Supp Tables.Pdf

Total Page:16

File Type:pdf, Size:1020Kb

Supp Tables.Pdf Supplemental Table 1 Inflammation KEGG ID Title Gene Count KEGG:mmu04662 B cell receptor signaling pathway 20 KEGG:mmu04060 Cytokine-cytokine receptor interaction 44 KEGG:mmu04010 MAPK signaling pathway 55 KEGG:mmu04650 Natural killer cell mediated cytotoxicity 30 KEGG:mmu04620 Toll-like receptor signaling pathway 36 133 unique genes Gene IDs locus description expression KO/WT 109689 Arrb1 arrestin, beta 1 0.741 216869 Arrb2 arrestin, beta 2 0.681 11911 Atf4 activating transcription factor 4 0.118 12042 Bcl10 B-cell leukemia/lymphoma 10 0.625 12122 Bid BH3 interacting domain death agonist 0.743 12370 Casp8 caspase 8 1.378 20296 Ccl2 chemokine (C-C motif) ligand 2 60.632 20301 Ccl27a chemokine (C-C motif) ligand 27A 0.676 20302 Ccl3 chemokine (C-C motif) ligand 3 2.549 20303 Ccl4 chemokine (C-C motif) ligand 4 2.4 20304 Ccl5 chemokine (C-C motif) ligand 5 0.405 20305 Ccl6 chemokine (C-C motif) ligand 6 5.443 20306 Ccl7 chemokine (C-C motif) ligand 7 101.398 20307 Ccl8 chemokine (C-C motif) ligand 8 24.988 20308 Ccl9 chemokine (C-C motif) ligand 9 1.361 12774 Ccr5 chemokine (C-C motif) receptor 5 6.792 21939 Cd40 CD40 antigen 0.6845 12506 Cd48 CD48 antigen 0.523 12517 Cd72 CD72 antigen 0.326 12524 Cd86 CD86 antigen 3 12977 Csf1 colony stimulating factor 1 (macrophage) 6.425 12978 Csf1r colony stimulating factor 1 receptor 0.492 12983 Csf2rb colony stimulating factor 2 receptor, beta, 0.607 13051 Cx3cr1 chemokine (C-X3-C) receptor 1 0.568 14825 Cxcl1 chemokine (C-X-C motif) ligand 1 1.479 15945 Cxcl10 chemokine (C(C-X-C-X-C motif) ligand 10 0.6620.662 20310 Cxcl2 chemokine (C-X-C motif) ligand 2 1.39 17329 Cxcl9 chemokine (C-X-C motif) ligand 9 0.604 13163 Daxx Fas death domain-associated protein 0.647 13198 Ddit3 DNA-damage inducible transcript 3 1.593 19252 Dusp1 dual specificity phosphatase 1 0.422 70686 Dusp16 dual specificity phosphatase 16 1.262 319520 Dusp4 dual specificity phosphatase 4 0.689 67603 Dusp6 dual specificity phosphatase 6 1.924 14127 Fcer1g Fc receptor, IgE, high affinity I, gamma po0.002 14130 Fcgr2b Fc receptor, IgG, low affinity IIb 1.78 14131 Fcgr3 Fc receptor, IgG, low affinity III 4.466 192176 Flna filamin, alpha 0.694 286940 Flnb filamin, beta 0.7445 14281 Fos FBJ osteosarcoma oncogene 0.673 17873 Gadd45b growth arrest and DNA-damage-inducible0.701 23882 Gadd45g growth arrest and DNA-damage-inducible0.566 14964 H2-D1 histocompatibility 2, D region locus 1 0.702 15040 H2-T23 histocompatibility 2, T region locus 23 1.358 23900 Hcst hematopoietic cell signal transducer 0.737 15896 Icam2 intercellular adhesion molecule 2 0.626 15979 Ifngr1 interferon gamma receptor 1 0.387 56489 Ikbke inhibitor of kappaB kinase epsilon 0.504 16154 Il10ra interleukin 10 receptor, alpha 0.236 16157 Il11ra1 interleukin 11 receptor, alpha chain 1 1.346 16173 Il18 interleukin 18 1.329 16175 Il1a interleukin 1 alpha 5.595 16176 Il1b interleukin 1 beta 4.626 16188 Il3ra interleukin 3 receptor, alpha chain 0.574 16194 Il6ra interleukin 6 receptor, alpha 0.695 16197 Il7r interleukin 7 receptor 1.409 16323 Inhba inhibin beta-A 8.497 16331 Inpp5d inositol polyphosphate-5-phosphatase D 0.617 16179 Irak1 interleukin-1 receptor-associated kinase 10.738 266632 Irak4 interleukin-1 receptor-associated kinase 40.708 54131 Irf3 interferon regulatory factor 3 0.714 27056 Irf5 interferon regulatory factor 5 0.397 54123 Irf7 interferon regulatory factor 7 1.75 16590 Kit kit oncogene 0.475 16634 Klra3 killer cell lectin-like receptor, subfamily A, 0.573 16653 Kras v-Ki-ras2 Kirsten rat sarcoma viral oncoge2.362 240354 Malt1 mucosa associated lymphoid tissue lymph1.51 23938 Map2k5 mitogen-activated protein kinase kinase 50.733 26401 Map3k1 mitogen-activated protein kinase kinase k 0.755 53859 Map3k14 mitogen-activated protein kinase kinase k 0.512 53608 Map3k6 mitogen-activated protein kinase kinase k 0.605 26410 Map3k8 mitogen-activated protein kinase kinase k 0.471 26412 Map4k2 mitogen-activated protein kinase kinase k 0.71 225028 Map4k3 mitogen-activated protein kinase kinase k 0.643 26413 Mapk1 mitogen-activated protein kinase 1 0.719 26416 Mapk14 mitogen-activated protein kinase 14 0.407 26417 Mapk3 mitogen-activated protein kinase 3 0.658 26419 Mapk8 mitogen-activated protein kinase 8 1.423 26420 Mapk9 mitogen-activated protein kinase 9 0.751 17164 Mapkapk2 MAP kinase-activated protein kinase 2 0.518 102626 Mapkapk3 mitogen-activated protein kinase-activated0.606 17260 Mef2c myocyte enhancer factor 2C 1.394 17347 Mknk2 MAP kinase-interacting serine/threonine k0.639 18018 Nfatc1 nuclear factor of activated T-cells, cytopla0.672 18035 Nfkbia nuclear factor of kappa light polypeptide g0.709 18413 Osm oncostatin M 3.691 18479 Pak1 p21 protein (Cdc42/Rac)-activated kinase0.647 18590 Pdgfa platelet derived growth factor, alpha 1.868 54635 Pdgfc platelet-derived growth factor, C polypept 2.225 18707 Pik3cd phosphatidylinositol 3-kinase catalytic del 0.719 30955 Pik3cg phosphoinositide-3-kinase, catalytic, gam 0.712 18709 Pik3r2 phosphatidylinositol 3-kinase, regulatory s0.703 234779 Plcg2 phospholipase C, gamma 2 0.75 19043 Ppm1b protein phosphatase 1B, magnesium depe1.374 19055 Ppp3ca protein phosphatase 3, catalytic subunit, a0.694 19056 Ppp3cb protein phosphatase 3, catalytic subunit, b0.762 19058 Ppp3r1pp proteinpp phosphatasep 3, regulatory subunit1.689 18751 Prkcb protein kinase C, beta 0.348 19229 Ptk2b PTK2 protein tyrosine kinase 2 beta 0.571 15170 Ptpn6 protein tyrosine phosphatase, non-recepto0.518 320139 Ptpn7 protein tyrosine phosphatase, non-recepto1.496 19353 Rac1 RAS-related C3 botulinum substrate 1 0.698 19369 Raet1b retinoic acid early transcript beta 1.412 19370 Raet1c retinoic acid early transcript gamma 2.977 110157 Raf1 v-raf-leukemia viral oncogene 1 0.47 19419 Rasgrp1 RAS guanyl releasing protein 1 0.532 240168 Rasgrp3 RAS, guanyl releasing protein 3 1.418 233046 Rasgrp4 RAS guanyl releasing protein 4 0.567 19697 Rela v-rel reticuloendotheliosis viral oncogene 0.728 19766 Ripk1 receptor (TNFRSF)-interacting serine-thre0.741 20111 Rps6ka1 ribosomal protein S6 kinase polypeptide 10.505 73086 Rps6ka5 ribosomal protein S6 kinase, polypeptide 0.611 20130 Rras Harvey rat sarcoma oncogene, subgroup 0.601 26904 Sh2d1b1 SH2 domain protein 1B1 0.575 20750 Spp1 secreted phosphoprotein 1 1.337 20846 Stat1 signal transducer and activator of transcri 0.689 16765 Stmn1 stathmin 1 1.473 68652 Tab2 TGF-beta activated kinase 1/MAP3K7 bin0.752 21803 Tgfb1 transforming growth factor, beta 1 0.71 21812 Tgfbr1 transforming growth factor, beta receptor 0.765 21813 Tgfbr2 transforming growth factor, beta receptor 1.773 106759 Ticam1 toll-like receptor adaptor molecule 1 0.697 225471 Ticam2 toll-like receptor adaptor molecule 2 0.739 21899 Tlr6 toll-like receptor 6 0.695 170744 Tlr8 toll-like receptor 8 0.731 18383 Tnfrsf11b tumor necrosis factor receptor superfamily4.188 27279 Tnfrsf12a tumor necrosis factor receptor superfamily1.455 21937 Tnfrsf1a tumor necrosis factor receptor superfamily0.71 21938 Tnfrsf1b tumor necrosis factor receptor superfamily0.441 94185 Tnfrsf21 tumor necrosis factor receptor superfamily0.722 24099 Tnfsf13b tumor necrosis factor (ligand) superfamily 1.84 50930 Tnfsf14 tumor necrosis factor (ligand) superfamily 2.022 22339 Vegfa vascular endothelial growth factor A 0.698 Differentiation Apoptosis Cancer KEGG ID Title Gene Count KEGG:mmu04115 p53 signaling 18 KEGG:mmu04210 Apoptosis 28 KEGG:mmu04110 Cell cycle 29 KEGG:mmu05220 Chronic myeloid leukemia 20 KEGG:mmu05210 Colorectal cancer 21 KEGG:mmu05212 Pancreatic cancer 23 KEGG:mmu05211 Renal cell carcinoma 19 92 unique genes Gene IDs locus description expression KO/WT 72993 Appl1 adaptor protein, phosphotyrosine interacti1.329 11863 Arnt aryl hydrocarbon receptor nuclear transloc0.757 11920 Atm ataxia telangiectasia mutated homolog (h 0.605 12015 Bad BCL2-associated agonist of cell death 0.748 170770 Bbc3 BCL2 binding component 3 0.623 12043 Bcl2 B-cell leukemia/lymphoma 2 1.406 12048 Bcl2l1 BCL2-like 1 1.56 12122 Bid BH3 interacting domain death agonist 0.743 11797 Birc2 baculoviral IAP repeat-containing 2 0.65 11799 Birc5 baculoviral IAP repeat-containing 5 1.313 12368 Casp6 caspase 6 0.587 12370 Casp8 caspase 8 1.378 268697 Ccnb1 cyclin B1 1.575 12443 Ccnd1 cyclin D1 2.234 12452 Ccng2 cyclin G2 0.451 12521 Cd82 CD82 antigen 0.635 52563 Cdc23 CDC23 (cell division cycle 23, yeast, hom1.551 12544 Cdc45l cell division cycle 45 homolog (S. cerevisi1.429 23834 Cdc6 cell division cycle 6 homolog (S. cerevisia1.811 12545 Cdc7 cell division cycle 7 (S. cerevisiae) 1.511 12534 Cdk1 cyclincyclin-dependent-dependent kinase 1 1.451.45 12575 Cdkn1a cyclin-dependent kinase inhibitor 1A (P210.681 12577 Cdkn1c cyclin-dependent kinase inhibitor 1C (P570.295 12579 Cdkn2b cyclin-dependent kinase inhibitor 2B (p15 0.402 12983 Csf2rb colony stimulating factor 2 receptor, beta, 0.607 13555 E2f1 E2F transcription factor 1 1.688 242705 E2f2 E2F transcription factor 2 0.425 112407 Egln3 EGL nine homolog 3 (C. elegans) 0.497 13663 Ei24 etoposide induced 2.4 mRNA 0.735 23871 Ets1 E26 avian leukemia oncogene 1, 5 domai 0.519 14194 Fh1 fumarate hydratase 1 1.343 14281 Fos FBJ osteosarcoma oncogene 0.673 14367 Fzd5 frizzled homolog 5 (Drosophila) 1.451 56371 Fzr1 fizzy/cell division cycle 20 related 1 (Droso0.72 14388 Gab1 growth factor receptor bound protein 2-as 3.013 17873 Gadd45b growth arrest and DNA-damage-inducible0.701 23882 Gadd45g growth arrest and DNA-damage-inducible0.566 29870 Gtse1 G two S phase expressed protein 1 1.325 16175 Il1a interleukin 1 alpha 5.595 16176 Il1b interleukin
Recommended publications
  • RT² Profiler PCR Array (384-Well Format) Human Apoptosis 384HT
    RT² Profiler PCR Array (384-Well Format) Human Apoptosis 384HT Cat. no. 330231 PAHS-3012ZE For pathway expression analysis Format For use with the following real-time cyclers RT² Profiler PCR Array, Applied Biosystems® models 7900HT (384-well block), Format E ViiA™ 7 (384-well block); Bio-Rad CFX384™ RT² Profiler PCR Array, Roche® LightCycler® 480 (384-well block) Format G Description The Human Apoptosis RT² Profiler PCR Array profiles the expression of 370 key genes involved in apoptosis, or programmed cell death. The array includes the TNF ligands and their receptors; members of the bcl-2 family, BIR (baculoviral IAP repeat) domain proteins, CARD domain (caspase recruitment domain) proteins, death domain proteins, TRAF (TNF receptor-associated factor) domain proteins and caspases. These 370 genes are also grouped by their functional contribution to apoptosis, either anti-apoptosis or induction of apoptosis. Using real-time PCR, you can easily and reliably analyze expression of a focused panel of genes related to apoptosis with this array. For further details, consult the RT² Profiler PCR Array Handbook. Sample & Assay Technologies Shipping and storage RT² Profiler PCR Arrays in formats E and G are shipped at ambient temperature, on dry ice, or blue ice packs depending on destination and accompanying products. For long term storage, keep plates at –20°C. Note: Ensure that you have the correct RT² Profiler PCR Array format for your real-time cycler (see table above). Note: Open the package and store the products appropriately immediately
    [Show full text]
  • ARTICLES Fibroblast Growth Factors 1, 2, 17, and 19 Are The
    0031-3998/07/6103-0267 PEDIATRIC RESEARCH Vol. 61, No. 3, 2007 Copyright © 2007 International Pediatric Research Foundation, Inc. Printed in U.S.A. ARTICLES Fibroblast Growth Factors 1, 2, 17, and 19 Are the Predominant FGF Ligands Expressed in Human Fetal Growth Plate Cartilage PAVEL KREJCI, DEBORAH KRAKOW, PERTCHOUI B. MEKIKIAN, AND WILLIAM R. WILCOX Medical Genetics Institute [P.K., D.K., P.B.M., W.R.W.], Cedars-Sinai Medical Center, Los Angeles, California 90048; Department of Obstetrics and Gynecology [D.K.] and Department of Pediatrics [W.R.W.], UCLA School of Medicine, Los Angeles, California 90095 ABSTRACT: Fibroblast growth factors (FGF) regulate bone growth, (G380R) or TD (K650E) mutations (4–6). When expressed at but their expression in human cartilage is unclear. Here, we deter- physiologic levels, FGFR3-G380R required, like its wild-type mined the expression of entire FGF family in human fetal growth counterpart, ligand for activation (7). Similarly, in vitro cul- plate cartilage. Using reverse transcriptase PCR, the transcripts for tivated human TD chondrocytes as well as chondrocytes FGF1, 2, 5, 8–14, 16–19, and 21 were found. However, only FGF1, isolated from Fgfr3-K644M mice had an identical time course 2, 17, and 19 were detectable at the protein level. By immunohisto- of Fgfr3 activation compared with wild-type chondrocytes and chemistry, FGF17 and 19 were uniformly expressed within the showed no receptor activation in the absence of ligand (8,9). growth plate. In contrast, FGF1 was found only in proliferating and hypertrophic chondrocytes whereas FGF2 localized predominantly to Despite the importance of the FGF ligand for activation of the resting and proliferating cartilage.
    [Show full text]
  • Cytokine Nomenclature
    RayBiotech, Inc. The protein array pioneer company Cytokine Nomenclature Cytokine Name Official Full Name Genbank Related Names Symbol 4-1BB TNFRSF Tumor necrosis factor NP_001552 CD137, ILA, 4-1BB ligand receptor 9 receptor superfamily .2. member 9 6Ckine CCL21 6-Cysteine Chemokine NM_002989 Small-inducible cytokine A21, Beta chemokine exodus-2, Secondary lymphoid-tissue chemokine, SLC, SCYA21 ACE ACE Angiotensin-converting NP_000780 CD143, DCP, DCP1 enzyme .1. NP_690043 .1. ACE-2 ACE2 Angiotensin-converting NP_068576 ACE-related carboxypeptidase, enzyme 2 .1 Angiotensin-converting enzyme homolog ACTH ACTH Adrenocorticotropic NP_000930 POMC, Pro-opiomelanocortin, hormone .1. Corticotropin-lipotropin, NPP, NP_001030 Melanotropin gamma, Gamma- 333.1 MSH, Potential peptide, Corticotropin, Melanotropin alpha, Alpha-MSH, Corticotropin-like intermediary peptide, CLIP, Lipotropin beta, Beta-LPH, Lipotropin gamma, Gamma-LPH, Melanotropin beta, Beta-MSH, Beta-endorphin, Met-enkephalin ACTHR ACTHR Adrenocorticotropic NP_000520 Melanocortin receptor 2, MC2-R hormone receptor .1 Activin A INHBA Activin A NM_002192 Activin beta-A chain, Erythroid differentiation protein, EDF, INHBA Activin B INHBB Activin B NM_002193 Inhibin beta B chain, Activin beta-B chain Activin C INHBC Activin C NM005538 Inhibin, beta C Activin RIA ACVR1 Activin receptor type-1 NM_001105 Activin receptor type I, ACTR-I, Serine/threonine-protein kinase receptor R1, SKR1, Activin receptor-like kinase 2, ALK-2, TGF-B superfamily receptor type I, TSR-I, ACVRLK2 Activin RIB ACVR1B
    [Show full text]
  • Katalog 2015 Cover Paul Lin *Hinweis Förderung.Indd
    Product List 2015 WE LIVE SERVICE Certificates quartett owns two productions sites that are certified according to EN ISO 9001:2008 Quality management systems - Requirements EN ISO 13485:2012 + AC:2012 Medical devices - Quality management systems - Requirements for regulatory purposes GMP Conformity Our quality management guarantees products of highest quality! 2 Foreword to the quartett product list 2015 quartett Immunodiagnostika, Biotechnologie + Kosmetik Vertriebs GmbH welcomes you as one of our new business partners as well as all of our previous loyal clients. You are now member of quartett´s worldwide customers. First of all we would like to introduce ourselves to you. Founded as a family-run company in 1986, quartett ensures for more than a quarter of a century consistent quality of products. Service and support of our valued customers are our daily businesses. And we will continue! In the end 80´s quartett offered radioimmunoassay and enzyme immunoassay kits from different manufacturers in the USA. In the beginning 90´s the company changed its strategy from offering products for routine diagnostic to the increasing field of research and development. Setting up a production plant in 1997 and a second one in 2011 supported this decision. The company specialized its product profile in the field of manufacturing synthetic peptides for antibody production, peptides such as protease inhibitors, biochemical reagents and products for histology, cytology and immunohistology. All products are exclusively manufactured in Germany without outsourcing any production step. Nowadays, we expand into all other diagnostic and research fields and supply our customers in universities, government institutes, pharmaceutical and biotechnological companies, hospitals, and private doctor offices.
    [Show full text]
  • Beta-Arrestin-Mediated Signaling in the Heart
    SPECIAL ARTICLE Circ J 2008; 72: 1725–1729 Beta-Arrestin-Mediated Signaling in the Heart Priyesh A. Patel, BS; Douglas G. Tilley, PhD*; Howard A. Rockman, MD*,** Beta-arrestin is a multifunctional adapter protein well known for its role in G-protein-coupled receptor (GPCR) desensitization. Exciting new evidence indicates thatβ-arrestin is also a signaling molecule capable of initiating its own G-protein-independent signaling at GPCRs. One of the best-studiedβ-arrestin signaling pathways is the one involvingβ-arrestin-dependent activation of a mitogen-activated protein kinase cascade, the extracellular regulated kinase (ERK). ERK signaling, which is classically activated by agonist stimulation of the epidermal growth factor receptor (EGFR), can be activated by a number of GPCRs in aβ-arrestin-dependent manner. Recent work in animal models of heart failure suggests thatβ-arrestin-dependent activation of EGFR/ERK signaling by theβ-1-adrenergic receptor, and possibly the angiotensin II Type 1A receptor, are cardioprotective. Hence, a new model of signaling at cardiac GPCRs has emerged and implicates classical G-protein-mediated signaling with promoting harmful remodeling in heart failure, while concurrently linkingβ-arrestin-dependent, G-protein-inde- pendent signaling with cardioprotective effects. Based on this paradigm, a new class of drugs could be identified, termed “biased ligands”, which simultaneously block harmful G-protein signaling, while also promoting cardio- protectiveβ-arrestin-dependent signaling, leading to a potential breakthrough
    [Show full text]
  • BMC Evolutionary Biology Biomed Central
    BMC Evolutionary Biology BioMed Central Research article Open Access On the origins of arrestin and rhodopsin Carlos E Alvarez1,2,3 Address: 1Center for Molecular and Human Genetics, The Research Institute at Nationwide Children's Hospital, Columbus, OH, 43205, USA, 2Department of Pediatrics, The Ohio State University College of Medicine, Columbus, OH, 43210, USA and 3Novartis Institutes of BioMedical Research, CH-4002 Basel, Switzerland Email: Carlos E Alvarez - [email protected] Published: 29 July 2008 Received: 11 January 2008 Accepted: 29 July 2008 BMC Evolutionary Biology 2008, 8:222 doi:10.1186/1471-2148-8-222 This article is available from: http://www.biomedcentral.com/1471-2148/8/222 © 2008 Alvarez; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Background: G protein coupled receptors (GPCRs) are the most numerous proteins in mammalian genomes, and the most common targets of clinical drugs. However, their evolution remains enigmatic. GPCRs are intimately associated with trimeric G proteins, G protein receptor kinases, and arrestins. We conducted phylogenetic studies to reconstruct the history of arrestins. Those findings, in turn, led us to investigate the origin of the photosensory GPCR rhodopsin. Results: We found that the arrestin clan is comprised of the Spo0M protein family in archaea and bacteria, and the arrestin and Vps26 families in eukaryotes. The previously known animal arrestins are members of the visual/beta subfamily, which branched from the founding "alpha" arrestins relatively recently.
    [Show full text]
  • Table 2. Significant
    Table 2. Significant (Q < 0.05 and |d | > 0.5) transcripts from the meta-analysis Gene Chr Mb Gene Name Affy ProbeSet cDNA_IDs d HAP/LAP d HAP/LAP d d IS Average d Ztest P values Q-value Symbol ID (study #5) 1 2 STS B2m 2 122 beta-2 microglobulin 1452428_a_at AI848245 1.75334941 4 3.2 4 3.2316485 1.07398E-09 5.69E-08 Man2b1 8 84.4 mannosidase 2, alpha B1 1416340_a_at H4049B01 3.75722111 3.87309653 2.1 1.6 2.84852656 5.32443E-07 1.58E-05 1110032A03Rik 9 50.9 RIKEN cDNA 1110032A03 gene 1417211_a_at H4035E05 4 1.66015788 4 1.7 2.82772795 2.94266E-05 0.000527 NA 9 48.5 --- 1456111_at 3.43701477 1.85785922 4 2 2.8237185 9.97969E-08 3.48E-06 Scn4b 9 45.3 Sodium channel, type IV, beta 1434008_at AI844796 3.79536664 1.63774235 3.3 2.3 2.75319499 1.48057E-08 6.21E-07 polypeptide Gadd45gip1 8 84.1 RIKEN cDNA 2310040G17 gene 1417619_at 4 3.38875643 1.4 2 2.69163229 8.84279E-06 0.0001904 BC056474 15 12.1 Mus musculus cDNA clone 1424117_at H3030A06 3.95752801 2.42838452 1.9 2.2 2.62132809 1.3344E-08 5.66E-07 MGC:67360 IMAGE:6823629, complete cds NA 4 153 guanine nucleotide binding protein, 1454696_at -3.46081884 -4 -1.3 -1.6 -2.6026947 8.58458E-05 0.0012617 beta 1 Gnb1 4 153 guanine nucleotide binding protein, 1417432_a_at H3094D02 -3.13334396 -4 -1.6 -1.7 -2.5946297 1.04542E-05 0.0002202 beta 1 Gadd45gip1 8 84.1 RAD23a homolog (S.
    [Show full text]
  • Multiple Interactions of the Cytosolic Polyproline Region of the CD95
    FEBS 25561 FEBS Letters 509 (2001) 255^262 View metadata, citation and similar papers at core.ac.uk brought to you by CORE Multiple interactions of the cytosolic polyproline region ofprovided the by CD95 Elsevier - Publisher Connector ligand: hints for the reverse signal transduction capacity of a death factor1 Jennifer Wenzela;2, Ralf Sanzenbachera;2, Markus Ghadimia, Marc Lewitzkyb, Qingchun Zhouc, David R. Kapland, Dieter Kabelitza, Stephan M. Fellerb, Ottmar Janssena;* aInstitute for Immunology, Christian-Albrechts-University, MichaelisstraMe 5, 24105 Kiel, Germany bCell Signalling Laboratory, Imperial Cancer Research Fund, University of Oxford, Institute of Molecular Medicine, John Radcli¡e Hospital, Headington, Oxford, UK cInstitute of Organic Synthesis, Center China Normal University, 430079 Wuhan, PR China dDepartment of Pathology, Case Western Reserve University, 2085 Adelbert Road, Cleveland, OH 44106, USA Received 19 September 2001; revised 7 November 2001; accepted 7 November 2001 First published online 20 November 2001 Edited by Giulio Superti-Furga regulate activation of CD4- and CD8-positive T cells in Abstract The CD95/Fas/Apo-1 ligand is expressed on activated lymphocytes, NK cells, platelets, certain immune-privileged cells vivo. Upon stimulation with T cell receptor (TCR) agonists and some tumor cells and induces apoptosis through the death in the presence of CD95, cell cycle progression of CD4-pos- receptor CD95/Fas/Apo-1. In murine T cells, membrane-bound itive cells was found to be inhibited [14^16], while CD8-pos- CD95L (Fas ligand) also acts as a costimulatory receptor to itive cells were activated to proliferate [13^16]. The molecular coordinate activation and function in vivo.
    [Show full text]
  • Disruption of Fibroblast Growth Factor Signal
    Cancer Therapy: Preclinical Disruption of Fibroblast Growth Factor Signal Pathway Inhibits the Growth of Synovial Sarcomas: Potential Application of Signal Inhibitors to MolecularTarget Therapy Ta t s u y a I s hi b e , 1, 2 Tomitaka Nakayama,2 Ta k e s h i O k a m o t o, 1, 2 Tomoki Aoyama,1Koichi Nishijo,1, 2 Kotaro Roberts Shibata,1, 2 Ya s u ko Shim a ,1, 2 Satoshi Nagayama,3 Toyomasa Katagiri,4 Yusuke Nakamura, 4 Takashi Nakamura,2 andJunya Toguchida 1 Abstract Purpose: Synovial sarcoma is a soft tissue sarcoma, the growth regulatory mechanisms of which are unknown.We investigatedthe involvement of fibroblast growth factor (FGF) signals in synovial sarcoma andevaluatedthe therapeutic effect of inhibiting the FGF signal. Experimental Design:The expression of 22 FGF and4 FGF receptor (FGFR) genes in18prima- ry tumors andfive cell lines of synovial sarcoma were analyzedby reverse transcription-PCR. Effects of recombinant FGF2, FGF8, andFGF18 for the activation of mitogen-activatedprotein kinase (MAPK) andthe growth of synovial sarcoma cell lines were analyzed.Growth inhibitory effects of FGFR inhibitors on synovial sarcoma cell lines were investigated in vitro and in vivo. Results: Synovial sarcoma cell lines expressedmultiple FGF genes especially those expressed in neural tissues, among which FGF8 showedgrowth stimulatory effects in all synovial sarcoma cell lines. FGF signals in synovial sarcoma induced the phosphorylation of extracellular signal ^ regulatedkinase (ERK1/2) andp38MAPK but not c-Jun NH 2-terminal kinase. Disruption of the FGF signaling pathway in synovial sarcoma by specific inhibitors of FGFR causedcell cycle ar- rest leading to significant growth inhibition both in vitro and in vivo.Growthinhibitionbythe FGFR inhibitor was associatedwith a down-regulation of phosphorylatedERK1/2 but not p38MAPK, andan ERK kinase inhibitor also showedgrowth inhibitory effects for synovial sar- coma, indicating that the growth stimulatory effect of FGF was transmitted through the ERK1/2.
    [Show full text]
  • Supporting Online Material
    1 2 3 4 5 6 7 Supplementary Information for 8 9 Fractalkine-induced microglial vasoregulation occurs within the retina and is altered early in diabetic 10 retinopathy 11 12 *Samuel A. Mills, *Andrew I. Jobling, *Michael A. Dixon, Bang V. Bui, Kirstan A. Vessey, Joanna A. Phipps, 13 Ursula Greferath, Gene Venables, Vickie H.Y. Wong, Connie H.Y. Wong, Zheng He, Flora Hui, James C. 14 Young, Josh Tonc, Elena Ivanova, Botir T. Sagdullaev, Erica L. Fletcher 15 * Joint first authors 16 17 Corresponding author: 18 Prof. Erica L. Fletcher. Department of Anatomy & Neuroscience. The University of Melbourne, Grattan St, 19 Parkville 3010, Victoria, Australia. 20 Email: [email protected] ; Tel: +61-3-8344-3218; Fax: +61-3-9347-5219 21 22 This PDF file includes: 23 24 Supplementary text 25 Figures S1 to S10 26 Tables S1 to S7 27 Legends for Movies S1 to S2 28 SI References 29 30 Other supplementary materials for this manuscript include the following: 31 32 Movies S1 to S2 33 34 35 36 1 1 Supplementary Information Text 2 Materials and Methods 3 Microglial process movement on retinal vessels 4 Dark agouti rats were anaesthetized, injected intraperitoneally with rhodamine B (Sigma-Aldrich) to label blood 5 vessels and retinal explants established as described in the main text. Retinal microglia were labelled with Iba-1 6 and imaging performed on an inverted confocal microscope (Leica SP5). Baseline images were taken for 10 7 minutes, followed by the addition of PBS (10 minutes) and then either fractalkine or fractalkine + candesartan 8 (10 minutes) using concentrations outlined in the main text.
    [Show full text]
  • Instability Restricts Signaling of Multiple Fibroblast Growth Factors
    Cell. Mol. Life Sci. DOI 10.1007/s00018-015-1856-8 Cellular and Molecular Life Sciences RESEARCH ARTICLE Instability restricts signaling of multiple fibroblast growth factors Marcela Buchtova • Radka Chaloupkova • Malgorzata Zakrzewska • Iva Vesela • Petra Cela • Jana Barathova • Iva Gudernova • Renata Zajickova • Lukas Trantirek • Jorge Martin • Michal Kostas • Jacek Otlewski • Jiri Damborsky • Alois Kozubik • Antoni Wiedlocha • Pavel Krejci Received: 18 June 2014 / Revised: 7 February 2015 / Accepted: 9 February 2015 Ó Springer Basel 2015 Abstract Fibroblast growth factors (FGFs) deliver ex- failure to activate FGF receptor signal transduction over tracellular signals that govern many developmental and long periods of time, and influence specific cell behavior regenerative processes, but the mechanisms regulating FGF in vitro and in vivo. Stabilization via exogenous heparin signaling remain incompletely understood. Here, we ex- binding, introduction of stabilizing mutations or lowering plored the relationship between intrinsic stability of FGF the cell cultivation temperature rescues signaling of un- proteins and their biological activity for all 18 members of stable FGFs. Thus, the intrinsic ligand instability is an the FGF family. We report that FGF1, FGF3, FGF4, FGF6, important elementary level of regulation in the FGF sig- FGF8, FGF9, FGF10, FGF16, FGF17, FGF18, FGF20, and naling system. FGF22 exist as unstable proteins, which are rapidly de- graded in cell cultivation media. Biological activity of Keywords Fibroblast growth factor Á FGF Á Unstable Á FGF1, FGF3, FGF4, FGF6, FGF8, FGF10, FGF16, FGF17, Proteoglycan Á Regulation and FGF20 is limited by their instability, manifesting as Electronic supplementary material The online version of this article (doi:10.1007/s00018-015-1856-8) contains supplementary material, which is available to authorized users.
    [Show full text]
  • Plasma Omentin Levels Are Inversely Associated with Atherosclerosis In
    Nishimura et al. Cardiovasc Diabetol (2019) 18:167 https://doi.org/10.1186/s12933-019-0973-3 Cardiovascular Diabetology ORIGINAL INVESTIGATION Open Access Plasma omentin levels are inversely associated with atherosclerosis in type 2 diabetes patients with increased plasma adiponectin levels: a cross-sectional study Masami Nishimura1, Tomoaki Morioka1* , Mariko Hayashi1, Yoshinori Kakutani1, Yuko Yamazaki1, Masafumi Kurajoh1, Katsuhito Mori2, Shinya Fukumoto3, Atsushi Shioi4,5, Tetsuo Shoji4,5, Masaaki Inaba1,5 and Masanori Emoto1 Abstract Background: Omentin and adiponectin are among the anti-infammatory and anti-atherogenic adipokines that have potentially benefcial efects on cardiovascular disorders. Recent studies indicate a paradoxical relationship between adiponectin and cardiovascular mortality across many clinical settings including type 2 diabetes. In this study, we characterized the clinical features of type 2 diabetes patients with increased adiponectin levels and exam- ined the association between omentin and atherosclerosis in those patients. Methods: The subjects were 413 patients with type 2 diabetes. Fasting plasma omentin and total adiponectin levels were measured by enzyme-linked immunosorbent assay. The intima-media thickness (IMT) of the common carotid artery was measured by ultrasonography. The subjects were stratifed according to the median value of plasma adiponectin. Results: In high-adiponectin group, omentin levels were higher, while IMT tended to be greater than those in low- adiponectin group. The high-adiponectin group also exhibited older age, higher systolic blood pressure, lower kidney function, body mass index, and insulin resistance index compared to the low-adiponectin group. Multivariate analysis revealed that omentin levels were independently and negatively associated with IMT in high-adiponectin group, but not in low-adiponectin group, after adjusting for adiponectin levels and traditional cardiovascular risk factors.
    [Show full text]