Gene List HTG Edgeseq Immune Response Panel
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Investigation of the Immune Receptors CEACAM3 and CEACAM4
Investigation of the human immune receptors CEACAM3 and CEACAM4 Dissertation Zur Erlangung des akademischen Grades eines Doktors der Naturwissenschaften (Dr. rer. nat.) vorgelegt von Julia Delgado Tascón An der Universität Konstanz des Fachbereichs Biologie Konstanz, Oktober 2015 Konstanzer Online-Publikations-System (KOPS) URL: http://nbn-resolving.de/urn:nbn:de:bsz:352-0-306516 Tag der mündlichen Prüfung: 05.11.2015 Vorsitzender und mündlicher Prüfer: Herr Professor Dr. Bürkle 1. Referent und und mündlicher Prüfer: Herr Professor Dr. Hauck 2. Referent und und mündlicher Prüfer: Herr Professor Dr. Tschan, Universität Bern A mi familia Acknowledgements I would like to express my special gratitude to my advisor Prof. Dr. Christof Hauck. His patient guidance and enthusiastic encouragement during these four years of PhD were a crucial aid to my process. I’m very thankful for his willingness and for granting me with his time in search for valuable and constructive suggestions during the planning and development of this research work. This certainly allowed me to grow as a person and as a scientist. I would also like to thank my committee members: to Prof. Dr. Mario Tschan for giving me his academic support at this last phase of my PhD thesis, and to Prof. M.Dr. Alexander Bürkle for his wise advices accompanied with Spanish greetings along this time. My thanks are extended to every member of the AG Hauck as well. To Anne, Susana, Petra and Claudia: thank you very much for your technical and personal guidance during these years. I’m also thankful to my fellow colleagues for countless ‘Kaffeepausen’ full of jokes, nice discussions, and delicious vegan cakes. -
Human and Mouse CD Marker Handbook Human and Mouse CD Marker Key Markers - Human Key Markers - Mouse
Welcome to More Choice CD Marker Handbook For more information, please visit: Human bdbiosciences.com/eu/go/humancdmarkers Mouse bdbiosciences.com/eu/go/mousecdmarkers Human and Mouse CD Marker Handbook Human and Mouse CD Marker Key Markers - Human Key Markers - Mouse CD3 CD3 CD (cluster of differentiation) molecules are cell surface markers T Cell CD4 CD4 useful for the identification and characterization of leukocytes. The CD CD8 CD8 nomenclature was developed and is maintained through the HLDA (Human Leukocyte Differentiation Antigens) workshop started in 1982. CD45R/B220 CD19 CD19 The goal is to provide standardization of monoclonal antibodies to B Cell CD20 CD22 (B cell activation marker) human antigens across laboratories. To characterize or “workshop” the antibodies, multiple laboratories carry out blind analyses of antibodies. These results independently validate antibody specificity. CD11c CD11c Dendritic Cell CD123 CD123 While the CD nomenclature has been developed for use with human antigens, it is applied to corresponding mouse antigens as well as antigens from other species. However, the mouse and other species NK Cell CD56 CD335 (NKp46) antibodies are not tested by HLDA. Human CD markers were reviewed by the HLDA. New CD markers Stem Cell/ CD34 CD34 were established at the HLDA9 meeting held in Barcelona in 2010. For Precursor hematopoetic stem cell only hematopoetic stem cell only additional information and CD markers please visit www.hcdm.org. Macrophage/ CD14 CD11b/ Mac-1 Monocyte CD33 Ly-71 (F4/80) CD66b Granulocyte CD66b Gr-1/Ly6G Ly6C CD41 CD41 CD61 (Integrin b3) CD61 Platelet CD9 CD62 CD62P (activated platelets) CD235a CD235a Erythrocyte Ter-119 CD146 MECA-32 CD106 CD146 Endothelial Cell CD31 CD62E (activated endothelial cells) Epithelial Cell CD236 CD326 (EPCAM1) For Research Use Only. -
Differential Physiological Role of BIN1 Isoforms in Skeletal Muscle Development, Function and Regeneration
bioRxiv preprint doi: https://doi.org/10.1101/477950; this version posted December 11, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. Differential physiological role of BIN1 isoforms in skeletal muscle development, function and regeneration Ivana Prokic1,2,3,4, Belinda Cowling1,2,3,4, Candice Kutchukian5, Christine Kretz1,2,3,4, Hichem Tasfaout1,2,3,4, Josiane Hergueux1,2,3,4, Olivia Wendling1,2,3,4, Arnaud Ferry10, Anne Toussaint1,2,3,4, Christos Gavriilidis1,2,3,4, Vasugi Nattarayan1,2,3,4, Catherine Koch1,2,3,4, Jeanne Lainné6,7, Roy Combe2,3,4,8, Laurent Tiret9, Vincent Jacquemond5, Fanny Pilot-Storck9, Jocelyn Laporte1,2,3,4 1Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Illkirch, France 2Centre National de la Recherche Scientifique (CNRS), UMR7104, Illkirch, France 3Institut National de la Santé et de la Recherche Médicale (INSERM), U1258, Illkirch, France 4Université de Strasbourg, Illkirch, France 5Univ Lyon, Université Claude Bernard Lyon 1, CNRS UMR-5310, INSERM U-1217, Institut NeuroMyoGène, 8 avenue Rockefeller, 69373 Lyon, France 6Sorbonne Université, INSERM, Institute of Myology, Centre of Research in Myology, UMRS 974, F- 75013, Paris, France 7Sorbonne Université, Department of Physiology, UPMC Univ Paris 06, Pitié-Salpêtrière Hospital, F- 75013, Paris, France 8CELPHEDIA-PHENOMIN, Institut Clinique de la Souris (ICS), Illkirch, France 9U955 – IMRB, Team 10 - Biology of the neuromuscular system, Inserm, UPEC, Ecole nationale vétérinaire d’Alfort, Maisons-Alfort, 94700, France 10Sorbonne Université, INSERM, Institute of Myology, Centre of Research in Myology, UMRS 794, F- 75013, Paris, France Correspondence to: [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/477950; this version posted December 11, 2018. -
Global-Scale Analysis of the Dynamic Transcriptional Adaptations Within Skeletal Muscle During Hypertrophic Growth
University of Kentucky UKnowledge Theses and Dissertations--Physiology Physiology 2015 GLOBAL-SCALE ANALYSIS OF THE DYNAMIC TRANSCRIPTIONAL ADAPTATIONS WITHIN SKELETAL MUSCLE DURING HYPERTROPHIC GROWTH Tyler Kirby University of Kentucky, [email protected] Right click to open a feedback form in a new tab to let us know how this document benefits ou.y Recommended Citation Kirby, Tyler, "GLOBAL-SCALE ANALYSIS OF THE DYNAMIC TRANSCRIPTIONAL ADAPTATIONS WITHIN SKELETAL MUSCLE DURING HYPERTROPHIC GROWTH" (2015). Theses and Dissertations--Physiology. 22. https://uknowledge.uky.edu/physiology_etds/22 This Doctoral Dissertation is brought to you for free and open access by the Physiology at UKnowledge. It has been accepted for inclusion in Theses and Dissertations--Physiology by an authorized administrator of UKnowledge. For more information, please contact [email protected]. STUDENT AGREEMENT: I represent that my thesis or dissertation and abstract are my original work. Proper attribution has been given to all outside sources. I understand that I am solely responsible for obtaining any needed copyright permissions. I have obtained needed written permission statement(s) from the owner(s) of each third-party copyrighted matter to be included in my work, allowing electronic distribution (if such use is not permitted by the fair use doctrine) which will be submitted to UKnowledge as Additional File. I hereby grant to The University of Kentucky and its agents the irrevocable, non-exclusive, and royalty-free license to archive and make accessible my work in whole or in part in all forms of media, now or hereafter known. I agree that the document mentioned above may be made available immediately for worldwide access unless an embargo applies. -
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. -
The Title of the Dissertation
UNIVERSITY OF CALIFORNIA SAN DIEGO Novel network-based integrated analyses of multi-omics data reveal new insights into CD8+ T cell differentiation and mouse embryogenesis A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Bioinformatics and Systems Biology by Kai Zhang Committee in charge: Professor Wei Wang, Chair Professor Pavel Arkadjevich Pevzner, Co-Chair Professor Vineet Bafna Professor Cornelis Murre Professor Bing Ren 2018 Copyright Kai Zhang, 2018 All rights reserved. The dissertation of Kai Zhang is approved, and it is accept- able in quality and form for publication on microfilm and electronically: Co-Chair Chair University of California San Diego 2018 iii EPIGRAPH The only true wisdom is in knowing you know nothing. —Socrates iv TABLE OF CONTENTS Signature Page ....................................... iii Epigraph ........................................... iv Table of Contents ...................................... v List of Figures ........................................ viii List of Tables ........................................ ix Acknowledgements ..................................... x Vita ............................................. xi Abstract of the Dissertation ................................. xii Chapter 1 General introduction ............................ 1 1.1 The applications of graph theory in bioinformatics ......... 1 1.2 Leveraging graphs to conduct integrated analyses .......... 4 1.3 References .............................. 6 Chapter 2 Systematic -
Propranolol-Mediated Attenuation of MMP-9 Excretion in Infants with Hemangiomas
Supplementary Online Content Thaivalappil S, Bauman N, Saieg A, Movius E, Brown KJ, Preciado D. Propranolol-mediated attenuation of MMP-9 excretion in infants with hemangiomas. JAMA Otolaryngol Head Neck Surg. doi:10.1001/jamaoto.2013.4773 eTable. List of All of the Proteins Identified by Proteomics This supplementary material has been provided by the authors to give readers additional information about their work. © 2013 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 10/01/2021 eTable. List of All of the Proteins Identified by Proteomics Protein Name Prop 12 mo/4 Pred 12 mo/4 Δ Prop to Pred mo mo Myeloperoxidase OS=Homo sapiens GN=MPO 26.00 143.00 ‐117.00 Lactotransferrin OS=Homo sapiens GN=LTF 114.00 205.50 ‐91.50 Matrix metalloproteinase‐9 OS=Homo sapiens GN=MMP9 5.00 36.00 ‐31.00 Neutrophil elastase OS=Homo sapiens GN=ELANE 24.00 48.00 ‐24.00 Bleomycin hydrolase OS=Homo sapiens GN=BLMH 3.00 25.00 ‐22.00 CAP7_HUMAN Azurocidin OS=Homo sapiens GN=AZU1 PE=1 SV=3 4.00 26.00 ‐22.00 S10A8_HUMAN Protein S100‐A8 OS=Homo sapiens GN=S100A8 PE=1 14.67 30.50 ‐15.83 SV=1 IL1F9_HUMAN Interleukin‐1 family member 9 OS=Homo sapiens 1.00 15.00 ‐14.00 GN=IL1F9 PE=1 SV=1 MUC5B_HUMAN Mucin‐5B OS=Homo sapiens GN=MUC5B PE=1 SV=3 2.00 14.00 ‐12.00 MUC4_HUMAN Mucin‐4 OS=Homo sapiens GN=MUC4 PE=1 SV=3 1.00 12.00 ‐11.00 HRG_HUMAN Histidine‐rich glycoprotein OS=Homo sapiens GN=HRG 1.00 12.00 ‐11.00 PE=1 SV=1 TKT_HUMAN Transketolase OS=Homo sapiens GN=TKT PE=1 SV=3 17.00 28.00 ‐11.00 CATG_HUMAN Cathepsin G OS=Homo -
ORIGINAL ARTICLE Flow Cytometric Protein Expression Profiling As a Systematic Approach for Developing Disease-Specific Assays
Leukemia (2006) 20, 2102–2110 & 2006 Nature Publishing Group All rights reserved 0887-6924/06 $30.00 www.nature.com/leu ORIGINAL ARTICLE Flow cytometric protein expression profiling as a systematic approach for developing disease-specific assays: identification of a chronic lymphocytic leukaemia-specific assay for use in rituximab-containing regimens AC Rawstron, R de Tute, AS Jack and P Hillmen Haematological Malignancy Diagnostic Service (HMDS), Leeds Teaching Hospitals, Leeds, UK Depletion of disease below the levels detected by sensitive sustained remissions only occur in patients achieving an MRD- minimal residual disease (MRD) assays is associated with negative complete response.12 Therefore MRD is increasingly prolonged survival in chronic lymphocytic leukaemia (CLL). being used as an end point for therapeutic trials, and several Flow cytometric MRD assays are now sufficiently sensitive and rapid to guide the duration of therapy in CLL, but generally rely studies are now using the assessment of MRD to define the on assessment of CD20 expression, which cannot be accurately duration of therapy. measured during and after therapeutic approaches containing Approaches using allele-specific oligonucleotide polymerase rituximab. The aim of this study was to use analytical software chain reaction (ASO-PCR) to the immunoglobulin gene of the developed for microarray analysis to provide a systematic B-CLL cell are generally accepted to show the highest sensitivity approach for MRD flow assay development. Samples from CLL for MRD detection. However, more recent four-colour ap- patients (n ¼ 49), normal controls (n ¼ 21) and other B-lympho- proaches show sensitivities nearing that of ASO-PCR6,11,13 with proliferative disorders (n ¼ 12) were assessed with a panel of 66 antibodies. -
CYLD Is a Deubiquitinating Enzyme That Negatively Regulates NF-Kb
letters to nature 13. Schwartz, S. et al. Human–mouse alignments with BLASTZ. Genome Res 13, 103–107 (2003). necrosis factor receptors (TNFRs). Loss of the deubiquitinating 14. Schwartz, S. et al. MultiPipMaker and supporting tools: alignments and analysis of multiple genomic activity of CYLD correlates with tumorigenesis. CYLD inhibits DNA sequences. Nucleic Acids Res. 31, 3518–3524 (2003). 15.Murphy,W.J.et al. Resolution of the early placental mammal radiation using Bayesian phylogenetics. activation of NF-kB by the TNFR family members CD40, XEDAR Science 294, 2348–2351 (2001). and EDAR in a manner that depends on the deubiquitinating 16. Poux, C., Van Rheede, T., Madsen, O. & de Jong, W. W. Sequence gaps join mice and men: activity of CYLD. Downregulation of CYLD by RNA-mediated phylogenetic evidence from deletions in two proteins. Mol. Biol. Evol. 19, 2035–2037 (2002). 17. Huelsenbeck, J. P., Larget, B. & Swofford, D. A compound Poisson process for relaxing the molecular interference augments both basal and CD40-mediated activation clock. Genetics 154, 1879–1892 (2000). of NF-kB. The inhibition of NF-kBactivationbyCYLDis 18. Cooper, G. M. et al. Quantitative estimates of sequence divergence for comparative analyses of mediated, at least in part, by the deubiquitination and inacti- mammalian genomes. Genome Res. 13, 813–820 (2003). vation of TNFR-associated factor 2 (TRAF2) and, to a lesser 19. Siepel, A. & Haussler, D. Proc. 7th Annual Int. Conf. Research in Computational Molecular Biology (ACM, New York, 2003). extent, TRAF6. These results indicate that CYLD is a negative 20. Hardison, R. C. et al. Covariation in frequencies of substitution, deletion, transposition, and regulator of the cytokine-mediated activation of NF-kB that is recombination during eutherian evolution. -
Seq2pathway Vignette
seq2pathway Vignette Bin Wang, Xinan Holly Yang, Arjun Kinstlick May 19, 2021 Contents 1 Abstract 1 2 Package Installation 2 3 runseq2pathway 2 4 Two main functions 3 4.1 seq2gene . .3 4.1.1 seq2gene flowchart . .3 4.1.2 runseq2gene inputs/parameters . .5 4.1.3 runseq2gene outputs . .8 4.2 gene2pathway . 10 4.2.1 gene2pathway flowchart . 11 4.2.2 gene2pathway test inputs/parameters . 11 4.2.3 gene2pathway test outputs . 12 5 Examples 13 5.1 ChIP-seq data analysis . 13 5.1.1 Map ChIP-seq enriched peaks to genes using runseq2gene .................... 13 5.1.2 Discover enriched GO terms using gene2pathway_test with gene scores . 15 5.1.3 Discover enriched GO terms using Fisher's Exact test without gene scores . 17 5.1.4 Add description for genes . 20 5.2 RNA-seq data analysis . 20 6 R environment session 23 1 Abstract Seq2pathway is a novel computational tool to analyze functional gene-sets (including signaling pathways) using variable next-generation sequencing data[1]. Integral to this tool are the \seq2gene" and \gene2pathway" components in series that infer a quantitative pathway-level profile for each sample. The seq2gene function assigns phenotype-associated significance of genomic regions to gene-level scores, where the significance could be p-values of SNPs or point mutations, protein-binding affinity, or transcriptional expression level. The seq2gene function has the feasibility to assign non-exon regions to a range of neighboring genes besides the nearest one, thus facilitating the study of functional non-coding elements[2]. Then the gene2pathway summarizes gene-level measurements to pathway-level scores, comparing the quantity of significance for gene members within a pathway with those outside a pathway. -
A Drosophila Ortholog of the Human Cylindromatosis Tumor Suppressor
RESEARCH ARTICLE 2605 Development 134, 2605-2614 (2007) doi:10.1242/dev.02859 A Drosophila ortholog of the human cylindromatosis tumor suppressor gene regulates triglyceride content and antibacterial defense Theodore Tsichritzis1, Peer C. Gaentzsch3, Stylianos Kosmidis2, Anthony E. Brown3, Efthimios M. Skoulakis2, Petros Ligoxygakis3,* and George Mosialos1,4,* The cylindromatosis (CYLD) gene is mutated in human tumors of skin appendages. It encodes a deubiquitylating enzyme (CYLD) that is a negative regulator of the NF-B and JNK signaling pathways, in vitro. However, the tissue-specific function and regulation of CYLD in vivo are poorly understood. We established a genetically tractable animal model to initiate a systematic investigation of these issues by characterizing an ortholog of CYLD in Drosophila. Drosophila CYLD is broadly expressed during development and, in adult animals, is localized in the fat body, ovaries, testes, digestive tract and specific areas of the nervous system. We demonstrate that the protein product of Drosophila CYLD (CYLD), like its mammalian counterpart, is a deubiquitylating enzyme. Impairment of CYLD expression is associated with altered fat body morphology in adult flies, increased triglyceride levels and increased survival under starvation conditions. Furthermore, flies with compromised CYLD expression exhibited reduced resistance to bacterial infections. All mutant phenotypes described were reversible upon conditional expression of CYLD transgenes. Our results implicate CYLD in a broad range of functions associated with fat homeostasis and host defence in Drosophila. KEY WORDS: Cylindromatosis, Drosophila, Fat body, Host defense, NF-kappaB INTRODUCTION disease and it is required for the proper development of T Familial cylindromatosis is an autosomal-dominant predisposition lymphocytes in mice (Costello et al., 2005; Reiley et al., 2006). -
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.