3 results match your criteria: "Faculty of Medicine and St. Anne's Faculty Hospital[Affiliation]"
European candidaemia is characterised by notable differential epidemiology and susceptibility pattern: Results from the ECMM Candida III study.
J Infect
November 2023
Biotech Med, Graz, Austria; Division of Infectious Diseases, Department of Internal Medicine, Medical University of Graz, Graz, Austria. Electronic address:
Article Synopsis
- The study aimed to evaluate the distribution of Candida species and their antifungal resistance in cases of candidaemia across Europe, analyzing data collected from 41 centers in 17 countries between 2018 and 2022.
- The most common isolates identified were C. albicans, C. glabrata, and C. parapsilosis, with notable geographical variations in their prevalence and antifungal resistance patterns.
- Resistance to fluconazole was observed in certain species, particularly C. glabrata and C. parapsilosis, with rare cases of echinocandin resistance found, including specific genetic mutations in resistant isolates.
Influence of Culture Media on Microbial Fingerprints Using Raman Spectroscopy.
Sensors (Basel)
November 2015
Department of Microbiology, Faculty of Medicine and St. Anne's Faculty Hospital, Brno 65691, Czech Republic.
Raman spectroscopy has a broad range of applications across numerous scientific fields, including microbiology. Our work here monitors the influence of culture media on the Raman spectra of clinically important microorganisms (Escherichia coli, Staphylococcus aureus, Staphylococcus epidermidis and Candida albicans). Choosing an adequate medium may enhance the reproducibility of the method as well as simplifying the data processing and the evaluation.
View Article and Find Full Text PDFCandida parapsilosis biofilm identification by Raman spectroscopy.
Int J Mol Sci
December 2014
Department of Microbiology, Faculty of Medicine and St. Anne's Faculty Hospital, Brno 65691, Czech Republic.
Colonies of Candida parapsilosis on culture plates were probed directly in situ using Raman spectroscopy for rapid identification of specific strains separated by a given time intervals (up to months apart). To classify the Raman spectra, data analysis was performed using the approach of principal component analysis (PCA). The analysis of the data sets generated during the scans of individual colonies reveals that despite the inhomogeneity of the biological samples unambiguous associations to individual strains (two biofilm-positive and two biofilm-negative) could be made.
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