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タイトル: Turing Pattern Formation in Reaction-Cross-Diffusion Systems with a Bilayer Geometry
著者: Diez, Antoine
Krause, Andrew L.
Maini, Philip K.
Gaffney, Eamonn A.
Seirin-Lee, Sungrim
著者名の別形: 李, 聖林
キーワード: Turing instabilities
Stratified systems
Skin patterns
Interface
Chemotaxis
発行日: Feb-2024
出版者: Springer Nature
誌名: Bulletin of Mathematical Biology
巻: 86
号: 2
論文番号: 13
抄録: Conditions for self-organisation via Turing’s mechanism in biological systems represented by reaction-diffusion or reaction-cross-diffusion models have been extensively studied. Nonetheless, the impact of tissue stratification in such systems is under-explored, despite its ubiquity in the context of a thin epithelium overlying connective tissue, for instance the epidermis and underlying dermal mesenchyme of embryonic skin. In particular, each layer can be subject to extensively different biochemical reactions and transport processes, with chemotaxis - a special case of cross-diffusion - often present in the mesenchyme, contrasting the solely molecular transport typically found in the epidermal layer. We study Turing patterning conditions for a class of reaction-cross-diffusion systems in bilayered regions, with a thin upper layer and coupled by a linear transport law. In particular, the role of differential transport through the interface is explored together with the presence of asymmetry between the homogeneous equilibria of the two layers. A linear stability analysis is carried out around a spatially homogeneous equilibrium state in the asymptotic limit of weak and strong coupling strengths, where quantitative approximations of the bifurcation curve can be computed. Our theoretical findings, for an arbitrary number of reacting species, reveal quantitative Turing conditions, highlighting when the coupling mechanism between the layered regions can either trigger patterning or stabilize a spatially homogeneous equilibrium regardless of the independent patterning state of each layer. We support our theoretical results through direct numerical simulations, and provide an open source code to explore such systems further.
著作権等: © The Author(s) 2023
This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
URI: http://hdl.handle.net/2433/287127
DOI(出版社版): 10.1007/s11538-023-01237-1
PubMed ID: 38170298
出現コレクション:学術雑誌掲載論文等

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