1
|
Buhas BA, Toma V, Beauval JB, Andras I, Couți R, Muntean LAM, Coman RT, Maghiar TA, Știufiuc RI, Lucaciu CM, Crisan N. Label-Free SERS of Urine Components: A Powerful Tool for Discriminating Renal Cell Carcinoma through Multivariate Analysis and Machine Learning Techniques. Int J Mol Sci 2024; 25:3891. [PMID: 38612705 PMCID: PMC11011951 DOI: 10.3390/ijms25073891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2024] [Revised: 03/29/2024] [Accepted: 03/29/2024] [Indexed: 04/14/2024] Open
Abstract
The advent of Surface-Enhanced Raman Scattering (SERS) has enabled the exploration and detection of small molecules, particularly in biological fluids such as serum, blood plasma, urine, saliva, and tears. SERS has been proposed as a simple diagnostic technique for various diseases, including cancer. Renal cell carcinoma (RCC) ranks as the sixth most commonly diagnosed cancer in men and is often asymptomatic, with detection occurring incidentally. The onset of symptoms typically aligns with advanced disease, aggressive histology, and unfavorable prognosis, and therefore new methods for an early diagnosis are needed. In this study, we investigated the utility of label-free SERS in urine, coupled with two multivariate analysis approaches: Principal Component Analysis combined with Linear Discriminant Analysis (PCA-LDA) and Support Vector Machine (SVM), to discriminate between 50 RCC patients and 44 healthy donors. Employing LDA-PCA, we achieved a discrimination accuracy of 100% using 13 principal components, and an 88% accuracy in discriminating between different RCC stages. The SVM approach yielded a training accuracy of 100%, a validation accuracy of 99% for discriminating between RCC and controls, and an 80% accuracy for discriminating between stages. The comparative analysis of raw and normalized SERS spectral data shows that while raw data disclose relative concentration variations in urine metabolites between the two classes, the normalization of spectral data significantly improves the accuracy of discrimination. Moreover, the selection of principal components with markedly distinct scores between the two classes serves to alleviate overfitting risks and reduces the number of components employed for discrimination. We obtained the accuracy of the discrimination between the RCC patients cases and healthy donors of 90% for three PCs and a linear discrimination function, and a 88% accuracy of discrimination between stages using six PCs, mitigating practically the risk of overfitting and increasing the robustness of our analysis. Our findings underscore the potential of label-free SERS of urine in conjunction with chemometrics for non-invasive and early RCC detection.
Collapse
Affiliation(s)
- Bogdan Adrian Buhas
- Department of Urology, La Croix du Sud Hospital, 52 Chemin de Ribaute St., 31130 Quint Fonsegrives, France; (B.A.B.); (J.-B.B.)
- Department of Urology, Clinical Municipal Hospital, 11 Tabacarilor St., 400139 Cluj-Napoca, Romania; (I.A.); (N.C.)
- Faculty of Medicine and Pharmacy, University of Oradea, 1 Universitatii St., 410087 Oradea, Romania; (R.C.); (T.A.M.)
| | - Valentin Toma
- Department of Nanobiophysics, MedFuture Research Center for Advanced Medicine, “Iuliu Hatieganu” University of Medicine and Pharmacy, 4-6 Pasteur St., 400337 Cluj-Napoca, Romania;
| | - Jean-Baptiste Beauval
- Department of Urology, La Croix du Sud Hospital, 52 Chemin de Ribaute St., 31130 Quint Fonsegrives, France; (B.A.B.); (J.-B.B.)
| | - Iulia Andras
- Department of Urology, Clinical Municipal Hospital, 11 Tabacarilor St., 400139 Cluj-Napoca, Romania; (I.A.); (N.C.)
- Faculty of Medicine, “Iuliu Hatieganu” University of Medicine and Pharmacy, 8 Victor Babes St., 400347 Cluj-Napoca, Romania
| | - Răzvan Couți
- Faculty of Medicine and Pharmacy, University of Oradea, 1 Universitatii St., 410087 Oradea, Romania; (R.C.); (T.A.M.)
| | - Lucia Ana-Maria Muntean
- Department of Medical Education, “Iuliu Hatieganu” University of Medicine and Pharmacy, 8 Victor Babes St., 400347 Cluj-Napoca, Romania;
| | - Radu-Tudor Coman
- Faculty of Medicine, “Iuliu Hatieganu” University of Medicine and Pharmacy, 8 Victor Babes St., 400347 Cluj-Napoca, Romania
| | - Teodor Andrei Maghiar
- Faculty of Medicine and Pharmacy, University of Oradea, 1 Universitatii St., 410087 Oradea, Romania; (R.C.); (T.A.M.)
| | - Rareș-Ionuț Știufiuc
- Department of Nanobiophysics, MedFuture Research Center for Advanced Medicine, “Iuliu Hatieganu” University of Medicine and Pharmacy, 4-6 Pasteur St., 400337 Cluj-Napoca, Romania;
- Department of Pharmaceutical Physics–Biophysics, Faculty of Pharmacy, “Iuliu Hatieganu” University of Medicine and Pharmacy, 6 Pasteur St., 400349 Cluj-Napoca, Romania
- Nanotechnology Laboratory, TRANSCEND Research Center, Regional Institute of Oncology, 700483 Iași, Romania
| | - Constantin Mihai Lucaciu
- Department of Pharmaceutical Physics–Biophysics, Faculty of Pharmacy, “Iuliu Hatieganu” University of Medicine and Pharmacy, 6 Pasteur St., 400349 Cluj-Napoca, Romania
| | - Nicolae Crisan
- Department of Urology, Clinical Municipal Hospital, 11 Tabacarilor St., 400139 Cluj-Napoca, Romania; (I.A.); (N.C.)
- Faculty of Medicine, “Iuliu Hatieganu” University of Medicine and Pharmacy, 8 Victor Babes St., 400347 Cluj-Napoca, Romania
| |
Collapse
|
2
|
Li S, Chen Y, Cao X, Yang C, Li W, Shen B. The application of nanotechnology in kidney transplantation. Nanomedicine (Lond) 2024; 19:413-429. [PMID: 38275168 DOI: 10.2217/nnm-2023-0286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2024] Open
Abstract
Kidney transplantation is a crucial treatment option for end-stage renal disease patients, but challenges related to graft function, rejection and immunosuppressant side effects persist. This review highlights the potential of nanotechnology in addressing these challenges. Nanotechnology offers innovative solutions to enhance organ preservation, evaluate graft function, mitigate ischemia-reperfusion injury and improve drug delivery for immunosuppressants. The integration of nanotechnology holds promise for improving outcomes in kidney transplantation.
Collapse
Affiliation(s)
- Shengzhou Li
- Department of Urology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, 200080, Shanghai, China
| | - Yiming Chen
- Department of Orthopedics, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, 200080, Shanghai, China
| | - Xiangqian Cao
- Department of Urology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, 200080, Shanghai, China
| | - Chenkai Yang
- Department of Urology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, 200080, Shanghai, China
| | - Wei Li
- Department of Nanomedicine & Shanghai Key Lab of Cell Engineering, Naval Medical University, 200433, Shanghai, China
| | - Bing Shen
- Department of Urology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, 200080, Shanghai, China
- Shanghai Tenth People's Hospital of Tongji University, 200072, Shanghai, China
| |
Collapse
|
3
|
Atta S, Canning AJ, Vo-Dinh T. Rapid SERS assay for determination of the opioid fentanyl using silver-coated sharply branched gold nanostars. Mikrochim Acta 2024; 191:110. [PMID: 38252139 DOI: 10.1007/s00604-023-06172-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 12/22/2023] [Indexed: 01/23/2024]
Abstract
A high-throughput surface-enhanced Raman scattering (SERS)-sensing platform is presented for FNT detection in human urine without any sample preparation. The sensing platform is based on plasmonics-active silver-coated sharply branched gold nanostars (SGNS). The effect of silver thickness was investigated experimentally and theoretically, and the results indicated that SERS enhancement was maximum at an optimum silver thickness of 45 nm on the sharply spiked SGNS. The proposed high-throughput SERS platform exhibited ultrahigh sensitivity and excellent enhancement uniformity for a model analyte, i.e., crystal violet. Moreover, the SERS-sensing platform demonstrated good sensitivity of FNT spiked in human urine samples with two differential linear response ranges of 2 to 0.2 µg/mL and 0.1 µg/mL to 100 pg/mL, respectively, with a detection limit as low as 10.02 pg/mL. The spiked human urine samples show satisfactory recovery values from 92.5 to 102% with relative standard deviations (RSD) of less than 10%. In summary, the high-throughput performance of the proposed microplate-based SERS platform demonstrated great potential for rapid low-cost SERS-based sensing applications.
Collapse
Affiliation(s)
- Supriya Atta
- Fitzpatrick Institute for Photonics, Duke University, Durham, NC, 27708, USA
- Department of Biomedical Engineering, Duke University, Durham, NC, 27708, USA
| | - Aidan J Canning
- Fitzpatrick Institute for Photonics, Duke University, Durham, NC, 27708, USA
- Department of Biomedical Engineering, Duke University, Durham, NC, 27708, USA
| | - Tuan Vo-Dinh
- Fitzpatrick Institute for Photonics, Duke University, Durham, NC, 27708, USA.
- Department of Biomedical Engineering, Duke University, Durham, NC, 27708, USA.
- Department of Chemistry, Duke University, Durham, NC, 27708, USA.
| |
Collapse
|
4
|
Khristoforova YA, Bratchenko LA, Skuratova MA, Lebedeva EA, Lebedev PA, Bratchenko IA. Raman spectroscopy in chronic heart failure diagnosis based on human skin analysis. JOURNAL OF BIOPHOTONICS 2023:e202300016. [PMID: 36999197 DOI: 10.1002/jbio.202300016] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 03/09/2023] [Accepted: 03/28/2023] [Indexed: 06/19/2023]
Abstract
This work aims at studying Raman spectroscopy in combination with chemometrics as an alternative fast noninvasive method to detect chronic heart failure (CHF) cases. Optical analysis is focused on the changes in the spectral features associated with the biochemical composition changes of skin tissues. A portable spectroscopy setup with the 785 nm excitation wavelength was used to record skin Raman features. In this in vivo study, 127 patients and 57 healthy volunteers were involved in measuring skin spectral features by Raman spectroscopy. The spectral data were analyzed with a projection on the latent structures and discriminant analysis. 202 skin spectra of patients with CHF and 90 skin spectra of healthy volunteers were classified with 0.888 ROC AUC for the 10-fold cross validated algorithm. To identify CHF cases, the performance of the proposed classifier was verified by means of a new test set that is equal to 0.917 ROC AUC.
Collapse
Affiliation(s)
- Yulia A Khristoforova
- Department of Laser and Biotechnical Systems, Samara National Research University, Samara, Russia
| | - Lyudmila A Bratchenko
- Department of Laser and Biotechnical Systems, Samara National Research University, Samara, Russia
| | - Maria A Skuratova
- Cardiology Department, City Clinical Hospital № 1 named after N. I. Pirogov, Samara, Russia
| | - Elena A Lebedeva
- Cardiology Department, City Clinical Hospital № 1 named after N. I. Pirogov, Samara, Russia
| | - Petr A Lebedev
- Therapy chair of Postgraduate Department, Samara State Medical University, Samara, Russia
| | - Ivan A Bratchenko
- Department of Laser and Biotechnical Systems, Samara National Research University, Samara, Russia
| |
Collapse
|
5
|
Delrue C, Speeckaert MM. The Potential Applications of Raman Spectroscopy in Kidney Diseases. J Pers Med 2022; 12:jpm12101644. [PMID: 36294783 PMCID: PMC9604710 DOI: 10.3390/jpm12101644] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 09/09/2022] [Accepted: 09/29/2022] [Indexed: 12/23/2022] Open
Abstract
Raman spectroscopy (RS) is a spectroscopic technique based on the inelastic interaction of incident electromagnetic radiation (from a laser beam) with a polarizable molecule, which, when scattered, carries information from molecular vibrational energy (the Raman effect). RS detects biochemical changes in biological samples at the molecular level, making it an effective analytical technique for disease diagnosis and prognosis. It outperforms conventional sample preservation techniques by requiring no chemical reagents, reducing analysis time even at low concentrations, and working in the presence of interfering agents or solvents. Because routinely utilized biomarkers for kidney disease have limitations, there is considerable interest in the potential use of RS. RS may identify and quantify urinary and blood biochemical components, with results comparable to reference methods in nephrology.
Collapse
Affiliation(s)
- Charlotte Delrue
- Department of Nephrology, Ghent University Hospital, 9000 Ghent, Belgium
| | - Marijn M. Speeckaert
- Department of Nephrology, Ghent University Hospital, 9000 Ghent, Belgium
- Research Foundation-Flanders (FWO), 1000 Brussels, Belgium
- Correspondence: ; Tel.: +32-9-332-4509
| |
Collapse
|
6
|
Bratchenko LA, Al-Sammarraie SZ, Tupikova EN, Konovalova DY, Lebedev PA, Zakharov VP, Bratchenko IA. Analyzing the serum of hemodialysis patients with end-stage chronic kidney disease by means of the combination of SERS and machine learning. BIOMEDICAL OPTICS EXPRESS 2022; 13:4926-4938. [PMID: 36187246 PMCID: PMC9484439 DOI: 10.1364/boe.455549] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 03/11/2022] [Accepted: 03/18/2022] [Indexed: 05/29/2023]
Abstract
The aim of this paper is a multivariate analysis of SERS characteristics of serum in hemodialysis patients, which includes constructing classification models (PLS-DA, CNN) by the presence/absence of end-stage chronic kidney disease (CKD) with dialysis and determining the most informative spectral bands for identifying dialysis patients by variable importance distribution. We found the spectral bands that are informative for detecting the hemodialysis patients: the 641 cm-1, 724 cm-1, 1094 cm-1 and 1393 cm-1 bands are associated with the degree of kidney function inhibition; and the 1001 cm-1 band is able to demonstrate the distinctive features of hemodialysis patients with end-stage CKD.
Collapse
Affiliation(s)
- Lyudmila A Bratchenko
- Department of Laser and Biotechnical Systems, Samara University, 34 Moskovskoe Shosse, Samara, 443086, Russia
| | - Sahar Z Al-Sammarraie
- Department of Laser and Biotechnical Systems, Samara University, 34 Moskovskoe Shosse, Samara, 443086, Russia
| | - Elena N Tupikova
- Department of Chemistry, Samara University, 34 Moskovskoe Shosse, Samara, 443086, Russia
| | - Daria Y Konovalova
- Department of Internal Medicine, Samara State Medical University, 159 Tashkentskaya Street, Samara, 443095, Russia
| | - Peter A Lebedev
- Department of Internal Medicine, Samara State Medical University, 159 Tashkentskaya Street, Samara, 443095, Russia
| | - Valery P Zakharov
- Department of Laser and Biotechnical Systems, Samara University, 34 Moskovskoe Shosse, Samara, 443086, Russia
| | - Ivan A Bratchenko
- Department of Laser and Biotechnical Systems, Samara University, 34 Moskovskoe Shosse, Samara, 443086, Russia
| |
Collapse
|
7
|
Iancu SD, Cozan RG, Stefancu A, David M, Moisoiu T, Moroz-Dubenco C, Bajcsi A, Chira C, Andreica A, Leopold LF, Eniu D, Staicu A, Goidescu I, Socaciu C, Eniu DT, Diosan L, Leopold N. SERS liquid biopsy in breast cancer. What can we learn from SERS on serum and urine? SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2022; 273:120992. [PMID: 35220052 DOI: 10.1016/j.saa.2022.120992] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 01/21/2022] [Accepted: 02/01/2022] [Indexed: 06/14/2023]
Abstract
SERS analysis of biofluids, coupled with classification algorithms, has recently emerged as a candidate for point-of-care medical diagnosis. Nonetheless, despite the impressive results reported in the literature, there are still gaps in our knowledge of the biochemical information provided by the SERS analysis of biofluids. Therefore, by a critical assignment of the SERS bands, our work aims to provide a systematic analysis of the molecular information that can be achieved from the SERS analysis of serum and urine obtained from breast cancer patients and controls. Further, we compared the relative performance of five different machine learning algorithms for breast cancer and control samples classification based on the serum and urine SERS datasets, and found comparable classification accuracies in the range of 61-89%. This result is not surprising since both biofluids show striking similarities in their SERS spectra providing similar metabolic information, related to purine metabolites. Lastly, by carefully comparing the two datasets (i.e., serum and urine) we show that it is possible to link the misclassified samples to specific metabolic imbalances, such as carotenoid levels, or variations in the creatinine concentration.
Collapse
Affiliation(s)
- Stefania D Iancu
- Faculty of Physics, Babeș-Bolyai University, 400084 Cluj-Napoca, Romania
| | - Ramona G Cozan
- Faculty of Physics, Babeș-Bolyai University, 400084 Cluj-Napoca, Romania
| | - Andrei Stefancu
- Faculty of Physics, Babeș-Bolyai University, 400084 Cluj-Napoca, Romania
| | - Maria David
- Faculty of Chemistry and Chemical Engineering, Babeș-Bolyai University, 400028 Cluj-Napoca, Romania
| | - Tudor Moisoiu
- Clinical Institute of Urology and Renal Transplant, 400006 Cluj-Napoca, Romania; Faculty of Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, 400349 Cluj-Napoca, Romania; Biomed Data Analytics SRL, 400696 Cluj-Napoca, Romania
| | - Cristiana Moroz-Dubenco
- Department of Computer Science, Faculty of Mathematics and Computer Science, Babeș-Bolyai University, 400084 Cluj-Napoca, Romania
| | - Adel Bajcsi
- Department of Computer Science, Faculty of Mathematics and Computer Science, Babeș-Bolyai University, 400084 Cluj-Napoca, Romania
| | - Camelia Chira
- Department of Computer Science, Faculty of Mathematics and Computer Science, Babeș-Bolyai University, 400084 Cluj-Napoca, Romania; Department of Computer Science, Faculty of Mathematics and Computer Science, Babeș-Bolyai University, 400084 Cluj-Napoca, Romania
| | - Anca Andreica
- Department of Computer Science, Faculty of Mathematics and Computer Science, Babeș-Bolyai University, 400084 Cluj-Napoca, Romania
| | - Loredana F Leopold
- Faculty of Food Science and Technology, University of Agricultural Sciences and Veterinary Medicine, 400372 Cluj-Napoca, Romania
| | - Daniela Eniu
- Faculty of Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, 400349 Cluj-Napoca, Romania
| | - Adelina Staicu
- Faculty of Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, 400349 Cluj-Napoca, Romania
| | - Iulian Goidescu
- Faculty of Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, 400349 Cluj-Napoca, Romania
| | - Carmen Socaciu
- Faculty of Food Science and Technology, University of Agricultural Sciences and Veterinary Medicine, 400372 Cluj-Napoca, Romania; BIODIATECH Research Centre for Applied Biotechnology, SC Proplanta, 400478 Cluj-Napoca, Romania
| | - Dan T Eniu
- Faculty of Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, 400349 Cluj-Napoca, Romania; Department of Surgical and Gynecological Oncology, Ion Chiricuta Clinical Cancer Center, 400015 Cluj-Napoca, Romania
| | - Laura Diosan
- Department of Computer Science, Faculty of Mathematics and Computer Science, Babeș-Bolyai University, 400084 Cluj-Napoca, Romania.
| | - Nicolae Leopold
- Faculty of Physics, Babeș-Bolyai University, 400084 Cluj-Napoca, Romania; Biomed Data Analytics SRL, 400696 Cluj-Napoca, Romania.
| |
Collapse
|
8
|
Moisoiu V, Iancu SD, Stefancu A, Moisoiu T, Pardini B, Dragomir MP, Crisan N, Avram L, Crisan D, Andras I, Fodor D, Leopold LF, Socaciu C, Bálint Z, Tomuleasa C, Elec F, Leopold N. SERS liquid biopsy: An emerging tool for medical diagnosis. Colloids Surf B Biointerfaces 2021; 208:112064. [PMID: 34517219 DOI: 10.1016/j.colsurfb.2021.112064] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 08/09/2021] [Accepted: 08/20/2021] [Indexed: 02/02/2023]
Abstract
Surface-enhanced Raman scattering (SERS) is emerging as a novel strategy for biofluid analysis. In this review, we delineate four experimental SERS protocols that are frequently used for the profiling of biofluids: 1) liquid SERS for the detection of purine metabolites; 2) iodide-modified liquid SERS for the detection of proteins; 3) dried SERS for the detection of both purine metabolites and proteins; 4) resonant Raman for the detection of carotenoids. To explain the selectivity of each experimental SERS protocol, we introduce a heuristic model for the chemisorption of analytes mediated by adsorbed ions (adions) onto the SERS substrate. Next, we show that the promising results of SERS liquid biopsy stem from the fact that the concentration levels of purine metabolites, proteins and carotenoids are informative of the cellular turnover rate, inflammation, and oxidative stress, respectively. These processes are perturbed in virtually every disease, from cancer to autoimmune maladies. Finally, we review recent SERS liquid biopsy studies and discuss future steps that are required for translating SERS in the clinical setting.
Collapse
Affiliation(s)
- Vlad Moisoiu
- Faculty of Physics, Babeș-Bolyai University, 400084, Cluj-Napoca, Romania
| | - Stefania D Iancu
- Faculty of Physics, Babeș-Bolyai University, 400084, Cluj-Napoca, Romania
| | - Andrei Stefancu
- Faculty of Physics, Babeș-Bolyai University, 400084, Cluj-Napoca, Romania
| | - Tudor Moisoiu
- Clinical Institute of Urology and Renal Transplant, 400006, Cluj-Napoca, Romania; Biomed Data Analytics SRL, 400696, Cluj-Napoca, Romania; Department of Urology, Faculty of Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, 400012, Cluj-Napoca, Romania
| | - Barbara Pardini
- Candiolo Cancer Institute, FPO-IRCCS, 10060, Candiolo, Italy; Italian Institute of Genomic Medicine (IIGM), 10060, Candiolo, Italy
| | - Mihnea P Dragomir
- Institute of Pathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117, Berlin, Germany
| | - Nicolae Crisan
- Department of Urology, Faculty of Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, 400012, Cluj-Napoca, Romania; Clinical Municipal Hospital, 400139, Cluj-Napoca, Romania
| | - Lucretia Avram
- Clinical Municipal Hospital, 400139, Cluj-Napoca, Romania; Department of Geriatrics, Faculty of Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, 400012, Cluj-Napoca, Romania
| | - Dana Crisan
- Clinical Municipal Hospital, 400139, Cluj-Napoca, Romania; 5th Internal Medicine Department, Faculty of Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, 400012, Cluj-Napoca, Romania
| | - Iulia Andras
- Department of Urology, Faculty of Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, 400012, Cluj-Napoca, Romania; Clinical Municipal Hospital, 400139, Cluj-Napoca, Romania
| | - Daniela Fodor
- 2nd Internal Medicine Department, Iuliu Hatieganu University of Medicine and Pharmacy, 400006, Cluj-Napoca, Romania
| | - Loredana F Leopold
- Faculty of Food Science and Technology, University of Agricultural Sciences and Veterinary Medicine, 400372, Cluj-Napoca, Romania
| | - Carmen Socaciu
- Faculty of Food Science and Technology, University of Agricultural Sciences and Veterinary Medicine, 400372, Cluj-Napoca, Romania; BIODIATECH Research Centre for Applied Biotechnology, SC Proplanta, 400478, Cluj-Napoca, Romania
| | - Zoltán Bálint
- Faculty of Physics, Babeș-Bolyai University, 400084, Cluj-Napoca, Romania
| | - Ciprian Tomuleasa
- Department of Hematology, Iuliu Hatieganu University of Medicine and Pharmacy, 400124, Cluj-Napoca, Romania; Department of Hematology, Ion Chiricuta Clinical Cancer Center, 400124, Cluj-Napoca, Romania; Medfuture Research Center for Advanced Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, 400349, Cluj-Napoca, Romania
| | - Florin Elec
- Clinical Institute of Urology and Renal Transplant, 400006, Cluj-Napoca, Romania; Department of Urology, Faculty of Medicine, Iuliu Hatieganu University of Medicine and Pharmacy, 400012, Cluj-Napoca, Romania.
| | - Nicolae Leopold
- Faculty of Physics, Babeș-Bolyai University, 400084, Cluj-Napoca, Romania; Biomed Data Analytics SRL, 400696, Cluj-Napoca, Romania.
| |
Collapse
|