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Estimating Dynamic Cellular Morphological Properties via the Combination of the RTCA System and a Hough-Transform-Based Algorithm

The xCELLigence real-time cell analysis (RTCA) system has the potential to detect cellular proliferation, migration, cytotoxicity, adherence, and remodeling. Although the RTCA system is widely recognized as a noninvasive and efficient tool for real-time monitoring of cellular fate, it cannot describ...

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Detalles Bibliográficos
Autores principales: Zhang, Lejun, Ye, Yang, Dhar, Rana, Deng, Jinsong, Tang, Huifang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6829879/
https://www.ncbi.nlm.nih.gov/pubmed/31640200
http://dx.doi.org/10.3390/cells8101287
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author Zhang, Lejun
Ye, Yang
Dhar, Rana
Deng, Jinsong
Tang, Huifang
author_facet Zhang, Lejun
Ye, Yang
Dhar, Rana
Deng, Jinsong
Tang, Huifang
author_sort Zhang, Lejun
collection PubMed
description The xCELLigence real-time cell analysis (RTCA) system has the potential to detect cellular proliferation, migration, cytotoxicity, adherence, and remodeling. Although the RTCA system is widely recognized as a noninvasive and efficient tool for real-time monitoring of cellular fate, it cannot describe detailed cell morphological parameters, such as length and intensity. Transforming growth factor beta(TGF-β) induced the epithelial–mesenchymal transition (EMT), which produces significant changes in cellular morphology, so we used TGF-β to treat A549 epithelial cells in this study. We compared it with lipopolysaccharide (LPS) and cigarette smoke extract (CSE) as stimulators. We developed an efficient algorithm to quantify the morphological cell changes. This algorithm is comprised of three major parts: image preprocessing, Hough transform (HT), and post-processing. We used the RTCA system to record the A549 cell index. Western blot was used to confirm the EMT. The RTCA system showed that different stimulators produce different cell index curves. The algorithm determined the lengths of the detected lines of cells, and the results were similar to the RTCA system in the TGF-β group. The Western blot results show that TGF-β changed the EMT markers, but the other stimulator remained unchanged. Optics-based computer vision techniques can supply the requisite information for the RTCA system based on good correspondence between the results.
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spelling pubmed-68298792019-11-18 Estimating Dynamic Cellular Morphological Properties via the Combination of the RTCA System and a Hough-Transform-Based Algorithm Zhang, Lejun Ye, Yang Dhar, Rana Deng, Jinsong Tang, Huifang Cells Article The xCELLigence real-time cell analysis (RTCA) system has the potential to detect cellular proliferation, migration, cytotoxicity, adherence, and remodeling. Although the RTCA system is widely recognized as a noninvasive and efficient tool for real-time monitoring of cellular fate, it cannot describe detailed cell morphological parameters, such as length and intensity. Transforming growth factor beta(TGF-β) induced the epithelial–mesenchymal transition (EMT), which produces significant changes in cellular morphology, so we used TGF-β to treat A549 epithelial cells in this study. We compared it with lipopolysaccharide (LPS) and cigarette smoke extract (CSE) as stimulators. We developed an efficient algorithm to quantify the morphological cell changes. This algorithm is comprised of three major parts: image preprocessing, Hough transform (HT), and post-processing. We used the RTCA system to record the A549 cell index. Western blot was used to confirm the EMT. The RTCA system showed that different stimulators produce different cell index curves. The algorithm determined the lengths of the detected lines of cells, and the results were similar to the RTCA system in the TGF-β group. The Western blot results show that TGF-β changed the EMT markers, but the other stimulator remained unchanged. Optics-based computer vision techniques can supply the requisite information for the RTCA system based on good correspondence between the results. MDPI 2019-10-21 /pmc/articles/PMC6829879/ /pubmed/31640200 http://dx.doi.org/10.3390/cells8101287 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Lejun
Ye, Yang
Dhar, Rana
Deng, Jinsong
Tang, Huifang
Estimating Dynamic Cellular Morphological Properties via the Combination of the RTCA System and a Hough-Transform-Based Algorithm
title Estimating Dynamic Cellular Morphological Properties via the Combination of the RTCA System and a Hough-Transform-Based Algorithm
title_full Estimating Dynamic Cellular Morphological Properties via the Combination of the RTCA System and a Hough-Transform-Based Algorithm
title_fullStr Estimating Dynamic Cellular Morphological Properties via the Combination of the RTCA System and a Hough-Transform-Based Algorithm
title_full_unstemmed Estimating Dynamic Cellular Morphological Properties via the Combination of the RTCA System and a Hough-Transform-Based Algorithm
title_short Estimating Dynamic Cellular Morphological Properties via the Combination of the RTCA System and a Hough-Transform-Based Algorithm
title_sort estimating dynamic cellular morphological properties via the combination of the rtca system and a hough-transform-based algorithm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6829879/
https://www.ncbi.nlm.nih.gov/pubmed/31640200
http://dx.doi.org/10.3390/cells8101287
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