Advanced Photonics Center, School of Electronic Science and Engineering, Southeast University, Nanjing 210096, China.
Advanced Photonics Center, School of Electronic Science and Engineering, Southeast University, Nanjing 210096, China.
Biosens Bioelectron. 2014 Dec 15;62:13-8. doi: 10.1016/j.bios.2014.06.026. Epub 2014 Jun 19.
As thiocyanate (SCN(-)) acts as an important biomarker in human health assessment, there remains an urgent need to realize rapid and reproducible analysis of SCN(-) in body fluids. Here, a droplet microfluidic device has been designed and fabricated for SCN(-) detection in real human serum and saliva using the surface enhanced Raman scattering (SERS) technique. Only a few minutes are needed for the whole detection process which simply cost a few microliters of real sample. Gold@silver core-shell nanorods (Au@Ag NRs) with a large SERS enhancement factor were selected to capture SCN(-) ions in body fluids. The intensity of SERS peak at around 2100 cm(-1), which originates from the -C≡N stretching mode, was used to indicate the concentrations of SCN(-) ions. Importantly, by generating a droplet environment for mixing reagents and acquiring signals, this microfluidic platform possesses the advantages of an improved reproducibility and reduced time consumption. For practical applications, the SERS-microfluidic system is capable to achieve rapid analysis of SCN(-) in the presence of human serum, which is very important for realizing the detection in real biological samples. Additionally, SCN(-) in saliva samples was detected in the SERS-microfluidic chip and the results provide useful information for distinguishing between smokers and nonsmokers.
由于硫氰酸根(SCN(-))作为人体健康评估的一个重要生物标志物,因此仍然迫切需要实现对体液中 SCN(-)的快速和可重复的分析。在此,设计并制造了一种用于使用表面增强拉曼散射(SERS)技术检测真实人体血清和唾液中 SCN(-)的液滴微流控装置。整个检测过程仅需几分钟,只需消耗几微升的实际样本。选择具有较大 SERS 增强因子的金@银核壳纳米棒(Au@Ag NRs)来捕获体液中的 SCN(-)离子。来自 -C≡N 伸缩模式的约 2100 cm(-1)处的 SERS 峰强度用于指示 SCN(-)离子的浓度。重要的是,通过为混合试剂和获取信号生成液滴环境,这种微流控平台具有提高的重现性和减少的时间消耗的优点。对于实际应用,SERS-微流控系统能够在存在人血清的情况下快速分析 SCN(-),这对于实现真实生物样本中的检测非常重要。此外,还在 SERS 微流控芯片中检测了唾液样本中的 SCN(-),结果为区分吸烟者和不吸烟者提供了有用信息。