Kyoto Encyclopedia Of Genes And Genomes Pathway Enrichment Analysis Research Articles

Transcriptome analysis reveals the molecular mechanisms underlying the enhancement of salt-tolerance in Melia azedarach under salinity stress

Melia azedarach demonstrates strong salt tolerance and thrives in harsh saline soil conditions, but the underlying mechanisms are poorly understood. In this study, we analyzed gene expression under low, medium, and high salinity conditions to gain a deeper understanding of adaptation mechanisms of M. azedarach under salt stress. The GO (gene ontology) analysis unveiled a prominent trend: as salt stress intensified, a greater number of differentially expressed genes (DEGs) became enriched in categories related to metabolic processes, catalytic activities, and membrane components. Through the analysis of the category GO:0009651 (response to salt stress), we identified four key candidate genes (CBL7, SAPK10, EDL3, and AKT1) that play a pivotal role in salt stress responses. Furthermore, the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis revealed that DEGs were significantly enriched in the plant hormone signaling pathways and starch and sucrose metabolism under both medium and high salt exposure in comparison to low salt conditions. Notably, genes involved in JAZ and MYC2 in the jasmonic acid (JA) metabolic pathway were markedly upregulated in response to high salt stress. This study offers valuable insights into the molecular mechanisms underlying M. azedarach salt tolerance and identifies potential candidate genes for enhancing salt tolerance in M. azedarach.

Transcriptomics reveals dynamic changes in the “gene profiles” of rat supraspinatus tendon at three different time points after diabetes induction

ObjectiveThere is increasing evidence that type 2 diabetes mellitus (T2DM) is an independent risk factor for the occur of tendinopathy. Therefore, this study is the first to explore the dynamic changes of the “gene profile” of supraspinatus tendon in rats at different time points after T2DM induction through transcriptomics, providing potential molecular markers for exploring the pathogenesis of diabetic tendinopathy.MethodsA total of 40 Sprague-Dawley rats were randomly divided into normal (NG, n = 10) and T2DM groups (T2DM, n = 30) and subdivided into three groups according to the duration of diabetes: T2DM-4w, T2DM-8w, and T2DM-12w groups; the duration was calculated from the time point of T2DM rat model establishment. The three comparison groups were set up in this study, T2DM-4w group vs. NG, T2DM-8w group vs. NG, and T2DM-12w group vs. NG. Differentially expressed genes (DEGs) in 3 comparison groups were screened. The intersection of the three comparison groups’ DEGs was defined as key genes that changed consistently in the supraspinatus tendon after diabetes induction. Cluster analysis, gene ontology (GO) functional annotation analysis and Kyoto encyclopedia of genes and genomes (KEGG) functional annotation and enrichment analysis were performed for DEGs.ResultsT2DM-4w group vs. NG, T2DM-8w group vs. NG, and T2DM-12w group vs. NG detected 519 (251 up-regulated and 268 down-regulated), 459 (342 up-regulated and 117 down-regulated) and 328 (255 up-regulated and 73 down-regulated) DEGs, respectively. 103 key genes of sustained changes in the supraspinatus tendon following induction of diabetes, which are the first identified biomarkers of the supraspinatus tendon as it progresses through the course of diabetes.The GO analysis results showed that the most significant enrichment in biological processes was calcium ion transmembrane import into cytosol (3 DEGs). The most significant enrichment in cellular component was extracellular matrix (9 DEGs). The most significant enrichment in molecular function was glutamate-gated calcium ion channel activity (3 DEGs). The results of KEGG pathway enrichment analysis showed that there were 17 major pathways (p < 0.05) that diabetes affected supratinusculus tendinopathy, including cAMP signaling pathway and Calcium signaling pathway.ConclusionsTranscriptomics reveals dynamic changes in the“gene profiles”of rat supraspinatus tendon at three different time points after diabetes induction. The 103 DEGs identified in this study may provide potential molecular markers for exploring the pathogenesis of diabetic tendinopathy, and the 17 major pathways enriched in KEGG may provide new ideas for exploring the pathogenesis of diabetic tendinopathy.

Identification of osteoporosis ferroptosis-related markers and potential therapeutic compounds based on bioinformatics methods and molecular docking technology

Research background and purposeOsteoporosis (OP) is one of the most common bone diseases worldwide, characterized by low bone mineral density and susceptibility to pathological fractures, especially in postmenopausal women and elderly men. Ferroptosis is one of the newly discovered forms of cell death regulated by genes in recent years. Many studies have shown that ferroptosis is closely related to many diseases. However, there are few studies on ferroptosis in osteoporosis, and the mechanism of ferroptosis in osteoporosis is still unclear. This study aims to identify biomarkers related to osteoporosis ferroptosis from the GEO (Gene Expression Omnibus) database through bioinformatics technology, and to mine potential therapeutic small molecule compounds through molecular docking technology, trying to provide a basis for the diagnosis and treatment of osteoporosis in the future.Materials and methodsWe downloaded the ferroptosis-related gene set from the FerrDb database (http://www.zhounan.org/ferrdb/index.html), downloaded the data sets GSE56815 and GSE7429 from the GEO database, and used the R software “limma” package to screen differentially expressed genes (DEGs) from GSE56815, and intersected with the ferroptosis gene set to obtain ferroptosis-related DEGs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed by the R software “clusterProfiler” package. The random forest model was further screened to obtain essential ferroptosis genes. R software “corrplot” package was used for correlation analysis of essential ferroptosis genes, and the Wilcox test was used for significance analysis. The lncRNA-miRNA-mRNA-TF regulatory network was constructed using Cytoscape software. The least absolute shrinkage and selection operator (LASSO) was used to construct a disease diagnosis model, and a Receiver operating characteristic (ROC) curve was drawn to evaluate the diagnostic performance, and then GSE7429 was used to verify the reliability of the diagnosis model. Molecular docking technology was used to screen potential small molecule compounds from the Drugbank database. Finally, a rat osteoporosis model was constructed, and peripheral blood mononuclear cells were extracted for qRT-PCR detection to verify the mRNA expression levels of crucial ferroptosis genes.ResultSix DEGs related to ferroptosis were initially screened out. GO function and KEGG pathway enrichment analysis showed that ferroptosis-related DEGs were mainly enriched in signaling pathways such as maintenance of iron ion homeostasis, copper ion binding function, and ferroptosis. The random forest model identified five key ferroptosis genes, including CP, FLT3, HAMP, HMOX1, and SLC2A3. Gene correlation analysis found a relatively low correlation between these five key ferroptosis genes. The lncRNA-miRNA-mRNA-TF regulatory network shows that BAZ1B and STAT3 may also be potential molecules. The ROC curve of the disease diagnosis model shows that the model has a good diagnostic performance. Molecular docking technology screened out three small molecule compounds, including NADH, Midostaurin, and Nintedanib small molecule compounds. qRT-PCR detection confirmed the differential expression of CP, FLT3, HAMP, HMOX1 and SLC2A3 between OP and normal control group.ConclusionThis study identified five key ferroptosis genes (CP, FLT3, HAMP, HMOX1, and SLC2A3), they were most likely related to OP ferroptosis. In addition, we found that the small molecule compounds of NADH, Midostaurin, and Nintedanib had good docking scores with these five key ferroptosis genes. These findings may provide new clues for the early diagnosis and treatment of osteoporosis in the future.

Exploring Acori Tatarinowii Rhizoma and Polygalae Radix in Alzheimer's: Network pharmacology and molecular docking analysis.

Explore Acori Tatarinowii Rhizoma (ATR) and Polygalae Radix (PR) mechanisms in Alzheimer's disease (AD) treatment through network pharmacology. ATR-PR was investigated in the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, Batman, and Traditional Chinese Medicines Integrated Database (TCMID) to gather information on its chemical components and target proteins. Target genes associated with AD were retrieved from the GeneCards and National Center for Biotechnology Information (NCBI) databases. The integration of these datasets with potential targets facilitated the construction of an AD and ATR-PR protein-protein interaction (PPI) network using the STRING database. The resulting network identified the core active ingredients and main targets of ATR-PR in AD treatment. Cluster analysis of the PPI network was performed using Cytoscape 3.7.1. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted using the Metascape database. Molecular docking simulations revealed potential interactions between the main active ingredients and core targets. Our analysis identified 8 putative components and 455 targets of ATR-PR. We systematically searched for 1306 genes associated with AD, conducted Venn diagram analysis resulting in 156 common targets, and constructed a PPI network with 57 key targets. GO functional analysis highlighted the primary biological processes associated with oxidative stress. KEGG pathway enrichment analysis revealed the involvement of 64 signaling pathways, with the PI3K/Akt signaling pathway playing a key role. Molecular docking analysis indicated a high affinity between the potential targets of ATR-PR and the main compounds of AD. This study sheds light on the complex network of interactions involving ATR-PR in the context of AD. The identified targets, pathways, and interactions provide a foundation for understanding the potential therapeutic mechanisms. The involvement of oxidative stress-related processes and the crucial role of the PI3K/Akt signaling pathway suggest avenues for targeted therapeutic interventions in Alzheimer's disease treatment. Our proposition of the combined use of ATR-PR has emerged as a potential treatment strategy for AD, supported by a network pharmacology approach. This framework provides a robust foundation for future clinical applications and experimental research in the pursuit of effective Alzheimer's disease treatments.

Bioinformatics-based screening and analysis of the key genes involved in the influence of antiangiogenesis on myeloid-derived suppressor cells and their effects on the immune microenvironment.

This study aimed to screen differentially expressed genes (DEGs) involved in the influence of antiangiogenic therapy on myeloid-derived suppressor cell (MDSC) infiltration and investigate their mechanisms of action. Data on DEGs after the action of antiangiogenic drugs in a pan-cancer context were obtained from the Gene Expression Omnibus (GEO) database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the clusterProfiler package in R software. Single-sample gene set enrichment analysis was performed using the gene set variation analysis package to evaluate the levels of immune cells and the activity of immune-related pathways. The relationships of DEGs with the infiltration levels of MDSCs and specific immune cell subpopulations were investigated via gene module analysis. The top 10 key genes were subsequently obtained from PPI network analysis using the cytoHubba plugin of the Cytoscape platform. When the DEGs of the four datasets were intersected, a DEG in the intersection of three datasets and 12 DEGs in the intersection of two datasets were upregulated, and 28 DEGs in the intersection of two datasets were downregulated. GO and KEGG pathway enrichment analyses revealed that the DEGs were associated with multiple important signaling pathways closely related to tumor onset and development, including cell differentiation, cell proliferation, the cell cycle, and immune responses. Most downregulated genes in lung adenocarcinoma (LUAD) were positively correlated with MDSC expression. Only MGP was negatively correlated; the correlation between CACNG6 and MDSC expression was statistically insignificant. In lung squamous cell carcinoma (LUSC), the relationships of PMEPA1, PCDH7, NEURL1B, and CACNG6 with MDSC expression were statistically insignificant; MGP was negatively correlated with MDSC expression. The top 10 key genes with the highest degree scores obtained using the cytoHubba plugin of Cytoscape were AURKB, RRM2, BUB1, NUSAP1, PRC1, TOP2A, NCAPH, CENPA, KIF2C, and CCNA2. Most of these genes were upregulated in LUAD and associated with immune cell infiltration and prognosis in tumors. An analysis of the relationships between DEGs and infiltration by other specific immune cells revealed the presence of consistent patterns in the downregulated genes, which exhibited positive correlations with the levels of Th2 cells, γδ T cells, and CD56dim NK cells, and negative correlations with other infiltrating immune cells. Antiangiogenic therapy may regulate MDSC infiltration through multiple important signaling pathways closely associated with tumor onset and development, such as cell differentiation, cell proliferation, the cell cycle, and immune responses. Antiangiogenic drugs may exert effects by affecting various types of infiltrating cells associated with immune suppression.

Network Pharmacology Prediction and Molecular Docking-Based Strategy to Explore the Potential Mechanism of Gualou Xiebai Banxia Decoction against Myocardial Infarction.

The aim of this study was to investigate targets through which Gualou Xiebai Banxia decoction aids in treating myocardial infarction (MI) using network pharmacology in combination with molecular docking. The principal active ingredients of Gualou Xiebai Banxia decoction were identified from the TCMSP database using the criteria of drug-likeness ≥30% and oral bioavailability ≥0.18. Interactions and pathway enrichment were investigated using protein-protein interaction (PPI) networks and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, respectively. Active component structures were docked with those of potential protein targets using AutoDock molecular docking relative softwares. HIF1A was of particular interest as it was identified by the PPI network, GO and KEGG pathway enrichment analyses. In conclusion, the use of network pharmacology prediction and molecular docking assessments provides further information on the active components and mechanisms of action Gualou Xiebai Banxia decoction.

Identification of EPSTI1 as a new potential biomarker for SLE based on GEO database.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease with highly heterogeneous. The aim of this study is to find the key genes in peripheral blood mononuclear cells (PBMCs) of SLE patients and to provide a new direction for the diagnosis and treatment of lupus. GSE121239, GSE50772, GSE81622, and GSE144390 mRNA expression profiles were obtained from the website of Gene Expression Omnibus (GEO), and differential expressed genes (DEGs) analysis was performed by R. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to elucidate signaling pathways for the DEGs. Real-time qPCR (RT-qPCR) was used to verify the key gene EPSTI1 in PBMCs of SLE patients. Finally, the correlation analysis and ROC curve analysis of EPSTI1 for SLE were performed. A total of 12 upregulated DEGs were identified, including MMP8, MX1, IFI44, EPSTI1, OAS1, OAS3, HERC5, IFIT1, RSAD2, USP18, IFI44L, and IFI27. GO and KEGG pathway enrichment analysis showed that those DEGs were mainly concentrated in the response to virus and IFN signaling pathways. Real-time qPCR (RT-qPCR) revealed that EPSTI1 was increased in PBMCs of SLE. EPSTI1 was positively correlated with SLEDAI score in SLE patients. Besides, EPSTI1 was positively correlated with T cell activation- or differentiation-associated genes (BCL6 and RORC). Furthermore, ROC analyses proved EPSTI1 may have diagnostic value for SLE. Together, EPSTI1 was found to be a potential biomarker for SLE, closely related to T cell immune imbalance. Key Points • EPSTI1 expression was significantly increased in PBMCs of SLE patients. • EPSTI1 was positively correlated with disease activity and T cell activation- or differentiation-associated genes in SLE patients. • EPSTI1 might have a good diagnostic value for SLE.

Identification of key autophagy-related genes and pathways in spinal cord injury

Spinal cord injury (SCI) can cause a range of functional impairments, and patients with SCI have limited potential for functional recovery. Previous studies have demonstrated that autophagy plays a role in the pathological process of SCI, but the specific mechanism of autophagy in this context remains unclear. Therefore, we explored the role of autophagy in SCI by identifying key autophagy-related genes and pathways. This study utilized the GSE132242 expression profile dataset, which consists of four control samples and four SCI samples; autophagy-related genes were sourced from GeneCards. R software was used to screen differentially expressed genes (DEGs) in the GSE132242 dataset, which were then intersected with autophagy-related genes to identify autophagy-related DEGs in SCI. Subsequently, the expression levels of these genes were confirmed and analyzed with gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). A protein–protein interaction (PPI) analysis was conducted to identify interaction genes, and the resulting network was visualized with Cytoscape. The MCODE plug-in was used to build gene cluster modules, and the cytoHubba plug-in was applied to screen for hub genes. Finally, the GSE5296 dataset was used to verify the reliability of the hub genes. We screened 129 autophagy-related DEGs, including 126 up-regulated and 3 down-regulated genes. GO and KEGG pathway enrichment analysis showed that these 129 genes were mainly involved in the process of cell apoptosis, angiogenesis, IL-1 production, and inflammatory reactions, the TNF signaling pathway and the p53 signaling pathway. PPI identified 10 hub genes, including CCL2, TGFB1, PTGS2, FN1, HGF, MYC, IGF1, CD44, CXCR4, and SERPINEL1. The GSE5296 dataset revealed that the control group exhibited lower expression levels than the SCI group, although only CD44 and TGFB1 showed significant differences. This study identified 129 autophagy-related genes that might play a role in SCI. CD44 and TGFB1 were identified as potentially important genes in the autophagy process after SCI. These findings provide new targets for future research and offer new perspectives on the pathogenesis of SCI.

The Analgesic Mechanism of Radix Wikstroemia indica “Sweat Soaking Method” Processed Product Based on Metabolomics and Network Pharmacology

Background: Miao medicine Radix Wikstroemia indica (RWI) is derived from the root of W. indica (L.) C. A. Mey. which has an analgesic effect, but its mechanism is not clear. Because of the toxicity of RWI, the research group used the “Sweat soaking method” to process RWI in the early stage to reduce its toxicity. Therefore, this study explored the analgesic effect and mechanism of processed RWI through network pharmacology and metabolomics. Purpose: To explore the analgesic effect and therapeutic mechanism of RWI processed by “Sweat soaking method”. Materials and methods: The torsion experiment was carried out with acetic acid. The metabolomic analysis of serum samples was carried out based on 1H-NMR technology, and the intersection targets of RWI and pain diseases were screened by network pharmacology for gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Results: RWI has an analgesic effect and is related to metabolites such as 4-pyridoxic acid, l-glutamic acid, and agmatine. It is involved in arginine and proline metabolism, arginine biosynthesis, and alanine, aspartate, and glutamate metabolism. In network pharmacology, there were 404 common targets between RWI and pain diseases, and eight core targets were screened, including SRC, STAT3, and HSP90AA1. GO functional enrichment analysis found that RWI had effects on molecular processes such as protein phosphorylation and response to xenobiotic stimulus, cell composition such as receptor complex and membrane raft, and molecular functions such as enzyme binding. KEGG pathway enrichment analysis obtained 193 pathways. Arginine proline metabolism and nitrogen metabolism are involved in the same pathway as metabolomic analysis. Conclusion: RWI has an analgesic effect, and its therapeutic mechanism mainly involves arginine and proline metabolism.

Network Pharmacology and Molecular Docking to Explore the Mechanism of Compound Qilian Tablets in Treating Diabetic Retinopathy

Background: Diabetic Retinopathy (DR) is one of the common chronic complications of diabetes mellitus, which has developed into the leading cause of irreversible visual impairment in adults worldwide. The Compound Qilian Tablets (CQLT) were developed in China for the treatment and prevention of DR, but their mechanism of action is still unclear. Objective: In the present study, network pharmacology, molecular docking, and in vivo validation experiments were used to investigate the active components and molecular mechanisms of CQLT against DR. Methods: The active components and targets of CQLT were collected through the TCSMP database, and the targets of DR were obtained from GeneCards, OMIM, and Drugbank databases. We established a protein-protein interaction network using the STRING database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted using the Metascape database. Molecular docking using AutoDock Vina was performed to investigate the interactions between components of CQLT and core targets. Moreover, we selected ZDF rats to establish a DR model for the experimental studies. Results: 39 active components and 448 targets in CQLT were screened, among which 90 targets were shared with DR. KEGG pathway enrichment analysis identified 181 pathways. The molecular docking results demonstrated that the main active components had strong binding ability to the core targets. The results from animal experiments indicate that the mechanism of CQLT against DR is associated with inhibiting the retinal mTOR/HIF-1α/VEGF signaling pathway, alleviating the inflammatory response, suppressing retinal neovascularization, and protecting the function and morphology of the retina. Conclusion: The present study preliminarily explored the mechanism of CQLT in treating DR and demonstrated that CQLT exerts anti-DR effects through multiple components, multiple targets, and multiple pathways. These findings suggest that CQLT shows promise as a potential therapeutic agent for DR and could contribute to developing novel treatments.

Multiplexing of TMT labeling reveals folate-deficient diet-specific proteome changes in NTDs.

Introduction: In the early stage of embryonic development, the neural tube (NT) cannot be closed properly due to some complex factors, including environmental factors, genetic factors, and the relationship between various factors, leading to the occurrence of neural tube defects (NTDs). Methods: In this study, we induced a mouse model of NTDs by feeding mice with a low-folate diet and intraperitoneally injecting them with 1.5mg/kg methotrexate on E7.5. Fetal mice were achieved at E13.5, and we extracted proteins from brain tissues with trypsin digestion. After enzymatic digestion, peptides were labeled with TMT/iTRAQ and separated in high-performance liquid chromatography (HPLC) for subsequent liquid chromatography tandem mass spectroscopy (LC-MS/MS) analysis. We used gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation to analyze proteomic changes and analyze the functional enrichment of differentially expressed proteins (DEPs) in the NTD mice tissues. Results: A low-folate-induced mouse model was successfully constructed. Folate was used as a sensitizing agent, and the teratogenicity rate of the NTD fetal mice increased to 36.5% when the concentration of methotrexate was at 1.5mg/kg. Mass spectrometry was used to identify 6,614 proteins, and among them, 5,656 proteins were quantified. In the following proteomic analysis, GO classification and KEGG pathway enrichment analysis were conducted, and heatmaps were drawn for differentially expressed proteins (DEPs). The main pathways associated with NTDs, such as the Hedgehog, Wnt, p53, and Hippo signaling pathways and the one-carbon pool mediated by folate, can be identified through a protein-protein interaction (PPI) network. It was also found that the regulation of ribosomal proteins, such as RPL13 and RPL14, which are upregulated in NTDs, has a certain impact on neural tube development. Discussion: Our results revealed proteomic changes in the tissues of low-folate-induced NTD mice. Validation showed that ribosomal proteins play a regulatory role during the development of NTDs and provides new ideas for the pathogenesis and preventive measures of NTDs.

Network Pharmacology and Experimental Validation of Jinwei Decoction for Enhancement of Glucocorticoid Anti-Inflammatory Effect in COPD through miR-155-5p

Background: Jinwei decoction can enhance the anti-inflammatory effect of glucocorticoid (GC) on chronic obstructive pulmonary disease (COPD) by restoring the activity of human histone deacetylase-2 (HDAC2). However the upstream mechanism of Jinwei decoction on HDAC2 expression is not clear. Objective: To explore the target of Jinwei decoction to enhance the anti-inflammatory effect of GC on COPD through microRNA155-5p (miR-155-5p) by network pharmacology and experimental verification. Methods: The TCMSP database was used to screen active ingredients and target genes of Jinwei decoction, and miRWalk2.0 was used to predict downstream target genes of miR-155-5p. COPD-related genes were identified by searching GeneCards, Grugbank and OMIM databases; Venny 2.1 was used to screen intersection genes; Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of intersection genes were analyzed by R software. Protein-protein interactions (PPIs) were analyzed by Cytoscape 3.7.2 software to identify core genes. Finally, interactions between main compounds and potential targets were verified by molecular docking. A COPD cell model was established by 5% cigarette smoke extract (CSE)- induced bronchial epithelial cell (BEAS-2B), and the results of network pharmacology were verified by in vitro experiments. Results: Two hundred thirty-one active ingredients, 352 Jinwei decoction drug targets, 5949 miR-155-5p target genes, 8286 COPD target genes, and 127 intersection genes were identified. Twelve core proteins of PPI networks may be involved. GO enrichment analysis showed that regulation of membrane potential， response to steroid hormone, and histone modification were involved; KEGG pathway enrichment analysis concentrated in the PI3K-Akt, mitogen-activated protein kinase (MAPK), HIF-1, and other signaling pathways. The molecular docking results showed that quercetin, luteolin and stigmasterol have higher affinity with PTGS2, HIF1A and AKT1. The results of cell experiments revealed that Jinwei decoction not only enhances the anti- inflammatory effect of GC in the COPD cell model but also reverses the high expression of miR-155-5p、PI3k、Akt, and low expression of HDAC2, thereby inhibiting the inflammatory response of COPD. result: Two hundred thirty-one active ingredients, 352 Jinwei decoction drug targets, 5949 miR-155-5p target genes, 8286 COPD target genes, and 127 intersection gene were identified. Twelve core proteins of PPI networks may be involved. GO enrichment analysis showed that regulation of membrane potential，response to steroid hormone, and histone modification were involved; KEGG pathway enrichment analysis concentrated in the PI3K-Akt, mitogen-activated protein kinase (MAPK), HIF-1, and other signaling pathways. The molecular docking results showed that quercetin, luteolin and stigmasterol have higher affinity with PTGS2, HIF1A and AKT1. The results of cell experiments revealed that Jinwei decoction not only enhances the anti-inflammatory effect of GC in the COPD cell model, but also reversed the high expression of miR-155-5p、PI3k、Akt, and low expression of HDAC2, thereby inhibiting the inflammatory response of COPD. Conclusion: Jinwei decoction can regulate HDAC2 activity and enhance the anti-inflammatory effect of GC on COPD by modulating miR-155-5p. Its mechanism of action may be related to its effect on the PI3K-Akt through miR-155-5p.

Elucidating the molecular mechanisms of sepsis: Identifying key aging-related biomarkers and potential therapeutic targets in the treatment of sepsis.

Sepsis remains a crucial global health issue characterized by high mortality rates and a lack of specific treatments. This study aimed to elucidate the molecular mechanisms underlying sepsis and to identify potential therapeutic targets and compounds. High-throughput sequencing data from the GEO database (GSE26440 as the training set and GSE13904 and GSE32707 as the validation sets), weighted gene co-expression network analysis (WGCNA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, alongside a combination of PPI and machine learning methods (LASSO and SVM) were utilized. WGCNA identified the black module as positively correlated, and the green module as negatively correlated with sepsis. Further intersections of these module genes with age-related genes yielded 57 sepsis-related genes. GO and KEGG pathway enrichment analysis, PPI, LASSO, and SVM selected six hub aging-related genes: BCL6, FOS, ETS1, ETS2, MAPK14, and MYC. A diagnostic model was constructed based on these six core genes, presenting commendable performance in both the training and validation sets. Notably, ETS1 demonstrated significant differential expression between mild and severe sepsis, indicating its potential as a biomarker of severity. Furthermore, immune infiltration analysis of these six core genes revealed their correlation with most immune cells and immune-related pathways. Additionally, compounds were identified in the traditional Chinese medicine Danshen, which upon further analysis, revealed 354 potential target proteins. GO and KEGG enrichment analysis of these targets indicated a primary enrichment in inflammation and immune-related pathways. A Venn diagram intersects these target proteins, and our aforementioned six core genes yielded three common genes, suggesting the potential efficacy of Danshen in sepsis treatment through these genes. This study highlights the pivotal roles of age-related genes in the molecular mechanisms of sepsis, offers potential biomarkers, and identifies promising therapeutic compounds, laying a robust foundation for future studies on the treatment of sepsis.

SKP alleviates the ferroptosis in diabetic kidney disease through suppression of HIF-1α/HO-1 pathway based on network pharmacology analysis and experimental validation.

Diabetic kidney disease (DKD) represents a microvascular complication of diabetes mellitus. Shenkang Pills (SKP), a traditional Chinese medicine formula, has been widely used in the treatment of DKD and has obvious antioxidant effect. Ferroptosis, a novel mode of cell death due to iron overload, has been shown to be associated with DKD. Nevertheless, the precise effects and underlying mechanisms of SKP on ferroptosis in diabetic kidney disease remain unclear. The active components of SKP were retrieved from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. Protein-protein interaction (PPI) network and Herb-ingredient-targets gene network were constructed using Cytoscape. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted utilizing the Metascape system database. Additionally, an in vivo model of DKD induced by Streptozotocin (STZ) was established to further investigate and validate the possible mechanisms underlying the effectiveness of SKP. We retrieved 56 compounds and identified 223 targets of SKP through the TCMSP database. Key targets were ascertained using PPI network analysis. By constructing a Herb-Ingredient-Targets gene network, we isolated the primary active components in SKP that potentially counteract ferroptosis in diabetic kidney disease. KEGG pathway enrichment analysis suggested that SKP has the potential to alleviate ferroptosis through HIF signaling pathway, thereby mitigating renal injury in DKD. In animal experiments, fasting blood glucose, 24h urine protein, urea nitrogen and serum creatine were measured. The results showed that SKP could improve DKD. Results from animal experiments were also confirmed the efficacy of SKP in alleviating renal fibrosis, oxidative stress and ferroptosis in DKD mice. These effects were accompanied by the significant reductions in renal tissue expression of HIF-1α and HO-1 proteins. The mRNA and immunohistochemistry results were the same as above. SKP potentially mitigating renal injury in DKD by subduing ferroptosis through the intricacies of the HIF-1α/HO-1 signaling pathway.

Identification of key genes of diabetic cardiomyopathy in hiPSCs-CMs based on bioinformatics analysis.

Diabetic cardiomyopathy (DbCM) is one of the most common vascular complications of diabetes, and can cause heart failure and threaten the life of patients. The pathogenesis is complex, and key genes have not fully identified. In this study, bioinformatics analysis was used to predict DbCM-related gene targets. Published datasets from the NCBI Gene Expression Omnibus with accession numbers GSE62203 and GSE197850 were selected for analysis. Differentially expressed genes (DEGs) were identified by the online tool GEO2R. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the DAVID online database. Protein-protein interaction network construction and hub gene identification were performed using STRING and Cytoscape. We used 30mM and 1μM hydrocortisone-stimulated AC16 cells as an in vitro model of diabetic cardiomyopathy. Quantitative real-time PCR (qRT-PCR) was performed to validate the expression levels of hub genes. A total of 73 common DEGs were identified in both datasets, including 47 upregulated and 26 downregulated genes. GO and KEGG pathway enrichment analyses revealed that the DEGs were significantly enriched in metabolism, hypoxia response, apoptosis, cell proliferation regulation, and cytoplasmic and HIF signalling pathways. The top 10 hub genes were LDHA, PGK1, SLC2A1, ENO1, PFKFB3, EGLN1, MYC, PDK1, EGLN3 and BNIP3. In our in vitro study, we found that PGK1, SLC2A1, PFKFB3, EGLN1, MYC, EGLN3 and BNIP3 were upregulated, ENO1 was downregulated, and LDHA was unchanged. Except for PGK1 and ENO1, these hub genes have been previously reported to be involved in DbCM. In summary, we identified DEGs and hub genes and first reported PGK1 and ENO1 in DbCM, which may serve as potential candidate genes for DbCM targeted therapy.

Tripterygium wilfordii Hook.f induced kidney injury through mediating inflammation via PI3K-Akt/HIF-1/TNF signaling pathway: A study of network toxicology and molecular docking.

We intend to explore potential mechanisms of Tripterygium wilfordii Hook.f (TwHF) induced kidney injury (KI) using the methods of network toxicology and molecular docking. We determined TwHF potential compounds with its targets and KI targets, obtained the TwHF induced KI targets after intersecting targets of TwHF and KI. Then we conducted protein-protein interaction (PPI) network, gene expression analysis, gene ontology (GO) function and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis to explore the mechanism of TwHF-induced KI. Finally we conducted molecular docking to verify the core toxic compounds and the targets. We obtained 12 TwHF toxic compounds and 62 TwHF-induced KI targets. PPI network, gene expression analysis and GO function enrichment analysis unveiled the key biological process and suggested the mechanism of TwHF-induced KI might be associated with inflammation, immune response, hypoxia as well as oxidative stress. KEGG pathway enrichment analysis indicated PI3K-Akt signaling pathway, HIF-1 signaling pathway and TNF signaling pathway were key signaling pathways of TwHF induced KI. Molecular docking showed that the binding energy of core targets and toxic compounds was all less than -6.5 kcal/mol that verified the screening ability of network pharmacology and provided evidence for modifying TwHF toxic compounds structure. Through the study, we unveiled the mechanism of TwHF induce KI that TwHF might activate PI3K-Akt signaling pathway as well as TNF signaling pathway to progress renal inflammation, mediate hypoxia via HIF-1 signaling pathway to accelerate inflammatory processes, and also provided a theoretical basis for modifying TwHF toxic compounds structure as well as supported the follow-up research.

Identification and analysis of mitochondria-related central genes in steroid-induced osteonecrosis of the femoral head, along with drug prediction.

Steroid-induced osteonecrosis of the femoral head (SONFH) is a refractory orthopedic hip joint disease that primarily affects middle-aged and young individuals. SONFH may be caused by ischemia and hypoxia of the femoral head, where mitochondria play a crucial role in oxidative reactions. Currently, there is limited literature on whether mitochondria are involved in the progression of SONFH. Here, we aim to identify and validate key potential mitochondrial-related genes in SONFH through bioinformatics analysis. This study aims to provide initial evidence that mitochondria play a role in the progression of SONFH and further elucidate the mechanisms of mitochondria in SONFH. The GSE123568 mRNA expression profile dataset includes 10 non-SONFH (non-steroid-induced osteonecrosis of the femoral head) samples and 30 SONFH samples. The GSE74089 mRNA expression profile dataset includes 4 healthy samples and 4 samples with ischemic necrosis of the femoral head. Both datasets were downloaded from the Gene Expression Omnibus (GEO) database. The mitochondrial-related genes are derived from MitoCarta3.0, which includes data for all 1136 human genes with high confidence in mitochondrial localization based on integrated proteomics, computational, and microscopy approaches. By intersecting the GSE123568 and GSE74089 datasets with a set of mitochondrial-related genes, we screened for mitochondrial-related genes involved in SONFH. Subsequently, we used the good Samples Genes method in R language to remove outlier genes and samples in the GSE123568 dataset. We further used WGCNA to construct a scale-free co-expression network and selected the hub gene set with the highest connectivity. We then intersected this gene set with the previously identified mitochondrial-related genes to select the genes with the highest correlation. A total of 7 mitochondrial-related genes were selected. Next, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on the selected mitochondrial-related genes using R software. Furthermore, we performed protein network analysis on the differentially expressed proteins encoded by the mitochondrial genes using STRING. We used the GSEA software to group the genes within the gene set in the GSE123568 dataset based on their coordinated changes and evaluate their impact on phenotype changes. Subsequently, we grouped the samples based on the 7 selected mitochondrial-related genes using R software and observed the differences in immune cell infiltration between the groups. Finally, we evaluated the prognostic significance of these features in the two datasets, consisting of a total of 48 samples, by integrating disease status and the 7 gene features using the cox method in the survival R package. We performed ROC analysis using the roc function in the pROC package and evaluated the AUC and confidence intervals using the ci function to obtain the final AUC results. Identification and analysis of 7 intersecting DEGs (differentially expressed genes) were obtained among peripheral blood, cartilage samples, hub genes, and mitochondrial-related genes. These 7 DEGs include FTH1, LACTB, PDK3, RAB5IF, SOD2, and SQOR, all of which are upregulated genes with no intersection in the downregulated gene set. Subsequently, GO and KEGG pathway enrichment analysis revealed that the upregulated DEGs are primarily involved in processes such as oxidative stress, release of cytochrome C from mitochondria, negative regulation of intrinsic apoptotic signaling pathway, cell apoptosis, mitochondrial metabolism, p53 signaling pathway, and NK cell-mediated cytotoxicity. GSEA also revealed enriched pathways associated with hub genes. Finally, the diagnostic value of these key genes for hormone-related ischemic necrosis of the femoral head (SONFH) was confirmed using ROC curves. BID, FTH1, LACTB, PDK3, RAB5IF, SOD2, and SQOR may serve as potential diagnostic mitochondrial-related biomarkers for SONFH. Additionally, they hold research value in investigating the involvement of mitochondria in the pathogenesis of ischemic necrosis of the femoral head.

Efficacy of Danlou tablet on myocardial ischemia/ reperfusion injury assessed by network pharmacology and experimental verification.

To investigate the potential pharmacological mechanism of Danlou tablet (, DLT) with a long-term clinical application in the treatment of myocardial ischemia/reperfusion (I/R) injury through network pharmacology, molecular docking and experimental verification. The main chemical ingredients in DLT were retrieved from the Traditional Chinese Medicine (TCM) System Pharmacology Database, the TCM information database, the bioinformatics analysis tool for molecular mechanism of TCM, and HERB database. Disease targets of I/R were accessed from the databases of Online Mendelian Inheritance in Man, GeneCards, Therapeutic Target Database, and DisGeNET database. The overlaying genes of DLT and I/R were obtained from the Venny online platform. The core targets and protein-protein interaction network were constructed and analyzed via the Search Tool for the Retrieval of Interacting Genes Proteins database and Cytoscape software. Furthermore, Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed by the Metascape platform. Based on the results, the component-target-pathway network was constructed and drafted via the Cytoscape software and the platform of Bioinformatics. Furthermore, we performed molecular docking to predict the binding information between chemical molecules and target proteins. Finally, oxygen-glucose deprivation/recovery (OGD/R)-induced H9c2 cardiomyocytes were used to validate the results of network pharmacology in vitro. A total of 189 active chemical components in DLT and 849 correlative targets of I/R were screened. Of note, 133 overlaying genes found from the Venny online platform were concentrated into 28 core genes. Furthermore, the GO and KEGG pathway enrichment analysis presented that DLT might participate in 42 types of GO molecular functions, 747 types of GO biological processes, 19 types of GO cellular components, and 140 kinds of pathways to treat I/R. In the component-target-pathway network, the indirect relationship between herbs and their possible effective pathways was clarified. Based on the molecular docking, we speculated that Baicalein-prostaglandin G/H synthase 2 (PTGS2) with -3.24 kcal/mol, Luteolin-heat shock protein 90 alpha family class A member 1 (HSP90AA1) with -3.22 kcal/mol, Baicalein-HSP90AA1 with -3.13 kcal/mol, and Quercetin-HSP90AA1 with -3.05 kcal/mol possessed the strongest binding force of less than -3 kcal/mol, sequentially. Experimental verification showed that Quercetin, Luteolin, and Baicalein could increase the relative cell viability of OGD/R-stimulated cardiomyocytes, probably by suppressing PTGS2, and activating HSP90AA1 and estrogen receptor 1 expression. We predicted the potential active compounds as the material basis of DLT that may provide a new approach to elucidate the novel pharmacological mechanism underlying the treatment of cardiac I/R damage.

Phenolic acids from Chicory roots ameliorate dextran sulfate sodium–induced colitis in mice by targeting TRP signaling pathways and the gut microbiota

BackgroundInflammatory bowel disease (IBD) is a type of immune–mediated condition associated with intestinal homeostasis. Our preliminary studies disclosed that Cichorium intybus L., a traditional medicinal plant, also known as Chicory in Western countries, contained substantial phenolic acids displaying significant anti–inflammatory activities. We recognized the potential of harnessing Chicory for the treatment of IBD, prompting a need for in–depth investigation into the underlying mechanisms. MethodsOn the third day, mice were given 100, 200 mg/kg of total phenolic acids (PA) from Chicory and 200 mg/kg of sulfasalazine (SASP) via gavage, while dextran sodium sulfate (DSS) concentration was 2.5 % for one week. The study measured and evaluated various health markers including body weight, disease activity index (DAI), colon length, spleen index, histological score, serum concentrations of myeloperoxidase (MPO), nitric oxide (NO), superoxide dismutase (SOD), lipid oxidation (MDA), and inflammatory factors. We evaluated the TRP family and the NLRP3 inflammatory signaling pathways by Western blot, while 16S rDNA sequencing was used to track the effects of PA on gut microbes. ResultsIt was shown that PA ameliorated the weight loss trend, attenuated inflammatory damage, regulated oxidative stress levels, and repaired the intestinal barrier in DSS mice. Analyses of Western blots demonstrated that PA suppressed what was expressed of transient receptor potential family TRPV4, TRPA1, and the expression of NLRP3 inflammatory signaling pathway, NLRP3 and GSDMD. In addition, PA exerted therapeutic effects on IBD by regulating gut microbiota richness and diversity. Meanwhile, the result of the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis showed that gut microbiota was mainly related to Membrane Transport, Replication and Repair, Carbohydrate Metabolism and Amino Acid Metabolism. ConclusionPA derived from Chicory may have therapeutic effects on IBD by regulating the TRPV4/NLRP3 signaling pathway and gut microbiome. This study provides new insights into the effects of phenolic acids from Chicory on TRP ion channels and gut microbiota, revealing previously unexplored modes of action.

Exploring the mechanism of Jingshen Xiaoke decoction in treating T2DM mice based on network pharmacology and molecular docking.

Jingshen Xiaoke decoction (JS) was prepared by studying the classic prescriptions of famous scholars in the past dynasties to prevent and treat diabetes. The related mechanism of JS against hyperlipidemia has yet to be revealed. To investigate the mechanism of action of JS in treating diabetes mellitus by using bioinformatics methods. A database was used to search the active ingredients and targets of the JS and targets for type 2 diabetes mellitus (T2DM). The protein interaction between the intersection targets, and the constructed the PPI network diagram was analyzed using the STRING database. Furthermore, the gene annotation tool DAVID was used to enrich the intersecting targets for the Gene ontology (GO) function and Kyoto encyclopedia of genes and genomes (KEGG) signaling pathway. Finally, Maestro software was used for molecular docking to verify the binding ability of the active ingredients to the core target genes. A total of 45 active ingredients in JS were screened out corresponding to 239 effective targets, of which 64 targets were potential targets for treating T2DM. The analysis of PPI network diagram analysis revealed that the ingredients' active components are quercetin, β-sitosterol, stigmasterol, luteolin, and 7-Methoxy-2-methyl isoflavone. GO functional enrichment analysis indicated 186 biological processes (BP), 23 molecular functions (MF) and 13 cellular components (CC). KEGG pathway enrichment analysis revealed the enrichment of 59 signal pathways. The molecular docking results demonstrated that the active ingredients and core targets had a good docking affinity with a binding activity less than -7 kcal/mol. Finally, the western blotting illustrated that JS could up-regulate the liver PI3K/AKT-signaling pathway. JS can regulate glucolipid metabolism, reduce the inflammatory response, improve insulin resistance and modulate the immune response through PI3K/AKT signaling pathway treating of T2DM and its complications effects.