Multiscale kinematic growth coupled with mechanosensitive systems biology in open-source software.

IF 1.7 4区 医学 Q4 BIOPHYSICS
Steven A LaBelle, Mohammadreza Soltany Sadrabadi, Seungik Baek, Mohammad Mofrad, Jeffrey A Weiss, Amirhossein Arzani
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引用次数: 0

Abstract

Multiscale coupling between cell scale biology and tissue-scale mechanics is a promising approach for modeling disease growth. In such models, tissue-level growth and remodeling (G&R) is driven by cell-level signaling pathways and systems biology models, where each model operates at different scales. Herein, we generate multiscale G&R models to capture the associated multiscale connections. At the cell-scale, we consider systems biology models in the form of systems of ordinary differential equations (ODEs) and partial differential equations (PDEs) representing the reactions between the biochemicals causing the growth based on mass-action or logic-based Hill-type kinetics. At the tissue-scale, we employ kinematic growth in continuum frameworks. Two illustrative test problems (a tissue graft and aneurysm growth) are examined with various chemical signaling networks, boundary conditions, and mechano-chemical coupling strategies. We extend two open-source software frameworks - FEBio and FEniCS - to disseminate examples of multiscale growth and remodeling simulations. One-way and two-way coupling between the systems biology and the growth models are compared and the effect of biochemical diffusivity and ODE vs. PDE based systems biology modeling on the G&R results are studied. The results show that growth patterns emerge from reactions between biochemicals, the choice between ODEs and PDEs systems biology modeling, and the coupling strategy. Cross-verification confirms that results for FEBio and FEniCS are nearly identical. We hope that these open-source tools will support reproducibility and education within the biomechanics community.

细胞尺度生物学和组织尺度力学之间的多尺度耦合是一种很有前景的疾病生长建模方法。在这类模型中,组织级生长和重塑(G&R)由细胞级信号通路和系统生物学模型驱动,每个模型在不同尺度上运行。在此,我们生成多尺度 G&R 模型,以捕捉相关的多尺度联系。在细胞尺度上,我们采用常微分方程(ODE)和偏微分方程(PDE)系统的形式来考虑系统生物学模型,这些系统表示基于质量作用或逻辑希尔型动力学的导致生长的生化反应。在组织尺度上,我们采用连续框架中的运动生长。我们利用各种化学信号网络、边界条件和机械化学耦合策略对两个示例性测试问题(组织移植和动脉瘤生长)进行了研究。我们扩展了两个开源软件框架--FEBio 和 FEniCS--来传播多尺度生长和重塑模拟的实例。我们比较了系统生物学和生长模型之间的单向和双向耦合,并研究了生化扩散性和基于 ODE 与 PDE 的系统生物学建模对 G&R 结果的影响。结果表明,生长模式源于生化反应、ODE 与 PDE 系统生物学建模之间的选择以及耦合策略。交叉验证证实,FEBio 和 FEniCS 的结果几乎完全相同。我们希望这些开源工具能为生物力学界的可重复性和教育提供支持。
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来源期刊
CiteScore
3.40
自引率
5.90%
发文量
169
审稿时长
4-8 weeks
期刊介绍: Artificial Organs and Prostheses; Bioinstrumentation and Measurements; Bioheat Transfer; Biomaterials; Biomechanics; Bioprocess Engineering; Cellular Mechanics; Design and Control of Biological Systems; Physiological Systems.
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