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Optimization of loading protocols for tissue engineering experiments

Tissue engineering (TE) combines cells and biomaterials to treat orthopedic pathologies. Maturation of de novo tissue is highly dependent on local mechanical environments. Mechanical stimulation influences stem cell differentiation, however, the role of various mechanical loads remains unclear. Whil...

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Autores principales: Ladner, Yann D., Armiento, Angela R., Kubosch, Eva J., Snedeker, Jess G., Stoddart, Martin J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8948220/
https://www.ncbi.nlm.nih.gov/pubmed/35332169
http://dx.doi.org/10.1038/s41598-022-08849-y
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author Ladner, Yann D.
Armiento, Angela R.
Kubosch, Eva J.
Snedeker, Jess G.
Stoddart, Martin J.
author_facet Ladner, Yann D.
Armiento, Angela R.
Kubosch, Eva J.
Snedeker, Jess G.
Stoddart, Martin J.
author_sort Ladner, Yann D.
collection PubMed
description Tissue engineering (TE) combines cells and biomaterials to treat orthopedic pathologies. Maturation of de novo tissue is highly dependent on local mechanical environments. Mechanical stimulation influences stem cell differentiation, however, the role of various mechanical loads remains unclear. While bioreactors simplify the complexity of the human body, the potential combination of mechanical loads that can be applied make it difficult to assess how different factors interact. Human bone marrow-derived mesenchymal stromal cells were seeded within a fibrin-polyurethane scaffold and exposed to joint-mimicking motion. We applied a full factorial design of experiment to investigate the effect that the interaction between different mechanical loading parameters has on biological markers. Additionally, we employed planned contrasts to analyze differences between loading protocols and a linear mixed model with donor as random effect. Our approach enables screening of multiple mechanical loading combinations and identification of significant interactions that could not have been studied using classical mechanobiology studies. This is useful to screen the effect of various loading protocols and could also be used for TE experiments with small sample sizes and further combinatorial medication studies.
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spelling pubmed-89482202022-03-28 Optimization of loading protocols for tissue engineering experiments Ladner, Yann D. Armiento, Angela R. Kubosch, Eva J. Snedeker, Jess G. Stoddart, Martin J. Sci Rep Article Tissue engineering (TE) combines cells and biomaterials to treat orthopedic pathologies. Maturation of de novo tissue is highly dependent on local mechanical environments. Mechanical stimulation influences stem cell differentiation, however, the role of various mechanical loads remains unclear. While bioreactors simplify the complexity of the human body, the potential combination of mechanical loads that can be applied make it difficult to assess how different factors interact. Human bone marrow-derived mesenchymal stromal cells were seeded within a fibrin-polyurethane scaffold and exposed to joint-mimicking motion. We applied a full factorial design of experiment to investigate the effect that the interaction between different mechanical loading parameters has on biological markers. Additionally, we employed planned contrasts to analyze differences between loading protocols and a linear mixed model with donor as random effect. Our approach enables screening of multiple mechanical loading combinations and identification of significant interactions that could not have been studied using classical mechanobiology studies. This is useful to screen the effect of various loading protocols and could also be used for TE experiments with small sample sizes and further combinatorial medication studies. Nature Publishing Group UK 2022-03-24 /pmc/articles/PMC8948220/ /pubmed/35332169 http://dx.doi.org/10.1038/s41598-022-08849-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Ladner, Yann D.
Armiento, Angela R.
Kubosch, Eva J.
Snedeker, Jess G.
Stoddart, Martin J.
Optimization of loading protocols for tissue engineering experiments
title Optimization of loading protocols for tissue engineering experiments
title_full Optimization of loading protocols for tissue engineering experiments
title_fullStr Optimization of loading protocols for tissue engineering experiments
title_full_unstemmed Optimization of loading protocols for tissue engineering experiments
title_short Optimization of loading protocols for tissue engineering experiments
title_sort optimization of loading protocols for tissue engineering experiments
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8948220/
https://www.ncbi.nlm.nih.gov/pubmed/35332169
http://dx.doi.org/10.1038/s41598-022-08849-y
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