Tissue biomarkers of breast cancer and their association with conventional pathologic features

Background:Tissue protein expression profiling has the potential to detect new biomarkers to improve breast cancer (BC) diagnosis, staging, and prognostication. This study aimed to identify tissue proteins that differentiate breast cancer tissue from healthy breast tissue using protein chip mass spectrometry and to examine associations with conventional pathological features.Methods:To develop a training model, 82 BC and 82 adjacent unaffected tissue (AT) samples were analysed on cation-exchange protein chips by time-of-flight mass spectrometry. For validation, 89 independent BC and AT sample pairs were analysed.Results:From the protein peaks that were differentially expressed between BC and AT by univariate analysis, binary logistic regression yielded two peaks that together classified BC and AT with a ROC area under the curve of 0.92. Two proteins, ubiquitin and S100P (in a novel truncated form), were identified by liquid chromatography/tandem mass spectrometry and validated by immunoblotting and reactive-surface protein chip immunocapture. The combined marker panel was positively associated with high histologic grade, larger tumour size, lymphovascular invasion, ER and PR positivity, and HER2 overexpression, suggesting that it may be associated with a HER2-enriched molecular subtype of breast cancer.Conclusion:This independently validated protein panel may be valuable in the classification and prognostication of breast cancer patients. © 2013 Cancer Research UK. All rights reserved

Diffractive Higgs Production by AdS Pomeron Fusion

The double diffractive Higgs production at central rapidity is formulated in terms of the fusion of two AdS gravitons/Pomerons first introduced by Brower, Polchinski, Strassler and Tan in elastic scattering. Here we propose a simple self-consistent holographic framework capable of providing phenomenologically compelling estimates of diffractive cross sections at the LHC. As in the traditional weak coupling approach, we anticipate that several phenomenological parameters must be tested and calibrated through factorization for a self-consistent description of other diffractive process such as total cross sections, deep inelastic scattering and heavy quark production in the central region.Comment: 53 pages, 8 figure

The solar eclipse and associated atmospheric variations observed in South Korea on 22 July 2009

A partial solar eclipse occurred in South Korea on 22 July 2009. It started at 09:30 a.m. and lasted until 12:14 LST with coverage of between 76.8% and 93.1% of the sun. The observed atmospheric effects of the eclipse are presented. It was found that from the onset of the eclipse, solar radiation was reduced by as much as 88.1 ∼ 89.9% at the present research centre. Also, during the eclipse, air temperature decreased slightly or remained almost unchanged. After the eclipse, however, it rose by 2.5 to 4.5°C at observed stations. Meanwhile, relative humidity increased and wind speeds were lowered by the eclipse. Ground-level ozone was observed to decrease during the event

Effects of Contact Network Models on Stochastic Epidemic Simulations

The importance of modeling the spread of epidemics through a population has led to the development of mathematical models for infectious disease propagation. A number of empirical studies have collected and analyzed data on contacts between individuals using a variety of sensors. Typically one uses such data to fit a probabilistic model of network contacts over which a disease may propagate. In this paper, we investigate the effects of different contact network models with varying levels of complexity on the outcomes of simulated epidemics using a stochastic Susceptible-Infectious-Recovered (SIR) model. We evaluate these network models on six datasets of contacts between people in a variety of settings. Our results demonstrate that the choice of network model can have a significant effect on how closely the outcomes of an epidemic simulation on a simulated network match the outcomes on the actual network constructed from the sensor data. In particular, preserving degrees of nodes appears to be much more important than preserving cluster structure for accurate epidemic simulations.Comment: To appear at International Conference on Social Informatics (SocInfo) 201

Structural subnetwork evolution across the life-span: rich-club, feeder, seeder

The impact of developmental and aging processes on brain connectivity and the connectome has been widely studied. Network theoretical measures and certain topological principles are computed from the entire brain, however there is a need to separate and understand the underlying subnetworks which contribute towards these observed holistic connectomic alterations. One organizational principle is the rich-club - a core subnetwork of brain regions that are strongly connected, forming a high-cost, high-capacity backbone that is critical for effective communication in the network. Investigations primarily focus on its alterations with disease and age. Here, we present a systematic analysis of not only the rich-club, but also other subnetworks derived from this backbone - namely feeder and seeder subnetworks. Our analysis is applied to structural connectomes in a normal cohort from a large, publicly available lifespan study. We demonstrate changes in rich-club membership with age alongside a shift in importance from 'peripheral' seeder to feeder subnetworks. Our results show a refinement within the rich-club structure (increase in transitivity and betweenness centrality), as well as increased efficiency in the feeder subnetwork and decreased measures of network integration and segregation in the seeder subnetwork. These results demonstrate the different developmental patterns when analyzing the connectome stratified according to its rich-club and the potential of utilizing this subnetwork analysis to reveal the evolution of brain architectural alterations across the life-span

Bino Dark Matter and Big Bang Nucleosynthesis in the Constrained E6SSM with Massless Inert Singlinos

We discuss a new variant of the E6 inspired supersymmetric standard model (E6SSM) in which the two inert singlinos are exactly massless and the dark matter candidate has a dominant bino component. A successful relic density is achieved via a novel mechanism in which the bino scatters inelastically into heavier inert Higgsinos during the time of thermal freeze-out. The two massless inert singlinos contribute to the effective number of neutrino species at the time of Big Bang Nucleosynthesis, where the precise contribution depends on the mass of the Z' which keeps them in equilibrium. For example for mZ' > 1300 GeV we find Neff \approx 3.2, where the smallness of the additional contribution is due to entropy dilution. We study a few benchmark points in the constrained E6SSM with massless inert singlinos to illustrate this new scenario.Comment: 24 pages, revised for publication in JHE

TiArA: A Virtual Appliance for the Analysis of Tiling Array Data

Genomic tiling arrays have been described in the scientific literature since 2003, yet there is a shortage of user-friendly applications available for their analysis.Tiling Array Analyzer (TiArA) is a software program that provides a user-friendly graphical interface for the background subtraction, normalization, and summarization of data acquired through the Affymetrix tiling array platform. The background signal is empirically measured using a group of nonspecific probes with varying levels of GC content and normalization is performed to enforce a common dynamic range.TiArA is implemented as a standalone program for Linux systems and is available as a cross-platform virtual machine that will run under most modern operating systems using virtualization software such as Sun VirtualBox or VMware. The software is available as a Debian package or a virtual appliance at http://purl.org/NET/tiara

Occult hepatitis B virus infection: diagnosis, implications and management?

Occult hepatitis B virus (HBV) infection is generally defined as the detection of HBV-DNA in the serum or liver tissue of patients who test negative for hepatitis B surface antigen. In most cases, occult HBV infection is related to low level HBV infection with subdetectable levels of HBsAg and not infection with HBV variants that cannot express S proteins or produce S proteins with aberrant epitopes that are not detected by conventional serological assays. Prevalence of occult HBV infection is related to the overall prevalence of HBV infection in that country, being more common in persons with prior exposure to HBV. Occult HBV infection has been found in a substantial proportion of patients with cirrhosis and hepatocellular carcinoma but other causes of liver disease are frequently present. Future studies should focus on delineating the pathogenic role of occult HBV infection and the basis for failure to detect circulating hepatitis B surface antigen.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75344/1/j.1440-1746.2004.03657.x.pd