Centre for Advanced Materials and Industrial Chemistry (CAMIC), School of Science, RMIT University, Melbourne, Victoria, 3001, Australia; CSIRO, Bayview Avenue, Clayton, Victoria, 3168, Australia.
Centre for Advanced Materials and Industrial Chemistry (CAMIC), School of Science, RMIT University, Melbourne, Victoria, 3001, Australia.
Biosens Bioelectron. 2019 Sep 15;141:111479. doi: 10.1016/j.bios.2019.111479. Epub 2019 Jun 26.
While glucose monitoring technology is widely available, the continued prevalence of diabetes around the world coupled with its debilitating effects continues to grow. The significant limitations which exist in the current technology, instils the need for materials capable of non-invasive glucose detection. In this study a unique non-enzymatic electrochemical glucose sensor was developed, utilising a gold honeycomb-like framework upon which sharp CoO needles are anchored. This composite nanomaterial demonstrates excellent sensing performance in glucose concentrations ranging between 20 μM and 4 mM, exceeding the range required for non-invasive glucose sensing. In conjunction with this high sensitivity (2.014 mA mM·cm), the material possesses excellent selectivity towards glucose for commonly interfering physiological species such as uric acid and ascorbic acid. Glucose detection in synthetic saliva was then performed showing excellent capability in the low concentration range (20 μM-1 mM) for non-invasive sensing performance. Further tests showed good selectivity of the sensor in physiological contaminants commonly found in saliva such as cortisol and dopamine. This development provides excellent scope to create next-generation non-invasive diabetes monitoring platforms, with excellent performance when detecting low glucose concentrations in complex solutions such as saliva.
虽然葡萄糖监测技术已经广泛应用,但全球范围内糖尿病的持续流行及其致残影响仍在不断加剧。当前技术存在显著的局限性,这促使人们需要开发能够进行非侵入性葡萄糖检测的材料。在这项研究中,开发了一种独特的非酶电化学葡萄糖传感器,利用金蜂窝状框架固定尖锐的 CoO 针。这种复合纳米材料在 20µM 至 4mM 的葡萄糖浓度范围内表现出优异的传感性能,超过了非侵入性葡萄糖传感所需的范围。该材料具有高灵敏度(2.014 mA mM·cm),对尿酸和抗坏血酸等常见干扰生理物质具有优异的葡萄糖选择性。随后在合成唾液中进行了葡萄糖检测,显示出在非侵入性传感性能的低浓度范围(20µM-1mM)内具有出色的性能。进一步的测试表明,该传感器对唾液中常见的生理污染物如皮质醇和多巴胺具有良好的选择性。这项研究为开发下一代非侵入性糖尿病监测平台提供了极好的机会,在检测复杂溶液(如唾液)中的低葡萄糖浓度时具有优异的性能。