Screening for microbial load and antibiotic resistance pattern in Escherichia coli isolated from paper currency circulating in Kushtia, Bangladesh

Background: Paper currency is used for every type of commerce and plays an important role in the life of human beings. They are exchanged and come into contact with different environments and many different individuals during their circulation. Therefore, they can become contaminated with microorganisms and transfer bacteria across environments. The present study was aimed for quantitative assessment of microorganisms in circulated paper currency from Kushtia, Bangladesh and antibiotic resistant profiles of isolated Escherichia coli.Methods: A total of 10 paper currency samples currently in circulation involving three denominations (5, 10 and 500) were randomly collected from individuals involved in various occupations including street beggar, local hotel, bus conductor, poultry seller, vegetable seller, fish seller, commercial bank, ATM booth, tea seller, grocery store in Kushtia city, Bangladesh. Selective culture and biochemical tests were performed for the isolation and identification of microbial pathogens. Antibiotic resistance profiles were evaluated for isolated Escherichia coli using Kirby-Bauer method according to CLSI guidelines.Results: Aerobic mesophilic bacteria, Enterobacteriaceae and Pseudomonas spp. were the highest in paper currency from local hotel and ATM booth. Enterobacteriaceae (including coliforms) were predominantly present in paper currencies collected from local hotel, grocery, fish seller and beggar while Pseudomonas spp. were found in currency notes obtained from ATM booth, poultry farm, vegetable seller and local hotel. Antibiotic resistant profiles of E. coli isolated from local hotel currency showed that 50% of E. coli isolates were multidrug resistant. The highest resistant profile was observed against penicillin (95%) followed by polypeptide (75%), cephalosporin (50%), quinolone (30%) and sulfonamide (5%) groups of antibiotics.Conclusions: Multiple antibiotic resistant pathogenic bacteria are prevalent in paper currency regardless of their sources. Paper currency could contribute in transmission of infectious disease as well as in antibiotic resistance, therefore, should be handled carefully

3D harmonic loss: towards task-consistent and time-friendly 3D object detection on edge for V2X orchestration.

The use of edge computing for 3D perception has garnered interest in intelligent transportation systems (ITS) due to its potential to enhance Vehicle-to-Everything (V2X) orchestration through real-time traffic monitoring. The ability to accurately measure depth information in the environment using LiDAR has led to a growing emphasis on 3D detection based on this technology, which has significantly advanced the field of 3D perception. However, the computationally-intensive nature of these operations has made it challenging to meet the real-time deployment requirements using existing methods. The object detection task in the pointcloud domain is hindered by a substantial inconsistency problem caused by its high sparsity, which remains unaddressed. This paper conducts an in-depth analysis of the issue, which has been brought to light by recent research on detecting inconsistency problems in image specialization. To address this problem, we propose a solution in the form of a 3D harmonic loss function, which aims to alleviate the inconsistent predictions based on pointcloud data. In addition, we showcase the viability of optimizing 3D harmonic loss mathematically. Our simulations employ the KITTI dataset and DAIR-V2X-I dataset, and our proposed approach significantly surpasses the performance of benchmark models. Additionally, we validate the efficiency of our proposed model through its deployment on an edge device (Jetson Xavier TX) in a simulated environment

Pathogenetic profiling of COVID-19 and SARS-like viruses.

The novel coronavirus (2019-nCoV) has recently emerged, causing COVID-19 outbreaks and significant societal/global disruption. Importantly, COVID-19 infection resembles SARS-like complications. However, the lack of knowledge about the underlying genetic mechanisms of COVID-19 warrants the development of prospective control measures. In this study, we employed whole-genome alignment and digital DNA-DNA hybridization analyses to assess genomic linkage between 2019-nCoV and other coronaviruses. To understand the pathogenetic behavior of 2019-nCoV, we compared gene expression datasets of viral infections closest to 2019-nCoV with four COVID-19 clinical presentations followed by functional enrichment of shared dysregulated genes. Potential chemical antagonists were also identified using protein-chemical interaction analysis. Based on phylogram analysis, the 2019-nCoV was found genetically closest to SARS-CoVs. In addition, we identified 562 upregulated and 738 downregulated genes (adj. P ≤ 0.05) with SARS-CoV infection. Among the dysregulated genes, SARS-CoV shared ≤19 upregulated and ≤22 downregulated genes with each of different COVID-19 complications. Notably, upregulation of BCL6 and PFKFB3 genes was common to SARS-CoV, pneumonia and severe acute respiratory syndrome, while they shared CRIP2, NSG1 and TNFRSF21 genes in downregulation. Besides, 14 genes were common to different SARS-CoV comorbidities that might influence COVID-19 disease. We also observed similarities in pathways that can lead to COVID-19 and SARS-CoV diseases. Finally, protein-chemical interactions suggest cyclosporine, resveratrol and quercetin as promising drug candidates against COVID-19 as well as other SARS-like viral infections. The pathogenetic analyses, along with identified biomarkers, signaling pathways and chemical antagonists, could prove useful for novel drug development in the fight against the current global 2019-nCoV pandemic

A Non-Linear Biostatistical Graphical Modeling of Preventive Actions and Healthcare Factors in Controlling COVID-19 Pandemic

Background: With the insurgence of the COVID-19 pandemic, many people died in the past several months, and the situation is ongoing with increasing health, social, and economic panic and vulnerability. As most of the countries relying on different preventive actions to control the outcomes of COVID-19, it is necessary to boost the knowledge about the effectiveness of such actions so that the policymakers take their country-based appropriate actions. This study generates evidence of taking the most impactful actions to combat COVID-19. Objective: In order to generate community-based scientific evidence, this study analyzed the outcome of COVID-19 in response to different control measures, healthcare facilities, life expectancy, and prevalent diseases. Methods: It used more than a hundred countries’ data collected from different databases. We performed a comparative graphical analysis with non-linear correlation estimation using R. Results: The reduction of COVID-19 cases is strongly correlated with the earliness of preventive initiation. The apathy of taking nationwide immediate precaution measures has been identified as one of the critical reasons to make the circumstances worse. There is significant non-linear relationship between COVID-19 case fatality and number of physicians (NCC = 0.22; p-value ≤ 0.001), nurses and midwives (NCC = 0.17; p-value ≤ 0.001), hospital beds (NCC = 0.20; p-value ≤ 0.001), life expectancy of both sexes (NCC = 0.22; p-value ≤ 0.001), life expectancy of female (NCC = 0.27; p-value ≤ 0.001), and life expectancy of male (NCC = 0.19; p-value ≤ 0.001). COVID-19 deaths were found to be reduced with increased medical personnel and hospital beds. Interestingly, no association between the comorbidities and severity of COVID-19 was found excluding asthma, cancer, Alzheimer’s, and smoking. Conclusions: Enhancing healthcare facilities and early imposing the control measures could be valuable to prevent the COVID-19 pandemic. No association between COVID-19 and other comorbidities warranted further investigation at the pathobiological level

Structural basis and designing of peptide vaccine using PE-PGRS family protein of Mycobacterium ulcerans : an integrated vaccinomics approach

Buruli ulcer is an emerging tissue-necrosis infectious disease, caused by the pathogen Mycobacterium ulcerans, leading to permanent deformity if untreated. Despite this debilitating condition, no specific disease-modifying therapeutics or vaccination is available to date. Therefore, we aimed to design an effective multi-epitope vaccine against M. ulcerans using vaccinomics approach. Briefly, the highest antigenic PE-PGRS protein was selected from which the promiscuous T- and B-cell epitopes were predicted. After rigorous assessment, 15 promising T- and B-cell epitopes were selected. The identified T-cell epitopes showed marked interactions towards their HLA-binding alleles and provided 99.8 % world population coverage. Consequently, a vaccine chimera was designed by connecting these epitopes with suitable linkers and LprG adjuvant. The vaccine construct was highly antigenic, immunogenic and non-allergenic; hence, subjected to homology modelling. The molecular docking and dynamics simulation revealed a strong and stable interaction between vaccine and toll-like receptor 2. The binding energy and dissociation constant were -15.3 kcal/mol and 5.9 × 10−12 M, respectively. The computer-simulated immune responses showed abundance of immunoglobulins, increased interferon-γ production, and macrophages activation which are crucial for immune response against M. ulcerans. Furthermore, disulfide bridging and in silico cloning were also performed. These results suggest that the vaccine, if validated experimentally, will be a promising candidate against M. ulcerans and prevent Buruli ulcer disease

Energy-optimized pharmacophore coupled virtual screening in the discovery of quorum sensing inhibitors of LasR protein of Pseudomonas aeruginosa

Pseudomonas aeruginosa is an emerging opportunistic pathogen responsible for cystic fibrosis and nosocomial infections. In addition, empirical treatments are become inefficient due to their multiple-antibiotic resistance and extensive colonizing ability. Quorum sensing (QS) plays a vital role in the regulation of virulence factors in P. aeruginosa. Therefore, attenuation of virulence by QS inhibition could be an alternative and effective approach to control the infections. In this study, we sought to discover new QS inhibitors (QSIs) against LasR receptor in P. aeruginosa using chemoinformatics. Initially, a structure-based high-throughput virtual screening was performed using the LasR active site that identified 61404 relevant molecules. The e-pharmacophore (ADAHH) screening of these molecules rendered 72 QSI candidates. In standard-precision docking, only 7 compounds were found as potential QSIs based on their higher binding affinity to LasR receptor (−7.53 to −10.32 kcal/mol compared to −7.43 kcal/mol of native ligand). The ADMET properties of these compounds were suitable to be QSIs. Later, extra-precision docking and binding energy calculation suggested ZINC19765885 and ZINC72387263 as the most promising QSIs. The dynamic simulation of the docked complexes showed stable binding affinity and molecular interactions. The current study suggested that these two compounds could be used in P. aeruginosa QS inhibition to combat bacterial infections. Communicated by Ramaswamy H. Sarma

In vitro study of biocontrol potential of rhizospheric Pseudomonas aeruginosa against Fusarium oxysporum f. sp. cucumerinum

Abstract Fusarium wilt is an economically important disease of cucumber caused by the fungus Fusarium oxysporum f. sp. cucumerinum (Foc). It causes severe losses in the yield and quality of cucumber and is extremely difficult to control conventionally using chemical fungicides. Biological control offers an eco-friendly alternative to chemical pesticide for sustainable plant disease management. In this context, biocontrol activity of rhizosphere soil bacteria was investigated against Foc in vitro. Thirty-five rhizobacterial isolates were screened for antagonistic activity in dual culture, and isolate BA5 showed the highest antagonistic activity (58.33% mycelial growth inhibition) against Foc. Maximum fungal biomass reduction (90.20%) was found in King’s B broth in shake flask culture. Cell-free culture filtrate and ethyl acetate crude extract inhibited mycelial growth of Foc by 56.66 and 25.0%, respectively. Further, the selected isolate produced siderophores, volatile compound(s), hydrocyanic acid, and protease. Siderophores and volatile compound(s) were involved in the isolate-induced antagonism. In addition, the isolate exhibited several plant growth-promoting traits, including phosphate and zinc solubilization, ammonia production, organic acid production, and in vitro biofilm formation. Based on the morphological, physiological, biochemical characteristics, and phylogeny analysis, the isolate BA5 was identified as Pseudomonas aeruginosa, and the 16S rDNA sequence was submitted in the NCBI GenBank under the strain name RKA5. Because of the novel antifungal and plant growth promotion potentials, the strain can be used as a promising biocontrol agent against the fungal pathogen Foc

A molecular modelling approach for identifying antiviral selenium-containing heterocyclic compounds that inhibit the main protease of SARS-CoV-2: an in silico investigation

Coronavirus disease 2019 (COVID-19), an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been declared a global pandemic by the World Health Organization, and the situation worsens daily, associated with acute increases in case fatality rates. The main protease (Mpro) enzyme produced by SARS-CoV-2 was recently demonstrated to be responsible for not only viral reproduction but also impeding host immune responses. The element selenium (Se) plays a vital role in immune functions, both directly and indirectly. Thus, we hypothesised that Se-containing heterocyclic compounds might curb the activity of SARS-CoV-2 Mpro. We performed a molecular docking analysis and found that several of the selected selenocompounds showed potential binding affinities for SARS-CoV-2 Mpro, especially ethaselen (49), which exhibited a docking score of −6.7 kcal/mol compared with the −6.5 kcal/mol score for GC376 (positive control). Drug-likeness calculations suggested that these compounds are biologically active and possess the characteristics of ideal drug candidates. Based on the binding affinity and drug-likeness results, we selected the 16 most effective selenocompounds as potential anti-COVID-19 drug candidates. We also validated the structural integrity and stability of the drug candidate through molecular dynamics simulation. Using further in vitro and in vivo experiments, we believe that the targeted compound identified in this study (ethaselen) could pave the way for the development of prospective drugs to combat SARS-CoV-2 infections and trigger specific host immune responses

CRISPR-Cas9 : a promising genome editing therapeutic tool for Alzheimer’s disease : a narrative review

Alzheimer’s disease (AD) is a chronic and irreversible neurodegenerative disorder characterized by cognitive deficiency and development of amyloid-β (Aβ) plaques and neurofibrillary tangles, comprising hyperphosphorylated tau. The number of patients with AD is alarmingly increasing worldwide; currently, at least 50 million people are thought to be living with AD. The mutations or alterations in amyloid-β precursor protein (APP), presenilin-1 (PSEN1), or presenilin-2 (PSEN2) genes are known to be associated with the pathophysiology of AD. Effective medication for AD is still elusive and many gene-targeted clinical trials have failed to meet the expected efficiency standards. The genome editing tool clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 has been emerging as a powerful technology to correct anomalous genetic functions and is now widely applied to the study of AD. This simple yet powerful tool for editing genes showed the huge potential to correct the unwanted mutations in AD-associated genes such as APP, PSEN1, and PSEN2. So, it has opened a new door for the development of empirical AD models, diagnostic approaches, and therapeutic lines in studying the complexity of the nervous system ranging from different cell types (in vitro) to animals (in vivo). This review was undertaken to study the related mechanisms and likely applications of CRISPR-Cas9 as an effective therapeutic tool in treating AD

Identifying molecular insight of synergistic complexities for SARS-CoV-2 infection with pre-existing type 2 diabetes

The ongoing COVID-19 outbreak, caused by SARS-CoV-2, has posed a massive threat to global public health, especially to people with underlying health conditions. Type 2 diabetes (T2D) is lethal comorbidity of COVID-19. However, its pathogenetic link remains unclear. This research aims to determine the genetic factors and processes contributing to the synergistic severity of SARS-CoV-2 infection among T2D patients through bioinformatics approaches. We analyzed two sets of transcriptomic data of SARS-CoV-2 infection obtained from lung epithelium cells and PBMCs, and two sets of T2D data from pancreatic islet cells and PBMCs to identify the associated differentially expressed genes (DEGs) followed by their functional enrichment analyses in terms of protein-protein interaction (PPI) to detect hub-proteins and associated comorbidities, transcription factors (TFs), microRNAs (miRNAs) as well as the potential drug candidates. In PPI analysis, four potential hub-proteins (i.e., BIRC3, C3, MME, and IL1B) were identified among 25 DEGs shared between the disease pair. Enrichment analyses using the mutually overlapped DEGs revealed the most prevalent GO and cell signalling pathways, including TNF signalling, cytokine-cytokine receptor interaction, and IL-17 signalling, which are related to cytokine activities. Furthermore, as significant TFs, we identified IRF1, KLF11, FOSL1, and CREB3L1 while miRNAs including miR-1-3p, 34a-5p, 16-5p, 155-5p, 20a-5p, and let-7b-5p were found to be noteworthy. The findings illustrated the significant association between COVID-19 and T2D at the molecular level. These genetic determinants can further be explored for their specific roles in disease progression and therapeutic intervention, while significant pathways can also be studied as molecular checkpoints. Finally, the identified drug candidates may be evaluated for their potency to minimize the severity of COVID-19 patients with pre-existing T2D