Continuous Biosensor Based on Particle Motion: How Does the Concentration Measurement Precision Depend on Time Scale?

被引:0
|
作者
Lubken, Rafiq M. [1 ]
Lin, Yu-Ting [1 ]
Haenen, Stijn R. R. [1 ]
Bergkamp, Max H. [1 ]
Yan, Junhong [1 ]
Nommensen, Paul A. [2 ]
Prins, Menno W. J. [1 ,3 ,4 ,5 ]
机构
[1] Helia Biomonitoring, NL-5612 AR Eindhoven, Netherlands
[2] Avebe Innovat Ctr, NL-9747 AA Groningen, Netherlands
[3] Eindhoven Univ Technol, Dept Biomed Engn, Dept Appl Phys, NL-5612 AZ Eindhoven, Netherlands
[4] Eindhoven Univ Technol, Dept Appl Phys, NL-5612 AZ Eindhoven, Netherlands
[5] Eindhoven Univ Technol, Inst Complex Mol Syst ICMS, NL-5612 AZ Eindhoven, Netherlands
来源
ACS SENSORS | 2024年 / 9卷 / 09期
关键词
continuous biosensing; continuous monitoring; affinity-based sensing; measurement precision; analytical performance; TECHNOLOGY;
D O I
10.1021/acssensors.4c01586
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Continuous biosensors measure concentration-time profiles of biomolecular substances in order to allow for comparisons of measurement data over long periods of time. To make meaningful comparisons of time-dependent data, it is essential to understand how measurement imprecision depends on the time interval between two evaluation points, as the applicable imprecision determines the significance of measured concentration differences. Here, we define a set of measurement imprecisions that relate to different sources of variation and different time scales, ranging from minutes to weeks, and study these using statistical analyses of measurement data. The methodology is exemplified for Biosensing by Particle Motion (BPM), a continuous, affinity-based sensing technology with single-particle and single-molecule resolution. The studied BPM sensor measures specific small molecules (glycoalkaloids) in an industrial food matrix (potato fruit juice). Measurements were performed over several months at two different locations, on nearly 50 sensor cartridges with in total more than 1000 fluid injections. Statistical analyses of the measured signals and concentrations show that the relative residuals are normally distributed, allowing extraction and comparisons of the proposed imprecision parameters. The results indicate that sensor noise is the most important source of variation followed by sample pretreatment. Variations caused by fluidic transport, changes of the sensor during use (drift), and variations due to different sensor cartridges and cartridge replacements appear to be small. The imprecision due to sensor noise is recorded over few-minute time scales and is attributed to stochastic fluctuations of the single-molecule measurement principle, false-positive signals in the signal processing, and nonspecific interactions. The developed methodology elucidates both time-dependent and time-independent factors in the measurement imprecision, providing essential knowledge for interpreting concentration-time profiles as well as for further development of continuous biosensing technologies.
引用
收藏
页码:4924 / 4933
页数:10
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  • [1] Real-time continuous monitoring of dynamic concentration profiles studied with biosensing by particle motion
    Bergkamp, Max H.
    Cajigas, Sebastian
    van IJzendoorn, Leo J.
    Prins, Menno W. J.
    [J]. LAB ON A CHIP, 2023, 23 (20) : 4600 - 4609
  • [2] A Wireless Fiber Photometry System Based on a High-Precision CMOS Biosensor With Embedded Continuous-Time ΣΔ Modulation
    Khiarak, Mehdi Noormohammadi
    Martianova, Ekaterina
    Bories, Cyril
    Martel, Sylvain
    Proulx, Christophe. D.
    De Koninck, Yves
    Gosselin, Benoit
    [J]. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS, 2018, 12 (03) : 495 - 509
  • [3] Scale-up of bubbling fluidized beds with continuous particle flow based on particle-residence-time distribution
    Juwei Zhang
    Guangwen Xu
    [J]. Particuology, 2015, 19 (02) : 155 - 163
  • [4] Scale-up of bubbling fluidized beds with continuous particle flow based on particle-residence-time distribution
    Zhang, Juwei
    Xu, Guangwen
    [J]. PARTICUOLOGY, 2015, 19 : 155 - 163
  • [5] Exploring the potential for continuous measurement of ultrafine particle mass concentration (PM0.1) based on measurements of particle number concentration above 50nm (N50)
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    Patoulias, David
    Pandis, Spyros N.
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  • [6] Novel method for the continuous mass concentration measurement of ultrafine particles (PM0.1) with a water-based condensation particle counter (CPC)
    Argyropoulou, Georgia A.
    Kaltsonoudis, Christos
    Patoulias, David
    Pandis, Spyros N.
    [J]. AEROSOL SCIENCE AND TECHNOLOGY, 2024, 58 (10) : 1182 - 1193
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    So, Sunghyun
    Yoo, Miyeon
    Maeng, Saerom
    Hwang, Jungho
    Lee, Changyeop
    [J]. NANOSCIENCE AND NANOTECHNOLOGY LETTERS, 2018, 10 (08) : 1080 - 1087
  • [8] Sandwich Immunosensor Based on Particle Motion: How Do Reactant Concentrations and Reaction Pathways Determine the Time-Dependent Response of the Sensor?
    Michielsen, Claire M. S.
    Buskermolen, Alissa D.
    de Jong, Arthur M.
    Prins, Menno W. J.
    [J]. ACS SENSORS, 2023, 8 (11) : 4216 - 4225
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    Meszaros, Lilla Alexandra
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    Nagy, Zsombor Kristof
    [J]. INTERNATIONAL JOURNAL OF PHARMACEUTICS, 2023, 641