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Selective and Automated Detection of Airborne Asbestos Fibers Using Chrysotile-Adhesive Protein and High-Throughput Microscopy (HTM)

[+] Author Affiliations
Myoung-Ock Cho, Hyo Mi Chang, Yeon Gyu Yu, Hwataik Han, Jung Kyung Kim

Kookmin University, Seoul, Korea

Paper No. IMECE2011-63721, pp. 407-411; 5 pages
doi:10.1115/IMECE2011-63721
From:
  • ASME 2011 International Mechanical Engineering Congress and Exposition
  • Volume 2: Biomedical and Biotechnology Engineering; Nanoengineering for Medicine and Biology
  • Denver, Colorado, USA, November 11–17, 2011
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-5488-4
  • Copyright © 2011 by ASME

abstract

There are several methods to detect asbestos including phase contrast microscopy (PCM), polarized light microscopy, X-ray diffraction, and electron microscopy. Although the PCM method is widely used due to its simple process and relatively low cost, it is a time-consuming and laborious process that is manually performed by a human counter. We developed a high-throughput microscopy (HTM) system for automated counting of airborne asbestos fibers to automate the conventional PCM method. Our results show that automatic image acquisition by synchronization of charge-coupled device (CCD) camera with movement of stages, and image analysis using image processing software, significantly reduced time consumption and labor. In this study, we used DksA chrysotile-adhesive protein for the selective detection of asbestos. DksA, known as the protein that specifically attaches to chrysotile, was extracted from Escherichia coli through a recombinant protein technique. We tried to detect chrysotile selectively from other fibers or particles, and we developed a highly selective and automated low-cost device for automated identification and enumeration of airborne asbestos fibers based on the HTM method.

Copyright © 2011 by ASME

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