Goda, Keisuke, Ayazi, Ali, Gossett, Daniel R., Sadasivam, Jagannath, Lonappan, Cejo K., Sollier, Elodie, Fard, Ali M., Hur, Soojung Claire, Adam, Jost, Murray, Coleman, and others. (2012) High-throughput single-microparticle imaging flow analyzer. Proceedings of the National Academy of Sciences, 109 (29). pp. 11630-11635. ISSN 0027-8424. (doi:10.1073/pnas.1204718109) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:35553)
| The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
| Official URL: http://dx.doi.org/10.1073/pnas.1204718109 |
Abstract
Optical microscopy is one of the most widely used diagnostic methods in scientific, industrial, and biomedical applications. However, while useful for detailed examination of a small number (< 10,000) of microscopic entities, conventional optical microscopy is incapable of statistically relevant screening of large populations (> 100,000,000) with high precision due to its low throughput and limited digital memory size. We present an automated flow-through single-particle optical microscope that overcomes this limitation by performing sensitive blur-free image acquisition and nonstop real-time image-recording and classification of microparticles during high-speed flow. This is made possible by integrating ultrafast optical imaging technology, self-focusing microfluidic technology, optoelectronic communication technology, and information technology. To show the system’s utility, we demonstrate high-throughput image-based screening of budding yeast and rare breast cancer cells in blood with an unprecedented throughput of 100,000 particles/s and a record false positive rate of one in a million.
| Item Type: | Article |
|---|---|
| DOI/Identification number: | 10.1073/pnas.1204718109 |
| Uncontrolled keywords: | photonics; microfluidics; instrumentation; high-throughput screening; medical diagnostics |
| Subjects: | T Technology |
| Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts |
| Depositing User: | Tina Thompson |
| Date Deposited: | 21 Oct 2013 11:26 UTC |
| Last Modified: | 05 Nov 2024 10:19 UTC |
| Resource URI: | https://kar.kent.ac.uk/id/eprint/35553 (The current URI for this page, for reference purposes) |
University of Kent Author Information
Wang, Chao.
| Creator's ORCID: |
 https://orcid.org/0000-0002-0454-8079
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|---|---|
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