TWF2 (NM 007284) Human 3' UTR Clone – SC206178 | Origene

Total Page：16

File Type：pdf, Size：1020Kb

TWF2 (NM 007284) Human 3' UTR Clone – SC206178 | Origene

OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for SC206178 TWF2 (NM_007284) Human 3' UTR Clone Product data: Product Type: 3' UTR Clones Product Name: TWF2 (NM_007284) Human 3' UTR Clone Vector: pMirTarget (PS100062) Symbol: TWF2 Synonyms: A6r; A6RP; MSTP011; PTK9L ACCN: NM_007284 Insert Size: 452 bp Insert Sequence: >SC206178 3’UTR clone of NM_007284 The sequence shown below is from the reference sequence of NM_007284. The complete sequence of this clone may contain minor differences, such as SNPs. Blue=Stop Codon Red=Cloning site GGCAAGTTGGACGCCCGCAAGATCCGCGAGATTCTCATTAAGGCCAAGAAGGGCGGAAAGATCGCCGTG TAACAATTGGCAGAGCTCAGAATTCAAGCGATCGCC GGCCCGGGTGAAAATGGGGATGACAGCTAGGAGGCTGGAGCAGGGCCGGCCACGTGTGGACTGTGGGGC TGCCCACCTTCCGCTCCCTGCCACCATCCTCCTTCCTGGGCTCCAGGAAAGTGTTTCTGGGAGGTCAGG AGGGCTGGCAGCTGAACGCACTTGCAGCGTCCGAGGGCCACCGGGCTGGCATTTTGTGACCCTTCCCTG TTGCTGTCCCTGCATCTCGTCTGTGTGCCCAGGGTGTCCGGGGACCCTGCCTGGCTGGCTTAAGGGGGC TGGGTCAGGGGCCTGGCATGAACCTGGCCTCCCGGGGAGCTGAGACTAGGGTCCCAGCACAGCCCAGAA ACCTTTGGCCACAAGAAGTGGGGTCAGTCAGGGCTGGGGCAGGGGTCACTGCAGTTTGGGATGGTTGAA TGCTGTATTTTCTAAAGAATAAAATATTTTTAAATCAA ACGCGTAAGCGGCCGCGGCATCTAGATTCGAAGAAAATGACCGACCAAGCGACGCCCAACCTGCCATCA CGAGATTTCGATTCCACCGCCGCCTTCTATGAAAGG Restriction Sites: SgfI-MluI OTI Disclaimer: Our molecular clone sequence data has been matched to the sequence identifier above as a point of reference. Note that the complete sequence of this clone is largely the same as the reference sequence but may contain minor differences , e.g., single nucleotide polymorphisms (SNPs). RefSeq: NM_007284.4 Summary: The protein encoded by this gene was identified by its interaction with the catalytic domain of protein kinase C-zeta. The encoded protein contains an actin-binding site and an ATP-binding site. It is most closely related to twinfilin (PTK9), a conserved actin monomer-binding protein. [provided by RefSeq, Jul 2008] This product is to be used for laboratory only. Not for diagnostic or therapeutic use. View online » ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 1 / 2 TWF2 (NM_007284) Human 3' UTR Clone – SC206178 Locus ID: 11344 MW: 16.1 This product is to be used for laboratory only. Not for diagnostic or therapeutic use. ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 2 / 2.

Copy Link

Recommended publications

PARSANA-DISSERTATION-2020.Pdf
DECIPHERING TRANSCRIPTIONAL PATTERNS OF GENE REGULATION: A COMPUTATIONAL APPROACH by Princy Parsana A dissertation submitted to The Johns Hopkins University in conformity with the requirements for the degree of Doctor of Philosophy Baltimore, Maryland July, 2020 © 2020 Princy Parsana All rights reserved Abstract With rapid advancements in sequencing technology, we now have the ability to sequence the entire human genome, and to quantify expression of tens of thousands of genes from hundreds of individuals. This provides an extraordinary opportunity to learn phenotype relevant genomic patterns that can improve our understanding of molecular and cellular processes underlying a trait. The high dimensional nature of genomic data presents a range of computational and statistical challenges. This dissertation presents a compilation of projects that were driven by the motivation to efficiently capture gene regulatory patterns in the human transcriptome, while addressing statistical and computational challenges that accompany this data. We attempt to address two major difficulties in this domain: a) artifacts and noise in transcriptomic data, andb) limited statistical power. First, we present our work on investigating the effect of artifactual variation in gene expression data and its impact on trans-eQTL discovery. Here we performed an in-depth analysis of diverse pre-recorded covariates and latent confounders to understand their contribution to heterogeneity in gene expression measurements. Next, we discovered 673 trans-eQTLs across 16 human tissues using v6 data from the Genotype Tissue Expression (GTEx) project. Finally, we characterized two trait-associated trans-eQTLs; one in Skeletal Muscle and another in Thyroid. Second, we present a principal component based residualization method to correct gene expression measurements prior to reconstruction of co-expression networks.
[Show full text]
A Novel Mode of Capping Protein-Regulation by Twinfilin
Washington University School of Medicine Digital Commons@Becker Open Access Publications 10-23-2018 A novel mode of capping protein-regulation by Twinfilin Adam B. Johnston Denise M. Hilton Patrick McConnell Britney Johnson Meghan T. Harris See next page for additional authors Follow this and additional works at: https://digitalcommons.wustl.edu/open_access_pubs Authors Adam B. Johnston, Denise M. Hilton, Patrick McConnell, Britney Johnson, Meghan T. Harris, Avital Simone, Gaya K. Amarasinghe, John A. Cooper, and Bruce L. Goode RESEARCH ARTICLE A novel mode of capping protein- regulation by twinfilin Adam B Johnston1†, Denise M Hilton1†, Patrick McConnell2, Britney Johnson3, Meghan T Harris1, Avital Simone1, Gaya K Amarasinghe3, John A Cooper2, Bruce L Goode1* 1Department of Biology, Rosenstiel Basic Medical Science Research Center, Brandeis University, Waltham, United States; 2Department of Biochemistry and Molecular Biophysics, Washington University, St Louis, United states; 3Department of Pathology and Immunology, Washington University, St Louis, United States Abstract Cellular actin assembly is controlled at the barbed ends of actin filaments, where capping protein (CP) limits polymerization. Twinfilin is a conserved in vivo binding partner of CP, yet the significance of this interaction has remained a mystery. Here, we discover that the C-terminal tail of Twinfilin harbors a CP-interacting (CPI) motif, identifying it as a novel CPI-motif protein. Twinfilin and the CPI-motif protein CARMIL have overlapping binding sites on CP. Further, Twinfilin binds competitively with CARMIL to CP, protecting CP from barbed-end displacement by CARMIL. Twinfilin also accelerates dissociation of the CP inhibitor V-1, restoring CP to an active capping state.
[Show full text]
IDENTIFICATION and CHARACTERIZATION of ACTIN-REGULATORY PROTEINS in the HAIR CELL's CUTICULAR PLATE by LANA MARY POLLOCK Subm
IDENTIFICATION AND CHARACTERIZATION OF ACTIN-REGULATORY PROTEINS IN THE HAIR CELL’S CUTICULAR PLATE by LANA MARY POLLOCK Submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy Dissertation advisor: Brian M. McDermott Jr., Ph.D. Department of Genetics and Genome Sciences CASE WESTERN RESERVE UNIVERSITY January 2016 Case Western Reserve University School of Graduate Studies We, the thesis committee, hereby approve the thesis/dissertation of Lana Pollock, candidate for the degree of Doctor of Philosophy (PhD).* (signed)_________Zhenghe Wang, Ph.D._________________ (chair of committee) ___________Brian McDermott, Ph.D._______________ ___________ Hua Lou, Ph.D._____________________ ___________Stephen Maricich, Ph.D., M.D.___________ ___________Anthony Wynshaw-Boris, Ph.D., M.D._____ Date of defense_____September 8th, 2015_______________ *we also certify that written approval has been obtained for release of any proprietary material contained therein 2 This thesis is dedicated to Daniel Margevicius. Thank you for your unwavering love and support. Ačiū!! 3 Table of contents List of Tables ........................................................................................................ 7 List of Figures ....................................................................................................... 8 List of abbreviations ............................................................................................ 13 Abstract .............................................................................................................
[Show full text]
The Proximal End of Mouse Chromosome 17: New Molecular Markers Identify a Deletion Associatedwith Quaking"'"""
Copyright 0 1992 by the Genetics Societyof America The Proximal End of Mouse Chromosome 17: New Molecular Markers Identify a Deletion AssociatedWith quaking"'""" Thomas Ebersole, Okkyung Rho and KarenArtzt Department of Zoology, The University of Texas, Austin, Texas 78712-1064 Manuscript received November 4, 1991 Accepted for publication January10, 1992 ABSTRACT Five randomly identified cosmids have been mapped proximal to the Leh66D locus on mouse chromosome 17. Two of these cosmids, AulO and Aull9, map near the neurological mutationquaking. Au119 is deleted in qk-blt/qk~ab'cDNA, whereas AulO is not. Au76 maps to a gene-rich region near the Tme locus. The Au76 locus encodes a member of a low copy gene family expressed in embryos, the adult central nervous system and testis. A second member of this family has been mapped to chromosome 15 near c-sis (PDGF-B). At the centromeric end of chromosome 17, Au116 maps near the Tu1 locus, and along with Au217rs identifies a region of unusually high recombinational activity between t-haplotypes and wild-type chromosomes. Au217I and II map to the large inverted repeats found at the proximal end of the wild-type chromosome. In addition, the Au2171 and/or II loci encode testis transcripts not expressed from t-haplotypes. HE attention given the proximal third of mouse and classical recombination analysis, many markers T chromosome 17 derives, in large part, from the have been mapped into the proximal end. The distri- analysis of t-haplotypes, a variant form found in wild bution of markers is, however, quite variable. The populations of mice.
[Show full text]
Downloaded from Here
bioRxiv preprint doi: https://doi.org/10.1101/017566; this version posted November 19, 2015. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 1 1 Testing for ancient selection using cross-population allele 2 frequency differentiation 1;∗ 3 Fernando Racimo 4 1 Department of Integrative Biology, University of California, Berkeley, CA, USA 5 ∗ E-mail: [email protected] 6 1 Abstract 7 A powerful way to detect selection in a population is by modeling local allele frequency changes in a 8 particular region of the genome under scenarios of selection and neutrality, and finding which model is 9 most compatible with the data. Chen et al. [2010] developed a composite likelihood method called XP- 10 CLR that uses an outgroup population to detect departures from neutrality which could be compatible 11 with hard or soft sweeps, at linked sites near a beneficial allele. However, this method is most sensitive 12 to recent selection and may miss selective events that happened a long time ago. To overcome this, 13 we developed an extension of XP-CLR that jointly models the behavior of a selected allele in a three- 14 population tree. Our method - called 3P-CLR - outperforms XP-CLR when testing for selection that 15 occurred before two populations split from each other, and can distinguish between those events and 16 events that occurred specifically in each of the populations after the split.
[Show full text]
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.
[Show full text]
Human Social Genomics in the Multi-Ethnic Study of Atherosclerosis
Getting “Under the Skin”: Human Social Genomics in the Multi-Ethnic Study of Atherosclerosis by Kristen Monét Brown A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Epidemiological Science) in the University of Michigan 2017 Doctoral Committee: Professor Ana V. Diez-Roux, Co-Chair, Drexel University Professor Sharon R. Kardia, Co-Chair Professor Bhramar Mukherjee Assistant Professor Belinda Needham Assistant Professor Jennifer A. Smith © Kristen Monét Brown, 2017 [email protected] ORCID iD: 0000-0002-9955-0568 Dedication I dedicate this dissertation to my grandmother, Gertrude Delores Hampton. Nanny, no one wanted to see me become “Dr. Brown” more than you. I know that you are standing over the bannister of heaven smiling and beaming with pride. I love you more than my words could ever fully express. ii Acknowledgements First, I give honor to God, who is the head of my life. Truly, without Him, none of this would be possible. Countless times throughout this doctoral journey I have relied my favorite scripture, “And we know that all things work together for good, to them that love God, to them who are called according to His purpose (Romans 8:28).” Secondly, I acknowledge my parents, James and Marilyn Brown. From an early age, you two instilled in me the value of education and have been my biggest cheerleaders throughout my entire life. I thank you for your unconditional love, encouragement, sacrifices, and support. I would not be here today without you. I truly thank God that out of the all of the people in the world that He could have chosen to be my parents, that He chose the two of you.
[Show full text]
Co-Expression Network Analysis Identifies a Gene Signature As A
Zhu et al. Cancer Cell Int (2020) 20:259 https://doi.org/10.1186/s12935-020-01352-2 Cancer Cell International PRIMARY RESEARCH Open Access Co-expression network analysis identifes a gene signature as a predictive biomarker for energy metabolism in osteosarcoma Naiqiang Zhu1* , Jingyi Hou2, Guiyun Ma1, Shuai Guo1, Chengliang Zhao1 and Bin Chen1 Abstract Background: Osteosarcoma (OS) is a common malignant bone tumor originating in the interstitial tissues and occur- ring mostly in adolescents and young adults. Energy metabolism is a prerequisite for cancer cell growth, proliferation, invasion, and metastasis. However, the gene signatures associated with energy metabolism and their underlying molecular mechanisms that drive them are unknown. Methods: Energy metabolism-related genes were obtained from the TARGET database. We applied the “NFM” algo- rithm to classify putative signature gene into subtypes based on energy metabolism. Key genes related to progression were identifed by weighted co-expression network analysis (WGCNA). Based on least absolute shrinkage and selec- tion operator (LASSO) Cox proportional regression hazards model analyses, a gene signature for the predication of OS progression and prognosis was established. Robustness and estimation evaluations and comparison against other models were used to evaluate the prognostic performance of our model. Results: Two subtypes associated with energy metabolism was determined using the “NFM” algorithm, and signif- cant modules related to energy metabolism were identifed by WGCNA. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) suggested that the genes in the signifcant modules were enriched in kinase, immune metabolism processes, and metabolism-related pathways. We constructed a seven-gene signature consisting of SLC18B1, RBMXL1, DOK3, HS3ST2, ATP6V0D1, CCAR1, and C1QTNF1 to be used for OS progression and prognosis.
[Show full text]
Association of Germline Variation with the Survival of Women with BRCA1/2 Pathogenic Variants and Breast Cancer ✉ Taru A
www.nature.com/npjbcancer ARTICLE OPEN Association of germline variation with the survival of women with BRCA1/2 pathogenic variants and breast cancer ✉ Taru A. Muranen 1 ,Sofia Khan1,2, Rainer Fagerholm1, Kristiina Aittomäki3, Julie M. Cunningham 4, Joe Dennis 5, Goska Leslie 5, Lesley McGuffog5, Michael T. Parsons 6, Jacques Simard 7, Susan Slager8, Penny Soucy7, Douglas F. Easton 5,9, Marc Tischkowitz10,11, Amanda B. Spurdle 6, kConFab Investigators*, Rita K. Schmutzler12,13, Barbara Wappenschmidt12,13, Eric Hahnen12,13, Maartje J. Hooning14, HEBON Investigators*, Christian F. Singer15, Gabriel Wagner15, Mads Thomassen16, Inge Sokilde Pedersen 17,18, Susan M. Domchek19, Katherine L. Nathanson 19, Conxi Lazaro 20, Caroline Maria Rossing21, Irene L. Andrulis 22,23, Manuel R. Teixeira 24,25, Paul James 26,27, Judy Garber28, Jeffrey N. Weitzel 29, SWE-BRCA Investigators*, Anna Jakubowska 30,31, Drakoulis Yannoukakos 32, Esther M. John33, Melissa C. Southey34,35, Marjanka K. Schmidt 36,37, Antonis C. Antoniou5, Georgia Chenevix-Trench6, Carl Blomqvist38,39 and Heli Nevanlinna 1 Germline genetic variation has been suggested to influence the survival of breast cancer patients independently of tumor pathology. We have studied survival associations of genetic variants in two etiologically unique groups of breast cancer patients, the carriers of germline pathogenic variants in BRCA1 or BRCA2 genes. We found that rs57025206 was significantly associated with the overall survival, predicting higher mortality of BRCA1 carrier patients with estrogen receptor-negative breast cancer, with a hazard ratio 4.37 (95% confidence interval 3.03–6.30, P = 3.1 × 10−9). Multivariable analysis adjusted for tumor characteristics suggested that rs57025206 was an independent survival marker.
[Show full text]
Heat-Shock Factor 2 Is a Suppressor of Prostate Cancer Invasion
Oncogene (2016) 35, 1770–1784 OPEN © 2016 Macmillan Publishers Limited All rights reserved 0950-9232/16 www.nature.com/onc ORIGINAL ARTICLE Heat-shock factor 2 is a suppressor of prostate cancer invasion JK Björk1,2,4, M Åkerfelt1,2,4, J Joutsen1,3, MC Puustinen1,3, F Cheng1,3, L Sistonen1,3,4 and M Nees1,4 Heat-shock factors (HSFs) are key transcriptional regulators in cell survival. Although HSF1 has been identified as a driver of carcinogenesis, HSF2 has not been explored in malignancies. Here, we report that HSF2 suppresses tumor invasion of prostate cancer (PrCa). In three-dimensional organotypic cultures and the in vivo xenograft chorioallantoic membrane model HSF2 knockdown perturbs organoid differentiation and promotes invasiveness. Gene expression profiling together with functional studies demonstrated that the molecular mechanism underlying the effect on tumor progression originates from HSF2 steering the switch between acinar morphogenesis and invasion. This is achieved by the regulation of genes connected to, for example, GTPase activity, cell adhesion, extracellular matrix and actin cytoskeleton dynamics. Importantly, low HSF2 expression correlates with high Gleason score, metastasis and poor survival of PrCa patients, highlighting the clinical relevance of our findings. Finally, the study was expanded beyond PrCa, revealing that the expression of HSF2 is decreased in a wide range of cancer types. This study provides the first evidence for HSF2 acting as a suppressor of invasion in human malignancies. Oncogene (2016) 35, 1770–1784; doi:10.1038/onc.2015.241; published online 29 June 2015 INTRODUCTION HSF1 was highlighted in a cohort of breast cancer patients, Prostate cancer (PrCa) is the most commonly diagnosed male showing correlation between high HSF1 expression and 15 cancer in Western countries.1 Gleason grading, which is based on decreased survival.
[Show full text]
Hormone and Inhibitor Treatment T47DM Cells Were Used for All Experiments Unless Otherwise Stated
Extended Data Extended Materials Methods Cell culture; hormone and inhibitor treatment T47DM cells were used for all experiments unless otherwise stated. For hormone induction experiments, cells were grown in RPMI medium without Phenol Red, supplemented with 10% dextran-coated charcoal-treated FBS (DCC/FBS) after 24 h in serum-free conditions; cells were incubated with R5020 (10 nM) or vehicle (ethanol) as described (Vicent et al. 2011). For hormone induction experiments in MCF7 cells a similar procedure was performed; cells were grown in DMEM medium without Phenol Red, supplemented with 10% dextran-coated charcoal-treated FBS (DCC/FBS) after 24 h in serum-free conditions; cells were incubated with Estradiol (10 nM) or vehicle (ethanol). PARG and PARP inhibition were carried out via incubating cells with 5uM TA (tannic acid) or 10uM 3AB (3-amino-benzamide) respectively 1 hour prior to hormone treatment. All transfections were performed using Lipofectamine2000 (Invitrogen) according to manufacturers instructions. PAR-capture ELISA Hormone and or inhibitor treatments were carried out as described, and sample preparation was carried out as follows: At the required time point, cells were washed twice with ice-cold PBS and scraped in lysis buffer (0.4 M NaCl, 1% Triton X-100) plus protease inhibitors. Cell suspensions were then incubated for 30 min on ice with periodic vortexing. The disrupted cell suspension was centrifuged at 10,000g for 10 min at 4°C, and the supernatant was recovered, snap-frozen, and stored at 80°C until required. Ninety-six-well black-walled plates were incubated with 2 ng/mL anti-PAR monoclonal antibody (Trevigen) in 50 mM sodium carbonate (pH 7.6) overnight at 4°C.
[Show full text]
Coexpression Networks Based on Natural Variation in Human Gene Expression at Baseline and Under Stress
University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations Fall 2010 Coexpression Networks Based on Natural Variation in Human Gene Expression at Baseline and Under Stress Renuka Nayak University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Computational Biology Commons, and the Genomics Commons Recommended Citation Nayak, Renuka, "Coexpression Networks Based on Natural Variation in Human Gene Expression at Baseline and Under Stress" (2010). Publicly Accessible Penn Dissertations. 1559. https://repository.upenn.edu/edissertations/1559 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/1559 For more information, please contact [email protected]. Coexpression Networks Based on Natural Variation in Human Gene Expression at Baseline and Under Stress Abstract Genes interact in networks to orchestrate cellular processes. Here, we used coexpression networks based on natural variation in gene expression to study the functions and interactions of human genes. We asked how these networks change in response to stress. First, we studied human coexpression networks at baseline. We constructed networks by identifying correlations in expression levels of 8.9 million gene pairs in immortalized B cells from 295 individuals comprising three independent samples. The resulting networks allowed us to infer interactions between biological processes. We used the network to predict the functions of poorly-characterized human genes, and provided some experimental support. Examining genes implicated in disease, we found that IFIH1, a diabetes susceptibility gene, interacts with YES1, which affects glucose transport. Genes predisposing to the same diseases are clustered non-randomly in the network, suggesting that the network may be used to identify candidate genes that influence disease susceptibility.
[Show full text]