A computational bio-chemo-mechanical model of in vivo tissue-engineered vascular graft development
Abstract Stenosis is the primary complication of current tissue-engineered vascular grafts used in pediatric congenital cardiac surgery. Murine models provide considerable insight into the possible mechanisms underlying this situation, but they are not efficient for identifying optimal changes in sc...
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Veröffentlicht in: | Integrative biology (Cambridge) 2020-04, Vol.12 (3), p.47-63 |
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creator | Khosravi, Ramak Ramachandra, Abhay B Szafron, Jason M Schiavazzi, Daniele E Breuer, Christopher K Humphrey, Jay D |
description | Abstract
Stenosis is the primary complication of current tissue-engineered vascular grafts used in pediatric congenital cardiac surgery. Murine models provide considerable insight into the possible mechanisms underlying this situation, but they are not efficient for identifying optimal changes in scaffold design or therapeutic strategies to prevent narrowing. In contrast, computational modeling promises to enable time- and cost-efficient examinations of factors leading to narrowing. Whereas past models have been limited by their phenomenological basis, we present a new mechanistic model that integrates molecular- and cellular-driven immuno- and mechano-mediated contributions to in vivo neotissue development within implanted polymeric scaffolds. Model parameters are inferred directly from in vivo measurements for an inferior vena cava interposition graft model in the mouse that are augmented by data from the literature. By complementing Bayesian estimation with identifiability analysis and simplex optimization, we found optimal parameter values that match model outputs with experimental targets and quantify variability due to measurement uncertainty. Utility is illustrated by parametrically exploring possible graft narrowing as a function of scaffold pore size, macrophage activity, and the immunomodulatory cytokine transforming growth factor beta 1 (TGF-β1). The model captures salient temporal profiles of infiltrating immune and synthetic cells and associated secretion of cytokines, proteases, and matrix constituents throughout neovessel evolution, and parametric studies suggest that modulating scaffold immunogenicity with early immunomodulatory therapies may reduce graft narrowing without compromising compliance. |
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Stenosis is the primary complication of current tissue-engineered vascular grafts used in pediatric congenital cardiac surgery. Murine models provide considerable insight into the possible mechanisms underlying this situation, but they are not efficient for identifying optimal changes in scaffold design or therapeutic strategies to prevent narrowing. In contrast, computational modeling promises to enable time- and cost-efficient examinations of factors leading to narrowing. Whereas past models have been limited by their phenomenological basis, we present a new mechanistic model that integrates molecular- and cellular-driven immuno- and mechano-mediated contributions to in vivo neotissue development within implanted polymeric scaffolds. Model parameters are inferred directly from in vivo measurements for an inferior vena cava interposition graft model in the mouse that are augmented by data from the literature. By complementing Bayesian estimation with identifiability analysis and simplex optimization, we found optimal parameter values that match model outputs with experimental targets and quantify variability due to measurement uncertainty. Utility is illustrated by parametrically exploring possible graft narrowing as a function of scaffold pore size, macrophage activity, and the immunomodulatory cytokine transforming growth factor beta 1 (TGF-β1). The model captures salient temporal profiles of infiltrating immune and synthetic cells and associated secretion of cytokines, proteases, and matrix constituents throughout neovessel evolution, and parametric studies suggest that modulating scaffold immunogenicity with early immunomodulatory therapies may reduce graft narrowing without compromising compliance.</description><identifier>ISSN: 1757-9708</identifier><identifier>ISSN: 1757-9694</identifier><identifier>EISSN: 1757-9708</identifier><identifier>DOI: 10.1093/intbio/zyaa004</identifier><identifier>PMID: 32222759</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Algorithms ; Animal models ; Animals ; Bayes Theorem ; Bayesian analysis ; Blood Vessel Prosthesis ; Computer applications ; Computer Simulation ; Cytokines ; Fibroblasts - metabolism ; Grafting ; Growth factors ; Heart ; Heart surgery ; Heart transplantation ; Immunogenicity ; Immunomodulation ; Inflammation ; Macrophages ; Macrophages - metabolism ; Mathematical models ; Mice ; Monocytes - metabolism ; Optimization ; Original ; Parameter identification ; Pediatrics ; Polymers - chemistry ; Pore size ; Prosthesis Design ; Scaffolds ; Sensitivity and Specificity ; Signal Transduction ; Stenosis ; Tissue engineering ; Tissue Engineering - methods ; Tissue Scaffolds ; Transforming Growth Factor beta1 - metabolism ; Transforming growth factor-b1 ; Vena Cava, Inferior - surgery</subject><ispartof>Integrative biology (Cambridge), 2020-04, Vol.12 (3), p.47-63</ispartof><rights>The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. 2020</rights><rights>The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c452t-8d95f3f8e37f19b2a74ec4eb9be8fdf776593e65e568bbf1b68fb2dc25ddf77e3</citedby><cites>FETCH-LOGICAL-c452t-8d95f3f8e37f19b2a74ec4eb9be8fdf776593e65e568bbf1b68fb2dc25ddf77e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,776,780,881,1578,27903,27904</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32222759$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Khosravi, Ramak</creatorcontrib><creatorcontrib>Ramachandra, Abhay B</creatorcontrib><creatorcontrib>Szafron, Jason M</creatorcontrib><creatorcontrib>Schiavazzi, Daniele E</creatorcontrib><creatorcontrib>Breuer, Christopher K</creatorcontrib><creatorcontrib>Humphrey, Jay D</creatorcontrib><title>A computational bio-chemo-mechanical model of in vivo tissue-engineered vascular graft development</title><title>Integrative biology (Cambridge)</title><addtitle>Integr Biol (Camb)</addtitle><description>Abstract
Stenosis is the primary complication of current tissue-engineered vascular grafts used in pediatric congenital cardiac surgery. Murine models provide considerable insight into the possible mechanisms underlying this situation, but they are not efficient for identifying optimal changes in scaffold design or therapeutic strategies to prevent narrowing. In contrast, computational modeling promises to enable time- and cost-efficient examinations of factors leading to narrowing. Whereas past models have been limited by their phenomenological basis, we present a new mechanistic model that integrates molecular- and cellular-driven immuno- and mechano-mediated contributions to in vivo neotissue development within implanted polymeric scaffolds. Model parameters are inferred directly from in vivo measurements for an inferior vena cava interposition graft model in the mouse that are augmented by data from the literature. By complementing Bayesian estimation with identifiability analysis and simplex optimization, we found optimal parameter values that match model outputs with experimental targets and quantify variability due to measurement uncertainty. Utility is illustrated by parametrically exploring possible graft narrowing as a function of scaffold pore size, macrophage activity, and the immunomodulatory cytokine transforming growth factor beta 1 (TGF-β1). The model captures salient temporal profiles of infiltrating immune and synthetic cells and associated secretion of cytokines, proteases, and matrix constituents throughout neovessel evolution, and parametric studies suggest that modulating scaffold immunogenicity with early immunomodulatory therapies may reduce graft narrowing without compromising compliance.</description><subject>Algorithms</subject><subject>Animal models</subject><subject>Animals</subject><subject>Bayes Theorem</subject><subject>Bayesian analysis</subject><subject>Blood Vessel Prosthesis</subject><subject>Computer applications</subject><subject>Computer Simulation</subject><subject>Cytokines</subject><subject>Fibroblasts - metabolism</subject><subject>Grafting</subject><subject>Growth factors</subject><subject>Heart</subject><subject>Heart surgery</subject><subject>Heart transplantation</subject><subject>Immunogenicity</subject><subject>Immunomodulation</subject><subject>Inflammation</subject><subject>Macrophages</subject><subject>Macrophages - metabolism</subject><subject>Mathematical models</subject><subject>Mice</subject><subject>Monocytes - metabolism</subject><subject>Optimization</subject><subject>Original</subject><subject>Parameter identification</subject><subject>Pediatrics</subject><subject>Polymers - chemistry</subject><subject>Pore size</subject><subject>Prosthesis Design</subject><subject>Scaffolds</subject><subject>Sensitivity and Specificity</subject><subject>Signal Transduction</subject><subject>Stenosis</subject><subject>Tissue engineering</subject><subject>Tissue Engineering - methods</subject><subject>Tissue Scaffolds</subject><subject>Transforming Growth Factor beta1 - metabolism</subject><subject>Transforming growth factor-b1</subject><subject>Vena Cava, Inferior - surgery</subject><issn>1757-9708</issn><issn>1757-9694</issn><issn>1757-9708</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkc1LNSEUhyWKvrctQ2hTiynnw3HcBBF9QdCm1qLO8V5jRiedGej961_j3qLa5EbxPD7q-SF0lJPznPDywrpRWX_x711KQqoNtJszyjLOSLP5bb2D9mJ8JaSuErSNdsoiDUb5LlJXWPt-mEY5Wu9kh5Mt00vofdaDXkpnddrsfQsd9gZbh2c7ezzaGCfIwC2sAwjQ4llGPXUy4EWQZsQtzND5oQc3HqAtI7sIh-t5H73c3jxf32ePT3cP11ePma5oMWZNy6kpTQMlMzlXhWQV6AoUV9CY1jBWU15CTYHWjVImV3VjVNHqgrYfVSj30eXKO0yqh1anq4PsxBBsL8O78NKKnxVnl2LhZ8FySqucJsHpWhD82wRxFL2NGrpOOvBTFEXZVBXntC4SevILffVTSP1LFOUkdZqRMlHnK0oHH2MA8_WYnIiP-MQqPrGOLx04_v6FL_wzrwScrQA_DX_J_gNWFKpm</recordid><startdate>20200414</startdate><enddate>20200414</enddate><creator>Khosravi, Ramak</creator><creator>Ramachandra, Abhay B</creator><creator>Szafron, Jason M</creator><creator>Schiavazzi, Daniele E</creator><creator>Breuer, Christopher K</creator><creator>Humphrey, Jay D</creator><general>Oxford University Press</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>7QP</scope><scope>7QR</scope><scope>7T5</scope><scope>7TK</scope><scope>7TM</scope><scope>8FD</scope><scope>FR3</scope><scope>H94</scope><scope>P64</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20200414</creationdate><title>A computational bio-chemo-mechanical model of in vivo tissue-engineered vascular graft development</title><author>Khosravi, Ramak ; Ramachandra, Abhay B ; Szafron, Jason M ; Schiavazzi, Daniele E ; Breuer, Christopher K ; Humphrey, Jay D</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c452t-8d95f3f8e37f19b2a74ec4eb9be8fdf776593e65e568bbf1b68fb2dc25ddf77e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Algorithms</topic><topic>Animal models</topic><topic>Animals</topic><topic>Bayes Theorem</topic><topic>Bayesian analysis</topic><topic>Blood Vessel Prosthesis</topic><topic>Computer applications</topic><topic>Computer Simulation</topic><topic>Cytokines</topic><topic>Fibroblasts - metabolism</topic><topic>Grafting</topic><topic>Growth factors</topic><topic>Heart</topic><topic>Heart surgery</topic><topic>Heart transplantation</topic><topic>Immunogenicity</topic><topic>Immunomodulation</topic><topic>Inflammation</topic><topic>Macrophages</topic><topic>Macrophages - metabolism</topic><topic>Mathematical models</topic><topic>Mice</topic><topic>Monocytes - metabolism</topic><topic>Optimization</topic><topic>Original</topic><topic>Parameter identification</topic><topic>Pediatrics</topic><topic>Polymers - chemistry</topic><topic>Pore size</topic><topic>Prosthesis Design</topic><topic>Scaffolds</topic><topic>Sensitivity and Specificity</topic><topic>Signal Transduction</topic><topic>Stenosis</topic><topic>Tissue engineering</topic><topic>Tissue Engineering - methods</topic><topic>Tissue Scaffolds</topic><topic>Transforming Growth Factor beta1 - metabolism</topic><topic>Transforming growth factor-b1</topic><topic>Vena Cava, Inferior - surgery</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Khosravi, Ramak</creatorcontrib><creatorcontrib>Ramachandra, Abhay B</creatorcontrib><creatorcontrib>Szafron, Jason M</creatorcontrib><creatorcontrib>Schiavazzi, Daniele E</creatorcontrib><creatorcontrib>Breuer, Christopher K</creatorcontrib><creatorcontrib>Humphrey, Jay D</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Immunology Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Integrative biology (Cambridge)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Khosravi, Ramak</au><au>Ramachandra, Abhay B</au><au>Szafron, Jason M</au><au>Schiavazzi, Daniele E</au><au>Breuer, Christopher K</au><au>Humphrey, Jay D</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A computational bio-chemo-mechanical model of in vivo tissue-engineered vascular graft development</atitle><jtitle>Integrative biology (Cambridge)</jtitle><addtitle>Integr Biol (Camb)</addtitle><date>2020-04-14</date><risdate>2020</risdate><volume>12</volume><issue>3</issue><spage>47</spage><epage>63</epage><pages>47-63</pages><issn>1757-9708</issn><issn>1757-9694</issn><eissn>1757-9708</eissn><abstract>Abstract
Stenosis is the primary complication of current tissue-engineered vascular grafts used in pediatric congenital cardiac surgery. Murine models provide considerable insight into the possible mechanisms underlying this situation, but they are not efficient for identifying optimal changes in scaffold design or therapeutic strategies to prevent narrowing. In contrast, computational modeling promises to enable time- and cost-efficient examinations of factors leading to narrowing. Whereas past models have been limited by their phenomenological basis, we present a new mechanistic model that integrates molecular- and cellular-driven immuno- and mechano-mediated contributions to in vivo neotissue development within implanted polymeric scaffolds. Model parameters are inferred directly from in vivo measurements for an inferior vena cava interposition graft model in the mouse that are augmented by data from the literature. By complementing Bayesian estimation with identifiability analysis and simplex optimization, we found optimal parameter values that match model outputs with experimental targets and quantify variability due to measurement uncertainty. Utility is illustrated by parametrically exploring possible graft narrowing as a function of scaffold pore size, macrophage activity, and the immunomodulatory cytokine transforming growth factor beta 1 (TGF-β1). The model captures salient temporal profiles of infiltrating immune and synthetic cells and associated secretion of cytokines, proteases, and matrix constituents throughout neovessel evolution, and parametric studies suggest that modulating scaffold immunogenicity with early immunomodulatory therapies may reduce graft narrowing without compromising compliance.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>32222759</pmid><doi>10.1093/intbio/zyaa004</doi><tpages>17</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Animal models Animals Bayes Theorem Bayesian analysis Blood Vessel Prosthesis Computer applications Computer Simulation Cytokines Fibroblasts - metabolism Grafting Growth factors Heart Heart surgery Heart transplantation Immunogenicity Immunomodulation Inflammation Macrophages Macrophages - metabolism Mathematical models Mice Monocytes - metabolism Optimization Original Parameter identification Pediatrics Polymers - chemistry Pore size Prosthesis Design Scaffolds Sensitivity and Specificity Signal Transduction Stenosis Tissue engineering Tissue Engineering - methods Tissue Scaffolds Transforming Growth Factor beta1 - metabolism Transforming growth factor-b1 Vena Cava, Inferior - surgery |
title | A computational bio-chemo-mechanical model of in vivo tissue-engineered vascular graft development |
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