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Dynamic Multiscale Regulation of Perfusion Recovery in Experimental Peripheral Arterial Disease: A Mechanistic Computational Model
In peripheral arterial disease (PAD), the degree of endogenous capacity to modulate revascularization of limb muscle is central to the management of leg ischemia. To characterize the multiscale and multicellular nature of revascularization in PAD, we have developed the first computational systems bi...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8807862/ https://www.ncbi.nlm.nih.gov/pubmed/35128207 http://dx.doi.org/10.1016/j.jacbts.2021.10.014 |
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author | Zhao, Chen Heuslein, Joshua L. Zhang, Yu Annex, Brian H. Popel, Aleksander S. |
author_facet | Zhao, Chen Heuslein, Joshua L. Zhang, Yu Annex, Brian H. Popel, Aleksander S. |
author_sort | Zhao, Chen |
collection | PubMed |
description | In peripheral arterial disease (PAD), the degree of endogenous capacity to modulate revascularization of limb muscle is central to the management of leg ischemia. To characterize the multiscale and multicellular nature of revascularization in PAD, we have developed the first computational systems biology model that mechanistically incorporates intracellular, cellular, and tissue-level features critical for the dynamic reconstitution of perfusion after occlusion-induced ischemia. The computational model was specifically formulated for a preclinical animal model of PAD (mouse hindlimb ischemia [HLI]), and it has gone through multilevel model calibration and validation against a comprehensive set of experimental data so that it accurately captures the complex cellular signaling, cell–cell communication, and function during post-HLI perfusion recovery. As an example, our model simulations generated a highly detailed description of the time-dependent spectrum-like macrophage phenotypes in HLI, and through model sensitivity analysis we identified key cellular processes with potential therapeutic significance in the pathophysiology of PAD. Furthermore, we computationally evaluated the in vivo effects of different targeted interventions on post-HLI tissue perfusion recovery in a model-based, data-driven, virtual mouse population and experimentally confirmed the therapeutic effect of a novel model-predicted intervention in real HLI mice. This novel multiscale model opens up a new avenue to use integrative systems biology modeling to facilitate translational research in PAD. |
format | Online Article Text |
id | pubmed-8807862 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-88078622022-02-04 Dynamic Multiscale Regulation of Perfusion Recovery in Experimental Peripheral Arterial Disease: A Mechanistic Computational Model Zhao, Chen Heuslein, Joshua L. Zhang, Yu Annex, Brian H. Popel, Aleksander S. JACC Basic Transl Sci Preclinical Research In peripheral arterial disease (PAD), the degree of endogenous capacity to modulate revascularization of limb muscle is central to the management of leg ischemia. To characterize the multiscale and multicellular nature of revascularization in PAD, we have developed the first computational systems biology model that mechanistically incorporates intracellular, cellular, and tissue-level features critical for the dynamic reconstitution of perfusion after occlusion-induced ischemia. The computational model was specifically formulated for a preclinical animal model of PAD (mouse hindlimb ischemia [HLI]), and it has gone through multilevel model calibration and validation against a comprehensive set of experimental data so that it accurately captures the complex cellular signaling, cell–cell communication, and function during post-HLI perfusion recovery. As an example, our model simulations generated a highly detailed description of the time-dependent spectrum-like macrophage phenotypes in HLI, and through model sensitivity analysis we identified key cellular processes with potential therapeutic significance in the pathophysiology of PAD. Furthermore, we computationally evaluated the in vivo effects of different targeted interventions on post-HLI tissue perfusion recovery in a model-based, data-driven, virtual mouse population and experimentally confirmed the therapeutic effect of a novel model-predicted intervention in real HLI mice. This novel multiscale model opens up a new avenue to use integrative systems biology modeling to facilitate translational research in PAD. Elsevier 2022-01-05 /pmc/articles/PMC8807862/ /pubmed/35128207 http://dx.doi.org/10.1016/j.jacbts.2021.10.014 Text en © 2022 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Preclinical Research Zhao, Chen Heuslein, Joshua L. Zhang, Yu Annex, Brian H. Popel, Aleksander S. Dynamic Multiscale Regulation of Perfusion Recovery in Experimental Peripheral Arterial Disease: A Mechanistic Computational Model |
title | Dynamic Multiscale Regulation of Perfusion Recovery in Experimental Peripheral Arterial Disease: A Mechanistic Computational Model |
title_full | Dynamic Multiscale Regulation of Perfusion Recovery in Experimental Peripheral Arterial Disease: A Mechanistic Computational Model |
title_fullStr | Dynamic Multiscale Regulation of Perfusion Recovery in Experimental Peripheral Arterial Disease: A Mechanistic Computational Model |
title_full_unstemmed | Dynamic Multiscale Regulation of Perfusion Recovery in Experimental Peripheral Arterial Disease: A Mechanistic Computational Model |
title_short | Dynamic Multiscale Regulation of Perfusion Recovery in Experimental Peripheral Arterial Disease: A Mechanistic Computational Model |
title_sort | dynamic multiscale regulation of perfusion recovery in experimental peripheral arterial disease: a mechanistic computational model |
topic | Preclinical Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8807862/ https://www.ncbi.nlm.nih.gov/pubmed/35128207 http://dx.doi.org/10.1016/j.jacbts.2021.10.014 |
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