Gene Ontology Functional Enrichment Research Articles

Identification and Verification of Hub Mitochondrial Dysfunction Genes in Osteoarthritis Based on Bioinformatics Analysis.

Age-related mitochondrial dysfunction and associated oxidative stress may contribute to the development of osteoarthritis. The aim of this study was to identify hub genes associated with mitochondrial dysfunction in osteoarthritis (OA) patients, helping predict the risk of OA, and revealing the mechanism of OA progression. OA expression data and mitochondrial dysfunction genes were downloaded from GEO (GSE55235, GSE82107, and GSE114007) and GeneCard databases. The differentially expressed mitochondrial dysfunction genes (DEMDFGs) between OA and control samples were screened. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes pathways were analyzed for DEMDFGs. The hub genes were determined by WGCNA and LASSO regression analysis. ROC curves manifested the diagnostic efficacy of each hub gene. A nomogram model was constructed and validated to predict OA risk. The expression of hub genes in OA and normal chondrocytes was verified by external datasets, qRT-PCR and western blotting. A total of 31 DEMDFGs were identified, with 15 genes upregulated and 16 genes downregulated. GO functional enrichment analysis revealed that DEMDFGs were enriched in biological processes related to energy metabolism and cellular respiration. By employing weighted gene coexpression network analysis, we identified four distinct coexpression modules, among which the blue module exhibited the strongest correlation with OA. The intersection between DEMDFGs and this module yielded eight candidate genes. After LASSO analysis of the data, four hub genes (ACADL, CYBA, SLC19A2, and UCP2) were identified as potential biomarkers for OA. The expression levels of these four genes were externally validated in the GSE114007 dataset. And the biologically differential expression of these four genes has been verified in OA and normal chondrocytes. Moreover, the four hub genes had good sensitivity and specificity by ROC curve analysis, and the risk model constructed with these four genes showed promising performance. In conclusion, our study may provide novel mitochondrial dysfunction hub genes with potential clinical applications for understanding the pathology, diagnosis, and treatment of OA.

Biomarkers of UVB radiation-related senescent fibroblasts

Excessive exposure to ultraviolet (UV) light is known to induce photoaging in the skin, necessitating the development of effective anti-photoaging strategies to mitigate the adverse effects of UV radiation. Understanding the biofunctional characteristics of diverse skin cell types and unraveling the molecular modifications implicated in the aging process are pivotal in comprehending the intricacies of photoaging in human skin. Such insights are essential for paving the way for innovative interventions to counteract the deleterious impact of UV radiation on the skin. The single-cell RNA sequencing data of UVB-irradiated and normal control mouse skin in GSE173385 were downloaded from the Gene Expression Omniniub (GEO) database. First, cell types were identified using Seurat for normalization, dimensionality reduction and clustering. Next, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis were executed on these cell subpopulations. Using FindAllMarkers in the Seurat package to identify differential gene expression and Monocle2 cell trajectory analysis, we screened out hub genes related to the development trajectory of senescent fibroblasts during photoaging, and then combined it with 307 aging-related genes collected in the HAGR library, we finally identified two biomarkers. The efficiency of biomarkers in diagnosing UV radiation photoaging was also evaluated in the dataset. Concurrently, the immune infiltration of identified biomarkers under UV radiation has also been further explored. Moreover, we employed the Enrichr platform to conduct a comprehensive screening of drug molecules associated with the identified biomarkers. Our comprehensive analysis, employing Seurat for normalization, dimensionality reduction, and clustering, successfully identified ten distinct cell types within the samples. Then GO functional enrichment analysis showed that senescent fibroblasts are mainly involved in the regulation of immune effector processes such as cytokine-mediated signaling pathways, regulation of epithelial cell proliferation and intercellular adhesion. Afterwards, KEGG analysis determined the main biological pathways are: IL-17 signaling pathway, Cytokine–cytokine receptor interaction, Metabolism of xenobiotics by cytochrome P450. After differential gene expression and Monocle2 cell trajectory analysis, we matched the obtained hub genes with the aging-related genes collected in the HAGR library, and finally screened out two relevant biomarkers: Apoe and Gdf15 which are related to the development trajectory of senescent fibroblasts during photoaging. Meanwhile, the immune infiltration further implied that the expression of these two biomarkers was significantly correlated with immune cells. In addition, the Enrichr platform was used to screen the drug molecules related to these biomarkers. This strategic approach aimed to pinpoint effective molecular targets for the prevention and treatment of photoaging. Our investigation has effectively characterized biomarkers associated with fibroblast senescence during photoaging at the single-cell level, We have validated their correlation with cellular immune inflammation and identified potential drug targets through the utilization of the Enrichr platform. This foundational research establishes a robust basis for the development of therapeutic interventions targeting skin diseases resulting from photoaging.

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

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

Poly-p-dioxanone Thread Leads to Fat Metabolism Around the Thread in Pig Subcutaneous Back Fat.

When poly-p-dioxanone (PDO) thread is implanted subcutaneously, in addition to collagen hyperplasia, it can also cause denaturation of surrounding adipocytes and reduce the thickness of the fat layer. Hitherto, no studies have thoroughly investigated the effects of PDO thread on adipose tissue. In this study, the effect of PDO thread on adipose tissue was investigated in an animal model. In the current study, PDO thread was implanted into subcutaneous adipose tissue of the back in a miniature pig. Implantation site tissue and control site tissue were taken 12 weeks after implantation for hematoxylin and eosin (H&E) staining and transcriptome sequencing. Gene ontology functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis were performed to investigate the differential gene expression between PDO thread implantation and control site tissue. An obvious decrease in the number, fusion, and denaturation of adipocytes can be seen by H&E staining. Sequencing analysis results showed that many of the genes identified, which were downregulated after PDO thread implantation, were involved in functions and pathways related to lipid metabolism, such as fatty acid metabolism, fatty acid degradation, and lipid cell lipolysis regulation. Some genes related to fatty acid metabolism were significantly downregulated in the PDO tissue at 12 weeks compared to the control tissue. Our results showed PDO thread implantation can cause a decrease in the number of adipocytes, as well as a significant alteration of the expression levels of some genes involved in lipid metabolism-related pathways. PDO thread might play an important role in promoting lipolysis.

Identification of genes and pathways associated with menopausal status in breast cancer patients using two algorithms

BackgroundMenopausal status has a known relationship with the levels of estrogen, progesterone, and other sex hormones, potentially influencing the activity of ER, PR, and many other signaling pathways involved in the initiation and progression of breast cancer. However, the differences between premenopausal and postmenopausal breast cancer patients at the molecular level are unclear.MethodsWe retrieved eight datasets from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) associated with menopausal status in breast cancer patients were identified using the MAMA and LIMMA methods. Based on these validated DEGs, we performed Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Protein–protein interaction (PPI) networks were constructed. We used DrugBank data to investigate which of these validated DEGs are targetable. Survival analysis was performed to explore the influence of these genes on breast cancer patient prognosis.ResultsWe identified 762 DEGs associated with menopausal status in breast cancer patients. PPI network analysis indicated that these genes are primarily involved in pathways such as the cell cycle, oocyte meiosis and progesterone-mediated oocyte maturation pathways. Notably, several genes played roles in multiple signaling pathways and were associated with patient survival. These genes were also observed to be targetable according to the DrugBank database.ConclusionWe identified DEGs associated with menopausal status in breast cancer patients. The association of these genes with several key pathways may promote understanding of the complex characterizations of breast cancer. Our findings offer valuable insights for developing new therapeutic strategies tailored to the menopausal status of breast cancer patients.

Transcriptome blood profile of the Yili horse before and after training

Proper training improves the horse’s performance. In the present study, blood transcriptome of the Yili horse was analysed before and after training. Overall, six Yili horses were trained for 3 months; blood samples at rest were collected before and after the training period. Transcriptome libraries were created from the blood samples using high-throughput sequencing; Gene Ontology functional enrichment and Kyoto Encyclopaedia of Genes and Genomes pathway analyses were performed for differentially expressed genes to identify the pathways and candidate genes associated with training and locomotor performance. In total, transcriptome analysis screened 33 significantly differentially expressed genes; of these, 23 and 10 were up-regulated and down-regulated after training, respectively. These differentially expressed genes were significantly enriched in metabolic pathways associated with exercise physiology, including sphingolipid metabolism, tryptophan metabolism, and the cGMP-PKG signalling pathway. The results of this study provide a theoretical basis for exploring the molecular mechanisms underlying locomotor performance of the Yili horse as well as a novel insight into the kinematics of this breed.

Transcriptome analysis of anaerobic glycolysis effects on Jurkat T cell proliferation.

To explore the effects of anaerobic glycolysis on Jurkat T cell proliferation and clarify the possible mechanism via transcriptomic analysis. The monocarboxylate transporter 1 inhibitor AZD3965 was used to target and block the transmembrane transport of lactate, thereby inhibiting anaerobic glycolysis in Jurkat T cells. Then, genes with differential expression between treated and untreated cells were detected by transcriptomic analysis, and constructs were generated. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses as well as protein-protein interaction (PPI) network analysis were performed to explore the potential mechanism. Inhibition of anaerobic glycolysis reduced Jurkat T-cell proliferation. RNA sequencing identified 1723 transcripts that were differentially expressed, including 1460 upregulated genes and 263 downregulated genes. GO functional enrichment analysis showed that the differentially expressed genes were mainly involved in the biological processes of response to unfolded protein, response to topologically incorrect protein, and protein folding. KEGG pathway analysis of differentially expressed genes or hub genes from the PPI network analysis revealed enrichment in the estrogen signaling and PI3K-Akt pathways. Anaerobic glycolysis contributes to the regulation of Jurkat T-cell proliferation. The underlying mechanism may involve the estrogen signaling pathway or PI3K-Akt signaling pathway as well as protein metabolism.

Investigating the mechanism of Qu Du Qiang Fei 1 Hao Fang Formula against coronavirus disease 2019 based on network pharmacology method

Objective: Qu Du Qiang Fei 1 Hao Fang (QDQF1) is a novel Chinese herbal medicine formula used to treat coronavirus disease 2019 (COVID-19). However, the pharmacological mechanisms of action of QDQF1 remain unclear. The objective of this study was to identify the effective ingredients and biological targets of QDQF1 for COVID-19 treatment. Materials and Methods: The effective ingredients and mechanisms of action of QDQF1 were analyzed by using network pharmacology methods, which included an analysis of the effective ingredients and corresponding targets, COVID-19-related target acquisition, compound-target network analyses, protein-protein interaction network analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses, and molecular docking studies. Results: In total, 288 effective QDQF1 ingredients were identified. We identified 51 core targets from the 148 targets through an overlap between putative QDQF1 targets and COVID-19-related targets. Six key components, including formononetin, kaempferol, luteolin, naringenin, quercetin, and wogonin were identified through component-target network analyses. GO functional enrichment analysis of the core targets revealed 1296 items, while KEGG pathway enrichment analysis identified 148 signaling pathways. Nine central targets (CCL2, CXCL8, IL1B, IL6, MAPK1, MAPK3, MAPK8, STAT3, and TNF) related to the COVID-19 pathway were identified in the KEGG pathway enrichment analysis. Furthermore, molecular docking analysis suggested that the docking scores of the six key components to the nine central targets were better than those to remdesivir. Conclusions: QDQF1 may regulate multiple immune-and inflammation-related targets to inhibit the progression of severe acute respiratory syndrome coronavirus 2, and thus, may be suitable for the treatment of COVID-19.

A novel immune cell signature for predicting glioblastoma after radiotherapy prognosis and guiding therapy.

Background: Glioblastoma, a highly aggressive brain tumor, poses a significant clinical challenge, particularly in the context of radiotherapy. In this study, we aimed to explore infiltrating immune cells and identify immune-related genes associated with glioblastoma radiotherapy prognosis. Subsequently, we constructed a signature based on these genes to discern differences in molecular and tumor microenvironment immune characteristics, ultimately informing potential therapeutic strategies for patients with varying risk profiles. Methods: We leveraged UCSC Xena and CGGA gene expression profiles from post-radiotherapy glioblastoma as verification cohorts. Infiltration ratios were stratified into high and low groups based on the median value. Differential gene expression was determined through Limma differential analysis. A signature comprising four genes was constructed, guided by Gene Ontology (GO) functional enrichment results and Kaplan-Meier survival analysis. We evaluated differences in cell infiltration levels, Immune Score, Stromal Score, and ESTIMATE Score and their Pearson correlations with the signature. Spearman's correlation was computed between the signature and patient drug sensitivity (IC50), predicted using Genomics of Drug Sensitivity in Cancer (GDSC) and CCLE databases. Results: Notably, the infiltration of central memory CD8+T cells exhibited a significant correlation with glioblastoma radiotherapy prognosis. Samples were dichotomized into high- and low-risk groups based on the optimal signature threshold (2.466642). Kaplan-Meier (K-M) survival analysis revealed that the high-risk group experienced a significantly poorer prognosis (p = .0068), with AUC values exceeding 0.82 at 1, 3, and 5 years, underscoring the robust predictive potential of the signature scoring system. Independent validation sets substantiated the validity of the signature. Statistically significant differences in tumor microenvironments (p < .05) were observed between high- and low-risk groups, and these differences were significantly correlated with the signature (p < .05). Furthermore, there were significant correlations between high and low-risk groups regarding immune checkpoint expressions, Immune Prognostic Score (IPS), and Tumor Immune Dysfunction and Exclusion (TIDE) scores. Conclusion: The immune cell signature, comprising SDC-1, PLAUR, FN1, and CXCL13, holds promise as a predictive tool for assessing glioblastoma prognosis following radiotherapy. This signature also offers valuable guidance for tailoring treatment strategies, emphasizing its potential clinical relevance in improving patient outcomes.

Molecular mechanism of Xuebijing in treating pyogenic liver abscess complicated with sepsis.

Xuebijing (XBJ) can alleviate the inflammatory response, improve organ function, and shorten the intensive care unit (ICU) stay in patients with pyogenic liver abscess (PLA) complicated with sepsis, but the molecular mechanisms have not been elucidated. This study aimed to explore the molecular mechanism of XBJ in treating PLA complicated with sepsis using a network pharmacology approach. The active ingredients and targets of XBJ were retrieved from the ETCM database. Potential targets related to PLA and sepsis were retrieved from the GeneCards, PharmGKB, DisGeNet, Online Mendelian Inheritance in Man (OMIM), Therapeutic Targets Database (TTD), and DrugBank databases. The targets of PLA complicated with sepsis were mapped to the targets of XBJ to identify potential treatment targets. Protein-protein interaction networks were analyzed using the STRING database. Potential treatment targets were imported into the Metascape platform for Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Molecular docking was performed to validate the interactions between active ingredients and core targets. XBJ was found to have 54 potential treatment targets for PLA complicated with sepsis. Interleukin-1β (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor (TNF) were identified as core targets. KEGG enrichment analysis revealed important pathways, including the interleukin-17 (IL-17) signaling pathway, the TNF signaling pathway, the nuclear factor-kappa B (NF-κB) signaling pathway, and the Toll-like receptor (TLR) signaling pathway. Molecular docking experiments indicated stable binding between XBJ active ingredients and core targets. XBJ may exert therapeutic effects on PLA complicated with sepsis by modulating signaling pathways, such as the IL-17, TNF, NF-κB, and TLR pathways, and targeting IL-1β, IL-6, and TNF.

Potential mechanism of Luoshi Neiyi prescription in endometriosis based on serum pharmacochemistry and network pharmacology.

Endometriosis (EMs) is characterized by ectopic growth of active endometrial tissue outside the uterus. The Luoshi Neiyi prescription (LSNYP) has been extensively used for treating EMs in China. However, data on the active chemical components of LSNYP are insufficient, and its pharmacological mechanism in EMs treatment remains unclear. This study aimed to explore the potential mechanism of LSNYP for EMs through network pharmacology based on the components absorbed into the blood. Ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry was used to analyze blood components, and a series of network pharmacology strategies were utilized to predict targets of these components and EMs. Protein-protein interaction (PPI) network analysis, component-target-disease network construction, gene ontology (GO) functional enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed. Additionally, molecular docking, molecular dynamics simulations, and in vitro and in vivo experiments were conducted to validate the HIF1A/EZH2/ANTXR2 pathway associated with hypoxic pathology in EMs. Thirty-four absorbed components suitable for network pharmacology analysis were identified, and core targets, such as interleukin 6, EGFR, HIF1A, and EZH2, were founded. Enrichment results indicated that treatment of EMs with LSNYP may involve the regulation of hypoxia and inflammatory-related signaling pathways and response to oxidative stress and transcription factor activity. Experimental results demonstrated that LSNYP could decrease the expression of HIF1A, ANTXR2, YAP1, CD44, and β-catenin, and increased EZH2 expression in ectopic endometrial stromal cells and endometriotic tissues. Molecular docking and molecular dynamics simulations manifested that there was stable combinatorial activity between core components and key targets of the HIF1A/EZH2/ANTXR2 pathway. LSNYP may exert pharmacological effects on EMs via the HIF1A/EZH2/ANTXR2 pathway; hence, it is a natural herb-related therapy for EMs.

Aconitum coreanum alleviates cerebral ischemic stroke through the PI3K/Akt signaling pathway in gerbils model

Cerebral ischemic stroke (CIS) is a kind of acute cerebrovascular disease with fast onset, low-cure rate, and high case-fatality rate. The application of Aconitum coreanum on CIS was recorded in many ancient books in China with it mechanism and effective components unclear. This study aimed to analyze the potential mechanism and effetvie components of A. coreanum on treating CIS. Neurological function score, cerebral infarction rate, and inflammatory indicators were applied to evaluate the efficacy of A. coreanum on gerbils with CIS. The prototype compounds in A. coreanum which were absorbed into blood was analyzed and identified by Ultra high performance liquid chromatography-Q exactive focus-Mass spectrometer (UPLC-QE-MS). And bioinformatics analysis was used to predict their potential targets or pathways of action. Western blotting and immunofluorescence were adopted to validate the targets or pathway with high relation. After treatment with A. coreanum, the neurological function status of gerbils with CIS was significantly improved, the ischemic area of the brain and the levels of inflammatory indicators significantly reduced. 22 prototype compounds in A. coreanum absorbed into blood were identified mainly including C-20 and C-19 diterpenoid alkaloids. Gene ontology (GO) function enrichment analysis illustrated that A. coreanum acted on protein phosphorylation, receptor complexes, protein kinase activity, and inflammatory response to impove CIS. The kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis results revealed that PI3K/Akt signaling pathway was a key pathway. Western blotting and immunofluorescence validated that A. coreanum acted on PI3K/Akt signaling pathway. In conclusion, A. coreanum improved the inflammantory condition in CIS by acting on PI3K/Akt signaling pathway and the effective components were the diterpenoid alkaloids in it.

Enzyme production mechanism of anaerobic fungus Orpinomyces sp. YF3 in yak rumen induced by different carbon source

In order to investigate the enzyme production mechanism of yak rumen-derived anaerobic fungus Orpinomyces sp. YF3 under the induction of different carbon sources, anaerobic culture tubes were used for in vitro fermentation. 8 g/L of glucose (Glu), filter paper (Flp) and avicel (Avi) were respectively added to 10 mL of basic culture medium as the sole carbon source. The activity of fiber-degrading enzyme and the concentration of volatile fatty acid in the fermentation liquid were detected, and the enzyme producing mechanism of Orpinomyces sp. YF3 was explored by transcriptomics. It was found that, in glucose-induced fermentation solution, the activities of carboxymethyl cellulase, microcrystalline cellulase, filter paper enzyme, xylanase and the proportion of acetate were significantly increased (P < 0.05), the proportion of propionate, butyrate, isobutyrate were significantly decreased (P < 0.05). The results of transcriptome analysis showed that there were 5 949 differentially expressed genes (DEGs) between the Glu group and the Flp group, 10 970 DEGs between the Glu group and the Avi group, and 6 057 DEGs between the Flp group and the Avi group. It was found that the DEGs associated with fiber degrading enzymes were significantly up-regulated in the Glu group. Gene ontology (GO) function enrichment analysis identified that DEGs were mainly associated with the xylan catabolic process, hemicellulose metabolic process, β-glucan metabolic process, cellulase activity, endo-1,4-β-xylanase activity, cell wall polysaccharide metabolic process, carbohydrate catabolic process, glucan catabolic process and carbohydrate metabolic process. Moreover, the differentially expressed pathways associated with fiber degrading enzymes enriched by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were mainly starch and sucrose metabolic pathways and other glycan degradation pathways. In conclusion, Orpinomyces sp. YF3 with glucose as carbon source substrate significantly increased the activity of cellulose degrading enzyme and the proportion of acetate, decreased the proportion of propionate, butyrate and isobutyrate. Furthermore, the degradation ability and energy utilization efficiency of fungus in the presence of glucose were improved by means of regulating the expression of cellulose degrading enzyme gene and participating in starch and sucrose metabolism pathway, and other glycan degradation pathways, which provides a theoretical basis for the application of Orpinomyces sp. YF3 in practical production and facilitates the application of Orpinomyces sp. YF3 in the future.

Combining bioinformatics and machine learning algorithms to identify and analyze shared biomarkers and pathways in COVID-19 convalescence and diabetes mellitus.

Most patients who had coronavirus disease 2019 (COVID-19) fully recovered, but many others experienced acute sequelae or persistent symptoms. It is possible that acute COVID-19 recovery is just the beginning of a chronic condition. Even after COVID-19 recovery, it may lead to the exacerbation of hyperglycemia process or a new onset of diabetes mellitus (DM). In this study, we used a combination of bioinformatics and machine learning algorithms to investigate shared pathways and biomarkers in DM and COVID-19 convalescence. Gene transcriptome datasets of COVID-19 convalescence and diabetes mellitus from Gene Expression Omnibus (GEO) were integrated using bioinformatics methods and differentially expressed genes (DEGs) were found using the R programme. These genes were also subjected to Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis to find potential pathways. The hub DEGs genes were then identified by combining protein-protein interaction (PPI) networks and machine learning algorithms. And transcription factors (TFs) and miRNAs were predicted for DM after COVID-19 convalescence. In addition, the inflammatory and immune status of diabetes after COVID-19 convalescence was assessed by single-sample gene set enrichment analysis (ssGSEA). In this study, we developed genetic diagnostic models for 6 core DEGs beteen type 1 DM (T1DM) and COVID-19 convalescence and 2 core DEGs between type 2 DM (T2DM) and COVID-19 convalescence and demonstrated statistically significant differences (p<0.05) and diagnostic validity in the validation set. Analysis of immune cell infiltration suggests that a variety of immune cells may be involved in the development of DM after COVID-19 convalescence. We identified a genetic diagnostic model for COVID-19 convalescence and DM containing 8 core DEGs and constructed a nomogram for the diagnosis of COVID-19 convalescence DM.

Network pharmacology, molecular docking and experimental verification reveal the mechanism of Yiguanjian decoction in treating acute liver failure

Introduction: The potential targets and action mechanism of Yiguanjian (YGJ) decoction in treating acute liver failure (ALF) were determined using network pharmacology, molecular docking and cell experiments.Methods: The Pharmacology of Traditional Chinese Medicine Systems (TCMSP) and BATMAN-TCM databases were used to find YGJ decoction targets. The Genecard database was employed to predict targets associated with ALF. Cytascape software was utilised to visualise and select common targets along with establishing a protein–protein interaction (PPI) network. Core targets were screened and putative function was assessed via gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyzes. Molecular docking was performed using AutodockTools, PyMoL and Discovery Studio software to verify the correlation between the YGJ decoction and selected targets. MTT assay was conducted to determine the effect of the YGJ decoction on the viability of Huh-7 human hepatoma cells. The effects of the YGJ decoction on the expression of putative targets in Huh-7 cells were determined via western blot and quantitative real-time polymerase chain reaction analyzes.Results: Overall, 9153 YGJ decoction and 576 ALF-related targets were obtained, and 469 YGJ decoction and ALF cross targets were obtained. Of these, 20 key targets, including AKT1, estrogen receptor 1 (ESR1), catalase (CAT), interleukin-1β (IL-1β) and discs large homolog 4 (DLG4), were selected from the PPI network. GO function enrichment analysis revealed that these targets were primarily associated with regulating system processes, cell body, oxidoreductase activity and other processes. An enrichment analysis using the KEGG pathway database revealed that the treatment of ALF using the YGJ decoction was primarily associated with the AGE-RAGE, cGMP-PKG and HIF-1 signalling pathways. Molecular docking indicated that quercetin, stigmasterol and β- sitosterol as well as AKT1, ESR1, CAT, IL-1β and DLG4 exhibited good binding affinity. In vitro experiments revealed that the YGJ decoction significantly reversed lipopolysaccharide (LPS)-induced apoptosis (P < 0.01), inhibited LPS-induced increase in IL-1β and ESR1 levels and upregulated LPS-induced decrease in AKT1, CAT and DLG4 levels (P < 0.05).Conclusions: The YGJ decoction alleviates ALF by regulating multiple targets and its action mechanism may be associated with ameliorating oxidative stress and inflammation.

Unveiling the role of miR-137-3p/miR-296-5p/SERPINA3 signaling in colorectal cancer progression: integrative analysis of gene expression profiles and in vitro studies

BackgroundColorectal cancer (CRC) is a prevalent malignancy worldwide, with increasing incidence and mortality rates. Although treatment options have improved, CRC remains a leading cause of death due to metastasis. Early intervention can significantly improve patient outcomes, making it crucial to understand the molecular mechanisms underlying CRC metastasis. In this study, we performed bioinformatics analysis to identify potential genes associated with CRC metastasis.MethodsWe downloaded and integrated gene expression datasets (GSE89393, GSE100243, and GSE144259) from GEO database. Differential expression analysis was conducted, followed by Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The hub gene SERPINA3 was selected for further in vitro functional studies. Additionally, the role of miR-137-3p/miR-296-5p/ Serpin family A member 3 (SERPINA3) in CRC cell function was investigated using in vitro assays.ResultsAnalysis of the gene expression datasets revealed differentially expressed genes (DEGs) associated with CRC metastasis. GO analysis showed enrichment in biological processes such as blood coagulation regulation and wound healing. Cellular component analysis highlighted extracellular matrix components and secretory granules. Molecular function analysis identified activities such as serine-type endopeptidase inhibition and lipoprotein receptor binding. KEGG analysis revealed involvement in pathways related to complement and coagulation cascades, cholesterol metabolism, and immune responses. The common DEGs among the datasets were further investigated. We identified SERPINA3 as a hub gene associated with CRC metastasis. SERPINA3 exerted enhanced effects on migration, proliferation and epithelial-mesenchymal transition (EMT) and inhibitory effects on caspase-3/-9 activities in HT29 and SW620 cells. MiR-137-3p overexpression increased activities of caspase-3/-9, decreased migration and proliferation, and also repressed EMT in HT29 cells, which were obviously attenuated by SERPINA3 enforced overexpression. Consistently, SERPINA3 enforced overexpression also largely reversed miR-296-5p mimics-induced increased in activities of caspase-3/-9, decrease in migration, proliferation and EMT in HT29 cells.ConclusionThrough bioinformatics analysis, we identified potential genes associated with CRC metastasis. The functional studies focusing on SERPINA3/miR-137-3p/miR-296-5p further consolidated its role in regulating CRC progression. Our findings provide insights into novel mechanisms underlying CRC metastasis and might contribute to the development of effective treatment strategies. However, the role of SERPINA3/miR-137-3p/miR-296-5p signaling in CRC still requires further investigation.

Network pharmacology integrated with molecular docking technology to reveal the potential mechanism of Shuganfang against drug-induced liver injury.

This study aimed to investigate the active composition and mechanism of the Shuganfang (SGF) in treating drug-induced liver injury (DILI) using network pharmacology and molecular docking. The potential active ingredients and targets of SGF were obtained from the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) database. DILI-related targets were queried from various databases including GEO, GeneCards, OMIM, NCBI, and DisGeNET. The STRING database was used to establish a protein-protein interaction (PPI) network. DAVID was utilized for conducting gene ontology (GO) function enrichment and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses. The data visualization and analysis of herb-ingredient-target and disease-pathway-target-ingredient networks were conducted using Cytoscape software (version 3.7.2). PyMoL and AutoDock software was used to select the best binding target for molecular docking. A total of 177 active ingredients,126 targets and 10112 disease targets were obtained, including 122 intersection targets. The identified potential active ingredients consisted of quercetin, kaempferol, luteolin, tanshinone IIa, nobiletin, isorhamnetin, beta-sitosterol and naringenin. The core targets implicated in the study were IL6, estrogen receptor 1 (ESR1), hypoxia-inducible factor alpha subunit 1 (HIF1A), MYC and vascular endothelial growth factor A (VEGFA). KEGG analysis revealed that the treatment of DILI with SGF mainly acted through apoptosis, the PI3K-Akt signaling pathway, and the tumor necrosis factor (TNF) signaling pathway. Furthermore, the binding affinities between the potential ingredients and the core targets were subsequently confirmed through molecular docking experiments. The findings indicated that the docking outcomes remained consistent and demonstrated a favorable capacity for binding. SGF exerts a therapeutic effect on DILI through multiple active ingredients, multiple targets and multiple pathways. Our findings contribute to a positive investigation and establish a theoretical basis for further extensive exploration of SGF as a potential treatment for DILI in future research.

Screening of key genes in the pathogenesis of muscle atrophy in CKD-PEW children based on RNA sequencing

BackgroundIn children with CKD, Protein Energy Wasting (PEW) is common, which affects the outcome of children and is an important cause of poor prognosis. We are aiming to explore the pathogenesis of muscle wasting in CKD-PEW children.MethodsBlood samples of 32 children diagnosed with chronic kidney disease (CKD) and protein energy wasting (PEW) in our hospital from January 2016 to June 2021 were collected. RNA sequencing and bioinformatics analysis were performed.ResultsBased on GO (Gene Ontology) functional enrichment analysis, KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis and differential gene expression analysis, a total of 25 CKD-PEW related genes were obtained including CRP, IL6, TNF, IL1B, CXCL8, IL12B, IL12A, IL18, IL1A, IL4, IL10, TGFB2, TGFB1, TGFB3, ADIPOQ, NAMPT, RETN, RETNLB, LEP, CD163, ICAM1, VCAM1, SELE, NF-κB1, NF-κB2. The most significantly differentially expressed gene was NF-κB2 (adjusted P = 2.81 × 10–16), and its expression was up-regulated by 3.92 times (corresponding log2FoldChange value was 1.979). Followed by RETN (adjusted P = 1.63 × 10–7), and its expression was up-regulated by 8.306 times (corresponding log2FoldChange value was 2.882). SELE gene were secondly significant (adjusted P = 5.81 × 10–7), and its expression was down-regulated by 22.05 times (corresponding log2FoldChange value was -4.696).ConclusionsA variety of inflammatory factors are involved in the pathogenesis of CKD-PEW in children, and chronic inflammation may lead to the development of muscle atrophy in CKD-PEW. It is suggested for the first time that NF-κB is a key gene in the pathogenesis of muscle wasting in CKD-PEW children, and its increased expression may play an important role in the pathogenesis of muscle wasting in children with CKD-PEW.

Based on Bioinformatics to Explore the Mechanism of "Tangzhiqing" Decoction Alleviating Type 2 Diabetes-associated Cognitive Dysfunction in Mice by Regulating Hippocampal Neuron Apoptosis and Autophagy.

Diabetic cognitive dysfunction (DCD) is emerging as a chronic complication of diabetes that is gaining increasing international recognition. The traditional Chinese medicine (TCM) formulation, Tangzhiqing decoction (TZQ), has shown the capacity to modulate the memory function of mice with DCD by ameliorating insulin resistance. Nevertheless, the precise mechanism underlying the effects of TZQ remains elusive. The chemical constituents of TZQ were screened using TCMSP databases, and DCDassociated disease targets were retrieved from various databases. Subsequently, core targets were identified through network topology analysis. The core targets underwent analysis using Gene Ontology (GO) functional annotations and enrichment in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Models were established through high-fat and high-glucose diet feeding along with intraperitoneal injection of streptozotocin (STZ). TZQ and metformin were administered at varying doses over 8 weeks. The Morris water maze was employed to evaluate the cognitive capabilities of each rat group, while indicators of oxidative stress and insulin were assessed in mice. Neuronal apoptosis in distinct groups of mice's hippocampi was detected using TdT-mediated dUTP Nick-End Labeling (TUNEL), and western blot (WB) analysis was conducted to assess the expression of apoptosis- and autophagy-related proteins, including Bax, Bcl2, Caspase3, Caspase8, Beclin1, ATG7, LC3, p62, and Lamp2, within the hippocampus. TZQ exhibited the capacity to modulate neuronal autophagy, ameliorate endoplasmic reticulum stress, apoptosis, inflammation, and oxidative stress, as well as to regulate synaptic plasticity and conduction. TZQ mitigated cognitive dysfunction in mice, while also regulating hippocampal inflammation and apoptosis. Additionally, it influenced the protein expression of autophagy-related factors such as Bax, Bcl2, Caspase3, Caspase8, Beclin1, ATG7, and LC3. Notably, this modulation significantly reduced neuronal apoptosis in the hippocampus and curbed excessive autophagy. TZQ demonstrated a substantial reduction in neuronal apoptosis within the hippocampus and effectively suppressed excessive autophagy.

The mechanism of the Shuang Bai Su Qing recipe in treating periodontitis based on network pharmacology and molecular docking technology.

To explore the material basis of action of the Shuang Bai Su Qing recipe in the treatment of periodontitis using network pharmacology. Using TCMSP, we screened the chemical components of 5 drugs. The components were input into the UniProt and PubChem databases to obtain target proteins; Genecards, Online Mendelian Inheritance in Man (OMIM), and CEO databases were used to screen target proteins for periodontal disease. The targets were imported into the Cytoscape software to obtain intersecting targets, and conduct visual analysis to build the PPI network. The intersecting targets were then input into the Matescape database and subjected to biological process (BP) analysis, molecular function (MF) analysis, cell component (CC) analysis, and KEGG enrichment analysis. Twenty-seven TCM chemical components were obtained, with 198 target proteins associated with drugs and 2587 target proteins for periodontitis. Ten core targets were identified. Gene Ontology (GO) functional enrichment analysis yielded results for 20 BP, 11 MF, and 10 CC. KEGG analysis revealed that the main mechanisms of action were related to MAPK signaling pathway. Molecular docking results showed that luteolin strongly bind to TNF, IL6, and IL1B target proteins. The mechanism underlying the treatment of periodontitis with the recipe formula may be closely related to multiple targets in the MAPK signaling pathway.