Title |
Nanozyme‐Based Robotics Approach for Targeting Fungal Infection
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Published in |
Advanced Materials, July 2023
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DOI | 10.1002/adma.202300320 |
Pubmed ID | |
Authors |
Min Jun Oh, Seokyoung Yoon, Alaa Babeer, Yuan Liu, Zhi Ren, Zhenting Xiang, Yilan Miao, David P. Cormode, Chider Chen, Edward Steager, Hyun Koo |
Abstract |
Fungal pathogens have been designated by the World Health Organization as microbial threats of the highest priority for global health. It remains a major challenge to improve antifungal efficacy at the site of infection while avoiding off-target effects, fungal spreading, and drug tolerance. Here, w e develop a nanozyme-based microrobotic platform that directs localized catalysis to the infection site with microscale precision to achieve targeted and rapid fungal killing. Using electromagnetic field frequency modulation and fine-scale spatiotemporal control, structured iron oxide nanozyme assemblies are formed that display tunable dynamic shape transformation and catalysis activation. The catalytic activity varies depending on the motion, velocity, and shape providing controllable reactive oxygen species (ROS) generation. Unexpectedly, nanozyme assemblies bind avidly to fungal (Candida albicans) surfaces to enable concentrated accumulation and targeted ROS-mediated killing in situ. By exploiting these tunable properties and selective binding, localized antifungal activity is achieved using in vivo-like cell spheroid and animal tissue infection models. Structured nanozyme assemblies are directed to Candida-infected sites using programmable algorithms to perform precisely guided spatial targeting and on-site catalysis resulting in fungal eradication within 10 minutes. This nanozyme-based microrobotics approach provides a uniquely effective and targeted therapeutic modality for pathogen elimination at the infection site. This article is protected by copyright. All rights reserved. |
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India | 1 | 10% |
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Unknown | 6 | 60% |
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Researcher | 1 | 11% |
Lecturer | 1 | 11% |
Student > Doctoral Student | 1 | 11% |
Unknown | 6 | 67% |
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Engineering | 2 | 22% |
Business, Management and Accounting | 1 | 11% |
Unknown | 6 | 67% |