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Article

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Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence

Disciplines

1.4 CHEMICAL SCIENCES

Publication Details

Analyst, 10, 2019

Abstract

Analysis of biomarkers present in the blood stream can potentially deliver crucial information on patient health and indicate the presence of numerous pathologies. The potential of vibrational spectroscopic analysis of human serum for diagnostic purposes has been widely investigated and, in recent times, infrared absorption spectroscopy, coupled with ultra-filtration and multivariate analysis techniques, has attracted increasing attention, both clinical and commercial. However, such methods commonly employ a drying step, which may hinder the clinical work flow and thus hamper their clinical deployment. As an alternative, this study explores the use of Raman spectroscopy, similarly coupled with ultra-filtration and multivariate analysis techniques, to quantitatively monitor diagnostically relevant changes of glucose in liquid serum samples, and compares the results with similar analysis protocols using infrared spectroscopy of dried samples. The analysis protocols to detect the imbalances in glucose using Raman spectroscopy are first demonstrated for aqueous solutions and spiked serum samples. As in the case of infrared absorption studies, centrifugal filtration is utilised to deplete abundant analytes and to reveal the spectral features of Low Molecular Weight Fraction analytes in order to improve spectral sensitivity and detection limits. Improved Root Mean Square Error of Cross Validation (RMSECV) was observed for Raman prediction models, whereas slightly higher R2 values were reported for infrared absorption prediction models. Summarising, it is demonstrated that the Raman analysis protocol can yield accuracies which are comparable with those reported using infrared absorption based measurements of dried serum, without the need for additional drying steps.

DOI

https://doi.org/10.1039/C9AN00125E

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Creative Commons License

Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.


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