Zhang, S., Qi, Y., Tan, S. P. H., Bi, R., & Olivo, M. (2023). Molecular Fingerprint Detection Using Raman and Infrared Spectroscopy Technologies for Cancer Detection: A Progress Review. Biosensors, 13(5), 557. https://doi.org/10.3390/bios13050557
Abstract:
Molecular vibrations play a crucial role in physical chemistry and biochemistry, and Raman and infrared spectroscopy are the two most used techniques for vibrational spectroscopy. These techniques provide unique fingerprints of the molecules in a sample, which can be used to identify the chemical bonds, functional groups, and structures of the molecules. In this review article, recent research and development activities for molecular fingerprint detection using Raman and infrared spectroscopy are discussed, with a focus on identifying specific biomolecules and studying the chemical composition of biological samples for cancer diagnosis applications. The working principle and instrumentation of each technique are also discussed for a better understanding of the analytical versatility of vibrational spectroscopy. Raman spectroscopy is an invaluable tool for studying molecules and their interactions, and its use is likely to continue to grow in the future. Research has demonstrated that Raman spectroscopy is capable of accurately diagnosing various types of cancer, making it a valuable alternative to traditional diagnostic methods such as endoscopy. Infrared spectroscopy can provide complementary information to Raman spectroscopy and detect a wide range of biomolecules at low concentrations, even in complex biological samples. The article concludes with a comparison of the techniques and insights into future directions.
License type:
Attribution 4.0 International (CC BY 4.0)
Funding Info:
This research / project is supported by the A*STAR - BMRC Central Research Fund (ATR) 2021
Grant Reference no. : N.A
This research / project is supported by the A*STAR - Horizontal Technology Programme Office Seed Fund
Grant Reference no. : N.A
This research / project is supported by the A*STAR - Biomedical Engineering Programme 2021
Grant Reference no. : C211318004
This research / project is supported by the A*STAR - Career Development Award
Grant Reference no. : 202D800042