A Photometric Study of Five Open Clusters in the SDSS

We present a photometric study of five open clusters (Czernik 5, Alessi 53, Berkeley 49, Berkeley 84, and Pfleiderer 3) in the Sloan Digital Sky Survey. The position and size of these clusters are determined using the radial number density profiles of the stars, and the member stars of the clusters are selected using the proper motion data in the literature. We estimate the reddening, distance, and age of the clusters based on the isochrone fitting in the color-magnitude diagram. The foreground reddenings for these clusters are estimated to be E(B-V) = 0.71 - 1.55 mag. The distances to these clusters are derived to be 2.0 - 4.4 kpc, and their distances from the Galactic center range from 7.57 kpc to 12.35 kpc. Their ages are in the range from 250 Myr to 1 Gyr. Berkeley 49 and Berkeley 84 are located in the Orion spur, Czernik 5 is in the Perseus arm, and Pfleiderer 3 and Alessi 53 are at beyond the Perseus arm.Comment: 18 pages, 21 figures, accepted for publication in JKA

Mg2+ Effect on Argonaute and RNA Duplex by Molecular Dynamics and Bioinformatics Implications

RNA interference (RNAi), mediated by small non-coding RNAs (e.g., miRNAs, siRNAs), influences diverse cellular functions. Highly complementary miRNA-target RNA (or siRNA-target RNA) duplexes are recognized by an Argonaute family protein (Ago2), and recent observations indicate that the concentration of Mg2+ ions influences miRNA targeting of specific mRNAs, thereby modulating miRNA-mRNA networks. In the present report, we studied the thermodynamic effects of differential [Mg2+] on slicing (RNA silencing cycle) through molecular dynamics simulation analysis, and its subsequent statistical analysis. Those analyses revealed different structural conformations of the RNA duplex in Ago2, depending on Mg2+ concentration. We also demonstrate that cation effects on Ago2 structural flexibility are critical to its catalytic/functional activity, with low [Mg2+] favoring greater Ago2 flexibility (e.g., greater entropy) and less miRNA/mRNA duplex stability, thus favoring slicing. The latter finding was supported by a negative correlation between expression of an Mg2+ influx channel, TRPM7, and one miRNA’s (miR-378) ability to downregulate its mRNA target, TMEM245. These results imply that thermodynamics could be applied to siRNA-based therapeutic strategies, using highly complementary binding targets, because Ago2 is also involved in RNAi slicing by exogenous siRNAs. However, the efficacy of a siRNA-based approach will differ, to some extent, based on the Mg2+ concentration even within the same disease type; therefore, different siRNA-based approaches might be considered for patient-to-patient needs

Bacterial Uracil Modulates Drosophila DUOX-Dependent Gut Immunity via Hedgehog-Induced Signaling Endosomes

SummaryGenetic studies in Drosophila have demonstrated that generation of microbicidal reactive oxygen species (ROS) through the NADPH dual oxidase (DUOX) is a first line of defense in the gut epithelia. Bacterial uracil acts as DUOX-activating ligand through poorly understood mechanisms. Here, we show that the Hedgehog (Hh) signaling pathway modulates uracil-induced DUOX activation. Uracil-induced Hh signaling is required for intestinal expression of the calcium-dependent cell adhesion molecule Cadherin 99C (Cad99C) and subsequent Cad99C-dependent formation of endosomes. These endosomes play essential roles in uracil-induced ROS production by acting as signaling platforms for PLCβ/PKC/Ca2+-dependent DUOX activation. Animals with impaired Hh signaling exhibit abolished Cad99C-dependent endosome formation and reduced DUOX activity, resulting in high mortality during enteric infection. Importantly, endosome formation, DUOX activation, and normal host survival are restored by genetic reintroduction of Cad99C into enterocytes, demonstrating the important role for Hh signaling in host resistance to enteric infection

Solvent-solid hybrid additive: simultaneous control of macro and micromorphology of bulk heterojunction organic solar cells

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Hyper stress induced charge generation in nano sized BaTiO3 particles below critical ferroelectric particle size

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Protein NMR Structures Refined without NOE Data

<div><p>The refinement of low-quality structures is an important challenge in protein structure prediction. Many studies have been conducted on protein structure refinement; the refinement of structures derived from NMR spectroscopy has been especially intensively studied. In this study, we generated flat-bottom distance potential instead of NOE data because NOE data have ambiguity and uncertainty. The potential was derived from distance information from given structures and prevented structural dislocation during the refinement process. A simulated annealing protocol was used to minimize the potential energy of the structure. The protocol was tested on 134 NMR structures in the Protein Data Bank (PDB) that also have X-ray structures. Among them, 50 structures were used as a training set to find the optimal “width” parameter in the flat-bottom distance potential functions. In the validation set (the other 84 structures), most of the 12 quality assessment scores of the refined structures were significantly improved (total score increased from 1.215 to 2.044). Moreover, the secondary structure similarity of the refined structure was improved over that of the original structure. Finally, we demonstrate that the combination of two energy potentials, statistical torsion angle potential (STAP) and the flat-bottom distance potential, can drive the refinement of NMR structures.</p></div

Comparison between our refinement and the re-refinement structures^a^,^b.

a<p> See the footnotes in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0108888#pone-0108888-t001" target="_blank">Table 1</a>.</p>b<p> A total of 24 NMR structures were used (lists are in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0108888#pone.0108888.s011" target="_blank">Table S9</a>). Because no corresponding X-ray structures exist, the TM-score cannot be measured.</p><p>Comparison between our refinement and the re-refinement structures^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0108888#nt108" target="_blank">a</a>}^,^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0108888#nt109" target="_blank">b</a>}.</p