Table S1: Mouse AKR Vs DBA Tumor Gene List Probe Set GB Acc Symbol
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Types of Acute Phase Reactants and Their Importance in Vaccination (Review)
BIOMEDICAL REPORTS 12: 143-152, 2020 Types of acute phase reactants and their importance in vaccination (Review) RAFAAT H. KHALIL1 and NABIL AL-HUMADI2 1Department of Biology, College of Science and Technology, Florida Agricultural and Mechanical University, Tallahassee, FL 32307; 2Office of Vaccines, Food and Drug Administration, Center for Biologics Evaluation and Research, Silver Spring, MD 20993, USA Received May 10, 2019; Accepted November 25, 2019 DOI: 10.3892/br.2020.1276 Abstract. Vaccines are considered to be one of the most human and veterinary medicine. Proteins which are expressed cost-effective life-saving interventions in human history. in the acute phase are potential biomarkers for the diagnosis The body's inflammatory response to vaccines has both of inflammatory disease, for example, acute phase proteins desired effects (immune response), undesired effects [(acute (APPs) are indicators of successful organ transplantation phase reactions (APRs)] and trade‑offs. Trade‑offs are and can be used to predict the ameliorative effect of cancer more potent immune responses which may be potentially therapy (1,2). APPs are primarily synthesized in hepatocytes. difficult to separate from potent acute phase reactions. The acute phase response is a spontaneous reaction triggered Thus, studying acute phase proteins (APPs) during vaccina- by disrupted homeostasis resulting from environmental distur- tion may aid our understanding of APRs and homeostatic bances (3). Acute phase reactions (APRs) usually stabilize changes which can result from inflammatory responses. quickly, after recovering from a disruption to homeostasis Depending on the severity of the response in humans, these within a few days to weeks; however, APPs expression levels reactions can be classified as major, moderate or minor. -
Genome-Wide Analysis of 5-Hmc in the Peripheral Blood of Systemic Lupus Erythematosus Patients Using an Hmedip-Chip
INTERNATIONAL JOURNAL OF MOLECULAR MEDICINE 35: 1467-1479, 2015 Genome-wide analysis of 5-hmC in the peripheral blood of systemic lupus erythematosus patients using an hMeDIP-chip WEIGUO SUI1*, QIUPEI TAN1*, MING YANG1, QIANG YAN1, HUA LIN1, MINGLIN OU1, WEN XUE1, JIEJING CHEN1, TONGXIANG ZOU1, HUANYUN JING1, LI GUO1, CUIHUI CAO1, YUFENG SUN1, ZHENZHEN CUI1 and YONG DAI2 1Guangxi Key Laboratory of Metabolic Diseases Research, Central Laboratory of Guilin 181st Hospital, Guilin, Guangxi 541002; 2Clinical Medical Research Center, the Second Clinical Medical College of Jinan University (Shenzhen People's Hospital), Shenzhen, Guangdong 518020, P.R. China Received July 9, 2014; Accepted February 27, 2015 DOI: 10.3892/ijmm.2015.2149 Abstract. Systemic lupus erythematosus (SLE) is a chronic, Introduction potentially fatal systemic autoimmune disease characterized by the production of autoantibodies against a wide range Systemic lupus erythematosus (SLE) is a typical systemic auto- of self-antigens. To investigate the role of the 5-hmC DNA immune disease, involving diffuse connective tissues (1) and modification with regard to the onset of SLE, we compared is characterized by immune inflammation. SLE has a complex the levels 5-hmC between SLE patients and normal controls. pathogenesis (2), involving genetic, immunologic and envi- Whole blood was obtained from patients, and genomic DNA ronmental factors. Thus, it may result in damage to multiple was extracted. Using the hMeDIP-chip analysis and valida- tissues and organs, especially the kidneys (3). SLE arises from tion by quantitative RT-PCR (RT-qPCR), we identified the a combination of heritable and environmental influences. differentially hydroxymethylated regions that are associated Epigenetics, the study of changes in gene expression with SLE. -
Influence of Infection and Inflammation on Biomarkers of Nutritional Status
A2.4 INFLUENCE OF INFECTION AND INFLAMMATION ON BIOMARKERS OF NUTRITIONAL STATUS A2.4 Influence of infection and inflammation on biomarkers of nutritional status with an emphasis on vitamin A and iron David I. Thurnham1 and George P. McCabe2 1 Northern Ireland Centre for Food and Health, University of Ulster, Coleraine, United Kingdom of Great Britain and Northern Ireland 2 Statistics Department, Purdue University, West Lafayette, Indiana, United States of America Corresponding author: David I. Thurnham; [email protected] Suggested citation: Thurnham DI, McCabe GP. Influence of infection and inflammation on biomarkers of nutritional status with an emphasis on vitamin A and iron. In: World Health Organization. Report: Priorities in the assessment of vitamin A and iron status in populations, Panama City, Panama, 15–17 September 2010. Geneva, World Health Organization, 2012. Abstract n Many plasma nutrients are influenced by infection or tissue damage. These effects may be passive and the result of changes in blood volume and capillary permeability. They may also be the direct effect of metabolic alterations that depress or increase the concentration of a nutrient or metabolite in the plasma. Where the nutrient or metabolite is a nutritional biomarker as in the case of plasma retinol, a depression in retinol concentrations will result in an overestimate of vitamin A deficiency. In contrast, where the biomarker is increased due to infection as in the case of plasma ferritin concentrations, inflammation will result in an underestimate of iron deficiency. Infection and tissue damage can be recognized by their clinical effects on the body but, unfortunately, subclinical infection or inflammation can only be recognized by measur- ing inflammation biomarkers in the blood. -
Role of Myeloid-Derived Suppressor Cells in Tumor-Associated Pregnancy
MASTER THESIS IN MEDECINE No 747 Role of Myeloid-Derived Suppressor Cells in tumor-associated pregnancy Student Sabine Waeber Tutor Prof. Ivan Stamenkovic Institute of Pathology, CHUV Supervisor Marie-Aude Le Bitoux, Postdoctoral Fellow Expert Prof. Michel Aguet Institute of Pathology, EPFL-ISREC Lausanne, December 2012 1 ABSTRACT 3 INTRODUCTION 4 1. Tumor-host interactions ......................................................................................................................... 4 2. Metastasis during pregnancy .................................................................................................................. 4 3. Immunity & pregnancy ........................................................................................................................... 5 4. MDSC and their potential role in pregnancy .......................................................................................... 5 SPECIFIC AIMS OF THE STUDY 7 RESULTS & DISCUSSION 8 1. Gene expression profiles of MDSC extracted from pregnant mice display features that may augment permissiveness for tumor progression ............................................................................................................. 8 1.1. Results 8 1.1.1. Enrichment of MDSC 8 1.1.2. Hybridization on Affymetrix microarrays 9 1.1.3. Validation of microarray results by qReal-Time RT-PCR 11 1.1.4. Comparison of MDSC genes expressed in pregnant and tumor-bearing mice 12 1.2. Discussion 13 2. MDSC functions during human pregnancy ......................................................................................... -
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 -
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. -
Supplementary Table 3 Complete List of RNA-Sequencing Analysis of Gene Expression Changed by ≥ Tenfold Between Xenograft and Cells Cultured in 10%O2
Supplementary Table 3 Complete list of RNA-Sequencing analysis of gene expression changed by ≥ tenfold between xenograft and cells cultured in 10%O2 Expr Log2 Ratio Symbol Entrez Gene Name (culture/xenograft) -7.182 PGM5 phosphoglucomutase 5 -6.883 GPBAR1 G protein-coupled bile acid receptor 1 -6.683 CPVL carboxypeptidase, vitellogenic like -6.398 MTMR9LP myotubularin related protein 9-like, pseudogene -6.131 SCN7A sodium voltage-gated channel alpha subunit 7 -6.115 POPDC2 popeye domain containing 2 -6.014 LGI1 leucine rich glioma inactivated 1 -5.86 SCN1A sodium voltage-gated channel alpha subunit 1 -5.713 C6 complement C6 -5.365 ANGPTL1 angiopoietin like 1 -5.327 TNN tenascin N -5.228 DHRS2 dehydrogenase/reductase 2 leucine rich repeat and fibronectin type III domain -5.115 LRFN2 containing 2 -5.076 FOXO6 forkhead box O6 -5.035 ETNPPL ethanolamine-phosphate phospho-lyase -4.993 MYO15A myosin XVA -4.972 IGF1 insulin like growth factor 1 -4.956 DLG2 discs large MAGUK scaffold protein 2 -4.86 SCML4 sex comb on midleg like 4 (Drosophila) Src homology 2 domain containing transforming -4.816 SHD protein D -4.764 PLP1 proteolipid protein 1 -4.764 TSPAN32 tetraspanin 32 -4.713 N4BP3 NEDD4 binding protein 3 -4.705 MYOC myocilin -4.646 CLEC3B C-type lectin domain family 3 member B -4.646 C7 complement C7 -4.62 TGM2 transglutaminase 2 -4.562 COL9A1 collagen type IX alpha 1 chain -4.55 SOSTDC1 sclerostin domain containing 1 -4.55 OGN osteoglycin -4.505 DAPL1 death associated protein like 1 -4.491 C10orf105 chromosome 10 open reading frame 105 -4.491 -
Supplementary Materials
1 Supplementary Materials: Supplemental Figure 1. Gene expression profiles of kidneys in the Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice. (A) A heat map of microarray data show the genes that significantly changed up to 2 fold compared between Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice (N=4 mice per group; p<0.05). Data show in log2 (sample/wild-type). 2 Supplemental Figure 2. Sting signaling is essential for immuno-phenotypes of the Fcgr2b-/-lupus mice. (A-C) Flow cytometry analysis of splenocytes isolated from wild-type, Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice at the age of 6-7 months (N= 13-14 per group). Data shown in the percentage of (A) CD4+ ICOS+ cells, (B) B220+ I-Ab+ cells and (C) CD138+ cells. Data show as mean ± SEM (*p < 0.05, **p<0.01 and ***p<0.001). 3 Supplemental Figure 3. Phenotypes of Sting activated dendritic cells. (A) Representative of western blot analysis from immunoprecipitation with Sting of Fcgr2b-/- mice (N= 4). The band was shown in STING protein of activated BMDC with DMXAA at 0, 3 and 6 hr. and phosphorylation of STING at Ser357. (B) Mass spectra of phosphorylation of STING at Ser357 of activated BMDC from Fcgr2b-/- mice after stimulated with DMXAA for 3 hour and followed by immunoprecipitation with STING. (C) Sting-activated BMDC were co-cultured with LYN inhibitor PP2 and analyzed by flow cytometry, which showed the mean fluorescence intensity (MFI) of IAb expressing DC (N = 3 mice per group). 4 Supplemental Table 1. Lists of up and down of regulated proteins Accession No. -
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, -
Chromosomal Rearrangements Are Commonly Post-Transcriptionally Attenuated in Cancer
bioRxiv preprint doi: https://doi.org/10.1101/093369; this version posted February 1, 2017. 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. Chromosomal rearrangements are commonly post-transcriptionally attenuated in cancer 1 3 1 3, 4, 5 Emanuel Gonçalves , Athanassios Fragoulis , Luz Garcia-Alonso , Thorsten Cramer , 1,2# 1# Julio Saez-Rodriguez , Pedro Beltrao 1 European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Cambridge CB10 1SD, UK 2 RWTH Aachen University, Faculty of Medicine, Joint Research Centre for Computational Biomedicine, Aachen 52057, Germany 3 Molecular Tumor Biology, Department of General, Visceral and Transplantation Surgery, RWTH University Hospital, Pauwelsstraße 30, 52074 Aachen, Germany 4 NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands 5 ESCAM – European Surgery Center Aachen Maastricht, Germany and The Netherlands # co-last authors: [email protected]; [email protected] Running title: Chromosomal rearrangement attenuation in cancer Keywords: Cancer; Gene dosage; Proteomics; Copy-number variation; Protein complexes 1 bioRxiv preprint doi: https://doi.org/10.1101/093369; this version posted February 1, 2017. 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. Abstract Chromosomal rearrangements, despite being detrimental, are ubiquitous in cancer and often act as driver events. -
LEUKOCYTE SURFACE ORIGIN of HUMAN At-ACID GLYCOPROTEIN (OROSOMUCOID)*
LEUKOCYTE SURFACE ORIGIN OF HUMAN at-ACID GLYCOPROTEIN (OROSOMUCOID)* BY CARL G. GAHMBERG AND LEIF C. ANDERSSON (From the Department of Bacteriology and Immunology, and the Transplantation Laboratory, Department of Surgery IV, University of Helsinki, Helsinki 29, Finland) Human al-acid glycoprotein (orosomucoid) (o~I-AG)1 constitutes the main component of the seromucoid fraction of human plasma. It belongs to the acute phase proteins, which increase under conditions such as inflammation, pregnancy, and cancer (1, 2). al-AG has previously been found to be synthesized in liver (3), and after removal of terminal sialic acids, it is cleared from the circulation by binding to a receptor protein on liver cell plasma membranes (4). The structure of al-AG is well known. It is composed of a single polypeptide chain and contains 245% carbohydrate including a large amount of sialic acid. The carbohydrate is located in the first half of the peptide chain linked to asparagine residues (5, 6). The function of al-AG is unclear. However, Schmid et al. (5) and Ikenaka et al. (7) and reported that the amino acid sequence of the protein shows a significant homology with human IgG. This finding and the striking increase in inflammatory and lymphopro- liferative disorders made us consider the possibility that leukocytes could be directly involved in the synthesis and release of a~-AG. We report here the presence of a membrane form of al-AG, with an apparent tool wt of 52,000, on normal human lymphocytes, granulocytes, and monocytes. By the use of internal labeling with [3H]leucine in vitro, we demonstrate that the membrane protein is synthesized by lymphocytes. -
Downloaded from Bioscientifica.Com at 09/25/2021 07:25:24AM Via Free Access 812 M Andreassen and Others EUROPEAN JOURNAL of ENDOCRINOLOGY (2012) 166
European Journal of Endocrinology (2012) 166 811–819 ISSN 0804-4643 CLINICAL STUDY GH activity and markers of inflammation: a crossover study in healthy volunteers treated with GH and a GH receptor antagonist Mikkel Andreassen1, Jan Frystyk2,3, Jens Faber1,4 and Lars Østergaard Kristensen1 1Endocrine Unit, Laboratory of Endocrinology 54o4, Department of Internal Medicine O, Herlev Hospital, University of Copenhagen, Herlev Ringvej 75, DK-2730 Herlev, Denmark, 2Department of Endocrinology and Internal Medicine, Aarhus University Hospital, Aarhus, Denmark and 3Medical Research Laboratories, Faculty of Health Sciences, Institute of Clinical Medicine, Aarhus University, Aarhus, Denmark and 4Faculty of Health Science, Copenhagen University, Copenhagen, Denmark (Correspondence should be addressed to M Andreassen; Email: [email protected]) Abstract Introduction: The GH/IGF1 axis may modulate inflammatory processes. However, the relationship seems complicated as both pro- and anti-inflammatory effects have been demonstrated. Methods/design: Twelve healthy volunteers (mean age 36, range 27–49 years) were treated in random order with increasing doses of GH for 3 weeks (first week 0.01 mg/kg per day, second week 0.02 mg/kg per day, and third week 0.03 mg/kg per day) or a GH receptor antagonist (pegvisomant; first week 10 mg/day and last two weeks 15 mg/day), separated by 8 weeks of washout. Circulating levels of the pro-inflammatory cytokines tumor necrosis factor a (TNFa (TNFA)), interleukin 6 (IL6), and IL1b (IL1B) and the acute phase proteins (APPs) C-reactive protein (CRP), haptoglobin, orosomucoid, YKL40 (CHI3L1), and fibrinogen were measured. Results: During GH treatment, IGF1 (median 131 (Inter-quartile range (IQR) 112–166) vs 390 (322– 524) mg/l, PZ0.002) increased together with TNFa (0.87 (0.74–1.48) vs 1.27 (0.80–1.69) ng/l, PZ0.003), IL6 (1.00 (0.83–1.55) vs 1.35 (0.80–4.28) ng/l, PZ0.045), and fibrinogen (9.2 (8.8–9.6) vs 11.1 (9.4–12.4) mM, PZ0.002).