ArticleJournal of inflammation research2024
Bioinformatics Identification and Validation of Ferroptosis-Related Key Genes and Therapeutic Compounds in Septic Lung Injury.
Article in Journal of inflammation research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Decoding the HIF-1-driven metabolic-inflammatory-immune axis in sepsis-associated lung injury: a comprehensive overview.Frontiers in immunology · 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
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Septic lung injury (SLI) is a severe condition with high mortality, and ferroptosis, a form of programmed cell death, is implicated in its pathogenesis. However, the explicit mechanisms underlying this condition remain unclear. This study aimed to elucidate and validate key ferroptosis-related genes involved in the pathogenesis of SLI through bioinformatics analysis and experimental validation. Methods: Microarray data related to SLI from the GSE130936 dataset were downloaded from the Gene Expression Omnibus (GEO) database. These data were then intersected with the FerrDb database to obtain ferroptosis-related differentially expressed genes (DEGs). Protein-protein interaction (PPI) networks and functional enrichment analysis were employed to identify key ferroptosis-related DEGs. The Connectivity Map (c-MAP) tool was used to search for potential compounds or drugs that may inhibit ferroptosis-related DEGs. The transcriptional levels of the key genes and potential therapeutic compounds were verified in an LPS-induced mouse model of lung injury. The expression of these key genes was further verified using the GSE60088 and GSE137342 datasets. Results: 38 ferroptosis-related DEGs were identified between the septic and control mice. PPI network analysis revealed four modules, the most significant of which included eight ferroptosis-related DEGs. Functional enrichment analysis showed that these genes were enriched in the HIF-1 signaling pathway, including IL-6 (Interleukin-6), TIMP1 (Tissue Inhibitor of Metalloproteinase 1), HIF-1α (Hypoxia-Inducible Factor-1α), and HMOX1 (Heme Oxygenase-1). Phloretin, a natural compound, was identified as a potential inhibitor of these genes. Treatment with phloretin significantly reduced the expression of these genes ( Conclusion: This study elucidates the significant role of ferroptosis in SLI and identifies phloretin as a potential therapeutic agent. However, further research, particularly involving human clinical trials, is necessary to validate these findings for clinical use.
Indexed as
Identifiers
What Socratic 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 Socratic graph.