Effect of Redox-Cycling Agents on Nitric Oxide Synthase Activity In
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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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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. -
FKBP2 Antibody Cat
FKBP2 Antibody Cat. No.: 23-414 FKBP2 Antibody Western blot analysis of extracts of various cell lines, using FKBP2 antibody (23-414) at 1:1000 dilution. Secondary antibody: HRP Goat Anti-Rabbit IgG (H+L) at 1:10000 dilution. Lysates/proteins: 25ug per lane. Blocking buffer: 3% nonfat dry milk in TBST. Detection: ECL Basic Kit. Exposure time: 90s. Specifications HOST SPECIES: Rabbit SPECIES REACTIVITY: Human, Mouse, Rat Recombinant fusion protein containing a sequence corresponding to amino acids 22-142 IMMUNOGEN: of human FKBP2 (NP_004461.2). TESTED APPLICATIONS: IF, IHC, WB October 2, 2021 1 https://www.prosci-inc.com/fkbp2-antibody-23-414.html WB: ,1:500 - 1:2000 APPLICATIONS: IHC: ,1:100 - 1:200 IF: ,1:50 - 1:200 POSITIVE CONTROL: 1) MCF7 2) SKOV3 3) Jurkat 4) HeLa 5) Mouse thymus 6) Mouse liver PREDICTED MOLECULAR Observed: 14kDa WEIGHT: Properties PURIFICATION: Affinity purification CLONALITY: Polyclonal ISOTYPE: IgG CONJUGATE: Unconjugated PHYSICAL STATE: Liquid BUFFER: PBS with 0.02% sodium azide, 50% glycerol, pH7.3. STORAGE CONDITIONS: Store at -20˚C. Avoid freeze / thaw cycles. Additional Info OFFICIAL SYMBOL: FKBP2 FKBP-13, FKBP13, PPIase, peptidyl-prolyl cis-trans isomerase FKBP2, 13 kDa FK506-binding protein, 13 kDa FKBP, FK506 binding protein 2, 13kDa, FK506-binding protein 2, PPIase ALTERNATE NAMES: FKBP2, epididymis secretory sperm binding protein, immunophilin FKBP13, proline isomerase, rapamycin-binding protein, rotamase GENE ID: 2286 USER NOTE: Optimal dilutions for each application to be determined by the researcher. Background and References October 2, 2021 2 https://www.prosci-inc.com/fkbp2-antibody-23-414.html The protein encoded by this gene is a member of the immunophilin protein family, which play a role in immunoregulation and basic cellular processes involving protein folding and trafficking. -
Molecular Mechanisms Underlying Noncoding Risk Variations in Psychiatric Genetic Studies
OPEN Molecular Psychiatry (2017) 22, 497–511 www.nature.com/mp REVIEW Molecular mechanisms underlying noncoding risk variations in psychiatric genetic studies X Xiao1,2, H Chang1,2 and M Li1 Recent large-scale genetic approaches such as genome-wide association studies have allowed the identification of common genetic variations that contribute to risk architectures of psychiatric disorders. However, most of these susceptibility variants are located in noncoding genomic regions that usually span multiple genes. As a result, pinpointing the precise variant(s) and biological mechanisms accounting for the risk remains challenging. By reviewing recent progresses in genetics, functional genomics and neurobiology of psychiatric disorders, as well as gene expression analyses of brain tissues, here we propose a roadmap to characterize the roles of noncoding risk loci in the pathogenesis of psychiatric illnesses (that is, identifying the underlying molecular mechanisms explaining the genetic risk conferred by those genomic loci, and recognizing putative functional causative variants). This roadmap involves integration of transcriptomic data, epidemiological and bioinformatic methods, as well as in vitro and in vivo experimental approaches. These tools will promote the translation of genetic discoveries to physiological mechanisms, and ultimately guide the development of preventive, therapeutic and prognostic measures for psychiatric disorders. Molecular Psychiatry (2017) 22, 497–511; doi:10.1038/mp.2016.241; published online 3 January 2017 RECENT GENETIC ANALYSES OF NEUROPSYCHIATRIC neurodevelopment and brain function. For example, GRM3, DISORDERS GRIN2A, SRR and GRIA1 were known to involve in the neuro- Schizophrenia, bipolar disorder, major depressive disorder and transmission mediated by glutamate signaling and synaptic autism are highly prevalent complex neuropsychiatric diseases plasticity. -
Metabolism of Purines and Pyrimidines in Health and Disease
39th Meeting of the Polish Biochemical Society Gdañsk 16–20 September 2003 SESSION 6 Metabolism of purines and pyrimidines in health and disease Organized by A. C. Sk³adanowski, A. Guranowski 182 Session 6. Metabolism of purines and pyrimidines in health and disease 2003 323 Lecture The role of DNA methylation in cytotoxicity mechanism of adenosine analogues in treatment of leukemia Krystyna Fabianowska-Majewska Zak³ad Chemii Medycznej IFiB, Uniwersytet Medyczny, ul. Mazowiecka 6/8, 92 215 £ódŸ Changes in DNA methylation have been recognized tory effects of cladribine and fludarabine on DNA as one of the most common molecular alterations in hu- methylation, after 48 hr growth of K562 cells with the man neoplastic diseases and hypermethylation of drugs, are non-random and affect mainly CpG rich is- gene-promoter regions is one of the most frequent lands or CCGG sequences but do not affect sepa- mechanisms of the loss of gene functions. For this rea- rately-located CpG sequences. The analysis showed son, DNA methylation may be a tool for detection of that cladribine (0.1 mM) reduced the methylated early cell transformations as well as predisposition to cytosines in CpG islands and CCGG sequences to a sim- metastasis process. Moreover, DNA methylation seems ilar degree. The inhibition of cytosine methylation by to be a promissing target for new preventive and thera- fludarabine (3 mM) was observed mainly in CCGG se- peutic strategies. quences, sensitive to HpaII, but the decline in the meth- Our studies on DNA methylation and cytotoxicity ylated cytosine, located in CpG island was 2-fold lower mechanism of antileukemic drugs, cladribine and than that with cladribine. -
Expressed Sequence Tag Analysis of the Response of Apple
Physiologia Plantarum 133: 298–317. 2008 Copyright ª Physiologia Plantarum 2008, ISSN 0031-9317 Expressed sequence tag analysis of the response of apple (Malus x domestica ‘Royal Gala’) to low temperature and water deficit Michael Wisniewskia,*, Carole Bassetta,*, John Norellia, Dumitru Macarisina, Timothy Artlipa, Ksenija Gasicb and Schuyler Korbanb aUnited States Department of Agriculture – Agricultural Research Service (USDA-ARS), Appalachian Fruit Research Station, 2217 Wiltshire Road, Kearneysville, WV 25430, USA bDepartment of Natural Resources and Environmental Sciences, University of Illinois, 310 ERML, 1201 W. Gregory Drive, Urbana, IL 61801, USA Correspondence Leaf, bark, xylem and root tissues were used to make nine cDNA libraries from *Corresponding author, non-stressed (control) ‘Royal Gala’ apple trees, and from ‘Royal Gala’ trees e-mail: [email protected]; exposed to either low temperature (5°C for 24 h) or water deficit (45% of [email protected] saturated pot mass for 2 weeks). Over 22 600 clones from the nine libraries # Received 26 September 2007; revised 3 were subjected to 5 single-pass sequencing, clustered and annotated using January 2008 BLASTX. The number of clusters in the libraries ranged from 170 to 1430. Regarding annotation of the sequences, BLASTX analysis indicated that within doi: 10.1111/j.1399-3054.2008.01063.x the libraries 65–72% of the clones had a high similarity to known function genes, 6–15% had no functional assignment and 15–26% were completely novel. The expressed sequence tags were combined into three classes (control, low-temperature and water deficit) and the annotated genes in each class were placed into 1 of 10 different functional categories. -
S100A10 in Cancer Progression and Chemotherapy Resistance: a Novel Therapeutic Target Against Ovarian Cancer
Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 15 October 2018 doi:10.20944/preprints201810.0318.v1 Peer-reviewed version available at Int. J. Mol. Sci. 2018, 19, 4122; doi:10.3390/ijms19124122 Review S100A10 in Cancer Progression and Chemotherapy Resistance: A Novel Therapeutic Target against Ovarian Cancer Tannith M Noye1, Noor A Lokman1 Martin K Oehler1, 2 and Carmela Ricciardelli1,* 1 Discipline of Obstetrics and Gynaecology, Adelaide Medical School, Robinson Research Institute, The University of Adelaide, Adelaide, South Australia, Australia emails: [email protected] (T.M.N.); [email protected] (N.A.L.); [email protected] (M.K.O); [email protected](C.R) 2 Department of Gynaecological Oncology, Royal Adelaide Hospital, Adelaide, South Australia, Australia * Correspondence: [email protected]; Tel.: +61-0883138255 Abstract: S100A10, which is also known as p11 is located in the plasma membrane and forms a heterotetramer with annexin A2. The heterotetramer, comprising of 2 subunits of annexin A2 and S100A10, activates the plasminogen activation pathway which is involved in cellular repair of normal tissues. Increased expression of annexin A2 and S100A10 in cancer cells leads to increased levels of plasmin which promote degradation of the extracellular matrix, increased angiogenesis and invasion of the surrounding organs. Although many studies have investigated the functional role of annexin A2 in cancer cells including ovarian cancer, S100A10 has been less studied. We recently demonstrated that high stromal annexin A2 and high cytoplasmic S100A10 expression is associated with a 3.4 fold increased risk of progression and 7.9 fold risk of death in ovarian cancer patients. -
The Role of Genetic Variation in Predisposition to Alcohol-Related Chronic Pancreatitis
The Role of Genetic Variation in Predisposition to Alcohol-related Chronic Pancreatitis Thesis submitted in accordance with the requirements of the University of Liverpool for the degree of Doctor in Philosophy by Marianne Lucy Johnstone April 2015 The Role of Genetic Variation in Predisposition to Alcohol-related Chronic Pancreatitis 2015 Abstract Background Chronic pancreatitis (CP) is a disease of fibrosis of the pancreas for which alcohol is the main causative agent. However, only a small proportion of alcoholics develop chronic pancreatitis. Genetic polymorphism may affect pancreatitis risk. Aim To determine the factors required to classify a chronic pancreatic population and identify genetic variations that may explain why only some alcoholics develop chronic pancreatitis. Methods The most appropriate method of diagnosing CP was assessed using a systematic review. Genetics of different populations of alcohol-related chronic pancreatitics (ACP) were explored using four different techniques: genome-wide association study (GWAS); custom arrays; PCR of variable nucleotide tandem repeats (VNTR) and next generation sequencing (NGS) of selected genes. Results EUS and sMR were identified as giving the overall best sensitivity and specificity for diagnosing CP. GWAS revealed two associations with CP (identified and replicated) at PRSS1-PRSS2_rs10273639 (OR 0.73, 95% CI 0.68-0.79) and X-linked CLDN2_rs12688220 (OR 1.39, 1.28-1.49) and the association was more pronounced in the ACP group (OR 0.56, 0.48-0.64)and OR 2.11, 1.84-2.42). The previously identified VNTR in CEL was shown to have a lower frequency of the normal repeat in ACP than alcoholic liver disease (ALD; OR 0.61, 0.41-0.93). -
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) -
Supplemental Information IRF4 Transcription Factor-Dependent Cd11b+ Dendritic Cells in Human and Mouse Control Mucosal IL-17 C
Immunity, Volume 38 Supplemental Information IRF4 Transcription Factor-Dependent CD11b+ Dendritic Cells in Human and Mouse Control Mucosal IL-17 Cytokine Responses Andreas Schlitzer, Naomi McGovern, Pearline Teo, Teresa Zelante, Koji Atarashi, Donovan Low, Adrian W.S. Ho, Peter See, Amanda Shin, Pavandip Singh Wasan, Guillaume Hoeffel, Benoit Malleret, Alexander Heiseke, Samantha Chew, Laura Jardine, Harriet A. Purvis, Catharien M.U. Hilkens, John Tam, Michael Poidinger, E. Richard Stanley, Anne B. K rug, Laurent Renia, Baalasubramanian Sivasankar, Lai Guan Ng, Matthew Collin, Paola Ricciardi-Castagnoli, Kenya Honda, Muzlifah Haniffa, and Florent Ginhoux Supplemental Inventory 1. Supplemental Figures and Tables Figure S1, Related to Figure 1 Figure S2, Related to Figure 2 and 3 Figure S3, Related to Figure 4 Figure S4, Related to Figure 5 Figure S5, Related to Figure 5 Figure S6, Related to Figure 7 Table S1, Related to Figure 3 Table S2, Related to Figure 6 Table S3, Related to Figure 6 2. Supplemental Experimental Procedures 3. Supplemental References Supplementary figure 1 Sorting strategy for mouse lung and small intestinal DC A Sorting strategy, Lung Singlets Dapi-CD45+ 250K 250K 250K 105 200K 200K 200K 104 A I - 150K 150K 150K C P C C 3 10 S A S S 100K 100K S 100K D S S 102 50K 50K 50K 0 0 0 0 0 50K 100K 150K 200K 250K 0 50K 100K 150K 200K 250K 0 103 104 105 0 103 104 105 FSC FSC-W CD45 GR1 Auto Fluor.- MHCII+ GR1- SSClow CD11c+ CD11b+ 250K 105 105 105 200K 4 104 10 104 150K I 3 I 3 4 3 0 10 3 C 2 H 10 10 100K 1 S D C D S C M 2 C 10 50K 0 0 0 0 0 102 103 104 105 0 103 104 105 0 103 104 105 0 103 104 105 Auto fluor. -
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. -
Enzyme DHRS7
Toward the identification of a function of the “orphan” enzyme DHRS7 Inauguraldissertation zur Erlangung der Würde eines Doktors der Philosophie vorgelegt der Philosophisch-Naturwissenschaftlichen Fakultät der Universität Basel von Selene Araya, aus Lugano, Tessin Basel, 2018 Originaldokument gespeichert auf dem Dokumentenserver der Universität Basel edoc.unibas.ch Genehmigt von der Philosophisch-Naturwissenschaftlichen Fakultät auf Antrag von Prof. Dr. Alex Odermatt (Fakultätsverantwortlicher) und Prof. Dr. Michael Arand (Korreferent) Basel, den 26.6.2018 ________________________ Dekan Prof. Dr. Martin Spiess I. List of Abbreviations 3α/βAdiol 3α/β-Androstanediol (5α-Androstane-3α/β,17β-diol) 3α/βHSD 3α/β-hydroxysteroid dehydrogenase 17β-HSD 17β-Hydroxysteroid Dehydrogenase 17αOHProg 17α-Hydroxyprogesterone 20α/βOHProg 20α/β-Hydroxyprogesterone 17α,20α/βdiOHProg 20α/βdihydroxyprogesterone ADT Androgen deprivation therapy ANOVA Analysis of variance AR Androgen Receptor AKR Aldo-Keto Reductase ATCC American Type Culture Collection CAM Cell Adhesion Molecule CYP Cytochrome P450 CBR1 Carbonyl reductase 1 CRPC Castration resistant prostate cancer Ct-value Cycle threshold-value DHRS7 (B/C) Dehydrogenase/Reductase Short Chain Dehydrogenase Family Member 7 (B/C) DHEA Dehydroepiandrosterone DHP Dehydroprogesterone DHT 5α-Dihydrotestosterone DMEM Dulbecco's Modified Eagle's Medium DMSO Dimethyl Sulfoxide DTT Dithiothreitol E1 Estrone E2 Estradiol ECM Extracellular Membrane EDTA Ethylenediaminetetraacetic acid EMT Epithelial-mesenchymal transition ER Endoplasmic Reticulum ERα/β Estrogen Receptor α/β FBS Fetal Bovine Serum 3 FDR False discovery rate FGF Fibroblast growth factor HEPES 4-(2-Hydroxyethyl)-1-Piperazineethanesulfonic Acid HMDB Human Metabolome Database HPLC High Performance Liquid Chromatography HSD Hydroxysteroid Dehydrogenase IC50 Half-Maximal Inhibitory Concentration LNCaP Lymph node carcinoma of the prostate mRNA Messenger Ribonucleic Acid n.d. -
A Human Population-Based Organotypic in Vitro Model for Cardiotoxicity Screening1
ALTEX preprint published July 8, 2018 doi:10.14573/altex.1805301 Research Article A human population-based organotypic in vitro model for cardiotoxicity screening1 Fabian A. Grimm1, Alexander Blanchette1, John S. House2, Kyle Ferguson1, Nan-Hung Hsieh1, Chimeddulam Dalaijamts1, Alec A. Wright1, Blake Anson5, Fred A. Wright3,4, Weihsueh A. Chiu1, Ivan Rusyn1 1Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, USA; 2Bioinformatics Research Center, 3Department of Biological Sciences, and 4Department of Statistics, North Carolina State University, Raleigh, NC, USA; 5Cellular Dynamics International, Madison, WI, USA Abstract Assessing inter-individual variability in responses to xenobiotics remains a substantial challenge, both in drug development with respect to pharmaceuticals and in public health with respect to environmental chemicals. Although approaches exist to characterize pharmacokinetic variability, there are no methods to routinely address pharmacodynamic variability. In this study, we aimed to demonstrate the feasibility of characterizing inter-individual variability in a human in vitro model. Specifically, we hypothesized that genetic variability across a population of iPSC- derived cardiomyocytes translates into reproducible variability in both baseline phenotypes and drug responses. We measured baseline and drug-related effects in iPSC-derived cardiomyocytes from 27 healthy donors on kinetic Ca2+ flux and high-content live cell imaging. Cells were treated in concentration-response with cardiotoxic drugs: isoproterenol (β- adrenergic receptor agonist/positive inotrope), propranolol (β-adrenergic receptor antagonist/negative inotrope), and cisapride (hERG channel inhibitor/QT prolongation). Cells from four of the 27 donors were further evaluated in terms of baseline and treatment-related gene expression. Reproducibility of phenotypic responses was evaluated across batches and time.