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Ghaithi AKA, Al Maskari SM, Al Mutani MM, Bimani AMA, Al Jabri Z, Badi KSA, Husband J. Specific discrimination of pathogenic bacteria causing septic arthritis using Raman spectroscopy: In-vitro study. Diagn Microbiol Infect Dis 2024; 109:116339. [PMID: 38735148 DOI: 10.1016/j.diagmicrobio.2024.116339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Revised: 04/14/2024] [Accepted: 05/03/2024] [Indexed: 05/14/2024]
Abstract
In this study we performed preliminary experiments using Raman spectroscopy as an evolving technology in biofluid and microbial characterization, to explore its potential for rapid diagnosis of pathogenic bacteria in an in-vitro synovial fluid infection model. Normal human synovial fluids samples were collected from patients undergoing knee surgery and the three most common pathogenic bacteria introduced in-vitro into the samples. The bacterial growth was systematically monitored using a Raman spectroscopy. Multivariate regression analysis of acquired spectra showed bacterial characteristic Raman bands related to bacterial cell membranes and DNA structures to increase continuously as the incubation period was increased. Spectra signature recorded from cultured synovial fluid samples showed a significant loss in synovial quality and protein morphology over time compared to control samples. In this study, Raman spectroscopy shows promise for rapid pathogenic bacteria identification in synovial fluid. Marker peaks distinguished inoculated bacteria, while chemical changes reveal infection dynamics.
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Affiliation(s)
- Ahmed K Al Ghaithi
- Department of Surgery, Division of Orthopedic, Sultan Qaboos University, Muscat, Oman.
| | - Sultan M Al Maskari
- Department of Surgery, Division of Orthopedic, Sultan Qaboos University, Muscat, Oman
| | - Mohammad M Al Mutani
- Department of Surgery, Division of Orthopedic, Sultan Qaboos University, Muscat, Oman
| | - Atika M Al Bimani
- Department of Microbiology, College of Medicine, Sultan Qaboos University, Muscat, Oman
| | - Zaaima Al Jabri
- Department of Microbiology, College of Medicine, Sultan Qaboos University, Muscat, Oman
| | - Khoula S Al Badi
- Department of Surgery, Division of Orthopedic, Sultan Qaboos University, Muscat, Oman
| | - John Husband
- Department of Chemistry, College of Science, Sultan Qaboos University, Muscat, Oman
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2
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Leong N, Yaacob MH, Md Zain AR, Tengku Abdul Aziz TH, Christianus A, Chong CM, Mahdi MA. Colloidal surface-enhanced Raman spectroscopic study of grouper epidermal mucus using acidified sodium sulphate as the aggregating agent. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 311:123974. [PMID: 38377639 DOI: 10.1016/j.saa.2024.123974] [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: 10/13/2023] [Revised: 01/24/2024] [Accepted: 01/27/2024] [Indexed: 02/22/2024]
Abstract
Fish epidermal mucus is an important reservoir of antipathogenic compounds which serves as the first line of the immune defence. Despite its significant role in the physiology and health of fish, detailed profiling of fish epidermal mucus has yet to be explored. Therefore, this study investigates a label-free colloidal surface-enhanced Raman spectroscopic (SERS) method for profiling grouper mucus. Gold nanoparticles were first synthesised using the standard citrate reduction and characterised using ultraviolet-visible spectroscopy, transmission electron microscopy and dynamic light scattering. The influence of acidified sodium sulphate (Na2SO4) at pH 3 as the aggregating agent on the enhancement of the SERS spectrum of different analyte samples including rhodamine 6G (R6G) dye, lysozyme solution and hybrid grouper (Epinephelus fuscoguttatus × Epinephelus lanceolatus) mucus was observed. Based on the results, an optimal Na2SO4 concentration of 1 M was recorded to achieve the highest enhancement of the SERS signal for R6G and grouper mucus, while the optimal concentration for lysozyme was 0.1 M. The results indicated a higher degree of aggregation induced by lysozyme than R6G and grouper mucus. A few overlapping peaks of the SERS spectra of lysozyme and grouper mucus made it possible to confirm the presence of lysozyme as potential biomarkers.
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Affiliation(s)
- Nathaniel Leong
- Wireless and Photonics Networks Research Centre, Faculty of Engineering, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia
| | - Mohd Hanif Yaacob
- Wireless and Photonics Networks Research Centre, Faculty of Engineering, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia
| | - Ahmad Rifqi Md Zain
- Institute of Microengineering and Nanoelectronics (IMEN), Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia
| | | | - Annie Christianus
- Department of Aquaculture, Faculty of Agriculture, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia
| | - Chou Min Chong
- Department of Aquaculture, Faculty of Agriculture, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia; Laboratory of Sustainable Aquaculture (AquaLab), International Institute of Aquaculture and Aquatic Sciences (I-AQUAS), Universiti Putra Malaysia, 71050 Port Dickson, Negeri Sembilan, Malaysia
| | - Mohd Adzir Mahdi
- Wireless and Photonics Networks Research Centre, Faculty of Engineering, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia; Institute of Nanoscience and Nanotechnology (ION2), Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia.
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Wu J, Dong J, Bao Y, Shang L, Wu Q, Yang Z, Wang H, Yin J. Synovial fluid research based on SERS and SERRS for enhanced detection of biomarkers in staged osteoarthritis. JOURNAL OF BIOPHOTONICS 2024:e202400024. [PMID: 38566479 DOI: 10.1002/jbio.202400024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 03/10/2024] [Accepted: 03/24/2024] [Indexed: 04/04/2024]
Abstract
Surface-enhanced (resonance) Raman scattering (SER(R)S) can extremely enhance Raman intensity of samples, which is helpful for detecting synovial fluid (SF) that does not show Raman activity under normal conditions. In this study, SER(R)S spectra of SF from three different osteoarthritis (OA) stages were collected and analyzed for OA progress, finding that the content of collagen increased throughout the disease, while non-collagen proteins and polysaccharides decreased sharply at advanced OA stage accompanied by the increase of phospholipid. The spectral features and differences were enhanced by salting-out and centrifugation. Much more information on biomolecules at different OA stages was disclosed by using SERRS for the first time, these main trace components (β-carotene, collagen, hyaluronic acid, nucleotide, and phospholipid) can be used as potential biomarkers. It indicates that SERRS has a more comprehensive ability to assist SERS in seeking micro(trace) biomolecules as biomarkers and facilitating accurate and efficient diagnosis and mechanism research of OA.
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Affiliation(s)
- Jinjin Wu
- Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Jiachun Dong
- Department of Orthopaedics, Sir Run Run Hospital, Nanjing Medical University, Nanjing, China
| | - Yilin Bao
- Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Linwei Shang
- Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Qingxia Wu
- Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Zichun Yang
- Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Huijie Wang
- Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Jianhua Yin
- Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China
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Fan X, Sun AR, Young RSE, Afara IO, Hamilton BR, Ong LJY, Crawford R, Prasadam I. Spatial analysis of the osteoarthritis microenvironment: techniques, insights, and applications. Bone Res 2024; 12:7. [PMID: 38311627 PMCID: PMC10838951 DOI: 10.1038/s41413-023-00304-6] [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: 09/05/2023] [Revised: 11/21/2023] [Accepted: 11/27/2023] [Indexed: 02/06/2024] Open
Abstract
Osteoarthritis (OA) is a debilitating degenerative disease affecting multiple joint tissues, including cartilage, bone, synovium, and adipose tissues. OA presents diverse clinical phenotypes and distinct molecular endotypes, including inflammatory, metabolic, mechanical, genetic, and synovial variants. Consequently, innovative technologies are needed to support the development of effective diagnostic and precision therapeutic approaches. Traditional analysis of bulk OA tissue extracts has limitations due to technical constraints, causing challenges in the differentiation between various physiological and pathological phenotypes in joint tissues. This issue has led to standardization difficulties and hindered the success of clinical trials. Gaining insights into the spatial variations of the cellular and molecular structures in OA tissues, encompassing DNA, RNA, metabolites, and proteins, as well as their chemical properties, elemental composition, and mechanical attributes, can contribute to a more comprehensive understanding of the disease subtypes. Spatially resolved biology enables biologists to investigate cells within the context of their tissue microenvironment, providing a more holistic view of cellular function. Recent advances in innovative spatial biology techniques now allow intact tissue sections to be examined using various -omics lenses, such as genomics, transcriptomics, proteomics, and metabolomics, with spatial data. This fusion of approaches provides researchers with critical insights into the molecular composition and functions of the cells and tissues at precise spatial coordinates. Furthermore, advanced imaging techniques, including high-resolution microscopy, hyperspectral imaging, and mass spectrometry imaging, enable the visualization and analysis of the spatial distribution of biomolecules, cells, and tissues. Linking these molecular imaging outputs to conventional tissue histology can facilitate a more comprehensive characterization of disease phenotypes. This review summarizes the recent advancements in the molecular imaging modalities and methodologies for in-depth spatial analysis. It explores their applications, challenges, and potential opportunities in the field of OA. Additionally, this review provides a perspective on the potential research directions for these contemporary approaches that can meet the requirements of clinical diagnoses and the establishment of therapeutic targets for OA.
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Affiliation(s)
- Xiwei Fan
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia
- School of Mechanical, Medical & Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia
| | - Antonia Rujia Sun
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia
- School of Mechanical, Medical & Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia
| | - Reuben S E Young
- Central Analytical Research Facility, Queensland University of Technology, Brisbane, QLD, Australia
- Molecular Horizons, University of Wollongong, Wollongong, NSW, Australia
| | - Isaac O Afara
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland
- School of Electrical Engineering and Computer Science, Faculty of Engineering, Architecture and Information Technology, University of Queensland, Brisbane, QLD, Australia
| | - Brett R Hamilton
- Centre for Microscopy and Microanalysis, University of Queensland, Brisbane, QLD, Australia
| | - Louis Jun Ye Ong
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia
- School of Mechanical, Medical & Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia
| | - Ross Crawford
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia
- The Prince Charles Hospital, Brisbane, QLD, Australia
| | - Indira Prasadam
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia.
- School of Mechanical, Medical & Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia.
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Xie X, Yu W, Chen Z, Wang L, Yang J, Liu S, Li L, Li Y, Huang Y. Early-stage oral cancer diagnosis by artificial intelligence-based SERS using Ag NWs@ZIF core-shell nanochains. NANOSCALE 2023; 15:13466-13472. [PMID: 37548371 DOI: 10.1039/d3nr02662k] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Surface-enhanced Raman spectroscopy (SERS) has great potential in the early diagnosis of diseases by detecting the changes of volatile biomarkers in exhaled breath, because of its high sensitivity, rich chemical molecular fingerprint information, and immunity to humidity. Here, an accurate diagnosis of oral cancer (OC) is demonstrated using artificial intelligence (AI)-based SERS of exhaled breath in plasmonic-metal organic framework (MOF) nanoparticles. These plasmonic-MOF nanoparticles were prepared using a zeolitic imidazolate framework coated on Ag nanowires (Ag NWs@ZIF), which offers Raman enhancement from the plasmonic nanowires and gas enrichment from the ZIF shells. Then, the core-shell nanochains of Ag NWs@ZIF prepared with 0.5 mL Ag NWs were selected to capture gaseous methanethiol, which is a tumor biomarker, from the exhalation of OC patients. The substrate was used to collect a total of 400 SERS spectra of exhaled breath of simulated healthy people and simulated OC patients. The artificial neural network (ANN) model in the AI algorithm was trained with these SERS spectra and could classify them with an accuracy of 99%. Notably, the model predicted OC with an area under the curve (AUC) of 0.996 for the simulated OC breath samples. This work suggests the great potential of the combination of breath analysis and AI as a method for the early-stage diagnosis of oral cancer.
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Affiliation(s)
- Xin Xie
- State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing Key Laboratory of Soft Condensed Matter Physics and Smart Materials, College of Physics, Chongqing University, Chongqing 400044, China.
| | - Wenrou Yu
- State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing Key Laboratory of Soft Condensed Matter Physics and Smart Materials, College of Physics, Chongqing University, Chongqing 400044, China.
| | - Zhaoxian Chen
- State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing Key Laboratory of Soft Condensed Matter Physics and Smart Materials, College of Physics, Chongqing University, Chongqing 400044, China.
| | - Li Wang
- School of Optoelectronics Engineering, Chongqing University, Chongqing 401331, China
| | - Junjun Yang
- State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing Key Laboratory of Soft Condensed Matter Physics and Smart Materials, College of Physics, Chongqing University, Chongqing 400044, China.
| | - Shihong Liu
- Department of Geriatric Oncology and Department of Palliative Care, Chongqing University Cancer Hospital, Chongqing, 400030, China
| | - Linze Li
- State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing Key Laboratory of Soft Condensed Matter Physics and Smart Materials, College of Physics, Chongqing University, Chongqing 400044, China.
| | - Yanxi Li
- State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing Key Laboratory of Soft Condensed Matter Physics and Smart Materials, College of Physics, Chongqing University, Chongqing 400044, China.
| | - Yingzhou Huang
- State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing Key Laboratory of Soft Condensed Matter Physics and Smart Materials, College of Physics, Chongqing University, Chongqing 400044, China.
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Lian T, Liu G, Qu B, Xia X, Yang Z, Wang L, Huang L, Wang X. Serum Raman spectroscopy can be used to screen patients with early rheumatoid arthritis. JOURNAL OF BIOPHOTONICS 2023; 16:e202200368. [PMID: 36606758 DOI: 10.1002/jbio.202200368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 12/20/2022] [Accepted: 12/27/2022] [Indexed: 06/07/2023]
Abstract
In this study, Raman spectroscopy was used to analyze the serum of patients with early rheumatoid arthritis (RA), and to explore the screening value of Raman spectroscopy in patients with early RA. A total of 216 patients were included in the study. Fasting venous blood was collected for routine biochemical detection, and the remaining samples were tested by serum Raman spectroscopy. Support vector machine was used for model building and training. The area under the curve (AUC) values of the model were as follows: (1) healthy group versus early RA group: 0.860, (2) healthy group versus non-early RA group: 0.903, and (3) early RA group versus non-early RA group: 0.918. This study shows that serum Raman spectroscopy has a good ability to screen RA and can be staged according to the course of the disease, which can provide new ideas and technical support for the diagnosis or screening of early RA.
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Affiliation(s)
- Tianxing Lian
- Department of Orthopedics, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China
- School of Clinical Medicine, Chengdu Medical College, Chengdu, China
| | - Gang Liu
- Department of Orthopedics, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China
| | - Bo Qu
- Department of Orthopedics, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China
| | - Xun Xia
- Department of Neurosurgery, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China
| | - Zixuan Yang
- Department of Orthopedics, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China
- School of Clinical Medicine, Chengdu Medical College, Chengdu, China
| | - Liping Wang
- Department of Orthopedics, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China
- School of Clinical Medicine, Chengdu Medical College, Chengdu, China
| | - Lin Huang
- School of Clinical Medicine, Chengdu Medical College, Chengdu, China
- Department of Neurosurgery, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China
| | - Xiaokai Wang
- School of Clinical Medicine, Chengdu Medical College, Chengdu, China
- Department of Neurosurgery, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China
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Vibrational Spectroscopy in Assessment of Early Osteoarthritis-A Narrative Review. Int J Mol Sci 2021; 22:ijms22105235. [PMID: 34063436 PMCID: PMC8155859 DOI: 10.3390/ijms22105235] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 05/07/2021] [Accepted: 05/13/2021] [Indexed: 12/21/2022] Open
Abstract
Osteoarthritis (OA) is a degenerative disease, and there is currently no effective medicine to cure it. Early prevention and treatment can effectively reduce the pain of OA patients and save costs. Therefore, it is necessary to diagnose OA at an early stage. There are various diagnostic methods for OA, but the methods applied to early diagnosis are limited. Ordinary optical diagnosis is confined to the surface, while laboratory tests, such as rheumatoid factor inspection and physical arthritis checks, are too trivial or time-consuming. Evidently, there is an urgent need to develop a rapid nondestructive detection method for the early diagnosis of OA. Vibrational spectroscopy is a rapid and nondestructive technique that has attracted much attention. In this review, near-infrared (NIR), infrared, (IR) and Raman spectroscopy were introduced to show their potential in early OA diagnosis. The basic principles were discussed first, and then the research progress to date was discussed, as well as its limitations and the direction of development. Finally, all methods were compared, and vibrational spectroscopy was demonstrated that it could be used as a promising tool for early OA diagnosis. This review provides theoretical support for the application and development of vibrational spectroscopy technology in OA diagnosis, providing a new strategy for the nondestructive and rapid diagnosis of arthritis and promoting the development and clinical application of a component-based molecular spectrum detection technology.
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Dina NE, Gherman AMR, Colniță A, Marconi D, Sârbu C. Fuzzy characterization and classification of bacteria species detected at single-cell level by surface-enhanced Raman scattering. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2021; 247:119149. [PMID: 33188974 DOI: 10.1016/j.saa.2020.119149] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 10/08/2020] [Accepted: 10/26/2020] [Indexed: 06/11/2023]
Abstract
Advanced chemometric methods, such as fuzzy c-means, a semi-supervised clustering method, and fuzzy linear discriminant analysis (FLDA), a new robust supervised classification method in combination with principal component analysis (PCA), namely PCA-FLDA, have been successfully applied for characterization and classification of bacterial species detected at single-cell level by surface-enhanced Raman scattering (SERS) spectroscopy. SERS spectra of three species (S. aureus, E. faecalis and P. aeruginosa) were recorded in an original fashion, using in situ laser induced silver spot as metallic substrate. The detection process of bacteria was isolated inside a hermetically sealed in-house built microfluidic device, connected to a syringe pump for injecting the analytes and a portable Raman spectrometer as detection tool. The obtained results (fuzzy partitions) and spectra of the prototypes (robust fuzzy spectra mean corresponding to each fuzzy partition) clearly demonstrated the efficiency and information power of the advanced fuzzy methods in bacteria characterization and classification based on SERS spectra, and allowed a rationale assigning to a specific group. Also, this powerful detection and classification methodology generates the premises for future investigations of Raman and other spectroscopic data obtained for various samples.
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Affiliation(s)
- Nicoleta Elena Dina
- Department of Molecular and Biomolecular Physics, National Institute for Research and Development of Isotopic and Molecular Technologies, 400293 Cluj-Napoca, Romania.
| | - Ana Maria Raluca Gherman
- Department of Molecular and Biomolecular Physics, National Institute for Research and Development of Isotopic and Molecular Technologies, 400293 Cluj-Napoca, Romania; Faculty of Physics, Babeş-Bolyai University, 400084 Cluj-Napoca, Romania
| | - Alia Colniță
- Department of Molecular and Biomolecular Physics, National Institute for Research and Development of Isotopic and Molecular Technologies, 400293 Cluj-Napoca, Romania.
| | - Daniel Marconi
- Department of Molecular and Biomolecular Physics, National Institute for Research and Development of Isotopic and Molecular Technologies, 400293 Cluj-Napoca, Romania
| | - Costel Sârbu
- Faculty of Chemistry and Chemical Engineering, Babeş-Bolyai University, 400028 Cluj-Napoca, Romania
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Casal-Beiroa P, González P, Blanco FJ, Magalhães J. Molecular analysis of the destruction of articular joint tissues by Raman spectroscopy. Expert Rev Mol Diagn 2020; 20:789-802. [PMID: 32538250 DOI: 10.1080/14737159.2020.1782747] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
INTRODUCTION Osteoarthritis (OA) is a highly heterogenous disease influenced by different molecular, anatomic, and physiologic imbalances. Some of the bottlenecks for enhanced diagnosis and therapeutic assessment are the lack of validated biomarkers and early diagnosis tools. In this narrative review, we analyze the potential of Raman spectroscopy (RS) as a label-free optical tool for the characterization of articular joint tissues and its application as a diagnosis tool for OA. AREAS COVERED Raman spectra produce a unique 'molecular fingerprint' providing rotational and vibrational molecular information, allowing the identification and follow-up of molecular changes associated with OA pathological mechanisms. Focusing on multiple joint tissues (cartilage, synovium, bone, tendons, ligaments, and meniscus) and their contribution in disease incidence and progression, this review highlights the current knowledge on the application of RS in the characterization of organic and inorganic molecules present at these tissues and alterations that occur in the onset of OA. EXPERT OPINION Vibrational spectroscopy techniques, such as RS, are low cost, rapid and minimally invasive approaches that offer high specificity in the assessment of the molecular composition of complex tissues. Combined with multivariate statistical methods, RS offers great potential for optical biomarkers discovery or disease diagnosis applications, and we hereby discuss clinical translational progresses on the field.
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Affiliation(s)
- Paula Casal-Beiroa
- Unidad de Medicina Regenerativa, Grupo de Investigación en Reumatología, Instituto de Investigación Biomédica de A Coruña (INIBIC) ., A Coruña, Spain.,Centro de Investigaciones Científicas Avanzadas (CICA), Universidad de A Coruña (UDC) ,A Coruña, Spain
| | - Pío González
- New Materials Group, Department of Applied Physics, University of Vigo , Vigo, Spain
| | - Francisco J Blanco
- Unidad de Medicina Regenerativa, Grupo de Investigación en Reumatología, Instituto de Investigación Biomédica de A Coruña (INIBIC) ., A Coruña, Spain.,Centro de Investigaciones Científicas Avanzadas (CICA), Universidad de A Coruña (UDC) ,A Coruña, Spain
| | - Joana Magalhães
- Unidad de Medicina Regenerativa, Grupo de Investigación en Reumatología, Instituto de Investigación Biomédica de A Coruña (INIBIC) ., A Coruña, Spain.,Centro de Investigaciones Científicas Avanzadas (CICA), Universidad de A Coruña (UDC) ,A Coruña, Spain.,Centro de Investigación Biomédica en Red (CIBER) , Madrid, Spain
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DUICA L, SZAKÁCS J, SILIȘTEANU Sînziana Călina. Study on the correlation between knee osteoarthritis and anxiety in patients aged over 55. BALNEO RESEARCH JOURNAL 2020. [DOI: 10.12680/balneo.2020.323] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Introduction. Osteoarthritis, which is a cause of chronic pain and disability with manifestation in any joint, with greater frequency in the joints of the lower limbs, upper limbs, but also at the spine level , affects around 250 million people in the entire world. This condition affects around 10% of the global population (18) and has an impressive impact on people, as it is one of the first 5 causes of disability. Material and method. The objectives of the treatment made by the patients diagnosed with knee osteoarthritis were: pain reduction, increased joint amplitude, increased muscle strength, increased muscle tone, increased quality of life and reintegration into the family and social environment. In the study, there were discussed demographic data regarding the patients. In order to assess the pain parameter, the VAS scale was used, as well as WOMAC subscales. To assess the quality of life of patients with knee osteoarthritis, the QOL scale (Quality of Life) was used. Anxiety was assessed with the help of a test that comprises the evaluation of symptoms at the cognitive, behavioral and physical level. Results and discussions. The pain was evaluated on the VAS scale, having a statistically significant evolution for the evaluation moments. Also with the help of the WOMAC index, two other parameters were evaluated, namely joint rigidity and functional capacity, the results being statistically significant in the 3 evaluation moments. The patients’ anxiety was evaluated with the help of the anxiety test; the results obtained were statistically significant at the 3 evaluation moments. Conclusions. It is vital that the recovery treatment in osteoarthritis be individualized and adapted to the age group. In our group, it enabled the reduction of pain and anxiety, the increase of the functional capacity and the quality of the patients’ lives.Taking into account the fact that the most affected group in the study group was the active professional one, we can evaluate the size of the recovery and the social, family and professional integration for these patients.
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Affiliation(s)
- Lavinia DUICA
- 1 Lucian Blaga University of Sibiu, Faculty of Medicine, Sibiu, România 2 Hospital of Psychiatry „Doctor Gheorghe Preda” Sibiu, Romania
| | - Juliánna SZAKÁCS
- 3George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures, Faculty of Medicine, Department of Biophysics
| | - SILIȘTEANU Sînziana Călina
- 4 Railway Hospital Iasi - Specialty Ambulatory of Suceava 5 "Stefan cel Mare" University of Suceava FEFS-DSDU
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Ralbovsky NM, Lednev IK. Towards development of a novel universal medical diagnostic method: Raman spectroscopy and machine learning. Chem Soc Rev 2020; 49:7428-7453. [DOI: 10.1039/d0cs01019g] [Citation(s) in RCA: 70] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
This review summarizes recent progress made using Raman spectroscopy and machine learning for potential universal medical diagnostic applications.
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Affiliation(s)
| | - Igor K. Lednev
- Department of Chemistry
- University at Albany
- SUNY
- Albany
- USA
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