, the estimated intrinsic structures are unreliable/inaccurate when the redundant and noisy features are not removed. Therefore, we face a dilemma here: one need the true structures of data to identify the informative features, and one need the informative features to accurately estimate the true structures of data. To address this, we propose a unified learning framework which performs structure learning and feature selection simultaneously. The structures are adaptively learned from the results of feature selection, and the informative features are reselected to preserve the refined structures of data. By leveraging the interactions between these two essential tasks, we are able to capture accurate structures and select more informative features. Experimental results on many benchmark data sets demonstrate that the proposed method outperforms many state of the art unsupervised feature selection methods

Formation and observation of a quasi-two-dimensional dxyd_{xy} electron liquid in epitaxially stabilized Sr2−x_{2-x}Lax_{x}TiO4_{4} thin films

We report the formation and observation of an electron liquid in Sr$_{2-x}$La$_{x}$TiO$_4$, the quasi-two-dimensional counterpart of SrTiO$_3$, through reactive molecular-beam epitaxy and {\it in situ} angle-resolved photoemission spectroscopy. The lowest lying states are found to be comprised of Ti 3$d_{xy}$ orbitals, analogous to the LaAlO$_3$/SrTiO$_3$ interface and exhibit unusually broad features characterized by quantized energy levels and a reduced Luttinger volume. Using model calculations, we explain these characteristics through an interplay of disorder and electron-phonon coupling acting co-operatively at similar energy scales, which provides a possible mechanism for explaining the low free carrier concentrations observed at various oxide heterostructures such as the LaAlO$_3$/SrTiO$_3$ interface

Optical spectroscopy study of Nd(O,F)BiS2 single crystals

We present an optical spectroscopy study on F-substituted NdOBiS$_2$ superconducting single crystals grown using KCl/LiCl flux method. The measurement reveals a simple metallic response with a relatively low screened plasma edge near 5000 \cm. The plasma frequency is estimated to be 2.1 eV, which is much smaller than the value expected from the first-principles calculations for an electron doping level of x=0.5, but very close to the value based on a doping level of 7$\%$ of itinerant electrons per Bi site as determined by ARPES experiment. The energy scales of the interband transitions are also well reproduced by the first-principles calculations. The results suggest an absence of correlation effect in the compound, which essentially rules out the exotic pairing mechanism for superconductivity or scenario based on the strong electronic correlation effect. The study also reveals that the system is far from a CDW instability as being widely discussed for a doping level of x=0.5.Comment: 5 pages, 5 figure

Electrochemical Sensing and Characterization of Aerobic Marine Bacterial Biofilms on Gold Electrode Surfaces

Reliable and accurate in situ sensors capable of detecting and quantifying troublesome marine biofilms on metallic surfaces are increasingly necessary. A 0.2 mm diameter gold electrochemical sensor was fully characterized using cyclic voltammetry in abiotic and biotic artificial seawater media within a continuous culture flow cell to detect the growth and development of an aerobic Pseudoalteromonas sp. biofilm. Deconvolution of the abiotic and biotic responses enable the constituent extracellular electron transfer and biofilm responses to be resolved. Differentiation of enhanced oxygen reduction kinetics within the aerobic bacterial biofilm is linked to enzyme and redox mediator activities