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Öğe Analysis of follicular fluid and serum markers of oxidative stress in women with unexplained infertility by Raman and machine learning methods(Wiley, 2023) Depciuch, Joanna; Paja, Wieslaw; Pancerz, Krzysztof; Uzun, Ozgur; Bulut, Huri; Tarhan, Nevzat; Guleken, ZozanOocytes are surrounded by a fluid called follicular fluid, which provides an essential microenvironment for developing oocytes in human fertility. Various molecules exist in antral follicles, including proteins, steroid hormones, polysaccharides, metabolites, reactive oxygen species, and antioxidants. Oxidative stress is involved in the etiology of defective oocyte development or poor oocyte and embryo quality. Raman spectroscopy, a noninvasive method, can be used for biological diagnostics and direct chemical identification of follicular fluid. Therefore, we measured the oxidative index of follicular fluids and then attempted Raman spectroscopy on the follicular fluids combined with machine learning techniques to identify, detect, and quantify follicular fluid of unexplained infertility-diagnosed women as a safe and effective tool to use as adjacent for clinical studies. This was a retrospective study set in an academic hospital where the patients were selected from an unexplained infertility-diagnosed population in the in vitro fertilization (IVF) center. Raman spectra of 128 follicular fluid samples (n = 63 control; and 65 unexplained infertility) were obtained. To profile Raman-based results of follicular fluid, oxidative load measurements, multivariate analysis, correlation tests, and six machine learning methods were used. Raman bands associated with oxidative load and amide III and lipids differed significantly. Classification using stacks of Raman signals was applied by random forest, C5.0 decision tree algorithm, k-nearest neighbors, deep neural networks, support vector machine, and XGBoost trees algorithms achieved an overall accuracy of 92.04% to 99.17% in assigned correctly. Group has an oxidative load in their follicle fluids consistent with clinical results and biochemical measurements and performing testing based on Raman spectra validated by kNN clustering and SVM object vector separation machine learning methods. The study suggests that Raman spectroscopy can detect changes in follicle fluid in unexplained infertility.Öğe Assessment of oxidative stress effects in serum determined by FT-IR spectroscopy in cholangiocarcinoma patients(AMG Transcend Association, 2023) Bulut, Huri; Tarhan, Nevzat; Büyük, Melek; Serin, Kürşat Rahmi; Ulukaya, Engin; Depciuch, Joanna; Parlinska-Wojtan, Magdalena; Güleken, ZozanCholangiocarcinoma (CCA) is a heterogeneous malignant tumor containing intrahepatic and extrahepatic bile ducts and gallbladder carcinoma. Mostly diagnosed at an advanced stage with a <5% cure chance. Early-stage diagnosis may increase the number of patients who reach curative treatment. Fourier Transform InfraRed (FT-IR) spectroscopy was used to detect chemical changes in serum collected from CCA patients vs. healthy individuals. The study aims to correlate the FTIR spectra with biochemical indices such as TAS, TOS, OSI, and total protein levels. Decreased TAS and increased TOS, OSI, and total protein levels in CCA patients vs. healthy individuals were found. FTIR spectra showed higher absorbance of the peaks corresponding to C–O and bending vibration of C–O–H groups in CCA patients, while more CH2 functional groups than lipids could be seen in the FTIR spectra of controls serum. PLS analysis showed IR ranges of 1500 cm-1 to 1700 cm-1, and 2700 cm-1 to 3000 cm-1 were able to distinguish between CCA from controls, respectively. PCA confirmed this, while HCA did not differentiate between CCA and those without the disease. Lipids and some functional groups changes caused by oxidative stress can be applied to predict CCA by using FTIR spectroscopy. © 2022 by the authors.Öğe Assessment of structural protein expression by FTIR and biochemical assays as biomarkers of metabolites response in gastric and colon cancer(Elsevier B.V., 2021) Güleken, Zozan; Bulut, Huri; Gültekin, Güldal İnal; Arıkan, Soykan; Yaylım, İlhan; Hakan, Mehmet Tolgahan; Sönmez, Dilara; Tarhan, Nevzat K.; Depciuch, JoannaColon and gastric cancers are the widespread benign types of cancers which are synchronous and metachronous neoplasms. In terms of the progression and progress of the disease, metabolic processes and differentiation in protein structures have an important role in for treatment of the disease. In this study we proposed to investigate the metabolic process and the differentiation of protein secondary structure among colon and gastric cancer as well as healthy controls using biochemistry and Fourier Transform InfraRed spectroscopy (FTIR) methods. For this purpose, we measured blood serum of 133 patients, which were conducted upon oncology department (45 colon cancer, 45 gastric cancer and 43 control individuals). The obtained spectroscopic results and biochemical assays showed significant reduction in the amount of functional groups in cancer groups contrary with total protein measurements and structure of protein differences between colon and gastric cancers. Differentiations were visible in serum levels of CEA, CA-125, CA-15-3, CA-19-9 AFP (Alpha fetoprotein) of gastric and colon cancer patients as well as in amide III and secondly described amide I regions. Our findings suggest that amide I bonds in colon cancer cells can be helpful in diagnosis of colon cancer. Indeed, our results showed that metabolic processes were higher in gastric cancer group than in colon cancer. Hence, FTIR spectroscopy and curve-fitting analysis of amide I profile can be successfully applied as tools for identifying quantitative and qualitative changes of proteins in human cancerous blood serum. However, what is very important, in PCA analysis we see, that the scatter plot of PC1 (variability 80%) and PC2 (variability 15%) show that the data related to the control and two cancer groups are clustered together with different magnitudes and directions.Öğe Assessment of the effect of endocrine abnormalities on biomacromolecules and lipids by FT-IR and biochemical assays as biomarker of metabolites in early Polycystic ovary syndrome women(Elsevier, 2021) Güleken, Zozan; Bulut, Huri; Bulut, Berk; Depciuch, JoannaPolycystic ovary syndrome (PCOS) is a common endocrinopathy associated with metabolic disturbances.Both in the development and improvement of the disease, the structure of phospholipids and proteinsin the blood serum plays important role in the treatment of these disease. Herein, to investigate themetabolic process and the variations of biomacromolecules and lipids between young PCOS women andhealthy subjects, biochemistry and Fourier Transform InfraRed spectroscopy (FTIR) methods, were used.Moreover, partial least squares regression (PLS) and Principal component analysis (PCA) to researchdifferentiation of biomacromolecules, were performed. We obtained blood serum of of 100 individ-uals including 57 with PCOS and 43 healthy controls. The biochemical blood profile of PCOS womenwas presented by spectroscopic measurements, which is an analytical technique, as well as by labora-tory indexes and oxidative stress status measurements. There was a significant structural differentiationbetween studied groups in the number of functional groups and biomolecules differentiation dependingon the protein expression and oxidative stress status. Hence, FTIR spectroscopy and oxidative load can beeffectively utilized as tools for classifying quantitative and qualitative changes of biomolecules in PCOSsamples. PCOS samples did not correlate with luteinizing hormone (LH) level and proteins but had anegative correlation between carbohydrates and fatty acids, compared with control group.Öğe Blood serum lipid profiling may improve the management of recurrent miscarriage: a combination of machine learning of mid-infrared spectra and biochemical assays(SPRINGER HEIDELBERG, 2022) Guleken, Zozan; Bahat, Pınar Yalçın; Toto, Ömer Faruk; Bulut, Huri; Jakubczyk, Pawel; Cebulski, Jozef; Paja, Wieslaw; Pancerz, Krzysztof; Wosiak, Agnieszka; Depciuch, JoannaThe present article is focused on developing and validating an efficient, credible, minimally invasive technique based on spectral signatures of blood samples of women with recurrent miscarriage vs. those of healthy individuals who were followed in the Department of Obstetrics and Gynecology for 2 years. For this purpose, blood samples from a total of 120 participants, including healthy women (n=60) and women with diagnosed recurrent miscarriage (n=60), were obtained. The lipid profile (high-density lipoprotein, low-density lipoprotein, triglyceride, and total cholesterol levels) and lipid peroxidation (malondialdehyde and glutathione levels) were evaluated with a Beckman Coulter analyzer system for chemical analysis. Biomolecular structure and composition were determined using an attenuated total reflectance sampling methodology with Fourier transform infrared spectroscopy alongside machine learning technology to advance toward clinical translation. Here, we developed and validated instrumentation for the analysis of recurrent miscarriage patient serum that was able to differentiate recurrent miscarriage and control patients with an accuracy of 100% using a Fourier transform infrared region corresponding to lipids. We found that predictors of lipid profile abnormalities in maternal serum could significantly improve this patient pathway. The study also presents preliminary results from the first prospective clinical validation study of its kind.Öğe Characterization of Covid-19 infected pregnant women sera using laboratory indexes, vibrational spectroscopy, and machine learning classifications(Elsevier B.V., 2022) Güleken, Zozan; Jakubczyk, Pawe?; Paja, W.; Krzysztof, Pancerz; Bulut, Huri; Öten, Esra; Depciuch, Joanna; Tarhan, Nevzat K.Herein, we show differences in blood serum of asymptomatic and symptomatic pregnant women infected with COVID-19 and correlate them with laboratory indexes, ATR FTIR and multivariate machine learning methods. We collected the sera of COVID-19 diagnosed pregnant women, in the second trimester (n = 12), third-trimester (n = 7), and second-trimester with severe symptoms (n = 7) compared to the healthy pregnant (n = 11) women, which makes a total of 37 participants. To assign the accuracy of FTIR spectra regions where peak shifts occurred, the Random Forest algorithm, traditional C5.0 single decision tree algorithm and deep neural network approach were used. We verified the correspondence between the FTIR results and the laboratory indexes such as: the count of peripheral blood cells, biochemical parameters, and coagulation indicators of pregnant women. CH2 scissoring, amide II, amide I vibrations could be used to differentiate the groups. The accuracy calculated by machine learning methods was higher than 90%. We also developed a method based on the dynamics of the absorbance spectra allowing to determine the differences between the spectra of healthy and COVID-19 patients. Laboratory indexes of biochemical parameters associated with COVID-19 validate changes in the total amount of proteins, albumin and lipase.Öğe Diagnosis of endometriosis using endometrioma volume and vibrational spectroscopy with multivariate methods as a noninvasive method(Elsevier Science, 2022) Güleken, Zozan; Bulut, Huri; Depciuch, Joanna; Tarhan, NevzatEndometriomas are typically an advanced form of endometriosis that leads to the formation of scar tissue, adhesions, and an inflammatory reaction. There is no certain serum marker for the diagnosis of endometriosis. This study aims to research the correlation between the amount of peaks corresponding to proteins and lipids with the volume of endometrioma and determine the chemical structure of blood serum collected from women suffering from endometriosis patients with endometrioma and healthy subjects using Fourier Transform Infrared (FTIR) spectroscopy. FTIR spectroscopy is used as a non-invasive diagnostic technique for the discrimination of endometriosis women with endometrioma and control blood sera. The FTIR spectra of 100 serum samples acquired from 50 patients and 50 healthy individuals were used for this study. For this purpose, multivariate analyses such as Principal Component Analysis (PCA), Partial Last Square analysis (PLS) with Variables Importance in Projection (VIP), and probability models, were performed. Our results showed that FTIR range 1500 cm-1 and 1700 cm-1 and around 2700 cm-1 - 3000 cm-1, regions may be used for the diagnosis of endometriosis. Also, we find that proteins and lipids fraction increase with the volume of endometrioma. Moreover, PLS and VIP analysis suggested that lipids could be helpful in the diagnosis of endometriosis women with endometrioma.Öğe Differential of cholangiocarcinoma disease using Raman spectroscopy combined with multivariate analysis(2022) Depciuch, Joanna; Parlinska-Wojtan, Magdalena; Serin, Kürşat Rahmi; Bulut, Huri; Ulukaya, Engin; Tarhan, Nevzat; Güleken, ZozanCholangiocarcinoma (CCA) is a type of cancer, which 5-year survival is lower than 20 %, and which is detected mostly in advanced stage of the disease. Unfortunately, there are no diagnostic tools, which could show changes in the body indicating the development of the disease. Therefore, in this study, we investigate Raman spectroscopy as a promising analytical tool in medical diagnostics and as a method, which would allow to distinguish between healthy patients and patients suffering from cholangiocarcinoma. The obtained Raman spectra showed, that lower intensities of peaks corresponding to amino acids and proteins, as well as higher intensities of peaks originating from lipids vibrations were observed in healthy individuals in comparison with cancer patients. Moreover, Partial Last Square (PLS), Principal Component Analysis (PCA) and Hierarchical Component Analysis (HCA) of Raman spectra indicate that the ranges between 800 cm-1 and 1800 cm-1, 3477 cm-1 -3322 cm-1 and 1394 cm-1 -1297 cm-1 allow to distinguish cancer patients from healthy ones. The obtained results showed, that Raman spectroscopy is a good candidate, to become in future one of the diagnostic tools of Cholangiocarcinoma.Öğe Increased levels of nerve growth factor accompany oxidative load in recurrent pregnancy loss. machine learning applied to FT-raman spectra study(Springer, 2023) Depciuch, Joanna; Jakubczyk, Pawel; Paja, Wieslaw; Pancerz, Krzysztof; Wosiak, Agnieszka; Bahat, Pinar Yalcin; Toto, Omer Faruk; Bulut, Huri; Guleken, ZozanThe presented article is focused on developing and validating an efficient, credible, minimally invasive technique based on spectral signatures of blood serum samples in patients with diagnosed recurrent pregnancy loss (RPL) versus healthy individuals who were followed at the Gynecology department. A total of 120 participants, RPL disease (n = 60) and healthy individuals (n = 60), participated in the study. First, we investigated the effect of circulating nerve growth factor (NGF) in RPL and healthy groups. To show NGF's effect, we measured the level of oxidative loads such as Total Antioxidant Level (TAS), Total Oxidant Level (TOS), and Oxidative Stress Index (OSI) with Beckman Coulter AU system and biochemical assays. We find a correlation between oxidative load and NGF level. Oxidative load mainly causes structural changes in the blood. Therefore, we obtained Raman measurements of the participant's serum. Then we selected two Raman regions, 800 and 1800 cm(-1), and between 2700 cm(-1) and 3000 cm(-1), to see chemical changes. We noted that Raman spectra obtained for RPL and healthy women differed. The findings confirm that the imbalance between reactive oxygen species and antioxidants has important implications for the pathogenesis of RPL and that NGF levels accompany the level of oxidative load in the RPL state. Biomolecular structure and composition were determined using Raman spectroscopy and machine learning methods, and the correlation of these parameters was studied alongside machine learning technologies to advance toward clinical translation. Here we determined and validated the development of instrumentation for the Analysis of RPL patients' serum that can differentiate from control individuals with an accuracy of 100% using the Raman region corresponding to structural changes. Furthermore, this study found a correlation between traditional biochemical parameters and Raman data. This suggests that Raman spectroscopy is a sensitive tool for detecting biochemical changes in serum caused by RPL or other diseases.Öğe Spectrochemical and biochemical assay comparison study of the healing effect of the aloe vera and hypericum perforatum loaded nanofiber dressings on diabetic wound(Elsevier, 2021) Güleken, Zozan; Depciuch, Joanna; Ege, Hasan; İlbay, Gül; Kalkandelen, Cevriye; Özbeyli, Dilek; Bulut, Huri; Tarhan, Nevzat; Erdem Kuruca, SerapDiabetic wounds have a slow healing process and easy to be infected. In addition to current drug treatments, supportive approaches are needed for diabetic wound treatment. In this study, we aimed to load Aloe Vera (AV) and Hypericum perforatum oil (HPO) with PCL/Ge (Poly (?-caprolactone)/Gelatine) polymeric biodegradable by electrospinning method into nanofiber dressings on an experimental diabetic wound model to compare the diabetic wound healing effect. Changes in the amount and chemical structure of phospholipids, proteins, and lipids were investigated in the blood and serum samples of the animals using Fourier transform infrared (FTIR) analysis. To evaluate biological events associated with the wound repair process in inflammatory phase we used oxidant and antioxidant status to determine the healing status of wounds such as Total antioxidant status (TAS), Total oxidant level (TOS) and tumor necrosis factor alpha (TNF-?) levels. TOS level increased in DM groups and decreased in the AV and HPO group. Oxidative stress index decreased and TNF-? level increased in the HPO group. FTIR spectra showed changes in the phospholipids, proteins, and carbon chain of lipids in the whole blood as well as serum of DM rats. FTIR spectra combined with Principal component analysis (PCA) showed, that treated DM rats by AV and HPO caused return chemical structure of blood and serum to this observed in control group. Higher similarity with control group for HPO rats was observed. HPO is better than AV in the alternative for healing on diabetic wound. Thus, we have demonstrated that IR spectroscopy and multivariate data analysis and biochemical assays are consistent and correlative with each other.
