Cu-DHM nanozymes treat flap ischemia-reperfusion injury by amplifying immune modulation in a cascade manner and inhibiting cell apoptosis
Source abstract
Abstract
Flap ischemia-reperfusion (I/R) injury triggers intense inflammatory responses and oxidative stress following blood flow restoration, often resulting in tissue dysfunction. Currently, no effective and widely recognized treatment strategies are available in clinical practice. During flap I/R injury, macrophages, T cells, and neutrophils form a complex regulatory network that jointly participates in inflammatory responses, immune modulation, and tissue repair. Achieving a dynamic balance among these three cell types is critical for flap survival and healing. In this study, a novel Cu-DHM NP metal-polyphenol nanozyme that effectively amplifies immune modulation in a cascade manner, inhibits apoptosis, and treats flap I/R injury was developed. Leveraging their excellent antioxidant properties and SOD-like and CAT-like enzyme activities, Cu-DHM NPs eliminate ROS, alleviate intracellular oxidative stress, protect mitochondrial function, and reduce apoptosis. Moreover, Cu-DHM NPs can regulate the immune microenvironment, cascade and amplify the immunomodulatory effect between macrophages and Naive CD4 + T cells, increase the proportions of M2 macrophages and Treg cells, and alleviate inflammation. In animal experiments, Cu-DHM NPs downregulated several pathways associated with inflammation and cell death. Cu-DHM NPs inhibited apoptosis, reduced neutrophil infiltration, alleviated inflammation, enhanced angiogenesis, and ultimately improved flap survival rates. This novel metal-polyphenol nanozyme offers a new strategy for treating flap I/R injury by increasing immune modulation and inhibiting apoptosis.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Nanomaterials in Catalysis · Nanoplatforms for cancer theranostics · Infectious Aortic and Vascular Conditions
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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