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DOI 10.1021/jacs.5c18235

Медицинская библиотека · Journal of the American Chemical Society · 2026

Electrochemomics Profiling Metabolic Dynamics in Biofluids.

Wang Jianwu, Xia Huarong, Huang Chenyan, Deng Qianyun, Wang Ting, Cai Pingqiang, Li Xiao, Chi Xiaopei, Goh Wei Peng, Liu Yahui, Nie Chenyao, Zhang Feilong, Wang Changxian, Yu Jing, Lv Zhisheng, Wang Xiaoshi, Ng Rayner Bao Feng, Cao Jinwei, Fu Youquan, Yi Junqi, Loh Xian Jun, Mandler Daniel, Gu Bing, Wei Yan, Chen Xiaodong

СтатьяПоддержка исследования: вне правительства СШАПеревод пока не подготовлен

Аннотация

Conventional electrochemical sensing techniques detect predefined molecular biomarkers for disease diagnosis, while compromised by the biases in the calibration process due to the complexity and volatility of peripheral biofluids. Meanwhile, abundant electrochemical information at the electrode-biofluid interfaces remains to be discovered to gain comprehensive metabolic signatures for diagnostic applications. Here, we propose an electrochemomics (EC-omics) approach to comprehensively profile the dynamics of electrochemical properties of biomolecules in peripheral biofluids during disease onset. As a proof of concept, we customized a portable electrochemical profiling platform, where the high sensitivity and low background noise of the carbon nanotube/bacterial cellulose (CNT/BC) electrodes enabled a holistic and unbiased capturing of the electrochemical features in biofluids. We applied the EC-omics platform to profile saliva for periodontitis diagnosis. The obtained saliva EC-omics database is compatible with various intelligent algorithms, which could accurately discriminate periodontitis (93%), surpassing the untargeted nuclear magnetic resonance data (89%) and significantly outperforming the periodontitis-related molecular biomarkers (70%) and peak intensity features (57%). Additionally, our study demonstrated the feasibility of EC-omics in human urine and mouse serum analysis, suggesting its potential to expand our understanding of the complex metabolic networks of biofluids and further foster a broader range of novel diagnostic tools across various sensing paradigms for decentralized healthcare.

Для цитирования: Wang Jianwu, Xia Huarong, Huang Chenyan, Deng Qianyun, Wang Ting, Cai Pingqiang, Li Xiao, Chi Xiaopei, Goh Wei Peng, Liu Yahui, Nie Chenyao, Zhang Feilong, Wang Changxian, Yu Jing, Lv Zhisheng, Wang Xiaoshi, Ng Rayner Bao Feng, Cao Jinwei, Fu Youquan, Yi Junqi, Loh Xian Jun, Mandler Daniel, Gu Bing, Wei Yan, Chen Xiaodong. Electrochemomics Profiling Metabolic Dynamics in Biofluids.. Journal of the American Chemical Society. 2026. DOI: 10.1021/jacs.5c18235.

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