Lactylation-Related Gene Expression for Diabetic Foot Ulcer Diagnosis via Machine Learning

A gene expression dataset for diabetic foot ulcers (DFU) analysis, identified from bulk and single-cell RNA sequencing. The data includes ten differential expressed lactylation-related genes and a diagnostic model built on five genes (ADH1B, ARTN, KY, PFKFB2, PFKFB4). The 1.2 MB dataset was authored by Xiaotian Zhang and last updated on April 30, 2026.

Use Cases

• Building a diagnostic model for diabetic foot ulcers based on the five identified lactylation-related genes (ADH1B, ARTN, KY, PFKFB2, PFKFB4).
• Exploring immune infiltration patterns and pathway enrichment in DFU subtypes defined by consensus clustering.
• Investigating lactylation levels across nine DFU-associated cell types, such as myeloid cells, fibroblasts, and epithelial cells, using single-cell RNA-seq data.
• Validating the role of the hub gene PFKFB2 in endothelial cell migration and tube formation under high-glucose conditions.

Strengths

• Includes analysis of 376 lactylation-related genes to identify DFU-associated markers.
• Diagnostic model built using five specific genes (ADH1B, ARTN, KY, PFKFB2, PFKFB4) with reported high diagnostic accuracy.
• Integrates both bulk RNA-seq and single-cell RNA-seq datasets for cellular landscape exploration.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data may reflect bias inherent to the specific RNA sequencing studies aggregated on figshare.

Provenance

Source

figshare

Collection Method

Analysis of bulk and single-cell RNA sequencing datasets, with validation via a high-glucose-induced HUVEC cell model.

Freshness

Last updated 2026-04-30 10:18:28; freshness should be verified.