Moment-based parameter estimation in binomial random intersection graph models

Binomial random intersection graphs can be used as parsimonious statistical models of large and sparse networks, with one parameter for the average degree and another for transitivity, the tendency of neighbours of a node to be connected. This paper discusses the estimation of these parameters from a single observed instance of the graph, using moment estimators based on observed degrees and frequencies of 2-stars and triangles. The observed data set is assumed to be a subgraph induced by a set of $n_0$ nodes sampled from the full set of $n$ nodes. We prove the consistency of the proposed estimators by showing that the relative estimation error is small with high probability for $n_0 \gg n^{2/3} \gg 1$. As a byproduct, our analysis confirms that the empirical transitivity coefficient of the graph is with high probability close to the theoretical clustering coefficient of the model.Comment: 15 pages, 6 figure

Drifters, Party Boys and Incumbents: The Life Patterns of Male Street-based Sex Workers

This paper is based on a qualitative study of male street-based prostitution. It suggests that the street-based sector is more varied, with sellers adopting a wider range of working practices, than is commonly acknowledged in the literature on male prostitution. Drawing on data from Manchester, England I identify a number of ‘life patterns’ among male street sellers that reflect varied working practices based on issues around rational decision-making and the sex worker’s relationship to place and environment. The discussion has implications for urban policies around street-based sex work but also for a more general understanding of male sex work in international and comparative perspective

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Th17 cells are more protective than Th1 cells against the intracellular parasite Trypanosoma cruzi

Th17 cells are a subset of CD4+ T cells known to play a central role in the pathogenesis of many autoimmune diseases, as well as in the defense against some extracellular bacteria and fungi. However, Th17 cells are not believed to have a significant function against intracellular infections. In contrast to this paradigm, we have discovered that Th17 cells provide robust protection against Trypanosoma cruzi, the intracellular protozoan parasite that causes Chagas disease. Th17 cells confer significantly stronger protection against T. cruzi-related mortality than even Th1 cells, traditionally thought to be the CD4+ T cell subset most important for immunity to T. cruzi and other intracellular microorganisms. Mechanistically, Th17 cells can directly protect infected cells through the IL-17A-dependent induction of NADPH oxidase, involved in the phagocyte respiratory burst response, and provide indirect help through IL-21-dependent activation of CD8+ T cells. The discovery of these novel Th17 cell-mediated direct protective and indirect helper effects important for intracellular immunity highlights the diversity of Th17 cell roles, and increases understanding of protective T. cruzi immunity, aiding the development of therapeutics and vaccines for Chagas disease

NETIMIS: Dynamic Simulation of Health Economics Outcomes Using Big Data

Many healthcare organizations are now making good use of electronic health record (EHR) systems to record clinical information about their patients and the details of their healthcare. Electronic data in EHRs is generated by people engaged in complex processes within complex environments, and their human input, albeit shaped by computer systems, is compromised by many human factors. These data are potentially valuable to health economists and outcomes researchers but are sufficiently large and complex enough to be considered part of the new frontier of ‘big data’. This paper describes emerging methods that draw together data mining, process modelling, activity-based costing and dynamic simulation models. Our research infrastructure includes safe links to Leeds hospital’s EHRs with 3 million secondary and tertiary care patients. We created a multidisciplinary team of health economists, clinical specialists, and data and computer scientists, and developed a dynamic simulation tool called NETIMIS (Network Tools for Intervention Modelling with Intelligent Simulation; http://www.netimis.com) suitable for visualization of both human-designed and data-mined processes which can then be used for ‘what-if’ analysis by stakeholders interested in costing, designing and evaluating healthcare interventions. We present two examples of model development to illustrate how dynamic simulation can be informed by big data from an EHR. We found the tool provided a focal point for multidisciplinary team work to help them iteratively and collaboratively ‘deep dive’ into big data

27 years of benthic and coral community dynamics on turbid, highly urbanised reefs off Singapore

Coral cover on reefs is declining globally due to coastal development, overfishing and climate change. Reefs isolated from direct human influence can recover from natural acute disturbances, but little is known about long term recovery of reefs experiencing chronic human disturbances. Here we investigate responses to acute bleaching disturbances on turbid reefs off Singapore, at two depths over a period of 27 years. Coral cover declined and there were marked changes in coral and benthic community structure during the first decade of monitoring at both depths. At shallower reef crest sites (3–4 m), benthic community structure recovered towards pre-disturbance states within a decade. In contrast, there was a net decline in coral cover and continuing shifts in community structure at deeper reef slope sites (6–7 m). There was no evidence of phase shifts to macroalgal dominance but coral habitats at deeper sites were replaced by unstable substrata such as fine sediments and rubble. The persistence of coral dominance at chronically disturbed shallow sites is likely due to an abundance of coral taxa which are tolerant to environmental stress. In addition, high turbidity may interact antagonistically with other disturbances to reduce the impact of thermal stress and limit macroalgal growth rates

Robust tests for time-invariant individual heterogeneity versus dynamic state dependence

We derive tests for persistent effects in a general linear dynamic panel data context. Two sources of persistent behavior are considered: time-invariant unobserved factors (captured by an individual random effect) and dynamic persistence or “state dependence” (captured by autoregressive behavior). We will use a maximum likelihood framework to derive a family of tests that help researchers learn whether persistence is due to individual heterogeneity, dynamic effect, or both. The proposed tests have power only in the direction they are designed to perform, that is, they are locally robust to the presence of alternative sources of persistence, and consequently, are able to identify which source of persistence is active. A Monte Carlo experiment is implemented to explore the finite sample performance of the proposed procedures. The tests are applied to a panel data series of real GDP growth for the period 1960–2005

Peripheral blood T-cell signatures from high-resolution immune phenotyping of γδ and αβ T-cells in younger and older subjects in the Berlin Aging Study II

Background Aging and latent infection with Cytomegalovirus (CMV) are thought to be major factors driving the immune system towards immunosenescence, primarily characterized by reduced amounts of naïve T-cells and increased memory T-cells, potentially associated with higher morbidity and mortality. The composition of both major compartments, γδ as well as αβ T-cells, is altered by age and CMV, but detailed knowledge of changes to the γδ subset is currently limited. Results Here, we have surveyed a population of 73 younger (23–35 years) and 144 older (62–85 years) individuals drawn from the Berlin Aging Study II, investigating the distribution of detailed differentiation phenotypes of both γδ and αβ T-cells. Correlation of frequencies and absolute counts of the identified phenotypes with age and the presence of CMV revealed a lower abundance of Vδ2-positive and a higher amount of Vδ1-positive cells. We found higher frequencies of late-differentiated and lower frequencies of early-differentiated cells in the Vδ1+ and Vδ1-Vδ2-, but not in the Vδ2+ populations in elderly CMV-seropositive individuals confirming the association of these Vδ2-negative cells with CMV-immunosurveillance. We identified the highest Vδ1:Vδ2 ratios in the CMV-seropositive elderly. The observed increased CD4:CD8 ratios in the elderly were significantly lower in CMV-seropositive individuals, who also possessed a lower naïve and a larger late-differentiated compartment of CD8+ αβ T-cells, reflecting the consensus in the literature. Conclusions Our findings illustrate in detail the strong influence of CMV on the abundance and differentiation pattern of γδ T-cells as well as αβ T-cells in older and younger people. Mechanisms responsible for the phenotypic alterations in the γδ T-cell compartment, associated both with the presence of CMV and with age require further clarification

Silibinin induces mitochondrial NOX4-mediated endoplasmic reticulum stress response and its subsequent apoptosis

Background: Silibinin, a biologically active compound of milk thistle, has chemopreventive effects on cancer cell lines. Recently it was reported that silibinin inhibited tumor growth through activation of the apoptotic signaling pathway. Although various evidences showed multiple signaling pathways of silibinin in apoptosis, there were no reports to address the clear mechanism of ROS-mediated pathway in prostate cancer PC-3 cells. Several studies suggested that reactive oxygen species (ROS) play an important role in various signaling cascades, but the primary source of ROS was currently unclear. Methods: The effect of silibinin was investigated on cell growth of prostate cell lines by MTT assay. We examined whether silibinin induced apoptosis through production of ROS using flow cytometry. Expression of apoptosis-, endoplasmic reticulum (ER)-related protein and gene were determined by western blotting and RT-PCR, respectively. Results: Results showed that silibinin triggered mitochondrial ROS production through NOX4 expression and finally led to induce apoptosis. In addition, mitochondrial ROS caused ER stress through disruption of Ca2+ homeostasis. Co-treatment of ROS inhibitor reduced the silibinin-induced apoptosis through the inhibition of NOX4 expression, resulting in reduction of both Ca2+ level and ER stress response. Conclusions: Taken together, silibinin induced mitochondrial ROS-dependent apoptosis through NOX4, which is associated with disruption of Ca2+ homeostasis and ER stress response. Therefore, the regulation of NOX4, mitochondrial ROS producer, could be a potential target for the treatment of prostate cancer.ope

Zanamivir Conjugated to Poly-L-Glutamine is Much More Active Against Influenza Viruses in Mice and Ferrets Than the Drug Itself

Purpose: Previously, polymer-attached zanamivir had been found to inhibit influenza A viruses in vitro far better than did small-molecule zanamivir (1) itself. The aim of this study was to identify in vitro—using the plaque reduction assay—a highly potent 1-polymer conjugate, and subsequently test its antiviral efficacy in vivo. Methods: By examining the structure-activity relationship of 1-polymer conjugates in the plaque assay, we have determined that the most potent inhibitor against several representative influenza virus strains has a neutral high-molecular-weight backbone and a short alkyl linker. We have examined this optimal polymeric inhibitor for efficacy and immunogenicity in the mouse and ferret models of infection. Results: 1 attached to poly-L-glutamine is an effective therapeutic for established influenza infection in ferrets, reducing viral titers up to 30-fold for 6 days. There is also up to a 190-fold reduction in viral load when the drug is used as a combined prophylactic/therapeutic in mice. Additionally, we see no evidence that the drug conjugate stimulates an immune response in mice upon repeat administration. Conclusions: 1 attached to a neutral high-molecular-weight backbone through a short alkyl linker drastically reduced both in vitro and in vivo titers compared to those observed with 1 itself. Thus, further development of this polymeric zanamivir for the mitigation of influenza infection seems warranted.National Institutes of Health (U.S.) (Grant U01-AI074443