Expression Profiling Associates Blood and Brain Glucocorticoid Receptor
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1 Evidence for Gliadin Antibodies As Causative Agents in Schizophrenia
1 Evidence for gliadin antibodies as causative agents in schizophrenia. C.J.Carter PolygenicPathways, 20 Upper Maze Hill, Saint-Leonard’s on Sea, East Sussex, TN37 0LG [email protected] Tel: 0044 (0)1424 422201 I have no fax Abstract Antibodies to gliadin, a component of gluten, have frequently been reported in schizophrenia patients, and in some cases remission has been noted following the instigation of a gluten free diet. Gliadin is a highly immunogenic protein, and B cell epitopes along its entire immunogenic length are homologous to the products of numerous proteins relevant to schizophrenia (p = 0.012 to 3e-25). These include members of the DISC1 interactome, of glutamate, dopamine and neuregulin signalling networks, and of pathways involved in plasticity, dendritic growth or myelination. Antibodies to gliadin are likely to cross react with these key proteins, as has already been observed with synapsin 1 and calreticulin. Gliadin may thus be a causative agent in schizophrenia, under certain genetic and immunological conditions, producing its effects via antibody mediated knockdown of multiple proteins relevant to the disease process. Because of such homology, an autoimmune response may be sustained by the human antigens that resemble gliadin itself, a scenario supported by many reports of immune activation both in the brain and in lymphocytes in schizophrenia. Gluten free diets and removal of such antibodies may be of therapeutic benefit in certain cases of schizophrenia. 2 Introduction A number of studies from China, Norway, and the USA have reported the presence of gliadin antibodies in schizophrenia 1-5. Gliadin is a component of gluten, intolerance to which is implicated in coeliac disease 6. -
Activated Peripheral-Blood-Derived Mononuclear Cells
Transcription factor expression in lipopolysaccharide- activated peripheral-blood-derived mononuclear cells Jared C. Roach*†, Kelly D. Smith*‡, Katie L. Strobe*, Stephanie M. Nissen*, Christian D. Haudenschild§, Daixing Zhou§, Thomas J. Vasicek¶, G. A. Heldʈ, Gustavo A. Stolovitzkyʈ, Leroy E. Hood*†, and Alan Aderem* *Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103; ‡Department of Pathology, University of Washington, Seattle, WA 98195; §Illumina, 25861 Industrial Boulevard, Hayward, CA 94545; ¶Medtronic, 710 Medtronic Parkway, Minneapolis, MN 55432; and ʈIBM Computational Biology Center, P.O. Box 218, Yorktown Heights, NY 10598 Contributed by Leroy E. Hood, August 21, 2007 (sent for review January 7, 2007) Transcription factors play a key role in integrating and modulating system. In this model system, we activated peripheral-blood-derived biological information. In this study, we comprehensively measured mononuclear cells, which can be loosely termed ‘‘macrophages,’’ the changing abundances of mRNAs over a time course of activation with lipopolysaccharide (LPS). We focused on the precise mea- of human peripheral-blood-derived mononuclear cells (‘‘macro- surement of mRNA concentrations. There is currently no high- phages’’) with lipopolysaccharide. Global and dynamic analysis of throughput technology that can precisely and sensitively measure all transcription factors in response to a physiological stimulus has yet to mRNAs in a system, although such technologies are likely to be be achieved in a human system, and our efforts significantly available in the near future. To demonstrate the potential utility of advanced this goal. We used multiple global high-throughput tech- such technologies, and to motivate their development and encour- nologies for measuring mRNA levels, including massively parallel age their use, we produced data from a combination of two distinct signature sequencing and GeneChip microarrays. -
KLF2 Induced
UvA-DARE (Digital Academic Repository) The transcription factor KLF2 in vascular biology Boon, R.A. Publication date 2008 Link to publication Citation for published version (APA): Boon, R. A. (2008). The transcription factor KLF2 in vascular biology. General rights It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulations If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: https://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. UvA-DARE is a service provided by the library of the University of Amsterdam (https://dare.uva.nl) Download date:23 Sep 2021 Supplementary data: Genes induced by KLF2 Dekker et al. LocusLink Accession Gene Sequence Description Fold p-value ID number symbol change (FDR) 6654 AK022099 SOS1 cDNA FLJ12037 fis, clone HEMBB1001921. 100.00 5.9E-09 56999 AF086069 ADAMTS9 full length insert cDNA clone YZ35C05. 100.00 1.2E-09 6672 AF085934 SP100 full length insert cDNA clone YR57D07. 100.00 6.7E-13 9031 AF132602 BAZ1B Williams Syndrome critical region WS25 mRNA, partial sequence. -
Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model
Downloaded from http://www.jimmunol.org/ by guest on September 25, 2021 T + is online at: average * The Journal of Immunology , 34 of which you can access for free at: 2016; 197:1477-1488; Prepublished online 1 July from submission to initial decision 4 weeks from acceptance to publication 2016; doi: 10.4049/jimmunol.1600589 http://www.jimmunol.org/content/197/4/1477 Molecular Profile of Tumor-Specific CD8 Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. Waugh, Sonia M. Leach, Brandon L. Moore, Tullia C. Bruno, Jonathan D. Buhrman and Jill E. Slansky J Immunol cites 95 articles Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html http://www.jimmunol.org/content/suppl/2016/07/01/jimmunol.160058 9.DCSupplemental This article http://www.jimmunol.org/content/197/4/1477.full#ref-list-1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material References Permissions Email Alerts Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2016 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of September 25, 2021. The Journal of Immunology Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. -
Independence of Hif1a and Androgen Signaling Pathways in Prostate Cancer
bioRxiv preprint doi: https://doi.org/10.1101/848424; this version posted November 26, 2019. 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. Independence of HIF1a and androgen signaling pathways in prostate cancer Maxine GB Tran1, 2*, Becky AS Bibby3†*, Lingjian Yang3, Franklin Lo1, Anne Warren1, Deepa Shukla1, Michelle Osborne1, James Hadfield1, Thomas Carroll1, Rory Stark1, Helen Scott1, Antonio Ramos-Montoya1, Charlie Massie1, Patrick Maxwell1, Catharine ML West3, 4, Ian G. Mills5,6** and David E. Neal1** 1Uro-oncology Research Group, Cancer Research UK Cambridge Institute, Cambridge, CB02 0RE, United Kingdom 2UCL division of Surgery and Interventional Science, Royal Free Hospital, Pond Street, London NW3 2QG 3Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Christie Hospital NHS Trust, Manchester, M20 4BX, United Kingdom 4Manchester Biomedical Research Centre, University of Manchester, Central Manchester University Hospitals NHS Foundation Trust, Manchester, United Kingdom. 5Centre for Cancer Research and Cell Biology, Queens University Belfast, Belfast, BT9 7AE, United Kingdom 6Nuffield Department of Surgical Sciences, University of Oxford, OX3 9DU, UK *These authors contributed equally to this work **These authors contributed equally to this work †Corresponding author email: Becky Bibby, Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Christie Hospital NHS Trust, Manchester, M20 4BX, United Kingdom, [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/848424; this version posted November 26, 2019. -
The Title of the Dissertation
UNIVERSITY OF CALIFORNIA SAN DIEGO Novel network-based integrated analyses of multi-omics data reveal new insights into CD8+ T cell differentiation and mouse embryogenesis A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Bioinformatics and Systems Biology by Kai Zhang Committee in charge: Professor Wei Wang, Chair Professor Pavel Arkadjevich Pevzner, Co-Chair Professor Vineet Bafna Professor Cornelis Murre Professor Bing Ren 2018 Copyright Kai Zhang, 2018 All rights reserved. The dissertation of Kai Zhang is approved, and it is accept- able in quality and form for publication on microfilm and electronically: Co-Chair Chair University of California San Diego 2018 iii EPIGRAPH The only true wisdom is in knowing you know nothing. —Socrates iv TABLE OF CONTENTS Signature Page ....................................... iii Epigraph ........................................... iv Table of Contents ...................................... v List of Figures ........................................ viii List of Tables ........................................ ix Acknowledgements ..................................... x Vita ............................................. xi Abstract of the Dissertation ................................. xii Chapter 1 General introduction ............................ 1 1.1 The applications of graph theory in bioinformatics ......... 1 1.2 Leveraging graphs to conduct integrated analyses .......... 4 1.3 References .............................. 6 Chapter 2 Systematic -
Harnessing Gene Expression Profiles for the Identification of Ex Vivo Drug
cancers Article Harnessing Gene Expression Profiles for the Identification of Ex Vivo Drug Response Genes in Pediatric Acute Myeloid Leukemia David G.J. Cucchi 1 , Costa Bachas 1 , Marry M. van den Heuvel-Eibrink 2,3, Susan T.C.J.M. Arentsen-Peters 3, Zinia J. Kwidama 1, Gerrit J. Schuurhuis 1, Yehuda G. Assaraf 4, Valérie de Haas 3 , Gertjan J.L. Kaspers 3,5 and Jacqueline Cloos 1,* 1 Hematology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands; [email protected] (D.G.J.C.); [email protected] (C.B.); [email protected] (Z.J.K.); [email protected] (G.J.S.) 2 Department of Pediatric Oncology/Hematology, Erasmus MC–Sophia Children’s Hospital, 3015 CN Rotterdam, The Netherlands; [email protected] 3 Princess Máxima Center for Pediatric Oncology, 3584 CS Utrecht, The Netherlands; [email protected] (S.T.C.J.M.A.-P.); [email protected] (V.d.H.); [email protected] (G.J.L.K.) 4 The Fred Wyszkowski Cancer Research, Laboratory, Department of Biology, Technion-Israel Institute of Technology, 3200003 Haifa, Israel; [email protected] 5 Emma’s Children’s Hospital, Amsterdam UMC, Vrije Universiteit Amsterdam, Pediatric Oncology, 1081 HV Amsterdam, The Netherlands * Correspondence: [email protected] Received: 21 April 2020; Accepted: 12 May 2020; Published: 15 May 2020 Abstract: Novel treatment strategies are of paramount importance to improve clinical outcomes in pediatric AML. Since chemotherapy is likely to remain the cornerstone of curative treatment of AML, insights in the molecular mechanisms that determine its cytotoxic effects could aid further treatment optimization. -
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. -
The Autophagy Receptor SQSTM1/P62 Mediates Anti-Inflammatory Actions of the Selective NR3C1/ Glucocorticoid Receptor Modulator Compound a (Cpda) in Macrophages
Autophagy ISSN: 1554-8627 (Print) 1554-8635 (Online) Journal homepage: http://www.tandfonline.com/loi/kaup20 The autophagy receptor SQSTM1/p62 mediates anti-inflammatory actions of the selective NR3C1/ glucocorticoid receptor modulator compound A (CpdA) in macrophages Viacheslav Mylka, Julie Deckers, Dariusz Ratman, Lode De Cauwer, Jonathan Thommis, Riet De Rycke, Francis Impens, Claude Libert, Jan Tavernier, Wim Vanden Berghe, Kris Gevaert & Karolien De Bosscher To cite this article: Viacheslav Mylka, Julie Deckers, Dariusz Ratman, Lode De Cauwer, Jonathan Thommis, Riet De Rycke, Francis Impens, Claude Libert, Jan Tavernier, Wim Vanden Berghe, Kris Gevaert & Karolien De Bosscher (2018) The autophagy receptor SQSTM1/p62 mediates anti- inflammatory actions of the selective NR3C1/glucocorticoid receptor modulator compound A (CpdA) in macrophages, Autophagy, 14:12, 2049-2064, DOI: 10.1080/15548627.2018.1495681 To link to this article: https://doi.org/10.1080/15548627.2018.1495681 © 2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. Published online: 14 Sep 2018. Submit your article to this journal Article views: 907 View Crossmark data Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=kaup20 AUTOPHAGY 2018, VOL. 14, NO. 12, 2049–2064 https://doi.org/10.1080/15548627.2018.1495681 RESEARCH PAPER - BASIC SCIENCE The autophagy receptor SQSTM1/p62 mediates anti-inflammatory actions of the selective NR3C1/glucocorticoid receptor modulator -
The DNA Methylation of FOXO3 and TP53 As a Blood Biomarker of Late
Yuan et al. J Transl Med (2020) 18:467 https://doi.org/10.1186/s12967-020-02643-y Journal of Translational Medicine RESEARCH Open Access The DNA methylation of FOXO3 and TP53 as a blood biomarker of late-onset asthma Lin Yuan1,2,3, Leyuan Wang2, Xizi Du2, Ling Qin1,3, Ming Yang4, Kai Zhou2, Mengping Wu2, Yu Yang2, Zhiyuan Zheng1,3, Yang Xiang2, Xiangping Qu2, Huijun Liu2, Xiaoqun Qin2 and Chi Liu1,2,5* Abstract Background: Late-onset asthma (LOA) is beginning to account for an increasing proportion of asthma patients, which is often underdiagnosed in the elderly. Studies on the possible relations between aging-related genes and LOA contribute to the diagnosis and treatment of LOA. Forkhead Box O3 (FOXO3) and TP53 are two classic aging-related genes. DNA methylation varies greatly with age which may play an important role in the pathogenesis of LOA. We supposed that the diferentially methylated sites of FOXO3 and TP53 associated with clinical phenotypes of LOA may be useful biomarkers for the early screening of LOA. Methods: The mRNA expression and DNA methylation of FOXO3 and TP53 in peripheral blood of 43 LOA patients (15 mild LOA, 15 moderate LOA and 13 severe LOA) and 60 healthy controls (HCs) were determined. The association of methylated sites with age was assessed by Cox regression to control the potential confounders. Then, the correlation between diferentially methylated sites (DMSs; p-value < 0.05) and clinical lung function in LOA patients was evalu- ated. Next, candidate DMSs combining with age were evaluated to predict LOA by receiver operating characteristic (ROC) analysis and principal components analysis (PCA). -
Heat Shock Factor 1 Mediates Latent HIV Reactivation
www.nature.com/scientificreports OPEN Heat Shock Factor 1 Mediates Latent HIV Reactivation Xiao-Yan Pan1,*, Wei Zhao1,2,*, Xiao-Yun Zeng1, Jian Lin1, Min-Min Li3, Xin-Tian Shen1 & Shu-Wen Liu1,2 Received: 19 October 2015 HSF1, a conserved heat shock factor, has emerged as a key regulator of mammalian transcription Accepted: 29 April 2016 in response to cellular metabolic status and stress. To our knowledge, it is not known whether Published: 18 May 2016 HSF1 regulates viral transcription, particularly HIV-1 and its latent form. Here we reveal that HSF1 extensively participates in HIV transcription and is critical for HIV latent reactivation. Mode of action studies demonstrated that HSF1 binds to the HIV 5′-LTR to reactivate viral transcription and recruits a family of closely related multi-subunit complexes, including p300 and p-TEFb. And HSF1 recruits p300 for self-acetylation is also a committed step. The knockout of HSF1 impaired HIV transcription, whereas the conditional over-expression of HSF1 improved that. These findings demonstrate that HSF1 positively regulates the transcription of latent HIV, suggesting that it might be an important target for different therapeutic strategies aimed at a cure for HIV/AIDS. The long-lived latent viral reservoir of HIV-1 prevents its eradication and the development of a cure1. The recent combination antiretroviral therapy (cART) aimed at inhibiting viral enzymatic activities prevents HIV-1 repli- cation and halts the viral destruction of the host immune system2. However, proviruses in the latent reservoir persist in a transcriptionally inactive state, are insuppressible by cART and undetectable by the immune system3. -
4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4).