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Search results for: UROSEPSIS
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Optical method supported by machine learning for urinary tract infection detection and urosepsis risk assessment
PublicationThe study presents an optical method supported by machine learning for discriminating urinary tract infections from an infection capable of causing urosepsis. The method comprises spectra of spectroscopy measurement of artificial urine samples with bacteria from solid cultures of clinical E. coli strains. To provide a reliable classification of results assistance of 27 algorithms was tested. We proved that is possible to obtain...
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Beata Krawczyk dr hab.
PeopleBeata Krawczyk, PhD, Professor Academic degrees, education, qualifications: B. Krawczyk earned his master degree in Biology at the University of Gdansk, Biology Faculty, in 1986, and her PhD in Molecular Biology at the University of Gdansk, Biology Faculty, in 1996. Postdoctoral degree (habilitation) in biological sciences in the discipline biology, Faculty of Natural Sciences, University of Szczecin, Szczecin, in 2009. In 2012...
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A subset of two adherence systems, acute pro-inflammatory pap genes and invasion coding dra, fim, or sfa, increases the risk of Escherichia coli translocation to the bloodstream
PublicationAn analysis of the phylogenetic distribution and virulence genes of Escherichia coli isolates which predispose this bacteria to translocate from the urinary tract to the bloodstream is presented. One-dimensional analysis indicated that the occurrence of P fimbriae and α-hemolysin coding genes is more frequent among the E. coli which cause bacteremia. However, a two-dimensional analysis revealed that a combination of genes coding...