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迈向预测植入物诱导的纤维化:巨噬细胞-成纤维细胞相互作用的标准化网络模型。

Towards predicting implant-induced fibrosis: A standardized network model of macrophage-fibroblast interactions.

作者信息

Marradi Matilde, van Griensven Martijn, Beijer Nick R M, de Boer Jan, Carlier Aurélie

机构信息

Department of Cell Biology-Inspired Tissue Engineering, MERLN Institute for Technology-Inspired Regenerative Medicine, Maastricht University, P.O. Box 616, Maastricht, MD 6200, the Netherlands.

National Institute of Public Health and Environment, Centre for Health Protection, Antonie van Leeuwenhoeklaan 9, Bilthoven, MA 3721, the Netherlands.

出版信息

Comput Struct Biotechnol J. 2025 Jul 13;27:3251-3263. doi: 10.1016/j.csbj.2025.07.022. eCollection 2025.


DOI:10.1016/j.csbj.2025.07.022
PMID:40746411
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12312070/
Abstract

The foreign body response (FBR) is a complex and multifaceted process that remains incompletely understood, often leading to complications in medical device integration. In this study, we constructed a literature-based network of the FBR and developed it into a semi-quantitative predictive model to better understand its dynamics. The FBR model incorporates key material-related factors, including immunogenic properties and mechanical mismatch, which influence immune cell activation and extracellular matrix (ECM) deposition. Predictions align with existing knowledge, showing that material stiffness and tissue progressive stiffening due to increased ECM deposition can exacerbate the FBR and that feedback interactions can protect the system from pathological outcome by gradually reducing the initial inflammatory input. The model also successfully replicated six out of eight experimental cases of anti-fibrotic interventions, demonstrating its potential as a predictive tool. Assessing implant safety in the early pre-clinical stages of device development is critical for ensuring long-term functionality and reducing adverse reactions. By systematically analyzing and integrating all interacting aspects of the FBR, modeling can provide valuable insights and complement and studies for improved implant safety assessment.

摘要

异物反应(FBR)是一个复杂且多方面的过程,目前仍未被完全理解,常常导致医疗器械整合过程中出现并发症。在本研究中,我们构建了一个基于文献的FBR网络,并将其发展为一个半定量预测模型,以更好地理解其动态变化。FBR模型纳入了与材料相关的关键因素,包括免疫原性特性和机械不匹配,这些因素会影响免疫细胞激活和细胞外基质(ECM)沉积。预测结果与现有知识相符,表明材料硬度以及由于ECM沉积增加导致的组织渐进性硬化会加剧FBR,并且反馈相互作用可以通过逐渐减少初始炎症输入来保护系统免受病理结果的影响。该模型还成功复制了八例抗纤维化干预实验中的六例,证明了其作为预测工具的潜力。在器械开发的临床前早期阶段评估植入物安全性对于确保长期功能和减少不良反应至关重要。通过系统地分析和整合FBR的所有相互作用方面,建模可为改进植入物安全性评估提供有价值的见解,并补充和完善相关研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1e3/12312070/e1d3cad39250/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1e3/12312070/590d9cd93843/ga1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1e3/12312070/a948ddaf6066/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1e3/12312070/bc8a638d7f06/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1e3/12312070/bc835e0bc6a0/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1e3/12312070/e1d3cad39250/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1e3/12312070/590d9cd93843/ga1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1e3/12312070/a948ddaf6066/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1e3/12312070/bc8a638d7f06/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1e3/12312070/bc835e0bc6a0/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1e3/12312070/e1d3cad39250/gr4.jpg

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本文引用的文献

[1]
Tuning Biomaterial Surfaces to Modulate Host-Immune Reactions.

Langmuir. 2025-7-15

[2]
Profiling of the macrophage response to polypropylene mesh burden in vivo.

Biomaterials. 2025-7

[3]
A call for standardization: Evaluating different methodologies to induce in vitro foreign body giant cell formation for biomaterials research and design.

Acta Biomater. 2025-3-1

[4]
Modulation of Biomaterial-Associated Fibrosis by Means of Combined Physicochemical Material Properties.

Adv Sci (Weinh). 2025-1

[5]
Insights gained from computational modeling of YAP/TAZ signaling for cellular mechanotransduction.

NPJ Syst Biol Appl. 2024-8-15

[6]
Fibroblast and myofibroblast activation in normal tissue repair and fibrosis.

Nat Rev Mol Cell Biol. 2024-8

[7]
A two-way street - cellular metabolism and myofibroblast contraction.

NPJ Regen Med. 2024-4-3

[8]
Beyond Encapsulation: Exploring Macrophage-Fibroblast Cross Talk in Implant-Induced Fibrosis.

Tissue Eng Part B Rev. 2024-12

[9]
An in silico modeling approach to understanding the dynamics of the post-burn immune response.

Front Immunol. 2024

[10]
Investigating Immunomodulatory Biomaterials for Preventing the Foreign Body Response.

Bioengineering (Basel). 2023-12-11

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