at Google ScholarTitle data
Žukovskaja, Olga ; Ryabchykov, Oleg ; Straßburger, Maria ; Heinekamp, Thorsten ; Brakhage, Axel A. ; Hennings, Christopher J. ; Hübner, Christian A. ; Wegmann, Michael ; Cialla-May, Dana ; Bocklitz, Thomas ; Weber, Karina ; Popp, Jürgen:
Towards Raman spectroscopy of urine as screening tool.
In: Journal of Biophotonics.
Vol. 13
(2020)
Issue 1
.
- e201900143.
ISSN 1864-0648
DOI: https://doi.org/10.1002/jbio.201900143
Abstract in another language
For the screening purposes urine is an especially attractive biofluid, since it offers easy and noninvasive sample collection and provides a snapshot of the whole metabolic status of the organism, which may change under different pathological conditions. Raman spectroscopy (RS) has the potential to monitor these changes and utilize them for disease diagnostics. The current study utilizes mouse models aiming to compare the feasibility of the urine based RS combined with chemometrics for diagnosing kidney diseases directly influencing urine composition and respiratory tract diseases having no direct connection to urine formation. The diagnostic models for included diseases were built using principal component analysis with linear discriminant analysis and validated with a leave-one-mouse-out cross-validation approach. Considering kidney disorders, the accuracy of 100% was obtained in discrimination between sick and healthy mice, as well as between two different kidney diseases. For asthma and invasive pulmonary aspergillosis achieved accuracies were noticeably lower, being, respectively, 77.27% and 78.57%. In conclusion, our results suggest that RS of urine samples not only provides a solution for a rapid, sensitive and noninvasive diagnosis of kidney disorders, but also holds some promises for the screening of nonurinary tract diseases.
Further data
| Item Type: | Article in a journal |
|---|---|
| Refereed: | Yes |
| Keywords: | linear discriminant analysis; principal component analysis; Raman spectroscopy; screening; urine |
| 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: | 12 May 2023 07:09 |
| Last Modified: | 12 May 2023 07:09 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/76388 |