File:Schematic illustration of the blood-based Raman spectroscopic diagnostic test for ME-CFS and MS.jpg

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From the study "Developing a Blood Cell-Based Diagnostic Test for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Using Peripheral Blood Mononuclear Cells"

Summary[edit]

Description
English: "Schematic illustration of the blood-based Raman spectroscopic diagnostic test for ME/CFS and MS at a single-cell level. A) PBMCs were isolated from blood samples. B) Raman spectra of single PBMCs from 98 individuals were measured. C) Around 5–7 spectra were measured in each cell which was then averaged to one spectrum for one cell; ≈30 spectra were obtained for each cell. D) SCRS at the single-cell level from 98 individuals was then split into a train set (80%) and a test set (20%) with balanced subgroup distribution. The train set was used to train an ensemble learner and the independent test set was input into the trained learner for diagnosing the cell as HC, ME, or MS." "Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is characterized by debilitating fatigue that profoundly impacts patients' lives. Diagnosis of ME/CFS remains challenging, with most patients relying on self-report, questionnaires, and subjective measures to receive a diagnosis, and many never receiving a clear diagnosis at all. In this study, a single-cell Raman platform and artificial intelligence are utilized to analyze blood cells from 98 human subjects, including 61 ME/CFS patients of varying disease severity and 37 healthy and disease controls. These results demonstrate that Raman profiles of blood cells can distinguish between healthy individuals, disease controls, and ME/CFS patients with high accuracy (91%), and can further differentiate between mild, moderate, and severe ME/CFS patients (84%). Additionally, specific Raman peaks that correlate with ME/CFS phenotypes and have the potential to provide insights into biological changes and support the development of new therapeutics are identified. This study presents a promising approach for aiding in the diagnosis and management of ME/CFS and can be extended to other unexplained chronic diseases such as long COVID and post-treatment Lyme disease syndrome, which share many of the same symptoms as ME/CFS."
Date
Source https://onlinelibrary.wiley.com/doi/10.1002/advs.202302146
Author Authors of the study: Jiabao Xu, Tiffany Lodge, Caroline Kingdon, James W. L. Strong, John Maclennan, Eliana Lacerda, Slawomir Kujawski, Pawel Zalewski, Wei E. Huang, Karl J. Morten

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current11:12, 15 October 2023Thumbnail for version as of 11:12, 15 October 20231,367 × 717 (152 KB)Prototyperspective (talk | contribs)Uploaded a work by Authors of the study: Jiabao Xu, Tiffany Lodge, Caroline Kingdon, James W. L. Strong, John Maclennan, Eliana Lacerda, Slawomir Kujawski, Pawel Zalewski, Wei E. Huang, Karl J. Morten from https://onlinelibrary.wiley.com/doi/10.1002/advs.202302146 with UploadWizard

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