Conventional versus molecular diagnostic tests

Conventional versus molecular diagnostic tests

Autor Costa, MRE Google Scholar
Lacaz, C. D. Google Scholar
Kawasaki, M. Google Scholar
De Camargo, Z. P. Google Scholar
Instituição Univ Buenos Aires
Universidade de São Paulo (USP)
Kanazawa Med Univ
Kanazawa Univ
Universidade Federal de São Paulo (UNIFESP)
Resumo In this session, emphasis was placed on the diagnosis of various mycoses through the identification of antibodies and antigens in sera, as well as on new techniques to properly identify medically important fungi through molecular biological procedures. the use of restriction fragment length polymorphism (RFLP) on fungal mitochondrial DNA (mtDNA) has enabled the identification of different strains of Sporothrix schenkii, several dermatophytes, Candida spp. and black fungi according to their species-specific mtDNA-RFLP patterns. in some species, distinct specific types where found in relation to the geographic origin of the patients. These particular molecular diagnostic tests are useful in the identification of strains and in epidemiological studies. An account of the applications of serological methods in the diagnosis of paracoccidioidomycosis was presented. Serology has been used in the identification of paracoccidioidomycosis using a specific, sensitive and rapid antibody-based immunodiagnosis method. Using the gp43 antigen, the diagnostic coverage of inmunodifussion has been improved from the 93-95% achieved with crude antigens, to 100% in an enzyme-linked immunodiffusion assay capture test. Cross-reactions were eliminated by treatment of the antigen with sodium metaperiodate. Antibody detection is useful, especially in paracoccidioidomycosis and histoplasmosis.
Assunto conventional diagnosis
molecular diagnosis
Idioma Inglês
Data 2000-01-01
Publicado em Medical Mycology. London: Informa Healthcare, v. 38, p. 139-145, 2000.
ISSN 1369-3786 (Sherpa/Romeo, fator de impacto)
Editor Informa Healthcare
Extensão 139-145
Direito de acesso Acesso restrito
Tipo Artigo
Web of Science WOS:000166958800015

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