Early virus identification is a key component of both patient treatment and epidemiological monitoring. In the case of influenza A virus infections, where the detection of subtypes associated with bird flu in humans could lead to a pandemic, rapid subtype-level identification is important. Surface-enhanced Raman spectroscopy coupled with machine learning can be used to rapidly detect and identify viruses in a label-free manner. As there is a range of available excitation wavelengths for performing Raman spectroscopy, we must choose the best one to permit discrimination between highly similar subtypes of a virus. We show that the spectra produced by influenza A subtypes H1N1 and H3N2 exhibit a higher degree of dissimilarity when using 785 nm excitation wavelength in comparison with 532 nm excitation wavelength. Furthermore, the cross-validated area under the curve (AUC) for identification was higher for the 785 nm excitation, reaching 0.95 as compared to 0.86 for 532 nm. Ultimately, this study suggests that exciting with a 785 nm wavelength is better able to differentiate two closely related influenza viruses and likely can extend to other closely related pathogens.
This content will become publicly available on May 22, 2025
East Asian inks are a major component of calligraphy, paintings, and prints in China, Japan, and Korea and are historically made from either pine soot or oil‐lamp soot mixed with a proteinaceous binder. Although the inks from the two different soot sources have different properties in East Asian works of art, no non‐destructive methods to differentiate them scientifically currently exist. Raman spectroscopy (RS) of carbonaceous materials is commonly used to extract information about their properties and has been applied here to East Asian inks. Soots used in making modern inks were collected from 10 sources in China and Japan and analyzed using RS. RS using 405‐, 633‐, and 785‐nm excitation has been able to differentiate pine soot from oil‐lamp soot, also called lampblack. In addition, principal component analysis (PCA) of only 785‐nm Raman spectra has been able to discriminate between two different soots used in a 19th‐century Japanese woodblock printing of
- Award ID(s):
- 1706757
- PAR ID:
- 10508895
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Journal of Raman Spectroscopy
- ISSN:
- 0377-0486
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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