Graphical Abstract
![](https://wqketang.oss-cn-beijing.aliyuncs.com/unzip/large-zip/zip-a02a13d0-2dcb-4736-beb2-ef37c6d67f5b/6384/files/6384-TOC.jpg?Expires=1725757432&OSSAccessKeyId=STS.NSssK71aLjDMY9SbRgGRGskMT&Signature=aFt%2FSU3%2FnehbQEtCtdicqwBJG7w%3D&security-token=CAISywJ1q6Ft5B2yfSjIr5DGOPGD3L5t3YamWx%2FihlIyS91rnK7mtjz2IHtKenhsBOsbtfk1mG5W5%2FgZlqJ9SptIAEfJa9d99Myjb%2F9FltCT1fau5Jko1beHewHKeTOZsebWZ%2BLmNqC%2FHt6md1HDkAJq3LL%2Bbk%2FMdle5MJqP%2B%2FUFB5ZtKWveVzddA8pMLQZPsdITMWCrVcygKRn3mGHdfiEK00he8TouufTinpHMskGA1Aell7Mvyt6vcsT%2BXa5FJ4xiVtq55utye5fa3TRYgxowr%2Fwo0v0YpGya5YzHXwcPskvdKZbo78UqLQlla6w%2BGqFJqvPxr%2Fp8t%2Fx5fWJKAezhVgs8cVM8JOjIqKOscIsixo262SmqFV55c8Fdm%2BgUooJVgIMhTnduUfAPJAGOxzJitP%2BUVGGphr60TEnBL4rB5MUctfzRpwT64j3UTzDnGoABhFRSspTLrn9GrEN9pQYzC6eepGdfWDQh3fr5hA1VnwVUJMCz%2BNQEDWKceF%2FnEjWVMtfbvqYxuyhSCmIMMyh5bEREEKEiD%2BFVv4ZfsqnV7hQy5w6HhIkN8kZzP6L0zPvPgkBLOtdMDeDxhf8dVPrCSG4etXHjxcwUaRVb3ZR7Yu8gAA%3D%3D)
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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.
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