journal article·2021-10

Emerging two-dimensional materials-based diagnosis of neurodegenerative diseases: Status and challenges

Jingwen Wu, Wentao Dong, Zhongsheng Zhang, Jia Liu, Miriam Akioma, Jun Liu, Yibiao Liu, Artem Pliss, Xueji Zhang, Ping Luan

Nano Today· Volume 40
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Abstract

Abstract Neurodegenerative diseases (NDs), conventionally characterized by multifarious impacts on patients’ cognitive skill, motor function and memory, have been brought into focus with the aging tendency worldwide. Accurate and sensitive diagnosis is a sine qua non for effective therapies, but unfortunately, there still remain insufficient approaches to identifying the occurrence of NDs at clinical frontline and laboratory. Furthermore, most diagnostic methods, such as PET, MRI, ELISA, etc. are generally expensive and time-consuming. Based on this status quo, promising two-dimensional (2D) materials, with ultrathin atomic layer structure (one or several atoms thick generally) and huge specific surface area, have been researched to overcome those shortcomings owing to their extraordinary performances. The idea of integrating 2D materials and biomolecules provides inspiration for the development of the detection of various sensitive pathological substances. The atomic-level construction of biological probes with 2D materials can be an effective method for precise control of the sensing process, thus optimizing various performances of detection methods. This review provides some representative researches concerning how current 2D materials can shorten reaction time and elevate sensitivity via modifying electrodes, shortening quenching time and triggering signal amplification to elevate the properties of diagnostic methods. Here we summarize current strategies and challenges for 2D material-based applications of NDs to provide a clue to overcome the formidable obstacles in early diagnosis.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Alzheimer's disease research and treatments · Supramolecular Self-Assembly in Materials · S100 Proteins and Annexins

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

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