ArticleInternational journal of molecular sciences2024
Identifying Diagnostic Markers and Constructing Predictive Models for Oxidative Stress in Multiple Sclerosis.
Article in International journal of molecular sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Oxidative-Stress-Associated Molecular Signatures in Immune-Mediated Diseases: A Systematic Review Integrating Machine Learning and Systems Biology Approaches.Antioxidants (Basel, Switzerland) · 2026Review
- Advancing the frontier of rare disease modeling: a critical appraisal of in silico technologies.NPJ digital medicine · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
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 (
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Registered trials
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