Abstract：
Citizen scientist-based environmental monitoring and public education are becoming increasingly popular. However, current technologies for antibiotic-based novel contaminant identification are still restricted to laboratory sample collection and analysis due to detection methodologies and apparatus limitations. This study developed a time-resolved immunofluorescence-based simultaneous field-based assay for ciprofloxacin (CIP) and enrofloxacin (ENR) that matches test results to geographic locations. The assay helps the public understand the potential levels of antibiotic exposures in their environments and helps them take appropriate action to reduce risk. The assay was developed using smartphones and social software in addition to rapid testing. The method uses a portable, low-cost analytical kit with a smartphone app to build a field-based detection platform for the detection and analysis of ENR and CIP in water and aquatic products. The methodological evaluation was good, with detection limits of 0.4 ng/mL and 0.5 ng/g for ENR in water and fish, and quantification limits of 1.2 ng/mL and 1.4 ng/g, with recoveries of 89.0 %-101.0 % and 78.0 %-97.0 %. For CIP in water and fish, the limits of detection were 0.3 ng/mL and 0.4 ng/g, the limits of quantification were 0.9 ng/mL and 1.2 ng/g, and the recoveries were 75.0 %-91.0 % and 72.0 %-89.0 %, both with coefficients of variation <15 %. These limits were sufficient to prevent the two antibiotics from crossing over during simultaneous detection. The assay was validated using real samples to assess the effectiveness of the assay platform in field deployments, and the results were consistent with those obtained through liquid chromatography-tandem mass spectrometry (LC-MS) and enzyme-linked immunoassay (ELISA) techniques. In addition, the TRFIA assay process requires less time, uses more portable instruments, and is less complex than traditional methods. This study provides a new scientific, accurate, and rapid detection method for antibiotic detection by citizen scientists, helping scientists to obtain a wider range of data and providing more opportunities to solve scientific problems.
摘要：
基于公民科学家的环境监测和公共教育正变得越来越受欢迎。然而,由于检测方法和设备的限制，目前基于抗生素的新型污染物识别技术仍然局限于实验室样品收集和分析。这项研究开发了一种基于时间分辨免疫荧光的同时基于现场的环丙沙星（CIP）和恩诺沙星（ENR）测定法，该测定法将测试结果与地理位置相匹配。该检测有助于公众了解其环境中抗生素暴露的潜在水平，并帮助他们采取适当的行动来降低风险。除了快速测试之外，还使用智能手机和社交软件开发了该测定。该方法使用便携式,带有智能手机应用程序的低成本分析套件，可构建基于现场的检测平台，用于检测和分析水和水产品中的ENR和CIP。方法评价良好,ENR在水和鱼中的检测限为0.4ng/mL和0.5ng/g，定量限为1.2ng/mL和1.4ng/g，回收率为89.0%-101.0%,78.0%-97.0%。在水和鱼中的CIP，检测限为0.3ng/mL和0.4ng/g，定量限为0.9ng/mL和1.2ng/g，回收率分别为75.0%-91.0%和72.0%-89.0%,两者的变异系数均<15%。这些限制足以防止两种抗生素在同时检测期间交叉。使用真实样品验证了该测定，以评估该测定平台在现场部署中的有效性。结果与通过液相色谱-串联质谱（LC-MS）和酶联免疫分析（ELISA）技术获得的结果一致。此外,TRFIA测定过程需要更少的时间，使用更多的便携式仪器，并且没有传统方法复杂。这项研究提供了一种新的科学,准确,以及公民科学家检测抗生素的快速检测方法，帮助科学家获得更广泛的数据，并提供更多解决科学问题的机会。
