1. Article overview
As we all know, sutures are commonly used in surgical operations, but the current sutures used are limited by the performance and mechanical mismatch of the tissue and the lack of advanced functions. Unfortunately, existing improvement strategies can result in a decrease in the overall performance of the suture or lead to thin coatings that are easily broken or delamination. Inspired by tendon sheaths, researchers from the Department of Mechanical Engineering at McGill University in Canada reported a multifunctional strategy to functionalize fiber-based products such as sutures. Related research results were published on Science Advances with the title "Bioinspired tough gel sheath for robust and versatile surface functionalization", which attracted great attention.
This work shows that using this strategy can seamlessly combine surgical sutures, a hard gel protective layer, and various functional materials. Among them, the strong interface adhesion (> 2000 J m-2) shows a strong modification ability. When connected to the tissue, the surface stiffness, friction and resistance of the suture can be significantly reduced without affecting the tensile strength. The article then introduces multifunctional sutures for infection prevention, wound monitoring, drug delivery, and near-infrared imaging. This strategy is also applicable to other fiber-based equipment, and it is foreseeable that it will have a profound impact on a wide range of technical fields from wound treatment to smart textiles.

Two, graphic guide


Figure 1 Biologically inspired design of TGS suture.


Figure 2 Firm adhesion between TGS and suture.


Figure 3 Biomechanical properties of the improved TGS suture.


Figure 4 Universal TGS suture functionalization.


Figure 5 Fluorescent sutures used for NIR bioimaging.


Figure 6 In vivo biocompatibility and wound closure of original and TGS sutures.

3. Thesis information

Bioinspired tough gel sheath for robust and versatile surface functionalization
Science Advances (IF=13.116)
Pub Date: 2021-04-07
DOI: 10.1126/sciadv.abc3012
Zhenwei Ma, Zhen Yang, Qiman Gao, Guangyu Bao, Amin Valiei, Fan Yang, Ran Huo, Chen Wang, Guolong Song, Dongling Ma, Zu-Hua Gao, Jianyu Li
Department of Mechanical Engineering, McGill University, Montréal, QC H3A 0C3, Canada.