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Subject: SARS-CoV-2WoS Q: Q2

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Now showing 1 - 3 of 3
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    Editorial
    Citation - Scopus: 1
    Safety and Feasibility of Surgery for Oropharyngeal Cancers During the Sars-Cov
    (Frontiers Media Sa, 2021) Gorphe, Philippe; Grandbastien, Bruno; Dietz, Andreas; Duvvuri, Umamaheswar; Ferris, Robert L.; Golusinski, Wojciech; Simon, Christian
    [No Abstract Available]
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    Article
    Citation - WoS: 4
    Citation - Scopus: 7
    Real-Time Learning and Monitoring System in Fighting Against Sars-Cov in a Private Indoor Environment
    (Mdpi, 2022) Erisen, Serdar
    The SARS-CoV-2 virus has posed formidable challenges that must be tackled through scientific and technological investigations on each environmental scale. This research aims to learn and report about the current state of user activities, in real-time, in a specially designed private indoor environment with sensors in infection transmission control of SARS-CoV-2. Thus, a real-time learning system that evolves and updates with each incoming piece of data from the environment is developed to predict user activities categorized for remote monitoring. Accordingly, various experiments are conducted in the private indoor space. Multiple sensors, with their inputs, are analyzed through the experiments. The experiment environment, installed with microgrids and Internet of Things (IoT) devices, has provided correlating data of various sensors from that special care context during the pandemic. The data is applied to classify user activities and develop a real-time learning and monitoring system to predict the IoT data. The microgrids were operated with the real-time learning system developed by comprehensive experiments on classification learning, regression learning, Error-Correcting Output Codes (ECOC), and deep learning models. With the help of machine learning experiments, data optimization, and the multilayered-tandem organization of the developed neural networks, the efficiency of this real-time monitoring system increases in learning the activity of users and predicting their actions, which are reported as feedback on the monitoring interfaces. The developed learning system predicts the real-time IoT data, accurately, in less than 5 milliseconds and generates big data that can be deployed for different usages in larger-scale facilities, networks, and e-health services.
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    Article
    Citation - WoS: 3
    Citation - Scopus: 3
    Predicted Sars-Cov Mirnas Associated With Epigenetic Viral Pathoge-Nesis and the Detection of New Possible Drugs for Covid-19
    (Bentham Science Publ Ltd, 2021) Cetin, Zafer; Bayrak, Tuncay; Ogul, Hasan; Saygili, Eyup Ilker; Akkol, Esra Kupeli
    Objective: The outbreak of COVID-19 caused by SARS-CoV-2 has promptly spread worldwide. This study aimed to predict mature miRNA sequences in the SARS-CoV-2 genome, their effects on protein-protein interactions in the affected cells, and gene-drug relationships to detect possible drug candidates. Methods: Viral hairpin structure prediction, classification of hairpins, mutational examination of precursor miRNA candidate sequences, Minimum Free Energy (MFE) and regional entropy analysis, mature miRNA sequences, target gene prediction, gene ontology enrichment, and Protein-Protein Interaction (PPI) analysis, and gene-drug interactions were performed. Results: A total of 62 candidate hairpins were detected by VMir analysis. Three hairpin structures were classified as true precursor miRNAs by miRBoost. Five different mutations were detected in precursor miRNA sequences in 100 SARS-CoV-2 viral genomes. Mutations slightly elevated MFE values and entropy in precursor miRNAs. Gene ontology terms associated with fibrotic pathways and immune system were found to be enriched in PANTHER, KEGG and Wiki pathway analysis. PPI analysis showed a network between 60 genes. CytoHubba analysis showed SMAD1 as a hub gene in the network. The targets of the predicted miRNAs, FAM214A, PPM1E, NUFIP2 and FAT4, were downregulated in SARS-CoV-2 infected A549 cells. Conclusion: miRNAs in the SARS-CoV-2 virus genome may contribute to the emergence of the Covid-19 infection by activating pathways associated with fibrosis in the cells infected by the virus and modulating the innate immune system. The hub protein between these pathways may be the SMAD1, which has an effective role in TGF signal transduction.