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Sensors 2013, 13(5), 5686-5699; doi:10.3390/s130505686
Article

Selective Detection and Automated Counting of Fluorescently-Labeled Chrysotile Asbestos Using a Dual-Mode High-Throughput Microscopy (DM-HTM) Method

1
,
2
,
1,†
,
2
,
3
 and
3,4,*
1 Department of Mechanical Engineering, Graduate School, Kookmin University, Jeongneung-ro 77, Seongbuk-gu, Seoul 136-702, Korea 2 Department of Chemistry, Graduate School, Kookmin University, Jeongneung-ro 77, Seongbuk-gu, Seoul 136-702, Korea 3 School of Mechanical Systems Engineering, Kookmin University, Jeongneung-ro 77, Seongbuk-gu, Seoul 136-702, Korea 4 Department of Integrative Biomedical Science and Engineering, Graduate School, Kookmin University, Jeongneung-ro 77, Seongbuk-gu, Seoul 136-702, Korea Current address: Department of Mechanical and Materials Engineering, University of Nebraska-Lincoln, 1400 R street, Lincoln, NE 68588, USA.
* Author to whom correspondence should be addressed.
Received: 16 February 2013 / Revised: 22 April 2013 / Accepted: 24 April 2013 / Published: 2 May 2013
(This article belongs to the Section Biosensors)
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Abstract

Phase contrast microscopy (PCM) is a widely used analytical method for airborne asbestos, but it is unable to distinguish asbestos from non-asbestos fibers and requires time-consuming and laborious manual counting of fibers. Previously, we developed a high-throughput microscopy (HTM) method that could greatly reduce human intervention and analysis time through automated image acquisition and counting of fibers. In this study, we designed a dual-mode HTM (DM-HTM) device for the combined reflection and fluorescence imaging of asbestos, and automated a series of built-in image processing commands of ImageJ software to test its capabilities. We used DksA, a chrysotile-adhesive protein, for selective detection of chrysotile fibers in the mixed dust-free suspension of crysotile and amosite prepared in the laboratory. We demonstrate that fluorescently-stained chrysotile and total fibers can be identified and enumerated automatically in a high-throughput manner by the DM-HTM system. Combined with more advanced software that can correctly identify overlapping and branching fibers and distinguish between fibers and elongated dust particles, the DM-HTM method should enable fully automated counting of airborne asbestos.
Keywords: asbestos; chrysotile; DksA; high-throughput microscopy; dual-mode imaging; reflection; fluorescence; image processing and analysis; automated counting asbestos; chrysotile; DksA; high-throughput microscopy; dual-mode imaging; reflection; fluorescence; image processing and analysis; automated counting
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).
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Cho, M.-O.; Chang, H.M.; Lee, D.; Yu, Y.G.; Han, H.; Kim, J.K. Selective Detection and Automated Counting of Fluorescently-Labeled Chrysotile Asbestos Using a Dual-Mode High-Throughput Microscopy (DM-HTM) Method. Sensors 2013, 13, 5686-5699.

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