Search

In spite of 150 years of studying malaria, the unique features of the malarial parasite, Plasmodium, still perplex researchers. One of the methods by which the parasite manages its gene expression is epigenetic regulation, the champion of which is PfGCN5, an essential enzyme responsible for acetylating histone proteins. PfGCN5 is a ∼170 kDa chromatin-remodeling enzyme that harbors the conserved bromodomain and acetyltransferase domain situated in its C-terminus domain. Although the PfGCN5 proteolytic processing is essential for its activity, the specific protease involved in this process still remains elusive. Identification of PfGCN5 interacting proteins through immunoprecipitation (IP) followed by LC-tandem mass spectrometry analysis revealed the presence of food vacuolar proteins, such as the cysteine protease Falcipain 3 (FP3), in addition to the typical members of the PfGCN5 complex. The direct interaction between FP3 and PfGCN5 was further validated by in vitro pull-down assay as well as IP assay. Subsequently, use of cysteine protease inhibitor E64d led to the inhibition of protease-specific processing of PfGCN5 with concomitant enrichment and co-localization of PfGCN5 and FP3 around the food vacuole as evidenced by confocal microscopy as well as electron microscopy. Remarkably, the proteolytic cleavage of the nuclear protein PfGCN5 by food vacuolar protease FP3 is exceptional and atypical in eukaryotic organisms. Targeting the proteolytic processing of GCN5 and the associated protease FP3 could provide a novel approach for drug development aimed at addressing the growing resistance of parasites to current antimalarial drugs., (© 2024 International Union of Biochemistry and Molecular Biology, Inc.)

Objective: This study explores the frequency of human leukocyte antigen (HLA) genes, particularly HLA-B alleles, within the Kuwaiti population. We aim to identify alleles with known associations to adverse drug reactions (ADRs) based on existing literature. We focus on the HLA-B gene due to its well-documented associations with severe cutaneous adverse reactions and the extensive pharmacogenetic research supporting its clinical relevance., Methods: We utilized the HLA-HD tool to extract, annotate, and analyse HLA-B alleles from the exome data of 561 Kuwaiti individuals, sequenced on the Illumina HiSeq platform. HLA typing was conducted using the HLA-HD tool with a reference panel from the IPD-IMGT/HLA database. The major HLA-B pharmacogenetic markers were obtained from the HLA Adverse Drug Reaction Database, focusing on alleles with significant ADR associations in published literature., Results: The distribution of HLA-B alleles in the Kuwaiti population revealed that the most frequent alleles were HLA-B*50:01 (10.52%), HLA-B*51:01 (9.89%), HLA-B*08:01 (6.06%), HLA-B*52:01 (4.55%), HLA-B*18:01 (3.92%), and HLA-B*41:01 (3.65%). Notably, alleles HLA-B*13:01, HLA-B*13:02, HLA-B*15:02, HLA-B*15:13, HLA-B*35:02, HLA-B*35:05, HLA-B*38:01, HLA-B*40:02, HLA-B*44:03, HLA-B*51:01, HLA-B*57:01 and HLA-B*58:01 were identified with known associations to various ADRs. For example, HLA-B*51:01 was associated with clindamycin, phenobarbital, and phenytoin, and was found in 18% of individuals., Conclusion: Our study enriches the regional genetic landscape by delineating HLA-B allele variations within Kuwait and across the Arabian Peninsula. This genetic insight, along with the identification of markers previously linked to drug hypersensitivity, provides a foundation for future pharmacogenetic research and potential personalized medicine strategies in the region., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Dashti, Malik, Al-Matrouk, Bhatti, Nizam, Jacob, Al-Mulla and Thanaraj.)

Introduction: Increasing evidence from human and animal model studies indicates the significant role of microRNAs (miRNAs) in pancreatic beta cell function, insulin signaling, immune responses, and pathogenesis of type 1 diabetes (T1D)., Methods: We aimed, using next-generation sequencing, to screen miRNAs from peripheral blood mononuclear cells of eight independent Kuwaiti-Arab families with T1D affected siblings, consisting of 18 T1D patients and 18 unaffected members, characterized by no parent-to-child inheritance pattern., Results: Our analysis revealed 20 miRNAs that are differentially expressed in T1D patients compared with healthy controls. Module-based weighted gene co-expression network analysis prioritized key consensus miRNAs in T1D pathogenesis. These included hsa-miR-320a-3p, hsa-miR-139-3p, hsa-miR-200-3p, hsa-miR-99b-5p and hsa-miR-6808-3p. Functional enrichment analysis of differentially expressed miRNAs indicated that PI3K-AKT is one of the key pathways perturbed in T1D. Gene ontology analysis of hub miRNAs also implicated PI3K-AKT, along with mTOR, MAPK, and interleukin signaling pathways, in T1D. Using quantitative RT-PCR, we validated one of the key predicted miRNA-target gene-transcription factor networks in an extended cohort of children with new-onset T1D positive for islet autoantibodies. Our analysis revealed that hsa-miR-320a-3p and its key targets, including PTEN, AKT1, BCL2, FOXO1 and MYC , are dysregulated in T1D, along with their interacting partners namely BLIMP3, GSK3B , CAV1, CXCL3, TGFB , and IL10 . Receiver Operating Characteristic analysis highlighted the diagnostic potential of hsa-miR-320a-3p, CAV1, GSK3B and MYC for T1D., Discussion: Our study presents a novel link between hsa-miR-320a-3p and T1D, and highlights its key regulatory role in the network of mRNA markers and transcription factors involved in T1D pathogenesis., Competing Interests: JT is a stock owner in Orion Pharma. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be constructed as a potential conflict of interest., (Copyright © 2024 Nizam, Malik, Jacob, Alsmadi, Koistinen, Tuomilehto, Alkandari, Al-Mulla and Thanaraj.)

Lung cancer is among leading causes of death worldwide. The five-year survival rate of this disease is extremely low (17.8 %), mainly due to difficult early diagnosis and to the limited efficacy of currently available chemotherapeutics. This underlines the necessity to develop innovative therapies for lung cancer. In this context, drug repurposing represents a viable approach, as it reduces the turnaround time of drug development removing costs associated to safety testing of new molecular entities. Ribavirin, an antiviral molecule used to treat hepatitis C virus infections, is particularly promising as repurposed drug for cancer treatment, having shown therapeutic activity against glioblastoma, acute myeloid leukemia, and nasopharyngeal carcinoma. In the present study, we thoroughly investigated the in vitro anticancer activity of ribavirin against A549 human lung adenocarcinoma cells. From a functional standpoint, ribavirin significantly inhibits cancer hallmarks such as cell proliferation, migration, and colony formation. Mechanistically, ribavirin downregulates the expression of numerous proteins and genes regulating cell migration, proliferation, apoptosis, and cancer angiogenesis. The anticancer potential of ribavirin was further investigated in silico through gene ontology pathway enrichment and protein-protein interaction networks, identifying five putative molecular interactors of ribavirin (Erb-B2 Receptor Tyrosine Kinase 4 (Erb-B4); KRAS; Intercellular Adhesion Molecule 1 (ICAM-1); amphiregulin (AREG); and neuregulin-1 (NRG1)). These interactions were characterized via molecular docking and molecular dynamic simulations. The results of this study highlight the potential of ribavirin as a repurposed chemotherapy against lung cancer, warranting further studies to ascertain the in vivo anticancer activity of this molecule., Competing Interests: Declaration of competing interest The authors of the manuscript “Computational and Biological Approaches in Repurposing Ribavirin for Lung Cancer Treatment: Unveiling Antitumorigenic Strategies”, submitted to the journal “Life Sciences”, have no conflict of interest to declare., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

High-fat diets (HFDs) shape the gut microbiome and promote obesity, inflammation, and liver steatosis. Fish and soybean are part of a healthy diet; however, the impact of these fats, in the absence of sucrose, on gut microbial dysbiosis and its association with liver steatosis remains unclear. Here, we investigated the effect of sucrose-free soybean oil-and fish oil-based high fat diets (HFDs) (SF-Soy-HFD and SF-Fish-HFD, respectively) on gut dysbiosis, obesity, steatosis, hepatic inflammation, and insulin resistance. C57BL/6 mice were fed these HFDs for 24 weeks. Both diets had comparable effects on liver and total body weights. But 16S-rRNA sequencing of the gut content revealed induction of gut dysbiosis at different taxonomic levels. The microbial communities were clearly separated, showing differential dysbiosis between the two HFDs. Compared with the SF-Fish-HFD control group, the SF-Soy-HFD group had an increased abundance of Bacteroidetes, Firmicutes, and Deferribacteres, but a lower abundance of Verrucomicrobia. The Clostridia/Bacteroidia (C/B) ratio was higher in the SF-Soy-HFD group (3.11) than in the SF-Fish-HFD group (2.5). Conversely, the Verrucomicrobiacae/S24_7 (also known as Muribaculaceae family) ratio was lower in the SF-Soy-HFD group (0.02) than that in the SF-Fish-HFD group (0.75). The SF-Soy-HFD group had a positive association with S24_7, Clostridiales, Allobaculum, Coriobacteriaceae, Adlercreutzia, Christensenellaceae, Lactococcus, and Oscillospira, but was related to a lower abundance of Akkermansia, which maintains gut barrier integrity. The gut microbiota in the SF-Soy-HFD group had predicted associations with host genes related to fatty liver and inflammatory pathways. Mice fed the SF-Soy-HFD developed liver steatosis and showed increased transcript levels of genes associated with de novo lipogenesis (Acaca, Fasn, Scd1, Elovl6) and cholesterol synthesis (Hmgcr) pathways compared to those in the SF-Fish-HFD-group. No differences were observed in the expression of fat uptake genes (Cd36 and Fabp1). The expression of the fat efflux gene (Mttp) was reduced in the SF-Soy-HFD group. Moreover, hepatic inflammation markers (Tnfa and Il1b) were notably expressed in SF-Soy-HFD-fed mice. In conclusion, SF-Soy-HFD feeding induced gut dysbiosis in mice, leading to steatosis, hepatic inflammation, and impaired glucose homeostasis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Jacob, Sindhu, Hasan, Malik, Arefanian, Al-Rashed, Nizam, Kochumon, Thomas, Bahman, Shenouda, Wilson, Akther, Al-Roub, Abukhalaf, Albeloushi, Abu-Farha, Al Madhoun, Alzaid, Thanaraj, Koistinen, Tuomilehto, Al-Mulla and Ahmad.)

Head and neck cancer ranks as the sixth-most common malignancy worldwide, characterized by high mortality and recurrence rates. Research studies indicate that molecular diagnostics play a crucial role in the early detection and prognostic evaluation of these diseases. This study aimed to identify potential biomarkers for head and neck cancer and elucidate their interactions with miRNAs and possible therapeutic drugs. Four drivers, namely, FN1 , IL1A , COL1A1 , and MMP9 , were identified using network biology and machine learning approaches. Gene set variation analysis (GSVA) showed that these genes were significantly involved in different biological processes and pathways, including coagulation, UV-response-down, apoptosis, NOTCH signaling, Wnt-beta catenin, and other signal pathways. The diagnostic value of these hub genes was validated using receiver operating characteristic (ROC) curves. The top interactive miRNAs, including miR-128-3p , miR-218-5p , miR-214-3p , miR-124-3p , miR-129-2-3p , and miR-1-3p , targeted the key genes. Furthermore, the interaction between the key genes and drugs was also identified. In summary, the key genes and miRNAs or drugs reported in this study might provide valuable information for potential biomarkers to increase the prognosis and diagnosis of head and neck cancer.

Background: High-fat diets cause gut dysbiosis and promote triglyceride accumulation, obesity, gut permeability changes, inflammation, and insulin resistance. Both cocoa butter and fish oil are considered to be a part of healthy diets. However, their differential effects on gut microbiome perturbations in mice fed high concentrations of these fats, in the absence of sucrose, remains to be elucidated. The aim of the study was to test whether the sucrose-free cocoa butter-based high-fat diet (C-HFD) feeding in mice leads to gut dysbiosis that associates with a pathologic phenotype marked by hepatic steatosis, low-grade inflammation, perturbed glucose homeostasis, and insulin resistance, compared with control mice fed the fish oil based high-fat diet (F-HFD)., Results: C57BL/6 mice (5-6 mice/group) were fed two types of high fat diets (C-HFD and F-HFD) for 24 weeks. No significant difference was found in the liver weight or total body weight between the two groups. The 16S rRNA sequencing of gut bacterial samples displayed gut dysbiosis in C-HFD group, with differentially-altered microbial diversity or relative abundances. Bacteroidetes, Firmicutes , and Proteobacteria were highly abundant in C-HFD group, while the Verrucomicrobia , Saccharibacteria (TM7), Actinobacteria , and Tenericutes were more abundant in F-HFD group. Other taxa in C-HFD group included the Bacteroides, Odoribacter, Sutterella, Firmicutes bacterium (AF12), Anaeroplasma, Roseburia, and Parabacteroides distasonis. An increased Firmicutes/Bacteroidetes (F/B) ratio in C-HFD group, compared with F-HFD group, indicated the gut dysbiosis. These gut bacterial changes in C-HFD group had predicted associations with fatty liver disease and with lipogenic, inflammatory, glucose metabolic, and insulin signaling pathways. Consistent with its microbiome shift, the C-HFD group showed hepatic inflammation and steatosis, high fasting blood glucose, insulin resistance, increased hepatic de novo lipogenesis (Acetyl CoA carboxylases 1 ( Acaca ), Fatty acid synthase ( Fasn ), Stearoyl-CoA desaturase-1 ( Scd1 ), Elongation of long-chain fatty acids family member 6 ( Elovl6 ), Peroxisome proliferator-activated receptor-gamma ( Pparg ) and cholesterol synthesis (β-(hydroxy β-methylglutaryl-CoA reductase ( Hmgcr ). Non-significant differences were observed regarding fatty acid uptake (Cluster of differentiation 36 ( CD36 ), Fatty acid binding protein-1 ( Fabp1 ) and efflux (ATP-binding cassette G1 ( Abcg1 ), Microsomal TG transfer protein ( Mttp ) in C-HFD group, compared with F-HFD group. The C-HFD group also displayed increased gene expression of inflammatory markers including Tumor necrosis factor alpha ( Tnfa ), C-C motif chemokine ligand 2 ( Ccl2 ), and Interleukin-12 ( Il12 ), as well as a tendency for liver fibrosis., Conclusion: These findings suggest that the sucrose-free C-HFD feeding in mice induces gut dysbiosis which associates with liver inflammation, steatosis, glucose intolerance and insulin resistance.

Background: Diabetic nephropathy (DN) represents a major chronic kidney disorder and a leading cause of end-stage renal disease (ESRD). Small RNAs have been showing great promise as diagnostic markers as well as drug targets. Identifying dysregulated micro RNAs (miRNAs) could help in identifying disease biomarkers and investigation of downstream interactions, shedding light on the molecular pathophysiology of DN. In this study, we analyzed small RNAs within human urinary extracellular vesicles (ECVs) from DN patients using small RNA next-generation sequencing., Method: In this cross-sectional study, urine samples were collected from 88 participants who were divided into 3 groups: type 2 diabetes (T2D) with DN (T2D + DN, n = 20), T2D without DN (T2D - DN, n = 40), and healthy individuals (n = 28). The study focused on isolating urinary ECVs to extract and sequence small RNAs. Differentially expressed small RNAs were identified, and a functional enrichment analysis was conducted., Results: The study revealed a distinct subset of 13 miRNAs and 10 Piwi-interacting RNAs that were significantly dysregulated in urinary ECVs of the DN group when compared to other groups. Notably, miR-151a-3p and miR-182-5p exhibited a unique expression pattern, being downregulated in the T2D - DN group, and upregulated in the T2D + DN group, thus demonstrating their effectiveness in distinguishing patients between the 2 groups. Eight driver genes were identified PTEN , SMAD2 , SMAD4 , VEGFA , CCND2 , CDK6 , LIN28B , and CHD1 ., Conclusion: Our findings contribute valuable insights into the pathogenesis of DN, uncovering novel biomarkers and identifying potential therapeutic targets that may aid in managing and potentially decelerating the progression of the disease., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Endocrine Society.)

Cardio-metabolic disease is a significant global health challenge with increasing prevalence. Recent research underscores the disruption of gut microbial balance as a key factor in disease susceptibility. We aimed to characterize the gut microbiota composition and function in cardio-metabolic disease and healthy controls. For this purpose, we collected stool samples of 18 subjects (12 diseased, 6 healthy) and we performed metagenomics analysis and functional prediction using QIIME2 and PICRUSt. Furthermore, we carried out assessments of microbe-gene interactions, gene ontology, and microbe-disease associations. Our findings revealed distinct microbial patterns in the diseased group, particularly evident in lower taxonomic levels with significant variations in 14 microbial features. The diseased cohort exhibited an enrichment of Lachnospiraceae family, correlating with obesity, insulin resistance, and metabolic disturbances. Conversely, reduced levels of Clostridium, Gemmiger, and Ruminococcus genera indicated a potential inflammatory state, linked to compromised butyrate production and gut permeability. Functional analyses highlighted dysregulated pathways in amino acid metabolism and energy equilibrium, with perturbations correlating with elevated branch-chain amino acid levels-a known contributor to insulin resistance and type 2 diabetes. These findings were consistent across biomarker assessments, microbe-gene associations, and gene ontology analyses, emphasizing the intricate interplay between gut microbial dysbiosis and cardio-metabolic disease progression. In conclusion, our study unveils significant shifts in gut microbial composition and function in cardio-metabolic disease, emphasizing the broader implications of microbial dysregulation. Addressing gut microbial balance emerges as a crucial therapeutic target in managing cardio-metabolic disease burden., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Introduction: HLA typing is a critical tool in both clinical and research applications at the individual and population levels. Benchmarking studies have indicated HLA-HD as the preferred tool for accurate and comprehensive HLA allele calling. The advent of next-generation sequencing (NGS) has revolutionized genetic analysis by providing high-throughput sequencing data. This study aims to evaluate, using the HLA-HD tool, the HLA typing content of whole exome, whole genome, and HLA-targeted panel sequence data from the consanguineous population of Arab ethnicity, which has been underrepresented in prior benchmarking studies. Methods: We utilized sequence data from family trios and individuals, sequenced on one or more of the whole exome, whole genome, and HLA-targeted panel sequencing technologies. The performance and resolution across various HLA genes were evaluated. We incorporated a comparative quality control analysis, assessing the results obtained from HLA-HD by comparing them with those from the HLA-Twin tool to authenticate the accuracy of the findings. Results: Our analysis found that alleles across 29 HLA loci can be successfully and consistently typed from NGS datasets. Clinical-grade whole exome sequencing datasets achieved the highest consistency rate at three-field resolution, followed by targeted HLA panel, research-grade whole exome, and whole genome datasets. Discussion: The study catalogues HLA typing consistency across NGS datasets for a large array of HLA genes and highlights assessments regarding the feasibility of utilizing available NGS datasets in HLA allele studies. These findings underscore the reliability of HLA-HD for HLA typing in underrepresented populations and demonstrate the utility of various NGS technologies in achieving accurate HLA allele calling., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Dashti, Malik, Nizam, Jacob, Al-Mulla and Thanaraj.)

Background: The plasma virome represents the overall composition of viral sequences present in it. Alteration in plasma virome has been reported in treatment naïve and immunocompromised (CD4 count < 200) people with HIV (PWH). However, the effect of ART on virome composition in PWH on ART with preserved CD4 counts is poorly understood., Objectives: We aimed to assess the alterations in plasma virome in PWH on ART in comparison to HIV-negative uninfected controls and to further investigate possible associations of plasma viruses with inflammation and immune dysfunction, namely, immunosenescence and immune exhaustion., Methods: Plasma viral DNA from PWH on ART and controls was used for sequencing on the Illumina Nextseq500 platform, followed by the identification of viral sequences using an automated pipeline, VIROMATCH. Multiplex cytokine assay was performed to measure the concentrations of various cytokines in plasma. Immunophenotyping was performed on PBMCs to identify T cell markers of immunosenescence and immune exhaustion., Results: In our observational, cross-sectional pilot study, chronically infected PWH on ART had significantly different viral species compositions compared to controls. The plasma virome of PWH showed a significantly high relative abundance of species Human gammaherpesvirus 4, also known as Epstein-Barr virus (EBV). Moreover, EBV emerged as a significant viral taxon differentially enriched in PWH on ART, which further correlated positively with the exhaustion phenotype of T cells and significantly increased TNF-α in PWH on ART. Additionally, a significantly increased proportion of senescent T cells and IL-8 cytokine was detected in PWH on ART., Conclusion: Altered plasma virome influenced the inflammatory response and T-cell phenotype in PWH on ART., Competing Interests: The authors declare no conflict of interest, financial or otherwise., (© 2024 Bentham Science Publishers.)

Cardiovascular disease (CVD) is a collective term for disorders of the heart and blood vessels. The molecular events and biochemical pathways associated with CVD are difficult to study in clinical settings on patients and in vitro conditions. Animal models play a pivotal and indispensable role in CVD research. Caenorhabditis elegans, a nematode species, has emerged as a prominent experimental organism widely utilized in various biomedical research fields. However, the specific number of CVD-related genes and pathways within the C. elegans genome remains undisclosed to date, limiting its in-depth utilization for investigations. In the present study, we conducted a comprehensive analysis of genes and pathways related to CVD within the genomes of humans and C. elegans through a systematic bioinformatic approach. A total of 1113 genes in C. elegans orthologous to the most significant CVD-related genes in humans were identified, and the GO terms and pathways were compared to study the pathways that are conserved between the two species. In order to infer the functions of CVD-related orthologous genes in C. elegans, a PPI network was constructed. Orthologous gene PPI network analysis results reveal the hubs and important KRs: pmk-1, daf-21, gpb-1, crh-1, enpl-1, eef-1G, acdh-8, hif-1, pmk-2, and aha-1 in C. elegans. Modules were identified for determining the role of the orthologous genes at various levels in the created network. We also identified 9 commonly enriched pathways between humans and C. elegans linked with CVDs that include autophagy (animal), the ErbB signaling pathway, the FoxO signaling pathway, the MAPK signaling pathway, ABC transporters, the biosynthesis of unsaturated fatty acids, fatty acid metabolism, glutathione metabolism, and metabolic pathways. This study provides the first systematic genomic approach to explore the CVD-associated genes and pathways that are present in C. elegans, supporting the use of C. elegans as a prominent animal model organism for cardiovascular diseases., (© 2024. The Author(s).)

Lung cancer poses a significant health threat globally, especially in regions like India, with 5-year survival rates remain alarmingly low. Our study aimed to uncover key markers for effective treatment and early detection. We identified specific genes related to lung cancer using the BioXpress database and delved into their roles through DAVID enrichment analysis. By employing network theory, we explored the intricate interactions within lung cancer networks, identifying ASPM and MKI67 as crucial regulator genes. Predictions of microRNA and transcription factor interactions provided additional insights. Examining gene expression patterns using GEPIA and KM Plotter revealed the clinical relevance of these key genes. In our pursuit of targeted therapies, Drug Bank pointed to methotrexate as a potential drug for the identified key regulator genes. Confirming this, molecular docking studies through Swiss Dock showed promising binding interactions. To ensure stability, we conducted molecular dynamics simulations using the AMBER 16 suite. In summary, our study pinpoints ASPM and MKI67 as vital regulators in lung cancer networks. The identification of hub genes and functional pathways enhances our understanding of molecular processes, offering potential therapeutic targets. Importantly, methotrexate emerged as a promising drug candidate, supported by robust docking and simulation studies. These findings lay a solid foundation for further experimental validations and hold promise for advancing personalized therapeutic strategies in lung cancer.Communicated by Ramaswamy H. Sarma.

Background: Autosomal dominant polycystic kidney disease (ADPKD) is the most prevalent monogenic renal disease progressing to end-stage renal disease. There is a pressing need for the identification of early ADPKD biomarkers to enable timely intervention and the development of effective therapeutic approaches. Here, we profiled human urinary extracellular vesicles small RNAs by small RNA sequencing in patients with ADPKD and compared their differential expression considering healthy control individuals to identify dysregulated small RNAs and analyze downstream interaction to gain insight about molecular pathophysiology., Methods: This is a cross-sectional study where urine samples were collected from a total of 23 PKD1-ADPKD patients and 28 healthy individuals. Urinary extracellular vesicles were purified, and small RNA was isolated and sequenced. Differentially expressed Small RNA were identified and functional enrichment analysis of the critical miRNAs was performed to identify driver genes and affected pathways., Results: miR-320b, miR-320c, miR-146a-5p, miR-199b-3p, miR-671-5p, miR-1246, miR-8485, miR-3656, has&#95;piR&#95;020497, has&#95;piR&#95;020496 and has&#95;piR&#95;016271 were significantly upregulated in ADPKD patient urine extracellular vesicles and miRNA-29c was significantly downregulated. Five 'driver' target genes (FBRS, EDC3, FMNL3, CTNNBIP1 and KMT2A) were identified., Conclusions: The findings of the present study make significant contributions to the understanding of ADPKD pathogenesis and to the identification of novel biomarkers and potential drug targets aimed at slowing disease progression in ADPKD., (© 2024 The Authors. The Journal of Gene Medicine published by John Wiley & Sons Ltd.)

Cardiovascular disease (CVD) is a collective term for disorders of the heart and blood vessels. The molecular events and biochemical pathways associated with CVD are difficult to study in clinical settings on patients and in vitro conditions. Animal models play a pivotal and indispensable role in cardiovascular disease (CVD) research. Caenorhabditis elegans , a nematode species, has emerged as a prominent experimental organism widely utilised in various biomedical research fields. However, the specific number of CVD-related genes and pathways within the C. elegans genome remains undisclosed to date, limiting its in-depth utilisation for investigations. In the present study, we conducted a comprehensive analysis of genes and pathways related to CVD within the genomes of humans and C. elegans through a systematic bioinformatic approach. A total of 1113 genes in C. elegans orthologous to the most significant CVD-related genes in humans were identified, and the GO terms and pathways were compared to study the pathways that are conserved between the two species. In order to infer the functions of CVD-related orthologous genes in C. elegans, a PPI network was constructed. Orthologous gene PPI network analysis results reveal the hubs and important KRs: pmk-1, daf-21, gpb-1, crh-1, enpl-1, eef-1G, acdh-8, hif-1, pmk-2, and aha-1 in C. elegans. Modules were identified for determining the role of the orthologous genes at various levels in the created network. We also identified 9 commonly enriched pathways between humans and C. elegans linked with CVDs that include autophagy (animal), the ErbB signalling pathway, the FoxO signalling pathway, the MAPK signalling pathway, ABC transporters, the biosynthesis of unsaturated fatty acids, fatty acid metabolism, glutathione metabolism, and metabolic pathways. This study provides the first systematic genomic approach to explore the CVD-associated genes and pathways that are present in C. elegans, supporting the use of C. elegans as a prominent animal model organism for cardiovascular diseases.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease caused by the loss of upper and lower motor neurons. The sporadic ALS (sALS) is a multigenic disorder and the complex mechanisms underlying its onset are still not fully delineated. Despite the recent scientific advancements, certain aspects of ALS pathogenic targets need to be yet clarified. The aim of the presented study is to identify potential genetic biomarkers and drug targets for sALS, by analysing gene expression profiles, presented in the publicly available GSE68605 dataset, of motor neurons cells obtained from sALS patients. We used different computational approaches including differential expression analysis, protein network mapping, candidate protein biomarker (CPB) identification, elucidation of the role of functional modules, and molecular docking analysis. The resultant top ten up- and downregulated genes were further used to construct protein-protein interaction network (PPIN). The PPIN analysis resulted in identifying four CPBs (namely RIOK2, AKT1, CTNNB1, and TNF) that commonly overlapped with one another in network parameters (degree, bottleneck and maximum neighbourhood component). The RIOK2 protein emerged as a potential mediator of top five functional modules that are associated with RNA binding, lipoprotein particle receptor binding in pre-ribosome, and interferon, cytokine-mediated signaling pathway. Furthermore, molecular docking analysis revealed that cyclosporine exhibited the highest binding affinity (-8.6 kJ/mol) with RIOK2, and surpassed the FDA-approved ALS drugs, such as riluzole and edaravone. This suggested that cyclosporine may serve as a promising candidate for targeting RIOK2 downregulation observed in sALS patients. In order to validate our computational results, it is suggested that in vitro and in vivo studies may be conducted in future to provide a more detailed understanding of ALS diagnosis, prognosis, and therapeutic intervention., Competing Interests: Declaration of Competing Interest The authors declare no conflict of interest., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Acute lung injury (ALI)/acute respiratory distress syndrome (ARDS) are lung complications diagnosed by impaired gaseous exchanges leading to mortality. From the diverse etiologies, sepsis is a prominent contributor to ALI/ARDS. In the present study, we retrieved sepsis-induced ARDS mRNA expression profile and identified 883 differentially expressed genes (DEGs). Next, we established an ARDS-specific weighted gene co-expression network (WGCN) and picked the blue module as our hub module based on highly correlated network properties. Later we subjected all hub module DEGs to form an ARDS-specific 3-node feed-forward loop (FFL) whose highest-order subnetwork motif revealed one TF ( STAT6 ), one miRNA (miR-34a-5p), and one mRNA ( TLR6 ). Thereafter, we screened a natural product library and identified three lead molecules that showed promising binding affinity against TLR6. We then performed molecular dynamics simulations to evaluate the stability and binding free energy of the TLR6-lead molecule complexes. Our results suggest these lead molecules may be potential therapeutic candidates for treating sepsis-induced ALI/ARDS. In-silico studies on clinical datasets for sepsis-induced ARDS indicate a possible positive interaction between miR-34a and TLR6 and an antagonizing effect on STAT6 to promote inflammation. Also, the translational study on septic mice lungs by IHC staining reveals a hike in the expression of TLR6. We report here that miR-34a actively augments the effect of sepsis on lung epithelial cell apoptosis. This study suggests that miR-34a promotes TLR6 to heighten inflammation in sepsis-induced ALI/ARDS., Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-023-03700-1., Competing Interests: Conflict of interestThe authors declare that they have are no conflict of interest., (© King Abdulaziz City for Science and Technology 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

The anillin actin-binding protein (ANLN) is immensely overexpressed in cancers, including lung cancer (LC). Phytocompounds have gained interest due to their broader potential and reduced unwanted effects. Screening numerous compounds presents a challenge, but in silico molecular docking is pragmatic. The present study aims to identify the role of ANLN in lung adenocarcinoma (LUAD), along with identification and interaction analysis of anticancer and ANLN inhibitory phytocompounds followed by molecular dynamics (MD) simulation. Using a systematic approach, we found that ANLN is significantly overexpressed in LUAD and mutated with a frequency of 3.73%. It is linked with advanced stages, clinicopathological parameters, worsening of relapse-free survival (RFS), and overall survival (OS), pinpointing its oncogenic and prognostic potential. High-throughput screening and molecular docking of phytocompounds revealed that kaempferol (flavonoid aglycone) interacts strongly with the active site of ANLN protein via hydrogen bonds, Vander Waals interactions, and acts as a potent inhibitor. Furthermore, we discovered that ANLN expression was found to be significantly higher (p) in LC cells compared to normal cells. This is a propitious and first study to demonstrate ANLN and kaempferol interactions, which might eventually lead to removal of rout from cell cycle regulation posed by ANLN overexpression and allow it to resume normal processes of proliferation. Overall, this approach suggested a plausible biomarker role of ANLN and the combination of molecular docking subsequently led to the identification of contemporary phytocompounds, bearing symbolic anticancer effects. The findings would be advantageous for pharmaceutics but require validation using in vitro and in vivo methods. HIGHLIGHTS: • ANLN is significantly overexpressed in LUAD. • ANLN is implicated in the infiltration of TAMs and altering plasticity of TME. • Kaempferol (potential ANLN inhibitor) shows important interactions with ANLN which could remove the alterations in cell cycle regulation, imposed by ANLN overexpression eventually leading to normal process of cell proliferation., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Introduction: Circadian rhythm maintains the sleep-wake cycle in biological systems. Various biological activities are regulated and modulated by the circadian rhythm, disruption of which can result in onset of diseases. Robust rhythms of phosphorylation profiles and abundances of PERIOD (PER) proteins are thought to be the master keys that drive circadian clock functions. The role of casein kinase 2 (CK2) in circadian rhythm via its direct interactions with the PER protein has been extensively studied; however, the exact mechanism by which it affects circadian rhythms at the molecular level is not known., Methods: Here, we propose an extended circadian rhythm model in Drosophila that incorporates the crosstalk between the PER protein and CK2. We studied the regulatory role of CK2 in the dynamics of PER proteins involved in circadian rhythm using the stochastic simulation algorithm., Results: We observed that variations in the concentration of CK2 in the circadian rhythm model modulates the PER protein dynamics at different cellular states, namely, active, weakly active, and rhythmic death. These oscillatory states may correspond to distinct pathological cellular states of the living system. We find molecular noise at the expression level of CK2 to switch normal circadian rhythm to any of the three above-mentioned circadian oscillatory states. Our results suggest that the concentration levels of CK2 in the system has a strong impact on its dynamics, which is reflected in the time evolution of PER protein., Discussion: We believe that our findings can contribute towards understanding the molecular mechanisms of circadian dysregulation in pathways driven by the PER mutant genes and their pathological states, including cancer, obesity, diabetes, neurodegenerative disorders, and socio-psychological disease., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Malik, Dashti, Fatima, Channanath, John, Singh, Al-Mulla and Alphonse Thanaraj.)

The Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is related with the COVID-19 pandemic. Recent spike protein variations have had an effect on the transmission of the virus. In addition to ACE-2, spike proteins can employ DC-SIGN and its analogous receptor, DC-SIGNR, for host evasion. Spike variations in the DC-SIGN interaction region and role of DC-SIGN in immune evasion have not been well defined. To understand the spike protein variations and their binding mode, phylogenetic analysis of the complete GISAID (Global Initiative for Sharing Avian Influenza Data) data of the SARS-CoV-2 spike protein was considered. In addition, an in silico knockout network evaluation of the SARS-CoV-2 single-cell transcriptome was conducted to determine the key role of DC-SIGN/R in immunological dysregulation. Within the DC-SIGN-interacting region of the SARS-CoV spike protein, the spike protein of SARS-CoV-2 displayed remarkable similarity to the SARS-CoV spike protein. Surprisingly, the phylogenetic analysis revealed that the SARS-CoV-2's spike exhibited significantly diverse variants in the DC-SIGN interaction domain, which altered the frequency of these variants. The variation within the DC-SIGN-interacting domain of spike proteins affected the binding of a limited number of variants with DC-SIGN and DC-SIGNR and affected their evolution. MMGBSA binding free energies evaluation differed for variants from those of the wild type, suggesting the influence of substitution mutations on the interaction pattern. In silico knockout network analysis of the single-cell transcriptome of Bronchoalveolar Lavage and peripheral blood mononuclear cells revealed that SARS-CoV-2 altered DC-SIGN/R signaling. Early surveillance of diverse SARS-CoV-2 strains could preclude a worsening of the pandemic and facilitate the development of an optimum vaccine against variations. The spike Receptor Binding Domain genetic variants are thought to boost SARS CoV-2 immune evasion, resulting in its higher longevity., Supplementary Information: The online version contains supplementary material available at 10.1007/s13337-023-00820-3., Competing Interests: Conflict of interestAuthors declare there is no conflict of interest., (© The Author(s), under exclusive licence to Indian Virological Society 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

Sporadic cases of breast cancer being more prevalent than the hereditary cases, can be largely attributed to environmental pollutants like polycyclic aromatic hydrocarbons (PAHs). The aim of the present study was to identify gene dysregulations and the associations in DMBA (a PAH) induced breast cancer. A breast cancer model was developed in Wistar rats (n = 40), using DMBA. Serum proteomics (2D electrophoresis and MALDI-TOF MS) followed by relative gene expression analysis in mammary glands were conducted to reach to the differential gene signatures. The candidate genes were subjected to survival analysis (by GEPIA2 and KM plotter) and infiltration analysis (by ImmuCellAI) for correlating gene expression with patient survival and immune cell infiltration respectively. Further, the regulatory network investigation (by Cytoscape) was performed to find out the transcription factors (TFs) and miRNAs of the concerned genes. A gene trio (ANXA5, MTG1, PPP2R5B), expressing differentially in early mammary carcinogenesis at 4 months (precancerous stage) till full-fledged cancerous stage (post 6 months) was identified. The altered gene expression was associated with less survival among breast cancer patients (n = 4019). The dysregulated expression also has a correlation with enhanced mammary infiltration of immune cells. Moreover, a regulatory network (comprising of 77 transcription factors and 50 miRNAs) involved in the regulation of candidate genes was also deciphered. The deregulated target genes can therefore be explored for reregulation via identified TFs and miRNAs, and survival thereby improved., Competing Interests: Declaration of competing interest No conflict in terms of interests exists in connection with this article., (Copyright © 2023 Elsevier B.V. and Société Française de Biochimie et Biologie Moléculaire (SFBBM). All rights reserved.)

The Parkinson disease (PD) is the second most common neurodegenerative disorder affecting the central nervous system and motor functions. The biological complexity of PD is yet to reveal potential targets for intervention or to slow the disease severity. Therefore, this study aimed to compare the fidelity of blood to substantia nigra (SN) tissue gene expression from PD patients to provide a systematic approach to predict role of the key genes of PD pathobiology. Differentially expressed genes (DEGs) from multiple microarray data sets of PD blood and SN tissue from GEO database are identified. Using the theoretical network approach and variety of bioinformatic tools, we prioritized the key genes from DEGs. A total of 540 and 1024 DEGs were identified in blood and SN tissue samples, respectively. Functional pathways closely related to PD such as ERK1 and ERK2 cascades, mitogen-activated protein kinase (MAPK) signaling, Wnt, nuclear factor-κB (NF-κB), and PI3K-Akt signaling were observed by enrichment analysis. Expression patterns of 13 DEGs were similar in both blood and SN tissues. Comprehensive network topological analysis and gene regulatory networks identified additional 10 DEGs functionally connected with molecular mechanisms of PD through the mammalian target of rapamycin (mTOR), autophagy, and AMP-activated protein kinase (AMPK) signaling pathways. Potential drug molecules were identified by chemical-protein network and drug prediction analysis. These potential candidates can be further validated in vitro/in vivo to be used as biomarkers and/or novel drug targets for the PD pathology and/or to arrest or delay the neurodegeneration over the years, respectively., Competing Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2023.)

Curcumin is a natural anti-inflammatory and antioxidant substance which plays a major role in reducing the amyloid plaques formation, which is the major cause of Alzheimer's disease (AD). Consequently, a methodical approach was used to select the potential protein targets of curcumin in AD through network pharmacology. In this study, through integrative methods, AD targets of curcumin through SwissTargetPrediction database, STITCH database, BindingDB, PharmMapper, Therapeutic Target Database (TTD), Online Mendelian Inheritance in Man (OMIM) database were predicted followed by gene enrichment analysis, network construction, network topology, and docking studies. Gene ontology analysis facilitated identification of a list of possible AD targets of curcumin (74 targets genes). The correlation of the obtained targets with AD was analysed by using gene ontology (GO) pathway enrichment analyses and Kyoto Encyclopaedia of Genes and Genomes (KEGG). We have incorporated the applied network pharmacological approach to identify key genes. Furthermore, we have performed molecular docking for analysing the mechanism of curcumin. In order to validate the temporospatial expression of key genes in human central nervous system (CNS), we searched the Human Brain Transcriptome (HBT) dataset. We identified top five key genes namely, PPARγ, MAPK1, STAT3, KDR and APP. Further validated the expression profiling of these key genes in publicly available brain data expression profile databases. In context to a valuable addition in the treatment of AD, this study is concluded with novel insights into the therapeutic mechanisms of curcumin, will ease the treatment of AD with the clinical application of curcumin., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Introduction: Both obesity and a poor diet are considered major risk factors for triggering insulin resistance syndrome (IRS) and the development of type 2 diabetes mellitus (T2DM). Owing to the impact of low-carbohydrate diets, such as the keto diet and the Atkins diet, on weight loss in individuals with obesity, these diets have become an effective strategy for a healthy lifestyle. However, the impact of the ketogenic diet on IRS in healthy individuals of a normal weight has been less well researched. This study presents a cross-sectional observational study that aimed to investigate the effect of low carbohydrate intake in healthy individuals of a normal weight with regard to glucose homeostasis, inflammatory, and metabolic parameters., Methods: The study included 120 participants who were healthy, had a normal weight (BMI 25 kg/m 2 ), and had no history of a major medical condition. Self-reported dietary intake and objective physical activity measured by accelerometry were tracked for 7 days. The participants were divided into three groups according to their dietary intake of carbohydrates: the low-carbohydrate (LC) group (those consuming <45% of their daily energy intake from carbohydrates), the recommended range of carbohydrate (RC) group (those consuming 45-65% of their daily energy intake from carbohydrates), and the high-carbohydrate (HC) group (those consuming more than 65% of their daily energy intake from carbohydrates). Blood samples were collected for the analysis of metabolic markers. HOMA of insulin resistance (HOMA-IR) and HOMA of β-cell function (HOMA-β), as well as C-peptide levels, were used for the evaluation of glucose homeostasis., Results: Low carbohydrate intake (<45% of total energy) was found to significantly correlate with dysregulated glucose homeostasis as measured by elevations in HOMA-IR, HOMA-β% assessment, and C-peptide levels. Low carbohydrate intake was also found to be coupled with lower serum bicarbonate and serum albumin levels, with an increased anion gap indicating metabolic acidosis. The elevation in C-peptide under low carbohydrate intake was found to be positively correlated with the secretion of IRS-related inflammatory markers, including FGF2, IP-10, IL-6, IL-17A, and MDC, but negatively correlated with IL-3., Discussion: Overall, the findings of the study showed that, for the first time, low-carbohydrate intake in healthy individuals of a normal weight might lead to dysfunctional glucose homeostasis, increased metabolic acidosis, and the possibility of triggering inflammation by C-peptide elevation in plasma., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Al-Reshed, Sindhu, Al Madhoun, Bahman, AlSaeed, Akhter, Malik, Alzaid, Al-Mulla and Ahmad.)

Malaria still threatens half the globe population despite successful Artemisinin-based combination therapy. One of the reasons for our inability to eradicate malaria is the emergence of resistance to current antimalarials. Thus, there is a need to develop new antimalarials targeting Plasmodium proteins. The present study reported the design and synthesis of 4, 6 and 7-substituted quinoline-3-carboxylates 9(a - o) and carboxylic acids 10(a - b) for the inhibition of Plasmodium N-Myristoyltransferases (NMTs) using computational biology tools followed by chemical synthesis and functional analysis. The designed compounds exhibited a glide score of -9.241 to -6.960 kcal/mol for Pv NMT and -7.538 kcal/mol for Pf NMT model proteins. Development of the synthesized compounds was established via NMR, HRMS and single crystal X-ray diffraction study. The synthesized compounds were evaluated for their in vitro antimalarial efficacy against CQ-sensitive Pf 3D7 and CQ-resistant Pf INDO lines followed by cell toxicity evaluation. In silico results highlighted the compound ethyl 6-methyl-4-(naphthalen-2-yloxy)quinoline-3-carboxylate ( 9a ) as a promising inhibitor with a glide score of -9.084 kcal/mol for Pv NMT and -6.975 kcal/mol for Pf NMT with IC 50 values of 6.58 µM for Pf 3D7 line. Furthermore, compounds 9n and 9o exhibited excellent anti-plasmodial activity ( Pf 3D7 IC 50 = 3.96, 6.71 µM, and Pf INDO IC 50 = 6.38, 2.8 µM, respectively). The conformational stability of 9a with the active site of the target protein was analyzed through MD simulation and was found concordance with in vitro results. Thus, our study provides scaffolds for the development of potent antimalarials targeting both Plasmodium vivax and Plasmodium falciparum .Communicated by Ramaswamy H. Sarma.

Entamoeba histolytica (E. histolytica) is an anaerobic parasite that causes Amoebiasis in the intestine or extraintestinal, with immunology, genetics, and environmental variables all playing a part in the disease's development, but its molecular mechanism is unknown. One of the primary obstacles in understanding the etiology of Amoebiasis will be identifying the genetics profiling that controls the Amoebiasis network. By examining the gene expression profile of Amoebiasis and comparing it with healthy controls, we could identify differentially expressed genes (DEGs). DEGs were used to build the Amoebiasis protein interaction network and calculated its network topological properties. We discovered nine key hub genes (KHGs): JUN, PTGS2, FCGR3A, MNDA, CYBB, EGR1, CCL2, TLR8, and LRRK2 genes. The genes JUN and EGR1 were transcriptional factors (TFs) and up-regulated, others down-regulated. hsa-miR-155-5p, hsa-miR-101-3p, hsa-miR-124-3p, hsa-miR-26b-5p, and hsa-miR-16-5p are also among the essential miRNAs that have been demonstrated to be targeted by KHGs. These KHGs were primarily enriched in the IL-17 signaling pathway, TNF signaling pathway, NOD-like receptor signaling pathway, and Toll-like receptor signaling pathway. miRNAs were grouped in various pathways, focusing on the TGF-β signaling pathway, human immunodeficiency virus 1 infection, insulin signaling pathway, signaling pathways regulating pluripotency of stem cells, etc. Amoebiasis KHGs (JUN, PTGS2, CCL2, and MNDA) and their associated miRNAs are the primary targets for therapeutic methods and possible biomarkers. Furthermore, we identified drugs for genes JUN, PTGS2, FCGR3A, CCL2, and LRRK2. KHGs, on the other hand, required experimental validation to prove their efficacy., (© 2022 The Author(s).)

Curcumin is a hydrophobic polyphenol derived from turmeric with potent anti-oxidant, anti-microbial, anti-inflammatory and anti-carcinogenic effects. Curcumin is degraded into various derivatives under in vitro and in vivo conditions, and it appears that its degradation may be responsible for the pharmacological effects of curcumin. The primary risk factor for the cause of gastric cancer is Helicobacter pylori (H. pylori) . A virulence factor vacuolating cytotoxic A (VacA) is secreted by H. pylori as a 88 kDa monomer (p88), which can be fragmented into a 33 kDa N-terminal domain (p33) and a 55 kDa C-terminal domain (p55). Recently it has been reported that curcumin oxidation is required to inhibit the activity of another major H.pylori toxin CagA. We performed molecular docking of curcumin and its oxidative derivatives with p33 and p55 domains of VacA. Further, we have examined the effect of the oxidation of curcumin on the vacuolation activity of VacA protein. We observed the binding of curcumin to the p55 domain of VacA at five different sites with moderate binding affinities. Curcumin did not bind to p33 domain of VacA. Remarkably, cyclobutyl cyclopentadione and dihydroxy cyclopentadione, which are oxidized products of curcumin, showed a higher binding affinity with VacA protein at all sites except one as compared to parent curcumin itself. However, cyclobutyl cyclopentadione showed a significant binding affinity for the active site 5 of the p55 protein. Active site five (312-422) of p55 domain of VacA plays a crucial role in VacA-mediated vacuole formation. Invitro experiments showed that curcumin inhibited the vacuolation activity of H. pylori in human gastric cell line AGS cells whereas acetyl and diacetyl curcumin, which cannot be oxidized, failed to inhibit the vacuolation in AGS cells after H. pylori infection. Here our data showed that oxidation is essential for the activity of curcumin in inhibiting the vacuolation activity of H. pylori . Synthesis of these oxidized curcumin derivatives could potentially provide new therapeutic drug molecules for inhibiting H. pylori -mediated pathogenesis.

Network medicine provides network theoretical tools, methods and properties to study underlying laws governing human interactome to identify disease states and disease complexity leading to drug discovery. Within this framework, we investigated the topological properties of ovarian cancer network (OCN) and the roles of hubs to understand OCN organization to address disease states and complexity. The OCN constructed from the experimentally verified genes exhibits fractal nature in the topological properties with deeply rooted functional communities indicating self-organizing behavior. The network properties at all levels of organization obey one parameter scaling law which lacks centrality lethality rule. We showed that $\langle k\rangle $ can be taken as a scaling parameter, where, power law exponent can be estimated from the ratio of network diameters. The betweenness centrality $C&#95;B$ shows two distinct behaviors one shown by high degree hubs and the other by segregated low degree nodes. The $C&#95;B$ power law exponent is found to connect the exponents of distributions of high and low degree nodes. OCN showed the absence of rich-club formation which leads to the missing of a number of attractors in the network causing formation of weakly tied diverse functional modules to keep optimal network efficiency. In OCN, provincial and connector hubs, which includes identified key regulators, take major responsibility to keep the OCN integrity and organization. Further, most of the key regulators are found to be over expressed and positively correlated with immune infiltrates. Finally, few potential drugs are identified related to the key regulators., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Prostate cancer (PCa) is the most prevalent cancer (20%) in males and is accountable for a fifth (6.8%) cancer-related deaths in males globally. Smoking, obesity, race/ethnicity, diet, age, chemicals and radiation exposure, sexually transmitted diseases, etc. are among the most common risk factors for PCa. However, the basic change at the molecular level is the manifested confirmation of PCa. Thus, this study aims to evaluate the molecular signature for PCa in comparison to benign prostatic hyperplasia (BPH). Additionally, representation of differentially expressed genes (DEGs) are conducted with the help of some bioinformatics tools like DAVID, STRING, GEPIA, Cytoscape. The gene expression profile for the four data sets GSE55945, GSE104749, GSE46602, and GSE32571 was downloaded from NCBI, Gene Expression Omnibus (GEO). For the extracted DEGs, different types of analysis including functional and pathway enrichment analysis, protein-protein interaction (PPI) network construction, survival analysis and transcription factor (TF) prediction were conducted. We obtained 633 most significant upregulated genes and 1219 downregulated genes, and a sum total of 1852 DEGs were found from all four datasets after assessment. The key genes, including EGFR , MYC , VEGFA , and PTEN , are targeted by TF such as AR, Sp1, TP53, NF-KB1, STAT3, RELA. Moreover, miR-21-5p also found significantly associated with all the four key genes. Further, The Cancer Genome Atlas data (TCGA) independent database was used for validation of key genes EGFR , MYC , VEGFA , PTEN expression in prostate adenocarcinoma. All four key genes were found to be significantly correlated with overall survival in PCa. Therefore, the therapeutic target may be determined by the information of these key gene's findings for the diagnosis, prognosis and treatment of PCa.

Troxerutin (TXR) is a phytochemical reported to possess anti-inflammatory and hepatoprotective effects. In this study, we aimed to exploit the antiarthritic properties of TXR using an adjuvant-induced arthritic (AIA) rat model. AIA-induced rats showed the highest arthritis score at the disease onset and by oral administration of TXR (50, 100, and 200 mg/kg body weight), reduced to basal level in a dose-dependent manner. Isobaric tags for relative and absolute quantitative (iTRAQ) proteomics tool were employed to identify deregulated joint homogenate proteins in AIA and TXR-treated rats to decipher the probable mechanism of TXR action in arthritis. iTRAQ analysis identified a set of 434 proteins with 65 deregulated proteins (log 2 case/control≥1.5) in AIA. Expressions of a set of important proteins (AAT, T-kininogen, vimentin, desmin, and nucleophosmin) that could classify AIA from the healthy ones were validated using Western blot analysis. The Western blot data corroborated proteomics findings. In silico protein-protein interaction study of tissue-proteome revealed that complement component 9 (C9), the major building blocks of the membrane attack complex (MAC) responsible for sterile inflammation, get perturbed in AIA. Our dosimetry study suggests that a TXR dose of 200 mg/kg body weight for 15 days is sufficient to bring the arthritis score to basal levels in AIA rats. We have shown the importance of TXR as an antiarthritic agent in the AIA model and after additional investigation, its arthritic ameliorating properties could be exploited for clinical usability., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Sahu, Bishwal, Malik, Sahu, Kaushik, Sharma, Saini, Arya, Rastogi, Sharma, Sen, Singh, Liu, Nanda and Panda.)

Dementia-a syndrome affecting human cognition-is a major public health concern given to its rising prevalence worldwide. Though multiple research studies have analyzed disorders such as Alzheimer's disease and Frontotemporal dementia using a systems biology approach, a similar approach to dementia syndrome as a whole is required. In this study, we try to find the high-impact core regulating processes and factors involved in dementia's protein-protein interaction network. We also explore various aspects related to its stability and signal propagation. Using gene interaction databases such as STRING and GeneMANIA, a principal dementia network (PDN) consisting of 881 genes and 59,085 interactions was achieved. It was assortative in nature with hierarchical, scale-free topology enriched in various gene ontology (GO) categories and KEGG pathways, such as negative and positive regulation of apoptotic processes, macroautophagy, aging, response to drug, protein binding, etc. Using a clustering algorithm (Louvain method of modularity maximization) iteratively, we found a number of communities at different levels of hierarchy in PDN consisting of 95 "motif-localized hubs", out of which, 7 were present at deepest level and hence were key regulators (KRs) of PDN (HSP90AA1, HSP90AB1, EGFR, FYN, JUN, CELF2 and CTNNA3). In order to explore aspects of network's resilience, a knockout (of motif-localized hubs) experiment was carried out. It changed the network's topology from a hierarchal scale-free topology to scale-free, where independent clusters exhibited greater control. Additionally, network experiments on interaction of druggable genome and motif-localized hubs were carried out where UBC, EGFR, APP, CTNNB1, NTRK1, FN1, HSP90AA1, MDM2, VCP, CTNNA1 and GRB2 were identified as hubs in the resultant network (RN). We finally concluded that stability and resilience of PDN highly relies on motif-localized hubs (especially those present at deeper levels), making them important therapeutic intervention candidates. HSP90AA1, involved in heat shock response (and its master regulator, i.e., HSF1), and EGFR are most important genes in pathology of dementia apart from KRs, given their presence as KRs as well as hubs in RN.

Lung cancer is one of the most invasive cancers affecting over a million of the population. Non-small cell lung cancer (NSCLC) constitutes up to 85% of all lung cancer cases, and therefore, it is essential to identify predictive biomarkers of NSCLC for therapeutic purposes. Here we use a network theoretical approach to investigate the complex behavior of the NSCLC gene-regulatory interactions. We have used eight NSCLC microarray datasets GSE19188, GSE118370, GSE10072, GSE101929, GSE7670, GSE33532, GSE31547, and GSE31210 and meta-analyzed them to find differentially expressed genes (DEGs) and further constructed a protein-protein interaction (PPI) network. We analyzed its topological properties and identified significant modules of the PPI network using cytoscape network analyzer and MCODE plug-in. From the PPI network, top ten genes of each of the six topological properties like closeness centrality, maximal clique centrality (MCC), Maximum Neighborhood Component (MNC), radiality, EPC (Edge Percolated Component) and bottleneck were considered for key regulator identification. We further compared them with top ten hub genes (those with the highest degrees) to find key regulator (KR) genes. We found that two genes, CDK1 and HSP90AA1, were common in the analysis suggesting a significant regulatory role of CDK1 and HSP90AA1 in non-small cell lung cancer. Our study using a network theoretical approach, as a summary, suggests CDK1 and HSP90AA1 as key regulator genes in complex NSCLC network.

Sarcoidosis is a multi-organ disorder where immunology, genetic and environmental factors play a key role in causing Sarcoidosis, but its molecular mechanism remains unclear. Identification of its genetics profiling that regulates the Sarcoidosis network will be one of the main challenges to understand its aetiology. We have identified differentially expressed genes (DEGs) by analyzing the gene expression profiling of Sarcoidosis and compared it with healthy control. Gene set enrichment analysis showed that these DEGs were mainly enriched in the inflammatory response, immune system, and pathways in cancer. Sarcoidosis protein interaction network was constructed by a total of 877 DEGs (up-down) and calculated its network topological properties, which follow hierarchical scale-free fractal nature up to six levels of the organization. We identified a large number of leading hubs that contain six key regulators (KRs) including ICOS, CTLA4, FLT3LG, CD33, GPR29 and ITGA4 are deeply rooted in the network from top to bottom, considering a backbone of the network. We identified the transcriptional factors (TFs) which are closely interacted with KRs. These genes and their TFs regulating the Sarcoidosis network are expected to be the main target for the therapeutic approaches and potential biomarkers. However, experimental validations of KRs needed to confirm their efficacy., (© 2022. The Author(s).)

Small molecules that modulate biological functions are targets of modern-day drug discovery efforts. A new series of novel 1 H -benzo[ d ]imidazoles (BBZs) were designed and synthesized with different functional groups at the phenyl ring and variable lengths of the alkyl chain at the piperazine end as anticancer agents. We identified human topoisomerase I (Hu Topo I) as a probable target of these molecules through a computational study and DNA relaxation assay, a functional assay of the Hu Topo I enzyme. UV absorption, fluorescence, and circular dichroism spectroscopy were used to study interactions between BBZ and DNA. Out of 16 compounds, 11a , 12a , and 12b showed strong binding affinity and thermal stabilization of AT sequence-specific DNA. BBZs were screened against a panel of 60 human cancer cell lines at National Cancer Institute, USA. Most potent molecules 11a , 12a , and 12b showed 50% growth inhibition (GI 50 ) in a concentration range from 0.16 to 3.6 μM cancer cells. Moreover, 12b showed 50% inhibition of the relaxation of DNA by Hu Topo I at 16 μM. Furthermore, flow cytometry revealed that 11a , 12a , and 12b cause prominent G2M arrest of cancer cells. In view of the above, we propose that 12b deserves to be further evaluated for its therapeutic use as an anticancer agent., Competing Interests: The authors declare no competing financial interest., (© 2022 The Authors. Published by American Chemical Society.)

Cryptosporidium parvum (C. parvum) is a protozoan parasite known for cryptosporidiosis in pre-weaned calves. Animals and patients with immunosuppression are at risk of developing the disease, which can cause potentially fatal diarrhoea. The present study aimed to construct a network biology framework based on the differentially expressed genes (DEGs) of C. parvum infected subjects. In this way, the gene expression profiling analysis of C. parvum infected individuals can give us a snapshot of actively expressed genes and transcripts under infection conditions. In the present study, we have analyzed microarray data sets and compared the gene expression profiles of the patients with the different data sets of the healthy control. Using a network medicine approach to identify the most influential genes in the gene interaction network, we uncovered essential genes and pathways related to C. parvum infection. We identified 164 differentially expressed genes (109 up- and 54 down-regulated DEGs) and allocated them to pathway and gene set enrichment analysis. The results underpin the identification of seven significant hub genes with high centrality values: ISG15, MX1, IFI44L, STAT1, IFIT1, OAS1, IFIT3, RSAD2, IFITM1, and IFI44. These genes are associated with diverse biological processes not limited to host interaction, type 1 interferon production, or response to IL-gamma. Furthermore, four genes (IFI44, IFIT3, IFITM1, and MX1) were also discovered to be involved in innate immunity, inflammation, apoptosis, phosphorylation, cell proliferation, and cell signaling. In conclusion, these results reinforce the development and implementation of tools based on gene profiles to identify and treat Cryptosporidium parvum-related diseases at an early stage.

Background: System medicine approaches have played a pivotal role in identifying novel disease networks especially in miRNA research. It is no wonder that miRNAs are implicated in multiple clinical conditions, allowing us to establish the hubs and nodes for network models of Alzheimer's Disease (AD). AD is an age-related, progressive, irreversible, and multifactorial neurodegenerative disorder characterized by cognitive and memory impairment and is the most common cause of dementia in older adults. Worldwide, around 50 million people have dementia, and there are nearly 10 million new cases every year. δ-secretase, also known as asparagine endopeptidase (AEP) or legumain (LGMN), is a lysosomal cysteine protease that cleaves peptide bonds C-terminally to asparagine residues in both amyloid precursor protein (APP) and tau, mediating the amyloid-β and tau pathology in AD. The patient's miRNA expression was found to be deregulated in the brain, extracellular fluid, blood plasma, and serum., Methods: Protein-Protein Interaction (PPI) networks of LGMN or δ-secretase were constructed using the Genemania database. Network Analyzer, a Cytoscape plugin, analyzed the network topological properties of LGMN. miRNAs related to Alzheimer's were extracted from the HMDD (Human microRNA Disease Database) and experimentally verified miRNA-gene interaction was obtained by searching miRWalk. Starbase v2.0 and miRanda were used for screening miRNA of LGMN genes. Moreover, to understand the regulatory mechanism in AD, we have screened major transcription factors of LGMN targeted genes using the Network Analyst 3.0, TRRUST (v2.0) server, and ENCODE. The Genotype-Tissue Expression (GTEx) and BEST tool were used to investigate the expression pattern of the LGMN gene. In parallel, we performed in-silico drug designing of the novel inhibitor scaffold of δ-secretase as powerful therapeutic targets by using the concept of scaffolds and frameworks. In this context, this study also aimed at identifying effective small molecule inhibitors targeting δ-secretase., Results: Among the 16 experimentally verified miRNAs, Network analysis of the LGMN and its associated miRNA identify novel hsa-miRNA-106a-5p and hsa-miRNA-34a-5p being more expressed in the brain. Our in silico high throughput screening, followed by XP docking revealed Oprea1 as the lead. Molecular dynamic simulations of the δ-secretase-docked complex have been carried out for a time period of 200 ns and revealed that Root Mean Square Deviation (RMSD) of the protein Cα-backbone with respect to its starting position increased to 1.20 Å for the first 25 ns of the trajectory and then became stable around 0.6 Å in the last 170 ns course of the simulation. The radius of gyration (RGYR) reveals that compactness was maintained till the end of simulations., Conclusion: Network analysis of LGMN associated miRNAs lead to the identification of two novel miRNAs, being highly expressed in the brain. This study also lead to the identification and expression of 10 Transcription factors associated with LGMN. Expression Heatmap results show high and continuous expression of LGMN in most of the regions of the brain, especially in the frontal cortex. Further, in silico drug analysis led us to the identification of Oprea1 which could be taken for further investigation to explore its potential for AD therapy., Competing Interests: The authors declare no conflict of interest., (© 2021 The Authors. Published by Elsevier Ltd.)

Background: The spread of a novel severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) has affected both the public health and the global economy. The current study was aimed at analysing the genetic sequence of this highly contagious corona virus from an evolutionary perspective, comparing the genetic variation features of different geographic strains, and identifying the key miRNAs as well as their gene targets from the transcriptome data of infected lung tissues., Methods: A multilevel robust computational analysis was undertaken for viral genetic sequence alignment, phylogram construction, genome-wide transcriptome data interpretation of virus-infected lung tissues, miRNA mapping, and functional biology networking., Results: Our findings show both genetic similarities as well as notable differences in the S protein length among SARS-CoV-1, SARS-CoV-2 and MERS viruses. All SARS-CoV-2 strains showed a high genetic similarity with the parent Wuhan strain, but Saudi Arabian, South African, USA, Russia and New Zealand strains carry 3 additional genetic variations like P333L (RNA -dependant RNA polymerase), D614G (spike), and P4715L (ORF1ab). The infected lung tissues demonstrated the upregulation of 282 (56.51%) antiviral defensive response pathway genes and downregulation of 217 (43.48%) genes involved in autophagy and lung repair pathways. By miRNA mapping, 4 key miRNAs (hsa-miR-342-5p, hsa-miR-432-5p, hsa-miR-98-5p and hsa-miR-17-5p), targeting multiple host genes (MYC, IL6, ICAM1 and VEGFA) as well as SARS-CoV2 gene (ORF1ab) were identified., Conclusion: Systems biology methods offer a new perspective in understanding the molecular basis for the faster spread of SARS-CoV-2 infection. The antiviral miRNAs identified in this study may aid in the ongoing search for novel personalized therapeutic avenues for COVID patients., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Although COVID-19 largely causes respiratory complications, it can also lead to various extrapulmonary manifestations resulting in higher mortality and these comorbidities are posing a challenge to the health care system. Reports indicate that 30-60% of patients with COVID-19 suffer from neurological symptoms. To understand the molecular basis of the neurologic comorbidity in COVID-19 patients, we have investigated the genetic association between COVID-19 and various brain disorders through a systems biology-based network approach and observed a remarkable resemblance. Our results showed 123 brain-related disorders associated with COVID-19 and form a high-density disease-disease network. The brain-disease-gene network revealed five highly clustered modules demonstrating a greater complexity of COVID-19 infection. Moreover, we have identified 35 hub proteins of the network which were largely involved in the protein catabolic process, cell cycle, RNA metabolic process, and nuclear transport. Perturbing these hub proteins by drug repurposing will improve the clinical conditions in comorbidity. In the near future, we assumed that in COVID-19 patients, many other neurological manifestations will likely surface. Thus, understanding the infection mechanisms of SARS-CoV-2 and associated comorbidity is a high priority to contain its short- and long-term effects on human health. Our network-based analysis strengthens the understanding of the molecular basis of the neurological manifestations observed in COVID-19 and also suggests drug for repurposing.

The global pandemic crisis, coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has claimed the lives of millions of people across the world. Development and testing of anti-SARS-CoV-2 drugs or vaccines have not turned to be realistic within the timeframe needed to combat this pandemic. Here, we report a comprehensive computational approach to identify the multi-targeted drug molecules against the SARS-CoV-2 proteins, whichare crucially involved in the viral-host interaction, replication of the virus inside the host, disease progression and transmission of coronavirus infection. Virtual screening of 75 FDA-approved potential antiviral drugs against the target proteins, spike (S) glycoprotein, human angiotensin-converting enzyme 2 (hACE2), 3-chymotrypsin-like cysteine protease (3CLpro), cathepsin L (CTSL), nucleocapsid protein, RNA-dependent RNA polymerase (RdRp) and non-structural protein 6 (NSP6), resulted in the selection of seven drugs which preferentially bind to the target proteins. Further, the molecular interactions determined by molecular dynamics simulation revealed that among the 75 drug molecules, catechin can effectively bind to 3CLpro, CTSL, RBD of S protein, NSP6 and nucleocapsid protein. It is more conveniently involved in key molecular interactions, showing binding free energy (ΔGbind) in the range of -5.09 kcal/mol (CTSL) to -26.09 kcal/mol (NSP6). At the binding pocket, catechin is majorly stabilized by the hydrophobic interactions, displays ΔEvdW values: -7.59 to -37.39 kcal/mol. Thus, the structural insights of better binding affinity and favorable molecular interaction of catechin toward multiple target proteins signify that catechin can be potentially explored as a multi-targeted agent against COVID-19., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

The recurrent and recent global outbreak of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has turned into a global concern which has infected more than 42 million people all over the globe, and this number is increasing in hours. Unfortunately, no vaccine or specific treatment is available, which makes it more deadly. A vaccine-informatics approach has shown significant breakthrough in peptide-based epitope mapping and opens the new horizon in vaccine development. In this study, we have identified a total of 15 antigenic peptides [including thymus cells (T-cells) and bone marrow or bursa-derived cells] in the surface glycoprotein (SG) of SARS-CoV-2 which is nontoxic and nonallergenic in nature, nonallergenic, highly antigenic and non-mutated in other SARS-CoV-2 virus strains. The population coverage analysis has found that cluster of differentiation 4 (CD4+) T-cell peptides showed higher cumulative population coverage over cluster of differentiation 8 (CD8+) peptides in the 16 different geographical regions of the world. We identified 12 peptides ((LTDEMIAQY, WTAGAAAYY, WMESEFRVY, IRASANLAA, FGAISSVLN, VKQLSSNFG, FAMQMAYRF, FGAGAALQI, YGFQPTNGVGYQ, LPDPSKPSKR, QTQTNSPRRARS and VITPGTNTSN) that are $80\hbox{--} 90\%$ identical with experimentally determined epitopes of SARS-CoV, and this will likely be beneficial for a quick progression of the vaccine design. Moreover, docking analysis suggested that the identified peptides are tightly bound in the groove of human leukocyte antigen molecules which can induce the T-cell response. Overall, this study allows us to determine potent peptide antigen targets in the SG on intuitive grounds, which opens up a new horizon in the coronavirus disease (COVID-19) research. However, this study needs experimental validation by in vitro and in vivo., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has resulted in 92 million cases in a span of 1 year. The study focuses on understanding population-specific variations attributing its high rate of infections in specific geographical regions particularly in the United States. Rigorous phylogenomic network analysis of complete SARS-CoV-2 genomes (245) inferred five central clades named a (ancestral), b, c, d, and e (subtypes e1 and e2). Clade d and subclade e2 were found exclusively comprised of U.S. strains. Clades were distinguished by 10 co-mutational combinations in Nsp3, ORF8, Nsp13, S, Nsp12, Nsp2, and Nsp6. Our analysis revealed that only 67.46% of single nucleotide polymorphism (SNP) mutations were at the amino acid level. T1103P mutation in Nsp3 was predicted to increase protein stability in 238 strains except for 6 strains which were marked as ancestral type, whereas co-mutation (P409L and Y446C) in Nsp13 were found in 64 genomes from the United States highlighting its 100% co-occurrence. Docking highlighted mutation (D614G) caused reduction in binding of spike proteins with angiotensin-converting enzyme 2 (ACE2), but it also showed better interaction with the TMPRSS2 receptor contributing to high transmissibility among U.S. strains. We also found host proteins, MYO5A, MYO5B, and MYO5C, that had maximum interaction with viral proteins (nucleocapsid [N], spike [S], and membrane [M] proteins). Thus, blocking the internalization pathway by inhibiting MYO5 proteins which could be an effective target for coronavirus disease 2019 (COVID-19) treatment. The functional annotations of the host-pathogen interaction (HPI) network were found to be closely associated with hypoxia and thrombotic conditions, confirming the vulnerability and severity of infection. We also screened CpG islands in Nsp1 and N conferring the ability of SARS-CoV-2 to enter and trigger zinc antiviral protein (ZAP) activity inside the host cell. IMPORTANCE In the current study, we presented a global view of mutational pattern observed in SARS-CoV-2 virus transmission. This provided a who-infect-whom geographical model since the early pandemic. This is hitherto the most comprehensive comparative genomics analysis of full-length genomes for co-mutations at different geographical regions especially in U.S. strains. Compositional structural biology results suggested that mutations have a balance of opposing forces affecting pathogenicity suggesting that only a few mutations are effective at the translation level. Novel HPI analysis and CpG predictions elucidate the proof of concept of hypoxia and thrombotic conditions in several patients. Thus, the current study focuses the understanding of population-specific variations attributing a high rate of SARS-CoV-2 infections in specific geographical regions which may eventually be vital for the most severely affected countries and regions for sharp development of custom-made vindication strategies., (Copyright © 2021 Gupta et al.)

One of the main concerns about the fast spreading coronavirus disease 2019 (Covid-19) pandemic is how to intervene. We analysed severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) isolates data using the multifractal approach and found a rich in viral genome diversity, which could be one of the root causes of the fast Covid-19 pandemic and is strongly affected by pressure and health index of the hosts inhabited regions. The calculated mutation rate (mr) is observed to be maximum at a particular pressure, beyond which mr maintains diversity. Hurst exponent and fractal dimension are found to be optimal at a critical pressure (Pm), whereas, for P > Pm and P < Pm, we found rich genome diversity relating to complicated genome organisation and virulence of the virus. The values of these complexity measurement parameters are found to be increased linearly with health index values.

Cardio-renal syndrome (CRS) is a rapidly recognized clinical entity which refers to the inextricably connection between heart and renal impairment, whereby abnormality to one organ directly promotes deterioration of the other one. Biological markers help to gain insight into the pathological processes for early diagnosis with higher accuracy of CRS using known clinical findings. Therefore, it is of interest to identify target genes in associated pathways implicated linked to CRS. Hence, 119 CRS genes were extracted from the literature to construct the PPIN network. We used the MCODE tool to generate modules from network so as to select the top 10 modules from 23 available modules. The modules were further analyzed to identify 12 essential genes in the network. These biomarkers are potential emerging tools for understanding the pathophysiologic mechanisms for the early diagnosis of CRS. Ontological analysis shows that they are rich in MF protease binding and endo-peptidase inhibitor activity. Thus, this data help increase our knowledge on CRS to improve clinical management of the disease., (© 2021 Biomedical Informatics.)

We study a minimal model of the stress-driven p53 regulatory network that includes competition between active and mutant forms of the tumor-suppressor gene p53. Depending on the nature and level of the external stress signal, four distinct dynamical states of p53 are observed. These states can be distinguished by different dynamical properties which associate to active, apoptotic, pre-malignant and cancer states. Transitions between any two states, active, apoptotic, and cancer, are found to be unidirectional and irreversible if the stress signal is either oscillatory or constant. When the signal decays exponentially, the apoptotic state vanishes, and for low stress the pre-malignant state is bounded by two critical points, allowing the system to transition reversibly from the active to the pre-malignant state. For significantly large stress, the range of the pre-malignant state expands, and the system moves to irreversible cancerous state, which is a stable attractor. This suggests that identification of the pre-malignant state may be important both for therapeutic intervention as well as for drug delivery.

Parathyroid adenoma (PA) is marked by a certain benign outgrowth in the surface of parathyroid glands. The transcriptome analysis of parathyroid adenomas can provide a deep insight into actively expressed genes and transcripts. Hence, we analyzed and compared the gene expression profiles of parathyroid adenomas and healthy parathyroid gland tissues from Gene Expression Omnibus (GEO) database. We identified a total of 280 differentially expressed genes (196 up-regulated, 84 down-regulated), which are involved in a wide array of biological processes. We further constructed a gene interaction network and analyzed its topological properties to know the network structure and its hidden mechanism. This will help to understand the molecular mechanisms underlying parathyroid adenoma development. We thus identified 13 key regulators (PRPF19, SMC3, POSTN, SNIP1, EBF1, MEIS2, PAX9, SCUBE2, WNT4, ARHGAP10, DOCK5, CAV1 and VSIR), which are deep-rooted from top to bottom in the gene interaction network forming a backbone for the network. The structural features of the network are probably maintained by crosstalk between important genes within the network along with associated functional modules.Thus, gene-expression profiling and network approach could be used to provide an independent platform to glen insights from available clinical data., Competing Interests: The authors declare no conflict of interest., (© 2020 Biomedical Informatics.)

We propose a Hes1-Notch-miR-9 regulatory network and studied the regulating mechanism of miR-9 and Hes1 dynamics driven by Notch. Change in Notch concentration, which serves as a stress signal, can trigger the dynamics of Hes1 and miR-9 at five different states, namely, sTable (2), sustain (1) and mixed (2) states those may correspond to different cellular states. Further, this Notch stress signal introduce time reversal oscillation, which behaves as backward wave, after a certain threshold value of the stress signal and defends the system from moving to apoptosis. We also observe heterogeneous patterns of Hes1, miR-9 and other molecular species in various two dimensional parameter spaces and found that the variability in the patterns is triggered by Hill coefficient and Hes1 stress signal. The phase or bifurcation diagram in time period of oscillation (T N ) driven by Notch signal provides all five states, predicts minimum threshold value T N c beyond which tendency to build up backward wave starts and T N c serves as bifurcation point of the system., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Complex disease networks can be studied successfully using network theoretical approach which helps in finding key disease genes and associated disease modules. We studied prostate cancer (PCa) protein-protein interaction (PPI) network constructed from patients' gene expression datasets and found that the network exhibits hierarchical scale free topology which lacks centrality lethality rule. Knockout experiments of the sets of leading hubs from the network leads to transition from hierarchical (HN) to scale free (SF) topology affecting network integration and organization. This transition, HN → SF, due to removal of significant number of the highest degree hubs, leads to relatively decrease in information processing efficiency, cost effectiveness of signal propagation, compactness, clustering of nodes and energy distributions. A systematic transition from a diassortative PCa PPI network to assortative networks after the removal of top 50 hubs then again reverting to disassortativity nature on further removal of the hubs was also observed indicating the dominance of the largest hubs in PCa network intergration. Further, functional classification of the hubs done by using within module degrees and participation coefficients for PCa network, and leading hubs knockout experiments indicated that kinless hubs serve as the basis of establishing links among constituting modules and heterogeneous nodes to maintain network stabilization. We, then, checked the essentiality of the hubs in the knockout experiment by performing Fisher's exact test on the hubs, and showed that removal of kinless hubs corresponded to maximum lethality in the network. However, excess removal of these hubs essentially may cause network breakdown., (Copyright © 2020. Published by Elsevier Inc.)

Early detection of breast cancer can be best facilitated by the development of precancerous markers. Serum proteins being the sensitive signatures, can be the ideal choice. We previously demonstrated the reduced levels of two serum proteins at a very early stage of tumorigenesis in a breast cancer model, developed in Wistar rats by 7,12-dimethylbenz[a]anthracene (DMBA) administration. Here we report the dysregulation of three more proteins in the serum collected at another early stage (15 weeks) of tumorigenesis in the same model. The proteins were identified (as Alpha-1-inhibitor III (Mug1), Immunoglobulin heavy chain variable region (IGHV), and Hypertrophied skeletal muscle protein GTF3) by MALDI-TOF MS after the screening and fingerprinting of serum samples by one-dimensional (1D) and two-dimensional (2D) electrophoresis respectively. Relative expression analysis of corresponding genes was also carried out, and the results were found as supporting the proteomic findings. In addition, the candidate proteins of the study and their corresponding ribonucleic acids (RNAs) were subjected to homology modelling and docking (using softwares like MODELLER, 3dRNA, Autodock4.0, and GROMACS etc), which revealed the binding sites for carcinogen (DMBA) and its nature of interaction with proteins and RNAs. Moreover, the network analysis by GeneMANIA unraveled the protein/gene functional network in which Mug1, IGHV, and GTF3 are involved. Based on the significant protein and gene expression alterations in early tumorigenesis, these proteins may prove very effective in search for biomarkers for the early detection of mammary cancer. Further, these proteins can also be tried as targets for chemotherapy., Competing Interests: Declaration of competing interest Authors declare that there is no conflict of interest related to this article., (Copyright © 2020 Elsevier B.V. and Société Française de Biochimie et Biologie Moléculaire (SFBBM). All rights reserved.)

We study the origin of TB (tuberculosis) epidemic and complex distributions of various populations of TB infection within the stochastic framework. The stochastic nature of this disease infection could be linked to the stochastic behaviour at genome level which is exhibited in SNP (single nucleotide polymorphism) distributions of experimentally identified hotspot driver genes. Our results show the emergence of random clusters, and well-defined discrete domains of the respective species populations in the model driven by demographic stochasticity and intrinsic complex species interaction. The multifractal analysis of the time series of the species populations indicate that TB epidemic could be mainly caused by contact communication and is directional. We propose that any TB epidemic may have high chance of approximately periodic recurrence and can be controlled by optimizing some of the parameters involved in the system modelling., (Copyright © 2020 Elsevier Ltd. All rights reserved.)