[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-123483-en":3,"doc-seo-123483-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},123483,687197207919,"Theodora","https://ap-avatar.wpscdn.com/avatar/a000253d6f5f7c60be?x-image-process=image/resize,m_fixed,w_180,h_180&k=1779446848396160552",8,"Research & Report","A modified α-synuclein seed amplification assay in Lewy body dementia using Raman spectroscopy and machine learning analysis - Article","Lewy body dementias (DLB and Parkinson’s disease dementia) are driven by misfolded α-synuclein aggregation, and seed amplification assays can detect α-synuclein aggregates but often rely on binary readouts and fluorescence labeling. This proof-of-concept study evaluates whether Raman spectroscopy combined with machine learning can improve cerebrospinal fluid discrimination between Lewy body dementia and controls. Using a 7-day assay with PCA and UMAP analysis, spectra distinguished combined LBD from controls within 24 h, with shifts consistent with α-synuclein fibrillation.","Journal of Neuroscience Methods 425 (2026) 110617  \nContents lists available at ScienceDirect  \nJournal of Neuroscience Methods  \njournal [homepage: www.elsevier.com/locate/jneumeth](homepage: www.elsevier.com/locate/jneumeth)  \n| Short communication\u003Cbr>A modified α-synuclein seed amplification assay in Lewy body dementia using Raman spectroscopy and machine learning analysis\u003Cbr>Nathan P. Colesa,b, Suzan Elsheikh a,b, Alaa Gouda a,b, Agathe Quesnel c, Lucy Butler a,b, Ojodomo J. Achadua,b, Meez Islam a,b, Karunakaran Kalesha,b, Annalisa Occhipintib,d,e, Claudio Angioneb,d,e, Jon Marles-Wright f, David J. Kossg, Alan J. Thomas h,\u003Cbr>Tiago F. Outeiro i,j,k,l, Panagiota S. Filippou a,b,m, Ahmad A. Khundakara,b,i,* \u003Cbr>a School of Health & Life Sciences, Teesside University, Middlesbrough TS1 3BX, United Kingdom b National Horizons Centre, Teesside University, Darlington DL1 1HG, United Kingdom c Research Center In Cancer De Toulouse, 2 Av. Hubert Curien, Toulouse 31100, France\u003Cbr>d School of Computing, Engineering & Digital Technologies, Teesside University, Middlesbrough TS1 3BX, United Kingdome Centre for Digital Innovation, Teesside University, Middlesbrough TS1 3BX, United Kingdom\u003Cbr>f Biosciences Institute, Cookson Building, Framlington Place, Newcastle University, Newcastle upon Tyne NE2 4HH, United Kingdom g Division of Neuroscience, School of Medicine, University of Dundee, Nethergate, Dundee, Scotland DD1 4HN, United Kingdom h Newcastle Biomedical Research Centre, Newcastle University, Newcastle upon Tyne NE2 4HH, United Kingdom\u003Cbr>i Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne United Kingdom\u003Cbr>j University Medical Center G¨ottingen, Department of Experimental Neurodegeneration, Center for Biostructural Imaging of Neurodegeneration, G¨ottingen, Germany k Max Planck Institute for Multidisciplinary Sciences, G¨ottingen, Germany\u003Cbr>l Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), G¨ottingen, Germany\u003Cbr>m Laboratory of Biological Chemistry, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki 54124, Greece |  |  |  |\n| --- | --- | --- | --- |\n| A R T I C L E I N F O |  | A B S T R A C T |  |\n| Keywords:\u003Cbr>Lewy body dementia Raman spectroscopy α-synuclein aggregation Machine learning analysis Diagnostics |  | Background: Lewy body dementias (LBD), comprising dementia with Lewy bodies (DLB) and Parkinson’s disease dementia (PDD), are defined by misfolded α-synuclein aggregation. Seed amplification assays (SAAs), such as RTQuIC, enable sensitive detection of α-synuclein aggregates but typically provide binary readouts and require fluorescence labeling. Raman spectroscopy offers a label-free approach to detect subtle biochemical changes, and its diagnostic potential can be enhanced with machine learning.\u003Cbr>Objectives: This proof-of-concept study aimed to evaluate whether Raman spectroscopy combined with machine learning can improve SAA-based discrimination of LBD from controls in cerebrospinal fluid (CSF).\u003Cbr>Methods: We analyzed a small number of post-mortem CSF samples from pathologically confirmed DLB (n = 2), PDD (n = 2), and controls (n = 2) using a 7-day SAA. Raman spectra were collected on Days 1, 4, and 7 and analyzed using principal component analysis (PCA) and uniform manifold approximation and projection (UMAP).\u003Cbr>Results: Following SAA, both PCA and UMAP distinguished combined LBD samples from controls within 24 h (Day 1), reflecting biochemical changes consistent with α-synuclein fibrillation. Spectral shifts indicated decreased α-helical content with increased β-sheet structures. No consistent separation between DLB and PDD was observed.\u003Cbr>Conclusion: This preliminary study demonstrates that combining Raman spectroscopy with machine learning can enable rapid, label-free detection of disease-specific changes. Despite the very limited sample size, these findings highlight the poten","cbCaicsQsTQF6M0n","https://ap.wps.com/l/cbCaicsQsTQF6M0n","pdf",1593764,1,5,"English","en",105,"# Abstract\n## Background\n## Objectives\n## Methods\n## Results\n## Conclusion\n# Introduction\n## α-synuclein and Lewy body dementias\n## Seed amplification assays and limitations\n## Raman spectroscopy and machine learning potential","[{\"question\":\"What diagnostic problem does the study address?\",\"answer\":\"The study targets improving discrimination of Lewy body dementias from controls, focusing on detecting α-synuclein aggregates in cerebrospinal fluid.\"},{\"question\":\"How does the workflow combine Raman spectroscopy and machine learning?\",\"answer\":\"Raman spectra are collected after a 7-day seed amplification assay and analyzed with PCA and UMAP to classify samples based on spectral patterns.\"},{\"question\":\"What were the key findings and limitations?\",\"answer\":\"PCA and UMAP separated combined LBD from controls within 24 hours, indicating biochemical shifts consistent with α-synuclein fibrillation; however, no consistent separation between DLB and PDD was observed, and the sample size was very small.\"}]","A modified α-synuclein seed amplification assay in Lewy body dementia using Raman spectroscopy and machine learning analysis - Article | PDF",1785816772,13,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"a-modified-alpha-synuclein-seed-amplification-assay-in-lewy-body-dementia-using-raman-spectroscopy-and-machine-learning-analysis-article","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/a-modified-alpha-synuclein-seed-amplification-assay-in-lewy-body-dementia-using-raman-spectroscopy-and-machine-learning-analysis-article/123483/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What diagnostic problem does the study address?","Question",{"text":75,"@type":76},"The study targets improving discrimination of Lewy body dementias from controls, focusing on detecting α-synuclein aggregates in cerebrospinal fluid.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the workflow combine Raman spectroscopy and machine learning?",{"text":80,"@type":76},"Raman spectra are collected after a 7-day seed amplification assay and analyzed with PCA and UMAP to classify samples based on spectral patterns.",{"name":82,"@type":73,"acceptedAnswer":83},"What were the key findings and limitations?",{"text":84,"@type":76},"PCA and UMAP separated combined LBD from controls within 24 hours, indicating biochemical shifts consistent with α-synuclein fibrillation; 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