Mediating role of physician's empathy between physician's communication and patient's satisfaction.

Introduction: Physician communication is vital for an effective physician-patient relationship. Physician empathy is crucial to patient communication. The relationship between physician empathy, physician communication, and patient satisfaction is not very clear. This study aims to study the mediating role of physician's empathy between physician's communication, physician's empathy, and patient's satisfaction. Methods: A cross-sectional study was conducted at the National Institute of Psychology, Quaid-i-Azam University, during the time period of December 2018 to February 2019. Employing the technique of purposive convenience sampling, data were collected (N = 238) from psychiatric, cardiology, and dermatology wards of public and private sector hospitals of Islamabad and Rawalpindi. The Communication Assessment Tool, specifically the Patient's Perception of Physician's Empathy and Patient Satisfaction Scale, was used to assess study variables. The measures used in the research assess the patient's perception of the physician's communication, empathy, and patient's satisfaction. Formal permission for the research was taken from the hospital administration with approval from the institutional review boards. Participants were briefed about the purpose of the research. Both verbal and written informed consent was taken from them. Results: The result shows that a physician's empathy plays a mediating role between the physician's communication skills and patient satisfaction. Moreover, Pearson product-moment correlation indicated a significant positive relationship between doctors' communication skills, doctors' empathy, and patients' satisfaction. Conclusion: Building a positive doctor-patient relationship would not only lead to improved patient satisfaction but also reduce the likelihood of medical malpractice. Therefore, steps should be taken to enforce trust, interaction, and empathy in doctor-patient relationships, with patient-centered services. Physician's empathy plays a mediating role between physician's communication skills and patient's satisfaction.

Decomposing the inequalities in the catastrophic health expenditures on the hospitalization in India: empirical evidence from national sample survey data.

Introduction: Sustainable Development Goal (SDG) Target 3.8.2 entails financial protection against catastrophic health expenditure (CHE) by reducing out-of-pocket expenditure (OOPE) on healthcare. India is characterized by one of the highest OOPE on healthcare, in conjunction with the pervasive socio-economic disparities entrenched in the population. As a corollary, India has embarked on the trajectory of ensuring financial risk protection, particularly for the poor, with the launch of various flagship initiatives. Overall, the evidence on wealth-related inequities in the incidence of CHE in low- and middle-Income countries has been heterogenous. Thus, this study was conducted to estimate the income-related inequalities in the incidence of CHE on hospitalization and glean the individual contributions of wider socio-economic determinants in influencing these inequalities in India. Methods: The study employed cross-sectional data from the nationally represented survey on morbidity and healthcare (75th round of National Sample Survey Organization) conducted during 2017-2018, which circumscribed a sample size of 1,13,823 households and 5,57,887 individuals. The inequalities and need-adjusted inequities in the incidence of CHE on hospitalization care were assessed via the Erreygers corrected concentration index. Need-standardized concentration indices were further used to unravel the inter- and intra-regional income-related inequities in the outcome of interest. The factors associated with the incidence of CHE were explored using multivariate logistic regression within the framework of Andersen's model of behavioral health. Additionally, regression-based decomposition was performed to delineate the individual contributions of legitimate and illegitimate factors in the measured inequalities of CHE. Results: Our findings revealed pervasive wealth-related inequalities in the CHE for hospitalization care in India, with a profound gap between the poorest and richest income quintiles. The negative value of the concentration index (EI: -0.19) indicated that the inequalities were significantly concentrated among the poor. Furthermore, the need-adjusted inequalities also demonstrated the pro-poor concentration (EI: -0.26), denoting the unfair systemic inequalities in the CHE, which are disadvantageous to the poor. Multivariate logistic results indicated that households with older adult, smaller size, vulnerable caste affiliation, poorest income quintile, no insurance cover, hospitalization in a private facility, longer stay duration in the hospital, and residence in the region at a lower level of epidemiological transition level were associated with increased likelihood of incurring CHE on hospitalization. The decomposition analysis unraveled that the contribution of non-need/illegitimate factors (127.1%) in driving the inequality was positive and relatively high vis-à-vis negative low contribution of need/legitimate factors (35.3%). However, most of the unfair inequalities were accounted for by socio-structural factors such as the size of the household and enabling factors such as income group and utilization pattern. Conclusion: The study underscored the skewed distribution of CHE as the poor were found to incur more CHE on hospitalization care despite the targeted programs by the government. Concomitantly, most of the inequality was driven by illegitimate factors amenable to policy change. Thus, policy interventions such as increasing the awareness, enrollment, and utilization of Publicly Financed Health Insurance schemes, strengthening the public hospitals to provide improved quality of specialized care and referral mechanisms, and increasing the overall budgetary share of healthcare to improve the institutional capacities are suggested.

Face mask use in the city of Chennai, India: Results from three serial cross-sectional surveys, 2021.

INTRODUCTION: The Government of Tamil Nadu, India, mandated wearing face masks in public places to combat the COVID-19 pandemic. We established face mask surveillance and estimated the prevalence of appropriate mask use (covering the nose, mouth, and chin) in the slums and non-slums of Chennai at different time points in 2021. METHODS: We conducted three serial cross-sectional surveys in the outdoors and indoors of Chennai in March, July, and October 2021. We observed the mask wearing among 3200 individuals in the outdoors and 1280 in the indoors. We divided the outdoor and indoor locations into slums and non-slums. In October 2021, we also surveyed 150 individuals from each of the 11 shopping malls in the city. We calculated the proportions and 95% confidence interval (95%CI) for the appropriate mask use in the outdoor, indoor, and malls by age, gender, region, and setting (slum and non-slum). RESULTS: We observed 3200 individuals in the outdoor and 1280 individuals in the indoor setting, each from a slum and non-slum, during the three rounds of the study. In outdoor and indoors, males comprised three-fourths and middle-aged individuals were half the study population. Mask compliance changed significantly with time (p-value <0.001). Males consistently demonstrated better compliance in all rounds. The south region had the highest mask compliance in slums indoors and outdoors in rounds 4 and 5. Young adults had the highest mask compliance in both outdoor slums and non-slums in all rounds. Overall mask compliance in shopping malls was 57% (95% CI: 48-65). CONCLUSION: The mask compliance in Chennai outdoors during the COVID-19 pandemic was less than 50%, with variations across time points by gender, age groups, and geographical locations. We must develop more effective communication strategies for older age groups and crowded indoor settings.

Investigating the structural basis of piperine targeting AKT1 against prostate cancer through in vitro and molecular dynamics simulations.

AkT1, significantly impacts many tumours cell functions, like transcription, apoptosis, glucose metabolism, cell proliferation, and cell migration. For tumours to develop and spread, aberrant activation of AKT1 is essential. Therefore, a major focus of molecularly targeted PCa treatment is AKT1. The present study investigates the effect of piperine compared to SDF using in-vitro studies, viz colony formation assay, comet assay and AKT1 gene expression studies using human PCa cell line PC3. A cluster of approximately at least 50 cells constitutes a colony. The clonogenic assay showed that the number and size of colonies significantly decreased when treated with compounds (SDF and piperine) in comparison to the untreated cells which effectively proliferated to form more colonies. Piperine treatment showed significant inhibition of colony formation than SDF. Effective genotoxicity was observed in piperine-treated PC3 cells with an increased Tail length of 120 µm and it was moderately observed in SDF with a Tail length of 30 µm treated on PC3 cells. The control group did not show any considerable genotoxicity with a Tail length of 6 µm. Our data, both in vitro and in silico, suggested that piperine would be a good starting point for developing novel drugs for the treatment of PCa. The downstream functions of Akt1 may be inhibited by these effects, which could impede the proliferation of PCa cells. High stability of the piperine-AKT1 complex was found by the MD simulation. Higher hydrophilic residues like Lys268 and Ser205 at the active pocket may be the cause of the binding stability. Overall, the observed results confirmed the anti-PCa effect of piperine by causing effective DNA damage and proved to be genotoxic in nature against the human PCa. These effects may impede the downstream activities of Akt1 and result in PCa cell growth regression.Communicated by Ramaswamy H. Sarma.

A combined in vitro and molecular dynamics simulation studies unveil the molecular basis of the anticancer potential of piperine targeting AKT1 against prostate cancer.

The present study investigates the activity of the natural compound piperine on prostate cancer cell line (PC-3), followed by exploring its mechanistic inhibition on the RAC-alpha serine/threonine-protein kinase (AKT1) protein. The 3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide (MTT) assay showed that after 24 hrs of exposure to piperine (15 µmol/ml), cell viability fell to 50% compared to the standard drug flutamide (SDF) (51 µmol/ml) with a lower IC50 concentration. However, the Dual acridine orange/ethidium bromide (AO/EtBr) staining demonstrated that, as compared to the SDF, piperine caused substantial cellular death in PC-3 cells, presumably by triggering DNA fragmentation. In addition, compared to untreated cells, the proportion of the sub-G0/G1 and G2/M stages population increased considerably in piperine-treated cells. The cell cycle's sub-G0/G1 and G2/M phases were also arrested in piperine-treated cells compared to the SDF in cell cycle analysis. Based on our systems pharmacology and molecular docking studies, AKT1 is predicted as a potential target against piperine. The complementary charge between AKT1 and piperine was emphasized in the transient ligand-protein binding interaction in molecular dynamic modeling over 100 ns, and stable hydrogen bond interaction between Lys268 and Ser205 amino acid residues of the active pocket was hypothesized. Overall, the findings from our in vitro and MD simulations provide insights into the mechanism of piperine targeting AKT1 and offer a possible candidate for future prostate cancer therapeutic development.Communicated by Ramaswamy H. Sarma.

High-throughput screening and molecular dynamics simulations of natural products targeting LuxS/AI-2 system as a novel antibacterial strategy for antibiotic resistance in Helicobacter pylori.

The main goal of treating any Helicobacter pylori (H. pylori)-related gastrointestinal disease is completely eradicating infection. Falling eradication efficiency, off-target effects, and patient noncompliance with prolonged and broad spectrums have sparked clinical interest in exploring other effective, safer therapeutic choices. As natural substances are risk-free and privileged with high levels of antibacterial activity, most of these natural chemical's specific modes of action are unknown. With the aid of in silico molecular docking-based virtual screening studies and molecular dynamic simulations, the current study is intended to gather data on numerous such natural chemicals and assess their affinity for the S-ribosyl homocysteine lyase (LuxS) protein of H. pylori. The ligand with the highest binding energy with LuxS, glucoraphanin, catechin gallate and epigallocatechin gallate were rationally selected for further computational analysis. The solution stability of the three compounds' optimal docking postures with LuxS was initially assessed using long-run molecular dynamics simulations. Using molecular dynamics simulation, the epigallocatechin gallate was found to be the most stable molecule with the highest binding free energy, indicating that it might compete with the natural ligand of the inhibitors. According to ADMET analysis, his phytochemical was a promising therapeutic candidate for an antibacterial action since it had a range of physicochemical, pharmacokinetic, and drug-like qualities and had no discernible adverse effects. Additional in vitro, in vivo, and clinical trials are needed to confirm the drug's precise efficacy during H. pylori infection.Communicated by Ramaswamy H. Sarma.

System-level protein interaction network analysis and molecular dynamics study reveal interaction of ferulic acid with PTGS2 as a natural radioprotector.

Ferulic acid is a crucial bioactive component of broccoli, wheat, and rice bran and is also an essential natural product that has undergone significant research. Ferulic acid's precise mode of action and effect on system-level protein networks have not been thoroughly investigated. An interactome was built using the STRING database and Cytoscape tools, utilizing 788 key proteins collected from PubMed literature to identify the ferulic acid-governed regulatory action on protein interaction network (PIN). The scale-free biological network of ferulic acid-rewired PIN is highly interconnected. We discovered 15 sub-modules using the MCODE tool for sub-modulization analysis and 153 enriched signaling pathways. Further, functional enrichment of top bottleneck proteins revealed the FoxO signaling pathway involved in enhancing cellular defense against oxidative stress. The selection of the critical regulatory proteins of the ferulic acid-rewired PIN was completed by performing analyses of topological characteristics such as GO term/pathways analysis, degree, bottleneck, molecular docking, and dynamics investigations. The current research derives a precise molecular mechanism for ferulic acid's action on the body. This in-depth in silico model would aid in understanding how ferulic acid origins its antioxidant and scavenging properties in the human body.Communicated by Ramaswamy H. Sarma.

Domain Architecture Based Methods for Comparative Functional Genomics Toward Therapeutic Drug Target Discovery.

Genes duplicate, mutate, recombine, fuse or fission to produce new genes, or when genes are formed from de novo, novel functions arise during evolution. Researchers have tried to quantify the causes of these molecular diversification processes to know how these genes increase molecular complexity over a period of time, for instance protein domain organization. In contrast to global sequence similarity, protein domain architectures can capture key structural and functional characteristics, making them better proxies for describing functional equivalence. In Prokaryotes and eukaryotes it has proven that, domain designs are retained over significant evolutionary distances. Protein domain architectures are now being utilized to categorize and distinguish evolutionarily related proteins and find homologs among species that are evolutionarily distant from one another. Additionally, structural information stored in domain structures has accelerated homology identification and sequence search methods. Tools for functional protein annotation have been developed to discover, protein domain content, domain order, domain recurrence, and domain position as all these contribute to the prediction of protein functional accuracy. In this review, an attempt is made to summarise facts and speculations regarding the use of protein domain architecture and modularity to identify possible therapeutic targets among cellular activities based on the understanding their linked biological processes.

Integrated molecular-network analysis reveals infertility-associated key genes and transcription factors in the non-obstructive azoospermia.

BACKGROUND: Male infertility is a multifactorial reproductive health problem with complex causes. Non-obstructive azoospermia (NOA) is characterized by failure of spermatogenesis, leading to the absence of spermatozoa in ejaculates. The molecular mechanism underlying the NOA is still not well understood. OBJECTIVES: This study aims to identify the key genes involved in male infertility that could be a potential biomarker in the diagnosis and prognosis of azoospermia. STUDY DESIGN: The microarray expression profiles dataset GSE45885 and GSE45887 were downloaded from the NCBI's Gene Expression Omnibus (GEO) database and analyzed for male infertility-associated differentially expressed genes (DEGs) using the GEO2R tool. The common DEGs between the two datasets were combined and their protein-protein interaction (PPI) network was constructed using Cytoscape to reveal the hub genes by topology and module analysis. In addition, transcription factors (TFs) and protein kinases regulating the hub genes were identified using the X2K tool. Then, the expression of the hub genes was validated by analyzing the GSE190752 microarray dataset. Further, the PPI network was screened for biological roles and enriched pathways using DAVID software. RESULTS: About 256 DEGs associated with NOA were identified and constructed the PPI network to find the infertility-associated proteins. The biological processes linked with these proteins were spermatogenesis, cell differentiation, flagellated sperm motility, and spermatid development. The topology and module analysis of the infertility-associated protein network identified the hub genes TEX38, FAM71F, PRR30, FAM166A, LYZL6, TPPP2, ARMC12, SPACA4, and FAM205A, which were found to be upregulated in the non-obstructive azoospermia. In addition, a total of 23 transcription factors and 3 protein kinases that are regulating these key hub genes were identified. Further these hub genes expression was validated using the microarray data and found that their expression was increased in the testicular biopsies obtained from NOA subjects, compared to healthy individuals. CONCLUSION: The identified key genes and its associated transcription factors are known to regulate the infertility-related processes in the non-obstructive azoospermia. Also, the clinical sample-based microarray data validation for the expression of these key hub genes indicates their potentiality to develop them as diagnostic or prognostic biomarkers for NOA.

Early diagnostic and prognostic biomarkers for gastric cancer: systems-level molecular basis of subsequent alterations in gastric mucosa from chronic atrophic gastritis to gastric cancer.

PURPOSE: It is important to comprehend how the molecular mechanisms shift when gastric cancer in its early stages (GC). We employed integrative bioinformatics approaches to locate various biological signalling pathways and molecular fingerprints to comprehend the pathophysiology of the GC. To facilitate the discovery of their possible biomarkers, a rapid diagnostic may be made, which leads to an improved diagnosis and improves the patient's prognosis. METHODS: Through protein-protein interaction networks, functional differentially expressed genes (DEGs), and pathway enrichment studies, we examined the gene expression profiles of individuals with chronic atrophic gastritis and GC. RESULTS: A total of 17 DEGs comprising 8 upregulated and 9 down-regulated genes were identified from the microarray dataset from biopsies with chronic atrophic gastritis and GC. These DEGs were primarily enriched for CDK regulation of DNA replication and mitotic M-M/G1 phase pathways, according to KEGG analysis (p > 0.05). We discovered two hub genes, MCM7 and CDC6, in the protein-protein interaction network we obtained for the 17 DEGs (expanded with increased maximum interaction with 110 nodes and 2103 edges). MCM7 was discovered to be up-regulated in GC tissues following confirmation using the GEPIA and Human Protein Atlas databases. CONCLUSION: The elevated expression of MCM7 in both chronic atrophic gastritis and GC, as shown by our comprehensive investigation, suggests that this protein may serve as a promising biomarker for the early detection of GC.

Genome analysis of clinical genotype Vibrio vulnificus isolated from seafood in Mangaluru Coast, India provides insights into its pathogenicity.

Vibrio vulnificus an opportunistic human pathogen native to marine/estuarine environment, is one of the leading causes of death due to seafood consumption and exposure of wounds to seawater worldwide. The present study involves the whole genome sequence analysis of an environmental strain of V. vulnificus (clinical genotype) isolated from seafood along the Mangaluru coast of India. The sequenced genome data was subjected to in-silico analysis of phylogeny, virulence genes, antimicrobial resistance determinants, and secretary proteins using suitable bioinformatics tools. The sequenced isolate had an overall genome length of 4.8 Mb and GC content of 46% with 4400 coding DNA sequences. The sequenced strain belongs to a new sequence type (Multilocus sequence typing) and was also found to branch with a phylogenetic lineage that groups the most infectious strains of V. vulnificus. The seafood isolate had complete genes involved in conferring serum resistance yet showed limited serum resistance. The study identified several genes against the antibiotics that are commonly used in their treatment, highlighting the need for alternative treatments. Also, the secretory protein analysis revealed genes associated with major pathways like ABC transporters, two-component systems, quorum sensing, biofilm formation, cationic antimicrobial peptide (CAMP) resistance, and others that play a critical role in the pathogenesis of the V. vulnificus. To the best of our knowledge, this is the first report of a detailed analysis of the genomic information of a V. vulnificus isolated from the Indian subcontinent and provides evidence that raises public health concerns about the safety of seafood.

Exploring breast cancer exosomes for novel biomarkers of potential diagnostic and prognostic importance.

The comprehensive bioinformatics analysis of breast cancer exosomes revealed that HSP90AA1, CCT2, and ENO1 were novel hub genes in the giant protein-protein interaction network of 110 exosomal proteins. Exosomes and their cargo such as discrete proteins, nucleic acids, and lipids are having potential role in the pathophysiology of breast cancer (BC). This study showed that the identified hub genes were particularly abundant in GO and KEGG pathways relevant to the positive regulation of telomerase. In addition, these hub genes were found to be considerably overexpressed in breast adenocarcinoma patients compared to healthy controls, and further, this overexpression is linked to the poor prognosis in BC patients. Furthermore, the ROC analysis revealed that CCT2 gene has strong diagnostic and prognostic value for BC. Additionally, this in silico analysis found that the anticancer agents and HSP90 inhibitors such as ganetespib, retaspimycin, and tanespimycin would have considerable potential in the treatment of BC. Overall, this study findings imply that HSP90AA1, a molecular chaperon and CCT2, a chaperonin would serve as diagnostic and prognostic biomarkers, respectively, for BC. However, these findings need to be further confirmed by laboratory and clinical studies for validating their potential applications. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-022-03422-w.

Nrf2-regulated antioxidant response ameliorating ionizing radiation-induced damages explored through in vitro and molecular dynamics simulations.

This study aims to investigate the mechanism of natural antioxidant ferulic acid (FA) in reducing oxidative stress followed by its inhibitory effect on the Keap1-Nrf2 complex. FA was treated ex vivo with human blood for 30 min at 37 °C ± 1 °C and exposed to 1.5 Gy of γ- rays of 60Co (0.789 Gy/min) and allowed for repair for an hour at 37 °C ± 1 °C. FA's free radical scavenging capacity was measured using 2,7-dichlorofluorescein diacetate assay and cytogenetic assays. Further, a possible mechanism of protein-ligand interaction between FA and Keap1-Nrf2 pathway protein as a cellular drug target was studied using docking and molecular dynamics simulation. The 1.5 Gy of γ- rays exposed to pre-treated blood with FA showed a significant (p < 0.05) reduction in reactive oxygen species and DNA damage compared to the normal control blood group sample. The ligand-protein transient binding interaction in molecular dynamic simulation over a period of 100 ns was consistent and stable emphasizing complementary charge between the protein and ligand, speculating higher hydrophobic amino acid residues in the Keap1 active pocket. This might sway the Keap1 from interaction with Nrf2, and could lead to nuclear translocation of Nrf2 during radiation-induced oxidative stress. The present study emphasizes the radioprotective effect of FA against 1.5 Gy of γ- rays exposed to human blood and the application of in silico approaches helpful for the possible protective effect of FA.Communicated by Ramaswamy H. Sarma.

Gene expression profile analysis unravelled the systems level association of renal cell carcinoma with diabetic nephropathy and Matrix-metalloproteinase-9 as a potential therapeutic target.

Type 2 diabetes (T2D) and cancer share many common risk factors. However, the potential biological link that connects the two at the molecular level is still unclear. The experimental evidence suggests that several genes and their pathways may be involved in developing cancerous conditions associated with diabetes. In this study, we identified the protein-protein interaction (PPI) networks and the hub protein(s) that interlink T2D and cancer using genome-scale differential gene expression profiles. Further, the PPI network of AMP-activated protein kinase (AMPK) in cancer was analyzed to explore novel insights into the molecular association between the two conditions. The densely connected regions were analyzed by constructing the backbone and subnetworks with key nodes and shortest pathways, respectively. The PPI network studies identified Matrix-metalloproteinase-9 (MMP-9) as a hub protein playing a vital role in glomerulonephritis tubular diseases and some genetic kidney diseases. MMP-9 was also associated with different growth factors, like tumor necrosis factor (TNF-α), transforming growth factor 1 (TGF-1), and pathways like chemokine signaling, NOD-like receptor signaling, etc. Further, the molecular docking and molecular dynamic simulation studies supported the druggability of MMP-9, suggesting it as a potential therapeutic target in treating renal cell carcinoma linked with diabetic kidney disease.Communicated by Ramaswamy H. Sarma.

Systems Pharmacology and Pharmacokinetics Strategy to Decode Bioactive Ingredients and Molecular Mechanisms from Zingiber officinale as Phyto-therapeutics against Neurological Diseases.

BACKGROUND: The bioactive constituents from Zingiber officinale (Z. officinale) have shown a positive effect on neurodegenerative diseases like Alzheimer's disease (AD), which manifests as progressive memory loss and cognitive impairment. OBJECTIVE: This study investigates the binding ability and the pharmaco-therapeutic potential of Z. officinale with AD disease targets by molecular docking and molecular dynamic (MD) simulation approaches. METHODS: By coupling enormous available phytochemical data and advanced computational technologies, the possible molecular mechanism of action of these bioactive compounds was deciphered by evaluating phytochemicals, target fishing, and network biological analysis. RESULTS: As a result, 175 bioactive compounds and 264 human target proteins were identified. The gene ontology and Kyoto Encyclopaedia of Genes and Genomes pathway enrichment analysis and molecular docking were used to predict the basis of vital bioactive compounds and biomolecular mechanisms involved in the treatment of AD. Amongst selected bioactive compounds, 10- Gingerdione and 1-dehydro-[8]-gingerdione exhibited significant anti-neurological properties against AD targeting amyloid precursor protein with docking energy of -6.0 and -5.6, respectively. CONCLUSION: This study suggests that 10-Gingerdione and 1-dehydro-[8]-gingerdione strongly modulates the anti-neurological activity and are associated with pathological features like amyloid-ß plaques and hyperphosphorylated tau protein are found to be critically regulated by these two target proteins. This comprehensive analysis provides a clue for further investigation of these natural compounds' inhibitory activity in drug discovery for AD treatment.

Identification of key gene signatures and their characterization by expression correlation with drug sensitivity in smoking-associated oral squamous cell carcinoma.

AIMS: Oral squamous cell carcinoma (OSCC), a most frequent type of head-and-neck cancer, is becoming more common and posing a substantial health risk. Using a network biology strategy, this study intended to find and investigate critical genes associated with OSCC. MATERIALS AND METHODS: The extended protein-protein interaction networks for differentially expressed genes related to smoking and nonsmoking conditions of OSCC were constructed and visualized using Cytoscape software. The hub genes/proteins were determined based on degree and betweenness centrality measures and then evaluated and validated for expression using the Gene Expression Profiling Interactive Analysis 2 (GEPIA2), and their relationship to the sensitivity of small molecules was discovered utilizing the Gene Set Cancer Analysis (GSCA) web server. RESULTS: A total of 596 differentially expressed genes were screened, and four genes, interleukin (IL)-6, JUN, tumor necrosis factor (TNF), and vascular endothelial growth factor A (VEGFA), were identified as hub proteins, and their expression and overall survival in head-and-neck cancers were further investigated using GEPIA2. TNF and VEGFA gene expressions were considerably greater in cancers when compared to normal samples, while JUN and IL-6 gene expressions were not statistically significant. Further, these hub proteins are found to have a substantial favorable correlation with overall survival of head-and-neck cancer patients. Finally, GSCA was used to predict gene-specific potential drugs that act on these molecules by combining mRNA expression and drug sensitivity data from the Genomics of Drug Sensitivity in Cancer and the Cancer Therapeutics Response Portal. CONCLUSIONS: The hub genes/proteins identified in this study could help researchers better understand the molecular processes involved in the progression and metastasis of oral cancer in smokers.

Functional insights of antibiotic resistance mechanism in Helicobacter pylori: Driven by gene interaction network and centrality-based nodes essentiality analysis.

Increased antibiotic resistance in Helicobacter pylori (H. pylori), a major human pathogen, constitutes a substantial threat to human health. Understanding the pathophysiology and development of antibiotic resistance can aid our battle with the infections caused by H. pylori. The aim of this study is to discover the high-impact key regulatory mechanisms and genes involved in antimicrobial drug resistance (AMR). In this study, we constructed a functional gene interaction network by integrating multiple sources of data related to antibiotic resistant genes (number-77) from H. pylori. The gene interaction network was assortative, with a hierarchical, scale-free topology enriched in a variety of gene ontology (GO) categories and KEGG pathways. Using an iterative clustering methodology, we identified a number of communities in the AMR gene network that comprised nine genes (sodB, groEL, gyrA, recA, polA, tuf, infB, rpsJ, and gyrB) that were present at the deepest level and hence were key regulators of AMR. Further, an antibiotic-resistant gene network-based centrality analysis revealed superoxide dismutase (sodB) as a bottleneck node in the network. Our findings suggested that sodB is critically enriched in the cellular response to oxidative stress, removal of superoxide radicals, cellular oxidant detoxification processes, cellular component biogenesis, response to reactive oxygen species, urea metabolic process, nitrogen cycle metabolic process and reactive oxygen species metabolic process. We demonstrated how the sodB, which are involved in the response to reactive oxygen species, urea metabolic process, nitrogen cycle metabolic process, reactive oxygen species metabolic process, regulated by Fur gene/proteins, claim a major authority over regulation and signal propagation in the AMR.

Pathway enrichment analysis of virus-host interactome and prioritization of novel compounds targeting the spike glycoprotein receptor binding domain-human angiotensin-converting enzyme 2 interface to combat SARS-CoV-2.

SARS-CoV-2 has become a pandemic causing a serious global health concern. The absence of effective drugs for treatment of the disease has caused its rapid spread on a global scale. Similarly to the SARS-CoV, the SARS-CoV-2 is also involved in a complex interplay with the host cells. This infection is characterized by a diffused alveolar damage consistent with the Acute Respiratory Disease Syndrome (ARDS). To explore the complex mechanisms of the disease at the system level, we used a network medicine tools approach. The protein-protein interactions (PPIs) between the SARS-CoV and the associated human cell proteins are crucial for the viral pathogenesis. Since the cellular entry of SARS-CoV-2 is accomplished by binding of the spike glycoprotein binding domain (RBD) to the human angiotensin-converting enzyme 2 (hACE2), a molecule that can bind to the spike RDB-hACE2 interface could block the virus entry. Here, we performed a virtual screening of 55 compounds to identify potential molecules that can bind to the spike glycoprotein and spike-ACE2 complex interface. It was found that the compound ethyl 1-{3-[(2,4-dichlorobenzyl) carbamoyl]-1-ethyl-6-fluoro-4-oxo-1,4-dihydro-7-quinolinyl}-4-piperidine carboxylate (the S54 ligand) and ethyl 1-{3-[(2,4-dichlorobenzyl) carbamoyl]-1-ethyl-6-fluoro-4-oxo-1,4-dihydro-7-quinolinyl}-4 piperazine carboxylate (the S55 ligand) forms hydrophobic interactions with Tyr41A, Tyr505B and Tyr553B, Leu29A, Phe495B, respectively of the spike glycoprotein, the hotspot residues in the spike glycoprotein RBD-hACE2 binding interface. Furthermore, molecular dynamics simulations and free energy calculations using the MM-GBSA method showed that the S54 ligand is a stronger binder than a known SARS-CoV spike inhibitor SSAA09E3 (N-(9,10-dioxo-9, 10-dihydroanthracen-2-yl) benzamide).Communicated by Ramaswamy H. Sarma.

Utilizing the Potential of Antimicrobial Peptide LL-37 for Combating SARS-COV- 2 Viral Load in Saliva: an In Silico Analysis.

Limiting the spread of virus during the recent pandemic outbreak was a major challenge. Viral loads in saliva, nasopharyngeal and oropharyngeal swabs were the major cause for droplet transmission and aerosols. Saliva being the major contributor for the presence of viral load is the major key factor; various mouthwashes and their combination were analyzed and utilized in health care centers to hamper the spread of virus and decrease viral load. The compositions of these mouthwashes to an extent affected the viral load and thereby transmission, but there is always a scope for other protocols which may provide better results. Here we evaluated the potential of antimicrobial peptide LL-37 in decreasing the viral load of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) through an in silico work and evidence from other studies. This narrative review highlighted a brief nonsystematic methodology to include the selected articles for discussion. Accessible electronic databases (Medline, Scopus, Web of Science, SciELO, and PubMed) were used to find studies that reported the salivary viral load of SARS-CoV-2 published between December 2019 and June 2021. The following keywords were utilized for brief searching of the databases: "saliva," "viral load," and "SARS-CoV-2." Articles in English language, in vitro cell-line studies, ex vivo studies, and clinical trials explaining the viral load of SARS-CoV-2 in saliva and strategies to decrease viral load were included in this review. The search was complemented by manual searching of the reference lists of included articles and performing a citation search for any additional reviews. The antiviral potential of cationic host defense peptide LL-37 was evaluated using computational approaches providing in silico evidence. The analysis of docking studies and the display of positive interfacial hydrophobicity of LL-37 resulting in disruption of COVID-19 viral membrane elucidate the fact that LL-37 could be effective against all variants of SARS-CoV-2. Further experimental studies would be needed to confirm the binding of the receptor-binding domain with LL-37. The possibility of using it in many forms further to decrease the viral load by disrupting the viral membrane is seen.

Genome-scale protein interaction network construction and topology analysis of functional hypothetical proteins in Helicobacter pylori divulges novel therapeutic targets.

The emergence and spread of multi-drug resistance among Helicobacter pylori (H. pylori) strain raise more stakes for genetic research for discovering new drugs. The quantity of uncharacterized hypothetical proteins in the genome may provide an opportunity to explore their property and promulgation could act as a platform for designing the drugs, making them an intriguing genetic target. In this context, the present study aims to identify the key hypothetical proteins (HPs) and their biological regulatory processes in H. pylori. This investigation could provide a foundation to establish the molecular connectivity among the pathways using topological analysis of the protein interaction networks (PINs). The giant network derived from the extended network has 374 nodes connected via 925 edges. A total of 43 proteins with high betweenness centrality (BC), 54 proteins with a large degree, and 23 proteins with high BC and large degrees have been identified. HP 1479, HP 0056, HP 1481, HP 1021, HP 0043, HP 1019, gmd, flgA, HP 0472, HP 1486, HP 1478, and HP 1473 are categorized as hub nodes because they have a higher number of direct connections and are potentially more important in understanding HP's molecular interactions. The pathway enrichment analysis of the network clusters revealed significant involvement of HPs in pathways such as flagellar assembly, bacterial chemotaxis and lipopolysaccharide biosynthesis. This comprehensive computational study revealed HP's functional role and its druggability characteristics, which could be useful in the development of drugs to combat H. pylori infections.