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Mechanically Robust Hemostatic Hydrogel Membranes with Programmable Strain-Adaptive Microdomain Entanglement for Wound Treatment in Dynamic Tissues.

Lu TanChenxi HuyanYanqiu WangMenghuan LiDong LiuMinghan LiuZhong LuoKaiyong CaiYan Hu
Published in: ACS nano (2024)
Supramolecular hydrogels emerge as a promising paradigm for sutureless wound management. However, their translation is still challenged by the insufficient mechanical robustness in the context of complex wounds in dynamic tissues. Herein, we report a tissue-adhesive supramolecular hydrogel membrane based on biocompatible precursors for dressing wounds in highly dynamic tissues, featuring robust mechanical resilience through programmable strain-adaptive entanglement among microdomains. Specifically, the hydrogels are synthesized by incorporating a long-chain polyurethane segment into a Schiff base-ligated short-chain oxidized cellulose/quaternized chitosan network via acylhydrazone bonding, which readily establishes interpenetrating entangled microdomains in dynamic cross-linked hydrogel matrices to enhance their tear and fatigue resistance against extreme mechanical stresses. After being placed onto dynamic tissues, the hydrogel dressing could efficiently absorb blood to achieve rapid hemostasis. Moreover, metal ions released from ruptured erythrocytes could be scavenged by the Schiff base linkers to form additional ionic bonds, which would trigger the cross-linking of the short-chain components and establish abundant crystalline microdomains, eventually leading to the in situ stiffening of the hydrogels to endure heavy mechanical loads. Benefiting from its hemostatic capacity and strain adaptable mechanical performance, this hydrogel wound dressing shows promise for the clinical management of various traumatic wounds.
Keyphrases
  • wound healing
  • drug delivery
  • hyaluronic acid
  • tissue engineering
  • gene expression
  • ionic liquid
  • climate change
  • drug release
  • spinal cord injury
  • physical activity
  • abdominal aortic aneurysm
  • deep learning