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.

Chulalongkorn Interactive Virtual Memorial Hall (Museum)

Chulalongkorn University Memorial Hall is an important historic landmark in Thailand that collects and displays valuable and interesting documents and items from the history of the Chulalongkorn University, which is the first university established by the Thai dynasty. Many notable historical relics from Chulalongkorn University have been displayed for visitors inside the museum, including a miniature of King Chulalongkorn's equestrian statue, a coronet (Phra Kiew), and a graduation gown. Over the past two years, due to the COVID-19 situation, the number of visitors to the museum has been restricted. Therefore, we propose to solve this problem by introducing a virtual tour using virtual reality to cope with this challenging situation. This paper presents a description related to the Chulalongkorn University memorial hall in terms of 3D models through interactions in a virtual reality world, in which users gain in-depth experience and knowledge about the history of the Thai Royal and the Chulalongkorn University. Both the internal and external of the Chulalongkorn University Memorial Hall building are reproduced in 3D models, including furniture and belongings in the hall, for simulating the entire Chulalongkorn University Memorial Hall building. In addition to visiting the historical objects in the virtual museum, these objects are interactable with multimedia descriptions which are text, images, videos, and audio commentary. It makes visitors enjoy the ambiance while visiting the virtual Chulalongkorn University Memorial Hall. In addition, it is also the preservation of valuable cultural and historical knowledge resources. © 2022 ACM.

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.

A Theoretical Investigation of the SARS-CoV-2 Model via Fractional Order Epidemiological Model

We propose a theoretical study investigating the spread of the novel coronavirus (COVID-19) reported in Wuhan City of China in 2019. We develop a mathematical model based on the novel corona virus’s characteristics and then use fractional calculus to fractionalize it. Various fractional order epidemic models have been formulated and analyzed using a number of iterative and numerical approaches while the complications arise due to singular kernel. We use the well-known Caputo-Fabrizio operator for the purposes of fictionalization because this operator is based on the non-singular kernel. Moreover, to analyze the existence and uniqueness, we will use the well-known fixed point theory. We also prove that the considered model has positive and bounded solutions. We also draw some numerical simulations to verify the theoretical work via graphical representations. We believe that the proposed epidemic model will be helpful for health officials to take some positive steps to control contagious diseases. © 2023 Authors. All rights reserved.

An Efficient Deep Learning Framework for Face Mask Detection in Complex Scenes

COVID-19 has caused a global health crisis that has infected millions of people across the globe. Currently, the fourth wave of COVID-19 is about to be declared as Omicron. The new variant of COVID-19 has caused an unprecedented increase in cases. According to World Health Organization, safety measures must be adopted in public places to prevent the spread of the virus. One effective safety measure is to wear face masks in crowded places. To create a safe environment, government agencies adopt strict rules to ensure adherence to safety measures. However, it is difficult to manually analyze the crowded scenes and identify people violating the safety measures. This paper proposed an automated approach based on a deep learning framework that automatically analyses the complex scenes and identifies people with face masks or without facemasks. The proposed framework consists of two sequential parts. In the first part, we generate scale aware proposal to cover scale variations, and in the second part, the framework classifies each proposal. We evaluate the performance of the proposed framework on a challenging benchmark data set. We demonstrate that the proposed framework achieves high performance and outperforms other reference methods by a considerable margin from experimental results. © 2022, IFIP International Federation for Information Processing.

Covid-19 detection from X-ray images using Customized Convolutional Neural Network

COVID-19 continues to have a devastating impact on the lives of people all over the world. Various new technologies arose in the research environment to assist mankind in surviving and living a better life. It is important to screen the infected patients in a timely and cost-effective manner to combat this disease and avoid its transmission. To achieve this aim, detection of Covid-19 from radiological evaluation of chest x-ray images using deep learning algorithms is less expensive and easily available option as it ensures fast and efficient diagnosis of the disease. Therefore, this paper presents a novel customized convolutional neural network (CNN) approach for the detection of COVID-19 from chest x-ray images. The performance of the proposed model is evaluated on three different size datasets, created from publicly available datasets. Experimental results show that the proposed model has better performance on Dataset 2. A very large increase or decrease of the number of samples in the dataset degrades the performance of the proposed model. The performance of the CNN model is compared with traditional pretrained networks namely VGG-16, VGG-19, ResNet-50 and Inception-V3. All the models show promising performance on dataset 2 which shows that optimum amount of data is enough for the model to lean features from the input data. Overall, the best validation accuracy of 97.78 was achieved by the proposed model on dataset 2. © 2022 IEEE.

The asymptotic analysis of novel coronavirus disease via fractional-order epidemiological model

We develop a model and investigate the temporal dynamics of the transmission of the novel coronavirus. The main sources of the coronavirus disease were bats and unknown hosts, which left the infection in the seafood market and became the major cause of the spread among the population. Evidence shows that the infection spiked due to the interaction between humans. Hence, the formulation of the model proposed in this study is based on human-to-human and reservoir-to-human interaction. We formulate the model by keeping in view the esthetic of the novel disease. We then fractionalize it with the application of fractional calculus. Particularly, we will use the Caputo-Fabrizio operator for fractionalization. We analyze the existence and uniqueness of the well-known fixed point theory. Moreover, it will be proven that the considered model is biologically and mathematically feasible. We also calculate the threshold quantity (reproductive number) to discuss steady states and to show that the particular epidemic model is stable asymptotically under some restrictions. We also discuss the sensitivity analysis of the threshold quantity to find the relative impact of every epidemic parameter on the transmission of the coronavirus disease. Both the global and local properties of the proposed model will be analyzed for the developed model using the mean value theorem, Barbalat's lemma, and linearization. We also performed some numerical simulations to verify the theoretical work via some graphical representations. © 2022 Author(s).

A review of telephone consultations for head and neck cancer follow up: a patient satisfaction survey.

OBJECTIVE: To review patient satisfaction with the change in practice towards telephone consultations during and after the coronavirus disease 2019 pandemic for head and neck cancer follow up. METHOD: A retrospective analysis was conducted of head and neck cancer telephone appointments during a six-month period in a tertiary referral centre. RESULTS: Patients found the telephone consultations beneficial (98 per cent), with 30 per cent stating they were relieved to not have to attend hospital. Patients who travelled further, those with lower stage disease and patients with a greater interval from initial treatment were most satisfied with the telephone consultations. Sixty-eight per cent of patients stated they would be happy to have telephone consultations as part of their regular follow up after the pandemic. CONCLUSION: Patients found the telephone consultations beneficial and 30 per cent considered them preferable to face-to-face appointments. This study demonstrates that telephone consultations can be used as an adjunct to face-to-face appointments in an effort to reduce hospital attendances whilst maintaining close follow up.

Modeling the dynamics of the SARS-CoV-2 virus in a population with asymptomatic and symptomatic infected individuals and vaccination

The SARS-CoV-2 virus remains a pressing issue with unpredictable characteristics. The pandemic has spread worldwide through human interactions. Since the nature of the disease differs everywhere and it has a stochastic effect, we therefore develop a stochastic mathematical model to investigate its temporal dynamics. Asymptomatic individuals have a major effect on the spreading dynamics of the SARS-CoV-2 virus therefore, we divide the total population into susceptible, asymptomatic, symptomatic, and recovered groups. Multiple vaccinations have commenced across the globe. In this study, we assume that the vaccine confers permanent immunity. Moreover, due to the unpredictable characteristics of the disease random fluctuations are assumed in every population group. Using this model we show the existence and uniqueness of positive solutions to the proposed problem. We also discuss the disease extinction and persistence in the model to depict how contagious diseases can be eliminated from the community. We use the real data of SARS-CoV-2 virus, reported in Oman from the 1st January 2021 to 23rd May 2021 to parameterize the model. We then perform large-scale computational analysis to show the numerical simulation and verify the analytical findings.

COVID-19 and SARS-CoV-2: Everything we know so far - A comprehensive review

Coronavirus disease-2019 (COVID-19) emerged as a unique type of pneumonia outbreak in the Wuhan city of China in 2019 and spread to all its provinces in a matter of days and then to every continent of the world except Antarctica within 3-4 month. This paper aims to comprehensively consolidate the available information about COVID-19 and present all the possible information about this disease in form of a single paper to readers. Unparalleled research and exhaustive studies of everything about the disease and its causative virus, i.e., severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), are underway since its emergence. The genome sequence of the virus was made available within a record short time by China, making possible immediate study of its structure and characteristics. The routes of transmission of the disease, signs and symptoms, incubation period, pathogenesis, and pathophysiology have been extensively studied and presented in an organized way in this review paper. The number of confirmed cases and case fatality and mortality rates are updated regularly. The different diagnostic mechanisms have been characterized. Testing and management criteria and protocols have been adopted. Extensive efforts are underway for finding a treatment of the disease and developing a vaccine against it. A number of vaccines are available even in markets in different countries. More and more ways of personal protection, prevention, and mitigation of the disease are being explored and shared. While the outbreak has been declared as pandemic, the response of scientists was timely and enormous;thousands of publications about various aspects and impact of the diseases and its causative virus are there on the World Health Organization database and many more studies are underway. The purpose of writing this review article is to provide a comprehensive summary of the major aspects and important scientific findings so far, about COVID-19 and SARS-CoV-2, in a single article for ready reference. © 2021 Sumaira Naz et al., published by De Gruyter.

First COVID-19 related death in Pakistan in a patient with a travel history in Saudi Arabia

Rationale: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has been recognized as highly pathogenic. The current pandemic of SARS-CoV-2 has been spread globally and infected more than 200 countries. Patient concerns: We report the first confirmed fatal case of COVID-19 in Pakistan. A 50-year-old man returned from Saudi Arabia on March 09, 2020 and presented with cough, fever, malaise, poor appetite and difficulty in breathing to the Pulmonologist at District Headquarter Hospital Mardan. Diagnosis: The patient was initially diagnosed as COVID-19 suspected case. A oropharyngeal swab sample was positive by realtime RT-PCR tests. Lessons: This report highlights the importance of close coordination between clinicians and public health authorities as well as the importance of early laboratory-based confirmation of COVID-19 cases.

Coronavirus Treatments: What Drugs Might Work Against COVID-19?

The World Health Organization declared the severe acute respiratory syndrome (SARS)-coronavirus (CoV)-2 virus outbreak as a pandemic on May 27, 2020. Since then, more than 5 488 825 cases across the world have been recorded at the time of revising this article. Governments around the world have imposed serious containment measures, meanwhile, the healthcare system is overburdened due to large increases in COVID-19 cases. However, no specific anti-SARS-CoV-2 virus drugs or vaccines have yet been shown to be effective to fight this causative virus of acute infectious pneumonia. The current review was conducted to look for potential natural and synthesized drugs for the treatment of COVID-19 patients. Previously published data in journals, textbooks, periodicals, websites, and sources, including data about the treatment of human coronavirus with natural and synthesized drugs, were taken from the online bibliographical databases. The results showed that syndic drugs approved for other human diseases have been used to improve the symptoms of patients infected with SARS-CoV-2. Several clinical trials across the world evidenced beneficial effects of natural and synthesized drugs in the treatment of SARS-CoV-2 infections. On the other hand, many studies have provided a deep understanding of the therapeutic effects of conventional and traditional medicine in identifying naturally occurring drugs effective against the SARS-CoV-2 virus. Both natural and synthesized drugs should come together to fight the SARS-CoV-2 virus and other potential emerging dangerous viral diseases since they have shown promising findings in clinical trials conducted with COVID-19 patients.