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      Attenuation of clinical and immunological outcomes during SARS‐CoV‐2 infection by ivermectin

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          Abstract

          The devastating pandemic due to SARS‐CoV‐2 and the emergence of antigenic variants that jeopardize the efficacy of current vaccines create an urgent need for a comprehensive understanding of the pathophysiology of COVID‐19, including the contribution of inflammation to disease. It also warrants for the search of immunomodulatory drugs that could improve disease outcome. Here, we show that standard doses of ivermectin (IVM), an anti‐parasitic drug with potential immunomodulatory activities through the cholinergic anti‐inflammatory pathway, prevent clinical deterioration, reduce olfactory deficit, and limit the inflammation of the upper and lower respiratory tracts in SARS‐CoV‐2‐infected hamsters. Whereas it has no effect on viral load in the airways of infected animals, transcriptomic analyses of infected lungs reveal that IVM dampens type I interferon responses and modulates several other inflammatory pathways. In particular, IVM dramatically reduces the Il‐6/Il‐10 ratio in lung tissue and promotes macrophage M2 polarization, which might account for the more favorable clinical presentation of IVM‐treated animals. Altogether, this study supports the use of immunomodulatory drugs such as IVM, to improve the clinical condition of SARS‐CoV‐2‐infected patients.

          Abstract

          COVID‐19, caused by SARS‐CoV‐2, induces airways and pulmonary symptoms, and in severe cases can lead to respiratory distress and death. This study shows that the modulation of the host's inflammatory response using ivermectin as a repurposed drug, independently of the viral load, strongly diminished the clinical score and severity of the disease (including anosmia) observed in SARS‐CoV‐2‐infected golden hamsters. This study brings the proof‐of‐concept that a chemical therapy using ivermectin can preserve the clinical condition by modulating the inflammatory response, even without antiviral activity.

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          Most cited references101

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            STAR: ultrafast universal RNA-seq aligner.

            Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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              Cutadapt removes adapter sequences from high-throughput sequencing reads

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                Author and article information

                Contributors
                herve.bourhy@pasteur.fr
                Journal
                EMBO Mol Med
                EMBO Mol Med
                10.1002/(ISSN)1757-4684
                EMMM
                embomm
                EMBO Molecular Medicine
                John Wiley and Sons Inc. (Hoboken )
                1757-4676
                1757-4684
                12 July 2021
                09 August 2021
                : 13
                : 8 ( doiID: 10.1002/emmm.v13.8 )
                : e14122
                Affiliations
                [ 1 ] Lyssavirus Epidemiology and Neuropathology Unit Institut Pasteur Paris France
                [ 2 ] Perception and Memory Unit Institut Pasteur CNRS UMR 3571 Paris France
                [ 3 ] Biomics Technological Platform Center for Technological Resources and Research (C2RT) Institut Pasteur Paris France
                [ 4 ] Bioinformatics and Biostatistics Hub Computational Biology Department Institut Pasteur Paris France
                [ 5 ] Biology of Infection Unit Institut Pasteur Inserm U1117 Paris France
                [ 6 ] Nuclear Organization and Oncogenesis Unit Institut Pasteur Paris France
                [ 7 ] Experimental Neuropathology Unit Institut Pasteur Paris France
                [ 8 ] Division of Infectious Diseases and Tropical Medicine Institut Imagine Université de Paris Necker‐Enfants Malades University Hospital AP‐HP Paris France
                [ 9 ] Neuroscience Department Institut Pasteur Collège de France Paris France
                Author notes
                [*] [* ] Corresponding author. Tel: +33 1 45 68 87 85; E‐mail: herve.bourhy@ 123456pasteur.fr

                Author information
                https://orcid.org/0000-0003-0747-7760
                https://orcid.org/0000-0001-5572-6982
                https://orcid.org/0000-0003-0881-4263
                https://orcid.org/0000-0002-5805-1092
                https://orcid.org/0000-0002-5609-4398
                https://orcid.org/0000-0001-5874-4377
                https://orcid.org/0000-0001-6286-1138
                https://orcid.org/0000-0002-4491-1063
                https://orcid.org/0000-0003-0297-1583
                https://orcid.org/0000-0002-2608-5589
                Article
                EMMM202114122
                10.15252/emmm.202114122
                8350903
                34170074
                31e10801-b6d2-464e-af36-af90ae611815
                © 2021 The Authors. Published under the terms of the CC BY 4.0 license

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 22 June 2021
                : 11 February 2021
                : 23 June 2021
                Page count
                Figures: 10, Tables: 0, Pages: 14, Words: 12077
                Funding
                Funded by: Institut Pasteur , doi 10.13039/501100003762;
                Categories
                Article
                Articles
                Custom metadata
                2.0
                09 August 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.4 mode:remove_FC converted:09.08.2021

                Molecular medicine
                coronavirus,inflammation,ivermectin,sars‐cov‐2,viral infections,immunology,microbiology, virology & host pathogen interaction

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