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HPTLC-FLD-SERS 作为一种简便可靠的筛选工具:以奶酪中的酪胺为例。

HPTLC-FLD-SERS as a facile and reliable screening tool: Exemplarily shown with tyramine in cheese.

机构信息

State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, China.

School of Food Science and Technology, Jiangnan University, Wuxi 214122, China.

出版信息

J Food Drug Anal. 2018 Apr;26(2):688-695. doi: 10.1016/j.jfda.2017.07.007. Epub 2017 Aug 18.

Abstract

The serious cytotoxicity of tyramine attracted marked attention as it induced necrosis of human intestinal cells. This paper presented a novel and facile high performance thin-layer chromatography (HPTLC) method tailored for screening tyramine in cheese. Separation was performed on glass backed silica gel plates, using methanol/ethyl acetate/ammonia (6/4/1 v/v/v) as the mobile phase. Special efforts were focused on optimizing conditions (substrate preparation, laser wavelength, salt types and concentrations) of surface enhanced Raman spectroscopy (SERS) measurements directly on plates after derivatization, which enabled molecule-specific identification of targeted bands. In parallel, fluorescent densitometry (FLD) scanning at 380</400 nm offered satisfactory quantitative performances (LOD 9 ng/zone, LOQ 17 ng/zone, linearity 0.9996 and %RSD 6.7). Including a quick extraction/cleanup step, the established method was successfully validated with different cheese samples, both qualitatively (straightforward confirmation) and quantitatively (recovery rates from 83.7 to 108.5%). Beyond this application, HPTLC-FLD-SERS provided a new horizon in fast and reliable screening of sophisticated samples like food and herb drugs, striking an excellent balance between specificity, sensitivity and simplicity.

摘要

酪胺的严重细胞毒性引起了人们的关注,因为它会导致人体肠道细胞坏死。本文提出了一种新颖、简便的高效薄层色谱(HPTLC)方法,专门用于筛选奶酪中的酪胺。分离在玻璃背硅胶板上进行,使用甲醇/乙酸乙酯/氨水(6/4/1 v/v/v)作为流动相。特别关注的是优化表面增强拉曼光谱(SERS)测量的条件(底物制备、激光波长、盐的类型和浓度),这使得可以对衍生化后的板上的靶向带进行分子特异性识别。同时,在 380</400nm 处进行荧光密度计(FLD)扫描,提供了令人满意的定量性能(LOD 为 9ng/区,LOQ 为 17ng/区,线性度为 0.9996,%RSD 为 6.7)。包括快速提取/净化步骤在内,该方法已成功应用于不同的奶酪样品进行定性(直接确认)和定量(回收率为 83.7%至 108.5%)验证。除了这种应用之外,HPTLC-FLD-SERS 还为快速可靠地筛选食品和草药等复杂样品提供了新的前景,在特异性、灵敏度和简单性之间取得了极好的平衡。

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