Virus Signatures Research Articles

V- and VL-Scores Uncover Viral Signatures and Origins of Protein Families.

Viruses are key drivers of microbial diversity, nutrient cycling, and co-evolution in ecosystems, yet their study is hindered due to challenges in culturing. Traditional gene-centric methods, which focus on a few hallmark genes like for capsids, miss much of the viral genome, leaving key viral proteins and functions undiscovered. Here, we introduce two powerful annotation-free metrics, V-score and VL-score, designed to quantify the "virus-likeness" of protein families and genomes and create an open-access searchable database, 'V-Score-Search'. By applying V- and VL-scores to public databases (KEGG, Pfam, and eggNOG), we link 38-77% of protein families with viruses, a 9-16x increase over current estimates. These metrics outperform existing approaches, enabling precise detection of viral genomes, prophages, and host-derived auxiliary viral genes (AVGs) from fragmented sequences, and significantly improving genome binning. Remarkably, we identify up to 17x more AVGs, dominated by non-metabolic proteins of unknown function. This innovation unlocks new insights into virus signatures and host interactions, with wide-ranging implications from genomics to biotechnology.

Identified a novel prognostic model of HCC basing on virus signature for guiding immunotherapy

Oncolytic viral immunotherapy is a cancer treatment that uses native or genetically modified viruses that selectively replicate and destroy tumor cells. In this study, we aimed to construct a virus-based prognostic model for risk assessment and prognosis prediction in patients with hepatocellular carcinoma (HCC) and determine the most appropriate virus as a candidate vector for oncolytic virus immunotherapy. Microbiome and RNA sequencing data and clinical information were obtained from The Cancer Genome Atlas, and viruses with prognostic value were identified (Deltabaculovirus, Sicinivirus, and Cytomegalovirus) to construct the prognostic model. Correlation analyses were performed to evaluate the predictive function of the viral signature. Bioinformatics analyses were conducted to explore the functional enrichment of viral expression in HCC. The risk score generated by this model could distinguish patients with different survival outcomes, have excellent reliability and accuracy, and could be used as an independent prognostic indicator. The high-risk score group showed significantly lower overall survival, and this trend was also observed in subgroups with different clinicopathological features. Furthermore, Deltabaculovirus positively correlated with amino acid metabolism, energy metabolism signaling pathways, peroxisomes, and complement coagulation cascades. In addition, Deltabaculovirus was significantly related to immune cell infiltration; therefore, patients with high Delta-baculovirus expression might respond better to HCC immunotherapy. Our study identified a promising predictive viral signature for assessing clinical prognosis and guiding immunotherapy in HCC. Deltabaculovirus might be a suitable viral vector for oncolytic virus immunotherapy.

Detection of Viruses in Special Stands of Common Ash Reveals Insights into the Virome of Fraxinus excelsior

Plant diseases are mostly multicausal with several factors influencing the health status of affected hosts. Common ash (Fraxinus excelsior), a significant tree species of European forests, is currently mostly endangered by ash dieback, caused by the invasive fungus Hymenoscyphus fraxineus. However, contributing factors, including pathogenic viruses, are poorly understood. Here, we report the results of a virus screening conducted on selected special stands of F. excelsior. Over three consecutive years, ash trees from different origins were tested, including leaf material from mature seed trees, young trees and ash seedlings from the natural regeneration. Using RT-PCR, we screened for five viruses, including the generalist species ArMV (Nepovirus arabis) and CLRV (Nepovirus avii), as well as newly discovered viruses in ash, including the emaravirus ASaV (Emaravirus fraxini), the idaeovirus PrLBaV (Idaeovirus ligustri), and cytorhabdoviruses. The results revealed a high virus diversity in common ash. An association of ASaV detection with specific leaf symptoms, including shoestring, chlorotic ringspots, and vein yellowing, was documented. An analyses of relevant gene products of cytorhabdoviruses obtained from ashes of different sites revealed sequence diversities and two distinct phylogenetic groups present in ash populations. Signatures of novel viruses from different families have been identified by high-throughput sequencing. Together, our results provide insights into the virus diversity and distribution of viruses in ash and expand our knowledge about the virome of this endangered tree species.

PGAP3 regulates human bronchial epithelial cell mRNAs present in asthma and respiratory virus reference data sets.

PGAP3 is a glycosylphosphatidylinositol (GPI) phospholipase gene localized within chromosome 17q12-21, a region highly linked to asthma. Although much is known about the function of other chromosome 17q12-21 genes expressed at increased levels in bronchial epithelium such as ORMDL3 and GSDMB, little is known about the function of increased PGAP3 expression in bronchial epithelium in the context of asthma. The aim of this study was therefore to determine whether increased PGAP3 expression in human bronchial epithelial cells regulated expression of mRNA pathways important to the pathogenesis of asthma by utilizing RNA-sequencing and bioinformatic analysis. We performed RNA-sequencing on normal human bronchial epithelial cells transfected with PGAP3 for 24 and 48 hours. PGAP3 regulated genes were compared to asthma and respiratory virus (influenza A, rhinovirus, respiratory syncytial virus) reference data sets to identify PGAP3 target genes and pathways. Approximately 9% of the upregulated PGAP3-induced genes were found in an asthma reference data set, 41% in a rhinovirus reference data set, 33% in an influenza A reference data set, and 3% in a respiratory syncytial virus reference data set. PGAP3 significantly upregulated the expression of several genes associated with the innate immune response and viral signatures of respiratory viruses associated with asthma exacerbations. Two of the highest expressed genes induced by PGAP3 are RSAD2, OASL, and IFN-λ, which are anti-viral genes associated with asthma. PGAP3 also upregulated the antiviral gene BST2, which like PGAP3 is a GPI-anchored protein. We conclude that PGAP3 expression in human bronchial epithelial cells regulates expression of genes known to be linked to asthma, and also regulates the bronchial epithelial expression of genes pertinent to the pathogenesis of respiratory viral triggered asthma exacerbations.

Detection of Covid-19 Cases from Chest X-Ray Images using CNN

The occurrence of COVID-19 has brought the worldwide threat to the living society. The severity of the unwellness is often understood by the huge variety of deaths and affected patients globally. If the identification is fast, the illnesses are often controlled in a very higher manner. The factitious intelligence researcher’s square measure focusing their experience data to develop mathematical models for analyzing this epidemic scenario mistreatment nationwide shared information. To contribute towards the well-being of living society, during this project, Deep learning algorithmic program are going to be wont to determine the COVID infected patients through chest X-Ray pictures. By using, Convolutional Neural Network and Deep Neural Network, the chest X-Ray pictures are going to be analyzed to observe, whether or not the actual patient has the signatures of COVID-19 viruses or not. The performance of each the model is going to be compared on the experimental basis and deliver the simplest model to the clinical and health care domain.

Has avian influenza virus H9 originated from a bat source?

Influenza A viruses are important pathogens that can cause diseases with high mortality in humans, animals, and birds; and wild birds are considered the primary reservoir of all subtypes in nature. After discovering the H9 influenza A viruses in bats, questions arose about their potential to serve as an additional natural reservoir and about the priority of the viral origin: Did the virus initially circulate in bats and then transmit to birds or vice versa? Influenza A viruses of the H9 subtype are of particular interest because fatal infections of humans caused by H5, H7, and H10 influenza viruses contained RNA segments from H9 viruses. Recently, a novel subtype of influenza A virus (H19) was reported and it was closely related to the H9 bat influenza A virus by its hemagglutinin structure. The genome of novel H19 has revealed a mixed characteristic genomic signature of both avian and bat influenza viruses. The time to most recent common ancestor (TMRCA) estimates have shown that the divergence time between the bat and avian H9-similar influenza virus occurred approximately at the end of the XVIII century. This article discusses the evolution and possible origin of influenza viruses of the H9 subtype isolated from bats and birds. The obtained data, along with the known data, suggest that the primary reservoir of the H9 influenza virus is wild birds, from which the virus was transmitted to bats. We hypothesize that the novel H19 could be a descendant of an intermediate influenza virus that was in the transition stage of spillover from avian to bat hosts.

Instantaneous Viral Detection of SARS‐CoV‐2 and Beyond using Electromagnetic Sensing

AbstractThis study proposes a highly sensitive portable device that utilizes electromagnetic waves and data analytics for instantaneous Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS‐CoV‐2) detection. The device consists of a Radio Frequency (RF) circuit that interprets reflected and transmitted electromagnetic waves to identify virus signatures in physiologically significant matrices, including human saliva and diluted nasopharyngeal swabs. The sensor's accuracy is validated in both pre‐clinical and clinical settings, where clinical measurements demonstrate an instantaneous detection accuracy of 94%, sensitivity of 95%, and specificity of 97.5% between the sensor's physical parameters and SARS‐CoV‐2 detection. The sensor's accurate real‐time response is due to its unique design and precise modeling techniques. In addition, the same sensing system is tested across different viruses and its ability to differentiate between influenza A, respiratory syncytial, and SARS‐CoV‐2 viruses is proven. Hence this work presents a holistic system that can predict the viral concentration of SARS‐CoV‐2, as well as differentiate between different viruses instantaneously and without adding any amplifying agent.

Viruses Demonstrate Selective Survival During Simulated Anaerobic Digestion of Plant Biomass

Objective. This research aimed at laboratory simulation of anaerobic digestion of plant biomass contaminated by a mixture of viruses with a wide host range to evaluate if viruses can retain their infectivity and pose a biohazard during the use of plant-based reusable resources such as digestate. Methods. Anaerobic digestion was simulated in air-tight desiccators using anaerobic bags and indicator strips to ensure proper conditions, and using fresh biomass of naturallyvirus-infected plants. In one of the variants, a commercial mixture of anaerobic bacteria and enzymes was also added to see if it would be more efficient in terms of plant digestion and virus inactivation. For serological detection of the tomato mosaic virus, cucumber mosaic virus, and potato virus Y, DAS-ELISA was used with commercial diagnostic kits and positive controls. Absorbance values were measured at 405 nm. Total RNA was extracted using a RNeasy Plant Mini kit following the manufacturer’s instructions. Molecular detection of viruses was carried out by two-step RT-PCR using specific oligonucleotide primers available from the literature. To check if the viruses can retain their infectivity after the anaerobic digestion of plant biomass waste, a bioassay was used where Nicotiana rustica plants producing necrotic lesions upon infection with many viruses were mechanically inoculated at the stage of 2 true leaves. For statistical processing of data, the mean and standard error were calculated using Microsoft Excel software. Results. After prolonged anaerobic digestion, tomato mosaic virus was still detected in plant residues, but it is important to note that it was also found in high concentration in the liquid phase. Hence, during the anaerobic digestion, a significant proportion of the virus was successfully eluted from plant residues into the digestate. Interestingly and contrary to tomato mosaic virus, cucumber mosaic virus has not practically eluted to the liquid phase. On the other hand, potato virus Y was supposedly completely decomposed during the anaerobic digestion of plant biomass waste, as it was not detected either by ELISA or by PCR. It is likely that not all of the investigated viruses represent a potential biohazard in the context of the use of renewable resources. RT-PCR outcomes showed the presence of tomato mosaic virus and cucumber mosaic virus both in the solid and the liquid phases, augmenting the ELISA data. Lastly, bioassay results have confirmed that at least tomato mosaic tobamovirus may escape the aggressive process of waste decomposition and remain able to infect host plants raising issues about the safety of reusable plant resources. Conclusions. The survival of plant viruses during plant biomass waste processing was studied in the context of biological safety. The preservation of serological markers and genetic signatures of model viruses in the process of anaerobic digestion has been confirmed. For the first time, it was proven that tomato mosaic virus may preserve its infectivity during long-term incubation of plant biomass waste in anaerobic conditions, which requires further attention when using renewable resources. On the example of PVY, it has been shown that potyviruses do not survive during anaerobic digestion and therefore may not pose an epidemic risk in using processed renewable resources. It has been demonstrated that artificial introduction of anaerobic microorganisms does not have a decisive effect on the stability of the studied model viruses.

Uncovering the endemic circulation of rabies in Cambodia.

In epidemiology, endemicity characterizes sustained pathogen circulation in a geographical area, which involves a circulation that is not being maintained by external introductions. Because it could potentially shape the design of public health interventions, there is an interest in fully uncovering the endemic pattern of a disease. Here, we use a phylogeographic approach to investigate the endemic signature of rabies virus (RABV) circulation in Cambodia. Cambodia is located in one of the most affected regions by rabies in the world, but RABV circulation between and within Southeast Asian countries remains understudied. Our analyses are based on a new comprehensive data set of 199 RABV genomes collected between 2014 and 2017 as well as previously published Southeast Asian RABV sequences. We show that most Cambodian sequences belong to a distinct clade that has been circulating almost exclusively in Cambodia. Our results thus point towards rabies circulation in Cambodia that does not rely on external introductions. We further characterize within-Cambodia RABV circulation by estimating lineage dispersal metrics that appear to be similar to other settings, and by performing landscape phylogeographic analyses to investigate environmental factors impacting the dispersal dynamic of viral lineages. The latter analyses do not lead to the identification of environmental variables that would be associated with the heterogeneity of viral lineage dispersal velocities, which calls for a better understanding of local dog ecology and further investigations of the potential drivers of RABV spread in the region. Overall, our study illustrates how phylogeographic investigations can be performed to assess and characterize viral endemicity in a context of relatively limited data.

A holistic and proactive approach to forecasting cyber threats

Traditionally, cyber-attack detection relies on reactive, assistive techniques, where pattern-matching algorithms help human experts to scan system logs and network traffic for known virus or malware signatures. Recent research has introduced effective Machine Learning (ML) models for cyber-attack detection, promising to automate the task of detecting, tracking and blocking malware and intruders. Much less effort has been devoted to cyber-attack prediction, especially beyond the short-term time scale of hours and days. Approaches that can forecast attacks likely to happen in the longer term are desirable, as this gives defenders more time to develop and share defensive actions and tools. Today, long-term predictions of attack waves are mostly based on the subjective perceptiveness of experienced human experts, which can be impaired by the scarcity of cyber-security expertise. This paper introduces a novel ML-based approach that leverages unstructured big data and logs to forecast the trend of cyber-attacks at a large scale, years in advance. To this end, we put forward a framework that utilises a monthly dataset of major cyber incidents in 36 countries over the past 11 years, with new features extracted from three major categories of big data sources, namely the scientific research literature, news, blogs, and tweets. Our framework not only identifies future attack trends in an automated fashion, but also generates a threat cycle that drills down into five key phases that constitute the life cycle of all 42 known cyber threats.

Phenotypic analysis of HIV-1 resistance to CD4 binding site broadly-neutralizing antibodies

Abstract Broadly neutralizing antibodies (bNAbs) show strong immunotherapy potential by targeting conserved regions of the HIV-1 envelope. Single bNAb use in viremic individuals quickly results in the emergence of escape variants, likely originating from existing quasispecies. An ex vivo assay was developed to predict bNAb efficacy in viremic individuals. The development of a predictive bNAb efficacy model may assist with the planning of future clinical trials. The ex vivoassay used pre-infusion CD4 +T cells from participants enrolled in the VRC 607/ACTG A5378 phase I study of the CD4 binding site (CD4bs) bNAbs’ VRC01LS (n=7) or VRC07-523LS (n=9). From these assays, the escape variant signatures of outgrowth viruses that replicated in presence of CD4bs bNAbs, were identified. We found that these escape variants contained key changes to the ß23-V5 region of the gp120 envelope, including charge changes, glycan loss, and/or glycan shifts. Outgrowth viruses from each participant had similar escape mutation patterns. Resistance mutations of the viral env sequences were confirmed in pseudovirus-based neutralization assays. We found complementary escape profiles from 3 CD4bs bNAbs (1–18LS, N6LS, and VRC01v23) with ex vivoand neutralization assays showing suppression by 1 or 2 but not all 3 bNAbs, supporting the potential for combination bNAb therapy. Our data suggest that the simultaneous use of multiple CD4 binding site bNAbs together could aid in limiting viral escape. Supported by intramural funds from NIH.

Detection of Mutant Peptides of SARS-CoV-2 Variants by LC/MS in the DDA Approach Using an In-House Database.

Equipped with a dramatically high mutation rate, which happens to be a signature of RNA viruses, SARS-CoV-2 trampled across the globe infecting individuals of all ages and ethnicities. As the variants of concern (VOC) loomed large, definitive detection of SARS-CoV-2 strains became a matter of utmost importance in epidemiological and clinical research. Besides, unveiling the disease pathogenesis at the molecular level and deciphering the therapeutic targets became key priorities since the emergence of the pandemic. Mass spectrometry has been largely used in this regard. A critical part of mass spectrometric analyses is the proteome database required for the identification of peptides. Presently, the mutational information on proteins available on SARS-CoV-2 databases cannot be used to analyze data extracted from mass spectrometers. Hence, we developed the novel Mutant Peptide Database (MPD) for the mass spectrometry (MS)-based identification of mutated peptides, which contains information from 11 proteins of SARS-CoV-2 from a total of 21,549 SARS-CoV-2 variants across different regions of India. The database was validated using clinical samples, and its applicability was also demonstrated with the mutated peptides extracted from the literature. We believe that MPD will support broad-spectrum MS-based studies like viral detection, disease pathogenesis, and therapeutics with respect to SARS-CoV-2 and its variants.

Environmental viromes reveal the global distribution signatures of deep-sea DNA viruses

IntroductionViruses are abundant and ecologically significant in marine ecosystems. However, the virome of deep-sea sediments is not extensively investigated. ObjectivesTo explore the distribution pattern of deep-sea viruses on a global scale, the viromes of DNA viruses isolated from 138 sediments of 5 deep-sea ecosystems were characterized. MethodsThe viral particles were purified from each sediment sample. Then the viral DNAs were extracted and subjected to viral metagenomic analysis. ResultsHere, we constructed a global deep-sea environmental virome dataset by analyzing the viral DNA of 138 sediment samples. A total of 347,737 viral operational taxonomic units (vOTUs) were identified, of which 84.94% were hitherto unknown, indicating that deep sea was a reservoir of novel DNA viruses. Furthermore, circular viral genome analysis revealed 98,581 complete genomes. The classified vOTUs included eukaryotic (44.55%) and prokaryotic (25.75%) viruses, and were taxonomically assigned to 63 viral families. The composition and abundance of the deep-sea sediment viromes were dependent on the deep-sea ecosystem as opposed to geographical region. Further analysis revealed that the viral community differentiation in different deep-sea ecosystems was driven by the virus-mediated energy metabolism. ConclusionOur findings showed that deep-sea ecosystems are a reservoir of novel DNA viruses and the viral community is shaped by the environmental characteristics of deep-sea ecosystems, thus presenting critical information for determining the ecological significance of viruses in global deep-sea ecosystems.

Genome-resolved metagenomics inferred novel insights into the microbial community, metabolic pathways, and biomining potential of Malanjkhand acidic copper mine tailings.

Mine tailing sites provide profound opportunities to elucidate the microbial mechanisms involved in ecosystem functioning. In the present study, metagenomic analysis of dumping soil and adjacent pond around India's largest copper mine at Malanjkhand has been done. Taxonomic analysis deciphered the abundance of phyla Proteobacteria, Bacteroidetes, Acidobacteria, and Chloroflexi. Genomic signatures of viruses were predicted in the soil metagenome, whereas Archaea and Eukaryotes were noticed in water samples. Mesophilic chemolithotrophs, such as Acidobacteria bacterium, Chloroflexi bacterium, and Verrucomicrobia bacterium, were predominant in soil, whereas, in the water sample, the abundance of Methylobacterium mesophilicum, Pedobacter sp., and Thaumarchaeota archaeon was determined. The functional potential analysis highlighted the abundance of genes related to sulfur, nitrogen, methane, ferrous oxidation, carbon fixation, and carbohydrate metabolisms. The genes for copper, iron, arsenic, mercury, chromium, tellurium, hydrogen peroxide, and selenium resistance were found to be predominant in the metagenomes. Metagenome-assembled genomes (MAGs) were constructed from the sequencing data, indicating novel microbial species genetically related to the phylum predicted through whole genome metagenomics. Phylogenetic analysis, genome annotations, functional potential, and resistome analysis showed the resemblance of assembled novel MAGs with traditional organisms used in bioremediation and biomining applications. Microorganisms harboring adaptive mechanisms, such as detoxification, hydroxyl radical scavenging, and heavy metal resistance, could be the potent benefactions for their utility as bioleaching agents. The genetic information produced in the present investigation provides a foundation for pursuing and understanding the molecular aspects of bioleaching and bioremediation applications.

Calculation of the security level coefficient of the automated system of the internal affairs bodies based on the information security of the information security system with updates of virus and threat signatures

Objective. This paper considers protection against threats that occur more often in the period from the start of the operating system boot. Consideration of various configurations will allow an overview of a fairly wide range of situations that arise. To solve the problem, it is necessary to determine the vulnerabilities, as well as to designate the coefficients that determine the state of the automated system.Method. Computer facilities are a set of software and hardware components (including information security tools) of data processing systems that can function independently or as part of other systems. Methods for analyzing the process of the impact of computer threats at the stage of loading the operating system are applied.Result. A technique is proposed for calculating the security factor of automated systems in a secure design, depending on the availability of the necessary security policies and the timely updating of virus and threat signature databases. The vulnerabilities in the process of starting the operating system are summarized, conclusions are drawn on the calculation of the security level coefficient of the automated ATS system based on the information security of the information security system with updates of virus and threat signatures.Conclusion. The developed methodology makes it possible to assess the security of automated systems, taking into account the situation of information security in the field.

Nanomechanical and Vibrational Signature of Chikungunya Viral Particles.

Chikungunya virus (CHIKV) belongs to the genus Alphaviridae, with a single-stranded positive-sense RNA genome of 11.8 kbp encoding a polyprotein that generates both non-structural proteins and structural proteins. The virus is transmitted by the Aedes aegypti and A. albopictus mosquitoes, depending on the location. CHIKV infection leads to dengue-like musculoskeletal symptoms and has been responsible for several outbreaks worldwide since its discovery in 1952. Patients often experience fever, headache, muscle pain, joint swelling, and skin rashes. However, the ultrastructural and mechanical properties of CHIKV have not been fully characterized. Thus, this study aims to apply a physical approach to investigate CHIKV's ultrastructural morphology and mechanical properties, using atomic force microscopy and Raman spectroscopy as the main tools. Using nanomechanical assays of AFM and a gold nanoparticles substrate for Raman signal enhancement, we explored the conformational plasticity, morphology, vibrational signature, and nanomechanical properties of the chikungunya virus, providing new information on its ultrastructure at the nanoscale and offering a novel understanding of the virus' behavior upon mechanical disruptions besides its molecular composition.

Prognostic and therapeutic significance of microbial cell-free DNA in plasma of people with acute decompensation of cirrhosis

Although the effect of bacterial infection on cirrhosis has been well-described, the effect of non-hepatotropic virus (NHV) infection is unknown. This study evaluated the genome fragments of circulating microorganisms using metagenomic next-generation sequencing (mNGS) in individuals with acute decompensation (AD) of cirrhosis, focusing on NHVs, and related the findings to clinical outcomes. Plasma mNGS was performed in 129 individuals with AD of cirrhosis in the study cohort. Ten healthy volunteers and 20, 39, and 81 individuals with stable cirrhosis, severe sepsis and hematological malignancies, respectively, were enrolled as controls. Validation assays for human cytomegalovirus (CMV) reactivation were performed in a validation cohort (n= 58) and exploratory treatment was instituted. In the study cohort, 188 microorganisms were detected in 74.4% (96/129) of patients, including viruses (58.0%), bacteria (34.1%), fungi (7.4%) and chlamydia (0.5%). A NHV signature was identified in individuals with AD, and CMV was the most frequent NHV, which correlated with the clinical effect of empirical antibiotic treatment, progression to acute-on-chronic liver failure, and 90-day mortality. The NHV signature in individuals with acute-on-chronic liver failure was similar to that in those with sepsis and hematological malignancies. CMV was detected in 24.1% (14/58) of patients in the validation cohort. Of the 14 cases with detectable CMV by mNGS, nine were further validated by real-time PCR or pp65 antigenemia testing. Three patients with CMV reactivation received ganciclovir therapy in an exploratory manner and experienced clinical resolutions. The results of this study suggest that NHVs may play a pathogenic role in complicating the course of AD. Further validation is needed to define whether this should be incorporated into the routine management of individuals with AD of cirrhosis. A non-hepatotropic virus (NHV) signature, which was similar to that in individuals with sepsis and hematological malignancies, was identified in individuals with acute decompensation of cirrhosis. The detected viral signature had clinical correlates, including clinical efficacy of empirical antibiotic treatment, progression to acute-on-chronic liver failure and short-term mortality. Cytomegalovirus reactivation, which is treatable, may adversely affect clinical outcomes in some individuals with decompensated cirrhosis. Routine screening for NHVs, especially cytomegalovirus, may be useful for the management of individuals with acute decompensation of cirrhosis.

A study on detection and defence of malicious code under network security over biomedical devices

With the proliferation of massive varieties and unknown malicious viruses, it is difficult to achieve effective and timely defence by anti-virus technology with virus signature matching as the core. Hence, the research of malicious code detection and defence is investigated. Firstly, it introduces the defence technology and detection technology. The simulation results show that the default infection probability of the simulation program is 15.1%. The default detection probability is 60.1%, the default number of nodes is 1000, the default time step is 1000 ms, and the default initial infected node is only node 0, that is, only the malicious code on node 0 is activated. After start-up, the whole P2P starts to run, and the number of infected nodes increases. Finally, all nodes are infected. The infection speed becomes faster and faster. When the number of infected nodes reaches about half, the infection speed begins to slow down.

Label-Free Spectroscopic SARS-CoV-2 Detection on Versatile Nanoimprinted Substrates.

Widespread testing and isolation of infected patients is a cornerstone of viral outbreak management, as underscored during the ongoing COVID-19 pandemic. Here, we report a large-area and label-free testing platform that combines surface-enhanced Raman spectroscopy and machine learning for the rapid and accurate detection of SARS-CoV-2. Spectroscopic signatures acquired from virus samples on metal–insulator–metal nanostructures, fabricated using nanoimprint lithography and transfer printing, can provide test results within 25 min. Not only can our technique accurately distinguish between different respiratory and nonrespiratory viruses, but it can also detect virus signatures in physiologically relevant matrices such as human saliva without any additional sample preparation. Furthermore, our large area nanopatterning approach allows sensors to be fabricated on flexible surfaces allowing them to be mounted on any surface or used as wearables. We envision that our versatile and portable label-free spectroscopic platform will offer an important tool for virus detection and future outbreak preparedness.

Hyper-Variable Spike Protein of Omicron Corona Virus and Its Differences with Alpha and Delta Variants: Prospects of RT-PCR and New Vaccine

NCBI SARS-CoV-2 Database was analyzed between November-December, 2021 to decipher the spread of Delta corona virus variants in the USA and compared with highly transmissible new omicron variant recently originated in South Africa. Presently, B.1.617.2 and AY.103 lineages Delta variants with spike protein L452R, T478K, P681R mutations and F157/R158 two amino acids deletions were predominant in the USA and superseded the deadly outbreaks of B.1.1.7 Alpha variant with deletions of H69, V70 and Y145 amino acids as well as N501Y, and D614G highly transmissible mutations. Interestingly, omicron variant has six H69, V70, V143, Y144, Y145, L212 immune-escape deletions as well as 29 mutations in the spike protein including most deadly N501Y (Y498 in omicron) and D614G (G611 in omicron). This indicated that omicron variant was originated by combination among B.1.1.7, AY.X and B.1.617.2 lineages. A unique three amino acids (EPE) insertion at 215 position of spike protein was detected to compensate six deletions suggesting further recombination events. Three Serine residues were mutated at amino acids 371 (S=L, L368 in omicron), 373 (S=P, P370 in Omicron), 375 (S=F, F372 in omicron) but compensated at 446 (G=S, S443 in omicron) and 496 (G=S, S493 in omicron) at the RBD domain of omicron virus. The three amino acids (ERS) deletion at position 30 in the N-protein acts as another signature of omicron virus. Omicron variant has less mutation in the 2/3 5’-end of the genome that codes for ORF1ab poly-protein but dominant P4715L mutation in the RNA-dependent RNA polymerase. However, overall amino acid composition, alipathic index, and instability index were found fairly constant although hydrophobic plot gave some difference between spike protein of Wuhan and omicron corona viruses. BLAST search detected 20nt and 19nt perfect match of hyper-variable 22957-22977nt region comprising 488-493 amino acids (NH2-PLRSYS-CO2H) of the spike protein of omicron virus with the ch-2 of Seladonia tumulorum or ch-16 of Steromphala cineraria respectively. A primer set designed from the RBD domain of spike gene did not detected the omicron genome by BLAST search but primers from the constant regions of the genome worked well. Such hyper-variation in the spike protein suggested that DNA vaccine or mRNA vaccine using spike gene of corona virus may not efficiently protect omicron virus infection and attenuated whole corona virus vaccine will be safer vaccine.