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使用基于芯片的印迹传感器伏安法测定碎牛肉中的[具体物质未给出]

Voltammetric determination of in minced beef meat using a chip-based imprinted sensor.

作者信息

Khalid Shaimaa A, Hassan Rabeay Y A, El Nashar Rasha Mohamed, El-Sherbiny Ibrahim M

机构信息

Nanomedicine Research Labs, Center for Materials Science, Zewail City of Science and Technology 6th October City 12578 Giza Egypt

Food Hygiene Department, Animal Health Research Institute (AHRI), Agricultural Research Center (ARC) Egypt.

出版信息

RSC Adv. 2022 Jan 25;12(6):3445-3453. doi: 10.1039/d1ra08526c. eCollection 2022 Jan 24.

Abstract

Early detection of pathogens is necessary for food quality monitoring, and increasing the survival rate of individuals. Conventional microbiological methods used to identify microorganisms, starting from bacterial culture and ending with advanced PCR gene identification, are time-consuming, laborious and expensive. Thus, in this study, a bacterial imprinted polymer (BIP)-based biosensor was designed and fabricated for rapid and selective detection of . Bio-recognition sites were made by creating template-shaped cavities in the electro-polymerized polydopamine matrices on a gold screen-printed electrode. The overall changes of the sensor, during the imprinting process, have been investigated with cyclic voltammetry, atomic force microscopy and scanning electron microscopy. The assay optimization and validation were accomplished, hence the highest sensitivity and selectivity towards were achieved As a result, a very low limit of detection of 47 CFU ml, and a limit of quantification of 142 CFU ml were achieved using the newly-developed biosensor. No interference signals were detected when the was tested in a mixed culture with other non-targeted pathogens such as , and Eventually, the biosensor was applied to minced beef meat samples offering not only fast detection but also direct determination with no bacterial enrichment steps.

摘要

病原体的早期检测对于食品质量监测和提高个体存活率至关重要。用于识别微生物的传统微生物学方法,从细菌培养开始到先进的PCR基因鉴定结束,既耗时、费力又昂贵。因此,在本研究中,设计并制造了一种基于细菌印迹聚合物(BIP)的生物传感器,用于快速、选择性地检测 。通过在金丝网印刷电极上的电聚合聚多巴胺基质中创建模板形状的空腔来制备生物识别位点。在印迹过程中,利用循环伏安法、原子力显微镜和扫描电子显微镜研究了传感器的整体变化。完成了分析方法的优化和验证,从而实现了对 的最高灵敏度和选择性。结果,使用新开发的生物传感器实现了47 CFU/ml的极低检测限和142 CFU/ml的定量限。当 在与其他非目标病原体如 、 和 的混合培养物中进行测试时,未检测到干扰信号。最终,该生物传感器应用于碎牛肉样品,不仅提供了快速检测,而且无需细菌富集步骤即可直接测定。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5452/8979253/0de90d8725d9/d1ra08526c-f1.jpg

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