Kyoto Encyclopedia Of Genes And Genomes Pathway Analysis Research Articles

Integrative Bioinformatics and Experimental Analysis of Curcumin's Role in Regulating Ferroptosis to Combat Osteoporosis

This study utilized bioinformatics and data mining techniques to explore the molecular mechanism of curcumin in treating osteoporosis (OP) through the lens of ferroptosis, thereby identifying novel therapeutic targets. The datasets GSE35958, GSE35956, GSE7429, and GSE7158 were obtained from the Gene Expression Omnibus (GEO) database. GSE35958 and GSE35956 were employed as training sets for data integration, while GSE7429 and GSE7158 served as independent validation sets. Through retrieval from the FerrDb database, iron death-related genes (FRGs) were identified, and the differentially expressed genes (DEGs) were intersected to obtain differentially expressed FRGs (DEFRGs). Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted, followed by the construction of a Protein-Protein Interaction (PPI) network to identify Hub genes. The DGIdb database was utilized to predict candidate drugs associated with the Hub genes, and molecular docking and in vitro experiments confirmed that curcumin targets the Hub genes EGFR and PTGS2.Through in vitro testing of curcumin on BMSC cells, researchers examined cell vitality, iron death, osteogenic differentiation, mineralization, and the impact on EGFR and PTGS2 levels. The analysis yielded 2212 DEGs, 484 FRGs, with 45 FDEGs at the intersection. GO analysis revealed involvement in regulating mitochondrial proteins, amino acid transport across plasma membranes, and protein ubiquitination. KEGG pathway analysis indicated associations with iron death, FoxO signaling, mTOR signaling, cell aging, osteoclast differentiation, and GSH metabolism. Utilizing the MCC algorithm, five Hub genes were identified: MAPK3, PTGS2, TGFB1, CYBB, and EGFR, showing diagnostic potential for iron death. Curcumin displayed affinity for EGFR and PTGS2, mitigating iron-induced effects on BMSCs such as increased reactive oxygen species, Fe3+ levels, and decreased mitochondrial membrane potential. Furthermore, curcumin reversed these effects, suggesting EGFR and PTGS2 as targets for curcumin to inhibit BMSC ferroptosis and potentially delay osteoporosis development. Maintaining iron homeostasis and targeting BMSC ferroptosis could offer therapeutic avenues for iron overload-induced osteoporosis.

Unveiling the efficacy and mechanism of Danggui-Shaoyao-San in treating nephrotic syndrome: A meta-analysis and network pharmacology study

Aim of the studyThe purpose of this study was to investigate the efficacy and mechanism of DSS in treating nephrotic syndrome through meta-analysis and network pharmacology methods. Materials and methodsTo conduct a comprehensive search for randomized controlled trials on the efficacy of Danggui Shaoyao San (DSS) in the treatment of nephrotic syndrome, we searched across eight electronic databases from their establishment to May 1, 2023. The Cochrane Collaboration's Risk of Bias 2 tool was used to evaluate the quality of evidence regarding bias risk and outcomes. Statistical analysis was performed using RevMan software (version 5.4). Furthermore, network pharmacology was employed to validate the underlying mechanism. ResultsThis study included 14 articles that involved 1256 patients with nephrotic syndrome. The clinical efficacy of DSS against nephrotic syndrome was significantly higher than that of Western medical treatment alone. In comparison with the control groups, which were administered Western medicines alone, the use of DSS significantly increased plasma albumin levels (mean difference [MD] = 4.32, 95 % confidence interval [CI] [2.37, 6.24], p < 0.00001) and reduced 24 h urinary protein excretion (MD = −0.92, 95 % CI [−1.11, −0.73], p < 0.00001), total cholesterol levels (MD = −1.23, 95 % CI [−1.76, −0.70], p < 0.00001), triglyceride levels (MD = −0.37, 95 % CI [−0.54, −0.20], p < 0.00001). Furthermore, the combination of DSS with Western medicines achieved better control of adverse reactions in comparison with the control groups (relative risk = 0.37, 95 % CI [0.29, 0.49], p < 0.00001). Network pharmacology analysis identified 39 important active compounds and 18 core target genes involved in the treatment of primary nephrotic syndrome by DSS. Gene Ontology enrichment analysis identified 2126 biological processes, 64 cellular components, and 115 molecular functions, while Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis identified 149 signaling pathways. Key active compounds include ginsenoside Rg5, ginsenoside Rg1, schisandrin A, berberine, gallic acid, quercetin, and β-sitosterol, while potential core target genes include IL6, AKT1, TNF, VEGFA, IL1B, and TP53. KEGG pathway analysis indicated that DSS is involved in multiple mechanisms, such as neural development, synaptic plasticity, programmed cell death, inflammation, and immunity. ConclusionsDSS has higher efficacy and safety in the treatment of nephrotic syndrome and acts on nephrotic syndrome via mechanisms that involve multiple targets, components, and pathways.

Non-coding RNA alterations in occlusal disharmony-induced anxiety-like behaviour.

Occlusal disharmony (OD) may induce anxiety-like behaviours; however, the underlying mechanism remains unclear. Herein, we explored the expression profiles of non-coding RNAs (ncRNAs), along with their biological function and regulatory network, in anxiety-like behaviour induced by OD. Occlusal disharmony was produced by anterior crossbite of C57BL/6 mice. Behavioural tests, corticosterone (CORT) and serotonin (5-HT) levels were used to measure anxiety. In addition, RNA sequencing was used to screen all differentially expressed (DE) ncRNAs. Moreover, the RNA-binding proteins interacting with ncRNAs were predicted by the ENCORI database and confirmed using western blots. The significant differences in behavioural tests and CORT suggested the successful induction of anxiety-like behaviour by OD. In OD mice, ncRNAs were significantly dysregulated. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses suggested that the DE ncRNAs were enriched in anxiety-related pathways. CircRNA10039 was upregulated, and PTBP1 was predicted to interact with circRNA10039. In addition, KEGG pathway analysis showed that PTBP1 may be associated with messenger RNA biogenesis and spliceosomes. OD induced by anterior crossbite can lead to the anxiety-like behaviours. During this process, ncRNA also changes. CircRNA10039 and PTBP1 may play a role in OD-induced anxiety-like behaviours.

Exploring the mechanisms of Cornus officinalis in the treatment of non-alcoholic steatohepatitis using network pharmacology, molecular docking and molecular dynamics simulations

Non-alcoholic steatohepatitis (NASH) is a predominant metabolic liver disease, typically characterized by hepatic steatosis, oxidative stress, and inflammation. The traditional Chinese medicine Cornus officinalis possesses anti-inflammatory and hepatoprotective pharmacological properties and has shown ameliorative effects on NASH. however, its mechanism of action remains unclear. This study aims to elucidate the mechanisms by which C. officinalis ameliorates NASH. The active components of C. officinalis were analyzed using the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP), and the corresponding targets were predicted. Subsequently, the DisGeNET, GeneCards, and GEO databases were employed to identify NASH-related targets. Venn diagrams were used to intersect the C. officinalis targets with the NASH targets. Protein–protein interaction (PPI) networks were constructed using the STRING database, and PPI network analysis was performed using Cytoscape. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted using the Database for Annotation, Visualization, and Integrated Discovery (DAVID), followed by molecular docking validation. Cornus officinalis was found to contain 20 major active ingredients corresponding to 672 potential targets, 61 of which overlapped with NASH targets. PPI network, GO, and KEGG pathway analyses identified four targets with the highest correlation, and molecular docking results indicated that the active ingredients of C. officinalis exhibited strong binding affinities to NASH targets. The treatment of NASH with C. officinalis is characterized by multiple active ingredients and multiple targets, underscoring the major advantage of traditional Chinese medicine in treating NASH.

Research on the Regulatory Mechanism of Ginseng on the Tumor Microenvironment of Colorectal Cancer based on Network Pharmacology and Bioinformatics Validation.

A network pharmacology study on the biological action of ginseng in the treatment of colorectal cancer (CRC) by regulating the tumor microenvironment (TME). To investigate the potential mechanism of action of ginseng in the treatment of CRC by regulating TME. This research employed network pharmacology, molecular docking techniques, and bioinformatics validation. Firstly, the active ingredients and the corresponding targets of ginseng were retrieved using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), the Traditional Chinese Medicine Integrated Database (TCMID), and the Traditional Chinese Medicine Database@Taiwan (TCM Database@Taiwan). Secondly, the targets related to CRC were retrieved using Genecards, Therapeutic Target Database (TTD), and Online Mendelian Inheritance in Man (OMIM). Tertiary, the targets related to TME were derived from screening the GeneCards and National Center for Biotechnology Information (NCBI)-Gene. Then the common targets of ginseng, CRC, and TME were obtained by Venn diagram. Afterward, the Protein-protein interaction (PPI) network was constructed in the STRING 11.5 database, intersecting targets identified by PPI analysis were introduced into Cytoscape 3.8.2 software cytoHubba plugin, and the final determination of core targets was based on degree value. The OmicShare Tools platform was used to analyze the Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the core targets. Autodock and PyMOL were used for molecular docking verification and visual data analysis of docking results. Finally, we verified the core targets by Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) databases in bioinformatics. A total of 22 active ingredients and 202 targets were identified to be closely related to the TME of CRC. PPI network mapping identified SRC, STAT3, PIK3R1, HSP90AA1, and AKT1 as possible core targets. Go enrichment analysis showed that it was mainly involved in T cell co-stimulation, lymphocyte co-stimulation, growth hormone response, protein input, and other biological processes; KEGG pathway analysis found 123 related signal pathways, including EGFR tyrosine kinase inhibitor resistance, chemokine signaling pathway, VEGF signaling pathway, ErbB signaling pathway, PD-L1 expression and PD-1 checkpoint pathway in cancer, etc. The molecular docking results showed that the main chemical components of ginseng have a stable binding activity to the core targets. The results of the GEPIA database showed that the mRNA levels of PIK3R1 were significantly lowly expressed and HSP90AA1 was significantly highly expressed in CRC tissues. Analysis of the relationship between core target mRNA levels and the pathological stage of CRC showed that the levels of SRC changed significantly with the pathological stage. The HPA database results showed that the expression levels of SRC were increased in CRC tissues, while the expression of STAT3, PIK3R1, HSP90AA1, and AKT1 were decreased in CRC tissues. Ginseng may act on SRC, STAT3, PIK3R1, HSP90AA1, and AKT1 to regulate T cell costimulation, lymphocyte costimulation, growth hormone response, protein input as a molecular mechanism regulating TME for CRC. It reflects the multi-target and multi-pathway role of ginseng in modulating TME for CRC, which provides new ideas to further reveal its pharmacological basis, mechanism of action and new drug design and development.

Exploring the therapeutic potential of Xiangsha Liujunzi Wan in Crohn's disease: from network pharmacology approach to experimental validation

Ethnopharmacological relevanceXiangsha Liujunzi Wan (LJZW) is a traditional Chinese medicine (TCM) formula containing a variety of traditional Chinese herb components. Its principal components are often used in the treatment of gastrointestinal diseases and contribute to the treatment of Crohn's disease (CD). Aim of the studyTo explore the therapeutic potential of LJZW in CD through network pharmacology, bioinformatics, molecular docking, and experimental verification. MethodsThe principal bioactive components and corresponding targets of LJZW were ascertained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Potential targets for CD were identified in GeneCards, OMIM, DrugBank, DisGeNET, CTD, and Gene Expression Omnibus (GEO) databases. Intersection targets of LJZW and CD were identified using a Venn diagram and visualized using Cytoscape 3.8.0 to construct a protein-protein interaction (PPI) network. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were employed to assess the function of intersection targets. AutoDockTools and PyMOL were used for molecular docking to recognize the association between the core ingredients of LJZW and the core targets of CD. Subsequently, a series of experiments were conducted for validation. ResultsThe network pharmacology results indicated that there were 156 bioactive components and 268 corresponding targets for LJZW, 3023 primary relevant targets for CD, and 169 intersection targets for LJZW and CD. The PPI network was employed to identify five hub genes and six clusters. The GO functional analysis indicated that intersection targets are primarily correlated with oxidative stress and inflammatory responses. KEGG pathway analysis revealed that these targets were primarily associated with the phosphotylinosital 3 kinase (PI3K)-protein kinase B (AKT) and mitogen-activated protein kinase (MAPK) signaling pathways. The molecular docking results showed that the core ingredients of LJZW had good binding ability with the core targets of CD. A series of experiments demonstrated that LJZW could effectively attenuate TNBS-induced colitis symptoms, inhibit the inflammatory response, and protect intestinal barrier function by inhibiting the PI3K-AKT and MAPK signaling pathways, thus preventing and treating CD. ConclusionLJZW has the characteristics of multi-component, multi-target, and multi-pathway treatment, which helps to improve the treatment of CD, protect the intestinal barrier, and exert the effect of anti-inflammatory therapy by inhibiting PI3K-AKT and MAPK signaling pathways.

A Proteomic Analysis of Nasopharyngeal Carcinoma in a Moroccan Subpopulation.

Nasopharyngeal carcinoma (NPC) is a distinct cancer of the head and neck that is highly prevalent in Southeast Asia and North Africa. Though an extensive analysis of environmental and genetic contributors has been performed, very little is known about the proteome of this disease. A proteomic analysis of formalin-fixed paraffin-embedded (FFPE) tissues can provide valuable information on protein expression and molecular patterns for both increasing our understanding of the disease and for biomarker discovery. To date, very few NPC proteomic studies have been performed, and none focused on patients from Morocco and North Africa. Label-free Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) was used to perform a proteomic analysis of FFPE tissue samples from a cohort of 41 NPC tumor samples of Morocco and North Africa origins. The LC-MS/MS data from this cohort were analyzed alongside 21 healthy controls using MaxQuant 2.4.2.0. A differential expression analysis was performed using the MSstats package in R. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional annotations were carried out using the DAVID bioinformatic tool. 3341 proteins were identified across our NPC cases, revealing three main clusters and five DEPs with prognostic significance. The sex disparity of NPC was investigated from a proteomic perspective in which 59 DEPs were found between males and females, with significantly enriched terms associated with the immune response and gene expression. Furthermore, 26 DEPs were observed between patients with early and advanced stages of NPC with a significant cluster related to the immune response, implicating up-regulated DEPs such as IGHA, IGKC, and VAT1. Across both datasets, 6532 proteins were quantified between NPC patients and healthy controls. Among them, 1507 differentially expressed proteins (DEPs) were observed. GO and KEGG pathway analyses showed enriched terms of DEPs related to increased cellular activity, cell proliferation, and survival. PI3K and MAPK proteins as well as RAC1 BCL2 and PPIA were found to be overexpressed between cancer tissues and healthy controls. EBV infection was also one of the enriched pathways implicating its latent genes like LMP1 and LMP2 that activate several proteins and signaling pathways including NF-Kappa B, MAPK, and JAK-STAT pathways. Our findings unveil the proteomic landscape of NPC for the first time in the Moroccan population. These studies additionally may provide a foundation for identifying potential biomarkers. Further research is still needed to help develop tools for the early diagnosis and treatment of NPC in Moroccan and North African populations.

Double-negative T cells with a distinct transcriptomic profile are abundant in the peripheral blood of patients with breast cancer.

Double-negative T (DNT) cells comprise a distinct subset of T lymphocytes that have been implicated in immune responses. The aim of this study was to characterize the peripheral DNT population in breast cancer (BC) patients. DNT cells were isolated from the peripheral blood samples of BC patients and healthy controls by flow cytometry. The sorted DNT cells were analyzed by the Smart-seq2 for single-cell full-length transcriptome profiling. The differentially expressed genes (DEGs) between the BC and control groups were screened and functionally annotated by Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses using R. The protein-protein interaction (PPI) network of the DEGs was constructed using the CytoHubba and MCODE plug-in of Cytoscape software to identify the core genes. Survival status, DNA methylation level, immune infiltration and immune checkpoint expression were analyzed using Kaplan-Meier Plotter, UALCAN, MethSeuvr, TIMER, and TISIDB respectively. The sequencing results were verified by RT-qPCR. The percentage of DNT cells was higher in the BC patients compared to healthy controls. We identified 289 DEGs between the DNT populations of both groups. GO and KEGG pathway analyses revealed that the DEGs were mainly related to immunoglobulin mediated immune response, complement activation, and B cell receptor signaling. The PPI networks of the common DEGs were constructed using Cytoscape, and 10 core genes were identified, including TMEM176B, C1QB, C1QC, RASD2, and IFIT3. The expression levels of these genes correlated with the prognosis and immune infiltration in BC patients, and were validated by RT-qPCR (P < 0.05). DNT cells are abundant in patients with BC, and might exert anti-tumor immune responses by regulating genes such as TMEM176B and EGR1.

The breast cancer biomarkers associated with the development of the disease; an in-silico-based study

Introduction: Breast cancer (BC) is among the top causes of mortality among women worldwide. Identifying genes by differential expression associated with the development of the disease helps us to better understanding the molecular mechanisms of BC. Objectives: Our study used in-silico analysis to identify hub genes could trigger the development of BC. Materials and Methods: We identified GSE38959 and GSE45827 for differentially expressed genes (DEGs) in the Gene Expression Omnibus (GEO) database, with an adjusted P&lt;0.05. In both sets, logFC ≥ 2 and logFC ≤ -2 were observed in the DEGs that express themselves within cases and normal BC samples. A comparison was then performed, detecting two common datasets of DEGs using the GEO2R tool. Pathways were elucidated using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology databases. Thereafter, protein-protein interactions (PPIs) were analyzed using Cytoscape and Gephi. Finally, a GEPIA analysis was conducted to validate the target genes. Results: Using the GEO, 322 common DEGs were identified and 65 hub genes as PPIs. The DEGs were enriched in functions associated with cell division, chromosomes, centromeric regions, microtubule binding, and the cell cycle based on the gene ontology (GO) and KEGG pathways analysis. The expression of 6 genes, CDK1, CCNB1, TOP2A, CXCL12, IGF1, and KIT, represented statistically significant values when the normal and tumor samples were compared via GEPIA analysis. Conclusion: This study introduced six genes (CDK1, CCNB1, TOP2A, CXCL12, IGF1, and KIT) with high expression significantly, which could act as a biomarker for BC development (P&lt;0.05 for all genes). Further comprehensive experimental in vivo studies are needed to describe their role in BC.

New molecular mechanisms of quercetin in improving recurrent spontaneous abortion based on in-depth network pharmacology and molecular docking.

The increasing prevalence of recurrent spontaneous abortion (RSA) poses significant physical and psychological challenges for affected individuals. Quercetin, a natural plant flavonoid, shows promise in reducing miscarriage rates, yet its precise mechanism remains elusive. This study uses network pharmacology, molecular docking, and experimental validation to explore the molecular pathways through which quercetin mitigates RSA. Quercetin-related target genes were sourced from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and RSA target genes were retrieved from the Comparative Toxicogenomics Database (CTD), with overlapping targets identified using Venn diagrams. All genes were visualized using the STRING database, and core targets were selected with Cytoscape 3.7.3. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted using the DAVID and Reactome online resources. Subsequently, HTR-8/SVneo cells were stimulated with lipopolysaccharide (LPS) and treated with varying concentrations of quercetin (1, 5, and 10μM), then subjected to CCK-8, wound healing, transwell, and annexin V-FITC/PI apoptosis assays. Reverse-transcription quantitative PCR was used to determine the mRNA expression levels of IL-1β, TNF-α, and IL-6 in LPS-induced cells post-quercetin intervention, and western blotting was used to measure AKT1, MMP9, and caspase-3 protein levels. A total of 139 quercetin-associated target genes were identified from the TCMSP database, and 98 disease-associated target genes were obtained from the CTD, resulting in 25 shared target genes. Gene ontology enrichment highlighted the involvement of these targets in positive regulation of apoptosis, response to hypoxia, and intrinsic apoptotic signaling pathway in response to DNA damage. KEGG pathway analysis indicated enrichment in pathways related to interleukin-4 and interleukin-13 signaling, cytokine signaling in the immune system, and apoptosis. Molecular docking studies revealed robust binding of quercetin with MMP9, AKT1, IL-1β, TNF, and caspase-3. In vitro experiments demonstrated that quercetin enhanced LPS-induced cell activity, fostering proliferation, migration, and invasion, and reducing apoptosis. Moreover, quercetin reduced IL-1β, TNF-α, and IL-6 mRNA expression, increased AKT1 and MMP9 protein levels, and reduced caspase-3 expression. Quercetin could mitigate the incidence of RSA by modulating inflammatory responses and apoptotic processes, through upregulation of AKT1 and MMP9, and downregulation of caspase-3, IL-1β, TNF-α, and IL-6. Quercetin opens up a new way of thinking about treating RSA.

Identification of LINC02454-related key pathways and genes in papillary thyroid cancer by weighted gene coexpression network analysis (WGCNA)

BackgroundOur previous study demonstrated that long intergenic noncoding RNA 02454 (LINC02454) may act as an oncogene to promote the proliferation and inhibit the apoptosis of papillary thyroid cancer (PTC) cells. This study was designed to investigate the mechanisms whereby LINC02454 is related to PTC tumorigenesis.MethodsThyroid cancer RNA sequence data were obtained from The Cancer Genome Atlas (TCGA) database. Weighted gene coexpression network analysis (WGCNA) was applied to identify modules closely associated with PTC. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was used to identify the key pathways, and the maximal clique centrality (MCC) topological method was used to identify the hub genes. The Gene Expression Profiling Interactive Analysis (GEPIA) database was used to compare expression levels of key genes between PTC samples and normal samples and explore the prognostic value of key genes. The key genes were further validated with GEO dataset.ResultsThe top 5000 variable genes were investigated, followed by an analysis of 8 modules, and the turquoise module was the most positively correlated with the clinical stage of PTC. KEGG pathway analysis found the top two pathways of the ECM − receptor interaction and MAPK signaling pathway. In addition, five key genes (FN1, LAMB3, ITGA3, SDC4, and IL1RAP) were identified through the MCC algorithm and KEGG analysis. The expression levels of the five key genes were significantly upregulated in thyroid cancer in both TCGA and GEO datasets, and of these five genes, FN1 and ITGA3 were associated with poor disease-free prognosis.ConclusionsOur study identified five key genes and two key pathways associated with LINC02454, which might shed light on the underlying mechanism of LINC02454 action in PTC.

Integrative Network Pharmacology Unveils Limonia acidissima as a Potential Natural Product for Targeting Cancer

Cancer remains a formidable health challenge worldwide, with complex molecular mechanisms driving its initiation, progression, and therapeutic resistance. In this study, we employed bioinformatics analyses to elucidate the molecular underpinnings of cancer biology, focusing on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Our GO analysis revealed the enrichment of key biological processes such as protein phosphorylation, regulation of programmed cell death, and transmembrane receptor signaling pathways, underscoring the critical roles of signaling cascades and regulatory mechanisms in tumorigenesis. Similarly, molecular functions such as protein kinase activity and ATP binding were identified as significantly enriched, highlighting the importance of protein kinases and molecular interactions in cancer development and progression. The KEGG pathway analysis further delineated dysregulated signaling pathways associated with cancer, including the MAPK and PI3K-Akt signaling pathways, implicating these pathways as central regulators of cancer progression. These findings deepen our understanding of cancer biology and offer potential targets for therapeutic intervention. Integrating multi-omics data and systems biology approaches may provide deeper insights into the intricate networks underlying cancer pathogenesis, paving the way for developing more effective treatments for cancer patients.

Mechanisms of Luteolin Against Gastro-Esophageal Reflux Disease Based on Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation.

Luteolin is a naturally occurring flavonoid. The effectiveness of luteolin-rich drugs in treating gastro-esophageal reflux disease (GERD) through traditional Chinese medicine has been demonstrated. This study aimed to identify the potential targets and mechanisms of action of luteolin for the treatment of GERD. An innovative approach combining network pharmacology and molecular dynamics was used to explore the potential therapeutic mechanisms of luteolin and to facilitate the further development of GERD treatment. Drug and disease target information was screened from public databases to obtain 159 intersecting targets through the construction of Venn diagrams. Subsequently, a protein‒protein interaction (PPI) network was constructed, and 10 core targets were identified. Through Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, relevant biological processes, cellular components, and molecular functions related to the treatment of GERD were identified and revealed. KEGG pathway analyses showed enrichment of signaling pathways, including the TNF, IL-17, NF-kappa B, and Toll-like receptor pathways. The molecular docking results indicated that luteolin can effectively bind to 10 core targets. Finally, molecular dynamics simulations confirmed the formation of stable protein‒ligand complexes when IL6 binds to luteolin. In conclusion, network pharmacology, molecular docking, and molecular dynamics simulations were utilized to investigate the mechanism by which luteolin treats GERD. These findings establish a theoretical foundation for future research on the efficacy of luteolin in treating GERD.

Bioinformatics deciphers the thebaine biosynthesis pathway in opium poppy: Hub genes, network analysis, and miRNA regulation

Thebaine, a vital precursor in the codeine and morphine pathway, shows promise in addiction treatment. We conducted a comprehensive study on the thebaine biosynthesis pathway in opium poppy, utilizing bioinformatics tools. The dataset comprising the thirteen genes associated with the thebaine biosynthesis pathway was compiled from an extensive review of published literature and validated using the NCBI BLAST tool. Utilizing STRING and Cytoscape, we analyzed gene interactions and visualized the molecular interaction network, respectively. To identify hub proteins, CytoHubba was administered. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) at STRING were used for the enrichment analysis of the hub genes. CytoCluster was used to analyze the network in clusters. Promoter regions of hub genes and potential miRNAs were explored using MEME and the psRNATarget database. Hub genes crucial to thebaine biosynthesis were identified, contributing to essential cellular functions like growth, development, stress response, and signal transduction. Metabolic processes emerged as pivotal for thebaine production, indicating a broader role for the thebaine pathway gene network beyond primary metabolite production. Cell component subnetwork genes demonstrated associations with anatomical units, indicating involvement in plant defense responses. Dominant molecular functions drove plant defense responses. KEGG pathway analysis highlighted the significance of metabolic pathways and biosynthesis of secondary metabolites. Cluster analysis emphasized the relevance of the biosynthesis of amino acids, confirming the link between primary and secondary metabolites. Promoter analysis suggested the potential involvement of signal transduction in thebaine production. Hub genes were targeted by 40 miRNAs, suggesting potential novel biomarkers or target genes within the thebaine biosynthesis pathway. Based on the role of miRNAs identified in connection with the hub genes of the thebaine production process, the secondary metabolite pathway of thebaine appears to be associated with several key plant pathways, e.g. growth, development and stress response. However, these findings, based on bioinformatics analysis, warrant further experimental validation and promise to advance our understanding of the biosynthesis of thebaine and its interactions with other genes and metabolic pathways that influence the production of metabolites.

Analysis of Key Genes Related to Systemic Lupus Erythematosus and COVID-19.

Systemic Lupus Erythematosus (SLE) is a multifactorial and complex immune disease; however, the relevance of COVID-19 infection in SLE patients remains uncertain. This study aims to explore the key candidate genes and pathways in patients with SLE. It also seeks to employ bioinformatics analysis to unravel the molecular signatures inherent in both SLE and COVID-19 patients. The ultimate aim is to identify potential targets and markers specifically relevant to SLE patients who contract SARS-CoV-2. Datasets (GSE12374, GSE20864, GSE61635, GSE81622, and GSE144390) from the Gene Expression Omnibus (GEO) database were analyzed using Robust Rank Aggregation (RRA) method to identify differential expression genes (DEGs) in SLE patients compared to healthy individuals. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, tissue-specific gene analysis, and Protein-protein interaction (PPI) network were performed. Finally, the Venn diagram was employed to identify the intersections of COVID-19 genes, serving as potential targets for SLE patients with COVID-19 infection. A total of 154 DEGs were discovered, with GO enrichment indicating a predominant involvement in the defense response against the virus (P<0.001). KEGG pathway analysis showed enrichment in the NOD-like receptor signaling pathway and coronavirus disease, specifically COVID-19 (P<0.001). Tissue-specific genes related to the hematological and immune systems were emphasized (74%). The PPI network highlighted 22 genes, and 5 key genes, namely, IFIT1, IFIT3, MX1, MX2, and OAS3, which were identified after intersecting with COVID-19 patients' data. IFIT1, IFIT3, MX1, MX2, and OAS3 exhibiting differential expression, as well as the pathways associated with COVID-19, could potentially function as biomarkers and therapeutic targets for individuals with SLE infected with COVID-19.

Metabolomic Analysis of Follicular Fluid in Normal-Weight Patients with Polycystic Ovary Syndrome.

This study aimed to examine the differential variations in the metabolic composition of follicular fluid (FF) among normal-weight patients with polycystic ovary syndrome (PCOS) and controls and to identify potential biomarkers that may offer insights into the early identification and management of these patients. We collected FF samples from 45 normal-weight women with PCOS and 36 normal-weight controls without PCOS who were undergoing in vitro fertilization-embryo transfer. An untargeted metabolomic study of collected FF from infertile women was performed using high-performance liquid chromatography-tandem spectrometry (LC-MS). The tendency of the two groups to separate was demonstrated through multivariate analysis. Univariate analysis and variable importance in projection were used to screen out differential metabolites. Metabolic pathway analysis was conducted using the Kyoto Encyclopedia of Genes and Genomes (KEGG), and a diagnostic model was established using the random forest algorithm. The metabolomics analysis revealed an increase in the expression of 23 metabolites and a decrease in that of 10 metabolites in the FF of normal-weight women with PCOS. According to the KEGG pathway analysis, these differential metabolites primarily participated in the metabolism of glycerophospholipids and the biosynthesis of steroid hormones. Based on the biomarker combination of the top 10 metabolites, the area under the curve value was 0.805. The concentrations of prostaglandin E2 in the FF of individuals with PCOS exhibited an inverse association with the proportion of high-quality embryos (p < 0.05). Our research identified a distinct metabolic profile of the FF from normal-weight women with PCOS. The results offer a broader comprehension of the pathogenesis and advancement of PCOS, and the detected differential metabolites could be potential biomarkers and targets for the treatment of PCOS.

Treating chronic atrophic gastritis: identifying sub-population based on real-world TCM electronic medical records.

Chronic atrophic gastritis (CAG) is a complex chronic disease caused by multiple factors that frequently occurs disease in the clinic. The worldwide prevalence of CAG is high. Interestingly, clinical CAG patients often present with a variety of symptom phenotypes, which makes it more difficult for clinicians to treat. Therefore, there is an urgent need to improve our understanding of the complexity of the clinical CAG population, obtain more accurate disease subtypes, and explore the relationship between clinical symptoms and medication. Therefore, based on the integrated platform of complex networks and clinical research, we classified the collected patients with CAG according to their different clinical characteristics and conducted correlation analysis on the classification results to identify more accurate disease subtypes to aid in personalized clinical treatment. Traditional Chinese medicine (TCM) offers an empirical understanding of the clinical subtypes of complicated disorders since TCM therapy is tailored to the patient's symptom profile. We gathered 6,253 TCM clinical electronic medical records (EMRs) from CAG patients and manually annotated, extracted, and preprocessed the data. A shared symptom-patient similarity network (PSN) was created. CAG patient subgroups were established, and their clinical features were determined through enrichment analysis employing community identification methods. Different clinical features of relevant subgroups were correlated based on effectiveness to identify symptom-botanical botanical drugs correspondence. Moreover, network pharmacology was employed to identify possible biological relationships between screened symptoms and medications and to identify various clinical and molecular aspects of the key subtypes using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. 5,132 patients were included in the study: 2,699 males (52.60%) and 2,433 females (47.41%). The population was divided into 176 modules. We selected the first 3 modules (M29, M3, and M0) to illustrate the characteristic phenotypes and genotypes of CAG disease subtypes. The M29 subgroup was characterized by gastric fullness disease and internal syndrome of turbidity and poison. The M3 subgroup was characterized by epigastric pain and disharmony between the liver and stomach. The M0 subgroup was characterized by epigastric pain and dampness-heat syndrome. In symptom analysis, The top symptoms for symptom improvement in all three subgroups were stomach pain, bloating, insomnia, poor appetite, and heartburn. However, the three groups were different. The M29 subgroup was more likely to have stomach distention, anorexia, and palpitations. Citrus medica, Solanum nigrum, Jiangcan, Shan ci mushrooms, and Dillon were the most popular botanical drugs. The M3 subgroup has a higher incidence of yellow urine, a bitter tongue, and stomachaches. Smilax glabra, Cyperus rotundus, Angelica sinensis, Conioselinum anthriscoides, and Paeonia lactiflora were the botanical drugs used. Vomiting, nausea, stomach pain, and appetite loss are common in the M0 subgroup. The primary medications are Scutellaria baicalensis, Smilax glabra, Picrorhiza kurroa, Lilium lancifolium, and Artemisia scoparia. Through GO and KEGG pathway analysis, We found that in the M29 subgroup, Citrus medica, Solanum nigrum, Jiangcan, Shan ci mushrooms, and Dillon may exert their therapeutic effects on the symptoms of gastric distension, anorexia, and palpitations by modulating apoptosis and NF-κB signaling pathways. In the M3 subgroup, Smilax glabra, Cyperus rotundus, Angelica sinensis, Conioselinum anthriscoides, and Paeonia lactiflora may be treated by NF-κB and JAK-STAT signaling pathway for the treatment of stomach pain, bitter mouth, and yellow urine. In the M0 subgroup, Scutellaria baicalensis, Smilax glabra, Picrorhiza kurroa, Lilium lancifolium, and Artemisia scoparia may exert their therapeutic effects on poor appetite, stomach pain, vomiting, and nausea through the PI3K-Akt signaling pathway. Based on PSN identification and community detection analysis, CAG population division can provide useful recommendations for clinical CAG treatment. This method is useful for CAG illness classification and genotyping investigations and can be used for other complicated chronic diseases.

Identification of pivotal genes and crucial pathways in liver fibrosis through WGCNA analysis.

Liver fibrosis is a progressive liver disease with increasing incidence, yet its underlying pathogenic mechanisms remain incompletely understood. : This study aims to explore potential therapeutic targets for liver fibrosis using weighted gene co-expression network analysis (WGCNA) and experimental validation. We retrieved the microarray data (GSE174099) from the GEO database and performed differential expression analysis and WGCNA to identify co-expression modules associated with liver fibrosis. A module with the highest correlation to liver fibrosis was selected for further analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to investigate the biological functions and signaling pathways of the identified genes. Protein-protein interaction (PPI) networks were constructed using the STRING database. The correlation between core genes and immune cells was analyzed with the CIBERSORT algorithm. Additionally, pathological and molecular biology experiments were performed to validate the expression levels of core genes in liver tissue, including HE and Masson staining, immunohistochemistry, RT-qPCR, and Western blotting. We identified a total of 86 intersecting genes from the differential expression analysis and WGCNA. GO enrichment analysis revealed that these genes were involved in processes such as cellular response to cAMP, collagen-containing extracellular matrix, and G protein-coupled receptor binding. KEGG pathway analysis highlighted the involvement of these genes in pathways like Cell Adhesion Molecules and the PI3K-Akt signaling pathway. Using Cytoscape software, we identified four core genes: Cftr, Cldn4, Map2, and Spp1. Pathological examinations showed that the experimental group exhibited significant fibrous tissue proliferation compared to the control group. Immunohistochemistry, RT-qPCR, and Western blotting analyses confirmed that these core genes were significantly upregulated in the experimental group (P< 0.05). This study identified four key genes (Cftr, Cldn4, Map2, Spp1) that are significantly associated with liver fibrosis. These genes are upregulated in liver fibrosis and could potentially as biomarkers for diagnosis and targets for therapeutic interventions.

Identification and validation of key regulating circRNAs in Immune Thrombocytopenia by circRNAs sequencing

Dysfunction of T cells is a causative factor in Immune Thrombocytopenia (ITP), an autoimmune disorder. Circular RNAs (circRNAs), which have been associated with the pathophysiology of various immunological conditions, are of particular interest. Our study aimed to identify pivotal regulatory circRNAs within the peripheral T cells of ITP patients. We utilized circRNA sequencing to discern differences in circRNA expression between the ITP cohort and healthy controls. We identified 606 upregulated and 719 downregulated circRNAs. Subsequent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to scrutinize the parent genes of these differentially expressed circRNAs, revealing their significant involvement in metabolic processes and T cell receptor signaling pathways. Following a rigorous selection process that included DEG analysis, KEGG, and GO pathways analysis, along with an assessment of the potential roles of their parent genes, five top differentially expressed circRNAs were subjected to further validation via quantitative Polymerase Chain Reaction (RT-qPCR). Specifically, in the peripheral T cells of ITP patients, hsa_circ_0008866 (TAOK1), hsa_circ_0006856 (MAP3K5), and hsa_circ_0007444 (RHOBTB3) emerged as key regulatory circRNAs. The potential miRNA targets of these circRNAs were predicted employing miRanda, RNAhybrid, and TargetScan algorithms.

Molecular mechanism of basolateral amygdala involved in electroacupuncture-induced amelioration of cancer pain and concomitant depression based on transcriptomics techniques.

To observe the effect of electroacupuncture (EA) of "Zusanli" (ST36) and "Sanyinjiao" (SP6) on cancer pain and concomitant negative emotion in cancer pain model mice, and to explore its molecular mechanisms in the basolateral amygdala (BLA) by using transcriptomics techniques. C57BL/6 mice were randomized into sham operation, model and EA groups, with 10 mice in each group. The cancer pain model was established by injecting PBS suspension containing Lewis lung cancer cells into the femur. The mice in the EA group received EA stimulation(1 mA, 2 Hz) on ST36 and SP6 from the 10th day after modeling, 20 min per day for 12 successive days. The bone damage of the distal femur was observed with X-ray and H.E. staining, respectively. The mechanical pain threshold (MPT) was detected by using von Frey. The depression-like behavior was detected by using sucrose-preference test (sucrose preference index in 12 h), and the immobility (feeling of despair) duration of forced swimming within 4 min. The BLA tissue was extracted for RNA sequencing (RNA library construction, and screening differential gene profiling by transcriptomic sequencing) and bioinformatics analysis. The real-time PCR was used to validate the mRNA expression of differentially expressed genes：tumor necrosis factor superfamily 8 (Tnfsf8), bone marrow stromal cell antigen 1 (Bst1), prodynorphin (Pdyn) and voltage-gated sodium channelβ4 (Scn4b). H.E. staining and X-ray showed significant bone damage in the distal femur in cancer pain mice. In contrast to the sham operation group, the MPT on the 1st , 4th, 7th , 10th, 14th and 21st day after modeling and sucrose preference index were significantly decreased (P<0.001, P<0.000 1), and the immobility time of the forced swimming was considerably increased in the model group (P<0.001). In contrast to the model group, the MPT values on the 14th and 21st day and sucrose preference index were obviously increased (P<0.000 1, P<0.05), and the immobility time was strikingly decreased in the EA group (P<0.01). RNA sequencing showed that a total of 404 differentially expressed genes (205 up-regulated, 199 down-regulated) were screened in the model group compared with the sham operation group, and a total of 329 differentially expressed genes (206 up-regulated and 123 down-regulated) were screened in the EA group compared with the model group. Venn diagram analysis of the differentially expressed genes showed that 45 up-regulated and 28 down-regulated genes in the model group were completely reversed by EA. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of the screened differentially expressed genes revealed that the above differential genes were mainly enriched in the ligand receptor activity, cytokine receptor binding, and cytokine activity related to neuro-inflammation, as well as in neuropeptide signaling pathways related to neuronal excitability, and calcium ion mediated signal transduction. The analysis of KEGG pathway showed that the differentially expressed genes were mainly enriched in the inflammation-related pathways, such as interleukin-17 pathway. Validation analysis of the differentially expressed genes showed that the expression levels of Tnfsf8 and Bst1 were significantly up-regulated in the model group compared with the sham operation group (P<0.01, P<0.05), and down-regulated by EA (P<0.01, P<0.05), while the expression levels of Pdyn and Scn4b were down-regulated in the model group in comparison with the sham operation group (P<0.01), and up-regulated by EA (P<0.05, P<0.01), which was consistent with the changing trend of the gene sequencing results. Acupuncture of ST36 and SP6 can significantly relieve cancer pain and concomitant negative emotion in cancer pain mice, which may be related to its functions in alleviating neuro-inflammation and relieving the abnormal activities of specific neurons in the BLA.