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      Apoptotic vesicles restore liver macrophage homeostasis to counteract type 2 diabetes

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          Abstract

          Apoptosis is a naturally occurring process generating plenty of apoptotic vesicles (apoVs), but the feature, fate and function of apoVs remain largely unknown. Notably, as an appealing source for cell therapy, mesenchymal stem cells (MSCs) undergo necessary apoptosis and release apoVs during therapeutic application. In this study, we characterized and used MSC‐derived apoVs to treat type 2 diabetes (T2D) mice, and we found that apoVs were efferocytosed by macrophages and functionally modulated liver macrophage homeostasis to counteract T2D. We showed that apoVs can induce macrophage reprogramming at the transcription level in an efferocytosis‐dependent manner, leading to inhibition of macrophage accumulation and transformation of macrophages towards an anti‐inflammation phenotype in T2D liver. At the molecular level, we discovered that calreticulin (CRT) was exposed on the surface of apoVs to act as a critical ‘eat‐me’ signal mediating apoV efferocytosis and macrophage regulatory effects. Importantly, we demonstrated that CRT‐mediated efferocytosis of MSC‐derived apoVs contributes to T2D therapy with alleviation of T2D phenotypes including glucose intolerance and insulin resistance. These findings uncover that functional efferocytosis of apoVs restores liver macrophage homeostasis and ameliorates T2D.

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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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            Cytoscape: a software environment for integrated models of biomolecular interaction networks.

            Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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              STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

              Abstract Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein–protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein–protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.
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                Author and article information

                Contributors
                liushiyu@vip.163.com
                shisongtao@mail.sysu.edu.cn
                yanjin@fmmu.edu.cn
                Journal
                J Extracell Vesicles
                J Extracell Vesicles
                10.1002/(ISSN)2001-3078
                JEV2
                Journal of Extracellular Vesicles
                John Wiley and Sons Inc. (Hoboken )
                2001-3078
                24 May 2021
                May 2021
                : 10
                : 7 ( doiID: 10.1002/jev2.v10.7 )
                : e12109
                Affiliations
                [ 1 ] State Key Laboratory of Military Stomatology & National Clinical Research Center for Oral Diseases & Shaanxi International Joint Research Center for Oral Diseases Center for Tissue Engineering School of Stomatology The Fourth Military Medical University Xi'an Shaanxi China
                [ 2 ] South China Center of Craniofacial Stem Cell Research Guanghua School and Hospital of Stomatology Sun Yat‐sen University Guangzhou Guangdong China
                [ 3 ] Department of Prosthodontics National Laboratory for Digital and Material Technology of Stomatology Beijing Key Laboratory of Digital Stomatology National Clinical Research Center for Oral Diseases Peking University School and Hospital of Stomatology Beijing China
                [ 4 ] Department of Anatomy and Cell Biology School of Dental Medicine University of Pennsylvania Philadelphia Pennsylvania USA
                Author notes
                [*] [* ] Correspondence

                Prof. Yan Jin, Research and Development Center for Tissue Engineering, School of Stomatology, The Fourth Military Medical University, 145 West Changle Road, Xi'an, Shaanxi 710032, China.

                Email: yanjin@ 123456fmmu.edu.cn

                Prof. Songtao Shi, South China Center of Craniofacial Stem Cell Research, Guanghua School and Hospital of Stomatology, Sun Yat‐sen University, Guangzhou, Guangdong 510055, China.

                Email: shisongtao@ 123456mail.sysu.edu.cn

                Prof. Shiyu Liu, Research and Development Center for Tissue Engineering, School of Stomatology, The Fourth Military Medical University, 145 West Changle Road, Xi'an, Shaanxi 710032, China.

                Email: liushiyu@ 123456vip.163.com

                Author information
                https://orcid.org/0000-0002-2586-1152
                Article
                JEV212109
                10.1002/jev2.12109
                8144839
                34084287
                c7a27d3a-f928-4640-99b9-5183b40626f4
                © 2021 The Authors. Journal of Extracellular Vesicles published by Wiley Periodicals, LLC on behalf of the International Society for Extracellular Vesicles

                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
                : 26 April 2021
                : 31 October 2020
                : 12 May 2021
                Page count
                Figures: 10, Tables: 0, Pages: 26, Words: 16160
                Funding
                Funded by: National Key Research and Development Program of China , open-funder-registry 10.13039/501100012166;
                Award ID: 2016YFC1101400
                Funded by: National Natural Science Foundation of China , open-funder-registry 10.13039/501100001809;
                Award ID: 32000974
                Award ID: 31800817
                Award ID: 81670915
                Award ID: 31870970
                Funded by: Postdoctoral Innovative Talents Support Program of China
                Award ID: BX20190380
                Funded by: General Program of China Postdoctoral Science Foundation
                Award ID: 2019M663986
                Funded by: Guangdong Financial Fund for High‐Caliber Hospital Construction
                Award ID: 174‐2018‐XMZC‐0001‐03‐0125
                Funded by: Pearl River Talent Recruitment Program
                Award ID: 2019ZT08Y485
                Funded by: National Science and Technology Major Project of the Ministry of Science and Technology of China
                Award ID: 2018ZX10302207‐001‐002
                Funded by: Innovative Talent Project of Shaanxi province
                Award ID: 2020KJXX‐057
                Categories
                Research Article
                Research Articles
                Custom metadata
                2.0
                May 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.2 mode:remove_FC converted:25.05.2021

                apoptotic vesicles,calreticulin,efferocytosis,macrophages,mesenchymal stem cells,type 2 diabetes

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