ArticleFrontiers in genetics2022
Revealing Potential Spinal Cord Injury Biomarkers and Immune Cell Infiltration Characteristics in Mice.
Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- Kaempferide Promotes Neuroprotection and Functional Recovery After Spinal Cord Injury and is Associated with Differential Regulation of ARG1, CA4, CYP1B1, and OAT.Neuropsychiatric disease and treatment · 2026Article
- Identification and validation of glucocorticoid receptor and programmed cell death-related genes in spinal cord injury using machine learning.Scientific reports · 2025Article
- Machine Learning and Experiments Revealed Key Genes Related to PANoptosis Linked to Drug Prediction and Immune Landscape in Spinal Cord Injury.Molecular neurobiology · 2025Article
- Identification of Ifitm1 as a Pivotal Gene in Mouse Spinal Cord Injury Using Comprehensive Machine Learning Algorithms.Mediators of inflammation · 2025Article
- Bioinformatics analysis of genes associated with disulfidptosis in spinal cord injury.PloS one · 2025Article
- Hmox1 is Identified as a Ferroptosis Hub Gene and Associated with the M1 Type Microglia/Macrophage Polarization in Spinal Cord Injury: Bioinformatics and Experimental Validation.Molecular neurobiology · 2023Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Spinal cord injury (SCI) is a disabling condition with significant morbidity and mortality. Currently, no effective SCI treatment exists. This study aimed to identify potential biomarkers and characterize the properties of immune cell infiltration during this pathological event. To eliminate batch effects, we concurrently analyzed two mouse SCI datasets (GSE5296, GSE47681) from the GEO database. First, we identified differentially expressed genes (DEGs) using linear models for microarray data (LIMMA) and performed functional enrichment studies on those DEGs. Next, we employed bioinformatics and machine-learning methods to identify and define the characteristic genes of SCI. Finally, we validated them using immunofluorescence and qRT-PCR. Additionally, this study assessed the inflammatory status of SCI by identifying cell types using CIBERSORT. Furthermore, we investigated the link between key markers and infiltrating immune cells. In total, we identified 561 robust DEGs. We identified Rab20 and Klf6 as SCI-specific biomarkers and demonstrated their significance using qRT-PCR in the mouse model. According to the examination of immune cell infiltration, M0, M1, and M2 macrophages, along with naive CD8, dendritic cell-activated, and CD4 Follicular T cells may have a role in the progression of SCI. Therefore, Rab20 and Klf6 could be accessible targets for diagnosing and treating SCI. Moreover, as previously stated, immune cell infiltration may significantly impact the development and progression of SCI.
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