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A multi-scale computational model of the extracellular matrix of the lung

肺细胞外基质的多尺度计算模型

基本信息

批准号：
10187641
负责人：
BELA SUKI
金额：
$ 77.26万
依托单位：
BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-06-01 至 2023-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10187641
关键词：
3-Dimensional Accounting Alveolar Animal Model Behavior Biochemical Bleomycin Breathing Cells Characteristics Chronic Collagen Computer Models Connective Tissue Coupling Data Deposition Deterioration Disease Disease Progression Elastin Ensure Environment Equation Evaluation Evolution Extracellular Matrix Feedback Fibroblasts Fibrosis Functional disorder Gases Goals Human Impairment Inflammation Inflammatory Life Link Location Long-Term Effects Lung Lung diseases Maintenance Mechanics Microscopic Modeling Monte Carlo Method Movement Output Pathology Periodicity Physics Progressive Disease Property Proteins Pulmonary Emphysema Pulmonary Fibrosis Rattus Rodent Model Stress Structural Protein Structure Structure of parenchyma of lung Sum Testing Therapeutic procedure Time Tissues base cell injury cell motility cell type cigarette smoke-induced computational platform injury and repair insight mechanical behavior mechanical properties mechanotransduction microCT migration multi-scale modeling network models novel novel therapeutics response soft tissue stem cell therapy

项目摘要

Cells create their own biochemical and mechanical environment, and at the same time are exquisitely sensitive to it, displaying a non-equilibrium homeostatic state that ensures normal extracellular matrix (ECM) function throughout life. There are two currently incurable lung diseases for which this maintenance fails. Emphysema involves the progressive destruction of tissue with loss of ECM stiffness while pulmonary fibrosis is characterized by tissue stiffening due to excessive ECM deposition. These are also chronic progressive diseases in which inflammation, mechanotransduction and cellular migration destabilize local homeostatic control of the ECM. Our overarching hypothesis is that abnormalities in the homeostatic feedback between ECM mechanics and cellular responses are central to the pathophysiology of both emphysema and pulmonary fibrosis. The goal of this proposal is to develop and test a multi-scale computational platform that will advance critical new insight into how deterioration of homeostatic cell-ECM coupling leads to specific disease forms. Aim 1: Develop a multiscale computational model of the lung parenchyma. The alveolar structure of the parenchyma will be represented as a 3D network of elastic sheets. Autonomous agents will be used to represent various cell types, such as fibroblasts and inflammatory cells, in the tissue. The agents adhering to rule sets defining their stochastic migration and their secretion of inflammatory and enzymatic factors that remodel elastin and collagen will be placed throughout the network. Agent movement and activity will be determined throughout time as the network breathes. The physics-based and agent-based components of the model will be linked through the effects of stress and strain on agent responses that maintain local ECM properties, which in turn determine the global mechanics of the network. Aim 2: Determine the spatial and temporal distribution of ECM composition and inflammation in rodent models of emphysema and pulmonary fibrosis. Emphysema and fibrosis will be induced by cigarette smoke extract and bleomycin, respectively, in rats. The degree of correspondence between cell and injury locations throughout the tissue will be determined and used to derive rules of behavior for the various cell types for the agent-based model of Aim 1. Aim 3: Determine how macroscopic structure and parenchymal mechanics evolve over time in rodent models of emphysema and pulmonary fibrosis. The structure on micro-CT and the mechanical characteristics of the lungs in the animal models will be followed over time in order to determine how ECM structure-function evolves with advancing pathology, and to validate the physics-based ECM network model in Aim 1. Aim 4: Predict tissue structure and function during the evolution of emphysema and pulmonary fibrosis. The model of Aim 1 will be initialized away from the homeostatic state, allowed to evolve over time and its structure and function compared to experimental observations from Aims 2 and 3. Ultimately, we will develop a novel multi-scale modeling approach to ECM maintenance applicable to any ECM tissue, which in turn can be used to predict disease progression and understand novel therapeutic procedures.

细胞创造了自己的生化和机械环境，同时又非常敏感