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Ma Y, Wang F, Zhao Q, Zhang L, Chen S, Wang S. Identifying Diagnostic Markers and Constructing Predictive Models for Oxidative Stress in Multiple Sclerosis. Int J Mol Sci 2024; 25:7551. [PMID: 39062794 PMCID: PMC11276709 DOI: 10.3390/ijms25147551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2024] [Revised: 07/04/2024] [Accepted: 07/04/2024] [Indexed: 07/28/2024] Open
Abstract
Multiple sclerosis (MS) is a chronic disease characterized by inflammation and neurodegeneration of the central nervous system. Despite the significant role of oxidative stress in the pathogenesis of MS, its precise molecular mechanisms remain unclear. This study utilized microarray datasets from the GEO database to analyze differentially expressed oxidative-stress-related genes (DE-OSRGs), identifying 101 DE-OSRGs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicate that these genes are primarily involved in oxidative stress and immune responses. Through protein-protein interaction (PPI) network, LASSO regression, and logistic regression analyses, four genes (MMP9, NFKBIA, NFKB1, and SRC) were identified as being closely related to MS. A diagnostic prediction model based on logistic regression demonstrated good predictive power, as shown by the nomogram curve index and DAC results. An immune-cell infiltration analysis using CIBERSORT revealed significant correlations between these genes and immune cell subpopulations. Abnormal oxidative stress and upregulated expression of key genes were observed in the blood and brain tissues of EAE mice. A molecular docking analysis suggested strong binding potentials between the proteins of these genes and several drug molecules, including isoquercitrin, decitabine, benztropine, and curcumin. In conclusion, this study identifies and validates potential diagnostic biomarkers for MS, establishes an effective prediction model, and provides new insights for the early diagnosis and personalized treatment of MS.
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Affiliation(s)
- Yantuanjin Ma
- Institute of Biomedical Engineering, Kunming Medical Univesity, Kunming 650500, China; (Y.M.); (Q.Z.); (L.Z.)
| | - Fang Wang
- Department of Science and Technology, Kunming Medical University, Kunming 650500, China;
| | - Qiting Zhao
- Institute of Biomedical Engineering, Kunming Medical Univesity, Kunming 650500, China; (Y.M.); (Q.Z.); (L.Z.)
| | - Lili Zhang
- Institute of Biomedical Engineering, Kunming Medical Univesity, Kunming 650500, China; (Y.M.); (Q.Z.); (L.Z.)
| | - Shunmei Chen
- Institute of Biomedical Engineering, Kunming Medical Univesity, Kunming 650500, China; (Y.M.); (Q.Z.); (L.Z.)
| | - Shufen Wang
- Institute of Biomedical Engineering, Kunming Medical Univesity, Kunming 650500, China; (Y.M.); (Q.Z.); (L.Z.)
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Albanese GA, Bucchieri A, Podda J, Tacchino A, Buccelli S, De Momi E, Laffranchi M, Mannella K, Holmes MWR, Zenzeri J, De Michieli L, Brichetto G, Barresi G. Robotic systems for upper-limb rehabilitation in multiple sclerosis: a SWOT analysis and the synergies with virtual and augmented environments. Front Robot AI 2024; 11:1335147. [PMID: 38638271 PMCID: PMC11025362 DOI: 10.3389/frobt.2024.1335147] [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: 11/08/2023] [Accepted: 01/30/2024] [Indexed: 04/20/2024] Open
Abstract
The robotics discipline is exploring precise and versatile solutions for upper-limb rehabilitation in Multiple Sclerosis (MS). People with MS can greatly benefit from robotic systems to help combat the complexities of this disease, which can impair the ability to perform activities of daily living (ADLs). In order to present the potential and the limitations of smart mechatronic devices in the mentioned clinical domain, this review is structured to propose a concise SWOT (Strengths, Weaknesses, Opportunities, and Threats) Analysis of robotic rehabilitation in MS. Through the SWOT Analysis, a method mostly adopted in business management, this paper addresses both internal and external factors that can promote or hinder the adoption of upper-limb rehabilitation robots in MS. Subsequently, it discusses how the synergy with another category of interaction technologies - the systems underlying virtual and augmented environments - may empower Strengths, overcome Weaknesses, expand Opportunities, and handle Threats in rehabilitation robotics for MS. The impactful adaptability of these digital settings (extensively used in rehabilitation for MS, even to approach ADL-like tasks in safe simulated contexts) is the main reason for presenting this approach to face the critical issues of the aforementioned SWOT Analysis. This methodological proposal aims at paving the way for devising further synergistic strategies based on the integration of medical robotic devices with other promising technologies to help upper-limb functional recovery in MS.
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Affiliation(s)
| | - Anna Bucchieri
- Rehab Technologies Lab, Istituto Italiano di Tecnologia, Genoa, Italy
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
| | - Jessica Podda
- Scientific Research Area, Italian Multiple Sclerosis Foundation (FISM), Genoa, Italy
| | - Andrea Tacchino
- Scientific Research Area, Italian Multiple Sclerosis Foundation (FISM), Genoa, Italy
| | - Stefano Buccelli
- Rehab Technologies Lab, Istituto Italiano di Tecnologia, Genoa, Italy
| | - Elena De Momi
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
| | - Matteo Laffranchi
- Rehab Technologies Lab, Istituto Italiano di Tecnologia, Genoa, Italy
| | - Kailynn Mannella
- Department of Kinesiology, Brock University, St. Catharines, ON, Canada
| | | | | | | | - Giampaolo Brichetto
- Scientific Research Area, Italian Multiple Sclerosis Foundation (FISM), Genoa, Italy
- AISM Rehabilitation Center Liguria, Italian Multiple Sclerosis Society (AISM), Genoa, Italy
| | - Giacinto Barresi
- Rehab Technologies Lab, Istituto Italiano di Tecnologia, Genoa, Italy
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Tavazzi E, Bergsland N, Cattaneo D, Gervasoni E, Laganà MM, Dipasquale O, Grosso C, Saibene FL, Baglio F, Rovaris M. Effects of motor rehabilitation on mobility and brain plasticity in multiple sclerosis: a structural and functional MRI study. J Neurol 2018; 265:1393-1401. [DOI: 10.1007/s00415-018-8859-y] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2018] [Revised: 04/03/2018] [Accepted: 04/03/2018] [Indexed: 10/17/2022]
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