Evidence map›Paper›PMID 40319145›Full record

ArticleSpinal cord2025

Identification of disulfidptosis-related genes and subgroups in spinal cord injury.

Ye Tao, Shanhe Wang, Xiongfei Li, Letian Jin, Chen Liu, Kun Jiao, Xiaoyu Li, Yajun Cheng, Kehan Xu, Xiaoyi Zhou and 1 more

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Article in Spinal cord, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
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2citing papers in PubMed
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1 · What the graph read from it

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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.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Ye Tao *Naval Medical University, Shanghai, China.
Shanhe Wang *Naval Medical University, Shanghai, China.
Xiongfei Li *Department of Orthopaedic Surgery, Changhai Hospital, Shanghai, China.
Letian JinHangzhou Medical College, Hangzhou, China.
Chen LiuDepartment of Orthopaedic Surgery, Changhai Hospital, Shanghai, China.
Kun JiaoDepartment of Orthopaedic Surgery, Changhai Hospital, Shanghai, China.
Xiaoyu LiDepartment of Orthopaedic Surgery, Changhai Hospital, Shanghai, China.
Yajun ChengDepartment of Orthopaedic Surgery, Changhai Hospital, Shanghai, China.
Kehan XuDepartment of Orthopaedic Surgery, Changhai Hospital, Shanghai, China. kehanxu94@163.com.
Xiaoyi ZhouDepartment of Orthopaedic Surgery, Changhai Hospital, Shanghai, China. 13818909826@163.com.ORCID 0000-0003-0264-6342
Xianzhao WeiDepartment of Orthopaedic Surgery, Changhai Hospital, Shanghai, China. weixianzhao@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

STUDY

designBioinformatics analysis and experimental validation study.

objectivesTo investigate the role and expression patterns of disulfidptosis-related genes in spinal cord injury (SCI), identify potential pivotal genes, and explore possible therapeutic targets.

settingShanghai, China.

methodsData acquisition and pre-processing: Screened 27 disulfidptosis-related genes based on literature and downloaded RNA-sequencing data of ASCI patients from GEO database (GSE151371); Identification of differentially expressed genes (DEGs): Used R package "limma" for differential gene expression analysis between ASCI samples and normal controls; Evaluating immune cell infiltration: Employed ssGSEA algorithm and CIBERSORT to determine immune cell abundance; Identification and functional verification of key genes: Intersected disulfidptosis-related genes with DEGs, and used machine learning techniques (Random Forest, Lasso, Support Vector Machine) to identify hub genes. Validated hub genes expression by real-time PCR; Construction of a diagnostic model: Developed a backpropagation neural network clinical prediction model based on hub genes and clinical features, and evaluated its performance using ROC curve. 6. Subcluster analysis: Performed consensus cluster analysis of ASCI samples and hub genes, and used GSVA to elucidate functional differences between subgroups.

resultsIdentified 7764 DEGs in ASCI, with GO and KEGG enrichment in inflammation and autophagy-related pathways; Found differences in immune cell infiltration between ASCI and control groups, and correlation between immune cells and DRGs; Determined seven hub genes (MYL6, NUBPL, CYFIP1, IQGAP1, FLNB, SLC7A11, CD2AP) through machine learning; Validated the expression of hub genes by qRT-PCR; Constructed a clinical diagnostic model with good predictive accuracy (overall dataset accuracy of 83.3%); Identified two subtypes of ASCI based on hub genes, with different immune infiltration and pathway activity.

conclusionDisulfidptosis is closely related to spinal cord injury. The identified hub genes and subtypes provide new insights for biomarker and therapeutic target research. The diagnostic model has potential for clinical application, but further studies are needed due to limitations such as small sample size. SPONSORSHIP: This study was supported in part by the project of Youth Scientific and Technological Talents of PLA (2020QN06125), Changhong Talent Project in First affiliated hospital of Navy Medical University (Wei Xianzhao) and Basic Medical Research Project in First affiliated hospital of Navy Medical University (2023PY17). I want to reiterate that there is no prior publication of figures or tables and no conflict of interest in the submission of this manuscript. The graphical abstract is divided into two parts. The upper section sequentially illustrates the occurrence of disulfidptosis and changes in the immune microenvironment in the human body after SCI. The lower section displays the construction of a diagnostic model for SCI through the detection of changes in disulfidptosis-related genes, combined with patient clinical information.

Indexed as

Spinal Cord InjuriesComputational BiologyDatabases, GeneticDisulfidptosisGene Expression ProfilingHumans

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.