Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/38931
Title: Predicting the Efficacy of Stalk Cells Following Leading Cells Through a Micro-Channel Using Morphoelasticity and a Cell Shape Evolution Model
Authors: PENG, Qiyao 
VERMOLEN, Fred 
Weihs, D.
Editors: Tavares, JMRS
Bourauel, L.
Geris, L
Slote, JV
Issue Date: 2023
Publisher: SPRINGER INTERNATIONAL PUBLISHING AG
Source: COMPUTER METHODS, IMAGING AND VISUALIZATION IN BIOMECHANICS AND BIOMEDICAL ENGINEERING II, SPRINGER INTERNATIONAL PUBLISHING AG, p. 112 -122
Series/Report: Lecture Notes in Computational Vision and Biomechanics
Abstract: Cancer cell migration between different body parts is the driving force behind cancer metastasis, which causes mortality of patients. Migration of cancer cells often proceeds by penetration through narrow cavities in possibly stiff tissues. In our previous work [12], a model for the evolution of cell geometry is developed, and in the current study we use this model to investigate whether followers among (cancer) cells benefit from leading (cancer) cells during transmigration through microchannels and cavities. Using Wilcoxon's signed-rank text on the data collected from Monte Carlo simulations, we conclude that the transmigration time for the stalk cell is significantly smaller than for the leading cell with a p-value less than 0.0001, for the modelling set-up that we have used in this study.
Notes: Peng, Q (corresponding author), Leiden Univ, Math Inst, Niels Bohrweg 1, Leiden, Netherlands.; Peng, Q (corresponding author), Delft Univ Technol, Delft Inst Appl Math, Mekelweg 4, NL-2628 CD Delft, Netherlands.; Peng, Q (corresponding author), Hasselt Univ, Dept Math & Stat, Computat Math Grp, Fac Sci, Campus Diepenbeek, B-3590 Diepenbeek, Belgium.
q.peng@math.leidenuniv.nl; fred.vermolen@uhasselt.be;
daphnew@technion.ac.il
Keywords: Cell metastasis;Evolution of cell geometry;Morphoelasticity;Agent-based model
Document URI: http://hdl.handle.net/1942/38931
ISBN: 978-3-031-10015-4; 978-3-031-10014-7
DOI: 10.1007/978-3-031-10015-4_10
ISI #: 000876827700010
Rights: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
Category: C1
Type: Proceedings Paper
Appears in Collections:Research publications

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