Title |
Automated Cell Identification and Tracking Using Nanoparticle Moving-Light-Displays
|
---|---|
Published in |
PLOS ONE, July 2012
|
DOI | 10.1371/journal.pone.0040835 |
Pubmed ID | |
Authors |
James A. Tonkin, Paul Rees, Martyn R. Brown, Rachel J. Errington, Paul J. Smith, Sally C. Chappell, Huw D. Summers |
Abstract |
An automated technique for the identification, tracking and analysis of biological cells is presented. It is based on the use of nanoparticles, enclosed within intra-cellular vesicles, to produce clusters of discrete, point-like fluorescent, light sources within the cells. Computational analysis of these light ensembles in successive time frames of a movie sequence, using k-means clustering and particle tracking algorithms, provides robust and automated discrimination of live cells and their motion and a quantitative measure of their proliferation. This approach is a cytometric version of the moving light display technique which is widely used for analyzing the biological motion of humans and animals. We use the endocytosis of CdTe/ZnS, core-shell quantum dots to produce the light displays within an A549, epithelial, lung cancer cell line, using time-lapse imaging with frame acquisition every 5 minutes over a 40 hour time period. The nanoparticle moving light displays provide simultaneous collection of cell motility data, resolution of mitotic traversal dynamics and identification of familial relationships allowing construction of multi-parameter lineage trees. |
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Geographical breakdown
Country | Count | As % |
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United Kingdom | 2 | 6% |
Unknown | 34 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 11 | 31% |
Unspecified | 8 | 22% |
Researcher | 4 | 11% |
Student > Master | 3 | 8% |
Student > Doctoral Student | 2 | 6% |
Other | 5 | 14% |
Unknown | 3 | 8% |
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Unspecified | 8 | 22% |
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Computer Science | 2 | 6% |
Other | 9 | 25% |
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