Cytogenetic Analysis of a Pseudoangiomatous Pleomorphic/Spindle Cell Lipoma
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Chemical Tools for Studying Lipid-Binding Class a G Protein–Coupled Receptors
1521-0081/69/3/316–353$25.00 https://doi.org/10.1124/pr.116.013243 PHARMACOLOGICAL REVIEWS Pharmacol Rev 69:316–353, July 2017 Copyright © 2017 by The American Society for Pharmacology and Experimental Therapeutics ASSOCIATE EDITOR: STEPHEN P. H. ALEXANDER Chemical Tools for Studying Lipid-Binding Class A G Protein–Coupled Receptors Anna Cooper, Sameek Singh, Sarah Hook, Joel D. A. Tyndall, and Andrea J. Vernall School of Pharmacy, University of Otago, Dunedin, New Zealand Abstract. ....................................................................................317 I. Introduction. ..............................................................................317 A. Cannabinoid Receptor . ..................................................................317 1. Ligand Classes. ......................................................................318 B. Free Fatty Acid Receptor ................................................................320 1. Ligand Classes. ......................................................................320 C. Lysophospholipid Receptors. ............................................................321 1. Ligand Classes. ......................................................................321 D. Prostanoid Receptor . ..................................................................321 Downloaded from 1. Ligand Classes. ......................................................................322 E. Leukotriene Receptor . ..................................................................322 1. Ligand Classes. ......................................................................322 -
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. -
System, Method and Software for Calculation of a Cannabis Drug Efficiency Index for the Reduction of Inflammation
International Journal of Molecular Sciences Article System, Method and Software for Calculation of a Cannabis Drug Efficiency Index for the Reduction of Inflammation Nicolas Borisov 1,† , Yaroslav Ilnytskyy 2,3,†, Boseon Byeon 2,3,4,†, Olga Kovalchuk 2,3 and Igor Kovalchuk 2,3,* 1 Moscow Institute of Physics and Technology, 9 Institutsky lane, Dolgoprudny, Moscow Region 141701, Russia; [email protected] 2 Department of Biological Sciences, University of Lethbridge, Lethbridge, AB T1K 3M4, Canada; [email protected] (Y.I.); [email protected] (B.B.); [email protected] (O.K.) 3 Pathway Rx., 16 Sandstone Rd. S., Lethbridge, AB T1K 7X8, Canada 4 Biomedical and Health Informatics, Computer Science Department, State University of New York, 2 S Clinton St, Syracuse, NY 13202, USA * Correspondence: [email protected] † First three authors contributed equally to this research. Abstract: There are many varieties of Cannabis sativa that differ from each other by composition of cannabinoids, terpenes and other molecules. The medicinal properties of these cultivars are often very different, with some being more efficient than others. This report describes the development of a method and software for the analysis of the efficiency of various cannabis extracts to detect the anti-inflammatory properties of the various cannabis extracts. The method uses high-throughput gene expression profiling data but can potentially use other omics data as well. According to the signaling pathway topology, the gene expression profiles are convoluted into the signaling pathway activities using a signaling pathway impact analysis (SPIA) method. The method was tested by inducing inflammation in human 3D epithelial tissues, including intestine, oral and skin, and then exposing these tissues to various extracts and then performing transcriptome analysis. -
Regulation of Immune Cells by Eicosanoid Receptors
Regulation of Immune Cells by Eicosanoid Receptors The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Kim, Nancy D., and Andrew D. Luster. 2007. “Regulation of Immune Cells by Eicosanoid Receptors.” The Scientific World Journal 7 (1): 1307-1328. doi:10.1100/tsw.2007.181. http://dx.doi.org/10.1100/ tsw.2007.181. Published Version doi:10.1100/tsw.2007.181 Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:37298366 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA Review Article Special Issue: Eicosanoid Receptors and Inflammation TheScientificWorldJOURNAL (2007) 7, 1307–1328 ISSN 1537-744X; DOI 10.1100/tsw.2007.181 Regulation of Immune Cells by Eicosanoid Receptors Nancy D. Kim and Andrew D. Luster* Center for Immunology and Inflammatory Diseases, Division of Rheumatology, Allergy, and Immunology, Massachusetts General Hospital, Harvard Medical School, Boston E-mail: [email protected] Received March 13, 2007; Revised June 14, 2007; Accepted July 2, 2007; Published September 1, 2007 Eicosanoids are potent, bioactive, lipid mediators that regulate important components of the immune response, including defense against infection, ischemia, and injury, as well as instigating and perpetuating autoimmune and inflammatory conditions. Although these lipids have numerous effects on diverse cell types and organs, a greater understanding of their specific effects on key players of the immune system has been gained in recent years through the characterization of individual eicosanoid receptors, the identification and development of specific receptor agonists and inhibitors, and the generation of mice genetically deficient in various eicosanoid receptors. -
Literature Mining Sustains and Enhances Knowledge Discovery from Omic Studies
LITERATURE MINING SUSTAINS AND ENHANCES KNOWLEDGE DISCOVERY FROM OMIC STUDIES by Rick Matthew Jordan B.S. Biology, University of Pittsburgh, 1996 M.S. Molecular Biology/Biotechnology, East Carolina University, 2001 M.S. Biomedical Informatics, University of Pittsburgh, 2005 Submitted to the Graduate Faculty of School of Medicine in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Pittsburgh 2016 UNIVERSITY OF PITTSBURGH SCHOOL OF MEDICINE This dissertation was presented by Rick Matthew Jordan It was defended on December 2, 2015 and approved by Shyam Visweswaran, M.D., Ph.D., Associate Professor Rebecca Jacobson, M.D., M.S., Professor Songjian Lu, Ph.D., Assistant Professor Dissertation Advisor: Vanathi Gopalakrishnan, Ph.D., Associate Professor ii Copyright © by Rick Matthew Jordan 2016 iii LITERATURE MINING SUSTAINS AND ENHANCES KNOWLEDGE DISCOVERY FROM OMIC STUDIES Rick Matthew Jordan, M.S. University of Pittsburgh, 2016 Genomic, proteomic and other experimentally generated data from studies of biological systems aiming to discover disease biomarkers are currently analyzed without sufficient supporting evidence from the literature due to complexities associated with automated processing. Extracting prior knowledge about markers associated with biological sample types and disease states from the literature is tedious, and little research has been performed to understand how to use this knowledge to inform the generation of classification models from ‘omic’ data. Using pathway analysis methods to better understand the underlying biology of complex diseases such as breast and lung cancers is state-of-the-art. However, the problem of how to combine literature- mining evidence with pathway analysis evidence is an open problem in biomedical informatics research. -
ECM Alterations in Fndc3a (Fibronectin Domain Containing
www.nature.com/scientificreports OPEN ECM alterations in Fndc3a (Fibronectin Domain Containing Protein 3A) defcient zebrafsh Received: 22 April 2019 Accepted: 5 September 2019 cause temporal fn development Published: xx xx xxxx and regeneration defects Daniel Liedtke 1, Melanie Orth1, Michelle Meissler1, Sinje Geuer2,3, Sabine Knaup1, Isabell Köblitz1,4 & Eva Klopocki 1 Fin development and regeneration are complex biological processes that are highly relevant in teleost fsh. They share genetic factors, signaling pathways and cellular properties to coordinate formation of regularly shaped extremities. Especially correct tissue structure defned by extracellular matrix (ECM) formation is essential. Gene expression and protein localization studies demonstrated expression of fndc3a (fbronectin domain containing protein 3a) in both developing and regenerating caudal fns of zebrafsh (Danio rerio). We established a hypomorphic fndc3a mutant line (fndc3awue1/wue1) via CRISPR/ Cas9, exhibiting phenotypic malformations and changed gene expression patterns during early stages of median fn fold development. These developmental efects are mostly temporary, but result in a fraction of adults with permanent tail fn deformations. In addition, caudal fn regeneration in adult fndc3awue1/wue1 mutants is hampered by interference with actinotrichia formation and epidermal cell organization. Investigation of the ECM implies that loss of epidermal tissue structure is a common cause for both of the observed defects. Our results thereby provide a molecular link between these developmental processes and foreshadow Fndc3a as a novel temporal regulator of epidermal cell properties during extremity development and regeneration in zebrafsh. A wide number of conserved genetic and structural features have been identifed regulating fn development in ray fnned fsh species, like zebrafsh (Danio rerio), and imply shared mechanisms throughout evolution1. -
Identification of Genomic Regions Associated with Phenotypic Variation Between Dog Breeds Using Selection Mapping
Identification of Genomic Regions Associated with Phenotypic Variation between Dog Breeds using Selection Mapping Amaury Vaysse1., Abhirami Ratnakumar2., Thomas Derrien1, Erik Axelsson2, Gerli Rosengren Pielberg2, Snaevar Sigurdsson3, Tove Fall4, Eija H. Seppa¨la¨ 5, Mark S. T. Hansen6, Cindy T. Lawley6, Elinor K. Karlsson3,7, The LUPA Consortium, Danika Bannasch8, Carles Vila` 9, Hannes Lohi5, Francis Galibert1, Merete Fredholm10, Jens Ha¨ggstro¨ m11,A˚ ke Hedhammar11, Catherine Andre´ 1, Kerstin Lindblad-Toh2,3, Christophe Hitte1, Matthew T. Webster2* 1 Institut de Ge´ne´tique et De´veloppement de Rennes, CNRS-UMR6061, Universite´ de Rennes 1, Rennes, France, 2 Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden, 3 Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America, 4 Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden, 5 Department of Veterinary Biosciences, Research Programs Unit, Molecular Medicine, University of Helsinki and Folkha¨lsan Research Center, Helsinki, Finland, 6 Illumina, San Diego, California, United States of America, 7 FAS Center for Systems Biology, Harvard University, Cambridge, Massachusetts, United States of America, 8 Department of Population Health and Reproduction, School of Veterinary Medicine, University of California Davis, Davis, California, United States of America, 9 Department of Integrative Ecology, Don˜ana Biological Station (CSIC), Seville, Spain, 10 Faculty of Life Sciences, Division of Genetics and Bioinformatics, Department of Basic Animal and Veterinary Sciences, University of Copenhagen, Frederiksberg, Denmark, 11 Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden Abstract The extraordinary phenotypic diversity of dog breeds has been sculpted by a unique population history accompanied by selection for novel and desirable traits. -
ID AKI Vs Control Fold Change P Value Symbol Entrez Gene Name *In
ID AKI vs control P value Symbol Entrez Gene Name *In case of multiple probesets per gene, one with the highest fold change was selected. Fold Change 208083_s_at 7.88 0.000932 ITGB6 integrin, beta 6 202376_at 6.12 0.000518 SERPINA3 serpin peptidase inhibitor, clade A (alpha-1 antiproteinase, antitrypsin), member 3 1553575_at 5.62 0.0033 MT-ND6 NADH dehydrogenase, subunit 6 (complex I) 212768_s_at 5.50 0.000896 OLFM4 olfactomedin 4 206157_at 5.26 0.00177 PTX3 pentraxin 3, long 212531_at 4.26 0.00405 LCN2 lipocalin 2 215646_s_at 4.13 0.00408 VCAN versican 202018_s_at 4.12 0.0318 LTF lactotransferrin 203021_at 4.05 0.0129 SLPI secretory leukocyte peptidase inhibitor 222486_s_at 4.03 0.000329 ADAMTS1 ADAM metallopeptidase with thrombospondin type 1 motif, 1 1552439_s_at 3.82 0.000714 MEGF11 multiple EGF-like-domains 11 210602_s_at 3.74 0.000408 CDH6 cadherin 6, type 2, K-cadherin (fetal kidney) 229947_at 3.62 0.00843 PI15 peptidase inhibitor 15 204006_s_at 3.39 0.00241 FCGR3A Fc fragment of IgG, low affinity IIIa, receptor (CD16a) 202238_s_at 3.29 0.00492 NNMT nicotinamide N-methyltransferase 202917_s_at 3.20 0.00369 S100A8 S100 calcium binding protein A8 215223_s_at 3.17 0.000516 SOD2 superoxide dismutase 2, mitochondrial 204627_s_at 3.04 0.00619 ITGB3 integrin, beta 3 (platelet glycoprotein IIIa, antigen CD61) 223217_s_at 2.99 0.00397 NFKBIZ nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, zeta 231067_s_at 2.97 0.00681 AKAP12 A kinase (PRKA) anchor protein 12 224917_at 2.94 0.00256 VMP1/ mir-21likely ortholog -
Downloaded from Here
bioRxiv preprint doi: https://doi.org/10.1101/017566; this version posted November 19, 2015. 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-NC-ND 4.0 International license. 1 1 Testing for ancient selection using cross-population allele 2 frequency differentiation 1;∗ 3 Fernando Racimo 4 1 Department of Integrative Biology, University of California, Berkeley, CA, USA 5 ∗ E-mail: [email protected] 6 1 Abstract 7 A powerful way to detect selection in a population is by modeling local allele frequency changes in a 8 particular region of the genome under scenarios of selection and neutrality, and finding which model is 9 most compatible with the data. Chen et al. [2010] developed a composite likelihood method called XP- 10 CLR that uses an outgroup population to detect departures from neutrality which could be compatible 11 with hard or soft sweeps, at linked sites near a beneficial allele. However, this method is most sensitive 12 to recent selection and may miss selective events that happened a long time ago. To overcome this, 13 we developed an extension of XP-CLR that jointly models the behavior of a selected allele in a three- 14 population tree. Our method - called 3P-CLR - outperforms XP-CLR when testing for selection that 15 occurred before two populations split from each other, and can distinguish between those events and 16 events that occurred specifically in each of the populations after the split. -
Genotype-Phenotype Correlations in Patients with Retinoblastoma And
Genotype-phenotype correlations in patients with Retinoblastoma and an interstitial 13q deletion Diana Mitter, Reinhard Ullmann, Artur Muradyan, Ludger Klein-Hitpaß, Deniz Kanber, Dietmar R Lohmann, Katrin Ounap, Marc Kaulisch To cite this version: Diana Mitter, Reinhard Ullmann, Artur Muradyan, Ludger Klein-Hitpaß, Deniz Kanber, et al.. Genotype-phenotype correlations in patients with Retinoblastoma and an interstitial 13q deletion. European Journal of Human Genetics, Nature Publishing Group, 2011, 10.1038/ejhg.2011.58. hal- 00633984 HAL Id: hal-00633984 https://hal.archives-ouvertes.fr/hal-00633984 Submitted on 20 Oct 2011 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. 1 Genotype-phenotype correlations in patients with Retinoblastoma and interstitial 13q deletions 1, *Diana Mitter, 2Reinhard Ullmann, 2Artur Muradyan, 3Ludger Klein-Hitpaß, 1Deniz Kanber, 4Katrin Õunap, 5Marc Kaulisch, 1Dietmar Lohmann 1Institut für Humangenetik, Universitätsklinikum Essen, Germany; 2Max-Planck- Institute of Molecular Genetic, Berlin, Germany; 3Institute for Cell Biology (Tumor Research), University of Duisburg-Essen, Germany; 4Department of Genetics, United Laboratories, Tartu University Hospital, Estonia; 5Institute for Research Information and Quality Assurance, Germany. *Correspondence and present address: Diana Mitter, Institut für Humangenetik, Universitätsklinikum Leipzig, Philipp-Rosenthal-Str. -
Human Social Genomics in the Multi-Ethnic Study of Atherosclerosis
Getting “Under the Skin”: Human Social Genomics in the Multi-Ethnic Study of Atherosclerosis by Kristen Monét Brown A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Epidemiological Science) in the University of Michigan 2017 Doctoral Committee: Professor Ana V. Diez-Roux, Co-Chair, Drexel University Professor Sharon R. Kardia, Co-Chair Professor Bhramar Mukherjee Assistant Professor Belinda Needham Assistant Professor Jennifer A. Smith © Kristen Monét Brown, 2017 [email protected] ORCID iD: 0000-0002-9955-0568 Dedication I dedicate this dissertation to my grandmother, Gertrude Delores Hampton. Nanny, no one wanted to see me become “Dr. Brown” more than you. I know that you are standing over the bannister of heaven smiling and beaming with pride. I love you more than my words could ever fully express. ii Acknowledgements First, I give honor to God, who is the head of my life. Truly, without Him, none of this would be possible. Countless times throughout this doctoral journey I have relied my favorite scripture, “And we know that all things work together for good, to them that love God, to them who are called according to His purpose (Romans 8:28).” Secondly, I acknowledge my parents, James and Marilyn Brown. From an early age, you two instilled in me the value of education and have been my biggest cheerleaders throughout my entire life. I thank you for your unconditional love, encouragement, sacrifices, and support. I would not be here today without you. I truly thank God that out of the all of the people in the world that He could have chosen to be my parents, that He chose the two of you. -
Loss of PRDM1/BLIMP-1 Function Contributes to Poor Prognosis for Activated B-Cell–Like Diffuse Large B-Cell Lymphoma
HHS Public Access Author manuscript Author ManuscriptAuthor Manuscript Author Leukemia Manuscript Author . Author manuscript; Manuscript Author available in PMC 2018 March 05. Published in final edited form as: Leukemia. 2017 March ; 31(3): 625–636. doi:10.1038/leu.2016.243. Loss of PRDM1/BLIMP-1 function contributes to poor prognosis for activated B-cell–like diffuse large B-cell lymphoma Yi Xia1,2,*, Zijun Y. Xu-Monette1,*, Alexandar Tzankov3,*, Xin Li1, Ganiraju C. Manyam4, Vundavalli Murty5, Govind Bhagat5, Shanxiang Zhang1, Laura Pasqualucci5, Li Zhang4, Carlo Visco6, Karen Dybkaer7, April Chiu8, Attilio Orazi9, Youli Zu10, Kristy L. Richards11, Eric D. Hsi12, William W.L. Choi13, J. Han van Krieken14, Jooryung Huh15, Maurilio Ponzoni16, Andrés J.M. Ferreri16, Michael B. Møller17, Ben M. Parsons18, Jane N. Winter19, Miguel A. Piris20, Jason Westin21, Nathan Fowler21, Roberto N. Miranda1, Chi Young Ok1, Jianyong Li2,¶, L. Jeffrey Medeiros1, and Ken H. Young1,22,¶ 1Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA 2The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, China 3University Hospital, Basel, Switzerland 4Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA 5Columbia University Medical Center and New York Presbyterian Hospital, New York, NY, USA 6San Bortolo Hospital, Vicenza, Italy 7Aalborg University Hospital, Aalborg, Denmark 8Memorial Sloan-Kettering Cancer Center, New York, NY, USA 9Weill Medical College of Cornell University, New York, NY, USA 10The Methodist Hospital, Houston, TX, USA 11Cornell University, Ithaca, NY, USA 12Cleveland Clinic, Cleveland, OH, USA 13University of Hong Kong Li Ka Shing Faculty of Medicine, Hong Kong, China 14Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands 15Asan Medical Center, Ulsan University College of Medicine, Seoul, Korea 16San Raffaele H.