适体
生物传感器
化学
介电谱
分析化学(期刊)
电化学气体传感器
洗脱
动态范围
线性范围
色谱法
材料科学
检出限
电化学
电极
生物化学
计算机科学
生物
遗传学
物理化学
计算机视觉
作者
Antra Ganguly,Kai Lin,Sriram Muthukumar,Shalini Prasad
出处
期刊:ACS Sensors
[American Chemical Society]
日期:2020-12-31
卷期号:6 (1): 63-72
被引量:98
标识
DOI:10.1021/acssensors.0c01754
摘要
The proposed work involves the development of an autonomous, label-free electrochemical sensor for real-time monitoring of cortisol levels expressed naturally in sub-microliter sweat volumes, for prolonged sensing periods of ∼8 h. Highly specific single-stranded DNA (ssDNA) aptamer is used for affinity capture of cortisol hormone eluted in sweat dynamically. The cortisol present in sweat binds to the aptamer capture probe that changes conformation and modulates electrochemical properties at the electrode–buffer interface, which was studied using dynamic light scattering studies for the entire physiological sweat pH. Attenuated total reflectance-Fourier transform infrared spectroscopy and UV–vis spectroscopy were used to optimize the binding chemistry of the elements of the sensor stack. Nonfaradaic electrochemical impedance spectroscopy was used to calibrate the sensor for a dynamic range of 1–256 ng/mL. An R2 of 0.97 with an output signal range of 20–50% was obtained. Dynamic cortisol level variation tracking was studied using continuous dosing experiments to calibrate the sensor for temporal variation. The sensor did not show significant susceptibility to noise due to cross-reactive interferents and nonspecific buffer constituents. The performance of the developed aptasensor was compared with the previously established cortisol immunosensor in terms of surface charge behavior and nonfaradaic biosensing. The aptamer sensor shows a higher signal-to-noise ratio, better resolution, and has a larger output range for the same input range as the cortisol immunosensor. The feasibility of deploying the developed aptasensing scheme as continuous lifestyle and performance monitors was validated through human subject studies.
科研通智能强力驱动
Strongly Powered by AbleSci AI