19 research outputs found

    Detection and Localisation of PrPSc in the Liver of Sheep Infected with Scrapie and Bovine Spongiform Encephalopathy

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    Prions are largely contained within the nervous and lymphoid tissue of transmissible spongiform encephalopathy (TSE) infected animals. However, following advances in diagnostic sensitivity, PrPSc, a marker for prion disease, can now be located in a wide range of viscera and body fluids including muscle, saliva, blood, urine and milk, raising concerns that exposure to these materials could contribute to the spread of disease in humans and animals. Previously we demonstrated low levels of infectivity in the liver of sheep experimentally challenged with bovine spongiform encephalopathy. In this study we show that PrPSc accumulated in the liver of 89% of sheep naturally infected with scrapie and 100% of sheep challenged with BSE, at both clinical and preclinical stages of the disease. PrPSc was demonstrated in the absence of obvious inflammatory foci and was restricted to isolated resident cells, most likely Kupffer cells

    Trends in modeling Biomedical Complex Systems

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    In this paper we provide an introduction to the techniques for multi-scale complex biological systems, from the single bio-molecule to the cell, combining theoretical modeling, experiments, informatics tools and technologies suitable for biological and biomedical research, which are becoming increasingly multidisciplinary, multidimensional and information-driven. The most important concepts on mathematical modeling methodologies and statistical inference, bioinformatics and standards tools to investigate complex biomedical systems are discussed and the prominent literature useful to both the practitioner and the theoretician are presented

    Cokriging for multivariate Hilbert space valued random fields: application to multi-fidelity computer code emulation

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    In this paper we propose Universal trace co-kriging, a novel methodology for interpolation of multivariate Hilbert space valued functional data. Such data commonly arises in multi-fidelity numerical modeling of the subsurface and it is a part of many modern uncertainty quantification studies. Besides theoretical developments we also present methodological evaluation and comparisons with the recently published projection based approach by Bohorquez et al. (Stoch Environ Res Risk Assess 31(1):53–70, 2016. https://doi.org/10.1007/s00477-016-1266-y). Our evaluations and analyses were performed on synthetic (oil reservoir) and real field (uranium contamination) subsurface uncertainty quantification case studies. Monte Carlo analyses were conducted to draw important conclusions and to provide practical guidelines for all future practitioners

    IFITM3 restricts the morbidity and mortality associated with influenza

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    The 2009 H1N1 influenza pandemic showed the speed with which a novel respiratory virus can spread and the ability of a generally mild infection to induce severe morbidity and mortality in a subset of the population. Recent in vitro studies show that the interferon-inducible transmembrane (IFITM) protein family members potently restrict the replication of multiple pathogenic viruses1, 2, 3, 4, 5, 6, 7. Both the magnitude and breadth of the IFITM proteins’ in vitro effects suggest that they are critical for intrinsic resistance to such viruses, including influenza viruses. Using a knockout mouse model8, we now test this hypothesis directly and find that IFITM3 is essential for defending the host against influenza A virus in vivo. Mice lacking Ifitm3 display fulminant viral pneumonia when challenged with a normally low-pathogenicity influenza virus, mirroring the destruction inflicted by the highly pathogenic 1918 ‘Spanish’ influenza9, 10. Similar increased viral replication is seen in vitro, with protection rescued by the re-introduction of Ifitm3. To test the role of IFITM3 in human influenza virus infection, we assessed the IFITM3 alleles of individuals hospitalized with seasonal or pandemic influenza H1N1/09 viruses. We find that a statistically significant number of hospitalized subjects show enrichment for a minor IFITM3 allele (SNP rs12252-C) that alters a splice acceptor site, and functional assays show the minor CC genotype IFITM3 has reduced influenza virus restriction in vitro. Together these data reveal that the action of a single intrinsic immune effector, IFITM3, profoundly alters the course of influenza virus infection in mouse and human

    Wastewater-Based Epidemiology of Stimulant Drugs: Functional Data Analysis Compared to Traditional Statistical Methods

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    Background Wastewater-based epidemiology (WBE) is a new methodology for estimating the drug load in a population. Simple summary statistics and specification tests have typically been used to analyze WBE data, comparing differences between weekday and weekend loads. Such standard statistical methods may, however, overlook important nuanced information in the data. In this study, we apply functional data analysis (FDA) to WBE data and compare the results to those obtained from more traditional summary measures. Methods We analysed temporal WBE data from 42 European cities, using sewage samples collected daily for one week in March 2013. For each city, the main temporal features of two selected drugs were extracted using functional principal component (FPC) analysis, along with simpler measures such as the area under the curve (AUC). The individual cities’ scores on each of the temporal FPCs were then used as outcome variables in multiple linear regression analysis with various city and country characteristics as predictors. The results were compared to those of functional analysis of variance (FANOVA). Results The three first FPCs explained more than 99% of the temporal variation. The first component (FPC1) represented the level of the drug load, while the second and third temporal components represented the level and the timing of a weekend peak. AUC was highly correlated with FPC1, but other temporal characteristic were not captured by the simple summary measures. FANOVA was less flexible than the FPCA-based regression, and even showed concordance results. Geographical location was the main predictor for the general level of the drug load. Conclusion FDA of WBE data extracts more detailed information about drug load patterns during the week which are not identified by more traditional statistical methods. Results also suggest that regression based on FPC results is a valuable addition to FANOVA for estimating associations between temporal patterns and covariate information
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