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<p> A&#xa0;novel Micro-Electro-Mechanical Systems (MEMS) is introduced&#xa0;based biosensor architecture employing a three-dimensional localized electronic structure (3DLES) array capable of detecting trimethylamine N-oxide, (TMAO, (CH₃)₃NO),&#xa0;concentrations as low as 0.2&#xa0;μM in biological fluids such as urine or serum. The design incorporates a modified Cole–Cole model, wherein newly introduced parameters for the proposed 3DLES array biosensor are able to quantify enzymatic impedance effects. These variables offer insight into redox behavior and the fine-scale electrical currents generated by catalytic activity. On-chip signal processing is incorporated into the system, enabling fast detection within 1&#xa0;s and Yielding a high sensitivity of 320 ADC units per micromolar (equivalent to 5.5&#xa0;mV/μM). Very high repetition (98.1%) and low signal drift (0.4&#xa0;mV over time) further demonstrate the system’s reliability. TMAO detection is facilitated through minute variations in capacitive properties induced by the TorA enzyme, Yielding a detectable differential response of 10.6%. Comparison with traditional cyclic voltammetry (CV) shows excellent agreement, with only 0.024% deviation between methodologies. The 3DLES biosensor also exhibits a high TMAO-to-TMA conversion efficiency (88%) and impressive selectivity (97%) for the target analyte, making it a viable candidate for early-stage renal function assessment in non-clinical settings. The strong correlation between the proposed biosensor and mass spectrometry results across 100 urine samples (<i>R</i><sup>2</sup> = 0.954), along with the extracted linear equation <i>Y</i> = 120.9 − 39.2 × <i>X</i> (where <i>Y</i> is the ADC count of TMAO and <i>X</i> is the UACR), highlights the biosensor’s reliability and effectiveness in quantifying renal function biomarkers. This compact and cost-effective device offers a promising pathway toward at-home renal function pre-screening through metabolic profiling.</p> Graphical Abstract <p></p>

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Trimethylamine N-oxide detection for early prediction of renal function utilizing a three-dimensional localized electronic structure (3DLES) biosensor

  • 期刊论文

  • 发表日期：

    2025年10月6日

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  • Wei-Cheng Lin,
  • Wei-Lun Yen,
  • Yun-Yu Hsieh,
  • Bing-Hong Chen,
  • Yi-Huan Chang,
  • Tzu-Wei Chung

摘要

A novel Micro-Electro-Mechanical Systems (MEMS) is introduced based biosensor architecture employing a three-dimensional localized electronic structure (3DLES) array capable of detecting trimethylamine N-oxide, (TMAO, (CH₃)₃NO), concentrations as low as 0.2 μM in biological fluids such as urine or serum. The design incorporates a modified Cole–Cole model, wherein newly introduced parameters for the proposed 3DLES array biosensor are able to quantify enzymatic impedance effects. These variables offer insight into redox behavior and the fine-scale electrical currents generated by catalytic activity. On-chip signal processing is incorporated into the system, enabling fast detection within 1 s and Yielding a high sensitivity of 320 ADC units per micromolar (equivalent to 5.5 mV/μM). Very high repetition (98.1%) and low signal drift (0.4 mV over time) further demonstrate the system’s reliability. TMAO detection is facilitated through minute variations in capacitive properties induced by the TorA enzyme, Yielding a detectable differential response of 10.6%. Comparison with traditional cyclic voltammetry (CV) shows excellent agreement, with only 0.024% deviation between methodologies. The 3DLES biosensor also exhibits a high TMAO-to-TMA conversion efficiency (88%) and impressive selectivity (97%) for the target analyte, making it a viable candidate for early-stage renal function assessment in non-clinical settings. The strong correlation between the proposed biosensor and mass spectrometry results across 100 urine samples (R2 = 0.954), along with the extracted linear equation Y = 120.9 − 39.2 × X (where Y is the ADC count of TMAO and X is the UACR), highlights the biosensor’s reliability and effectiveness in quantifying renal function biomarkers. This compact and cost-effective device offers a promising pathway toward at-home renal function pre-screening through metabolic profiling.

Graphical Abstract