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      Novel Therapeutics Identification for Fibrosis in Renal Allograft Using Integrative Informatics Approach

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          Abstract

          Chronic allograft damage, defined by interstitial fibrosis and tubular atrophy (IF/TA), is a leading cause of allograft failure. Few effective therapeutic options are available to prevent the progression of IF/TA. We applied a meta-analysis approach on IF/TA molecular datasets in Gene Expression Omnibus to identify a robust 85-gene signature, which was used for computational drug repurposing analysis. Among the top ranked compounds predicted to be therapeutic for IF/TA were azathioprine, a drug to prevent acute rejection in renal transplantation, and kaempferol and esculetin, two drugs not previously described to have efficacy for IF/TA. We experimentally validated the anti-fibrosis effects of kaempferol and esculetin using renal tubular cells in vitro and in vivo in a mouse Unilateral Ureteric Obstruction (UUO) model. Kaempferol significantly attenuated TGF-β1-mediated profibrotic pathways in vitro and in vivo, while esculetin significantly inhibited Wnt/β-catenin pathway in vitro and in vivo. Histology confirmed significantly abrogated fibrosis by kaempferol and esculetin in vivo. We developed an integrative computational framework to identify kaempferol and esculetin as putatively novel therapies for IF/TA and provided experimental evidence for their therapeutic activities in vitro and in vivo using preclinical models. The findings suggest that both drugs might serve as therapeutic options for IF/TA.

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          Most cited references83

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          In silico prediction of protein-protein interactions in human macrophages

          Background: Protein-protein interaction (PPI) network analyses are highly valuable in deciphering and understanding the intricate organisation of cellular functions. Nevertheless, the majority of available protein-protein interaction networks are context-less, i.e. without any reference to the spatial, temporal or physiological conditions in which the interactions may occur. In this work, we are proposing a protocol to infer the most likely protein-protein interaction (PPI) network in human macrophages. Results: We integrated the PPI dataset from the Agile Protein Interaction DataAnalyzer (APID) with different meta-data to infer a contextualized macrophage-specific interactome using a combination of statistical methods. The obtained interactome is enriched in experimentally verified interactions and in proteins involved in macrophage-related biological processes (i.e. immune response activation, regulation of apoptosis). As a case study, we used the contextualized interactome to highlight the cellular processes induced upon Mycobacterium tuberculosis infection. Conclusion: Our work confirms that contextualizing interactomes improves the biological significance of bioinformatic analyses. More specifically, studying such inferred network rather than focusing at the gene expression level only, is informative on the processes involved in the host response. Indeed, important immune features such as apoptosis are solely highlighted when the spotlight is on the protein interaction level.
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            Taking dendritic cells into medicine.

            Dendritic cells (DCs) orchestrate a repertoire of immune responses that bring about resistance to infection and silencing or tolerance to self. In the settings of infection and cancer, microbes and tumours can exploit DCs to evade immunity, but DCs also can generate resistance, a capacity that is readily enhanced with DC-targeted vaccines. During allergy, autoimmunity and transplant rejection, DCs instigate unwanted responses that cause disease, but, again, DCs can be harnessed to silence these conditions with novel therapies. Here we present some medical implications of DC biology that account for illness and provide opportunities for prevention and therapy.
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              ImageJ for microscopy.

              ImageJ is an essential tool for us that fulfills most of our routine image processing and analysis requirements. The near-comprehensive range of import filters that allow easy access to image and meta-data, a broad suite processing and analysis routine, and enthusiastic support from a friendly mailing list are invaluable for all microscopy labs and facilities-not just those on a budget.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                04 January 2017
                2017
                : 7
                : 39487
                Affiliations
                [1 ]Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai , 770 exington Ave., New York, NY 10065, USA
                [2 ]Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place , New York, NY 10029, USA
                [3 ]Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai , 1255 5th Avenue, New York, NY 10029, USA
                [4 ]Section of Nephrology, University of Ulm , Albert-Einstein-Allee 23, Ulm, 89081 Germany
                [5 ]Department of Health Policy and Research, Icahn School of Medicine at Mount Sinai, One Gustave L Levy Place , New York, NY 10029, USA.
                [6 ]Institute for Next Generation Healthcare , Icahn School of Medicine at Mount Sinai.
                Author notes
                [*]

                These authors contributed equally to this work.

                Article
                srep39487
                10.1038/srep39487
                5209709
                28051114
                4f63a168-390e-4143-87b5-b379219c72d5
                Copyright © 2017, The Author(s)

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 02 June 2016
                : 21 November 2016
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