Selective Detection and Automated Counting of Fluorescently-Labeled Chrysotile Asbestos Using a Dual-Mode High-Throughput Microscopy (DM-HTM) Method
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 cou...
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| Format: | Article |
| Language: | English |
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MDPI AG
2013-05-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/13/5/5686 |
| _version_ | 1811299399977926656 |
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| author | Jung Kyung Kim Yeon Gyu Yu Hwataik Han Donghee Lee Myoung-Ock Cho Hyo Mi Chang |
| author_facet | Jung Kyung Kim Yeon Gyu Yu Hwataik Han Donghee Lee Myoung-Ock Cho Hyo Mi Chang |
| author_sort | Jung Kyung Kim |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-13T06:34:35Z |
| format | Article |
| id | doaj.art-44cc0e5376864e28af2abc91b391a049 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T06:34:35Z |
| publishDate | 2013-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-44cc0e5376864e28af2abc91b391a0492022-12-22T02:57:57ZengMDPI AGSensors1424-82202013-05-011355686569910.3390/s130505686Selective Detection and Automated Counting of Fluorescently-Labeled Chrysotile Asbestos Using a Dual-Mode High-Throughput Microscopy (DM-HTM) MethodJung Kyung KimYeon Gyu YuHwataik HanDonghee LeeMyoung-Ock ChoHyo Mi ChangPhase 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.http://www.mdpi.com/1424-8220/13/5/5686asbestoschrysotileDksAhigh-throughput microscopydual-mode imagingreflectionfluorescenceimage processing and analysisautomated counting |
| spellingShingle | Jung Kyung Kim Yeon Gyu Yu Hwataik Han Donghee Lee Myoung-Ock Cho Hyo Mi Chang Selective Detection and Automated Counting of Fluorescently-Labeled Chrysotile Asbestos Using a Dual-Mode High-Throughput Microscopy (DM-HTM) Method Sensors asbestos chrysotile DksA high-throughput microscopy dual-mode imaging reflection fluorescence image processing and analysis automated counting |
| title | Selective Detection and Automated Counting of Fluorescently-Labeled Chrysotile Asbestos Using a Dual-Mode High-Throughput Microscopy (DM-HTM) Method |
| title_full | Selective Detection and Automated Counting of Fluorescently-Labeled Chrysotile Asbestos Using a Dual-Mode High-Throughput Microscopy (DM-HTM) Method |
| title_fullStr | Selective Detection and Automated Counting of Fluorescently-Labeled Chrysotile Asbestos Using a Dual-Mode High-Throughput Microscopy (DM-HTM) Method |
| title_full_unstemmed | Selective Detection and Automated Counting of Fluorescently-Labeled Chrysotile Asbestos Using a Dual-Mode High-Throughput Microscopy (DM-HTM) Method |
| title_short | Selective Detection and Automated Counting of Fluorescently-Labeled Chrysotile Asbestos Using a Dual-Mode High-Throughput Microscopy (DM-HTM) Method |
| title_sort | selective detection and automated counting of fluorescently labeled chrysotile asbestos using a dual mode high throughput microscopy dm htm method |
| topic | asbestos chrysotile DksA high-throughput microscopy dual-mode imaging reflection fluorescence image processing and analysis automated counting |
| url | http://www.mdpi.com/1424-8220/13/5/5686 |
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