基于金铂双金属纳米粒子/碳纳米管杂化物的磁性免疫测定,用于灵敏检测四环素类抗生素

Biosensors Pub Date : 2024-07-15 DOI:10.3390/bios14070342
Jianxia Lv, Rui Huang, Kun Zeng, Zhen Zhang
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引用次数: 0

摘要

动物食品中四环素(TC)抗生素残留的滥用已对人类健康构成严重威胁。因此,迫切需要开发高灵敏度和稳健的检测方法来检测四环素。本研究通过叠加法(Au@Pt/CNTs-s)和一锅法(Au@Pt/CNTs-o)将金和铂纳米粒子沉积在碳纳米管(CNTs)上。与 Au@Pt/CNTs-o 相比,Au@Pt/CNTs-s 显示出更高的酶样活性,可用于开发灵敏的磁性免疫分析仪。在优化条件下,Au@Pt/CNTs-s 和 Au@Pt/CNTs-o辅助的磁性免疫分析仪对 TCs 的检出限(LODs)分别可达 0.74 ng/mL 和 1.74 ng/m,与传统磁性免疫分析仪相比分别提高了 6 倍和 2.5 倍。此外,该方法还实现了对TC-家族抗生素的检测,这归功于所使用的抗体能识别TC、土霉素、金霉素和强力霉素,且具有很高的交叉反应性。此外,该方法还具有良好的准确性(牛奶样品的回收率为 92.1%-114.5%;猪肉样品的回收率为 88.6%-92.4%),可用于实际样品中目标物的测定。该研究为基于高性能纳米催化剂的目标物快速检测提供了新的见解。
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Magnetic Immunoassay Based on Au Pt Bimetallic Nanoparticles/Carbon Nanotube Hybrids for Sensitive Detection of Tetracycline Antibiotics
Misusage of tetracycline (TC) antibiotics residue in animal food has posed a significant threat to human health. Therefore, there is an urgent need to develop highly sensitive and robust assays for detecting TC. In the current study, gold and platinum nanoparticles were deposited on carbon nanotubes (CNTs) through the superposition method (Au@Pt/CNTs-s) and one-pot method (Au@Pt/CNTs-o). Au@Pt/CNTs-s displayed higher enzyme-like activity than Au@Pt/CNTs-o, which were utilized for the development of sensitive magnetic immunoassays. Under the optimized conditions, the limits of detection (LODs) of magnetic immunoassays assisted by Au@Pt/CNTs-s and Au@Pt/CNTs-o against TCs could reach 0.74 ng/mL and 1.74 ng/m, respectively, which were improved 6-fold and 2.5-fold in comparison with conventional magnetic immunoassay. In addition, the measurement of TC-family antibiotics was implemented by this assay, and ascribed to the antibody used that could recognize TC, oxytetracycline, chlortetracycline, and doxycycline with high cross-reactivity. Furthermore, the method showed good accuracy (recoveries, 92.1–114.5% for milk; 88.6–92.4% for pork samples), which also were applied for determination of the targets in real samples. This study provides novel insights into the rapid detection of targets based on high-performance nanocatalysts.
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