Faculty of Science, Biochemistry Department, Ege University , Bornova, Izmir 35100, Turkey.
Institute of Drug Abuse Toxicology and Pharmaceutical Sciences, Ege University , Bornova, Izmir 35100, Turkey.
Anal Chem. 2017 Sep 19;89(18):9629-9632. doi: 10.1021/acs.analchem.7b03017. Epub 2017 Aug 28.
Lateral flow assays (LFAs) are an ideal choice for drug abuse testing favored by their practicability, portability, and rapidity. LFA based on-site rapid screening devices provide positive/negative judgment in a short response time. The conventionally applied competitive assay format used for small molecule analysis such as abused drugs restricts the quantitation ability of LFA strips. We report herein, for the first time, a new strategy using the noncompetitive assay format via a biomimetic material, namely, poly(p-phenylene) β-cyclodextrin poly(ethylene glycol) (PPP-CD-g-PEG) combined with gold nanoparticle (AuNP) conjugates as the labeling agent to recognize the target cocaine molecule in the test zone. The intensities of the visualized red color in the test line indicate that the cocaine concentrations were analyzed via a smartphone application. Significantly, a combination of this platform with a smartphone application provides quantitative data on the cocaine amount, making it a very inventive and attractive approach especially for on-site applications at critical points such as traffic stops and the workplace.
侧向流动检测法(LFA)因其实用性、便携性和快速性,是毒品滥用检测的理想选择。基于 LFA 的现场快速筛选设备可在短时间内提供阳性/阴性判断。传统应用于小分子分析(如滥用药物)的竞争性检测方法限制了 LFA 条的定量能力。我们首次报道了一种新策略,该策略使用仿生材料,即聚(对亚苯基)β-环糊精聚(乙二醇)(PPP-CD-g-PEG)与金纳米粒子(AuNP)缀合物作为标记物,通过非竞争性检测方法来识别测试区中的目标可卡因分子。测试线中可视化红色的强度表明,可卡因浓度通过智能手机应用进行分析。值得注意的是,该平台与智能手机应用程序的结合可提供可卡因数量的定量数据,使其成为一种非常有创意和吸引力的方法,特别是在交通检查站和工作场所等关键地点的现场应用。