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Advances in Candida detection platforms for clinical and point-of-care applications.

Authors
  • Safavieh, Mohammadali1
  • Coarsey, Chad2, 3
  • Esiobu, Nwadiuto4
  • Memic, Adnan5
  • Vyas, Jatin Mahesh6
  • Shafiee, Hadi1
  • Asghar, Waseem2, 3, 4
  • 1 a Division of Biomedical Engineering, Division of Renal medicine, Department of Medicine , Brigham and Women's Hospital, Harvard Medical School , Cambridge , MA , USA.
  • 2 b Department of Computer Engineering and Electrical Engineering and Computer Science , Florida Atlantic University , Boca Raton , FL , USA.
  • 3 c College of Engineering and Computer Science, Asghar-Lab, Micro and Nanotechnologies for Medicine , Boca Raton , FL , USA.
  • 4 d Biological Sciences Department , Florida Atlantic University , Davie , FL , USA.
  • 5 e Center of Nanotechnology, King Abdulaziz University , Jeddah , Saudi Arabia. , (Saudi Arabia)
  • 6 f Department of Medicine, Division of Infectious Disease , Massachusetts General Hospital , Boston , MA , USA.
Type
Published Article
Journal
Critical reviews in biotechnology
Publication Date
June 2017
Volume
37
Issue
4
Pages
441–458
Identifiers
DOI: 10.3109/07388551.2016.1167667
PMID: 27093473
Source
Medline
Keywords
License
Unknown

Abstract

Invasive candidiasis remains one of the most serious community and healthcare-acquired infections worldwide. Conventional Candida detection methods based on blood and plate culture are time-consuming and require at least 2-4 days to identify various Candida species. Despite considerable advances for candidiasis detection, the development of simple, compact and portable point-of-care diagnostics for rapid and precise testing that automatically performs cell lysis, nucleic acid extraction, purification and detection still remains a challenge. Here, we systematically review most prominent conventional and nonconventional techniques for the detection of various Candida species, including Candida staining, blood culture, serological testing and nucleic acid-based analysis. We also discuss the most advanced lab on a chip devices for candida detection.

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