A computational model for the joint onset and development

Márquez-Flórez, Kalenia; Monaghan, James R.; Shefelbine, Sandra J.; Ramírez-Martínez, Angélica; Garzón‐Alvarado, Diego Alexander

doi:10.1016/j.jtbi.2018.04.015

Cited by 7 publications

(3 citation statements)

References 49 publications

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“…Incorporating additional components into the reaction-diffusion model has allowed investigation of biological mechanisms driving digit patterning [48, 49], embryonic axis specification [49] and frog embryo gastrulation [50], among others. Coupling reaction-diffusion systems with tissue growth [51,52] provides additional means to explore the factors regulating these processes. The role of physical interactions between cells and how they respond to their mechanical environment have also been considered in mechanochemical models of pattern formation [10, 12].…”

Section: Discussionmentioning

confidence: 99%

Turing pattern prediction in three-dimensional domains: the role of initial conditions and growth

Tahar

Muñoz

Shefelbine

et al. 2023

Preprint

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Reaction-diffusion systems have been widely used to model pattern formation in biological systems. However, the emergence of Turing patterns in three-dimensional (3D) domains remains relatively unexplored. A few studies on this topic have shown that extending pattern formation from 2D to 3D is not straightforward. Linear stability analysis, which is commonly used to associate admissible wave modes with predicted patterns in 1D and 2D, has yet to be applied in 3D. We have used this approach, together with finite element modeling of a Turing system with Schnakenberg kinetics, to investigate the effects of initial conditions and growing domains on the competition between admissible modes in 3D Turing pattern emergence. Our results reveal that non-random initial conditions on the activator play a stronger role than those on the substrate. We also observe a path dependency of the evolving pattern within a growing domain. Our findings shed new light on the mechanisms ensuring reliable pattern formation in 3D domains and have important implications for the development of more robust models of morphogen patterning in developmental processes.

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Section: Discussionmentioning

confidence: 99%

Turing pattern prediction in three-dimensional domains: the role of initial conditions and growth

Tahar

Muñoz

Shefelbine

et al. 2023

Preprint

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“…These MSCs then differentiate into CCs, however, on the site of the future joint the CCs will de-differentiate to MSC; this place is known as the Interzone and is formed by packed layered condensation of MSCs [29]. This first step of joint development is known as Interzone onset [30].…”

Section: Overview Of Joint Onset and Morphogenesismentioning

confidence: 99%

From biological morphogenesis to engineering joint design: A bio-inspired algorithm

2023

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“…On the scale of a single cell, models have been designed to describe the molecular pathways that determine cell differentiation events in chondrocytes [20,21]. On the tissue scale, several studies designed continuous mathematical models of embryonic cartilage mechanics that do not account for cell-cell interactions, for example studies on embryonic joint formation [22,23] or endochondral ossification [24]. Similar continuum models are concerned with the maintenance and mechanics of adult cartilage [25][26][27][28][29].…”

Section: Plos Computational Biologymentioning

confidence: 99%

Contributions of cell behavior to geometric order in embryonic cartilage

Mathias,

Adameyko,

Hellander

et al. 2023

PLoS Comput Biol

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During early development, cartilage provides shape and stability to the embryo while serving as a precursor for the skeleton. Correct formation of embryonic cartilage is hence essential for healthy development. In vertebrate cranial cartilage, it has been observed that a flat and laterally extended macroscopic geometry is linked to regular microscopic structure consisting of tightly packed, short, transversal clonar columns. However, it remains an ongoing challenge to identify how individual cells coordinate to successfully shape the tissue, and more precisely which mechanical interactions and cell behaviors contribute to the generation and maintenance of this columnar cartilage geometry during embryogenesis. Here, we apply a three-dimensional cell-based computational model to investigate mechanical principles contributing to column formation. The model accounts for clonal expansion, anisotropic proliferation and the geometrical arrangement of progenitor cells in space. We confirm that oriented cell divisions and repulsive mechanical interactions between cells are key drivers of column formation. In addition, the model suggests that column formation benefits from the spatial gaps created by the extracellular matrix in the initial configuration, and that column maintenance is facilitated by sequential proliferative phases. Our model thus correctly predicts the dependence of local order on division orientation and tissue thickness. The present study presents the first cell-based simulations of cell mechanics during cranial cartilage formation and we anticipate that it will be useful in future studies on the formation and growth of other cartilage geometries.

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A computational model for the joint onset and development

Cited by 7 publications

References 49 publications

Turing pattern prediction in three-dimensional domains: the role of initial conditions and growth

Turing pattern prediction in three-dimensional domains: the role of initial conditions and growth

From biological morphogenesis to engineering joint design: A bio-inspired algorithm

Contributions of cell behavior to geometric order in embryonic cartilage

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