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Lookup NU author(s): Dr Ahmad Khundakar
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2024 by the authors. Surface-enhanced Raman spectroscopy (SERS) has recently emerged as a potent analytical technique with significant potential in the field of brain research. This review explores the applications and innovations of SERS in understanding the pathophysiological basis and diagnosis of brain disorders. SERS holds significant advantages over conventional Raman spectroscopy, particularly in terms of sensitivity and stability. The integration of label-free SERS presents promising opportunities for the rapid, reliable, and non-invasive diagnosis of brain-associated diseases, particularly when combined with advanced computational methods such as machine learning. SERS has potential to deepen our understanding of brain diseases, enhancing diagnosis, monitoring, and therapeutic interventions. Such advancements could significantly enhance the accuracy of clinical diagnosis and further our understanding of brain-related processes and diseases. This review assesses the utility of SERS in diagnosing and understanding the pathophysiological basis of brain disorders such as Alzheimer’s and Parkinson’s diseases, stroke, and brain cancer. Recent technological advances in SERS instrumentation and techniques are discussed, including innovations in nanoparticle design, substrate materials, and imaging technologies. We also explore prospects and emerging trends, offering insights into new technologies, while also addressing various challenges and limitations associated with SERS in brain research.
Author(s): Elsheikh S, Coles NP, Achadu OJ, Filippou PS, Khundakar AA
Publication type: Review
Publication status: Published
Journal: Biosensors
Year: 2024
Volume: 14
Issue: 1
Online publication date: 10/01/2024
Acceptance date: 20/12/2023
ISSN (electronic): 2079-6374
Publisher: MDPI
URL: https://doi.org/10.3390/bios14010033
DOI: 10.3390/bios14010033
PubMed id: 38248410
Data Access Statement: Not applicable.
