The aggregation and accumulation of amyloid-β (Aβ) peptides is a characteristic pathology for Alzheimer's disease (AD). Although noninvasive therapies involving stimulation by electric field (EF) have been reported, the efficiency of Aβ disaggregation needs to be further improved for this strategy to be used in clinical settings. In this study, we show that an electrode based on a vertical nanowire electrode array (VNEA) is far more superior to a typical flat-type electrode in disaggregating Aβ plaques. The enhanced disaggregation efficiency of VNEA is due to the formation of high-strength local EF between the nanowires, as verified by in silico and empirical evidence. Compared with those of the flat electrode, the simulation data revealed that 19.8-fold and 8.8-fold higher EFs are generated above and between the nanowires, respectively. Moreover, empirical cyclic voltammetry data demonstrated that VNEA had a 2.7-fold higher charge capacity than the flat electrode; this is associated with the higher surface area of VNEA. The conformational transition of Aβ peptides between the β-sheet and α-helix could be sensitively monitored in real time by the newly designed in situ circular dichroism instrument. This highly efficient EF-configuration of VNEA will lower the stimulation power for disaggregating the Aβ plaques, compared to that of other existing field-mediated modulation systems. Considering the complementary metal-oxide-semiconductor-compatibility and biocompatible strength of the EF for perturbing the Aβ aggregation, our study could pave the way for the potential use of electric stimulation devices for in vivo therapeutic application as well as scientific studies for AD.
Bibliographical noteFunding Information:
This research was supported by the Brain Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2018M3C7A1024654 and 2017R1A2A2A05069773) and the Korea government (MSIP) (No. 2017R1A2B3011586).
© 2020 American Chemical Society.
All Science Journal Classification (ASJC) codes
- Materials Science(all)