Bio-inspired artificial antioxidases with synergetic Cu/Zn redox-centers for mitochondrial dynamics regulation and senescent bone regeneration
Source abstract
Abstract
The regeneration of aging-associated bone defects is severely compromised by elevated oxidative stress and impaired mitochondrial function, which collectively undermine osteogenic capacity. Herein, we developed a biomimetic antioxidase based on a Cu/Zn synergistic metal–organic framework (CZpz-MOF) that structurally and functionally mimics the active center of natural Cu/Zn superoxide dismutase (SOD). The Zn-modulated Cu sites significantly enhanced the SOD-like activity, achieving a high catalytic efficiency of 45,173 U/mg, along with notable catalase (CAT)-like activity, enabling effective scavenging of multiple reactive oxygen species (ROS). By eliminating excess ROS, the CZpz-MOF ameliorated the pathological microenvironment and regulated macrophage polarization toward anti-inflammatory phenotype. In addition, the CZpz-MOF effectively scavenged mitochondrial ROS, restored mitochondrial membrane potential, and rebalanced mitochondrial dynamics, thereby interrupting the “ROS-induced ROS release” vicious cycle. It alleviated cellular senescence by reducing SA-β-gal activity and downregulating p21 and p16 expression. Significantly, the integration of Zn active element endowed the CZpz-MOF antioxidases with significant ability to promote osteogenesis. In an aged rat model of osteoporosis, the CZpz-MOF loaded hydrogel significantly accelerated bone regeneration. This study demonstrates that the biomimetic CZpz-MOF system synergistically integrates antioxidative and osteogenic functions via Cu/Zn cooperation, providing an effective strategy for treating aging-related bone defects.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Advanced Nanomaterials in Catalysis · Metal-Catalyzed Oxygenation Mechanisms · Nanoplatforms for cancer theranostics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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