Human Lectins, Their Carbohydrate Affinities and Where to Find Them
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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. -
Mouse Germ Line Mutations Due to Retrotransposon Insertions Liane Gagnier1, Victoria P
Gagnier et al. Mobile DNA (2019) 10:15 https://doi.org/10.1186/s13100-019-0157-4 REVIEW Open Access Mouse germ line mutations due to retrotransposon insertions Liane Gagnier1, Victoria P. Belancio2 and Dixie L. Mager1* Abstract Transposable element (TE) insertions are responsible for a significant fraction of spontaneous germ line mutations reported in inbred mouse strains. This major contribution of TEs to the mutational landscape in mouse contrasts with the situation in human, where their relative contribution as germ line insertional mutagens is much lower. In this focussed review, we provide comprehensive lists of TE-induced mouse mutations, discuss the different TE types involved in these insertional mutations and elaborate on particularly interesting cases. We also discuss differences and similarities between the mutational role of TEs in mice and humans. Keywords: Endogenous retroviruses, Long terminal repeats, Long interspersed elements, Short interspersed elements, Germ line mutation, Inbred mice, Insertional mutagenesis, Transcriptional interference Background promoter and polyadenylation motifs and often a splice The mouse and human genomes harbor similar types of donor site [10, 11]. Sequences of full-length ERVs can TEs that have been discussed in many reviews, to which encode gag, pol and sometimes env, although groups of we refer the reader for more in depth and general infor- LTR retrotransposons with little or no retroviral hom- mation [1–9]. In general, both human and mouse con- ology also exist [6–9]. While not the subject of this re- tain ancient families of DNA transposons, none view, ERV LTRs can often act as cellular enhancers or currently active, which comprise 1–3% of these genomes promoters, creating chimeric transcripts with genes, and as well as many families or groups of retrotransposons, have been implicated in other regulatory functions [11– which have caused all the TE insertional mutations in 13]. -
Single Cell Transcriptome Atlas of Immune Cells in Human Small
bioRxiv preprint doi: https://doi.org/10.1101/721258; this version posted August 1, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 1 Single cell transcriptome atlas of immune cells in human small 2 intestine and in celiac disease 3 4 Nader Atlasy1,a,4, Anna Bujko2,4, Peter B Brazda1,a, Eva Janssen-Megens1,a , Espen S. 5 Bækkevold2, Jørgen Jahnsen3, Frode L. Jahnsen2, Hendrik G. Stunnenberg1,a,* 6 7 8 1Department of Molecular Biology, Science Faculty, Radboud University, Nijmegen, The 9 Netherlands. 10 2 Department of Pathology, University of Oslo and Oslo University Hospital, Rikshospitalet, 11 Oslo, Norway 12 3 Department of Gastroenterology, Akershus University Hospital and University of Oslo, 13 Oslo, Norway. 14 15 acurrent address: Princess Maxima Centre for Pediatric Oncology, Heidelberglaan 25, 3584 16 CS Utrecht 17 18 19 4These authors contributed equally to this study 20 21 22 *Corresponding author: [email protected] 23 24 25 26 Celiac disease (CeD) is an autoimmune disorder in which ingestion of dietary gluten 27 triggers an immune reaction in the small intestine1,2. The CeD lesion is characterized by 28 crypt hyperplasia, villous atrophy and chronic inflammation with accumulation of 29 leukocytes both in the lamina propria (LP) and in the epithelium3, which eventually 30 leads to destruction of the intestinal epithelium1 and subsequent digestive complications 31 and higher risk of non-hodgkin lymphoma4. A lifetime gluten-free diet is currently the 32 only available treatment5. Gluten-specific LP CD4 T cells and cytotoxic intraepithelial 33 CD8+ T cells are thought to be central in disease pathology1,6-8, however, CeD is a 34 complex immune-mediated disorder and to date the findings are mostly based on 35 analysis of heterogeneous cell populations and on animal models. -
AML Serum Mir-150 Mir-155 Mir-1246 Prog
Supplementary Table S1. Summary of current studies on EVs as biomarkers Disease Source Cargo Role Reference AML serum TGF-β1, CD34, Prognostic [21] CD33, CD117 AML serum miR-150 Prognostic [23] miR-155 miR-1246 AML serum miR-125b Prognostic [24] AML serum miR-10b Prognostic [25] CLL serum CD19, CD37 Prognostic [27] CLL plasma S100-A9 protein Prognostic [29] CLL plasma CD52 Prognostic [30] CLL plasma miR-150, miR-155, Diagnostic [31] miR-223, miR-29 CD37, CD9, CD63 CLL plasma mc-COX2 Prognostic [33] MF plasma CD61, CD62P Prognostic [34] MM serum CD38, CD138, Prognostic [37] CD44, CD147 MM serum let-7b and miR-18a Prognostic [40] nHL /HL plasma CD20/CD30 Diagnostic/Prognostic [20] Lymphoma plasma CD20 Prognostic [43] HL plasma miR-23p Diagnostic [44] miR-127-3p miR-21-5p miR-155-5p let-7a-5p Lymphoma plasma BCL-6 Prognostic [45] c-myc 1 Supplementary Table S2. Summary of current studies on EVs: re-education of the bone marrow niche Disease EV Target Cargo Functional effects Reference origin/Source AML AML cells MSC/stromal / Downregulating of KITL, [52] cells CXCL12, IGF1; Reducing support to normal hemopoiesis AML AML cells Stromal cells miR-155 Reducing secretion of [54] miR-375 cytokines and growth factor; miR-150 Affecting retention and differentiation of HSC in the bone marrow AML/MDS AML/MDS cells MSC miR-7977 Reducing the hemopoiesis [55] supportive capacity CLL CLL cells MSC miR-202-3p Promoting migration, [32] survival and proliferation CLL Plasma Stromal cells / Production of VEGF, [26] promoting survival of B cells CLL CLL cells -
Harnessing Gene Expression Profiles for the Identification of Ex Vivo Drug
cancers Article Harnessing Gene Expression Profiles for the Identification of Ex Vivo Drug Response Genes in Pediatric Acute Myeloid Leukemia David G.J. Cucchi 1 , Costa Bachas 1 , Marry M. van den Heuvel-Eibrink 2,3, Susan T.C.J.M. Arentsen-Peters 3, Zinia J. Kwidama 1, Gerrit J. Schuurhuis 1, Yehuda G. Assaraf 4, Valérie de Haas 3 , Gertjan J.L. Kaspers 3,5 and Jacqueline Cloos 1,* 1 Hematology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands; [email protected] (D.G.J.C.); [email protected] (C.B.); [email protected] (Z.J.K.); [email protected] (G.J.S.) 2 Department of Pediatric Oncology/Hematology, Erasmus MC–Sophia Children’s Hospital, 3015 CN Rotterdam, The Netherlands; [email protected] 3 Princess Máxima Center for Pediatric Oncology, 3584 CS Utrecht, The Netherlands; [email protected] (S.T.C.J.M.A.-P.); [email protected] (V.d.H.); [email protected] (G.J.L.K.) 4 The Fred Wyszkowski Cancer Research, Laboratory, Department of Biology, Technion-Israel Institute of Technology, 3200003 Haifa, Israel; [email protected] 5 Emma’s Children’s Hospital, Amsterdam UMC, Vrije Universiteit Amsterdam, Pediatric Oncology, 1081 HV Amsterdam, The Netherlands * Correspondence: [email protected] Received: 21 April 2020; Accepted: 12 May 2020; Published: 15 May 2020 Abstract: Novel treatment strategies are of paramount importance to improve clinical outcomes in pediatric AML. Since chemotherapy is likely to remain the cornerstone of curative treatment of AML, insights in the molecular mechanisms that determine its cytotoxic effects could aid further treatment optimization. -
A Study of Chemotherapy Resistance in Acute Myeloid Leukemia
A Study of Chemotherapy Resistance in Acute Myeloid Leukemia A DISSERTATION SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL OF THE UNIVERSITY OF MINNESOTA BY Susan Kay Rathe IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY David A. Largaespada October, 2013 © Susan Kay Rathe 2013 Acknowledgements Funding: The leukemia research was funded by The Leukemia & Lymphoma Society (grant 7019-04). The MMuFLR workflow was funded by The Children's Cancer Research Fund. University of Minnesota Resources: The BioMedical Genomics Center provided services for gene expression microarray, RNA sequencing, oligo preparation, and Sanger sequencing. The Minnesota Supercomputing Institute maintains the Galaxy Software, as well as provides data management services and training. The Masonic Cancer Center Bioinformatics Core provided guidance in the analysis of the RNA-seq data. The FDA Drug Screen was performed at the Institute for Therapeutics Discovery and Development. Colleagues: First and foremost, I would like to recognize Dr. David Largaespada for his mentorship and the opportunity to continue research he started while a postdoc in Dr. Neal Copeland’s lab. I would also like to thank the many members of the Largaespada lab who provided direct or indirect assistance to my research. Dr. Bin Yin continued Dr. Largaespada’s work on the BXH-2 AML cell lines by making drug resistant derivatives and provided training in cell culture and drug assay techniques. Dr. Won-Il Kim developed the TNM mouse model and provided training in mouse related experimental techniques. Miechaleen Diers did all of the tail vein injections for the AML transplants and assisted with necropsies. -
Immunocytochemical Analysis of Human Synovial Lining Cells: Phenotypic Relation to Other Marrow Ann Rheum Dis: First Published As 10.1136/Ard.50.5.311 on 1 May 1991
Annals ofthe Rheumatic Diseases 1991; 50: 311-315 31 Immunocytochemical analysis of human synovial lining cells: phenotypic relation to other marrow Ann Rheum Dis: first published as 10.1136/ard.50.5.311 on 1 May 1991. Downloaded from derived cells N A Athanasou, J Quinn Abstract system,20 21 synovial lining cell specific The antigenic phenotype of human synovial progenitors are produced in the marrow by a lining cells in normal and hyperplastic synovial lining cell lineage that diverges at some synovium intima was determined with a panel early stage from that of monocytes and tissue of monoclonal antibodies directed against macrophages. a large number of well defined myeloid To investigate the origin and development of (macrophage/granulocyte associated) antigens. synovial lining cells further we sought to define Synovial lining cells express numerous macro- the antigenic phenotype of human synovial phage associated antigens, including CD11b lining cells and subintimal macrophages in the (CR3), CD13, CD14, CD16 (FcRIII), CD18, synovial membrane. We used a large number of CD32 (FcRII), CD45 (leucocyte common monoclonal antibodies directed against defined antigen), CD54 (ICAM-1), CD64 (FcRI), myeloid (granulocyte/macrophage associated) CD68, and CD71 (transferrin receptor). antigens for the immunohistochemical staining Few synovial lining cells expressed CD11a of human synovial lining cells and subintimal (LFA-1) and CD11c (p150,95). Subintimal macrophages in the synovial membrane. The macrophages expressed all the macrophage pattern of antigen expression by these cells not associated antigens which were present on only has implications for synovial lining cell synovial lining cells and, in addition, expressed origin and development but also for function CD15a, CD25 (interleukin-2 receptor), CD34, and interaction of these cells with other inflam- and CD35 (C3b receptor), none of which was matory cells. -
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. -
The Enigmatic Charcot-Leyden Crystal Protein
C al & ellu ic la n r li Im C m f u Journal of o n l o a l n o r Clarke et al., J Clin Cell Immunol 2015, 6:2 g u y o J DOI: 10.4172/2155-9899.1000323 ISSN: 2155-9899 Clinical & Cellular Immunology Review Article Open Access The Enigmatic Charcot-Leyden Crystal Protein (Galectin-10): Speculative Role(s) in the Eosinophil Biology and Function Christine A Clarke1,3, Clarence M Lee2 and Paulette M Furbert-Harris1,3,4* 1Department of Microbiology, Howard University College of Medicine, Washington, D.C., USA 2Department of Biology, Howard University College of Arts and Sciences, Washington, D.C., USA 3Howard University Cancer Center, Howard University College of Medicine, Washington, D.C., USA 4National Human Genome Center, Howard University College of Medicine, Washington, D.C., USA *Corresponding author: Furbert-Harris PM, Department of Microbiology, Howard University Cancer Center, 2041 Georgia Avenue NW, Room #530, 20060, Washington, D.C., USA, Tel: 202-806-7722, Fax: 202-667-1686; Email: [email protected] Received date: Febuary 22, 2015, Accepted date: April 25, 2015, Published date: April 29, 2015 Copyright: © 2015 Clarke CA, 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. Abstract Eosinophilic inflammation in peripheral tissues is typically marked by the deposition of a prominent eosinophil protein, Galectin-10, better known as Charcot-Leyden crystal protein (CLC). Unlike the eosinophil’s four distinct toxic cationic proteins and enzymes [major basic protein (MBP), eosinophil-derived neurotoxin (EDN), eosinophil cationic protein (ECP), and eosinophil peroxidase (EPO)], there is a paucity of information on the precise role of the crystal protein in the biology of the eosinophil. -
A Single-Cell Transcriptomic Landscape of Primate Arterial Aging
ARTICLE https://doi.org/10.1038/s41467-020-15997-0 OPEN A single-cell transcriptomic landscape of primate arterial aging Weiqi Zhang 1,2,3,4,5,13, Shu Zhang6,7,13, Pengze Yan3,8,13, Jie Ren7,9,13, Moshi Song3,5,8, Jingyi Li2,3,8, Jinghui Lei4, Huize Pan2,3, Si Wang3,5,8, Xibo Ma3,10, Shuai Ma2,3,8, Hongyu Li2,3, Fei Sun2,3, Haifeng Wan3,5,11, ✉ ✉ ✉ Wei Li 3,5,11, Piu Chan4, Qi Zhou3,5,11, Guang-Hui Liu 2,3,4,5,8 , Fuchou Tang 6,7,9,12 & Jing Qu 3,5,11 Our understanding of how aging affects the cellular and molecular components of the vas- 1234567890():,; culature and contributes to cardiovascular diseases is still limited. Here we report a single-cell transcriptomic survey of aortas and coronary arteries in young and old cynomolgus monkeys. Our data define the molecular signatures of specialized arteries and identify eight markers discriminating aortic and coronary vasculatures. Gene network analyses characterize tran- scriptional landmarks that regulate vascular senility and position FOXO3A, a longevity- associated transcription factor, as a master regulator gene that is downregulated in six subtypes of monkey vascular cells during aging. Targeted inactivation of FOXO3A in human vascular endothelial cells recapitulates the major phenotypic defects observed in aged monkey arteries, verifying FOXO3A loss as a key driver for arterial endothelial aging. Our study provides a critical resource for understanding the principles underlying primate arterial aging and contributes important clues to future treatment of age-associated vascular disorders. 1 CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China. -
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, -
Human Pigmentation Genes Under Environmental Selection Richard a Sturm1,* and David L Duffy2
CORE Metadata, citation and similar papers at core.ac.uk Provided by University of Queensland eSpace Sturm and Duffy Genome Biology 2012, 13:248 http://genomebiology.com/2012/13/9/248 revw Ie Human pigmentation genes under environmental selection Richard A Sturm1,* and David L Duffy2 Abstract the iridial melanocytes of the eye [3]. Variations in genes within this pathway are therefore in a position to be Genome-wide association studies and comparative pleiotropic in action, causing skin, hair and eye color to genomics have established major loci and specific become correlated, for example, in Northern European polymorphisms affecting human skin, hair and eye populations with a high frequency of light hair, light skin color. Environmental changes have had an impact and blue eyes or equatorial Africans with dark com plexion, on selected pigmentation genes as populations have dark hair and brown eye color. However, since melanocytes expanded into different regions of the globe. located in these three compartments repre sent indepen dent cellular populations [4] with alternative regulatory or signaling pathways [5], traitspecific variants also occur, Introduction producing assorted phenotypic com binations such as dark Skin, hair and eye color vary dramatically among hair, light skin and blue eyes common in Europeans or the geographically and temporally separated human light hair, dark skin and brown eyes seen in Solomon populations. It has long been speculated that this is due Islanders. Another example of this is the sensitivity of to adaptive changes, but the genetic causes and follicular melanocytes to aging, gradually producing a environmental selective pressures underlying this range silvergray to white hair color, indicating a loss of cells of phenotypic variation have remained largely unknown.