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IN COLON CANCER a Dissertation by SATYA SREEHARI PATHI Su
MECHANISMS OF ACTION OF NON-STEROIDAL ANTI-INFLAMMATORY DRUGS (NSAIDs) IN COLON CANCER A Dissertation by SATYA SREEHARI PATHI Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY August 2012 Major Subject: Toxicology MECHANISMS OF ACTION OF NON-STEROIDAL ANTI-INFLAMMATORY DRUGS (NSAIDs) IN COLON CANCER A Dissertation by SATYA SREEHARI PATHI Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Approved by: Chair of Committee, Stephen H. Safe Committee Members, Robert C. Burghardt Timothy Phillips Yanan Tian Interdisciplinary Faculty Chair of Toxicology, Weston Porter August 2012 Major Subject: Toxicology iii ABSTRACT Mechanisms of Action of Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) in Colon Cancer. (August 2012) Satya Sreehari Pathi, B.V.M., Acharya N. G. Ranga Agricultural University, India; M.S., Texas A&M University, Kingsville Chair of Advisory Committee: Dr. Stephen H. Safe Non-steroidal anti-inflammatory drugs (NSAIDs) and their NO derivatives (NO- NSAIDs), and synthetic analogs are highly effective as anticancer agents that exhibit relatively low toxicity compared to most clinically used drugs. However, the mechanisms of action for NSAIDs and NO-NSAIDs are not well defined and this has restricted their clinical applications and applications for combined therapies. Earlier studies from our laboratory reported that specificity protein (Sp) transcription factors (Sp1, Sp3 and Sp4) are overexpressed in several types of human cancers including colon cancer and many Sp-regulated genes are pro-oncogenic and individual targets for cancer chemotherapy. -
Genotyping for Response to Physical Training
Wright State University CORE Scholar Browse all Theses and Dissertations Theses and Dissertations 2019 Genotyping for Response to Physical Training Stacy Simmons Wright State University Follow this and additional works at: https://corescholar.libraries.wright.edu/etd_all Part of the Molecular Biology Commons Repository Citation Simmons, Stacy, "Genotyping for Response to Physical Training" (2019). Browse all Theses and Dissertations. 2109. https://corescholar.libraries.wright.edu/etd_all/2109 This Thesis is brought to you for free and open access by the Theses and Dissertations at CORE Scholar. It has been accepted for inclusion in Browse all Theses and Dissertations by an authorized administrator of CORE Scholar. For more information, please contact [email protected]. GENOTYPING FOR RESPONSE TO PHYSICAL TRAINING A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science By STACY SIMMONS B.S., Wright State University, 2014 _________________________________________________________ 2019 Wright State University WRIGHT STATE UNIVERSITY GRADUATE SCHOOL July 29, 2019 I HEREBY RECOMMEND THAT THE THESIS PREPARED UNDER MY SUPERVISION BY Stacy Simmons ENTITLED Genotyping for Response to Physical Training BE ACCEPTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF Master of Science. ___________________________________ Michael Markey, Ph.D. Thesis Director ____________________________________ Madhavi P. Kadakia, Ph.D. Committee on Chair, Department of Biochemistry Final Examination and -
Lupus-Associated Endogenous Retroviral LTR Polymorphism and Epigenetic Imprinting Promote HRES-1/Rab4 Expression and Mtor Activation
Lupus-associated endogenous retroviral LTR polymorphism and epigenetic imprinting promote HRES-1/Rab4 expression and mTOR activation Aparna Godavarthy, … , Katalin Banki, Andras Perl JCI Insight. 2019. https://doi.org/10.1172/jci.insight.134010. Research In-Press Preview Immunology Graphical abstract Find the latest version: https://jci.me/134010/pdf LUPUS-ASSOCIATED ENDOGENOUS RETROVIRAL LTR POLYMORPHISM AND EPIGENETIC IMPRINTING PROMOTE HRES-1/RAB4 EXPRESSION AND MTOR ACTIVATION Aparna Godavarthy*1, Ryan Kelly*1, John Jimah1, Miguel Beckford1, Tiffany Caza1,2, David Fernandez1,2, Nick Huang1,3, Manuel Duarte1,2, Joshua Lewis1,2, Hind J. Fadel4, Eric M. Poeschla4, Katalin Banki5, and Andras Perl1,2,3 * These authors contributed equally to the study. 1, Division of Rheumatology, Department of Medicine; 2, Department of Microbiology and Immunology; 3, Department of Biochemistry and Molecular Biology, and 5, Department of Pathology, State University of New York, Upstate Medical University, College of Medicine, 750 East Adams Street, Syracuse, New York 13210; 4, Department of Molecular Medicine; Mayo Clinic College of Medicine, 200 First Street SW, Rochester 55905, USA; Correspondence: Andras Perl, M.D., Ph.D. , State University of New York, College of Medicine, 750 East Adams Street, Syracuse, New York 13210; Phone: (315) 464-4194; Fax: (315) 464- 4176; E-mail: [email protected] Key Words: Systemic Lupus Erythematosus, T Cells, HRES-1/Rab4. mTOR, Autoimmunity The authors have declared that no conflict of interest exists. Supplementary Materials include Supplemental Methods and Supplementary Figures S1-S26. 1 ABSTRACT Overexpression and long terminal repeat (LTR) polymorphism of the HRES-1/Rab4 human endogenous retrovirus locus have been associated with T-cell activation and disease manifestations in systemic lupus erythematosus (SLE). -
Identification of Novel Pathways That Promote Anoikis Through Genome-Wide Screens
University of Massachusetts Medical School eScholarship@UMMS GSBS Dissertations and Theses Graduate School of Biomedical Sciences 2016-10-14 Identification of Novel Pathways that Promote Anoikis through Genome-wide Screens Victoria E. Pedanou University of Massachusetts Medical School Let us know how access to this document benefits ou.y Follow this and additional works at: https://escholarship.umassmed.edu/gsbs_diss Part of the Biology Commons, and the Cancer Biology Commons Repository Citation Pedanou VE. (2016). Identification of Novel Pathways that Promote Anoikis through Genome-wide Screens. GSBS Dissertations and Theses. https://doi.org/10.13028/M27G6D. Retrieved from https://escholarship.umassmed.edu/gsbs_diss/889 This material is brought to you by eScholarship@UMMS. It has been accepted for inclusion in GSBS Dissertations and Theses by an authorized administrator of eScholarship@UMMS. For more information, please contact [email protected]. i TITLE PAGE IDENTIFICATION OF NOVEL PATHWAYS THAT PROMOTE ANOIKIS THROUGH GENOME-WIDE SCREENS A Dissertation Presented By VICTORIA ELIZABETH PEDANOU Submitted to the Faculty of the University of Massachusetts Graduate School of Biomedical Sciences, Worcester in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY OCTOBER 14TH, 2016 CANCER BIOLOGY ii SIGNATURE PAGE IDENTIFICATION OF NOVEL PATHWAYS THAT PROMOTE ANOIKIS THROUGH GENOME-WIDE SCREENS A Dissertation Presented By VICTORIA ELIZABETH PEDANOU This work was undertaken in the Graduate School of Biomedical Sciences Cancer Biology The signature of the Thesis Advisor signifies validation of Dissertation content ___________________________ Michael R. Green, Thesis Advisor The signatures of the Dissertation Defense Committee signify completion and approval as to style and content of the Dissertation __________________________________ Eric H. -
Mathiomica: an Integrative Platform for Dynamic Omics George I
MathIOmica: An Integrative Platform for Dynamic Omics George I. Mias1,*, Tahir Yusufaly2, Raeuf Roushangar1, Lavida R. K. Brooks1, Vikas V. Singh1, and Christina Christou3 1Michigan State University, Biochemistry and Molecular Biology, East Lansing, MI 48824, USA 2University of Southern California, Department of Physics and Astronomy, Los Angeles, CA, 90089, USA 3Mercy Cancer Center, Department of Radiation Oncology, Mason City, IA 50401, USA *[email protected] SUPPLEMENTARY NOTE 1 1 1 MathIOmica: Omics Analysis Tutorial Loading the MathIOmica Package Metabolomic Data Data in MathIOmica Combined Data Clustering Transcriptome Data Visualization Proteomic Data Annotation and Enrichment MathIOmica is an omics analysis package designed to facilitate method development for the analysis of multiple omics in Mathematica, particularly for dynamics (time series/longitudinal data). This extensive tutorial follows the analysis of multiple dynamic omics data (transcriptomics, proteomics, and metabolomics from human samples). Various MathIOmica functions are introduced in the tutorial, including additional discussion of related functionality. We should note that the approach methods are simply an illustration of MathIOmica functionality, and should not be considered as a definitive appoach. Additionally, certain details are included to illustrate common complications (e.g. renaming samples, combining datasets, transforming accessions from one database to another, dealing with replicates and Missing data, etc.). After a brief discussion of data in MathIOmica, each example data (transcriptome, proteome and metabolome) are imported and preprocessed. Next a simulation is carried out to obtain datasets for each omics used to assess statistical significance cutoffs. The datasets are combined, and classified for time series patterns, followed by clustering. The clusters are visualized, and biological annotation of Gene Ontology (GO) and pathway analysis (KEGG: Kyoto Encyclopedia of Genes and Genomes) are finally considered. -
Katalog 2015 Cover Paul Lin *Hinweis Förderung.Indd
Product List 2015 WE LIVE SERVICE Certificates quartett owns two productions sites that are certified according to EN ISO 9001:2008 Quality management systems - Requirements EN ISO 13485:2012 + AC:2012 Medical devices - Quality management systems - Requirements for regulatory purposes GMP Conformity Our quality management guarantees products of highest quality! 2 Foreword to the quartett product list 2015 quartett Immunodiagnostika, Biotechnologie + Kosmetik Vertriebs GmbH welcomes you as one of our new business partners as well as all of our previous loyal clients. You are now member of quartett´s worldwide customers. First of all we would like to introduce ourselves to you. Founded as a family-run company in 1986, quartett ensures for more than a quarter of a century consistent quality of products. Service and support of our valued customers are our daily businesses. And we will continue! In the end 80´s quartett offered radioimmunoassay and enzyme immunoassay kits from different manufacturers in the USA. In the beginning 90´s the company changed its strategy from offering products for routine diagnostic to the increasing field of research and development. Setting up a production plant in 1997 and a second one in 2011 supported this decision. The company specialized its product profile in the field of manufacturing synthetic peptides for antibody production, peptides such as protease inhibitors, biochemical reagents and products for histology, cytology and immunohistology. All products are exclusively manufactured in Germany without outsourcing any production step. Nowadays, we expand into all other diagnostic and research fields and supply our customers in universities, government institutes, pharmaceutical and biotechnological companies, hospitals, and private doctor offices. -
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. -
Evidence for Differential Alternative Splicing in Blood of Young Boys With
Stamova et al. Molecular Autism 2013, 4:30 http://www.molecularautism.com/content/4/1/30 RESEARCH Open Access Evidence for differential alternative splicing in blood of young boys with autism spectrum disorders Boryana S Stamova1,2,5*, Yingfang Tian1,2,4, Christine W Nordahl1,3, Mark D Shen1,3, Sally Rogers1,3, David G Amaral1,3 and Frank R Sharp1,2 Abstract Background: Since RNA expression differences have been reported in autism spectrum disorder (ASD) for blood and brain, and differential alternative splicing (DAS) has been reported in ASD brains, we determined if there was DAS in blood mRNA of ASD subjects compared to typically developing (TD) controls, as well as in ASD subgroups related to cerebral volume. Methods: RNA from blood was processed on whole genome exon arrays for 2-4–year-old ASD and TD boys. An ANCOVA with age and batch as covariates was used to predict DAS for ALL ASD (n=30), ASD with normal total cerebral volumes (NTCV), and ASD with large total cerebral volumes (LTCV) compared to TD controls (n=20). Results: A total of 53 genes were predicted to have DAS for ALL ASD versus TD, 169 genes for ASD_NTCV versus TD, 1 gene for ASD_LTCV versus TD, and 27 genes for ASD_LTCV versus ASD_NTCV. These differences were significant at P <0.05 after false discovery rate corrections for multiple comparisons (FDR <5% false positives). A number of the genes predicted to have DAS in ASD are known to regulate DAS (SFPQ, SRPK1, SRSF11, SRSF2IP, FUS, LSM14A). In addition, a number of genes with predicted DAS are involved in pathways implicated in previous ASD studies, such as ROS monocyte/macrophage, Natural Killer Cell, mTOR, and NGF signaling. -
Ageing-Associated Changes in DNA Methylation in X and Y Chromosomes
Kananen and Marttila Epigenetics & Chromatin (2021) 14:33 Epigenetics & Chromatin https://doi.org/10.1186/s13072-021-00407-6 RESEARCH Open Access Ageing-associated changes in DNA methylation in X and Y chromosomes Laura Kananen1,2,3,4* and Saara Marttila4,5* Abstract Background: Ageing displays clear sexual dimorphism, evident in both morbidity and mortality. Ageing is also asso- ciated with changes in DNA methylation, but very little focus has been on the sex chromosomes, potential biological contributors to the observed sexual dimorphism. Here, we sought to identify DNA methylation changes associated with ageing in the Y and X chromosomes, by utilizing datasets available in data repositories, comprising in total of 1240 males and 1191 females, aged 14–92 years. Results: In total, we identifed 46 age-associated CpG sites in the male Y, 1327 age-associated CpG sites in the male X, and 325 age-associated CpG sites in the female X. The X chromosomal age-associated CpGs showed signifcant overlap between females and males, with 122 CpGs identifed as age-associated in both sexes. Age-associated X chro- mosomal CpGs in both sexes were enriched in CpG islands and depleted from gene bodies and showed no strong trend towards hypermethylation nor hypomethylation. In contrast, the Y chromosomal age-associated CpGs were enriched in gene bodies, and showed a clear trend towards hypermethylation with age. Conclusions: Signifcant overlap in X chromosomal age-associated CpGs identifed in males and females and their shared features suggest that despite the uneven chromosomal dosage, diferences in ageing-associated DNA methylation changes in the X chromosome are unlikely to be a major contributor of sex dimorphism in ageing. -
ARTICLE Doi:10.1038/Nature10523
ARTICLE doi:10.1038/nature10523 Spatio-temporal transcriptome of the human brain Hyo Jung Kang1*, Yuka Imamura Kawasawa1*, Feng Cheng1*, Ying Zhu1*, Xuming Xu1*, Mingfeng Li1*, Andre´ M. M. Sousa1,2, Mihovil Pletikos1,3, Kyle A. Meyer1, Goran Sedmak1,3, Tobias Guennel4, Yurae Shin1, Matthew B. Johnson1,Zˇeljka Krsnik1, Simone Mayer1,5, Sofia Fertuzinhos1, Sheila Umlauf6, Steven N. Lisgo7, Alexander Vortmeyer8, Daniel R. Weinberger9, Shrikant Mane6, Thomas M. Hyde9,10, Anita Huttner8, Mark Reimers4, Joel E. Kleinman9 & Nenad Sˇestan1 Brain development and function depend on the precise regulation of gene expression. However, our understanding of the complexity and dynamics of the transcriptome of the human brain is incomplete. Here we report the generation and analysis of exon-level transcriptome and associated genotyping data, representing males and females of different ethnicities, from multiple brain regions and neocortical areas of developing and adult post-mortem human brains. We found that 86 per cent of the genes analysed were expressed, and that 90 per cent of these were differentially regulated at the whole-transcript or exon level across brain regions and/or time. The majority of these spatio-temporal differences were detected before birth, with subsequent increases in the similarity among regional transcriptomes. The transcriptome is organized into distinct co-expression networks, and shows sex-biased gene expression and exon usage. We also profiled trajectories of genes associated with neurobiological categories and diseases, and identified associations between single nucleotide polymorphisms and gene expression. This study provides a comprehensive data set on the human brain transcriptome and insights into the transcriptional foundations of human neurodevelopment. -
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 -
Table SI. Primer List of Genes Used for Reverse Transcription‑Quantitative PCR Validation
Table SI. Primer list of genes used for reverse transcription‑quantitative PCR validation. Genes Forward (5'‑3') Reverse (5'‑3') Length COL1A1 AGTGGTTTGGATGGTGCCAA GCACCATCATTTCCACGAGC 170 COL6A1 CCCCTCCCCACTCATCACTA CGAATCAGGTTGGTCGGGAA 65 COL2A1 GGTCCTGCAGGTGAACCC CTCTGTCTCCTTGCTTGCCA 181 DCT CTACGAAACCAGGATGACCGT ACCATCATTGGTTTGCCTTTCA 192 PDE4D ATTGCCCACGATAGCTGCTC GCAGATGTGCCATTGTCCAC 181 RP11‑428C19.4 ACGCTAGAAACAGTGGTGCG AATCCCCGGAAAGATCCAGC 179 GPC‑AS2 TCTCAACTCCCCTCCTTCGAG TTACATTTCCCGGCCCATCTC 151 XLOC_110310 AGTGGTAGGGCAAGTCCTCT CGTGGTGGGATTCAAAGGGA 187 COL1A1, collagen type I alpha 1; COL6A1, collagen type VI, alpha 1; COL2A1, collagen type II alpha 1; DCT, dopachrome tautomerase; PDE4D, phosphodiesterase 4D cAMP‑specific. Table SII. The differentially expressed mRNAs in the ParoAF_Control group. Gene ID logFC P‑Value Symbol Description ENSG00000165480 ‑6.4838 8.32E‑12 SKA3 Spindle and kinetochore associated complex subunit 3 ENSG00000165424 ‑6.43924 0.002056 ZCCHC24 Zinc finger, CCHC domain containing 24 ENSG00000182836 ‑6.20215 0.000817 PLCXD3 Phosphatidylinositol‑specific phospholipase C, X domain containing 3 ENSG00000174358 ‑5.79775 0.029093 SLC6A19 Solute carrier family 6 (neutral amino acid transporter), member 19 ENSG00000168916 ‑5.761 0.004046 ZNF608 Zinc finger protein 608 ENSG00000134343 ‑5.56371 0.01356 ANO3 Anoctamin 3 ENSG00000110400 ‑5.48194 0.004123 PVRL1 Poliovirus receptor‑related 1 (herpesvirus entry mediator C) ENSG00000124882 ‑5.45849 0.022164 EREG Epiregulin ENSG00000113448 ‑5.41752 0.000577 PDE4D Phosphodiesterase