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      Urinary miRNA-27b-3p and miRNA-1228-3p correlate with the progression of Kidney Fibrosis in Diabetic Nephropathy

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          Abstract

          Diabetic Nephropathy (DN) is a chronic complication of diabetes and the primary cause of end stage renal disease. Differential diagnosis for DN requires invasive histological investigation, thus there is need for non-invasive biomarkers to discriminate among different histological lesions in diabetic patients. With the aim to identify a pattern of differentially expressed miRNAs in kidney biopsies of DN patients, we assayed miRNA expression in kidney biopsies from DN patients, diabetic patients with membranous nephropathy and patients with normal histology. Nine miRNAs were differentially expressed among the three groups, and 2 miRNAs (miR-27b-3p and miR-1228-3p) showed interaction with an ubiquitin-conjugating E2 enzyme variant (UBE2v1). UBE2v1 mediates the formation of lysine 63-linked ubiquitin chains, a mechanism we previously showed as involved in DN kidney fibrosis. Both miRNAs were validated as down-regulated in biopsies and urines of DN patients, possibly affected by DNA methylation. Interestingly, the urinary levels of both miRNAs could also discriminate among different degrees of renal fibrosis. Finally, we showed that the combined urinary expression of both miRNAs was also able to discriminate DN patients from other glomerulonephritides in diabetic patients. In conclusion we identified two miRNAs potentially useful as candidate biomarkers of tubular-interstitial fibrosis in diabetic patients with DN.

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          Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

          The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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            miRDB: an online resource for microRNA target prediction and functional annotations

            MicroRNAs (miRNAs) are small non-coding RNAs that are extensively involved in many physiological and disease processes. One major challenge in miRNA studies is the identification of genes regulated by miRNAs. To this end, we have developed an online resource, miRDB (http://mirdb.org), for miRNA target prediction and functional annotations. Here, we describe recently updated features of miRDB, including 2.1 million predicted gene targets regulated by 6709 miRNAs. In addition to presenting precompiled prediction data, a new feature is the web server interface that allows submission of user-provided sequences for miRNA target prediction. In this way, users have the flexibility to study any custom miRNAs or target genes of interest. Another major update of miRDB is related to functional miRNA annotations. Although thousands of miRNAs have been identified, many of the reported miRNAs are not likely to play active functional roles or may even have been falsely identified as miRNAs from high-throughput studies. To address this issue, we have performed combined computational analyses and literature mining, and identified 568 and 452 functional miRNAs in humans and mice, respectively. These miRNAs, as well as associated functional annotations, are presented in the FuncMir Collection in miRDB.
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              miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions

              Abstract MicroRNAs (miRNAs) are small non-coding RNAs of ∼ 22 nucleotides that are involved in negative regulation of mRNA at the post-transcriptional level. Previously, we developed miRTarBase which provides information about experimentally validated miRNA-target interactions (MTIs). Here, we describe an updated database containing 422 517 curated MTIs from 4076 miRNAs and 23 054 target genes collected from over 8500 articles. The number of MTIs curated by strong evidence has increased ∼1.4-fold since the last update in 2016. In this updated version, target sites validated by reporter assay that are available in the literature can be downloaded. The target site sequence can extract new features for analysis via a machine learning approach which can help to evaluate the performance of miRNA-target prediction tools. Furthermore, different ways of browsing enhance user browsing specific MTIs. With these improvements, miRTarBase serves as more comprehensively annotated, experimentally validated miRNA-target interactions databases in the field of miRNA related research. miRTarBase is available at http://miRTarBase.mbc.nctu.edu.tw/.
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                Author and article information

                Contributors
                paola.pontrelli@uniba.it
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                6 August 2019
                6 August 2019
                2019
                : 9
                : 11357
                Affiliations
                [1 ]ISNI 0000 0001 0120 3326, GRID grid.7644.1, Department of Emergency and Organ Transplantation - Nephrology Unit, , University of Bari Aldo Moro, ; Bari, Italy
                [2 ]ISNI 0000 0001 0120 3326, GRID grid.7644.1, Department of Emergency and Organ Transplantation – Section of Internal Medicine, Endocrinology, Andrology and Metabolic Disease, , University of Bari Aldo Moro, ; Bari, Italy
                [3 ]ISNI 0000 0001 0120 3326, GRID grid.7644.1, Department of Basic Medical Sciences, Neurosciences and Sense Organs, , University of Bari Aldo Moro, ; Bari, Italy
                Author information
                http://orcid.org/0000-0002-5132-6532
                http://orcid.org/0000-0001-7372-2678
                Article
                47778
                10.1038/s41598-019-47778-1
                6684817
                31388051
                75c5754c-3ca9-4dca-b7f8-b2d6cf687e6c
                © The Author(s) 2019

                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
                : 21 February 2019
                : 22 July 2019
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100003196, Ministero della Salute (Ministry of Health, Italy);
                Award ID: 245/RF-2009-1470765
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100010661, EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020);
                Award ID: 115974-BEAt-DKD
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2019

                Uncategorized
                renal fibrosis,molecular medicine
                Uncategorized
                renal fibrosis, molecular medicine

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