DOCSLIB.ORG

Genetic and Epigenetic Signatures in Cerebrovascular Disease

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Genetic and Epigenetic Signatures in Cerebrovascular Disease Genetic and Epigenetic Signatures in Cerebrovascular Disease The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Rudy, Robert. 2019. Genetic and Epigenetic Signatures in Cerebrovascular Disease. Doctoral dissertation, Harvard Medical School. Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:42069201 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use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`:%)<Y!"#+:3#!aA!8%EY!%)1!>*&++!WA! O$,00!%00,0+$1!@,+:!1%+%!%)%GE0,0!%)1!,)+$#B#$+%+,&)A!W:,0!0$*+,&)!,0!D$,)<!B#$B%#$1!'&#! 03D/,00,&)!'&#!B$$#!#$6,$@!%)1!:%0!D$$)!B#$0$)+$1!,)!%)!&#%G!B#$0$)+%+,&)!%+!+:$!(&)<#$00!&'! 2$3#&G&<,*%G!>3#<$&)0!,)!Q*+&D$#!&'!TVMRA! ! ;(/$'ML' ?!B$#'&#/$1!+:$!%)%GE0,0Y!*#$%+$1!+:$!',<3#$0Y!%)1!1#%'+$1!+:$!0$*+,&)A! ! 8#0A!O,GG,%/!.&#/G$EY!2,#%6!4%+$GY!b%,!F#$#,*:0Y!%)1!9A!"G,!"c,cN>3G+%)!%00,0+$1!@,+:!&D+%,),)<! 1%+%Y!8#A!8%@)!8$/$&Y!P,)*$!(%#$EY!>*&++!WA!O$,00Y!%)1!90A!>%#%53)$!8%<$)!%00,0+$1!@,+:! &D+%,),)<!1%+%!%)%GE0,0!%)1!,)+$#B#$+%+,&)A' ! ! %! 9.#)%#,'(#)'6%0&530./"0' ' ;(/$'DL'W:,0!@&#C!@%0!03BB&#+$1!DE!+:$!2%+,&)%G!?)0+,+3+$0!&'!Z$%G+:!<#%)+!bVR2>VJLMLT!\78]A! ;(/$'GL'W:,0!@&#C!@%0!03BB&#+$1!DE!+:$!8%),$G!KA!4&)+&)!F3)1A! ;(/$'ML'W:,0!@&#C!@%0!03BB&#+$1!DE!4%#+)$#0!Z$%G+:*%#$!4$#0&)%G,c$1!9$1,*,)$!%)1!+:$!8%)%! F&3)1%+,&)A! ' ' W:$!%3+:&#!#$B&#+0!)&!*&)'G,*+0!&'!,)+$#$0+!B$#+%,),)<!+:$!#$0$%#*:!B#$0$)+$1!,)!+:,0!+:$0,0A' ' ! &! !5300(/7' "("-!")+$#,&#!*$#$D#%G!%#+$#E! (W"-!(&/B3+$1!+&/&<#%B:E!%)<,&<#%B:E! 8?28?-!8$G%E$1!,0*:$/,*!)$3#&G&<,*%G!1$',*,+0!%)1!,)'%#*+,&)! 12>-!8,''$#$)*$!,)!)$3#&G&<,*%G!0*&#$! 8>"-!8,<,+%G!03D+#%*+,&)!%)<,&<#%B:E! F87-!F%G0$!1,0*&6$#E!#%+$! .(>-!.G%0<&@!*&/%!0*%G$! .O">-!.$)&/$N@,1$!%00&*,%+,&)!0+31E! ?4-!?)+#%B$#,+&)$%G! a7-!a,)1$<%%#1!#%+,&! 9"F-!9,)&#!%GG$G$!'#$d3$)*E! 9"4-!9$%)!%#+$#,%G!B#$003#$! 9("-!9,11G$!*$#$D#%G!%#+$#E! 9("Q-!9,11G$!*$#$D#%G!%#+$#E!&**G30,&)! /P>4-!9,),/3/!6%0&0B%0/!#%+,&! 4(7-!4&GE/$#%0$!*:%,)!#$%*+,&)! 77=>-!7$13*$1!#$B#$0$)+%+,&)!D,03G',+$!0$d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
Load more

Recommended publications
  • A Genome-Wide Study of Blood Pressure in African Americans Accounting for Gene-Smoking Interaction Jacquelyn Y
    A Genome-wide study of blood pressure in African Americans accounting for gene-smoking interaction Jacquelyn Y. Taylor, Yale University Karen Schwander, Washington University in St. Louis Sharon L. R. Kardia, University of Michigan Donna Arnett, University of Alabama, Birmingham Jingjing Liang, Case Western Reserve University Steven C. Hunt, University of Utah D.C. Rao, Washington University in St. Louis Yan Sun, Emory University Journal Title: Scientific Reports Volume: Volume 6 Publisher: Nature Publishing Group | 2016-01-11, Pages 18812-18812 Type of Work: Article | Final Publisher PDF Publisher DOI: 10.1038/srep18812 Permanent URL: https://pid.emory.edu/ark:/25593/rhb37 Final published version: http://dx.doi.org/10.1038/srep18812 Copyright information: © 2016, Macmillan Publishers Limited This is an Open Access work distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/). Accessed September 29, 2021 11:39 AM EDT www.nature.com/scientificreports OPEN A Genome-wide study of blood pressure in African Americans accounting for gene-smoking Received: 15 January 2015 Accepted: 09 November 2015 interaction Published: 11 January 2016 Jacquelyn Y. Taylor1, Karen Schwander2, Sharon L. R. Kardia3 & Donna Arnett4, Jingjing Liang5 Steven C. Hunt6, D.C. Rao2 & Yan V. Sun7,8 Cigarette smoking has been shown to be a health hazard. In addition to being considered a negative lifestyle behavior, studies have shown that cigarette smoking has been linked to genetic underpinnings of hypertension. Because African Americans have the highest incidence and prevalence of hypertension, we examined the joint effect of genetics and cigarette smoking on health among this understudied population.
    [Show full text]
  • Supplemental Figure 1. Vimentin
    Double mutant specific genes Transcript gene_assignment Gene Symbol RefSeq FDR Fold- FDR Fold- FDR Fold- ID (single vs. Change (double Change (double Change wt) (single vs. wt) (double vs. single) (double vs. wt) vs. wt) vs. single) 10485013 BC085239 // 1110051M20Rik // RIKEN cDNA 1110051M20 gene // 2 E1 // 228356 /// NM 1110051M20Ri BC085239 0.164013 -1.38517 0.0345128 -2.24228 0.154535 -1.61877 k 10358717 NM_197990 // 1700025G04Rik // RIKEN cDNA 1700025G04 gene // 1 G2 // 69399 /// BC 1700025G04Rik NM_197990 0.142593 -1.37878 0.0212926 -3.13385 0.093068 -2.27291 10358713 NM_197990 // 1700025G04Rik // RIKEN cDNA 1700025G04 gene // 1 G2 // 69399 1700025G04Rik NM_197990 0.0655213 -1.71563 0.0222468 -2.32498 0.166843 -1.35517 10481312 NM_027283 // 1700026L06Rik // RIKEN cDNA 1700026L06 gene // 2 A3 // 69987 /// EN 1700026L06Rik NM_027283 0.0503754 -1.46385 0.0140999 -2.19537 0.0825609 -1.49972 10351465 BC150846 // 1700084C01Rik // RIKEN cDNA 1700084C01 gene // 1 H3 // 78465 /// NM_ 1700084C01Rik BC150846 0.107391 -1.5916 0.0385418 -2.05801 0.295457 -1.29305 10569654 AK007416 // 1810010D01Rik // RIKEN cDNA 1810010D01 gene // 7 F5 // 381935 /// XR 1810010D01Rik AK007416 0.145576 1.69432 0.0476957 2.51662 0.288571 1.48533 10508883 NM_001083916 // 1810019J16Rik // RIKEN cDNA 1810019J16 gene // 4 D2.3 // 69073 / 1810019J16Rik NM_001083916 0.0533206 1.57139 0.0145433 2.56417 0.0836674 1.63179 10585282 ENSMUST00000050829 // 2010007H06Rik // RIKEN cDNA 2010007H06 gene // --- // 6984 2010007H06Rik ENSMUST00000050829 0.129914 -1.71998 0.0434862 -2.51672
    [Show full text]
  • Entrez Symbols Name Termid Termdesc 117553 Uba3,Ube1c
    Entrez Symbols Name TermID TermDesc 117553 Uba3,Ube1c ubiquitin-like modifier activating enzyme 3 GO:0016881 acid-amino acid ligase activity 299002 G2e3,RGD1310263 G2/M-phase specific E3 ubiquitin ligase GO:0016881 acid-amino acid ligase activity 303614 RGD1310067,Smurf2 SMAD specific E3 ubiquitin protein ligase 2 GO:0016881 acid-amino acid ligase activity 308669 Herc2 hect domain and RLD 2 GO:0016881 acid-amino acid ligase activity 309331 Uhrf2 ubiquitin-like with PHD and ring finger domains 2 GO:0016881 acid-amino acid ligase activity 316395 Hecw2 HECT, C2 and WW domain containing E3 ubiquitin protein ligase 2 GO:0016881 acid-amino acid ligase activity 361866 Hace1 HECT domain and ankyrin repeat containing, E3 ubiquitin protein ligase 1 GO:0016881 acid-amino acid ligase activity 117029 Ccr5,Ckr5,Cmkbr5 chemokine (C-C motif) receptor 5 GO:0003779 actin binding 117538 Waspip,Wip,Wipf1 WAS/WASL interacting protein family, member 1 GO:0003779 actin binding 117557 TM30nm,Tpm3,Tpm5 tropomyosin 3, gamma GO:0003779 actin binding 24779 MGC93554,Slc4a1 solute carrier family 4 (anion exchanger), member 1 GO:0003779 actin binding 24851 Alpha-tm,Tma2,Tmsa,Tpm1 tropomyosin 1, alpha GO:0003779 actin binding 25132 Myo5b,Myr6 myosin Vb GO:0003779 actin binding 25152 Map1a,Mtap1a microtubule-associated protein 1A GO:0003779 actin binding 25230 Add3 adducin 3 (gamma) GO:0003779 actin binding 25386 AQP-2,Aqp2,MGC156502,aquaporin-2aquaporin 2 (collecting duct) GO:0003779 actin binding 25484 MYR5,Myo1e,Myr3 myosin IE GO:0003779 actin binding 25576 14-3-3e1,MGC93547,Ywhah
    [Show full text]
  • Table S1 the Four Gene Sets Derived from Gene Expression Profiles of Escs and Differentiated Cells
    Table S1 The four gene sets derived from gene expression profiles of ESCs and differentiated cells Uniform High Uniform Low ES Up ES Down EntrezID GeneSymbol EntrezID GeneSymbol EntrezID GeneSymbol EntrezID GeneSymbol 269261 Rpl12 11354 Abpa 68239 Krt42 15132 Hbb-bh1 67891 Rpl4 11537 Cfd 26380 Esrrb 15126 Hba-x 55949 Eef1b2 11698 Ambn 73703 Dppa2 15111 Hand2 18148 Npm1 11730 Ang3 67374 Jam2 65255 Asb4 67427 Rps20 11731 Ang2 22702 Zfp42 17292 Mesp1 15481 Hspa8 11807 Apoa2 58865 Tdh 19737 Rgs5 100041686 LOC100041686 11814 Apoc3 26388 Ifi202b 225518 Prdm6 11983 Atpif1 11945 Atp4b 11614 Nr0b1 20378 Frzb 19241 Tmsb4x 12007 Azgp1 76815 Calcoco2 12767 Cxcr4 20116 Rps8 12044 Bcl2a1a 219132 D14Ertd668e 103889 Hoxb2 20103 Rps5 12047 Bcl2a1d 381411 Gm1967 17701 Msx1 14694 Gnb2l1 12049 Bcl2l10 20899 Stra8 23796 Aplnr 19941 Rpl26 12096 Bglap1 78625 1700061G19Rik 12627 Cfc1 12070 Ngfrap1 12097 Bglap2 21816 Tgm1 12622 Cer1 19989 Rpl7 12267 C3ar1 67405 Nts 21385 Tbx2 19896 Rpl10a 12279 C9 435337 EG435337 56720 Tdo2 20044 Rps14 12391 Cav3 545913 Zscan4d 16869 Lhx1 19175 Psmb6 12409 Cbr2 244448 Triml1 22253 Unc5c 22627 Ywhae 12477 Ctla4 69134 2200001I15Rik 14174 Fgf3 19951 Rpl32 12523 Cd84 66065 Hsd17b14 16542 Kdr 66152 1110020P15Rik 12524 Cd86 81879 Tcfcp2l1 15122 Hba-a1 66489 Rpl35 12640 Cga 17907 Mylpf 15414 Hoxb6 15519 Hsp90aa1 12642 Ch25h 26424 Nr5a2 210530 Leprel1 66483 Rpl36al 12655 Chi3l3 83560 Tex14 12338 Capn6 27370 Rps26 12796 Camp 17450 Morc1 20671 Sox17 66576 Uqcrh 12869 Cox8b 79455 Pdcl2 20613 Snai1 22154 Tubb5 12959 Cryba4 231821 Centa1 17897
    [Show full text]
  • University of Leicester, Msc Medical Statistics, Thesis, Wilmar
    Thesis MSc in Medical Statistics Department of Health Sciences University of Leicester, United Kingdom Application of Bayesian hierarchical generalized linear models using weakly informative prior distributions to identify rare genetic variant effects on blood pressure Wilmar Igl March 2015 Summary Background Currently rare genetic variants are discussed as a source of \missing heritability" of complex traits. Bayesian hierarchical models were proposed as an efficient method for the estimation and aggregation of conditional effects of rare variants. Here, such models are applied to identify rare variant effects on blood pressure. Methods Empirical data provided by the Genetic Analysis Workshop 19 (2014) included 1,851 Mexican-American individuals with diastolic blood pressure (DBP), systolic blood pressure (SBP), hypertension (HTN) and 461,868 variants from whole- exome sequencing of odd-numbered chromosomes. Bayesian hierarchical generalized linear models using weakly informative prior distributions were applied. Results Associations of rare variants chr1:204214013 (estimate = 39.6, Credible In- terval (CrI) 95% = [25.3, 53.9], Bayesian p = 6:8 × 10−8) in the PLEKHA6 gene and chr11:118518698 (estimate = 32.2, CrI95% = [20.6, 43.9], Bayesian p = 7:0 × 10−8) in the PHLEDB1 gene were identified. Joint effects of grouped rare variants on DBP in 23 genes (Bayesian p = [8:8 × 10−14, 9:3 × 10−8]) and on SBP in 21 genes (Bayesian p = [8:6 × 10−12, 7:8 × 10−8]) in pathways related to hemostasis, sodi- um/calcium transport, ciliary activity, and others were found. No association with hypertension was detected. Conclusions Bayesian hierarchical generalized linear models with weakly informa- tive priors can successfully be applied in exome-wide genetic association analyses of rare variants.
    [Show full text]
  • Supplementary Table S1. Upregulated Genes Differentially
    Supplementary Table S1. Upregulated genes differentially expressed in athletes (p < 0.05 and 1.3-fold change) Gene Symbol p Value Fold Change 221051_s_at NMRK2 0.01 2.38 236518_at CCDC183 0.00 2.05 218804_at ANO1 0.00 2.05 234675_x_at 0.01 2.02 207076_s_at ASS1 0.00 1.85 209135_at ASPH 0.02 1.81 228434_at BTNL9 0.03 1.81 229985_at BTNL9 0.01 1.79 215795_at MYH7B 0.01 1.78 217979_at TSPAN13 0.01 1.77 230992_at BTNL9 0.01 1.75 226884_at LRRN1 0.03 1.74 220039_s_at CDKAL1 0.01 1.73 236520_at 0.02 1.72 219895_at TMEM255A 0.04 1.72 201030_x_at LDHB 0.00 1.69 233824_at 0.00 1.69 232257_s_at 0.05 1.67 236359_at SCN4B 0.04 1.64 242868_at 0.00 1.63 1557286_at 0.01 1.63 202780_at OXCT1 0.01 1.63 1556542_a_at 0.04 1.63 209992_at PFKFB2 0.04 1.63 205247_at NOTCH4 0.01 1.62 1554182_at TRIM73///TRIM74 0.00 1.61 232892_at MIR1-1HG 0.02 1.61 204726_at CDH13 0.01 1.6 1561167_at 0.01 1.6 1565821_at 0.01 1.6 210169_at SEC14L5 0.01 1.6 236963_at 0.02 1.6 1552880_at SEC16B 0.02 1.6 235228_at CCDC85A 0.02 1.6 1568623_a_at SLC35E4 0.00 1.59 204844_at ENPEP 0.00 1.59 1552256_a_at SCARB1 0.02 1.59 1557283_a_at ZNF519 0.02 1.59 1557293_at LINC00969 0.03 1.59 231644_at 0.01 1.58 228115_at GAREM1 0.01 1.58 223687_s_at LY6K 0.02 1.58 231779_at IRAK2 0.03 1.58 243332_at LOC105379610 0.04 1.58 232118_at 0.01 1.57 203423_at RBP1 0.02 1.57 AMY1A///AMY1B///AMY1C///AMY2A///AMY2B// 208498_s_at 0.03 1.57 /AMYP1 237154_at LOC101930114 0.00 1.56 1559691_at 0.01 1.56 243481_at RHOJ 0.03 1.56 238834_at MYLK3 0.01 1.55 213438_at NFASC 0.02 1.55 242290_at TACC1 0.04 1.55 ANKRD20A1///ANKRD20A12P///ANKRD20A2///
    [Show full text]
  • Download The
    PROBING THE INTERACTION OF ASPERGILLUS FUMIGATUS CONIDIA AND HUMAN AIRWAY EPITHELIAL CELLS BY TRANSCRIPTIONAL PROFILING IN BOTH SPECIES by POL GOMEZ B.Sc., The University of British Columbia, 2002 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE STUDIES (Experimental Medicine) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) January 2010 © Pol Gomez, 2010 ABSTRACT The cells of the airway epithelium play critical roles in host defense to inhaled irritants, and in asthma pathogenesis. These cells are constantly exposed to environmental factors, including the conidia of the ubiquitous mould Aspergillus fumigatus, which are small enough to reach the alveoli. A. fumigatus is associated with a spectrum of diseases ranging from asthma and allergic bronchopulmonary aspergillosis to aspergilloma and invasive aspergillosis. Airway epithelial cells have been shown to internalize A. fumigatus conidia in vitro, but the implications of this process for pathogenesis remain unclear. We have developed a cell culture model for this interaction using the human bronchial epithelium cell line 16HBE and a transgenic A. fumigatus strain expressing green fluorescent protein (GFP). Immunofluorescent staining and nystatin protection assays indicated that cells internalized upwards of 50% of bound conidia. Using fluorescence-activated cell sorting (FACS), cells directly interacting with conidia and cells not associated with any conidia were sorted into separate samples, with an overall accuracy of 75%. Genome-wide transcriptional profiling using microarrays revealed significant responses of 16HBE cells and conidia to each other. Significant changes in gene expression were identified between cells and conidia incubated alone versus together, as well as between GFP positive and negative sorted cells.
    [Show full text]
  • 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
    [Show full text]
  • Cell Adhesion and Specificity
    RESEARCH ARTICLE Molecular basis of sidekick-mediated cell- cell adhesion and specificity Kerry M Goodman1†, Masahito Yamagata2,3†, Xiangshu Jin1,4‡, Seetha Mannepalli1, Phinikoula S Katsamba4,5, Go¨ ran Ahlse´ n4,5, Alina P Sergeeva4,5, Barry Honig1,4,5,6,7*, Joshua R Sanes2,3*, Lawrence Shapiro1,5,7* 1Department of Biochemistry and Molecular Biophysics, Columbia University, New York, United States; 2Department of Molecular and Cellular Biology, Harvard University, Cambridge, United States; 3Center for Brain Science, Harvard University, Cambridge, United States; 4Howard Hughes Medical Institute, Columbia University, New York, United States; 5Department of Systems Biology, Columbia University, New York, United States; 6Department of Medicine, Columbia University, New York, United States; 7Zuckerman Mind Brain and Behavior Institute, Columbia University, New York, United States *For correspondence: bh6@cumc. Abstract Sidekick (Sdk) 1 and 2 are related immunoglobulin superfamily cell adhesion proteins columbia.edu (BH); sanesj@mcb. required for appropriate synaptic connections between specific subtypes of retinal neurons. Sdks harvard.edu (JRS); shapiro@ mediate cell-cell adhesion with homophilic specificity that underlies their neuronal targeting convex.hhmi.columbia.edu (LS) function. Here we report crystal structures of Sdk1 and Sdk2 ectodomain regions, revealing similar †These authors contributed homodimers mediated by the four N-terminal immunoglobulin domains (Ig1–4), arranged in a equally to this work horseshoe conformation. These Ig1–4 horseshoes interact in a novel back-to-back orientation in both homodimers through Ig1:Ig2, Ig1:Ig1 and Ig3:Ig4 interactions. Structure-guided mutagenesis Present address: ‡Department results show that this canonical dimer is required for both Sdk-mediated cell aggregation (via trans of Chemistry, Michigan State interactions) and Sdk clustering in isolated cells (via cis interactions).
    [Show full text]
  • Supplementary Table 1: Adhesion Genes Data Set
    Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like,
    [Show full text]
  • NATURAL KILLER CELLS, HYPOXIA, and EPIGENETIC REGULATION of HEMOCHORIAL PLACENTATION by Damayanti Chakraborty Submitted to the G
    NATURAL KILLER CELLS, HYPOXIA, AND EPIGENETIC REGULATION OF HEMOCHORIAL PLACENTATION BY Damayanti Chakraborty Submitted to the graduate degree program in Pathology and Laboratory Medicine and the Graduate Faculty of the University of Kansas in partial fulfillment ofthe requirements for the degree of Doctor of Philosophy. ________________________________ Chair: Michael J. Soares, Ph.D. ________________________________ Jay Vivian, Ph.D. ________________________________ Patrick Fields, Ph.D. ________________________________ Soumen Paul, Ph.D. ________________________________ Michael Wolfe, Ph.D. ________________________________ Adam J. Krieg, Ph.D. Date Defended: 04/01/2013 The Dissertation Committee for Damayanti Chakraborty certifies that this is the approved version of the following dissertation: NATURAL KILLER CELLS, HYPOXIA, AND EPIGENETIC REGULATION OF HEMOCHORIAL PLACENTATION ________________________________ Chair: Michael J. Soares, Ph.D. Date approved: 04/01/2013 ii ABSTRACT During the establishment of pregnancy, uterine stromal cells differentiate into decidual cells and recruit natural killer (NK) cells. These NK cells are characterized by low cytotoxicity and distinct cytokine production. In rodent as well as in human pregnancy, the uterine NK cells peak in number around mid-gestation after which they decline. NK cells associate with uterine spiral arteries and are implicated in pregnancy associated vascular remodeling processes and potentially in modulating trophoblast invasion. Failure of trophoblast invasion and vascular remodeling has been shown to be associated with pathological conditions like preeclampsia syndrome, hypertension in mother and/or fetal growth restriction. We hypothesize that NK cells fundamentally contribute to the organization of the placentation site. In order to study the in vivo role of NK cells during pregnancy, gestation stage- specific NK cell depletion was performed in rats using anti asialo GM1 antibodies.
    [Show full text]
  • CHARACTERIZATION, EPIGENETIC DRUG EFFECT, and GENE DELIVERY to BREAST CANCER CELLS a Dissertation Presented to the Graduate Facu
    CHARACTERIZATION, EPIGENETIC DRUG EFFECT, AND GENE DELIVERY TO BREAST CANCER CELLS A Dissertation Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of Requirements for the Degree Doctor of Philosophy Shan Lu December, 2015 CHARACTERIZATION, EPIGENETIC DRUG EFFECT, AND GENE DELIVERY TO BREAST CANCER CELLS Shan Lu Dissertation Approved: Accepted: Advisor Department Chair Dr. Vinod Labhasetwar Dr. Stephen Weeks Committee Chair Dean of the College Dr. Coleen Pugh Dr. John Green Committee Member Dean of Graduate School Dr. Abraham Joy Dr. Chand Midha Committee Member Dr. Ali Dhinojwala Committee Member Dr. Anand Ramamurthi Committee Member Dr. Peter Niewiarowski ii ABSTRACT Cancer relapse is strongly associated with the presence of cancer stem cells (CSCs), which drive the development of metastasis and drug resistance. In human breast cancer, CSCs are identified by the CD44+/CD24- phenotype and characterized by drug resistance, high tumorigenicity and metastatic potential. In this study, I found that MCF-7/Adr cells that are breast cancer cells resistant to doxorubicin (Dox) uniformly displayed CSC surface markers, possessed CSC proteins, formed in vitro mammospheres, yet retained low migratory rate. They were also able to self-renew and differentiate under floating culture condition and are responsive to epigenetic drug treatment. High degree of DNA methylation (modifications of the cytosine residues of DNA) and histone deacetylation are major epigenetic landmarks of CSCs. In this work, I showed that MCF-7/Adr cells are sensitive to histone deacetylation inhibitor suberoylanilide hydroxamic acid (SAHA). Through RNA-sequencing technology, I also found that decitabine (DAC) and SAHA similarly affected a large number of the examined pathways, including drug and nanoparticle cellular uptake and transport, lipid metabolism, carcinogenesis and nuclear transport pathways.
    [Show full text]