17 research outputs found

    Identification of human pathogens isolated from blood using microarray hybridisation and signal pattern recognition

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    <p>Abstract</p> <p>Background</p> <p>Pathogen identification in clinical routine is based on the cultivation of microbes with subsequent morphological and physiological characterisation lasting at least 24 hours. However, early and accurate identification is a crucial requisite for fast and optimally targeted antimicrobial treatment. Molecular biology based techniques allow fast identification, however discrimination of very closely related species remains still difficult.</p> <p>Results</p> <p>A molecular approach is presented for the rapid identification of pathogens combining PCR amplification with microarray detection. The DNA chip comprises oligonucleotide capture probes for 25 different pathogens including Gram positive cocci, the most frequently encountered genera of <it>Enterobacteriaceae</it>, non-fermenter and clinical relevant <it>Candida </it>species. The observed detection limits varied from 10 cells (e.g. <it>E. coli</it>) to 10<sup>5 </sup>cells (<it>S. aureus</it>) per mL artificially spiked blood. Thus the current low sensitivity for some species still represents a barrier for clinical application. Successful discrimination of closely related species was achieved by a signal pattern recognition approach based on the k-nearest-neighbour method. A prototype software providing this statistical evaluation was developed, allowing correct identification in 100 % of the cases at the genus and in 96.7 % at the species level (n = 241).</p> <p>Conclusion</p> <p>The newly developed molecular assay can be carried out within 6 hours in a research laboratory from pathogen isolation to species identification. From our results we conclude that DNA microarrays can be a useful tool for rapid identification of closely related pathogens particularly when the protocols are adapted to the special clinical scenarios.</p

    RGG: A general GUI Framework for R scripts

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    <p>Abstract</p> <p>Background</p> <p>R is the leading open source statistics software with a vast number of biostatistical and bioinformatical analysis packages. To exploit the advantages of R, extensive scripting/programming skills are required.</p> <p>Results</p> <p>We have developed a software tool called R GUI Generator (RGG) which enables the easy generation of Graphical User Interfaces (GUIs) for the programming language R by adding a few Extensible Markup Language (XML) – tags. RGG consists of an XML-based GUI definition language and a Java-based GUI engine. GUIs are generated in runtime from defined GUI tags that are embedded into the R script. User-GUI input is returned to the R code and replaces the XML-tags. RGG files can be developed using any text editor. The current version of RGG is available as a stand-alone software (RGGRunner) and as a plug-in for JGR.</p> <p>Conclusion</p> <p>RGG is a general GUI framework for R that has the potential to introduce R statistics (R packages, built-in functions and scripts) to users with limited programming skills and helps to bridge the gap between R developers and GUI-dependent users. RGG aims to abstract the GUI development from individual GUI toolkits by using an XML-based GUI definition language. Thus RGG can be easily integrated in any software. The RGG project further includes the development of a web-based repository for RGG-GUIs. RGG is an open source project licensed under the Lesser General Public License (LGPL) and can be downloaded freely at <url>http://rgg.r-forge.r-project.org</url></p

    Plasmonic Hepatitis B Biosensor for the Analysis of Clinical Saliva

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    A biosensor for the detection of hepatitis B antibodies in clinical saliva was developed. Compared to conventional analysis of blood serum, it offers the advantage of noninvasive collection of samples. Detection of biomarkers in saliva imposes two major challenges associated with the low analyte concentration and increased surface fouling. The detection of minute amounts of hepatitis B antibodies was performed by plasmonically amplified fluorescence sandwich immunoassay. To have access to specific detection, we prevented the nonspecific adsorption of biomolecules present in saliva by brushes of poly[(N-(2-hydroxypropyl) methacrylamide)-co-(carboxybetaine methacrylamide)] grafted from the gold sensor surface and post modified with hepatitis B surface antigen. Obtained results were validated against the response measured with ELISA at a certified laboratory using serum from the same patients. © 201
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