RT Journal Article
T1 Magneto-mechanical system to reproduce and quantify complex strain patterns in biological materials
A1 Moreno Mateos, Miguel Ángel
A1 González-Rico, Jorge
A1 Nunez-Sardinha, Emanuel
A1 Gómez Cruz, Clara
A1 López-Donaire, María Luisa
A1 Lucarini San José, Sergio
A1 Arias Hernández, Ángel
A1 Muñoz Barrutia, María Arrate
A1 Velasco Bayón, Diego
A1 García González, Daniel
AB Biological cells and tissues are continuously subjected to mechanical stress and strain cues from their surrounding substrate. How these forces modulate cell and tissue behavior is a major question in mechanobiology. To conduct studies under controlled varying physiological strain scenarios, a new virtually-assisted experimental system is proposed allowing for non-invasive and real-time control of complex deformation modes within the substrates. This approach is based on the use of extremely soft magneto-active polymers, which mimic the stiffness of biological materials. Thus, the system enables the untethered control of biological substrates providing reversible mechanical changes and controlling heterogeneous patterns. Motivated on a deep magneto-mechanical characterization across scales, a multi-physics and multi-scale in silico framework was developed to guide the experimental stimulation setup. The versatility and viability of the system have been demonstrated through its ability to reproduce complex mechanical scenarios simulating local strain patterns in brain tissue during a head impact, and its capability to transmit physiologically relevant mechanical forces to dermal fibroblasts. The proposed framework opens the way to understanding the mechanobiological processes that occur during complex and dynamic deformation states, e.g., in traumatic brain injury, pathological skin scarring or fibrotic heart remodeling during myocardial infarction.
PB Elsevier
SN 2352-9407
YR 2022
FD 2022-06
LK https://hdl.handle.net/10016/36402
UL https://hdl.handle.net/10016/36402
LA eng
NO The authors thank Denis Wirtz (Johns Hopkins University) and Jean-Christophe Olivo-Marin (Institute Pasteur) for relevant discussion. The authors acknowledge support from the European Research Council (ERC) under the European Union's Horizon 2020 Research and Innovation Program (Grant agreement No. 947723, project: 4D-BIOMAP), and from Programa de Apoyo a la Realizacion de Proyectos Interdiscisplinares de I+D para Jovenes Investigadores de la Universidad Carlos III de Madrid and Comunidad de Madrid (project: BIOMASKIN). MAMM and CGC acknowledges support from the Ministerio de Ciencia, Innovacion y Universidades, Spain (FPU19/03874 and FPU20/01459) and DGG acknowledges support from the Talent Attraction grant (CM 2018 - 2018-T2/IND-9992) from the Comunidad de Madrid.
DS e-Archivo
RD 30 jun. 2024