Table S2 A375P Vs SK-MEL-2
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MLR) Model and Filtration
SUPPLEMENT Contents 1. Extended description of the Data sets. 2. Extended description of the multiple linear regression (MLR) model and filtration. 3. Extended description of the random-gene classifiers. 4. Extended description of the comparison with Dakhova et al. (1)and Richardson et al. (2) 5. Extended description of preparation of RNA and the XP_PCR protocol. 6. Table S1. Comparison of 131-probe set Diagnostic Classifier to classifiers generated with ‘random’ genes. 7. Table S2. Concordance of 38 overlapping genes/probe sets of the 339 probe sets ( basis) of the Diagnostic Classifier with the sign of differential change of Dakhova et al. (1). 8. Table S3. Function enrichment analysis. 9. Table S4. PCR validation of preferential expression in stroma by representative genes of the Diagnostic Classifier. 10. Figure S1. The incidence numbers of 339 probe sets obtained by 105-fold permutation procedure for gene selection. 11. Figure S2. Heatmap using the Diagnostic Classifier to categorize all training cases. 12. Figure S3. Heatmap of all 364 test samples used in this study as categorized by the 131 probe set Diagnostic Classifier. 13. Figure S4. Cluster diagram of the cases of Dakhova et al. (1) using only the 38 overlapping genes. 14. References for the Supplement. 1 1. Extended description of the Data Sets. Datasets 1 and 2 (Table 1) are based on post-prostatectomy frozen tissue samples obtained by informed consent using IRB-approved and HIPPA-compliant protocols. All tissues, except where noted, were collected at surgery and escorted to pathology for expedited review, dissection, and snap freezing in liquid nitrogen. -
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. -
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). -
Structural and Functional Diversity of Caspase Homologues in Non-Metazoan Organisms
Protoplasma DOI 10.1007/s00709-017-1145-5 REVIEW ARTICLE Structural and functional diversity of caspase homologues in non-metazoan organisms Marina Klemenčič1,2 & Christiane Funk1 Received: 1 June 2017 /Accepted: 5 July 2017 # The Author(s) 2017. This article is an open access publication Abstract Caspases, the proteases involved in initiation and supports the role of metacaspases and orthocaspases as im- execution of metazoan programmed cell death, are only pres- portant contributors to cell homeostasis during normal physi- ent in animals, while their structural homologues can be ological conditions or cell differentiation and ageing. found in all domains of life, spanning from simple prokary- otes (orthocaspases) to yeast and plants (metacaspases). All members of this wide protease family contain the p20 do- Keywords Algae . Cyanobacteria . Cell death . Cysteine main, which harbours the catalytic dyad formed by the two protease . Metacaspase . Orthocaspase amino acid residues, histidine and cysteine. Despite the high structural similarity of the p20 domain, metacaspases and orthocaspases were found to exhibit different substrate speci- ficities than caspases. While the former cleave their substrates Introduction after basic amino acid residues, the latter accommodate sub- strates with negative charge. This observation is crucial for BOut of life’s school of war: What does not destroy me, the re-evaluation of non-metazoan caspase homologues being makes me stronger.^ wrote the German philosopher involved in processes of programmed cell death. In this re- Friedrich Nietzsche in his book Twilight of the Idols or view, we analyse the structural diversity of enzymes contain- how to philosophize with a hammer. Even though ing the p20 domain, with focus on the orthocaspases, and reformatted to more common use, this phrase has been summarise recent advances in research of orthocaspases and used to describe the dual nature of caspase homologues metacaspases of cyanobacteria, algae and higher plants. -
Investigation of Candidate Genes and Mechanisms Underlying Obesity
Prashanth et al. BMC Endocrine Disorders (2021) 21:80 https://doi.org/10.1186/s12902-021-00718-5 RESEARCH ARTICLE Open Access Investigation of candidate genes and mechanisms underlying obesity associated type 2 diabetes mellitus using bioinformatics analysis and screening of small drug molecules G. Prashanth1 , Basavaraj Vastrad2 , Anandkumar Tengli3 , Chanabasayya Vastrad4* and Iranna Kotturshetti5 Abstract Background: Obesity associated type 2 diabetes mellitus is a metabolic disorder ; however, the etiology of obesity associated type 2 diabetes mellitus remains largely unknown. There is an urgent need to further broaden the understanding of the molecular mechanism associated in obesity associated type 2 diabetes mellitus. Methods: To screen the differentially expressed genes (DEGs) that might play essential roles in obesity associated type 2 diabetes mellitus, the publicly available expression profiling by high throughput sequencing data (GSE143319) was downloaded and screened for DEGs. Then, Gene Ontology (GO) and REACTOME pathway enrichment analysis were performed. The protein - protein interaction network, miRNA - target genes regulatory network and TF-target gene regulatory network were constructed and analyzed for identification of hub and target genes. The hub genes were validated by receiver operating characteristic (ROC) curve analysis and RT- PCR analysis. Finally, a molecular docking study was performed on over expressed proteins to predict the target small drug molecules. Results: A total of 820 DEGs were identified between -
Cell Reprogramming Technologies for Treatment And
CELL REPROGRAMMING TECHNOLOGIES FOR TREATMENT AND UNDERSTANDING OF GENETIC DISORDERS OF MYELIN by ANGELA MARIE LAGER Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Thesis advisor: Paul J Tesar, PhD Department of Genetics and Genome Sciences CASE WESTERN RESERVE UNIVERSITY May 2015 CASE WESTERN RESERVE UNIVERSITY SCHOOL OF GRADUATE STUDIES We hereby approve the thesis/dissertation of Angela Marie Lager Candidate for the Doctor of Philosophy degree*. (signed) Ronald A Conlon, PhD (Committee Chair) Paul J Tesar, PhD (Advisor) Craig A Hodges, PhD Warren J Alilain, PhD (date) 31 March 2015 *We also certify that written approval has been obtained from any proprietary material contained therein. TABLE OF CONTENTS Table of Contents……………………………………………………………………….1 List of Figures……………………………………………………………………………4 Acknowledgements……………………………………………………………………..7 Abstract…………………………………………………………………………………..8 Chapter 1: Introduction and Background………………………………………..11 1.1 Overview of mammalian oligodendrocyte development in the spinal cord and myelination of the central nervous system…………………..11 1.1.1 Introduction……………………………………………………..11 1.1.2 The establishment of the neuroectoderm and ventral formation of the neural tube…………………………………..12 1.1.3 Ventral patterning of the neural tube and specification of the pMN domain in the spinal cord……………………………….15 1.1.4 Oligodendrocyte progenitor cell production through the process of gliogenesis ………………………………………..16 1.1.5 Oligodendrocyte progenitor cell to oligodendrocyte differentiation…………………………………………………...22 -
Serine Proteases with Altered Sensitivity to Activity-Modulating
(19) & (11) EP 2 045 321 A2 (12) EUROPEAN PATENT APPLICATION (43) Date of publication: (51) Int Cl.: 08.04.2009 Bulletin 2009/15 C12N 9/00 (2006.01) C12N 15/00 (2006.01) C12Q 1/37 (2006.01) (21) Application number: 09150549.5 (22) Date of filing: 26.05.2006 (84) Designated Contracting States: • Haupts, Ulrich AT BE BG CH CY CZ DE DK EE ES FI FR GB GR 51519 Odenthal (DE) HU IE IS IT LI LT LU LV MC NL PL PT RO SE SI • Coco, Wayne SK TR 50737 Köln (DE) •Tebbe, Jan (30) Priority: 27.05.2005 EP 05104543 50733 Köln (DE) • Votsmeier, Christian (62) Document number(s) of the earlier application(s) in 50259 Pulheim (DE) accordance with Art. 76 EPC: • Scheidig, Andreas 06763303.2 / 1 883 696 50823 Köln (DE) (71) Applicant: Direvo Biotech AG (74) Representative: von Kreisler Selting Werner 50829 Köln (DE) Patentanwälte P.O. Box 10 22 41 (72) Inventors: 50462 Köln (DE) • Koltermann, André 82057 Icking (DE) Remarks: • Kettling, Ulrich This application was filed on 14-01-2009 as a 81477 München (DE) divisional application to the application mentioned under INID code 62. (54) Serine proteases with altered sensitivity to activity-modulating substances (57) The present invention provides variants of ser- screening of the library in the presence of one or several ine proteases of the S1 class with altered sensitivity to activity-modulating substances, selection of variants with one or more activity-modulating substances. A method altered sensitivity to one or several activity-modulating for the generation of such proteases is disclosed, com- substances and isolation of those polynucleotide se- prising the provision of a protease library encoding poly- quences that encode for the selected variants. -
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. -
RSC Advances
RSC Advances This is an Accepted Manuscript, which has been through the Royal Society of Chemistry peer review process and has been accepted for publication. Accepted Manuscripts are published online shortly after acceptance, before technical editing, formatting and proof reading. Using this free service, authors can make their results available to the community, in citable form, before we publish the edited article. This Accepted Manuscript will be replaced by the edited, formatted and paginated article as soon as this is available. You can find more information about Accepted Manuscripts in the Information for Authors. Please note that technical editing may introduce minor changes to the text and/or graphics, which may alter content. The journal’s standard Terms & Conditions and the Ethical guidelines still apply. In no event shall the Royal Society of Chemistry be held responsible for any errors or omissions in this Accepted Manuscript or any consequences arising from the use of any information it contains. www.rsc.org/advances Page 1 of 8 RSC Advances The Effects of Solvent Composition on the Affinity of a Peptide towards Hair Keratin: Experimental and Molecular Dynamics Data. Egipto Antunes a, Célia F. Cruz a, Nuno G. Azoia a, Artur Cavaco-Paulo a* a CEB – Centre of Biological Engineering, University of Minho, 4710-057 Braga, Portugal Table of Contents Manuscript Accepted Molecular dynamics simulations with a developed hair protofibril model demonstrated capability to improve a peptide uptake by hair shafts. Advances RSC RSC Advances Page 2 of 8 RSC Advances RSCPublishing ARTICLE The Effects of Solvent Composition on the Affinity of a Peptide towards Hair Keratin: Experimental and Cite this: DOI: 10.1039/x0xx00000x Molecular Dynamics Data. -
TITLE PAGE Oxidative Stress and Response to Thymidylate Synthase
Downloaded from molpharm.aspetjournals.org at ASPET Journals on October 2, 2021 -Targeted -Targeted 1 , University of of , University SC K.W.B., South Columbia, (U.O., Carolina, This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. -
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 -
Gene Expression Profiles Complement the Analysis of Genomic Modifiers of the Clinical Onset of Huntington Disease
bioRxiv preprint doi: https://doi.org/10.1101/699033; this version posted July 11, 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. 1 Gene expression profiles complement the analysis of genomic modifiers of the clinical onset of Huntington disease Galen E.B. Wright1,2,3; Nicholas S. Caron1,2,3; Bernard Ng1,2,4; Lorenzo Casal1,2,3; Xiaohong Xu5; Jolene Ooi5; Mahmoud A. Pouladi5,6,7; Sara Mostafavi1,2,4; Colin J.D. Ross3,7 and Michael R. Hayden1,2,3* 1Centre for Molecular Medicine and Therapeutics, Vancouver, British Columbia, Canada; 2Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada; 3BC Children’s Hospital Research Institute, Vancouver, British Columbia, Canada; 4Department of Statistics, University of British Columbia, Vancouver, British Columbia, Canada; 5Translational Laboratory in Genetic Medicine (TLGM), Agency for Science, Technology and Research (A*STAR), Singapore; 6Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; 7Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; 8Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia, Canada; *Corresponding author ABSTRACT Huntington disease (HD) is a neurodegenerative disorder that is caused by a CAG repeat expansion in the HTT gene. In an attempt to identify genomic modifiers that contribute towards the age of onset of HD, we performed a transcriptome wide association study assessing heritable differences in genetically determined expression in diverse tissues, employing genome wide data from over 4,000 patients.