Advanced Science (Jun 2024)

Ultrasensitive and Multiple Biomarker Discrimination for Alzheimer's Disease via Plasmonic & Microfluidic Sensing Technologies

  • Lijiao Zu,
  • Xicheng Wang,
  • Peng Liu,
  • Jiwei Xie,
  • Xuejun Zhang,
  • Weiru Liu,
  • Zhencheng Li,
  • Shiqing Zhang,
  • Kaiwei Li,
  • Ambra Giannetti,
  • Wei Bi,
  • Francesco Chiavaioli,
  • Lei Shi,
  • Tuan Guo

DOI
https://doi.org/10.1002/advs.202308783
Journal volume & issue
Vol. 11, no. 24
pp. n/a – n/a

Abstract

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Abstract As the population ages, the worldwide prevalence of Alzheimer's disease (AD) as the most common dementia in the elderly is increasing dramatically. However, a long‐term challenge is to achieve rapid and accurate early diagnosis of AD by detecting hallmarks such as amyloid beta (Aβ42). Here, a multi‐channel microfluidic‐based plasmonic fiber‐optic biosensing platform is established for simultaneous detection and differentiation of multiple AD biomarkers. The platform is based on a gold‐coated, highly‐tilted fiber Bragg grating (TFBG) and a custom‐developed microfluidics. TFBG excites a high‐density, narrow‐cladding‐mode spectral comb that overlaps with the broad absorption of surface plasmons for high‐precision interrogation, enabling ultrasensitive monitoring of analytes. In situ detection and in‐parallel discrimination of different forms of Aβ42 in cerebrospinal fluid (CSF) are successfully demonstrated with a detection of limit in the range of ≈30–170 pg mL−1, which is one order of magnitude below the clinical cut‐off level in AD onset, providing high detection sensitivity for early diagnosis of AD. The integration of the TFBG sensor with multi‐channel microfluidics enables simultaneous detection of multiple biomarkers using sub‐µL sample volumes, as well as combining initial binding rate and real‐time response time to differentiate between multiple biomarkers in terms of binding kinetics. With the advantages of multi‐parameter, low consumption, and highly sensitive detection, the sensor represents an urgently needed potentials for large‐scale diagnosis of diseases at early stage.

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