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    Correlation between endometriomas volume and Raman spectra. Attempting to use Raman spectroscopy in the diagnosis of endometrioma
    (Elsevier B.V., 2022) Güleken, Z.; Bulut, Huri; Bulut, Berk; Paja, W.; Parlinska-Wojtan, M.; Depciuch, J.
    The formation of the uterus lining, i.e. the endometrium, outside the uterus (ex. in the abdominal cavity, ovaries, or anywhere in the body) is called endometriosis. The presence of endometrial tissue present in the ovaries, thickens after menstruation, leading to menstrual-like bleeding and to the formation of chocolate cyst (Endometrioma) because of the accumulation of old, brown blood in the ovary. It is still unknown, what triggers the development of endometrioma. However, it leads to excessive bleeding during menstrual periods or abnormal bleeding between periods and infertility. Endometriosis is often first diagnosed in those who seek medical attention for infertility. Therefore, new markers of endometrioma as well as new methods of its diagnosis are sought. In this study we used Raman spectra of serum collected from 50 healthy women and 50 women suffering from endometriosis. The obtained Raman data were used in multivariate analysis to determine the Raman range, which can be used for endometrioma diagnostics. Partial Least Square (PLS), Principal Component Analysis (PCA) and Hierarchical Component Analysis (HCA) showed, that it is possible to distinguish between the serum collected from healthy and un-healthy women using the Raman range between 800 cm?1 and 1800 cm?1 and between 2956 cm?1 and 2840 cm?1, while the first range corresponds to the fingerprint region and the second one to lipids vibrations. Consequently, the Pearson correlation test showed a significant positive correlation between values of lipid intensity in Raman spectra and volume of endometriomas. Summarizing, Raman spectroscopy can be a helpful tool in endometrioma diagnosis and the lipid vibrations are candidates for being a spectroscopic marker of the disease being studied. © 2022 Elsevier B.V.
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    Identification of polycystic ovary syndrome from blood serum using hormone levels via Raman spectroscopy and multivariate analysis
    (Elsevier, 2022) Güleken, Z.; Bulut, Huri; Bulut, Berk; Paja, W.; Orzechowska, B.; Parlinska-Wojtan, M.; Depciuch, J.
    Polycystic ovarian syndrome (PCOS) is a disease, which causes infertility in women. The factors for the development of the disease are still not well understood and diagnostic methods need to be improved. Therefore, in this study, Raman spectroscopy as a potential diagnostic tool, was investigated and spectra of blood serum were collected from PCOS and healthy women. The obtained spectra showed distinct changes in intensities as well as shift of peaks for the blood serum collected from PCOS compared to healthy individuals. Partial Last Square (PLS) analysis and Principal Component Analysis (PCA) allowed to determine that Raman shifts of amides (1500 – 1700 cm?1) and CH2, CH3 lipid groups (2700 – 3000 cm?1), could be thus used as potential PCOS markers. Furthermore, the Pearson correlation test showed a strong correlation between hormones (lutropin (LH), prolactin (PRL), follicle-stimulating (FSH), dehydroepiandrosterone (DHEAS), thyroid-stimulating (TSH), Estradiol) and lipids, as well as between hormones and protein functional groups in PCOS women, compared to the control. These results show, that the lipid and protein balance could be potentially applied as a helpful PCOS marker in Raman spectra. © 2022 Elsevier B.V.