Supplementary Table S1 Demographic Characteristics Of
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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. -
Genetic Basis of Simple and Complex Traits with Relevance to Avian Evolution
Genetic basis of simple and complex traits with relevance to avian evolution Małgorzata Anna Gazda Doctoral Program in Biodiversity, Genetics and Evolution D Faculdade de Ciências da Universidade do Porto 2019 Supervisor Miguel Jorge Pinto Carneiro, Auxiliary Researcher, CIBIO/InBIO, Laboratório Associado, Universidade do Porto Co-supervisor Ricardo Lopes, CIBIO/InBIO Leif Andersson, Uppsala University FCUP Genetic basis of avian traits Nota Previa Na elaboração desta tese, e nos termos do número 2 do Artigo 4º do Regulamento Geral dos Terceiros Ciclos de Estudos da Universidade do Porto e do Artigo 31º do D.L.74/2006, de 24 de Março, com a nova redação introduzida pelo D.L. 230/2009, de 14 de Setembro, foi efetuado o aproveitamento total de um conjunto coerente de trabalhos de investigação já publicados ou submetidos para publicação em revistas internacionais indexadas e com arbitragem científica, os quais integram alguns dos capítulos da presente tese. Tendo em conta que os referidos trabalhos foram realizados com a colaboração de outros autores, o candidato esclarece que, em todos eles, participou ativamente na sua conceção, na obtenção, análise e discussão de resultados, bem como na elaboração da sua forma publicada. Este trabalho foi apoiado pela Fundação para a Ciência e Tecnologia (FCT) através da atribuição de uma bolsa de doutoramento (PD/BD/114042/2015) no âmbito do programa doutoral em Biodiversidade, Genética e Evolução (BIODIV). 2 FCUP Genetic basis of avian traits Acknowledgements Firstly, I would like to thank to my all supervisors Miguel Carneiro, Ricardo Lopes and Leif Andersson, for the demanding task of supervising myself last four years. -
Mechanism of Action Through an IFN Type I-Independent Responses To
Downloaded from http://www.jimmunol.org/ by guest on September 25, 2021 is online at: average * The Journal of Immunology , 12 of which you can access for free at: 2012; 188:3088-3098; Prepublished online 20 from submission to initial decision 4 weeks from acceptance to publication February 2012; doi: 10.4049/jimmunol.1101764 http://www.jimmunol.org/content/188/7/3088 MF59 and Pam3CSK4 Boost Adaptive Responses to Influenza Subunit Vaccine through an IFN Type I-Independent Mechanism of Action Elena Caproni, Elaine Tritto, Mario Cortese, Alessandro Muzzi, Flaviana Mosca, Elisabetta Monaci, Barbara Baudner, Anja Seubert and Ennio De Gregorio J Immunol cites 33 articles Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription http://www.jimmunol.org/content/suppl/2012/02/21/jimmunol.110176 4.DC1 This article http://www.jimmunol.org/content/188/7/3088.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 © 2012 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 -
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. -
Transcriptomic Analysis of Native Versus Cultured Human and Mouse Dorsal Root Ganglia Focused on Pharmacological Targets Short
bioRxiv preprint doi: https://doi.org/10.1101/766865; this version posted September 12, 2019. 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-ND 4.0 International license. Transcriptomic analysis of native versus cultured human and mouse dorsal root ganglia focused on pharmacological targets Short title: Comparative transcriptomics of acutely dissected versus cultured DRGs Andi Wangzhou1, Lisa A. McIlvried2, Candler Paige1, Paulino Barragan-Iglesias1, Carolyn A. Guzman1, Gregory Dussor1, Pradipta R. Ray1,#, Robert W. Gereau IV2, # and Theodore J. Price1, # 1The University of Texas at Dallas, School of Behavioral and Brain Sciences and Center for Advanced Pain Studies, 800 W Campbell Rd. Richardson, TX, 75080, USA 2Washington University Pain Center and Department of Anesthesiology, Washington University School of Medicine # corresponding authors [email protected], [email protected] and [email protected] Funding: NIH grants T32DA007261 (LM); NS065926 and NS102161 (TJP); NS106953 and NS042595 (RWG). The authors declare no conflicts of interest Author Contributions Conceived of the Project: PRR, RWG IV and TJP Performed Experiments: AW, LAM, CP, PB-I Supervised Experiments: GD, RWG IV, TJP Analyzed Data: AW, LAM, CP, CAG, PRR Supervised Bioinformatics Analysis: PRR Drew Figures: AW, PRR Wrote and Edited Manuscript: AW, LAM, CP, GD, PRR, RWG IV, TJP All authors approved the final version of the manuscript. 1 bioRxiv preprint doi: https://doi.org/10.1101/766865; this version posted September 12, 2019. 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. -
Investigation of Candidate Genes and Mechanisms Underlying Obesity
Prashanth et al. BMC Endocrine Disorders (2021) 21:80 https://doi.org/10.1186/s12902-021-00718-5 RESEARCH ARTICLE Open Access Investigation of candidate genes and mechanisms underlying obesity associated type 2 diabetes mellitus using bioinformatics analysis and screening of small drug molecules G. Prashanth1 , Basavaraj Vastrad2 , Anandkumar Tengli3 , Chanabasayya Vastrad4* and Iranna Kotturshetti5 Abstract Background: Obesity associated type 2 diabetes mellitus is a metabolic disorder ; however, the etiology of obesity associated type 2 diabetes mellitus remains largely unknown. There is an urgent need to further broaden the understanding of the molecular mechanism associated in obesity associated type 2 diabetes mellitus. Methods: To screen the differentially expressed genes (DEGs) that might play essential roles in obesity associated type 2 diabetes mellitus, the publicly available expression profiling by high throughput sequencing data (GSE143319) was downloaded and screened for DEGs. Then, Gene Ontology (GO) and REACTOME pathway enrichment analysis were performed. The protein - protein interaction network, miRNA - target genes regulatory network and TF-target gene regulatory network were constructed and analyzed for identification of hub and target genes. The hub genes were validated by receiver operating characteristic (ROC) curve analysis and RT- PCR analysis. Finally, a molecular docking study was performed on over expressed proteins to predict the target small drug molecules. Results: A total of 820 DEGs were identified between -
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 -
Involvement of Taste Receptors in the Effectiveness of Sublingual Immunotherapy
Allergology International 67 (2018) 421e424 Contents lists available at ScienceDirect Allergology International journal homepage: http://www.elsevier.com/locate/alit Letter to the Editor Involvement of taste receptors in the effectiveness of sublingual immunotherapy Dear Editor, RNA or DNA was damaged, 25 samples each in the HR and NR groups underwent microarray analyses. We identified 56 genes, Japanese cedar pollinosis (JCP) is a specific seasonal allergic dis- differentially expressed between the HR and NR patients, based ease which affects ~30% of the Japanese population, between on the log2 ratio of their averages (Fig. 1). Among these, 5 genes February and April, every year.1 Apart from a series of symptom- encoded taste receptors, 4 of which tended to increase in the HR reliever medications, allergen-specific immunotherapy (AIT) is group but not in the NR group, after SLIT. Consistently, the expres- þ one of the most effective treatments for JCP. After several years of sion of TAS2R13, 43 and 50 in CD4 T cells could be retrieved by relying on the application of subcutaneous immunotherapy (SCIT) BioGPS (http://biogps.org/)(Supplementary Figs. 1e3). Among with standardized Japanese cedar pollen extract (since the them, we confirmed the cell surface expression of TAS2R43 on þ 1960s), the use of sublingual immunotherapy (SLIT) was approved CD4 T cells (Supplementary Fig. 4). SLIT-induced increasing ten- in 2014.2 In addition to the numerous clinical and scientific evi- dency was also observed for several small nuclear RNAs and micro- dences pertaining to its effectiveness and safety on JCP including RNAs especially in the HR group. -
140503 IPF Signatures Supplement Withfigs Thorax
Supplementary material for Heterogeneous gene expression signatures correspond to distinct lung pathologies and biomarkers of disease severity in idiopathic pulmonary fibrosis Daryle J. DePianto1*, Sanjay Chandriani1⌘*, Alexander R. Abbas1, Guiquan Jia1, Elsa N. N’Diaye1, Patrick Caplazi1, Steven E. Kauder1, Sabyasachi Biswas1, Satyajit K. Karnik1#, Connie Ha1, Zora Modrusan1, Michael A. Matthay2, Jasleen Kukreja3, Harold R. Collard2, Jackson G. Egen1, Paul J. Wolters2§, and Joseph R. Arron1§ 1Genentech Research and Early Development, South San Francisco, CA 2Department of Medicine, University of California, San Francisco, CA 3Department of Surgery, University of California, San Francisco, CA ⌘Current address: Novartis Institutes for Biomedical Research, Emeryville, CA. #Current address: Gilead Sciences, Foster City, CA. *DJD and SC contributed equally to this manuscript §PJW and JRA co-directed this project Address correspondence to Paul J. Wolters, MD University of California, San Francisco Department of Medicine Box 0111 San Francisco, CA 94143-0111 [email protected] or Joseph R. Arron, MD, PhD Genentech, Inc. MS 231C 1 DNA Way South San Francisco, CA 94080 [email protected] 1 METHODS Human lung tissue samples Tissues were obtained at UCSF from clinical samples from IPF patients at the time of biopsy or lung transplantation. All patients were seen at UCSF and the diagnosis of IPF was established through multidisciplinary review of clinical, radiological, and pathological data according to criteria established by the consensus classification of the American Thoracic Society (ATS) and European Respiratory Society (ERS), Japanese Respiratory Society (JRS), and the Latin American Thoracic Association (ALAT) (ref. 5 in main text). Non-diseased normal lung tissues were procured from lungs not used by the Northern California Transplant Donor Network. -
PRODUCT SPECIFICATION Anti-GJC3 Product Datasheet
Anti-GJC3 Product Datasheet Polyclonal Antibody PRODUCT SPECIFICATION Product Name Anti-GJC3 Product Number HPA015024 Gene Description gap junction protein, gamma 3, 30.2kDa Clonality Polyclonal Isotype IgG Host Rabbit Antigen Sequence Recombinant Protein Epitope Signature Tag (PrEST) antigen sequence: RTWKHKSSSSKYFLTSESTRRHKKATDSLPVVETKEQFQEAVPGRSLAQE KQRPVGPRDA Purification Method Affinity purified using the PrEST antigen as affinity ligand Verified Species Human Reactivity Recommended IHC (Immunohistochemistry) Applications - Antibody dilution: 1:20 - 1:50 - Retrieval method: HIER pH6 WB (Western Blot) - Working concentration: 0.04-0.4 µg/ml Characterization Data Available at atlasantibodies.com/products/HPA015024 Buffer 40% glycerol and PBS (pH 7.2). 0.02% sodium azide is added as preservative. Concentration Lot dependent Storage Store at +4°C for short term storage. Long time storage is recommended at -20°C. Notes Gently mix before use. Optimal concentrations and conditions for each application should be determined by the user. For protocols, additional product information, such as images and references, see atlasantibodies.com. Product of Sweden. For research use only. Not intended for pharmaceutical development, diagnostic, therapeutic or any in vivo use. No products from Atlas Antibodies may be resold, modified for resale or used to manufacture commercial products without prior written approval from Atlas Antibodies AB. Warranty: The products supplied by Atlas Antibodies are warranted to meet stated product specifications and to conform to label descriptions when used and stored properly. Unless otherwise stated, this warranty is limited to one year from date of sales for products used, handled and stored according to Atlas Antibodies AB's instructions. Atlas Antibodies AB's sole liability is limited to replacement of the product or refund of the purchase price. -
Supplementary Tables Supplemental Table S1: Comparison of the Coverage of Reference Panels Used for SNP Imputation. the Markers
Supplementary Tables Supplemental Table S1: Comparison of the coverage of reference panels used for SNP imputation. The markers on the Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA) reference panel and Haplotype Reference Consortium (HRG) used to impute SNPs from our AA and CAU participants were compared to one thousand genomes (1kG) dataset. Loci information CAAPA vs 1kG HRC vs 1kG Total loci 45,639,158 90,558,388 Overlapping loci 24,880,301 49,826,569 Percent overlap 54.52% 55.02% 1kG-only loci 9,363,544 15,148,191 Ref-only loci 8,461,186 22,649,501 Supplemental Table S2: SNP imputation results. The total number of SNPs imputed for the AA and CAU participants either using the Michigan imputation server (Minimac) or Beagle. Targets prepared for: AA CAU Beagle 730,616 726,165 Minimac 698,343 660,733 Supplemental Table S3: Allele frequencies of TA2R38 SNPs by each ancestral group and time point. The rs number of each SNP, the location of SNP buy chromosome (CHR) and base pair position (POS) is provided along with the allele frequency (ALLELE:FREQ) for each SNP. Baseline 6-month Baseline 6-month AA (N = 297) AA (N = 234) CAU (N = 198) CAU (N = 151) SNP CHR POS ALLELE:FREQ ALLELE:FREQ ALLELE:FREQ ALLELE:FREQ rs10246939 7 141672604 T:0.49 C:0.51 T:0.50 C:0.50 T:0.54 C:0.46 T:0.54 C:0.46 rs1726866 7 141672705 G:0.68 A:0.32 G:0.68 A:0.32 G:0.46 A:0.54 G:0.46 A:0.54 rs713598 7 141673345 C:0.50 G:0.50 C:0.50 G:0.50 C:0.58 G:0.42 C:0.58 G:0.42 Supplemental Table S4: Linkage disequilibrium analysis of TAS2R38 SNPs at each time point of the intervention. -
(12) United States Patent (10) Patent No.: US 9,347,934 B2 Shekdar Et Al
USOO9347934B2 (12) United States Patent (10) Patent No.: US 9,347,934 B2 Shekdar et al. (45) Date of Patent: May 24, 2016 (54) ASSAYS FOR IDENTIFYING COMPOUNDS 2008, OO38739 A1 2/2008 Li et al. THAT MODULATE BITTERTASTE 2008/0167286 A1* 7/2008 Gopalakrishnan et al. ........................ 514,21016 (71) Applicants: CHROMOCELL CORPORATION, 2010/01298.33 A1* 5/2010 Brune et al. ................. 435/721 North Brunswick, NJ (US); KRAFT FOODS GROUP BRANDS LLC, FOREIGN PATENT DOCUMENTS Northfield, IL (US) CN 1341632 A 3, 2002 CN 101583717 A 11, 2009 (72) Inventors: Kambiz Shekdar, New York, NY (US); CN 101828.111 A 9, 2010 Purvi Manoj Shah, Bridgewater, NJ WO WO-0038536 A2 7, 2000 WO WO-2004O29087 4/2004 (US); Joseph Gunnet, Flemington, NJ WO WO-2006053771 A2 5, 2006 (US); Jane V. Leland, Wilmette, IL WO WO-2007002026 A2 1/2007 (US); Peter H. Brown, Glenview, IL WO WO-2008057470 5, 2008 (US); Louise Slade, Morris Plains, NJ WO WO-2008119.195 A1 10, 2008 (US) WO WO-20081191.96 10, 2008 WO WO-20081191.97 10, 2008 (73) Assignees: Chromocell Corporation, North W WSi. A2 1929 Brunswick, NJ (US); Kraft Foods WO WO-2010O886.33 8, 2010 Group Brands LLC, Northfield, IL WO WO-2010O99983 A1 9, 2010 (US) WO WO-2013022947 2, 2013 (*) Notice: Subject to any disclaimer, the term of this OTHER PUBLICATIONS patent is extended or adjusted under 35 U.S.C. 154(b) by 0 days. Bachmanov et al., Taste Receptor Genes, 2007, 27:389-414.* Behrens et al., Structural Requirements for Bitter Taste Receptor (21) Appl.