朱之灵

硕士生导师

所在单位:材料化学教研室

学历:博士研究生

办公地点:材料楼218房间

论文成果

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Machine Learning-Assisted High-Throughput Screening of Nanozymes for Ulcerative Colitis

发布时间:2025-07-14 点击次数:

关键字:TUMOR; MICROENVIRONMENT; EFFICACY
摘要:Remodeling of the tumor immune microenvironment and enhancement of antitumor immune responses are necessary to overcome immunotherapy resistance in tumors. However, tumor heterogeneity and complexity of immune evasion mechanisms pose significant therapeutic challenges. Nanozymes exhibit enzyme-like characteristics and unique nanomaterial properties, showing potential for tumor therapy. However, design of effective nanozymes remains complex, inefficient, and functionally limited. Therefore, in this study, a novel strategy combining rationally designed single-atom nanozymes (SAzymes) with immune checkpoint blockade (ICB) therapy is established. Molybdenum SAzymes supported on graphitic carbon nitride (Mo SAs) are constructed using 25 transition metal candidates from the 4th to 6th periods based on high-throughput calculations and optimal piezoelectric-enhanced multienzyme-like activities. Upon activation by ultrasound, Mo SAs exerted potent therapeutic effects against ICB-resistant tumors and remodeled the tumor immune microenvironment by inducing tumor immunogenic cell death, alleviating tumor hypoxia, and modulating chemokine in tumors. Combination of Mo SAs with anti-programmed death protein-1 antibodies further enhanced their antitumor efficacy, highlighting their potential to treat ICB-resistant tumors.
卷号:35
期号:10
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