Downloaded from the App Store and Nucleobase, Nucleotide and Nucleic Acid Metabolism 7 Google Play
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Screening and Identification of Key Biomarkers in Clear Cell Renal Cell Carcinoma Based on Bioinformatics Analysis
bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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. Screening and identification of key biomarkers in clear cell renal cell carcinoma based on bioinformatics analysis Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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 Clear cell renal cell carcinoma (ccRCC) is one of the most common types of malignancy of the urinary system. The pathogenesis and effective diagnosis of ccRCC have become popular topics for research in the previous decade. In the current study, an integrated bioinformatics analysis was performed to identify core genes associated in ccRCC. An expression dataset (GSE105261) was downloaded from the Gene Expression Omnibus database, and included 26 ccRCC and 9 normal kideny samples. Assessment of the microarray dataset led to the recognition of differentially expressed genes (DEGs), which was subsequently used for pathway and gene ontology (GO) enrichment analysis. -
Ovulation-Selective Genes: the Generation and Characterization of an Ovulatory-Selective Cdna Library
531 Ovulation-selective genes: the generation and characterization of an ovulatory-selective cDNA library A Hourvitz1,2*, E Gershon2*, J D Hennebold1, S Elizur2, E Maman2, C Brendle1, E Y Adashi1 and N Dekel2 1Division of Reproductive Sciences, Department of Obstetrics and Gynecology, University of Utah Health Sciences Center, Salt Lake City, Utah 84132, USA 2Department of Biological Regulation, Weizmann Institute of Science, Rehovot, Israel (Requests for offprints should be addressed to N Dekel; Email: [email protected]) *(A Hourvitz and E Gershon contributed equally to this paper) (J D Hennebold is now at Division of Reproductive Sciences, Oregon National Primate Research Center, Oregon Health and Science University, Beaverton, Oregon 97006, USA) Abstract Ovulation-selective/specific genes, that is, genes prefer- (FAE-1) homolog, found to be localized to the inner entially or exclusively expressed during the ovulatory periantral granulosa and to the cumulus granulosa cells of process, have been the subject of growing interest. We antral follicles. The FAE-1 gene is a -ketoacyl-CoA report herein studies on the use of suppression subtractive synthase belonging to the fatty acid elongase (ELO) hybridization (SSH) to construct a ‘forward’ ovulation- family, which catalyzes the initial step of very long-chain selective/specific cDNA library. In toto, 485 clones were fatty acid synthesis. All in all, the present study accom- sequenced and analyzed for homology to known genes plished systematic identification of those hormonally with the basic local alignment tool (BLAST). Of those, regulated genes that are expressed in the ovary in an 252 were determined to be nonredundant. -
Mapping Influenza-Induced Posttranslational Modifications On
viruses Article Mapping Influenza-Induced Posttranslational Modifications on Histones from CD8+ T Cells Svetlana Rezinciuc 1, Zhixin Tian 2, Si Wu 2, Shawna Hengel 2, Ljiljana Pasa-Tolic 2 and Heather S. Smallwood 1,3,* 1 Department of Pediatrics, University of Tennessee Health Science Center, Memphis, TN 38163, USA; [email protected] 2 Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99354, USA; [email protected] (Z.T.); [email protected] (S.W.); [email protected] (S.H.); [email protected] (L.P.-T.) 3 Children’s Foundation Research Institute, Memphis, TN 38105, USA * Correspondence: [email protected]; Tel.: +1-(901)-448–3068 Academic Editor: Italo Tempera Received: 10 October 2020; Accepted: 2 December 2020; Published: 8 December 2020 Abstract: T cell function is determined by transcriptional networks that are regulated by epigenetic programming via posttranslational modifications (PTMs) to histone proteins and DNA. Bottom-up mass spectrometry (MS) can identify histone PTMs, whereas intact protein analysis by MS can detect species missed by bottom-up approaches. We used a novel approach of online two-dimensional liquid chromatography-tandem MS with high-resolution reversed-phase liquid chromatography (RPLC), alternating electron transfer dissociation (ETD) and collision-induced dissociation (CID) on precursor ions to maximize fragmentation of uniquely modified species. The first online RPLC separation sorted histone families, then RPLC or weak cation exchange hydrophilic interaction liquid chromatography (WCX-HILIC) separated species heavily clad in PTMs. Tentative identifications were assigned by matching proteoform masses to predicted theoretical masses that were verified with tandem MS. We used this innovative approach for histone-intact protein PTM mapping (HiPTMap) to identify and quantify proteoforms purified from CD8 T cells after in vivo influenza infection. -
FARSB Antibody (C-Term) Affinity Purified Rabbit Polyclonal Antibody (Pab) Catalog # Ap14090b
10320 Camino Santa Fe, Suite G San Diego, CA 92121 Tel: 858.875.1900 Fax: 858.622.0609 FARSB Antibody (C-term) Affinity Purified Rabbit Polyclonal Antibody (Pab) Catalog # AP14090b Specification FARSB Antibody (C-term) - Product Information Application WB, IHC-P,E Primary Accession Q9NSD9 Other Accession NP_005678.3 Reactivity Human Host Rabbit Clonality Polyclonal Isotype Rabbit Ig Calculated MW 66116 Antigen Region 535-564 FARSB Antibody (C-term) - Additional Information Gene ID 10056 FARSB Antibody (C-term) (Cat. #AP14090b) western blot analysis in Y79 cell line lysates Other Names (35ug/lane).This demonstrates the FARSB Phenylalanine--tRNA ligase beta subunit, antibody detected the FARSB protein (arrow). Phenylalanyl-tRNA synthetase beta subunit, PheRS, FARSB, FARSLB, FRSB Target/Specificity This FARSB antibody is generated from rabbits immunized with a KLH conjugated synthetic peptide between 535-564 amino acids from the C-terminal region of human FARSB. Dilution WB~~1:1000 IHC-P~~1:10~50 Format Purified polyclonal antibody supplied in PBS with 0.09% (W/V) sodium azide. This antibody is purified through a protein A column, followed by peptide affinity purification. FARSB Antibody (C-term) (Cat. #AP14090b)immunohistochemistry analysis Storage in formalin fixed and paraffin embedded Maintain refrigerated at 2-8°C for up to 2 human cerebellum tissue followed by weeks. For long term storage store at -20°C peroxidase conjugation of the secondary in small aliquots to prevent freeze-thaw antibody and DAB staining.This data cycles. demonstrates the use of ANKS1B FARSB Antibody (C-term) for immunohistochemistry. Precautions Clinical relevance has not been evaluated. FARSB Antibody (C-term) is for research use Page 1/2 10320 Camino Santa Fe, Suite G San Diego, CA 92121 Tel: 858.875.1900 Fax: 858.622.0609 only and not for use in diagnostic or FARSB Antibody (C-term) - Background therapeutic procedures. -
UNIVERSITY of CALIFORNIA, SAN DIEGO Functional Analysis of Sall4
UNIVERSITY OF CALIFORNIA, SAN DIEGO Functional analysis of Sall4 in modulating embryonic stem cell fate A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Molecular Pathology by Pei Jen A. Lee Committee in charge: Professor Steven Briggs, Chair Professor Geoff Rosenfeld, Co-Chair Professor Alexander Hoffmann Professor Randall Johnson Professor Mark Mercola 2009 Copyright Pei Jen A. Lee, 2009 All rights reserved. The dissertation of Pei Jen A. Lee is approved, and it is acceptable in quality and form for publication on microfilm and electronically: ______________________________________________________________ ______________________________________________________________ ______________________________________________________________ ______________________________________________________________ Co-Chair ______________________________________________________________ Chair University of California, San Diego 2009 iii Dedicated to my parents, my brother ,and my husband for their love and support iv Table of Contents Signature Page……………………………………………………………………….…iii Dedication…...…………………………………………………………………………..iv Table of Contents……………………………………………………………………….v List of Figures…………………………………………………………………………...vi List of Tables………………………………………………….………………………...ix Curriculum vitae…………………………………………………………………………x Acknowledgement………………………………………………….……….……..…...xi Abstract………………………………………………………………..…………….....xiii Chapter 1 Introduction ..…………………………………………………………………………….1 Chapter 2 Materials and Methods……………………………………………………………..…12 -
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. -
Sequence Variation in the Dihydrofolate Reductase-Thymidylate Synthase (DHFR-TS) and Trypanothione Reductase (TR) Genes of Trypanosoma Cruzi
Molecular & Biochemical Parasitology 121 (2002) 33Á/47 www.parasitology-online.com Sequence variation in the dihydrofolate reductase-thymidylate synthase (DHFR-TS) and trypanothione reductase (TR) genes of Trypanosoma cruzi Carlos A. Machado *, Francisco J. Ayala Department of Ecology and Evolutionary Biology, University of California, Irvine, CA 92697-2525, USA Received 15 November 2001; received in revised form 25 January 2002 Abstract Dihydrofolate reductase-thymidylate synthase (DHFR-TS) and trypanothione reductase (TR) are important enzymes for the metabolism of protozoan parasites from the family Trypanosomatidae (e.g. Trypanosoma spp., Leishmania spp.) that are targets of current drug-design studies. Very limited information exists on the levels of genetic polymorphism of these enzymes in natural populations of any trypanosomatid parasite. We present results of a survey of nucleotide variation in the genes coding for those enzymes in a large sample of strains from Trypanosoma cruzi, the agent of Chagas’ disease. We discuss the results from an evolutionary perspective. A sample of 31 strains show 39 silent and five amino acid polymorphisms in DHFR-TS, and 35 silent and 11 amino acid polymorphisms in TR. No amino acid replacements occur in regions that are important for the enzymatic activity of these proteins, but some polymorphisms occur in sites previously assumed to be invariant. The sequences from both genes cluster in four major groups, a result that is not fully consistent with the current classification of T. cruzi in two major groups of strains. Most polymorphisms correspond to fixed differences among the four sequence groups. Two tests of neutrality show that there is no evidence of adaptivedivergence or of selectiveevents having shaped the distribution of polymorphisms and fixed differences in these genes in T. -
Natural Selection Has Shaped Coding and Non-Coding Transcription in Primate CD4+ T-Cells 2 3 Charles G
bioRxiv preprint doi: https://doi.org/10.1101/083212; this version posted October 25, 2016. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 1 Natural Selection has Shaped Coding and Non-coding Transcription in Primate CD4+ T-cells 2 3 Charles G. Danko1,2,*, Zhong Wang1, Edward J. Rice1, Tinyi Chu1,3, Andre L. Martins1, 4 Elia Tait Wojno1,4, John T. Lis5, W. Lee Kraus6,7, & Adam Siepel8,* 5 6 1 Baker Institute for Animal Health, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853. 7 2 Department of Biomedical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853. 8 3 Graduate field of Computational Biology, Cornell University, Ithaca, NY 14853. 9 4 Department of Microbiology & Immunology, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853. 10 5 Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14853. 11 6 Laboratory of Signaling and Gene Regulation, Cecil H. and Ida Green Center for Reproductive Biology Sciences, 12 University of Texas Southwestern Medical Center, Dallas, TX 75390. 13 7 Division of Basic Research, Department of Obstetrics and Gynecology, University of Texas Southwestern Medical 14 Center, Dallas, TX 75390. 15 8 Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724. 16 17 * Address correspondence to: 18 Charles G. Danko, Ph.D. Adam Siepel, Ph.D. 19 Baker Institute for Animal Health Simons Center for Quantitative Biology 20 Cornell University Cold Spring Harbor Laboratory 21 Hungerford Hill Rd. -
Supplementary Table S1. Table 1. List of Bacterial Strains Used in This Study Suppl
Supplementary Material Supplementary Tables: Supplementary Table S1. Table 1. List of bacterial strains used in this study Supplementary Table S2. List of plasmids used in this study Supplementary Table 3. List of primers used for mutagenesis of P. intermedia Supplementary Table 4. List of primers used for qRT-PCR analysis in P. intermedia Supplementary Table 5. List of the most highly upregulated genes in P. intermedia OxyR mutant Supplementary Table 6. List of the most highly downregulated genes in P. intermedia OxyR mutant Supplementary Table 7. List of the most highly upregulated genes in P. intermedia grown in iron-deplete conditions Supplementary Table 8. List of the most highly downregulated genes in P. intermedia grown in iron-deplete conditions Supplementary Figures: Supplementary Figure 1. Comparison of the genomic loci encoding OxyR in Prevotella species. Supplementary Figure 2. Distribution of SOD and glutathione peroxidase genes within the genus Prevotella. Supplementary Table S1. Bacterial strains Strain Description Source or reference P. intermedia V3147 Wild type OMA14 isolated from the (1) periodontal pocket of a Japanese patient with periodontitis V3203 OMA14 PIOMA14_I_0073(oxyR)::ermF This study E. coli XL-1 Blue Host strain for cloning Stratagene S17-1 RP-4-2-Tc::Mu aph::Tn7 recA, Smr (2) 1 Supplementary Table S2. Plasmids Plasmid Relevant property Source or reference pUC118 Takara pBSSK pNDR-Dual Clonetech pTCB Apr Tcr, E. coli-Bacteroides shuttle vector (3) plasmid pKD954 Contains the Porpyromonas gulae catalase (4) -
Drug Consumption in 2017 - 2020
Page 1 Drug consumption in 2017 - 2020 2020 2019 2018 2017 DDD/ DDD/ DDD/ DDD/ 1000 inhab./ Hospital 1000 inhab./ Hospital 1000 inhab./ Hospital 1000 inhab./ Hospital ATC code Subgroup or chemical substance day % day % day % day % A ALIMENTARY TRACT AND METABOLISM 322,79 3 312,53 4 303,08 4 298,95 4 A01 STOMATOLOGICAL PREPARATIONS 14,28 4 12,82 4 10,77 6 10,46 7 A01A STOMATOLOGICAL PREPARATIONS 14,28 4 12,82 4 10,77 6 10,46 7 A01AA Caries prophylactic agents 11,90 3 10,48 4 8,42 5 8,45 7 A01AA01 sodium fluoride 11,90 3 10,48 4 8,42 5 8,45 7 A01AA03 olaflur 0,00 - 0,00 - 0,00 - 0,00 - A01AB Antiinfectives for local oral treatment 2,36 8 2,31 7 2,31 7 2,02 7 A01AB03 chlorhexidine 2,02 6 2,10 7 2,09 7 1,78 7 A01AB11 various 0,33 21 0,21 0 0,22 0 0,24 0 A01AD Other agents for local oral treatment 0,02 0 0,03 0 0,04 0 - - A01AD02 benzydamine 0,02 0 0,03 0 0,04 0 - - A02 DRUGS FOR ACID RELATED DISORDERS 73,05 3 71,13 3 69,32 3 68,35 3 A02A ANTACIDS 2,23 1 2,22 1 2,20 1 2,30 1 A02AA Magnesium compounds 0,07 22 0,07 22 0,08 22 0,10 19 A02AA04 magnesium hydroxide 0,07 22 0,07 22 0,08 22 0,10 19 A02AD Combinations and complexes of aluminium, 2,17 0 2,15 0 2,12 0 2,20 0 calcium and magnesium compounds A02AD01 ordinary salt combinations 2,17 0 2,15 0 2,12 0 2,20 0 A02B DRUGS FOR PEPTIC ULCER AND 70,82 3 68,91 3 67,12 3 66,05 4 GASTRO-OESOPHAGEAL REFLUX DISEASE (GORD) A02BA H2-receptor antagonists 0,17 7 0,74 4 1,10 4 1,11 5 A02BA02 ranitidine 0,00 1 0,63 3 0,99 3 0,99 4 A02BA03 famotidine 0,16 7 0,11 8 0,11 10 0,12 9 A02BB Prostaglandins 0,04 62 -
770.Full-Text.Pdf
Published OnlineFirst January 14, 2019; DOI: 10.1158/1055-9965.EPI-18-0936 Research Article Cancer Epidemiology, Biomarkers Serum Metabolic Profiling Identified a Distinct & Prevention Metabolic Signature in Bladder Cancer Smokers: A Key Metabolic Enzyme Associated with Patient Survival Chandra Sekhar Amara1, Chandrashekar R. Ambati2, Venkatrao Vantaku1, Danthasinghe Waduge Badrajee Piyarathna1, Sri Ramya Donepudi2, Shiva Shankar Ravi1, James M. Arnold3, Vasanta Putluri2, Gurkamal Chatta4, Khurshid A. Guru5, Hoda Badr6, Martha K. Terris7, Roni J. Bollag7, Arun Sreekumar1,3, Andrea B. Apolo8, and Nagireddy Putluri1 Abstract Background: The current system to predict the outcome of nylalanine, proline, serine, valine, isoleucine, glycine, and smokers with bladder cancer is insufficient due to complex asparagine) and taurine were observed in bladder cancer genomic and transcriptomic heterogeneities. This study aims smokers. Integration of differential metabolomic gene signa- to identify serum metabolite-associated genes related to sur- ture and transcriptomics data from TCGA cohort revealed an vival in this population. intersection of 17 genes that showed significant correlation Methods: We performed LC/MS-based targeted metabo- with patient survival in bladder cancer smokers. Importantly, lomic analysis for >300 metabolites in serum obtained catechol-O-methyltransferase, iodotyrosine deiodinase, and from two independent cohorts of bladder cancer never tubulin tyrosine ligase showed a significant association with smokers, smokers, healthy smokers, and healthy never patient survival in publicly available bladder cancer smoker smokers. A subset of differential metabolites was validated datasets and did not have any clinical association in never using Biocrates absoluteIDQ p180 Kit. Genes associated smokers. with differential metabolites were integrated with a publicly Conclusions: Serum metabolic profiling of bladder cancer available cohort of The Cancer Genome Atlas (TCGA) to smokers revealed dysregulated amino acid metabolism. -
Differential Mitochondrial Proteomic Analysis of A549 Cells Infected With
Yang et al. Virol J (2021) 18:39 https://doi.org/10.1186/s12985-021-01512-4 RESEARCH Open Access Diferential mitochondrial proteomic analysis of A549 cells infected with avian infuenza virus subtypes H5 and H9 Yuting Yang1, Yun Zhang1, Changcheng Yang1, Fang Fang1, Ying Wang1, Haiyan Chang1*, Ze Chen1,2* and Ping Chen1* Abstract Background: Both the highly pathogenic avian infuenza (HPAI) H5N1 and low pathogenic avian infuenza (LPAI) H9N2 viruses have been reported to cross species barriers to infect humans. H5N1 viruses can cause severe damage and are associated with a high mortality rate, but H9N2 viruses do not cause such outcomes. Our purpose was to use proteomics technology to study the diferential expression of mitochondrial-related proteins related to H5N1 and H9N2 virus infections. Methods: According to the determined viral infection titer, A549 cells were infected with 1 multiplicity of infec- tion virus, and the mitochondria were extracted after 24 h of incubation. The protein from lysed mitochondria was analyzed by the BCA method to determine the protein concentration, as well as SDS-PAGE (preliminary analysis), two-dimensional gel electrophoresis, and mass spectrometry. Diferential protein spots were selected, and Western blotting was performed to verify the proteomics results. The identifed proteins were subjected to GO analysis for subcellular localization, KEGG analysis for functional classifcation and signaling pathways assessment, and STRING analysis for functional protein association network construction. Results: In the 2-D gel electrophoresis analysis, 227 protein spots were detected in the H5N1-infected group, and 169 protein spots were detected in the H9N2-infected group. Protein spots were further subjected to mass spectrom- etry identifcation and removal of redundancy, and 32 diferentially expressed proteins were identifed.