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From Transcript to Tissue: Multiscale Modeling from Cell Signaling to Matrix Remodeling

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From Transcript to Tissue: Multiscale Modeling from Cell Signaling to Matrix Remodeling

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dc.contributor.author Irons, Linda es_ES
dc.contributor.author Latorre, Marcos es_ES
dc.contributor.author Humphrey, Jay D. es_ES
dc.date.accessioned 2023-01-24T19:00:52Z
dc.date.available 2023-01-24T19:00:52Z
dc.date.issued 2021-07 es_ES
dc.identifier.issn 0090-6964 es_ES
dc.identifier.uri http://hdl.handle.net/10251/191453
dc.description.abstract [EN] Tissue-level biomechanical properties and function derive from underlying cell signaling, which regulates mass deposition, organization, and removal. Here, we couple two existing modeling frameworks to capture associated multiscale interactions¿one for vessel-level growth and remodeling and one for cell-level signaling¿and illustrate utility by simulating aortic remodeling. At the vessel level, we employ a constrained mixture model describing turnover of individual wall constituents (elastin, intramural cells, and collagen), which has proven useful in predicting diverse adaptations as well as disease progression using phenomenological constitutive relations. Nevertheless, we now seek an improved mechanistic understanding of these processes; we replace phenomenological relations in the mixture model with a logic-based signaling model, which yields a system of ordinary differential equations predicting changes in collagen synthesis, matrix metalloproteinases, and cell proliferation in response to altered intramural stress, wall shear stress, and exogenous angiotensin II. This coupled approach promises improved understanding of the role of cell signaling in achieving tissue homeostasis and allows us to model feedback between vessel mechanics and cell signaling. We verify our model predictions against data from the hypertensive murine infrarenal abdominal aorta as well as results from validated phenomenological models, and consider effects of noisy signaling and heterogeneous cell populations. es_ES
dc.description.sponsorship This work was supported by Grants from the US NIH (R01 HL105297, P01 HL134605, R01 HL139796, U01 HL142518, R01 HL146723) es_ES
dc.language Inglés es_ES
dc.publisher Springer-Verlag es_ES
dc.relation.ispartof Annals of Biomedical Engineering es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Mechanobiology es_ES
dc.subject Growth and remodeling es_ES
dc.subject Constrained mixtures es_ES
dc.subject Logic-based modeling es_ES
dc.subject Homeostasis es_ES
dc.title From Transcript to Tissue: Multiscale Modeling from Cell Signaling to Matrix Remodeling es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s10439-020-02713-8 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/NIH//R01 HL105297//Mechanisms Underlying the Progression of Arterial Stiffness in Hypertension/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/NIH//P01 HL134605 //Endothelial Mechanotransduction in Thoracic Aneurysm Formation and Progression/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/NIH//R01 HL139796//Improving Tissue Engineered Vascular Graft Performance via Computational Modeling/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/NIH//U01 HL142518//Multimodality imaging-driven multifidelity modeling of aortic dissection/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/NIH//R01 HL146723//Smooth Muscle Cell Proliferation and Degradative Phenotype in Thoracic Aorta Aneurysm and Dissection/ es_ES
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Irons, L.; Latorre, M.; Humphrey, JD. (2021). From Transcript to Tissue: Multiscale Modeling from Cell Signaling to Matrix Remodeling. Annals of Biomedical Engineering. 48(7):1701-1715. https://doi.org/10.1007/s10439-020-02713-8 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1007/s10439-020-02713-8 es_ES
dc.description.upvformatpinicio 1701 es_ES
dc.description.upvformatpfin 1715 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 48 es_ES
dc.description.issue 7 es_ES
dc.identifier.pmid 33415527 es_ES
dc.identifier.pmcid PMC8260704 es_ES
dc.relation.pasarela S\472454 es_ES
dc.contributor.funder National Institutes of Health, EEUU es_ES
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