The genus Malassezia comprises commensal yeasts on human skin. These yeasts are involved in superficial infections but are also isolated in deeper infections, such as fungemia, particularly in certain at-risk patients, such as neonates or patients with parenteral nutrition catheters. Very little is known about Malassezia epidemiology and virulence. This is due mainly to the difficulty of distinguishing species. Currently, species identification is based on morphological and biochemical characteristics. Only molecular biology techniques identify species with certainty, but they are time-consuming and expensive. The aim of this study was to develop and evaluate a matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) database for identifying Malassezia species by mass spectrometry. Eighty-five Malassezia isolates from patients in three French university hospitals were investigated. Each strain was identified by internal transcribed spacer sequencing. Forty-five strains of the six species Malassezia furfur, M. sympodialis, M. slooffiae, M. globosa, M. restricta, and M. pachydermatis allowed the creation of a MALDI-TOF database. Forty other strains were used to test this database. All strains were identified by our Malassezia database with log scores of >2.0, according to the manufacturer's criteria. Repeatability and reproducibility tests showed a coefficient of variation of the log score values of <10%. In conclusion, our new Malassezia database allows easy, fast, and reliable identification of Malassezia species. Implementation of this database will contribute to a better, more rapid identification of Malassezia species and will be helpful in gaining a better understanding of their epidemiology.
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http://dx.doi.org/10.1128/JCM.01763-16 | DOI Listing |
Clin Oral Investig
January 2025
Department of Operative Dentistry and Periodontology, Center for Dental Medicine, Medical Center- University of Freiburg, Faculty of Medicine, University of Freiburg, University of Freiburg, Freiburg, Germany.
Objective: Helicobacter pylori is known for colonizing the gastric mucosa and instigating severe upper gastrointestinal diseases such as gastritis, gastroduodenal ulcers, and gastric cancer. To date, there is no data available on the oral cavity as transmission site, whether H. pylori can survive in the oral cavity or in human saliva.
View Article and Find Full Text PDFComput Biol Med
January 2025
Department of Data Analysis and Mathematical Modelling, Ghent University, Coupure Links 653, Ghent, 9000, Belgium.
For the last decade, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been the reference method for species identification in clinical microbiology. Hampered by a historical lack of open data, machine learning research towards models specifically adapted to MALDI-TOF MS remains in its infancy. Given the growing complexity of available datasets (such as large-scale antimicrobial resistance prediction), a need for models that (1) are specifically designed for MALDI-TOF MS data, and (2) have high representational capacity, presents itself.
View Article and Find Full Text PDFAnalyst
January 2025
Jiangsu Key Laboratory for Carbon-based Functional Materials and Devices, Institute of Functional Nano and Soft Materials (FUNSOM), Soochow University, Suzhou, Jiangsu Province 215123, China.
The choices of matrices and protocols for sample deposition are critical factors, which impact each other in the matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI). Previous reports on MALDI MS matrices have only compared their performances in terms of their MS signal intensities and provided optical microphotos or MALDI MS images of sample spots but typically lacked quantitative evaluation. Therefore, there is an urgent need to develop a multivariate model to evaluate the performance of different combinations of matrices and sample protocols.
View Article and Find Full Text PDFJ Sep Sci
January 2025
Key Laboratory of Tropical Medicinal Resource Chemistry of Ministry of Education, Hainan Normal University, Haikou, China.
A comprehensive strategy, including spectroscopic, molecular simulation, proteomics, and bioinformatics techniques, was employed to investigate a novel triazole, 5-(4-methoxyphenyl)-1-phenyl-1H-1,2,3-triazole, its interactions with high-abundance blood proteins, and identification of low-abundance proteins. The binding constants and thermodynamic parameters of the triazole to two high-abundance blood globular proteins, human serum albumin, and human immunoglobulin G (HIgG), were obtained by spectroscopic techniques and computational chemistry. The two-dimensional gel electrophoresis in combination with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry was employed to isolate and identify differentially expressed low-abundance proteins in human blood serum samples following exposure to the triazole.
View Article and Find Full Text PDFJ Chromatogr A
January 2025
Home and Personal Care, The Dow Chemical Company, Shanghai 201203, PR China.
Rheology modifiers (RMs) are polymeric molecules providing rheological control of formulations, which are important in product application, shelf-life, and aesthetic perception. Bio-derived polyethylene glycol (PEG)-based RMs thicken formulations through nonionic-associative thickening where at least two hydrophobic end groups from a RM molecule interact with other hydrophobic groups of other RM molecules or ingredients in the formulation to form an associative network. We report a comprehensive two-dimensional liquid chromatography (2D-LC) separation of partly bio-derived PEG-based RMs in size exclusion chromatography (SEC) × reversed-phase liquid chromatography (RPLC) mode for the separation of RM components based on both molecular weight distribution and end group hydrophobe distribution.
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