Evidence of Decreased Gap Junction Coupling Between Astrocytes and Oligodendrocytes in the Anterior Cingulate Cortex of Depresse
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A Rare Missense Mutation in GJB3 (Cx31g45e) Is Associated with a Unique Cellular Phenotype Resulting in Necrotic Cell Death Easton, J
University of Dundee A rare missense mutation in GJB3 (Cx31G45E) is associated with a unique cellular phenotype resulting in necrotic cell death Easton, J. A.; Alboulshi, A. K.; Kamps, M. A. F.; Brouns, G. H.; Broers, M. R.; Coull, B. J.; Oji, V.; van Geel, M.; van Steensel, M. A. M.; Martin, P. E. Published in: Experimental Dermatology DOI: 10.1111/exd.13542 Publication date: 2018 Document Version Peer reviewed version Link to publication in Discovery Research Portal Citation for published version (APA): Easton, J. A., Alboulshi, A. K., Kamps, M. A. F., Brouns, G. H., Broers, M. R., Coull, B. J., ... Martin, P. E. (2018). A rare missense mutation in GJB3 (Cx31G45E) is associated with a unique cellular phenotype resulting in necrotic cell death. Experimental Dermatology. https://doi.org/10.1111/exd.13542 General rights Copyright and moral rights for the publications made accessible in Discovery Research Portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from Discovery Research Portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain. • You may freely distribute the URL identifying the publication in the public portal. Take down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. -
GJA4/Connexin 37 Mutations Correlate with Secondary Lymphedema Following Surgery in Breast Cancer Patients
biomedicines Article GJA4/Connexin 37 Mutations Correlate with Secondary Lymphedema Following Surgery in Breast Cancer Patients Mahrooyeh Hadizadeh 1,2, Seiied Mojtaba Mohaddes Ardebili 1, Mansoor Salehi 2, Chris Young 3, Fariborz Mokarian 4, James McClellan 5, Qin Xu 6, Mohammad Kazemi 2, Elham Moazam 4, Behzad Mahaki 7 ID and Maziar Ashrafian Bonab 8,* 1 Department of Medical Genetics, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz 5166614766, Iran; [email protected] (M.H.); [email protected] (S.M.M.A.) 2 Department of Genetics and Molecular Biology, Isfahan University of Medical Sciences, Isfahan 81746753461, Iran; [email protected] (M.S.); [email protected] (M.K.) 3 School of Allied Health Sciences, Faculty of Health and Life Sciences, De Montfort University, Leicester LE1 9BH, UK; [email protected] 4 Cancer Prevention Research Centre, Isfahan University of Medical Sciences, Isfahan 8184917911, Iran; [email protected] (F.M.); [email protected] (E.M.) 5 School of Biological Sciences, University of Portsmouth, Portsmouth PO1 2DY, UK; [email protected] 6 School of Pharmacy, Faculty of Health and Life Sciences, De Montfort University, Leicester LE1 9BH, UK; [email protected] 7 Department of Occupational Health Engineering, School of Health, Isfahan University of Medical Sciences, Isfahan 8174673461, Iran; [email protected] 8 Department of Biological Sciences, University of Chester, Chester CH1 4BJ, UK * Correspondence: [email protected]; Tel.: +44-(0)1244-513-056 Received: 31 December 2017; Accepted: 13 February 2018; Published: 22 February 2018 Abstract: Lymphedema is a condition resulting from mutations in various genes essential for lymphatic development and function, which leads to obstruction of the lymphatic system. -
Defining Functional Interactions During Biogenesis of Epithelial Junctions
ARTICLE Received 11 Dec 2015 | Accepted 13 Oct 2016 | Published 6 Dec 2016 | Updated 5 Jan 2017 DOI: 10.1038/ncomms13542 OPEN Defining functional interactions during biogenesis of epithelial junctions J.C. Erasmus1,*, S. Bruche1,*,w, L. Pizarro1,2,*, N. Maimari1,3,*, T. Poggioli1,w, C. Tomlinson4,J.Lees5, I. Zalivina1,w, A. Wheeler1,w, A. Alberts6, A. Russo2 & V.M.M. Braga1 In spite of extensive recent progress, a comprehensive understanding of how actin cytoskeleton remodelling supports stable junctions remains to be established. Here we design a platform that integrates actin functions with optimized phenotypic clustering and identify new cytoskeletal proteins, their functional hierarchy and pathways that modulate E-cadherin adhesion. Depletion of EEF1A, an actin bundling protein, increases E-cadherin levels at junctions without a corresponding reinforcement of cell–cell contacts. This unexpected result reflects a more dynamic and mobile junctional actin in EEF1A-depleted cells. A partner for EEF1A in cadherin contact maintenance is the formin DIAPH2, which interacts with EEF1A. In contrast, depletion of either the endocytic regulator TRIP10 or the Rho GTPase activator VAV2 reduces E-cadherin levels at junctions. TRIP10 binds to and requires VAV2 function for its junctional localization. Overall, we present new conceptual insights on junction stabilization, which integrate known and novel pathways with impact for epithelial morphogenesis, homeostasis and diseases. 1 National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK. 2 Computing Department, Imperial College London, London SW7 2AZ, UK. 3 Bioengineering Department, Faculty of Engineering, Imperial College London, London SW7 2AZ, UK. 4 Department of Surgery & Cancer, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK. -
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. -
Extraction of Dynamic Patterns from Static Rna Expression Data: an Application to Hematological Neoplasms
EXTRACTION OF DYNAMIC PATTERNS FROM STATIC RNA EXPRESSION DATA: AN APPLICATION TO HEMATOLOGICAL NEOPLASMS Relatore: Barbara Di Camillo Correlatore: Dott.ssa Alessandra Trojani Laureando: Giulia Bianchi ANNO ACCADEMICO 2012/2013 Nothing worth gaining was ever gained without effort. Theodore Roosevelt Index Section 1 INTRODUCTION 1 1.1. Extraction of temporal dynamics from gene expression data 2 1.2. Chronic Lymphocytic Leukemia 3 1.3. IgM Monoclonal Gammopathy of Undetermined Significance and Waldenstrӧm’s Macroglobulinemia 4 Section 2 DATA 7 2.1. CLL Data set 8 2.2. WM/MGUS Data set 8 Section 3 SAMPLE PROGRESSION DISCOVERY 10 3.1. Methods 10 3.2. SPD step by step 12 3.2.1. Input format 12 3.2.2. Gene filtering 12 3.2.3. Clustering 13 3.2.4. Construct MSTs – Compare modules and MSTs 14 3.2.5. Identify modules similar in terms of progression 16 3.3. Results and discussion 17 Section 4 PARAMETER SETTING 19 4.1. Input configuration 19 4.2. Result evaluation 20 4.3. Conclusions 26 Section 5 APPLICATION TO CHRONIC LYMPHOCYTIC LEUKEMIA 28 5.1. Gene selection 28 5.2. SPD results 29 Section 6 APPLICATION TO WALDENSTRÖM’S MACROGLOBULINEMIA AND IgM MGUS 39 6.1. Gene selection 39 6.2. SPD results 40 Section 7 DISCUSSION 45 Acknowledgements 49 Section 8 REFERENCES 51 Section 9 APPENDIX 55 i Section 1 INTRODUCTION Development and evolution of a disease are dynamic processes that, from a molecular point of view, involve changes in some gene expression levels in the involved organs and cells. A possible approach to study the behavior of such dynamic phenomena is to sample individuals, tissues or other relevant units at subsequent time-points throughout the progression. -
Protein Identities in Evs Isolated from U87-MG GBM Cells As Determined by NG LC-MS/MS
Protein 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, -
Cellular and Molecular Signatures in the Disease Tissue of Early
Cellular and Molecular Signatures in the Disease Tissue of Early Rheumatoid Arthritis Stratify Clinical Response to csDMARD-Therapy and Predict Radiographic Progression Frances Humby1,* Myles Lewis1,* Nandhini Ramamoorthi2, Jason Hackney3, Michael Barnes1, Michele Bombardieri1, Francesca Setiadi2, Stephen Kelly1, Fabiola Bene1, Maria di Cicco1, Sudeh Riahi1, Vidalba Rocher-Ros1, Nora Ng1, Ilias Lazorou1, Rebecca E. Hands1, Desiree van der Heijde4, Robert Landewé5, Annette van der Helm-van Mil4, Alberto Cauli6, Iain B. McInnes7, Christopher D. Buckley8, Ernest Choy9, Peter Taylor10, Michael J. Townsend2 & Costantino Pitzalis1 1Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK. Departments of 2Biomarker Discovery OMNI, 3Bioinformatics and Computational Biology, Genentech Research and Early Development, South San Francisco, California 94080 USA 4Department of Rheumatology, Leiden University Medical Center, The Netherlands 5Department of Clinical Immunology & Rheumatology, Amsterdam Rheumatology & Immunology Center, Amsterdam, The Netherlands 6Rheumatology Unit, Department of Medical Sciences, Policlinico of the University of Cagliari, Cagliari, Italy 7Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow G12 8TA, UK 8Rheumatology Research Group, Institute of Inflammation and Ageing (IIA), University of Birmingham, Birmingham B15 2WB, UK 9Institute of -
Localized Calcium Signaling and the Control of Coupling at Cx36 Gap Junctions
Research Article: New Research | Novel Tools and Methods Localized calcium signaling and the control of coupling at Cx36 gap junctions https://doi.org/10.1523/ENEURO.0445-19.2020 Cite as: eNeuro 2020; 10.1523/ENEURO.0445-19.2020 Received: 25 October 2019 Revised: 29 January 2020 Accepted: 21 February 2020 This Early Release article has been peer-reviewed and accepted, but has not been through the composition and copyediting processes. The final version may differ slightly in style or formatting and will contain links to any extended data. Alerts: Sign up at www.eneuro.org/alerts to receive customized email alerts when the fully formatted version of this article is published. Copyright © 2020 Moore et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed. 1 Localized calcium signaling and the control of coupling at Cx36 gap junctions 2 3 Abbreviated title: Calcium signaling at Cx36 gap junctions 4 5 Keith B. Moore1,†, Cheryl K. Mitchell1, Ya-Ping Lin1, Yuan-Hao Lee1, Eyad Shihabeddin1,2, and 6 John O'Brien1,2,* 7 8 1. Richard S. Ruiz, M.D. Department of Ophthalmology & Visual Science, McGovern Medical 9 School, The University of Texas Health Science Center at Houston, Houston, Texas, USA. 10 2. The MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, 11 Houston, Texas, USA. 12 †. Current Address: School of Public Health, The University of Texas Health Science Center at 13 Houston, Houston, Texas, USA. -
Placenta-Derived Exosomes Continuously Increase in Maternal
Sarker et al. Journal of Translational Medicine 2014, 12:204 http://www.translational-medicine.com/content/12/1/204 RESEARCH Open Access Placenta-derived exosomes continuously increase in maternal circulation over the first trimester of pregnancy Suchismita Sarker1, Katherin Scholz-Romero1, Alejandra Perez2, Sebastian E Illanes1,2,3, Murray D Mitchell1, Gregory E Rice1,2 and Carlos Salomon1,2* Abstract Background: Human placenta releases specific nanovesicles (i.e. exosomes) into the maternal circulation during pregnancy, however, the presence of placenta-derived exosomes in maternal blood during early pregnancy remains to be established. The aim of this study was to characterise gestational age related changes in the concentration of placenta-derived exosomes during the first trimester of pregnancy (i.e. from 6 to 12 weeks) in plasma from women with normal pregnancies. Methods: A time-series experimental design was used to establish pregnancy-associated changes in maternal plasma exosome concentrations during the first trimester. A series of plasma were collected from normal healthy women (10 patients) at 6, 7, 8, 9, 10, 11 and 12 weeks of gestation (n = 70). We measured the stability of these vesicles by quantifying and observing their protein and miRNA contents after the freeze/thawing processes. Exosomes were isolated by differential and buoyant density centrifugation using a sucrose continuous gradient and characterised by their size distribution and morphology using the nanoparticles tracking analysis (NTA; Nanosight™) and electron microscopy (EM), respectively. The total number of exosomes and placenta-derived exosomes were determined by quantifying the immunoreactive exosomal marker, CD63 and a placenta-specific marker (Placental Alkaline Phosphatase PLAP). -
Whole Exome Sequencing in Families at High Risk for Hodgkin Lymphoma: Identification of a Predisposing Mutation in the KDR Gene
Hodgkin Lymphoma SUPPLEMENTARY APPENDIX Whole exome sequencing in families at high risk for Hodgkin lymphoma: identification of a predisposing mutation in the KDR gene Melissa Rotunno, 1 Mary L. McMaster, 1 Joseph Boland, 2 Sara Bass, 2 Xijun Zhang, 2 Laurie Burdett, 2 Belynda Hicks, 2 Sarangan Ravichandran, 3 Brian T. Luke, 3 Meredith Yeager, 2 Laura Fontaine, 4 Paula L. Hyland, 1 Alisa M. Goldstein, 1 NCI DCEG Cancer Sequencing Working Group, NCI DCEG Cancer Genomics Research Laboratory, Stephen J. Chanock, 5 Neil E. Caporaso, 1 Margaret A. Tucker, 6 and Lynn R. Goldin 1 1Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 2Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 3Ad - vanced Biomedical Computing Center, Leidos Biomedical Research Inc.; Frederick National Laboratory for Cancer Research, Frederick, MD; 4Westat, Inc., Rockville MD; 5Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; and 6Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA ©2016 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol.2015.135475 Received: August 19, 2015. Accepted: January 7, 2016. Pre-published: June 13, 2016. Correspondence: [email protected] Supplemental Author Information: NCI DCEG Cancer Sequencing Working Group: Mark H. Greene, Allan Hildesheim, Nan Hu, Maria Theresa Landi, Jennifer Loud, Phuong Mai, Lisa Mirabello, Lindsay Morton, Dilys Parry, Anand Pathak, Douglas R. Stewart, Philip R. Taylor, Geoffrey S. Tobias, Xiaohong R. Yang, Guoqin Yu NCI DCEG Cancer Genomics Research Laboratory: Salma Chowdhury, Michael Cullen, Casey Dagnall, Herbert Higson, Amy A. -
Identification of Key Pathways and Genes in Dementia Via Integrated Bioinformatics Analysis
bioRxiv preprint doi: https://doi.org/10.1101/2021.04.18.440371; this version posted July 19, 2021. 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. Identification of Key Pathways and Genes in Dementia via Integrated Bioinformatics Analysis Basavaraj Vastrad1, Chanabasayya Vastrad*2 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karnataka, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2021.04.18.440371; this version posted July 19, 2021. 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. Abstract To provide a better understanding of dementia at the molecular level, this study aimed to identify the genes and key pathways associated with dementia by using integrated bioinformatics analysis. Based on the expression profiling by high throughput sequencing dataset GSE153960 derived from the Gene Expression Omnibus (GEO), the differentially expressed genes (DEGs) between patients with dementia and healthy controls were identified. With DEGs, we performed a series of functional enrichment analyses. Then, a protein–protein interaction (PPI) network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network was constructed, analyzed and visualized, with which the hub genes miRNAs and TFs nodes were screened out. Finally, validation of hub genes was performed by using receiver operating characteristic curve (ROC) analysis. -
Genetic Variability in a Holstein Population Using SNP Markers and Their Use for Monitoring Mating Strategies
https://doi.org/10.22319/rmcp.v10i3.4842 Article Genetic variability in a Holstein population using SNP markers and their use for monitoring mating strategies Kathy Scienski a,b,c Angelo Ialacci c Alessandro Bagnato c Davide Reginelli d Marina Durán-Aguilar e Maria Giuseppina Strillacci c* a Texas A&M University, College Station. Interdisciplinary Program in Genetics. Texas, USA. b Texas A&M University. Department of Animal Science, Texas, USA. c Università degli Studi di Milano. Department of Veterinary Medicine, Via Trentacoste 2, 20134 Milano, Italy. d Università degli Studi di Milano. Azienda Agraria Didattico Sperimentale Angelo Menozzi, Landriano, Pavia, Italy. e Universidad Autónoma de Querétaro. Facultad de Ciencias Naturales. Querétaro. México. * Corresponding author: [email protected] Abstract: As genotyping costs continue to decrease, the demand for genotyping has increased among farmers. In most livestock herds, an important issue is controlling the increase in inbreeding coefficient. While this remains a large motive to genotype, producers are often unaware of the other benefits that genotyping could bring. The aim of this study was to demonstrate that SNP chips could be used as an effective herd management tool by utilizing a population of Italian Holstein-Friesian cattle. After filtering, the total number 643 Rev Mex Cienc Pecu 2019;10(3):643-663 of animals and SNPs retained for analyses were 44 and 27,365, respectively. The principal component analyses (PCA) were able to identify a sire and origin-of-sire effect within the herd, while determining that sires do not influence individual genomic selection index values. The inbreeding coefficients calculated from genotypes (FIS) provided a glimpse into the herd’s heterozygosity and determined that the genetic variability is being well maintained.