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FC6 - Departamento de Ciência de Computadores FC5 - Edifício Central FC4 - Departamento de Biologia FC3 - Departamento de Física e Astronomia e Departamento GAOT FC2 - Departamento de Química e Bioquímica FC1 - Departamento de Matemática
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MobilityAnalyser: A novel approach for automatic quantification of cell mobility on periodic patterned substrates using brightfield microscopy images

Title
MobilityAnalyser: A novel approach for automatic quantification of cell mobility on periodic patterned substrates using brightfield microscopy images
Type
Article in International Scientific Journal
Year
2018
Authors
Ângela Carvalho
(Author)
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Tiago Esteves
(Author)
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Pedro Quelhas
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Fernando Jorge Monteiro
(Author)
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Journal
Vol. 162
Pages: 61-67
ISSN: 0169-2607
Publisher: Elsevier
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Publicação em ISI Web of Knowledge ISI Web of Knowledge - 0 Citations
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Authenticus ID: P-00Q-EV7
Abstract (EN): Background and objective: Surface topography of biomaterials has been shown to have an effect on cells behaviour. Cell-material interactions can be visually characterized by assessing both cell shape and spreading at initial time-points and, its migration patterns, as a response to the underlying topography. Whilst many have reported the study of cell migration and shape with fluorescence labelling, the focus on evaluating cells response to surface topography is to observe, under real-time conditions, interactions between cells and surfaces. In this manuscript we present a novel approach to automatically detect and remove periodic background patterns in brightfield microscopy images in order to perform automatic cell mobility analysis. Methods: The developed software, MobilityAnalyser, performs automatic tracking of unmarked cells and allows the user to manually correct any incorrectly detected or tracked cell. Human Mesenchymal Stem Cells (hMSCs) trajectory, migration distance, velocity and persistence were evaluated over line and pillar micropatterned SiO2 films and on a flat SiO2 control substrate. Results: The developed software proved to be effective in automatically removing background patterns of both line and pillar shapes and in performing cell detection and tracking. MobilityAnalyser accurately measured cell mobility in a fraction of the time required for manual analysis and eliminated user subjectivity. The results obtained with the software confirmed how different topographies affect cell trajectory, migration pathways and velocities, with a statistically significant increase for micropatterned surfaces, when compared with the flat control. The persistence parameter also proved the influence of both patterns on the directionality of cell movement. Conclusions: MobilityAnalyser is an automatic tool that removes periodic background patterns, detects and tracks cells, and provides cell mobility parameters that characterize the response of cells to different surface topographies. The software is freely available at: https://drive.google.com/open?id= 1Fbb32logLD19SlRjceMETNUqDHgpeBPl.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 7
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