4D printable semi-interpenetrating networks with robust tissue adhesion for smart self-deployable vascular closure

IF 7.7 2区 材料科学 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY
Kun Luo  (, ), Qiang Luo  (, ), Jing Guo  (, ), Zhong-Ming Xia  (, ), Mao Chen  (, ), Li Tang  (, ), Ke-Ke Yang  (, )
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引用次数: 0

Abstract

Interventional therapy has emerged as a transformative alternative to open surgery owing to its minimal invasiveness and fast recovery. However, it still presents risks of iatrogenic injury from vascular access, necessitating prompt and reliable vascular closure. Although various closure systems have been developed, they often suffer from complicated deployment procedures, potential for loosening, and risk of device migration. Herein, we develop a smart self-deployable vascular closure device enabled by a semi-interpenetrating network (sIPN) that synergistically integrates a programmable shape memory effect and robust tissue adhesion. The sIPN was designed by interpenetrating flexible, dopamine-functionalized poly(tetrahydrofuran) (PTD) chains into a photo-cross-linkable poly(ε-caprolactone)-based copolymer (PCC) network. The vascular closure model was fabricated via a UV-assisted fused deposition modeling printing strategy, significantly reducing mechanical anisotropy while facilitating structural customization. The resulting device exhibits autonomous self-deployment at 37 °C, along with reliable tissue adhesion under physiological conditions (maximum shear strength of 150.5 kPa). In vitro, the material demonstrates exceptional hemocompatibility (below 3%) and excellently enhanced cell migration (up to 38.9%). In vivo, immunofluorescence analysis reveals a promotion for CD31 (162.18%) and aSMA (154.93%) compared to the control group. These results highlight the PTD/PCC sIPN as a bioadaptive, multifunctional material platform for intelligent vascular closure, offering great promise for clinical translation in interventional therapies.

4D打印半互穿网络与强大的组织粘连智能自展开血管关闭
介入治疗因其侵入性小、恢复快而成为开放手术的一种变革性替代方法。然而,它仍然存在来自血管通路的医源性损伤风险,需要及时和可靠的血管关闭。尽管已经开发了各种封闭系统,但它们通常存在复杂的部署程序、松动的可能性和设备迁移的风险。在此,我们开发了一种由半互穿网络(sIPN)实现的智能自展开血管闭合装置,该装置协同集成了可编程形状记忆效应和强大的组织粘附性。通过互穿灵活的多巴胺功能化聚四氢呋喃(PTD)链,设计了可光交联的聚ε-己内酯基共聚物(PCC)网络。血管闭合模型通过uv辅助熔融沉积建模打印策略制作,显著降低了机械各向异性,同时便于结构定制。该装置在37°C下具有自主部署能力,在生理条件下具有可靠的组织粘附性(最大剪切强度为150.5 kPa)。在体外,该材料表现出优异的血液相容性(低于3%)和出色的细胞迁移能力(高达38.9%)。在体内,免疫荧光分析显示,与对照组相比,CD31(162.18%)和aSMA(154.93%)的表达有所提高。这些结果突出了PTD/PCC sin作为智能血管闭合的生物适应性多功能材料平台,为介入治疗的临床转化提供了巨大的希望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Science China Materials
Science China Materials Materials Science-General Materials Science
CiteScore
11.40
自引率
7.40%
发文量
949
期刊介绍: Science China Materials (SCM) is a globally peer-reviewed journal that covers all facets of materials science. It is supervised by the Chinese Academy of Sciences and co-sponsored by the Chinese Academy of Sciences and the National Natural Science Foundation of China. The journal is jointly published monthly in both printed and electronic forms by Science China Press and Springer. The aim of SCM is to encourage communication of high-quality, innovative research results at the cutting-edge interface of materials science with chemistry, physics, biology, and engineering. It focuses on breakthroughs from around the world and aims to become a world-leading academic journal for materials science.
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