@article{Yue2024, 
author = {Ouyang Yue and Xuechuan Wang and Mengdi Hou and Siwei Sun and Manhui Zheng and Xiaoliang Zou and Zhongxue Bai and Chunlin Liu and Xinhua Liu},
title = {Multifunctional electroactive bio-adhesive for robustly-integrated wound therapy and postoperative wound-status warning and assessment},
year = {2024},
journal = {Nano Research},
volume = {17},
number = {5},
pages = {4359-4370},
keywords = {electroactive bio-adhesive, quadruple energy dissipation, comprehensive wound therapy, postoperative wound-status warning and assessment},
url = {https://www.sciopen.com/article/10.1007/s12274-023-6384-5},
doi = {10.1007/s12274-023-6384-5},
abstract = {Wound abnormalities such as secondary wound laceration and inflammation are common postoperative health hazards during clinical procedures. The continuous treatment, healing induction, and real-time visualization of wound status and complications, including wound re-tearing, inflammation, and morphology, are key focal points for comprehensive healthcare. Herein, an on-demand quadruple energy dissipative strategy was proposed for the nanoengineering of a physically and chemically synergistic double-layer gelatin-based bio-adhesive (DLGel) by combining a multi-network adhesive layer and a versatile electroactive energy dissipative layer based on contrivable interlocking micro-pillar arrays and crosslinked polymer chains. The subtly multiple energy dissipation designs enable DLGel with robust adhesive strength to omnipotently wet and dynamic tissue, providing a basis for reliable wound closure. DLGel achieves comprehensive wound-healing induction through electrical stimulation and possesses reversible underwater light/thermal adhesion, excellent hemostatic performance, outstanding antimicrobial properties, and self-repair capability. Furthermore, a novel deep-learning strategy is creatively established to respond to mechanical deformation due to wound anomalies. This strategy translates biological information into visual graphics, providing real-time early warning and assessment of postoperative wound-abnormality/-morphology, such as laceration, inflammation, and necrosis. Therefore, DLGel and its associated signal collection and processing protocol enable the integration of reliable wound closure, wound healing, and real-time postoperative wound-status warning and assessment within the unobservable and undetectable “black box” regions in a context of non-clinical comprehensive therapy.}
}