Related Experiment Video
Updated: Jun 18, 2025

11:43
Hyperpolarized 13C Metabolic Magnetic Resonance Spectroscopy and Imaging
Published on: December 30, 2016
10.5K
Operational stability study of lactate biosensors: modeling, parameter identification, and stability analysis
Vasyl Martsenyuk1, Oleksandr Soldatkin2, Aleksandra Klos-Witkowska1
1Department of Computer Science and Automatics, University of Bielsko-Biala, Bielsko-Biala, Poland.
Frontiers in Bioengineering and Biotechnology
|August 2, 2024
Summary
This study analyzes lactate biosensor stability using kinetic models with delays. Findings show discrete delay models exhibit marginal stability, impacting sensor performance and requiring careful interpretation of results.
Area of Science:
- Biomedical Engineering
- Biotechnology
- Chemical Kinetics
Background:
- Lactate biosensors are vital for biomedical and biotechnological applications.
- Understanding their operational stability is crucial for reliable performance.
- Existing models may not fully capture the complex dynamics influenced by delays.
Purpose of the Study:
- To investigate the operational stability of lactate biosensors.
- To develop and analyze a mathematical model incorporating kinetic and delay elements.
- To provide insights into factors affecting biosensor performance and reliability.
Main Methods:
- Construction of an amperometric transducer for lactate measurement.
- Development of a modeling framework using Brown and Michaelis-Menten kinetics with distributed and discrete delays.
- Application of nonlinear optimization for parameter ascertainment.
- Stability analysis via linearization and quasi-polynomial root scrutiny.
Main Results:
- Discrete delay models demonstrate marginal stability, existing between stable and unstable states.
- Criteria for verifying marginal stability based on characteristic quasi-polynomial roots were established.
- Increasing delays induce transitions from stable focus to limit cycles and period-doubling.
Conclusions:
- The discrete delay model offers a nuanced understanding of lactate biosensor dynamics.
- Delay significantly influences biosensor behavior, leading to complex dynamic phenomena.
- Limitations include potential loss of solution positivity with increasing delays, necessitating cautious model application.

