Suppr超能文献

即时检测病原体的光子晶体和机器视觉技术在尿路感染诊断中的应用。

Point-of-Care Pathogen Testing Using Photonic Crystals and Machine Vision for Diagnosis of Urinary Tract Infections.

机构信息

Key Laboratory of Biomedical Polymers of Ministry of Education, College of Chemistry and Molecular Sciences, School of Microelectronics, Wuhan University, Wuhan 430072, China.

Institute of Chemical Biology and Nanomedicine, State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha 410082, China.

出版信息

Nano Lett. 2021 Apr 14;21(7):2854-2860. doi: 10.1021/acs.nanolett.0c04942. Epub 2021 Mar 26.

Abstract

Urinary tract infections (UTIs) caused by bacterial invasion can lead to life-threatening complications, posing a significant health threat to more than 150 million people worldwide. As a result, there is need for accurate and rapid diagnosis of UTIs to enable more effective treatment. Described here is an intelligent diagnostic system constructed for bacterial detection using an immunobiosensor, signal-amplification biochip, and image processing algorithm based on machine vision. This prototype can quickly detect bacteria by collection of enhanced luminescence enabled by the photonic crystals integrated into the biochip. By use of a machine vision algorithm, the very small luminescence signals are analyzed to provide a low detection limit and wide dynamic range. This sensor system can offer an affordable, accessible, and user-friendly digital diagnostic solution, possibly suitable for wearable technology, that could improve treatment of this challenging disease.

摘要

尿路感染(UTI)由细菌入侵引起,可能导致危及生命的并发症,对全球超过 1.5 亿人构成重大健康威胁。因此,需要准确、快速地诊断 UTI,以便更有效地治疗。这里描述的是一个使用免疫生物传感器、信号放大生物芯片和基于机器视觉的图像处理算法构建的用于细菌检测的智能诊断系统。该原型通过集成在生物芯片中的光子晶体实现增强发光的收集,从而快速检测细菌。通过使用机器视觉算法,对非常小的发光信号进行分析,提供低检测限和宽动态范围。该传感器系统可以提供负担得起、易于获得和用户友好的数字诊断解决方案,可能适合可穿戴技术,从而改善这种具有挑战性的疾病的治疗效果。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验