A Multichannel Fluorescent Tongue for Amyloid-β Aggregates Detection

Attention has been paid to the early diagnosis of Alzheimer's disease, due to the maximum benefit acquired from the early-stage intervention and treatment. However, the sensing techniques primarily depended upon for neuroimaging and immunological assays for the detection of AD biomarkers are expensive, time-consuming and instrument dependent. Here, we developed a multichannel fluorescent tongue consisting of four fluorescent dyes and GO through electrostatic and pi-pi interaction. The array distinguished multiple aggregation states of 1 mu M A beta 40/A beta 42 with 100% prediction accuracy via 10-channel signal outputs, illustrating the rationality of the array design. Screening vital sensor elements for the simplified sensor array and the optimization of sensing system was achieved by machine learning algorithms. Moreover, our sensing tongue was able to detect the aggregation states of A beta 40/A beta 42 in serum, demonstrating the great potential of multichannel array in diagnosing the Alzheimer's diseases.

Automated summary

This study developed a multichannel fluorescent tongue that can accurately detect the aggregation states of Alzheimer's disease through machine learning algorithm-based optimization.