Knock-down of ELMO1 in paediatric Rhabdomyosarcoma cells by nanoparticle mediated siRNA delivery by Huang, X, Townley, H

“…The ARMS subtype has higher rates of metastasis, as well as higher levels of ELMO1, which is thought to be involved in cell migration. …”

KAJIAN PENCEMARAN LINGKUNGAN PERAIRAN AKIBAT LIMBAH DOMESTIK DI DANAU SENTANI KABUPATEN JAYAPURA PROVINSI PAPUA (STUDI KASUS DI DESA YOKA DAN TANJUNG ELMO) by , GRACE ADELA DORA WAROY, S.Si., , Dr. Slamet Suprayogi, M.S.

Roosevelt Towers : a case study on environmental decision-making processes in a public housing project. by Ortiz, Elmo

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Permissioned blockchain for data provenance in the supply chain with fine grained data authorisation by Huang, Elmo Xuyun

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The Optimal Inventory Policy for Perishable Products under Packaging Postponement by Alfared, Elmo D., Esakki, Srinivasan

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Cold and hot gas distribution around the Milky-Way – M31 system in the HESTIA simulations by Damle, Mitali, Sparre, Martin, Richter, Philipp, Hani, Maan H, Nuza, Sebastián E, Pfrommer, Christoph, Grand, Robert JJ, Hoffman, Yehuda, Libeskind, Noam, Sorce, Jenny G, Steinmetz, Matthias, Tempel, Elmo, Vogelsberger, Mark, Wang, Peng

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The Hestia project: simulations of the Local Group by Libeskind, Noam I, Carlesi, Edoardo, Grand, Robert JJ, Khalatyan, Arman, Knebe, Alexander, Pakmor, Ruediger, Pilipenko, Sergey, Pawlowski, Marcel S, Sparre, Martin, Tempel, Elmo, Wang, Peng, Courtois, Hélène M, Gottlöber, Stefan, Hoffman, Yehuda, Minchev, Ivan, Pfrommer, Christoph, Sorce, Jenny G, Springel, Volker, Steinmetz, Matthias, Tully, R Brent, Vogelsberger, Mark, Yepes, Gustavo

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The over-expression of cell migratory genes in alveolar rhabdomyosarcoma could contribute to metastatic spread by Rapa, E, Hill, S, Morten, K, Potter, M, Mitchell, C

“…Over-expression of ELMO1 significantly increased cell invasion from 24.70 ± 7 % to 93 ± 5.4 % in primary myoblasts and from 29.43 ± 2.1 % to 87.33 ± 4.1 % in the ERMS cell line RD. siRNA knockout of ELMO1 in the ARMS cell line RH30 significantly reduced cell invasion from 88.2 ± 3.8 % to 35.2 ± 2.5 %. …”

The over-expression of cell migratory genes in alveolar rhabdomyosarcoma could contribute to metastatic spread. by Rapa, E, Hill, S, Morten, K, Potter, M, Mitchell, C

“…Over-expression of ELMO1 significantly increased cell invasion from 24.70 ± 7% to 93 ± 5.4% in primary myoblasts and from 29.43 ± 2.1% to 87.33 ± 4.1% in the ERMS cell line RD. siRNA knockout of ELMO1 in the ARMS cell line RH30 significantly reduced cell invasion from 88.2 ± 3.8% to 35.2 ± 2.5%. …”

Pre-training model based on the transfer learning in natural language processing by Tang, Jiayi

“…Then we horizontally compare BERT with ELMO and GPT; then vertically compare BERT with different parameters.…”
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The assessment of a number of different meso-porous silica nanoparticles for delivery of chemotherapeutics and siRNAs by Huang, X

“…</p> <p>A co-delivery system for LY294002 and ELMO1-targeted siRNA was established. Cell viability and ELMO1 expression were both suppressed after treatment with the co-delivery system.…”

Surveying and harnessing the genetic, (meta)genomic, and metabolic potential of the deep carbonated biosphere by Freedman, Adam Joshua Ehrich

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EUREC 4 A by Stevens, Bjorn, Bony, Sandrine, Farrell, David, Ament, Felix, Blyth, Alan, Fairall, Christopher, Karstensen, Johannes, Quinn, Patricia K., Speich, Sabrina, Acquistapace, Claudia, Aemisegger, Franziska, Albright, Anna Lea, Bellenger, Hugo, Bodenschatz, Eberhard, Caesar, Kathy-Ann, Chewitt-Lucas, Rebecca, de Boer, Gijs, Delanoë, Julien, Denby, Leif, Ewald, Florian, Fildier, Benjamin, Forde, Marvin, George, Geet, Gross, Silke, Hagen, Martin, Hausold, Andrea, Heywood, Karen J., Hirsch, Lutz, Jacob, Marek, Jansen, Friedhelm, Kinne, Stefan, Klocke, Daniel, Kölling, Tobias, Konow, Heike, Lothon, Marie, Mohr, Wiebke, Naumann, Ann Kristin, Nuijens, Louise, Olivier, Léa, Pincus, Robert, Pöhlker, Mira, Reverdin, Gilles, Roberts, Gregory, Schnitt, Sabrina, Schulz, Hauke, Siebesma, A. Pier, Stephan, Claudia Christine, Sullivan, Peter, Touzé-Peiffer, Ludovic, Vial, Jessica, Vogel, Raphaela, Zuidema, Paquita, Alexander, Nicola, Alves, Lyndon, Arixi, Sophian, Asmath, Hamish, Bagheri, Gholamhossein, Baier, Katharina, Bailey, Adriana, Baranowski, Dariusz, Baron, Alexandre, Barrau, Sébastien, Barrett, Paul A., Batier, Frédéric, Behrendt, Andreas, Bendinger, Arne, Beucher, Florent, Bigorre, Sebastien, Blades, Edmund, Blossey, Peter, Bock, Olivier, Böing, Steven, Bosser, Pierre, Bourras, Denis, Bouruet-Aubertot, Pascale, Bower, Keith, Branellec, Pierre, Branger, Hubert, Brennek, Michal, Brewer, Alan, Brilouet, Pierre-Etienne, Brügmann, Björn, Buehler, Stefan A., Burke, Elmo, Burton, Ralph, Calmer, Radiance, Canonici, Jean-Christophe, Carton, Xavier, Cato Jr., Gregory, Charles, Jude Andre, Chazette, Patrick, Chen, Yanxu, Chilinski, Michal T., Choularton, Thomas, Chuang, Patrick, Clarke, Shamal, Coe, Hugh, Cornet, Céline, Coutris, Pierre, Couvreux, Fleur, Crewell, Susanne, Cronin, Timothy, Cui, Zhiqiang, Cuypers, Yannis, Daley, Alton, Damerell, Gillian M., Dauhut, Thibaut, Deneke, Hartwig, Desbios, Jean-Philippe, Dörner, Steffen, Donner, Sebastian, Douet, Vincent, Drushka, Kyla, Dütsch, Marina, Ehrlich, André, Emanuel, Kerry, Emmanouilidis, Alexandros, Etienne, Jean-Claude, Etienne-Leblanc, Sheryl, Faure, Ghislain, Feingold, Graham, Ferrero, Luca, Fix, Andreas, Flamant, Cyrille, Flatau, Piotr Jacek, Foltz, Gregory R., Forster, Linda, Furtuna, Iulian, Gadian, Alan, Galewsky, Joseph, Gallagher, Martin, Gallimore, Peter, Gaston, Cassandra, Gentemann, Chelle, Geyskens, Nicolas, Giez, Andreas, Gollop, John, Gouirand, Isabelle, Gourbeyre, Christophe, de Graaf, Dörte, de Groot, Geiske E., Grosz, Robert, Güttler, Johannes, Gutleben, Manuel, Hall, Kashawn, Harris, George, Helfer, Kevin C., Henze, Dean, Herbert, Calvert, Holanda, Bruna, Ibanez-Landeta, Antonio, Intrieri, Janet, Iyer, Suneil, Julien, Fabrice, Kalesse, Heike, Kazil, Jan, Kellman, Alexander, Kidane, Abiel T., Kirchner, Ulrike, Klingebiel, Marcus, Körner, Mareike, Kremper, Leslie Ann, Kretzschmar, Jan, Krüger, Ovid, Kumala, Wojciech, Kurz, Armin, L'Hégaret, Pierre, Labaste, Matthieu, Lachlan-Cope, Tom, Laing, Arlene, Landschützer, Peter, Lang, Theresa, Lange, Diego, Lange, Ingo, Laplace, Clément, Lavik, Gauke, Laxenaire, Rémi, Le Bihan, Caroline, Leandro, Mason, Lefevre, Nathalie, Lena, Marius, Lenschow, Donald, Li, Qiang, Lloyd, Gary, Los, Sebastian, Losi, Niccolò, Lovell, Oscar, Luneau, Christopher, Makuch, Przemyslaw, Malinowski, Szymon, Manta, Gaston, Marinou, Eleni, Marsden, Nicholas, Masson, Sebastien, Maury, Nicolas, Mayer, Bernhard, Mayers-Als, Margarette, Mazel, Christophe, McGeary, Wayne, McWilliams, James C., Mech, Mario, Mehlmann, Melina, Meroni, Agostino Niyonkuru, Mieslinger, Theresa, Minikin, Andreas, Minnett, Peter, Möller, Gregor, Morfa Avalos, Yanmichel, Muller, Caroline, Musat, Ionela, Napoli, Anna, Neuberger, Almuth, Noisel, Christophe, Noone, David, Nordsiek, Freja, Nowak, Jakub L., Oswald, Lothar, Parker, Douglas J., Peck, Carolyn, Person, Renaud, Philippi, Miriam, Plueddemann, Albert, Pöhlker, Christopher, Pörtge, Veronika, Pöschl, Ulrich, Pologne, Lawrence, Posyniak, Michał, Prange, Marc, Quiñones Meléndez, Estefanía, Radtke, Jule, Ramage, Karim, Reimann, Jens, Renault, Lionel, Reus, Klaus, Reyes, Ashford, Ribbe, Joachim, Ringel, Maximilian, Ritschel, Markus, Rocha, Cesar B., Rochetin, Nicolas, Röttenbacher, Johannes, Rollo, Callum, Royer, Haley, Sadoulet, Pauline, Saffin, Leo, Sandiford, Sanola, Sandu, Irina, Schäfer, Michael, Schemann, Vera, Schirmacher, Imke, Schlenczek, Oliver, Schmidt, Jerome, Schröder, Marcel, Schwarzenboeck, Alfons, Sealy, Andrea, Senff, Christoph J., Serikov, Ilya, Shohan, Samkeyat, Siddle, Elizabeth, Smirnov, Alexander, Späth, Florian, Spooner, Branden, Stolla, M. Katharina, Szkółka, Wojciech, de Szoeke, Simon P., Tarot, Stéphane, Tetoni, Eleni, Thompson, Elizabeth, Thomson, Jim, Tomassini, Lorenzo, Totems, Julien, Ubele, Alma Anna, Villiger, Leonie, von Arx, Jan, Wagner, Thomas, Walther, Andi, Webber, Ben, Wendisch, Manfred, Whitehall, Shanice, Wiltshire, Anton, Wing, Allison A., Wirth, Martin, Wiskandt, Jonathan, Wolf, Kevin, Worbes, Ludwig, Wright, Ethan, Wulfmeyer, Volker, Young, Shanea, Zhang, Chidong, Zhang, Dongxiao, Ziemen, Florian, Zinner, Tobias, Zöger, Martin

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Emotion Detection on Indonesian Tweets Using CNN and Contextualized Word Embedding by Heldiansyah, Muhammad Fikri, Winarko, Edi

“…The models are based on Convolutional Neural Network (CNN) combined with ELMo (Embedding from Language Models, BERT (Bidirectional Encoder Representations from Transformers), or Word2Vec. …”
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Exome and whole-genome sequencing of esophageal adenocarcinoma identifies recurrent driver events and mutational complexity by Lander, Eric Steven

“…The new significantly mutated genes include chromatin-modifying factors and candidate contributors SPG20, TLR4, ELMO1 and DOCK2. Functional analyses of EAC-derived mutations in ELMO1 identifies increased cellular invasion. …”
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Shedding light on the enigmatic extinct insect order Glosselytrodea: new diversity and key morphological insights into non‐tegmenized Permian forms by Perez-De-La Fuente, R, Nel, A, Poschmann, MJ

“…A new, complete P. villosa specimen from Elmo preserves body structures hitherto not reported among glosselytrodeans, including complex pretarsal claws and detailed male genitalia. …”

Microbial potential for carbon and nutrient cycling in a geogenic supercritical carbon dioxide reservoir by Tan, BoonFei, Freedman, Adam Joshua Ehrich, Thompson, Janelle Renee

“…We sampled subsurface fluids from scCO₂-water separators at a natural scCO₂ reservoir at McElmo Dome, Colorado for analysis of 16S rRNA gene diversity and metagenome content. …”
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TFIDF meets deep document representation : a re-visit of co-training for text classification by Chen, Zhiwei

“…In this paper, we conduct exper- iments to evaluate the effectiveness of co-training with different combina- tions of document representations (e.g., TFIDF, Doc2vec, ELMo, BERT) and classifiers (e.g., SVM, Random Forest, XGBoost, MLP, and CNN) on two benchmark datasets (20 Newsgroup and Ohsumed). …”
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ntuer at SemEval-2019 Task 3 : Emotion classification with word and sentence representations in RCNN by Zhong, Peixiang, Miao, Chunyan

“…We also explored several other competitive pre-trained word and sentence representations including ELMo, BERT and InferSent but found inferior performance. …”
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Analysis of genetic polymorphism as risk factor of diabetes nephropathy among type 2 diabetic patients of a tertiary hospital by Yahya, Mohd Jokha

“…These nine genes were selected based on their function in the development of nephropathy in T2DM. IL8, CCR5, CCL2 ELMO1 are related to pro-inflammatory effect while CNDP1, NOS3, MnSOD are related to oxidative stress. …”
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