TLQP-21 facilitates diabetic wound healing by inducing angiogenesis through alleviating high glucose-induced injuries on endothelial progenitor cells

Diabetes mellitus (DM) is a metabolic disease with multiple complications, including diabetic cutaneous wounds, which lacks effective treating strategies and severely influences the patients' life. Endothelial progenitor cells (EPCs) are reported to participate in maintaining the normal function of blood vessels, which plays a critical role in diabetic wound healing. TLQP-21 is a VGF-derived peptide with promising therapeutic functions on DM. Herein, the protective effects of TLQP-21 on diabetic cutaneous wound and the underlying mechanism will be investigated. Cutaneous wound model was established in T2DM mice, followed by administering 120 nmol/kg and 240 nmol/kg TLQP-21 once a day for 12 days. Decreased wound closure, reduced number of capillaries and EPCs, declined tube formation function of EPCs, and inactivated PI3K/AKT/eNOS signaling in EPCs were observed in T2DM mice, which were sharply alleviated by TLQP-21. Normal EPCs were extracted from mice and stimulated by high glucose (HG), followed by incubated with TLQP-21 in the presence or absence of LY294002, an inhibitor of PI3K. The declined cell viability, increased apoptotic rate, reduced number of migrated cells, declined migration distance, repressed tube formation function, and inactivated PI3K/AKT/eNOS signaling observed in HG-treated EPCs were markedly reversed by TLQP-21, which were dramatically abolished by the co-culture of LY294002. Collectively, TLQP-21 facilitated diabetic wound healing by inducing angiogenesis through alleviating HG-induced injuries on EPCs.

Integration of RNA-Seq and Machine Learning Identifies Hub Genes for Empagliflozin Benefitable Heart Failure with Reduced Ejection Fraction

Purpose

This study aimed to analyze the hub genes of heart failure with reduced ejection fraction (HFrEF) treated with Empagliflozin using RNA sequencing (RNA-seq) and bioinformatics methods, including machine learning.

Methods

From February 2021 to February 2023, nine patients with HFrEF were enrolled from our hospital's cardiovascular department. In addition to routine drug treatment, these patients received 10 mg of Empagliflozin once daily for two months. Efficacy was assessed and RNA-seq was performed on peripheral blood before and after treatment with empagliflozin. HFrEF-related hub genes were identified through bioinformatics analyses including differential gene expression analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, immune infiltration analysis, machine learning, immune cell correlation analysis and clinical indicator correlation analysis.

Results

The nine patients included in this study completed a two-month treatment regimen, with an average age of 62.11 ± 6.36 years. By performing bioinformatics analysis on the transcriptome from the treatment groups, 42 differentially expressed genes were identified, with six being up-regulated and 36 being down-regulated (|log2FC|>1 and adj.pvalue<0.05). Immune infiltration analysis of these genes demonstrated a significant difference in the proportion of plasma between the pre-treatment and post-treatment groups (p<0.05). Two hub genes, GTF2IP14 and MTLN, were finally identified through machine learning. Further analysis of the correlation between the hub genes and immune cells suggested a negative correlation between GTF2IP14 and naive B cells, and a positive correlation between MTLN and regulatory T cells and resting memory CD4+ T cells (p<0.05).

Conclusion

Through RNA-seq and bioinformatics analysis, this study identified GTF2IP14 and MTLN as the hub genes of HFrEF, and their mechanisms may be related to immune inflammatory responses and various immune cells.