Comparing Spatial Expression Dynamics of Bovine
Total Page：16
File Type：pdf, Size：1020Kb
Load more
Recommended publications
-
KLF2 Induced
UvA-DARE (Digital Academic Repository) The transcription factor KLF2 in vascular biology Boon, R.A. Publication date 2008 Link to publication Citation for published version (APA): Boon, R. A. (2008). The transcription factor KLF2 in vascular biology. General rights It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulations If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: https://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. UvA-DARE is a service provided by the library of the University of Amsterdam (https://dare.uva.nl) Download date:23 Sep 2021 Supplementary data: Genes induced by KLF2 Dekker et al. LocusLink Accession Gene Sequence Description Fold p-value ID number symbol change (FDR) 6654 AK022099 SOS1 cDNA FLJ12037 fis, clone HEMBB1001921. 100.00 5.9E-09 56999 AF086069 ADAMTS9 full length insert cDNA clone YZ35C05. 100.00 1.2E-09 6672 AF085934 SP100 full length insert cDNA clone YR57D07. 100.00 6.7E-13 9031 AF132602 BAZ1B Williams Syndrome critical region WS25 mRNA, partial sequence. -
Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model
Downloaded from http://www.jimmunol.org/ by guest on September 25, 2021 T + is online at: average * The Journal of Immunology , 34 of which you can access for free at: 2016; 197:1477-1488; Prepublished online 1 July from submission to initial decision 4 weeks from acceptance to publication 2016; doi: 10.4049/jimmunol.1600589 http://www.jimmunol.org/content/197/4/1477 Molecular Profile of Tumor-Specific CD8 Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. Waugh, Sonia M. Leach, Brandon L. Moore, Tullia C. Bruno, Jonathan D. Buhrman and Jill E. Slansky J Immunol cites 95 articles Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html http://www.jimmunol.org/content/suppl/2016/07/01/jimmunol.160058 9.DCSupplemental This article http://www.jimmunol.org/content/197/4/1477.full#ref-list-1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material References Permissions Email Alerts Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2016 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of September 25, 2021. The Journal of Immunology Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. -
Regulation of Leukocytes by Tspanc8 Tetraspanins And
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by University of Birmingham Research Portal University of Birmingham Regulation of Leukocytes by TspanC8 Tetraspanins and the “Molecular Scissor” ADAM10 Matthews, Alexandra; Koo, Chek Ziu; Szyroka, Justyna; Harrison, Neale; Kanhere, Aditi; Tomlinson, Michael DOI: 10.3389/fimmu.2018.01451 License: Creative Commons: Attribution (CC BY) Document Version Publisher's PDF, also known as Version of record Citation for published version (Harvard): Matthews, A, Koo, CZ, Szyroka, J, Harrison, N, Kanhere, A & Tomlinson, M 2018, 'Regulation of Leukocytes by TspanC8 Tetraspanins and the “Molecular Scissor” ADAM10', Frontiers in immunology, vol. 9, 1451. https://doi.org/10.3389/fimmu.2018.01451 Link to publication on Research at Birmingham portal Publisher Rights Statement: Matthews AL, Koo CZ, Szyroka J, Harrison N, Kanhere A and Tomlinson MG (2018) Regulation of Leukocytes by TspanC8 Tetraspanins and the “Molecular Scissor” ADAM10. Front. Immunol. 9:1451. doi: 10.3389/fimmu.2018.01451. First published by Frontiers Media. Checked 30/7/18. General rights Unless a licence is specified above, all rights (including copyright and moral rights) in this document are retained by the authors and/or the copyright holders. The express permission of the copyright holder must be obtained for any use of this material other than for purposes permitted by law. •Users may freely distribute the URL that is used to identify this publication. •Users may download and/or print one copy of the publication from the University of Birmingham research portal for the purpose of private study or non-commercial research. -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
1 Metabolic Dysfunction Is Restricted to the Sciatic Nerve in Experimental
Page 1 of 255 Diabetes Metabolic dysfunction is restricted to the sciatic nerve in experimental diabetic neuropathy Oliver J. Freeman1,2, Richard D. Unwin2,3, Andrew W. Dowsey2,3, Paul Begley2,3, Sumia Ali1, Katherine A. Hollywood2,3, Nitin Rustogi2,3, Rasmus S. Petersen1, Warwick B. Dunn2,3†, Garth J.S. Cooper2,3,4,5* & Natalie J. Gardiner1* 1 Faculty of Life Sciences, University of Manchester, UK 2 Centre for Advanced Discovery and Experimental Therapeutics (CADET), Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, UK 3 Centre for Endocrinology and Diabetes, Institute of Human Development, Faculty of Medical and Human Sciences, University of Manchester, UK 4 School of Biological Sciences, University of Auckland, New Zealand 5 Department of Pharmacology, Medical Sciences Division, University of Oxford, UK † Present address: School of Biosciences, University of Birmingham, UK *Joint corresponding authors: Natalie J. Gardiner and Garth J.S. Cooper Email: [email protected]; [email protected] Address: University of Manchester, AV Hill Building, Oxford Road, Manchester, M13 9PT, United Kingdom Telephone: +44 161 275 5768; +44 161 701 0240 Word count: 4,490 Number of tables: 1, Number of figures: 6 Running title: Metabolic dysfunction in diabetic neuropathy 1 Diabetes Publish Ahead of Print, published online October 15, 2015 Diabetes Page 2 of 255 Abstract High glucose levels in the peripheral nervous system (PNS) have been implicated in the pathogenesis of diabetic neuropathy (DN). However our understanding of the molecular mechanisms which cause the marked distal pathology is incomplete. Here we performed a comprehensive, system-wide analysis of the PNS of a rodent model of DN. -
A CRISPR-Cas9–Engineered Mouse Model for GPI-Anchor Deficiency Mirrors Human Phenotypes and Exhibits Hippocampal Synaptic Dysfunctions
A CRISPR-Cas9–engineered mouse model for GPI-anchor deficiency mirrors human phenotypes and exhibits hippocampal synaptic dysfunctions Miguel Rodríguez de los Santosa,b,c,d, Marion Rivalane,f, Friederike S. Davidd,g, Alexander Stumpfh, Julika Pitschi,j, Despina Tsortouktzidisi, Laura Moreno Velasquezh, Anne Voigth, Karl Schillingk, Daniele Matteil, Melissa Longe,f, Guido Vogta,c, Alexej Knausd, Björn Fischer-Zirnsaka,c, Lars Wittlerm, Bernd Timmermannn, Peter N. Robinsono,p, Denise Horna, Stefan Mundlosa,c, Uwe Kornaka,c,q, Albert J. Beckeri, Dietmar Schmitzh, York Wintere,f, and Peter M. Krawitzd,1 aInstitute for Medical Genetics and Human Genetics, Charité–Universitätsmedizin Berlin, 13353 Berlin, Germany; bBerlin-Brandenburg School for Regenerative Therapies, Charité-Universitätsmedizin Berlin, 13353 Berlin, Germany; cResearch Group Development and Disease, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany; dInstitute for Genomic Statistics and Bioinformatics, University of Bonn, 53127 Bonn, Germany; eAnimal Outcome Core Facility of the NeuroCure Center, Charité–Universitätsmedizin Berlin, 10117 Berlin, Germany; fInstitute of Cognitive Neurobiology, Humboldt University, 10117 Berlin, Germany; gInstitute of Human Genetics, Faculty of Medicine, University Hospital Bonn, 53127 Bonn, Germany; hNeuroscience Research Center, Charité–Universitätsmedizin Berlin, 10117 Berlin, Germany; iSection for Translational Epilepsy Research, Department of Neuropathology, University Hospital Bonn, 53127 Bonn, Germany; jDepartment of Epileptology, -
Supplementary Table 1: Adhesion Genes Data Set
Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like, -
Cellular and Molecular Signatures in the Disease Tissue of Early
Cellular and Molecular Signatures in the Disease Tissue of Early Rheumatoid Arthritis Stratify Clinical Response to csDMARD-Therapy and Predict Radiographic Progression Frances Humby1,* Myles Lewis1,* Nandhini Ramamoorthi2, Jason Hackney3, Michael Barnes1, Michele Bombardieri1, Francesca Setiadi2, Stephen Kelly1, Fabiola Bene1, Maria di Cicco1, Sudeh Riahi1, Vidalba Rocher-Ros1, Nora Ng1, Ilias Lazorou1, Rebecca E. Hands1, Desiree van der Heijde4, Robert Landewé5, Annette van der Helm-van Mil4, Alberto Cauli6, Iain B. McInnes7, Christopher D. Buckley8, Ernest Choy9, Peter Taylor10, Michael J. Townsend2 & Costantino Pitzalis1 1Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK. Departments of 2Biomarker Discovery OMNI, 3Bioinformatics and Computational Biology, Genentech Research and Early Development, South San Francisco, California 94080 USA 4Department of Rheumatology, Leiden University Medical Center, The Netherlands 5Department of Clinical Immunology & Rheumatology, Amsterdam Rheumatology & Immunology Center, Amsterdam, The Netherlands 6Rheumatology Unit, Department of Medical Sciences, Policlinico of the University of Cagliari, Cagliari, Italy 7Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow G12 8TA, UK 8Rheumatology Research Group, Institute of Inflammation and Ageing (IIA), University of Birmingham, Birmingham B15 2WB, UK 9Institute of -
Identification of Arylsulfatase E Mutations, Functional Analysis of Novel Missense Alleles, and Determination of Potential Phenocopies
ORIGINAL RESEARCH ARTICLE © American College of Medical Genetics and Genomics A prospective study of brachytelephalangic chondrodysplasia punctata: identification of arylsulfatase E mutations, functional analysis of novel missense alleles, and determination of potential phenocopies Claudia Matos-Miranda, MSc, MD1, Graeme Nimmo, MSc1, Bradley Williams, MGC, CGC2, Carolyn Tysoe, PhD3, Martina Owens, BS3, Sherri Bale, PhD2 and Nancy Braverman, MS, MD1,4 Purpose: The only known genetic cause of brachytelephalangic Results: In this study, 58% of males had ARSE mutations. All mutant chondrodysplasia punctata is X-linked chondrodysplasia punctata 1 alleles had negligible arylsulfatase E activity. There were no obvi- (CDPX1), which results from a deficiency of arylsulfatase E (ARSE). ous genotype–phenotype correlations. Maternal etiologies were not Historically, ARSE mutations have been identified in only 50% of reported in most patients. male patients, and it was proposed that the remainder might rep- resent phenocopies due to maternal–fetal vitamin K deficiency and Conclusion: CDPX1 is caused by loss of arylsulfatase E activ- maternal autoimmune diseases. ity. Around 40% of male patients with brachytelephalangic chon- drodysplasia punctata do not have detectable ARSE mutations or Methods: To further evaluate causes of brachytelephalangic chon- known maternal etiological factors. Improved understanding of drodysplasia punctata, we established a Collaboration Education and arylsulfatase E function is predicted to illuminate other etiologies for Test Translation program for CDPX1 from 2008 to 2010. Of the 29 brachytelephalangic chondrodysplasia punctata. male probands identified, 17 had ARSE mutations that included 10 novel missense alleles and one single-codon deletion. To determine Genet Med 2013:15(8):650–657 pathogenicity of these and additional missense alleles, we transiently expressed them in COS cells and measured arylsulfatase E activity Key Words: arylsulfatase E; brachytelephalangic chondrodysplasia using the artificial substrate, 4-methylumbelliferyl sulfate. -
Supplemental Materials Supplemental Table 1
Electronic Supplementary Material (ESI) for RSC Advances. This journal is © The Royal Society of Chemistry 2016 Supplemental Materials Supplemental Table 1. The differentially expressed proteins from rat pancreas identified by proteomics (SAP vs. SO) No. Protein name Gene name ratio P value 1 Metallothionein Mt1m 3.35 6.34E-07 2 Neutrophil antibiotic peptide NP-2 Defa 3.3 8.39E-07 3 Ilf2 protein Ilf2 3.18 1.75E-06 4 Numb isoform o/o rCG 3.12 2.73E-06 5 Lysozyme Lyz2 3.01 5.63E-06 6 Glucagon Gcg 2.89 1.17E-05 7 Serine protease HTRA1 Htra1 2.75 2.97E-05 8 Alpha 2 macroglobulin cardiac isoform (Fragment) 2.75 2.97E-05 9 Myosin IF (Predicted) Myo1f 2.65 5.53E-05 10 Neuroendocrine secretory protein 55 Gnas 2.61 7.60E-05 11 Matrix metallopeptidase 8 Mmp8 2.57 9.47E-05 12 Protein Tnks1bp1 Tnks1bp1 2.53 1.22E-04 13 Alpha-parvin Parva 2.47 1.78E-04 14 C4b-binding protein alpha chain C4bpa 2.42 2.53E-04 15 Protein KTI12 homolog Kti12 2.41 2.74E-04 16 Protein Rab11fip5 Rab11fip5 2.41 2.84E-04 17 Protein Mcpt1l3 Mcpt1l3 2.33 4.43E-04 18 Phospholipase B-like 1 Plbd1 2.33 4.76E-04 Aldehyde dehydrogenase (NAD), cytosolic 19 2.32 4.93E-04 (Fragments) 20 Protein Dpy19l2 Dpy19l2 2.3 5.68E-04 21 Regenerating islet-derived 3 alpha, isoform CRA_a Reg3a 2.27 6.74E-04 22 60S acidic ribosomal protein P1 Rplp1 2.26 7.22E-04 23 Serum albumin Alb 2.25 7.98E-04 24 Ribonuclease 4 Rnase4 2.24 8.25E-04 25 Cct-5 protein (Fragment) Cct5 2.24 8.52E-04 26 Protein S100-A9 S100a9 2.22 9.71E-04 27 Creatine kinase M-type Ckm 2.21 1.00E-03 28 Protein Larp4b Larp4b 2.18 1.25E-03 -
Chromosome 14 Transfer and Functional Studies Identify a Candidate Tumor Suppressor Gene, Mirror Image Polydactyly 1, in Nasopharyngeal Carcinoma
Chromosome 14 transfer and functional studies identify a candidate tumor suppressor gene, Mirror image polydactyly 1, in nasopharyngeal carcinoma Arthur Kwok Leung Cheunga, Hong Lok Lungb, Josephine Mun Yee Kob, Yue Chenga,c, Eric J. Stanbridged, Eugene R. Zabarovskye, John M. Nichollsf, Daniel Chuab, Sai Wah Tsaog, Xin-Yuan Guanb, and Maria Li Lungb,1 aDepartment of Biology and Center for Cancer Research, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong (SAR), People’s Republic of China; bDepartment of Clinical Oncology, University of Hong Kong, Pokfulam, Hong Kong (SAR), People’s Republic of China; cDepartment of Biology, City of Hope, Beckman Research Institute, Duarte,CA 91010; dDepartment of Microbiology and Molecular Genetics, University of California, Irvine, CA 92697; eDepartment of Microbiology, Tumor and Cell Biology, Karolinska Institute, Stockholm, Sweden; and Departments of fPathology and gAnatomy, University of Hong Kong, Pokfulam, Hong Kong (SAR), People’s Republic of China Edited by George Klein, Karolinska Institutet, Stockholm, Sweden, and approved July 7, 2009 (received for review January 7, 2009) Chromosome 14 allelic loss is common in nasopharyngeal carcinoma particular interest to us that chromosome 14 loss is associated with (NPC) and may reflect essential tumor suppressor gene loss in tumor- cancer metastasis in breast tumors (15) and with poor clinical prognosis igenesis. An intact chromosome 14 was transferred to an NPC cell line for other head and neck cancers (16). Thus, it is possible that a using a microcell-mediated chromosome transfer approach. Microcell chromosome 14 TSG may be a useful prognostic marker in NPC. hybrids (MCHs) containing intact exogenously transferred chromo- In this study, we obtained functional evidence showing definitively some 14 were tumor suppressive in athymic mice, demonstrating that that chromosome 14 is tumor suppressive in NPC. -
System, Method and Software for Calculation of a Cannabis Drug Efficiency Index for the Reduction of Inflammation
International Journal of Molecular Sciences Article System, Method and Software for Calculation of a Cannabis Drug Efficiency Index for the Reduction of Inflammation Nicolas Borisov 1,† , Yaroslav Ilnytskyy 2,3,†, Boseon Byeon 2,3,4,†, Olga Kovalchuk 2,3 and Igor Kovalchuk 2,3,* 1 Moscow Institute of Physics and Technology, 9 Institutsky lane, Dolgoprudny, Moscow Region 141701, Russia; [email protected] 2 Department of Biological Sciences, University of Lethbridge, Lethbridge, AB T1K 3M4, Canada; [email protected] (Y.I.); [email protected] (B.B.); [email protected] (O.K.) 3 Pathway Rx., 16 Sandstone Rd. S., Lethbridge, AB T1K 7X8, Canada 4 Biomedical and Health Informatics, Computer Science Department, State University of New York, 2 S Clinton St, Syracuse, NY 13202, USA * Correspondence: [email protected] † First three authors contributed equally to this research. Abstract: There are many varieties of Cannabis sativa that differ from each other by composition of cannabinoids, terpenes and other molecules. The medicinal properties of these cultivars are often very different, with some being more efficient than others. This report describes the development of a method and software for the analysis of the efficiency of various cannabis extracts to detect the anti-inflammatory properties of the various cannabis extracts. The method uses high-throughput gene expression profiling data but can potentially use other omics data as well. According to the signaling pathway topology, the gene expression profiles are convoluted into the signaling pathway activities using a signaling pathway impact analysis (SPIA) method. The method was tested by inducing inflammation in human 3D epithelial tissues, including intestine, oral and skin, and then exposing these tissues to various extracts and then performing transcriptome analysis.