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      Corticotropin-releasing factor neurons in the bed nucleus of the stria terminalis exhibit sex-specific pain encoding in mice

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          Abstract

          The bed nucleus of the stria terminalis (BNST) plays an emerging role in pain regulation. Pharmacological studies have found that inhibiting corticotropin-releasing factor (CRF) signaling in the BNST can selectively mitigate the sensory and affective-motivational components of pain. However, mechanistic insight on the source of CRF that drives BNST responses to these harmful experiences remains unknown. In the present study, we used a series of genetic approaches to show that CRF in the BNST is engaged in the processing and modulation of pain. We conducted cell-type specific in vivo calcium imaging in CRF-Cre mice and found robust and synchronized recruitment of BNST CRF neurons during acute exposures to noxious heat. Distinct patterns of recruitment were observed by sex, as the magnitude and timing of heat responsive activity in BNST CRF neurons differed for male and female mice. We then used a viral approach in Floxed-CRF mice to selectively reduce CRF expression in the BNST and found it decreased nociceptive sensitivity for both sexes and increased paw attending for females. Together, these findings reveal that CRF in the BNST influences multiple facets of the pain experience to impact the sex-specific expression of pain-related behaviors.

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          Fiji: an open-source platform for biological-image analysis.

          Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
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            SciPy 1.0: fundamental algorithms for scientific computing in Python

            SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.
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              Animal research: reporting in vivo experiments: the ARRIVE guidelines.

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                Author and article information

                Contributors
                thomas_kash@med.unc.edu
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                14 June 2021
                14 June 2021
                2021
                : 11
                : 12500
                Affiliations
                [1 ]GRID grid.10698.36, ISNI 0000000122483208, Department of Pharmacology, School of Medicine, , University of North Carolina At Chapel Hill, ; CB 7178 Thurston Bowles Building, 104 Manning Drive, Chapel Hill, NC 27599 USA
                [2 ]GRID grid.10698.36, ISNI 0000000122483208, Bowles Center for Alcohol Studies, , University of North Carolina At Chapel Hill, ; Chapel Hill, NC 27599 USA
                [3 ]GRID grid.10698.36, ISNI 0000000122483208, Curriculum in Pharmacology, School of Medicine, , University of North Carolina At Chapel Hill School of Medicine, ; Chapel Hill, NC 27599 USA
                Article
                91672
                10.1038/s41598-021-91672-8
                8203647
                34127705
                a0b9d99d-f992-4781-8831-c9d5ee8f8cae
                © 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 6 January 2021
                : 24 May 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000027, National Institute on Alcohol Abuse and Alcoholism;
                Award ID: F31AA027129
                Award ID: R21AA027460
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000057, National Institute of General Medical Sciences;
                Award ID: T32GM007040
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                neuroscience,neuronal physiology,sensory processing,stress and resilience
                Uncategorized
                neuroscience, neuronal physiology, sensory processing, stress and resilience

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