Age and environment affect constitutive immune function in Red Knots (Calidris canutus)

We studied subspecies, age and environmental effects on constitutive immune function (natural antibody and complement titres, haptoglobin activity and leukocyte concentrations) in Red Knots (Calidris canutus). We compared C. c. islandica and C. c. canutus in the Wadden Sea and found no difference in immune function between subspecies. However, C. c. canutus on their wintering grounds in Banc d’Arguin had higher natural antibody and lower complement levels than C. c. canutus or C. c. islandica in the Wadden Sea. This suggests that immune function is determined more by the surrounding environment than by subspecies. We also compared age classes in the Wadden Sea and found that first year birds had significantly lower natural antibody levels than adults, but that second year birds no longer differed from adults. Finally, we examined the interaction of age and environment in Banc d’Arguin. We found that first year birds (but not adults) in a low quality habitat had higher leukocyte concentrations than first year birds or adults in a high quality habitat. Differences in available resources and defence needs between environments, and differences among individuals differentially distributed between sites, are likely important contributors to the variation in immune function we report. Future studies, which examine these factors on wild birds, will be important for our understanding of how animals function in their natural environment.

Approaches to the evaluation of outbreak detection methods

BACKGROUND: An increasing number of methods are being developed for the early detection of infectious disease outbreaks which could be naturally occurring or as a result of bioterrorism; however, no standardised framework for examining the usefulness of various outbreak detection methods exists. To promote comparability between studies, it is essential that standardised methods are developed for the evaluation of outbreak detection methods. METHODS: This analysis aims to review approaches used to evaluate outbreak detection methods and provide a conceptual framework upon which recommendations for standardised evaluation methods can be based. We reviewed the recently published literature for reports which evaluated methods for the detection of infectious disease outbreaks in public health surveillance data. Evaluation methods identified in the recent literature were categorised according to the presence of common features to provide a conceptual basis within which to understand current approaches to evaluation. RESULTS: There was considerable variation in the approaches used for the evaluation of methods for the detection of outbreaks in public health surveillance data, and appeared to be no single approach of choice. Four main approaches were used to evaluate performance, and these were labelled the Descriptive, Derived, Epidemiological and Simulation approaches. Based on the approaches identified, we propose a basic framework for evaluation and recommend the use of multiple approaches to evaluation to enable a comprehensive and contextualised description of outbreak detection performance. CONCLUSION: The varied nature of performance evaluation demonstrated in this review supports the need for further development of evaluation methods to improve comparability between studies. Our findings indicate that no single approach can fulfil all evaluation requirements. We propose that the cornerstone approaches to evaluation identified provide key contributions to support internal and external validity and comparability of study findings, and suggest these be incorporated into future recommendations for performance assessment

Toward unsupervised outbreak detection through visual perception of new patterns

<p>Abstract</p> <p>Background</p> <p>Statistical algorithms are routinely used to detect outbreaks of well-defined syndromes, such as influenza-like illness. These methods cannot be applied to the detection of emerging diseases for which no preexisting information is available.</p> <p>This paper presents a method aimed at facilitating the detection of outbreaks, when there is no a priori knowledge of the clinical presentation of cases.</p> <p>Methods</p> <p>The method uses a visual representation of the symptoms and diseases coded during a patient consultation according to the International Classification of Primary Care 2^ndversion (ICPC-2). The surveillance data are transformed into color-coded cells, ranging from white to red, reflecting the increasing frequency of observed signs. They are placed in a graphic reference frame mimicking body anatomy. Simple visual observation of color-change patterns over time, concerning a single code or a combination of codes, enables detection in the setting of interest.</p> <p>Results</p> <p>The method is demonstrated through retrospective analyses of two data sets: description of the patients referred to the hospital by their general practitioners (GPs) participating in the French Sentinel Network and description of patients directly consulting at a hospital emergency department (HED).</p> <p>Informative image color-change alert patterns emerged in both cases: the health consequences of the August 2003 heat wave were visualized with GPs' data (but passed unnoticed with conventional surveillance systems), and the flu epidemics, which are routinely detected by standard statistical techniques, were recognized visually with HED data.</p> <p>Conclusion</p> <p>Using human visual pattern-recognition capacities to detect the onset of unexpected health events implies a convenient image representation of epidemiological surveillance and well-trained "epidemiology watchers". Once these two conditions are met, one could imagine that the epidemiology watchers could signal epidemiological alerts, based on "image walls" presenting the local, regional and/or national surveillance patterns, with specialized field epidemiologists assigned to validate the signals detected.</p

Outsourcing with debt financing

This paper investigates the effect of capital structure on a firm’s choice between vertical integration and outsourcing. We model the production decision in a Principal-Agent framework and show that suppliers use debt as a strategic instrument to collect the surplus from outsourcing as their wealth constraint or limited liability ensures them more attractive compensation schemes. Investigating the buyer’s capital structure, we find that outsourcing with risky debt is more likely to occur for high values of the outsourcing surplus.info:eu-repo/semantics/publishedVersio

Using GIS to create synthetic disease outbreaks

BACKGROUND: The ability to detect disease outbreaks in their early stages is a key component of efficient disease control and prevention. With the increased availability of electronic health-care data and spatio-temporal analysis techniques, there is great potential to develop algorithms to enable more effective disease surveillance. However, to ensure that the algorithms are effective they need to be evaluated. The objective of this research was to develop a transparent user-friendly method to simulate spatial-temporal disease outbreak data for outbreak detection algorithm evaluation. A state-transition model which simulates disease outbreaks in daily time steps using specified disease-specific parameters was developed to model the spread of infectious diseases transmitted by person-to-person contact. The software was developed using the MapBasic programming language for the MapInfo Professional geographic information system environment. RESULTS: The simulation model developed is a generalised and flexible model which utilises the underlying distribution of the population and incorporates patterns of disease spread that can be customised to represent a range of infectious diseases and geographic locations. This model provides a means to explore the ability of outbreak detection algorithms to detect a variety of events across a large number of stochastic replications where the influence of uncertainty can be controlled. The software also allows historical data which is free from known outbreaks to be combined with simulated outbreak data to produce files for algorithm performance assessment. CONCLUSION: This simulation model provides a flexible method to generate data which may be useful for the evaluation and comparison of outbreak detection algorithm performance

Computing the Viscosity of Supercooled Liquids: Markov Network Model

The microscopic origin of glass transition, when liquid viscosity changes continuously by more than ten orders of magnitude, is challenging to explain from first principles. Here we describe the detailed derivation and implementation of a Markovian Network model to calculate the shear viscosity of deeply supercooled liquids based on numerical sampling of an atomistic energy landscape, which sheds some light on this transition. Shear stress relaxation is calculated from a master-equation description in which the system follows a transition-state pathway trajectory of hopping among local energy minima separated by activation barriers, which is in turn sampled by a metadynamics-based algorithm. Quantitative connection is established between the temperature variation of the calculated viscosity and the underlying potential energy and inherent stress landscape, showing a different landscape topography or “terrain” is needed for low-temperature viscosity (of order 10[superscript 7] Pa·s) from that associated with high-temperature viscosity (10[superscript −5] Pa·s). Within this range our results clearly indicate the crossover from an essentially Arrhenius scaling behavior at high temperatures to a low-temperature behavior that is clearly super-Arrhenius (fragile) for a Kob-Andersen model of binary liquid. Experimentally the manifestation of this crossover in atomic dynamics continues to raise questions concerning its fundamental origin. In this context this work explicitly demonstrates that a temperature-dependent “terrain” characterizing different parts of the same potential energy surface is sufficient to explain the signature behavior of vitrification, at the same time the notion of a temperature-dependent effective activation barrier is quantified.Corning IncorporatedBoston University. Center for Scientific Computing and VisualizationNational Science Foundation (U.S.) (grant DMR-1008104)National Science Foundation (U.S.) (grant DMR-0520020)United States. Air Force Office of Scientific Research (FA9550-08-1-0325

Constitutively elevated levels of SOCS1 suppress innate responses in DF-1 immortalised chicken fibroblast cells.

The spontaneously immortalised DF-1 cell line is rapidly replacing its progenitor primary chicken embryo fibroblasts (CEFs) for studies on avian viruses such as avian influenza but no comprehensive study has as yet been reported comparing their innate immunity phenotypes. We conducted microarray analyses of DF-1 and CEFs, under both normal and stimulated conditions using chicken interferon-α (chIFN-α) and the attenuated infectious bursal disease virus vaccine strain PBG98. We found that DF-1 have an attenuated innate response compared to CEFs. Basal expression levels of Suppressor of Cytokine Signalling 1 (chSOCS1), a negative regulator of cytokine signalling in mammals, are 16-fold higher in DF-1 than in CEFs. The chSOCS1 “SOCS box” domain (which in mammals, interacts with an E3 ubiquitin ligase complex) is not essential for the inhibition of cytokine-induced JAK/STAT signalling activation in DF-1. Overexpression of SOCS1 in chIFN-α-stimulated DF-1 led to a relative decrease in expression of interferon-stimulated genes (ISGs; MX1 and IFIT5) and increased viral yield in response to PBG98 infection. Conversely, knockdown of SOCS1 enhanced induction of ISGs and reduced viral yield in chIFN-α-stimulated DF-1. Consequently, SOCS1 reduces induction of the IFN signalling pathway in chicken cells and can potentiate virus replication

Ebola Virion Attachment and Entry into Human Macrophages Profoundly Effects Early Cellular Gene Expression

Zaire ebolavirus (ZEBOV) infections are associated with high lethality in primates. ZEBOV primarily targets mononuclear phagocytes, which are activated upon infection and secrete mediators believed to trigger initial stages of pathogenesis. The characterization of the responses of target cells to ZEBOV infection may therefore not only further understanding of pathogenesis but also suggest possible points of therapeutic intervention. Gene expression profiles of primary human macrophages exposed to ZEBOV were determined using DNA microarrays and quantitative PCR to gain insight into the cellular response immediately after cell entry. Significant changes in mRNA concentrations encoding for 88 cellular proteins were observed. Most of these proteins have not yet been implicated in ZEBOV infection. Some, however, are inflammatory mediators known to be elevated during the acute phase of disease in the blood of ZEBOV-infected humans. Interestingly, the cellular response occurred within the first hour of Ebola virion exposure, i.e. prior to virus gene expression. This observation supports the hypothesis that virion binding or entry mediated by the spike glycoprotein (GP1,2) is the primary stimulus for an initial response. Indeed, ZEBOV virions, LPS, and virus-like particles consisting of only the ZEBOV matrix protein VP40 and GP1,2 (VLPVP40-GP) triggered comparable responses in macrophages, including pro-inflammatory and pro-apoptotic signals. In contrast, VLPVP40 (particles lacking GP1,2) caused an aberrant response. This suggests that GP1,2 binding to macrophages plays an important role in the immediate cellular response

Association of total energy intake and macronutrient consumption with colorectal cancer risk: results from a large population-based case-control study in Newfoundland and Labrador and Ontario, Canada

<p>Abstract</p> <p>Background</p> <p>Diet is regarded as one of the most important environmental factors associated with colorectal cancer (CRC) risk. A recent report comprehensively concluded that total energy intake does not have a simple relationship with CRC risk, and that the data were inconsistent for carbohydrate, cholesterol and protein. The objective of this study was to identify the associations of CRC risk with dietary intakes of total energy, protein, fat, carbohydrate, fiber, and alcohol using data from a large case-control study conducted in Newfoundland and Labrador (NL) and Ontario (ON), Canada.</p> <p>Methods</p> <p>Incident colorectal cancer cases (n = 1760) were identified from population-based cancer registries in the provinces of ON (1997-2000) and NL (1999-2003). Controls (n = 2481) were a random sample of residents in each province, aged 20-74 years. Family history questionnaire (FHQ), personal history questionnaire (PHQ), and food frequency questionnaire (FFQ) were used to collect study data. Logistic regression was used to evaluate the association of intakes of total energy, macronutrients and alcohol with CRC risk.</p> <p>Results</p> <p>Total energy intake was associated with higher risk of CRC (OR: 1.56; 95% CI: 1.21-2.01, <it>p</it>-trend = 0.02, 5^thversus 1^stquintile), whereas inverse associations emerged for intakes of protein (OR: 0.85, 95%CI: 0.69-1.00, <it>p</it>-trend = 0.06, 5^thversus 1^stquintile), carbohydrate (OR: 0.81, 95%CI: 0.63-1.00, <it>p</it>-trend = 0.05, 5^thversus 1^stquintile) and total dietary fiber (OR: 0.84, 95% CI:0.67-0.99, <it>p</it>-trend = 0.04, 5^thversus 1^stquintile). Total fat, alcohol, saturated fatty acids, monounsaturated fatty acids, polyunsaturated fatty acids, and cholesterol were not associated with CRC risk.</p> <p>Conclusion</p> <p>This study provides further evidence that high energy intake may increase risk of incident CRC, whereas diets high in protein, fiber, and carbohydrate may reduce the risk of the disease.</p