Nanoformulation of Glycyrrhizic acid as a potent antiviral agent against Covid-19

In many previous studies, it has been found that liquorice plant (Glycyrrhiza glabra) extracts contain more than 300 natural compounds, most of which are triterpenoids and flavonoids, and had shown promising results in clinical studies for treating many microbial and viral infections. Triterpenoids like glycyrrhizic acid have shown anti-SARS-CoV activity in- vitro. Experimentally, certain glycyrrhizic acid derivatives have shown increased activity by many folds against SARS-associated viruses. These compounds can potentially inhibit the replication cycle of SARS-associated viruses by interfering with the viral gene expression or by inhibiting the spike protein expression, which in turn inhibits the adhesion and entry of the virus. Although the therapeutic has shown great antiviral activity in vitro, but in vivo its efficiency deteriorates till it reaches the liver for metabolism. In the current review, we analyze the unique replication strategy of SARS-CoV-2 and glycyrrhizic acid as a potential drug against SARS-CoV-2. We also discuss possible nano-formulations of glycyrrhizic acid for efficient drug delivery in humans, as a potent therapeutic strategy for COVID-19.

Crucial File Selection Strategy (CFSS) for Enhanced Download Response Time in Cloud Replication Environments

Cloud Computing is a mass platform to serve high volume data from multi-devices and numerous technologies. Cloud tenants have a high demand to access their data faster without any disruptions. Therefore, cloud providers are struggling to ensure every individual data is secured and always accessible. Hence, an appropriate replication strategy capable of selecting essential data is required in cloud replication environments as the solution. This paper proposed a Crucial File Selection Strategy (CFSS) to address poor response time in a cloud replication environment. A cloud simulator called CloudSim is used to conduct the necessary experiments, and results are presented to evidence the enhancement on replication performance. The obtained analytical graphs are discussed thoroughly, and apparently, the proposed CFSS algorithm outperformed another existing algorithm with a 10.47% improvement in average response time for multiple jobs per round.

Adaptive replication strategy based on popular content in cloud computing

The cloud is an infrastructure that provides decentralized on-demand services. It allows consumers to pay only for the services they use. The consumer is the important entity in the cloud. The violation of the SLA contract between the consumer and the provider often leads to consequences because the service provider has to pay penalties. Data replication is emerging as an ideal solution to meet the new challenges of the cloud. This paper proposes a new replication strategy based on the popularity of data. This strategy adaptively selects the files to be replicated to improve the overall availability of data in the system, minimize query response time, and achieve the required quality of service. In addition, it dynamically determines the number of replicas to add and the best locations to store them. Experimental results show the effectiveness of the proposed strategy.

Edge cloud task scheduling model based on layered excellent gene replication strategy

With the development of the Internet of Things and 5G. Edge cloud technology has gradually become a research hotspot. When facing the massive and concurrent tasks of terminal users, reasonable resource scheduling strategy is a key technology. Because edge cloud needs to respond quickly to real-time tasks and ensure the stability of nodes at the same time, the optimal task scheduling strategy needs to be selected to meet the low latency requirements of edge users. In view of the above problems in resource allocation of edge cloud, this paper established a layered excellent gene replication strategy (HEGPSO model), in which the optimal replicator is added, and an evolutionary particle swarm optimization algorithm is proposed. In each iteration, the population is divided into three layers based on individual fitness. After that, the optimal replication factor is added to each layer of individuals to enhance the global search ability of the algorithm and ensure the good convergence of the algorithm. Finally, a balanced resource allocation model is established. Experiments show that the HEGPSO model proposed in this paper has high fitness and fast convergence speed, and is suitable for large-scale task access scenarios.

The Bacillus phage SPβ and its relatives: A temperate phage model system reveals new strains, species, prophage integration loci, conserved proteins and lysogeny management components

The Bacillus phage SPβ has been known for about 50 years, but only a few strains are avalible. We isolated four new wild type strains of the SPbeta species. Phage vB_BsuS-Goe14 introduces its prophage into the spoVK locus, previously not observed to be used by SPβ-like phages. We could also reveal the SPβ-like phage genome replication strategy, the genome packaging mode, and the phage genome opening point. We extracted 55 SPβ-like prophages from public Bacillus genomes, thereby discovering three more integration loci and one additional type of integrase. The identified prophages resembled four new species clusters and three species orphans in the genus Spbetavirus. The determined core proteome of all SPβ-like prophages consists of 38 proteins. The integration cassette proved to be not conserved even though present in all strains. It consists of distinct integrases. Analysis of SPβ transcriptomes revealed three conserved genes, yopQ, yopR, and yokI, to be transcribed from a dormant prophage. While yopQ and yokI could be deleted from the prophage without activating the prophage, damaging of yopR led to a clear-plaque phenotype. Under the applied laboratory conditions, the yokI mutant showed an elevated virion release implying the YokI protein being a component of the arbitrium system.

Heterogeneity in the Response of Different Subtypes of Drosophila melanogaster Midgut Cells to Viral Infections

Single-cell RNA sequencing (scRNA-seq) offers the possibility to monitor both host and pathogens transcriptomes at the cellular level. Here, public scRNA-seq datasets from Drosophila melanogaster midgut cells were used to compare the differences in replication strategy and cellular responses between two fly picorna-like viruses, Thika virus (TV) and D. melanogaster Nora virus (DMelNV). TV exhibited lower levels of viral RNA accumulation but infected a higher number of cells compared to DMelNV. In both cases, viral RNA accumulation varied according to cell subtype. The cellular heat shock response to TV and DMelNV infection was cell-subtype- and virus-specific. Disruption of bottleneck genes at later stages of infection in the systemic response, as well as of translation-related genes in the cellular response to DMelNV in two cell subtypes, may affect the virus replication.

Comparative Analysis of Different Data Replication Strategies in Cloud Environment

In this paper, we performed a comparative study of the different data replication strategies such as Adaptive Data Replication Strategy (ADRS), Dynamic Cost Aware Re-Replication and Rebalancing Strategy (DCR2S) and Efficient Placement Algorithm (EPA) in the cloud environment. The implementation of these three techniques is done in JAVA and the performance analysis is conducted to study the performance of those replication techniques by various parameters. The parameters used for the performance analysis of these three techniques are Load Variance, Response Time, Probability of File Availability, System Byte Effective Rate (SBER), Latency, and Fault Ratio. From the analysis, it is evaluated that by varying the number of file replicas, it shows deviations in the outcomes of these parameters. The comparative results were also analyzed.