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Rapid detection of airborne protein from Mycobacterium tuberculosis using a biosensor detection system

生物传感器 结核分枝杆菌 微流控 软件可移植性 肺结核 材料科学 生物医学工程 化学 呼出气冷凝液 体积流量 色谱法 纳米技术 计算机科学 医学 物理 免疫学 病理 程序设计语言 哮喘 量子力学
作者
Jinbiao Ma,Guanyu Jiang,Qingqing Ma,Hao Wang,Manman Du,Can Wang,Xinwu Xie,Tie Li,Shixing Chen
出处
期刊:Analyst [The Royal Society of Chemistry]
卷期号:147 (4): 614-624 被引量:16
标识
DOI:10.1039/d1an02104d
摘要

Tuberculosis (TB), caused by infection with airborne Mycobacterium tuberculosis (MTB), seriously threatens human health and has become a public health problem of worldwide concern. To achieve effective control of TB, rapid and sensitive detection of MTB is particularly important. At present, the common detection methods for MTB cannot meet the requirements of speed, flexibility and portability simultaneously. In this work, a multichannel microfluidic chip was developed and packaged with an ultra-sensitive silicon nanowire field-effect-transistor biosensor. The fluid system was tested and optimized through simulation, and the best conditions were determined: the flow rate was 0.3 mL min-1 and the flow direction was perpendicular to a silicon nanowire. A one-way valve, a switching valve and a peristaltic pump were combined to establish a biosensor detection system to realize the automatic detection of TB samples. Then we systematically explained the factors affecting simulated exhaled breath condensate (SEBC) collection, and established and optimized the method for collection of SEBC from the perspective of collection volume and biological activity. The best collection conditions were determined for a 5 mm pipe diameter at 0 °C, and a sufficient sample volume was obtained in only 2 minutes for microfluidic detection. Then, the actual application value of the established collection method was further evaluated. Volunteers were recruited and this method was used to collect their exhaled breath condensate to analyze the collection effect. The system detected MTB in SEBC with good sensitivity (∼4 × 104 particles per mL). It is expected to be further integrated and miniaturized in the future to realize point-of-care testing.

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