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Machine Learning-Assisted Sensor Array Based on Poly(amidoamine) (PAMAM) Dendrimers for Diagnosing Alzheimer's Disease.

Lian XuHao WangYu XuWenyu CuiWeiwei NiMingqi ChenHui HuangCallum StewartLinxian LiFei LiJinsong Han
Published in: ACS sensors (2022)
Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder, and the early diagnosis of AD remains challenging. Here we have developed a fluorescent sensor array composed of three modified polyamidoamine dendrimers. Proteins of various properties were differentiated via this array with 100% accuracy, proving the rationality of the array's design. The mechanism of the fluorescence response was discussed. Furthermore, the robust three-element array enables parallel detection of multiple Aβ40/Aβ42 aggregates (0.5 μM) in diverse interferents, serum media, and cerebrospinal fluid (CSF) with high accuracy, through machine learning algorithms, demonstrating the tremendous potential of the sensor array in Alzheimer's disease diagnosis.
Keyphrases
  • machine learning
  • high resolution
  • high throughput
  • high density
  • cerebrospinal fluid
  • cognitive decline
  • artificial intelligence
  • big data
  • mild cognitive impairment
  • risk assessment
  • single cell
  • living cells
  • label free