Dongyu Chen, Yumei Wen, Ping Li, Can Zuo, Yao Wang, Zhiyi Wu
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引用次数: 0
Abstract
Accurate and synchronized assessment of biochemical parameters, such as biomarker concentration and body fluid viscosity, is crucial for advancing early disease detection and health management. Conventional biomolecular multiparameter detection methods often rely on multiple sensors or analytical techniques, which introduce cross-talk between sensing modalities, data inconsistencies, and complex calibration requirements, ultimately compromising detection precision and adaptability. We propose a streamlined detection approach that leverages a single uncoated Quartz Crystal Microbalance (QCM) sensor to monitor the dynamic magnetized motion of biomolecules under multimodal magnetic field modulation. Unlike conventional QCM methods that rely on static mass loading effects, this approach enables the sensor to capture motion signals that encode information about biomolecule concentration and base liquid viscosity. A backpropagation (BP) neural network is employed to model the nonlinear coupling between these motion-derived signal characteristics and the target biochemical parameters. The proposed method is validated using prostate-specific antigen (PSA) as a biomolecular model analyte. Experimental results from blind tests, where both concentration and viscosity were simultaneously unknown, demonstrate a prediction accuracy of 90 % for concentrations ranging from 0.01 to 1000 ng/mL and 87 % for viscosities between 1 and 6 cP. By integrating multimodal magnetic modulation with QCM-based motion sensing and machine learning, the BP-MMM-QCM technique provides a versatile and high-precision solution for biomolecule analysis. Accurate detection of biomolecule concentrations is essential for early disease diagnosis as well as monitoring disease progression and therapeutic responses. This approach overcomes the limitations of conventional QCM methods and enables real-time, multi-parameter detection in a single assay, making it a promising tool for disease diagnostics and health monitoring applications.
期刊介绍:
Talanta provides a forum for the publication of original research papers, short communications, and critical reviews in all branches of pure and applied analytical chemistry. Papers are evaluated based on established guidelines, including the fundamental nature of the study, scientific novelty, substantial improvement or advantage over existing technology or methods, and demonstrated analytical applicability. Original research papers on fundamental studies, and on novel sensor and instrumentation developments, are encouraged. Novel or improved applications in areas such as clinical and biological chemistry, environmental analysis, geochemistry, materials science and engineering, and analytical platforms for omics development are welcome.
Analytical performance of methods should be determined, including interference and matrix effects, and methods should be validated by comparison with a standard method, or analysis of a certified reference material. Simple spiking recoveries may not be sufficient. The developed method should especially comprise information on selectivity, sensitivity, detection limits, accuracy, and reliability. However, applying official validation or robustness studies to a routine method or technique does not necessarily constitute novelty. Proper statistical treatment of the data should be provided. Relevant literature should be cited, including related publications by the authors, and authors should discuss how their proposed methodology compares with previously reported methods.