ArticleZhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences2025
[Single-cell transcriptomic analysis reveals immune dysregula-tion and macrophage reprogramming in diabetic foot ulcers].
Article in Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences, 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.
- Jiedu-Shengji Ointment promotes diabetic wound repair by inhibiting the NLRP3/Caspase-1/GSDMD signaling pathway and regulating macrophage function.Frontiers in immunology · 2026Article
- Single-cell RNA sequencing in diabetic foot ulcers: pathogenesis, biomarkers, and translational potential.Frontiers in clinical diabetes and healthcare · 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
6 authors.
Funding
Abstract
objectivesTo elucidate the underlying mechanisms of macrophage-mediated inflammation and tissue injury in diabetic foot ulcer (DFU).
methodsSkin tissue samples were collected from patients with DFU and with non-DFU. A total of 79 272 high-quality cell transcriptomes were obtained using single-cell RNA sequencing. An unbiased clustering approach was employed to identify cell subpopulations. Seurat functions were used to identify differentially expressed genes between DFU and non-DFU groups, and gene ontology (GO) enrichment analysis was used to reveal gene function. Furthermore, cell-cell communication network construction and ligand-receptor interaction analysis were performed to reveal the mechanisms underlying cellular interactions and signaling regulation in the DFU microenvironment from multiple perspectives.
resultsThe results revealed a significant expansion of myeloid cells in DFU tissues, alongside a marked reduction in structural cells such as endothelial cells, epithelial cells, and smooth muscle cells. Major cell types underwent functional reprogramming, characterized by immune activation and impaired tissue remodeling. Specifically, macrophages in DFU skin tissues exhibited a shift toward a pro-inflammatory M1 phenotype, with upregulation of genes associated with inflammation and oxidative stress. Cell communication analysis further demonstrated that M1 macrophages served as both primary signal receivers and influencers in the COMPLEMENT pathway mediated communication network, and as key signal senders and mediators in the secreted phosphoprotein 1 (SPP1) pathway mediated communication network, actively shaping the inflammatory microenvironment. Key ligand-receptor interactions driving macrophage signaling were identified, including C3-(ITGAM+ITGB2) and SPP1-CD44.
conclusionsThis study establishes a comprehensive single-cell atlas of DFU, revealing the role of macrophage-driven cellular networks in chronic inflammation and impaired healing. These findings may offer potential novel therapeutic targets for DFU treatment.
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.