EMT) with Cisplatin Resistance
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FHL3 Contributes to EMT and Chemotherapy Resistance Through Inhibiting Ubiquitination of Slug and Activating Tgfβ/Smad-Independent Pathways in Gastric Cancer
FHL3 Contributes to EMT and Chemotherapy Resistance Through Inhibiting Ubiquitination of Slug and Activating TGFβ/Smad-Independent Pathways in Gastric Cancer Guodong Cao First Aliated Hospital of Anhui Medical University Pengping Li Hangzhou Xiaoshan No 1 People's Hospital Qiang Sun Xuzhou Medical University Sihan Chen First Aliated Hospital of Anhui Medical University Xin Xu First Aliated Hospital of Anhui Medical University Xiaobo He First Aliated Hospital of Anhui Medical University Zhenyu Wang Hangzhou Xiaoshan No 1 People's Hospital Peng Chen First Aliated Hospital of Anhui Medical University Maoming Xiong ( [email protected] ) First Aliated Hospital of Anhui Medical University Bo Chen First Aliated Hospital of Anhui Medical University Research Keywords: EMT, Chemotherapy resistance, FHL3, Ubiquitination, Gastric cancer Posted Date: October 9th, 2020 DOI: https://doi.org/10.21203/rs.3.rs-87249/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. ReLoaadd iFngu l[Ml LaitchJeanxs]/ejax/output/CommonHTML/jax.js Page 1/28 Loading [MathJax]/jax/output/CommonHTML/jax.js Page 2/28 Abstract Background: Gastric cancer presents high risk of metastasis and chemotherapy resistance. Hence, the mechanistic understanding of the tumor metastasis and chemotherapy resistance is quietly important. Methods: TCGA database and clinical samples are used for exploring the role of FHL3 in disease progression and prognosis. The roles of FHL3 in metastasis and chemotherapy resistance are explored in vitro and in vivo by siRNA or shRNA treatment. Finally, we explore the FHL3-mediated EMT and chemotherapy resistance. Results: mRNA and protein level of FHL3 is signicantly up-regulated in gastric cancer tissues when compares with it in adjacent tissue. -
In Vivo Studies Using the Classical Mouse Diversity Panel
The Mouse Diversity Panel Predicts Clinical Drug Toxicity Risk Where Classical Models Fail Alison Harrill, Ph.D The Hamner-UNC Institute for Drug Safety Sciences 0 The Importance of Predicting Clinical Adverse Drug Reactions (ADR) Figure: Cath O’Driscoll Nature Publishing 2004 Risk ID PGx Testing 1 People Respond Differently to Drugs Pharmacogenetic Markers Identified by Genome-Wide Association Drug Adverse Drug Risk Allele Reaction (ADR) Abacavir Hypersensitivity HLA-B*5701 Flucloxacillin Hepatotoxicity Allopurinol Cutaneous ADR HLA-B*5801 Carbamazepine Stevens-Johnson HLA-B*1502 Syndrome Augmentin Hepatotoxicity DRB1*1501 Ximelagatran Hepatotoxicity DRB1*0701 Ticlopidine Hepatotoxicity HLA-A*3303 Average preclinical populations and human hepatocytes lack the diversity to detect incidence of adverse events that occur only in 1/10,000 people. Current Rodent Models of Risk Assessment The Challenge “At a time of extraordinary scientific progress, methods have hardly changed in several decades ([FDA] 2004)… Toxicologists face a major challenge in the twenty-first century. They need to embrace the new “omics” techniques and ensure that they are using the most appropriate animals if their discipline is to become a more effective tool in drug development.” -Dr. Michael Festing Quantitative geneticist Toxicol Pathol. 2010;38(5):681-90 Rodent Models as a Strategy for Hazard Characterization and Pharmacogenetics Genetically defined rodent models may provide ability to: 1. Improve preclinical prediction of drugs that carry a human safety risk 2. -
Bioinformatic Analysis of Structure and Function of LIM Domains of Human Zyxin Family Proteins
International Journal of Molecular Sciences Article Bioinformatic Analysis of Structure and Function of LIM Domains of Human Zyxin Family Proteins M. Quadir Siddiqui 1,† , Maulik D. Badmalia 1,† and Trushar R. Patel 1,2,3,* 1 Alberta RNA Research and Training Institute, Department of Chemistry and Biochemistry, University of Lethbridge, 4401 University Drive, Lethbridge, AB T1K 3M4, Canada; [email protected] (M.Q.S.); [email protected] (M.D.B.) 2 Department of Microbiology, Immunology and Infectious Disease, Cumming School of Medicine, University of Calgary, 3330 Hospital Drive, Calgary, AB T2N 4N1, Canada 3 Li Ka Shing Institute of Virology, University of Alberta, Edmonton, AB T6G 2E1, Canada * Correspondence: [email protected] † These authors contributed equally to the work. Abstract: Members of the human Zyxin family are LIM domain-containing proteins that perform critical cellular functions and are indispensable for cellular integrity. Despite their importance, not much is known about their structure, functions, interactions and dynamics. To provide insights into these, we used a set of in-silico tools and databases and analyzed their amino acid sequence, phylogeny, post-translational modifications, structure-dynamics, molecular interactions, and func- tions. Our analysis revealed that zyxin members are ohnologs. Presence of a conserved nuclear export signal composed of LxxLxL/LxxxLxL consensus sequence, as well as a possible nuclear localization signal, suggesting that Zyxin family members may have nuclear and cytoplasmic roles. The molecular modeling and structural analysis indicated that Zyxin family LIM domains share Citation: Siddiqui, M.Q.; Badmalia, similarities with transcriptional regulators and have positively charged electrostatic patches, which M.D.; Patel, T.R. -
Mouse Population-Guided Resequencing Reveals That Variants in CD44 Contribute to Acetaminophen-Induced Liver Injury in Humans
Downloaded from genome.cshlp.org on October 2, 2021 - Published by Cold Spring Harbor Laboratory Press Letter Mouse population-guided resequencing reveals that variants in CD44 contribute to acetaminophen-induced liver injury in humans Alison H. Harrill,1,2,12 Paul B. Watkins,3,12 Stephen Su,6 Pamela K. Ross,2 David E. Harbourt,5 Ioannis M. Stylianou,7 Gary A. Boorman,8 Mark W. Russo,3 Richard S. Sackler,9 Stephen C. Harris,11 Philip C. Smith,5 Raymond Tennant,8 Molly Bogue,7 Kenneth Paigen,7 Christopher Harris,9,10 Tanupriya Contractor,9 Timothy Wiltshire,5 Ivan Rusyn,1,2,14 and David W. Threadgill1,4,13,14,15 1Curriculum in Toxicology, University of North Carolina, Chapel Hill, North Carolina 27599, USA; 2Department of Environmental Sciences and Engineering, University of North Carolina, Chapel Hill, North Carolina 27599, USA; 3Division of Gastroenterology and Hepatology, University of North Carolina, Chapel Hill, North Carolina 27599, USA; 4Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599, USA; 5School of Pharmacy, University of North Carolina, Chapel Hill, North Carolina 27599, USA; 6Department of Mouse Genetics, Genomics Institute of the Novartis Research Foundation, San Diego, California 92121, USA; 7The Jackson Laboratory, Bar Harbor, Maine 04609, USA; 8National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina 27709, USA; 9Verto Institute Research Laboratories, New Brunswick, New Jersey 08903, USA; 10Cancer Institute of New Jersey, New Brunswick, New Jersey 08903, USA; 11Purdue Pharma L.P., Stamford, Connecticut 06901, USA; 12Hamner-UNC Center for Drug Safety Sciences, The Hamner Institutes for Health Sciences, Research Triangle Park, North Carolina 27709, USA; 13Department of Genetics, North Carolina State University, Raleigh, North Carolina 27695, USA Interindividual variability in response to chemicals and drugs is a common regulatory concern. -
Functional Genomics Atlas of Synovial Fibroblasts Defining Rheumatoid Arthritis
medRxiv preprint doi: https://doi.org/10.1101/2020.12.16.20248230; this version posted December 18, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Functional genomics atlas of synovial fibroblasts defining rheumatoid arthritis heritability Xiangyu Ge1*, Mojca Frank-Bertoncelj2*, Kerstin Klein2, Amanda Mcgovern1, Tadeja Kuret2,3, Miranda Houtman2, Blaž Burja2,3, Raphael Micheroli2, Miriam Marks4, Andrew Filer5,6, Christopher D. Buckley5,6,7, Gisela Orozco1, Oliver Distler2, Andrew P Morris1, Paul Martin1, Stephen Eyre1* & Caroline Ospelt2*,# 1Versus Arthritis Centre for Genetics and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK 2Department of Rheumatology, Center of Experimental Rheumatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland 3Department of Rheumatology, University Medical Centre, Ljubljana, Slovenia 4Schulthess Klinik, Zurich, Switzerland 5Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK 6NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust, University of Birmingham, Birmingham, UK 7Kennedy Institute of Rheumatology, University of Oxford Roosevelt Drive Headington Oxford UK *These authors contributed equally #corresponding author: [email protected] NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. 1 medRxiv preprint doi: https://doi.org/10.1101/2020.12.16.20248230; this version posted December 18, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. -
Investigation of the Underlying Hub Genes and Molexular Pathogensis in Gastric Cancer by Integrated Bioinformatic Analyses
bioRxiv preprint doi: https://doi.org/10.1101/2020.12.20.423656; this version posted December 22, 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. Investigation of the underlying hub genes and molexular pathogensis in gastric cancer by integrated bioinformatic analyses Basavaraj Vastrad1, Chanabasayya Vastrad*2 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.20.423656; this version posted December 22, 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 The high mortality rate of gastric cancer (GC) is in part due to the absence of initial disclosure of its biomarkers. The recognition of important genes associated in GC is therefore recommended to advance clinical prognosis, diagnosis and and treatment outcomes. The current investigation used the microarray dataset GSE113255 RNA seq data from the Gene Expression Omnibus database to diagnose differentially expressed genes (DEGs). Pathway and gene ontology enrichment analyses were performed, and a proteinprotein interaction network, modules, target genes - miRNA regulatory network and target genes - TF regulatory network were constructed and analyzed. Finally, validation of hub genes was performed. The 1008 DEGs identified consisted of 505 up regulated genes and 503 down regulated genes. -
Ponatinib Shows Potent Antitumor Activity in Small Cell Carcinoma of the Ovary Hypercalcemic Type (SCCOHT) Through Multikinase Inhibition Jessica D
Published OnlineFirst February 9, 2018; DOI: 10.1158/1078-0432.CCR-17-1928 Cancer Therapy: Preclinical Clinical Cancer Research Ponatinib Shows Potent Antitumor Activity in Small Cell Carcinoma of the Ovary Hypercalcemic Type (SCCOHT) through Multikinase Inhibition Jessica D. Lang1,William P.D. Hendricks1, Krystal A. Orlando2, Hongwei Yin1, Jeffrey Kiefer1, Pilar Ramos1, Ritin Sharma3, Patrick Pirrotte3, Elizabeth A. Raupach1,3, Chris Sereduk1, Nanyun Tang1, Winnie S. Liang1, Megan Washington1, Salvatore J. Facista1, Victoria L. Zismann1, Emily M. Cousins4, Michael B. Major4, Yemin Wang5, Anthony N. Karnezis5, Aleksandar Sekulic1,6, Ralf Hass7, Barbara C. Vanderhyden8, Praveen Nair9, Bernard E. Weissman2, David G. Huntsman5,10, and Jeffrey M. Trent1 Abstract Purpose: Small cell carcinoma of the ovary, hypercalcemic type three SWI/SNF wild-type ovarian cancer cell lines. We further (SCCOHT) is a rare, aggressive ovarian cancer in young women identified ponatinib as the most effective clinically approved that is universally driven by loss of the SWI/SNF ATPase subunits RTK inhibitor. Reexpression of SMARCA4 was shown to confer SMARCA4 and SMARCA2. A great need exists for effective targeted a 1.7-fold increase in resistance to ponatinib. Subsequent therapies for SCCOHT. proteomic assessment of ponatinib target modulation in Experimental Design: To identify underlying therapeutic vul- SCCOHT cell models confirmed inhibition of nine known nerabilities in SCCOHT, we conducted high-throughput siRNA ponatinib target kinases alongside 77 noncanonical ponatinib and drug screens. Complementary proteomics approaches pro- targets in SCCOHT. Finally, ponatinib delayed tumor dou- filed kinases inhibited by ponatinib. Ponatinib was tested for bling time 4-fold in SCCOHT-1 xenografts while reducing efficacy in two patient-derived xenograft (PDX) models and one final tumor volumes in SCCOHT PDX models by 58.6% and cell-line xenograft model of SCCOHT. -
Chain Gene Induced by GM-CSF Β Receptor Regulation of Human High-Affinity Ige Molecular Mechanisms for Transcriptional
Molecular Mechanisms for Transcriptional Regulation of Human High-Affinity IgE Receptor β-Chain Gene Induced by GM-CSF This information is current as Kyoko Takahashi, Natsuko Hayashi, Shuichi Kaminogawa of September 23, 2021. and Chisei Ra J Immunol 2006; 177:4605-4611; ; doi: 10.4049/jimmunol.177.7.4605 http://www.jimmunol.org/content/177/7/4605 Downloaded from References This article cites 39 articles, 16 of which you can access for free at: http://www.jimmunol.org/content/177/7/4605.full#ref-list-1 http://www.jimmunol.org/ Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication by guest on September 23, 2021 *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2006 by The American Association of Immunologists All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. The Journal of Immunology Molecular Mechanisms for Transcriptional Regulation of Human High-Affinity IgE Receptor -Chain Gene Induced by GM-CSF1 Kyoko Takahashi,*† Natsuko Hayashi,*‡ Shuichi Kaminogawa,† and Chisei Ra2* The -chain of the high-affinity receptor for IgE (FcRI) plays an important role in regulating activation of FcRI-expressing cells such as mast cells in allergic reactions. -
PRKACA Mediates Resistance to HER2-Targeted Therapy in Breast Cancer Cells and Restores Anti-Apoptotic Signaling
Oncogene (2015) 34, 2061–2071 © 2015 Macmillan Publishers Limited All rights reserved 0950-9232/15 www.nature.com/onc ORIGINAL ARTICLE PRKACA mediates resistance to HER2-targeted therapy in breast cancer cells and restores anti-apoptotic signaling SE Moody1,2,3, AC Schinzel1, S Singh1, F Izzo1, MR Strickland1, L Luo1,2, SR Thomas3, JS Boehm3, SY Kim4, ZC Wang5,6 and WC Hahn1,2,3 Targeting HER2 with antibodies or small molecule inhibitors in HER2-positive breast cancer leads to improved survival, but resistance is a common clinical problem. To uncover novel mechanisms of resistance to anti-HER2 therapy in breast cancer, we performed a kinase open reading frame screen to identify genes that rescue HER2-amplified breast cancer cells from HER2 inhibition or suppression. In addition to multiple members of the MAPK (mitogen-activated protein kinase) and PI3K (phosphoinositide 3-kinase) signaling pathways, we discovered that expression of the survival kinases PRKACA and PIM1 rescued cells from anti-HER2 therapy. Furthermore, we observed elevated PRKACA expression in trastuzumab-resistant breast cancer samples, indicating that this pathway is activated in breast cancers that are clinically resistant to trastuzumab-containing therapy. We found that neither PRKACA nor PIM1 restored MAPK or PI3K activation after lapatinib or trastuzumab treatment, but rather inactivated the pro-apoptotic protein BAD, the BCl-2-associated death promoter, thereby permitting survival signaling through BCL- XL. Pharmacological blockade of BCL-XL/BCL-2 partially abrogated the rescue effects conferred by PRKACA and PIM1, and sensitized cells to lapatinib treatment. These observations suggest that combined targeting of HER2 and the BCL-XL/BCL-2 anti-apoptotic pathway may increase responses to anti-HER2 therapy in breast cancer and decrease the emergence of resistant disease. -
Pig Antibodies
Pig Antibodies gene_name sku Entry_Name Protein_Names Organism Length Identity CDX‐2 ARP31476_P050 D0V4H7_PIG Caudal type homeobox 2 (Fragment) Sus scrofa (Pig) 147 100.00% CDX‐2 ARP31476_P050 A7MAE3_PIG Caudal type homeobox transcription factor 2 (Fragment) Sus scrofa (Pig) 75 100.00% Tnnt3 ARP51286_P050 Q75NH3_PIG Troponin T fast skeletal muscle type Sus scrofa (Pig) 271 85.00% Tnnt3 ARP51286_P050 Q75NH2_PIG Troponin T fast skeletal muscle type Sus scrofa (Pig) 266 85.00% Tnnt3 ARP51286_P050 Q75NH1_PIG Troponin T fast skeletal muscle type Sus scrofa (Pig) 260 85.00% Tnnt3 ARP51286_P050 Q75NH0_PIG Troponin T fast skeletal muscle type Sus scrofa (Pig) 250 85.00% Tnnt3 ARP51286_P050 Q75NG8_PIG Troponin T fast skeletal muscle type Sus scrofa (Pig) 266 85.00% Tnnt3 ARP51286_P050 Q75NG7_PIG Troponin T fast skeletal muscle type Sus scrofa (Pig) 260 85.00% Tnnt3 ARP51286_P050 Q75NG6_PIG Troponin T fast skeletal muscle type Sus scrofa (Pig) 250 85.00% Tnnt3 ARP51286_P050 TNNT3_PIG Troponin T, fast skeletal muscle (TnTf) Sus scrofa (Pig) 271 85.00% ORF Names:PANDA_000462 EMBL EFB13877.1OrganismAiluropod High mobility group protein B2 (High mobility group protein a melanoleuca (Giant panda) ARP31939_P050 HMGB2_PIG 2) (HMG‐2) Sus scrofa (Pig) 210 100.00% Agpat5 ARP47429_P050 B8XTR3_PIG 1‐acylglycerol‐3‐phosphate O‐acyltransferase 5 Sus scrofa (Pig) 365 85.00% irf9 ARP31200_P050 Q29390_PIG Transcriptional regulator ISGF3 gamma subunit (Fragment) Sus scrofa (Pig) 57 100.00% irf9 ARP31200_P050 Q0GFA1_PIG Interferon regulatory factor 9 Sus scrofa (Pig) -
The Viral Oncoproteins Tax and HBZ Reprogram the Cellular Mrna Splicing Landscape
bioRxiv preprint doi: https://doi.org/10.1101/2021.01.18.427104; this version posted January 18, 2021. 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. The viral oncoproteins Tax and HBZ reprogram the cellular mRNA splicing landscape Charlotte Vandermeulen1,2,3, Tina O’Grady3, Bartimee Galvan3, Majid Cherkaoui1, Alice Desbuleux1,2,4,5, Georges Coppin1,2,4,5, Julien Olivet1,2,4,5, Lamya Ben Ameur6, Keisuke Kataoka7, Seishi Ogawa7, Marc Thiry8, Franck Mortreux6, Michael A. Calderwood2,4,5, David E. Hill2,4,5, Johan Van Weyenbergh9, Benoit Charloteaux2,4,5,10, Marc Vidal2,4*, Franck Dequiedt3*, and Jean-Claude Twizere1,2,11* 1Laboratory of Viral Interactomes, GIGA Institute, University of Liege, Liege, Belgium.2Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA.3Laboratory of Gene Expression and Cancer, GIGA Institute, University of Liege, Liege, Belgium.4Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA. 5Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA.6Laboratory of Biology and Modeling of the Cell, CNRS UMR 5239, INSERM U1210, University of Lyon, Lyon, France.7Department of Pathology and Tumor Biology, Kyoto University, Japan.8Unit of Cell and Tissue Biology, GIGA Institute, University of Liege, Liege, Belgium.9Laboratory of Clinical and Epidemiological Virology, Rega Institute for Medical Research, Department of Microbiology, Immunology and Transplantation, Catholic University of Leuven, Leuven, Belgium.10Department of Human Genetics, CHU of Liege, University of Liege, Liege, Belgium.11Lead Contact. *Correspondence: [email protected]; [email protected]; [email protected] bioRxiv preprint doi: https://doi.org/10.1101/2021.01.18.427104; this version posted January 18, 2021. -
Discovery and Systematic Characterization of Risk Variants and Genes For
medRxiv preprint doi: https://doi.org/10.1101/2021.05.24.21257377; this version posted June 2, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license . 1 Discovery and systematic characterization of risk variants and genes for 2 coronary artery disease in over a million participants 3 4 Krishna G Aragam1,2,3,4*, Tao Jiang5*, Anuj Goel6,7*, Stavroula Kanoni8*, Brooke N Wolford9*, 5 Elle M Weeks4, Minxian Wang3,4, George Hindy10, Wei Zhou4,11,12,9, Christopher Grace6,7, 6 Carolina Roselli3, Nicholas A Marston13, Frederick K Kamanu13, Ida Surakka14, Loreto Muñoz 7 Venegas15,16, Paul Sherliker17, Satoshi Koyama18, Kazuyoshi Ishigaki19, Bjørn O Åsvold20,21,22, 8 Michael R Brown23, Ben Brumpton20,21, Paul S de Vries23, Olga Giannakopoulou8, Panagiota 9 Giardoglou24, Daniel F Gudbjartsson25,26, Ulrich Güldener27, Syed M. Ijlal Haider15, Anna 10 Helgadottir25, Maysson Ibrahim28, Adnan Kastrati27,29, Thorsten Kessler27,29, Ling Li27, Lijiang 11 Ma30,31, Thomas Meitinger32,33,29, Sören Mucha15, Matthias Munz15, Federico Murgia28, Jonas B 12 Nielsen34,20, Markus M Nöthen35, Shichao Pang27, Tobias Reinberger15, Gudmar Thorleifsson25, 13 Moritz von Scheidt27,29, Jacob K Ulirsch4,11,36, EPIC-CVD Consortium, Biobank Japan, David O 14 Arnar25,37,38, Deepak S Atri39,3, Noël P Burtt4, Maria C Costanzo4, Jason Flannick40, Rajat M 15 Gupta39,3,4, Kaoru Ito18, Dong-Keun Jang4,