亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整的填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Highly efficient detection of deoxynivalenol and zearalenone in the aqueous environment based on nanoenzyme-mediated lateral flow immunoassay combined with smartphone

玉米赤霉烯酮 色谱法 检出限 免疫分析 化学 水溶液 真菌毒素 放射性检测 计算机科学 食品科学 生物 物理化学 人工智能 抗体 免疫学
作者
Weibin Li,Zedong Wang,Xinwei Wang,Cui Li,Wenyuan Huang,Zhaoyong Zhu,Zhenjiang Liu
出处
期刊:Journal of environmental chemical engineering [Elsevier]
卷期号:11 (5): 110494-110494 被引量:2
标识
DOI:10.1016/j.jece.2023.110494
摘要

Deoxynivalenol (DON) and zearalenone (ZEN) pose a serious threat to human health, and have been frequently detected in the aqueous environment. To protect consumers from the harm of mycotoxins, a nanozyme-mediated multiplexed lateral flow immunoassay (LFIA) integrated with a smartphone was developed for rapid, highly sensitive and simultaneous quantitative detection of DON and ZEN in the aqueous environment. Highly efficient peroxidase mimicking core-shell Au@Pt nanozymes were synthesized by one-pot method, and then used as signal amplification to highly improve sensitivity of the detection, while a smartphone-based quantitative detection device could rapidly quantify results to improve the detection efficiency of the LIFA for on-site detection. After optimization, the detection time of the assay was 10 min, and the detection limits of the LIFA for DON/ZEN were 0.24/0.04 ng/mL, which were improved 416 and 150 folds compared to the conventional gold nanoparticles (GNPs)-based LFIA. Moreover, there was no obvious cross-reaction with other related mycotoxins, indicating that LFIA had a high specificity. The average recoveries of DON and ZEN from corn, wheat and three water samples were obtained from 94.3 % to 107.9 % with relative standard deviations of 0.2–7.6 %. Furthermore, the accuracy and reliability of the LIFA were evaluated with three spiked water samples, and the results presented good correlations with analytic results from the enzyme-linked immunosorbent assay (R2 =0.988 for DON, and 0.983 for ZEN). The results indicate the proposed LIFA was potentially a rapid, on-site simultaneous and highly sensitive method for DON and ZEN detection in the aqueous environment.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
迅速易云发布了新的文献求助10
3秒前
传奇3应助小合采纳,获得10
4秒前
冫义斗完成签到 ,获得积分10
8秒前
思源应助坚强的初夏采纳,获得10
17秒前
斯文败类应助luna采纳,获得10
19秒前
Akim应助科研通管家采纳,获得10
25秒前
25秒前
大方的荟完成签到,获得积分10
32秒前
冷艳的立果应助luna采纳,获得10
35秒前
leafye发布了新的文献求助20
44秒前
YifanWang应助称心绮采纳,获得30
47秒前
fxh完成签到,获得积分10
1分钟前
隐形曼青应助任我行采纳,获得10
1分钟前
风趣的芝麻完成签到 ,获得积分10
1分钟前
1分钟前
称心绮完成签到,获得积分10
1分钟前
1分钟前
乌兰发布了新的文献求助10
1分钟前
2分钟前
2分钟前
李健的小迷弟应助祝人达采纳,获得10
2分钟前
pegasus0802完成签到,获得积分10
2分钟前
科研通AI2S应助北纬采纳,获得30
2分钟前
李健应助科研通管家采纳,获得30
2分钟前
英俊的铭应助科研通管家采纳,获得10
2分钟前
上官若男应助科研通管家采纳,获得10
2分钟前
2分钟前
2分钟前
2分钟前
zokor完成签到 ,获得积分10
2分钟前
任我行发布了新的文献求助10
3分钟前
3分钟前
3分钟前
Babyblue发布了新的文献求助10
3分钟前
刘刘完成签到 ,获得积分10
3分钟前
忐忑的黑猫应助Babyblue采纳,获得10
3分钟前
忐忑的黑猫应助Babyblue采纳,获得10
3分钟前
JamesPei应助Babyblue采纳,获得10
3分钟前
搜集达人应助TONG97采纳,获得10
3分钟前
DarwinZC发布了新的文献求助10
3分钟前
高分求助中
Production Logging: Theoretical and Interpretive Elements 2500
Healthcare Finance: Modern Financial Analysis for Accelerating Biomedical Innovation 2000
Applications of Emerging Nanomaterials and Nanotechnology 1111
Agaricales of New Zealand 1: Pluteaceae - Entolomataceae 1040
Les Mantodea de Guyane Insecta, Polyneoptera 1000
Neuromuscular and Electrodiagnostic Medicine Board Review 700
지식생태학: 생태학, 죽은 지식을 깨우다 600
热门求助领域 (近24小时)
化学 医学 材料科学 生物 工程类 有机化学 生物化学 纳米技术 内科学 物理 化学工程 计算机科学 复合材料 基因 遗传学 物理化学 催化作用 细胞生物学 免疫学 电极
热门帖子
关注 科研通微信公众号,转发送积分 3466798
求助须知:如何正确求助?哪些是违规求助? 3059583
关于积分的说明 9067131
捐赠科研通 2750043
什么是DOI,文献DOI怎么找? 1508952
科研通“疑难数据库(出版商)”最低求助积分说明 697124
邀请新用户注册赠送积分活动 696896