Actin Contributes to the Hyperexpression of Baculovirus Polyhedrin (polh) and p10 as a Component of Transcription Initiation Complex (TIC)

Hyperexpression of polh and p10, two very late genes, is one of the remarkable characteristics in the baculovirus life cycle. However, the mechanisms underlying the hyperexpression of these two genes are still incompletely understood. In this study, actin was identified as a highly potential binding partner of polh and p10 promoters by conducting DNA pull-down and LC–MS/MS analyses. Inhibiting actin dynamics delayed and decreased the transcription of polh and p10. Actin interacted with viral RNA polymerase and transcription regulators, and the nuclear import of viral polymerase was inhibited with the disruption of actin dynamics. Simultaneously, the high enrichment of actin in polh and p10 promoters discovered via a chromatin immunoprecipitation (ChIP) assay indicated that actin was a component of the viral polymerase TIC. Moreover, overexpression of actin surprisingly upregulated the expression of luciferase (Luc) under the control of polh and p10 promoters. Taken together, actin participated in the hyperexpression of polh and p10 as a component of TIC. These results facilitate the promotion of the expression efficiency of foreign genes in the baculovirus expression vector system (BEVS).

Optimization of SARS-CoV-2 Spike Protein Expression in the Silkworm and Induction of Efficient Protective Immunity by Inoculation With Alum Adjuvants

The newly emerged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is causing a spread of coronavirus disease 2019 (COVID-19) globally. In order to end the COVID-19 pandemic, an effective vaccine against SARS-CoV-2 must be produced at low cost and disseminated worldwide. The spike (S) protein of coronaviruses plays a pivotal role in the infection to host cells. Therefore, targeting the S protein is one of the most rational approaches in developing vaccines and therapeutic agents. In this study, we optimized the expression of secreted trimerized S protein of SARS-CoV-2 using a silkworm-baculovirus expression vector system and evaluated its immunogenicity in mice. The results showed that the S protein forming the trimeric structure was the most stable when the chicken cartilage matrix protein was used as the trimeric motif and could be purified in large amounts from the serum of silkworm larvae. The purified S protein efficiently induced antigen-specific antibodies in mouse serum without adjuvant, but its ability to induce neutralizing antibodies was low. After examining several adjuvants, the use of Alum adjuvant was the most effective in inducing strong neutralizing antibody induction. We also examined the adjuvant effect of paramylon from Euglena gracilis when administered with the S protein. Our results highlight the effectiveness and suitable construct design of the S protein produced in silkworms for the subunit vaccine development against SARS-CoV-2.

Text-independent Speaker Verification Using Hybrid Convolutional Neural Networks

Automatic speaker verification is an active research area for more than four decades, and the technology has gradually upgraded for real application. In this paper, a hybrid convolutional neural network (CNN) model is proposed where a combination of the 3D CNN & 2D CNN model is used for speaker verification in the text-independent scenario. For speaker verification, this novel convolutional neural network architecture was built to capture and discard speaker and non-speaker information at the same time. In the training process, the network is trained to differentiate between different identities of a speaker to establish the background model. The model development of the speaker is one of the important aspects. Most conventional techniques employed the d-vector system to create speaker models by means of an average of the features collected from the speaker utterance. Here a hybrid of convolutional neural networks model is utilized in the development and registration phases for building a speaker model. The approach suggested exceeds the existing methods of speaker verification.

Adenine Base Editing in vivo with a Single Adeno-Associated Virus Vector

Base editors (BEs) have opened new avenues for the treatment of genetic diseases. However, advances in delivery approaches are needed to enable disease targeting of a broad range of tissues and cell types. Adeno-associated virus (AAV) vectors remain one of the most promising delivery vehicles for gene therapies. Currently, most BE/guide combinations and their promoters exceed the packaging limit (~5 kb) of AAVs. Dual-AAV delivery strategies often require high viral doses that impose safety concerns. In this study, we engineered an adenine base editor using a compact Cas9 from Neisseria meningitidis (Nme2Cas9). Compared to the well-characterized Streptococcus pyogenes Cas9-containing ABEs, Nme2-ABE possesses a distinct PAM (N4CC) and editing window, exhibits fewer off-target effects, and can efficiently install therapeutically relevant mutations in both human and mouse genomes. Importantly, we showed that in vivo delivery of Nme2-ABE and its guide RNA by a single-AAV vector can revert the disease mutation and phenotype in an adult mouse model of tyrosinemia. We anticipate that Nme2-ABE, by virtue of its compact size and broad targeting range, will enable a range of therapeutic applications with improved safety and efficacy due in part to packaging in a single-vector system.

Regulatory and Legal Enforcement of Cyber Security in Countries of the European Union: The Experience of Germany and France

This article is devoted to the study of information security in the EU member states, in particular Germany and France, in the context of the analysis of their national legislation, state, national programs and regulations. Particular attention is paid to the study of the features of regulatory and legal security of information security of Germany and France in the context of the study of their national legislation in terms of economic security as an inherent component of national security. In the course of this study the peculiarities of the functioning of the institutional and legal mechanism of cyber defense in the context of the multi-vector system of international security and legal regulation of international cooperation are analyzed. The article substantiates the expediency of developing an integrated, coordinated information policy of the EU member states in order to unify approaches to information security.At the same time, the current realities of European Union policy require comprehensive research in the context of ensuring national interests, developing effective mechanisms for protecting the information space, and legal mechanisms for shaping the economic system as a strategic factor of national security. Accordingly, the approaches to information security adopted in the European Union are currently not unified due to the geopolitical specifics of the EU’s countries. Therefore, the research, evaluation, and implementation of the positive experience of Germany and France in this area, according to the authors, is important in building the information security system of the European Union in the context of reliable protection against cyber threats.

Enhancement of Predicting Students Performance Model Using Ensemble Approaches and Educational Data Mining Techniques

Student performance prediction is extremely important in today’s educational system. Predicting student achievement in advance can assist students and teachers in keeping track of the student’s progress. Today, several institutes have implemented a manual ongoing evaluation method. Students benefit from such methods since they help them improve their performance. In this study, we can use educational data mining (EDM), which we recommend as an ensemble classifier to anticipate the understudy accomplishment forecast model based on data mining techniques as classification techniques. This model uses distinct datasets which represent the student’s intercommunication with the instructive model. The exhibition of an understudy’s prescient model is evaluated by a kind of classifiers, for instance, logistic regression, naïve Bayes tree, artificial neural network, support vector system, decision tree, random forest, and k -nearest neighbor. Additionally, we used set processes to evolve the presentation of these classifiers. We utilized Boosting, Random Forest, Bagging, and Voting Algorithms, which are the normal group of techniques used in studies. By using ensemble methods, we will have a good result that demonstrates the dependability of the proposed model. For better productivity, the various classifiers are gathered and, afterward, added to the ensemble method using the Vote procedure. The implementation results demonstrate that the bagging method accomplished a cleared enhancement with the DT model, where the DT algorithm accuracy with bagging increased from 90.4% to 91.4%. Recall results improved from 0.904 to 0.914. Precision results also increased from 0.905 to 0.915.

Unique features of a recombinant haemagglutinin influenza vaccine that influence vaccine performance

The influenza vaccine field has been constantly evolving to improve the speed, scalability, and flexibility of manufacturing, and to improve the breadth and longevity of the protective immune response across age groups, giving rise to an array of next generation vaccines in development. Among these, the recombinant influenza vaccine tetravalent (RIV4), using a baculovirus expression vector system to express recombinant haemagglutinin (rHA) in insect cells, is the only one to have reached the market and has been studied extensively. We describe how the unique structural features of rHA in RIV4 improve protective immune responses compared to conventional influenza vaccines made from propagated influenza virus. In addition to the sequence integrity, characteristic of recombinant proteins, unique post-translational processing of the rHA in insect cells instills favourable tertiary and quaternary structural features. The absence of protease-driven cleavage and addition of simple N-linked glycans help to preserve and expose certain conserved epitopes on HA molecules, which are likely responsible for the high levels of broadly cross-reactive and protective antibodies with rare specificities observed with RIV4. Furthermore, the presence of uniform compact HA oligomers and absence of egg proteins, viral RNA or process impurities, typically found in conventional vaccines, are expected to eliminate potential adverse reactions to these components in susceptible individuals with the use of RIV4. These distinct structural features and purity of the recombinant HA vaccine thus provide a number of benefits in vaccine performance which can be extended to other viral targets, such as for COVID-19.

A Shuttle-Vector System Allows Heterologous Gene Expression in the Thermophilic Methanogen Methanothermobacter thermautotrophicus ΔH

The world economies are facing permanently increasing energy demands. At the same time, carbon emissions from fossil sources need to be circumvented to minimize harmful effects from climate change.