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Related Experiment Video

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A Surface-Engineered Microfluidic Platform with Algorithmic Optimization for Plasma Biomarker Detection in

Yue Cheng1,2,3,4, Limoran Tang1,2,3,4, Yi Tan1,2,3,4

  • 1Department of Neurology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210008, China.

ACS Sensors
|November 24, 2025
PubMed
Summary

A new microfluidic platform improves Alzheimer's disease (AD) blood biomarker detection by reducing errors and extending measurement range. This enhances early diagnosis and monitoring of neurodegenerative diseases.

Keywords:
Alzheimer’s diseaseAβ1−42algorithm-optimized digital immunoassayelectric field-assisted microsphere assemblypTau181surface-engineered microfluidic platformsurface-modified microspheres

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Area of Science:

  • Biomedical Engineering
  • Neuroscience
  • Analytical Chemistry

Background:

  • Early Alzheimer's disease (AD) diagnosis relies on detecting low-abundance blood biomarkers.
  • Conventional assays like enzyme-linked immunosorbent assay (ELISA) and even the sensitive Simoa platform face limitations in clinical utility due to nonspecific binding and limited dynamic range.
  • Accurate quantification of biomarkers such as Aβ1-42 and pTau181 is crucial for effective disease management.

Purpose of the Study:

  • To develop and validate a surface-engineered microfluidic platform for sensitive and accurate detection of Alzheimer's disease biomarkers in blood.
  • To overcome the limitations of existing platforms, specifically addressing nonspecific binding and extending the dynamic range for improved clinical utility.
  • To assess the diagnostic performance of the novel platform compared to established methods and evaluate its potential for clinical translation.

Main Methods:

  • Development of a microfluidic platform with engineered beads to minimize nonspecific binding.
  • Implementation of electrostatic bead-microwell pairing to enhance biomarker capture efficiency.
  • Integration of an algorithmic calibration model to extend the dynamic range of biomarker quantification.
  • Validation of the platform's performance using plasma samples from Alzheimer's disease patients and cognitively normal controls, with comparisons to Quanterix Simoa.

Main Results:

  • The surface-engineered microfluidic platform demonstrated improved analytical sensitivity and quantification accuracy for plasma Aβ1-42 and pTau181.
  • Statistical analysis confirmed a strong correlation between the microfluidic platform and the Quanterix Simoa, with superior diagnostic performance observed.
  • The platform showed significant potential in differentiating individuals with AD from controls and enabling reliable longitudinal biomarker monitoring.

Conclusions:

  • The developed surface-engineered microfluidic platform offers enhanced capabilities for sensitive and accurate detection of Alzheimer's disease biomarkers.
  • This innovative platform addresses key limitations of current assays, paving the way for improved early diagnosis and monitoring of neurodegenerative diseases.
  • The findings support the clinical translation potential of this microfluidic technology in the field of neurological diagnostics.