Ginger ring compounds as an inhibitor of spike binding protein of alpha, beta, gamma and delta variants of SARS-CoV-2: An in-silico study

The available drugs against coronavirus disease 2019 (COVOD-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), are limited. This study aimed to identify ginger-derived compounds that might neutralize SARS-CoV-2 and prevent its entry into host cells. Ring compounds of ginger were screened against spike (S) protein of alpha, beta, gamma, and delta variants of SARS-CoV-2. The S protein FASTA sequence was retrieved from Global Initiative on Sharing Avian Influenza Data (GISAID) and converted into ".pdb” format using Open Babel tool. A total of 306 compounds were identified from ginger through food and phyto-databases. Out of those, 38 ring compounds were subjected to docking analysis using CB Dock online program which implies AutoDock Vina for docking. The Vina score was recorded, which reflects the affinity between ligands and receptors. Further, the Protein Ligand Interaction Profiler (PLIP) program for detecting the type of interaction between ligand-receptor was used. SwissADME was used to compute druglikeness parameters and pharmacokinetics characteristics. Furthermore, energy minimization was performed by using Swiss PDB Viewer (SPDBV) and energy after minimization was recorded. Molecular dynamic simulation was performed to find the stability of protein-ligand complex and root-mean-square deviation (RMSD) as well as root-mean-square fluctuation (RMSF) were calculated and recorded by using myPresto v5.0. Our study suggested that 17 out of 38 ring compounds of ginger were very likely to bind the S protein of SARS-CoV-2. Seventeen out of 38 ring compounds showed high affinity of binding with S protein of alpha, beta, gamma, and delta variants of SARS-CoV-2. The RMSD showed the stability of the complex was parallel to the S protein monomer. These computer-aided predictions give an insight into the possibility of ginger ring compounds as potential anti-SARS-CoV-2 worthy of in vitro investigations. © 2023, School of Medicine, Universitas Syiah Kuala. All rights reserved.

Detection of Mutations in SARS-CoV-2 Genomic Clades using COVIDSeq-NGS among International Travelers

Introduction/Objective Numerous SARS-CoV-2 variants/lineages have been identified based on genome sequencing. As of June 15, 2022 almost 11,399,573 whole genome sequences have been deposited in the GISAID-database. Severity and spread of COVID19 is based on their efficiency of infection and to multiply in host. That largely depend upon the structural mutation in spike, ORF and N proteins etc. That happens due to translation of genomic mutations during polypeptide synthesis. Also, the mutations are region/country specific. Specific mutation and combination of mutation causes the emergence of new strains. However, the strains can migrate from one region to other through travelers. The main objective of the current study is profiling of mutations in the genome of SARSCoV2 using Next- Generation-Sequencing (NGS) in international travelers and phylogenetic analysis of the sequences to find out different clades of SARSCoV2. Methods/Case Report A total of 557 SARSCoV2 genomes were sequenced on S4-sequencing flow-cell on NovaSeq 6000. For NGS of SARS-CoV-2 genome, Illumina, COVIDSeq kits and the protocols will be used strictly as recommended by the manufacturer. After NGS the analysis was done followed by FASTA sequences retrieval, mutations recording and phylogeny. Results (if a Case Study enter NA) This study reports 11 clades (19A, B, 20A, B, C, D, 20E;EU1, 20G, 20H;Beta V2, 20I: Alpha V1, 21D;and Eta) for the first time in international travelers. To best of our knowledge, this is the first report of the COVIDSeq approach for detection of mutation in SARSCoV2 genomic clades. The study revealed some dominants mutations was (Orf1a: P2018Q, K1053R, E176V, Orf1b: A520V, T2165A, S: D1127G, D614G, L18F etc. in other genes). Conclusion Profiling of common mutations among travelers could fill some gaps about the existence of SARS-CoV-2 variants information. However, further studies are needed to consolidate these findings before to be utilized for development of a potential therapeutic strategy.

Technology Dependency and Impact during COVID-19: A Systematic Literature Review and Open Challenges

The COVID-19 pandemic is still a challenge in many countries, although life must proceed while ensuring the pandemic is managed critically. Due to the delay in producing permanent medical intervention, despite the availability of vaccines, there is still a need to depend on technology in performing several tasks. A systematic literature review that provides comprehensive evidence on technology dependence and the impact of technology on individuals during the pandemic is lacking. This study systematically reviewed scholarly works related to technology dependency from a broad view since the pandemic and mapped the research findings into a taxonomy, thus establishing the trend in technology type, major areas of technology dependency, and the impact of technology during the pandemic. The mapped taxonomy is used to expound on open challenges and recommendations. The final set from the systematic search was 76 articles. Technology might be an avenue for administering and enhancing health services, improving outreaches, and supporting curbing the spread of diseases. However, the impact of technology dependence is both positive and negative. A systematic mapping was conducted to explore the literature on the impacts of technology, where there is a need for further research. Notwithstanding the category, most of the reviewed articles emphasized the usage and impact of technology at such a time of the pandemic and provided insights on the manner of addressing them. Realistically, there has been an acceleration of digitalization trends in the present era of the COVID-19 pandemic and the possibility of rapid development of novel digital technologies. Author

SIR model for the spread of COVID-19: A case study

In this article, we study the spread pattern of the epidemic of COVID-19 disease from the point of view of mathematical modeling. Considering that this virus follows the basic rules of epidemic disease transmission, we use the SIR model to show the spread process of this disease in Iran. Then we estimate the primary reproduction number (R0) of COVID-19 in Iran by matching an epidemic model with the data of reported cases. © 2022

The Preliminary Investigation on Micro-Credentials Practices in Malaysia

This COVID-19 has lately changed the way individuals study and teach by making it available at any time, from any location, and at a low cost. Traditional face-to-face teaching and learning are losing popularity as more students opt for hybrid or all-online learning. In today's fast-paced business, the advent of the gig economy needs the development of individuals and experts with specialised skill sets to fill increasingly specialised positions. Higher education providers needed a more dynamic and quick style of learning to match these demands, which Micro-Credential, a well-known player in 21st-century training and education, delivered. Micro-credentials are nanodegrees, also known as small qualifications, that demonstrate a person's talents, knowledge, and/or experience in a certain subject area or ability. After completing a micro-credentials course, the learner will receive a digital badge. The adoption of Micro-Credential courses in Malaysia was investigated using desktop research and a survey questionnaire in this study. This study examines how Micro-Credentials are used in Malaysia's top three public universities, as well as a poll of Malaysian students' Micro-Credentials habits. Micro-credentialing appears to be gaining popularity at Malaysian universities. The research will be broadened to collect and analyse data for the preliminary study, which will focus on learners' attainment of Digital Badges for Micro Credential Computing Courses using a quantitative research technique. © 2022 IEEE.

Detection of SARS-CoV-2 Eta VOI among international travelers using COVIDSeq-NGS

Rationale: SARS-CoV-2 has been identified as a highly infective and contagious viral infection. The SARS-CoV-2 pandemic has been spread worldwide and affected more than 210 countries. Globally, the fast spread of novel SARS-CoV-2 variants has been mostly attributed to international travel. Patient concerns: We are reporting the genomic evidence of SARS-CoV-2 Eta VOI among two international travelers. Both travelers were males from Nigeria aged 24 and 34 years and both were asymptomatic. Diagnosis: The nasopharyngeal swab samples were in both travelers positive by real-time RT-PCR followed by COVIDSeq-NGS. Interventions: Paracetamol 3 times daily for 5 days. Outcomes: Patient recovered completely within 10 days and discharged after 14 days of quarantine duration. Lessons: This report highlights genomic variation of SARS-CoV-2 among the travelers. For managing the present health crisis, molecular identification of viral variants present in different geographical locations will be very helpful.

The creative industries effects on economic performance in the time of pandemic

Purpose: This paper aims to investigate empirically whether creative industries are boosting the economic performance of the ASEAN countries (Malaysia, Indonesia, Singapore, Thailand, Vietnam and Brunei Darussalam) during the Coronavirus disease (COVID-19) pandemic. Design/methodology/approach: This paper applied a random effect and fixed effect estimation approach to investigate the impact of creative industries’ development (government expenditure on education, export of creative industries, trade openness, innovation index, sukuk issuances) on the economic performance spanning from 2010 to 2020. Findings: The economic performance was proxied by two dependent variables, namely, the gross domestic product and the Misery Index. On top of containment and vaccination measures, the findings demonstrated that creative industries are enhancing economic growth in Association of Southeast Asian Nations (ASEAN) countries, supported by the significant role of the sukuk market as a vital contributor to economic growth. Originality/value: This study is unique because it provides novel and empirical results of the creative industries’ development on economic performance in the ASEAN countries before and during the COVID-19 pandemic. © 2022, Emerald Publishing Limited.

USING DATA MINING TECHNIQUES TO MEASURE STUDENTS’ ACADEMIC PERFORMANCE AND THE EFFECTIVENESS OF LEARNING METHODS: A LITERATURE REVIEW

Analyzing students' academic performance in online learning to improve the overall quality and effectiveness of education has been one of the main focuses of Higher Educational Institutions (HEIs). A practical analysis utilizing the academic performance data to improve the quality of online learning has become a vital issue urgently required to guide HEIs for the improvement of the academic performance of students. The changes affected in the Covid-19 framework have affected the academic performance of students and educators. This study aims to summarize the various aspects of educational data mining and how it can be utilized to improve the teaching process. Using EDM, the study analyzed students' academic performance for the past five years. It focused on the various learning methods that the students used. The study provided a detailed analysis of the multiple attributes that influenced the students' academic performance. We presented 12 out of 56 papers/documents that fit the inclusion and exclusion criteria of students' academic performance based on the educational setting. This study revealed that the most commonly used methods for assessing students' academic performance are not done in the face-to-face learning method. © 2022 Little Lion Scientific.

An Analysis of Students’ Academic Performance Using K-Means Clustering Algorithm

A massive amount of data is often used to evaluate the academic performance of students in higher education. Analysis can solve this challenge through various strategies and methods. Due to the spread of the pandemic Covid-19, traditional modes of education have shifted to include online learning. This study aims to analyze the academic performance of students through data mining techniques. The objective aims to investigate the academic performance of business students at a private university in Malaysia using Educational Data Mining techniques. Students’ academic performance data of a private university in Malaysia is used to analyze students’ performance using demographic and academic attributes. This study used students’ academic performance in the learning method to identify the patterns before and during Covid-19 using the K-Means data mining clustering technique. The results of the k-means clustering analysis showed that students were achieving higher CGPA during Covid-19 online learning compared to before Covid-19. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.