System biology-based assessment of the molecular mechanism of IMPHY000797 in Parkinson's disease: a network pharmacology and in-silico evaluation.

IMPHY000797 derivatives have been well known for their efficacy in various diseases. Moreover, IMPHY000797 derivatives have been found to modulate such genes involved in multiple neurological disorders. Hence, this study seeks to identify such genes and the probable molecular mechanism that could be involved in the pathogenesis of Parkinson's disease. The study utilized various biological tools such as DisGeNET, STRING, Swiss target predictor, Cytoscape, AutoDock 4.2, Schrodinger suite, ClueGo, and GUSAR. All the reported genes were obtained using DisGeNET, and further, the common genes were incorporated into the STRING to get the KEGG pathway, and all the data was converted to a protein/pathway network via Cytoscape. The clustering of the genes was performed for the gene-enriched data using two-sided hypergeometrics (p-value). The binding affinity of the IMPHY000797 was verified with the highest regulated 25 proteins via utilizing the "Monte Carlo iterated search technique" and the "Emodel and Glide score" function. Three thousand five hundred eighty-three genes were identified for Parkinson's disease and 31 genes for IMPHY000797 compound, among which 25 common genes were identified. Further, the "FOXO-signaling pathway" was identified to be a modulated pathway. Among the 25 proteins, the highest modulated genes and highest binding affinity were exhibited by SIRT3, FOXO1, and PPARGC1A with the compound IMPHY000797. Further, rat toxicity analysis provided the efficacy and safety of the compound. The study was required to identify the probable molecular mechanism, which needs more confirmation from other studies, which is still a significant hit-back.

Exploring the protective effect and molecular mechanism of betulin in Alzheimer's disease based on network pharmacology, molecular docking and experimental validation.

Alzheimer's disease (AD) is a neurodegenerative disorder that impairs learning and memory, with high rates of mortality. Birch bark has been traditionally used in the treatment of various skin ailments. Betulin (BT) is a key compound of birch bark that exhibits diverse pharmacological benefits and therapeutic potential in AD. However, the therapeutic effects and molecular mechanisms of BT in AD remain unclear. The present study aimed to predict the potential therapeutic targets of BT in the treatment of AD, and to determine the specific underlying molecular mechanisms through network pharmacology analysis and experimental validation. PharmMapper was used to predict the target genes of BT, and four disease databases were searched to screen for AD targets. The intersection targets were identified using the jveen website. Drug­disease target protein­protein interaction networks and hub genes were obtained and visualized using the Search Tool for the Retrieval of Interacting Genes/Proteins database and Cytoscape. The Database for Annotation, Visualization and Integrated Discovery was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, and AutoDock was used for molecular docking analysis of BT and hub genes. Subsequently, the network­predicted mechanisms of BT in AD were verified in vitro. A total of 495 BT and 1,386 AD targets were identified, and 120 were identified as potential targets of BT in the treatment of AD. The results of the molecular docking analysis revealed a strong binding affinity between BT and the hub genes. In addition, enrichment analyses of GO and KEGG pathways indicated that the neuroprotective effects of BT mainly involved the 'PI3K­Akt signaling pathway'. The results of in vitro experiments demonstrated that pretreatment with BT for 2 h may ameliorate formaldehyde (FA)­induced cytotoxicity and morphological changes in HT22 cells, and decrease FA­induced Tau hyperphosphorylation and reactive oxygen species levels. Furthermore, the PI3K/AKT signaling pathway was activated and the expression levels of downstream proteins, namely GSK3ß, Bcl­2 and Bax, were modified following pre­treatment with BT. Overall, the results of network pharmacology and in vitro analyses revealed that BT may reduce FA­induced AD­like pathology by modulating the PI3K/AKT signaling pathway, highlighting it as a potential multi­target drug for the treatment of AD.

Role and molecular mechanisms of HuangQiSiJunZi decoction for treating triple-negative breast cancer as explored via network pharmacology and bioinformatics analyses.

OBJECTIVE: In this study, we evaluated the molecular mechanisms of HuangQiSiJunZi Decoction (HQSJZD) for treating triple-negative breast cancer (TNBC) using network pharmacology and bioinformatics analyses. METHODS: Effective chemical components together with action targets of HQSJZD were selected based on the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Meanwhile, differentially expressed genes (DEGs) were extracted from TNBC sample data in The Cancer Genome Atlas (TCGA) database. Additionally, we built a protein-protein interaction (PPI) network and acquired hub genes. Gene Expression Omnibus(GEO) datasets were utilized to verify the accuracy of hub gene expression. Additionally, enrichment analyses were conducted on key genes. Furthermore, TNBC severity-related high-risk factors were screened through univariate together with multivariate Cox regressions; next, the logistic regression prediction model was built. Moreover, differential levels of 22 immune cell types in TNBC tissues compared with normal tissues were analyzed. The hub gene levels within pan-cancer and the human body were subsequently visualized and analyzed. Finally, quantitative PCR (RT-qPCR) was used to validate the correlation of the hub genes in TNBC cells. RESULTS: The study predicted 256 targets of active ingredients and 1791 DEGs in TNBC, and obtained 16 hub genes against TNBC. The prognostic signature based on FOS, MMP9, and PGR was independent in predicting survival. A total of seven types of immune cells, such as CD4 + memory T cells, showed a significant difference in infiltration (p < 0.05), and immune cells were related to the hub genes. The HPA database was adopted for hub gene analyses, and as determined, FOS was highly expressed in most human organs. The results of RT-qPCR validation for the FOS hub gene were consistent with those of bioinformatic analyses. CONCLUSION: HQSJZD might regulate the interleukin-17 and aging pathways via FOS genes to increase immune cell infiltration in TNBC tissues, and thus, may treat TNBC and improve the prognosis. The FOS genes are likely to be a new marker for TNBC.

Network pharmacology-based investigation and experimental validation of the mechanism of metformin in the treatment of acute myeloid leukemia.

Metformin, a widely used anti-diabetic agent, has shown significant anti-cancer properties as reported in in various cancers, including acute myeloid leukemia. However, the detailed mechanisms by which metformin influences acute myeloid leukemia remain unrevealed. Employing a synergistic approach of network pharmacology and experimental validation, this study systematically identifies and analyzes potential metformin targets and AML-related genes. These findings are then cross-referenced with biomedical databases to construct a target-gene network, providing insights into metformin's pharmacodynamics in AML treatment. Protein-Protein Interaction (PPI), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses are utilized. Results show metformin's effectiveness in inhibiting AML cell proliferation and inducing apoptosis through the AKT/HIF1A/PDK1 signaling pathway. This research provides insights into metformin's clinical application in AML treatment.

Integrating network pharmacology, molecular docking and experimental verification to explore the therapeutic effect and potential mechanism of nomilin against triple-negative breast cancer.

BACKGROUND: Nomilin is a limonoid compound known for its multiple biological activities, but its role in triple negative breast cancer (TNBC) remains unclear. This study aims to uncover the potential therapeutic effect of nomilin on TNBC and elucidate the specific mechanism of its action. METHODS: We employed weighted gene co-expression network analysis (WGCNA), differential expression analysis, and the GeneCards database to identify potential targets for TNBC. Simultaneously, we utilized the Swiss Target Prediction, ChEMBL, and STITCH databases to identify potential targets of nomilin. The core targets and mechanisms of nomilin against TNBC were predicted through protein-protein interaction (PPI) network analysis, molecular docking, and enrichment analysis. The results of the network pharmacology were corroborated by conducting experiments. RESULTS: A total of 17,204 TNBC targets were screened, and 301 potential targets of nomilin were identified. Through the PPI network, eight core targets of nomilin against TNBC were pinpointed, namely BCL2, Caspase3, CyclinD1, EGFR, HSP90AA1, KRAS, PARP1, and TNF. Molecular docking, molecular dynamics simulation and proteome microarray revealed that nomilin exhibits strong binding activity to these core proteins. Enrichment analysis results indicated that the anti-TNBC effect of nomilin is associated with PI3K/Akt pathway. In vitro and in vivo experiments have demonstrated that nomilin inhibits TNBC cell proliferation and migration while promoting cell apoptosis through the PI3K/Akt pathway. CONCLUSION: For the first time, the research effectively discovered the objectives and mechanisms of nomilin in combating TNBC using network pharmacology, molecular docking, molecular dynamics simulation, proteome microarray and experimental confirmation, presenting a hopeful approach for treating TNBC.

Integrating network pharmacology and bioinformatics to explore the mechanism of Xiaojian Zhongtang in treating major depressive disorder: An observational study.

Major depressive disorder (MDD) is a common mental illness. The traditional Chinese medicine compound Xiaojian Zhongtang (XJZT) has a good therapeutic effect on MDD, but the specific mechanism is not clear. The aim of this study is to explore the molecular mechanism of XJZT in the treatment of MDD through network pharmacology and bioinformatics. The traditional Chinese medicine system pharmacology database was used to screen the chemical components and targets of XJZT, while the online Mendelian inheritance in man, DisGeNET, Genecards, and therapeutic target database databases were used to collect MDD targets and identify the intersection targets of XJZT and MDD. A "drugs-components-targets" network was constructed using the Cytoscape platform, and the STRING was used for protein-protein interaction analysis of intersecting targets. Gene Ontology and Kyoto encyclopedia of genes and genomes analysis of intersecting targets was performed using the DAVID database. Obtain serum and brain transcriptome datasets of MDD from the gene expression omnibus database, and perform differentially expressed genes, weighted gene co-expression network analysis, gene set enrichment analysis, and receiver operating characteristic analysis. A total of 127 chemical components and 767 targets were obtained from XJZT, among which quercetin, kaempferol, and maltose are the core chemical components, and 1728 MDD targets were screened out, with 77 intersecting targets between XJZT and MDD. These targets mainly involve AGE-RAGE signaling pathway in diabetic complexes, epidermal growth factor receptor tyrosine kinase inhibitor resistance, and HIF-1 signaling pathway, and these core targets have strong binding activity with core components. In addition, 1166 differentially expressed genes were identified in the MDD serum transcriptome dataset, and weighted gene co-expression network analysis identified the most relevant gene modules (1269 genes), among which RAC-alpha serine/threonine-protein kinase (AKT1), D(4) dopamine receptor (DRD4), and kynurenine 3-monooxygenase (KMO) were target genes for the treatment of MDD with XJZT, these 3 genes are mainly related to the ubiquitin-mediated proteolysis, arachidonic acid (AA) metabolism, and Huntington disease pathways, and the expression of AKT1, DRD4, and KMO was also found in the MDD brain transcriptome dataset, which is significantly correlated with the occurrence of MDD. We have identified 3 key targets for XJZT treatment of MDD, including AKT1, KMO, and DRD4, and they can be regulated by the key components of XJZT, including quercetin, maltose, and kaempferol. This provides valuable insights for the early clinical diagnosis and development of therapeutic drugs for MDD.

The Chronic Toxicity of Endocrine-Disrupting Chemical to Daphnia magna: A Transcriptome and Network Analysis of TNT Exposure.

Endocrine-disrupting chemicals (EDCs) impair growth and development. While EDCs can occur naturally in aquatic ecosystems, they are continuously introduced through anthropogenic activities such as industrial effluents, pharmaceutical production, wastewater, and mining. To elucidate the chronic toxicological effects of endocrine-disrupting chemicals (EDCs) on aquatic organisms, we collected experimental data from a standardized chronic exposure test using Daphnia magna (D. magna), individuals of which were exposed to a potential EDC, trinitrotoluene (TNT). The chronic toxicity effects of this compound were explored through differential gene expression, gene ontology, network construction, and putative adverse outcome pathway (AOP) proposition. Our findings suggest that TNT has detrimental effects on the upstream signaling of Tcf/Lef, potentially adversely impacting oocyte maturation and early development. This study employs diverse bioinformatics approaches to elucidate the gene-level toxicological effects of chronic TNT exposure on aquatic ecosystems. The results provide valuable insights into the molecular mechanisms of the adverse impacts of TNT through network construction and putative AOP proposition.

Identification of autophagy-related signatures in doxorubicin-induced cardiotoxicity.

PURPOSE: Doxorubicin is an antibiotic drug used clinically to treat infectious diseases and tumors. Unfortunately, it is cardiotoxic. Autophagy is a cellular self-decomposition process that is essential for maintaining homeostasis in the internal environment. Accordingly, the present study was proposed to characterize the autophagy-related signatures of doxorubicin-induced cardiotoxicity. METHODS: Datasets related to doxorubicin-induced cardiotoxicity were retrieved by searching the GEO database and differentially expressed genes (DEGs) were identified. DEGs were taken to intersect with autophagy-related genes to obtain autophagy-related signatures, and Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and protein-protein interaction (PPI) network were performed on them. Further, construction of miRNA-hub gene networks and identification of target drugs to reveal potential molecular mechanisms and therapeutic strategies. Animal models of doxorubicin-induced cardiotoxicity were constructed to validate differences in gene expression for autophagy-related signatures. RESULTS: PBMC and heart samples from the GSE37260 dataset were selected for analysis. There were 995 and 2357 DEGs in PBMC and heart samples, respectively, and they had 23 intersecting genes with autophagy-related genes. RT-qPCR confirmed the differential expression of 23 intersecting genes in doxorubicin-induced cardiotoxicity animal models in general agreement with the bioinformatics results. An autophagy-related signatures consisting of 23 intersecting genes is involved in mediating processes and pathways such as autophagy, oxidative stress, apoptosis, protein ubiquitination and phosphorylation. Moreover, Akt1, Hif1a and Mapk3 are hub genes in autophagy-associated signatures and their upstream miRNAs are mainly rno-miR-1188-5p, rno-miR-150-3p and rno-miR-326-3p, and their drugs are mainly CHEMBL55802, Carboxyamidotriazole and 3-methyladenine. CONCLUSION: This study identifies for the first-time autophagy-related signatures in doxorubicin's cardiotoxicity, which could provide potential molecular mechanisms and therapeutic strategies for doxorubicin-induced cardiotoxicity.

Network medicine analysis for dissecting the therapeutic mechanism of consensus TCM formulae in treating hepatocellular carcinoma with different TCM syndromes.

Introduction: Hepatocellular carcinoma (HCC) is a major cause of cancer-related mortality worldwide. Traditional Chinese Medicine (TCM) is widely utilized as an adjunct therapy, improving patient survival and quality of life. TCM categorizes HCC into five distinct syndromes, each treated with specific herbal formulae. However, the molecular mechanisms underlying these treatments remain unclear. Methods: We employed a network medicine approach to explore the therapeutic mechanisms of TCM in HCC. By constructing a protein-protein interaction (PPI) network, we integrated genes associated with TCM syndromes and their corresponding herbal formulae. This allowed for a quantitative analysis of the topological and functional relationships between TCM syndromes, HCC, and the specific formulae used for treatment. Results: Our findings revealed that genes related to the five TCM syndromes were closely associated with HCC-related genes within the PPI network. The gene sets corresponding to the five TCM formulae exhibited significant proximity to HCC and its related syndromes, suggesting the efficacy of TCM syndrome differentiation and treatment. Additionally, through a random walk algorithm applied to a heterogeneous network, we prioritized active herbal ingredients, with results confirmed by literature. Discussion: The identification of these key compounds underscores the potential of network medicine to unravel the complex pharmacological actions of TCM. This study provides a molecular basis for TCM's therapeutic strategies in HCC and highlights specific herbal ingredients as potential leads for drug development and precision medicine.

Transcriptome Profiles Reveal Key Regulatory Networks during Single and Multifactorial Stresses Coupled with Melatonin Treatment in Pitaya (Selenicereus undatus L.).

In response to evolving climatic conditions, plants frequently confront multiple abiotic stresses, necessitating robust adaptive mechanisms. This study focuses on the responses of Selenicereus undatus L. to both individual stresses (cadmium; Cd, salt; S, and drought; D) and their combined applications, with an emphasis on evaluating the mitigating effects of (M) melatonin. Through transcriptome analysis, this study identifies significant gene expression changes and regulatory network activations. The results show that stress decreases pitaya growth rates by 30%, reduces stem and cladode development by 40%, and increases Cd uptake under single and combined stresses by 50% and 70%, respectively. Under stress conditions, enhanced activities of H2O2, POD, CAT, APX, and SOD and elevated proline content indicate strong antioxidant defenses. We identified 141 common DEGs related to stress tolerance, most of which were related to AtCBP, ALA, and CBP pathways. Interestingly, the production of genes related to signal transduction and hormones, including abscisic acid and auxin, was also significantly induced. Several calcium-dependent protein kinase genes were regulated during M and stress treatments. Functional enrichment analysis showed that most of the DEGs were enriched during metabolism, MAPK signaling, and photosynthesis. In addition, weighted gene co-expression network analysis (WGCNA) identified critical transcription factors (WRKYs, MYBs, bZIPs, bHLHs, and NACs) associated with antioxidant activities, particularly within the salmon module. This study provides morpho-physiological and transcriptome insights into pitaya's stress responses and suggests molecular breeding techniques with which to enhance plant resistance.

Exploration of N6-methyladenosine modification in ascorbic acid 2-glucoside constructed stem cell sheets.

The aim of this study was to explore the mechanism of bone marrow stem cells (BMSCs) sheets constructed with different doses of Ascorbic acid 2-glucoside (AA-2G) in conjunction with N6-methyladenosine (m6A)-associated epigenetic genes analysing transcriptome sequencing data. Experimental groups of BMSCs induced by different AA-2G concentrations were set up, and the tissue structures were observed by histological staining of cell slices and scanning electron microscopy. Expression patterns of DEGs were analysed using short-time sequence expression mining software, and DEGs associated with m6A were selected for gene ontology analysis and pathway analysis. The protein-protein interaction (PPI) network of DEGs was analysed and gene functions were predicted using the search tool of the Retrieve Interacting Genes database. There were 464 up-regulated DEGs and 303 down-regulated DEGs between the control and high-dose AA-2G treatment groups, and 175 up-regulated DEGs and 37 down-regulated DEGs between the low and high-dose AA-2G treatment groups. The profile 7 exhibited a gradual increase in gene expression levels over AA-2G concentration. In contrast, profile 0 exhibited a gradual decrease in gene expression levels over AA-2G concentration. In the PPI network of m6A-related DEGs in profile 7, the cluster of metallopeptidase inhibitor 1 (Timp1), intercellular adhesion molecule 1 (Icam1), insulin-like growth factor 1 (Igf1), matrix metallopeptidase 2 (Mmp2), serpin family E member 1 (Serpine1), C-X-C motif chemokine ligand 2 (Cxcl2), galectin 3 (Lgals3) and angiopoietin-1 (Angpt1) was the top hub gene cluster. The expression of all hub genes was significantly increased after AA-2G intervention (P < 0.05), and the expression of Igf1 and Timp1 increased with increasing intervention concentration. The m6A epigenetic modifications were involved in the AA-2G-induced formation of BMSCs. Igf1, Serpine1 and Cxcl2 in DEGs were enriched for tissue repair, promotion of endothelial and epithelial proliferation and regulation of apoptosis.

An integrated bioinformatics approach reveals the potential role of microRNA-30b-5p and let-7a-5p during SARS CoV-2 spike-1 mediated neuroinflammation.

SARS-CoV-2 induced neuroinflammation contributing to neurological sequelae is one of the critical outcomes of long-COVID, however underlying regulatory mechanisms involved therein are poorly understood. We deciphered the profile of dysregulated microRNAs, their targets, associated pathways, protein-protein interactions (PPI), transcription factor-hub genes interaction networks, hub genes-microRNA co-regulatory networks in SARS-CoV-2 Spike-1 (S1) stimulated microglial cells along with candidate drug prediction using RNA-sequencing and multiple bioinformatics approaches. We identified 11 dysregulated microRNAs in the S1-stimulated microglial cells (p < 0.05). KEGG analysis revealed involvement of important neuroinflammatory pathways such as MAPK signalling, PI3K-AKT signalling, Ras signalling and axon guidance. PPI analysis further identified 11 hub genes involved in these pathways. Real time PCR validation confirmed a significant upregulation of microRNA-30b-5p and let-7a-5p; proinflammatory cytokines- IL-6, TNF-α, IL-1ß, GM-CSF; and inflammatory genes- PIK3CA and AKT in the S1-stimulated microglial cells, while PTEN and SHIP1 expression was decreased as compared to the non-stimulated cells. Drug prediction analysis further indicated resveratrol, diclofenac and rapamycin as the potential drugs based on their degree of interaction with hub genes. Thus, targeting of these microRNAs and/or their intermediate signalling molecules would be a prospective immunotherapeutic approach in alleviating SARS-CoV-2-S1 mediated neuroinflammation; and needs further investigations.

Screening of differentially expressed RNAs and identifying a ceRNA axis during cadmium-induced oxidative damage in pancreatic ß cells.

Cadmium, a common metal pollutant, has been demonstrated to induce type 2 diabetes by disrupting pancreatic ß cells function. In this study, transcriptome microarray was utilized to identify differential gene expression in oxidative damage to pancreatic ß cells following cadmium exposure. The results indicated that a series of mRNAs, LncRNAs, and miRNAs were altered. Of the differentially expressed miRNAs, miR-29a-3p exhibited the most pronounced alteration, with an 11.62-fold increase relative to the control group. Following this, the target gene of miR-29a-3p was identified as Col3a1 through three databases (miRDB, miRTarbase and Tarbase), which demonstrated a decrease across the transcriptome microarray. The upstream target gene of miR-29a-3p was identified as NONMMUT036805, with decreased expression observed in the microarray. Finally, the expression trend of NONMMUT036805/miR-29a-3p/Col3a1 was reversed following NAC pretreatment. This was accompanied by a reduction in oxidative damage indicators, MDA/ROS/GSH-Px appeared to be negatively affected to varying degrees. In conclusion, this study has demonstrated that multiple RNAs are altered during cadmium exposure-induced oxidative damage in pancreatic ß cells. The NONMMUT036805/miR-29a-3p/Col3a1 axis has been shown to be involved in this process, which provides a foundation for the identification of potential targets for cadmium toxicity intervention.

Bioinformatics analysis of oxidative stress genes in the pathogenesis of ulcerative colitis based on a competing endogenous RNA regulatory network.

Background: Ulcerative colitis (UC) is a common chronic disease associated with inflammation and oxidative stress. This study aimed to construct a long noncoding RNA (lncRNA)-microRNA (miRNA)-messenger RNA (mRNA) network based on bioinformatics analysis and to explore oxidative stress-related genes underlying the pathogenesis of UC. Methods: The GSE75214, GSE48959, and GSE114603 datasets were downloaded from the Gene Expression Omnibus database. Following differentially expressed (DE) analysis, the regulatory relationships among these DERNAs were identified through miRDB, miRTarBase, and TargetScan; then, the lncRNA-miRNA-mRNA network was established. The Molecular Signatures Database (MSigDB) was used to search oxidative stress-related genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed for functional annotation and enrichment analyses. Based on the drug gene interaction database DGIdb, drugs that interact with oxidative stress-associated genes were explored. A dextran sulfate sodium (DSS)-induced UC mouse model was used for experimental validation. Results: A total of 30 DE-lncRNAs, 3 DE-miRNAs, and 19 DE-mRNAs were used to construct a lncRNA-miRNA-mRNA network. By comparing these 19 DE-mRNAs with oxidative stress-related genes in MSigDB, three oxidative stress-related genes (CAV1, SLC7A11, and SLC7A5) were found in the 19 DEM sets, which were all negatively associated with miR-194. GO and KEGG analyses showed that CAV1, SLC7A11, and SLC7A5 were associated with immune inflammation and steroid hormone synthesis. In animal experiments, the results showed that dexamethasone, a well-known glucocorticoid drug, could significantly decrease the expression of CAV1, SLC7A11, and SLC7A5 as well as improve UC histology, restore antioxidant activities, inhibit inflammation, and decrease myeloperoxidase activity. Conclusion: SLC7A5 was identified as a representative gene associated with glucocorticoid therapy resistance and thus may be a new therapeutic target for the treatment of UC in the clinic.

Towards an enhanced understanding of osteoanabolic effects of PTH-induced microRNAs on osteoblasts using a bioinformatic approach.

In this study, we used a bioinformatic approach to construct a miRNA-target gene interaction network potentially involved in the anabolic effect of parathyroid hormone analogue teriparatide [PTH (1-34)] on osteoblasts. We extracted a dataset of 26 microRNAs (miRNAs) from previously published studies and predicted miRNA target interactions (MTIs) using four software tools: DIANA, miRWalk, miRDB, and TargetScan. By constructing an interactome of PTH-regulated miRNAs and their predicted target genes, we elucidated signaling pathways regulating pluripotency of stem cells, the Hippo signaling pathway, and the TGF-beta signaling pathway as the most significant pathways in the effects of PTH on osteoblasts. Furthermore, we constructed intersection of MTI networks for these three pathways and added validated interactions. There are 8 genes present in all three selected pathways and a set of 18 miRNAs are predicted to target these genes, according to literature data. The most important genes in all three pathways were BMPR1A, BMPR2 and SMAD2 having the most interactions with miRNAs. Among these miRNAs, only miR-146a-5p and miR-346 have validated interactions in these pathways and were shown to be important regulators of these pathways. In addition, we also propose miR-551b-5p and miR-338-5p for further experimental validation, as they have been predicted to target important genes in these pathways but none of their target interactions have yet been verified. Our wet-lab experiment on miRNAs differentially expressed between PTH (1-34) treated and untreated mesenchymal stem cells supports miR-186-5p from the literature obtained data as another prominent miRNA. The meticulous selection of miRNAs outlined will significantly support and guide future research aimed at discovering and understanding the crucial pathways of osteoanabolic PTH-epigenetic effects on osteoblasts. Additionally, they hold potential for the discovery of new PTH target genes, innovative biomarkers for the effectiveness and safety of osteoporosis-affected treatment, as well as novel therapeutic targets.

Identification of hub genes and key pathways in arsenic-treated rice (Oryza sativa L.) based on 9 topological analysis methods of CytoHubba.

BACKGROUND: Arsenic is a toxic metalloid that can cause acute and chronic adverse health problems. Unfortunately, rice, the primary staple food for more than half of the world's population, is generally regarded as a typical arsenic-accumulating crop plant. Evidence indicates that arsenic stress can influence the growth and development of the rice plant, and lead to high concentrations of arsenic in rice grain. But the underlying mechanisms remain unclear. METHODS: In the present research, the possible molecules and pathways involved in rice roots in response to arsenic stress were explored using bioinformatics methods. Datasets that involving arsenic-treated rice root and the "study type" that was restricted to "Expression profiling by array" were selected and downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between the arsenic-treated group and the control group were obtained using the online web tool GEO2R. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed to investigate the functions of DEGs. The protein-protein interactions (PPI) network and the molecular complex detection algorithm (MCODE) of DEGs were analyzed using STRING and Cystoscope, respectively. Important nodes and hub genes in the PPI network were predicted and explored using the Cytoscape-cytoHubba plug-in. RESULTS: Two datasets, GSE25206 and GSE71492, were downloaded from Gene Expression Omnibus (GEO) database. Eighty common DEGs from the two datasets, including sixty-three up-regulated and seventeen down-regulated genes, were then selected. After functional enrichment analysis, these common DEGs were enriched mainly in 10 GO items, including glutathione transferase activity, glutathione metabolic process, toxin catabolic process, and 7 KEGG pathways related to metabolism. After PPI network and MCODE analysis, 49 nodes from the DEGs PPI network were identified, filtering two significant modules. Next, the Cytoscape-cytoHubba plug-in was used to predict important nodes and hub genes. Finally, five genes [Os01g0644000, PRDX6 (Os07g0638400), PRX112 (Os07g0677300), ENO1(Os06g0136600), LOGL9 (Os09g0547500)] were verified and could serve as the best candidates associated with rice root in response to arsenic stress. CONCLUSIONS: In summary, we elucidated the potential pathways and genes in rice root in response to arsenic stress through a comprehensive bioinformatics analysis.

Insight into Mantle Cell Lymphoma Pathobiology, Diagnosis, and Treatment Using Network-Based and Drug-Repurposing Approaches.

Mantle cell lymphoma (MCL) is a rare, incurable, and aggressive B-cell non-Hodgkin lymphoma (NHL). Early MCL diagnosis and treatment is critical and puzzling due to inter/intra-tumoral heterogeneity and limited understanding of the underlying molecular mechanisms. We developed and applied a multifaceted analysis of selected publicly available transcriptomic data of well-defined MCL stages, integrating network-based methods for pathway enrichment analysis, co-expression module alignment, drug repurposing, and prediction of effective drug combinations. We demonstrate the "butterfly effect" emerging from a small set of initially differentially expressed genes, rapidly expanding into numerous deregulated cellular processes, signaling pathways, and core machineries as MCL becomes aggressive. We explore pathogenicity-related signaling circuits by detecting common co-expression modules in MCL stages, pointing out, among others, the role of VEGFA and SPARC proteins in MCL progression and recommend further study of precise drug combinations. Our findings highlight the benefit that can be leveraged by such an approach for better understanding pathobiology and identifying high-priority novel diagnostic and prognostic biomarkers, drug targets, and efficacious combination therapies against MCL that should be further validated for their clinical impact.

Identification and Comprehensive Analysis of circRNA-miRNA-mRNA Regulatory Networks in A2780 Cells Treated with Resveratrol.

Ovarian cancer (OC) is one of the most commonplace gynecological malignancies. This study explored the effects of resveratrol (RES) on OC cell proliferation and apoptosis. Proliferation activity was measured for A2780 cells treated with RES for 24 h and 48 h at concentrations of 0, 10, 25, 50, 75, 100, 150, 200, and 300 µM. RNA sequencing (RNA-seq) was performed to analyze the circular RNA (circRNA), microRNA (miRNA), and messenger RNA (mRNA) expression spectrum. The differentially expressed genes included 460 circRNAs, 1988 miRNAs, and 1671 mRNAs, and they were subjected to analyses including Gene Ontology, the Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome enrichment. We selected signaling pathways enriched in the cell processes by mRNA KEGG, comprehensively analyzed the circRNA-miRNA-mRNA regulatory network, and verified several miRNAs expressed in the regulatory network diagram using the quantitative real-time polymerase chain reaction. The data showed that the cell proliferation of A2780 cells treated with RES for 24 h or 48 h decreased with increasing concentrations of RES. The circRNA-miRNA-mRNA regulatory network that we constructed provides new insights into the ability of RES to inhibit cell proliferation and promote apoptosis in A2780 cells.

Non-Hereditary Obesity Type Networks and New Drug Targets: An In Silico Approach.

Obesity, a chronic, preventable disease, has significant comorbidities that are associated with a great human and financial cost for society. The aim of the present work is to reconstruct the interactomes of non-hereditary obesity to highlight recent advances of its pathogenesis, and discover potential therapeutic targets. Obesity and biological-clock-related genes and/or gene products were extracted from the biomedical literature databases PubMed, GeneCards and OMIM. Their interactions were investigated using STRING v11.0 (a database of known and predicted physical and indirect associations among genes/proteins), and a high confidence interaction score of >0.7 was set. We also applied virtual screening to discover natural compounds targeting obesity- and circadian-clock-associated proteins. Two updated and comprehensive interactomes, the (a) stress- and (b) inflammation-induced obesidomes involving 85 and 93 gene/gene products of known and/or predicted interactions with an average node degree of 9.41 and 10.8, respectively, were produced. Moreover, 15 of these were common between the two non-hereditary entities, namely, ADIPOQ, ADRB2/3, CCK, CRH, CXCL8, FOS, GCG, GNRH1, IGF1, INS, LEP, MC4R, NPY and POMC, while phelligridin E, a natural product, may function as a potent FOX1-DBD interaction blocker. Molecular networks may contribute to the understanding of the integrated regulation of energy balance/obesity pathogenesis and may associate chronopharmacology schemes with natural products.

Network pharmacology-based approach to investigate the molecular targets and molecular mechanisms of Rosmarinus officinalis L. for treating aging-related disorders.

Aging, a natural biological process, presents challenges in maintaining physiological well-being and is associated with increased vulnerability to diseases. Addressing aging mechanisms is crucial for developing effective preventive and therapeutic strategies against age-related ailments. Rosmarinus officinalis L. is a medicinal herb widely used in traditional medicine, containing diverse bioactive compounds that have been studied for their antioxidant and anti-inflammatory properties, which are associated with potential health benefits. Using network pharmacology, this study investigates the anti-aging function and underlying mechanisms of R. officinalis. Through network pharmacology analysis, the top 10 hub genes were identified, including TNF, CTNNB1, JUN, MTOR, SIRT1, and others associated with the anti-aging effects. This analysis revealed a comprehensive network of interactions, providing a holistic perspective on the multi-target mechanism underlying Rosemary's anti-aging properties. GO and KEGG pathway enrichment analysis revealed the relevant biological processes, molecular functions, and cellular components involved in treating aging-related conditions. KEGG pathway analysis shows that anti-aging targets of R. officinalis involved endocrine resistance, pathways in cancer, and relaxin signaling pathways, among others, indicating multifaceted mechanisms. Genes like MAPK1, MMP9, and JUN emerged as significant players. These findings enhance our understanding of R. officinalis's potential in mitigating aging-related disorders through multi-target effects on various biological processes and pathways. Such approaches may reduce the risk of failure in single-target and symptom-based drug discovery and therapy.