Kyoto Encyclopedia Of Genes And Genomes Pathway Enrichment Research Articles

Changes in the expression profile of serum lncRNAs in pregnant women with high hepatitis B viral load during antiviral and non-antiviral treatment

ObjectiveThis research analyzes the potential of long non-coding RNAs (lncRNAs) as markers in determining the necessity of antiviral treatment in pregnant women by examining alterations in the expression profile of serum lncRNAs in pregnant women with elevated hepatitis B viral load (HBVL) under antiviral and non-antiviral treatment regimens between the second trimester and delivery.MethodsSerum was obtained from 6 s-trimester pregnant women with high HBVL and no intrauterine infection. Then, 3 of these women were randomly selected for antiviral treatment, with the remaining 3 women undergoing non-antiviral treatment as control. Serum samples were again collected from these 6 women before delivery. The expression profile of lncRNAs was analyzed with microarray technology, followed by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The axes of hub lncRNA-miRNA-mRNA were identified based on the competing endogenous RNA (ceRNA) network.ResultsThe expression profile of serum lncRNAs in pregnant women with high HBVL changed significantly from the second trimester of pregnancy until delivery under antiviral or non-antiviral treatment. The Venn diagram was utilized to screen out the jointly up-regulated and down-regulated lncRNAs in the serum of pregnant women under antiviral and non-antiviral treatment before delivery. Additionally, the KEGG pathway enrichment analysis results showed that lncRNAs might mediate the Hippo pathway in HBV infection. Based on the ceRNA network, 3 hub lncRNAs (CATG00000076041.1, LINC01310, and G014655) were found to potentially regulate the key gene TP73 in the Hippo pathway.ConclusionIn this study, we retrieved co-differentially expressed lncRNAs in pregnant women with high HBVL under antiviral or non-antiviral treatment, which may be used as markers for evaluating whether pregnant women with high HBVL may be free of antiviral treatment. This study may provide a basis for preventing potential adverse effects of antiviral treatment on maternal and fetal health.

Serum proteomic analysis identified ITIH4 as a potential novel biomarker for feline infectious peritonitis

Feline infectious peritonitis (FIP) is a fatal feline disease. At present, the reference standard for FIP diagnosis is immunohistochemistry (IHC) of organs, but this method involves high time-related costs, invasive sampling procedures and professional requirements. Serological detection is a common auxiliary method for diagnosing diseases. As a result, we assessed the changes in the serum proteome of FIP patients with the aim of identifying novel specific serum biomarkers that could aid in the clinical diagnosis of FIP. Pre- and postinfection groups were compared and 92 differentially expressed proteins (DEPs) were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the DEPs revealed that the enriched GO terms and KEGG pathways among the DEPs were immune activation, peptidase regulator activity and the complement and coagulation cascade pathways. The level of peptidase regulator interalpha-trypsin inhibitor heavy chain 4 (ITIH4) in cat serum was significantly correlated with FIP. The areas under the ROC curve (AUCs) of full-length ITIH4 (f-ITIH4) and cleaved ITIH4 (c-ITIH4) expression were 0.922 and 1.000, respectively, which allowed the discrimination of FIP cats from healthy cats. These results suggest that ITIH4 may be a potential serum biomarker for detecting early FIP. SignificanceFIP causes fatal disease in cats of almost all ages, and there is currently no effective vaccine or treatment for FIP. Therefore, early diagnosis is extremely important for disease prevention and control. The results of the model and clinical samples revealed that ITIH4 was significantly increased in the serum of FIP cats. This study is the first to propose ITIH4 as a diagnostic biomarker in cats with FIP and our results suggest that serum ITIH4 levels might identify cats with FIP during the early stage.

Transcriptome Analysis of Porphyromonas gingivalis Lipopolysaccharide-Induced Early Gene Expression in Human Gingival Keratinocytes.

Porphyromonas gingivalis lipopolysaccharide (PgLPS) is a significant virulence factor and a driver of early innate immune responses in epithelial cells. The presence of PgLPS in immediate proximity to gingival epithelium induces significant inflammatory responses. In primary human gingival keratinocytes (HGK), we utilized transcriptome analysis to elucidate the change in early gene expression induced by PgLPS. HGK cell cultures were treated with PgLPS (4 h), and RNA was extracted and prepared for RNA sequence (RNAseq) analysis. Differentially expressed genes (DEGs) were identified, and potential interactions between these genes were subsequently examined using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analytic approaches to identify significantly enriched pathways. Expression of genes associated with relevant pathways was evaluated using real-time quantitative reverse-transcription polymerase chain reaction (RT-qPCR). RNAseq analysis identified 25 DEGs, and GO and KEGG analytic approaches showed related genes expressed in two general pathways. First, pathways broadly related to urokinase and coagulation included the genes PLAU, PLAUR, and SerpinB2. In RT-qPCR analysis, these genes were induced by PgLPS over time (4-24 h), and these data were consistent with PgLPS induction of cell migration. Second, interleukin-1 (IL-1) receptor binding and cytokine-activity pathways were also enriched. Genes associated with these pathways included IL36G, IL1B, IL1RN, and CXCL14. RT-qPCR analysis confirmed PgLPS induction of genes associated with the IL-1family. When expression of IL1B and IL36G genes was examined in relation to their respective antagonists, only IL36G gene expression was increased. CXCL14 gene expression was reduced over time, and this was consistent with RNAseq analysis. Genes associated with significantly enriched GO and KEGG pathways are relevant to aspects of periodontal disease (PDD) pathogenesis. First, PgLPS induced expression of PLAU, PLAUR, and SerpinB2, and these changes were consistent with an increase in cell migration that was found. Second, both IL36G and IL1B gene expression was significantly induced, but only IL36G in relation to its selective antagonist (IL36RN) was increased. These data support that early upregulation of IL36G may serve as an alarmin that can drive early innate immune inflammatory responses in HGK. Further invivo testing of these findings is ongoing.

Integrative analysis of the efficacy and pharmacological mechanism of Xuefu Zhuyu decoction in idiopathic pulmonary fibrosis via evidence-based medicine, bioinformatics, and experimental verification

ObjectiveWe used evidence-based medicine, bioinformatics and experimental verification to comprehensively analyze the efficacy and pharmacological mechanism of Xuefu Zhuyu decoction (XFZYD) in the treatment of idiopathic pulmonary fibrosis (IPF). MethodsMajor databases were retrieved for randomized controlled trials (RCTs) of XFZYD treating IPF to perform meta-analysis. Active ingredients and target genes of XFZYD were identified from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). IPF-related differentially expressed genes (DEGs) were identified from the Gene Expression Omnibus (GEO) database. The RGUI software was utilized for Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The ingredient-target and protein-protein interaction (PPI) networks were achieved through Cytoscape software and the STRING database to identify the key compounds and target proteins. Molecular docking was performed using AutoDockTool and AutoDock Vina software. The effect between key compounds and target proteins was verified in animal experiments. ResultsSix RCTs were included for meta-analysis, which uncovered that the total effective rate of clinical efficacy was higher in the experimental group than control group. Then, 156 active ingredients and 254 target genes of XFZYD, and 1,566 IPF-related DEGs were identified. The intersection analysis identified 48 target genes correlating with 130 active ingredients of XFZYD treating IPF. GO functional enrichment, KEGG pathway enrichment, ingredient-target network and PPI network were achieved. Following the identification of key compounds and target proteins, we performed molecular docking. Ultimately, our research focused on the key compound quercetin for experimental validation to assess its interactions with two key target proteins, JUN and PTGS2. ConclusionThe effectiveness of XFZYD on IPF has been substantiated through evidence-based medicine. The pharmacological mechanism of XFZYD for IPF treatment involves a complex interplay of various compounds and targets, with quercetin exerting pronounced impacts on JUN and PTGS2 proteins.

Targets and Mechanisms of Resveratrol against Endothelial-Mesenchymal Transition in Atherosclerosis: A Network Pharmacology Analysis Combined with In vivo Experiments

Background: Atherosclerosis (AS) is a chronic inflammatory disease characterized by plaque formation and endothelial dysfunction. Under pro-inflammatory conditions, the endothelial-mesenchymal transition (EndMT) plays an important role in the pathogenesis of AS. Resveratrol (RES) is a natural polyphenol in traditional Chinese medicines, which has been proven to possess anti-AS effects. However, the mechanism of RES treating AS through EndMT is not clear at present. Methods: RES targets were screened using databases such as SwissTargetPrediction and TargetNet, and AS and EndMT targets were searched using databases such as OMIM and DisGeNET. With the help of Venny 2.1, the key targets were selected by intersection. Next, the protein-protein interaction (PPI) network was constructed through the STRING 11.0 platform and Cytoscape software; gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotations were performed using DAVID. Further, Cytoscape was used to construct a drug-component-gene target-pathway network diagram to identify the core components and genes. Subsequently, an AS rat model was established. The blood lipid level of rats was detected by an automatic biochemical analyzer, and the expression level of the target protein was measured by western blotting. Results: Through network pharmacology analysis, 37 potential targets for RES treating AS and EndMT were identified, and the core targets for RES treating AS consisted of AKT1, TNF, MIMP9, and PPARG. GO enrichment analysis indicated that the treatment of AS with RES mainly involved the migration and proliferation of epithelial and endothelial cells. The KEGG pathway enrichment analysis revealed that the enrichment of TNF and Rap1 signaling pathways was most significant. Besides, RES effectively reduced the levels of total cholesterol (TC), triglyceride (TG) and low-density lipoprotein cholesterol (LDL-C) in the serum of AS rats, increased the level of high-density lipoprotein cholesterol (HDL-C), and significantly cut down the atherosclerosis index (AI). Twist1, calponin, α-SMA and VE-cadherin were considered as EndMT indexes. The results of the western blot demonstrated that the protein levels of Twist1, calponin and α-SMA were significantly decreased, while the protein expression level of VE-cadherin was notably increased in rats treated with RES. Moreover, RES could also reduce the expression levels of Rap1 and Epac1 proteins. Conclusion: RES is an effective anti-AS drug. Briefly, RES can effectively improve the blood lipid level of AS patients, regulate the expression of EndMT-related proteins, and alleviate the dysfunction of endothelial cells. Notably, the functions of RES are closely associated with the EPAC1-Rap1 pathway.

189 Association of the liver phosphoproteome with divergent dry matter intake in finishing beef steers

Abstract As the need for improving the sustainability of the beef industry increases, optimizing feed efficiency is of the utmost importance. The liver has a central role in nutrient metabolism, and for ruminants particularly, it is essential for providing glucose through gluconeogenesis via substrates such as propionate, lactate, and glycerol. Further, through cell signaling and vagal afferent signals, the liver acts to stimulate and inhibit dry matter intake (DMI). Thus, the objective of this study was to investigate alterations in the phosphoproteome of finishing beef steers in relation to divergent DMI to identify changes in the abundance of signaling proteins. Angus steers [n = 57; initial body weight (BW) = 518 ± 27 kg] underwent a 63-d intake trial utilizing an Insentec Roughage Intake Control System (Hokofarm Group, Emmeloord, The Netherlands). Prior to beginning the trial, liver biopsy samples were collected from all steers. Samples from steers with the greatest and least DMI (n = 8 each) were utilized for phosphoproteomic analysis. Liver protein was isolated and labeled with isobaric tandem mass tagging reagents. Samples were enriched for phosphopeptides using immobilized metal affinity chromatography and subsequently analyzed using high-performance liquid chromatography tandem mass spectrometry. Spectral data were searched in the National Center for Biotechnology Information Bos taurus protein database using MaxQuant (version 2.2.0.0; Max Planck Inst., Munich, Germany), and the data were analyzed using Perseus (version 2.0.10.0; Max Planck Inst.). Two sample t-tests were conducted to determine the difference in phosphopeptide abundance between steers with high and low DMI. A total of 16,365 phosphopeptides were identified, and 287 were differentially expressed (False Discovery Rate < 0.05). In addition, 2,777 phosphopeptides were differentially expressed based on an unadjusted P < 0.05 which were used for enrichment analysis of Gene Ontology processes and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways using the Database for Annotation, Visualization, and Integrated Discovery. The background for this analysis was all identified phosphopeptides. Gene ontology terms enriched included processes related to phosphorylation activity, intracellular signal transduction, response to insulin, kinase activity, and signaling protein binding. Enriched KEGG pathways included pathways related to insulin signaling, such as AMPK signaling, mTOR signaling, and MAPK signaling. Further, pathways related to glycolysis and gluconeogenesis, glucagon signaling, insulin resistance, carbon metabolism, and various other signaling pathways were also enriched. These results suggest a link between the liver phosphoproteome and DMI, indicating that divergent DMI is associated with alterations in signaling pathways related to nutrient uptake and metabolic processes.

Analysis of action of 1,4-naphthoquinone scaffold-derived compounds against acute myeloid leukemia based on network pharmacology, molecular docking and molecular dynamics simulation

1,4-Naphthoquinone scaffold-derived compounds has shown considerable pharmacological properties against cancer, including acute myeloid leukemia (AML) However, its impact and mechanisms in AML are uncertain. In this study, the mechanisms of 1,4-naphthoquinone scaffold-derived compounds against AML were investigated via network pharmacology, molecular docking and molecular dynamics simulation. ASINEX database was used to collect the 1,4-naphthoquinone scaffold-derived compounds, and compounds were extracted from the software to evaluate their drug similarity and toxicity. The potential targets of compounds were retrieved from the SwissTargetPrediction Database and the Similarity Ensemble Approach Database, while the potential targets of AML were obtained from the GeneCards databases and Gene Expression Omnibus. The STRING database was used to construct a protein–protein interaction (PPI) network, topologically and Cyto Hubb plugin of Cytoscape screen the central targets. After selecting the potential key targets, the gene ontology (GO) function annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed for the intersection targets, and a network map of “compounds-potential targets-pathway-disease” were constructed. Molecular docking of the compounds with the core target was performed, and core target with the strongest binding force and 1,4-naphthoquinone scaffold-derived compounds was selected for further molecular dynamics simulation and further molecular mechanics/Poisson–Boltzmann surface area (MM/PBSA) approach verification. In addition, the Bloodspot database was applied to perform the overall survival of core targets. A total of 19 1,4-naphthoquinone scaffold-derived compounds were chosen out, and then 836 targets of compounds, 96 intersection targets of AML were screened. Core targets include STAT3, TLR4, HSP90AA1, JUN, MMP9, PTPRC, JAK2, PTGS2, KIT and CSF1R. GO functional enrichment analysis revealed that 90 biological processes, 10 cell components and 12 molecular functions were enriched while KEGG pathway enrichment analysis revealed 34 enriched signaling pathways. Analysis of KEGG enrichment hinted that these 10 core genes were located in the pathways in cancer, suggesting that 1,4-naphthoquinone scaffold-derived compounds had potential activity against AML. Molecular docking analysis revealed that the binding energies between 1,4-naphthoquinone scaffold-derived compounds and the core proteins were all higher than − 6 kcal/mol, indicating that the 10 core targets all had strong binding ability with compounds. Moreover, a good binding capacity was inferred from molecular dynamics simulations between compound 7 and MMP9. The total binding free energy calculated using the MM/GBSA approach revealed values of − 6356.865 kcal/mol for the MMP9-7 complex. In addition, Bloodspot database results exhibited that HSP90AA1, MMP9 and PTPRC were associated with overall survival. The findings provide foundations for future studies into the interaction underlying the anti-AML potential of compounds with 1,4-naphthoquinone-based scaffold structures. Compounds with 1,4-naphthoquinone-based scaffold structures exhibits considerable potential in mitigating and treating AML through multiple targets and pathways.

Multi-Omics Analysis Revealed the rSNPs Potentially Involved in T2DM Pathogenic Mechanism and Metformin Response.

The goal of our study was to identify and assess the functionally significant SNPs with potentially important roles in the development of type 2 diabetes mellitus (T2DM) and/or their effect on individual response to antihyperglycemic medication with metformin. We applied a bioinformatics approach to identify the regulatory SNPs (rSNPs) associated with allele-asymmetric binding and expression events in our paired ChIP-seq and RNA-seq data for peripheral blood mononuclear cells (PBMCs) of nine healthy individuals. The rSNP outcomes were analyzed using public data from the GWAS (Genome-Wide Association Studies) and Genotype-Tissue Expression (GTEx). The differentially expressed genes (DEGs) between healthy and T2DM individuals (GSE221521), including metformin responders and non-responders (GSE153315), were searched for in GEO RNA-seq data. The DEGs harboring rSNPs were analyzed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). We identified 14,796 rSNPs in the promoters of 5132 genes of human PBMCs. We found 4280 rSNPs to associate with both phenotypic traits (GWAS) and expression quantitative trait loci (eQTLs) from GTEx. Between T2DM patients and controls, 3810 rSNPs were detected in the promoters of 1284 DEGs. Based on the protein-protein interaction (PPI) network, we identified 31 upregulated hub genes, including the genes involved in inflammation, obesity, and insulin resistance. The top-ranked 10 enriched KEGG pathways for these hubs included insulin, AMPK, and FoxO signaling pathways. Between metformin responders and non-responders, 367 rSNPs were found in the promoters of 131 DEGs. Genes encoding transcription factors and transcription regulators were the most widely represented group and many were shown to be involved in the T2DM pathogenesis. We have formed a list of human rSNPs that add functional interpretation to the T2DM-association signals identified in GWAS. The results suggest candidate causal regulatory variants for T2DM, with strong enrichment in the pathways related to glucose metabolism, inflammation, and the effects of metformin.

Bioinformatics strategy to identify the pathogenesis of intracerebral hemorrhage

Objective: A bioinformatics approach was used to determine the key targets for the pathogenesis of intracerebral hemorrhage (ICH). Methods: Entering "intracerebral hemorrhage " as keywords, we searched for and downloaded ICH-related targets using the GeneCards database. Meanwhile, we collected the relevant targets from cortex through GeneCards database. Then, downloaded data were integrated so as to obtain the intersected genes from the targets between ICH and cortex, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were conducted using R language. Lastly, we map the key genes from protein-protein interaction (PPI) into GO and KEGG so as to acquire hub genes in cortex subjected to ICH injury. Results: After inputting the terms "intracerebral hemorrhage" into GeneCards, 1159 targets were recognized in the GeneCards database, 87465 cortex-related targets were retrieved. Furthermore, 1125 intersected genes were identified through Venny analysis. Subsequently, GO enrichment analysis revealed that these genes are primarily involved in biological processes such as wound healing, regulation of body fluid levels, response to peptides, positive regulation of responses to external stimuli, and cytokine-mediated signaling pathways. KEGG pathway enrichment analysis indicated that these genes are mainly associated with inflammatory pathways, including PI3K-AKT, JAK-STAT, and HIF-1. Conclusions: Our results comprehensively illustrated the potential targets involved in the pathogenesis of ICH, therefore, providing new insights for molecular therapy of ICH in future clinic trial development. Keywords: Bioinformatics; intracerebral hemorrhage (ICH); cortex

Mechanism of mangiferin in the treatment of oral submucous fibrosis based on Gene Expression Omnibus database chip mining combined with network pharmacology and molecular docking.

This study aims to investigate the primary target and potential mechanism of mangiferin (MF) in treating oral submucous fibrosis (OSF) through Gene Expression Omnibus (GEO) database chip mining, network pharmacology, and molecular docking techniques. Potential therapeutic targets for OSF were identified using GEO chip data. The potential targets of MF were predicted, and disease-related targets for OSF were collected from databases. A Venn diagram was created using the EVenn platform to identify overlapping targets. The protein-protein interaction (PPI) network was constructed using the STRING database. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using the DAVID platform. Cytoscape 3.10.1 software was used to visualize a drug-target-pathway-disease network, while AutoDocktools 1.5.6 software was employed for molecular docking analysis. A total of 356 potential targets for MF and 360 disease-related targets for OSF were obtained from multiple databases. The top 15 key target proteins in the PPI network were selected as significant candidates. GO function and KEGG pathway enrichment analyses revealed that MF treatment primarily involved advanced glycation end products-receptor (AGE-RAGE), epidermal growth factor receptor (EGFR), and other signaling pathways associated with OSF pathogenesis. Molecular docking analysis demonstrated that MF exhibited a strong binding activity toward AKT serine kinase 1 (AKT1), tumor necrosis factor (TNF), and other core targets. These findings suggest that MF may exert its therapeutic effects on OSF through a multitarget approach involving various signaling pathways.

Investigating the potential mechanisms of Litsea cubeba essential oil for anti-melanoma through experimental validation, network pharmacology, and molecular docking analysis

Abstract Objectives Melanoma remains a challenge due to the lack of effective and low-toxicity treatments. Litsea cubeba essential oil (LEO), known for its tyrosinase inhibitory activity, has shown promise as an anti-melanoma compound, although robust scientific evidence is lacking. Methods We conducted GC-MS analysis to identify the major components of LEO and screened for effective components were further evaluated on A375 and HaCaT cells using the CCK-8 assay. Network pharmacology was employed to predict potential targets using PharmMapper and SwissTarget Prediction databases, with melanoma-related targets sourced from the GeneCards database. Protein–protein interaction (PPI) network was created using STRING and Cytoscape. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed through the DAVI database. Additionally, we constructed a natural product-main components-core targets-pathways-disease (NMCPD) network in Cytoscape and conducted molecular docking using PyMOL and Autodock Vina. Results GC-MS analysis revealed neral (cis-citral) and geranial (trans-citral) as the primary active components of LEO. Cell assays demonstrated that a citral mixture, in combination with LEO, effectively inhibited A375 cell growth with IC50 values of 35.94 ± 1.23 μM and 12.00 ± 0.96 μg/mL, while exhibiting minimal toxicity to HaCaT cells with IC50 values of 67.72 ± 2.96 μM and 22.32 ± 2.53 μg/mL. Screening identified10 hub targets among 190 common targets between drug and disease-related targets. KEGG pathway enrichment analysis suggested therapeutic effects of citral on melanoma by modulating signaling pathways. Molecular docking revealed strong binding affinity of neral and geranial with RXRA and ESR1, suggesting that citral, the principal LEO component, regulates multiple pathways for potential melanoma therapy. Conclusions These findings support the potential utility of LEO as a treatment for melanoma and highlight the importance of exploring tyrosinase inhibitors for the development of novel anti-melanoma drugs.

Network pharmacology- and molecular docking-based exploration of the molecular mechanism underlying Jianpi Yiwei Recipe treatment of gastric cancer.

Traditional Chinese medicine (TCM) is widely used as an important complementary and alternative healthcare system for cancer treatment in Asian countries. Network pharmacology, which utilizes various database platforms and computer software to study the interactions between complex drug components in vivo, is particularly useful for studying the pharmacodynamic mechanisms of multi-pathway and multi-target Chinese medicines. To explore the potential targets and function of Jianpi Yiwei Recipe treatment of gastric cancer (GC) through network pharmacology and molecular docking. Data on the components of Jianpi Yiwei Recipe (Radix Astragali, Radix Codonopsis, Agrimonia eupatoria, Atractylodes macrocephala Koidz., Poria cocos, stir-baked rhizoma dioscoreae, Amomum villosum Lour., fried Fructus Aurantii, pericarpium citri reticulatae, Rhizoma Pinelliae Preparata, and Radix Glycyrrhizae Preparata) were collected and screened by using the TCM systems pharmacology database and analysis platform (TCMSP). Then the targets of these compounds were predicted. GC-related targets were screened using the GeneCards database. Venn diagram was used to identify common targets. An active ingredient-core target interaction network and a protein-protein interaction (PPI) network were built. Moreover, we performed gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses on the core targets and validated them by molecular docking. TCMSP screening revealed 11 active components and 184 targets, whereas GeneCards found 10118 disease-related targets, with 180 shared targets between them. Topology analysis of the PPI network identified 38 targets, including ATK1, TP53, and tumor necrosis factor, as key targets for the treatment of GC by Jianpi Yiwei Recipe. Quercetin, naringenin, luteolin, etc., may be the main active components of Jianpi Yiwei Recipe. GO enrichment analysis identified 2809, 1218, and 553 functions related to biological process, molecular function, and cellular component, respectively. KEGG pathway enrichment analysis revealed 167 related pathways, mainly involved in cancer, endocrine resistance, and AGE-RAGE signaling in diabetic complication. Validation with molecular docking analysis showed docking of key active components with core targets. Jianpi Yiwei Recipe plays a therapeutic role in GC through multiple components, targets, and pathways. These findings form a basis for follow-up exploration of Jianpi Yiwei Recipe in the treatment of GC.

Network pharmacology and molecular dynamics study of the effect of the Astragalus-Coptis drug pair on diabetic kidney disease.

Diabetic kidney disease (DKD) is the primary cause of end-stage renal disease. The Astragalus-Coptis drug pair is frequently employed in the management of DKD. However, the precise molecular mechanism underlying its therapeutic effect remains elusive. To investigate the synergistic effects of multiple active ingredients in the Astragalus-Coptis drug pair on DKD through multiple targets and pathways. The ingredients of the Astragalus-Coptis drug pair were collected and screened using the TCMSP database and the SwissADME platform. The targets were predicted using the SwissTargetPrediction database, while the DKD differential gene expression analysis was obtained from the Gene Expression Omnibus database. DKD targets were acquired from the GeneCards, Online Mendelian Inheritance in Man database, and DisGeNET databases, with common targets identified through the Venny platform. The protein-protein interaction network and the "disease-active ingredient-target" network of the common targets were constructed utilizing the STRING database and Cytoscape software, followed by the analysis of the interaction relationships and further screening of key targets and core active ingredients. Gene Ontology (GO) function and Kyoto Ency-clopedia of Genes and Genomes (KEGG) pathway enrichments were performed using the DAVID database. The tissue and organ distributions of key targets were evaluated. PyMOL and AutoDock software validate the molecular docking between the core ingredients and key targets. Finally, molecular dynamics (MD) simulations were conducted to simulate the optimal complex formed by interactions between core ingredients and key target proteins. A total of 27 active ingredients and 512 potential targets of the Astragalus-Coptis drug pair were identified. There were 273 common targets between DKD and the Astragalus-Coptis drug pair. Through protein-protein interaction network topology analysis, we identified 9 core active ingredients and 10 key targets. GO and KEGG pathway enrichment analyses revealed that Astragalus-Coptis drug pair treatment for DKD involves various biological processes, including protein phosphorylation, negative regulation of apoptosis, inflammatory response, and endoplasmic reticulum unfolded protein response. These pathways are mainly associated with the advanced glycation end products (AGE)-receptor for AGE products signaling pathway in diabetic complications, as well as the Lipid and atherosclerosis. Molecular docking and MD simulations demonstrated high affinity and stability between the core active ingredients and key targets. Notably, the quercetin-AKT serine/threonine kinase 1 (AKT1) and quercetin-tumor necrosis factor (TNF) protein complexes exhibited exceptional stability. This study demonstrated that DKD treatment with the Astragalus-Coptis drug pair involves multiple ingredients, targets, and signaling pathways. We propose a novel approach for investigating the molecular mechanism underlying the therapeutic effects of the Astragalus-Coptis drug pair on DKD. Furthermore, we suggest that quercetin is the most potent active ingredient and specifically targets AKT1 and TNF, providing a theoretical foundation for further exploration of pharmacologically active ingredients and elucidating their molecular mechanisms in DKD treatment.

Integrated proteomic and metabolomic profiling reveals novel insights on the inflammation and immune response in HFpEF

BackgroundThe precise mechanisms leading to the development of heart failure with preserved ejection fraction (HFpEF) remain incompletely defined. In this study, an integrative approach utilizing untargeted proteomics and metabolomics was employed to delineate the altered proteomic and metabolomic profiles in patients with HFpEF compared to healthy controls.Materials and methodsData were collected from a prospective cohort consisting of 30 HFpEF participants and 30 healthy controls, matched by gender and age. plasma samples were analyzed by multi-omics platforms. The quantification of plasma proteins and metabolites was performed using data-independent acquisition-based liquid chromatography-tandem mass spectrometry (LC-MS/MS) and ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS), respectively. Additionally, Proteomic and metabolomic results were analyzed separately and integrated using correlation and pathway analysis. This was followed by the execution of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment studies to elucidate the biological relevance of the observed results.ResultsA total of 46 significantly differentially expressed proteins (DEPs) and 102 differentially expressed metabolites (DEMs) were identified. Then, GO and KEGG pathway enrichment analyses were performed by DEPs and DEMs. Integrated analysis of proteomics and metabolomics has revealed Tuberculosis and African trypanosomiasis pathways that are significantly enriched and the DEPs and DEMs enriched within them, are associated with inflammation and immune response.ConclusionsIntegrated proteomic and metabolomic analyses revealed distinct inflammatory and immune response pathways in HFpEF, highlighting novel therapeutic avenues.

Effects and Mechanism of Morinda Officinalis How on Metabolism-Associated Fatty Liver Disease.

This study aims to investigate the effects and mechanism of Morinda Officinalis How (MOH), a lianoid shrub with potential therapeutic properties, on Metabolism- Associated Fatty Liver Disease (MAFLD). bjective: The objective of this study was to construct a MOH-MAFLD network prediction model and explore the effect of MOH on MAFLD and its underlying mechanism in vivo. Screening of MAFLD targets was performed using the DisGeNET database. Venny database was used to establish the MOH-MAFLD interaction network map, while the STRING database was applied to assess the Protein-Protein Interaction (PPI) network. The central target gene was screened using Gene Ontology (GO) function analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. GO function enrichment analysis revealed that MOH affected MAFLD through apoptosis and estrogen-related pathways. KEGG pathway enrichment and PPI network analysis indicated that MOH might mitigate MAFLD by reducing apoptosis and improving lipid metabolism. Additionally, 6 weeks of MOH treatment in rats decreased caspase-3 levels and increased Bcl-2, Estrogen receptor α(Esr1), and JUN proteins, thus ameliorating MAFLD progression. MOH could delay the progression of MAFLD by affecting estrogen-related pathways, reducing cell stress, and inhibiting apoptosis.

Preliminary study of metabonomic changes during the progression of atherosclerosis in miniature pigs.

To explore potential biomarkers for early diagnosis of atherosclerosis (AS) and provide basic data for further research on AS, the characteristics of serum metabolomics during the progression of AS in mini-pigs were observed dynamically. An AS model in Bama miniature pigs was established by a high-cholesterol and high-fat diet. Fasting serum samples were collected monthly for metabolomics and serum lipid detection. At the end of the treatment period, pathological analysis of the abdominal aorta and coronary artery was performed to evaluate the lesions of AS, thereby distinguishing the susceptibility of mini-pigs to AS. The metabolomics was detected using a high-resolution untargeted metabolomic approach. Statistical analysis was used to identify metabolites associated with AS susceptibility. Based on pathological analysis, mini-pigs were divided into two groups: a susceptible group (n = 3) and a non-susceptible group (n = 6). A total of 1318 metabolites were identified, with significant shifting of metabolic profiles over time in both groups. Dynamic monitoring analysis highlighted 57 metabolites that exhibited an obvious trend of differential changes between two groups with the advance of time. The KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis indicated significant disorders in cholesterol metabolism, primary bile acid metabolism, histidine metabolism, as well as taurine and hypotaurine metabolism. During the progression of AS in mini-pigs induced by high-cholesterol/high-fat diet, the alterations in serum metabolic profile exhibited a time-dependent pattern, accompanied by notable disturbances in lipid metabolism, cholesterol metabolism, and amino acid metabolism. These metabolites may become potential biomarkers for early diagnosis of AS.

Network Pharmacology, Molecular Docking, and Experimental Validation of the Mechanism of Jiedu Xiaoliu Formula against Diffuse Large B-Cell Lymphoma.

Diffuse Large B-Cell Lymphoma (DLBCL) is the most common Bcell lymphoma type. Detoxification and tumor elimination formula, a herbal compound, can potentially treat lymphoma. In this study, network pharmacology and molecular docking approaches were utilized to reveal the potential mechanism of the Jiedu Xiaoliu formula (JDXLF) against DLBCL. Active compounds and targets of JDXLF were obtained from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. Targets related to DLBCL were retrieved from GeneCards and Online Mendelian Inheritance in Man (OMIM) databases. Protein- Protein Interaction (PPI) networks were established to screen core targets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using R 4.2.2. Model interactions between potential disease targets and pharmacologically active compounds were determined by molecular docking. Screening of 14 herbal active ingredients yielded 129 active compounds and 1414 disease targets for DLBCL. GO annotations showed that the effects of JDXLF were related to protein phosphorylation and reactive oxygen species response. KEGG pathway enrichment analysis indicated that the detoxification and elimination of tumors formula mainly regulated apoptosis pathways. Nobiletin showed good interaction with AKT1, TP53, and CASP3, and the cell counting kit-8 (CCK-8) assay confirmed that nobiletin inhibited the proliferation of SU-DHL-4 cells. Western blot analysis showed that nobiletin downregulated the expressions of p-PI3K, p- AKT, and BCL-2 proteins and upregulated those of cleaved-caspase3 and BAX. Our findings preliminarily suggested that the active ingredient of JDXLF, nobiletin, may induce apoptosis in Diffuse Large B-Cell Lymphoma SU-DHL-4 cells by regulating the PI3K/AKT signaling pathway.

CD1d affects the proliferation, migration, and apoptosis of human papillary thyroid carcinoma TPC-1 cells via regulating MAPK/NF-κB signaling pathway.

The study aimed to investigate the effect of CD1d down-regulation on the proliferation, migration, and apoptosis of papillary thyroid carcinoma cells and explore the underlying mechanism. CD1d expression was silenced in TPC-1 cells by transfection of CD1d siRNA lentivirus. The proliferation, apoptosis rate, and migration ability of TPC-1 cells were detected by CCK-8 assay, flow cytometry, and scratch assay, respectively. Western blot and qPCR analyses were performed to detect the expression of related proteins. CD1d was highly expressed in TPC-1 cells. Down-regulation of CD1d significantly decreased ALMS1, CDKN3, CDK6, Ki-67, Bcl2 expression, increased Bax and Caspase 3 expression (all P < 0.05), and decreased the migration ability of TPC-1 cells. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed to identify the relevant signaling pathways. KEGG pathway enrichment analysis showed that the differentially expressed genes were mainly enriched in MAPK and NF-κB signaling pathways. Our findings suggest that CD1d down-regulation inhibited the proliferation and migration abilities of TPC-1 cells, increased cell apoptosis possibly via the MAPK/NF-κB signaling pathway.

Transcriptome analysis of Kunming mice responses to the bite of Xenopsylla cheopis

BackgroundFlea bites could trigger a series of complex molecular responses in the host. However, our understanding of the responses at the molecular level is still relatively limited. This study quantifies the changes in gene expression in mice after flea bites by RNA sequencing (RNA-seq) from their spleens, revealing the potential biological effects of host response to flea bites.MethodsRNA-seq was used for transcriptome analysis to screen for differentially expressed genes (DEGs) between the control mice group and the flea bite mice group. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed on DEGs. Protein–protein interaction (PPI) network analysis on DEGs related to immune processes was performed. Finally, we randomly selected several genes from the screened DEGs to validate the results from the transcriptome data by real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR).ResultsA total of 521 DEGs were identified, including 277 upregulated and 244 downregulated. There were 258 GO terms significantly enriched by upregulated DEGs and 419 GO terms significantly enriched by downregulated DEGs. Among the upregulated DEGs, 22 GO terms were associated with immune cells (e.g., B cells and T cells) and immune regulatory processes, while among the downregulated DEGs, 58 GO terms were associated with immune cells and immune regulatory processes. Through PPI analysis, we found that CD40 molecules with significantly downregulated expression levels after flea bites may play an important role in host immune regulation. Through KEGG pathway enrichment analysis, a total of 26 significantly enriched KEGG pathways were identified. The RT-qPCR analysis results indicated that the transcriptome sequencing results were reliable.ConclusionsThrough in-depth analysis of transcriptome changes in mice caused by flea bites, we revealed that flea bites could stimulate a series of biological and immunological responses in mice. These findings not only provided a deeper understanding of the impact of flea bites on the host but also provided a basis for further research on the interaction between ectoparasites and the host. We believe that digging deeper into the significance of these transcriptome changes will help reveal more about the adaptive response of the host to ectoparasites.Graphical

Potential Mechanism by which Eriodictyol Protects against Doxorubicininduced Cardiotoxicity based on Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation

Background: The clinical use of doxorubicin (DOX), an anthracycline antibiotic with broad-spectrum applications against various malignant tumors, is limited by doxorubicininduced cardiotoxicity (DIC). Eriodictyol (ERD) has shown cardioprotective effects, but the mechanism of its protective effect on DIC remains unknown. Aims: This study aimed to explore the potential mechanisms by which ERD confers protection against DIC. Methods: ERD and DIC targets were identified from the TCMSP, PharmMaper, SwissTargetPrediction, TargetNet, BATMAN, GeneCards, and PharmGKB databases. Differential gene expression data between DIC and normal tissues were extracted from the GEO database. A protein‒ protein interaction (PPI) network of the intersecting ERD-DIC targets was constructed using the STRING platform and visualized with Cytoscape 3.10.0 software. Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for ERD-DIC cross-targets were conducted. Validation included molecular docking with AutoDock Tools software and molecular dynamics simulations with Gromacs 2019.6 software. Results: Network pharmacology analysis revealed 43 intersecting ERD-DIC targets, including 6 key targets. GO functional enrichment analysis indicated that the intersecting targets were enriched in 550 biological processes, 45 cell components, and 41 molecular functions. KEGG pathway enrichment analysis identified 114 enriched signaling pathways. Molecular docking revealed a strong binding affinity between ERD and 6 key targets, as well as multiple targets within the ROS pathway. Molecular dynamics simulations indicated that ERD has favorable binding with 3 crucial targets. Conclusion: The systematic network pharmacology analysis suggests that ERD may mitigate DIC through multiple targets and pathways, with the ROS pathway potentially playing a crucial role. These findings provide a reference for foundational research and clinical applications of ERD in treating DIC. conclusion: Systematic network pharmacology analysis suggests that ERD may mitigate DIC through multiple targets and pathways, with the ROS pathway potentially playing a crucial role. These findings provide references for foundational research and clinical applications of ERD in treating DIC.