Label-free surfaced enhanced raman spectroscopic analysis of polyamines for skin diagnostics
The quantification of polyamines has been used in many research as an indication of wound status. In the early stages of many diseases, the onset of symptoms is not visible with only minor changes in biological components. As such, the use of Label-free Surface-Enhanced Raman Spectroscopy (SERS) is...
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Format: | Final Year Project |
Language: | English |
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Nanyang Technological University
2021
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Online Access: | https://hdl.handle.net/10356/145857 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | The quantification of polyamines has been used in many research as an indication of wound status. In the early stages of many diseases, the onset of symptoms is not visible with only minor changes in biological components. As such, the use of Label-free Surface-Enhanced Raman Spectroscopy (SERS) is highly suitable as its high sensitivity and “fingerprint” specificity allows the detection of small quantities of polyamines amongst other biological molecules with similar structures allowing for early diagnosis and treatment. This study aims to prove the preliminary development of the coupled model comprising of experiment and data analysis. Three pure polyamines found in diseased human skin were mixed with DNA, RNA, and Protein in different combinations simulating the complex biochemical composition in human cells. Their respective spectra were subsequently analysed via Non-Negative Least Squares (NNLS) for spectral unmixing after pre-processing and Principal Component Analysis (PCA)/Principal Component Analysis-Linear Discriminant Analysis (PCA-LDA) for classification. Overall, the multiplex model was able to clearly differentiate the mixture of up to six biological components. The potential of this program reinforces the capability of SERS in diagnostic and possibly treatment monitoring. This rapid and inexpensive Label-free SERS method serves as an alternative to the current expensive mass spectroscopy and time-consuming ELISA taking medical diagnostics to new heights. |
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