Evidence mapPaperPMID 40775466Full record

ArticleJournal of molecular neuroscience : MN2025

Finerenone Modulates PANoptosis to Improve Immune Microenvironment in Diabetic Nephropathy: A Machine Learning-Based Mechanistic Analysis.

Aihua Chen, Fenghua Wang

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In one paragraph

Article in Journal of molecular neuroscience : MN, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. PANoptosis in diabetes: immunometabolic insights and treatments.Apoptosis : an international journal on programmed cell death · 2026
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Aihua ChenDepartment of Pharmacy, Affiliated Rehabilitation Hospital of Nanchang University, Nanchang, 330003, People's Republic of China.
Fenghua WangDepartment of Pharmacy, Affiliated Rehabilitation Hospital of Nanchang University, Nanchang, 330003, People's Republic of China. wfh1019@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetic nephropathy (DN) is characterized by nephron degeneration induced by hyperglycemia, driven by complex interactions between glucose metabolism dysregulation and immune microenvironment dynamics. This study employed machine learning and bioinformatics techniques to investigate the role of finerenone, a novel nonsteroidal mineralocorticoid receptor antagonist, in modulating immune dysregulation associated with DN through targeted intervention in PANoptosis-related networks. Using machine learning algorithms, five key PANoptosis-associated genes (CASP3, FLT3, KDR, HIF1A, and MMP2) were identified, and a diagnostic model incorporating these biomarkers demonstrated high efficacy in distinguishing patients with DN from controls. These genes were strongly correlated with immune cell infiltration, particularly mast cells, M2 macrophages, and B lymphocytes. KEGG and GSVA enrichment analyses highlighted significant pathway enrichment in PI3K-Akt signaling and glycosphingolipid biosynthesis (lacto and neolacto series). These results suggest that finerenone mitigates DN-related immune disruptions by modulating PANoptosis-linked gene expression, thereby influencing PI3K-Akt signaling and glycosphingolipid biosynthesis in mast cells, M2 macrophages, and B cells. This study provides new insights into potential therapeutic targets and pharmacological evidence for precision immunomodulation in DN treatment.

Indexed as

Diabetic NephropathiesMachine LearningMineralocorticoid Receptor AntagonistsNaphthyridinesB-LymphocytesHumansMacrophagesMast CellsPhosphatidylinositol 3-KinasesProto-Oncogene Proteins c-aktfinerenoneMineralocorticoid Receptor AntagonistsNaphthyridinesPhosphatidylinositol 3-KinasesProto-Oncogene Proteins c-aktDiabetic nephropathyFinerenoneImmune cell infiltrationMachine learningPANoptosis

What Socratic holds

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Registered trials

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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.