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通过生物识别驱动的非特异性结合的抑制来提高亲和生物传感器的选择性

Yang Zhang¹, Feng Hu¹, Ruiyun Zhou¹

¹School of Food and Biological Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, China.

|January 27, 2026

概括

实现可靠的生物传感器性能需要克服非特异性结合,这阻碍了现实世界样品的选择性. 本综述探讨了非特异性结合的起源以及提高生物传感器选择性以实现准确诊断的策略.

科学领域:

生物医学工程生物医学工程
分析化学分析化学
材料科学材料科学材料科学

背景情况:

生物传感器开发在实现可靠的灵敏度和选择性方面面临挑战,特别是在复杂的样本矩阵中.
选择性对于实际应用至关重要,但往往受到无意种类的非特异性结合 (NSB) 的限制.
了解NSB的起源和机制对于提高生物传感器准确性至关重要.

研究的目的:

批判性地审查生物传感器中非特异性结合的概念发展和物理化学起源.
评估生物识别元素的最新进展及其对非目标相互作用的易感性.
总结新兴的减轻非特异性结合和增强生物传感器选择性的策略.

主要方法:

对非特异性结合的概念分析.
对基质和生物识别元素的物理化学起源进行批判性检查.
识别元素 (抗体,体,酶) 和缓解策略的评估.

主要成果:

非特定的结合在复杂环境中显著影响生物传感器的选择性和可靠性.
目前的识别元素对非目标交互有局限性和脆弱性.
优化结合,结构设计,干扰消除和信号级方法等策略显示出有希望.

结论:

提高生物传感器的选择性需要一个多方面的方法,在各个层面解决NSB.
需要进一步研究NSB机制和先进的设计策略.
下一代生物传感器需要高精度和强大的选择性,以便在现实世界中应用.

关键词:

生物传感器生物传感器错误的结果导致错误的结果.矩阵效应是一种矩阵效应.纳米材料的使用方法不特定的结合性结合物识别元素的识别元素选择性的选择性特殊性的特异性

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