at Google ScholarTitle data
Pistiki, Aikaterini ; Ryabchykov, Oleg ; Bocklitz, Thomas ; Rösch, Petra ; Popp, Jürgen:
Use of polymers as wavenumber calibration standards in deep-UVRR.
In: Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy.
Vol. 287, Part 2
(2023)
.
- 122062.
ISSN 1873-3557
DOI: https://doi.org/10.1016/j.saa.2022.122062
Abstract in another language
Deep-UV resonance Raman spectroscopy (UVRR) allows the classification of bacterial species with high accuracy and is a promising tool to be developed for clinical application. For this attempt, the optimization of the wavenumber calibration is required to correct the overtime changes of the Raman setup. In the present study, different polymers were investigated as potential calibration agents. The ones with many sharp bands within the spectral range 400–1900 cm−1 were selected and used for wavenumber calibration of bacterial spectra. Classification models were built using a training cross-validation dataset that was then evaluated with an independent test dataset obtained after 4 months. Without calibration, the training cross-validation dataset provided an accuracy for differentiation above 99 % that dropped to 51.2 % after test evaluation. Applying the test evaluation with PET and Teflon calibration allowed correct assignment of all spectra of Gram-positive isolates. Calibration with PS and PEI leads to misclassifications that could be overcome with majority voting. Concerning the very closely related and similar in genome and cell biochemistry Enterobacteriaceae species, all spectra of the training cross-validation dataset were correctly classified but were misclassified in test evaluation. These results show the importance of selecting the most suitable calibration agent in the classification of bacterial species and help in the optimization of the deep-UVRR technique.
Further data
| Item Type: | Article in a journal |
|---|---|
| Refereed: | Yes |
| Keywords: | Deep-UV resonance Raman spectroscopy; Wavenumber calibration; Polymers; Bacterial species differentiation |
| Institutions of the University: | Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Lehrstuhl Künstliche Intelligenz in der Mikroskopie und Spektroskopie > Lehrstuhl Künstliche Intelligenz in der Mikroskopie und Spektroskopie - Univ.-Prof. Dr. Thomas Wilhelm Bocklitz |
| Result of work at the UBT: | No |
| DDC Subjects: | 500 Science > 530 Physics |
| Date Deposited: | 31 May 2023 12:22 |
| Last Modified: | 31 May 2023 12:22 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/81073 |