Department of Chemistry, Faculty of Science, University of Malaya, 50603, Kuala Lumpur, Malaysia.
Department of Chemistry, Faculty of Science, University of Malaya, 50603, Kuala Lumpur, Malaysia; Centre for Innovation in Medical Engineering, Faculty of Engineering, University of Malaya, 50603, Kuala Lumpur, Malaysia.
Talanta. 2020 Oct 1;218:121169. doi: 10.1016/j.talanta.2020.121169. Epub 2020 May 23.
Food contamination is a serious concern because of a high level of chemicals in food causes severe health issues. Safeguarding the public from the risk of adulterated foods has become a challenging mission. Chloropropanols are of importance to food safety and food security because they are common chemical food contaminants and believed to be carcinogenic to humans. In chemical sensing, chloropropanols are challenging analytes owing to the lacking diversity of functional groups and difficulty in targeting the hydroxyl group in aqueous environments. Moreover, because of their small molecular size, the compositions of chloropropanols remain challenging for achieving chromatographic determination. Herein, to simulate human smell and taste sensations, serum albumins, which are protein-based receptors, were introduced as low-selective receptors for differential sensing. Utilizing serum albumins, a fluorophore (PRODAN), and an additive (ascorbic acid), a differential-based optical biosensor array was developed to detect and differentiate chloropropanols. By integrating the sensor array with linear discriminant analysis (LDA), four chloropropanols were effectively differentiated based on their isomerism properties and the number of the hydroxyl groups, even at ultra-low concentration (5 nM). This concentration is far below the maximum tolerable level of 0.18 μM for chloropropanols. The sensing array was then employed for chloropropanols differentiation and quantification in the complex mixtures (e.g., synthetic soy and dark soy sauces). Leave-one-out cross-validation (LOOCV) analysis demonstrated 100% accurate classification for all tests. These results signify our differential sensing array as a practical and powerful tool to speedily identify, differentiate, and even quantify chloropropanols in food matrices.
食品污染是一个严重的问题,因为食品中高水平的化学物质会导致严重的健康问题。保护公众免受掺假食品的风险已经成为一项具有挑战性的任务。氯丙醇是食品安全和粮食安全的重要组成部分,因为它们是常见的化学食品污染物,被认为对人类具有致癌性。在化学传感中,氯丙醇是具有挑战性的分析物,因为它们缺乏官能团的多样性,并且难以在水相环境中靶向羟基。此外,由于其分子尺寸较小,氯丙醇的组成对于实现色谱测定仍然具有挑战性。在这里,为了模拟人类的嗅觉和味觉感知,血清白蛋白作为基于蛋白质的受体被引入,作为差异传感的低选择性受体。利用血清白蛋白、荧光团(PRODAN)和添加剂(抗坏血酸),开发了一种基于差异的光学生物传感器阵列来检测和区分氯丙醇。通过将传感器阵列与线性判别分析(LDA)集成,基于其异构体性质和羟基数目,即使在超低浓度(5 nM)下,也可以有效地区分四种氯丙醇。这个浓度远远低于氯丙醇的最大允许水平 0.18 μM。该传感阵列随后用于复杂混合物(例如,合成酱油和老抽酱油)中的氯丙醇的区分和定量。留一法交叉验证(LOOCV)分析表明,所有测试的分类准确率均为 100%。这些结果表明,我们的差分传感阵列是一种实用且强大的工具,可以快速识别、区分甚至定量食品基质中的氯丙醇。