Treffer: A Multiscale Computational Model of Endothelial-Immune Cell Interactions Regulated by Dynamic Wall Shear Stress.
Title:
A Multiscale Computational Model of Endothelial-Immune Cell Interactions Regulated by Dynamic Wall Shear Stress.
Authors:
Zhang YY; Institute of Cardio-Cerebrovascular Medicine, Central Hospital of Dalian University of Technology, Dalian, Liaoning, People's Republic of China.; School of Biomedical Engineering, Faculty of Medicine, Dalian University of Technology, Dalian, Liaoning, People's Republic of China., Wang YT; Institute of Cardio-Cerebrovascular Medicine, Central Hospital of Dalian University of Technology, Dalian, Liaoning, People's Republic of China.; School of Biomedical Engineering, Faculty of Medicine, Dalian University of Technology, Dalian, Liaoning, People's Republic of China., Li YJ; Institute of Cardio-Cerebrovascular Medicine, Central Hospital of Dalian University of Technology, Dalian, Liaoning, People's Republic of China.; School of Biomedical Engineering, Faculty of Medicine, Dalian University of Technology, Dalian, Liaoning, People's Republic of China., Qiu Y; Institute of Cardio-Cerebrovascular Medicine, Central Hospital of Dalian University of Technology, Dalian, Liaoning, People's Republic of China.; School of Biomedical Engineering, Faculty of Medicine, Dalian University of Technology, Dalian, Liaoning, People's Republic of China., Chen D; Institute of Cardio-Cerebrovascular Medicine, Central Hospital of Dalian University of Technology, Dalian, Liaoning, People's Republic of China.; School of Biomedical Engineering, Faculty of Medicine, Dalian University of Technology, Dalian, Liaoning, People's Republic of China., Qin KR; Institute of Cardio-Cerebrovascular Medicine, Central Hospital of Dalian University of Technology, Dalian, Liaoning, People's Republic of China.; School of Biomedical Engineering, Faculty of Medicine, Dalian University of Technology, Dalian, Liaoning, People's Republic of China.
Source:
International journal for numerical methods in biomedical engineering [Int J Numer Method Biomed Eng] 2026 Jan; Vol. 42 (1), pp. e70137.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Wiley Country of Publication: England NLM ID: 101530293 Publication Model: Print Cited Medium: Internet ISSN: 2040-7947 (Electronic) Linking ISSN: 20407939 NLM ISO Abbreviation: Int J Numer Method Biomed Eng Subsets: MEDLINE
Imprint Name(s):
Original Publication: [Oxford, UK] : Wiley
MeSH Terms:
References:
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S. S. Adkar and N. J. Leeper, “Efferocytosis in Atherosclerosis,” Nature Reviews Cardiology 21, no. 11 (2024): 762–779, https://doi.org/10.1038/s41569‐024‐01037‐7.
D. A. Chistiakov, A. N. Orekhov, and Y. V. Bobryshev, “Effects of Shear Stress on Endothelial Cells: Go With the Flow,” Acta Physiologica 219, no. 2 (2017): 382–408, https://doi.org/10.1111/apha.12725.
F. Li, S. Kumar, A. Pokutta‐Paskaleva, et al., “Endothelial Cell (EC)‐specific Ctgf/Ccn2 Expression Increases EC Reprogramming and Atherosclerosis,” Matrix Biology 136 (2025): 102–110, https://doi.org/10.1016/j.matbio.2025.01.003.
H. Ni, Y. Ge, Y. Zhuge, et al., “LncRNA MIR181A1HG Deficiency Attenuates Vascular Inflammation and Atherosclerosis,” Circulation Research 136, no. 8 (2025): 862–883, https://doi.org/10.1161/CIRCRESAHA.124.325196.
L. He, C.‐L. Zhang, Q. Chen, L. Wang, and Y. Huang, “Endothelial Shear Stress Signal Transduction and Atherogenesis: From Mechanisms to Therapeutics,” Pharmacology & Therapeutics 235 (2022): 108152, https://doi.org/10.1016/j.pharmthera.2022.108152.
X. Zhang, W. C. Sessa, and C. Fernández‐Hernando, “Endothelial Transcytosis of Lipoproteins in Atherosclerosis,” Frontiers in Cardiovascular Medicine 5 (2018): 5, https://doi.org/10.3389/fcvm.2018.00130.
H. Cheng, W. Zhong, L. Wang, et al., “Effects of Shear Stress on Vascular Endothelial Functions in Atherosclerosis and Potential Therapeutic Approaches,” Biomedicine & Pharmacotherapy 158 (2023): 114198, https://doi.org/10.1016/j.biopha.2022.114198.
L. Chen, H. Qu, B. Liu, et al., “Low or Oscillatory Shear Stress and Endothelial Permeability in Atherosclerosis,” Frontiers in Physiology 15 (2024): 15, https://doi.org/10.3389/fphys.2024.1432719.
Y.‐Y. Zhang, Y.‐J. Li, X.‐Q. Hu, et al., “Unveiling the Negative Synergistic Effect of Wall Shear Stress and Insulin on Endothelial NO Dynamics by Mathematical Modeling,” Bulletin of Mathematical Biology 87, no. 4 (2025): 46, https://doi.org/10.1007/s11538‐025‐01424‐2.
J. Amersfoort, G. Eelen, and P. Carmeliet, “Immunomodulation by Endothelial Cells — Partnering Up With the Immune System?,” Nature Reviews Immunology 22, no. 9 (2022): 576–588, https://doi.org/10.1038/s41577‐022‐00694‐4.
R. Bhui and H. N. Hayenga, “An Agent‐Based Model of Leukocyte Transendothelial Migration During Atherogenesis,” PLoS Computational Biology 13, no. 5 (2017): e1005523, https://doi.org/10.1371/journal.pcbi.1005523.
H. Zheng, L. Tai, C. Xu, W. Wang, Q. Ma, and W. Sun, “Microfluidic‐Based Cardiovascular Systems for Advanced Study of Atherosclerosis,” Journal of Materials Chemistry B 12, no. 30 (2024): 7225–7245, https://doi.org/10.1039/D4TB00756E.
R. Maringanti, C. G. M. Van Dijk, E. M. Meijer, et al., “Atherosclerosis on a Chip: A 3‐Dimensional Microfluidic Model of Early Arterial Events in Human Plaques,” Arteriosclerosis, Thrombosis, and Vascular Biology 44 (2024): ATVBAHA.124.321332, https://doi.org/10.1161/ATVBAHA.124.321332.
M. Cilla, E. Peña, and M. A. Martínez, “Mathematical Modelling of Atheroma Plaque Formation and Development in Coronary Arteries,” Journal of the Royal Society, Interface 11, no. 90 (2014): 20130866, https://doi.org/10.1098/rsif.2013.0866.
A. Parton, V. McGilligan, M. O'Kane, F. R. Baldrick, and S. Watterson, “Computational Modelling of Atherosclerosis,” Briefings in Bioinformatics 17, no. 4 (2016): 562–575, https://doi.org/10.1093/bib/bbv081.
G. Abi Younes and N. El Khatib, “Mathematical Modeling of Inflammatory Processes of Atherosclerosis,” Mathematical Modelling of Natural Phenomena 17 (2022): 5, https://doi.org/10.1051/mmnp/2022004.
J. Azimi‐Boulali, G. J. Mahler, B. T. Murray, and P. Huang, “Multiscale Computational Modeling of Aortic Valve Calcification,” Biomechanics and Modeling in Mechanobiology 23, no. 2 (2024): 581–599, https://doi.org/10.1007/s10237‐023‐01793‐4.
G. Jia, H. Yang, K. Wang, D. Huang, W. Chen, and Y. Shan, “The Modeling Study of the Effect of Morphological Behaviors of Extracellular Matrix Fibers on the Dynamic Interaction Between Tumor Cells and Antitumor Immune Response,” International Journal for Numerical Methods in Biomedical Engineering 38, no. 9 (2022): e3633, https://doi.org/10.1002/cnm.3633.
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Grant Information:
12372304 National Natural Science Foundation of China
Contributed Indexing:
Keywords: atherosclerosis; endothelial phenotype switching; monocyte cell recruitment; multiscale computational modeling; wall shear stress
Substance Nomenclature:
0 (Chemokine CCL2)
31C4KY9ESH (Nitric Oxide)
31C4KY9ESH (Nitric Oxide)
Entry Date(s):
Date Created: 20260111 Date Completed: 20260112 Latest Revision: 20260111
Update Code:
20260112
DOI:
10.1002/cnm.70137
PMID:
41521423
Database:
MEDLINE
Weitere Informationen
Atherosclerotic plaque formation alters local vascular geometry, leading to disturbed blood flow patterns. These geometric irregularities produce spatial heterogeneity in wall shear stress (WSS), which plays a critical role in endothelial dysfunction and early immune cell recruitment during atherogenesis. However, the dynamic effect of spatial heterogeneity of wall shear stress on endothelial-immune interactions remains unclear. A multiscale computational model that integrates hemodynamics, endothelial cell phenotype transitions, and immune responses was developed. The model is used to investigate endothelial cell (EC) phenotype transitions and immune cell dynamics under varying damage threshold (D <subscript>NO</subscript> ) conditions. Low-shear stress regions were found to expand with increasing D <subscript>NO</subscript> . Nitric oxide (NO) production was decreased, leading to accelerated EC activation and death. Monocyte Chemoattractant Protein-1 (MCP-1) expression was elevated, and monocyte recruitment and differentiation were enhanced, resulting in a higher proportion of pro-inflammatory M1 macrophages. The model reproduced experimental observations and provided robust predictions under different D <subscript>NO</subscript> scenarios. These results indicate that dynamic WSS drives EC state transitions and regulates immune cell recruitment and differentiation, providing a framework for studying vascular inflammation. Spatially heterogeneous WSS induces local NO depletion, which accelerates EC activation and death in low-shear stress regions, explaining focal endothelial dysfunction. EC injury further increases MCP-1 production, enhances monocyte recruitment, and promotes macrophage polarization toward a pro-inflammatory phenotype, demonstrating the ability of the model to capture flow-dependent vascular immune dynamics and inflammatory lesion development. This work provides mechanistic insight into the interplay between mechanical forces and vascular immune responses and may guide strategies for preventing endothelial injury and promoting anti-inflammatory therapy.
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