Wen Hu’s research while affiliated with Guiyang Medical University and other places

Background Esketamine ameliorates propofol-induced brain damage and cognitive impairment in mice. However, the precise role and underlying mechanism of esketamine in perioperative neurocognitive disorders (PND) remain unclear. Therefore, this study aimed to investigate the key genes associated with the role of esketamine in PND through animal modeling and transcriptome sequencing. Methods The present study established a mice model of PND and administered esketamine intervention to the model, and mice were divided into control, surgical group, and surgical group with esketamine. Behavioral assessments were conducted using the Morris water maze and Y maze paradigms, while transcriptome sequencing was performed on hippocampal samples obtained from 3 groups. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were performed on sequencing data to identify candidate genes related to esketamine treating PND. Thereafter, protein-protein interaction (PPI) network analysis was implemented to select key genes. The genes obtained from each step were subjected to enrichment analysis, and a regulatory network for key genes was constructed. Results The Morris water maze and Y maze findings demonstrated the successful construction of our PND model, and indicated that esketamine exhibits a certain therapeutic efficacy for PND. Ank1, Cbln4, L1cam, Gap43, and Shh were designated as key genes for subsequent analysis. The 5 key genes were significantly enriched in cholesterol biosynthesis, nonsense mediated decay (NMD), formation of a pool of free 40s subunits, major pathway of rRNA processing in the nucleolus and cytosol, among others. Notably, the miRNAs, mmu-mir-155-5p and mmu-mir-1a-3p, functionally co-regulated the expression of Ank1, Gap43, and L1cam. Conclusion We uncovered the therapeutic efficacy of esketamine in treating PND and identified 5 key genes (Ank1, Cbln4, L1cam, Gap43, and Shh) that contribute to its therapeutic effects, providing a valuable reference for further mechanistic studies on esketamine’s treatment of PND.

Purpose Sepsis can induce sepsis-associated encephalopathy (SAE), with Ulinastatin (UTI) serving a critical anti-inflammatory role. This study aimed to identify the hub genes in an SAE mouse model following UTI intervention and investigate the underlying molecular mechanisms. Materials and Methods Through differential expression analysis to obtain differentially expressed genes (DEGs), ie, UTI vs CLP (DEGs1) and Con vs CLP (DEGs2). After taking the intersection of the genes with opposite differential trends in these two parts and immune-related genes (IRGs), DE-IRGs were obtained. Hub genes in the protein-protein interaction (PPI) network were then determined using six algorithms from the Cytohubba plugin in Cytoscape. Gene set enrichment analysis (GSEA) was employed to explore the functional relevance of these hub genes. Additionally, the immune microenvironment across the three groups was compared, and hub gene-related drugs were predicted using an online database. Finally, qRT-PCR was used to validate the expression of the hub genes in hippocampal tissue from CLP mice. Results RNA sequencing obtained 864 differentially expressed genes (DEGs) (CLP vs Con) and 279 DEGs (UTI vs CLP). Taking the intersection of DEGs with opposite expression trends yielded 165 DEGs. Six key genes (ICAM - 1, IRF7, IL - 1β, CCL2, IL - 6 and SOCS3) were screened by six algorithms. Immune infiltration analysis found that Treg cells were reversed after treatment with UTI in the diseased state. A total of 106 hub - gene - related drugs were predicted, among which BINDARIT - CCL2 and LIFITEGRAST - ICAM1 showed particularly high affinities. The qRT - PCR verification results were consistent with the sequencing results. Conclusion In conclusion, ICAM-1, IRF7, IL-1β, CCL2, IL-6, and SOCS3 were identified as potential therapeutic targets in SAE mice treated with UTI. This study offers theoretical support for UTI as a treatment option for SAE.

The polarization of microglia to the pro-inflammatory phenotype plays a crucial role in the initiation and progression of neuroinflammatory diseases, primarily owing to the secretion of pro-inflammatory cytokines that exacerbate damage within the central nervous system (CNS). Investigating the mechanisms underlying the inhibition of microglial pro-inflammatory polarization could be the potential targets for the prevention of neuroinflammatory diseases. The activation of N-methyl-D-aspartic acid (NMDA) receptors can mediate the over-activation and toxicity of microglia. Due to the unique structure of NMDA receptors, it has different subtypes and perform distinct functions. Our study indicates that Esketamine, a non-competitive antagonist of NMDAR, can up-regulate the phosphorylated Mammalian target of rapamycin (mTOR) and Brain-derived neurotrophic factor (BDNF)-Tropomyosin-related kinase receptor B (TrkB) signaling pathway by inhibiting the 2A subtype of NMDA receptors, attenuates LPS-induced pro-inflammatory polarization of BV2 microglia and reduces the expression of pro-inflammatory cytokines. However, the NMDAR2B subtype does not appear to be involved in this process.

Background Sepsis can result in acute lung injury (ALI). Studies have shown that pharmacological inhibition of ferroptosis can treat ALI. However, the regulatory mechanisms of ferroptosis in sepsis-induced ALI remain unclear. Methods Transcriptome sequencing was performed on lung tissue samples from 10 sepsis-induced mouse models of ALI and 10 control mice. After quality control measures, clean data were used to screen for differentially expressed genes (DEGs) between the groups. The DEGs were then overlapped with ferroptosis-related genes (FRGs) to obtain ferroptosis-related DEGs (FR-DEGs). Subsequently, least absolute shrinkage and selection operator (Lasso) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) were used to obtain key genes. In addition, Ingenuity Pathway Analysis (IPA) was employed to explore the disease, function, and canonical pathways related to the key genes. Gene set enrichment analysis (GSEA) was used to investigate the functions of the key genes, and regulatory miRNAs of key genes were predicted using the NetworkAnalyst and StarBase databases. Finally, the expression of key genes was validated with the GSE165226 and GSE168796 datasets sourced from the Gene Expression Omnibus (GEO) database and using quantitative real-time polymerase chain reaction (qRT-PCR). Results Thirty-three FR-DEGs were identified between 1843 DEGs and 259 FRGs. Three key genes, Ncf2, Steap3, and Gclc, were identified based on diagnostic models established by the two machine learning methods. They are mainly involved in infection, immunity, and apoptosis, including lymphatic system cell migration and lymphocyte and T cell responses. Additionally, the GSEA suggested that Ncf2 and Steap3 were similarly enriched in mRNA processing, response to peptides, and leukocyte differentiation. Furthermore, a key gene-miRNA network including 2 key genes (Steap3 and Gclc) and 122 miRNAs, and a gene-miRNA network with 1 key gene (Steap3) and 3 miRNAs were constructed using NetworkAnalyst and StarBase, respectively. Both databases predicted that mmu-miR-15a-5p was the target miRNA of Steap3. Finally, Ncf2 expression was validated using both datasets and qRT-PCR, and Steap3 was validated using GSE165226 and qRT-PCR. Conclusions This study identified two FR-DEGs (Ncf2 and Steap3) associated with sepsis-induced ALI via transcriptome analyses, as well as their functional and metabolic pathways.