In the early 2000s, a particular MRSA clonal complex (CC398) was found mainly in pigs and pig farmers in Europe. Since then, CC398 has been detected among a wide variety of animal species worldwide. We investigated the population structure of CC398 through mutation discovery at 97 genetic housekeeping loci, which are distributed along the CC398 chromosome within 195 CC398 isolates, collected from various countries and host species, including humans. Most of the isolates in this collection were received from collaborating microbiologists, who had preserved them over years. We discovered 96 bi-allelic polymorphisms, and phylogenetic analyses revealed that an epidemic sub-clone within CC398 (dubbed ‘clade (C)’) has spread within and between equine hospitals, where it causes nosocomial infections in horses and colonises the personnel. While clade (C) was strongly associated with S. aureus from horses in veterinary-care settings (p = 2×10−7), it remained extremely rare among S. aureus isolates from human infections.
Zusammenfassung: Der Beitrag beschreibt eine MATLABToolbox zur Segmentierung der Gesteinskörnungen in Asphalt-Probekörpern und deren Kopplung an die DataMining-Toolbox Gait-CAD. Auf der Basis von einfachen Kameraaufnahmen mit eingebrachtem Maẞstab wird ein Algorithmus vorgestellt, der Gesteinskörnungen robust erkennt und in vorgegebene Kornklassen einteilt. Innerhalb einer grafischen Benutzerschnittstelle kann der Anwender die Prozessierung durch Standardelemente (Menüein-träge, Check-Boxen etc.) steuern und grundlegende Parameter anpassen. Alle Gesteinskörnungen werden dann in einen Merkmalsraum überführt und können mit der DataMining-Toolbox Gait-CAD prozessiert werden.Schlüsselwörter: Asphaltproben, Segmentierung, DataMining, Gait-CAD.Abstract: This paper presents an open source MATLAB toolbox for segmentation of grains in asphalt-samples and its coupling to the data mining toolbox Gait-CAD. On the basis of simple digital camera images containing a scale item we present an algorithm robustly detecting grains and grouping them into given grain classes. Within a graphical user interface the user is able to control processing steps and parameters via standard elements like menu items, check-boxes etc. All grains are transformed into a feature space and can be processed using the data mining toolbox Gait-CAD.
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