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Biomechanics and Modeling in Mechanobiology
Article . 2024 . Peer-reviewed
License: CC BY
Data sources: Crossref
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PubMed Central
Other literature type . 2024
License: CC BY
Data sources: PubMed Central
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Discrete network models of endothelial cells and their interactions with the substrate

Authors: Raphael Jakob; Ben R. Britt; Costanza Giampietro; Edoardo Mazza; Alexander E. Ehret;

Discrete network models of endothelial cells and their interactions with the substrate

Abstract

AbstractEndothelial cell monolayers line the inner surfaces of blood and lymphatic vessels. They are continuously exposed to different mechanical loads, which may trigger mechanobiological signals and hence play a role in both physiological and pathological processes. Computer-based mechanical models of cells contribute to a better understanding of the relation between cell-scale loads and cues and the mechanical state of the hosting tissue. However, the confluency of the endothelial monolayer complicates these approaches since the intercellular cross-talk needs to be accounted for in addition to the cytoskeletal mechanics of the individual cells themselves. As a consequence, the computational approach must be able to efficiently model a large number of cells and their interaction. Here, we simulate cytoskeletal mechanics by means of molecular dynamics software, generally suitable to deal with large, locally interacting systems. Methods were developed to generate models of single cells and large monolayers with hundreds of cells. The single-cell model was considered for a comparison with experimental data. To this end, we simulated cell interactions with a continuous, deformable substrate, and computationally replicated multistep traction force microscopy experiments on endothelial cells. The results indicate that cell discrete network models are able to capture relevant features of the mechanical behaviour and are thus well-suited to investigate the mechanics of the large cytoskeletal network of individual cells and cell monolayers.

Keywords

Random networks, Original Paper, Endothelial Cells, Cell Communication, Models, Biological, Biomechanical Phenomena, Humans, Computer Simulation, Stress, Mechanical, Endothelial monolayers, Traction force microscopy, Cytoskeleton, LAMMPS, Finite element model

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Top 10%
Average
Top 10%
Green
hybrid