Mechanism of Calculus Bovis treating keratitis based on network pharmacology / 中华实验眼科杂志

Objective:To investigate the complex Calculus Bovis-target-keratitis network and to explore the molecular mechanism of Calculus Bovis treating keratitis through network pharmacology. Methods:Genes related to keratitis were searched in the online DisGeNET database and the protein-protein interaction (PPI) network of keratitis-associated proteins was constructed.The components isolated and identified in Calculus Bovis were collected through the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP, https: //tcmsp-e.com/tcmsp.php), Chemistry Database by Shanghai Institute of Organic Chemistry of CAS (http: //www.organchem.csdb.cn), and published literature.The canonical SMILES information of the collected components was exported, which were submitted to the SwissTargetPrediction platform to predict potential targets of the components.The active component-predicted target network of Calculus Bovis was constructed and merged with the PPI network of keratitis-associated proteins to build the active component-potential target network of Calculus Bovis and systemically investigate the potential targets and signal pathways of Calculus Bovis in treatment of keratitis.The component-target-pathway network was established to analyze the mechanism of Calculus Bovis treating keratitis. Results:Thirty-nine components isolated and identified in Calculus Bovis were searched and 65 target genes related to keratitis were screened.Of the 28 potential targets involved in Calculus Bovis treating keratitis, there were 7 direct targets, including tumor necrosis factor, caspase 1, Toll-like receptor 9, C-X-C motif chemokine ligand 8, interleukin-6, mitogen-activated protein kinase 8, neurotrophic receptor tyrosine kinase 1.The 28 potential targets were annotated to 12 entries for biological process, 18 for cellular components and 13 for molecular function.In the Kyoto encyclopedia of genes and genomes pathway enrichment analysis, 10 signal pathways were identified as enriched categories, which were mainly related to human cytomegalovirus infection, amoebiasis, antifolate resistance, PI3K-Akt signaling pathway, rheumatoid arthritis, apoptosis, cytokine-cytokine receptor interaction, malaria, non-alcoholic fatty liver disease, interleukin-17 signaling pathway. Conclusions:Calculus Bovis may play an adjuvant therapeutic effect on keratitis through anti-inflammatory, antibacterial, antiviral, immune regulation, inflammatory regulation and other functions.

Identification of key immune related genes in diabetes retinopathy based on weighted gene co-expression network / 国际眼科杂志(Guoji Yanke Zazhi)

AIM: To explore the key genes related to immunity and immune cell infiltration levels in diabetes retinopathy(DR)using bioinformatics.METHODS: Differential expression genes(DEGs)were obtained by “limma” R from Gene Expression Omnibus(GEO)data from September to October 2022, Gene ontology(GO)and Kyoto encyclopedia of genes and genomes(KEGG)were analyzed, and the infiltration of immune cell types in each sample was calculated based on CIBERSORT algorithm. Weighted gene co-expression network analysis(WGCNA)was used to screen for DEGs in immune-related gene modules. The protein-protein interaction(PPI)network was established by STRING online database and Cytoscape, and the hub genes were screened by MCODE and cytoHubba plug-ins.RESULTS: The results showed that 1 426 up-regulated and 206 down-regulated differential genes were screened, where 7 immune cell types, including B cell naive, Plasma cells, CD4+T cells, T cells regulatory(Tregs), Macrophages M0, Macrophages M1 and Neutrophils were significantly overexpressed(P<0.05), while others were low expressed(P<0.05). After WGCNA, a total of 820 DEGs were found in the modules most related to immunity. After constructing the PPI network, 10 key genes were screened using plug-ins, and two key genes were further screened using the expression amount of each differential gene in PPI: DLGAP5 and AURKB.CONCLUSION: This study used bioinformatics to screen the infiltration of immune cells and key genes related to immunity in patients with DR. These findings may provide evidences for future research, diagnosis, and treatment of DR.

Bioinformatic analysis identifies potential key genes in the pathogenesis of age-related macular degeneration

Purpose: Age?related macular degeneration (AMD) is the leading cause of irreversible blindness in older individuals. More studies focused on screening the genes, which may be correlated with the development of AMD. With advances in various technologies like multiple microarray datasets, researchers could identify differentially expressed genes (DEGs) more accurately. Exploring abnormal gene expression in disease status can help to understand pathophysiological changes in complex diseases. This study aims to identify the key genes and upstream regulators in AMD and reveal factors, especially genetic association, and the prognosis of the development of this disease. Methods: Data from expression profile GSE125564 and profile GSE29801 were obtained from the Gene Expression Omnibus (GEO) database. We analyzed DEGs using R software (version 3.6.3). Functional enrichment and PPI network analysis were performed using the R package and online database STRING (version 11.0). Results: We compared AMD with normal and found 68 up?regulated genes (URGs) and 25 down?regulated genes (DRGs). We also compared wet AMD with dry AMD and found 41 DRGs in dry AMD. Further work including PPI network analysis, GO classification, and KEGG analysis was done to find connections with AMD. The URGs were mainly enriched in the biological process such as DNA replication, nucleoplasm, extracellular exosome, and cadherin binding. Besides, DRGs were mainly enriched in these functions such as an integral component of membrane and formation of the blood?aqueous barrier (BAB). Conclusion: This study implied that core genes might involve in the process of AMD. Our findings may contribute to revealing the pathogenesis, developing new biomarkers, and raising strategies of treatment for AMD

Macrophage differential genes and their functions in silicosis based on single cell RNA sequencing and spatial transcriptome sequencing / 环境与职业医学

Background The rise of single cell RNA sequencing (scRNA-seq) and spatial transcriptome sequencing technologies has allowed for intensive study of lung diseases, but both have been poorly studied in silicosis. Objective To explore differentially expressed genes DEGs in silicosis macrophages by scRNA-seq combined with spatial transcriptome sequencing and analyze the potential diagnostic genes. Methods Male C57BL/6 mice (5-6 weeks old, 22-30 g) were randomly divided into 4 groups: normal saline (NS) group for 7 d, NS group for 56 d, SiO2 group for 7 d, and SiO2 group for 56 d, with 1 mouse in each group. A silicosis model was constructed by tracheal drip injection of SiO2 suspension (0.2 g·kg−1, 50 g·cm−2), and the control mice were given the same volume of NS. The right lung was removed for scRNA-seq and the left lung for spatial transcriptome sequencing on day 7 and day 56, respectively. Cell populations were captured using principal component analysis techniques and dimensionality reduction of uniform manifold approximation and projection. The Find Markers function in R language was applied to analyze the DEGs changes of macrophages in two groups of lung tissues, and the corresponding DEGs were subjected to Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes signaling pathway analysis, while STRING and CytoHubba plug-ins of Cytoscape software were applied to protein-protein interaction network analysis to screen out key (Hub) genes. Spatial transcriptome sequencing was used to explore the original location of Hub genes on lung tissue sections and their mapping in lung macrophages. Finally, the correlation of Hub gene expression levels in lung tissues of silicosis patients and mouse silicosis models was verified, the diagnostic efficacy of Hub gene using subject operating characteristic curves (ROC). In vitro experiments by applying cell viability assay were conducted to verify the changes in viability of mouse macrophages (RAW264.7) under SiO2 stimulation. Results The scRNA-seq revealed a total of 20 clusters captured and defined. The results of scRNA-seq and spatial transcriptome sequencing showed an increased number of macrophages in the lung tissue of the SiO2 group compared to the NS group and clustered in the focal areas. Among the 97 macrophage DEGs screened out, 75 were up-regulated genes, and mainly enriched in chemotaxis and migration of neutrophils, chemokine receptor binding, tumor necrosis factor signaling pathway, cytokine-cytokine receptor interaction pathway, and interleukin-17 signaling pathway; and 22 were down-regulated genes, and mainly enriched in late endosomes, peroxisome proliferator-activated receptors signaling pathway, and alcoholic liver disease signaling pathway. A total of 2 core modules and 3 Hub genes were screened out, including Ccl2, Ccl7, and Ptgs2. The scRNA-seq showed that they were expressed at elevated levels in the SiO2 group compared to the NS group and clustered in additional macrophages, and the spatial transcriptome sequencing showed that they clustered in inflammatory areas with nodular lesions. The CCL7 and PTGS2 expressions were increased in the lung tissue of SiO2 patients compared with the healthy subjects, and the areas under the working curve of the subjects were 0.850 and 0.786, respectively. The viability of RAW264.7 cells was enhanced under SiO2 stimulation at 3 h, 6 h, and 12 h compared to those without the stimulation (P<0.05). Conclusion Bioinformatics screening have identified 3 Hub genes (Ccl2, Ccl7, and Ptgs2)and 2 potential diagnostic genes (CCL7 and PTGS2) in the lung tissue of silicosis mice, which may be potential molecular markers of early-stage silicosis with implications for the development and prognosis of silicosis.

Analysis of sepsis-related genes through weighted gene co-expression network / 中华危重病急救医学

Objective:To identify the Key genes in the development of sepsis through weighted gene co-expression network analysis (WGCNA).Methods:The gene expression dataset GSE154918 was downloaded from the public database Gene Expression Omnibus (GEO) database, which containes data from 105 microarrays of 40 control cases, 12 cases of asymptomatic infection, 39 cases of sepsis, and 14 cases of follow-up sepsis. The R software was used to screen out differentially expressed genes (DEG) in sepsis, and the distributed access view integrated database (DAVID), search tool for retrieval of interacting neighbouring genes (STRING) and visualization software Cytoscape were used to perform gene function and pathway enrichment analysis, Protein-protein interaction (PPI) network analysis and key gene analysis to screen out the key genes in the development of sepsis.Results:Forty-six candidate genes were obtained by WGCNA and combined with DEG expression analysis, and these 46 genes were analyzed by gene ontology (GO) and Kyoto City Encyclopedia of Genes and Genomes (KEGG) pathway enrichment to obtain gene functions and involved signaling pathways. The PPI network was further constructed using the STRING database, and 5 key genes were selected by the PPI network visualization software Cytoscape, including the mast cell expressed membrane protein 1 gene (MCEMP1), the S100 calcium-binding protein A12 gene (S100A12), the adipokine resistance factor gene (RETN), the c-type lectin structural domain family 4 member gene (CLEC4D), and peroxisome proliferator-activated receptor gene (PPARG), and differential expression analysis of each of these 5 genes showed that the expression levels of the above 5 genes were significantly upregulated in sepsis patients compared with healthy controls.Conclusion:In this study, 5 key genes related to sepsis were screened by constructing WGCNA method, which may be potential candidate targets related to sepsis diagnosis and treatment.

Gene co-expression network analysis provides a novel insight into the dynamic response of wheat to powdery mildew stress

Powdery mildew (Blumeria graminis f. sp. Tritici, (Bgt)) is an important worldwide fungal foliar disease of wheat (Triticum aestivum) responsible for severe yield losses. The development of resistance genes and dissection of the resistance mechanism will therefore be beneficial in wheat breeding. The Bgt resistance gene PmAS846 was transferred to the hexaploid wheat lines N9134 from Triticum dicoccoides, and it is still one of the most effective resistance genes. Here, by RNA sequencing, we identified three co-expressed gene modules using pairwise comparisons and weighted gene co-expression network analysis during wheat–Bgt interactions compared with mock-infected plants. Hub genes of stress-specific modules were significantly enriched in spliceosomes, phagosomes, the mRNA surveillance pathway, protein processing in the endoplasmic reticulum, and endocytosis. Induced module genes located on chromosome 5BL were selected to construct a protein–protein interaction network. Several proteins were predicted as the key hub node, including Hsp70, DEAD/DEAH box RNA helicase PRH75, elongation factor EF-2, cell division cycle 5, ARF guanine-nucleotide exchange factor GNOM-like, and protein phosphatase 2C 70 protein, which interacted with several disease resistance proteins such as RLP37, RPP13 and RPS2 analogues. Gene ontology enrichment results showed that wheat could activate binding functional genes via an mRNA transcription mechanism in response to Bgt stress. Of these node genes, GNOM-like, PP2C isoform X1 and transmembrane 9 superfamily member 9 were mapped onto the genetic fragment of PmAS846 with a distance of 4.8 Mb. This work provides the foundations for understanding the resistance mechanism and cloning the resistance gene PmAS846

Study of comparative proteome between normal and inverted karyotypes of human mesenchymal stem cells

Multipotent mesenchymal stem cells have been expanded in vitro for cellular therapy in numerous clinical settings without standardized culture conditions or quality-control schemes. The in vitro expansion is necessary to obtain sufficient cells for clinical applications. However, the expansion may induce genetic and functional abnormalities which may affect the safety and functionality of MSC, especially the chromosomal stability. This study aimed to investigate the protein profile of umbilical cord-derived MSC with normal and inverted karyotypes after expansion in the laboratory. Mass spectrometry analysis was performed and the Bradford method, Scaffold software, String and Cytoscape databases were employed to measure and characterize the protein content of umbilical cord-derived MSC. Networks of protein interactions, hub and bottleneck proteins were identified by proteomics and systems biology approaches. We found that proteins related to cellular stress were super expressed in inverted karyotype cells. Moreover, a high expression of Serpine 1, RHOA, and CTSB was found in these cells, which are proteins related to cancer. The albumin and ubiquitin proteins have been associated with a positive prognosis in cancer and cellular stress, and were up- and down-regulated in normal karyotype cells, respectively. The results suggests that the paracentric inversion inv(3)(p25p13) induced some type of cellular stress and genetic instability in human mesenchymal stem cells. These analyses showed the importance of carrying out studies related to the genetic instability of human mesenchymal stem cells using the protein expression profile as a parameter.

Analysis of Molecular Mechanism of Huangliantang in Treatment of Gastritis Based on Integrated Pharmacology Platform of Traditional Chinese Medicine / 中国实验方剂学杂志

Objective: To investigate the effective substance basis and possible mechanism of Huangliantang in treatment of gastritis. Method: Integrated pharmacology platform of traditional Chinese medicine was employed to predict the main active ingredients and functional targets of Huangliantang in treatment of gastritis, network of composition target-disease target of Huangliantang was constructed, key nodes were screened for enrichment analysis of pathways, and the possible mechanism of Huangliantang in treatment of gastritis with multiple ingredients-multiple targets-multiple pathways was explored. Result: A total of 175 predicted active ingredients of Huangliantang interacted with 538 key targets about gastritis, the regulation and treatment of gastritis during its different pathological stages, such as Helicobacter pylori infection, gastric mucosal damage and gastric mucosal atrophy, were involved through chemokine, T cell receptor, estrogen and other signaling pathways. Conclusion: This research may reveal the potential active ingredients of Huangliantang in treatment of gastritis and its possible mechanism, and it also provides a theoretical basis for further experimental research of pharmacodynamic substance basis and mechanism of action.

Effective Components and Mechanisms of Drynariae Rhizoma Anti-osteoporosis Based on Network Pharmacology / 中国实验方剂学杂志

Objective:To predict the target of active components of Drynariae Rhizoma by the network pharmacology, map related targets of osteoporosis (OP), and analyze key nodes of interaction topologically, so as to comprehensively explore the pharmacological mechanism of anti-op of osteoclasts. Method:Firstly, the main active components of Drynariae Rhizoma were screened out from TCMSP based on the pharmacokinetic characteristics, and the related targets were predicted by Pubchem and Swiss Target Prediction database according to the Two-dimensional/Three-dimensional(2D/3D)structural similarity. Then, through Online Mendelian Inheritance in Man (OMIM) and Pubmed text, known OP therapeutic targets were mined, based on putative targets, String database was imported to build Drynariae Rhizoma treatment target OP interaction network diagram. With the help of CytoNCA software, the interaction key nodes were topologically identified according to relevant node parameters, and then imported into String database to build the protein interaction network graph. Finally, biological functions and metabolic pathways of key nodes were analyzed through DAVID database. Result:Sixteen active components of Drynariae Rhizoma were screened out, and 118 related targets were predicted according to the target prediction technique. Totally 316 known therapeutic targets for OP were retrieved. The protein interaction network was constructed according to the String network database. A total of 97 key nodes were screened via CytoNCA topology. The enrichment analysis showed that Drynariae Rhizoma may play an anti-osteoporosis role by regulating stem cells, osteoblasts, osteoclasts and immune cells through multiple signaling pathways in aspects of proliferation, differentiation, immunity and oxidative stress. Conclusion:Studies based on network pharmacology have shown that Drynariae Rhizoma may play an anti-op role through direct or indirect targets and multiple major signaling pathways and affect the proliferation and differentiation of multiple types of cells, in order to provid a scientific basis for explaining the material basis and mechanism of Drynariae Rhizoma's anti-osteoporosis effect.

Nature-effect relationship research of traditional Chinese medicine for promoting blood circulation and removing blood stasis based on nature combination / 中国中药杂志

The efficacy of traditional Chinese medicine is the therapeutic effect of the drug on the body. The nature of traditional Chinese medicine is a further generalization of the effect of efficacy,and there is an intrinsic relationship between efficacy and nature of traditional Chinese medicine. In this study,the nature-effect relationship is found on the whole level,through the research mode of " nature combination-targets of traditional Chinese medicine-modules of protein interaction network-efficiency". The results showed that the warm-pungent-liver protein interaction network mainly participated in lipid catabolic process,blood coagulation,platelet activation,heme oxidation,platelet degranulation,apoptotic process,acute inflammatory response to exert the effect of anti-tumor,antithrombotic,anti-myocardial ischemia and anti-inflammatory.

Nature-effect relationship research of cold and warm medicinal properties of traditional Chinese medicine for promoting blood circulation and removing blood stasis based on nature combination / 中国中药杂志

Traditional Chinese medicine for promoting blood circulation and removing blood stasis is a kind of drug with cold or warm medicinal properties which is commonly used in clinical practice. It is an excellent carrier for studying the nature-effect relationship of traditional Chinese medicine. Therefore,this study will acquire the main active components and targets based on the drug-based research method. The Cytoscape 3. 5. 1 platform was used to construct the protein interaction network,and the Bin GO plug-in was used to perform functional annotation and statistical analysis on the identified functional modules. The results showed that the bitter-liver protein interaction network mainly participates in cell cycle process,lipid catabolic process,blood circulation to exert the effect of promoting blood circulation and removing blood stasis; the cold protein interaction network mainly participates in vasoconstriction through targets such as EDNRA,regulates blood coagulation through targets such as PLAU,and thus exerts the effect of cooling blood and eliminating phlegm; warm protein interaction network mainly participates in the regulation of platelet activation through targets such as P2 RY12,thereby exerting the effect of promoting blood circulation,relieving pain and relieving pain. This study explains the common characteristics of the bitter-liver combination and the specific characteristics of cold or warm medicinal properties from the molecular network level,which provides a new idea for the intrinsic relationship between the medicinal properties and efficacy of traditional Chinese medicine.

Molecular mechanism of Cinnamomi Ramulus-Paeoniae Radix Alba drug pair against sepsis based on integrative pharmacology platform of traditional Chinese medicine / 中国中药杂志

Guizhi Decoction is a resolving agent,which is a classic prescription for traditional Chinese medicine. It is effective in the treatment of sepsis in clinical practice. However,due to the complexity of the prescription,its anti-sepsis mechanism is difficult to be clarified. The " Cinnamomi Ramulus-Paeoniae Radix Alba" drug pair,as the classic compatibility for medicinal and medicinal herbs,is the core of Guizhi Decoction. In this study,Cinnamomi Ramulus-Paeoniae Radix Alba drug pair was used as the research object and the molecular mechanism of its treatment of sepsis was investigated by analyzing the chemical compositions with integrative pharmacology platform( TCMIP,http://www.tcmip.cn/),predicting disease target,analyzing gene function and pathway of " Cinnamomi Ramulus-Paeoniae Radix Alba" in treatment of sepsis,and establishing a multi-dimensional network relationship of " Chinese medicine-chemical components-core targets-key pathways". The prediction results of " Cinnamomi Ramulus-Paeoniae Radix Alba" drug pair showed that its anti-sepsis effect was associated with 45 active components,and the active components played an anti-sepsis role through multiple targets and pathways,involving inflammatory targets such as PF4,MyD88,TLR4,BDKRB2,CD14,and NOS3. The sepsis was relieved mainly by regulating Toll like signaling pathway,Fox O signaling pathway,chemokines signaling pathway,thyroid and insulin endocrine signaling pathways and biological processes. This study provides a scientific basis for further development of Cinnamomi Ramulus-Paeoniae Radix Alba drug pair and Guizhi Decoction against sepsis.

Study on mechanism of Xixian Tongshuan Capsules based on network pharmacology / 中国中药杂志

Xixian Tongshuan Capsules with functions of promoting blood circulation and removing blood stasis,dispelling wind and resolving phlegm,relaxing muscles and activating collaterals,restoring consciousness and inducing resuscitation,has significant effects on main and concurrently symptoms of apoplexy. In this research,908 chemical compounds of Xixian Tongshuan Capsules were collected,and 337 potential targets were discovered by pharmacophore based reverse target identification. Protein interaction network( PIN)was then constructed and Identifying Protein Complex Algorithm( IPCA) was used to obtain the modules of the capsule and analyze the potential action mechanism. According to the research,Xixian Tongshuan Capsules could play a therapeutic role for hyperlipidemia and hypertension by regulating lipid metabolic process and blood pressure,the most direct risk factors of apoplexy. It could be used to treat the cerebral thrombosis and irreversible death of nerve tissue caused by insufficient supply of cerebral tissue blood and oxygen,in a way of regulating blood circulation system and nervous system. Xixian Tongshuan Capsules could also treat stroke-induced inflammation and inflammatory immune response through its regulatory effect on inflammatory immune response. Based on the network analysis,the antiinflammatory activity of Xixian Tongshuan Capsules extracts was investigated by measuring the NO release with Griess reagent method through LPS-induced in vitro inflammation model of RAW264. 7 cells. The results showed that Xixian Tongshuan Capsules extracts inhibited the secretion of NO by LPS-induced RAW264. 7 cells,indicating favorable anti-inflammatory activity. This research illuminates the mechanism of Xixian Tongshuan Capsules based on the PIN analysis at molecular network level,providing a scientific basis for its clinical application.

Identification of prognosis-related genes in hepatocellular carcinoma based on bioinformatical analysis / 中国肿瘤生物治疗杂志

@# Objective: To identify the differentially expressed genes (DEGs) between hepatocellular carcinoma (HCC) tissues and normal liver tissues by bioinformatic methods, and to explore the intrinsic mechanism of these candidate genes involving in the occurrence and development of HCC from transcriptome level as well as the clinical significance of their associations with the prognosis of HCC patients. Methods: Gene expression profiles of GSE45267, GSE64041, GSE84402 and TCGA were downloaded from GEO (Gene Expression Omnibus) and TCGA(The Cancer GenomeAtlas), respectively. R software and Bioconductor packages were used to identify the DEGs between HCC tissues and para-cancer tissues, and then Gene Ontology (GO) Enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, Protein-Protein Interaction (PPI) network analysis and survival analysis were performed. Results: Forty-six up-regulated genes and 154 down-regulated genes were screened out,and GO enrichment analysis showed that these DEGs were mainly related to cell division, proliferation, cycle regulation, oxidation-reduction process and certain metabolic pathways. KEGG pathway analysis revealed that DEGs were mainly involved in tryptophan metabolism, retinol metabolism and other metabolic pathways as well as p53 pathway. Over-expression of a panel of up-regulated genes (CCNA2, CDK1, DLGAP5, KIF20A, KPNA2 and MELK) was shown to be significantly negatively correlated with the prognosis of HCC patients in the TCGA dataset (all P<0.01). Conclusion: A set of up-regulated hub genes that are negatively correlated with prognosis will provide potential guiding value for the clinical research on the diagnosis and treatment of HCC.

Identification of the targets of hematoporphyrin derivative in lung adenocarcinoma using integrated network analysis

BACKGROUND: Hematoporphyrin derivative (HPD) has a sensibilization effect in lung adenocarcinoma. This study was conducted to identify the target genes of HPD in lung adenocarcinoma. METHODS: RNA sequencing was performed using the lung adenocarcinoma cell line A549 after no treatment or treatment with X-ray or X-ray + HPD. The differentially expressed genes (DEGs) were screened using Mfuzz package by noise-robust soft clustering analysis. Enrichment analysis was carried out using "BioCloud" online tool. Protein-protein interaction (PPI) network and module analyses were performed using Cytoscape software. Using WebGestalt tool and integrated transcription factor platform (ITFP), microRNA target and transcription factor (TF) target pairs were separately predicted. An integrated regulatory network was visualized with Cytoscape software. RESULTS: A total of 815 DEGs in the gene set G1 (continuously dysregulated genes along with changes in processing conditions [untreated-treated with X-ray-X-ray + treated with HPD]) and 464 DEGs in the gene set G2 (significantly dysregulated between X-ray + HPD-treated group and untreated/X-ray-treated group) were screened. The significant module identified from the PPI network for gene set G1 showed that ribosomal protein L3 (RPL3) gene could interact with heat shock protein 90 kDa alpha, class A member 1 (HSP90AA1). TFs AAA domain containing 2 (ATAD2) and protein inhibitor of activated STAT 1 (PIAS1) were separately predicted for the genes in gene set G1 and G2, respectively. In the integrated network for gene set G2, ubiquitin-specific peptidase 25 (USP25) was targeted by miR-200b, miR-200c, and miR-429. CONCLUSION: RPL3, HSP90AA1, ATAD2, and PIAS1 as well as USP25, which is targeted by miR-200b, miR-200c, and miR-429, may be the potential targets of HPD in lung adenocarcinoma.

Identification of the molecular mechanisms associated with acute type A aortic dissection through bioinformatics methods

Aortic dissection is characterized by the redirection of blood flow, which flows through an intimal tear into the aortic media. The purpose of this study was to find potential acute type A aortic dissection (AAAD)-related genes and molecular mechanisms by bioinformatics. The gene expression profiles of GSE52093 were obtained from Gene Expression Omnibus (GEO) database, including 7 AAAD samples and 5 normal samples. The differentially expressed genes (DEGs) were detected between AAAD and normal samples. The functional annotation and pathway enrichment analysis were conducted through the Database for Annotation, Visualization and Integration Discovery (DAVID). A protein-protein interaction network was established by the Search Tool for the Retrieval of Interacting Genes (STRING) software. The microRNAs (miRNAs) of these differentially expressed genes were predicted using <microRNA.org> database. Moreover, DEGs were analyzed in the comparative toxicogenomics (CTD) database to screen out the potential therapeutic small molecules. As a result, there were 172 DEGs identified in patients with AAAD. These DEGs were significantly enriched in 6 pathways, including cell cycle, oocyte meiosis, DNA replication, extracellular matrix-receptor interaction, and mineral absorption pathway. Notably, CDC20, CDK1, CHEK1, KIF20A, MCM10, PBK, PTTG1, RACGAP, and TOP2A were crucial genes with a high degree in the protein-protein interaction network. Furthermore, potential miRNAs (miR-301, miR-302 family, and miR-130 family) were identified. In addition, small molecules like azathioprine and zoledronic acid were identified to be potential drugs for AAAD.

Identification of Key Genes of Airway Epithelial Cells in Asthma Patients by Bioinformatics-based Analysis / 中国医科大学学报

Objective We aimed to identify key genes and pathways of airway epithelial cells involved in bronchial asthma by comparing genetic information in the databases for patients with bronchial asthma and normal people. Methods To find differentially expressed genes (DEGs), mRNA microarray dataset, GSE43696, of airway epithelial cells in asthma was analyzed by GE02R. Functional and pathway enrichment analyses were performed for DEGs using the DAVID database. The protein-protein interaction networks were established using STRING to identify key genes and important complexes. Results A total of 355 DEGs were identified; of which, 130 were up-regulated and 225, down-regulated. The genes identified were involved in cell movement, growth factor binding, and ion channel activity. Nine key genes were recognized, including BDNF, ERBB2 IL6, VEGFA, KIT, ADCY4, PRKAR2B, CCR6, and NMU. Conclusion All nine key genes identified play important roles in asthma and serve as potential targets for treatment of bronchial asthma.

Gender-related Gene Expression in Sarcopenia in Old People:A Bioinformatic Analysis / 中国康复理论与实践

Objective To explore the gender differences in the genes expression of sarcopenia with bioinformatics. Methods The gene expression profiles downloaded from Gene Expression Omnibus database were analysed with BRB-Array Tools and STRING,then the protein-protein interaction network was built with Cytoscape. Results There were 152 genes up-regulated and 67 genes down-regulated in sarcopenic men,and 90 up-regulated and 52 down-regulated in women,with the same 47 up-regulated and 21 down-regulated.The gene ontology(GO)terms were found to be more complex in the sarcopenic women.The function analysis showed the same module genes were enriched in regulation of fat cell differentiation,protein kinase inhibitor activity and protein kinase regula-tor activity.In the protein-protein interaction networks,dystrophin,vimentin and tropomyosin α-3 were the most important in men,and metallothionein 1H and dynein light chain in women. Conclusion The nosogenesis of sarcopenia is different between genders from differentially expressed genes,that may be important for the future study.

Label-free quantitative proteomics reveals fibrinopeptide B and heparin cofactor II as potential serum biomarkers in respiratory syncytial virus-infected mice treated with Qingfei oral liquid formula / 中国天然药物

Respiratory syncytial virus (RSV) is a leading cause of acute lower respiratory tract infections. Qingfei oral liquid (QFOL), a traditional Chinese medicine, is widely used in clinical treatment for RSV-induced pneumonia. The present study was designed to reveal the potential targets and mechanism of action for QFOL by exploring its influence on the host cellular network following RSV infection. We investigated the serum proteomic changes and potential biomarkers in an RSV-infected mouse pneumonia model treated with QFOL. Eighteen BALB/c mice were randomly divided into three groups: RSV pneumonia model group (M), QFOL-treated group (Q) and the control group (C). Serum proteomes were analyzed and compared using a label-free quantitative LC-MS/MS approach. A total of 172 protein groups, 1009 proteins, and 1073 unique peptides were successfully identified. 51 differentially expressed proteins (DEPs) were identified (15 DEPs when M/C and 43 DEPs when Q/M; 7 DEPs in common). Classification and interaction network showed that these proteins participated in various biological processes including immune response, blood coagulation, complement activation, and so forth. Particularly, fibrinopeptide B (FpB) and heparin cofactor II (HCII) were evaluated as important nodes in the interaction network, which was closely involved in coagulation and inflammation. Further, the FpB level was increased in Group M but decreased in Group Q, while the HCII level exhibited the opposite trend. These findings not only indicated FpB and HCII as potential biomarkers and targets of QFOL in the treatment of RSV pneumonia, but also suggested a regulatory role of QFOL in the RSV-induced disturbance of coagulation and inflammation-coagulation interactions.

Label-free quantitative proteomics reveals fibrinopeptide B and heparin cofactor II as potential serum biomarkers in respiratory syncytial virus-infected mice treated with Qingfei oral liquid formula / 中国天然药物

Respiratory syncytial virus (RSV) is a leading cause of acute lower respiratory tract infections. Qingfei oral liquid (QFOL), a traditional Chinese medicine, is widely used in clinical treatment for RSV-induced pneumonia. The present study was designed to reveal the potential targets and mechanism of action for QFOL by exploring its influence on the host cellular network following RSV infection. We investigated the serum proteomic changes and potential biomarkers in an RSV-infected mouse pneumonia model treated with QFOL. Eighteen BALB/c mice were randomly divided into three groups: RSV pneumonia model group (M), QFOL-treated group (Q) and the control group (C). Serum proteomes were analyzed and compared using a label-free quantitative LC-MS/MS approach. A total of 172 protein groups, 1009 proteins, and 1073 unique peptides were successfully identified. 51 differentially expressed proteins (DEPs) were identified (15 DEPs when M/C and 43 DEPs when Q/M; 7 DEPs in common). Classification and interaction network showed that these proteins participated in various biological processes including immune response, blood coagulation, complement activation, and so forth. Particularly, fibrinopeptide B (FpB) and heparin cofactor II (HCII) were evaluated as important nodes in the interaction network, which was closely involved in coagulation and inflammation. Further, the FpB level was increased in Group M but decreased in Group Q, while the HCII level exhibited the opposite trend. These findings not only indicated FpB and HCII as potential biomarkers and targets of QFOL in the treatment of RSV pneumonia, but also suggested a regulatory role of QFOL in the RSV-induced disturbance of coagulation and inflammation-coagulation interactions.