Continuous Biosensor Based on Particle Motion: How Does the Concentration Measurement Precision Depend on Time Scale?: How Does the Concentration Measurement Precision Depend on Time Scale?
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| Název: | Continuous Biosensor Based on Particle Motion: How Does the Concentration Measurement Precision Depend on Time Scale?: How Does the Concentration Measurement Precision Depend on Time Scale? |
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| Autoři: | Rafiq M. Lubken, Yu-Ting Lin, Stijn R. R. Haenen, Max H. Bergkamp, Junhong Yan, Paul A. Nommensen, Menno W. J. Prins |
| Zdroj: | ACS Sens |
| Informace o vydavateli: | American Chemical Society (ACS), 2024. |
| Rok vydání: | 2024 |
| Témata: | analytical performance, Time Factors, 4. Education, Biosensing Techniques, measurement precision, affinity-based sensing, continuous monitoring, Solanum tuberosum/chemistry, Fruit and Vegetable Juices, Motion, Fruit and Vegetable Juices/analysis, Biosensing Techniques/methods, continuous biosensing, Solanum tuberosum |
| Popis: | 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. |
| Druh dokumentu: | Article Other literature type |
| Jazyk: | English |
| ISSN: | 2379-3694 |
| DOI: | 10.1021/acssensors.4c01586 |
| Přístupová URL adresa: | https://pubmed.ncbi.nlm.nih.gov/39166946 https://research.tue.nl/en/publications/8e317caf-040b-498f-ab81-51913e686898 https://doi.org/10.1021/acssensors.4c01586 |
| Rights: | CC BY URL: http://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (http://creativecommons.org/licenses/by/4.0/). |
| Přístupové číslo: | edsair.doi.dedup.....63bf0eecf21bd6486621413fdc845057 |
| Databáze: | OpenAIRE |
Nájsť tento článok vo Web of Science | Abstrakt: | 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. |
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| ISSN: | 23793694 |
| DOI: | 10.1021/acssensors.4c01586 |