Evidence map›Paper›PMID 38170298›Full record

ArticleBulletin of mathematical biology2024

Turing Pattern Formation in Reaction-Cross-Diffusion Systems with a Bilayer Geometry.

Antoine Diez, Andrew L Krause, Philip K Maini, Eamonn A Gaffney, Sungrim Seirin-Lee

Abstract read
In one paragraph

Article in Bulletin of mathematical biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Antoine DiezInstitute for the Advanced Study of Human Biology (ASHBi), Kyoto University Institute for Advanced Study (KUIAS), Kyoto University, Yoshida-Konoe-cho, Sakyo-ku, Kyoto, 606-8501, Japan.
Andrew L KrauseMathematical Sciences Department, Durham University, Upper Mountjoy Campus, Stockton Rd, Durham, DH1 3LE, UK.
Philip K MainiWolfson Centre For Mathematical Biology, Mathematical Institute, Andrew Wiles Building, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG, UK.
Eamonn A GaffneyWolfson Centre For Mathematical Biology, Mathematical Institute, Andrew Wiles Building, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG, UK. gaffney@maths.ox.ac.uk.
Sungrim Seirin-LeeInstitute for the Advanced Study of Human Biology (ASHBi), Kyoto University Institute for Advanced Study (KUIAS), Kyoto University, Yoshida-Konoe-cho, Sakyo-ku, Kyoto, 606-8501, Japan. lee.seirin.2c@kyoto-u.ac.jp.ORCID 0000-0002-8466-8037

Funding

Japan Society for the Promotion of Science JP17KK0094Japan Society for the Promotion of Science JP22H05110
6 · The paper itself

Abstract

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.

Indexed as

Mathematical ConceptsModels, BiologicalDiffusionChemotaxisInterfaceSkin patternsStratified systemsTuring instabilities

Identifiers

PMID38170298
PMCPMC10764571

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.