Reusable ring-like Fe3O4/Au nanozymes with enhanced peroxidase-like activities for colorimetric-SERS dual-mode sensing of biomolecules in human blood

生物分子 生物传感器 化学 过氧化物酶 双模 拉曼散射 过氧化氢 纳米技术 分析物 检出限 组合化学 拉曼光谱 材料科学 色谱法 生物化学 航空航天工程 工程类 物理 光学
作者
Yi Huang,Yingqiu Gu,Xinyu Liu,Tangtang Deng,Shuang Dai,Jingfeng Qu,Guohai Yang,Lulu Qu
出处
期刊:Biosensors and Bioelectronics [Elsevier BV]
卷期号:209: 114253-114253 被引量:133
标识
DOI:10.1016/j.bios.2022.114253
摘要

Peroxidase-like nanozymes have led to important progress in biosensing, but most of nanozyme sensing systems are currently established by a single-signal output mode, which is susceptible to environmental and operational factors. Thus construction of a dual-signal output nanozyme sensing system is essential for obtaining reliable and robust performance. In this study, a novel peroxidase mimicking nanozyme was developed by decorating magnetic ring-like Fe3O4 with gold nanoparticles (R-Fe3O4/Au) for the colorimetric and surface-enhanced Raman scattering (SERS) dual-mode detection of biomolecules in human serum. The R-Fe3O4/Au nanozymes served as mimetic peroxidase which can catalyze the oxidation of colorless 3,3',5,5'-tetramethylbenzidine by hydrogen peroxide, and concomitantly as SERS substrates for detecting the Raman signals of oxidized products, providing an effective approach to investigate the reaction kinetics of enzymes. Based on the redox reactions, the nanozymes achieved colorimetric-SERS dual-mode sensing of glutathione (GSH) and cholesterol with detection limits as low as 0.10 μM and 0.08 μM, respectively. Furthermore, the nanozymes enabled rapid detection of GSH and cholesterol in serum without any complicated sample pretreatment. The R-Fe3O4/Au catalyst still displayed excellent peroxidase activity even after repeated use for 5 times. The proposed colorimetric-SERS dual-mode sensors exhibited good accuracy and reproducibility, which provides a new avenue for exploiting multifunctional sensors and has a great application prospect in biosensing.
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
刚刚
1秒前
1秒前
1秒前
Akim应助阳光大楚采纳,获得10
1秒前
maiden发布了新的文献求助10
2秒前
2秒前
威武的戎发布了新的文献求助10
2秒前
2秒前
舒适香菇发布了新的文献求助10
2秒前
2秒前
在水一方应助申奎源采纳,获得10
3秒前
大胆凡白完成签到,获得积分10
3秒前
3秒前
3秒前
汐云月沙发布了新的文献求助20
3秒前
3秒前
彭于晏应助赵浩楠采纳,获得10
3秒前
White Night完成签到,获得积分10
3秒前
ZhangYuheng完成签到 ,获得积分10
3秒前
大白发布了新的文献求助10
3秒前
3秒前
费尔明娜完成签到,获得积分0
3秒前
4秒前
4秒前
trl发布了新的文献求助10
4秒前
畅快的豆芽完成签到,获得积分10
4秒前
4秒前
木印天完成签到,获得积分10
4秒前
王耀发布了新的文献求助10
5秒前
5秒前
5秒前
斯文败类应助咿呀采纳,获得30
5秒前
6秒前
nini应助高贵涵阳采纳,获得10
6秒前
7秒前
希望天下0贩的0应助Promise采纳,获得10
7秒前
511完成签到,获得积分10
7秒前
xzy发布了新的文献求助10
7秒前
苏羽发布了新的文献求助10
7秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Principles of town planning: translating concepts to applications 1000
1 Peter and Christ's Descent to the Dead in Its Early Christian Reception 700
Perfectionism in School 600
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7729233
求助须知:如何正确求助?哪些是违规求助? 9281306
关于积分的说明 20142368
捐赠科研通 7306535
什么是DOI,文献DOI怎么找? 3303006
关于科研通互助平台的介绍 2456060
邀请新用户注册赠送积分活动 2311319