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Visible resonance Raman spectroscopy detect key molecular biomarker vibrations to characterize for human brain gliomas
Resource type
Authors/contributors
- Zhou, Yan (Author)
- Liu, Cheng-hui (Author)
- Wu, Binlin (Author)
- Yu, Xinguang (Author)
- Gangge Cheng (Author)
- Zhang, Chunyuan (Author)
- Chen, Hong (Author)
- Li, Shenglin (Author)
- Zong, Rui (Author)
- Liang, Qijun (Author)
- Zhang, Ce (Author)
- Zhang, Mingqian (Author)
- Lu, Cuicui (Author)
- Zhu, Ke (Author)
- Alfano, Robert R. (Author)
Title
Visible resonance Raman spectroscopy detect key molecular biomarker vibrations to characterize for human brain gliomas
Abstract
Visible resonant Raman (VRR) spectroscopy provides an effective way to enhance Raman signal from particular bonds associated with key molecules due to changes on molecular level. This paper reports on the VRR use for detection of human brain the control and gliomas of three grades. From the RR spectra additional two molecular vibrational biomarkers at 1129cm-1 and 1338cm-1, for the four types of brain tissues are significantly different in intensity. The new RR spectral peaks can be used as molecular biomarkers to evaluate glioma grades and identify the margin of gliomas from the controls. The metabolic process of glioma cells based on the RR spectral changes may reveal the Warburg hypothesis.
Proceedings Title
Biomedical Imaging and Sensing Conference
Conference Name
Biomedical Imaging and Sensing Conference
Publisher
International Society for Optics and Photonics
Date
2018/04/24
Volume
10711
Pages
107110O
ISBN
0277786X (ISSN); 9781510619791 (ISBN)
Citation Key
zhouVisibleResonanceRaman2018
Accessed
12/24/19, 7:44 PM
Language
English
Library Catalog
Extra
0 citations (Crossref) [2023-10-31]
Citation Key Alias: lens.org/088-024-165-475-100, pop00126
Citation
Zhou, Y., Liu, C., Wu, B., Yu, X., Gangge Cheng, Zhang, C., Chen, H., Li, S., Zong, R., Liang, Q., Zhang, C., Zhang, M., Lu, C., Zhu, K., & Alfano, R. R. (2018). Visible resonance Raman spectroscopy detect key molecular biomarker vibrations to characterize for human brain gliomas. Biomedical Imaging and Sensing Conference, 10711, 107110O. https://doi.org/10.1117/12.2318751
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