2026

Biosensor-Based Detection of Calprotectin and Lactoferrin as Neutrophil-Derived Markers of Inflammatory Bowel Diseases: From Molecular Pathophysiology to Point-of-Care Platforms.

International journal of molecular sciences Sitkov N, Ryabko A, Ivanov S, Cheburkin Y, Kolobov A, Khasanova D, Nikolaev V, Kaplun D, Gareev K
阅读原文 PDF DOI PubMed

组成图示

示意图生成中

传感器类型

检测对象

检测原理

检测灵敏度

效应效果

传感器的构成

中文摘要

英文摘要

Inflammatory bowel diseases (IBD) are chronic, relapsing, immune-mediated disorders that require regular and preferably noninvasive monitoring of inflammatory activity. Fecal biomarkers of neutrophilic inflammation, namely calprotectin and lactoferrin, therefore represent key analytical targets for diagnosis and longitudinal disease management. Despite their widespread clinical use, existing publications predominantly address either their clinical relevance or individual technical solutions, without establishing a comprehensive engineering-translational framework for their biosensor-based implementation. This review bridges this gap by providing an integrative analysis of the molecular and biological nature of calprotectin and lactoferrin, the mechanisms underlying their appearance in fecal matrices, and the analytical constraints that directly influence the design of hybrid point-of-care (PoC) biosensor systems. We systematically compare major biosensing platforms, emphasizing sensor architecture, signal transduction mechanisms, and sample preparation strategies as critical determinants of sensitivity, selectivity, reproducibility, and clinical relevance. The novelty of this review lies in combining the pathophysiological context of neutrophilic inflammation with physicochemical and technological aspects of biosensor development, enabling a transition from laboratory prototypes to evaluation of real translational readiness. The practical significance resides in establishing a methodological basis for rational design of next-generation hybrid-integrated biosensor systems and outlining perspectives for digital analytics and artificial intelligence in clinically interpretable IBD monitoring.

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