ArticleApoptosis : an international journal on programmed cell death2025
LCN2 drives ferroptosis-associated ischemia-reperfusion injury after renal transplantation: integrated machine learning and in vivo validation.
Article in Apoptosis : an international journal on programmed cell death, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- PLIN3 overexpression in lung adenocarcinoma promotes M2 macrophage-myofibroblast transition in the tumor microenvironment.Biology direct · 2026Article
- High-Dose Voclosporin Protects Against Acute Kidney Injury via Regnase-2-Mediated NGAL MRNA Decay.International journal of molecular sciences · 2026Article
- Integrative analysis via bioinformatics and machine learning identifies SERPING1 as a biomarker candidate for major depressive disorder.BMC psychiatry · 2026Article
- Lipocalin 2: a double-edged sword in cellular ferroptosis.Cell biology and toxicology · 2026Review
- Targeting lipocalin-2 in atherosclerosis: biological functions, pathogenic mechanisms, and therapeutic potential.Frontiers in cardiovascular medicine · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Renal ischemia-reperfusion injury (IRI) remains a critical obstacle to optimal renal transplant outcomes, driving acute graft dysfunction and long-term allograft failure. While ferroptosis-an iron-dependent form of cell death-has been linked to IRI pathogenesis, the role of lipocalin-2 (LCN2), a regulator of iron homeostasis and inflammation, in transplant-related renal IRI remains uncharacterized. Six murine IRI transcriptomic datasets (83 samples) were integrated using weighted gene co-expression network analysis (WGCNA) and differential expression profiling to screen for IRI-associated hub genes. Findings were validated in two human transplant cohorts (212 samples) via 113 machine learning algorithms, including logistic regression, random forest, and ensemble models. Single-cell RNA sequencing (GSE237429) was used to map gene expression to specific renal cell populations, while a murine warm IRI model evaluated the effects of LCN2 inhibition (ZINC00640089) on tubular injury, ferroptosis markers (MDA, GSH, Fe²⁺), and inflammatory cytokines (IL-6, TNF-α) across mild (50-minute) and severe (80-minute) ischemia subgroups. WGCNA identified 36 hub genes, with LCN2 emerging as a key node in ferroptosis and immune regulation pathways. A six-gene machine learning model, including LCN2, CLU, and SOX9, demonstrated robust predictive accuracy for IRI (AUC = 0.93). Single-cell analysis revealed elevated LCN2 expression in neutrophils and macrophages in IRI kidneys, correlated with increased immune cell infiltration. In vivo, LCN2 inhibition significantly reduced severe ischemia-induced tubular injury, suppressed lipid peroxidation (MDA), restored glutathione levels (GSH), and alleviated iron overload (Fe
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.