In order to clarify the pathways closely linked to denervated muscle contracture, this work uses IoMT-enabled healthcare stratergies to examine changes in gene expression patterns inside atrophic muscles following brachial plexus damage. The gene expression Omnibus (GEO) database searching was used to locate the dataset GSE137606, which is connected to brachial plexus injuries. Strict criteria (|logFC|≥2 & adj.p < 0.05) were used to extract differentially expressed genes (DEGs). To identify dysregulated activities and pathways in denervated muscles, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and Gene Set Enrichment Analysis (GSEA) were used. Hub genes were found using Cytoscape software\'s algorithms, which took into account parameters like as proximity, degree, and MNC. Their expression, enriched pathways, and correlations were then examined. The results showed that 316 DEGs were predominantly concentrated in muscle-related processes such as tissue formation and contraction pathways. Of these, 297 DEGs were highly expressed in denervated muscles, whereas 19 DEGs were weakly expressed. GSEA showed improvements in the contraction of striated and skeletal muscles. In addition, it was shown that in denervated muscles, Myod1, Myog, Myh7, Myl2, Tnnt2, and Tnni1 were elevated hub genes with enriched pathways such adrenergic signaling and tight junction. These results point to possible therapeutic targets for denervated muscular contracture, including Myod1, Myog, Myh7, Myl2, Tnnt2, and Tnni1. This highlights treatment options for this ailment which enhances the mental state of patient.

Rhododendron arboreum: Sm., also known as Burans is traditionally used as an anti-inflammatory, anti-diabetic, hepatoprotective, adaptogenic, and anti-oxidative agent. It has been used since ancient times in Indian traditional medicine for various liver disorders. However, the exact mechanism behind its activity against NAFLD is not known. The aim of the present study is to investigate the molecular mechanism of Rhododendron arboreum flower (RAF) in the treatment of NAFLD using network pharmacology and molecular docking methods. Bioactives were also predicted for their drug-likeness score, probable side effects and ADMET profile. Protein-protein interaction (PPI) data was obtained using the STRING platform. For the visualisation of GO analysis, a bioinformatics server was employed. Through molecular docking, the binding affinity between potential targets and active compounds were assessed. A total of five active compounds of RAF and 30 target proteins were selected. The targets with higher degrees were identified through the PPI network. GO analysis indicated that the NAFLD treatment with RAF primarily entails a response to the fatty acid biosynthetic process, lipid metabolic process, regulation of cell death, regulation of stress response, and cellular response to a chemical stimulus. Molecular docking and molecular dynamic simulation exhibited that rutin has best binding affinity among active compounds and selected targets as indicated by the binding energy, RMSD, and RMSF data. The findings comprehensively elucidated toxicity data, potential targets of bioactives and molecular mechanisms of RAF against NAFLD, providing a promising novel strategy for future research on NAFLD treatment.

BACKGROUND: Drug research is increasingly using Network Pharmacology (NP) to tackle complex conditions like Metabolic Syndrome (MetS), which is characterized by obesity, hyperglycemia, and dyslipidemia. Single-action drugs are inadequate to treat MetS, which is marked by a range of complications including glucose intolerance, hyperlipidemia, mitochondrial dysfunction, and inflammation.
OBJECTIVE: To analyze Chandraprabha vati using Network Pharmacology to assess its potential in alleviating MetS-related complications.
METHODS: The genes related to MetS, inflammation, and the target genes of the CPV components were identified using network pharmacology tools like DisgNET and BindingDB. Followed by mapping of the CPV target genes with the genes implicated in MetS and inflammation to identify putative potential targets. Gene ontology, pathway enrichment analysis, and STRING database were employed for further exploration. Furthermore, drug-target-protein interactions network were visualized using Cytoscape 3.9.1.
RESULTS: The results showed that out of the 225 target genes of the CPV components, 33 overlapping and 19 non-overlapping genes could be potential targets for MetS. Similarly, 14 overlapping and 7 non-overlapping genes could be potential targets for inflammation. The CPV bioactives target genes were found to be involved in lipid and insulin homeostasis via several pathways revealed by the pathway analysis. The importance of CPV in treating MetS was supported by GO enrichment data; this could be due to its potential to influence pathways linked to metabolism, ER stress, mitochondrial dysfunction, oxidative stress, and inflammation.
CONCLUSIONS: These results offer a promising approach to developing treatment and repurposing CPV for complex conditions such as MetS.

As a traditional Chinese medicinal herb with a long history, Codonopsis pilosula (CP) has attracted much attention from the medical community in recent years. This review summarizes the research progress of CP in the medical field in the past 5 years. By searching and analyzing the literature, and combining with Cytoscape software, we comprehensively examined the role and mechanism of action of CP in individual application, combination drug application, and the role and mechanism of action of codonopsis pilosula\'s active ingredients in a variety of diseases. It also analyzes the medicinal use of CP and its application value in medicine. This review found that CP mainly manifests important roles in several diseases, such as cardiovascular system, nervous system, digestive system, immune system, etc., and regulates the development of many diseases mainly through the mechanisms of inflammation regulation, oxidative stress, immunomodulation and apoptosis. Its rich pharmacological activities and diverse medicinal effects endow CP with broad prospects and application values. This review provides valuable reference and guidance for the further development of CP in traditional Chinese medicine.

Alzheimer\'s disease (AD) is the leading cause of dementia worldwide with therapeutic lacunae till date. The beta-amyloid (Aβ) accumulation triggers AD pathogenesis, though clinical trials lowering Aβ have not altered disease outcomes suggesting other interacting factors to be identified for drug design of AD. Therefore, it is of interest to identify potential hub proteins interlinked with disease-driving pathways using a network-based approach for AD therapeutic designing. Literature mining was done to identify proteins implicated in AD etiology. Protein-protein interactions (PPIs) were retrieved from the STRING database and merged into a single network using Cytoscape 3.10.1. The hub proteins involved in AD etiology were predicted based on the topological algorithms of CytoHubba. Six major proteins, with STRING database identifiers - APP, BACE1, PSEN1, MAPT, APOE4 and TREM2, were identified to be involved in AD pathogenesis. The merged network of PPIs of these proteins contained 51 nodes and 211 edges, as predicted by Analyzer module of Cytoscape. The Amyloid precursor protein (APP) emerged as the highest-scoring hub protein across multiple centrality measures and topological algorithms. Thus, current data provides evidence to support the ongoing investigation of APP\'s multifaceted functions and therapeutic potential for AD.

BACKGROUND: This is a unique and novel study delineating the genotyping and subsequent prediction of AMR determinants of Vibrio cholerae revealing the potential of contemporary strains to serve as precursors of severe AMR crisis in cholera.
RESULTS: Genotyping of representative strains, VC1 and VC2 was undertaken to characterize antimicrobial resistance genes (ARGs) against chloramphenicol, SXT, nalidixic acid and streptomycin against which they were found to be resistant by antibiogram analysis in our previous investigation. strAB, sxt, sul2, qace∆1-sul1 were detected by PCR. Genome annotation and identification of ARGs with WGS helped to detect the presence of almG, varG, strA (APH(3\'\')-Ib), strB (APH(6)-Id), sul2, catB9, floR, CRP, dfrA1 genes. Signatures of resistance determinants and protein domains involved in antimicrobial resistance, primarily, efflux of antibiotics were identified on the basis of 30-100% homology to reference proteins. These domains were predicted to be involved in other metabolic functions on the basis of 100% identity with 100% coverage with reference protein and nucleotide sequences and were predicted to be of a diverse taxonomic origin accentuating the influence of the microbiota on AMR acquisition. Sequence analysis of QRDR (quinolone resistance-determining region) revealed SNPs. Cytoscape v3.8.2 was employed to analyse protein-protein interaction of MDR proteins, MdtA and EmrD-2, with nodes of vital AMR pathways. Vital nodes involved in efflux of different classes of antibiotics were found to be absent in VC1 and VC2 justifying the sensitivity of these strains to most antibiotics.
CONCLUSIONS: The study helped to examine the resistome of VC isolated from recent outbreaks to understand the underlying reason of sensitivity to most antibiotics and also to characterize the ARGs in their genome. It revealed that VC is a reservoir of signatures of resistance determinants and serving as precursors for severe AMR crisis in cholera. This is the first study, to our knowledge, which has scrutinized and presented systematically, information on prospective domains which bear the potential of serving as AMR determinants in VC with the help of bioinformatic tools. This pioneering approach may help in the prediction of AMR landfalls and benefit epidemiological surveillance and early warning systems.

This study presents a strategy for extracting significant gene complexes and then provides prospective therapeutics for AD. In this research, a total of 7905 reports published from 1981 to 2022 were retrieved. Following a review of all those articles, only the genetic association studies on AD were considered. Finally, there is a list of 453 Alzheimer-related genes in our dataset for network analysis. To this end, an experimentally derived protein-protein interaction (PPI) network from the String database was utilized to extract four meaningful gene complexes functionally interconnected using Cytoscape v3.9.1 software. The acquired gene complexes were subjected to an enrichment analysis using the ClueGO v2.5.9 tool to emphasize the most significant biological processes and pathways. Afterward, extracted gene complexes were used to extract the drugs related to AD from DGI v3.0 database and introduce some new drugs which may be helpful for this disease. Finally, a comprehensive network that included every gene connected to each gene complex group as well as the drug targets for each gene has been shown. Moreover, molecular docking studies have been performed with the selected compounds to identify the interaction pattern with the respective targets. Finally, we proposed a list of 62 compounds as multi-targeted directed drug-like compounds with a degree value between 2 and 5 and 30 compounds as target-specific drug-like compounds, which have not been proclaimed as AD-related drugs in prior scientific and medical investigations. Then, new drugs were suggested that can be experimentally examined for future work. In addition to this, four bipartite networks representing each group\'s genes and target miRNAs were established to introduce target miRNAs by using the miRWalk v3 server.

The spread of drug-resistant strains of tuberculosis has hampered efforts to control the disease worldwide. The Mycobacterium tuberculosis cell wall envelope is dynamic, with complex features that protect it from the host immunological response. As a result, the bacterial cell wall components represent a potential target for drug discovery. Protein-protein interaction networks (PPIN) are critical for understanding disease conditions and identifying precise therapeutic targets. We used a rational theoretical approach by constructing a PPIN with the proteins involved in cell wall biosynthesis. The PPIN was constructed through the STRING database and embB was identified as a key protein by using four topological measures, betweenness, closeness, degree, and eigenvector, in the CytoNCA tool in Cytoscape. The \'Drug repurposing\' approach was employed to find suitable inhibitors against embB. We used the Schrödinger suites for molecular docking, molecular dynamics simulation, and binding free energy calculations to validate the binding of protein with the ligand. FDA-approved drugs from the ZINC database and DrugBank were screened against embB (PDB ID: 7BVF) using high-throughput virtual screening, standard precision, and extra precision docking. The drugs were screened based on the XP docking score of the standard drug ethambutol. Accordingly, from the top five hits, azilsartan and dihydroergotamine were selected based on the binding free energy values and were further subjected to Molecular Dynamics Simulation studies for 100 ns. Our study confirms that Azilsartan and Dihydroergotamine form stable complexes with embB and can be used as potential lead molecules based on further in vitro and in vivo experimental validation.Communicated by Ramaswamy H. Sarma.

Pancreatic cancer shows malignancy around the world standing in 4th position for causing death globally. This cancer is majorly divided into exocrine and neuroendocrine where exocrine pancreatic ductal adenocarcinoma is observed to be nearly 85% of cases. The lack of diagnosis of pancreatic cancer is considered to be one of the major drawbacks to the prognosis and treatment of pancreatic cancer patients. The survival rate after diagnosis is very low, due to the higher incidence of drug resistance to cancer which leads to an increase in the mortality rate. The transcriptome analysis for pancreatic cancer involves dataset collection from the ENA database, incorporating them into quality control analysis to the quantification process to get the summarized read counts present in collected samples and used for further differential gene expression analysis using the DESeq2 package. Additionally, explore the enriched pathways using GSEA software and represented them by utilizing the enrichment map finally, the gene network has been constructed by Cytoscape software. Furthermore, explored the hub genes that are present in the particular pathways and how they are interconnected from one pathway to another has been analyzed. Finally, we identified the CDKN1A, IL6, and MYC genes and their associated pathways can be better biomarker for the clinical processes to increase the survival rate of of pancreatic cancer.

Protein-protein interactions (PPIs) are essential for understanding cell physiology in normal and pathological conditions, as they might involve in all cellular processes. PPIs have been widely used to elucidate the pathobiology of human and plant diseases. Therefore, they can also be used to unveil the pathobiology of infectious diseases in shrimp, which is one of the high-risk factors influencing the success or failure of shrimp production. PPI network analysis, specifically host-pathogen PPI (HP-PPI), provides insights into the molecular interactions between the shrimp and pathogens. This review quantitatively analyzed the research trends within this field through bibliometric analysis using specific keywords, countries, authors, organizations, journals, and documents. This analysis has screened 206 records from the Scopus database for determining eligibility, resulting in 179 papers that were retrieved for bibliometric analysis. The analysis revealed that China and Thailand were the driving forces behind this specific field of research and frequently collaborated with the United States. Aquaculture and Diseases of Aquatic Organisms were the prominent sources for publications in this field. The main keywords identified included \"white spot syndrome virus,\" \"WSSV,\" and \"shrimp.\" We discovered that studies on HP-PPI are currently quite scarce. As a result, we further discussed the significance of HP-PPI by highlighting various approaches that have been previously adopted. These findings not only emphasize the importance of HP-PPI but also pave the way for future researchers to explore the pathogenesis of infectious diseases in shrimp. By doing so, preventative measures and enhanced treatment strategies can be identified.