Estimation of maximal lactate steady state using the sweat lactate sensor

Area of Science:

• Exercise Physiology
• Sports Science
• Biotechnology

Background:

• Maximal lactate steady state (MLSS) is crucial for endurance performance.
• A simple, non-invasive method for MLSS assessment is lacking.
• Sweat lactate threshold (sLT) is a potential non-invasive biomarker.

Purpose of the Study:

• To investigate if MLSS can be estimated from sLT using a novel sweat lactate sensor.
• To compare MLSS estimation between trained and untrained adults.
• To explore the relationship between sLT, MLSS, and tissue oxygenation index (TOI).

Main Methods:

• Fifteen healthy adults (trained/untrained) underwent constant-load testing at varying percentages of their sLT.
• MLSS was determined through incremental exercise testing.
• Sweat lactate levels and thigh TOI were monitored using a novel sensor and near-infrared spectroscopy.

Main Results:

• MLSS estimation from sLT varied, with higher values observed in trained individuals.
• Trained participants demonstrated higher MLSS percentages relative to sLT (≥120%) compared to untrained participants (≤115%).
• Trained individuals maintained constant-load exercise despite decreased TOI, unlike untrained participants.

Conclusions:

• Sweat lactate threshold (sLT) can be used to estimate MLSS in healthy adults, with differing thresholds for trained and untrained individuals.
• Trained individuals exhibit a greater capacity to sustain exercise intensity despite reduced oxygen saturation in lower extremity muscles.
• Novel sweat lactate sensors offer a promising non-invasive tool for assessing exercise physiology markers like MLSS.