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      Repeated exposure with short-term behavioral stress resolves pre-existing stress-induced depressive-like behavior in mice

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          Abstract

          Chronic stress induces adaptive changes in the brain via the cumulative action of glucocorticoids, which is associated with mood disorders. Here we show that repeated daily five-minute restraint resolves pre-existing stress-induced depressive-like behavior in mice. Repeated injection of glucocorticoids in low doses mimics the anti-depressive effects of short-term stress. Repeated exposure to short-term stress and injection of glucocorticoids activate neurons in largely overlapping regions of the brain, as shown by c-Fos staining, and reverse distinct stress-induced gene expression profiles. Chemogenetic inhibition of neurons in the prelimbic cortex projecting to the nucleus accumbens, basolateral amygdala, or bed nucleus of the stria terminalis results in anti-depressive effects similarly to short-term stress exposure, while only inhibition of neurons in the prelimbic cortex projecting to the bed nucleus of the stria terminalis rescues defective glucocorticoid release. In summary, we show that short-term stress can reverse adaptively altered stress gains and resolve stress-induced depressive-like behavior.

          Abstract

          Chronic stress induces maladaptive changes in the neural networks and it’s associated with mood disorders. Here, the authors show that repeated exposure to short-term stress can resolve pre-existing chronic stress induced depressive-like behaviour in mice.

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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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            Individual differences in two emotion regulation processes: Implications for affect, relationships, and well-being.

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              Cytoscape stringApp: Network analysis and visualization of proteomics data

              Protein networks have become a popular tool for analyzing and visualizing the often long lists of proteins or genes obtained from proteomics and other high-throughput technologies. One of the most popular sources of such networks is the STRING database, which provides protein networks for more than 2000 organisms, including both physical interactions from experimental data and functional associations from curated pathways, automatic text mining, and prediction methods. However, its web interface is mainly intended for inspection of small networks and their underlying evidence. The Cytoscape software, on the other hand, is much better suited for working with large networks and offers greater flexibility in terms of network analysis, import, and visualization of additional data. To include both resources in the same workflow, we created stringApp, a Cytoscape app that makes it easy to import STRING networks into Cytoscape, retains the appearance and many of the features of STRING, and integrates data from associated databases. Here, we introduce many of the stringApp features and show how they can be used to carry out complex network analysis and visualization tasks on a typical proteomics data set, all through the Cytoscape user interface. stringApp is freely available from the Cytoscape app store: http://apps.cytoscape.org/apps/stringapp .
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                Author and article information

                Contributors
                plhan@ewha.ac.kr
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                18 November 2021
                18 November 2021
                2021
                : 12
                : 6682
                Affiliations
                [1 ]GRID grid.255649.9, ISNI 0000 0001 2171 7754, Department of Brain and Cognitive Sciences, Scranton College, , Ewha Womans University, ; Seoul, 03760 Republic of Korea
                [2 ]GRID grid.255649.9, ISNI 0000 0001 2171 7754, Department of Chemistry and Nano Science, College of Natural Science, , Ewha Womans University, ; Seoul, 03760 Republic of Korea
                Author information
                http://orcid.org/0000-0001-5881-964X
                http://orcid.org/0000-0001-7277-0248
                http://orcid.org/0000-0002-1735-6746
                Article
                26968
                10.1038/s41467-021-26968-4
                8602389
                34795225
                bf49e282-30dd-49aa-81e2-11fee98ae175
                © The Author(s) 2021

                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/.

                History
                : 8 October 2020
                : 28 October 2021
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100003621, Ministry of Science, ICT and Future Planning (MSIP);
                Award ID: 2021R1A2B5B02002245
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                neural circuits,stress and resilience,molecular neuroscience
                Uncategorized
                neural circuits, stress and resilience, molecular neuroscience

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