化学
唾液
计算生物学
电化学噪声
仿形(计算机编程)
生物分子
纳米技术
电化学
生物系统
原位
生物标志物
生物流体
先验与后验
生物标志物发现
电极
牙周病
作者
Jianwu Wang,Jiaofu Li,Chenyan Huang,Qianyun Deng,Ting Wang,Sa Wang,Xiao Li,Xiaopei Chi,Wei Peng Goh,Yuyu Liu,Chenyao Nie,F. Zhang,Zhisheng Lv,Jing Yu,Zhisheng Lv,Xiaoshi Wang,Rayner Bao Feng Ng,Jinwei Cao,Youquan Fu,Junqi Yi
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI