journal article·2026-07

A potent antioxidant and antimicrobial caffeic acid-Cu2+ crosslinked gelatin hydrogel for rapid hemostasis and inflammation-resolving wound healing

Yue Zhu, Shuang Yan, Lan Yin, Changqiang Wu, Siyu Wang, Ying Zhou, Yongchao Yao, Zuhua Wang

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Abstract

Traumatic injuries present a critical challenge in emergency medicine, requiring multifunctional materials that can provide hemostasis, antibacterial protection, and tissue regeneration. Herein, we report an injectable caffeic acid-gelatin-borax hydrogel (CAGAB) prepared via a facile one-step mixing method. In this design, borax forms a reversible dynamic network with gelatin to enhance mechanical integrity and wet-tissue adhesion, while Cu2+-CA coordination network provides antibacterial and antioxidant bioactivity and further reinforces the matrix. CAGAB demonstrates superior reactive oxygen species (ROS)-scavenging activity, with up to 96% radical elimination, and effectively protects fibroblasts from oxidative stress. It exhibits broad-spectrum antibacterial activity, nearly eradicating Staphylococcus aureus and Escherichia coli disrupting established biofilms. In vitro and in vivo hemostatic assays show rapid coagulation, reducing bleeding time from 300 s to 110 s. Additionally, CAGAB accelerates wound closure (82% within 7 days) and promotes near-complete healing by day 14. Histological analysis reveals dense collagen deposition, minimal inflammation, and a downregulation of proinflammatory cytokines (IL-6, TNF-α). Transcriptomic analysis further indicates suppression of oxidative stress- and inflammation-related pathways, including TNF and IL-17 signaling. Overall, this simple, multifunctional CAGAB hydrogel offers a promising strategy for emergency hemostasis and infected wound healing.
Source: europepmc · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Wound Healing and Treatments · Hydrogels: synthesis, properties, applications · Collagen: Extraction and Characterization

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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