Development of Frequency Based Taste Receptors Using Bioinspired Glucose Nanobiosensor

Area of Science:

• Biomedical Engineering
• Nanotechnology
• Biosensors

Background:

• Current glucose monitoring methods face limitations in sensitivity and specificity.
• Artificial taste receptors offer a promising avenue for developing advanced diagnostic tools.
• Bioinspired designs can enhance the functionality and efficiency of biosensors.

Purpose of the Study:

• To fabricate a bioinspired nanobiosensor for glucose diagnosis using electronic-based artificial taste receptors.
• To mimic the signal-processing mechanism of taste nerves for enhanced glucose detection.
• To validate the sensor's performance through oscillation analysis and computational modeling.

Main Methods:

• Fabrication of a bioinspired glucose nanobiosensor integrating an amperometric glucose biosensor with taste bud-inspired circuits.
• Design of two-layered circuits (Type II and Type III cells) inspired by taste nerve signal processing.
• Utilizing glucose oxidase for glucose detection and transducing signals into pulse patterns.
• Analyzing output pulse frequency and interpulse intervals as a function of glucose concentration.
• Conducting computational analysis to validate the sensor's behavior.

Main Results:

• The nanobiosensor demonstrated an increased output pulse frequency with rising glucose concentrations.
• At high glucose levels, the sensor exhibited a distinct pulse train with alternating short and long interpulse intervals.
• Computational analysis successfully reproduced the observed alternating pulse behavior, confirming the sensor's hypothesis.
• The sensor's performance correlated with changes in resistivity, validated by computational modeling.

Conclusions:

• The developed bioinspired glucose nanobiosensor effectively detects glucose concentrations through pulse pattern analysis.
• The artificial taste bud-inspired circuitry provides a novel approach for neural-like signal processing in biosensing.
• This technology holds potential for improved glucose diagnostics and continuous monitoring applications.