Study of kaempferol in the treatment of COVID-19 combined with Chikungunya co-infection by network pharmacology and molecular docking technology.

Chikungunya (CHIK) patients may be vulnerable to coronavirus disease (COVID-19). However, presently there are no anti-COVID-19/CHIK therapeutic alternatives available. The purpose of this research was to determine the pharmacological mechanism through which kaempferol functions in the treatment of COVID-19-associated CHIK co-infection. We have used a series of network pharmacology and computational analysis-based techniques to decipher and define the binding capacity, biological functions, pharmacological targets, and treatment processes in COVID-19-mediated CHIK co-infection. We identified key therapeutic targets for COVID-19/CHIK, including TP53, MAPK1, MAPK3, MAPK8, TNF, IL6 and NFKB1. Gene ontology, molecular and upstream pathway analysis of kaempferol against COVID-19 and CHIK showed that DEGs were confined mainly to the cytokine-mediated signalling pathway, MAP kinase activity, negative regulation of the apoptotic process, lipid and atherosclerosis, TNF signalling pathway, hepatitis B, toll-like receptor signaling, IL-17 and IL-18 signaling pathways. The study of the gene regulatory network revealed several significant TFs including KLF16, GATA2, YY1 and FOXC1 and miRNAs such as let-7b-5p, mir-16-5p, mir-34a-5p, and mir-155-5p that target differential-expressed genes (DEG). According to the molecular coupling results, kaempferol exhibited a high affinity for 5 receptor proteins (TP53, MAPK1, MAPK3, MAPK8, and TNF) compared to control inhibitors. In combination, our results identified significant targets and pharmacological mechanisms of kaempferol in the treatment of COVID-19/CHIK and recommended that core targets be used as potential biomarkers against COVID-19/CHIK viruses. Before conducting clinical studies for the intervention of COVID-19 and CHIK, kaempferol might be evaluated in wet lab tests at the molecular level.

An integrated complete-genome sequencing and systems biology approach to predict antimicrobial resistance genes in the virulent bacterial strains of Moraxella catarrhalis.

Moraxella catarrhalis is a symbiotic as well as mucosal infection-causing bacterium unique to humans. Currently, it is considered as one of the leading factors of acute middle ear infection in children. As M. catarrhalis is resistant to multiple drugs, the treatment is unsuccessful; therefore, innovative and forward-thinking approaches are required to combat the problem of antimicrobial resistance (AMR). To better comprehend the numerous processes that lead to antibiotic resistance in M. catarrhalis, we have adopted a computational method in this study. From the NCBI-Genome database, we investigated 12 strains of M. catarrhalis. We explored the interaction network comprising 74 antimicrobial-resistant genes found by analyzing M. catarrhalis bacterial strains. Moreover, to elucidate the molecular mechanism of the AMR system, clustering and the functional enrichment analysis were assessed employing AMR gene interactions networks. According to the findings of our assessment, the majority of the genes in the network were involved in antibiotic inactivation; antibiotic target replacement, alteration and antibiotic efflux pump processes. They exhibit resistance to several antibiotics, such as isoniazid, ethionamide, cycloserine, fosfomycin, triclosan, etc. Additionally, rpoB, atpA, fusA, groEL and rpoL have the highest frequency of relevant interactors in the interaction network and are therefore regarded as the hub nodes. These genes can be exploited to create novel medications by serving as possible therapeutic targets. Finally, we believe that our findings could be useful to advance knowledge of the AMR system present in M. catarrhalis.

An integrated in-silico Pharmaco-BioInformatics approaches to identify synergistic effects of COVID-19 to HIV patients.

BACKGROUND: With high inflammatory states from both COVID-19 and HIV conditions further result in complications. The ongoing confrontation between these two viral infections can be avoided by adopting suitable management measures. PURPOSE: The aim of this study was to figure out the pharmacological mechanism behind apigenin's role in the synergetic effects of COVID-19 to the progression of HIV patients. METHOD: We employed computer-aided methods to uncover similar biological targets and signaling pathways associated with COVID-19 and HIV, along with bioinformatics and network pharmacology techniques to assess the synergetic effects of apigenin on COVID-19 to the progression of HIV, as well as pharmacokinetics analysis to examine apigenin's safety in the human body. RESULT: Stress-responsive, membrane receptor, and induction pathways were mostly involved in gene ontology (GO) pathways, whereas apoptosis and inflammatory pathways were significantly associated in the Kyoto encyclopedia of genes and genomes (KEGG). The top 20 hub genes were detected utilizing the shortest path ranked by degree method and protein-protein interaction (PPI), as well as molecular docking and molecular dynamics simulation were performed, revealing apigenin's strong interaction with hub proteins (MAPK3, RELA, MAPK1, EP300, and AKT1). Moreover, the pharmacokinetic features of apigenin revealed that it is an effective therapeutic agent with minimal adverse effects, for instance, hepatoxicity. CONCLUSION: Synergetic effects of COVID-19 on the progression of HIV may still be a danger to global public health. Consequently, advanced solutions are required to give valid information regarding apigenin as a suitable therapeutic agent for the management of COVID-19 and HIV synergetic effects. However, the findings have yet to be confirmed in patients, suggesting more in vitro and in vivo studies.

Bioinformatics and In silico approaches to identify novel biomarkers and key pathways for cancers that are linked to the progression of female infertility: A comprehensive approach for drug discovery.

Despite modern treatment, infertility remains one of the most common gynecologic diseases causing severe health effects worldwide. The clinical and epidemiological data have shown that several cancerous risk factors are strongly linked to Female Infertility (FI) development, but the exact causes remain unknown. Understanding how these risk factors affect FI-affected cell pathways might pave the door for the discovery of critical signaling pathways and hub proteins that may be targeted for therapeutic intervention. To deal with this, we have used a bioinformatics pipeline to build a transcriptome study of FI with four carcinogenic risk factors: Endometrial Cancer (EC), Ovarian Cancer (OC), Cervical Cancer (CC), and Thyroid Cancer (TC). We identified FI sharing 97, 211, 87 and 33 differentially expressed genes (DEGs) with EC, OC, CC, and TC, respectively. We have built gene-disease association networks from the identified genes based on the multilayer network and neighbour-based benchmarking. Identified TNF signalling pathways, ovarian infertility genes, cholesterol metabolic process, and cellular response to cytokine stimulus were significant molecular and GO pathways, both of which improved our understanding the fundamental molecular mechanisms of cancers associated with FI progression. For therapeutic intervention, we have targeted the two most significant hub proteins VEGFA and PIK3R1, out of ten proteins based on Maximal Clique Centrality (MCC) value of cytoscape and literature analysis for molecular docking with 27 phytoestrogenic compounds. Among them, sesamin, galangin and coumestrol showed the highest binding affinity for VEGFA and PIK3R1 proteins together with favourable ADMET properties. We recommended that our identified pathway, hub proteins and phytocompounds may be served as new targets and therapeutic interventions for accurate diagnosis and treatment of multiple diseases.

Differential gene expression profiling reveals potential biomarkers and pharmacological compounds against SARS-CoV-2: Insights from machine learning and bioinformatics approaches.

The COVID-19 pandemic, caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has created an urgent global situation. Therefore, it is necessary to identify the differentially expressed genes (DEGs) in COVID-19 patients to understand disease pathogenesis and the genetic factor(s) responsible for inter-individual variability and disease comorbidities. The pandemic continues to spread worldwide, despite intense efforts to develop multiple vaccines and therapeutic options against COVID-19. However, the precise role of SARS-CoV-2 in the pathophysiology of the nasopharyngeal tract (NT) is still unfathomable. This study utilized machine learning approaches to analyze 22 RNA-seq data from COVID-19 patients (n = 8), recovered individuals (n = 7), and healthy individuals (n = 7) to find disease-related differentially expressed genes (DEGs). We compared dysregulated DEGs to detect critical pathways and gene ontology (GO) connected to COVID-19 comorbidities. We found 1960 and 153 DEG signatures in COVID-19 patients and recovered individuals compared to healthy controls. In COVID-19 patients, the DEG-miRNA, and DEG-transcription factors (TFs) interactions network analysis revealed that E2F1, MAX, EGR1, YY1, and SRF were the highly expressed TFs, whereas hsa-miR-19b, hsa-miR-495, hsa-miR-340, hsa-miR-101, and hsa-miR-19a were the overexpressed miRNAs. Three chemical agents (Valproic Acid, Alfatoxin B1, and Cyclosporine) were abundant in COVID-19 patients and recovered individuals. Mental retardation, mental deficit, intellectual disability, muscle hypotonia, micrognathism, and cleft palate were the significant diseases associated with COVID-19 by sharing DEGs. Finally, the detected DEGs mediated by TFs and miRNA expression indicated that SARS-CoV-2 infection might contribute to various comorbidities. Our results provide the common DEGs between COVID-19 patients and recovered humans, which suggests some crucial insights into the complex interplay between COVID-19 progression and the recovery stage, and offer some suggestions on therapeutic target identification in COVID-19 caused by the SARS-CoV-2.

A system biology approach to determine therapeutic targets by identifying molecular mechanisms and key pathways for type 2 diabetes that are linked to the development of tuberculosis and rheumatoid arthritis.

AIMS: Due to traditional endocrinological techniques, there is currently no shared work available, and no therapeutic choices have been presented in type 2 diabetes (T2D), rheumatoid arthritis (RA), and tuberculosis (TB). The purpose of this research is to summarize the prospective molecular complications and potential therapeutic targets associated with T2D that have been connected to the development of TB and RA. MATERIALS AND METHODS: We collected the transcriptomic data as GSE92724, GSE110999 and GSE 148036 for T2D, RA and TB patients. After collecting from NCBI, then GREIN were employed to process our datasets. STRING and Enrichr were used to construct protein-protein interaction (PPI), gene regulatory network (GRN), protein-drug-chemical, gene ontology and pathway network. Finally, Cytoscape and R studio were employed to visualize our proposed network. KEY FINDINGS: We discovered a number of strong candidate hub proteins in significant pathways, namely RAB25, MAL2, SFN, MYO5B, and HLA-DQB1 out of 75 common genes. We also identified a number of TFs (JUN, TFAP2A, FOXC1, and GATA2); miRNA (mir-1-3p, mir-16-5p, and mir-34a5p); drugs (sulfasalazine, cholic acid, and nilflumic acid) and chemicals (Valproic acid, and Aflatoxin B1) may control DEGs in transcription as well as post- transcriptional expression levels. SIGNIFICANCE: To summarize, our computational techniques discovered unique potential biomarkers that show how T2D, RA, and TB interacted, as well as pathways and gene regulators by which T2D may influence autoimmune inflammation and infectious diseases. In the future, more clinical and pharmacological research is needed to confirm the findings at the transcriptional and translational levels.

Systems Biology and Bioinformatics approach to Identify blood based signatures molecules and drug targets of patient with COVID-19.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection results in the development of a highly contagious respiratory ailment known as new coronavirus disease (COVID-19). Despite the fact that the prevalence of COVID-19 continues to rise, it is still unclear how people become infected with SARS-CoV-2 and how patients with COVID-19 become so unwell. Detecting biomarkers for COVID-19 using peripheral blood mononuclear cells (PBMCs) may aid in drug development and treatment. This research aimed to find blood cell transcripts that represent levels of gene expression associated with COVID-19 progression. Through the development of a bioinformatics pipeline, two RNA-Seq transcriptomic datasets and one microarray dataset were studied and discovered 102 significant differentially expressed genes (DEGs) that were shared by three datasets derived from PBMCs. To identify the roles of these DEGs, we discovered disease-gene association networks and signaling pathways, as well as we performed gene ontology (GO) studies and identified hub protein. Identified significant gene ontology and molecular pathways improved our understanding of the pathophysiology of COVID-19, and our identified blood-based hub proteins TPX2, DLGAP5, NCAPG, CCNB1, KIF11, HJURP, AURKB, BUB1B, TTK, and TOP2A could be used for the development of therapeutic intervention. In COVID-19 subjects, we discovered effective putative connections between pathological processes in the transcripts blood cells, suggesting that blood cells could be used to diagnose and monitor the disease's initiation and progression as well as developing drug therapeutics.

Automated Detection and Characterization of Colon Cancer with Deep Convolutional Neural Networks.

Colon cancer is a momentous reason for illness and death in people. The conclusive diagnosis of colon cancer is made through histological examination. Convolutional neural networks are being used to analyze colon cancer via digital image processing with the introduction of whole-slide imaging. Accurate categorization of colon cancers is necessary for capable analysis. Our objective is to promote a system for detecting and classifying colon adenocarcinomas by applying a deep convolutional neural network (DCNN) model with some preprocessing techniques on digital histopathology images. It is a leading cause of cancer-related death, despite the fact that both traditional and modern methods are capable of comparing images that may encompass cancer regions of various sorts after looking at a significant number of colon cancer images. The fundamental problem for colon histopathologists is differentiating benign from malignant illnesses to having some complicated factors. A cancer diagnosis can be automated through artificial intelligence (AI), enabling us to appraise more patients in less time and at a decreased cost. Modern deep learning (MDL) and digital image processing (DIP) approaches are used to accomplish this. The results indicate that the proposed structure can accurately analyze cancer tissues to a maximum of 99.80%. By implementing this approach, medical practitioners will establish an automated and reliable system for detecting various forms of colon cancer. Moreover, CAD systems will be built in the near future to extract numerous aspects from colonoscopic images for use as a preprocessing module for colon cancer diagnosis.

Biosorption of organic dye Acridine orange from aqueous solution using dry biomass of Bacillus cereus M116.

Acridine orange (AO), a basic carcinogenic fluorochrome dye, is used in the industry for staining. In this study, Gram-positive bacteria, Bacillus cereus M116 (MTCC 5521) dry biomass was tested as an eco-friendly, easily available, and cheap biosorbent for the AO dye removal. We obtained optimum biosorption of AO at a biomass concentration of 0.25 g/L and initial dye concentrations of 50-400 mg/L at neutral to basic pH within the 300 min contact time. Kinetics analysis of the biosorption process was best fitted with the pseudo-second-order reaction type. We also performed the isotherm analysis to predict the nature of the reaction taking place, which was found to follow the Redlich Peterson isotherm model with high determination coefficients. The maximum sorption capacity was 210.46 mg/g of dry biomass. The differential FTIR spectroscopic analysis of pristine and AO-treated Bacillus cereus M116 cells suggested the potential involvement of carbonyl, hydroxyl, and amine groups in the biosorption process. Also, the scanning electron microscopy of the cells after AO removal confirmed a gross surface alteration compared to the untreated cells. Furthermore, Response Surface Model (RSM) analysis with the three-way ANOVA test confirms statistically significant interactions between the dye concentration, pH, and temperature with the biosorption capacity (p < 0.001). Hence, the dry biomass of Bacillus cereus M116 was found to be an effective bio-remedial for the AO removal.

Seizure in Children Under Five Presenting With Pneumonia in a Critical Care Ward in Bangladesh: Prevalence, Associated Factors, and Outcome.

BACKGROUND: Pneumonia is the leading infectious cause of deaths in children under 5 for the last few decades. Development of seizure in those children is common and associated with increased risk of deaths. We therefore investigated the prevalence, associated factors and outcome of seizure in children hospitalized with pneumonia. METHODS: We conducted a retrospective chart analysis in the intensive care unit of the Dhaka Hospital of icddr,b. Children under 5 with World Health Organization (WHO) classified clinical (excluding seizure as 1 of the clinical diagnostics) and radiologic pneumonia, admitted to the intensive care unit at Dhaka Hospital of icddr,b between August 2013 and December 2017 were analyzed. We initially identified the children with pneumonia who had seizure. For comparison, we have taken 2 folds randomly selected controls from rest of the children with pneumonia having no seizure. Prevalence and outcome of children with pneumonia and seizure were measured. Factors associated with seizure in children with pneumonia compared with those without seizure were also identified. Seizure was characterized by sudden, violent, involuntary, and abnormal repetitive movements with or without loss or impairment of consciousness confirmed by attending physician. RESULTS: Among a total of 4101 children with pneumonia, 514 (12.5%) had seizure. Compared with children with pneumonia alone children having pneumonia and seizure more often developed respiratory failure (18% vs. 3%, P < 0.001) and died (13% vs. 3%, P < 0.001) during hospitalization. In logistic regression analysis hypoxemia (95% CI: 1.59-3.17, P < 0.001), severe pneumonia (95% CI: 2.13-6.52, P < 0.001), severe sepsis (95% CI: 1.30-2.88, P = 0.001), and hypernatremia (95% CI: 5.31-10.93, P < 0.001) were found to be independent risk factors for seizure. On the contrary, children with pneumonia having seizure were less likely to have severe acute malnutrition (95% CI: 0.26-0.50, P < 0.001). CONCLUSIONS: Early identification of risk factors for seizure in children with pneumonia may be helpful for clinicians to promptly treat them and therefore may have potential to reduce deaths in those children especially in resource limited settings.

Band-edge mediated frequency down-conversion in a gas-filled anti-resonant hollow-core fiber.

We demonstrate frequency down-conversions of femtosecond pulses through dispersive wave generation and degenerate four-wave mixing in a gas-filled anti-resonant hollow-core fiber. These are achieved by exploiting the rapid variation of the dispersion in the fiber's transmission band edge. In this approach, the wavelength of the down-shifted radiation is governed solely by the thickness of the dielectric wall at the core-cladding interface, while other system parameters are accountable only for inducing sufficient nonlinear phase shifts. With the right choice of cladding wall thickness, the concept can be applied directly for generating high-power mid-infrared femtosecond pulses.

Determinants of stunting during the first 1,000 days of life in Bangladesh: A review.

Stunting is a major problem in Bangladesh, with a prevalence of 31% in 2017. The prevalence of stunting in children aged under two has reduced by only 6% since 2004. After children reach 2 years of age, the consequences of stunting become almost irreversible. This paper seeks to examine and analyze the determinants associated with stunting during the first 1,000 days of life in Bangladesh to assist in developing evidence-based interventions in Bangladesh. A literature review was conducted comprehensively on all relevant peer-reviewed and gray literature of studies conducted in Bangladesh. The existing literature was searched and examined using the World Health Organization (WHO) conceptual framework for stunting. Evidence indicates that low maternal weight, lack of maternal education, severe food insecurity, lack of access to suitable nutrition, nonexclusive breastfeeding, pathogen-specific diarrhea, and low weight and height at birth are associated with early childhood stunting in Bangladesh. The relation of the quality of drinking water with stunting is not clear in Bangladesh. Literature about the association between stunting and determinants such as the political economy, education systems, and agriculture and food systems is not found. This synthesis shows that the factors of stunting are multifaceted. As such, a multi-sectoral approach is essential in Bangladesh, employing evidence-based interventions to address the determinants that contribute to the risk of stunting to achieve the global nutrition target by 2025.

A Record Review on the Health Status of Rohingya Refugees in Bangladesh.

The Rohingya refugee crisis is neither new nor a sudden problem for Bangladesh. However, the recent violence in August 2017 instigated the migration of 6,93,000 additional Rohingyas into Bangladesh and as of June 2018, around one million Rohingya refugees were residing in Bangladesh. Against this backdrop, it is important to know their current health status because, without this information, equal and equitable health service provision is not possible. So, we conducted this review to understand the current health status of the Rohingya refugees in Bangladesh. For this purpose, a systematic literature search was conducted in July 2018 using transparent selection criteria and the keywords "Rohingya", "Health", Bangladesh". After screening the title and abstract and removing duplication, 12 articles and 21 organizational reports were found eligible for final review. Major health problems prevailing among Rohingya refugees are unexplained fever, acute respiratory infection, and diarrhea. Non-communicable diseases like hypertension, diabetes, and their risk factors are also highly prevalent among these people. More than half of the Rohingya refugees are women and many of them experience sexual abuse or exploitation. More than 50,000 Rohingya refugee women were pregnant, however, a significant portion of pregnant women did not have access to quality antenatal care. Mental health problems like post-traumatic stress disorder (PTSD), depression, and suicidal thoughts were also commonly prevailing in the Rohingya community.

Effect of the second ring of antiresonant tubes in negative-curvature fibers.

We present a numerical investigation on the effect of introducing the second ring of antiresonant tubes on the guiding properties of the negative-curvature fiber. We determine the range of structural parameters for achieving the optimum light guidance in the double-ring geometry. Our study shows that the double-ring negative-curvature fiber can improve the confinement loss by up to four orders of magnitude with considerably better bending and single-mode performance when compared to its single-ring counterpart.

Predictors of Self-Reported Health Status of Ready-made Garment Workers in Bangladesh in Post Global Economic Recession Period.

Introduction There has been disagreement within academia in Bangladesh on whether the global economic recession of 2008-2009 came out as a bane or a boon to their economy and for their people, particularly workers in the ready-made garments (RMG) sector; therefore, we sought to conduct a study among currently employed and recently unemployed RMG workers to examine the influence of recession on their self-reported health status. Methods This cross-sectional study was conducted among 200 workers across 20 factories and 108 recently unemployed workers from different locations of Dhaka. Workers were selected based on a systematic sampling method from 20 randomly selected factories. Unemployed respondents were selected via snowball sampling. A questionnaire was prepared to cover different socio-demographic variables, which were then explored against an outcome variable of how the respondents rate their current health status (2009) compared with their past health status during the economic recession period (2008). A simple logistic regression was conducted for each of the independent variables with the outcome variable. Finally, all independent variables were loaded against the outcome variable, and multiple logistic regression was run. Results The only statistically significant predictor of self-reported health status was age, which indicated a 4% decrease (p = 0.05; 95% confidence interval (CI), 0.9203417 to 1.000015) in improved or better health with each year increase in age, holding other variables constant. Respondent health status was unchanged or even improved after the period of recession. The employed group had 1542.061 Taka (approximately $20) more average monthly family income than the unemployed group (two-sample t-test p-value 0.007), their health status was not affected (odds ratio (OR) 0.998; p-value 0.907). Conclusion The absence of an association between self-reported health status and economic recession is not uncommon, and explanations have been proposed for this phenomenon.

Iceberg of workplace violence in health sector of Bangladesh.

OBJECTIVES: 'Negligence of Physicians' and 'Wrong Treatment' have become commonly-used phrases in print and electronic media of Bangladesh, while violence against healthcare workers has always been under-reported. Unfortunately, there is little evidence regarding physical violence against healthcare workers, while there is no data on the magnitude of psychological violence. The objective of this study was to quantify and explore the magnitude of workplace violence in health sector of Bangladesh to guide future research and adopt preventive policies. RESULTS: The Majority (96%, n = 54) of the violence cases were physical in nature and 91% violence (n = 51) took place in public healthcare settings. More than one-third (39%) of the violence cases occurred at primary healthcare level and one-third (39%) at tertiary healthcare level. It was mostly (61%) the entry-level physicians who were affected by violence. The report reveals the tip of the iceberg of workplace violence in health sector of Bangladesh. Further studies should be undertaken to assess the prevalence, magnitude, and associated factors for workplace violence against healthcare workers.

Positive and negative curvatures nested in an antiresonant hollow-core fiber.

We propose a negative curvature hollow-core fiber that has a nested elliptical element in the antiresonant tubes. The additional elliptical element effectively adds two curvatures, namely, a positive and a negative curvature. Our numerical study shows that it enhances the confinement of the light in the core. Moreover, the nested elements provided an extra degree of freedom that can be exploited to suppress higher-order modes through the change of the ellipticity. The resulting low confinement loss and single-mode guidance properties of the proposed fiber make it a suitable candidate for applications in ultrashort pulse delivery and gas-based nonlinear systems.

Mid-infrared supercontinuum generation in supercritical xenon-filled hollow-core negative curvature fibers.

We present an investigation on the generation of supercontinuum in the mid-infrared (mid-IR) spectral region. Namely, we study a silica-based anti-resonant hollow-core fiber which has good guidance properties in the mid-IR filled with supercritical xenon providing the necessary high nonlinearity. Our numerical study shows that by launching a 200 nJ pump of 100 fs centered at 3.70 µm, a supercontinuum that spans from 1.85 to 5.20 µm can be generated. Such sources are potentially useful for applications, such as the remote sensing of various molecules, medical imaging diagnosis, and surgery.