ABSTRACT Gene Expression Profiling to Understand the Alterations In
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												  Fine Tuning by Human Cd1e of Lipid-Specific Immune ResponsesFine tuning by human CD1e of lipid-specific immune responses Federica Facciottia, Marco Cavallaria, Catherine Angénieuxb, Luis F. Garcia-Allesc, François Signorino-Gelob, Lena Angmana, Martine Gilleronc, Jacques Prandic, Germain Puzoc, Luigi Panzad, Chengfeng Xiae, Peng George Wangf, Paolo Dellabonag, Giulia Casoratig, Steven A. Porcellih, Henri de la Salleb, Lucia Moria,i,1, and Gennaro De Liberoa,1 aExperimental Immunology, Department of Biomedicine, University Hospital Basel, 4031 Basel, Switzerland; bInstitut National de la Santé et de la Recherche Médicale, Unité Mixte de Recherche S725, Biology of Human Dendritic Cells, Université de Strasbourg and Etablissement Français du Sang-Alsace, 67065 Strasbourg, France; cCentre National de la Recherche Scientifique, Institut de Pharmacologie et de Biologie Structurale, 31077 Toulouse, France; dDepartment of Chemistry, Food, Pharmaceuticals, and Pharmacology, Università del Piemonte Orientale, 28100 Novara, Italy; eState Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, Yunnan 650204, China; fDepartment of Biochemistry and Chemistry, The Ohio State University, Columbus, OH 43210; gExperimental Immunology Unit, Division of Immunology, Transplantation, and Infectious Diseases, Dipartimento di Biotecnologie (DIBIT), San Raffaele Scientific Institute, 20132 Milano, Italy; hAlbert Einstein College of Medicine, Bronx, NY 10461; and iSingapore Immunology Network, Agency for Science Technology and Research, Biopolis, Singapore 138648 Edited by Peter Cresswell, Yale University School of Medicine, New Haven, CT, and approved July 20, 2011 (received for review June 5, 2011) CD1e is a member of the CD1 family that participates in lipid an- molecules traffic to early recycling endosomes and, to a lesser tigen presentation without interacting with the T-cell receptor.
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												  Human and Mouse CD Marker Handbook Human and Mouse CD Marker Key Markers - Human Key Markers - MouseWelcome 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.
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												  Differential Physiological Role of BIN1 Isoforms in Skeletal Muscle Development, Function and RegenerationbioRxiv preprint doi: https://doi.org/10.1101/477950; this version posted December 11, 2018. 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. Differential physiological role of BIN1 isoforms in skeletal muscle development, function and regeneration Ivana Prokic1,2,3,4, Belinda Cowling1,2,3,4, Candice Kutchukian5, Christine Kretz1,2,3,4, Hichem Tasfaout1,2,3,4, Josiane Hergueux1,2,3,4, Olivia Wendling1,2,3,4, Arnaud Ferry10, Anne Toussaint1,2,3,4, Christos Gavriilidis1,2,3,4, Vasugi Nattarayan1,2,3,4, Catherine Koch1,2,3,4, Jeanne Lainné6,7, Roy Combe2,3,4,8, Laurent Tiret9, Vincent Jacquemond5, Fanny Pilot-Storck9, Jocelyn Laporte1,2,3,4 1Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Illkirch, France 2Centre National de la Recherche Scientifique (CNRS), UMR7104, Illkirch, France 3Institut National de la Santé et de la Recherche Médicale (INSERM), U1258, Illkirch, France 4Université de Strasbourg, Illkirch, France 5Univ Lyon, Université Claude Bernard Lyon 1, CNRS UMR-5310, INSERM U-1217, Institut NeuroMyoGène, 8 avenue Rockefeller, 69373 Lyon, France 6Sorbonne Université, INSERM, Institute of Myology, Centre of Research in Myology, UMRS 974, F- 75013, Paris, France 7Sorbonne Université, Department of Physiology, UPMC Univ Paris 06, Pitié-Salpêtrière Hospital, F- 75013, Paris, France 8CELPHEDIA-PHENOMIN, Institut Clinique de la Souris (ICS), Illkirch, France 9U955 – IMRB, Team 10 - Biology of the neuromuscular system, Inserm, UPEC, Ecole nationale vétérinaire d’Alfort, Maisons-Alfort, 94700, France 10Sorbonne Université, INSERM, Institute of Myology, Centre of Research in Myology, UMRS 794, F- 75013, Paris, France Correspondence to: [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/477950; this version posted December 11, 2018.
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												  Characterization of FLT3-Itdmut Acute Myeloid LeukemiaTravaglini et al. Blood Cancer Journal (2020) 10:85 https://doi.org/10.1038/s41408-020-00352-9 Blood Cancer Journal ARTICLE Open Access Characterization of FLT3-ITDmut acute myeloid leukemia: molecular profiling of leukemic precursor cells Serena Travaglini1, Daniela Francesca Angelini 2, Valentina Alfonso1, Gisella Guerrera2,SerenaLavorgna1, Mariadomenica Divona1, Anna Maria Nardozza1, Maria Irno Consalvo1, Emiliano Fabiani1,MarcoDeBardi 2, Benedetta Neri3,FabioForghieri4, Francesco Marchesi5, Giovangiacinto Paterno1, Raffaella Cerretti1, Eva Barragan 6, Valentina Fiori7,SabrinaDominici7, Maria Ilaria Del Principe1, Adriano Venditti 1, Luca Battistini2, William Arcese1, Francesco Lo-Coco1, Maria Teresa Voso 1,2 and Tiziana Ottone1,2 Abstract Acute myeloid leukemia (AML) with FLT3-ITD mutations (FLT3-ITDmut) remains a therapeutic challenge, with a still high relapse rate, despite targeted treatment with tyrosine kinase inhibitors. In this disease, the CD34/CD123/CD25/CD99+ leukemic precursor cells (LPCs) phenotype predicts for FLT3-ITD-positivity. The aim of this study was to characterize the distribution of FLT3-ITD mutation in different progenitor cell subsets to shed light on the subclonal architecture of FLT3-ITDmut AML. Using high-speed cell sorting, we sequentially purified LPCs and CD34+ progenitors in samples from patients with FLT3-ITDmut AML (n = 12). A higher FLT3-ITDmut load was observed within CD34/CD123/CD25/CD99+ LPCs, as compared to CD34+ progenitors (CD123+/−,CD25−,CD99low/−)(p = 0.0005) and mononuclear cells (MNCs) (p < 0.0001). This was associated with significantly increased CD99 mean fluorescence intensity in LPCs. 1234567890():,; 1234567890():,; 1234567890():,; 1234567890():,; Significantly higher FLT3-ITDmut burden was also observed in LPCs of AML patients with a small FLT3-ITDmut clones at diagnosis.
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												  Roles of the CSE1L-Mediated Nuclear Import Pathway in EpigeneticRoles of the CSE1L-mediated nuclear import pathway PNAS PLUS in epigenetic silencing Qiang Donga,b,c, Xiang Lia,b,c, Cheng-Zhi Wangb, Shaohua Xuc, Gang Yuanc, Wei Shaoc, Baodong Liud, Yong Zhengb, Hailin Wangd, Xiaoguang Leic,e,f, Zhuqiang Zhangb,1, and Bing Zhua,b,g,1 aGraduate Program, Peking Union Medical College and Chinese Academy of Medical Sciences, 100730 Beijing, China; bNational Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, 100101 Beijing, China; cNational Institute of Biological Sciences, 102206 Beijing, China; dThe State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, 100085 Beijing, China; eBeijing National Laboratory for Molecular Sciences, Department of Chemical Biology, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China; fPeking-Tsinghua Center for Life Sciences, Peking University, 100871 Beijing, China; and gCollege of Life Sciences, University of Chinese Academy of Sciences, 100049 Beijing, China Edited by Arthur D. Riggs, Beckman Research Institute of City of Hope, Duarte, CA, and approved March 21, 2018 (received for review January 17, 2018) Epigenetic silencing can be mediated by various mechanisms, CSE1L, a key player in the nuclear import pathway, as an es- and many regulators remain to be identified. Here, we report a sential factor for maintaining the repression of many methyl- genome-wide siRNA screening to identify regulators essential for ated genes. Mechanistically, CSE1L functions by facilitating maintaining gene repression of a CMV promoter silenced by DNA the nuclear import of certain cargo proteins that are essential methylation.
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												  Supplementary Table S1. Upregulated Genes DifferentiallySupplementary Table S1. Upregulated genes differentially expressed in athletes (p < 0.05 and 1.3-fold change) Gene Symbol p Value Fold Change 221051_s_at NMRK2 0.01 2.38 236518_at CCDC183 0.00 2.05 218804_at ANO1 0.00 2.05 234675_x_at 0.01 2.02 207076_s_at ASS1 0.00 1.85 209135_at ASPH 0.02 1.81 228434_at BTNL9 0.03 1.81 229985_at BTNL9 0.01 1.79 215795_at MYH7B 0.01 1.78 217979_at TSPAN13 0.01 1.77 230992_at BTNL9 0.01 1.75 226884_at LRRN1 0.03 1.74 220039_s_at CDKAL1 0.01 1.73 236520_at 0.02 1.72 219895_at TMEM255A 0.04 1.72 201030_x_at LDHB 0.00 1.69 233824_at 0.00 1.69 232257_s_at 0.05 1.67 236359_at SCN4B 0.04 1.64 242868_at 0.00 1.63 1557286_at 0.01 1.63 202780_at OXCT1 0.01 1.63 1556542_a_at 0.04 1.63 209992_at PFKFB2 0.04 1.63 205247_at NOTCH4 0.01 1.62 1554182_at TRIM73///TRIM74 0.00 1.61 232892_at MIR1-1HG 0.02 1.61 204726_at CDH13 0.01 1.6 1561167_at 0.01 1.6 1565821_at 0.01 1.6 210169_at SEC14L5 0.01 1.6 236963_at 0.02 1.6 1552880_at SEC16B 0.02 1.6 235228_at CCDC85A 0.02 1.6 1568623_a_at SLC35E4 0.00 1.59 204844_at ENPEP 0.00 1.59 1552256_a_at SCARB1 0.02 1.59 1557283_a_at ZNF519 0.02 1.59 1557293_at LINC00969 0.03 1.59 231644_at 0.01 1.58 228115_at GAREM1 0.01 1.58 223687_s_at LY6K 0.02 1.58 231779_at IRAK2 0.03 1.58 243332_at LOC105379610 0.04 1.58 232118_at 0.01 1.57 203423_at RBP1 0.02 1.57 AMY1A///AMY1B///AMY1C///AMY2A///AMY2B// 208498_s_at 0.03 1.57 /AMYP1 237154_at LOC101930114 0.00 1.56 1559691_at 0.01 1.56 243481_at RHOJ 0.03 1.56 238834_at MYLK3 0.01 1.55 213438_at NFASC 0.02 1.55 242290_at TACC1 0.04 1.55 ANKRD20A1///ANKRD20A12P///ANKRD20A2///
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												  Dual Proteome-Scale Networks Reveal Cell-Specific Remodeling of the Human InteractomebioRxiv preprint doi: https://doi.org/10.1101/2020.01.19.905109; this version posted January 19, 2020. 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. Dual Proteome-scale Networks Reveal Cell-specific Remodeling of the Human Interactome Edward L. Huttlin1*, Raphael J. Bruckner1,3, Jose Navarrete-Perea1, Joe R. Cannon1,4, Kurt Baltier1,5, Fana Gebreab1, Melanie P. Gygi1, Alexandra Thornock1, Gabriela Zarraga1,6, Stanley Tam1,7, John Szpyt1, Alexandra Panov1, Hannah Parzen1,8, Sipei Fu1, Arvene Golbazi1, Eila Maenpaa1, Keegan Stricker1, Sanjukta Guha Thakurta1, Ramin Rad1, Joshua Pan2, David P. Nusinow1, Joao A. Paulo1, Devin K. Schweppe1, Laura Pontano Vaites1, J. Wade Harper1*, Steven P. Gygi1*# 1Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA. 2Broad Institute, Cambridge, MA, 02142, USA. 3Present address: ICCB-Longwood Screening Facility, Harvard Medical School, Boston, MA, 02115, USA. 4Present address: Merck, West Point, PA, 19486, USA. 5Present address: IQ Proteomics, Cambridge, MA, 02139, USA. 6Present address: Vor Biopharma, Cambridge, MA, 02142, USA. 7Present address: Rubius Therapeutics, Cambridge, MA, 02139, USA. 8Present address: RPS North America, South Kingstown, RI, 02879, USA. *Correspondence: [email protected] (E.L.H.), [email protected] (J.W.H.), [email protected] (S.P.G.) #Lead Contact: [email protected] bioRxiv preprint doi: https://doi.org/10.1101/2020.01.19.905109; this version posted January 19, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder.
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												  A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes MellitusPage 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.
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												  Screening of a Clinically and Biochemically Diagnosed SOD Patient Using Exome Sequencing: a Case Report with a Mutations/Variations Analysis ApproachThe Egyptian Journal of Medical Human Genetics (2016) 17, 131–136 HOSTED BY Ain Shams University The Egyptian Journal of Medical Human Genetics www.ejmhg.eg.net www.sciencedirect.com CASE REPORT Screening of a clinically and biochemically diagnosed SOD patient using exome sequencing: A case report with a mutations/variations analysis approach Mohamad-Reza Aghanoori a,b,1, Ghazaleh Mohammadzadeh Shahriary c,2, Mahdi Safarpour d,3, Ahmad Ebrahimi d,* a Department of Medical Genetics, Shiraz University of Medical Sciences, Shiraz, Iran b Research and Development Division, RoyaBioGene Co., Tehran, Iran c Department of Genetics, Shahid Chamran University of Ahvaz, Ahvaz, Iran d Cellular and Molecular Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran Received 12 May 2015; accepted 15 June 2015 Available online 22 July 2015 KEYWORDS Abstract Background: Sulfite oxidase deficiency (SOD) is a rare neurometabolic inherited disor- Sulfite oxidase deficiency; der causing severe delay in developmental stages and premature death. The disease follows an auto- Case report; somal recessive pattern of inheritance and causes deficiency in the activity of sulfite oxidase, an Exome sequencing enzyme that normally catalyzes conversion of sulfite to sulfate. Aim of the study: SOD is an underdiagnosed disorder and its diagnosis can be difficult in young infants as early clinical features and neuroimaging changes may imitate some common diseases. Since the prognosis of the disease is poor, using exome sequencing as a powerful and efficient strat- egy for identifying the genes underlying rare mendelian disorders can provide important knowledge about early diagnosis, disease mechanisms, biological pathways, and potential therapeutic targets.
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												  Protein Identities in Evs Isolated from U87-MG GBM Cells As Determined by NG LC-MS/MSProtein identities in EVs isolated from U87-MG GBM cells as determined by NG LC-MS/MS. No. Accession Description Σ Coverage Σ# Proteins Σ# Unique Peptides Σ# Peptides Σ# PSMs # AAs MW [kDa] calc. pI 1 A8MS94 Putative golgin subfamily A member 2-like protein 5 OS=Homo sapiens PE=5 SV=2 - [GG2L5_HUMAN] 100 1 1 7 88 110 12,03704523 5,681152344 2 P60660 Myosin light polypeptide 6 OS=Homo sapiens GN=MYL6 PE=1 SV=2 - [MYL6_HUMAN] 100 3 5 17 173 151 16,91913397 4,652832031 3 Q6ZYL4 General transcription factor IIH subunit 5 OS=Homo sapiens GN=GTF2H5 PE=1 SV=1 - [TF2H5_HUMAN] 98,59 1 1 4 13 71 8,048185945 4,652832031 4 P60709 Actin, cytoplasmic 1 OS=Homo sapiens GN=ACTB PE=1 SV=1 - [ACTB_HUMAN] 97,6 5 5 35 917 375 41,70973209 5,478027344 5 P13489 Ribonuclease inhibitor OS=Homo sapiens GN=RNH1 PE=1 SV=2 - [RINI_HUMAN] 96,75 1 12 37 173 461 49,94108966 4,817871094 6 P09382 Galectin-1 OS=Homo sapiens GN=LGALS1 PE=1 SV=2 - [LEG1_HUMAN] 96,3 1 7 14 283 135 14,70620005 5,503417969 7 P60174 Triosephosphate isomerase OS=Homo sapiens GN=TPI1 PE=1 SV=3 - [TPIS_HUMAN] 95,1 3 16 25 375 286 30,77169764 5,922363281 8 P04406 Glyceraldehyde-3-phosphate dehydrogenase OS=Homo sapiens GN=GAPDH PE=1 SV=3 - [G3P_HUMAN] 94,63 2 13 31 509 335 36,03039959 8,455566406 9 Q15185 Prostaglandin E synthase 3 OS=Homo sapiens GN=PTGES3 PE=1 SV=1 - [TEBP_HUMAN] 93,13 1 5 12 74 160 18,68541938 4,538574219 10 P09417 Dihydropteridine reductase OS=Homo sapiens GN=QDPR PE=1 SV=2 - [DHPR_HUMAN] 93,03 1 1 17 69 244 25,77302971 7,371582031 11 P01911 HLA class II histocompatibility antigen,
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												  Supplemental Materials ZNF281 Enhances Cardiac ReprogrammingSupplemental Materials ZNF281 enhances cardiac reprogramming by modulating cardiac and inflammatory gene expression Huanyu Zhou, Maria Gabriela Morales, Hisayuki Hashimoto, Matthew E. Dickson, Kunhua Song, Wenduo Ye, Min S. Kim, Hanspeter Niederstrasser, Zhaoning Wang, Beibei Chen, Bruce A. Posner, Rhonda Bassel-Duby and Eric N. Olson Supplemental Table 1; related to Figure 1. Supplemental Table 2; related to Figure 1. Supplemental Table 3; related to the “quantitative mRNA measurement” in Materials and Methods section. Supplemental Table 4; related to the “ChIP-seq, gene ontology and pathway analysis” and “RNA-seq” and gene ontology analysis” in Materials and Methods section. Supplemental Figure S1; related to Figure 1. Supplemental Figure S2; related to Figure 2. Supplemental Figure S3; related to Figure 3. Supplemental Figure S4; related to Figure 4. Supplemental Figure S5; related to Figure 6. Supplemental Table S1. Genes included in human retroviral ORF cDNA library. Gene Gene Gene Gene Gene Gene Gene Gene Symbol Symbol Symbol Symbol Symbol Symbol Symbol Symbol AATF BMP8A CEBPE CTNNB1 ESR2 GDF3 HOXA5 IL17D ADIPOQ BRPF1 CEBPG CUX1 ESRRA GDF6 HOXA6 IL17F ADNP BRPF3 CERS1 CX3CL1 ETS1 GIN1 HOXA7 IL18 AEBP1 BUD31 CERS2 CXCL10 ETS2 GLIS3 HOXB1 IL19 AFF4 C17ORF77 CERS4 CXCL11 ETV3 GMEB1 HOXB13 IL1A AHR C1QTNF4 CFL2 CXCL12 ETV7 GPBP1 HOXB5 IL1B AIMP1 C21ORF66 CHIA CXCL13 FAM3B GPER HOXB6 IL1F3 ALS2CR8 CBFA2T2 CIR1 CXCL14 FAM3D GPI HOXB7 IL1F5 ALX1 CBFA2T3 CITED1 CXCL16 FASLG GREM1 HOXB9 IL1F6 ARGFX CBFB CITED2 CXCL3 FBLN1 GREM2 HOXC4 IL1F7
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												  Murine Megakaryopoiesis Is Critical for P21 SCL-Mediated Regulation OfFrom bloodjournal.hematologylibrary.org at UNIVERSITY OF BIRMINGHAM on March 1, 2012. For personal use only. 2011 118: 723-735 Prepublished online May 19, 2011; doi:10.1182/blood-2011-01-328765 SCL-mediated regulation of the cell-cycle regulator p21 is critical for murine megakaryopoiesis Hedia Chagraoui, Mira Kassouf, Sreemoti Banerjee, Nicolas Goardon, Kevin Clark, Ann Atzberger, Andrew C. Pearce, Radek C. Skoda, David J. P. Ferguson, Steve P. Watson, Paresh Vyas and Catherine Porcher Updated information and services can be found at: http://bloodjournal.hematologylibrary.org/content/118/3/723.full.html Articles on similar topics can be found in the following Blood collections Platelets and Thrombopoiesis (260 articles) Information about reproducing this article in parts or in its entirety may be found online at: http://bloodjournal.hematologylibrary.org/site/misc/rights.xhtml#repub_requests Information about ordering reprints may be found online at: http://bloodjournal.hematologylibrary.org/site/misc/rights.xhtml#reprints Information about subscriptions and ASH membership may be found online at: http://bloodjournal.hematologylibrary.org/site/subscriptions/index.xhtml Blood (print ISSN 0006-4971, online ISSN 1528-0020), is published weekly by the American Society of Hematology, 2021 L St, NW, Suite 900, Washington DC 20036. Copyright 2011 by The American Society of Hematology; all rights reserved. From bloodjournal.hematologylibrary.org at UNIVERSITY OF BIRMINGHAM on March 1, 2012. For personal use only. PLATELETS AND THROMBOPOIESIS SCL-mediated regulation of the cell-cycle regulator p21 is critical for murine megakaryopoiesis Hedia Chagraoui,1 *Mira Kassouf,1 *Sreemoti Banerjee,1 Nicolas Goardon,1 Kevin Clark,1 Ann Atzberger,1 Andrew C.