The DOI matches its Crossref record; 129 of the 129 references it cites were found in a registry or an index.
Molecular diagnostics of infectious diseases
Abstract
Over the past several years, the development and application of molecular diagnostic techniques has initiated a revolution in the diagnosis and monitoring of infectious diseases. Microbial phenotypic characteristics, such as protein, bacteriophage, and chromatographic profiles, as well as biotyping and susceptibility testing, are used in most routine laboratories for identification and differentiation. Nucleic acid techniques, such as plasmid profiling, various methods for generating restriction fragment length polymorphisms, and the polymerase chain reaction (PCR), are making increasing inroads into clinical laboratories. PCR-based systems to detect the etiologic agents of disease directly from clinical samples, without the need for culture, have been useful in rapid detection of unculturable or fastidious microorganisms. Additionally, sequence analysis of amplified microbial DNA allows for identification and better characterization of the pathogen. Subspecies variation, identified by various techniques, has been shown to be important in the prognosis of certain diseases. Other important advances include the determination of viral load and the direct detection of genes or gene mutations responsible for drug resistance. Increased use of automation and user-friendly software makes these technologies more widely available. In all, the detection of infectious agents at the nucleic acid level represents a true synthesis of clinical chemistry and clinical microbiology techniques.
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Cites
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Cited by
Point-of-Care Diagnostics for Global Health
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Turning the Page: Advancing Paper-Based Microfluidics for Broad Diagnostic Application
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Mathematical models of malaria - a review
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Metadata
- Authors
- Tang, Y.-W., Procop, G. W., & Persing, D. H.
- Venue
- Clinical Chemistry
- Publisher
- Oxford University Press (OUP)
- Published
- 1997-11-01
- Volume
- 43
- Issue
- 11
- Pages
- 2021-2038
- ISSN
- 0009-9147 (ISSN-L)
- 1530-8561
- OpenAlex
- W2099114511
- Cited by
- 305
- References
- 129
- FWCI
- 4.68
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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