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Cellular automaton for kidney branching morphogenesis

Citation Link: https://doi.org/10.15480/882.9642
Publikationstyp
Journal Article
Date Issued
2021-11-13
Sprache
English
Author(s)
Poorkhanalikoudehi, Afshin
Zimmermann, Karl-Heinz  
Eingebettete Systeme E-13  
TORE-DOI
10.15480/882.9642
TORE-URI
https://hdl.handle.net/11420/47730
Journal
WSEAS transactions on biology and biomedicine  
Volume
18
Start Page
170
End Page
182
Citation
WSEAS Transactions on Biology and Biomedicine 18: 170-182 (2021-11-13)
Publisher DOI
10.37394/23208.2021.18.20
Scopus ID
2-s2.0-85122752805
Publisher
WSEAS
Epithelium is a complex component in the mammalian kidney that has a highly branched duct system. Branching morphogenesis has a hierarchy structure in the ureteric bud and produces the collecting duct tree through repetitive processes. Epithelial and mesenchymal cells surround the tips of growing branches, and their cellular reactions adjust the ureteric bud branching. Mesenchymal cells produce a small protein called glial cellline derived neurotrophic factor (GDNF) that connects to te Rearranged in Transfection (RET) receptors on the surface of epithelial cells. The identified reactions are a necessity for the normal branching growth and their roles exist for using biological features in the proposed model. This paper presents an agent-based model based on cellular automaton for kidney branching in ex-vivo using the features that are expressed as artificial patterns in algorithms. This model extending the groundbreaking approach of Lambert et al. is flexible in features and high compatibility with experimental data. Mesenchymal cells and RET receptors are also expressed as mathematical patterns in the algorithms. The growth mechanism is determined by the growth factor, which indicates the epithelial cell branch when its cell division depends on the local concentration growth factor. Cell division occurs when the level of stimulus growth factor exceeds the threshold. Comparison shows that the model mimics experimental data with high consistency and reveals the dependence between growth factor parameters and features. Results indicate the superiority of compatibility with nature when compared with the model mentioned above.
Subjects
Agent-based model
Cellular automaton
Mathematical modeling of branching morphogenesis
Morphology
Organogenesis
DDC Class
570: Life Sciences, Biology
610: Medicine, Health
004: Computer Sciences
Publication version
publishedVersion
Lizenz
https://creativecommons.org/licenses/by/4.0/
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