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◆ ACS Sensors2025-11-24· Microfluidics

A Surface-Engineered Microfluidic Platform with Algorithmic Optimization for Plasma Biomarker Detection in Alzheimer’s Disease

Yue Cheng, Limoran Tang, Tan Yi, Hongpan Xu, Dan Yang, Zhixin Zhou, Wenqian Gao, Zhihong Ke, Chenglu Mao, Zheqi Hu, Hao Chen, Han Shen, Peng Cheng, Shujuan Xu, Yun Xu

原始摘要(英文原文)· Original abstract
Sensitive detection of low-abundance biomarkers in blood is essential for the early diagnosis of Alzheimer’s disease (AD). Although the single molecule array (Simoa) platform offers femtomolar-level sensitivity and surpasses conventional assays such as enzyme-linked immunosorbent assay, its broader clinical utility is constrained by issues like nonspecific binding and a limited dynamic range. In this study, we present a surface-engineered microfluidic platform incorporating engineered beads to reduce nonspecific binding, electrostatic bead–microwell pairing for improved capture efficiency, and an algorithmic calibration model to extend the dynamic range. These innovations collectively improve the analytical sensitivity and quantification accuracy for plasma Aβ1–42 and pTau181. Statistical analyses assessed correlation between our microfluidic platform and Quanterix Simoa, and evaluated our diagnostic ability using the Quanterix Simoa measurements as the reference standard in individuals with AD ( N = 107) and cognitively normal controls ( N = 100). We further validated diagnostic cutoff values in an independent cohort. The microfluidic platform demonstrates a superior diagnostic performance and enables reliable longitudinal monitoring of plasma biomarkers. Our results highlight the potential of the surface-engineered microfluidic platform for clinical translation in neurodegenerative disease diagnostics.
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A Surface-Engineered Microfluidic Platform with Algorithmic Optimization for Plasma Biomarker Detection in Alzheimer’s Disease — 科研速览 Science Skim