化学
分子印迹聚合物
电化学气体传感器
聚合物
适应性
纳米技术
样品(材料)
航程(航空)
动态范围
生化工程
协议(科学)
电化学
单体
选择(遗传算法)
宽动态范围
相似性(几何)
生物系统
过程(计算)
鉴定(生物学)
样品制备
持续监测
目标射程
工艺工程
信号(编程语言)
作者
Oliver Jamieson,Amy Dann,X. Liu,T. Oliveira Abib,K. Novakovic,Jake McClements,S. Seyedin,Jonas Gruber,R.D. Crapnell,H. Snyder,CE Banks,J.A. Dawson,Marloes Peeters
标识
DOI:10.1016/j.aca.2026.345174
摘要
Current estimates see 25.2 million people living with from Parkinson's disease (PD) worldwide by 2050, with no cure close to being available. With therapeutic LDp (LDp) use being the mainstay treatment for a vast proportion of individuals with PD, an effective protocol for managing medication in real-time, is not only essential but long overdue. Presented hereafter is a highly reproducible polymeric electrochemical detection platform with an economically viable production process that can specifically and selectively detect LDp at the relevant physiological range. Computational modelling of target-monomer interactions is employed to direct monomer selection and polymer synthesis. Testing the sensor platform within a dynamic range (5-50 μM) of LDp and its metabolite Dp (Dp) in a range of different sample media affords a 42% higher response of current change upon binding to LDp compared to Dp despite high structural similarity between the compounds. Furthermore, the sensor shows no significant difference when tested in different sample media, allowing this electrochemical sensor to operate across a range of different sample sources, further enhancing its adaptability and applicability in an ever-changing landscape of medical technology.
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