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Gentaur Products List
Chapter 2 : Gentaur Products List • Rabbit Anti LAMR1 Polyclonal Antibody Cy5 Conjugated Conjugated • Rabbit Anti Podoplanin gp36 Polyclonal Antibody Cy5 • Rabbit Anti LAMR1 CT Polyclonal Antibody Cy5 • Rabbit Anti phospho NFKB p65 Ser536 Polyclonal Conjugated Conjugated Antibody Cy5 Conjugated • Rabbit Anti CHRNA7 Polyclonal Antibody Cy5 Conjugated • Rat Anti IAA Monoclonal Antibody Cy5 Conjugated • Rabbit Anti EV71 VP1 CT Polyclonal Antibody Cy5 • Rabbit Anti Connexin 40 Polyclonal Antibody Cy5 • Rabbit Anti IAA Indole 3 Acetic Acid Polyclonal Antibody Conjugated Conjugated Cy5 Conjugated • Rabbit Anti LHR CGR Polyclonal Antibody Cy5 Conjugated • Rabbit Anti Integrin beta 7 Polyclonal Antibody Cy5 • Rabbit Anti Natrexone Polyclonal Antibody Cy5 Conjugated • Rabbit Anti MMP 20 Polyclonal Antibody Cy5 Conjugated Conjugated • Rabbit Anti Melamine Polyclonal Antibody Cy5 Conjugated • Rabbit Anti BCHE NT Polyclonal Antibody Cy5 Conjugated • Rabbit Anti NAP1 NAP1L1 Polyclonal Antibody Cy5 • Rabbit Anti Acetyl p53 K382 Polyclonal Antibody Cy5 • Rabbit Anti BCHE CT Polyclonal Antibody Cy5 Conjugated Conjugated Conjugated • Rabbit Anti HPV16 E6 Polyclonal Antibody Cy5 Conjugated • Rabbit Anti CCP Polyclonal Antibody Cy5 Conjugated • Rabbit Anti JAK2 Polyclonal Antibody Cy5 Conjugated • Rabbit Anti HPV18 E6 Polyclonal Antibody Cy5 Conjugated • Rabbit Anti HDC Polyclonal Antibody Cy5 Conjugated • Rabbit Anti Microsporidia protien Polyclonal Antibody Cy5 • Rabbit Anti HPV16 E7 Polyclonal Antibody Cy5 Conjugated • Rabbit Anti Neurocan Polyclonal -
Mutant IDH, (R)-2-Hydroxyglutarate, and Cancer
Downloaded from genesdev.cshlp.org on October 1, 2021 - Published by Cold Spring Harbor Laboratory Press REVIEW What a difference a hydroxyl makes: mutant IDH, (R)-2-hydroxyglutarate, and cancer Julie-Aurore Losman1 and William G. Kaelin Jr.1,2,3 1Department of Medical Oncology, Dana-Farber Cancer Institute, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02215, USA; 2Howard Hughes Medical Institute, Chevy Chase, Maryland 20815, USA Mutations in metabolic enzymes, including isocitrate whether altered cellular metabolism is a cause of cancer dehydrogenase 1 (IDH1) and IDH2, in cancer strongly or merely an adaptive response of cancer cells in the face implicate altered metabolism in tumorigenesis. IDH1 of accelerated cell proliferation is still a topic of some and IDH2 catalyze the interconversion of isocitrate and debate. 2-oxoglutarate (2OG). 2OG is a TCA cycle intermediate The recent identification of cancer-associated muta- and an essential cofactor for many enzymes, including tions in three metabolic enzymes suggests that altered JmjC domain-containing histone demethylases, TET cellular metabolism can indeed be a cause of some 5-methylcytosine hydroxylases, and EglN prolyl-4-hydrox- cancers (Pollard et al. 2003; King et al. 2006; Raimundo ylases. Cancer-associated IDH mutations alter the enzymes et al. 2011). Two of these enzymes, fumarate hydratase such that they reduce 2OG to the structurally similar (FH) and succinate dehydrogenase (SDH), are bone fide metabolite (R)-2-hydroxyglutarate [(R)-2HG]. Here we tumor suppressors, and loss-of-function mutations in FH review what is known about the molecular mechanisms and SDH have been identified in various cancers, in- of transformation by mutant IDH and discuss their im- cluding renal cell carcinomas and paragangliomas. -
Gene PMID WBS Locus ABR 26603386 AASDH 26603386
Supplementary material J Med Genet Gene PMID WBS Locus ABR 26603386 AASDH 26603386 ABCA1 21304579 ABCA13 26603386 ABCA3 25501393 ABCA7 25501393 ABCC1 25501393 ABCC3 25501393 ABCG1 25501393 ABHD10 21304579 ABHD11 25501393 yes ABHD2 25501393 ABHD5 21304579 ABLIM1 21304579;26603386 ACOT12 25501393 ACSF2,CHAD 26603386 ACSL4 21304579 ACSM3 26603386 ACTA2 25501393 ACTN1 26603386 ACTN3 26603386;25501393;25501393 ACTN4 21304579 ACTR1B 21304579 ACVR2A 21304579 ACY3 19897463 ACYP1 21304579 ADA 25501393 ADAM12 21304579 ADAM19 25501393 ADAM32 26603386 ADAMTS1 25501393 ADAMTS10 25501393 ADAMTS12 26603386 ADAMTS17 26603386 ADAMTS6 21304579 ADAMTS7 25501393 ADAMTSL1 21304579 ADAMTSL4 25501393 ADAMTSL5 25501393 ADCY3 25501393 ADK 21304579 ADRBK2 25501393 AEBP1 25501393 AES 25501393 AFAP1,LOC84740 26603386 AFAP1L2 26603386 AFG3L1 21304579 AGAP1 26603386 AGAP9 21304579 Codina-Sola M, et al. J Med Genet 2019; 56:801–808. doi: 10.1136/jmedgenet-2019-106080 Supplementary material J Med Genet AGBL5 21304579 AGPAT3 19897463;25501393 AGRN 25501393 AGXT2L2 25501393 AHCY 25501393 AHDC1 26603386 AHNAK 26603386 AHRR 26603386 AIDA 25501393 AIFM2 21304579 AIG1 21304579 AIP 21304579 AK5 21304579 AKAP1 25501393 AKAP6 21304579 AKNA 21304579 AKR1E2 26603386 AKR7A2 21304579 AKR7A3 26603386 AKR7L 26603386 AKT3 21304579 ALDH18A1 25501393;25501393 ALDH1A3 21304579 ALDH1B1 21304579 ALDH6A1 21304579 ALDOC 21304579 ALG10B 26603386 ALG13 21304579 ALKBH7 25501393 ALPK2 21304579 AMPH 21304579 ANG 21304579 ANGPTL2,RALGPS1 26603386 ANGPTL6 26603386 ANK2 21304579 ANKMY1 26603386 ANKMY2 -
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). -
The Role of EZH2 in the Induction and Maintenance of Acute Myeloid Leukaemia
The Role of EZH2 in the Induction and Maintenance of Acute Myeloid Leukaemia Faisal Basheer Downing College University of Cambridge This dissertation is submitted for the degree of Doctor of Philosophy September 2017 Declaration The work presented in this dissertation was carried out under the supervision of Professor Brian Huntly from November 2013 to November 2016 in the Department of Haematology, University of Cambridge. This dissertation is the result of my own work and includes nothing which is the outcome of work done in collaboration except as declared in the Preface and specified in the text. It is not substantially the same as any that I have submitted, or, is being concurrently submitted for a degree or diploma or other qualification at the University of Cambridge or any other University or similar institution except as declared in the Preface and specified in the text. It does not exceed the prescribed word limit set by the Clinical Medicine and Clinical Veterinary Medicine Degree Committee. Faisal Basheer September 2017 i Acknowledgements First and foremost, I would like to thank my supervisor, Professor Brian Huntly, for providing me with the opportunity to work towards this thesis - for his help, encouragement and support over the last four years of my PhD. His dedicated high-level supervision, meticulous attention to detail and excellent direction throughout this time has undoubtedly helped me to maximise my potential in the lab throughout a highly interesting and rewarding project. I would also like to thank all of my colleagues and friends in the Huntly laboratory over the past four years - working together with all of you as a team has been an unforgettable and rewarding experience. -
High Density Genome Wide Genotyping-By-Sequencing and Association
www.nature.com/scientificreports OPEN High density genome wide genotyping-by-sequencing and association identifies common and Received: 24 March 2016 Accepted: 14 July 2016 low frequency SNPs, and novel Published: 10 August 2016 candidate genes influencing cow milk traits Eveline M. Ibeagha-Awemu1, Sunday O. Peters2, Kingsley A. Akwanji3, Ikhide G. Imumorin4 & Xin Zhao3 High-throughput sequencing technologies have increased the ability to detect sequence variations for complex trait improvement. A high throughput genome wide genotyping-by-sequencing (GBS) method was used to generate 515,787 single nucleotide polymorphisms (SNPs), from which 76,355 SNPs with call rates >85% and minor allele frequency ≥1.5% were used in genome wide association study (GWAS) of 44 milk traits in 1,246 Canadian Holstein cows. GWAS was accomplished with a mixed linear model procedure implementing the additive and dominant models. A strong signal within the centromeric region of bovine chromosome 14 was associated with test day fat percentage. Several SNPs were associated with eicosapentaenoic acid, docosapentaenoic acid, arachidonic acid, CLA:9c11t and gamma linolenic acid. Most of the significant SNPs for 44 traits studied are novel and located in intergenic regions or introns of genes. Novel potential candidate genes for milk traits or mammary gland functions include ERCC6, TONSL, NPAS2, ACER3, ITGB4, GGT6, ACOX3, MECR, ADAM12, ACHE, LRRC14, FUK, NPRL3, EVL, SLCO3A1, PSMA4, FTO, ADCK5, PP1R16A and TEP1. Our study further demonstrates the utility of the GBS approach for identifying population-specific SNPs for use in improvement of complex dairy traits. Milk is an important source of nutrients in human nutrition all over the world. -
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 -
The Metabolic Serine Hydrolases and Their Functions in Mammalian Physiology and Disease Jonathan Z
REVIEW pubs.acs.org/CR The Metabolic Serine Hydrolases and Their Functions in Mammalian Physiology and Disease Jonathan Z. Long* and Benjamin F. Cravatt* The Skaggs Institute for Chemical Biology and Department of Chemical Physiology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States CONTENTS 2.4. Other Phospholipases 6034 1. Introduction 6023 2.4.1. LIPG (Endothelial Lipase) 6034 2. Small-Molecule Hydrolases 6023 2.4.2. PLA1A (Phosphatidylserine-Specific 2.1. Intracellular Neutral Lipases 6023 PLA1) 6035 2.1.1. LIPE (Hormone-Sensitive Lipase) 6024 2.4.3. LIPH and LIPI (Phosphatidic Acid-Specific 2.1.2. PNPLA2 (Adipose Triglyceride Lipase) 6024 PLA1R and β) 6035 2.1.3. MGLL (Monoacylglycerol Lipase) 6025 2.4.4. PLB1 (Phospholipase B) 6035 2.1.4. DAGLA and DAGLB (Diacylglycerol Lipase 2.4.5. DDHD1 and DDHD2 (DDHD Domain R and β) 6026 Containing 1 and 2) 6035 2.1.5. CES3 (Carboxylesterase 3) 6026 2.4.6. ABHD4 (Alpha/Beta Hydrolase Domain 2.1.6. AADACL1 (Arylacetamide Deacetylase-like 1) 6026 Containing 4) 6036 2.1.7. ABHD6 (Alpha/Beta Hydrolase Domain 2.5. Small-Molecule Amidases 6036 Containing 6) 6027 2.5.1. FAAH and FAAH2 (Fatty Acid Amide 2.1.8. ABHD12 (Alpha/Beta Hydrolase Domain Hydrolase and FAAH2) 6036 Containing 12) 6027 2.5.2. AFMID (Arylformamidase) 6037 2.2. Extracellular Neutral Lipases 6027 2.6. Acyl-CoA Hydrolases 6037 2.2.1. PNLIP (Pancreatic Lipase) 6028 2.6.1. FASN (Fatty Acid Synthase) 6037 2.2.2. PNLIPRP1 and PNLIPR2 (Pancreatic 2.6.2. -
Genome Sequencing Unveils a Regulatory Landscape of Platelet Reactivity
ARTICLE https://doi.org/10.1038/s41467-021-23470-9 OPEN Genome sequencing unveils a regulatory landscape of platelet reactivity Ali R. Keramati 1,2,124, Ming-Huei Chen3,4,124, Benjamin A. T. Rodriguez3,4,5,124, Lisa R. Yanek 2,6, Arunoday Bhan7, Brady J. Gaynor 8,9, Kathleen Ryan8,9, Jennifer A. Brody 10, Xue Zhong11, Qiang Wei12, NHLBI Trans-Omics for Precision (TOPMed) Consortium*, Kai Kammers13, Kanika Kanchan14, Kruthika Iyer14, Madeline H. Kowalski15, Achilleas N. Pitsillides4,16, L. Adrienne Cupples 4,16, Bingshan Li 12, Thorsten M. Schlaeger7, Alan R. Shuldiner9, Jeffrey R. O’Connell8,9, Ingo Ruczinski17, Braxton D. Mitchell 8,9, ✉ Nauder Faraday2,18, Margaret A. Taub17, Lewis C. Becker1,2, Joshua P. Lewis 8,9,125 , 2,14,125✉ 3,4,125✉ 1234567890():,; Rasika A. Mathias & Andrew D. Johnson Platelet aggregation at the site of atherosclerotic vascular injury is the underlying patho- physiology of myocardial infarction and stroke. To build upon prior GWAS, here we report on 16 loci identified through a whole genome sequencing (WGS) approach in 3,855 NHLBI Trans-Omics for Precision Medicine (TOPMed) participants deeply phenotyped for platelet aggregation. We identify the RGS18 locus, which encodes a myeloerythroid lineage-specific regulator of G-protein signaling that co-localizes with expression quantitative trait loci (eQTL) signatures for RGS18 expression in platelets. Gene-based approaches implicate the SVEP1 gene, a known contributor of coronary artery disease risk. Sentinel variants at RGS18 and PEAR1 are associated with thrombosis risk and increased gastrointestinal bleeding risk, respectively. Our WGS findings add to previously identified GWAS loci, provide insights regarding the mechanism(s) by which genetics may influence cardiovascular disease risk, and underscore the importance of rare variant and regulatory approaches to identifying loci contributing to complex phenotypes. -
Experimental Eye Research 129 (2014) 93E106
Experimental Eye Research 129 (2014) 93e106 Contents lists available at ScienceDirect Experimental Eye Research journal homepage: www.elsevier.com/locate/yexer Transcriptomic analysis across nasal, temporal, and macular regions of human neural retina and RPE/choroid by RNA-Seq S. Scott Whitmore a, b, Alex H. Wagner a, c, Adam P. DeLuca a, b, Arlene V. Drack a, b, Edwin M. Stone a, b, Budd A. Tucker a, b, Shemin Zeng a, b, Terry A. Braun a, b, c, * Robert F. Mullins a, b, Todd E. Scheetz a, b, c, a Stephen A. Wynn Institute for Vision Research, The University of Iowa, Iowa City, IA, USA b Department of Ophthalmology and Visual Sciences, Carver College of Medicine, The University of Iowa, Iowa City, IA, USA c Department of Biomedical Engineering, College of Engineering, The University of Iowa, Iowa City, IA, USA article info abstract Article history: Proper spatial differentiation of retinal cell types is necessary for normal human vision. Many retinal Received 14 September 2014 diseases, such as Best disease and male germ cell associated kinase (MAK)-associated retinitis pigmen- Received in revised form tosa, preferentially affect distinct topographic regions of the retina. While much is known about the 31 October 2014 distribution of cell types in the retina, the distribution of molecular components across the posterior pole Accepted in revised form 4 November 2014 of the eye has not been well-studied. To investigate regional difference in molecular composition of Available online 5 November 2014 ocular tissues, we assessed differential gene expression across the temporal, macular, and nasal retina and retinal pigment epithelium (RPE)/choroid of human eyes using RNA-Seq. -
1 Endothelial Lipase Is Synthesized by Hepatic and Aorta Endothelial
Endothelial Lipase Is Synthesized by Hepatic and Aorta Endothelial Cells and Its Expression Is Altered in apoE Deficient Mice Kenneth C-W. Yu†, Christopher David¶, Sujata Kadambi¶, Andreas Stahl†¶, Ken-Ichi Hirata†§, Tatsuro Ishida†§, Thomas Quertermous†, Allen D Cooper†¶ and Sungshin Y. Choi¶* Palo Alto Medical Foundation-Research Institute¶, Palo Alto, CA, School of Medicine, Stanford University†, Palo Alto, CA. *Corresponding author: Sungshin Y. Choi, Ph.D. Research Institute, Palo Alto Medical Foundation 795 El Camino Real – Ames Bldg. Palo Alto, CA 94301 650-853-2866 email address: [email protected] §: Current Address: Division of Cardiovascular and Respiratory Medicine, Kobe University Graduate School of Medicine, Kobe, Japan Short title: Tissue specific expression of endothelial lipase Abbreviations: EL = endothelial lipase, EC = endothelial cells, HL = hepatic lipase, LPL = lipoprotein lipase, EKO = apoE knockout, WT = wild-type, CA = cholic acid, HL = high fat, NC = normal chow, RT-PCR = real-time PCR, vWF = von Willbrand Factor, EC = endothelial cells. 1 ABSTRACT Both LPL and HL are synthesized in parenchymal cells, secreted and bind to endothelial cells. To learn where endothelial lipase (EL) is synthesized in the adult animals the localization of EL in mouse and rat liver was studied by immunohistochemical analysis. Further, to test if EL could play a role in atherogenesis, expression of EL in the aorta and liver of apoE knockout mice was determined. EL, in both mouse and rat liver was colocalized with the vascular endothelial cells and not hepatocytes. In contrast, hepatic lipase (HL) was present in both hepatocytes and endothelial cells. By in situ hybridization EL mRNA was present only in endothelial cells in liver sections.