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      MicroRNAs regulating cluster of differentiation 46 ( CD46) in cardioembolic and non-cardioembolic stroke

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          Abstract

          Ischemic stroke is a major cause of mortality and morbidity globally. Among the ischemic stroke subtypes, cardioembolic stroke is with poor functional outcome (Modified Rankin score ≥ 2). Early diagnosis of cardioembolic stroke will prove beneficial. This study examined the microRNAs targeting cluster of differentiation 46 (CD46), a potential biomarker for cardioembolic stroke. CD46 mRNA level was shown to be differentially expressed ( p < 0.001) between cardioembolic stroke (median = 1.32) and non-cardioembolic stroke subtypes (large artery stroke median = 5.05; small vessel stroke median = 6.45). Bioinformatic search showed that miR-19a, -20a, -185 and -374b were found to target CD46 mRNA and further verified by luciferase reporter assay. The levels of miRNAs targeting CD46 were significantly reduced ( p < 0.05) in non-cardioembolic stroke patients (large artery stroke median: miR-19a = 0.63, miR-20a = 0.42, miR-185 = 0.32, miR-374b = 0.27; small artery stroke median: miR-19a = 0.07, miR-20a = 0.06, miR-185 = 0.07, miR-374b = 0.05) as compared to cardioembolic stroke patients (median: miR-19a = 2.69, miR-20a = 1.36, miR-185 = 1.05, miR-374b = 1.23). ROC curve showed that the miRNAs could distinguish cardioembolic stroke from non-cardioembolic stroke with better AUC value as compared to CD46. Endogenous expression of CD46 in Human Umbilical Vein Endothelial Cells (HUVECs) were found to be regulated by miR-19a and miR-20a. Thus implicating that miR-19a and -20a may play a role in pathogenesis of cardioembolic stroke, possibly via the endothelial cells.

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          NIH Image to ImageJ: 25 years of image analysis.

          For the past 25 years NIH Image and ImageJ software have been pioneers as open tools for the analysis of scientific images. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.
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            Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites

            mirSVR is a new machine learning method for ranking microRNA target sites by a down-regulation score. The algorithm trains a regression model on sequence and contextual features extracted from miRanda-predicted target sites. In a large-scale evaluation, miRanda-mirSVR is competitive with other target prediction methods in identifying target genes and predicting the extent of their downregulation at the mRNA or protein levels. Importantly, the method identifies a significant number of experimentally determined non-canonical and non-conserved sites.
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              MicroRNA Targets in Drosophila

              Additional data files Additional data file 1, 2, 3 and 4. Supplementary Material Additional data file 1 Additional data file 1 Click here for additional data file Additional data file 2 Additional data file 2 Click here for additional data file Additional data file 3 Additional data file 3 Click here for additional data file Additional data file 4 Additional data file 4 Click here for additional data file
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                15 February 2017
                2017
                : 12
                : 2
                : e0172131
                Affiliations
                [1 ]Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
                [2 ]Department of Medicine, Faculty of Medicine, University Malaya, Kuala Lumpur, Malaysia
                [3 ]Department of Biochemistry, Faculty of Medicine, MAHSA University, Kuala Lumpur, Malaysia
                [4 ]Department of Anatomy and Developmental Biology, School of Biomedical Sciences, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, Victoria, Australia
                [5 ]Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, MD3, Singapore
                Institut d'Investigacions Biomediques de Barcelona, SPAIN
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: KJ AA KST.

                • Formal analysis: JRT AA.

                • Funding acquisition: KJ PT-HW KST.

                • Investigation: JRT AA.

                • Methodology: KJ AA KST.

                • Resources: KST FLY CWW.

                • Validation: JRT AA.

                • Writing – original draft: JRT.

                • Writing – review & editing: KJ PT-HW AA.

                Article
                PONE-D-16-33680
                10.1371/journal.pone.0172131
                5310775
                28199366
                19bb2821-7572-4e98-9203-4510bc76963b
                © 2017 Tan et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 23 August 2016
                : 31 January 2017
                Page count
                Figures: 3, Tables: 3, Pages: 16
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100001381, National Research Foundation Singapore;
                Award ID: R-184-002-165-281
                Award Recipient : Peter T.-H. Wong
                Funded by: funder-id http://dx.doi.org/10.13039/501100001349, National Medical Research Council;
                Award ID: R-183-000-230-275
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100001349, National Medical Research Council;
                Award ID: R-183-000-290-213
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100004386, Universiti Malaya;
                Award ID: E0067
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100004386, Universiti Malaya;
                Award ID: E0036
                Award Recipient :
                This work was supported by the research grants from National Research Foundation (NRF): R-184-002-165-281, National Medical Research Council (NMRC/EDG): R-183-000-230-275, and the National Medical Research Council (NMRC/IRG): R-183-000-290-213, Singapore; and the University of Malaya (UM/HIR): E0067 & E0036. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and life sciences
                Genetics
                Gene expression
                Gene regulation
                MicroRNAs
                Biology and life sciences
                Biochemistry
                Nucleic acids
                RNA
                Non-coding RNA
                MicroRNAs
                Medicine and Health Sciences
                Neurology
                Cerebrovascular Diseases
                Stroke
                Ischemic Stroke
                Medicine and Health Sciences
                Vascular Medicine
                Stroke
                Ischemic Stroke
                Medicine and Health Sciences
                Neurology
                Cerebrovascular Diseases
                Stroke
                Medicine and Health Sciences
                Vascular Medicine
                Stroke
                Biology and Life Sciences
                Anatomy
                Cardiovascular Anatomy
                Blood Vessels
                Arteries
                Medicine and Health Sciences
                Anatomy
                Cardiovascular Anatomy
                Blood Vessels
                Arteries
                Biology and Life Sciences
                Cell Biology
                Cellular Types
                Animal Cells
                Epithelial Cells
                Endothelial Cells
                Biology and Life Sciences
                Anatomy
                Biological Tissue
                Epithelium
                Epithelial Cells
                Endothelial Cells
                Medicine and Health Sciences
                Anatomy
                Biological Tissue
                Epithelium
                Epithelial Cells
                Endothelial Cells
                Biology and Life Sciences
                Cell Biology
                Signal Transduction
                Cell Signaling
                Calcium Signaling
                Biology and Life Sciences
                Cell Biology
                Signal Transduction
                Cell Signaling
                Signaling Cascades
                WNT Signaling Cascade
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Gene Ontologies
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Analysis
                Gene Ontologies
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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