Numerical Methods for Two-Dimensional Stem Cell Tissue Growth

Growth of developing and regenerative biological tissues of different cell types is usually driven by stem cells and their local environment. Here, we present a computational framework for continuum tissue growth models consisting of stem cells, cell lineages, and diffusive molecules that regulate p...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:Journal of scientific computing. - 1999. - 58(2014) vom: 01., Seite 149-175
1. Verfasser: Ovadia, Jeremy (VerfasserIn)
Weitere Verfasser: Nie, Qing
Format: Aufsatz
Sprache:English
Veröffentlicht: 2014
Zugriff auf das übergeordnete Werk:Journal of scientific computing
Schlagworte:Journal Article Cell lineages Interfacial motion Multigrid Tissue modeling
LEADER 01000caa a22002652 4500
001 NLM23439935X
003 DE-627
005 20250216132312.0
007 tu
008 231224s2014 xx ||||| 00| ||eng c
028 5 2 |a pubmed25n0781.xml 
035 |a (DE-627)NLM23439935X 
035 |a (NLM)24415847 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a Ovadia, Jeremy  |e verfasserin  |4 aut 
245 1 0 |a Numerical Methods for Two-Dimensional Stem Cell Tissue Growth 
264 1 |c 2014 
336 |a Text  |b txt  |2 rdacontent 
337 |a ohne Hilfsmittel zu benutzen  |b n  |2 rdamedia 
338 |a Band  |b nc  |2 rdacarrier 
500 |a Date Revised 30.03.2024 
500 |a published: Print-Electronic 
500 |a Citation Status PubMed-not-MEDLINE 
520 |a Growth of developing and regenerative biological tissues of different cell types is usually driven by stem cells and their local environment. Here, we present a computational framework for continuum tissue growth models consisting of stem cells, cell lineages, and diffusive molecules that regulate proliferation and differentiation through feedback. To deal with the moving boundaries of the models in both open geometries and closed geometries (through polar coordinates) in two dimensions, we transform the dynamic domains and governing equations to fixed domains, followed by solving for the transformation functions to track the interface explicitly. Clustering grid points in local regions for better efficiency and accuracy can be achieved by appropriate choices of the transformation. The equations resulting from the incompressibility of the tissue is approximated by high-order finite difference schemes and is solved using the multigrid algorithms. The numerical tests demonstrate an overall spatiotemporal second-order accuracy of the methods and their capability in capturing large deformations of the tissue boundaries. The methods are applied to two biological systems: stratified epithelia for studying the effects of two different types of stem cell niches and the scaling of a morphogen gradient with the size of the Drosophila imaginal wing disc during growth. Direct simulations of both systems suggest that that the computational framework is robust and accurate, and it can incorporate various biological processes critical to stem cell dynamics and tissue growth 
650 4 |a Journal Article 
650 4 |a Cell lineages 
650 4 |a Interfacial motion 
650 4 |a Multigrid 
650 4 |a Tissue modeling 
700 1 |a Nie, Qing  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t Journal of scientific computing  |d 1999  |g 58(2014) vom: 01., Seite 149-175  |w (DE-627)NLM098177567  |x 0885-7474  |7 nnns 
773 1 8 |g volume:58  |g year:2014  |g day:01  |g pages:149-175 
912 |a GBV_USEFLAG_A 
912 |a SYSFLAG_A 
912 |a GBV_NLM 
912 |a GBV_ILN_350 
951 |a AR 
952 |d 58  |j 2014  |b 01  |h 149-175