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Computationally-assisted wearable system for continuous cortisol monitoring.

作者信息

Liu Ying, Su Xiaoyu, Fan Peidi, Liu Xin, Pan Yuxiang, Ping Jianfeng

机构信息

Laboratory of Agricultural Information Intelligent Sensing, School of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China.

Innovation Platform of Micro/Nano Technology for Biosensing, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou 311200, China.

出版信息

Sci Bull (Beijing). 2025 Jun 30;70(12):2004-2013. doi: 10.1016/j.scib.2025.03.060. Epub 2025 Apr 17.

Abstract

Continuous cortisol monitoring (CCM) is essential for stress management, providing physiological insights into psychology and physical health. However, promising platform for CCM urges the design of effective biorecognition moieties and the skin integration of sophisticated functions. Herein, we present a computationally-assisted wearable system for CCM (CWSCCM) that leverages cutting-edge interdisciplinary technologies of in-situ regenerative molecularly imprinted polymers (MIP), signal amplifier organic electrochemical transistor (OECT), iontophoresis-based sweat induction, and microfluidic sweat sampling. The highly integrated system incorporated with OECT biosensor enables in-situ MIP regeneration, and offers continuous approach for cortisol monitoring, with an ultra-low limit of detection of 0.36 nmol/L. We validated the capability of the CWSCCM for long-term cortisol circadian rhythm monitoring in human participants, which shows superior sensitivity, selectivity, and continuous monitoring capabilities. In conclusion, we demonstrated how computational chemistry and OECT technology can extend the capabilities of current wearable CCM, which could potentially advance closed-loop therapeutics applications.

摘要

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