A Multiplexed and In Situ Self‐Calibration Biosensor Integrated System for Metabolic Health Analysis in Human Urine

Abstract Metabolic health is a major global health challenge associated with increased risks of disability, cancers, premature deaths, and a negative impact on patient quality of life. Precise monitoring of biomarkers in human urine, including metabolites and electrolytes, provides crucial guidance for treatment. While rich impurities in urine will induce cross‐interference of the biosensors array, making continuous and reliable analysis of multiple biomarkers challenging. To address these issues, a multiplexed and in situ self‐calibrated biosensing system (MSSCBS) is proposed with remarkably high stability and sensitivity in untreated urine samples. These desirable characteristics are achieved through the design of multiple electrochemical channels with self‐assembled nanostructure and an in situ bio‐signals self‐calibration method of dynamic normalized least mean squares. MSSCBS delivers reliable sensitivities (e.g., 0.04 µA/µ m for uric acid), a wide linear range (e.g., 0.2–23.6 m m for glucose), and long‐term stability (>20 days) of urinary impurities. Combination with a customized circuit for signal processing and wireless data transmission to mobiles supports convenient and long‐term continuous monitoring of urine. This study validates MSSCBS's usability in assessing metabolic states in healthy participants and patients with diabetes, kidney disease, showing the potential of at‐home biosensing platform for healthcare applications.

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Publication Details

Journal
Advanced Functional Materials
Published
2025-10-28
DOI
https://doi.org/10.1002/adfm.202520270
Citations
3
Primary Topic
Electrochemical sensors and biosensors
Type
article
Field-Weighted Citation Impact
2.19
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article

A Multiplexed and In Situ Self‐Calibration Biosensor Integrated System for Metabolic Health Analysis in Human Urine

Haipeng Wang, Chao Gai, Duan Wu, Yan Peng et al.
3 citations
Advanced Functional Materials
Electrochemical sensors and biosensors
2.19
article

A Multiplexed and In Situ Self‐Calibration Biosensor Integrated System for Metabolic Health Analysis in Human Urine

Haipeng Wang, Chao Gai, Duan Wu, Yan Peng, Zhongjing Ren, Bomi Gweon, Rui You, Zaiyu Zhang, Chen Wang, Yang Zhang, Luyang Zhang, Yu-Ting Huang, Ziran Wang
article en
3 citations

Abstract

Abstract Metabolic health is a major global health challenge associated with increased risks of disability, cancers, premature deaths, and a negative impact on patient quality of life. Precise monitoring of biomarkers in human urine, including metabolites and electrolytes, provides crucial guidance for treatment. While rich impurities in urine will induce cross‐interference of the biosensors array, making continuous and reliable analysis of multiple biomarkers challenging. To address these issues, a multiplexed and in situ self‐calibrated biosensing system (MSSCBS) is proposed with remarkably high stability and sensitivity in untreated urine samples. These desirable characteristics are achieved through the design of multiple electrochemical channels with self‐assembled nanostructure and an in situ bio‐signals self‐calibration method of dynamic normalized least mean squares. MSSCBS delivers reliable sensitivities (e.g., 0.04 µA/µ m for uric acid), a wide linear range (e.g., 0.2–23.6 m m for glucose), and long‐term stability (>20 days) of urinary impurities. Combination with a customized circuit for signal processing and wireless data transmission to mobiles supports convenient and long‐term continuous monitoring of urine. This study validates MSSCBS's usability in assessing metabolic states in healthy participants and patients with diabetes, kidney disease, showing the potential of at‐home biosensing platform for healthcare applications.

Advanced Functional MaterialsVol. 36(22)
Ludong University (CN), Sejong University (KR), Ministry of Education (PT), Suzhou Research Institute (CN), Qilu Hospital of Shandong University (CN), Artificial Intelligence in Medicine (Canada) (CA), Beijing Information Science & Technology University (CN)
Openalex Percentile: Top 11%
Electrochemical sensors and biosensors
2.19
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