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Metallothionein (MTs) serves as one of the biomarkers for early clinical diagnosis of malignant tumors, and developing economical and convenient detection methods remains of great significance. Metal-organic frameworks (MOFs) nanozymes have attracted much attention due to their excellent coordination networks, mesoporous structures, and adjustable pore volumes. Among them, the derivatization treatment of MOFs can further enhance the catalytic performance of MOF nanozymes and solve the problem of poor structural stability. However, the monotonization of the MOF derivatization strategy limits the diversity of the structure and composition of the nanozymes, which fundamentally restricts the further expansion of the catalytic activity and application scope of the nanozymes.
Based on this, the team led by Professor Yang Zhanjun and Li Juan from the College of Chemistry and Materials of Yangzhou University, and the team led by Director Xue Yadong from the Central Hospital of Jinhua, Zhejiang Province, proposed a SiO2 shell-mediated MOF hierarchical derivatization strategy. Through two steps of incomplete pyrolysis and NaOH etching, multi-dimensional flower-like Cu-Co3O4/CoOOH nanozymes were constructed. Thanks to their unique structure, diverse components, and uniform and abundant active sites, the constructed Cu-Co3O4/CoOOH nanozymes exhibit enhanced peroxidase-like (POD) activity. By utilizing the •OH scavenging property of MTs, a highly sensitive colorimetric biosensing metallothionein sensor mediated by Cu-Co3O4/CoOOH nanozymes was constructed, achieving the high-sensitivity detection of MTs (Figure 1). The research work was titled "Metal Organic Framework-Derived Multivariate Flower-Like Cu-Co3O4/CoOOH Nanozymes for Designing Colorimetric Biosensing Metallothioneins" and was published in Analytical Chemistry. The College of Chemistry and Materials of Yangzhou University is the first corresponding unit, and doctoral student Li Jiayin from the College of Chemistry and Materials is the first author of the paper, while doctoral students Chen Qingwen and Zhu Haibing are co-first authors.
