Repurposing Mitragynine as Anti-SARS- CoV-2 Agent Evidenced by In Silico Predictive Approach

The outbreak of a new coronavirus strain (SARS-CoV-2) calls for the development of treatment approaches to address the disease. Therefore, an in silico study was conducted to evaluate druggability capacity of mitragynine, a natural indole alkaloid compound, using adsorption, distribution, metabolism, and excretion (ADME) prediction and molecular docking simulation to the region binding domain of severe acute respiratory coronavirus 2 (SARS-CoV-2 RBD). The pharmacodynamics of mitragynine were evaluated for its druggability using SwissADME software, and molecular docking simulation was performed using AutoDock software, using SARS-CoV-2 RBD (PDB ID: 6M0J) as the protein target retrieved from Protein Data Bank (PDB). ADME predicted that this compound has excellent druggability, transport properties, and pharmacokinetics, following Lipinski's rule of five. Mitragynine was also nonmutagenic based on the AMES toxicity test. No PAINS alert was observed and the synthetic acceptability score was 4.49, suggesting a moderately synthesised compound. Through the molecular docking approach, mitragynine successfully docked the binding site of SARS-CoV-2 RBD with a binding energy of -6.3kcal/mol and formed hydrogen bonds with the residue N501, which is one of the residues at the binding site of RBD. These findings, together with other therapeutic qualities of mitragynine warrant more research into molecular dynamics, in vitro, and in vivo studies in COVID-19 therapy.

A literature review of dual disaster challenges for resilient office building toward reducing disaster risks

Flood is acknowledged as the most common natural disaster in several parts of the globe. For Malaysia, flood is considered as the most frequent natural disaster, with the frequency of at least once a year. The risks of flood can be seen through property loss and damages, infrastructure casualties, and disruption to socio-economic activities. Adding to that, Malaysia also faced the flood during the pandemic when it hit several states, namely Pahang, Johor, and Kelantan, during the monsoon season in 2020 and 2021, amid the rising cases of Covid-19. The ongoing COVID-19 pandemic has posed significant challenges for disaster response, calling for the “new norms” to be quickly established for better disaster risk reduction. Several mitigation strategies have been taken by the government to reduce the risks of floods in Malaysia. As office buildings possess important roles in delivering effective services to the public while maintaining their critical documents, this paper focuses on providing related literature on building resilience. Having an early understanding of the core elements of office building resilience in dual disaster challenges will provide the basis for further investigation in the later stage of data collection.

Comparison of meta-heuristic algorithms for fuzzy modelling of COVID-19 illness’ severity classification

The world health organization (WHO) proclaimed the COVID-19, commonly known as the coronavirus disease 2019, was a pandemic in March 2020. When people are in close proximity to one another, the virus spreads mostly through the air. It causes some symptoms in the affected person. COVID-19 symptoms are quite variable, ranging from none to severe sickness. As a result, the fuzzy method is seen favourably as a tool for determining the severity of a person’s COVID-19 sickness. However, when applied to a large situation, manually generating a fuzzy parameter is challenging. This could be because of the identification of a large number of fuzzy parameters. A mechanism, such as an automatic procedure, is consequently required to identify the right fuzzy parameters. The meta-heuristic algorithm is regarded as a viable strategy. Five meta-heuristic algorithms were analyzed and utilized in this article to classify the severity of COVID-19 sickness data. The performance of the five meta-heuristic algorithms was evaluated using the COVID-19 symptoms dataset. The COVID-19 symptom dataset was created in accordance with WHO and the Indian ministry of health and family welfare criteria. The findings provide the average classification accuracy for each approach. © 2022, Institute of Advanced Engineering and Science. All rights reserved.

Are You Aware of Your Data Privacy? The Case of Digital Contact Tracing Applications (MySejahtera)

Digital Contact Tracing (DCT) apps have been widely used as one of the control measures in mitigating the COVID-19 pandemic all over the countries. Despite the various benefits, the use of the DCT apps has raised several issues, particularly in the area of data privacy. Thus, it is important for users to be aware of their privacy while using such apps. This study was conducted to identify the level of user awareness on data privacy and investigate whether the data privacy concern can influence the adoption of the MySejahtera application. A total of 505 responses were obtained from an online survey distributed through social media. The data were then analyzed quantitatively using descriptive statistics and Structural Equation Modelling (SEM) techniques. Empirical results found that the user awareness level on data privacy in using MySejahtera App is moderately high. The respondents are highly aware that their personal data were collected while using the app although they demonstrate less awareness on the privacy risk towards misusing of their personal data. The study also found out that data privacy concern does influence the adoption of MySejahtera App. Even though the awareness level towards their data privacy is considered high, it is believed that this finding is largely influenced by the enforcement made by the Malaysian Government to mitigate the CO VID-19 outbreak. This study provides insights into users' understanding of data privacy pertaining to DCT applications focusing on MySejahtera. The findings offer the government some recommendation to formulate effective strategies to reduce personal concern towards the apps. The government can make use of the findings in handling the stored data for strengthening public trust. © 2021 IEEE.

An Initiative to Measure the impact of Social Media Adoption on Bumiputera Micro-Entrepreneurs' Business Performance: A Conceptual Paper

Pandemic COVID-19 has changed the business landscape dramatically. Many large business and corporate sectors are able to adapt to the change but the micro-entrepreneurs continue their struggling to adapt to the change. Due to the movement restrictions while battling with COVID-19, businesses are forced to switch from conventional brick-and-mortar business to digital business application involving developing their own e-commerce sites. The emerging social media in society provides opportunity for the micro-enterprises to virtually engage with their customers. The social media has now become one of the important business tools for marketing, branding, networking and developing the business strategy. Despite of the active social media involvement among the micro-entrepreneurs, the outcome of the social media activities is still at its infancy. Micro-entrepreneurs especially the Bumiputeras have still not fully utilized the social media as their business tool. Micro-entrepreneurs lack the knowledge on how to interpret the social media platform analysis tools such as site traffic, post engagement, post impressions and others. Therefore, it is necessary to further study of degree social media adoption among the Bumiputera micro-entrepreneurs and how it affects the business performance. A quantitative method is proposed for this study by considering the existing UTAUT variables like performance expectancy, effort expectancy, social influence and facilitating conditions. This paper proposes a conceptual research model based on the underpinning theory and aim to measure the outcome from adoption of social media on Bumiputera micro-entrepreneurs' business performance. © 2021 IEEE.

Does therapeutic plasma exchange have a role in resistant cytokine storm state of COVID-19 infection?

Introduction Among the main causes of mortality in COVID-19 patients is cytokine storm (CS) state. Few treatment options with variable efficacy results are available for its management. We aimed to illustrate the efficacy of Therapeutic Plasma Exchange (TPE) treatment in COVID-19 patients with resistant CS. Material and methods This research is a prospective pilot study which included ten COVID-19 positive patients with CS state with no response after two doses of tocilizumab. Each patient received three to five TPE sessions according to his/her response. Respiratory status {oxygen (O-2) requirements and data of mechanical ventilation} and laboratory markers (IL-6, CRP, ferritin, D dimer, LDH) were assessed before and after TPE. We reported mortality at 28 day of illness. Results Six males and four females were enrolled in the study with a mean age of (52.9 years). Seven patients (70%) were on mechanical ventilation (MV). After TPE, oxygenation parameters and most laboratory markers improved significantly in all patients (p < 0.05). Four patients survived and were discharged (40%). One was on MV and three were not. The four patients had better hypoxic index (PaO2/FiO2 ratio) (>100 vs <100), started TPE sooner after tocilizumab failure (2-3 vs 5-6 days), needed fewer TPE sessions (3 vs 4-5, p = 0.03), and less duration in ICU (6.5 vs 12.5 days) compared to those who did not benefit. Conclusions In patients with CS state who did not respond well to tocilizumab and steroids, TPE could be a good option. Larger randomized clinical trials are needed to support its use.