DOCSLIB.ORG

Studies on Mature Endothelial Cells and CD34+ Stem Cells

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

Exploring Mechanisms for Improvement of Cardiovascular Disease; Studies on Mature + Endothelial Cells and CD34 Stem Cells Sherin M. Bakhashab Institute of Cellular Medicine Faculty of Medical Sciences University of Newcastle A thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy May 2015 Abstract ABSTRACT Cardiovascular disease (CVD) is the major cause of morbidity and mortality worldwide and in particular in diabetes mellitus (DM). Although metformin has been shown to reduce CVD in Type-2 DM clinical trials, the underlying cardioprotective mechanism remains unexplored. Objective: to determine the effect of metformin on mature endothelial and stem cells exposed to hypoxia, hyperglycaemia or both conditions combined. Human umbilical vein endothelial cells (HUVEC) were studied by scratch test for migration and flow cytometry for apoptosis after culture in euglycaemia or hyperglycaemia, and/or hypoxia with or without metformin. mRNA was assayed by whole transcript microarrays. Genes of interest were confirmed by quantitative real-time PCR (qRT-PCR), proteins by western blot assay or flow cytometry. Metformin increased cell survival and migration via activation of vascular endothelial growth factor (VEGF) signalling, through upregulation of matrix metalloproteinase 16, and ERK/mitogen-activated protein kinase signalling under hyperglycaemia-hypoxia. Paracrine secretion of CD34+ cells treated with euglycaemia or hyperglycaemia, and/or hypoxia with or without metformin was assessed by measuring pro-inflammatory cytokines, VEGFA, chemokine (C-X-C Motif) ligand 10 (CXCL10), tissue inhibitor of metalloproteinase 1 (TIMP1) and efficacy to promote in vitro tube formation by HUVECs. Additionally, miR-126 was evaluated in exosomes and exosome-depleted medium, which was found to be increased by metformin. mRNA from treated CD34+ cells was assayed by microarray and genes of interest were validated by qRT-PCR. An anti-inflammatory effect of metformin was detected under euglycaemia and euglycaemia-hypoxia through upregulation of STEAP family member 4. Metformin enhanced angiogenesis via increased VEGFA and miR-126 under hyperglycaemia-hypoxia. Metformin downregulated the expression of angiogenic inhibitors CXCL10 and TIMP1, which were upregulated under hyperglycaemia-hypoxia. ii Abstract In conclusion, our data from HUVEC and CD34+ cells are commensurate with a vascular protective effect of metformin in a model of a diabetic state combined with hypoxia, and add to understanding of the underlying mechanism. iii Dedication Dedication I dedicated this thesis to my parents, For my mother and the pride that I know she would have felt if she was with us today For my father enduring love and generous support Declaration DECLARATION The work described in this thesis was undertaken in the laboratory of Visiting Professor Jolanta Weaver at the Institute of Cellular Medicine (Newcastle University) in fulfilment of the degree of Doctor of Philosophy. This thesis is the result of my work, and I have acknowledged the contributions of others. No portion of the work referred to in the thesis has been submitted in support of an application for another degree or qualification of this or any other university or other institution of learning. Sherin Bakhashab 2015 Acknowledgments ACKNOWLEDGEMENTS I would like to extend my sincere gratitude to my supervisor Prof. Jolanta Weaver for giving me the opportunity to perform this research in her laboratory and for passing on her knowledge and guidance to me. Additionally, I am thankful for Prof. Weaver continuous help and support in this project. I would like to express a special thanks to Dr. Michael Glanville for his great help and advice in molecular techniques. I am particularly grateful to Mrs. Elizabeth Anne Douglas for her help in ordering reagents required for my work. I would like to acknowledge the excellent teamwork by Dr. Fahad Ahmed, Ayat Bashir and other members of our group in Haematological Sciences Laboratory. As a Joint Supervision Program Ph.D. student at Newcastle University and King Abdulaziz University (KAU), Saudi Arabia, I would like to thank all the people in KAU who supported me with their time and help. I would like especially to thank Prof. Ammar Amin, Supervisor General of the Joint Supervision Program, my KAU supervisors Prof. Abdulrahman Al-Malki, and Dr. Sahira Lary. I was lucky to be associated with the Centre of Excellence in Genomic Medicine Research (CEGMR), Jeddah, Saudi Arabia, where I was able to perform part of my research. I would therefore like to express my gratitude to Prof. Mohammed Al-Qahtani, the director of CEGMR and Prof. Mamdooh Qari for allowing access to the CEGMR labs and facilities. I am thankful to Dr. Farid Ahmed, for his help in tissue culture and flow cytometry techniques and his guidance in preparing this thesis. I would also like to thank Dr. Hans- Juergen Schulten for his excellent support in microarray technology. I thank Prof. David Jones and Dr. Gabriele Saretzki for their input and guidance during the internal assessment stages of my Ph.D. I would like to express my appreciation to Prof. Dianne Ford and Prof. Stefan Przyborski for volunteering to be my examiners. Financial support for this work has been generously provided by Joint Supervision Program, KAU, Jeddah, Saudi Arabia and King Abdulaziz City for Science and Technology (KACST), Saudi Arabia. vi Acknowledgments Finally, I am forever grateful for the open-handed support of my husband, Ali Binladen, and close family members who have shared the excitements and struggles of my Ph.D. years. vii Table of Contents Table of Contents Chapter 1. Introduction .................................................................................................. 1 1.1 Diabetes mellitus and cardiovascular disease ....................................................... 2 1.1.1 Definition and classification of diabetes mellitus .......................................... 2 1.1.2 Complications of diabetes ............................................................................. 3 1.2 Vasculogenesis and angiogenesis ......................................................................... 3 1.2.1 Origin of vascular endothelium ..................................................................... 3 1.2.2 Endothelial cell differentiation and vascular development ............................. 5 1.2.3 Molecular mechanisms involved in angiogenesis .......................................... 7 1.3 Endothelial dysfunction in diabetes .................................................................... 12 1.4 Molecular mechanisms of ischaemic cardiovascular disease .............................. 14 1.4.1 Hypoxia ...................................................................................................... 14 1.4.2 Structure and function of HIF-1 .................................................................. 14 1.5 Role of microRNAs in vascular biology ............................................................. 19 1.5.1 MicroRNA biogenesis and mechanism of action ......................................... 19 1.5.2 Identification and quantification of miRNAs ............................................... 22 1.5.3 Role of miRNAs in angiogenesis ................................................................ 22 1.6 Human stem cells ............................................................................................... 24 1.6.1 Stem cell classification based on origin ....................................................... 25 1.6.2 The stem cell niche ..................................................................................... 25 1.7 CD34+ stem cells ............................................................................................... 28 1.7.1 CD34+ cells as a therapeutic agent .............................................................. 28 1.7.2 Paracrine function of human CD34+ stem cells ........................................... 29 1.8 Metformin ......................................................................................................... 31 viii Table of Contents 1.8.1 History of metformin .................................................................................. 31 1.8.2 Mechanism of action of metformin as anti-diabetic drug ............................. 32 1.8.3 Action of metformin on cardiovascular disease ........................................... 35 1.9 Aims of the thesis .............................................................................................. 36 Chapter 2. Material and Methods ................................................................................. 38 2.1 Cell culture techniques ....................................................................................... 38 2.1.1 Tissue supply .............................................................................................. 38 2.1.2 Isolation of HUVEC from umbilical cord.................................................... 38 2.1.3 Incubation of HUVEC with various concentrations of glucose and hypoxia 40 2.1.4 Metformin treatment ................................................................................... 41 2.1.5 Isolation of mononuclear cells from umbilical cord blood ........................... 42 2.1.6 Isolation of CD34+ stem cells ...................................................................... 42 2.1.7 CD34+ cell culture .....................................................................................
Recommended publications
  • The Inhibitory NKR-P1B:Clr-B Recognition Axis Facilitates Detection of Oncogenic Transformation and Cancer Immunosurveillance Miho Tanaka1,2, Jason H

    The Inhibitory NKR-P1B:Clr-B Recognition Axis Facilitates Detection of Oncogenic Transformation and Cancer Immunosurveillance Miho Tanaka1,2, Jason H

    Published OnlineFirst April 24, 2018; DOI: 10.1158/0008-5472.CAN-17-1688 Cancer Tumor Biology and Immunology Research The Inhibitory NKR-P1B:Clr-b Recognition Axis Facilitates Detection of Oncogenic Transformation and Cancer Immunosurveillance Miho Tanaka1,2, Jason H. Fine1,2, Christina L. Kirkham1,2, Oscar A. Aguilar1,2, Antoaneta Belcheva1, Alberto Martin1, Troy Ketela3,4, Jason Moffat3,4, David S.J. Allan1,2, and James R. Carlyle1,2 Abstract Natural killer (NK) cells express receptors specific for MHC class in a primary lymphoma model despite preferential rejection of – – I (MHC-I) molecules involved in "missing-self" recognition of Clr-b / hematopoietic cells previously observed following adop- cancer and virus-infected cells. Here we elucidate the role of MHC- tive transfer into na€ve wild-type mice in vivo. Collectively, these I-independent NKR-P1B:Clr-b interactions in the detection of findings suggest that the inhibitory NKR-P1B:Clr-b axis plays a oncogenic transformation by NK cells. Ras oncogene overexpres- beneficial role in innate detection of oncogenic transformation sion was found to promote a real-time loss of Clr-b on mouse via NK-cell–mediated cancer immune surveillance, in addition fibroblasts and leukemia cells, mediated in part via the Raf/MEK/ to a pathologic role in the immune escape of primary lympho- ERK and PI3K pathways. Ras-driven Clr-b downregulation ma cells in Em-cMyc mice in vivo. These results provide a model occurred at the level of the Clrb (Clec2d) promoter, nascent Clr-b for the human NKR-P1A:LLT1 system in cancer immunosur- transcripts, and cell surface Clr-b protein, in turn promoting veillance in patients with lymphoma and suggest it may rep- missing-self recognition via the NKR-P1B inhibitory receptor.
  • Integrated Bioinformatic Analysis of RNA Binding Proteins in Hepatocellular Carcinoma

    Integrated Bioinformatic Analysis of RNA Binding Proteins in Hepatocellular Carcinoma

    www.aging-us.com AGING 2021, Vol. 13, No. 2 Research Paper Integrated bioinformatic analysis of RNA binding proteins in hepatocellular carcinoma Ling Wang1,*, Zhen Zhang2,3,*, Yuan Li1, Yanyan Wan1, Baocai Xing1,& 1Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education, Hepatopancreatobiliary Surgery Department I, Peking University Cancer Hospital and Institute, Beijing 100142, China 2Department of Gastroenterological Surgery, Peking University People’s Hospital, Beijing 100044, China 3Laboratory of Surgical Oncology, Beijing Key Laboratory of Colorectal Cancer Diagnosis and Treatment Research, Peking University People’s Hospital, Beijing 100044, China *Equal contribution Correspondence to: Baocai Xing; email: [email protected] Keywords: RNA binding protein, hepatocellular carcinoma, biomarker, transcriptomics, proteomics Received: June 8, 2020 Accepted: November 3, 2020 Published: December 19, 2020 Copyright: © 2020 Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ABSTRACT RNA binding proteins (RBPs) are aberrantly expressed in a tissue-specific manner across many tumors. These proteins, which play a vital role in post-transcriptional gene regulation, are involved in RNA splicing, maturation, transport, stability, degradation, and translation. We set out to establish an accurate risk score model based on RBPs to estimate prognosis in hepatocellular carcinoma (HCC). RNA-sequencing data, proteomic data and corresponding clinical information were acquired from the Cancer Genome Atlas database and the Clinical Proteomic Tumor Analysis Consortium database respectively. We identified 406 differentially expressed RBPs between HCC tumor and normal tissues at the transcriptional and protein level.
  • Supplementary Table 1: Adhesion Genes Data Set

    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,
  • Predicting Clinical Response to Treatment with a Soluble Tnf-Antagonist Or Tnf, Or a Tnf Receptor Agonist

    Predicting Clinical Response to Treatment with a Soluble Tnf-Antagonist Or Tnf, Or a Tnf Receptor Agonist

    (19) TZZ _ __T (11) EP 2 192 197 A1 (12) EUROPEAN PATENT APPLICATION (43) Date of publication: (51) Int Cl.: 02.06.2010 Bulletin 2010/22 C12Q 1/68 (2006.01) (21) Application number: 08170119.5 (22) Date of filing: 27.11.2008 (84) Designated Contracting States: (72) Inventor: The designation of the inventor has not AT BE BG CH CY CZ DE DK EE ES FI FR GB GR yet been filed HR HU IE IS IT LI LT LU LV MC MT NL NO PL PT RO SE SI SK TR (74) Representative: Habets, Winand Designated Extension States: Life Science Patents AL BA MK RS PO Box 5096 6130 PB Sittard (NL) (71) Applicant: Vereniging voor Christelijk Hoger Onderwijs, Wetenschappelijk Onderzoek en Patiëntenzorg 1081 HV Amsterdam (NL) (54) Predicting clinical response to treatment with a soluble tnf-antagonist or tnf, or a tnf receptor agonist (57) The invention relates to methods for predicting a clinical response to a therapy with a soluble TNF antagonist, TNF or a TNF receptor agonist and a kit for use in said methods. EP 2 192 197 A1 Printed by Jouve, 75001 PARIS (FR) EP 2 192 197 A1 Description [0001] The invention relates to methods for predicting a clinical response to a treatment with a soluble TNF antagonist, with TNF or a TNF receptor agonist using expression levels of genes of the Type I INF pathway and a kit for use in said 5 methods. In another aspect, the invention relates to a method for evaluating a pharmacological effect of a treatment with a soluble TNF antagonist, TNF or a TNF receptor agonist.
  • The Transcriptomic Landscape of Prostate Cancer Development and Progression: an Integrative Analysis

    The Transcriptomic Landscape of Prostate Cancer Development and Progression: an Integrative Analysis

    cancers Article The Transcriptomic Landscape of Prostate Cancer Development and Progression: An Integrative Analysis Jacek Marzec 1,† , Helen Ross-Adams 1,*,† , Stefano Pirrò 1 , Jun Wang 1 , Yanan Zhu 2, Xueying Mao 2, Emanuela Gadaleta 1 , Amar S. Ahmad 3, Bernard V. North 3, Solène-Florence Kammerer-Jacquet 2, Elzbieta Stankiewicz 2, Sakunthala C. Kudahetti 2, Luis Beltran 4, Guoping Ren 5, Daniel M. Berney 2,4, Yong-Jie Lu 2 and Claude Chelala 1,6,* 1 Bioinformatics Unit, Centre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London EC1M 6BQ, UK; [email protected] (J.M.); [email protected] (S.P.); [email protected] (J.W.); [email protected] (E.G.) 2 Centre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London EC1M 6BQ, UK; [email protected] (Y.Z.); [email protected] (X.M.); solenefl[email protected] (S.-F.K.-J.); [email protected] (E.S.); [email protected] (S.C.K.); [email protected] (D.M.B.); [email protected] (Y.-J.L.) 3 Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Barts and the London School of Medicine, Queen Mary University of London, London EC1M 6BQ, UK; [email protected] (A.S.A.); [email protected] (B.V.N.) 4 Department of Pathology, Barts Health NHS, London E1 F1R, UK; [email protected] 5 Department of Pathology, The First Affiliated Hospital, Zhejiang University Medical College, Hangzhou 310058, China; [email protected] 6 Centre for Computational Biology, Life Sciences Initiative, Queen Mary University London, London EC1M 6BQ, UK * Correspondence: [email protected] (H.R.-A.); [email protected] (C.C.) † These authors contributed equally to this work.
  • Rrna Types in Zebrafish Development

    Rrna Types in Zebrafish Development

    UvA-DARE (Digital Academic Repository) Distinct maternal and somatic rRNA types in zebrafish development Locati, M. Publication date 2017 Document Version Final published version License Other Link to publication Citation for published version (APA): Locati, M. (2017). Distinct maternal and somatic rRNA types in zebrafish development. 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:04 Oct 2021 DISTINCT MATERNAL AND SOMATIC rRNA TYPES IN ZEBRAFISH DEVELOPMENT MAURO LOCATI DISTINCT MATERNAL AND SOMATIC rRNA TYPES IN ZEBRAFISH DEVELOPMENT MAURO LOCATI Distinct Maternal and Somatic rRNA Types in Zebrafish Development ACADEMISCH PROEFSCHRIFT ter verkrijging van de graad van doctor aan de Universiteit van Amsterdam op gezag van de Rector Magnificus prof. dr. ir. K.I.J. Maex ten overstaan van een door het College voor Promoties ingestelde commissie, in het openbaar te verdedigen in de Aula der Universiteit op woensdag 6 december 2017, te 13:00 uur door Mauro Locati geboren te Palermo, Italië Promotiecommissie: Promotor: Prof.
  • Human Lectins, Their Carbohydrate Affinities and Where to Find Them

    Human Lectins, Their Carbohydrate Affinities and Where to Find Them

    biomolecules Review Human Lectins, Their Carbohydrate Affinities and Where to Review HumanFind Them Lectins, Their Carbohydrate Affinities and Where to FindCláudia ThemD. Raposo 1,*, André B. Canelas 2 and M. Teresa Barros 1 1, 2 1 Cláudia D. Raposo * , Andr1 é LAQVB. Canelas‐Requimte,and Department M. Teresa of Chemistry, Barros NOVA School of Science and Technology, Universidade NOVA de Lisboa, 2829‐516 Caparica, Portugal; [email protected] 12 GlanbiaLAQV-Requimte,‐AgriChemWhey, Department Lisheen of Chemistry, Mine, Killoran, NOVA Moyne, School E41 of ScienceR622 Co. and Tipperary, Technology, Ireland; canelas‐ [email protected] NOVA de Lisboa, 2829-516 Caparica, Portugal; [email protected] 2* Correspondence:Glanbia-AgriChemWhey, [email protected]; Lisheen Mine, Tel.: Killoran, +351‐212948550 Moyne, E41 R622 Tipperary, Ireland; [email protected] * Correspondence: [email protected]; Tel.: +351-212948550 Abstract: Lectins are a class of proteins responsible for several biological roles such as cell‐cell in‐ Abstract:teractions,Lectins signaling are pathways, a class of and proteins several responsible innate immune for several responses biological against roles pathogens. such as Since cell-cell lec‐ interactions,tins are able signalingto bind to pathways, carbohydrates, and several they can innate be a immuneviable target responses for targeted against drug pathogens. delivery Since sys‐ lectinstems. In are fact, able several to bind lectins to carbohydrates, were approved they by canFood be and a viable Drug targetAdministration for targeted for drugthat purpose. delivery systems.Information In fact, about several specific lectins carbohydrate were approved recognition by Food by andlectin Drug receptors Administration was gathered for that herein, purpose. plus Informationthe specific organs about specific where those carbohydrate lectins can recognition be found by within lectin the receptors human was body.
  • Literature Mining Sustains and Enhances Knowledge Discovery from Omic Studies

    Literature Mining Sustains and Enhances Knowledge Discovery from Omic Studies

    LITERATURE MINING SUSTAINS AND ENHANCES KNOWLEDGE DISCOVERY FROM OMIC STUDIES by Rick Matthew Jordan B.S. Biology, University of Pittsburgh, 1996 M.S. Molecular Biology/Biotechnology, East Carolina University, 2001 M.S. Biomedical Informatics, University of Pittsburgh, 2005 Submitted to the Graduate Faculty of School of Medicine in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Pittsburgh 2016 UNIVERSITY OF PITTSBURGH SCHOOL OF MEDICINE This dissertation was presented by Rick Matthew Jordan It was defended on December 2, 2015 and approved by Shyam Visweswaran, M.D., Ph.D., Associate Professor Rebecca Jacobson, M.D., M.S., Professor Songjian Lu, Ph.D., Assistant Professor Dissertation Advisor: Vanathi Gopalakrishnan, Ph.D., Associate Professor ii Copyright © by Rick Matthew Jordan 2016 iii LITERATURE MINING SUSTAINS AND ENHANCES KNOWLEDGE DISCOVERY FROM OMIC STUDIES Rick Matthew Jordan, M.S. University of Pittsburgh, 2016 Genomic, proteomic and other experimentally generated data from studies of biological systems aiming to discover disease biomarkers are currently analyzed without sufficient supporting evidence from the literature due to complexities associated with automated processing. Extracting prior knowledge about markers associated with biological sample types and disease states from the literature is tedious, and little research has been performed to understand how to use this knowledge to inform the generation of classification models from ‘omic’ data. Using pathway analysis methods to better understand the underlying biology of complex diseases such as breast and lung cancers is state-of-the-art. However, the problem of how to combine literature- mining evidence with pathway analysis evidence is an open problem in biomedical informatics research.
  • Intersections Spring Symposium

    Intersections Spring Symposium

    INTERSECTIONS SPRING SYMPOSIUM APRIL TH, 8 Last Name First Name Project Title Page Analyzing the Effect of Urbanization on Abboud Bissan Phylogenetic signal in the Species Columba 1 Abouzahra Sharifah Peripheral IV Catheter Sterilization Device 2 Development of a Liquid Crystal Based Electron Adkins Raymond Shower Detector 2 Purification of Secreted Protein, Acidic and Rich in Cysteine (SPARC) Implicated for its Effects on Al Bahrani Zaid Intraocular Pressure 3 A Window into Metabolite Changes of Live Aljawad Yaqeen Bacteria Following Drug Infusion 3 Anderson Emily In-situ Resource Utilization on Mars 4 The Relationship Between Subjective and Objective Language Assessments For Second- Arredondo Kaitlynn Language Learners 4 Atkinson Scott MotionSense Wave: Toucheless Faucet 5 Ayyar Aneeka Hand Tremor Reduction Device 6 Modifying Low-Emissivity Glass for Use with Bailey Jessica Surface Enhanced Raman Spectroscopy 5 Automated Segmentation and Radiomic Characterization of Visceral Fat on Bowel MRIs for Barbur Iulia Crohn's Disease 6 Periodic Liquid Crystal Order: Theory and Barnaby Gavin-Rae Simulations 7 The Role of Dentistry in the U.S. Opioid Epidemic: Basore Makenna A Literature Review 7 Berends Hannah A Leader’s Role in a Nation’s Stability 8 A Study on Daily Cycles in Activity Levels of Bhatia Shireen Coyotes (Canis latrans) 8 Co-creation of an Intervention with African American Older Adults to Manage Stress Blackshire Gabrielle Associated with Self-management of 9 Developing to Developed: Entrepreneurship in Blatt Noah Latin America
  • CLEC2D (NM 001197317) Human Tagged ORF Clone – RG230997 | Origene

    CLEC2D (NM 001197317) Human Tagged ORF Clone – RG230997 | Origene

    OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for RG230997 CLEC2D (NM_001197317) Human Tagged ORF Clone Product data: Product Type: Expression Plasmids Product Name: CLEC2D (NM_001197317) Human Tagged ORF Clone Tag: TurboGFP Symbol: CLEC2D Synonyms: CLAX; LLT1; OCIL Vector: pCMV6-AC-GFP (PS100010) E. coli Selection: Ampicillin (100 ug/mL) Cell Selection: Neomycin ORF Nucleotide >RG230997 representing NM_001197317 Sequence: Red=Cloning site Blue=ORF Green=Tags(s) TTTTGTAATACGACTCACTATAGGGCGGCCGGGAATTCGTCGACTGGATCCGGTACCGAGGAGATCTGCC GCCGCGATCGCC ATGCATGACAGTAACAATGTGGAGAAAGACATTACACCATCTGAATTGCCTGCAAACCCAGCAATAAGAG CTAACTGCCATCAAGAGCCATCAGTATGTCTTCAAGCTGCATGCCCAGAAAGCTGGATTGGTTTTCAAAG AAAGTGTTTCTATTTTTCTGATGACACCAAGAACTGGACATCAAGTCAGAGGTTTTGTGACTCACAAGAT GCTGATCTTGCTCAGGTTGAAAGCTTCCAGGAACTGAATTTCCTGTTGAGATATAAAGGCCCATCTGATC ACTGGATTGGGCTGAGCAGAGAACAAGGCCAACCATGGAAATGGATAAATGGTACTGAATGGACAAGACA GTTTCCTATCCTGGGAGCAGGAGAGTGTGCCTATTTGAATGACAAAGGTGCCAGTAGTGCCAGGCACTAC ACAGAGAGGAAGTGGATTTGTTCCAAATCAGATATACATGTC ACGCGTACGCGGCCGCTCGAG - GFP Tag - GTTTAA Protein Sequence: >RG230997 representing NM_001197317 Red=Cloning site Green=Tags(s) MHDSNNVEKDITPSELPANPAIRANCHQEPSVCLQAACPESWIGFQRKCFYFSDDTKNWTSSQRFCDSQD ADLAQVESFQELNFLLRYKGPSDHWIGLSREQGQPWKWINGTEWTRQFPILGAGECAYLNDKGASSARHY TERKWICSKSDIHV TRTRPLE - GFP Tag - V Restriction Sites: SgfI-MluI This product is to be used for laboratory only. Not
  • This Thesis Has Been Submitted in Fulfilment of the Requirements for a Postgraduate Degree (E.G

    This Thesis Has Been Submitted in Fulfilment of the Requirements for a Postgraduate Degree (E.G

    This thesis has been submitted in fulfilment of the requirements for a postgraduate degree (e.g. PhD, MPhil, DClinPsychol) at the University of Edinburgh. Please note the following terms and conditions of use: • This work is protected by copyright and other intellectual property rights, which are retained by the thesis author, unless otherwise stated. • A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. • This thesis cannot be reproduced or quoted extensively from without first obtaining permission in writing from the author. • The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the author. • When referring to this work, full bibliographic details including the author, title, awarding institution and date of the thesis must be given. Regulation and Function of miR-199-3p in Murine and Human Cytomegalovirus Infections Nouf N. M. Laqtom s0898296 A thesis submitted in fulfilment of requirements for the degree of Doctor of Philosophy Division of Pathway Medicine, School of Biomedical Sciences The University of Edinburgh May 2013 Supervisors: Dr. Amy Buck and Dr. Bernadette Dutia i Declaration of Authorship I hereby declare that this thesis is of my own composition, and that it contains no material previously submitted for the award of any other degree. The work reported in this thesis has been executed by myself, except where due acknowledgement is made in the text. Nouf N. M. Laqtom ii Abstract Human Cytomegalovirus (HCMV), the prototypic β-herpesvirus, is the most common cause of congenital infections as well as morbidity and mortality in immunocompromised patients.
  • C07k - 2021.08

    C07k - 2021.08

    CPC - C07K - 2021.08 C07K PEPTIDES (peptides in foodstuffs A23; obtaining protein compositions for foodstuffs, working-up proteins for foodstuffs A23J; preparations for medicinal purposes A61K; peptides containing beta-lactam rings C07D; cyclic dipeptides not having in their molecule any other peptide link than those which form their ring, e.g. piperazine-2,5-diones, C07D; ergot alkaloids of the cyclic peptide type C07D 519/02; macromolecular compounds having statistically distributed amino acid units in their molecules, i.e. when the preparation does not provide for a specific; but for a random sequence of the amino acid units, homopolyamides and block copolyamides derived from amino acids C08G 69/00; macromolecular products derived from proteins C08H 1/00; preparation of glue or gelatine C09H; single cell proteins, enzymes C12N; genetic engineering processes for obtaining peptides C12N 15/00; compositions for measuring or testing processes involving enzymes C12Q; investigation or analysis of biological material G01N 33/00) Relationships with other classification places An amino acid per se is classified in C07D while peptides (starting from dipeptides) are classified in C07K. Subclass C07K is a function oriented entry for the compounds themselves and does not cover the application or use of the compounds under the subclass definition. For classifying such information other entries exist, for example: preservation of bodies of humans or animals or plants or parts thereof; Biocides, e.g. as disinfectants, as pesticides, as herbicides; pest repellants or attractants; plant growth regulators are classified in A01N. Preparations for medical, dental, or toilet purposes are classified in A61K. Amino acids or derivatives thereof are classified in C07C or C07D.