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Simin Xia, Xi Chen
Cell Discovery, Volume 6, pp 1-4; doi:10.1038/s41421-020-0175-x

Abstract:
Wang, C., Horby, P. W., Hayden, F. G. & Gao, G. F. A novel coronavirus outbreak of global health concern. Lancet 395, 496–496 (2020). Zhang, Y.-Z. Novel 2019 coronavirus genome. Virological. Org. Available from: http://virological.org/t/novel-2019-coronavirus-genome/319 (2020). Corman, V. M. et al. Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR. Eurosurveillance 25, 23–30 (2020). Chu, D. K. W. et al. Molecular diagnosis of a novel coronavirus (2019-nCoV) causing an outbreak of pneumonia. Clin. Chem. 4, 549–555 (2020). Huang, C., Wang, Y. & Li, X. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 395, 496–496 (2020). Li, Q. et al. Early transmission dynamics in wuhan, China, of novel coronavirus-infected pneumonia. N. Engl. J. Med. 382, 1199–1207 (2020). Balmaseda, A. et al. Antibody-based assay discriminates Zika virus infection from other flaviviruses. Proc. Natl. Acad. Sci. USA 114, 8384–8389 (2017). Myhrvold, C. et al. Field-deployable viral diagnostics using CRISPR-Cas13. Science 360, 444–448 (2018). Piepenburg, O., Williams, C. H., Stemple, D. L. & Armes, N. A. DNA detection using recombination proteins. PLoS Biol. 4, 1115–1121 (2006). Zhao, Y. X., Chen, F., Li, Q., Wang, L. H. & Fan, C. H. Isothermal amplification of nucleic acids. Chem. Rev. 115, 12491–12545 (2015). Daher, R. K., Stewart, G., Boissinot, M. & Bergeron, M. G. Recombinase polymerase amplification for diagnostic applications. Clin. Chem. 62, 947–958 (2016). Obande, G. A. & Singh, K. K. B. Current and future perspectives on isothermal nucleic acid amplification technologies for diagnosing infections. Infect. Drug Resist. 13, 455–483 (2020). Download references We thank the core facilities at The HIT Center for Life Sciences of Harbin Institute of Technology (HIT) and the startup grant from HIT. X.C. conceived and designed the experiments; S.X. and X.C. participated in multiple experiments and analyzed the data; X.C. wrote the manuscript. Correspondence to Xi Chen. The authors declare that they have no conflict of interest. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. Reprints and Permissions Xia, S., Chen, X. Single-copy sensitive, field-deployable, and simultaneous dual-gene detection of SARS-CoV-2 RNA via modified RT–RPA. Cell Discov 6, 37 (2020). https://doi.org/10.1038/s41421-020-0175-x Download citation Received: 01 April 2020 Accepted: 05 May 2020 Published: 28 May 2020 DOI: https://doi.org/10.1038/s41421-020-0175-x
Ahmed Saeed Yahya, Shakil Khawaja, Jude Chukwuma
The Primary Care Companion For CNS Disorders, Volume 22; doi:10.4088/pcc.20com02642

Augusto Fey, João Vilson Cláudio Teixeira, Gabriela Bernardino Fey
Journal of Pharmacy and Pharmacology, Volume 8; doi:10.17265/2328-2150/2020.05.005

Published: 28 May 2020
Abstract:
The world is facing new challenges every day; however, with the spread of the pandemic around the world, this new challenge is different. The pandemic is increasing and concentrating various challenges simultaneously. Although different sectors are facing consequences, the most important sectors, that is, health and economy are the most affected. When the pandemic began, it was not known how long it would last, which complicated health and economic planning. Therefore, it is important for decision makers and the public to know the predictions and expectations of the future of these challenges. In this work, the current situation is analyzed. Then, an expectation model is developed based on the statistics of the pandemic using a growth rate model based on an exponential and logarithmic rate of increase. Based on the available open data about the pandemic spread, the model can successfully predict future expectations, including the duration and maximum number of cases of the pandemic. The model uses the equilibrium point as the day the cases decrease. The model can be used for planning and the development of strategies to overcome these challenges.
D A Petrusevich
IOP Conference Series: Materials Science and Engineering, Volume 862; doi:10.1088/1757-899x/862/4/042037

Sciprofile linkJiantao Pu, Joseph Leader, Andriy Bandos, Junli Shi, Pang Du, Juezhao Yu, Bohan Yang, Shi Ke, Youmin Guo, Jessica B. Field, et al.
European Radiology pp 1-7; doi:10.1007/s00330-020-06956-w

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Sciprofile linkSrijit Das, Sakthiswary Rajalingham
Indian Journal of Surgery pp 1-2; doi:10.1007/s12262-020-02411-8

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MMW - Fortschritte der Medizin, Volume 162, pp 11-11; doi:10.1007/s15006-020-0498-4

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MMW - Fortschritte der Medizin, Volume 162, pp 35-35; doi:10.1007/s15006-020-0518-4

Gerd W. Zimmermann
MMW - Fortschritte der Medizin, Volume 162, pp 30-31; doi:10.1007/s15006-020-0512-x

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