Chemistry Faculty, M.V. Lomonosov Moscow State University, 119991 Moscow, Russia.
Biosensors (Basel). 2024 Oct 8;14(10):486. doi: 10.3390/bios14100486.
We report on the possibility of noninvasive diabetes monitoring through continuous analysis of sweat. The prediction of the blood glucose level in diabetic patients is possible on the basis of their sweat glucose content due to the positive correlation discovered. The ratio between the blood glucose and sweat glucose concentrations for a certain diabetic subject is stable within weeks, excluding requirements for frequent blood probing. The glucose variations in sweat display allometric (non-linear) dependence on those in blood, allowing more precise blood glucose estimation. Selective (avoiding false-positive responses) and sensitive (sweat glucose is on average 30-50 times lower) detection is possible with biosensors based on the glucose oxidase enzyme coupled with a Prussian Blue transducer. Reliable glucose detection in just secreted sweat would allow noninvasive monitoring of the glycemia level in diabetic patients.
我们报告了通过连续分析汗液来进行非侵入性糖尿病监测的可能性。由于发现了相关性，通过分析糖尿病患者的汗液葡萄糖含量，就有可能预测其血糖水平。对于特定的糖尿病患者，血糖和汗液葡萄糖浓度之间的比例在数周内是稳定的，不需要频繁地进行血液探测。汗液中的葡萄糖变化与血液中的葡萄糖变化呈比例关系（非线性），从而可以更精确地估计血糖水平。基于葡萄糖氧化酶与普鲁士蓝换能器偶联的生物传感器可以实现选择性（避免假阳性反应）和灵敏性（汗液中的葡萄糖平均低 30-50 倍）检测。仅在刚分泌的汗液中进行可靠的葡萄糖检测，将允许对糖尿病患者的血糖水平进行非侵入性监测。
