Lactate Sensors for Early Detection of Metabolic Disorders in Dynamic Muscle Tissue Models

Area of Science:

• Biomedical Engineering
• Electrochemical Sensing
• Metabolic Diagnostics

Background:

• Lactate monitoring is crucial for diagnosing metabolic disorders like mitochondrial myopathies.
• Assessing lactate during physiological states like exercise is promising but limited by current sensor instability and slow response times.
• Existing metabolite sensors struggle with mechanical stress from muscle contractions, hindering real-time lactate dynamics capture.

Purpose of the Study:

• To develop and evaluate a novel, biocompatible, and acutely implantable lactate sensor.
• To assess the sensor's performance in a biomechanical environment mimicking muscle tissue.
• To enable real-time lactate monitoring for improved diagnosis and management of metabolic disorders.

Main Methods:

• Fabrication of a flexible substrate sensor with a lactate oxidase enzyme layer for electrochemical detection.
• Testing sensor performance in a hydrogel model simulating resting and contracting muscle states.
• Evaluation of sensor's mechanical stability, response time, and lactate diffusion dynamics.

Main Results:

• The sensor successfully detected physiologically relevant lactate concentrations (0.2-40 mM).
• Demonstrated robust mechanical stability and rapid response times under simulated muscle contractions.
• Successfully monitored lactate diffusion dynamics in a biomechanical environment.

Conclusions:

• The developed lactate sensor platform offers robust, real-time monitoring capabilities.
• This technology advances precision medicine for metabolic disorders by providing new diagnostic tools.
• Supports the use of lactate microsensors for screening metabolite imbalances and guiding interventions.