Tendons/ligaments (T/L) regeneration is complex since scaffolds must have a nanometric fibrous structure and ensure appropriate biomimetic mechanical properties [1]. Electrospinning can replicate T/L from the fibrillarlevel up to the whole tissue [1,2]. Recently, Poly-Llactic acid/Collagen (PLLA/Coll) based, electrospun bundles and hierarchical scaffolds (EHS) have demonstrated to drive fibroblasts morphology and alignment both in static and dynamic cultures [3,4]. However, the full-field strain distribution, which drives the cellular fate, morphology and extracellular-matrix production on these structures at work, is totally unexplored so far. To achieve this goal, digital volume correlation (DVC) has proven to be a suitable technique [5]. This study aims at developing the first micro-CT in situ protocol in literature, to investigate the multiscale full-field strain distribution of electrospun scaffolds using DVC.

3d strain distribution via DVC in electrospun hierarchical scaffolds for tendon/ligament regeneration

Andrea Zucchelli;Nicola Sancisi;Carlo Gotti;Maria Letizia Focarete;Luca Cristofolini;
2023

Abstract

Tendons/ligaments (T/L) regeneration is complex since scaffolds must have a nanometric fibrous structure and ensure appropriate biomimetic mechanical properties [1]. Electrospinning can replicate T/L from the fibrillarlevel up to the whole tissue [1,2]. Recently, Poly-Llactic acid/Collagen (PLLA/Coll) based, electrospun bundles and hierarchical scaffolds (EHS) have demonstrated to drive fibroblasts morphology and alignment both in static and dynamic cultures [3,4]. However, the full-field strain distribution, which drives the cellular fate, morphology and extracellular-matrix production on these structures at work, is totally unexplored so far. To achieve this goal, digital volume correlation (DVC) has proven to be a suitable technique [5]. This study aims at developing the first micro-CT in situ protocol in literature, to investigate the multiscale full-field strain distribution of electrospun scaffolds using DVC.
2023
Proceedings of ESB 2023
202
202
Alberto Sensini, Andrea Zucchelli, Olga Stamati, Gregorio Marchiori, Nicola Sancisi, Carlo Gotti, Milena Fini, Maria Letizia Focarete, Luca Cristofolini, Gianluca Tozzi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/965171
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