基于分子印迹聚合物的组胺传感器的护理点健康诊断和食品质量监测

Shahzad Ahmed, Arshiya Ansari, Zhixuan Li, Hirak Mazumdar, Moin Ali Siddiqui, Afzal Khan, Pranay Ranjan, Ajeet Kaushik, Ajayan Vinu, Prashant Kumar
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引用次数: 0

摘要

组胺是一种生物胺(BA),在各种病理生理过程中起着重要作用,存在于食物供应中,作为新鲜度和微生物降解的指标。它是食物中毒爆发的主要原因,引发过敏性炎症反应。检测食物中的组胺是至关重要的,因为它的毒性阈值不会影响食物的味道,使受污染的食物看起来正常。为了应对这一挑战,利用分子印迹聚合物(MIPs)的无标签和无生物活性电化学传感器提供了所需的选择性、可扩展性和效率。MIPs是设计用来模拟生物受体的合成材料。本文综述了近十年来mip辅助电化学传感器用于组胺检测的研究,重点是它们的可扩展性、鲁棒性、速度和选择性。这篇综述批判性地分析了这些传感器在检测食品、饮料、人类血清和身体诊断中的组胺的性能。此外,综述了目前对内源性和摄入组胺的生理作用的理解,重点介绍了其在食品和健康管理中的量化方法。还讨论了通过个性化的护理点(POC)系统,结合人工智能(AI)和医疗物联网(IoMT)技术,改变医疗保健服务的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Point-of-Care Health Diagnostics and Food Quality Monitoring by Molecularly Imprinted Polymers-Based Histamine Sensors

Point-of-Care Health Diagnostics and Food Quality Monitoring by Molecularly Imprinted Polymers-Based Histamine Sensors

Histamine, a biogenic amine (BA), plays a significant role in various pathophysiological processes and is present in food supplies, serving as an indicator of freshness and microbial degradation. It is a major cause of food poisoning outbreaks, triggering allergic inflammatory responses. Detecting histamine in food is crucial because its toxic threshold does not affect the food's taste, making contaminated items appear normal. To address this challenge, label-free and bioactive-free electrochemical sensors utilizing molecularly imprinted polymers (MIPs) offer the desired selectivity, scalability, and efficiency. MIPs are synthetic materials designed to mimic biological receptors. This paper reviews a decade of research on MIP-assisted electrochemical sensors for histamine detection, focusing on their scalability, robustness, speed, and selectivity. The review critically analyzes the performance of these sensors in detecting histamine in food, beverages, human serum, and body diagnostics. Additionally, the current understanding of the physiological effects of endogenous and ingested histamine is reviewed, highlighting both established and emerging methods for its quantification in food and health management. The potential for transforming healthcare delivery through personalized Point-of-Care (POC) systems, integrated with Artificial Intelligence (AI) and Internet-of-Medical Things (IoMT) technologies, is also discussed.

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