Zhang Yong, Zeng Xin, Wang Cuncun, Liu Yiyi, Jin Changpeng, Chen Jian, Hou Jingzhou, Huo Danqun, Hou Changjun
Key Laboratory for Biorheological Science and Technology of Ministry of Education, Bioengineering College of Chongqing University, Chongqing, 400044, PR China.
Chongqing University Three Gorges Hospital, Chongqing, 404000, PR China.
Talanta. 2025 Apr 1;285:127404. doi: 10.1016/j.talanta.2024.127404. Epub 2024 Dec 16.
Simultaneous detection of biomarkers in sweat is crucial for comprehensive health assessment and personalized monitoring. However, the low sweat secretion rate and low metabolite concentrations present challenges for developing non-invasive wearable sensors. This study aims to develop a flexible wearable biosensor for simultaneous detection of low-concentration biomarkers in sweat, enabling comprehensive health assessment. This study synthesized an innovative bimetallic tungstate Ag@AgWO and evaluated its performance for detecting uric acid (UA, 10-1000 μM), dopamine (DA, 3-500 μM), and tyrosine (Tyr, 5-1000 μM). The detection limits (LODs) for DA, UA, and Tyr sensors were 3.10 μM, 8.47 μM, and 4.17 μM, respectively, with relative standard deviations (RSDs) of 4.76 %, 2.66 %, and 3.51 %, respectively. Additionally, this study designed a hydrophilic microfluidic collection system inspired by bamboo leaf structures to enhance sweat collection efficiency. Validation studies demonstrated that the wearable biosensor effectively detects UA and TA in the sweat of volunteers. We believe this research could contribute to advancing personalized healthcare by improving the convenience and effectiveness of health monitoring technologies.
同时检测汗液中的生物标志物对于全面的健康评估和个性化监测至关重要。然而,低汗液分泌率和低代谢物浓度给开发无创可穿戴传感器带来了挑战。本研究旨在开发一种灵活的可穿戴生物传感器,用于同时检测汗液中的低浓度生物标志物,以实现全面的健康评估。本研究合成了一种创新的双金属钨酸盐Ag@AgWO,并评估了其检测尿酸(UA,10 - 1000 μM)、多巴胺(DA,3 - 500 μM)和酪氨酸(Tyr,5 - 1000 μM)的性能。DA、UA和Tyr传感器的检测限分别为3.10 μM、8.47 μM和4.17 μM,相对标准偏差(RSD)分别为4.76%、2.66%和3.51%。此外,本研究设计了一种受竹叶结构启发的亲水性微流体收集系统,以提高汗液收集效率。验证研究表明,该可穿戴生物传感器能够有效检测志愿者汗液中的UA和TA。我们相信这项研究可以通过提高健康监测技术的便利性和有效性,为推进个性化医疗做出贡献。