<br>基于多色发射碳点的荧光分析平台，用于快速定量和区分硝基咪唑抗生素残留,Talanta

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基于多色发射碳点的荧光分析平台，用于快速定量和区分硝基咪唑抗生素残留
Talanta ( IF 5.6 ) Pub Date : 2024-01-17 , DOI: 10.1016/j.talanta.2024.125679
Shaojie Wang ₁ , Yongbo Wang ₁ , Yuanna Ning ₁ , Wencai Wang ₁ , Qiming Liu ₁

Affiliation

食品安全评估迫切需要开发高效、快速、便携式、准确的食品基质中兽药残留分析方法。在这里，我们开发了一个智能手机集成平台，用于甲硝唑（MNZ）残留物的荧光定量，并构建了一个传感器阵列来区分不同的硝基咪唑抗生素（NIIM）。制备了多色 CD（B-CD、C-CD、Y-CD 和 R-CD），并对 MNZ 显示出不同的荧光响应。 C-CDs的荧光由于C-CDs和MNZ之间的内滤效应(IFE)而被猝灭，而R-CDs的荧光由于MNZ对表面缺陷的钝化而增强。基于响应模式，基于C-CD + R-CD系统的荧光图像（R/G值）实现了MNZ的荧光定量，检测限低至0.45 μM。通过设计智能手机集成平台，分析可以在20分钟内完成。此外，还开发了基于 C-CD 和 R-CD 的荧光传感器阵列。通过响应模式的线性判别分析 (LDA) 获得了每个 NIIM 的独特指纹，表明可以有效区分 5 个 NIIM。此外，该平台用于食品样品中MNZ的定量，回收率在84.0-106.3%之间，相对标准偏差为1.2-10.2%。因此，该方法作为快速检测兽药残留的通用平台具有巨大的潜力。

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Multicolor emissive carbon dot-based fluorometric analysis platform for rapid quantification and discrimination of nitroimidazole antibiotic residues

The development of efficient, rapid, portable, and accurate analysis of veterinary drug residues in food matrices is in great demand for food safety assessment. Here, we have developed a smartphone-integrated platform for fluorometric quantification of metronidazole (MNZ) residues and constructed a sensor array for discrimination of different nitroimidazole antibiotics (NIIMs). Multicolor CDs (B-CDs, C-CDs, Y-CDs, and R-CD) were prepared and showed different fluorescence response to MNZ. The fluorescence of C-CDs was quenched Because of the inner filter eﬀect (IFE) between the C-CDs and MNZ, while that of R-CDs was enhanced due to the passivation of surface defects by MNZ. Based on the response pattern, the fluorometric quantification of MNZ based on the fluorescence images of C-CD + R-CD system (R/G values) was achieved with a low detection limit of 0.45 μM. By designing a smartphone-integrated platform, the analysis can be completed within 20 min. In addition, a ﬂuorescence sensor array based C-CDs and R-CDs was also developed. The unique fingerprint of each NIIMs was obtained by linear discriminant analysis (LDA) of the response patterns, indicating an effective discrimination of five NIIMs. Moreover, the platform was used for quantification of MNZ in food samples and the recoveries were within 84.0–106.3 % with relative standard deviations 1.2–10.2 %. Therefore, the proposed method shows great potential as a universal platform for rapid detection of veterinary drug residues.

更新日期：2024-01-17

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