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Tao J, Wang Y, Zhai W, Wang M. A core-shell AuNRs@BUT-16 nanocomposite for enhancement SERS detection and efficient removal of deoxynivalenol. J Adv Res 2025; 67:15-23. [PMID: 38237769 DOI: 10.1016/j.jare.2024.01.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Revised: 01/05/2024] [Accepted: 01/11/2024] [Indexed: 01/27/2024] Open
Abstract
INTRODUCTION Deoxynivalenol (DON) is widely found in grains and poses a serious threat to human health, so there is an urgent need to develop methods for its simultaneous removal and detection. The novel metal organic framework (MOF) material BUT-16 has a high adsorption capacity (79.8%) for DON. Meanwhile, surface-enhanced Raman spectroscopy (SERS) has been widely used for rapid detection of analytes. OBJECTIVES The aim of this work is to prepare a material that can be used for enhancement SERS detection and efficient removal of DON. METHODS AuNRs@BUT-16 was prepared by in-situ solvothermal method and characterized using a series of characterization tools. AuNRs@BUT-16 was used as an adsorbent and SERS substrate for the removal and detection of DON, and some factors affecting the adsorption and SERS detection were investigated. The adsorption mechanism between DON and AuNRs@BUT-16 was investigated using molecular docking. The proposed SERS method was used to detect DON contamination in real samples. RESULTS The prepared core-shell AuNRs@BUT-16 showed a synergistic effect in improving DON adsorption and SERS response. 97.6 % of DON was removed by AuNRs@BUT-16 in aqueous solution, and 70 % in 80 % methanol. The pre-enrichment effect of BUT-16 could trap more DON molecules in the "hot spots" of AuNRs, thus the proposed SERS sensor based on AuNRs@BUT-16 substrate displayed outstanding SERS response and the limit of detection of DON was 3.87 × 10-3 μg/mL. Molecular docking revealed that hydrogen bond and π-alkyl interaction were the main reasons for high affinity between BUT-16 and DON, and Au-O bonds facilitated the adsorption of DON on AuNRs. CONCLUSIONS AuNRs@BUT-16 with superior enrichment and SERS detection capabilities has been used for simultaneous removal and SERS detection of DON, and it also has great potential to realize sensitive and selective detection and removal of DON in multiple disciplines.
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Affiliation(s)
- Jing Tao
- Institute of Quality Standard and Testing Technology, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
| | - Yudan Wang
- Institute of Quality Standard and Testing Technology, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
| | - Wenlei Zhai
- Institute of Quality Standard and Testing Technology, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
| | - Meng Wang
- Institute of Quality Standard and Testing Technology, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China.
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Feng X, Xu Q, Liu Y, Wang S, Cao Y, Zhao C, Peng S. Smartphone-enabled colorimetric immunoassay for deoxynivalenol based on Mn 2+-mediated aggregation of AuNPs. Anal Biochem 2024; 692:115572. [PMID: 38777290 DOI: 10.1016/j.ab.2024.115572] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 04/27/2024] [Accepted: 05/17/2024] [Indexed: 05/25/2024]
Abstract
Deoxynivalenol (DON) is a common mycotoxin in food that mainly pollutes grain crops and feeds, such as barley, wheat and corn. DON has caused widespread concern in the field of food and feed safety. In this study, a colorimetric immunoassay was proposed based on the aggregation of gold nanoparticles (AuNPs) due to the decomposition of Mn2+ from gold-coated manganese dioxide (AuNP@MnO2) nanosheets. In this study, 2-(dihydrogen phosphate)-l-ascorbic acid (AAP) was hydrolyzed by alkaline phosphatase (ALP) and converted to ascorbic acid (AA). Then, AuNP@MnO2 was reduced to Mn2+ and AuNPs aggregation occurred. Using the unique optical characteristics of AuNPs and AuNP@MnO2, visible color changes realized simple detection of DON with high sensitivity and portability. With increasing DON content, the color changed more obviously. To quantitatively detect DON, pictures can be taken and the blue value can be read by a smartphone. The detection limit (Ic10) of this method was 0.098 ng mL-1, which was 326 times higher than that of traditional competitive ELISA, and the detection range was 0.177-6.073 ng mL-1. This method exhibited high specificity with no cross-reaction in other structural analogs. The average recovery rate of DON in corn flour samples was 89.1 %-110.2 %, demonstrating the high accuracy and stability of this assay in actual sample detection. Therefore, the colorimetric immunoassay can be used for DON-related food safety monitoring.
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Affiliation(s)
- Xinrui Feng
- College of Public Health, Jilin Medical University, Jilin, Jilin, China; Medical College, Yanbian University, Yanji, Jilin, China
| | - Qinwei Xu
- Department of Pulmonary and Critical Care Medicine, Qilu Hospital of Shandong University (Qingdao), Qingdao, Shandong, China
| | - Yan Liu
- College of Public Health, Jilin Medical University, Jilin, Jilin, China
| | - Sijia Wang
- College of Food Science and Engineering, Jilin Agricultural University, Changchun, Jilin, China
| | - Yong Cao
- College of Food Science and Engineering, Jilin Agricultural University, Changchun, Jilin, China
| | - Chen Zhao
- College of Public Health, Jilin Medical University, Jilin, Jilin, China; Medical College, Yanbian University, Yanji, Jilin, China.
| | - Shuai Peng
- College of Food Science and Engineering, Jilin Agricultural University, Changchun, Jilin, China.
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Dib AA, Assaf JC, Debs E, Khatib SE, Louka N, Khoury AE. A comparative review on methods of detection and quantification of mycotoxins in solid food and feed: a focus on cereals and nuts. Mycotoxin Res 2023; 39:319-345. [PMID: 37523055 DOI: 10.1007/s12550-023-00501-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 07/13/2023] [Accepted: 07/14/2023] [Indexed: 08/01/2023]
Abstract
Many emerging factors and circumstances urge the need to develop and optimize the detection and quantification techniques of mycotoxins in solid food and feed. The diversity of mycotoxins, which have different properties and affinities, makes the standardization of the analytical procedures and the adoption of a single protocol that covers the attributes of all mycotoxins a tedious or even an impossible mission. Several modifications and improvements have been undergone in order to optimize the performance of these methods including the extraction solvents, the extraction methods, the clean-up procedures, and the analytical techniques. The techniques range from the rapid screening methods, which lack sensitivity and specificity such as TLC, to a spectrum of more advanced protocols, namely, ELISA, HPLC, and GC-MS and LC-MS/MS. This review aims at assessing the current studies related to these analytical techniques of mycotoxins in solid food and feed. It discusses and evaluates, through a critical approach, various sample treatment techniques, and provides an in-depth examination of different mycotoxin detection methods. Furthermore, it includes a comparison of their actual accuracy and a thorough analysis of the observed benefits and drawbacks.
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Affiliation(s)
- Alaa Abou Dib
- Centre d'Analyses Et de Recherche (CAR), Faculté Des Sciences, Unité de Recherche Technologies Et Valorisation Agro-Alimentaire (UR-TVA), Université Saint-Joseph de Beyrouth, Campus Des Sciences Et TechnologiesMar Roukos, Matn, 1104-2020, Lebanon
- Department of Food Sciences and Technology, Faculty of Arts and Sciences, Bekaa Campus, Lebanese International University, Khiyara, 1108, Bekaa, Lebanon
| | - Jean Claude Assaf
- Department of Chemical Engineering, Faculty of Engineering, University of Balamand, P.O. Box 100, Tripoli, Lebanon
| | - Espérance Debs
- Department of Biology, Faculty of Arts and Sciences, University of Balamand, P.O. Box 100, Tripoli, 1300, Lebanon
| | - Sami El Khatib
- Department of Food Sciences and Technology, Faculty of Arts and Sciences, Bekaa Campus, Lebanese International University, Khiyara, 1108, Bekaa, Lebanon
- Center for Applied Mathematics and Bioinformatics, Gulf University for Science and Technology, Hawally, Kuwait
| | - Nicolas Louka
- Centre d'Analyses Et de Recherche (CAR), Faculté Des Sciences, Unité de Recherche Technologies Et Valorisation Agro-Alimentaire (UR-TVA), Université Saint-Joseph de Beyrouth, Campus Des Sciences Et TechnologiesMar Roukos, Matn, 1104-2020, Lebanon
| | - André El Khoury
- Centre d'Analyses Et de Recherche (CAR), Faculté Des Sciences, Unité de Recherche Technologies Et Valorisation Agro-Alimentaire (UR-TVA), Université Saint-Joseph de Beyrouth, Campus Des Sciences Et TechnologiesMar Roukos, Matn, 1104-2020, Lebanon.
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