Tool String Research Articles

Based on the Network Pharmacology to Analyze the Effect of Chuanxiong in Improving Diabetic Nephropathy

Aim: Chuanxiong diabetic nephropathy, network pharmacology, molecular docking, NCOA1, NCOA2, diabetic nephropathy (DN), ACEI/ARB. Background: The development of network pharmacology promotes the process of medicinal transformation of traditional Chinese medicine. This study took Chuanxiong as an example to analyze the active components in the treatment of DN. Objective: Molecular docking and other technologies have effectively helped the complex find the disease's active ingredients. Methods: The data of Chuanxiong was collected from the TCPSP database, DN gene expression data were collected through the NCBI database, and DN-related genes were obtained through differential analysis. In addition, the regulatory network of Chuanxiong and the main active components of DN treatment was constructed using String and Cytoscape tools. At the same time, PPI network interaction analysis was performed on core genes and GO. KEGG analysis was performed to predict essential genes using the Auto Dock tool. Results: Eight active components of Chuanxiong were screened out. NCOA1 and NCOA2 could interact with Angelica lactone A, Myricetin, Chrysophanol, Chuanxiong, naphthalize, and Chrysophanol. Meanwhile, Angelica Lactone A, Myricetin, Chrysophanol, Chuanxiong, naphthafunolide, and Chrysophanol can affect the regulation of estrogen signaling pathway, endocrine and other factors regulating calcium reabsorption and adipogenesis of adipocytes through the regulation of steroid hormone stimulation and regulation of cAMP-dependent protein kinase complex. Conclusion: NCOA1 and NCOA2 can be used as pharmacodynamic targets of Chuanxiong for improving DN.

In silico Analysis of Structure and Function of Hypothetical Proteins in Salmonella typhimurium (SL1344)

Salmonella typhimurium strain SL1344(S.typhi) is a non typhoidal bacteria which may cause infection in human gastrointestinal tract, may cause abdominal pain, fever, diarrhea, and inflammation some times which may lead to the human death. A comparative study of hypothetical outer membrane proteins of Salmonella typhimurium strain SL1344 (S.typhi) was performed using bioinformatic tools. Bioinformatics is a source to analyse whole genomic sequence of a vast number of uncharacterized genes. Online databases like UniProt, String, Pfam and other tools were used. Thirteen uncharacterized and hypothetical protein present in outer membrane of the bacteria S.typhi were retrieved from UniProt and its structure and function were studied. In this study the cellular function, pathway of enzyme interaction, antibiotic resistance were analyzed. The structure of the protein as well the function of these proteins provides better understanding to perform molecular docking and identification of small molecule inhibitors.

Identification of metabolic pathways and key genes associated with atypical parkinsonism using a systems biology approach.

Atypical parkinsonism (AP) is a group of complex neurodegenerative disorders with marked clinical and pathophysiological heterogeneity. The use of systems biology tools may contribute to the characterization of hub-bottleneck genes, and the identification of its biological pathways to broaden the understanding of the bases of these disorders. A systematic search was performed on the DisGeNET database, which integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. The tools STRING 11.0 and Cytoscape 3.8.2 were used for analysis of protein-protein interaction (PPI) network. The PPI network topography analyses were performed using the CytoHubba 0.1 plugin for Cytoscape. The hub and bottleneck genes were inserted into 4 different sets on the InteractiveVenn. Additional functional enrichment analyses were performed to identify Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and gene ontology for a described set of genes. The systematic search in the DisGeNET database identified 485 genes involved with Atypical Parkinsonism. Superimposing these genes, we detected a total of 31 hub-bottleneck genes. Moreover, our functional enrichment analyses demonstrated the involvement of these hub-bottleneck genes in 3 major KEGG pathways. We identified 31 highly interconnected hub-bottleneck genes through a systems biology approach, which may play a key role in the pathogenesis of atypical parkinsonism. The functional enrichment analyses showed that these genes are involved in several biological processes and pathways, such as the glial cell development, glial cell activation and cognition, pathways were related to Alzheimer disease and Parkinson disease. As a hypothesis, we highlight as possible key genes for AP the MAPT (microtubule associated protein tau), APOE (apolipoprotein E), SNCA (synuclein alpha) and APP (amyloid beta precursor protein) genes.

Network pharmacology and molecular docking study of Ermiaosan (二妙散) in the treatment of ulcerative colitis with dampness-heat syndrome

ObjectiveTo study Ermiaosan in the treatment of UC by using network pharmacology and molecular docking, and to provide references for experiments and clinical application for treating UC with dampness-heat syndrome.MethodsThe main active chemical components of Ermiaosan were screened out through TCMSP, the targets of components were obtained from TCMSP, the SwissTargetPrediction, TTD and the DrugBank database, and these targets genes were retrieved by UniProt database, the disease genes were obtained from TTD and Genecard database. String tool was used to constructed the PPI network, to built these components and their corresponding targets, Cytoscape software was applied to merge the networks and screen out the core network. And Bioinformatic analysis was performed using the OECloud tools to explore the enrichment analyses of GO and KEGG. Molecular docking was applied to check the affinity between the components and selected targets.ResultsForty-six main active components were predicted from Ermiaosan, and 408 intersection genes were screened from drug-disease genes. The enrichment included PI3K–Akt, TNF and HIF-1 signaling pathway, and the networks analysis showed that Ermiaosan acted on seven key targets AKT1, TNF, IL6,TP53, VEGFA, IL1B and CTNNB1 to play roles in treating UC. Molecular docking showed that top 3 chemical components could bind stably with these targets.ConclusionErmiaosan can relieve dampness-heat syndrome of UC, the possible potential mechanism might be related to the targets AKT1, TNF, IL6,TP53, VEGFA, IL1B and CTNNB1 linked with TNF, PI3K-Akt, and HIF-1 signaling pathway, it will provide meaningful references for further study in experiments and clinical investigations.

ACAT2 may be a novel predictive biomarker and therapeutic target in lung adenocarcinoma.

Acyl-coenzyme A cholesterol acyltransferase (ACAT) is a membrane-binding enzyme localized in the endoplasmic reticulum. ACAT2 can promote the development of colon cancer, but its efficacy in lung adenocarcinoma (LUAD) remains uncertain. ACAT2 expression was performed by using the TIMER2.0 database. The GEPIA database was utilized to analyze the correlation between ACAT2 expression and pathological stage of the tumor. Clinical prognosis was assessed through the Kaplan-Meier analysis. The CancerSEA database was employed to scrutinize the correlations between the ACAT2 expression and the functional status of various tumors, which were subsequently visualized as a heatmap. Furthermore, molecular interaction network analysis was performed by the STRING tool. High ACAT2 expression was associated with a poor DFS and OS in LUAD patients. Cox regression analysis indicated that the poor outcomes may be related to tumor stage, nodal stage, distant metastatic stage. ACAT2 was found to play a crucial role in various biological processes, including the cell cycle, DNA repair, DNA damage response, and proliferation. Enrichment pathway analysis revealed four ACAT2 related genes, ACOX1, EHHADH, OXCT1, and DLAT. Our study showed that ACAT2 was upregulated in LUAD, and had a worse survival. ACAT2 could be a novel predictive biomarker and therapeutic target in LUAD.

Proteomic changes of the bovine blood plasma in response to heat stress in a tropically adapted cattle breed.

Identifying molecular mechanisms responsible for the response to heat stress is essential to increase production, reproduction, health, and welfare. This study aimed to identify early biological responses and potential biomarkers involved in the response to heat stress and animal's recovery in tropically adapted beef cattle through proteomic analysis of blood plasma. Blood samples were collected from 14 Caracu males during the heat stress peak (HSP) and 16h after it (heat stress recovery-HSR) assessed based on wet bulb globe temperature index and rectal temperature. Proteome was investigated by liquid chromatography-tandem mass spectrometry from plasma samples, and the differentially regulated proteins were evaluated by functional enrichment analysis using DAVID tool. The protein-protein interaction network was evaluated by STRING tool. A total of 1,550 proteins were detected in both time points, of which 84 and 65 were downregulated and upregulated during HSR, respectively. Among the differentially regulated proteins with the highest absolute log-fold change values, those encoded by the GABBR1, EPHA2, DUSP5, MUC2, DGCR8, MAP2K7, ADRA1A, CXADR, TOPBP1, and NEB genes were highlighted as potential biomarkers because of their roles in response to heat stress. The functional enrichment analysis revealed that 65 Gene Ontology terms and 34 pathways were significant (P < 0.05). We highlighted those that could be associated with the response to heat stress, such as those related to the immune system, complement system, hemostasis, calcium, ECM-receptor interaction, and PI3K-Akt and MAPK signaling pathways. In addition, the protein-protein interaction network analysis revealed several complement and coagulation proteins and acute-phase proteins as important nodes based on their centrality and edges. Identifying differentially regulated proteins and their relationship, as well as their roles in key pathways contribute to improve the knowledge of the mechanisms behind the response to heat stress in naturally adapted cattle breeds. In addition, proteins highlighted herein are potential biomarkers involved in the early response and recovery from heat stress in tropically adapted beef cattle.

Dysregulated microRNAs in prostate cancer: In silico prediction and in vitro validation.

MicroRNAs, which are micro-coordinators of gene expression, have been recently investigated as a potential treatment for cancer. The study used computational techniques to identify microRNAs that could target a set of genes simultaneously. Due to their multi-target-directed nature, microRNAs have the potential to impact multiple key pathways and their pathogenic cross-talk. We identified microRNAs that target a prostate cancer-associated gene set using integrated bioinformatics analyses and experimental validation. The candidate gene set included genes targeted by clinically approved prostate cancer medications. We used STRING, GO, and KEGG web tools to confirm gene-gene interactions and their clinical significance. Then, we employed integrated predicted and validated bioinformatics approaches to retrieve hsa-miR-124-3p, 16-5p, and 27a-3p as the top three relevant microRNAs. KEGG and DIANA-miRPath showed the related pathways for the candidate genes and microRNAs. The Real-time PCR results showed that miR-16-5p simultaneously down-regulated all genes significantly except for PIK3CA/CB in LNCaP; miR-27a-3p simultaneously down-regulated all genes significantly, excluding MET in LNCaP and PIK3CA in PC-3; and miR-124-3p could not down-regulate significantly PIK3CB, MET, and FGFR4 in LNCaP and FGFR4 in PC-3. Finally, we used a cell cycle assay to show significant G0/G1 arrest by transfecting miR-124-3p in LNCaP and miR-16-5p in both cell lines. Our findings suggest that this novel approach may have therapeutic benefits and these predicted microRNAs could effectively target the candidate genes.

Discovery of ferroptosis-related genes in renal ischemia reperfusion and evaluate the potential impact on kidney transplantation.

Renal ischemia reperfusion injury (IRI) is one of the pivotal event of acute kidney injury (AKI), and they are unavoidable in the process of kidney transplantation, which eventually leads to the loss of renal allograft. Ferroptosis is a newly identified programmed cell death. Recent studies have suggested that ferroptosis may participate in the pathophysiological process of renal IRI. Therefore, we aimed to determine biomarkers associated with ferroptosis during renal IRI and their impact on renal allografts. We conducted a comprehensive bioinformatics analysis and established an IRI-AKI animal model to illustrate the critical role of ferroptosis-related hub genes (FRHGs) in IRI-AKI and their potential impact on kidney transplantation. In this study, we identified 60 ferroptosis-related genes (FRGs) in renal IRI based on the GSE148420 dataset and FerrDb database. And then we performed functional annotation analysis using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Protein-protein interaction (PPI) network was constructed by online tool String. EZH2, CDKN1A, PPARA, EGR1, ATF3, and CD44 were identited as six ferroptosis-related hubgenes (FRHGs) using four methods, including MMC, Degree, DMNC, and EPC. FRHGs expression level were verified by the validation sets GSE58438 and GSE126805. Protein expression level of FRHGs verified by Proteomics and Western blot. Cibersort was utilized to analyze immune cell infiltration during renal IRI as well as the correlation between FRHGs and immune cells. The GSE21374 dataset was used for renal allografts survival analysis. Finally, We induced the IRI-AKI animal model and illustrated the importance of FRGHs CD44 in ferroptosis and the accumulation of macrophages. We identified 6 FRHGs. We found that FRHGs not only exhibited significant correlation with immune cells but also directly influenced the survival of transplanted kidneys in the human population. Among six FRHGs, only CD44 was overexpressed at both the gene and protein levels. Anti-CD44 exerts a protective effect by inhibiting ferroptosis and the accumulation of M1 macrophages during renal IRI. This study provided new insights into the pathogenesis of renal IRI and provided new evidence for its treatment.

Statistical and network analyses reveal mechanisms for the enhancement of macrophage immunity by manganese in Mycobacterium tuberculosis infection

Tuberculosis is a significant infectious disease that poses a serious risk to human health. Our previous research has indicated that manganese ions reduce the bacterial load of Mycobacterium tuberculosis in macrophages, but the exact immune defense mechanism remains unknown. Several critical proteins and pathways involved in the host's immune response during this process are still unidentified. Our research aims to identify these proteins and pathways and provide a rationale for the use of manganese ions in the adjuvant treatment of tuberculosis. We downloaded GSE211666 data from the GEO database and selected the RM (Post-infection manganese ion treatment group) and Ra (single-infection group) groups for comparison and analysis to identify differential genes. These differential genes were then enriched and analyzed using STRING, Cytoscape, and NDEx tools to identify the two most relevant pathways of the “Host Response Signature Network.” After conducting an in-depth analysis of these two pathways, we found that manganese ions mainly mediate (1) the interferon -gamma (IFN-γ) and its receptor IFNGR and the downstream JAK-STAT pathway and (2) the NFκB pathway to enhance macrophage response to interferon, autophagy, polarization, and cytokine release. Using qPCR experiments, we verified the increased expression of CXCL10, MHCII, IFNγ, CSF2, and IL12, all of which are cytokines that play a key role in resistance to Mycobacterium tuberculosis infection, suggesting that macrophages enter a state of pro-inflammatory and activation after the addition of manganese ions, which enhances their immunosuppressive effect against Mycobacterium tuberculosis. We conclude that our study provides evidence of manganese ion's ability to treat tuberculosis adjuvantly.

Expression and Functional Analysis of core stemness factors OSKM (OCT4, SOX2, KLF4, and MYC) in Pan-cancer.

The dedifferentiation process of tumorigenesis and somatic cell reprogramming has some commonness and differences, which is the key question to cancer therapeutic strategy and stem cell applications. To further explore the commonalities and variance between carcinogenesis and induced pluripotent stem cell reprogramming, we investigated the role of stemness factors OSKM (OCT4, SOX2, KLF4, and MYC) in the pan-cancer process using public clinical data. Expression of OSKM in human pan-cancer was analyzed via the Genotype Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) database based on the RNA-seq data of tissues. The correlation of expression between OSKM genes was analyzed via the Tumor Immune Evaluation Resource (TIMER) database, while the STRING tool was used to construct the protein-protein interaction network for OSKM. Prognostic impact of OSKM in pan-cancer was analyzed by Cox proportional hazards regression model. The relationships between OSKM and tumor stemness, tumor microenvironment and immune checkpoint and were performed by Sangerbox platform using Pearson correlation analysis. Our results showed that OSKM were universally expressed and significantly altered in tumors compared with adjacent normal tissues in most tumor types. In addition, correlation analysis revealed the relevance of OSKM genes to patient prognosis, cancer cell stemness, tumor microenvironment or immune checkpoint. However, there is little similarity between these genes in terms of how they function in each cancer type. This study elucidates the different roles of core stemness factors OSKM in pan-cancer, offering potential therapeutic targets for novel anti-cancer strategies and knowledge to minimize the potential carcinogenic effects during stem cell transplantation.

Research on a Calculation Model of Cable Tension and Pumping Displacement of a Logging Tool String of Horizontal-Well Drillpipes

Summary With the vigorous development of unconventional oil and gas reservoirs, logging technology of horizontal-well drillpipes has become increasingly important. The improper selection of displacement during the pumping of drilling rods into horizontal wells can lead to accidents such as cable entanglement or tool-string pump detachment. Based on a comprehensive consideration of multiple factors such as drillpipe joints, small gap flow, pressure loss along the pipe, temperature, pressure, tool-string passability, and waterhole diameter variation, a cable tension analysis model for a logging tool string of a horizontal-well drillpipe is established. This model can predict a reasonable pumping displacement by analyzing the tension in the entire wellbore section, thereby avoiding cable entanglement or even tool-string pump detachment accidents during downhole operation. To verify the effectiveness of the model, we analyzed the cable tension during logging operations in Wells M1 and M2 using on-site test data and compared them with the measured tension data. The determination coefficient (R2), mean absolute error (MAE), and root mean square error (RMSE) were used to evaluate the degree of fit and accuracy of the model. The experimental results showed that the model can accurately predict the pumping displacement range before logging operations, ensuring that the cable does not entangle and the tool string is not pumped out during the downhole operation, thus providing effective methods and theoretical guidance for on-site drilling rod-pumping logging operations.

Stress Measurement Campaign in Scientific Deep Boreholes: Focus on Tools and Methods

As part of the Sectoral Plan for Deep Geological Repositories, three potential siting regions are currently being investigated by means of a focused geological exploration program in northern Switzerland. The program involved drilling eight vertical boreholes and one deviated deep borehole with at least two vertical boreholes per siting region. Stress testing was undertaken with a wireline formation testing tool in each borehole (around 20 stress tests per borehole). Improvements in the tool string were introduced step by step to sharpen the range of the stress estimates and enable 100% coverage of the desired lithological column. This is the first time that a single tool string with three packers has been run to perform the complete combination of sleeve fracturing (SF), hydraulic fracturing, and sleeve reopening (SR) tests. A dedicated stress testing protocol was developed to ensure the most robust estimate of the stress in a large variety of formations. A detailed planning process was developed to maximize the success rate and coverage of stress test stations, integrating all available information as it becomes available. A review of the techniques enabled by the new tool string for estimating the closure stress from a stress test, especially in low-permeability formations, is presented, and detailed stress testing examples are provided. A preliminary comparison between the stress estimates for the first two boreholes in the campaign is shown.

Decoding the significant diagnostic and prognostic importance of maternal embryonic leucine zipper kinase in human cancers through deep integrative analyses.

Cancer is a multifactorial disease and the second leading cause of human deaths worldwide. So far, the underlying mechanisms of cancer have not been yet fully elucidated. By using TCGA expression data, we determine the pathogenic roles of the maternal embryonic leucine zipper kinase (MELK) gene in various human cancers in this study. For this purpose, different online databases and tools (UALCAN, Kaplan-Meier (KM) plotter, TNMplot, GENT2, GEPIA, HPA, cBioPortal, STRING, Enrichr, TIMER, Cytoscape, DAVID, MuTarget, and CTD) were used. MELK gene expression was analyzed in a total of 24 human cancers and was found notably up-regulated in all the 24 analyzed tumor tissues relative to controls. Moreover, across a few specific cancers, including kidney renal clear cell carcinoma (KIRC), stomach adenocarcinoma (STAD), lung adenocarcinoma (LUAD), and liver hepatocellular carcinoma (LIHC) patients, MELK up-regulation was observed to be correlated with the shorter survival duration and metastasis. This valuable information highlighted that MELK plays a significant role in the development and progression of these four cancers. Based on clinical variables, MELK higher expression was also found in KIRC, STAD, LUAD, and LIHC patients with different clinical variables. Gene ontology and pathway analysis outcomes showed that MELK-associated genes notably co-expressed with MELK and belongs to a variety of diverse biological processes, molecular functions, and pathways. MELK expression was also correlated with promoter methylation levels, genetic alterations, other mutant genes, tumor purity, CD8+ T, and CD+4 T immune cells infiltrations in KIRC, STAD, LUAD, and LIHC. This pan-cancer study revealed the diagnostic and prognostic roles of MELK across four different cancers.

The molecular targets of Kangai injection in gastric cancer by in silico network pharmacology approach and experiment confirmation.

This study aimed to identify the phytochemical constituents that could target gastric cancer in Kangai injection using a network pharmacology-based approach. Protein-protein interactions (PPI), Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were conducted utilizing String and OmicShare tools. In the in vitro experiments, the related mRNA and protein levels were assessed via real-time quantitative polymerase chain reaction and Western blotting, respectively. Cell proliferation was assessed using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazoliumbromide (MTT) assay. Kangai injection comprises several compounds, which target multiple substrates and pathways related to gastric cancer. The PPI and Gene Ontology analyses revealed that tumor necrosis factor (TNF) was a hub gene. KEGG pathway enrichment analysis indicated that the the TNF pathway was significantly enriched. Kangai injection decreased the mRNA levels of TNFR2, TRAF2, PI3K, AKT, and IκBα and inhibited the phosphorylation of PI3K, AKT, and IκBα phosphorylations. Kangai injection inhibited cell proliferation, while TNFR2 overexpression or treatment with the PI3K activator 740 Y-P partially restored it. Kangai injection operates through multiple targets and pathways in gastric cancer, with the TNFR2/PI3K/AKT/NF-κB pathway playing a crucial role in its mechanism against gastric cancer.

Gymnemasylvestre as a potential therapeutic agent for PCOS: insights from mRNA differential gene expression and molecular docking analysis

BackgroundIn spite of the increased prevalence of Polycystic Ovary Syndrome in bilateral ovaries (PCOS) in females globally (~ 20%), the rate of decisive treatment is limited due to late and invasive diagnostics and the unavailability of stand-alone drugs against phenotypic symptoms associated with PCOS. This study aims at unravelling molecular mechanisms allied with this disorder and identifying genes and pathways that are altered causing PCOS as a pre-requisite need. Furthermore, this study intends at assessing the therapeutic potentials of Gymnemasylvestre phytocompounds mainly triterpene saponins against targeted proteins and helps in seeking exemplar drug candidates. The study is designed in 2 major parts—firstly identifying key proteins involved in pathophysiology by tracing back the deregulated genes in mRNA expression profiles of PCOS Patients obtained from GEO datasets database further compared and analysed by GEO2R Analyzer and significantly deregulated genes were subjected to PPI network, KEGG and GO analysis using STRING and ShinyGO tools. The second half of the study involved molecular docking its visualisation and in silico pharmacological analysis of imminent phytocompounds revealing plausible drug candidates.ResultsIn the study, most implied deregulated genes were MRP gene family, ICT1, NDUFA12, VDAC3, APOO, TOMM5, COX6C, COX7B, EDN1 and EDN3 genes whose functional enrichment suggests flawed metabolism of proteins and damaged mitochondrial translation. With high binding affinity, less toxicity at higher dose level Lupeol, Beta-Amyrin, Beta-Elemene, Stigmasterol, Gymnestrogenin and Dammarane proves to be efficient drug candidates.ConclusionThe findings of this study imply better understanding of the molecular mechanism of the disorder and encourage further clinical studies pertaining to medicinal natural phytocompounds of Gymnemasylvestre.

Identification of potential molecular mechanisms and therapeutic targets for recurrent pelvic organ prolapse

BackgroundThe pathogenesis of recurrent pelvic organ prolapse (POP) is currently unclear. Therefore, developing targeted preventive measures is difficult. This study identified potential key pathways, crucial genes, comorbidities, and therapeutic targets associated with the occurrence and development of recurrent POP. MethodsThe original microarray data GSE28660, GSE53868, and GSE12852 were downloaded from the GEO database. Identification and validation of differentially expressed genes (DEGs) and hub genes associated with recurrent POP were performed using R software and cytoHubba of Cytoscape. Protein–protein interaction (PPI) networks were constructed using the STRING tool and visualized using Cytoscape. Gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) enrichment analyses were effectively performed using DAVID platforms. In addition, the NetworkAnalyst platform was used to explore and visualize the miRNA–hub gene network, TF–hub gene network, hub gene–disease network, and hub gene–drug/chemical network. ResultsA total of 110 DEGs and 6 hub genes (ADIPOQ, IL6, PPARG, CEBPA, LPL, and LIPE) were identified in this study. These genes were primarily enriched in the PPAR, AMPK, and adipocytokine, non-alcoholic fatty liver disease, and signaling pathways related to glycerol metabolism. Moreover, 96 miRNAs and 97 TFs were identified to as being associated with recurrent POP. These genes were closely linked to adipocyte metabolism and distribution, energy metabolism, and the longevity regulatory pathway. In addition, 192 diseases or chronic complications were potentially related to the recurrence of POP, including diabetes, hypertension, obesity, inflammatory diseases, and chronic obstructive pulmonary disease. Furthermore, 954 drugs or compounds were shown to have therapeutic potential for recurrent POP, and the most critical target drugs were dexamethasone, bisphenol A, efavirenz, 1-methyl-3-isobutylxanthine, and estradiol. ConclusionsThe results of this study revealed that ADIPOQ, IL6, PPARG, CEBPA, LPL, and LIPE as potential hub genes associated with recurrent POP, and these hub genes may aid in the understanding of the mechanism underlying POP recurrence and the development of potential molecular drugs.

COVID-19: A novel holistic systems biology approach to predict its molecular mechanisms (in vitro) and repurpose drugs.

COVID-19 strangely kills some youth with no history of physical weakness, and in addition to the lungs, it may even directly harm other organs. Its complex mechanism has led to the loss of any significantly effective drug, and some patients with severe forms still die daily. Common methods for identifying disease mechanisms and drug design are often time-consuming or reductionist. Here, we use a novel holistic systems biology approach to predict its molecular mechanisms (in vitro), significant molecular relations with SARS, and repurpose drugs. We have utilized its relative phylogenic similarity to SARS. Using the available omics data for SARS and the fewer data for COVID-19 to decode the mechanisms and their significant relations, We applied the Cytoscape analyzer, MCODE, STRING, and DAVID tools to predict the topographically crucial molecules, clusters, protein interaction mappings, and functional analysis. We also applied a novel approach to identify the significant relations between the two infections using the Fischer exact test for MCODE clusters. We then constructed and analyzed a drug-gene network using PharmGKB and DrugBank (retrieved using the dgidb). Some of the shared identified crucial molecules, BPs and pathways included Kaposi sarcoma-associated herpesvirus infection, Influenza A, and NOD-like receptor signaling pathways. Besides, our identified crucial molecules specific to host response against SARS-CoV-2 included FGA, BMP4, PRPF40A, and IFI16. We also introduced seven new repurposed candidate drugs based on the drug-gene network analysis for the identified crucial molecules. Therefore, we suggest that our newly recommended repurposed drugs be further investigated in Vitro and in Vivo against COVID-19.

Bacterial network construction and molecular docking approach to study interaction of Myristica fragrans on Acne infections

Acne vulgaris is a very common bacterial infection caused. Herbal remedies have always give a positive response in treatment of various disease in disorders. The present study works on predicting the probable interactions between the Myristica fragrans bioactives with the bacterial targets via network pharmacology and docking techniques. The bio-actives and disease targets were obtained from open databases and literature review. Protein and pathway enrichment analysis was done by utilizing metascape and STRING tool. Cytoscape tool were utilized for construction of network. The compounds were further assessed using molsoft tools and docking was done using auto-dock tools. The potential bio-actives were selected further the network construction gave insights on the highest degree values. The targets with highest interactions were docked and the complex which showed good binding was selected. It was found that Stigmasterol and Campesterol have the highest potential and can be considered as hit compounds for further studies too. &#x0D;

Prognostic impact of MICALL1 and associates with immune infiltration in liver hepatocellular carcinoma patients.

Liver hepatocellular carcinoma (LIHC) is one of the most malignancy over the world. Previous studies have proven that Molecules Interacting with CasL-Like 1 (MICALL1) participated in cellular trafficking cascades, while there has no study to explore the function and carcinogenic mechanism MICALL1 in LIHC. We aimed to investigate the relationship between MICALL1 mRNA expression and LIHC using TCGA database. The expression of MICALL1 protein in clinic samples were examined by UALCAN database. Kaplan-Meier method was used for survival analysis. Logistic regression and Cox regression were performed to evaluate the prognostic significance of MICALL1. The MICALL1-binding protein were built by the STRING tool. Enrichment analysis by GO, KEGG and GSEA was used to explore possible function of MICALL1. The ssGSEA method was used to investigate the association between MICALL1 expression and the immune infiltration level in LIHC. The expression and prognostic value of different MICAL family members in LIHC were evaluated. The expression of MICALL1 was significantly increased at both the transcript and protein levels in LIHC tissues. Further, the LIHC patients with high MICALL1 levels showed a worse OS, DSS and PFI. Some clinicopathologic features were identified to be related to MICALL1 expression in LIHC included clinical T stage, pathologic stage, histologic grade and AFP concentration. Univariate and multivariate survival analysis showed that MICALL1 was an independent prognostic marker for OS and DSS. Further enrichment analysis revealed that the K-RAS, TNFα/NF-κB and inflammatory response were significantly enriched in the high MICALL1 expression group. Immune infiltration analysis showed that high MICALL1 expression was correlated with infiltration level of macrophage cells, Th2 cells and some other immune cell types, including TFH. MICALL1 expression was significantly associated with immune cell infiltration and may regarded as a promising prognostic biomarker for LIHC patients.

Identification of 5 hub genes for diagnosis of coronary artery disease.

Coronary artery disease (CAD) is a main cause leading to increasing mortality of cardiovascular disease (CVD) worldwide. We aimed to discover marker genes and develop a diagnostic model for CAD. CAD-related target genes were searched from DisGeNET. Count expression data and clinical information were screened from the GSE202626 dataset. edgeR package identified differentially expressed genes (DEGs). Using online STRING tool and Cytoscape, protein-protein reactions (PPI) were predicted. WebGestaltR package was employed to functional enrichment analysis. We used Metascape to conduct module-based network analysis. VarElect algorithm provided genes-phenotype correlation analysis. Immune infiltration was assessed by ESTIMATE package and ssGSEA analysis. mRNAsi was determined by one class logistic regression (OCLR). A diagnostic model was constructed by SVM algorithm. 162 target genes were screened by intersection 1,714 DEGs and 1,708 CAD related target genes. 137 target genes of the 162 target genes were obtained using PPI analysis, in which those targets were enriched in inflammatory cytokine pathways, such as chemokine signaling pathway, and IL-17 signaling pathway. From the above 137 target genes, four functional modules (MCODE1-4) were extracted. From the 162 potential targets, CAD phenotype were directly and indirectly associated with 161 genes and 22 genes, respectively. Finally, 5 hub genes (CCL2, PTGS2, NLRP3, VEGFA, LTA) were screened by intersections with the top 20, directly and indirectly, and genes in MCODE1. PTGS2, NLRP3 and VEGFA were positively, while LTA was negatively correlated with immune cells scores. PTGS2, NLRP3 and VEGFA were negatively, while LTA was positively correlated with mRNAsi. A diagnostic model was successfully established, evidenced by 92.59% sensitivity and AUC was 0.9230 in the GSE202625 dataset and 94.11% sensitivity and AUC was 0.9706 in GSE120774 dataset. In this work, we identified 5 hub genes, which may be associated with CAD development.