Issue 9, 2024

A nature-inspired multifunctional adhesive for cartilage tissue—biomaterial integration

Abstract

Surgical adhesives play a crucial role in tissue integration and repair, yet their application in wet conditions has been severely limited by inadequate adhesive strength and subpar biocompatibility. Furthermore, tissue adhesives have rarely been reported in cartilage tissue repair. In this study, a three-armed dopamine-modified hyaluronic acid derivative adhesive was prepared to function as a bio-inspired adhesive in moist environments. To meet the clinical requirements for cartilage tissue adhesion, we studied its chemical structure, including microscopic morphology, adhesion properties with materials and tissues, in vivo degradation rules, and biological evaluation. The OGMHA8-DOPA adhesive with the optimal aldehyde substitution degree and dopamine-grafting rate was determined by analyzing the experimental conditions. SEM results revealed that the cartilage tissue adhered to a porous interconnected structure. The excellent biocompatibility of the material not only facilitated chondrocyte adhesion but also supported their proliferation on its surface. Animal experiments have demonstrated that this material has no observable inflammatory response or incidence of fibrous capsule formation. The degradation timeline of the material extends beyond the duration of two weeks. The dopamine-modified adhesive exhibited a tight interfacial binding force between the biomaterial and cartilage tissue and excellent biocompatibility in watery tissue, revealing its potential for application in cartilage tissue repair and minimally invasive surgery.

Graphical abstract: A nature-inspired multifunctional adhesive for cartilage tissue—biomaterial integration

Article information

Article type
Paper
Submitted
16 Jan 2024
Accepted
30 Jan 2024
First published
09 Feb 2024

Soft Matter, 2024,20, 2017-2023

A nature-inspired multifunctional adhesive for cartilage tissue—biomaterial integration

B. Chu, Y. Chu, J. He, Z. Lin, C. Chen, S. Wang, W. Liu and X. Li, Soft Matter, 2024, 20, 2017 DOI: 10.1039/D4SM00065J

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