ArticleMedicine2026
Identification of VEGFB associated with NKT cells in diabetic foot ulcers: Single-cell analysis and machine learning.
Article in Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The management options for diabetic foot are restricted, and the outlook is unfavorable. Immune cells have been implicated in diabetic foot ulcer (DFU), but the exact role of natural killer T (NKT) cells in DFU remains unclear. Vascular endothelial growth factor B (VEGFB), a member of the VEGF family, is distinguished by its potential roles in metabolic regulation and immune modulation, yet its connection to NKT cells in DFU is unexplored. This study was to identify specific genes associated with NKT cells in DFU and to ascertain potential targets. We analyzed single-cell ribonucleic acid sequencing and bulk transcriptome data from DFU datasets. Differential expression analysis identified genes associated with NKT cells in DFU. Machine learning algorithms were applied to pinpoint the most significant genes from these candidates. The functional characteristics of the identified key gene were further investigated through gene set enrichment analysis and immune infiltration analysis. Single-cell analysis revealed 390 NKT cell-related genes, and differential analysis identified 728 differentially expressed genes. Cross-referencing yielded 37 NKT cell-related differentially expressed genes. Machine learning consistently identified VEGFB as a key biomarker. Functional analysis linked VEGFB to cell adhesion, vasculature development, and angiogenesis pathways. VEGFB was significantly overexpressed in DFU samples compared to controls. Our study identifies VEGFB as a valuable biomarker associated with NKT cells in DFU. The overexpression of VEGFB suggests its involvement in DFU pathogenesis, potentially bridging immune regulation and vascular pathways. This finding enhances the understanding of NKT cell mechanisms in DFU and positions VEGFB as a potential target for future diagnostic and therapeutic strategies aimed at immunomodulation.
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.