X-rays from Colliding Stellar Winds: the case of close WR+O binary systems

We have analysed the X-ray emission from a sample of close WR+O binaries using data from the public Chandra and XMM-Newton archives. Global spectral fits show that two-temperature plasma is needed to match the X-ray emission from these objects as the hot component (kT > 2 keV) is an important ingredient of the spectral models. In close WR+O binaries, X-rays likely originate in colliding stellar wind (CSW) shocks driven by the massive winds of the binary components. CSW shocks in these objects are expected to be radiative due to the high density of the plasma in the interaction region. Opposite to this, our analysis shows that the CSW shocks in the sample of close WR+O binaries are adiabatic. This is possible only if the mass-loss rates of the stellar components in the binary are at least one order of magnitude smaller than the values currently accepted. The most likely explanation for the X-ray properties of close WR+O binaries could be that their winds are two-component flows. The more massive component (dense clumps) play role for the optical/UV emission from these objects, while the smooth rarefied component is a key factor for their X-ray emission.Comment: MNRAS, accepted for publication (Feb 6, 2012); 13 pages, 6 figures, 3 table

On the Suitability of Estelle for Multimedia Systems

Formal Description Techniques have been widely used for the specification of traditional networked applications. They have not been applied to the specification of new applications such as multimedia systems yet. In this paper, we examine the FDT Estelle with respect to its suitability for multimedia system specification and automatic derivation of efficient implementations. We show that it is possible to specify certain aspects of multimedia systems, but that Estelle is not sufficient for others. The derived implementations often perform badly. We show the reasons and propose to use a slightly modified Estelle syntax and semantics to solve the problems. The implemented solution was tested successfully

Distinguishing Asthma Phenotypes Using Machine Learning Approaches.

Asthma is not a single disease, but an umbrella term for a number of distinct diseases, each of which are caused by a distinct underlying pathophysiological mechanism. These discrete disease entities are often labelled as asthma endotypes. The discovery of different asthma subtypes has moved from subjective approaches in which putative phenotypes are assigned by experts to data-driven ones which incorporate machine learning. This review focuses on the methodological developments of one such machine learning technique-latent class analysis-and how it has contributed to distinguishing asthma and wheezing subtypes in childhood. It also gives a clinical perspective, presenting the findings of studies from the past 5 years that used this approach. The identification of true asthma endotypes may be a crucial step towards understanding their distinct pathophysiological mechanisms, which could ultimately lead to more precise prevention strategies, identification of novel therapeutic targets and the development of effective personalized therapies

Complete structure of the enterococcal polysaccharide antigen (EPA) of vancomycin-resistant enterococcus faecalis V583 reveals that EPA decorations are teichoic acids covalently linked to a rhamnopolysaccharide backbone

All enterococci produce a complex polysaccharide called the enterococcal polysaccharide antigen (EPA). This polymer is required for normal cell growth and division and for resistance to cephalosporins and plays a critical role in host-pathogen interaction. The EPA contributes to host colonization and is essential for virulence, conferring resistance to phagocytosis during the infection. Recent studies revealed that the “decorations” of the EPA polymer, encoded by genetic loci that are variable between isolates, underpin the biological activity of this surface polysaccharide. In this work, we investigated the structure of the EPA polymer produced by the high-risk enterococcal clonal complex Enterococcus faecalis V583. We analyzed purified EPA from the wild-type strain and a mutant lacking decorations and elucidated the structure of the EPA backbone and decorations. We showed that the rhamnan backbone of EPA is composed of a hexasaccharide repeat unit of C2- and C3-linked rhamnan chains, partially substituted in the C3 position by α-glucose (α-Glc) and in the C2 position by β-N-acetylglucosamine (β-GlcNAc). The so-called “EPA decorations” consist of phosphopolysaccharide chains corresponding to teichoic acids covalently bound to the rhamnan backbone. The elucidation of the complete EPA structure allowed us to propose a biosynthetic pathway, a first essential step toward the design of antimicrobials targeting the synthesis of this virulence factor

A survey of security issue in multi-agent systems

Multi-agent systems have attracted the attention of researchers because of agents' automatic, pro-active, and dynamic problem solving behaviors. Consequently, there has been a rapid development in agent technology which has enabled us to provide or receive useful and convenient services in a variety of areas such as banking, transportation, e-business, and healthcare. In many of these services, it is, however, necessary that security is guaranteed. Unless we guarantee the security services based on agent-based systems, these services will face significant deployment problems. In this paper, we survey existing work related to security in multi-agent systems, especially focused on access control and trust/reputation, and then present our analyses. We also present existing problems and discuss future research challenges. © Springer Science+Business Media B.V 2011

Analysis of early mesothelial cell responses to Staphylococcus epidermidis isolated from patients with peritoneal dialysis-associated peritonitis

The major complication of peritoneal dialysis (PD) is the development of peritonitis, an infection within the abdominal cavity, primarily caused by bacteria. PD peritonitis is associated with significant morbidity, mortality and health care costs. Staphylococcus epidermidis is the most frequently isolated cause of PD-associated peritonitis. Mesothelial cells are integral to the host response to peritonitis, and subsequent clinical outcomes, yet the effects of infection on mesothelial cells are not well characterised. We systematically investigated the early mesothelial cell response to clinical and reference isolates of S. epidermidis using primary mesothelial cells and the mesothelial cell line Met-5A. Using an unbiased whole genome microarray, followed by a targeted panel of genes known to be involved in the human antibacterial response, we identified 38 differentially regulated genes (adj. p-value < 0.05) representing 35 canonical pathways after 1 hour exposure to S. epidermidis. The top 3 canonical pathways were TNFR2 signaling, IL-17A signaling, and TNFR1 signaling (adj. pvalues of 0.0012, 0.0012 and 0.0019, respectively). Subsequent qPCR validation confirmed significant differences in gene expression in a number of genes not previously described in mesothelial cell responses to infection, with heterogeneity observed between clinical isolates of S. epidermidis, and between Met-5A and primary mesothelial cells. Heterogeneity between different S. epidermidis isolates suggests that specific virulence factors may play critical roles in influencing outcomes from peritonitis. This study provides new insights into early mesothelial cell responses to infection with S. epidermidis, and confirms the importance of validating findings in primary mesothelial cells