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Fernández-Manteca MG, Ocampo-Sosa AA, Vecilla DF, Ruiz MS, Roiz MP, Madrazo F, Rodríguez-Grande J, Calvo-Montes J, Rodríguez-Cobo L, López-Higuera JM, Fariñas MC, Cobo A. Identification of hypermucoviscous Klebsiella pneumoniae K1, K2, K54 and K57 capsular serotypes by Raman spectroscopy. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 319:124533. [PMID: 38820814 DOI: 10.1016/j.saa.2024.124533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 05/17/2024] [Accepted: 05/24/2024] [Indexed: 06/02/2024]
Abstract
Antimicrobial resistance poses a significant challenge in modern medicine, affecting public health. Klebsiella pneumoniae infections compound this issue due to their broad range of infections and the emergence of multiple antibiotic resistance mechanisms. Efficient detection of its capsular serotypes is crucial for immediate patient treatment, epidemiological tracking and outbreak containment. Current methods have limitations that can delay interventions and increase the risk of morbidity and mortality. Raman spectroscopy is a promising alternative to identify capsular serotypes in hypermucoviscous K. pneumoniae isolates. It provides rapid and in situ measurements with minimal sample preparation. Moreover, its combination with machine learning tools demonstrates high accuracy and reproducibility. This study analyzed the viability of combining Raman spectroscopy with one-dimensional convolutional neural networks (1-D CNN) to classify four capsular serotypes of hypermucoviscous K. pneumoniae: K1, K2, K54 and K57. Our approach involved identifying the most relevant Raman features for classification to prevent overfitting in the training models. Simplifying the dataset to essential information maintains accuracy and reduces computational costs and training time. Capsular serotypes were classified with 96 % accuracy using less than 30 Raman features out of 2400 contained in each spectrum. To validate our methodology, we expanded the dataset to include both hypermucoviscous and non-mucoid isolates and distinguished between them. This resulted in an accuracy rate of 94 %. The results obtained have significant potential for practical healthcare applications, especially for enabling the prompt prescription of the appropriate antibiotic treatment against infections.
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Affiliation(s)
- María Gabriela Fernández-Manteca
- Instituto de Investigación Sanitaria Valdecilla (IDIVAL), Santander, Spain; Photonics Engineering Group, Universidad de Cantabria, Santander, Spain.
| | - Alain A Ocampo-Sosa
- Instituto de Investigación Sanitaria Valdecilla (IDIVAL), Santander, Spain; Servicio de Microbiología, Hospital Universitario Marqués de Valdecilla, Santander, Spain; CIBER de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain
| | - Domingo Fernandez Vecilla
- Clinical Microbiology and Parasitology Department, Basurto University Hospital, Bilbao, Vizcaya, Spain; Biocruces Bizkaia Health Research Institute, Barakaldo, Vizcaya, Spain
| | - María Siller Ruiz
- Instituto de Investigación Sanitaria Valdecilla (IDIVAL), Santander, Spain; Servicio de Microbiología, Hospital Universitario Marqués de Valdecilla, Santander, Spain
| | - María Pía Roiz
- Instituto de Investigación Sanitaria Valdecilla (IDIVAL), Santander, Spain; Servicio de Microbiología, Hospital Universitario Marqués de Valdecilla, Santander, Spain
| | - Fidel Madrazo
- Instituto de Investigación Sanitaria Valdecilla (IDIVAL), Santander, Spain
| | - Jorge Rodríguez-Grande
- Instituto de Investigación Sanitaria Valdecilla (IDIVAL), Santander, Spain; Servicio de Microbiología, Hospital Universitario Marqués de Valdecilla, Santander, Spain
| | - Jorge Calvo-Montes
- Instituto de Investigación Sanitaria Valdecilla (IDIVAL), Santander, Spain; Servicio de Microbiología, Hospital Universitario Marqués de Valdecilla, Santander, Spain; CIBER de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain
| | - Luis Rodríguez-Cobo
- Instituto de Investigación Sanitaria Valdecilla (IDIVAL), Santander, Spain; Photonics Engineering Group, Universidad de Cantabria, Santander, Spain; CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Instituto de Salud Carlos III, Madrid, Spain
| | - José Miguel López-Higuera
- Instituto de Investigación Sanitaria Valdecilla (IDIVAL), Santander, Spain; Photonics Engineering Group, Universidad de Cantabria, Santander, Spain; CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Instituto de Salud Carlos III, Madrid, Spain
| | - María Carmen Fariñas
- Instituto de Investigación Sanitaria Valdecilla (IDIVAL), Santander, Spain; CIBER de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain; Servicio de Enfermedades Infecciosas, Hospital Universitario Marqués de Valdecilla, Santander, Spain; Departamento de Medicina y Psiquiatría, Universidad de Cantabria, Santander, Spain
| | - Adolfo Cobo
- Instituto de Investigación Sanitaria Valdecilla (IDIVAL), Santander, Spain; Photonics Engineering Group, Universidad de Cantabria, Santander, Spain; CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Instituto de Salud Carlos III, Madrid, Spain.
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2
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Guleken Z, Ceylan Z, Çeçen S, Elgörmüş Y, Cebulski J, Depciuch J. Quantitative or qualitative biomolecular changes in blood serum composition induced by childhood obesity: A Fourier transform infrared examination. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 313:124153. [PMID: 38492465 DOI: 10.1016/j.saa.2024.124153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Revised: 03/10/2024] [Accepted: 03/11/2024] [Indexed: 03/18/2024]
Abstract
Childhood obesity (CO) negatively affects one in three children and stands as the fourth most common risk factor of health and well-being. Clarifying the molecular and structural modifications that transpire during the development of obesity is crucial for understanding its progression and devising effective therapies. The study was indeed conducted as part of an ongoing CO treatment trial, where data were collected from children diagnosed with CO before the initiation of non-drug treatment interventions. Our primary aim was to analyze the biochemical changes associated with childhood obesity, specifically focusing on concentrations of lipids, lipoproteins, insulin, and glucose. By comparing these parameters between the CO group (n = 60) and a control group of healthy children (n = 43), we sought to elucidate the metabolic differences present in individuals with CO. Our biochemical analyses unveiled lower LDL (low-density lipoproteins) levels and higher HDL (high-density lipoproteins), cholesterol, triglycerides, insulin, and glucose levels in CO individuals compared to controls. To scrutinize these changes in more detail, we employed Fourier transform infrared (FTIR) spectroscopy on the serum samples. Our results indicated elevated levels of lipids and proteins in the serum of CO, compared to controls. Additionally, we noted structural changes in the vibrations of glucose, β-sheet, and lipids in CO group. The FTIR technique, coupled with principal component analysis (PCA), demonstrated a marked differentiation between CO and controls, particularly in the FTIR region corresponding to amide and lipids. The Pearson test revealed a stronger correlation between biochemical data and FTIR spectra than between 2nd derivative FTIR spectra. Overall, our study provides valuable insights into the molecular and structural changes occurring in CO.
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Affiliation(s)
- Zozan Guleken
- Gaziantep University of Science and Technology, Faculty of Medicine, Department of Physiology Gaziantep, Turkey
| | - Zeynep Ceylan
- Samsun University, Faculty of Engineering, Department of Industrial Engineering, Samsun, Turkey
| | - Serpil Çeçen
- Health Science University, Hamidiye Faculty of Medicine, Department of Physiology, İstanbul, Turkey
| | - Yusuf Elgörmüş
- Faculty of Medicine, Department of Pediatrics, İstanbul Atlas University Medicine Hospital, İstanbul 34408, Turkey
| | - Jozef Cebulski
- Institute of Physics, University of Rzeszow, 35-959 Rzeszow, Poland
| | - Joanna Depciuch
- Department of Biochemistry and Molecular Biology, Medical University of Lublin, Lublin 20-093, Poland; Institute of Nuclear Physics, PAS, 31342 Krakow, Poland.
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3
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Li S, Zheng Y, Yang Y, Yang H, Han C, Du P, Wang X, Yang H. Diagnosis and classification of intestinal diseases with urine by surface-enhanced Raman spectroscopy. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 312:124081. [PMID: 38422936 DOI: 10.1016/j.saa.2024.124081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 02/21/2024] [Accepted: 02/22/2024] [Indexed: 03/02/2024]
Abstract
Intestinal Disease (ID) is often characterized by clinical symptoms such as malabsorption, intestinal dysfunction, and injury. If treatment is not timely, it will increase the risk of cancer. Early diagnosis of ID is the key to cure it. There are certain limitations of the conventional diagnostic methods, such as low sensitivity and specificity. Therefore, development of a highly sensitive, non-invasive diagnostic method for ID is extremely important. Urine samples are easier to collect and more sensitive to changes in biomolecules than other pathological diagnostic samples such as tissue and blood. In this paper, a diagnostic method of ID with urine by surface-enhanced Raman spectroscopy (SERS) is proposed. A classification model between ID patients and healthy controls (HC) and a classification model between different pathological types of ID (i.e., benign intestinal disease (BID) and colorectal cancer (CRC)) are established. Here, 830 urine samples, including 100 HC, 443 BID, and 287 CRC, were investigated by SERS. The ID/HC classification model was developed by analyzing the SERS spectra of 150 ID and 100 HC, while BID/CRC classification model was built with 300 BID and 150 CRC patients by principal component analysis (PCA)-support vector machines (SVM). The two established models were internally verified by leave-one-out-cross-validation (LOOCV). Finally, the BID/CRC classification model was further evaluated by 143 BID and 137 CRC patients as an external test set. It shows that the accuracy of the classification model validated by the LOOCV for ID/HC and BID/CRC is 86.4% and 85.56%, respectively. And the accuracy of the BID/CRC classification model with external test set is 82.14%. It shows that high accuracy can be achieved with these two established classification models. It indicates that ID patients in the general population can be identified and BID and CRC patients can be further classified with measuring urine by SERS. It shows that the proposed diagnostic method and established classification models provide valuable information for clinicians to early diagnose ID patients and analyze different stages of ID.
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Affiliation(s)
- Silong Li
- School of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
| | - Yuqing Zheng
- School of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
| | - Yiheng Yang
- Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China
| | - Haojie Yang
- Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China
| | - Changpeng Han
- Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China
| | - Peng Du
- Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200092, China
| | - Xiaolei Wang
- Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai 200072, China.
| | - Huinan Yang
- School of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
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Depciuch J, Jakubczyk P, Paja W, Pancerz K, Wosiak A, Kula-Maximenko M, Yaylım İ, Gültekin Gİ, Tarhan N, Hakan MT, Sönmez D, Sarıbal D, Arıkan S, Guleken Z. Correlation between human colon cancer specific antigens and Raman spectra. Attempting to use Raman spectroscopy in the determination of tumor markers for colon cancer. NANOMEDICINE : NANOTECHNOLOGY, BIOLOGY, AND MEDICINE 2023; 48:102657. [PMID: 36646194 DOI: 10.1016/j.nano.2023.102657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 12/06/2022] [Accepted: 01/02/2023] [Indexed: 01/15/2023]
Abstract
Colorectal cancer is the second most common cause of cancer-related deaths worldwide. To follow up on the progression of the disease, tumor markers are commonly used. Here, we report serum analysis based on Raman spectroscopy to provide a rapid cancer diagnosis with tumor markers and two new cell adhesion molecules measured using the ELİSA method. Raman spectra showed higher Raman intensities at 1447 cm-1 1560 cm-1, 1665 cm-1, and 1769 cm-1, which originated from CH2 proteins and lipids, amide II and amide I, and CO lipids vibrations. Furthermore, the correlation test showed, that only the CEA colon cancer marker correlated with the Raman spectra. Importantly, machine learning methods showed, that the accuracy of the Raman method in the detection of colon cancer was around 95 %. Obtained results suggest, that Raman shifts at 1302 cm-1 and 1306 cm-1 can be used as spectroscopy markers of colon cancer.
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Affiliation(s)
- Joanna Depciuch
- Institute of Nuclear Physics Polish Academy of Science, 31-342 Krakow, Poland.
| | | | - Wiesław Paja
- Institute of Computer Science, University of Rzeszow, Poland
| | - Krzysztof Pancerz
- Institute of Philosophy, John Paul II Catholic University of Lublin, Poland
| | - Agnieszka Wosiak
- Institute of Information Technology, Lodz University of Technology, Poland
| | - Monika Kula-Maximenko
- The Franciszek Górski Institute of Plant Physiology, Polish Academy of Sciences, ul. Niezapominajek 21, 30-239 Kraków, Poland
| | - İlhan Yaylım
- Istanbul University, Aziz Sancar Institute of Molecular Medicine, Istanbul, Turkey
| | | | | | | | - Dilara Sönmez
- Istanbul University, Aziz Sancar Institute of Molecular Medicine, Istanbul, Turkey
| | - Devrim Sarıbal
- Department of Biophysics, Cerrahpaşa Medical School, Istanbul, Turkey
| | - Soykan Arıkan
- Istanbul Education and Research Hospital, Department of General Surgery, Istanbul, Turkey; Cam and Sakura City Hospital, Istanbul, Turkey
| | - Zozan Guleken
- Uskudar University, Faculty of Medicine, Department of Physiology, Istanbul, Turkey.
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Su N, Dawuti W, Hu Y, Zhao H. Noninvasive cholangitis and cholangiocarcinoma screening based on serum Raman spectroscopy and support vector machine. Photodiagnosis Photodyn Ther 2022; 40:103156. [PMID: 36252780 DOI: 10.1016/j.pdpdt.2022.103156] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 09/17/2022] [Accepted: 10/11/2022] [Indexed: 11/06/2022]
Abstract
The feasibility of serum Raman spectroscopy for rapid screening of cholangitis and cholangiocarcinoma (CCA) was explored Raman spectra were collected from 49 patients with cholangitis, 38 patients with CCA, and 55 healthy volunteers. Normalized mean Raman spectra and spectral attributions reveal disease-specific biomolecular differences. Support vector machine (SVM) was used to establish the two-way (cholangitis vs healthy, CCA vs healthy etc.) and 3-way (cholangitis vs CCA vs healthy) classification model, and leave-one-out cross-validation (LOOCV) was used to verify these models' performance. Based on the support vector machine algorithm, serum Raman spectroscopy could identify cholangitis and CCA. Its diagnostic sensitivity, and specificity were 89.80%, 94.55%, and 89.50%, 98.18%, respectively. This study demonstrates that label-free serum Raman spectroscopy analysis technique combined with SVM diagnostic algorithm has great potential for noninvasive cholangitis and CCA screening.
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Affiliation(s)
- Na Su
- Department of Clinical Laboratory, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
| | - Wubulitalifu Dawuti
- School of Public Health, Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Yan Hu
- Science and Technology Talent Development, Center of Xinjiang Uygur Autonomous Region, Urumqi, China.
| | - Hui Zhao
- Department of Clinical Laboratory, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
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Depciuch J, Jakubczyk P, Paja W, Sarzyński J, Pancerz K, Açıkel Elmas M, Keskinöz E, Bingöl Özakpınar Ö, Arbak S, Özgün G, Altuntaş S, Guleken Z. Apocynin reduces cytotoxic effects of monosodium glutamate in the brain: A spectroscopic, oxidative load, and machine learning study. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2022; 279:121495. [PMID: 35700610 DOI: 10.1016/j.saa.2022.121495] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Revised: 06/02/2022] [Accepted: 06/07/2022] [Indexed: 06/15/2023]
Abstract
Herein, we examined the modulatory effects ofApocynum (APO) on Monosodium Glutamate (MSG)-induced oxidative damage on the brain tissue of rats after long-term consumption of blood serum components by biochemical assays, Fourier transform infrared spectroscopy(FTIR), and machine learning methods. Sprague-Dawley male rats were randomly divided into the Control, Control + APO, MSG, and MSG + APO groups (n = 8 per group). All administrations were made by oral gavage saline, MSG, or APO and they were repeated for 28 days of the experiments. Brain tissue and blood serum samples were collected and analyzed for measurement levels ofmalondialdehyde (MDA),glutathione (GSH),myeloperoxidase (MPO), superoxide dismutase (SOD) activity, and Spectroscopic analysis. After 29 days, the results were evaluated using machine learning (ML). The levels of MDA and MPO showed changes in the MSG and MSG + APO groups, respectively. Changes in the proteins and lipids were observed in the FTIR spectra of the MSG groups. Additionally, APO in these animals improved the FTIR spectra to be similar to those in the Control group. The accuracy of the FTIR results calculated by ML was 100%. The findings of this study demonstrate that Apocynin treatment protectsagainst MSG-induced oxidative damage by inhibitingreactive oxygen speciesand upregulatingantioxidant capacity, indicating its potential in alleviatingthe toxic effects of MSG.
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Affiliation(s)
- Joanna Depciuch
- Institute of Nuclear Physics Polish Academy of Science, 31-342 Krakow, Poland.
| | | | - Wiesław Paja
- Institute of Computer Science, University of Rzeszów, Poland
| | | | - Krzysztof Pancerz
- Institute of Technology and Computer Science, Academy of Zamosc, Poland
| | - Merve Açıkel Elmas
- Department of Histology and Embryology, Acibadem Mehmet Ali Aydinlar University, School of Medicine, Istanbul, Turkey
| | - Elif Keskinöz
- Department of Anatomy, Acibadem Mehmet Ali Aydinlar University, School of Medicine, Istanbul, Turkey
| | | | - Serap Arbak
- Department of Histology and Embryology, Acibadem Mehmet Ali Aydinlar University, School of Medicine, Istanbul, Turkey
| | - Gökçe Özgün
- Department of Medical Biotechnology, Health Sciences Institute, Acibadem Mehmet Ali Aydinlar University, School of Medicine, Istanbul, Turkey
| | - Sevde Altuntaş
- Tissue Engineering Department, University of Health Sciences Turkey, Istanbul 34662, Turkey; Experimental Medicine Research and Application Center, Validebag Research Park, University of Health Sciences, Istanbul 34662, Turkey
| | - Zozan Guleken
- Department of Physiology, Uskudar University, Faculty of Medicine, Istanbul, Turkey.
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Beton K, Brożek-Płuska B. Biochemistry and Nanomechanical Properties of Human Colon Cells upon Simvastatin, Lovastatin, and Mevastatin Supplementations: Raman Imaging and AFM Studies. J Phys Chem B 2022; 126:7088-7103. [PMID: 36083294 PMCID: PMC9511485 DOI: 10.1021/acs.jpcb.2c03724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
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One of the most important areas of medical science is
oncology,
which is responsible for both the diagnostics and treatment of cancer
diseases. Over the years, there has been an intensive development
of cancer diagnostics and treatment. This paper shows the comparison
of normal (CCD-18Co) and cancerous (CaCo-2) cell lines of the human
gastrointestinal tract on the basis of nanomechanical and biochemical
properties to obtain information on cancer biomarkers useful in oncological
diagnostics. The research techniques used were Raman spectroscopy
and imaging and atomic force microscopy (AFM). In addition, the studies
also included the effect of the statin compounds—mevastatin,
lovastatin, and simvastatin—and their influence on biochemical
and nanomechanical changes of cell properties using Raman imaging
and AFM techniques. The cytotoxicity of statins was determined using
XTT tests.
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Affiliation(s)
- Karolina Beton
- Laboratory of Laser Molecular Spectroscopy, Institute of Applied Radiation Chemistry, Lodz University of Technology, Wroblewskiego 15, 93-590 Lodz, Poland
| | - Beata Brożek-Płuska
- Laboratory of Laser Molecular Spectroscopy, Institute of Applied Radiation Chemistry, Lodz University of Technology, Wroblewskiego 15, 93-590 Lodz, Poland
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8
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Jakubczyk P, Paja W, Pancerz K, Cebulski J, Depciuch J, Uzun Ö, Tarhan N, Guleken Z. Determination of idiopathic female infertility from infrared spectra of follicle fluid combined with gonadotrophin levels, multivariate analysis and machine learning methods. Photodiagnosis Photodyn Ther 2022; 38:102883. [PMID: 35487430 DOI: 10.1016/j.pdpdt.2022.102883] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 04/20/2022] [Accepted: 04/25/2022] [Indexed: 01/24/2023]
Abstract
By in vitro fertilization, oocytes can be removed and the embryo can be cultured, and then trans cervically replaced when they reach cleavage or when the blastocyst stage. The characterization of the follicular fluid is important for the treatment process. Women who applied to the Academic Hospital in vitro fertilization (IVF) Center diagnosed with idiopathic female infertility (IFI) were sought in the patient group. Demographics and clinical gonadotropin measurements of the study population were recorded. Of the 116 follicular fluid samples (n=58 male-induced infertility; n=58 control) were analyzed using the FTIR system. To identify FTIR spectral characteristics of follicular fluids associated with an ovarian reserve and reproductive hormone levels from control and IFI, six machine learning methods and multivariate analysis were used. To assess the quantitative information about the total biochemical composition of a follicular fluid across various diagnoses. FTIR spectra showed a higher level of vibrations corresponding to lipids and a lower level of amide vibrations in the IFI group. Furthermore, the T square plot from Partial Last Square (PLS) analysis showed, that these vibrations can be used to distinguish IFI from the control group which was obtained by principal component analysis (PCA). Proteins and lipids play an important role in the development of IFI. The absorption dynamics of FTIR spectra showed wavenumbers with around 100% discrimination probability, which means, that the presented wavenumbers can be used as a spectroscopic marker of IFI. Also, six machine learning methods showed, that classification accuracy for the original set was from 93.75% to 100% depending on the learning algorithm used. These results can inform about IFI women's follicular fluid has biomacromolecular differentiation in their follicular fluid. By using a safe and effective tool for the characterization of changes in follicular fluid during in vitro fertilization, this study builds upon a comprehensive examination of the idiopathic female infertility remodeling process in human studies. We anticipate that this technology will be a valuable adjunct for clinical studies.
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Affiliation(s)
| | - Wiesław Paja
- Institute of Computer Science, University of Rzeszów, Poland
| | - Krzysztof Pancerz
- Institute of Technology and Computer Science, Academy of Zamosc, Poland
| | | | - Joanna Depciuch
- Institute of Nuclear Physics Polish Academy of Science, 31-342 Krakow, Poland, Turkey.
| | - Özgur Uzun
- Istanbul University-Cerrahpaşa, Cerrahpasa Faculty of Medicine, Department of Histology and Embryology, Istanbul, Turkey
| | | | - Zozan Guleken
- Uskudar University, Faculty of Medicine, Department of Physiology, Istanbul Turkey.
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9
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Guleken Z, Kula-Maximenko M, Depciuch J, Kılıç AM, Sarıbal D. Detection of the chemical changes in blood, liver, and brain caused by electromagnetic field exposure using Raman spectroscopy, biochemical assays combined with multivariate analyses. Photodiagnosis Photodyn Ther 2022; 38:102779. [DOI: 10.1016/j.pdpdt.2022.102779] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 02/16/2022] [Accepted: 02/17/2022] [Indexed: 12/20/2022]
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