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    Liquid-Core Microstructured Polymer Optical Fiber as Fiber-Enhanced Raman Spectroscopy Probe for Glucose Sensing
    (Washington, DC : OSA, 2020) Azkune, Mikel; Frosch, Timea; Arrospide, Eneko; Aldabaldetreku, Gotzon; Bikandi, Iñaki; Zubia, Joseba; Popp, Jürgen; Frosch, Torsten
    This work reports the development and application of two liquid-core microstructured polymer optical fibers (LC-mPOF) with different microstructure sizes. They are used in a fiber-enhanced Raman spectroscopy sensing platform, with the aim of detecting glucose in aqueous solutions in the clinically relevant range for sodium-glucose cotransporter 2 inhibitor therapy. The sensing platform is tested for low-concentration glucose solutions using each LC-mPOF. Results confirm that a significant enhancement of the Raman signal is achieved in comparison to conventional Raman spectroscopy. Additional measurements are carried out to obtain the valid measurement range, the resolution, and the limit of detection, showing that the LC-mPOF with 66-µm-diameter central hollow core has the highest potential for future clinical applications. Finally, preliminary tests successfully demonstrate glucose identification in urine. © 1983-2012 IEEE.
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    New methodology to process shifted excitation Raman difference spectroscopy data : a case study of pollen classification
    ([London] : Macmillan Publishers Limited, 2020) Korinth, F.; Mondol, A.S.; Stiebing, C.; Schie, I.W.; Krafft, C.; Popp, J.
    Shifted excitation Raman difference spectroscopy (SERDS) is a background correction method for Raman spectroscopy. Here, the difference spectra were directly used as input for SERDS-based classification after an optimization procedure to correct for photobleaching of the autofluorescence. Further processing included a principal component analysis to compensate for the reduced signal to noise ratio of the difference spectra and subsequent classification by linear discriminant analysis. As a case study 6,028 Raman spectra of single pollen originating from plants of eight different genera and four different growth habits were automatically recorded at excitation wavelengths 784 and 786 nm using a high-throughput screening Raman system. Different pollen were distinguished according to their growth habit, i.e. tree versus non-tree with an accuracy of 95.9%. Furthermore, all pollen were separated according to their genus, providing also insight into similarities based on their families. Classification results were compared using spectra reconstructed from the differences and raw spectra after state-of-art baseline correction as input. Similar sensitivities, specificities, accuracies and precisions were found for all spectra with moderately background. Advantages of SERDS are expected in scenarios where Raman spectra are affected by variations due to detector etaloning, ambient light, and high background.