The focus of this review is the evolution of biochemical phenotypic yeast identification methods with emphasis on conventional approaches, rapid screening tests, chromogenic agars, comprehensive commercial methods, and the eventual migration to genotypic methods. As systemic yeast infections can be devastating and resistance is common in certain species, accurate identification to the species level is paramount for successful therapy and appropriate patient care.
Paper spray mass spectrometry ambient ionization is utilized for rapid discrimination of bacteria without sample preparation. Bacterial colonies were smeared onto filter paper precut to a sharp point, then wetted with solvent and held at a high potential. Charged droplets released by field emission were sucked into the mass spectrometer inlet and mass spectra were recorded. Sixteen different species representing eight different genera from Gram-positive and Gram-negative bacteria were investigated. Phospholipids were the predominant species observed in the mass spectra in both the negative and positive ion modes. Multivariate data analysis based on principal component analysis, followed by linear discriminant analysis, allowed bacterial discrimination. The lipid information in the negative ion mass spectra proved useful for species level differentiation of the investigated Gram-positive bacteria. Gram-negative bacteria were differentiated at the species level by using a numerical data fusion strategy of positive and negative ion mass spectra.
Candida dubliniensis is a newly described species that is closely related phylogenetically to Candida albicans and that is commonly associated with oral candidiasis in human immunodeficiency virus-positive patients. Several recent studies have attempted to elucidate phenotypic and genotypic characteristics of use in separating the two species. However, results obtained with simple phenotypic tests were too variable and tests that provided more definitive data were too complex for routine use in the clinical laboratory setting. The objective of this study was to determine if reproducible identification of C. dubliniensis could be obtained with commercial identification kits. The substrate reactivity profiles of 80 C. dubliniensis isolates were obtained by using the API 20C AUX, ID 32 C, RapID Yeast Plus, VITEK YBC, and VITEK 2 ID-YST systems. The percentages of C. dubliniensisisolates capable of assimilating or hydrolyzing each substrate were compared with the percentages from the C. albicans profiles in each kit's database, and the results were expressed as percentC. dubliniensis and percent C. albicans. Any substrate that showed >50% difference in reactivity was considered useful in differentiating the species. In addition, assimilation of methyl-α-d-glucoside (MDG), d-trehalose (TRE), and d-xylose (XYL) by the same isolates was investigated by the traditional procedure of Wickerham and Burton (L. J. Wickerham and K. A. Burton, J. Bacteriol. 56:363–371, 1948). At 48 h (the time recommended by the manufacturer for its new database), we found that the assimilation of four carbohydrates in the API 20C AUX system could be used to distinguish the species, i.e., glycerol (GLY; 88 and 14%), XYL (0 and 88%), MDG (0 and 85%), and TRE (15 and 97%). Similarly, results with the ID 32 C system at 48 h showed that XYL (0 and 98%), MDG (0 and 98%), lactate (LAT; 0 and 96%), and TRE (30 and 96%) could be used to separate the two species. Phosphatase (PHS; 9 and 76%) and α-d-glucosidase (23 and 94%) proved to be the most useful for separation of the species in the RapID Yeast Plus system. While at 24 h the profiles obtained with the VITEK YBC system showed that MDG (10 and 95%), XYL (0 and 95%), and GLY (26 and 80%) could be used to separate the two species, at 48 h only XYL (6 and 95%) could be used to separate the two species. The most useful substrates in the VITEK 2 ID-YST system were TRE (1 and 89%), MDG (1 and 99%), LAT (4 and 98%), and PHS (83 and 1%). While the latter kit was not yet commercially available at the time of the study, it would appear to be the most valuable for the identification of C. dubliniensis. Although assimilation of MDG, TRE, and XYL proved to be the most useful for species differentiation by the majority of commercial systems, the results with these carbohydrates by the Wickerham and Burton procedure were essentially the same for both species, albeit following protracted incubation. Thus, it is the rapidity of the assimilation achieved with the commercial systems that allows the differentiation of C. dubliniensis from C. albicans.
Fraenkel-Mostowski models are a particularly simple and conceptual tool for proving consistency results involving the axiom of choice, AC. These models satisfy the theory, FM, of a well founded universe of sets built from a ground set of individuals. Zermelo-Fraenkel set theory, ZF, is the extension of FM in which the set of individuals is assumed to be empty. In this paper we show that there is a large class of statements whose consistency with ZF can be proven directly by means of a Fraenkel-Mostowski model.A statement, Φ, of set theory is said to be transferable if there is a metatheorem: If Φ is true in a Fraenkel-Mostowski model then Φ is consistent with ZF. Jech and Sochor introduced, in [12], the class of boundable statements and proved them to be transferable. Most existential contradictions of AC are boundable. It remains to find criteria under which Ψ ∧ Φ is transferable where Ψ is a universal consequence of AC and Φ is an existential contradiction of AC. To this end we give two classes of statements. Each class is closed under conjunction, contains the boundable statements, and contains a number of universal consequences of AC. Nearly every Fraenkel-Mostowski consistency in the literature falls into one of these two classes.In §2 we give two generalizations of the boundable statements. In §§3 and 4 the classes of transferable statements are discussed. In §5 we discuss the transfer problem and prove a metatheorem concerning nontransferable statements.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.