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

A Lateral-Flow Device for the Rapid Detection of Scedosporium Species

This is the final version. Available on open access from MDPI via the DOI in this recordData Availability Statement: The data presented in this study are available on request from the corresponding author but are not publicly available due to commercial confidentialities. Monoclonal antibody HG12 and the LFD are available through ISCA Diagnostics Ltd.Scedosporium species are human pathogenic fungi, responsible for chronic, localised, and life-threatening disseminated infections in both immunocompetent and immunocompromised individuals. Diagnosis of Scedosporium infections currently relies on non-specific CT, lengthy and insensitive culture from invasive biopsy, and time-consuming histopathology of tissue samples. At present, there are no rapid antigen tests that detect Scedosporium-specific biomarkers. Here we report the development of a rapid (30 min) and sensitive (pmol/L sensitivity) lateral-flow device (LFD) test, incorporating a Scedosporium-specific IgG1 monoclonal antibody (mAb), HG12, which binds to extracellular polysaccharide (EPS) antigens of between ~15 kDa and 250 kDa secreted during hyphal growth of the pathogens. The test is compatible with human serum, and allows the detection of the Scedosporium species most frequently reported as agents of human disease (Scedosporium apiospermum, Scedosporium aurantiacum, and Scedosporium boydii), with limits of detection (LOD) of the EPS biomarkers in human serum of ~0.81 ng/mL (S. apiospermum), ~0.94 ng/mL (S. aurantiacum), and ~1.95 ng/mL (S. boydii). The Scedosporium-specific LFD (ScedLFD) test therefore provides a potential novel opportunity for the detection of infections caused by different Scedosporium species.ISCA Diagnostics Ltd

A Layer-Wise Information Reinforcement Approach to Improve Learning in Deep Belief Networks

With the advent of deep learning, the number of works proposing new methods or improving existent ones has grown exponentially in the last years. In this scenario, "very deep" models were emerging, once they were expected to extract more intrinsic and abstract features while supporting a better performance. However, such models suffer from the gradient vanishing problem, i.e., backpropagation values become too close to zero in their shallower layers, ultimately causing learning to stagnate. Such an issue was overcome in the context of convolution neural networks by creating "shortcut connections" between layers, in a so-called deep residual learning framework. Nonetheless, a very popular deep learning technique called Deep Belief Network still suffers from gradient vanishing when dealing with discriminative tasks. Therefore, this paper proposes the Residual Deep Belief Network, which considers the information reinforcement layer-by-layer to improve the feature extraction and knowledge retaining, that support better discriminative performance. Experiments conducted over three public datasets demonstrate its robustness concerning the task of binary image classification

Exome sequencing followed by large-scale genotyping suggests a limited role for moderately rare risk factors of strong effect in schizophrenia.

Schizophrenia is a severe psychiatric disorder with strong heritability and marked heterogeneity in symptoms, course, and treatment response. There is strong interest in identifying genetic risk factors that can help to elucidate the pathophysiology and that might result in the development of improved treatments. Linkage and genome-wide association studies (GWASs) suggest that the genetic basis of schizophrenia is heterogeneous. However, it remains unclear whether the underlying genetic variants are mostly moderately rare and can be identified by the genotyping of variants observed in sequenced cases in large follow-up cohorts or whether they will typically be much rarer and therefore more effectively identified by gene-based methods that seek to combine candidate variants. Here, we consider 166 persons who have schizophrenia or schizoaffective disorder and who have had either their genomes or their exomes sequenced to high coverage. From these data, we selected 5,155 variants that were further evaluated in an independent cohort of 2,617 cases and 1,800 controls. No single variant showed a study-wide significant association in the initial or follow-up cohorts. However, we identified a number of case-specific variants, some of which might be real risk factors for schizophrenia, and these can be readily interrogated in other data sets. Our results indicate that schizophrenia risk is unlikely to be predominantly influenced by variants just outside the range detectable by GWASs. Rather, multiple rarer genetic variants must contribute substantially to the predisposition to schizophrenia, suggesting that both very large sample sizes and gene-based association tests will be required for securely identifying genetic risk factors. © 2012 The American Society of Human Genetics

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

Ant-like task allocation and recruitment in cooperative robots

One of the greatest challenges in robotics is to create machines that are able to interact with unpredictable environments in real time. A possible solution may be to use swarms of robots behaving in a self-organized manner, similar to workers in an ant colony. Efficient mechanisms of division of labour, in particular series-parallel operation and transfer of information among group members, are key components of the tremendous ecological success of ants. Here we show that the general principles regulating division of labour in ant colonies indeed allow the design of flexible, robust and effective robotic systems. Groups of robots using ant-inspired algorithms of decentralized control techniques foraged more efficiently and maintained higher levels of group energy than single robots. But the benefits of group living decreased in larger groups, most probably because of interference during foraging. Intriguingly, a similar relationship between group size and efficiency has been documented in social insects. Moreover, when food items were clustered, groups where robots could recruit other robots in an ant-like manner were more efficient than groups without information transfer, suggesting that group dynamics of swarms of robots may follow rules similar to those governing social insects