Dataset Information

A novel device for detecting anaerobic threshold using sweat lactate during exercise.

ABSTRACT: The lactate threshold (LT1), which is defined as the first rise in lactate concentration during incremental exercise, has not been non-invasively and conveniently determined in a clinical setting. We aimed to visualize changes in lactate concentration in sweat during exercise using our wearable lactate sensor and investigate the relationship between the lactate threshold (LT1) and ventilatory threshold (VT1). Twenty-three healthy subjects and 42 patients with cardiovascular diseases (CVDs) were enrolled. During exercise, the dynamic changes in lactate values in sweat were visualized in real-time with a sharp continuous increase up to volitional exhaustion and a gradual decrease during the recovery period. The LT1 in sweat was well correlated with the LT1 in blood and the VT1 (r?=?0.92 and 0.71, respectively). In addition, the Bland-Altman plot described no bias between the mean values (mean differences: - 4.5 and 2.5 W, respectively). Continuous monitoring of lactate concentrations during exercise can provide additional information for detecting the VT1.

SUBMITTER: Seki Y

PROVIDER: S-EPMC7925537 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A novel device for detecting anaerobic threshold using sweat lactate during exercise.

Seki Yuta Y Nakashima Daisuke D Shiraishi Yasuyuki Y Ryuzaki Toshinobu T Ikura Hidehiko H Miura Kotaro K Suzuki Masato M Watanabe Takatomo T Nagura Takeo T Matsumato Morio M Nakamura Masaya M Sato Kazuki K Fukuda Keiichi K Katsumata Yoshinori Y

Scientific reports 20210302 1

The lactate threshold (LT1), which is defined as the first rise in lactate concentration during incremental exercise, has not been non-invasively and conveniently determined in a clinical setting. We aimed to visualize changes in lactate concentration in sweat during exercise using our wearable lactate sensor and investigate the relationship between the lactate threshold (LT1) and ventilatory threshold (VT1). Twenty-three healthy subjects and 42 patients with cardiovascular diseases (CVDs) were ...[more]

PMID: 33654133

Similar Datasets

Project description:Background: Metabolite-based sensors are attractive and highly valued for monitoring physiological parameters during rest and/or during physical activities. Owing to their molecular composition consisting of nucleic acids, proteins, and metabolites, extracellular vesicles (EVs) have become acknowledged as a novel tool for disease diagnosis. However, the evidence for sweat related EVs delivering information of physical and recovery states remains to be addressed. Methods: Taking advantage of our recently published methodology allowing the enrichment and isolation of sweat EVs from clinical patches, we investigated the metabolic load of sweat EVs in healthy participants exposed to exercise test or recovery condition. -Ten healthy volunteers (-three females and -seven males) were recruited to participate in this study. During exercise test and recovery condition, clinical patches were attached to participants' skin, on their back. Following exercise test or recovery condition, the patches were carefully removed and proceed for sweat EVs isolation. To explore the metabolic composition of sweat EVs, a targeted global metabolomics profiling of 41 metabolites was performed. Results: Our results identified seventeen metabolites in sweat EVs. These are associated with amino acids, glutamate, glutathione, fatty acids, creatine, and glycolysis pathways. Furthermore, when comparing the metabolites' levels in sweat EVs isolated during exercise to the metabolite levels in sweat EVs collected after recovery, our findings revealed a distinct metabolic profiling of sweat EVs. Furthermore, the level of these metabolites, mainly myristate, may reflect an inverse correlation with blood glucose, heart rate, and respiratory rate levels. Conclusion: Our data demonstrated that sweat EVs can be purified using routinely used clinical patches during physical activity, setting the foundations for larger-scale clinical cohort work. Furthermore, the metabolites identified in sweat EVs also offer a realistic means to identify relevant sport performance biomarkers. This study thus provides proof-of-concept towards a novel methodology that will focus on the use of sweat EVs and their metabolic composition as a non-invasive approach for developing the next-generation of sport wearable sensors.

Project description:Wearable lactate sensors for sweat analysis are highly appealing for both the sports and healthcare fields. Electrochemical biosensing is the approach most widely used for lactate determination, and this technology generally demonstrates a linear range of response far below the expected lactate levels in sweat together with a high influence of pH and temperature. In this work, we present a novel analytical strategy based on the restriction of the lactate flux that reaches the enzyme lactate oxidase, which is immobilized in the biosensor core. This is accomplished by means of an outer plasticized polymeric layer containing the quaternary salt tetradodecylammonium tetrakis(4-chlorophenyl) borate (traditionally known as ETH500). Also, this layer prevents the enzyme from being in direct contact with the sample, and hence, any influence with the pH and temperature is dramatically reduced. An expanded limit of detection in the millimolar range (from 1 to 50 mM) is demonstrated with this new biosensor, in addition to an acceptable response time; appropriate repeatability, reproducibility, and reversibility (variations lower than 5% for the sensitivity); good resiliency; excellent selectivity; low drift; negligible influence of the flow rate; and extraordinary correlation (Pearson coefficient of 0.97) with a standardized method for lactate detection such as ion chromatography (through analysis of 22 sweat samples collected from 6 different subjects performing cycling or running). The developed lactate biosensor is suitable for on-body sweat lactate monitoring via a microfluidic epidermal patch additionally containing pH and temperature sensors. This applicability was demonstrated in three different body locations (forehead, thigh, and back) in a total of five on-body tests while cycling, achieving appropriate performance and validation. Moreover, the epidermal patch for lactate sensing is convenient for the analysis of sweat stimulated by iontophoresis in the subjects' arm, which is of great potential toward healthcare applications.

Dataset Information

A novel device for detecting anaerobic threshold using sweat lactate during exercise.

Publications

A novel device for detecting anaerobic threshold using sweat lactate during exercise.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets