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Continuous Metabolic Monitoring Based on Multi-Analyte Biomarkers to Predict Exhaustion

机译:基于多分析物生物标志物的连续代谢监测以预测疲劳

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This work introduces the concept of multi-analyte biomarkers for continuous metabolic monitoring. The importance of using more than one marker lies in the ability to obtain a holistic understanding of the metabolism. This is showcased for the detection and prediction of exhaustion during intense physical exercise. The findings presented here indicate that when glucose and lactate changes over time are combined into multi-analyte biomarkers, their monitoring trends are more sensitive in the subcutaneous tissue, an implantation-friendly peripheral tissue, compared to the blood. This unexpected observation was confirmed in normal as well as type 1 diabetic rats. This study was designed to be of direct value to continuous monitoring biosensor research, where single analytes are typically monitored. These findings can be implemented in new multi-analyte continuous monitoring technologies for more accurate insulin dosing, as well as for exhaustion prediction studies based on objective data rather than the subject’s perception.
机译:这项工作介绍了用于连续代谢监测的多分析物生物标志物的概念。使用不止一种标记物的重要性在于获得对代谢的全面了解的能力。这是为了在剧烈运动中检测和预测疲劳而展示的。此处提出的发现表明,当葡萄糖和乳酸随时间的变化组合成多种分析物生物标志物时,与皮下组织相比,它们的监测趋势在皮下组织(一种易于植入的外围组织)中更为敏感。在正常以及1型糖尿病大鼠中均证实了这一意外发现。该研究被设计为对连续监测生物传感器研究具有直接价值,在该研究中通常监测单个分析物。这些发现可以在新的多分析物连续监测技术中实现,以实现更准确的胰岛素剂量,以及基于客观数据而非受试者感知的疲劳预测研究。

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