Integrating Pt nanoparticles with 3D Cu2-xSe/GO nanostructure to achieve nir-enhanced peroxidizing Nano-enzymes for dynamic monitoring the level of H2O2 during the inflammation

Autor: Man Shen, Xianling Dai, Dongni Ning, Hanqing Xu, Yang Zhou, Gangan Chen, Zhangyin Ren, Ming Chen, Mingxuan Gao, Jing Bao
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Frontiers in Immunology, Vol 15 (2024)
Druh dokumentu: article
ISSN: 1664-3224
DOI: 10.3389/fimmu.2024.1392259
Popis: The treatment of wound inflammation is intricately linked to the concentration of reactive oxygen species (ROS) in the wound microenvironment. Among these ROS, H2O2 serves as a critical signaling molecule and second messenger, necessitating the urgent need for its rapid real-time quantitative detection, as well as effective clearance, in the pursuit of effective wound inflammation treatment. Here, we exploited a sophisticated 3D Cu2-xSe/GO nanostructure-based nanonzymatic H2O2 electrochemical sensor, which is further decorated with evenly distributed Pt nanoparticles (Pt NPs) through electrodeposition. The obtained Cu2-xSe/GO@Pt/SPCE sensing electrode possesses a remarkable increase in specific surface derived from the three-dimensional surface constructed by GO nanosheets. Moreover, the localized surface plasma effect of the Cu2-xSe nanospheres enhances the separation of photogenerated electron-hole pairs between the interface of the Cu2-xSe NPs and the Pt NPs. This innovation enables near-infrared light-enhanced catalysis, significantly reducing the detection limit of the Cu2-xSe/GO@Pt/SPCE sensing electrode for H2O2 (from 1.45 μM to 0.53μM) under NIR light. Furthermore, this biosensor electrode enables in-situ real-time monitoring of H2O2 released by cells. The NIR-enhanced Cu2-xSe/GO@Pt/SPCE sensing electrode provide a simple-yet-effective method to achieve a detection of ROS (H2O2、-OH) with high sensitivity and efficiency. This innovation promises to revolutionize the field of wound inflammation treatment by providing clinicians with a powerful tool for accurate and rapid assessment of ROS levels, ultimately leading to improved patient outcomes.
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