Differentiation of the emerging human pathogens Trichosporon asahii and Trichosporon asteroides from other pathogenic yeasts and moulds by using species-specific monoclonal antibodies

This is the final version of the article. Available from the publisher via the DOI in this record.The fungal genus Trichosporon contains emerging opportunistic pathogens of humans, and is the third most commonly isolated non-candidal yeast from humans. Trichosporon asahii and T. asteroides are the most important species causing disseminated disease in immunocompromised patients, while inhalation of T. asahii spores is the most important cause of summer-type hypersensitivity pneumonitis in healthy individuals. Trichosporonosis is misdiagnosed as candidiasis or cryptococcosis due to a lack of awareness and the ambiguity of diagnostic tests for these pathogens. In this study, hybridoma technology was used to produce two murine monoclonal antibodies (MAbs), CA7 and TH1, for detection and differentiation of Trichosporon from other human pathogenic yeasts and moulds. The MAbs react with extracellular antigens from T. asahii and T. asteroides, but do not recognise other related Trichosporon spp., or unrelated pathogenic yeasts and moulds including Candida, Cryptococcus, Aspergillus, Fusarium, and Scedosporium spp., or the etiologic agents of mucormycosis. Immunofluorescence and Western blotting studies show that MAb CA7, an immunoglobulin G1 (IgG1), binds to a major 60 kDa glycoprotein antigen produced on the surface of hyphae, while TH1, an immunoglobulin M (IgM), binds to an antigen produced on the surface of conidia. The MAbs were used in combination with a standard mycological growth medium (Sabouraud Dextrose Agar) to develop an enzyme-linked immunosorbent assay (ELISA) for differentiation of T. asahii from Candida albicans and Cryptococcus neoformans in single and mixed species cultures. The MAbs represent a major advance in the identification of T. asahii and T. asteroides using standard mycological identification methods

Anticipating the species jump: surveillance for emerging viral threats.

Zoonotic disease surveillance is typically triggered after animal pathogens have already infected humans. Are there ways to identify high-risk viruses before they emerge in humans? If so, then how and where can identifications be made and by what methods? These were the fundamental questions driving a workshop to examine the future of predictive surveillance for viruses that might jump from animals to infect humans. Virologists, ecologists and computational biologists from academia, federal government and non-governmental organizations discussed opportunities as well as obstacles to the prediction of species jumps using genetic and ecological data from viruses and their hosts, vectors and reservoirs. This workshop marked an important first step towards envisioning both scientific and organizational frameworks for this future capability. Canine parvoviruses as well as seasonal H3N2 and pandemic H1N1 influenza viruses are discussed as exemplars that suggest what to look for in anticipating species jumps. To answer the question of where to look, prospects for discovering emerging viruses among wildlife, bats, rodents, arthropod vectors and occupationally exposed humans are discussed. Finally, opportunities and obstacles are identified and accompanied by suggestions for how to look for species jumps. Taken together, these findings constitute the beginnings of a conceptual framework for achieving a virus surveillance capability that could predict future species jumps

The response of embedded strain sensors in concrete beams subjected to thermal loading

A wide range of commercially available sensors are frequently used to record the response of civil engineering structures that may be subjected to unexpected loading scenarios, changes of environmental conditions or material deterioration. However, a common problem faced when using these sensors is to distinguish strain changes experienced by the structure due to a temperature change from strain changes that occur due to other causes. Temperature effects on strain sensors are usually accommodated by allowing for temperature effects (temperature compensation); however, there is limited research in the literature that investigates the performance of strain sensor measurements when subjected to temperature change. Understanding the temperature effect on strain sensors will greatly enhance the ability of civil engineers to monitor the performance of structural materials. In this paper, different types of commonly used and advanced strain sensors have been installed in a reinforced concrete beam to measure the thermal strain response of concrete under different temperature conditions. The experimental results demonstrated a 25-30% difference in strain measurements from the different sensors. It is shown in this paper that this difference is due to the combined effects of sensor inaccuracy, uncertainties related to the testing conditions and uncertainties associated with the temperature compensation methods.The authors would like to acknowledge Dr. Peter Long, Martin Touhey and the Engineering Structures Laboratory technical staff at University of Cambridge for their assistance through the experimental program. The authors are also grateful to the Cambridge Center for Smart Infrastructure and Construction for supporting this research project.This is the accepted manuscript. The final version is available from Elsevier at http://www.sciencedirect.com/science/article/pii/S0950061814008642

The effect of cigarette price increase on the cigarette consumption in Taiwan: evidence from the National Health Interview Surveys on cigarette consumption

BACKGROUND: This study uses cigarette price elasticity to evaluate the effect of a new excise tax increase on cigarette consumption and to investigate responses from various types of smokers. METHODS: Our sample consisted of current smokers between 17 and 69 years old interviewed during an annual face-to-face survey conducted by Taiwan National Health Research Institutes between 2000 to 2003. We used Ordinary Least Squares (OLS) procedure to estimate double logarithmic function of cigarette demand and cigarette price elasticity. RESULTS: In 2002, after Taiwan had enacted the new tax scheme, cigarette price elasticity in Taiwan was found to be -0.5274. The new tax scheme brought about an average annual 13.27 packs/person (10.5%) reduction in cigarette consumption. Using the cigarette price elasticity estimate from -0.309 in 2003, we calculated that if the Health and Welfare Tax were increased by another NT$ 3 per pack and cigarette producers shifted this increase to the consumers, cigarette consumption would be reduced by 2.47 packs/person (2.2%). The value of the estimated cigarette price elasticity is smaller than one, meaning that the tax will not only reduce cigarette consumption but it will also generate additional tax revenues. Male smokers who had no income or who smoked light cigarettes were found to be more responsive to changes in cigarette price. CONCLUSIONS: An additional tax added to the cost of cigarettes would bring about a reduction in cigarette consumption and increased tax revenues. It would also help reduce incidents smoking-related illnesses. The additional tax revenues generated by the tax increase could be used to offset the current financial deficiency of Taiwan's National Health Insurance program and provide better public services

Design principles of hair-like structures as biological machines

Hair-like structures are prevalent throughout biology and frequently act to sense or alter interactions with an organism's environment. The overall shape of a hair is simple: a long, filamentous object that protrudes from the surface of an organism. This basic design, however, can confer a wide range of functions, owing largely to the flexibility and large surface area that it usually possesses. From this simple structural basis, small changes in geometry, such as diameter, curvature and inter-hair spacing, can have considerable effects on mechanical properties, allowing functions such as mechanosensing, attachment, movement and protection. Here, we explore how passive features of hair-like structures, both individually and within arrays, enable diverse functions across biology. Understanding the relationships between form and function can provide biologists with an appreciation for the constraints and possibilities on hair-like structures. Additionally, such structures have already been used in biomimetic engineering with applications in sensing, water capture and adhesion. By examining hairs as a functional mechanical unit, geometry and arrangement can be rationally designed to generate new engineering devices and ideas

Role of P-selectin in platelet sequestration in pulmonary capillaries during endotoxemia

Background: There is growing evidence that platelets accumulate in the lung and contribute to the pathogenesis of acute lung injury during endotoxemia. The aims of the present study were to localize platelet sequestration in the pulmonary microcirculation and to investigate the role of P-selectin as a molecular mechanism of platelet endothelial cell interaction. Methods: We used in vivo fluorescence microscopy to quantify the kinetics of fluorescently labeled erythrocytes and platelets in alveolar capillary networks in rabbit lungs. Results: Six hours after onset of endotoxin infusion we observed a massive rolling along and firm adherence of platelets to lung capillary endothelial cells whereas under control conditions no platelet sequestration was detected. P-selectin was expressed on the surface of separated platelets which were incubated with endotoxin and in lung tissue. Pretreatment of platelets with fucoidin, a P-selectin antagonist, significantly attenuated the endotoxin-induced platelet rolling and adherence. In contrast, intravenous infusion of fucoidin in endotoxin-treated rabbits did not inhibit platelet sequestration in pulmonary capillaries. Conclusion: We conclude that platelets accumulate in alveolar capillaries following endotoxemia. P-selectin expressed on the surface of platelets seems to play an important role in mediating this platelet-endothelial cell interaction. Copyright (c) 2006 S. Karger AG, Basel

Weather in stellar atmosphere: the dynamics of mercury clouds in alpha Andromedae

The formation of long-lasting structures at the surfaces of stars is commonly ascribed to the action of strong magnetic fields. This paradigm is supported by observations of evolving cool spots in the Sun and active late-type stars, and stationary chemical spots in the early-type magnetic stars. However, results of our seven-year monitoring of mercury spots in non-magnetic early-type star alpha Andromedae show that the picture of magnetically-driven structure formation is fundamentally incomplete. Using an indirect stellar surface mapping technique, we construct a series of 2-D images of starspots and discover a secular evolution of the mercury cloud cover in this star. This remarkable structure formation process, observed for the first time in any star, is plausibly attributed to a non-equilibrium, dynamical evolution of the heavy-element clouds created by atomic diffusion and may have the same underlying physics as the weather patterns on terrestrial and giant planets.Comment: 10 pages, 2 figures; to be published in Nature Physic

Walks4work: Rationale and study design to investigate walking at lunchtime in the workplace setting

Background: Following recruitment of a private sector company, an 8week lunchtime walking intervention was implemented to examine the effect of the intervention on modifiable cardiovascular disease risk factors, and further to see if walking environment had any further effect on the cardiovascular disease risk factors. Methods. For phase 1 of the study participants were divided into three groups, two lunchtime walking intervention groups to walk around either an urban or natural environment twice a week during their lunch break over an 8week period. The third group was a waiting-list control who would be invited to join the walking groups after phase 1. In phase 2 all participants were encouraged to walk during their lunch break on self-selecting routes. Health checks were completed at baseline, end of phase 1 and end of phase 2 in order to measure the impact of the intervention on cardiovascular disease risk. The primary outcome variables of heart rate and heart rate variability were measured to assess autonomic function associated with cardiovascular disease. Secondary outcome variables (Body mass index, blood pressure, fitness, autonomic response to a stressor) related to cardiovascular disease were also measured. The efficacy of the intervention in increasing physical activity was objectively monitored throughout the 8-weeks using an accelerometer device. Discussion. The results of this study will help in developing interventions with low researcher input with high participant output that may be implemented in the workplace. If effective, this study will highlight the contribution that natural environments can make in the reduction of modifiable cardiovascular disease risk factors within the workplace. © 2012 Brown et al.; licensee BioMed Central Ltd

The Stokes Phenomenon and Quantum Tunneling for de Sitter Radiation in Nonstationary Coordinates

We study quantum tunneling for the de Sitter radiation in the planar coordinates and global coordinates, which are nonstationary coordinates and describe the expanding geometry. Using the phase-integral approximation for the Hamilton-Jacobi action in the complex plane of time, we obtain the particle-production rate in both coordinates and derive the additional sinusoidal factor depending on the dimensionality of spacetime and the quantum number for spherical harmonics in the global coordinates. This approach resolves the factor of two problem in the tunneling method.Comment: LaTex 10 pages, no figur

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur