{"title":"Simulation of a Free Boundary Cell Migration Model through Physics Informed Neural Networks","authors":"Sanchita Malla , Dietmar Oelz , Sitikantha Roy","doi":"10.1016/j.jmbbm.2025.106961","DOIUrl":null,"url":null,"abstract":"<div><div>Understanding the complexities of single-cell migration is facilitated by computational modeling, which provides important insights into the physiological processes that underlie migration mechanisms. This study developed a computational model for one-dimensional actomyosin flow in a migrating cell with moving boundaries. The model incorporates the complex interplay of actin polymerization, substrate adhesion, and actomyosin dynamics through a system of coupled nonlinear partial differential equations. A physics-informed neural network is designed to understand the dynamic behavior of actin flow and actin concentration within the cell along with the unknown moving boundaries, taking into account the computational cost of solving a dynamic model with a deformable domain. The model’s capacity to depict the complex interaction between biological and physical processes within the cell is demonstrated by the numerical results, which qualitatively agree with experimental and computational data available in the literature. This study demonstrates the application of a deep learning method to simulate a challenging biophysical problem with moving boundaries. The model does not require synthetic data for training and accurately reflects the intricate biophysics of cell migration.</div></div>","PeriodicalId":380,"journal":{"name":"Journal of the Mechanical Behavior of Biomedical Materials","volume":"167 ","pages":"Article 106961"},"PeriodicalIF":3.3000,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Mechanical Behavior of Biomedical Materials","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1751616125000773","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Understanding the complexities of single-cell migration is facilitated by computational modeling, which provides important insights into the physiological processes that underlie migration mechanisms. This study developed a computational model for one-dimensional actomyosin flow in a migrating cell with moving boundaries. The model incorporates the complex interplay of actin polymerization, substrate adhesion, and actomyosin dynamics through a system of coupled nonlinear partial differential equations. A physics-informed neural network is designed to understand the dynamic behavior of actin flow and actin concentration within the cell along with the unknown moving boundaries, taking into account the computational cost of solving a dynamic model with a deformable domain. The model’s capacity to depict the complex interaction between biological and physical processes within the cell is demonstrated by the numerical results, which qualitatively agree with experimental and computational data available in the literature. This study demonstrates the application of a deep learning method to simulate a challenging biophysical problem with moving boundaries. The model does not require synthetic data for training and accurately reflects the intricate biophysics of cell migration.
期刊介绍：
The Journal of the Mechanical Behavior of Biomedical Materials is concerned with the mechanical deformation, damage and failure under applied forces, of biological material (at the tissue, cellular and molecular levels) and of biomaterials, i.e. those materials which are designed to mimic or replace biological materials.
The primary focus of the journal is the synthesis of materials science, biology, and medical and dental science. Reports of fundamental scientific investigations are welcome, as are articles concerned with the practical application of materials in medical devices. Both experimental and theoretical work is of interest; theoretical papers will normally include comparison of predictions with experimental data, though we recognize that this may not always be appropriate. The journal also publishes technical notes concerned with emerging experimental or theoretical techniques, letters to the editor and, by invitation, review articles and papers describing existing techniques for the benefit of an interdisciplinary readership.
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