Association studies between COVID-19 and SSc-ILD

Severe COVID-19 patients may develop pulmonary fibrosis, similar to SSc-ILD disease, suggesting a potential link between the two diseases. However, there are limited treatment options for SSc-ILD-type diseases. Therefore, investigating pathological markers of the two diseases can provide valuable insights for treating related conditions. RNA sequencing technology offers high throughput and precision. However, the bimodal nature of RNA-Seq data cannot be accurately captured by commonly used algorithms such as DESeq2. To address this issue, the Beta-Poisson model has been developed to identify differentially expressed genes. Unlike the classical DESeq2 algorithm, the Beta-Poisson model introduces a Beta distribution to construct a new hybrid distribution in place of the Gamma distribution of the Gamma-Poisson distribution, effectively characterizing the bimodal features of RNA-Seq data. The transcriptomes of SARS-CoV infection and SSc-ILD disease in the lung epithelial cell dataset were analyzed to identify common differentially expressed genes of SARS-CoV and SSc-ILD disease. Gene function and signaling pathway enrichment analysis and protein-protein interaction (PPI) network were used to identify common pathways and drug targets for SSc-ILD with COVID-19 infection. The results show that there are 50 differentially expressed genes in common between COVID-19 and SSC-ILD. The functions of these genes are mainly enriched in immune system response, interferon signaling pathway and other related signaling pathways, and enriched in biological processes such as cell defense response to virus and interferon regulation. Based on the detection of hub genes based on PPIs network, it is predicted that STAT1, ISG15, IRF7, MX1, EIF2AK2, DDX58, OAS1, OAS2, IFIT1 and IFIT3 are the key genes involved in the pathological phenotype of the two diseases. Based on the key genes, the interaction of transcription factor (TF) and miRNA with common differentially expressed genes is also identified. The possible pathological markers of the two diseases and related molecular regulatory mechanisms of disease treatment are revealed to provide theoretical basis for the treatment of the two diseases. © 2023 Editorial Office of Journal of Shenzhen University. All rights reserved.

Updates of precision medicine in type 2 diabetes

Diabetes mellitus is prevalent worldwide and affects 1 in 10 adults. Despite the successful development of glucose-lowering drugs, such as glucagon-like peptide-1 (GLP-1) receptor agonists and sodium-glucose cotransporter-2 inhibitors recently, the proportion of patients achieving satisfactory glucose control has not risen as expected. The heterogeneity of diabetes determines that a one-size-fits-all strategy is not suitable for people with diabetes. Diabetes is undoubtedly more heterogeneous than the conventional subclassification, such as type 1, type 2, monogenic and gestational diabetes. The recent progress in genetics and epigenetics of diabetes has gradually unveiled the mechanisms underlying the heterogeneity of diabetes, and cluster analysis has shown promising results in the substratification of type 2 diabetes, which accounts for 95% of diabetic patients. More recently, the rapid development of sophisticated glucose monitoring and artificial intelligence technologies further enabled comprehensive consideration of the complex individual genetic and clinical information and might ultimately realize a precision diagnosis and treatment in diabetics.

Establishment and application of triple PCR method for CPV, CCoV and CRV

Canine parvovirus (CPV), canine coronavirus (CCoV) and canine rotavirus (CRV) are the three main causative viruses of diarrhea in dogs with similar clinical symptoms;thereby it is necessary to establish a high effective molecular detection method for differentiating the above pathogens. By optimizing the primer concentration and annealing temperature, a triple PCR method was established for simultaneous detection of CPV, CCoV and CRV, and then the specificity, sensitivity and repeatability of the method were tested. The results showed that the target fragments of CPV VP2 gene (253 bp), CCoV ORF-1b gene (379 bp) and CRV VP6 gene (852 bp) could be accurately amplified by the triple PCR method with high specificity, the detection limits of CPV, CCOV and CRV were 6.44x10-1 pg/L, 8.72x10-1 pg/L and 8.35x10-1 pg/L respectively with high sensitivity, and the method had good stability. Using this triple PCR method, 135 canine diarrhea fecal samples collected in Chengdu region from 2019 to 2020 were detected, and compared with those of single PCR method. The detection rates of CPV, CCoV and CRV were 16.30%, 20.74% and 4.44%, respectively, and the total infection rate was 51.11% (65/135) with 20.00% (13/65) co-infection rate. The detection results were consistent with three single PCR methods. In conclusion, CPV/CCoV/CRV triple PCR method successfully established in this paper can be applied as an effective molecular method to detection of related pathogens and to the epidemiological investigation.

Multi-objective Evolutionary Discretization of Gene Expression Profiles: Application to COVID-19 Severity Prediction

Machine learning models can use information from gene expressions in patients to efficiently predict the severity of symptoms for several diseases. Medical experts, however, still need to understand the reasoning behind the predictions before trusting them. In their day-to-day practice, physicians prefer using gene expression profiles, consisting of a discretized subset of all data from gene expressions: in these profiles, genes are typically reported as either over-expressed or under-expressed, using discretization thresholds computed on data from a healthy control group. A discretized profile allows medical experts to quickly categorize patients at a glance. Building on previous works related to the automatic discretization of patient profiles, we present a novel approach that frames the problem as a multi-objective optimization task: on the one hand, after discretization, the medical expert would prefer to have as few different profiles as possible, to be able to classify patients in an intuitive way;on the other hand, the loss of information has to be minimized. Loss of information can be estimated using the performance of a classifier trained on the discretized gene expression levels. We apply one common state-of-the-art evolutionary multi-objective algorithm, NSGA-II, to the discretization of a dataset of COVID-19 patients that developed either mild or severe symptoms. The results show not only that the solutions found by the approach dominate traditional discretization based on statistical analysis and are more generally valid than those obtained through single-objective optimization, but that the candidate Pareto-optimal solutions preserve the sense-making that practitioners find necessary to trust the results. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

PROTEIN SIGNALING MOLECULES AFFECTING THE DEVELOPMENT OF INNATE IMMUNITY MECHANISMS

The principle protein molecules (interferon gene stimulator, adapter proteins, B-cell lymphoma 2 proteins, zinc-finger antiviral protein, and others), mechanisms of apoptosis, necroptosis, perforation of plasma membranes with kinase-like proteins of a mixed line, and ribonucleic acid neutralization, which ensure the development of innate immunity, are described. The main defense mechanisms that viruses have developed at the various stages of evolution are considered. The features of the development of the mechanisms of apoptosis and autophagy in a new coronavirus infection, which are associated with increased secretion of pro-inflammatory cytokines and chemokines, leading to severe damage to host cells, are given. It has been found that serum levels of several proteins formed during autophagy caused by SARS-CoV-2 can be used to predict disease severity. These include a protein associated with microtubules 1A/1B, a protein of sequestoma 1, and a protein of the cellular system of autophagy ― beclin-1. The multifaceted role of interferons in the inhibition of viral infection and the features of the violation of the activating functions of interferons in coronavirus infection are described. The article can be used under the CC BY-NC-ND 4.0 license © Authors, 2022.

Silent superbug killers in a river near you how factory farms contaminate public water courses on three continents

Water downstream from factory farms harbours an invisible threat to people's health which could eclipse the COVID-19 crisis. The threat? Antibiotic Resistance Genes (ARGs) which are driving antimicrobial resistance the world's superbug crisis - projected to kill up to 10 million people annually by 2050. This publication reports the presence of ARGs in animal waste discharged from industrial farms into public waterways or onto soil (or crops) in four countries. Gauge community impact and sentiment regarding the issue was also highlighted. The water and sediment from public water courses connected to effluent discharges from 6-10 pig farms were tested in each of four countries (Canada, Spain, Thailand and the USA).

Effect of Drebrin protein on the proliferation of PEDV in Vero cells

Previous studies have revealed that developmental regulated brain protein (Drebrin) is involved in cell- to-cell communication, nerve transmission, tumor metastasis, spermatogenesis and other life activities, but there are few studies on viruses. The aim of the current research was therefore, to study the function of Drebrin and its effect on the proliferation of porcine epidemic diarrhea virus (PEDV). The Drebrin gene was cloned according to the Drebrin gene sequence (XM_008015438.2) of Chlorocebus sabaeus registered by GenBank, and the phylogenetic tree was constructed to analyze its homology. The results showed that the CDS region of Vero cells Drebrin gene was 2088 bp long, encoding 695 amino acids, and was relatively conserved and had high homology with all species. To investigate the effect of Drebrin on the proliferation of PEDV in Vero cells, the eukaryotic expression vector pcDNA3.1-Drebrin-Flag was constructed. After transfection of Vero cells with different concentrations of pcDNA3.1-Drebrin-Flag, cells were infected with PEDV. Our results showed that overexpression of Drebrin in Vero cells could significantly inhibit the intracellular PEDV mRNA level and N protein expression, reduce the extracellular virus titer and inhibit the proliferation of PEDV. Further study on the interaction between Drebrin and PEDV S proteins by laser confocal technique was also performed. The results showed that Drebrin and S protein were co-located in the cytoplasm, suggesting that the two proteins may interact with each other. This study demonstrated for the first time that Drebrin can inhibit PEDV proliferation in Vero cells, laying a foundation for further research in to Drebrin function and provides a valuable information for anti-PEDV research.

Mucormycosis Metabolic Network Modeling: A Constraint-Based Approach

Mucormycosis is an uncommon illness caused by the fungus Mucorales. India was concerned about mucormycosis and COVID-19 in 2020. To minimize morbidity and occurrence, prevent, and treat mucormycosis, analysis is required. Combining systems biology and bioinformatics-based mucormycosis research, this study simulates the Genome-scale metabolic model (GSSM) of a Rhizopus oryzae strain for the comprehension of the organism's metabolic mechanism. Several key metabolic pathways for a mucormycosis-causing fungus strain were identified in research publications and targeted for inclusion in a model of a metabolic network. Based on the Flux Balance Analysis (FBA) approach, an integrated model of these pathways at the scale of the genome's metabolism was developed and appropriate constraints were applied to the numerous reactions involved in Rhizopus oryzae's metabolism using the COBRA package in MATLAB. Hence, unique evidence of pharmacological targets and biomarkers that may function as diagnostic, early analytic, and therapeutic agents in mucormycosis was discovered. Our study investigates the role of key metabolites in the model by applying constraints and altering fluxes, which provides valuable candidates for drug development. . © 2023 IEEE.

Not a waste: Wastewater surveillance to enhance public health

Domestic wastewater, when collected and evaluated appropriately, can provide valuable health-related information for a community. As a relatively unbiased and non-invasive approach, wastewater surveillance may complement current practices towards mitigating risks and protecting population health. Spurred by the COVID-19 pandemic, wastewater programs are now widely implemented to monitor viral infection trends in sewersheds and inform public health decision-making. This review summarizes recent developments in wastewater-based epidemiology for detecting and monitoring communicable infectious diseases, dissemination of antimicrobial resistance, and illicit drug consumption. Wastewater surveillance, a quickly advancing Frontier in environmental science, is becoming a new tool to enhance public health, improve disease prevention, and respond to future epidemics and pandemics.

Natural Evolution of Porcine Epidemic Diarrhea Viruses Isolated from Maternally Immunized Piglets

Simple SummaryDuring the long-term co-evolution of the virus and the host, even closely related vaccines may emerge with incomplete protective immunity due to the mutations or deletions of amino acids at specific antigenic sites. The mutation of PEDV was accelerated by the recombination of different strains and the mutation of the strains adapting to the environment. These mutations either cause immune escape from conventional vaccines or affect the virulence of the virus. Therefore, researching and developing new vaccines with cross-protection through continuous monitoring, isolation and sequencing are important to determine whether their genetic characteristics are changed and to evaluate the protective efficacy of current vaccines. The porcine epidemic diarrhea virus (PEDV) can cause severe piglet diarrhea or death in some herds. Genetic recombination and mutation facilitate the continuous evolution of the virus (PEDV), posing a great challenge for the prevention and control of porcine epidemic diarrhea (PED). Disease materials of piglets with PEDV vaccination failure in some areas of Shanxi, Henan and Hebei provinces of China were collected and examined to understand the prevalence and evolutionary characteristics of PEDV in these areas. Forty-seven suspicious disease materials from different litters on different farms were tested by multiplex PCR and screened by hematoxylin-eosin staining and immunohistochemistry. PEDV showed a positivity rate of 42.6%, infecting the small and large intestine and mesenteric lymph node tissues. The isolated strains infected Vero, PK-15 and Marc-145 multihost cells and exhibited low viral titers in all three cell types, as indicated by their growth kinetic curves. Possible putative recombination events in the isolates were identified by RDP4.0 software. Sequencing and phylogenetic analysis showed that compared with the classical vaccine strain, PEDV SX6 contains new insertion and mutations in the S region and belongs to genotype GIIa. Meanwhile, ORF3 has the complete amino acid sequence with aa80 mutated wild strains, compared to vaccine strains CV777, AJ1102, AJ1102-R and LW/L. These results will contribute to the development of new PEDV vaccines based on prevalent wild strains for the prevention and control of PED in China.

POLYMORPHISMS OF LEUKOCYTE GENES HUMAN AND CONGENITAL ANTIGEN IMMUNITY ASSOCIATED WITH DIFFERENT THE SEVERITY OF THE COURSE OF THE NEW CORONAVIRUS INFECTIONS

The most significant single nucleotide human leukocyte antigen genes polymorphisms and innate immunity genes associated with varying degrees of acute respiratory infection severity are considered–COVID-19 caused by the SARS-CoV-2 coronavirus. As data accumulated, it became clear that the SARS-CoV-2 virus exhibits significant regional, ethnic, and individual specificity. This is due to the population groups' genetic characteristics. This is necessary to reliably know the human genotype relationship with the COVID-19 course severity (asymptomatic, mild, moderate, severe, and extremely severe up to fatal outcomes) for more successful therapy and vaccination. At the same time, it was also known that the innate immunity system is on the first line of defense against the pathogenic penetration into the body, and the human leukocyte antigen system encodes molecules of the same name on the surface of cells that present various antigens, including viral infection pathogens, and determine the severity of the course of many diseases;therefore, these systems' genes. This approach makes it possible to assess the likelihood of a severe and extremely severe disease course in healthy and infected people, which in turn contributes to the correct therapy strategy, pharmacotherapy, and vaccination, as well as to create new antiviral therapeutic and preventive medicines. The genetically determined immune response heterogeneity to SARS-CoV-2 infection requires further study, since there is no unambiguous opinion about the leading mechanism that determines disease severity. The article can be used under the CC BY-NC-ND 4.0 license © Authors, 2022.

Evaluation of expression and titration of recombinant nucleocapsid protein as an immunogenic candidate against SARS-CoV2

Introduction: Covid-19 epidemic results from an infection caused by SARS-CoV2. Evolution-based analyses on the nucleotide sequences show that SARS-CoV2 is a member of the genus Beta-coronaviruses and its genome consists of a single-stranded RNA, encoding 16 proteins. Among the structural proteins, the nucleocapsid is the most abundant protein in virus structure, highly immunogenic, with sequence conservatory. Due to a large number of mutations in the spike protein, the aim of this study was to investigate bioinformatics, expression of nucleocapsid protein and evaluate its immunogenicity as an immunogenic candidate. Materials and Methods: B and T cell epitopes of nucleocapsid protein were examined in the IEDB database. The PET28a-N plasmid was transferred to E. coli BL21(DE3) expression host, and IPTG induced recombinant protein expression. The protein was purified using Ni-NTA column affinity chromatography, and the Western blotting method was utilized to confirm it. Finally, mice were immunized with three routes of purified protein. Statistical analysis of the control group injection and test results was carried out by t-test from SPSS software. Results: The optimized gene had a Codon adaptation index (CAI) of 0/97 Percentage of codons having high- frequency distribution was improved to 85%. Expression of recombinant protein in E. coli led to the production of BoNT/B-HCC with a molecular weight of 45 kDa. The total yield of purified protein was 43 mg/L. Immunization of mice induced serum antibody response. Statistical analysis showed that the antibody titer ratio was significantly different compared to the control sample and the antibody titer was acceptable up to a dilution of 1.256000. Conclusion: According to the present study results, the protein can be used as an immunogenic candidate for developing vaccines against SARS-CoV2 in future research.

Molecular epidemiology and genetic diversity of canine coronavirus from domestic dogs in Chengdu, China from 2020 to 2021 using a multiplex RT-PCR.

Recent reports on identification of canine coronavirus (CCoV) in humans have emphasized the urgency to strengthen surveillance of animal CoVs. The fact that recombinations between CCoV with feline, porcine CoVs brought about new types of CoVs indicated that more attention should be paid to domestic animals like dogs, cats and pigs, and the CoVs they carried. However, there are about ten kinds of CoVs that infect above animals, and thus representative CoVs with zoonotic potentials were considered in this study. Multiplex RT-PCR against CCoV, Feline coronavirus (FCoV), porcine deltacoronavirus and porcine acute diarrhea syndrome coronavirus was developed to investigate the prevalence of CoVs from domestic dogs in Chengdu, Southwest China. Samples from a total of 117 dogs were collected from a veterinary hospital, and only CCoV (34.2%, 40/117) was detected. Therefore, this study focused on CCoV and its characteristics of S, E, M, N and ORF3abc genes. Compared with CoVs that are capable of infecting humans, CCoV strains showed highest nucleotide identity with the novel canine-feline recombinant detected from humans (CCoV-Hupn-2018). Phylogenetic analysis based on S gene, CCoV strains were not only clustered with CCoV-II strains, but also closely related to FCoV-II strains ZJU1617 and SMU-CD59/2018. As for assembled ORF3abc, E, M, N sequences, CCoV strains had the closest relationship with CCoV-II (B203_GZ_2019, B135_JS_2018 and JS2103). What's more, specific amino acid variations were found, especially in S and N proteins, and some mutations were consistent with FCoV, TGEV strains. Altogether, this study provided a novel insight into the identification, diversification and evolution of CoVs from domestic dogs. It is of top priority to recognize zoonotic potential of CoVs, and continued comprehensive surveillance will help better understand the emergence, spreading, and ecology of animal CoVs.

Next-generation sequencing for surveillance of antimicrobial resistance and pathogenicity in municipal wastewater treatment plants.

The World Health Organization (WHO) ranks antimicrobial resistance (AMR) and various pathogens among the top 10 health threats. It is estimated that by 2050, the number of human deaths due to AMR will reach 10 million annually. On the other hand, several infectious outbreaks such as SARS, H1N1 influenza, Ebola, Zika fever, and COVID-19 have severely affected human populations worldwide in the last 20 years. These recent global diseases have generated the need to monitor outbreaks of pathogens and AMR to establish effective public health strategies. This review presents AMR and pathogenicity associated with wastewater treatment plants (WWTP), focusing on Next Generation Sequencing (NGS) monitoring as a complementary system to clinical surveillance. In this regard, WWTP may be monitored at three main points. First, at the inlet (raw wastewater or influent) to identify a broad spectrum of AMR and pathogens contained in the excretions of residents served by sewer networks, with a specific spatio-temporal location. Second, at the effluent, to ensure the elimination of AMR and pathogens in the treated water, considering the rising demand for safe wastewater reuse. Third, in sewage sludge or biosolids, since their beneficial use or final disposal can represent a significant risk to public health. This review is divided into two sections to address the importance and implications of AMR and pathogen surveillance in wastewater and WWTP, based on NGS. The first section presents the fundamentals of surveillance techniques applied in WWTP (metataxonomics, metagenomics, functional metagenomics, metaviromics, and metatranscriptomics). Their scope and limitations are analyzed to show how microbiological and qPCR techniques complement NGS surveillance, overcoming its limitations. The second section discusses the contribution of 36 NGS research papers on WWTP surveillance, highlighting the current situation and perspectives. In both sections, research challenges and opportunities are presented.

Antibiotic Resistance and Its Impact on Disease Management.

Antibiotic resistance has been a challenge to the medical fraternity and has had a massive impact on disease management. The overuse of antibiotics and careless prescription by doctors have been one of the primary reasons for the development of antibiotic resistance among the masses. This article draws attention to the significant reasons causing antibiotic resistance, such as overuse, antibiotic resistance genes, and extensive use of antibiotics in agriculture. It also brings forward the challenges posed by antibiotic resistance in the management of various diseases like tuberculosis, COVID-19, and vancomycin-resistant enterococci infections. The article includes a case study that depicts the threat posed by antibiotic resistance in tuberculosis treatment. This article also shows the effects of antibiotic resistance on COVID-19 patient care and treatment. It further includes methods that can be implemented on international levels as well as individual ground levels to curb antibiotic resistance. One of the methods has a recent finding in which proteins produced in the body are being modified and used in treatments to reduce the use of antibiotics, which ultimately serves the goal of curbing antibiotic resistance by reducing overuse.

Comprehensive DNA methylation profiling of COVID-19 and hepatocellular carcinoma to identify common pathogenesis and potential therapeutic targets.

BACKGROUND & AIMS: The effects of SARS-CoV-2 infection can be more complex and severe in patients with hepatocellular carcinoma (HCC) as compared to other cancers. This is due to several factors, including pre-existing conditions such as viral hepatitis and cirrhosis, which are commonly associated with HCC. METHODS: We conducted an analysis of epigenomics in SARS-CoV-2 infection and HCC patients, and identified common pathogenic mechanisms using weighted gene co-expression network analysis (WGCNA) and other analyses. Hub genes were identified and analyzed using LASSO regression. Additionally, drug candidates and their binding modes to key macromolecular targets of COVID-19 were identified using molecular docking. RESULTS: The epigenomic analysis of the relationship between SARS-CoV-2 infection and HCC patients revealed that the co-pathogenesis was closely linked to immune response, particularly T cell differentiation, regulation of T cell activation and monocyte differentiation. Further analysis indicated that CD4+ T cells and monocytes play essential roles in the immunoreaction triggered by both conditions. The expression levels of hub genes MYLK2, FAM83D, STC2, CCDC112, EPHX4 and MMP1 were strongly correlated with SARS-CoV-2 infection and the prognosis of HCC patients. In our study, mefloquine and thioridazine were identified as potential therapeutic agents for COVID-19 in combined with HCC. CONCLUSIONS: In this research, we conducted an epigenomics analysis to identify common pathogenetic processes between SARS-CoV-2 infection and HCC patients, providing new insights into the pathogenesis and treatment of HCC patients infected with SARS-CoV-2.

Bioinformatics and system biology approach to identify the influences among COVID-19, ARDS and sepsis.

Background Severe coronavirus disease 2019 (COVID -19) has led to severe pneumonia or acute respiratory distress syndrome (ARDS) worldwide. we have noted that many critically ill patients with COVID-19 present with typical sepsis-related clinical manifestations, including multiple organ dysfunction syndrome, coagulopathy, and septic shock. The molecular mechanisms that underlie COVID-19, ARDS and sepsis are not well understood. The objectives of this study were to analyze potential molecular mechanisms and identify potential drugs for the treatment of COVID-19, ARDS and sepsis using bioinformatics and a systems biology approach. Methods Three RNA-seq datasets (GSE171110, GSE76293 and GSE137342) from Gene Expression Omnibus (GEO) were employed to detect mutual differentially expressed genes (DEGs) for the patients with the COVID-19, ARDS and sepsis for functional enrichment, pathway analysis, and candidate drugs analysis. Results We obtained 110 common DEGs among COVID-19, ARDS and sepsis. ARG1, FCGR1A, MPO, and TLR5 are the most influential hub genes. The infection and immune-related pathways and functions are the main pathways and molecular functions of these three diseases. FOXC1, YY1, GATA2, FOXL, STAT1 and STAT3 are important TFs for COVID-19. mir-335-5p, miR-335-5p and hsa-mir-26a-5p were associated with COVID-19. Finally, the hub genes retrieved from the DSigDB database indicate multiple drug molecules and drug-targets interaction. Conclusion We performed a functional analysis under ontology terms and pathway analysis and found some common associations among COVID-19, ARDS and sepsis. Transcription factors-genes interaction, protein-drug interactions, and DEGs-miRNAs coregulatory network with common DEGs were also identified on the datasets. We believe that the candidate drugs obtained in this study may contribute to the effective treatment of COVID-19.

Multi-faceted CRISPR/Cas technological innovation aspects in the framework of 3P medicine.

Since 2009, the European Association for Predictive, Preventive and Personalised Medicine (EPMA, Brussels) promotes the paradigm change from reactive approach to predictive, preventive, and personalized medicine (PPPM/3PM) to protect individuals in sub-optimal health conditions from the health-to-disease transition, to increase life-quality of the affected patient cohorts improving, therefore, ethical standards and cost-efficacy of healthcare to great benefits of the society at large. The gene-editing technology utilizing CRISPR/Cas gene-editing approach has demonstrated its enormous value as a powerful tool in a broad spectrum of bio/medical research areas. Further, CRISPR/Cas gene-editing system is considered applicable to primary and secondary healthcare, in order to prevent disease spread and to treat clinically manifested disorders, involving diagnostics of SARS-Cov-2 infection and experimental treatment of COVID-19. Although the principle of the proposed gene editing is simple and elegant, there are a lot of technological challenges and ethical considerations to be solved prior to its broadly scaled clinical implementation. This article highlights technological innovation beyond the state of the art, exemplifies current achievements, discusses unsolved technological and ethical problems, and provides clinically relevant outlook in the framework of 3PM.

Discovering common pathogenic processes between COVID-19 and HFRS by integrating RNA-seq differential expression analysis with machine learning.

Zoonotic virus spillover in human hosts including outbreaks of Hantavirus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) imposes a serious impact on the quality of life of patients. Recent studies provide a shred of evidence that patients with Hantavirus-caused hemorrhagic fever with renal syndrome (HFRS) are at risk of contracting SARS-CoV-2. Both RNA viruses shared a higher degree of clinical features similarity including dry cough, high fever, shortness of breath, and certain reported cases with multiple organ failure. However, there is currently no validated treatment option to tackle this global concern. This study is attributed to the identification of common genes and perturbed pathways by combining differential expression analysis with bioinformatics and machine learning approaches. Initially, the transcriptomic data of hantavirus-infected peripheral blood mononuclear cells (PBMCs) and SARS-CoV-2 infected PBMCs were analyzed through differential gene expression analysis for identification of common differentially expressed genes (DEGs). The functional annotation by enrichment analysis of common genes demonstrated immune and inflammatory response biological processes enriched by DEGs. The protein-protein interaction (PPI) network of DEGs was then constructed and six genes named RAD51, ALDH1A1, UBA52, CUL3, GADD45B, and CDKN1A were identified as the commonly dysregulated hub genes among HFRS and COVID-19. Later, the classification performance of these hub genes were evaluated using Random Forest (RF), Poisson Linear Discriminant Analysis (PLDA), Voom-based Nearest Shrunken Centroids (voomNSC), and Support Vector Machine (SVM) classifiers which demonstrated accuracy >70%, suggesting the biomarker potential of the hub genes. To our knowledge, this is the first study that unveiled biological processes and pathways commonly dysregulated in HFRS and COVID-19, which could be in the next future used for the design of personalized treatment to prevent the linked attacks of COVID-19 and HFRS.

Association of microplastics with heavy metals and antibiotic resistance bacteria/genes in natural ecosystems - A perspective through science mapping approach

Micro and nano-plastics (MNPs) have been considered one of the major emerging contaminants that require immediate attention. Their potential impact on the natural ecosystems is yet to be understood, especially their associations with other contaminants like heavy metals and organisms essential for the sustenance of life, i.e., microbes. Microplastics (MPs) also act as sources and carriers of pollutants, similar to macro and mesoplastics, that leach harmful chemicals such as Polybrominated Diphenyl Ethers (PBDEs), Pharmaceutical and Personal Care Products (PPCPs), Endocrine Disruptive Chemicals (EDCs), etc. They also behave like super sponge materials which adsorb microbes such as antibiotic resistance bacteria (ARBs), and coronavirus, making their concentration much higher than the ambient environment. Among these microbes, heavy metal-resistance (MRGs) and antibiotic-resistance genes (ARGs) carry immense significance. The present study provides an in-depth review analysis of the works published related to the association of MPs to heavy metals and ARGs. 1526 articles were investigated after the dataset was subjected to a three-stage screening process. A scientometric analysis revealing details about the most productive and influential journals, co-authorship details, most influential publications, most cited keywords, and most active countries in the research domain was conducted. This provided significant information regarding various aspects of the published works of literature. Subsequently, a qualitative discussion was carried out wherein a detailed discussion with regard to the trends in research on sub-areas in the broad domain was conducted. This resulted in identifying the gaps in the available literature, which paved the way for providing a framework for future research. Through this study, it is expected that the readers will be exposed to a summary of the overall research that has been conducted to date, and the manuscript will act as a guide for future research.