Whole-Exome Sequencing Identifies Germline Mutation in TP53 and ATRX in a Child with Ge- Nomically Aberrant AT/RT and Her Mother with Anaplastic Astrocytoma
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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. -
Supplementary Material
BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) J Neurol Neurosurg Psychiatry Page 1 / 45 SUPPLEMENTARY MATERIAL Appendix A1: Neuropsychological protocol. Appendix A2: Description of the four cases at the transitional stage. Table A1: Clinical status and center proportion in each batch. Table A2: Complete output from EdgeR. Table A3: List of the putative target genes. Table A4: Complete output from DIANA-miRPath v.3. Table A5: Comparison of studies investigating miRNAs from brain samples. Figure A1: Stratified nested cross-validation. Figure A2: Expression heatmap of miRNA signature. Figure A3: Bootstrapped ROC AUC scores. Figure A4: ROC AUC scores with 100 different fold splits. Figure A5: Presymptomatic subjects probability scores. Figure A6: Heatmap of the level of enrichment in KEGG pathways. Kmetzsch V, et al. J Neurol Neurosurg Psychiatry 2021; 92:485–493. doi: 10.1136/jnnp-2020-324647 BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) J Neurol Neurosurg Psychiatry Appendix A1. Neuropsychological protocol The PREV-DEMALS cognitive evaluation included standardized neuropsychological tests to investigate all cognitive domains, and in particular frontal lobe functions. The scores were provided previously (Bertrand et al., 2018). Briefly, global cognitive efficiency was evaluated by means of Mini-Mental State Examination (MMSE) and Mattis Dementia Rating Scale (MDRS). Frontal executive functions were assessed with Frontal Assessment Battery (FAB), forward and backward digit spans, Trail Making Test part A and B (TMT-A and TMT-B), Wisconsin Card Sorting Test (WCST), and Symbol-Digit Modalities test. -
A High-Throughput Approach to Uncover Novel Roles of APOBEC2, a Functional Orphan of the AID/APOBEC Family
Rockefeller University Digital Commons @ RU Student Theses and Dissertations 2018 A High-Throughput Approach to Uncover Novel Roles of APOBEC2, a Functional Orphan of the AID/APOBEC Family Linda Molla Follow this and additional works at: https://digitalcommons.rockefeller.edu/ student_theses_and_dissertations Part of the Life Sciences Commons A HIGH-THROUGHPUT APPROACH TO UNCOVER NOVEL ROLES OF APOBEC2, A FUNCTIONAL ORPHAN OF THE AID/APOBEC FAMILY A Thesis Presented to the Faculty of The Rockefeller University in Partial Fulfillment of the Requirements for the degree of Doctor of Philosophy by Linda Molla June 2018 © Copyright by Linda Molla 2018 A HIGH-THROUGHPUT APPROACH TO UNCOVER NOVEL ROLES OF APOBEC2, A FUNCTIONAL ORPHAN OF THE AID/APOBEC FAMILY Linda Molla, Ph.D. The Rockefeller University 2018 APOBEC2 is a member of the AID/APOBEC cytidine deaminase family of proteins. Unlike most of AID/APOBEC, however, APOBEC2’s function remains elusive. Previous research has implicated APOBEC2 in diverse organisms and cellular processes such as muscle biology (in Mus musculus), regeneration (in Danio rerio), and development (in Xenopus laevis). APOBEC2 has also been implicated in cancer. However the enzymatic activity, substrate or physiological target(s) of APOBEC2 are unknown. For this thesis, I have combined Next Generation Sequencing (NGS) techniques with state-of-the-art molecular biology to determine the physiological targets of APOBEC2. Using a cell culture muscle differentiation system, and RNA sequencing (RNA-Seq) by polyA capture, I demonstrated that unlike the AID/APOBEC family member APOBEC1, APOBEC2 is not an RNA editor. Using the same system combined with enhanced Reduced Representation Bisulfite Sequencing (eRRBS) analyses I showed that, unlike the AID/APOBEC family member AID, APOBEC2 does not act as a 5-methyl-C deaminase. -
An Algorithm for Identifying Fusion Transcripts from Paired-End RNA
Jia et al. Genome Biology 2013, 14:R12 http://genomebiology.com/content/14/2/R12 METHOD Open Access SOAPfuse: an algorithm for identifying fusion transcripts from paired-end RNA-Seq data Wenlong Jia1,2†, Kunlong Qiu1,2†, Minghui He1,2†, Pengfei Song2†, Quan Zhou1,2,3, Feng Zhou2,4, Yuan Yu2, Dandan Zhu2, Michael L Nickerson5, Shengqing Wan1,2, Xiangke Liao6, Xiaoqian Zhu6,7, Shaoliang Peng6,7, Yingrui Li1,2, Jun Wang1,2,8,9 and Guangwu Guo1,2* Abstract We have developed a new method, SOAPfuse, to identify fusion transcripts from paired-end RNA-Seq data. SOAPfuse applies an improved partial exhaustion algorithm to construct a library of fusion junction sequences, which can be used to efficiently identify fusion events, and employs a series of filters to nominate high-confidence fusion transcripts. Compared with other released tools, SOAPfuse achieves higher detection efficiency and consumed less computing resources. We applied SOAPfuse to RNA-Seq data from two bladder cancer cell lines, and confirmed 15 fusion transcripts, including several novel events common to both cell lines. SOAPfuse is available at http://soap.genomics.org.cn/soapfuse.html. Background of species [9-16]. In addition, RNA-Seq has been proven Gene fusions, arising from the juxtaposition of two distinct to be a sensitive and efficient approach to gene fusion regions in chromosomes, play important roles in carcino- discovery in many types of cancers [17-20]. Compared genesis and can serve as valuable diagnostic and therapeu- with whole genome sequencing, which is also able to tic targets in cancer. Aberrant gene fusions have been detect gene-fusion-creating rearrangements, RNA-Seq widely described in malignant hematological disorders and identifies fusion events that generate aberrant transcripts sarcomas [1-3], with the recurrent BCR-ABL fusion gene that are more likely to be functional or causal in biologi- in chronic myeloid leukemia as the classic example [4]. -
Proteomic Signatures of Brain Regions Affected by Tau Pathology in Early and Late Stages of Alzheimer's Disease
Neurobiology of Disease 130 (2019) 104509 Contents lists available at ScienceDirect Neurobiology of Disease journal homepage: www.elsevier.com/locate/ynbdi Proteomic signatures of brain regions affected by tau pathology in early and T late stages of Alzheimer's disease Clarissa Ferolla Mendonçaa,b, Magdalena Kurasc, Fábio César Sousa Nogueiraa,d, Indira Plác, Tibor Hortobágyie,f,g, László Csibae,h, Miklós Palkovitsi, Éva Renneri, Péter Dömej,k, ⁎ ⁎ György Marko-Vargac, Gilberto B. Domonta, , Melinda Rezelic, a Proteomics Unit, Department of Biochemistry, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil b Gladstone Institute of Neurological Disease, San Francisco, USA c Division of Clinical Protein Science & Imaging, Department of Clinical Sciences (Lund) and Department of Biomedical Engineering, Lund University, Lund, Sweden d Laboratory of Proteomics, LADETEC, Institute of Chemistry, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil e MTA-DE Cerebrovascular and Neurodegenerative Research Group, University of Debrecen, Debrecen, Hungary f Institute of Pathology, Faculty of Medicine, University of Szeged, Szeged, Hungary g Centre for Age-Related Medicine, SESAM, Stavanger University Hospital, Stavanger, Norway h Department of Neurology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary i SE-NAP – Human Brain Tissue Bank Microdissection Laboratory, Semmelweis University, Budapest, Hungary j Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary k National Institute of Psychiatry and Addictions, Nyírő Gyula Hospital, Budapest, Hungary ARTICLE INFO ABSTRACT Keywords: Background: Alzheimer's disease (AD) is the most common neurodegenerative disorder. Depositions of amyloid β Alzheimer's disease peptide (Aβ) and tau protein are among the major pathological hallmarks of AD. Aβ and tau burden follows Proteomics predictable spatial patterns during the progression of AD. -
NIH Public Access Author Manuscript Neuroimage
NIH Public Access Author Manuscript Neuroimage. Author manuscript; available in PMC 2010 June 1. NIH-PA Author ManuscriptPublished NIH-PA Author Manuscript in final edited NIH-PA Author Manuscript form as: Neuroimage. 2010 June ; 51(2): 542±554. doi:10.1016/j.neuroimage.2010.02.068. Genome-Wide Analysis Reveals Novel Genes Influencing Temporal Lobe Structure with Relevance to Neurodegeneration in Alzheimer’s Disease Jason L. Stein1, Xue Hua1, Jonathan H. Morra1, Suh Lee1, Derrek P. Hibar1, April J. Ho1, Alex D. Leow1,2, Arthur W. Toga1, Jae Hoon Sul3, Hyun Min Kang4, Eleazar Eskin3,5, Andrew J. Saykin6, Li Shen6, Tatiana Foroud7, Nathan Pankratz7, Matthew J. Huentelman8, David W. Craig8, Jill D. Gerber8, April N. Allen8, Jason J. Corneveaux8, Dietrich A. Stephan8, Jennifer Webster8, Bryan M. DeChairo9, Steven G. Potkin10, Clifford R. Jack Jr.11, Michael W. Weiner12,13, Paul M. Thompson1, and Alzheimer’s Disease Neuroimaging Initiative* 1 Laboratory of Neuro Imaging, Dept. of Neurology, UCLA School of Medicine, Los Angeles, CA 2 Resnick Neuropsychiatric Hospital at UCLA, Los Angeles, CA 3 Department of Computer Science, UCLA, Los Angeles, CA 4 Computer Science and Engineering, UC San Diego, La Jolla, CA 5 Department of Human Genetics, UCLA, Los Angeles, CA 6 Center for Neuroimaging, Department of Radiology, Indiana University School of Medicine, Indianapolis, IN 7 Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 8 The Translational Genomics Research Institute, Phoenix, AZ 9 Neuroscience, Molecular Medicine, Pfizer Global R&D, New London, CT 10 Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA 11 Mayo Clinic, Rochester, MN 12 Depts. -
Genome Functional Annotation Across Species Using Deep Convolutional Neural Networks
bioRxiv preprint doi: https://doi.org/10.1101/330308; this version posted June 7, 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. Genome Functional Annotation across Species using Deep Convolutional Neural Networks Ghazaleh Khodabandelou1,*, Etienne Routhier1, and Julien Mozziconacci1,* 1Sorbonne Universite,´ CNRS, Laboratoire de Physique Theorique´ de la Matiere` Condensee,` LPTMC, 75005 Paris, France. *[email protected], [email protected] ABSTRACT Deep neural network application is today a skyrocketing field in many disciplinary domains. In genomics the development of deep neural networks is expected to revolutionize current practice. Several approaches relying on convolutional neural networks have been developed to associate short genomic sequences with a functional role such as promoters, enhancers or protein binding sites along genomes. These approaches rely on the generation of sequences batches with known annotations for learning purpose. While they show good performance to predict annotations from a test subset of these batches, they usually perform poorly when applied genome-wide. In this study, we address this issue and propose an optimal strategy to train convolutional neural networks for this specific application. We use as a case study transcription start sites and show that a model trained on one organism can be used to predict transcription start sites in a different specie. This cross-species application of convolutional neural networks trained with genomic sequence data provides a new technique to annotate any genome from previously existing annotations in related species. It also provides a way to determine whether the sequence patterns recognized by chromatin associated proteins in different species are conserved or not. -
New Insights on Human Essential Genes Based on Integrated Multi
bioRxiv preprint doi: https://doi.org/10.1101/260224; this version posted February 5, 2018. 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. New insights on human essential genes based on integrated multi- omics analysis Hebing Chen1,2, Zhuo Zhang1,2, Shuai Jiang 1,2, Ruijiang Li1, Wanying Li1, Hao Li1,* and Xiaochen Bo1,* 1Beijing Institute of Radiation Medicine, Beijing 100850, China. 2 Co-first author *Correspondence: [email protected]; [email protected] Abstract Essential genes are those whose functions govern critical processes that sustain life in the organism. Comprehensive understanding of human essential genes could enable breakthroughs in biology and medicine. Recently, there has been a rapid proliferation of technologies for identifying and investigating the functions of human essential genes. Here, according to gene essentiality, we present a global analysis for comprehensively and systematically elucidating the genetic and regulatory characteristics of human essential genes. We explain why these genes are essential from the genomic, epigenomic, and proteomic perspectives, and we discuss their evolutionary and embryonic developmental properties. Importantly, we find that essential human genes can be used as markers to guide cancer treatment. We have developed an interactive web server, the Human Essential Genes Interactive Analysis Platform (HEGIAP) (http://sysomics.com/HEGIAP/), which integrates abundant analytical tools to give a global, multidimensional interpretation of gene essentiality. bioRxiv preprint doi: https://doi.org/10.1101/260224; this version posted February 5, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. -
Anticancer Effect of Natural Product Sulforaphane by Targeting MAPK Signal Through Mirna-1247-3P in Human Cervical Cancer Cells
Article Volume 11, Issue 1, 2021, 7943 - 7972 https://doi.org/10.33263/BRIAC111.79437972 Anticancer Effect of Natural Product Sulforaphane by Targeting MAPK Signal through miRNA-1247-3p in Human Cervical Cancer Cells Meng Luo 1 , Dian Fan 2 , Yinan Xiao 2 , Hao Zeng 2 , Dingyue Zhang 2 , Yunuo Zhao 2 , Xuelei Ma 1,* 1 Department of Biotherapy, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P.R. China; [email protected] (L.M.); 2 West China Medical School, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P.R. China; [email protected] (F.D.); [email protected] (X.Y.N.); [email protected] (Z.H.); [email protected] (Z.D.Y.); [email protected] (Z.Y.N.); * Correspondence: [email protected]; Scopus Author ID 55523405000 Received: 11.06.2020; Revised: 3.07.2020; Accepted: 5.07.2020; Published: 9.07.2020 Abstract: The prognosis of cervical cancer remains poor. Sulforaphane, an active ingredient from cruciferous plants, has been identified as a potential anticancer agent in various cancers. However, there is little information about its effect on cervical cancer. Here, we conducted a present study to uncover the effect and the potential mechanisms of sulforaphane on cervical cancer. HeLa cells were treated with sulforaphane, and cell proliferation and apoptosis were assessed by Cell Counting Kit-8, Western blot, flow cytometry, and immunofluorescence. Then, next-generation sequencing (NGS) and bioinformatics tools were used to analyze mRNA-seq, miRNA-seq, and potential pathways. Finally, qRT-PCR, Cell Counting Kit-8, flow cytometry, small RNAs analysis, and Western blot were performed to evaluate the biological function of miR1247-3p and MAPK pathway in HeLa cell lines. -
Table S4. RAE Analysis of Dedifferentiated Liposarcoma
Table S4. RAE analysis of dedifferentiated liposarcoma Model Chromosome Region start Region end Size q value freqX0* # genes genes Amp 1 57809872 60413476 2603605 0.00026 34.6 10 DAB1,RPS26P15,OMA1,TACSTD2,MYSM1,JUN,FGGY,HOOK1,CYP2J2,C1orf87 Amp 1 158619146 158696968 77823 0.053 25 1 VANGL2 Amp 1 158883523 158922841 39319 0.081 23.1 2 SLAMF1,CD48 Amp 1 162042586 162118557 75972 0.072 25 0 [Nearest:NUF2] Amp 1 162272460 162767627 495168 0.017 26.9 0 [Nearest:PBX1] Amp 1 165486554 165532374 45821 0.057 25 1 POU2F1 Amp 1 167138282 167483267 344986 0.024 26.9 2 ATP1B1,NME7 Amp 1 167612872 167708844 95973 0.041 25 3 BLZF1,C1orf114,SLC19A2 Amp 1 167728199 167808161 79963 0.076 21.2 1 F5 Amp 1 168436370 169233893 797524 0.018 26.9 3 GORAB,PRRX1,C1orf129 Amp 1 169462231 170768440 1306210 1.3E-06 38.5 10 FMO1,FMO4,TOP1P1,BAT2D1,MYOC,VAMP4,METTL13,DNM3,C1orf105,PIGC Amp 1 171026247 171291427 265181 0.015 26.9 1 TNFSF18 Del 1 201860394 202299299 438906 0.0047 25 6 ATP2B4,SNORA77,LAX1,ZC3H11A,SNRPE,C1orf157 Del 1 210909187 212021116 1111930 0.017 19.2 8 BATF3,NSL1,TATDN3,C1orf227,FLVCR1,VASH2,ANGEL2,RPS6KC1 Del 1 215937857 216049214 111358 0.079 23.1 1 SPATA17 Del 1 218237257 218367476 130220 0.0063 26.9 3 EPRS,BPNT1,IARS2 Del 1 222100886 222727238 626353 5.2E-05 32.7 5 FBXO28,DEGS1,NVL,CNIH4,WDR26 Del 1 223166548 224519805 1353258 0.0063 26.9 15 DNAH14,LBR,ENAH,SRP9,EPHX1,TMEM63A,LEFTY1,PYCR2,LEFTY2,C1orf55,H3F3A,LOC440926 ,ACBD3,MIXL1,LIN9 Del 1 225283136 225374166 91031 0.054 23.1 1 CDC42BPA Del 1 227278990 229012661 1733672 0.091 21.2 13 RAB4A,SPHAR,C1orf96,ACTA1,NUP133,ABCB10,TAF5L,URB2,GALNT2,PGBD5,COG2,AGT,CAP -
Soapfuse: an Algorithm for Identifying Fusion Transcripts from Paired-End RNA-Seq Data
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Copenhagen University Research Information System SOAPfuse an algorithm for identifying fusion transcripts from paired-end RNA-Seq data Jia, Wenlong; Qiu, Kunlong; He, Minghui; Song, Pengfei; Zhou, Quan; Zhou, Feng; Yu, Yuan; Zhu, Dandan; Nickerson, Michael L.; Wan, Shengqing; Liao, Xiangke; Zhu, Xiaoqian; Peng, Shaoliang; Li, Yingrui; Wang, Jun; Guo, Guangwu Published in: Genome Biology (Online Edition) DOI: 10.1186/gb-2013-14-2-r12 Publication date: 2013 Document version Publisher's PDF, also known as Version of record Citation for published version (APA): Jia, W., Qiu, K., He, M., Song, P., Zhou, Q., Zhou, F., ... Guo, G. (2013). SOAPfuse: an algorithm for identifying fusion transcripts from paired-end RNA-Seq data. Genome Biology (Online Edition), 14(2), [R12]. https://doi.org/10.1186/gb-2013-14-2-r12 Download date: 08. apr.. 2020 Jia et al. Genome Biology 2013, 14:R12 http://genomebiology.com/content/14/2/R12 METHOD Open Access SOAPfuse: an algorithm for identifying fusion transcripts from paired-end RNA-Seq data Wenlong Jia1,2†, Kunlong Qiu1,2†, Minghui He1,2†, Pengfei Song2†, Quan Zhou1,2,3, Feng Zhou2,4, Yuan Yu2, Dandan Zhu2, Michael L Nickerson5, Shengqing Wan1,2, Xiangke Liao6, Xiaoqian Zhu6,7, Shaoliang Peng6,7, Yingrui Li1,2, Jun Wang1,2,8,9 and Guangwu Guo1,2* Abstract We have developed a new method, SOAPfuse, to identify fusion transcripts from paired-end RNA-Seq data. SOAPfuse applies an improved partial exhaustion algorithm to construct a library of fusion junction sequences, which can be used to efficiently identify fusion events, and employs a series of filters to nominate high-confidence fusion transcripts. -
Quantitative Trait Loci Mapping of Macrophage Atherogenic Phenotypes
QUANTITATIVE TRAIT LOCI MAPPING OF MACROPHAGE ATHEROGENIC PHENOTYPES BRIAN RITCHEY Bachelor of Science Biochemistry John Carroll University May 2009 submitted in partial fulfillment of requirements for the degree DOCTOR OF PHILOSOPHY IN CLINICAL AND BIOANALYTICAL CHEMISTRY at the CLEVELAND STATE UNIVERSITY December 2017 We hereby approve this thesis/dissertation for Brian Ritchey Candidate for the Doctor of Philosophy in Clinical-Bioanalytical Chemistry degree for the Department of Chemistry and the CLEVELAND STATE UNIVERSITY College of Graduate Studies by ______________________________ Date: _________ Dissertation Chairperson, Johnathan D. Smith, PhD Department of Cellular and Molecular Medicine, Cleveland Clinic ______________________________ Date: _________ Dissertation Committee member, David J. Anderson, PhD Department of Chemistry, Cleveland State University ______________________________ Date: _________ Dissertation Committee member, Baochuan Guo, PhD Department of Chemistry, Cleveland State University ______________________________ Date: _________ Dissertation Committee member, Stanley L. Hazen, MD PhD Department of Cellular and Molecular Medicine, Cleveland Clinic ______________________________ Date: _________ Dissertation Committee member, Renliang Zhang, MD PhD Department of Cellular and Molecular Medicine, Cleveland Clinic ______________________________ Date: _________ Dissertation Committee member, Aimin Zhou, PhD Department of Chemistry, Cleveland State University Date of Defense: October 23, 2017 DEDICATION I dedicate this work to my entire family. In particular, my brother Greg Ritchey, and most especially my father Dr. Michael Ritchey, without whose support none of this work would be possible. I am forever grateful to you for your devotion to me and our family. You are an eternal inspiration that will fuel me for the remainder of my life. I am extraordinarily lucky to have grown up in the family I did, which I will never forget.