'Dynamic Gene Expression Response to Altered Gravity in Human
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Identification of Key Candidate Genes for Colorectal Cancer by Bioinformatics Analysis
ONCOLOGY LETTERS 18: 6583-6593, 2019 Identification of key candidate genes for colorectal cancer by bioinformatics analysis ZHIHUA CHEN1*, YILIN LIN1*, JI GAO2*, SUYONG LIN1, YAN ZHENG1, YISU LIU1 and SHAO QIN CHEN1 1Department of Gastrointestinal Surgery, The First Affiliated Hospital of Fujian Medical University; 2School of Nursing, Fujian Medical University, Fuzhou, Fujian 350004, P.R. China Received December 27, 2018; Accepted August 16, 2019 DOI: 10.3892/ol.2019.10996 Abstract. Colorectal cancer (CRC) is one of the most Introduction common cancers of the digestive tract. Although numerous studies have been conducted to elucidate the cause of CRC, Colorectal cancer (CRC) ranks third (13.5%) and second the exact mechanism of CRC development remains to be (9.5%) among the incidence of malignancies worldwide determined. To identify candidate genes that may be involved in male and female patients, respectively, and is a serious in CRC development and progression, the microarray datasets hazard to human health (1). Previous studies have demon- GSE41657, GSE77953 and GSE113513 were downloaded from strated that the molecular pathogenesis of CRC is mostly the Gene Expression Omnibus database. Gene Ontology and caused by genetic mutations (2,3). Numerous studies over Kyoto Encyclopedia of Genes and Genomes were used for the past two decades have reported that genetic mutations functional enrichment analysis of differentially expressed are associated with the prognosis and treatment of CRC, and genes (DEGs). A protein-protein interaction network was targeted therapies have been developed (4-7). The progres- constructed, and the hub genes were subjected to module sion of CRC is usually accompanied by the activation of the analysis and identification using Search Tool for the Retrieval KRAS and BRAF genes and the inhibition of the p53 tumour of Interacting Genes/Proteins and Cytoscape. -
Anti-RBM3 Antibody [HB9] (ARG23691)
Product datasheet [email protected] ARG23691 Package: 50 μg anti-RBM3 antibody [HB9] Store at: -20°C Summary Product Description Mouse Monoclonal antibody [HB9] recognizes RBM3 Tested Reactivity Hu Tested Application ICC/IF Specificity The antibody reacts against the recombinant human RBM3 full length under oxidative conditions without DTT or under reducing conditions with DTT. Cross reactivity of the antibody with the recombinant human Cold inducible Binding protein (CIRBP, full length 20.5 kDa) could not be detected. The apparent MW of hRBM3 in SDS-PAGE is ~17 kDa. Host Mouse Clonality Monoclonal Clone HB9 Isotype IgG1 Target Name RBM3 Antigen Species Human Immunogen Human RNA-binding protein 3. Conjugation Un-conjugated Alternate Names RNPL; IS1-RNPL; RNA-binding motif protein 3; RNA-binding protein 3 Application Instructions Application table Application Dilution ICC/IF 1:50 Application Note * The dilutions indicate recommended starting dilutions and the optimal dilutions or concentrations should be determined by the scientist. Calculated Mw 17 kDa Properties Form Liquid Purification Purification with Protein G. The IgG1 fraction was purified by affinity chromatography. Buffer PBS (pH 7.4) and 0.01% Sodium azide. Preservative 0.01% Sodium azide Storage instruction For continuous use, store undiluted antibody at 2-8°C for up to a week. For long-term storage, aliquot and store at -20°C or below. Storage in frost free freezers is not recommended. Avoid repeated freeze/thaw cycles. Suggest spin the vial prior to opening. The antibody solution should be gently mixed before use. www.arigobio.com 1/2 Note For laboratory research only, not for drug, diagnostic or other use. -
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. -
Identification of the Rna Binding Protein Rbm3 As a Novel Effector of Β-Catenin Signaling and Colon Cancer Stem Cells
IDENTIFICATION OF THE RNA BINDING PROTEIN RBM3 AS A NOVEL EFFECTOR OF β-CATENIN SIGNALING AND COLON CANCER STEM CELLS By Anand Venugopal Submitted to the graduate degree program in Molecular and Integrative Physiology and the Graduate Faculty of the University of Kansas in partial fulfillment of the requirements for the degree of Doctor of Philosophy. ________________________________ Chairperson Shrikant Anant, Ph.D. ________________________________ Roy Jensen, M.D. ________________________________ Andrew Godwin, Ph.D. ________________________________ Danny Welch, Ph.D. ________________________________ John Wood, Ph.D. Date Defended: ________________________________March 14, 2014 The Dissertation Committee for Anand Venugopal certifies that this is the approved version of the following dissertation: IDENTIFICATION OF THE RNA BINDING PROTEIN RBM3 AS A NOVEL EFFECTOR OF β-CATENIN SIGNALING AND COLON CANCER STEM CELLS ________________________________ Chairperson Shrikant Anant, Ph.D. Date approved: ________________________________March 14, 2014 ii Abstract The intestinal epithelium is one of the fastest renewing tissues within the adult. This renewal is primarily driven by the intestinal epithelial stem cell compartment and homeostasis of this compartment needs to be strictly maintained. Loss of regulation can lead to hyperplasia and subsequent malignant transformation. Moreover, cancers are also thought to contain a stem cell population which maintains long term tumor viability and recurrence following therapy. Therefore, a thorough understanding of the molecular machinery that governs stem cell homeostasis can further our understanding of colon cancer initiation and progression. The RNA binding protein RBM3 is upregulated in many solid tumors including colon, prostate and breast. It also serves as a proto-oncogene inducing the malignant transformation of normal cells when overexpressed. To further characterize the mechanism, we overexpressed RBM3 in DLD-1 and HCT 116 colon cancer cell lines. -
Fine Mapping Studies of Quantitative Trait Loci for Baseline Platelet Count in Mice and Humans
Fine mapping studies of quantitative trait loci for baseline platelet count in mice and humans A thesis submitted in fulfillment of the requirements for the degree of Doctor of Philosophy Melody C Caramins December 2010 University of New South Wales ORIGINALITY STATEMENT ‘I hereby declare that this submission is my own work and to the best of my knowledge it contains no materials previously published or written by another person, or substantial proportions of material which have been accepted for the award of any other degree or diploma at UNSW or any other educational institution, except where due acknowledgement is made in the thesis. Any contribution made to the research by others, with whom I have worked at UNSW or elsewhere, is explicitly acknowledged in the thesis. I also declare that the intellectual content of this thesis is the product of my own work, except to the extent that assistance from others in the project's design and conception or in style, presentation and linguistic expression is acknowledged.’ Signed …………………………………………….............. Date …………………………………………….............. This thesis is dedicated to my father. Dad, thanks for the genes – and the environment! ACKNOWLEDGEMENTS “Nothing can come out of nothing, any more than a thing can go back to nothing.” - Marcus Aurelius Antoninus A PhD thesis is never the work of one person in isolation from the world at large. I would like to thank the following people, without whom this work would not have existed. Thank you firstly, to all my teachers, of which there have been many. Undoubtedly, the greatest debt is owed to my supervisor, Dr Michael Buckley. -
CD29 Identifies IFN-Γ–Producing Human CD8+ T Cells With
+ CD29 identifies IFN-γ–producing human CD8 T cells with an increased cytotoxic potential Benoît P. Nicoleta,b, Aurélie Guislaina,b, Floris P. J. van Alphenc, Raquel Gomez-Eerlandd, Ton N. M. Schumacherd, Maartje van den Biggelaarc,e, and Monika C. Wolkersa,b,1 aDepartment of Hematopoiesis, Sanquin Research, 1066 CX Amsterdam, The Netherlands; bLandsteiner Laboratory, Oncode Institute, Amsterdam University Medical Center, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; cDepartment of Research Facilities, Sanquin Research, 1066 CX Amsterdam, The Netherlands; dDivision of Molecular Oncology and Immunology, Oncode Institute, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands; and eDepartment of Molecular and Cellular Haemostasis, Sanquin Research, 1066 CX Amsterdam, The Netherlands Edited by Anjana Rao, La Jolla Institute for Allergy and Immunology, La Jolla, CA, and approved February 12, 2020 (received for review August 12, 2019) Cytotoxic CD8+ T cells can effectively kill target cells by producing therefore developed a protocol that allowed for efficient iso- cytokines, chemokines, and granzymes. Expression of these effector lation of RNA and protein from fluorescence-activated cell molecules is however highly divergent, and tools that identify and sorting (FACS)-sorted fixed T cells after intracellular cytokine + preselect CD8 T cells with a cytotoxic expression profile are lacking. staining. With this top-down approach, we performed an un- + Human CD8 T cells can be divided into IFN-γ– and IL-2–producing biased RNA-sequencing (RNA-seq) and mass spectrometry cells. Unbiased transcriptomics and proteomics analysis on cytokine- γ– – + + (MS) analyses on IFN- and IL-2 producing primary human producing fixed CD8 T cells revealed that IL-2 cells produce helper + + + CD8 Tcells. -
Screening and Identification of Hub Genes in Bladder Cancer by Bioinformatics Analysis and KIF11 Is a Potential Prognostic Biomarker
ONCOLOGY LETTERS 21: 205, 2021 Screening and identification of hub genes in bladder cancer by bioinformatics analysis and KIF11 is a potential prognostic biomarker XIAO‑CONG MO1,2*, ZI‑TONG ZHANG1,3*, MENG‑JIA SONG1,2, ZI‑QI ZHOU1,2, JIAN‑XIONG ZENG1,2, YU‑FEI DU1,2, FENG‑ZE SUN1,2, JIE‑YING YANG1,2, JUN‑YI HE1,2, YUE HUANG1,2, JIAN‑CHUAN XIA1,2 and DE‑SHENG WENG1,2 1State Key Laboratory of Oncology in South China, Collaborative Innovation Centre for Cancer Medicine; 2Department of Biotherapy, Sun Yat‑Sen University Cancer Center; 3Department of Radiation Oncology, Sun Yat‑Sen University Cancer Center, Guangzhou, Guangdong 510060, P.R. China Received July 31, 2020; Accepted December 18, 2020 DOI: 10.3892/ol.2021.12466 Abstract. Bladder cancer (BC) is the ninth most common immunohistochemistry and western blotting. In summary, lethal malignancy worldwide. Great efforts have been devoted KIF11 was significantly upregulated in BC and might act as to clarify the pathogenesis of BC, but the underlying molecular a potential prognostic biomarker. The present identification mechanisms remain unclear. To screen for the genes associated of DEGs and hub genes in BC may provide novel insight for with the progression and carcinogenesis of BC, three datasets investigating the molecular mechanisms of BC. were obtained from the Gene Expression Omnibus. A total of 37 tumor and 16 non‑cancerous samples were analyzed to Introduction identify differentially expressed genes (DEGs). Subsequently, 141 genes were identified, including 55 upregulated and Bladder cancer (BC) is the ninth most common malignancy 86 downregulated genes. The protein‑protein interaction worldwide with substantial morbidity and mortality. -
UNIVERSITY of CALIFORNIA RIVERSIDE Investigations Into The
UNIVERSITY OF CALIFORNIA RIVERSIDE Investigations into the Role of TAF1-mediated Phosphorylation in Gene Regulation A Dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Cell, Molecular and Developmental Biology by Brian James Gadd December 2012 Dissertation Committee: Dr. Xuan Liu, Chairperson Dr. Frank Sauer Dr. Frances M. Sladek Copyright by Brian James Gadd 2012 The Dissertation of Brian James Gadd is approved Committee Chairperson University of California, Riverside Acknowledgments I am thankful to Dr. Liu for her patience and support over the last eight years. I am deeply indebted to my committee members, Dr. Frank Sauer and Dr. Frances Sladek for the insightful comments on my research and this dissertation. Thanks goes out to CMDB, especially Dr. Bachant, Dr. Springer and Kathy Redd for their support. Thanks to all the members of the Liu lab both past and present. A very special thanks to the members of the Sauer lab, including Silvia, Stephane, David, Matt, Stephen, Ninuo, Toby, Josh, Alice, Alex and Flora. You have made all the years here fly by and made them so enjoyable. From the Sladek lab I want to thank Eugene, John, Linh and Karthi. Special thanks go out to all the friends I’ve made over the years here. Chris, Amber, Stephane and David, thank you so much for feeding me, encouraging me and keeping me sane. Thanks to the brothers for all your encouragement and prayers. To any I haven’t mentioned by name, I promise I haven’t forgotten all you’ve done for me during my graduate years. -
Human RBM3 ELISA Kit (ARG81349)
Product datasheet [email protected] ARG81349 Package: 96 wells Human RBM3 ELISA Kit Store at: 4°C Summary Product Description ARG81349 Human RBM3 ELISA Kit is an Enzyme Immunoassay kit for the quantification of Human RBM3 in serum and plasma. Tested Reactivity Hu Tested Application ELISA Specificity No significant cross reactivity to Cold inducible Binding protein (CIRBP), human. Target Name RBM3 Conjugation HRP Conjugation Note Substrate: TMB and read at 450 nm. Sensitivity 10 pg/ml Sample Type Serum and plasma. Standard Range 31.25 - 2000 pg/ml Sample Volume 50 µl Alternate Names RNPL; IS1-RNPL; RNA-binding motif protein 3; RNA-binding protein 3 Application Instructions Assay Time ~ 2.5 hours Properties Form 96 well Storage instruction Store the kit at 2-8°C. Keep microplate wells sealed in a dry bag with desiccants. Do not expose test reagents to heat, sun or strong light during storage and usage. Please refer to the product user manual for detail temperatures of the components. Note For laboratory research only, not for drug, diagnostic or other use. Bioinformation Gene Symbol RBM3 Gene Full Name RNA binding motif (RNP1, RRM) protein 3 Background This gene is a member of the glycine-rich RNA-binding protein family and encodes a protein with one RNA recognition motif (RRM) domain. Expression of this gene is induced by cold shock and low oxygen tension. A pseudogene exists on chromosome 1. Multiple alternatively spliced transcript variants that are predicted to encode different isoforms have been characterized although some of these variants fit nonsense-mediated decay (NMD) criteria. -
GENOME EDITING in AFRICA’S AGRICULTURE 2021 an EARLY TAKE-OFF TABLE of CONTENTS Abbreviations and Acronyms 3
GENOME EDITING IN AFRICA’S AGRICULTURE 2021 AN EARLY TAKE-OFF TABLE OF CONTENTS Abbreviations and Acronyms 3 1. Introduction 4 1.1 Milestones in Plant Breeding 5 1.2 How CRISPR genome editing works in agriculture 6 2 . Genome editing projects and experts in eastern Africa 7 2.1 Kenya 8 2.2 Ethiopia 14 2.3 Uganda 15 3 . Gene editing projects and experts in southern Africa 17 3.1 South Africa 18 4. Gene editing projects and experts in West Africa 19 4.1 Nigeria 20 5. Gene editing projects and experts in Central Africa 21 5.1 Cameroon 22 6. Gene editing projects and experts in North Africa 23 6.1 Egypt 24 7. Conclusion 25 8. CRISPR genome editing: inside a crop breeder’s toolkit 26 9. Regulatory Approaches for Genome Edited Products in Various Countries 27 10. Communicating about Genome Editing in Africa 28 2 ABBREVIATIONS AND ACRONYMS CRISPR Clustered Regularly Interspaced Short Palindromic Repeats DNA Deoxyribonucleic acid GM Genetically Modified GMO Genetically Modified Organism HDR Homology Directed Repair ISAAA International Service for the Acquisition of Agri-biotech Applications NHEJ Non Homologous End Joining PCR Polymerase Chain Reaction RNA Ribonucleic Acid LGS1 Low germination stimulant 1 3 1.0 INTRODUCTION Genome editing (also referred to as gene editing) comprises a arm is provided with the CRISPR-Cas9 cassette, homology-directed group of technologies that give scientists the ability to change an repair (HDR) will occur, otherwise the cell will employ non- organism’s DNA. These technologies allow addition, removal or homologous end joining (NHEJ) to create small indels at the cut site alteration of genetic material at particular locations in the genome. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Identification of Differentially Methylated Cpg
biomedicines Article Identification of Differentially Methylated CpG Sites in Fibroblasts from Keloid Scars Mansour A. Alghamdi 1,2 , Hilary J. Wallace 3,4 , Phillip E. Melton 5,6 , Eric K. Moses 5,6, Andrew Stevenson 4 , Laith N. Al-Eitan 7,8 , Suzanne Rea 9, Janine M. Duke 4, 10 11 4,9,12 4, , Patricia L. Danielsen , Cecilia M. Prêle , Fiona M. Wood and Mark W. Fear * y 1 Department of Anatomy, College of Medicine, King Khalid University, Abha 61421, Saudi Arabia; [email protected] 2 Genomics and Personalized Medicine Unit, College of Medicine, King Khalid University, Abha 61421, Saudi Arabia 3 School of Medicine, The University of Notre Dame Australia, Fremantle 6959, Australia; [email protected] 4 Burn Injury Research Unit, School of Biomedical Sciences, Faculty of Health and Medical Sciences, The University of Western Australia, Perth 6009, Australia; andrew@fionawoodfoundation.com (A.S.); [email protected] (J.M.D.); fi[email protected] (F.M.W.) 5 Centre for Genetic Origins of Health and Disease, Faculty of Health and Medical Sciences, The University of Western Australia, Perth 6009, Australia; [email protected] (P.E.M.); [email protected] (E.K.M.) 6 School of Pharmacy and Biomedical Sciences, Faculty of Health Science, Curtin University, Perth 6102, Australia 7 Department of Applied Biological Sciences, Jordan University of Science and Technology, Irbid 22110, Jordan; [email protected] 8 Department of Biotechnology and Genetic Engineering, Jordan University of Science and Technology, Irbid 22110,