ArticleScientific reports2025
Machine learning selection of basement membrane-associated genes and development of a predictive model for kidney fibrosis.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Integration of artificial intelligence and multi-omics for precision medicine.Functional & integrative genomics · 2026Review
- Deciphering the potential molecular network underlying nicotine- and its metabolite cotinine-induced myocardial infarction via network toxicology, molecular dynamics, and in vitro experimental validation.Functional & integrative genomics · 2026Article
- Multi-omics characterization of benzo[a]pyrene toxicity networks identifies SERPINE1 and STK3 as prognostic biomarkers and therapeutic targets in head and neck squamous cell carcinoma.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Artificial Intelligence in Nephrology-State of the Art on Theoretical Background, Molecular Applications, and Clinical Interpretation.International journal of molecular sciences · 2026Review
- Mitochondrial-related biomarkers as the diagnostic markers in sepsis induced acute respiratory distress syndrome.European journal of medical research · 2026Article
- Baricitinib alleviates interstitial lung disease in CIA mice by inhibiting macrophage polarization and increase exosomal miR-126a-3p with anti-fibrotic activityFrontiers in pharmacology · 2026Article
- Supervised Machine-Based Learning and Computational Analysis to Reveal Unique Molecular Signatures Associated with Wound Healing and Fibrotic Outcomes to Lens Injury.International journal of molecular sciences · 2025Article
- Identification of progression-related genes and construction of prognostic model for chronic kidney disease by machine learning.Frontiers in cell and developmental biology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study investigates the role of basement membrane-related genes in kidney fibrosis, a significant factor in the progression of chronic kidney disease that can lead to end-stage renal failure. The authors aim to develop a predictive model using machine learning techniques due to the limitations of existing diagnostic methods, which often lack sensitivity and specificity. Utilizing gene expression data from the GEO database, the researchers applied LASSO, Random Forest, and SVM-RFE methods to identify five pivotal genes: ARID4B, EOMES, KCNJ3, LIF, and STAT1. These genes were analyzed across training and validation datasets, resulting in the development of a Nomogram prediction model. Performance metrics, including the area under the ROC curve (AUC), calibration curves, and decision curve analysis, indicated excellent predictive capabilities with an AUC of 0.923. Experimental validation through qRT-PCR in clinical samples and TGF-β-treated HK-2 cells corroborated the expression patterns identified in silico, showing upregulation of ARID4B, EOMES, LIF, and STAT1, and downregulation of KCNJ3. The findings emphasize the importance of basement membrane-related genes in kidney fibrosis and pave the way for enhanced early diagnosis and targeted therapeutic strategies.
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.