Rationally Constructed De Novo Fluorescent Nanosensor for Nitric Oxide Detection and Imaging in Living Cells and Inflammatory Mice Models

化学 纳米传感器 荧光团 荧光 生物相容性 一氧化氮 生物物理学 纳米技术 组合化学 有机化学 物理 材料科学 量子力学 生物
作者
Qiaomei Yang,Yizhuang Zhou,Libin Tan,Can Xie,Kun Luo,Xiaowen Li,Miao Zeng,Liyi Zhou
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:95 (4): 2452-2459 被引量:41
标识
DOI:10.1021/acs.analchem.2c04640
摘要

For the early diagnosis and effective evaluation of treatment effects of inflammation, a de novo bioanalytical method is urgently needed to monitor the metabolite nitric oxide (NO) associated with inflammatory diseases. However, developing a reliable detection method with excellent water solubility, biocompatibility, long retention time, and blood circulation is still challenging. In this work, we reported for the first time a de novo host–guest self-assembled nanosensor CTA for the quantitative detection and visualization of NO levels in inflammatory models. CTA mainly consists of two parts: (i) an adamantyl-labeled guest small-molecule RN-adH containing a classical response moiety o-phenylenediamine for a chemical-specific response toward NO and fluorophore rhodamine B with excellent optical properties as an internal reference for self-calibration and (ii) a remarkable water-soluble and biocompatible supramolecular β-cyclodextrin polymer (Poly-β-CD) host. In the presence of NO, the o-phenylenediamine unit was reacted with NO at a low pH value of ∼7.0, accompanied by changes in the intensity of the two emission peaks corrected for each other and the change in fluorescence color of the CTA solution from fuchsia to pink. Furthermore, CTA was an effective tool for NO detection with a fast response time (∼60 s), high selectivity, and sensitivity (LOD: 22.3 nM). Impressively, the CTA nanosensor has successfully achieved the targeted imaging of NO in living inflammatory RAW 264.7 cells and mice models with satisfactory results, which can provide a powerful molecular tool for the visualization and assessment of the occurrence and development of NO-related inflammatory diseases in complex biosystems.
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
刚刚
小二郎应助淡蓝色采纳,获得10
1秒前
1秒前
无辜的安蕾完成签到 ,获得积分10
2秒前
湘湘完成签到,获得积分10
2秒前
3秒前
重要问丝发布了新的文献求助10
3秒前
ZeKaWa应助asdlxz采纳,获得10
4秒前
卷卷心发布了新的文献求助10
4秒前
lhx完成签到,获得积分10
4秒前
乐观发布了新的文献求助10
4秒前
4秒前
柯温发布了新的文献求助10
5秒前
5秒前
瓶盖完成签到 ,获得积分10
5秒前
清河剑客发布了新的文献求助10
5秒前
1234发布了新的文献求助20
5秒前
5秒前
香蕉灵槐完成签到,获得积分10
5秒前
隐形曼青应助活力丹秋采纳,获得10
6秒前
明东完成签到,获得积分10
6秒前
莎莎发布了新的文献求助10
6秒前
6秒前
6秒前
湘湘发布了新的文献求助10
6秒前
7秒前
sharkmelon应助light采纳,获得10
7秒前
7秒前
李彦完成签到,获得积分10
7秒前
8秒前
orixero应助TAA66采纳,获得10
8秒前
小浣熊发布了新的文献求助10
8秒前
云为翳完成签到,获得积分10
8秒前
无情天川完成签到,获得积分20
8秒前
9秒前
Orange应助柠檬小白采纳,获得10
9秒前
9秒前
10秒前
OsamaKareem应助刻苦熊猫采纳,获得50
10秒前
高分求助中
Overcoming Stigma and Bias in Obesity Management 1200
Signals, Systems, and Signal Processing 610
Software that combines deep learning,3D reconstruction and CFD to analyze the state of carotid arteries from ultrasound imaging 500
Bounds for Statistical Estimation in Semiparametric Models 500
Forced degradation and stability indicating LC method for Letrozole: A stress testing guide 500
Ideology and Meaning-Making under the Putin Regime 450
Adhesion Science: Principles & Practice 400
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 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6492681
求助须知:如何正确求助?哪些是违规求助? 8290272
关于积分的说明 17690439
捐赠科研通 5584589
什么是DOI,文献DOI怎么找? 2915411
邀请新用户注册赠送积分活动 1892511
关于科研通互助平台的介绍 1750705