journal article·2026-04

Multimodal Analysis of the Early Stage of Amyloid Formation via Graphene Liquid Cell Electron Microscopy

Jungjae Park, Namgyu Noh, Ji Su Park, Sanghyeon Ji, Kunmo Koo, Junpyo Hur, Jae Deok Kim, Sung Kang, Yonghee Lee, Kyeong Min Song, Yeon Sik Jung, Yoon Huh, Jong Min Yuk

Small· Volume 22· Issue 21
Publisher page

Abstract

ABSTRACT Elucidating the early‐stage dynamics of amyloid aggregation is crucial for comprehending the pathological mechanisms underlying neurodegenerative diseases. Conventional techniques, such as cryo‐electron microscopy and ensemble‐based spectroscopy, offer valuable structural insights but face challenges in capturing real‐time molecular interactions due to low temporal resolution and the need for ensemble averaging, which obscures transient intermediate states. To investigate the early‐stage dynamics of amyloid‐β oligomer (AβO) formation, here, we introduce a multimodal analytical framework that integrates semi‐ensemble population analysis and time‐sequential analysis based on movie frame images obtained using a liquid‐flowing graphene liquid cell platform. This method enables high‐resolution observation of AβO aggregates, aggregation kinetics, and structural transitions at both the semi‐ensemble and individual‐species levels. Our analysis reveals that early‐stage AβOs reside in a kinetic quasi‐equilibrium regime, characterized by rapid microscopic association–dissociation events while maintaining nearly invariant aggregate populations. By addressing the limitations of ensemble macroscopic techniques, this approach provides new insights into the fundamental mechanisms of amyloid nucleation, paving the way for advanced studies in protein misfolding diseases.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Alzheimer's disease research and treatments · Topological and Geometric Data Analysis · Advanced Electron Microscopy Techniques and Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Materials Science and Engineering Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea

Analysis and Assessment Research Center Research Institute of Industrial Science and Technology (RIST) Pohang Republic of Korea

Department of Nano & Advanced Materials Science and Engineering Kyungpook National University (KNU) Sangju Republic of Korea

Energy Storage Material Center Korea Institute of Ceramic Engineering and Technology (KICET) Jinju Republic of Korea

GIST InnoCORE AI‐Nano Convergence Initiative for Early Detection of Neurodegenerative Diseases Gwangju Institute of Science and Technology (GIST) Gwangju Republic of Korea

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