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Ranasinghe JC, Wang Z, Huang S. Unveiling brain disorders using liquid biopsy and Raman spectroscopy. NANOSCALE 2024; 16:11879-11913. [PMID: 38845582 DOI: 10.1039/d4nr01413h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/28/2024]
Abstract
Brain disorders, including neurodegenerative diseases (NDs) and traumatic brain injury (TBI), present significant challenges in early diagnosis and intervention. Conventional imaging modalities, while valuable, lack the molecular specificity necessary for precise disease characterization. Compared to the study of conventional brain tissues, liquid biopsy, which focuses on blood, tear, saliva, and cerebrospinal fluid (CSF), also unveils a myriad of underlying molecular processes, providing abundant predictive clinical information. In addition, liquid biopsy is minimally- to non-invasive, and highly repeatable, offering the potential for continuous monitoring. Raman spectroscopy (RS), with its ability to provide rich molecular information and cost-effectiveness, holds great potential for transformative advancements in early detection and understanding the biochemical changes associated with NDs and TBI. Recent developments in Raman enhancement technologies and advanced data analysis methods have enhanced the applicability of RS in probing the intricate molecular signatures within biological fluids, offering new insights into disease pathology. This review explores the growing role of RS as a promising and emerging tool for disease diagnosis in brain disorders, particularly through the analysis of liquid biopsy. It discusses the current landscape and future prospects of RS in the diagnosis of brain disorders, highlighting its potential as a non-invasive and molecularly specific diagnostic tool.
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Affiliation(s)
- Jeewan C Ranasinghe
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA.
| | - Ziyang Wang
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA.
| | - Shengxi Huang
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA.
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2
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Alix JJP, Plesia M, Dudgeon AP, Kendall CA, Hewamadduma C, Hadjivassiliou M, Gorman GS, Taylor RW, McDermott CJ, Shaw PJ, Mead RJ, Day JC. Conformational fingerprinting with Raman spectroscopy reveals protein structure as a translational biomarker of muscle pathology. Analyst 2024; 149:2738-2746. [PMID: 38533726 PMCID: PMC11056770 DOI: 10.1039/d4an00320a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Accepted: 03/11/2024] [Indexed: 03/28/2024]
Abstract
Neuromuscular disorders are a group of conditions that can result in weakness of skeletal muscles. Examples include fatal diseases such as amyotrophic lateral sclerosis and conditions associated with high morbidity such as myopathies (muscle diseases). Many of these disorders are known to have abnormal protein folding and protein aggregates. Thus, easy to apply methods for the detection of such changes may prove useful diagnostic biomarkers. Raman spectroscopy has shown early promise in the detection of muscle pathology in neuromuscular disorders and is well suited to characterising the conformational profiles relating to protein secondary structure. In this work, we assess if Raman spectroscopy can detect differences in protein structure in muscle in the setting of neuromuscular disease. We utilise in vivo Raman spectroscopy measurements from preclinical models of amyotrophic lateral sclerosis and the myopathy Duchenne muscular dystrophy, together with ex vivo measurements of human muscle samples from individuals with and without myopathy. Using quantitative conformation profiling and matrix factorisation we demonstrate that quantitative 'conformational fingerprinting' can be used to identify changes in protein folding in muscle. Notably, myopathic conditions in both preclinical models and human samples manifested a significant reduction in α-helix structures, with concomitant increases in β-sheet and, to a lesser extent, nonregular configurations. Spectral patterns derived through non-negative matrix factorisation were able to identify myopathy with a high accuracy (79% in mouse, 78% in human tissue). This work demonstrates the potential of conformational fingerprinting as an interpretable biomarker for neuromuscular disorders.
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Affiliation(s)
- James J P Alix
- Sheffield Institute for Translational Neuroscience, University of Sheffield, UK.
- Neuroscience Institute, University of Sheffield, Western Bank, Sheffield, UK
- National Institute for Health and Care Research Sheffield Biomedical Research Centre, Sheffield, UK
| | - Maria Plesia
- Sheffield Institute for Translational Neuroscience, University of Sheffield, UK.
| | - Alexander P Dudgeon
- Biophotonics Research Unit, Gloucestershire Hospitals NHS Foundation Trust, UK
- Department of Physics and Astronomy, University of Exeter, UK
| | - Catherine A Kendall
- Biophotonics Research Unit, Gloucestershire Hospitals NHS Foundation Trust, UK
| | - Channa Hewamadduma
- National Institute for Health and Care Research Sheffield Biomedical Research Centre, Sheffield, UK
- Department of Neurology, Academic Directorate of Neurosciences, Sheffield Teaching Hospitals NHS Foundation Trust, Royal Hallamshire Hospital, UK
| | - Marios Hadjivassiliou
- National Institute for Health and Care Research Sheffield Biomedical Research Centre, Sheffield, UK
- Department of Neurology, Academic Directorate of Neurosciences, Sheffield Teaching Hospitals NHS Foundation Trust, Royal Hallamshire Hospital, UK
| | - Gráinne S Gorman
- Wellcome Centre for Mitochondrial Research, Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
- NHS Highly Specialised Service for Rare Mitochondrial Disorders, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
- National Institute for Health and Care Research Newcastle Biomedical Research Centre, Newcastle upon Tyne, UK
| | - Robert W Taylor
- Wellcome Centre for Mitochondrial Research, Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
- NHS Highly Specialised Service for Rare Mitochondrial Disorders, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Christopher J McDermott
- Sheffield Institute for Translational Neuroscience, University of Sheffield, UK.
- Neuroscience Institute, University of Sheffield, Western Bank, Sheffield, UK
- National Institute for Health and Care Research Sheffield Biomedical Research Centre, Sheffield, UK
| | - Pamela J Shaw
- Sheffield Institute for Translational Neuroscience, University of Sheffield, UK.
- Neuroscience Institute, University of Sheffield, Western Bank, Sheffield, UK
- National Institute for Health and Care Research Sheffield Biomedical Research Centre, Sheffield, UK
| | - Richard J Mead
- Sheffield Institute for Translational Neuroscience, University of Sheffield, UK.
- Neuroscience Institute, University of Sheffield, Western Bank, Sheffield, UK
| | - John C Day
- Interface Analysis Centre, School of Physics, University of Bristol, UK
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3
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Zheng X, Li J, Lü G, Li X, Lü X, Wu G, Xu L. Machine learning-assisted serum SERS strategy for rapid and non-invasive screening of early cystic echinococcosis. JOURNAL OF BIOPHOTONICS 2024; 17:e202300376. [PMID: 38163898 DOI: 10.1002/jbio.202300376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 12/11/2023] [Accepted: 12/17/2023] [Indexed: 01/03/2024]
Abstract
Early and accurate diagnosis of cystic echinococcosis (CE) with existing technologies is still challenging. Herein, we proposed a novel strategy based on the combination of label-free serum surface-enhanced Raman scattering (SERS) spectroscopy and machine learning for rapid and non-invasive diagnosis of early-stage CE. Specifically, by establishing early- and middle-stage mouse models, the corresponding CE-infected and normal control serum samples were collected, and silver nanoparticles (AgNPs) were utilized as the substrate to obtain SERS spectra. The early- and middle-stage discriminant models were developed using a support vector machine, with diagnostic accuracies of 91.7% and 95.7%, respectively. Furthermore, by analyzing the serum SERS spectra, some biomarkers that may be related to early CE were found, including purine metabolites and protein-related amide bands, which was consistent with other biochemical studies. Thus, our findings indicate that label-free serum SERS analysis is a potential early-stage CE detection method that is promising for clinical translation.
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Affiliation(s)
- Xiangxiang Zheng
- Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems, School of Electrical Engineering and Automation, Tianjin University of Technology, Tianjin, China
| | - Jintian Li
- School of Public Healthy, Xinjiang Medical University, Urumqi, China
| | - Guodong Lü
- State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Clinical Medical Research Institute, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
| | - Xiaojing Li
- Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems, School of Electrical Engineering and Automation, Tianjin University of Technology, Tianjin, China
| | - Xiaoyi Lü
- School of Software, Xinjiang University, Urumqi, China
| | - Guohua Wu
- School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, China
| | - Liang Xu
- Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems, School of Electrical Engineering and Automation, Tianjin University of Technology, Tianjin, China
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Chen C, Qi J, Li Y, Li D, Wu L, Li R, Chen Q, Sun N. Applications of Raman spectroscopy in the diagnosis and monitoring of neurodegenerative diseases. Front Neurosci 2024; 18:1301107. [PMID: 38370434 PMCID: PMC10869569 DOI: 10.3389/fnins.2024.1301107] [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: 09/25/2023] [Accepted: 01/17/2024] [Indexed: 02/20/2024] Open
Abstract
Raman scattering is an inelastic light scattering that occurs in a manner reflective of the molecular vibrations of molecular structures and chemical conditions in a given sample of interest. Energy changes in the scattered light can be assessed to determine the vibration mode and associated molecular and chemical conditions within the sample, providing a molecular fingerprint suitable for sample identification and characterization. Raman spectroscopy represents a particularly promising approach to the molecular analysis of many diseases owing to clinical advantages including its instantaneous nature and associated high degree of stability, as well as its ability to yield signal outputs corresponding to a single molecule type without any interference from other molecules as a result of its narrow peak width. This technology is thus ideally suited to the simultaneous assessment of multiple analytes. Neurodegenerative diseases represent an increasingly significant threat to global public health owing to progressive population aging, imposing a severe physical and social burden on affected patients who tend to develop cognitive and/or motor deficits beginning between the ages of 50 and 70. Owing to a relatively limited understanding of the etiological basis for these diseases, treatments are lacking for the most common neurodegenerative diseases, which include Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis. The present review was formulated with the goal of briefly explaining the principle of Raman spectroscopy and discussing its potential applications in the diagnosis and evaluation of neurodegenerative diseases, with a particular emphasis on the research prospects of this novel technological platform.
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Affiliation(s)
- Chao Chen
- Central Laboratory, Liaocheng People’s Hospital and Liaocheng School of Clinical Medicine, Shandong First Medical University, Liaocheng, China
| | - Jinfeng Qi
- Department of Geriatrics, Tianjin Medical University General Hospital, Tianjin Geriatrics Institute, Tianjin, China
| | - Ying Li
- Department of Geriatrics, Tianjin Medical University General Hospital, Tianjin Geriatrics Institute, Tianjin, China
| | - Ding Li
- Department of Clinical Laboratory, Liaocheng People’s Hospital and Liaocheng School of Clinical Medicine, Shandong First Medical University, Liaocheng, China
| | - Lihong Wu
- Department of Geriatrics, Tianjin Medical University General Hospital, Tianjin Geriatrics Institute, Tianjin, China
| | - Ruihua Li
- Department of Geriatrics, Tianjin Medical University General Hospital, Tianjin Geriatrics Institute, Tianjin, China
| | - Qingfa Chen
- Institute of Tissue Engineering and Regenerative Medicine, Liaocheng People’s Hospital and Liaocheng School of Clinical Medicine, Shandong First Medical University, Liaocheng, China
- Research Center of Basic Medicine, Jinan Central Hospital, Jinan, China
| | - Ning Sun
- Department of Geriatrics, Tianjin Medical University General Hospital, Tianjin Geriatrics Institute, Tianjin, China
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Elsheikh S, Coles NP, Achadu OJ, Filippou PS, Khundakar AA. Advancing Brain Research through Surface-Enhanced Raman Spectroscopy (SERS): Current Applications and Future Prospects. BIOSENSORS 2024; 14:33. [PMID: 38248410 PMCID: PMC10813143 DOI: 10.3390/bios14010033] [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: 11/21/2023] [Revised: 12/15/2023] [Accepted: 12/20/2023] [Indexed: 01/23/2024]
Abstract
Surface-enhanced Raman spectroscopy (SERS) has recently emerged as a potent analytical technique with significant potential in the field of brain research. This review explores the applications and innovations of SERS in understanding the pathophysiological basis and diagnosis of brain disorders. SERS holds significant advantages over conventional Raman spectroscopy, particularly in terms of sensitivity and stability. The integration of label-free SERS presents promising opportunities for the rapid, reliable, and non-invasive diagnosis of brain-associated diseases, particularly when combined with advanced computational methods such as machine learning. SERS has potential to deepen our understanding of brain diseases, enhancing diagnosis, monitoring, and therapeutic interventions. Such advancements could significantly enhance the accuracy of clinical diagnosis and further our understanding of brain-related processes and diseases. This review assesses the utility of SERS in diagnosing and understanding the pathophysiological basis of brain disorders such as Alzheimer's and Parkinson's diseases, stroke, and brain cancer. Recent technological advances in SERS instrumentation and techniques are discussed, including innovations in nanoparticle design, substrate materials, and imaging technologies. We also explore prospects and emerging trends, offering insights into new technologies, while also addressing various challenges and limitations associated with SERS in brain research.
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Affiliation(s)
- Suzan Elsheikh
- National Horizons Centre, Teesside University, 38 John Dixon Ln, Darlington DL1 1HG, UK (N.P.C.); (O.J.A.); (P.S.F.)
| | - Nathan P. Coles
- National Horizons Centre, Teesside University, 38 John Dixon Ln, Darlington DL1 1HG, UK (N.P.C.); (O.J.A.); (P.S.F.)
| | - Ojodomo J. Achadu
- National Horizons Centre, Teesside University, 38 John Dixon Ln, Darlington DL1 1HG, UK (N.P.C.); (O.J.A.); (P.S.F.)
- School of Health and Life Science, Teesside University, Campus Heart, Southfield Rd, Middlesbrough TS1 3BX, UK
| | - Panagiota S. Filippou
- National Horizons Centre, Teesside University, 38 John Dixon Ln, Darlington DL1 1HG, UK (N.P.C.); (O.J.A.); (P.S.F.)
- School of Health and Life Science, Teesside University, Campus Heart, Southfield Rd, Middlesbrough TS1 3BX, UK
| | - Ahmad A. Khundakar
- National Horizons Centre, Teesside University, 38 John Dixon Ln, Darlington DL1 1HG, UK (N.P.C.); (O.J.A.); (P.S.F.)
- School of Health and Life Science, Teesside University, Campus Heart, Southfield Rd, Middlesbrough TS1 3BX, UK
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
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Tipatet K, Du Boulay I, Muir H, Davison-Gates L, Ellederová Z, Downes A. Raman spectroscopy of brain and skin tissue in a minipig model of Huntington's disease. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2024; 16:253-261. [PMID: 38108410 DOI: 10.1039/d3ay00970j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
We applied Raman spectroscopy to brain and skin tissues from a minipig model of Huntington's disease. Differences were observed between measured spectra of tissues with and without Huntington's disease, for both brain tissue and skin tissue. There are linked to changes in the chemical composition between tissue types. Using machine learning we correctly classified 96% of test spectra as diseased or wild type, indicating that the test would have a similar accuracy when used as a diagnostic tool for the disease. This suggests the technique has great potential in the rapid and accurate diagnosis of Huntington's and other neurodegenerative diseases in a clinical setting.
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Affiliation(s)
- Kevin Tipatet
- a, Institute for Bioengineering, School of Engineering, University of Edinburgh, King's Buildings, Edinburgh EH9 3DW, UK.
| | - Isla Du Boulay
- a, Institute for Bioengineering, School of Engineering, University of Edinburgh, King's Buildings, Edinburgh EH9 3DW, UK.
| | - Hamish Muir
- a, Institute for Bioengineering, School of Engineering, University of Edinburgh, King's Buildings, Edinburgh EH9 3DW, UK.
| | - Liam Davison-Gates
- a, Institute for Bioengineering, School of Engineering, University of Edinburgh, King's Buildings, Edinburgh EH9 3DW, UK.
| | - Zdenka Ellederová
- a, Institute for Bioengineering, School of Engineering, University of Edinburgh, King's Buildings, Edinburgh EH9 3DW, UK.
- Institute of Animal Physiology and Genetics, Czech Academy of Sciences, Rumburská 89, 277 21 Liběchov, UK
| | - Andrew Downes
- a, Institute for Bioengineering, School of Engineering, University of Edinburgh, King's Buildings, Edinburgh EH9 3DW, UK.
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Nikolaev VV, Kistenev YV, Kröger M, Zuhayri H, Darvin ME. Review of optical methods for noninvasive imaging of skin fibroblasts-From in vitro to ex vivo and in vivo visualization. JOURNAL OF BIOPHOTONICS 2024; 17:e202300223. [PMID: 38018868 DOI: 10.1002/jbio.202300223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Revised: 10/21/2023] [Accepted: 10/25/2023] [Indexed: 11/30/2023]
Abstract
Fibroblasts are among the most common cell types in the stroma responsible for creating and maintaining the structural organization of the extracellular matrix in the dermis, skin regeneration, and a range of immune responses. Until now, the processes of fibroblast adaptation and functioning in a varying environment have not been fully understood. Modern laser microscopes are capable of studying fibroblasts in vitro and ex vivo. One-photon- and two-photon-excited fluorescence microscopy, Raman spectroscopy/microspectroscopy are well-suited noninvasive optical methods for fibroblast imaging in vitro and ex vivo. In vivo staining-free fibroblast imaging is not still implemented. The exception is fibroblast imaging in tattooed skin. Although in vivo noninvasive staining-free imaging of fibroblasts in the skin has not yet been implemented, it is expected in the future. This review summarizes the state-of-the-art in fibroblast visualization using optical methods and discusses the advantages, limitations, and prospects for future noninvasive imaging.
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Affiliation(s)
- Viktor V Nikolaev
- Tomsk State University, Laboratory of Molecular Imaging and Machine Learning, Tomsk, Russia
| | - Yury V Kistenev
- Tomsk State University, Laboratory of Molecular Imaging and Machine Learning, Tomsk, Russia
| | - Marius Kröger
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Dermatology, Venerology and Allergology, Center of Experimental and Applied Cutaneous Physiology, Berlin, Germany
| | - Hala Zuhayri
- Tomsk State University, Laboratory of Molecular Imaging and Machine Learning, Tomsk, Russia
| | - Maxim E Darvin
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Dermatology, Venerology and Allergology, Center of Experimental and Applied Cutaneous Physiology, Berlin, Germany
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8
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Yang J, Chen X, Luo C, Li Z, Chen C, Han S, Lv X, Wu L, Chen C. Application of serum SERS technology combined with deep learning algorithm in the rapid diagnosis of immune diseases and chronic kidney disease. Sci Rep 2023; 13:15719. [PMID: 37735599 PMCID: PMC10514316 DOI: 10.1038/s41598-023-42719-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 09/14/2023] [Indexed: 09/23/2023] Open
Abstract
Surface-enhanced Raman spectroscopy (SERS), as a rapid, non-invasive and reliable spectroscopic detection technique, has promising applications in disease screening and diagnosis. In this paper, an annealed silver nanoparticles/porous silicon Bragg reflector (AgNPs/PSB) composite SERS substrate with high sensitivity and strong stability was prepared by immersion plating and heat treatment using porous silicon Bragg reflector (PSB) as the substrate. The substrate combines the five deep learning algorithms of the improved AlexNet, ResNet, SqueezeNet, temporal convolutional network (TCN) and multiscale fusion convolutional neural network (MCNN). We constructed rapid screening models for patients with primary Sjögren's syndrome (pSS) and healthy controls (HC), diabetic nephropathy patients (DN) and healthy controls (HC), respectively. The results showed that the annealed AgNPs/PSB composite SERS substrates performed well in diagnosing. Among them, the MCNN model had the best classification effect in the two groups of experiments, with an accuracy rate of 94.7% and 92.0%, respectively. Previous studies have indicated that the AgNPs/PSB composite SERS substrate, combined with machine learning algorithms, has achieved promising classification results in disease diagnosis. This study shows that SERS technology based on annealed AgNPs/PSB composite substrate combined with deep learning algorithm has a greater developmental prospect and research value in the early identification and screening of immune diseases and chronic kidney disease, providing reference ideas for non-invasive and rapid clinical medical diagnosis of patients.
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Affiliation(s)
- Jie Yang
- College of Information Science and Engineering, Xinjiang University, Urumqi, 830046, China
| | - Xiaomei Chen
- Department of Rheumatology and Immunology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, 830001, China
- Xinjiang Clinical Research Center for Rheumatoid arthritis, Urumqi, 830001, China
- Xinjiang Medical University, Urumqi, 830054, China
| | - Cainan Luo
- Department of Rheumatology and Immunology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, 830001, China
- Xinjiang Clinical Research Center for Rheumatoid arthritis, Urumqi, 830001, China
| | - Zhengfang Li
- Department of Rheumatology and Immunology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, 830001, China
- Xinjiang Clinical Research Center for Rheumatoid arthritis, Urumqi, 830001, China
| | - Chen Chen
- College of Information Science and Engineering, Xinjiang University, Urumqi, 830046, China
| | - Shibin Han
- College of Physics Science and Technology, Xinjiang University, Urumqi, 830046, China
| | - Xiaoyi Lv
- College of Software, Xinjiang University, Urumqi, 830046, China
| | - Lijun Wu
- Department of Rheumatology and Immunology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, 830001, China.
- Xinjiang Clinical Research Center for Rheumatoid arthritis, Urumqi, 830001, China.
| | - Cheng Chen
- College of Software, Xinjiang University, Urumqi, 830046, China.
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Chrabąszcz K, Kołodziej M, Roman M, Pięta E, Piergies N, Rudnicka-Czerwiec J, Bartosik-Psujek H, Paluszkiewicz C, Cholewa M, Kwiatek WM. Carotenoids contribution in rapid diagnosis of multiple sclerosis by Raman spectroscopy. Biochim Biophys Acta Gen Subj 2023:130395. [PMID: 37271406 DOI: 10.1016/j.bbagen.2023.130395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 04/28/2023] [Accepted: 05/29/2023] [Indexed: 06/06/2023]
Abstract
Rapid and accurate diagnosis of any illness determines the success of treatment. The same applies to multiple sclerosis (MS), chronic, inflammatory, and neurodegenerative diseases (ND) of the central nervous system (CNS). Unfortunately, the definitive diagnosis of MS is prolonged and involves mainly clinical symptoms observation and magnetic resonance imaging (MRI) of the CNS. However, as we previously reported, Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) spectroscopy shed new light on the minimally invasive, label-free, and rapid diagnosis of this illness through blood fraction. Herein we introduce Raman spectroscopy coupled with chemometric analysis to provide more detailed information about the biochemical changes behind MS. This pilot study demonstrates that mentioned combination may provide a new diagnostic biomarker and bring closer to rapid MS diagnosis. It has been shown that Raman spectroscopy provides lipid and carotenoid molecules as useful biomarkers which may be applied for both diagnosis and treatment monitoring.
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Affiliation(s)
- Karolina Chrabąszcz
- Institute of Nuclear Physics, Polish Academy of Sciences, Radzikowskiego 152, 31-342 Krakow, Poland.
| | - Magdalena Kołodziej
- Institute of Medical Sciences, Medical College of Rzeszow University, Kopisto 2a, 35-315 Rzeszow, Poland
| | - Maciej Roman
- Institute of Nuclear Physics, Polish Academy of Sciences, Radzikowskiego 152, 31-342 Krakow, Poland; SOLARIS, National Synchrotron Radiation Centre, Jagiellonian University, Czerwone Maki 98, 30-392, Krakow, Poland
| | - Ewa Pięta
- Institute of Nuclear Physics, Polish Academy of Sciences, Radzikowskiego 152, 31-342 Krakow, Poland
| | - Natalia Piergies
- Institute of Nuclear Physics, Polish Academy of Sciences, Radzikowskiego 152, 31-342 Krakow, Poland
| | - Julia Rudnicka-Czerwiec
- Department of Neurology, Institute of Medical Sciences, Medical College of Rzeszow University, Warzywna 1a, 35-310 Rzeszow, Poland
| | - Halina Bartosik-Psujek
- Department of Neurology, Institute of Medical Sciences, Medical College of Rzeszow University, Warzywna 1a, 35-310 Rzeszow, Poland
| | - Czesława Paluszkiewicz
- Institute of Nuclear Physics, Polish Academy of Sciences, Radzikowskiego 152, 31-342 Krakow, Poland
| | - Marian Cholewa
- Institute of Physics, College of Natural Sciences, University of Rzeszow, Pigonia Street 1, 35-959 Rzeszow, Poland
| | - Wojciech M Kwiatek
- Institute of Nuclear Physics, Polish Academy of Sciences, Radzikowskiego 152, 31-342 Krakow, Poland
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10
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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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11
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Colniță A, Toma VA, Brezeștean IA, Tahir MA, Dina NE. A Review on Integrated ZnO-Based SERS Biosensors and Their Potential in Detecting Biomarkers of Neurodegenerative Diseases. BIOSENSORS 2023; 13:bios13050499. [PMID: 37232860 DOI: 10.3390/bios13050499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 04/15/2023] [Accepted: 04/20/2023] [Indexed: 05/27/2023]
Abstract
Surface-enhanced Raman spectroscopy (SERS) applications in clinical diagnosis and spectral pathology are increasing due to the potential of the technique to bio-barcode incipient and differential diseases via real-time monitoring of biomarkers in fluids and in real-time via biomolecular fingerprinting. Additionally, the rapid advancements in micro/nanotechnology have a visible influence in all aspects of science and life. The miniaturization and enhanced properties of materials at the micro/nanoscale transcended the confines of the laboratory and are revolutionizing domains such as electronics, optics, medicine, and environmental science. The societal and technological impact of SERS biosensing by using semiconductor-based nanostructured smart substrates will be huge once minor technical pitfalls are solved. Herein, challenges in clinical routine testing are addressed in order to understand the context of how SERS can perform in real, in vivo sampling and bioassays for early neurodegenerative disease (ND) diagnosis. The main interest in translating SERS into clinical practice is reinforced by the practical advantages: portability of the designed setups, versatility in using nanomaterials of various matter and costs, readiness, and reliability. As we will present in this review, in the frame of technology readiness levels (TRL), the current maturity reached by semiconductor-based SERS biosensors, in particular that of zinc oxide (ZnO)-based hybrid SERS substrates, is situated at the development level TRL 6 (out of 9 levels). Three-dimensional, multilayered SERS substrates that provide additional plasmonic hot spots in the z-axis are of key importance in designing highly performant SERS biosensors for the detection of ND biomarkers.
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Affiliation(s)
- Alia Colniță
- Department of Molecular and Biomolecular Physics, National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donat, 400293 Cluj-Napoca, Romania
| | - Vlad-Alexandru Toma
- Department of Molecular and Biomolecular Physics, National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donat, 400293 Cluj-Napoca, Romania
- Department of Molecular Biology and Biotechnology, Faculty of Biology and Geology, Babeș-Bolyai University, 5-7 Clinicilor, 400006 Cluj-Napoca, Romania
- Institute of Biological Research, Department of Biochemistry and Experimental Biology, 48 Republicii, Branch of NIRDBS Bucharest, 400015 Cluj-Napoca, Romania
| | - Ioana Andreea Brezeștean
- Department of Molecular and Biomolecular Physics, National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donat, 400293 Cluj-Napoca, Romania
| | - Muhammad Ali Tahir
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai 200433, China
| | - Nicoleta Elena Dina
- Department of Molecular and Biomolecular Physics, National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donat, 400293 Cluj-Napoca, Romania
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12
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Alkhuder K. Raman Scattering-Based Optical Sensing Of Chronic Liver Diseases. Photodiagnosis Photodyn Ther 2023; 42:103505. [PMID: 36965755 DOI: 10.1016/j.pdpdt.2023.103505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 02/26/2023] [Accepted: 03/07/2023] [Indexed: 03/27/2023]
Abstract
Chronic liver diseases (CLDs) are a major public health problem. Despite the progress achieved in fighting against viral hepatitis, the emergence of non-alcoholic fatty liver disease might pose a serious challenge to the public's health in the coming decades. Medical management of CLDs represents a substantial burden on the public health infrastructures. The health care cost of these diseases is an additional burden that weighs heavily on the economies of developing countries. Effective management of CLDs requires the adoption of reliable and cost-effective screening and diagnosing methods to ensure early detection and accurate clinical assessment of these diseases. Vibrational spectroscopies have emerged as universal analytical methods with promising applications in various industrial and biomedical fields. These revolutionary analytical techniques rely on analyzing the interaction between a light beam and the test sample to generate a spectral fingerprint. This latter is defined by the analyte's chemical structure and the molecular vibrations of its functional groups. Raman spectroscopy and surface-enhanced Raman spectroscopy have been used in combination with various chemometric tests to diagnose a wide range of malignant, metabolic and infectious diseases. The aim of the current review is to cast light on the use of these optical sensing methods in the diagnosis of CLDs. The vast majority of research works that investigated the potential application of these spectroscopic techniques in screening and detecting CLDs were discussed here. The advantages and limitations of these modern analytical methods, as compared with the routine and gold standard diagnostic approaches, were also reviewed in details.
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13
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Xu Y, Pan X, Li H, Cao Q, Xu F, Zhang J. Accuracy of Raman spectroscopy in the diagnosis of Alzheimer's disease. Front Psychiatry 2023; 14:1112615. [PMID: 37009107 PMCID: PMC10060832 DOI: 10.3389/fpsyt.2023.1112615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 03/01/2023] [Indexed: 03/18/2023] Open
Abstract
ObjectiveTo systematically evaluate the accuracy of Raman spectroscopy in the diagnosis of Alzheimer's disease.MethodsDatabases including Web of Science, PubMed, The Cochrane Library, EMbase, CBM, CNKI, Wan Fang Data, and VIP were electronically searched for studies on Raman spectroscopy in diagnosis of Alzheimer's disease from inception to November 2022. Two reviewers independently screened the literature, extracted data, and assessed the risk of bias in the included studies. Then, meta-analysis was performed using Meta-Disc1.4 and Stata 16.0 software.ResultsA total of eight studies were finally included. The pooled sensitivity of Raman spectroscopy was 0.86 [95% CI (0.80–0.91)], specificity was 0.87 [95% CI (0.79–0.92)], positive likelihood ratio was 5.50 [95% CI (3.55–8.51)], negative likelihood ratio was 0.17 [95% CI (0.09–0.34)], diagnosis odds ratio and area under the curve of SROC were 42.44 [95% CI (19.80–90.97)] and 0.931, respectively. Sensitivity analysis was carried out after each study was excluded one by one, and the results showed that pooled sensitivity and specificity had no significant change, indicating that the stability of the meta-analysis results was great.ConclusionsOur findings indicated that Raman spectroscopy had high accuracy in the diagnosis of AD, though it still did not rule out the possibility of misdiagnosis and missed diagnosis. Limited by the quantity and quality of the included studies, the above conclusions need to be verified by more high-quality studies.
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Affiliation(s)
- Yanmei Xu
- General Practice Ward/International Medical Center Ward, General Practice Medical Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xinyu Pan
- School of Pharmacy, Chengdu Medical College, Chengdu, Sichuan, China
| | - Huan Li
- School of Pharmacy, Chengdu Medical College, Chengdu, Sichuan, China
| | - Qiongfang Cao
- Department of Public Health, Chengdu Medical College, Chengdu, Sichuan, China
| | - Fan Xu
- Department of Public Health, Chengdu Medical College, Chengdu, Sichuan, China
- *Correspondence: Fan Xu
| | - Jianshu Zhang
- General Practice Ward/International Medical Center Ward, General Practice Medical Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Jianshu Zhang
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14
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Alix JJP, Plesia M, Schooling CN, Dudgeon AP, Kendall CA, Kadirkamanathan V, McDermott CJ, Gorman GS, Taylor RW, Mead RJ, Shaw PJ, Day JC. Non-negative matrix factorisation of Raman spectra finds common patterns relating to neuromuscular disease across differing equipment configurations, preclinical models and human tissue. JOURNAL OF RAMAN SPECTROSCOPY : JRS 2023; 54:258-268. [PMID: 38505661 PMCID: PMC10947050 DOI: 10.1002/jrs.6480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 10/04/2022] [Accepted: 11/02/2022] [Indexed: 03/21/2024]
Abstract
Raman spectroscopy shows promise as a biomarker for complex nerve and muscle (neuromuscular) diseases. To maximise its potential, several challenges remain. These include the sensitivity to different instrument configurations, translation across preclinical/human tissues and the development of multivariate analytics that can derive interpretable spectral outputs for disease identification. Nonnegative matrix factorisation (NMF) can extract features from high-dimensional data sets and the nonnegative constraint results in physically realistic outputs. In this study, we have undertaken NMF on Raman spectra of muscle obtained from different clinical and preclinical settings. First, we obtained and combined Raman spectra from human patients with mitochondrial disease and healthy volunteers, using both a commercial microscope and in-house fibre optic probe. NMF was applied across all data, and spectral patterns common to both equipment configurations were identified. Linear discriminant models utilising these patterns were able to accurately classify disease states (accuracy 70.2-84.5%). Next, we applied NMF to spectra obtained from the mdx mouse model of a Duchenne muscular dystrophy and patients with dystrophic muscle conditions. Spectral fingerprints common to mouse/human were obtained and able to accurately identify disease (accuracy 79.5-98.8%). We conclude that NMF can be used to analyse Raman data across different equipment configurations and the preclinical/clinical divide. Thus, the application of NMF decomposition methods could enhance the potential of Raman spectroscopy for the study of fatal neuromuscular diseases.
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Affiliation(s)
- James J. P. Alix
- Sheffield Institute for Translational NeuroscienceUniversity of SheffieldSheffieldUK
- Neuroscience InstituteUniversity of SheffieldSheffieldUK
| | - Maria Plesia
- Sheffield Institute for Translational NeuroscienceUniversity of SheffieldSheffieldUK
| | - Chlöe N. Schooling
- Sheffield Institute for Translational NeuroscienceUniversity of SheffieldSheffieldUK
- Department of Automatic Control and Systems EngineeringUniversity of SheffieldSheffieldUK
| | - Alexander P. Dudgeon
- Biophotonics Research UnitGloucestershire Hospitals NHS Foundation TrustGloucesterUK
- Biomedical Spectroscopy, School of Physics and AstronomyUniversity of ExeterExeterUK
- Interface Analysis Centre, School of PhysicsUniversity of BristolBristolUK
| | - Catherine A. Kendall
- Biophotonics Research UnitGloucestershire Hospitals NHS Foundation TrustGloucesterUK
| | | | - Christopher J. McDermott
- Sheffield Institute for Translational NeuroscienceUniversity of SheffieldSheffieldUK
- Neuroscience InstituteUniversity of SheffieldSheffieldUK
| | - Gráinne S. Gorman
- Wellcome Centre for Mitochondrial Research, Translational and Clinical Research Institute, Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
- NHS Highly Specialised Service for Rare Mitochondrial DisordersNewcastle upon Tyne Hospitals NHS Foundation TrustNewcastle upon TyneUK
| | - Robert W. Taylor
- Wellcome Centre for Mitochondrial Research, Translational and Clinical Research Institute, Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
- NHS Highly Specialised Service for Rare Mitochondrial DisordersNewcastle upon Tyne Hospitals NHS Foundation TrustNewcastle upon TyneUK
| | - Richard J. Mead
- Sheffield Institute for Translational NeuroscienceUniversity of SheffieldSheffieldUK
- Neuroscience InstituteUniversity of SheffieldSheffieldUK
| | - Pamela J. Shaw
- Sheffield Institute for Translational NeuroscienceUniversity of SheffieldSheffieldUK
- Neuroscience InstituteUniversity of SheffieldSheffieldUK
| | - John C. Day
- Interface Analysis Centre, School of PhysicsUniversity of BristolBristolUK
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15
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Cao L, Zheng X, Han P, Ren L, Hu F, Li Z. Raman spectroscopy as a promising diagnostic method for rheumatoid arthritis. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2023; 15:709-718. [PMID: 36598183 DOI: 10.1039/d2ay01904c] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Background: Diagnosis of rheumatoid arthritis (RA) basically relies on clinical symptoms and autoantibodies, especially anti-citrullinated protein antibodies (ACPAs) and rheumatoid factor (RF). However, the lack of autoantibodies is still a dilemma clinically in seronegative RA, especially in the early stage of the disease. This study aimed to provide a unique disease fingerprint with high diagnostic value to discriminate RA based on Raman spectroscopy. Methods: Raman spectroscopy provides a repertoire of biomolecules in serum from RA. Multivariate dimension-reducing methods and machine-learning algorithms were exploited to reveal the intrinsic differences and the potential discrimination power. The underlying differential biomolecules were retrieved by the assignment of Raman peaks. Moreover, the correlations between the spectral differences and RA patient's clinical and immunological manifestations were also analyzed. Results: RA patients exhibited unique Raman spectra characterized by biomolecular alterations during the disease progression. The discrimination power yielded 97.3% sensitivity and 94.8% specificity for RA diagnosis. In the recognition of ACPA-negative RA, the sensitivity and specificity also reached 95.6% and 92.8%, respectively. In particular, the differential Raman spectrum peaks of RA patients mainly represented lipids, amino acids, glycogen, and fatty acids. Further analysis showed that the different serum Raman spectra correlated with the clinical features of RA, including disease duration, RF, anticyclic citrullinated peptide antibodies (anti-CCPs), IgA, IgM, IgG, tender joint count, and swollen joint count (|rs| = 0.15-0.52, p < 0.05). Conclusions: Raman spectroscopy was revealed to be a promising diagnostic method for RA, especially for ACPA-negative patients.
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Affiliation(s)
- Lulu Cao
- Department of Rheumatology and Immunology, Peking University People's Hospital and Beijing Key Laboratory for Rheumatism Mechanism and Immune Diagnosis (BZ0135), Beijing, China.
| | - Xi Zheng
- Department of Rheumatology and Immunology, Peking University People's Hospital and Beijing Key Laboratory for Rheumatism Mechanism and Immune Diagnosis (BZ0135), Beijing, China.
- Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Peng Han
- Department of Rheumatology and Immunology, Peking University People's Hospital and Beijing Key Laboratory for Rheumatism Mechanism and Immune Diagnosis (BZ0135), Beijing, China.
| | - Limin Ren
- Department of Rheumatology and Immunology, Peking University People's Hospital and Beijing Key Laboratory for Rheumatism Mechanism and Immune Diagnosis (BZ0135), Beijing, China.
| | - Fanlei Hu
- Department of Rheumatology and Immunology, Peking University People's Hospital and Beijing Key Laboratory for Rheumatism Mechanism and Immune Diagnosis (BZ0135), Beijing, China.
- State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, Beijing, China
- Department of Integration of Chinese and Western Medicine, School of Basic Medical Sciences, Peking University, Beijing, China
| | - Zhanguo Li
- Department of Rheumatology and Immunology, Peking University People's Hospital and Beijing Key Laboratory for Rheumatism Mechanism and Immune Diagnosis (BZ0135), Beijing, China.
- Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
- State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, Beijing, China
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16
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Ranasinghe JC, Wang Z, Huang S. Raman Spectroscopy on Brain Disorders: Transition from Fundamental Research to Clinical Applications. BIOSENSORS 2022; 13:27. [PMID: 36671862 PMCID: PMC9855372 DOI: 10.3390/bios13010027] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 12/13/2022] [Accepted: 12/23/2022] [Indexed: 06/17/2023]
Abstract
Brain disorders such as brain tumors and neurodegenerative diseases (NDs) are accompanied by chemical alterations in the tissues. Early diagnosis of these diseases will provide key benefits for patients and opportunities for preventive treatments. To detect these sophisticated diseases, various imaging modalities have been developed such as computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). However, they provide inadequate molecule-specific information. In comparison, Raman spectroscopy (RS) is an analytical tool that provides rich information about molecular fingerprints. It is also inexpensive and rapid compared to CT, MRI, and PET. While intrinsic RS suffers from low yield, in recent years, through the adoption of Raman enhancement technologies and advanced data analysis approaches, RS has undergone significant advancements in its ability to probe biological tissues, including the brain. This review discusses recent clinical and biomedical applications of RS and related techniques applicable to brain tumors and NDs.
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17
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Alix JJP, Verber NS, Schooling CN, Kadirkamanathan V, Turner MR, Malaspina A, Day JCC, Shaw PJ. Label-free fibre optic Raman spectroscopy with bounded simplex-structured matrix factorization for the serial study of serum in amyotrophic lateral sclerosis. Analyst 2022; 147:5113-5120. [PMID: 36222101 PMCID: PMC9639415 DOI: 10.1039/d2an00936f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Amyotrophic lateral sclerosis (ALS) is an incurable neurodegenerative disease in urgent need of disease biomarkers for the assessment of promising therapeutic candidates in clinical trials. Raman spectroscopy is an attractive technique for identifying disease related molecular changes due to its simplicity. Here, we describe a fibre optic fluid cell for undertaking spontaneous Raman spectroscopy studies of human biofluids that is suitable for use away from a standard laboratory setting. Using this system, we examined serum obtained from patients with ALS at their first presentation to our centre (n = 66) and 4 months later (n = 27). We analysed Raman spectra using bounded simplex-structured matrix factorization (BSSMF), a generalisation of non-negative matrix factorisation which uses the distribution of the original data to limit the factorisation modes (spectral patterns). Biomarkers associated with ALS disease such as measures of symptom severity, respiratory function and inflammatory/immune pathways (C3/C-reactive protein) correlated with baseline Raman modes. Between visit spectral changes were highly significant (p = 0.0002) and were related to protein structure. Comparison of Raman data with established ALS biomarkers as a trial outcome measure demonstrated a reduction in required sample size with BSSMF Raman. Our portable, simple to use fibre optic system allied to BSSMF shows promise in the quantification of disease-related changes in ALS over short timescales.
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Affiliation(s)
- James J P Alix
- Sheffield Institute for Translational Neuroscience, University of Sheffield, UK.
- Neuroscience Institute, University of Sheffield, UK
| | - Nick S Verber
- Sheffield Institute for Translational Neuroscience, University of Sheffield, UK.
- Neuroscience Institute, University of Sheffield, UK
| | - Chlöe N Schooling
- Sheffield Institute for Translational Neuroscience, University of Sheffield, UK.
- Department of Automatic Control and Systems Engineering, University of Sheffield, UK
| | | | - Martin R Turner
- Nuffield Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | | | - John C C Day
- Interface Analysis Centre, School of Physics, University of Bristol, UK
| | - Pamela J Shaw
- Sheffield Institute for Translational Neuroscience, University of Sheffield, UK.
- Neuroscience Institute, University of Sheffield, UK
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18
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New Insights into the Multivariate Analysis of SER Spectra Collected on Blood Samples for Prostate Cancer Detection: Towards a Better Understanding of the Role Played by Different Biomolecules on Cancer Screening: A Preliminary Study. Cancers (Basel) 2022; 14:cancers14133227. [PMID: 35804993 PMCID: PMC9264810 DOI: 10.3390/cancers14133227] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 06/24/2022] [Accepted: 06/27/2022] [Indexed: 11/24/2022] Open
Abstract
Simple Summary In recent years, research on biofluids using Raman and SERS has expanded dramatically, indicating the enormous promise of this technology as a high-throughput tool for identifying cancer and other disorders. In the investigations thus far, researchers have concentrated on a specific illness or condition, but the techniques employed to acquire experimental spectra prevent direct comparison of the data. This necessitates comparative research of a variety of diseases and an increase in scientific cooperation to standardize experimental conditions. In our study, positive results were reached by applying a combined SERS multivariate analysis (MVA) to the urgent problem of prostate cancer diagnosis that was directly linked to real-world settings in healthcare. Moreover, in comparison to the prostate-specific antigen (PSA) test, which has a high sensitivity but limited specificity, our combined SERS-MVA method has greater specificity, which may assist in preventing the overtreatment of patients. Abstract It is possible to obtain diagnostically relevant data on the changes in biochemical elements brought on by cancer via the use of multivariate analysis of vibrational spectra recorded on biological fluids. Prostate cancer and control groups included in this research generated almost similar SERS spectra, which means that the values of peak intensities present in SERS spectra can only give unspecific and limited information for distinguishing between the two groups. Our diagnostic algorithm for prostate cancer (PCa) differentiation was built using principal component analysis and linear discriminant analysis (PCA-LDA) analysis of spectral data, which has been widely used in spectral data management in many studies and has shown promising results so far. In order to fully utilize the entire SERS spectrum and automatically determine the most meaningful spectral features that can be used to differentiate PCa from healthy patients, we perform a multivariate analysis on both the entire and specific spectral intervals. Using the PCA-LDA model, the prostate cancer and control groups are clearly distinguished in our investigation. The separability of the following two data sets is also evaluated using two alternative discrimination techniques: principal least squares discriminant analysis (PLS-DA) and principal component analysis—support vector machine (PCA-SVM).
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19
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Alix JJP, Plesia M, Hool SA, Coldicott I, Kendall CA, Shaw PJ, Mead RJ, Day JC. Fibre optic Raman spectroscopy for the evaluation of disease state in Duchenne muscular dystrophy: an assessment using the mdx model and human muscle. Muscle Nerve 2022; 66:362-369. [PMID: 35762576 PMCID: PMC9541045 DOI: 10.1002/mus.27671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 06/22/2022] [Accepted: 06/26/2022] [Indexed: 12/04/2022]
Abstract
Introduction/Aims Raman spectroscopy is an emerging technique for the evaluation of muscle disease. In this study we evaluate the ability of in vivo intramuscular Raman spectroscopy to detect the effects of voluntary running in the mdx model of Duchenne muscular dystrophy (DMD). We also compare mdx data with muscle spectra from human DMD patients. Methods Thirty 90‐day‐old mdx mice were randomly allocated to an exercised group (48‐hour access to a running wheel) and an unexercised group (n = 15 per group). In vivo Raman spectra were collected from both gastrocnemius muscles and histopathological assessment subsequently performed. Raman data were analyzed using principal component analysis–fed linear discriminant analysis (PCA‐LDA). Exercised and unexercised mdx muscle spectra were compared with human DMD samples using cosine similarity. Results Exercised mice ran an average of 6.5 km over 48 hours, which induced a significant increase in muscle necrosis (P = .03). PCA‐LDA scores were significantly different between the exercised and unexercised groups (P < .0001) and correlated significantly with distance run (P = .01). Raman spectra from exercised mice more closely resembled human spectra than those from unexercised mice. Discussion Raman spectroscopy provides a readout of the biochemical alterations in muscle in both the mdx mouse and human DMD muscle.
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Affiliation(s)
- James J P Alix
- Sheffield Institute for Translational Neuroscience, University of Sheffield.,Neuroscience Institute, University of Sheffield
| | - Maria Plesia
- Sheffield Institute for Translational Neuroscience, University of Sheffield
| | - Sarah A Hool
- Sheffield Institute for Translational Neuroscience, University of Sheffield
| | - Ian Coldicott
- Sheffield Institute for Translational Neuroscience, University of Sheffield
| | | | - Pamela J Shaw
- Sheffield Institute for Translational Neuroscience, University of Sheffield.,Neuroscience Institute, University of Sheffield
| | - Richard J Mead
- Sheffield Institute for Translational Neuroscience, University of Sheffield.,Neuroscience Institute, University of Sheffield
| | - John C Day
- Interface Analysis Centre, School of Physics, University of Bristol
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20
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Cameron JM, Rinaldi C, Rutherford SH, Sala A, G Theakstone A, Baker MJ. Clinical Spectroscopy: Lost in Translation? APPLIED SPECTROSCOPY 2022; 76:393-415. [PMID: 34041957 DOI: 10.1177/00037028211021846] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
This Focal Point Review paper discusses the developments of biomedical Raman and infrared spectroscopy, and the recent strive towards these technologies being regarded as reliable clinical tools. The promise of vibrational spectroscopy in the field of biomedical science, alongside the development of computational methods for spectral analysis, has driven a plethora of proof-of-concept studies which convey the potential of various spectroscopic approaches. Here we report a brief review of the literature published over the past few decades, with a focus on the current technical, clinical, and economic barriers to translation, namely the limitations of many of the early studies, and the lack of understanding of clinical pathways, health technology assessments, regulatory approval, clinical feasibility, and funding applications. The field of biomedical vibrational spectroscopy must acknowledge and overcome these hurdles in order to achieve clinical efficacy. Current prospects have been overviewed with comment on the advised future direction of spectroscopic technologies, with the aspiration that many of these innovative approaches can ultimately reach the frontier of medical diagnostics and many clinical applications.
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Affiliation(s)
| | - Christopher Rinaldi
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, Glasgow, UK
| | - Samantha H Rutherford
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, Glasgow, UK
| | - Alexandra Sala
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, Glasgow, UK
| | - Ashton G Theakstone
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, Glasgow, UK
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21
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Zheng X, Wu G, Wang J, Yin L, Lv X. Rapid detection of hysteromyoma and cervical cancer based on serum surface-enhanced Raman spectroscopy and a support vector machine. BIOMEDICAL OPTICS EXPRESS 2022; 13:1912-1923. [PMID: 35519280 PMCID: PMC9045898 DOI: 10.1364/boe.448121] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 01/30/2022] [Accepted: 02/05/2022] [Indexed: 06/14/2023]
Abstract
In this study, we investigated the feasibility of using surface-enhanced Raman spectroscopy (SERS) combined with a support vector machine (SVM) algorithm to discriminate hysteromyoma and cervical cancer from healthy volunteers rapidly. SERS spectra of serum samples were recorded from 30 hysteromyoma patients, 36 cervical cancer patients as well as 30 healthy subjects. SVM was used to establish the classification models, and three types of kernel functions, namely linear, polynomial, and Gaussian radial basis function (RBF), were utilized for comparison. When the polynomial kernel function was employed, the overall diagnostic accuracy for classifying the three groups could achieve 86.5%. In addition, when the optimal kernel function was selected, the diagnostic accuracy for identifying healthy versus hysteromyoma, healthy versus cervical cancer, and hysteromyoma versus cervical cancer reached 98.3%, 93.9%, and 90.9%, respectively. The current results indicate that serum SERS technology, together with the SVM algorithm, is expected to become a clinical tool for rapid screening of hysteromyoma and cervical cancer.
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Affiliation(s)
- Xiangxiang Zheng
- School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Guohua Wu
- School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Jing Wang
- State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Department of Gynecology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi 830054, China
| | - Longfei Yin
- School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Xiaoyi Lv
- School of Software, Xinjiang University, Urumqi 830091, China
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22
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Alix JJP, Plesia M, Lloyd GR, Dudgeon AP, Kendall CA, Hewamadduma C, Hadjivassiliou M, McDermott CJ, Gorman GS, Taylor RW, Shaw PJ, Day JCC. Rapid identification of human muscle disease with fibre optic Raman spectroscopy. Analyst 2022; 147:2533-2540. [PMID: 35545877 PMCID: PMC9150427 DOI: 10.1039/d1an01932e] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
We demonstrate the use of fibre optic Raman spectroscopy for the rapid identification of muscle disorders.
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Affiliation(s)
- James J. P. Alix
- Sheffield Institute for Translational Neuroscience, University of Sheffield, UK
- Neuroscience Institute, University of Sheffield, UK
| | - Maria Plesia
- Sheffield Institute for Translational Neuroscience, University of Sheffield, UK
| | | | - Alexander P. Dudgeon
- Biophotonics Research Unit, Gloucestershire Hospitals NHS Foundation Trust, UK
- Biomedical Spectroscopy, School of Physics and Astronomy, University of Exeter, UK
| | | | - Channa Hewamadduma
- Sheffield Institute for Translational Neuroscience, University of Sheffield, UK
- Neuroscience Institute, University of Sheffield, UK
- Department of Neurology, Sheffield Teaching Hospitals NHS Foundation Trust, UK
| | | | - Christopher J. McDermott
- Sheffield Institute for Translational Neuroscience, University of Sheffield, UK
- Neuroscience Institute, University of Sheffield, UK
| | - Gráinne S. Gorman
- Wellcome Centre for Mitochondrial Research, Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
- NHS Highly Specialised Service for Rare Mitochondrial Disorders, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Robert W. Taylor
- Wellcome Centre for Mitochondrial Research, Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
- NHS Highly Specialised Service for Rare Mitochondrial Disorders, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Pamela J. Shaw
- Sheffield Institute for Translational Neuroscience, University of Sheffield, UK
- Neuroscience Institute, University of Sheffield, UK
| | - John C. C. Day
- Interface Analysis Centre, School of Physics, University of Bristol, UK
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23
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Imanbekova M, Suarasan S, Rojalin T, Mizenko RR, Hilt S, Mathur M, Lepine P, Nicouleau M, Mohamed NV, Durcan TM, Carney RP, Voss JC, Wachsmann-Hogiu S. Identification of amyloid beta in small extracellular vesicles via Raman spectroscopy. NANOSCALE ADVANCES 2021; 3:4119-4132. [PMID: 34355118 PMCID: PMC8276787 DOI: 10.1039/d1na00330e] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 06/07/2021] [Indexed: 05/20/2023]
Abstract
One of the hallmarks of Alzheimer's disease (AD) pathogenesis is believed to be the production and deposition of amyloid-beta (Aβ) peptide into extracellular plaques. Existing research indicates that extracellular vesicles (EVs) can carry Aβ associated with AD. However, characterization of the EVs-associated Aβ and its conformational variants has yet to be realized. Raman spectroscopy is a label-free and non-destructive method that is able to assess the biochemical composition of EVs. This study reports for the first time the Raman spectroscopic fingerprint of the Aβ present in the molecular cargo of small extracellular vesicles (sEVs). Raman spectra were measured from sEVs isolated from Alzheimer's disease cell culture model, where secretion of Aβ is regulated by tetracycline promoter, and from midbrain organoids. The averaged spectra of each sEV group showed considerable variation as a reflection of the biochemical content of sEVs. Spectral analysis identified more intense Raman peaks at 1650 cm-1 and 2930 cm-1 attributable to the Aβ peptide incorporated in sEVs produced by the Alzheimer's cell culture model. Subsequent analysis of the spectra by principal component analysis differentiated the sEVs of the Alzheimer's disease cell culture model from the control groups of sEVs. Moreover, the results indicate that Aβ associated with secreted sEVs has a α-helical secondary structure and the size of a monomer or small oligomer. Furthermore, by analyzing the lipid content of sEVs we identified altered fatty acid chain lengths in sEVs that carry Aβ that may affect the fluidity of the EV membrane. Overall, our findings provide evidence supporting the use of Raman spectroscopy for the identification and characterization of sEVs associated with potential biomarkers of neurological disorders such as toxic proteins.
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Affiliation(s)
| | - Sorina Suarasan
- Department of Bioengineering, McGill University Montreal QC H3A 0E9 Canada
| | - Tatu Rojalin
- Department of Biomedical Engineering, University of California Davis CA 95616 USA
| | - Rachel R Mizenko
- Department of Biomedical Engineering, University of California Davis CA 95616 USA
| | - Silvia Hilt
- Department of Biochemistry & Molecular Medicine, University of California Davis CA 95616 USA
| | - Meghna Mathur
- The Early Drug Discovery Unit (EDDU), Montreal Neurological Institute and Hospital, McGill University Montreal QC H3A 2B4 Canada
| | - Paula Lepine
- The Early Drug Discovery Unit (EDDU), Montreal Neurological Institute and Hospital, McGill University Montreal QC H3A 2B4 Canada
| | - Michael Nicouleau
- The Early Drug Discovery Unit (EDDU), Montreal Neurological Institute and Hospital, McGill University Montreal QC H3A 2B4 Canada
| | - Nguyen-Vi Mohamed
- The Early Drug Discovery Unit (EDDU), Montreal Neurological Institute and Hospital, McGill University Montreal QC H3A 2B4 Canada
| | - Thomas M Durcan
- The Early Drug Discovery Unit (EDDU), Montreal Neurological Institute and Hospital, McGill University Montreal QC H3A 2B4 Canada
| | - Randy P Carney
- Department of Biomedical Engineering, University of California Davis CA 95616 USA
| | - John C Voss
- Department of Biochemistry & Molecular Medicine, University of California Davis CA 95616 USA
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24
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de Armas-Rillo S, Fumagallo-Reading F, Luis-Ravelo D, Abdul-Jalbar B, González-Hernández T, Lahoz F. Random Lasing Detection of Mutant Huntingtin Expression in Cells. SENSORS (BASEL, SWITZERLAND) 2021; 21:3825. [PMID: 34073127 PMCID: PMC8198928 DOI: 10.3390/s21113825] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Revised: 05/24/2021] [Accepted: 05/26/2021] [Indexed: 11/24/2022]
Abstract
Huntington's disease (HD) is an autosomal dominant, incurable neurodegenerative disease caused by mutation in the huntingtin gene (HTT). HTT mutation leads to protein misfolding and aggregation, which affect cells' functions and structural features. Because these changes might modify the scattering strength of affected cells, we propose that random lasing (RL) is an appropriate technique for detecting cells that express mutated HTT. To explore this hypothesis, we used a cell model of HD based on the expression of two different forms-pathogenic and non-pathogenic-of HTT. The RL signals from both cell profiles were compared. A multivariate statistical analysis of the RL signals based on the principal component analysis (PCA) and linear discriminant analysis (LDA) techniques revealed substantial differences between cells that expressed the pathogenic and the non-pathogenic forms of HTT.
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Affiliation(s)
- Sergio de Armas-Rillo
- Departamento de Física, Instituto Universitario de Estudios Avanzados en Física Atómica, Molecular y Fotónica (IUdEA), Universidad de La Laguna, 38206 Santa Cruz de Tenerife, Spain;
| | - Felipe Fumagallo-Reading
- Departamento de Ciencias Médicas Básicas, Instituto de Tecnologías Biomédicas (ITB), Universidad de La Laguna, 38320 Santa Cruz de Tenerife, Spain; (F.F.-R.); (D.L.-R.); (T.G.-H.)
| | - Diego Luis-Ravelo
- Departamento de Ciencias Médicas Básicas, Instituto de Tecnologías Biomédicas (ITB), Universidad de La Laguna, 38320 Santa Cruz de Tenerife, Spain; (F.F.-R.); (D.L.-R.); (T.G.-H.)
| | - Beatriz Abdul-Jalbar
- Departamento de Matemáticas, Estadística e Investigación Operativa, Universidad de La Laguna, 38206 Santa Cruz de Tenerife, Spain;
| | - Tomás González-Hernández
- Departamento de Ciencias Médicas Básicas, Instituto de Tecnologías Biomédicas (ITB), Universidad de La Laguna, 38320 Santa Cruz de Tenerife, Spain; (F.F.-R.); (D.L.-R.); (T.G.-H.)
| | - Fernando Lahoz
- Departamento de Física, Instituto Universitario de Estudios Avanzados en Física Atómica, Molecular y Fotónica (IUdEA), Universidad de La Laguna, 38206 Santa Cruz de Tenerife, Spain;
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25
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Devitt G, Crisford A, Rice W, Weismiller HA, Fan Z, Commins C, Hyman BT, Margittai M, Mahajan S, Mudher A. Conformational fingerprinting of tau variants and strains by Raman spectroscopy. RSC Adv 2021; 11:8899-8915. [PMID: 34381596 PMCID: PMC8330415 DOI: 10.1039/d1ra00870f] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Accepted: 02/18/2021] [Indexed: 12/11/2022] Open
Abstract
Tauopathies are a group of disorders in which the deposition of abnormally folded tau protein accompanies neurodegeneration. The development of methods for detection and classification of pathological changes in protein conformation are desirable for understanding the factors that influence the structural polymorphism of aggregates in tauopathies. We have previously demonstrated the utility of Raman spectroscopy for the characterization and discrimination of different protein aggregates, including tau, based on their unique conformational signatures. Building on this, in the present study, we assess the utility of Raman spectroscopy for characterizing and distinguishing different conformers of the same protein which in the case of tau are unique tau strains generated in vitro. We now investigate the impact of aggregation environment, cofactors, post-translational modification and primary sequence on the Raman fingerprint of tau fibrils. Using quantitative conformational fingerprinting and multivariate statistical analysis, we found that the aggregation of tau in different buffer conditions resulted in the formation of distinct fibril strains. Unique spectral markers were identified for tau fibrils generated using heparin or RNA cofactors, as well as for phosphorylated tau. We also determined that the primary sequence of the tau monomer influenced the conformational signature of the resulting tau fibril, including 2N4R, 0N3R, K18 and P301S tau variants. These results highlight the conformational polymorphism of tau fibrils, which is reflected in the wide range of associated neurological disorders. Furthermore, the analyses presented in this study provide a benchmark for the Raman spectroscopic characterization of tau strains, which may shed light on how the aggregation environment, cofactors and post-translational modifications influence tau conformation in vivo in future studies.
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Affiliation(s)
- George Devitt
- School of Biological Sciences, Faculty of Environmental and Life Sciences, University of Southampton Highfield Southampton SO17 1BJ UK .,School of Chemistry, Faculty of Engineering and Physical Sciences, University of Southampton Highfield Southampton SO17 1BJ UK.,Institute for Life Sciences, University of Southampton Highfield Southampton SO17 1BJ UK
| | - Anna Crisford
- School of Biological Sciences, Faculty of Environmental and Life Sciences, University of Southampton Highfield Southampton SO17 1BJ UK .,School of Chemistry, Faculty of Engineering and Physical Sciences, University of Southampton Highfield Southampton SO17 1BJ UK
| | - William Rice
- School of Chemistry, Faculty of Engineering and Physical Sciences, University of Southampton Highfield Southampton SO17 1BJ UK
| | - Hilary A Weismiller
- Department of Chemistry and Biochemistry, University of Denver 2190 E. Iliff Ave. Denver CO 80208 USA
| | - Zhanyun Fan
- Department of Neurology, Harvard Medical School, MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital Charlestown MA 02129 USA
| | - Caitlin Commins
- Department of Neurology, Harvard Medical School, MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital Charlestown MA 02129 USA
| | - Bradley T Hyman
- Department of Neurology, Harvard Medical School, MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital Charlestown MA 02129 USA
| | - Martin Margittai
- Department of Chemistry and Biochemistry, University of Denver 2190 E. Iliff Ave. Denver CO 80208 USA
| | - Sumeet Mahajan
- School of Chemistry, Faculty of Engineering and Physical Sciences, University of Southampton Highfield Southampton SO17 1BJ UK.,Institute for Life Sciences, University of Southampton Highfield Southampton SO17 1BJ UK
| | - Amrit Mudher
- School of Biological Sciences, Faculty of Environmental and Life Sciences, University of Southampton Highfield Southampton SO17 1BJ UK .,Institute for Life Sciences, University of Southampton Highfield Southampton SO17 1BJ UK
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