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

Abstract

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.

• Authors: Lian Xu, Hao Wang, Yu Xu, Wenyu Cui, Weiwei Ni, Mingqi Chen, Hui Huang, Callum Stewart, Linxian Li, Fei Li, Jinsong Han
• Journal: ACS sensors (ACS Sens) Vol. 7 Issue 5 Pg. 1315-1322 (05 27 2022) ISSN: 2379-3694 [Electronic] United States
• PMID: 35584464 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)

Chemical References

• Amyloid beta-Peptides
• Dendrimers
• Poly(amidoamine)
• Polyamines
• Poly A

Topics

• Alzheimer Disease
• Amyloid beta-Peptides (metabolism)
• Dendrimers
• Humans
• Machine Learning
• Poly A
• Polyamines