Astronomy: Starbursts near and far

Observations of intensely bright star-forming galaxies both close by and in the distant Universe at first glance seem to emphasize their similarity. But look a little closer, and differences emerge.Comment: 6 pages including 1 figur

Polymer Dynamics in Block Copolymer Electrolytes Detected by Neutron Spin Echo

Polymer chain dynamics of a nanostructured block copolymer electrolyte, polystyrene-block-poly(ethylene oxide) (SEO) mixed with lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) salt, are investigated by neutron spin echo (NSE) spectroscopy on the 0.1-100 ns time scale and analyzed using the Rouse model at short times (t ≤ 10 ns) and the reptation tube model at long times (t ≥ 50 ns). In the Rouse regime, the monomeric friction coefficient increases with increasing salt concentration, as seen previously in homopolymer electrolytes. In the reptation regime, the tube diameters, which represent entanglement constraints, decrease with increasing salt concentration. The normalized longest molecular relaxation time, calculated from the NSE results, increases with increasing salt concentration. We argue that quantifying chain motion in the presence of ions is essential for predicting the behavior of polymer-electrolyte-based batteries operating at large currents

Ori-Finder: A web-based system for finding oriCs in unannotated bacterial genomes

<p>Abstract</p> <p>Background</p> <p>Chromosomal replication is the central event in the bacterial cell cycle. Identification of replication origins (<it>oriC</it>s) is necessary for almost all newly sequenced bacterial genomes. Given the increasing pace of genome sequencing, the current available software for predicting <it>oriC</it>s, however, still leaves much to be desired. Therefore, the increasing availability of genome sequences calls for improved software to identify <it>oriC</it>s in newly sequenced and unannotated bacterial genomes.</p> <p>Results</p> <p>We have developed Ori-Finder, an online system for finding <it>oriC</it>s in bacterial genomes based on an integrated method comprising the analysis of base composition asymmetry using the <it>Z</it>-curve method, distribution of DnaA boxes, and the occurrence of genes frequently close to <it>oriC</it>s. The program can also deal with unannotated genome sequences by integrating the gene-finding program ZCURVE 1.02. Output of the predicted results is exported to an HTML report, which offers convenient views on the results in both graphical and tabular formats.</p> <p>Conclusion</p> <p>A web-based system to predict replication origins of bacterial genomes has been presented here. Based on this system, <it>oriC </it>regions have been predicted for the bacterial genomes available in GenBank currently. It is hoped that Ori-Finder will become a useful tool for the identification and analysis of <it>oriC</it>s in both bacterial and archaeal genomes.</p

From Nonspecific DNA–Protein Encounter Complexes to the Prediction of DNA–Protein Interactions

©2009 Gao, Skolnick. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.doi:10.1371/journal.pcbi.1000341DNA–protein interactions are involved in many essential biological activities. Because there is no simple mapping code between DNA base pairs and protein amino acids, the prediction of DNA–protein interactions is a challenging problem. Here, we present a novel computational approach for predicting DNA-binding protein residues and DNA–protein interaction modes without knowing its specific DNA target sequence. Given the structure of a DNA-binding protein, the method first generates an ensemble of complex structures obtained by rigid-body docking with a nonspecific canonical B-DNA. Representative models are subsequently selected through clustering and ranking by their DNA–protein interfacial energy. Analysis of these encounter complex models suggests that the recognition sites for specific DNA binding are usually favorable interaction sites for the nonspecific DNA probe and that nonspecific DNA–protein interaction modes exhibit some similarity to specific DNA–protein binding modes. Although the method requires as input the knowledge that the protein binds DNA, in benchmark tests, it achieves better performance in identifying DNA-binding sites than three previously established methods, which are based on sophisticated machine-learning techniques. We further apply our method to protein structures predicted through modeling and demonstrate that our method performs satisfactorily on protein models whose root-mean-square Ca deviation from native is up to 5 Å from their native structures. This study provides valuable structural insights into how a specific DNA-binding protein interacts with a nonspecific DNA sequence. The similarity between the specific DNA–protein interaction mode and nonspecific interaction modes may reflect an important sampling step in search of its specific DNA targets by a DNA-binding protein

A direct physical interaction between Nanog and Sox2 regulates embryonic stem cell self-renewal

Embryonic stem (ES) cell self-renewal efficiency is determined by the Nanog protein level. However, the protein partners of Nanog that function to direct self-renewal are unclear. Here, we identify a Nanog interactome of over 130 proteins including transcription factors, chromatin modifying complexes, phosphorylation and ubiquitination enzymes, basal transcriptional machinery members, and RNA processing factors. Sox2 was identified as a robust interacting partner of Nanog. The purified Nanog–Sox2 complex identified a DNA recognition sequence present in multiple overlapping Nanog/Sox2 ChIP-Seq data sets. The Nanog tryptophan repeat region is necessary and sufficient for interaction with Sox2, with tryptophan residues required. In Sox2, tyrosine to alanine mutations within a triple-repeat motif (S X T/S Y) abrogates the Nanog–Sox2 interaction, alters expression of genes associated with the Nanog-Sox2 cognate sequence, and reduces the ability of Sox2 to rescue ES cell differentiation induced by endogenous Sox2 deletion. Substitution of the tyrosines with phenylalanine rescues both the Sox2–Nanog interaction and efficient self-renewal. These results suggest that aromatic stacking of Nanog tryptophans and Sox2 tyrosines mediates an interaction central to ES cell self-renewal

PKC Theta Ablation Improves Healing in a Mouse Model of Muscular Dystrophy

Inflammation is a key pathological characteristic of dystrophic muscle lesion formation, limiting muscle regeneration and resulting in fibrotic and fatty tissue replacement of muscle, which exacerbates the wasting process in dystrophic muscles. Limiting immune response is thus one of the therapeutic options to improve healing, as well as to improve the efficacy of gene- or cell-mediated strategies to restore dystrophin expression. Protein kinase C θ (PKCθ) is a member of the PKCs family highly expressed in both immune cells and skeletal muscle; given its crucial role in adaptive, but also innate, immunity, it is being proposed as a valuable pharmacological target for immune disorders. In our study we asked whether targeting PKCθ could represent a valuable approach to efficiently prevent inflammatory response and disease progression in a mouse model of muscular dystrophy. We generated the bi-genetic mouse model mdx/θ−/−, where PKCθ expression is lacking in mdx mice, the mouse model of Duchenne muscular dystrophy. We found that muscle wasting in mdx/θ−/− mice was greatly prevented, while muscle regeneration, maintenance and performance was significantly improved, as compared to mdx mice. This phenotype was associated to reduction in inflammatory infiltrate, pro-inflammatory gene expression and pro-fibrotic markers activity, as compared to mdx mice. Moreover, BM transplantation experiments demonstrated that the phenotype observed was primarily dependent on lack of PKCθ expression in hematopoietic cells

Characterization of novel microsatellite markers in Musa acuminata subsp. burmannicoides, var. Calcutta 4

<p>Abstract</p> <p>Background</p> <p>Banana is a nutritionally important crop across tropical and sub-tropical countries in sub-Saharan Africa, Central and South America and Asia. Although cultivars have evolved from diploid, triploid and tetraploid wild Asian species of <it>Musa acuminata </it>(A genome) and <it>Musa balbisiana </it>(B genome), many of today's commercial cultivars are sterile triploids or diploids, with fruit developing via parthenocarpy. As a result of restricted genetic variation, improvement has been limited, resulting in a crop frequently lacking resistance to pests and disease. Considering the importance of molecular tools to facilitate development of disease resistant genotypes, the objectives of this study were to develop polymorphic microsatellite markers from BAC clone sequences for <it>M. acuminata </it>subsp. <it>burmannicoides</it>, var. Calcutta 4. This wild diploid species is used as a donor cultivar in breeding programs as a source of resistance to diverse biotic stresses.</p> <p>Findings</p> <p>Microsatellite sequences were identified from five Calcutta 4 BAC consensi datasets. Specific primers were designed for 41 loci. Isolated di-nucleotide repeat motifs were the most abundant, followed by tri-nucleotides. From 33 tested loci, 20 displayed polymorphism when screened across 21 diploid <it>M. acuminata </it>accessions, contrasting in resistance to Sigatoka diseases. The number of alleles per SSR locus ranged from two to four, with a total of 56. Six repeat classes were identified, with di-nucleotides the most abundant. Expected heterozygosity values for polymorphic markers ranged from 0.31 to 0.75.</p> <p>Conclusions</p> <p>This is the first report identifying polymorphic microsatellite markers from <it>M. acuminata </it>subsp. <it>burmannicoides</it>, var. Calcutta 4 across accessions contrasting in resistance to Sigatoka diseases. These BAC-derived polymorphic microsatellite markers are a useful resource for banana, applicable for genetic map development, germplasm characterization, evolutionary studies and marker assisted selection for traits.</p

Cellular Radiosensitivity: How much better do we understand it?

Purpose: Ionizing radiation exposure gives rise to a variety of lesions in DNA that result in genetic instability and potentially tumorigenesis or cell death. Radiation extends its effects on DNA by direct interaction or by radiolysis of H2O that generates free radicals or aqueous electrons capable of interacting with and causing indirect damage to DNA. While the various lesions arising in DNA after radiation exposure can contribute to the mutagenising effects of this agent, the potentially most damaging lesion is the DNA double strand break (DSB) that contributes to genome instability and/or cell death. Thus in many cases failure to recognise and/or repair this lesion determines the radiosensitivity status of the cell. DNA repair mechanisms including homologous recombination (HR) and non-homologous end-joining (NHEJ) have evolved to protect cells against DNA DSB. Mutations in proteins that constitute these repair pathways are characterised by radiosensitivity and genome instability. Defects in a number of these proteins also give rise to genetic disorders that feature not only genetic instability but also immunodeficiency, cancer predisposition, neurodegeneration and other pathologies. Conclusions: In the past fifty years our understanding of the cellular response to radiation damage has advanced enormously with insight being gained from a wide range of approaches extending from more basic early studies to the sophisticated approaches used today. In this review we discuss our current understanding of the impact of radiation on the cell and the organism gained from the array of past and present studies and attempt to provide an explanation for what it is that determines the response to radiation

Digital payments adoption research: A meta-analysis for generalising the effects of attitude, cost, innovativeness, mobility and price value on behavioural intention

yesThe rapid evolution of mobile-based technologies and applications has led to the development of several different forms of digital payment methods (DPMs) but with limited enthusiasm in consumers for adopting them. Hence, several academic studies have already been conducted to examine the role of various antecedents that determines consumers’ intention to adopt DPMs. The degree of effect and significance of several antecedents found to be inconsistent across different studies. This provided us a basis for undertaking a meta-analysis of existing research for estimating the cumulative effect of such antecedents. Therefore, this study aims to perform a meta-analysis of five antecedents (i.e. attitude, cost, mobility, price value and innovativeness) for confirming their overall influence on intentions to adopt DPMs. The results of this study suggest that the cumulative effect of four out of five antecedents found to be significant while influence of price value was found insignificant on behavioural intentions. The recommendations drawn from this research would help to decide if and when to use such antecedents for predicting consumer intention to adopt DPMs