Characterization and Mapping of Human Genes Encoding Zinc Finger Proteins (Transcription/Chromosome/Sequence-Tagged Site) P
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Supplementary Data
Figure 2S 4 7 A - C 080125 CSCs 080418 CSCs - + IFN-a 48 h + IFN-a 48 h + IFN-a 72 h 6 + IFN-a 72 h 3 5 MRFI 4 2 3 2 1 1 0 0 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 7 B 13 080125 FBS - D 080418 FBS - + IFN-a 48 h 12 + IFN-a 48 h + IFN-a 72 h + IFN-a 72 h 6 080125 FBS 11 10 5 9 8 4 7 6 3 MRFI 5 4 2 3 2 1 1 0 0 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 Molecule Molecule FIGURE 4S FIGURE 5S Panel A Panel B FIGURE 6S A B C D Supplemental Results Table 1S. Modulation by IFN-α of APM in GBM CSC and FBS tumor cell lines. Molecule * Cell line IFN-α‡ HLA β2-m# HLA LMP TAP1 TAP2 class II A A HC§ 2 7 10 080125 CSCs - 1∞ (1) 3 (65) 2 (91) 1 (2) 6 (47) 2 (61) 1 (3) 1 (2) 1 (3) + 2 (81) 11 (80) 13 (99) 1 (3) 8 (88) 4 (91) 1 (2) 1 (3) 2 (68) 080125 FBS - 2 (81) 4 (63) 4 (83) 1 (3) 6 (80) 3 (67) 2 (86) 1 (3) 2 (75) + 2 (99) 14 (90) 7 (97) 5 (75) 7 (100) 6 (98) 2 (90) 1 (4) 3 (87) 080418 CSCs - 2 (51) 1 (1) 1 (3) 2 (47) 2 (83) 2 (54) 1 (4) 1 (2) 1 (3) + 2 (81) 3 (76) 5 (75) 2 (50) 2 (83) 3 (71) 1 (3) 2 (87) 1 (2) 080418 FBS - 1 (3) 3 (70) 2 (88) 1 (4) 3 (87) 2 (76) 1 (3) 1 (3) 1 (2) + 2 (78) 7 (98) 5 (99) 2 (94) 5 (100) 3 (100) 1 (4) 2 (100) 1 (2) 070104 CSCs - 1 (2) 1 (3) 1 (3) 2 (78) 1 (3) 1 (2) 1 (3) 1 (3) 1 (2) + 2 (98) 8 (100) 10 (88) 4 (89) 3 (98) 3 (94) 1 (4) 2 (86) 2 (79) * expression of APM molecules was evaluated by intracellular staining and cytofluorimetric analysis; ‡ cells were treatead or not (+/-) for 72 h with 1000 IU/ml of IFN-α; # β-2 microglobulin; § β-2 microglobulin-free HLA-A heavy chain; ∞ values are indicated as ratio between the mean of fluorescence intensity of cells stained with the selected mAb and that of the negative control; bold values indicate significant MRFI (≥ 2). -
Topological Scoring of Protein Interaction Networks
bioRxiv preprint doi: https://doi.org/10.1101/438408; this version posted October 8, 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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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. Topological Scoring of Protein Interaction Networks Mihaela E. Sardiu1, Joshua M. Gilmore1,2, Brad D. Groppe1,3, Arnob Dutta1,4, Laurence Florens1, and Michael P. Washburn1,5‡ 1Stowers Institute for Medical Research, Kansas City, MO 64110 U.S.A. 2Current Address: Boehringer Ingelheim Vetmedica, St. Joseph, MO 64506 U.S.A. 3Current Address: Thermo Fisher Scientific, Waltham, MA 02451, U.S.A. 4Current Address: Department of Cell and Molecular Biology, University of Rhode Island, 287 CBLS, 120 Flagg Road, Kingston, RI 02881. 5 Department of Pathology and Laboratory Medicine, The University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, Kansas 66160, USA ‡To whom correspondence should be addressed: Michael Washburn, Ph.D. Stowers Institute for Medical Research 1000 E. 50th St. Kansas City, MO 64110 Phone: 816-926-4457 E-mail: [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/438408; this version posted October 8, 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. Abstract It remains a significant challenge to define individual protein associations within networks where an individual protein can directly interact with other proteins and/or be part of large complexes, which contain functional modules. Here we demonstrate the topological scoring (TopS) algorithm for the analysis of quantitative proteomic analyses of affinity purifications. -
Genetic Causes of Severe Childhood Obesity: a Remarkably High Prevalence in an Inbred Population of Pakistan
1424 Diabetes Volume 69, July 2020 Genetic Causes of Severe Childhood Obesity: A Remarkably High Prevalence in an Inbred Population of Pakistan Sadia Saeed,1,2 Muhammad Arslan,3 Jaida Manzoor,4 Sadia M. Din,5 Qasim M. Janjua,5,6 Hina Ayesha,7 Qura-tul Ain,5 Laraib Inam,3 Stephane Lobbens,1 Emmanuel Vaillant,1 Emmanuelle Durand,1 Mehdi Derhourhi,1 Souhila Amanzougarene,1 Alaa Badreddine,1 Lionel Berberian,1 Stefan Gaget,1 Waqas I. Khan,8 Taeed A. Butt,9 Amélie Bonnefond,1,2 and Philippe Froguel1,2 Diabetes 2020;69:1424–1438 | https://doi.org/10.2337/db19-1238 Monogenic forms of obesity have been identified in £10% material in the quest of new genes/variants influencing of severely obese European patients. However, the overall energy balance. spectrum of deleterious variants (point mutations and structural variants) responsible for childhood severe obe- sity remains elusive. In this study, we genetically screened The monogenic forms of obesity have defined the current 225 severely obese children from consanguineous Pakis- concepts of the central regulation of energy balance and have tani families through a combination of techniques, includ- opened new avenues for precision medicine (1,2). Monogenic ing an in-house–developed augmented whole-exome nonsyndromic obesity is due to pathogenic mutations in sequencing method (CoDE-seq) that enables simultaneous genes involved in leptin-melanocortin signaling, resulting in detection of whole-exome copy number variations (CNVs) extreme, early-onset obesity with an insatiable craving for fi and point mutations in coding regions. We identi ed food (2). In addition to excessive adiposity, syndromic obesity OBESITY STUDIES 110 (49%) probands carrying 55 different pathogenic point associates with other abnormalities such as dysmorphic fea- mutations and CNVs in 13 genes/loci responsible for non- tures, intellectual disability, and organ-specific anomalies (3). -
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. -
Distinguishing Pleiotropy from Linked QTL Between Milk Production Traits
Cai et al. Genet Sel Evol (2020) 52:19 https://doi.org/10.1186/s12711-020-00538-6 Genetics Selection Evolution RESEARCH ARTICLE Open Access Distinguishing pleiotropy from linked QTL between milk production traits and mastitis resistance in Nordic Holstein cattle Zexi Cai1*†, Magdalena Dusza2†, Bernt Guldbrandtsen1, Mogens Sandø Lund1 and Goutam Sahana1 Abstract Background: Production and health traits are central in cattle breeding. Advances in next-generation sequencing technologies and genotype imputation have increased the resolution of gene mapping based on genome-wide association studies (GWAS). Thus, numerous candidate genes that afect milk yield, milk composition, and mastitis resistance in dairy cattle are reported in the literature. Efect-bearing variants often afect multiple traits. Because the detection of overlapping quantitative trait loci (QTL) regions from single-trait GWAS is too inaccurate and subjective, multi-trait analysis is a better approach to detect pleiotropic efects of variants in candidate genes. However, large sample sizes are required to achieve sufcient power. Multi-trait meta-analysis is one approach to deal with this prob- lem. Thus, we performed two multi-trait meta-analyses, one for three milk production traits (milk yield, protein yield and fat yield), and one for milk yield and mastitis resistance. Results: For highly correlated traits, the power to detect pleiotropy was increased by multi-trait meta-analysis com- pared with the subjective assessment of overlapping of single-trait QTL confdence intervals. Pleiotropic efects of lead single nucleotide polymorphisms (SNPs) that were detected from the multi-trait meta-analysis were confrmed by bivariate association analysis. The previously reported pleiotropic efects of variants within the DGAT1 and MGST1 genes on three milk production traits, and pleiotropic efects of variants in GHR on milk yield and fat yield were con- frmed. -
Mouse Lsm10 Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Lsm10 Knockout Project (CRISPR/Cas9) Objective: To create a Lsm10 knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Lsm10 gene (NCBI Reference Sequence: NM_138721 ; Ensembl: ENSMUSG00000050188 ) is located on Mouse chromosome 4. 2 exons are identified, with the ATG start codon in exon 2 and the TGA stop codon in exon 2 (Transcript: ENSMUST00000055575). Exon 2 will be selected as target site. Cas9 and gRNA will be co-injected into fertilized eggs for KO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Exon 2 starts from about 0.27% of the coding region. Exon 2 covers 100.0% of the coding region. The size of effective KO region: ~366 bp. The KO region does not have any other known gene. Page 1 of 8 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele 5' gRNA region gRNA region 3' 1 2 Legends Exon of mouse Lsm10 Knockout region Page 2 of 8 https://www.alphaknockout.com Overview of the Dot Plot (up) Window size: 15 bp Forward Reverse Complement Sequence 12 Note: The 2000 bp section upstream of start codon is aligned with itself to determine if there are tandem repeats. Tandem repeats are found in the dot plot matrix. The gRNA site is selected outside of these tandem repeats. Overview of the Dot Plot (down) Window size: 15 bp Forward Reverse Complement Sequence 12 Note: The 2000 bp section downstream of stop codon is aligned with itself to determine if there are tandem repeats. -
The Evolutionarily Conserved Kruppel-Associated Box Domain
Proc. Natl. Acad. Sci. USA Vol. 88, pp. 3608-3612, May 1991 Biochemistry The evolutionarily conserved Kruppel-associated box domain defines a subfamily of eukaryotic multifingered proteins (DNA-binding proteins/sequence conservation/ceil differentiation) ERIC J. BELLEFROID, DOMINIQUE A. PONCELET, PIERRE J. LECOCQ, OLIVIER REVELANT, AND JOSEPH A. MARTIAL Laboratoire de Biologie Moldculaire et de Genie G6ndtique, Universit6 de Liege, Institut de Chimie B6, B-4000 Sart Tilman, Belgium Communicated by William J. Rutter, January 2, 1991 ABSTRACT We have previously shown that the human number of finger proteins (20-23), is highly conserved in genome includes hundreds of genes coding for putative factors evolution and appears always associated with finger repeats. related to the Krfippel zinc-ringer protein, which regulates Drosophila segmentation. We report herein that about one- third of these genes code for proteins that share a very MATERIALS AND METHODS conserved region of about 75 amino acids in their N-terminal cDNA Library Screening. A human AgtlO cDNA library nonfinger portion. Homologous regions are found in a number from undifferentiated NT2D1 cells (24) was screened with a of previously described finger proteins, including mouse Zfp-l 546-base-pair EcoRI-EcoRI fragment corresponding to the 5' and Xenopus Xfin. We named this region the Kruppel- nonfinger portion of the coding region of HPF4 (where HPF associated box (KRAB). This domain has the potential to form is human placental finger) (19). The DNA probes were two amphipathic a-helices. Southern blot analysis of "zoo" labeled with a multiprimed labeling kit (Boehringer Mann- blots suggests that the Krfippel-associated box is highly con- heim) to a specific activity of5 x 101 cpm/pug. -
Noelia Díaz Blanco
Effects of environmental factors on the gonadal transcriptome of European sea bass (Dicentrarchus labrax), juvenile growth and sex ratios Noelia Díaz Blanco Ph.D. thesis 2014 Submitted in partial fulfillment of the requirements for the Ph.D. degree from the Universitat Pompeu Fabra (UPF). This work has been carried out at the Group of Biology of Reproduction (GBR), at the Department of Renewable Marine Resources of the Institute of Marine Sciences (ICM-CSIC). Thesis supervisor: Dr. Francesc Piferrer Professor d’Investigació Institut de Ciències del Mar (ICM-CSIC) i ii A mis padres A Xavi iii iv Acknowledgements This thesis has been made possible by the support of many people who in one way or another, many times unknowingly, gave me the strength to overcome this "long and winding road". First of all, I would like to thank my supervisor, Dr. Francesc Piferrer, for his patience, guidance and wise advice throughout all this Ph.D. experience. But above all, for the trust he placed on me almost seven years ago when he offered me the opportunity to be part of his team. Thanks also for teaching me how to question always everything, for sharing with me your enthusiasm for science and for giving me the opportunity of learning from you by participating in many projects, collaborations and scientific meetings. I am also thankful to my colleagues (former and present Group of Biology of Reproduction members) for your support and encouragement throughout this journey. To the “exGBRs”, thanks for helping me with my first steps into this world. Working as an undergrad with you Dr. -
WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT
(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization I International Bureau (10) International Publication Number (43) International Publication Date WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT (51) International Patent Classification: CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, C12Q 1/68 (2018.01) A61P 31/18 (2006.01) DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, C12Q 1/70 (2006.01) HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, (21) International Application Number: MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, PCT/US2018/056167 OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, (22) International Filing Date: SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, 16 October 2018 (16. 10.2018) TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. (25) Filing Language: English (84) Designated States (unless otherwise indicated, for every kind of regional protection available): ARIPO (BW, GH, (26) Publication Language: English GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, (30) Priority Data: UG, ZM, ZW), Eurasian (AM, AZ, BY, KG, KZ, RU, TJ, 62/573,025 16 October 2017 (16. 10.2017) US TM), European (AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, ΓΕ , IS, IT, LT, LU, LV, (71) Applicant: MASSACHUSETTS INSTITUTE OF MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TECHNOLOGY [US/US]; 77 Massachusetts Avenue, TR), OAPI (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, Cambridge, Massachusetts 02139 (US). -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
WO 2012/174282 A2 20 December 2012 (20.12.2012) P O P C T
(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization International Bureau (10) International Publication Number (43) International Publication Date WO 2012/174282 A2 20 December 2012 (20.12.2012) P O P C T (51) International Patent Classification: David [US/US]; 13539 N . 95th Way, Scottsdale, AZ C12Q 1/68 (2006.01) 85260 (US). (21) International Application Number: (74) Agent: AKHAVAN, Ramin; Caris Science, Inc., 6655 N . PCT/US20 12/0425 19 Macarthur Blvd., Irving, TX 75039 (US). (22) International Filing Date: (81) Designated States (unless otherwise indicated, for every 14 June 2012 (14.06.2012) kind of national protection available): AE, AG, AL, AM, AO, AT, AU, AZ, BA, BB, BG, BH, BR, BW, BY, BZ, English (25) Filing Language: CA, CH, CL, CN, CO, CR, CU, CZ, DE, DK, DM, DO, Publication Language: English DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IS, JP, KE, KG, KM, KN, KP, KR, (30) Priority Data: KZ, LA, LC, LK, LR, LS, LT, LU, LY, MA, MD, ME, 61/497,895 16 June 201 1 (16.06.201 1) US MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, 61/499,138 20 June 201 1 (20.06.201 1) US OM, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SC, SD, 61/501,680 27 June 201 1 (27.06.201 1) u s SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, TR, 61/506,019 8 July 201 1(08.07.201 1) u s TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. -
Whole Exome Sequencing Reveals NOTCH1 Mutations in Anaplastic Large Cell Lymphoma and Points to Notch Both As a Key Pathway and a Potential Therapeutic Target
Non-Hodgkin Lymphoma SUPPLEMENTARY APPENDIX Whole exome sequencing reveals NOTCH1 mutations in anaplastic large cell lymphoma and points to Notch both as a key pathway and a potential therapeutic target Hugo Larose, 1,2 Nina Prokoph, 1,2 Jamie D. Matthews, 1 Michaela Schlederer, 3 Sandra Högler, 4 Ali F. Alsulami, 5 Stephen P. Ducray, 1,2 Edem Nuglozeh, 6 Mohammad Feroze Fazaludeen, 7 Ahmed Elmouna, 6 Monica Ceccon, 2,8 Luca Mologni, 2,8 Carlo Gambacorti-Passerini, 2,8 Gerald Hoefler, 9 Cosimo Lobello, 2,10 Sarka Pospisilova, 2,10,11 Andrea Janikova, 2,11 Wilhelm Woessmann, 2,12 Christine Damm-Welk, 2,12 Martin Zimmermann, 13 Alina Fedorova, 14 Andrea Malone, 15 Owen Smith, 15 Mariusz Wasik, 2,16 Giorgio Inghirami, 17 Laurence Lamant, 18 Tom L. Blundell, 5 Wolfram Klapper, 19 Olaf Merkel, 2,3 G. A. Amos Burke, 20 Shahid Mian, 6 Ibraheem Ashankyty, 21 Lukas Kenner 2,3,22 and Suzanne D. Turner 1,2,10 1Department of Pathology, University of Cambridge, Cambridge, UK; 2European Research Initiative for ALK Related Malignancies (ERIA; www.ERIALCL.net ); 3Department of Pathology, Medical University of Vienna, Vienna, Austria; 4Unit of Laboratory Animal Pathology, Uni - versity of Veterinary Medicine Vienna, Vienna, Austria; 5Department of Biochemistry, University of Cambridge, Tennis Court Road, Cam - bridge, UK; 6Molecular Diagnostics and Personalised Therapeutics Unit, Colleges of Medicine and Applied Medical Sciences, University of Ha’il, Ha’il, Saudi Arabia; 7Neuroinflammation Research Group, Department of Neurobiology, A.I Virtanen Institute