ArticleJournal of inflammation research2025
Machine Learning-Based Identification and Experimental Validation of Hub Ferroptosis-Related Cuproptosis Genes in Lupus Nephritis.
Article in Journal of inflammation research, 2025. 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
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
- [Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The role of ferroptosis and cuproptosis in lupus nephritis (LN) is unclear. The aim of this study was to explore the expression and effects of ferroptosis-related cuproptosis genes (FRCGs) in LN using bioinformatics and experimental validation. Methods: The LN-related datasets GSE112943 and GSE32591 were downloaded from the GEO database. We collected 834 ferroptosis-related genes and 1046 cuproptosis-related genes. Weighted gene co-expression network analysis (WGCNA) and machine learning algorithms identified hub FRCGs in the LN. We then analyzed the relationship of hub FRCGs with immune infiltration and clinical traits. Finally, we validated the expression of the hub FRCGs in vivo and in vitro. Results: A total of 31 differentially expressed FRCGs (DE-FRCGs) in the LN were screened, which were mainly involved in the response to metal ions and oxidative stress. And they were engaged in autophagy-animal signaling pathway. Machine learning identified two hub FRCGs ( Conclusion: This study elucidates the contribution of ferroptosis-related cuproptosis genes to the onset and progression of LN.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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 OpenQuestion graph.