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Book ; Online: Macroeconomic Modelling of R&D and Innovation Policies

Akcigit, Ufuk / Benedetti Fasil, Cristiana / Impullitti, Giammario / Licandro, Omar / Sanchez-Martinez, Miguel

2022

Keywords	Economic growth ; Macroeconomics ; Research & development management ; R&D ; Innovation policy ; Macroeconomic modelling ; Endogenous technological progress ; Endogenous growth theory ; Economic growth challenges ; Open Access
Size	1 electronic resource (212 pages)
Publisher	Springer Nature
Document type	Book ; Online
Note	English ; Open Access
HBZ-ID	HT021229763
ISBN	9783030714574 ; 3030714578
Database	ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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Article ; Online: Measurement of the Ratios of Branching Fractions R(D^{*}) and R(D^{0}).

Aaij, R / Abdelmotteleb, A S W / Abellan Beteta, C / Abudinén, F / Ackernley, T / Adeva, B / Adinolfi, M / Adlarson, P / Afsharnia, H / Agapopoulou, C / Aidala, C A / Ajaltouni, Z / Akar, S / Akiba, K / Albicocco, P / Albrecht, J / Alessio, F / Alexander, M / Alfonso Albero, A /

Aliouche, Z / Alvarez Cartelle, P / Amalric, R / Amato, S / Amey, J L / Amhis, Y / An, L / Anderlini, L / Andersson, M / Andreianov, A / Andreotti, M / Andreou, D / Ao, D / Archilli, F / Artamonov, A / Artuso, M / Aslanides, E / Atzeni, M / Audurier, B / Bachiller Perea, I B / Bachmann, S / Bachmayer, M / Back, J J / Bailly-Reyre, A / Baladron Rodriguez, P / Balagura, V / Baldini, W / Baptista de Souza Leite, J / Barbetti, M / Barlow, R J / Barsuk, S / Barter, W / Bartolini, M / Baryshnikov, F / Basels, J M / Bassi, G / Batsukh, B / Battig, A / Bay, A / Beck, A / Becker, M / Bedeschi, F / Bediaga, I B / Beiter, A / Belin, S / Bellee, V / Belous, K / Belov, I / Belyaev, I / Benane, G / Bencivenni, G / Ben-Haim, E / Berezhnoy, A / Bernet, R / Bernet Andres, S / Berninghoff, D / Bernstein, H C / Bertella, C / Bertolin, A / Betancourt, C / Betti, F / Bezshyiko, Ia / Bhasin, S / Bhom, J / Bian, L / Bieker, M S / Biesuz, N V / Billoir, P / Biolchini, A / Birch, M / Bishop, F C R / Bitadze, A / Bizzeti, A / Blago, M P / Blake, T / Blanc, F / Blank, J E / Blusk, S / Bobulska, D / Boelhauve, J A / Boente Garcia, O / Boettcher, T / Boldyrev, A / Bolognani, C S / Bolzonella, R / Bondar, N / Borgato, F / Borghi, S / Borsato, M / Borsuk, J T / Bouchiba, S A / Bowcock, T J V / Boyer, A / Bozzi, C / Bradley, M J / Braun, S / Brea Rodriguez, A / Brodzicka, J / Brossa Gonzalo, A / Brown, J / Brundu, D / Buonaura, A / Buonincontri, L / Burke, A T / Burr, C / Bursche, A / Butkevich, A / Butter, J S / Buytaert, J / Byczynski, W / Cadeddu, S / Cai, H / Calabrese, R / Calefice, L / Cali, S / Calvi, M / Calvo Gomez, M / Campana, P / Campora Perez, D H / Campoverde Quezada, A F / Capelli, S / Capriotti, L / Carbone, A / Cardinale, R / Cardini, A / Carniti, P / Carus, L / Casais Vidal, A / Caspary, R / Casse, G / Cattaneo, M / Cavallero, G / Cavallini, V / Celani, S / Cerasoli, J / Cervenkov, D / Chadwick, A J / Chahrour, I / Chapman, M G / Charles, M / Charpentier, Ph / Chavez Barajas, C A / Chefdeville, M / Chen, C / Chen, S / Chernov, A / Chernyshenko, S / Chobanova, V / Cholak, S / Chrzaszcz, M / Chubykin, A / Chulikov, V / Ciambrone, P / Cicala, M F / Cid Vidal, X / Ciezarek, G / Cifra, P / Ciullo, G / Clarke, P E L / Clemencic, M / Cliff, H V / Closier, J / Cobbledick, J L / Coco, V / Coelho, J A B / Cogan, J / Cogneras, E / Cojocariu, L / Collins, P / Colombo, T / Congedo, L / Contu, A / Cooke, N / Corredoira, I / Corti, G / Couturier, B / Craik, D C / Cruz Torres, M / Currie, R / Da Silva, C L / Dadabaev, S / Dai, L / Dai, X / Dall'Occo, E / Dalseno, J / D'Ambrosio, C / Daniel, J / Danilina, A / d'Argent, P / Davies, J E / Davis, A / De Aguiar Francisco, O / de Boer, J / De Bruyn, K / De Capua, S / De Cian, M / De Freitas Carneiro Da Graca, U / De Lucia, E / De Miranda, J M / De Paula, L / De Serio, M / De Simone, D / De Simone, P / De Vellis, F / de Vries, J A / Dean, C T / Debernardis, F / Decamp, D / Dedu, V / Del Buono, L / Delaney, B / Dembinski, H-P / Denysenko, V / Deschamps, O / Dettori, F / Dey, B / Di Nezza, P / Diachkov, I / Didenko, S / Dieste Maronas, L / Ding, S / Dobishuk, V / Dolmatov, A / Dong, C / Donohoe, A M / Dordei, F / Dos Reis, A C / Douglas, L / Downes, A G / Duda, P / Dudek, M W / Dufour, L / Duk, V / Durante, P / Duras, M M / Durham, J M / Dutta, D / Dziurda, A / Dzyuba, A / Easo, S / Egede, U / Egorychev, V / Eirea Orro, C / Eisenhardt, S / Ejopu, E / Ek-In, S / Eklund, L / Elashri, M E / Ellbracht, J / Ely, S / Ene, A / Epple, E / Escher, S / Eschle, J / Esen, S / Evans, T / Fabiano, F / Falcao, L N / Fan, Y / Fang, B / Fantini, L / Faria, M / Farry, S / Fazzini, D / Felkowski, L F / Feo, M / Fernandez Gomez, M / Fernez, A D / Ferrari, F / Ferreira Lopes, L / Ferreira Rodrigues, F / Ferreres Sole, S / Ferrillo, M / Ferro-Luzzi, M / Filippov, S / Fini, R A / Fiorini, M / Firlej, M / Fischer, K M / Fitzgerald, D S / Fitzpatrick, C / Fiutowski, T / Fleuret, F / Fontana, M / Fontanelli, F / Forty, R / Foulds-Holt, D / Franco Lima, V / Franco Sevilla, M / Frank, M / Franzoso, E / Frau, G / Frei, C / Friday, D A / Frontini, L / Fu, J / Fuehring, Q / Fulghesu, T / Gabriel, E / Galati, G / Galati, M D / Gallas Torreira, A / Galli, D / Gambetta, S / Gandelman, M / Gandini, P / Gao, Y / Garau, M / Garcia Martin, L M / Garcia Moreno, P / García Pardiñas, J / Garcia Plana, B / Garcia Rosales, F A / Garrido, L / Gaspar, C / Geertsema, R E / Gerick, D / Gerken, L L / Gersabeck, E / Gersabeck, M / Gershon, T / Giambastiani, L / Gibson, V / Giemza, H K / Gilman, A L / Giovannetti, M / Gioventù, A / Gironella Gironell, P / Giugliano, C / Giza, M A / Gizdov, K / Gkougkousis, E L / Gligorov, V V / Göbel, C / Golobardes, E / Golubkov, D / Golutvin, A / Gomes, A / Gomez Fernandez, S / Goncalves Abrantes, F / Goncerz, M / Gong, G / Gorelov, I V / Gotti, C / Grabowski, J P / Grammatico, T / Granado Cardoso, L A / Graugés, E / Graverini, E / Graziani, G / Grecu, A T / Greeven, L M / Grieser, N A / Grillo, L / Gromov, S / Gruberg Cazon, B R / Gu, C / Guarise, M / Guittiere, M / Günther, P A / Gushchin, E / Guth, A / Guz, Y / Gys, T / Hadavizadeh, T / Hadjivasiliou, C / Haefeli, G / Haen, C / Haimberger, J / Haines, S C / Halewood-Leagas, T / Halvorsen, M M / Hamilton, P M / Hammerich, J / Han, Q / Han, X / Hansen, E B / Hansmann-Menzemer, S / Hao, L / Harnew, N / Harrison, T / Hasse, C / Hatch, M / He, J / Heijhoff, K / Hemmer, F H / Henderson, C / Henderson, R D L / Hennequin, A M / Hennessy, K / Henry, L / Herd, J / Heuel, J / Hicheur, A / Hill, D / Hilton, M / Hollitt, S E / Horswill, J / Hou, R / Hou, Y / Hu, J / Hu, W / Hu, X / Huang, W / Huang, X / Hulsbergen, W / Hunter, R J / Hushchyn, M / Hutchcroft, D / Ibis, P / Idzik, M / Ilin, D / Ilten, P / Inglessi, A / Iniukhin, A / Ishteev, A / Ivshin, K / Jacobsson, R / Jage, H / Jaimes Elles, S J / Jakobsen, S / Jans, E / Jashal, B K / Jawahery, A / Jevtic, V / Jiang, E / Jiang, X / Jiang, Y / John, M / Johnson, D / Jones, C R / Jones, T P / Jost, B / Jurik, N / Juszczak, I / Kandybei, S / Kang, Y / Karacson, M / Karpenkov, D / Karpov, M / Kautz, J W / Keizer, F / Keller, D M / Kenzie, M / Ketel, T / Khanji, B / Kharisova, A / Kholodenko, S / Khreich, G / Kirn, T / Kirsebom, V S / Kitouni, O / Klaver, S / Kleijne, N / Klimaszewski, K / Kmiec, M R / Koliiev, S / Kolk, L / Kondybayeva, A / Konoplyannikov, A / Kopciewicz, P / Kopecna, R / Koppenburg, P / Korolev, M / Kostiuk, I / Kot, O / Kotriakhova, S / Kozachuk, A / Kravchenko, P / Kravchuk, L / Krawczyk, R D / Kreps, M / Kretzschmar, S / Krokovny, P / Krupa, W / Krzemien, W / Kubat, J / Kubis, S / Kucewicz, W / Kucharczyk, M / Kudryavtsev, V / Kulikova, E K / Kupsc, A / Lacarrere, D / Lafferty, G / Lai, A / Lampis, A / Lancierini, D / Landesa Gomez, C / Lane, J J / Lane, R / Langenbruch, C / Langer, J / Lantwin, O / Latham, T / Lazzari, F / Lazzaroni, M / Le Gac, R / Lee, S H / Lefèvre, R / Leflat, A / Legotin, S / Lenisa, P / Leroy, O / Lesiak, T / Leverington, B / Li, A / Li, H / Li, K / Li, P / Li, P-R / Li, S / Li, T / Li, Y / Li, Z / Liang, X / Lin, C / Lin, T / Lindner, R / Lisovskyi, V / Litvinov, R / Liu, G / Liu, H / Liu, Q / Liu, S / Lobo Salvia, A / Loi, A / Lollini, R / Lomba Castro, J / Longstaff, I / Lopes, J H / Lopez Huertas, A / López Soliño, S / Lovell, G H / Lu, Y / Lucarelli, C / Lucchesi, D / Luchuk, S / Lucio Martinez, M / Lukashenko, V / Luo, Y / Lupato, A / Luppi, E / Lusiani, A / Lynch, K / Lyu, X-R / Ma, R / Maccolini, S / Machefert, F / Maciuc, F / Mackay, I / Macko, V / Madhan Mohan, L R / Maevskiy, A / Maisuzenko, D / Majewski, M W / Malczewski, J J / Malde, S / Malecki, B / Malinin, A / Maltsev, T / Manca, G / Mancinelli, G / Mancuso, C / Manera Escalero, R / Manuzzi, D / Manzari, C A / Marangotto, D / Marchand, J F / Marconi, U / Mariani, S / Marin Benito, C / Marks, J / Marshall, A M / Marshall, P J / Martelli, G / Martellotti, G / Martinazzoli, L / Martinelli, M / Martinez Santos, D / Martinez Vidal, F / Massafferri, A / Materok, M / Matev, R / Mathad, A / Matiunin, V / Matteuzzi, C / Mattioli, K R / Mauri, A / Maurice, E / Mauricio, J / Mazurek, M / McCann, M / Mcconnell, L / McGrath, T H / McHugh, N T / McNab, A / McNulty, R / Mead, J V / Meadows, B / Meier, G / Melnychuk, D / Meloni, S / Merk, M / Merli, A / Meyer Garcia, L / Miao, D / Mikhasenko, M / Milanes, D A / Millard, E / Milovanovic, M / Minard, M-N / Minotti, A / Miralles, T / Mitchell, S E / Mitreska, B / Mitzel, D S / Mödden, A / Mohammed, R A / Moise, R D / Mokhnenko, S / Mombächer, T / Monk, M / Monroy, I A / Monteil, S / Morello, G / Morello, M J / Morgenthaler, M P / Moron, J / Morris, A B / Morris, A G / Mountain, R / Mu, H / Muhammad, E / Muheim, F / Mulder, M / Müller, K / Murphy, C H / Murray, D / Murta, R / Muzzetto, P / Naik, P / Nakada, T / Nandakumar, R / Nanut, T / Nasteva, I / Needham, M / Neri, N / Neubert, S / Neufeld, N / Neustroev, P / Newcombe, R / Nicolini, J / Nicotra, D / Niel, E M / Nieswand, S / Nikitin, N / Nolte, N S / Normand, C / Novoa Fernandez, J / Nowak, G N / Nunez, C / Oblakowska-Mucha, A / Obraztsov, V / Oeser, T / Okamura, S / Oldeman, R / Oliva, F / Onderwater, C J G / O'Neil, R H / Otalora Goicochea, J M / Ovsiannikova, T / Owen, P / Oyanguren, A / Ozcelik, O / Padeken, K O / Pagare, B / Pais, P R / Pajero, T / Palano, A / Palutan, M / Pan, Y / Panshin, G / Paolucci, L / Papanestis, A / Pappagallo, M / Pappalardo, L L / Pappenheimer, C / Parker, W / Parkes, C / Passalacqua, B / Passaleva, G / Pastore, A / Patel, M / Patrignani, C / Pawley, C J / Pellegrino, A / Pepe Altarelli, M / Perazzini, S / Pereima, D / Pereiro Castro, A / Perret, P / Petridis, K / Petrolini, A / Petrov, A / Petrucci, S / Petruzzo, M / Pham, H / Philippov, A / Piandani, R / Pica, L / Piccini, M / Pietrzyk, B / Pietrzyk, G / Pili, M / Pinci, D / Pisani, F / Pizzichemi, M / Placinta, V / Plews, J / Plo Casasus, M / Polci, F / Poli Lener, M / Poluektov, A / Polukhina, N / Polyakov, I / Polycarpo, E / Ponce, S / Popov, D / Poslavskii, S / Prasanth, K / Promberger, L / Prouve, C / Pugatch, V / Puill, V / Punzi, G / Qi, H R / Qian, W / Qin, N / Qu, S / Quagliani, R / Raab, N V / Rachwal, B / Rademacker, J H / Rajagopalan, R / Rama, M / Ramos Pernas, M / Rangel, M S / Ratnikov, F / Raven, G / Rebollo De Miguel, M / Redi, F / Reich, J / Reiss, F / Remon Alepuz, C / Ren, Z / Resmi, P K / Ribatti, R / Ricci, A M / Ricciardi, S / Richardson, K / Richardson-Slipper, M / Rinnert, K / Robbe, P / Robertson, G / Rodrigues, A B / Rodrigues, E / Rodriguez Fernandez, E / Rodriguez Lopez, J A / Rodriguez Rodriguez, E / Rolf, D L / Rollings, A / Roloff, P / Romanovskiy, V / Romero Lamas, M / Romero Vidal, A / Roth, J D / Rotondo, M / Rudolph, M S / Ruf, T / Ruiz Fernandez, R A / Ruiz Vidal, J / Ryzhikov, A / Ryzka, J / Saborido Silva, J J / Sagidova, N / Sahoo, N / Saitta, B / Salomoni, M / Sanchez Gras, C / Sanderswood, I / Santacesaria, R / Santamarina Rios, C / Santimaria, M / Santovetti, E / Saranin, D / Sarpis, G / Sarpis, M / Sarti, A / Satriano, C / Satta, A / Saur, M / Savrina, D / Sazak, H / Scantlebury Smead, L G / Scarabotto, A / Schael, S / Scherl, S / Schiller, M / Schindler, H / Schmelling, M / Schmidt, B / Schmitt, S / Schneider, O / Schopper, A / Schubiger, M / Schulte, S / Schune, M H / Schwemmer, R / Sciascia, B / Sciuccati, A / Sellam, S / Semennikov, A / Senghi Soares, M / Sergi, A / Serra, N / Sestini, L / Seuthe, A / Shang, Y / Shangase, D M / Shapkin, M / Shchemerov, I / Shchutska, L / Shears, T / Shekhtman, L / Shen, Z / Sheng, S / Shevchenko, V / Shi, B / Shields, E B / Shimizu, Y / Shmanin, E / Shorkin, R / Shupperd, J D / Siddi, B G / Silva Coutinho, R / Simi, G / Simone, S / Singla, M / Skidmore, N / Skuza, R / Skwarnicki, T / Slater, M W / Smallwood, J C / Smeaton, J G / Smith, E / Smith, K / Smith, M / Snoch, A / Soares Lavra, L / Sokoloff, M D / Soler, F J P / Solomin, A / Solovev, A / Solovyev, I / Song, R / Souza De Almeida, F L / Souza De Paula, B / Spaan, B / Spadaro Norella, E / Spedicato, E / Spiridenkov, E / Spradlin, P / Sriskaran, V / Stagni, F / Stahl, M / Stahl, S / Stanislaus, S / Stein, E N / Steinkamp, O / Stenyakin, O / Stevens, H / Stone, S / Strekalina, D / Su, Y S / Suljik, F / Sun, J / Sun, L / Sun, Y / Svihra, P / Swallow, P N / Swientek, K / Szabelski, A / Szumlak, T / Szymanski, M / Tan, Y / Taneja, S / Tat, M D / Terentev, A / Teubert, F / Thomas, E / Thompson, D J D / Thomson, K A / Tilquin, H / Tisserand, V / T'Jampens, S / Tobin, M / Tomassetti, L / Tonani, G / Tong, X / Torres Machado, D / Tou, D Y / Trilov, S M / Trippl, C / Tuci, G / Tuning, N / Ukleja, A / Unverzagt, D J / Usachov, A / Ustyuzhanin, A / Uwer, U / Vagner, A / Vagnoni, V / Valassi, A / Valenti, G / Valls Canudas, N / Van Dijk, M / Van Hecke, H / van Herwijnen, E / Van Hulse, C B / van Veghel, M / Vazquez Gomez, R / Vazquez Regueiro, P / Vázquez Sierra, C / Vecchi, S / Velthuis, J J / Veltri, M / Venkateswaran, A / Veronesi, M / Vesterinen, M / Vieira, D / Vieites Diaz, M / Vilasis-Cardona, X / Vilella Figueras, E / Villa, A / Vincent, P / Volle, F C / Vom Bruch, D / Vorobyev, A / Vorobyev, V / Voropaev, N / Vos, K / Vrahas, C / Walsh, J / Walton, E J / Wan, G / Wang, C / Wang, G / Wang, J / Wang, M / Wang, R / Wang, X / Wang, Y / Wang, Z / Ward, J A / Watson, N K / Websdale, D / Wei, Y / Westhenry, B D C / White, D J / Whitehead, M / Wiederhold, A R / Wiedner, D / Wilkinson, G / Wilkinson, M K / Williams, I / Williams, M / Williams, M R J / Williams, R / Wilson, F F / Wislicki, W / Witek, M / Witola, L / Wong, C P / Wormser, G / Wotton, S A / Wu, H / Wu, J / Wyllie, K / Xiang, Z / Xie, Y / Xu, A / Xu, J / Xu, L / Xu, M / Xu, Q / Xu, Z / Yang, D / Yang, S / Yang, X / Yang, Y / Yang, Z / Yeomans, L E / Yeroshenko, V / Yeung, H / Yin, H / Yu, J / Yuan, X / Zaffaroni, E / Zavertyaev, M / Zdybal, M / Zeng, M / Zhang, C / Zhang, D / Zhang, L / Zhang, S / Zhang, Y / Zhao, Y / Zharkova, A / Zhelezov, A / Zheng, Y / Zhou, T / Zhou, X / Zhou, Y / Zhovkovska, V / Zhu, X / Zhu, Z / Zhukov, V / Zou, Q / Zucchelli, S / Zuliani, D / Zunica, G

Physical review letters

2023 Volume 131, Issue 11, Page(s) 111802

Abstract: The ratios of branching fractions R(D^{*})≡B(B[over ¯]→D^{*}τ^{-}ν[over ¯]_{τ})/B(B[over ¯]→D^{*}μ^ ... ν[over ¯]_{μ}) and R(D^{0})≡B(B^{-}→D^{0}τ^{-}ν[over ¯]_{τ})/B(B^{-}→D^{0}μ^{-}ν[over ¯]_{μ}) are ... is identified in the decay mode τ^{-}→μ^{-}ν_{τ}ν[over ¯]_{μ}. The measured values are R(D^{*})=0 ...

Abstract	The ratios of branching fractions R(D^{})≡B(B[over ¯]→D^{}τ^{-}ν[over ¯]_{τ})/B(B[over ¯]→D^{}μ^{-}ν[over ¯]_{μ}) and R(D^{0})≡B(B^{-}→D^{0}τ^{-}ν[over ¯]_{τ})/B(B^{-}→D^{0}μ^{-}ν[over ¯]_{μ}) are measured, assuming isospin symmetry, using a sample of proton-proton collision data corresponding to 3.0 fb^{-1} of integrated luminosity recorded by the LHCb experiment during 2011 and 2012. The tau lepton is identified in the decay mode τ^{-}→μ^{-}ν_{τ}ν[over ¯]_{μ}. The measured values are R(D^{})=0.281±0.018±0.024 and R(D^{0})=0.441±0.060±0.066, where the first uncertainty is statistical and the second is systematic. The correlation between these measurements is ρ=-0.43. The results are consistent with the current average of these quantities and are at a combined 1.9 standard deviations from the predictions based on lepton flavor universality in the standard model.
Language	English
Publishing date	2023-09-29
Publishing country	United States
Document type	Journal Article
ZDB-ID	208853-8
ISSN	1079-7114 ; 0031-9007
ISSN (online)	1079-7114
ISSN	0031-9007
DOI	10.1103/PhysRevLett.131.111802
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Article ; Online: Comparative efficacy and safety of tisagenlecleucel and axicabtagene ciloleucel among adults with r/r follicular lymphoma.

Dickinson, Michael / Martinez-Lopez, Joaquin / Jousseaume, Etienne / Yang, Hongbo / Chai, Xinglei / Xiang, Cheryl / Wang, Travis / Zhang, Jie / Ramos, Roberto / Schuster, Stephen J / Fowler, Nathan

Leukemia & lymphoma

2024 Volume 65, Issue 3, Page(s) 323–332

Abstract: ... with relapsed or refractory follicular lymphoma (r/r FL). This study used individual patient data from ELARA ... outcomes in r/r FL using matching-adjusted indirect comparison methods. After adjustment for baseline ...

Abstract	Regulatory approvals of tisagenlecleucel (tisa-cel) and axicabtagene ciloleucel (axi-cel) have established the feasibility of chimeric antigen receptor T-cell therapies for the treatment of adults with relapsed or refractory follicular lymphoma (r/r FL). This study used individual patient data from ELARA (tisa-cel) and aggregate published patient data from ZUMA-5 (axi-cel) to compare efficacy and safety outcomes in r/r FL using matching-adjusted indirect comparison methods. After adjustment for baseline differences in the trial populations, the results suggested that tisa-cel (
MeSH term(s)	Adult ; Humans ; Lymphoma, Follicular/therapy ; Immunotherapy, Adoptive/adverse effects ; Biological Products/adverse effects ; Cytokine Release Syndrome ; Lymphoma, Large B-Cell, Diffuse ; Antigens, CD19/adverse effects ; Receptors, Antigen, T-Cell
Chemical Substances	tisagenlecleucel (Q6C9WHR03O) ; axicabtagene ciloleucel (U2I8T43Y7R) ; Biological Products ; Antigens, CD19 ; Receptors, Antigen, T-Cell
Language	English
Publishing date	2024-01-05
Publishing country	United States
Document type	Journal Article
ZDB-ID	1042374-6
ISSN	1029-2403 ; 1042-8194
ISSN (online)	1029-2403
ISSN	1042-8194
DOI	10.1080/10428194.2023.2289854
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Book ; Online: The growclusters Package for R

Powers, Randall / Martinez, Wendy / Savitsky, Terrance

2023

Abstract: The growclusters package for R implements an enhanced version of k-means clustering that allows ... including the creation of R Shiny applications designed to visually illustrate the operation and ...

Abstract	The growclusters package for R implements an enhanced version of k-means clustering that allows discovery of local clusterings or partitions for a collection of data sets that each draw their cluster means from a single, global partition. The package contains functions to estimate a partition structure for multivariate data. Estimation is performed under a penalized optimization derived from Bayesian non-parametric formulations. This paper describes some of the functions and capabilities of the growclusters package, including the creation of R Shiny applications designed to visually illustrate the operation and functionality of the growclusters package. Comment: 10 pages, 6 figures, paper presented at 2022 Joint Statistical Meetings
Keywords	Computer Science - Mathematical Software ; Computer Science - Machine Learning ; I.5.3 ; I.3.8 ; J.0
Publishing date	2023-04-12
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Comparing R-Bendamustine vs. R-CHOP Plus Maintenance Therapy as First-Line Systemic Treatment in Follicular Lymphoma: A Multicenter Retrospective GELTAMO Study.

Bastos-Oreiro, Mariana / Gutierrez, Antonio / Cabero, Almudena / López, Javier / Villafuerte, Paola / Jiménez-Ubieto, Ana / de Oña, Raquel / De la Fuente, Adolfo / Navarro, Belén / Peñalver, Javier / Martínez, Pilar / Alonso, Carmen / Infante, María / Córdoba, Raúl / Perez-Montero, Blanca / Pérez de Oteyza, Jaime / González de Villambrosio, Sonia / Fernández-Caldas, Paula / Del Campo, Raquel /

García Belmonte, Daniel / Diaz-Gálvez, Javier / Salar, Antonio / Sancho, Juan-Manuel

Cancers

2024 Volume 16, Issue 7

Abstract: Rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) and R-bendamustine ... R-B) are the most common frontline treatment strategies for advanced-stage follicular lymphoma (FL ... After R-CHOP induction therapy, using rituximab for maintenance therapy notably improves outcomes ...

Abstract	Rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) and R-bendamustine (R-B) are the most common frontline treatment strategies for advanced-stage follicular lymphoma (FL). After R-CHOP induction therapy, using rituximab for maintenance therapy notably improves outcomes; however, whether this can be achieved by using the same approach after R-B therapy is still being determined. This retrospective analysis compared 476 FL patients from 17 GELTAMO centers who received R-based regimens followed by rituximab maintenance therapy for untreated advanced-stage FL. The complete response rate at the end of induction was higher with R-B and relapses were more frequent with R-CHOP. During induction, cytopenias were significantly more frequent with R-CHOP and so was the use of colony-stimulating factors. During maintenance therapy, R-B showed more neutropenia and infectious toxicity. After a median follow-up of 81 months (95% CI: 77-86), the 6-year rates of progression-free survival (PFS) were 79% (95% CI: 72-86) for R-bendamustine vs. 67% (95% CI: 61-73) for R-CHOP (
Language	English
Publishing date	2024-03-26
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2527080-1
ISSN	2072-6694
ISSN	2072-6694
DOI	10.3390/cancers16071285
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Article ; Online: SUMOylation controls Hu antigen R posttranscriptional activity in liver cancer.

Lachiondo-Ortega, Sofia / Rejano-Gordillo, Claudia M / Simon, Jorge / Lopitz-Otsoa, Fernando / C Delgado, Teresa / Mazan-Mamczarz, Krystyna / Goikoetxea-Usandizaga, Naroa / Zapata-Pavas, L Estefanía / García-Del Río, Ana / Guerra, Pietro / Peña-Sanfélix, Patricia / Hermán-Sánchez, Natalia / Al-Abdulla, Ruba / Fernandez-Rodríguez, Carmen / Azkargorta, Mikel / Velázquez-Cruz, Alejandro / Guyon, Joris / Martín, César / Zalamea, Juan Diego /

Egia-Mendikute, Leire / Sanz-Parra, Arantza / Serrano-Maciá, Marina / González-Recio, Irene / Gonzalez-Lopez, Monika / Martínez-Cruz, Luis Alfonso / Pontisso, Patrizia / Aransay, Ana M / Barrio, Rosa / Sutherland, James D / Abrescia, Nicola G A / Elortza, Félix / Lujambio, Amaia / Banales, Jesus M / Luque, Raúl M / Gahete, Manuel D / Palazón, Asís / Avila, Matias A / G Marin, Jose J / De, Supriyo / Daubon, Thomas / Díaz-Quintana, Antonio / Díaz-Moreno, Irene / Gorospe, Myriam / Rodríguez, Manuel S / Martínez-Chantar, María Luz

Cell reports

2024 Volume 43, Issue 3, Page(s) 113924

Abstract: ... is a key mechanism that regulates the function of the RNA-binding protein Hu antigen R (HuR), a hub ...

Abstract	The posttranslational modification of proteins critically influences many biological processes and is a key mechanism that regulates the function of the RNA-binding protein Hu antigen R (HuR), a hub in liver cancer. Here, we show that HuR is SUMOylated in the tumor sections of patients with hepatocellular carcinoma in contrast to the surrounding tissue, as well as in human cell line and mouse models of the disease. SUMOylation of HuR promotes major cancer hallmarks, namely proliferation and invasion, whereas the absence of HuR SUMOylation results in a senescent phenotype with dysfunctional mitochondria and endoplasmic reticulum. Mechanistically, SUMOylation induces a structural rearrangement of the RNA recognition motifs that modulates HuR binding affinity to its target RNAs, further modifying the transcriptomic profile toward hepatic tumor progression. Overall, SUMOylation constitutes a mechanism of HuR regulation that could be potentially exploited as a therapeutic strategy for liver cancer.
MeSH term(s)	Animals ; Humans ; Mice ; Carcinoma, Hepatocellular/metabolism ; Disease Models, Animal ; ELAV-Like Protein 1/metabolism ; Liver Neoplasms/pathology ; RNA/metabolism ; Sumoylation
Chemical Substances	ELAV-Like Protein 1 ; RNA (63231-63-0) ; Elavl1 protein, mouse ; ELAVL1 protein, human
Language	English
Publishing date	2024-03-18
Publishing country	United States
Document type	Journal Article
ZDB-ID	2649101-1
ISSN	2211-1247 ; 2211-1247
ISSN (online)	2211-1247
ISSN	2211-1247
DOI	10.1016/j.celrep.2024.113924
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Article ; Online: Fast Parabolic Fitting: An R-Peak Detection Algorithm for Wearable ECG Devices.

Félix, Ramón A / Ochoa-Brust, Alberto / Mata-López, Walter / Martínez-Peláez, Rafael / Mena, Luis J / Valdez-Velázquez, Laura L

Sensors (Basel, Switzerland)

2023 Volume 23, Issue 21

Abstract: ... intervals, specifically the R peaks. In this study, we introduce a novel algorithm designed for wearable ... which can inadvertently smooth the R peaks, making them more challenging to identify. We compared the algorithm's ...

Abstract	Heart diseases rank among the most fatal health concerns globally, with the majority being preventable through early diagnosis and effective treatment. Electrocardiogram (ECG) analysis is critical in detecting heart diseases, as it captures the heart's electrical activities. For continuous monitoring, wearable electrocardiographic devices must ensure user comfort over extended periods, typically 24 to 48 h. These devices demand specialized algorithms with low computational complexity to accommodate memory and power consumption constraints. One of the most crucial aspects of ECG signals is accurately detecting heartbeat intervals, specifically the R peaks. In this study, we introduce a novel algorithm designed for wearable devices, offering two primary attributes: robustness against noise and low computational complexity. Our algorithm entails fitting a least-squares parabola to the ECG signal and adaptively shaping it as it sweeps through the signal. Notably, our proposed algorithm eliminates the need for band-pass filters, which can inadvertently smooth the R peaks, making them more challenging to identify. We compared the algorithm's performance using two extensive databases: the meta-database QT database and the BIH-MIT database. Importantly, our method does not necessitate the precise localization of the ECG signal's isoelectric line, contributing to its low computational complexity. In the analysis of the QT database, our algorithm demonstrated a substantial advantage over the classical Pan-Tompkins algorithm and maintained competitiveness with state-of-the-art approaches. In the case of the BIH-MIT database, the performance results were more conservative; they continued to underscore the real-world utility of our algorithm in clinical contexts.
MeSH term(s)	Humans ; Signal Processing, Computer-Assisted ; Electrocardiography/methods ; Algorithms ; Heart Diseases ; Wearable Electronic Devices
Language	English
Publishing date	2023-10-28
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s23218796
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Article ; Online: The R in PRES.

Jiménez-Ruiz, Amado / García-Grimshaw, Miguel / Calderón-Martínez, Juan Andrés / Reyes-Melo, Isael

Cleveland Clinic journal of medicine

2020 Volume 87, Issue 10, Page(s) 584–585

MeSH term(s)	Humans ; Posterior Leukoencephalopathy Syndrome
Keywords	covid19
Language	English
Publishing date	2020-10-01
Publishing country	United States
Document type	Letter ; Comment
ZDB-ID	639116-3
ISSN	1939-2869 ; 0891-1150
ISSN (online)	1939-2869
ISSN	0891-1150
DOI	10.3949/ccjm.87c.10001
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Article: SLESIS-R: an improved score for prediction of serious infection in patients with systemic lupus erythematosus based on the RELESSER prospective cohort.

Rua-Figueroa, Iñigo / García de Yébenes, M Jesus / Martinez-Barrio, Julia / Galindo Izquierdo, Maria / Calvo Alén, Jaime / Fernandez-Nebro, Antonio / Menor-Almagro, Raúl / Carmona, Loreto / Tejera Segura, Beatriz / Tomero, Eva / Freire-González, Mercedes / Sangüesa, Clara / Horcada, Loreto / Blanco, Ricardo / Uriarte Itzazelaia, Esther / Narváez, Javier / Rosas Gómez de Salazar, José Carlos / Gómez-Sabater, Silvia / Morales, Claudia Moriano /

Andreu, Jose L / Segarra, Vicente Torrente / Aurrecoechea, Elena / Perez, Ana / Nóvoa Medina, Javier / Salgado, Eva / Lozano-Rivas, Nuria / Montilla, Carlos / Ruiz-Lucea, Esther / Arevalo, Marta / Iñiguez, Carlota / García-Villanueva, María Jesús / Exposito, Lorena / Ibáñez-Barceló, Mónica / Bonilla, Gema / Carrión-Barberà, Irene / Erausquin, Celia / Fragio Gil, Jorge Juan / Pecondón, Angela / Toyos, Francisco J / Cobo, Tatiana / Muñoz-Jiménez, Alejandro / Oller, Jose / Nolla, Joan M / Pego-Reigosa, J M

Lupus science & medicine

2024 Volume 11, Issue 1

Abstract: ... with systemic lupus erythematosus (SLE), namely, the SLE Severe Infection Score-Revised (SLESIS-R) and ... a positive likelihood ratio of 5.48.: Conclusions: SLESIS-R is an accurate and feasible instrument ... for predicting infections in patients with SLE. SLESIS-R could help to make informed decisions on the use ...

Abstract	Objective: To develop an improved score for prediction of severe infection in patients with systemic lupus erythematosus (SLE), namely, the SLE Severe Infection Score-Revised (SLESIS-R) and to validate it in a large multicentre lupus cohort. Methods: We used data from the prospective phase of RELESSER (RELESSER-PROS), the SLE register of the Spanish Society of Rheumatology. A multivariable logistic model was constructed taking into account the variables already forming the SLESIS score, plus all other potential predictors identified in a literature review. Performance was analysed using the C-statistic and the area under the receiver operating characteristic curve (AUROC). Internal validation was carried out using a 100-sample bootstrapping procedure. ORs were transformed into score items, and the AUROC was used to determine performance. Results: A total of 1459 patients who had completed 1 year of follow-up were included in the development cohort (mean age, 49±13 years; 90% women). Twenty-five (1.7%) had experienced ≥1 severe infection. According to the adjusted multivariate model, severe infection could be predicted from four variables: age (years) ≥60, previous SLE-related hospitalisation, previous serious infection and glucocorticoid dose. A score was built from the best model, taking values from 0 to 17. The AUROC was 0.861 (0.777-0.946). The cut-off chosen was ≥6, which exhibited an accuracy of 85.9% and a positive likelihood ratio of 5.48. Conclusions: SLESIS-R is an accurate and feasible instrument for predicting infections in patients with SLE. SLESIS-R could help to make informed decisions on the use of immunosuppressants and the implementation of preventive measures.
MeSH term(s)	Humans ; Female ; Adult ; Middle Aged ; Male ; Lupus Erythematosus, Systemic/complications ; Prospective Studies ; Immunosuppressive Agents ; Logistic Models
Chemical Substances	Immunosuppressive Agents
Language	English
Publishing date	2024-04-08
Publishing country	England
Document type	Review ; Journal Article
ZDB-ID	2779620-6
ISSN	2053-8790
ISSN	2053-8790
DOI	10.1136/lupus-2023-001096
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Article ; Online: JBrowseR: an R interface to the JBrowse 2 genome browser.

Hershberg, Elliot A / Stevens, Garrett / Diesh, Colin / Xie, Peter / De Jesus Martinez, Teresa / Buels, Robert / Stein, Lincoln / Holmes, Ian

Bioinformatics (Oxford, England)

2021 Volume 37, Issue 21, Page(s) 3914–3915

Abstract: ... expertise in web development.: Results: We have developed an R package that provides an interface ... to the JBrowse 2 genome browser. The package can be used to configure and customize the browser entirely with R ... code. The browser can be deployed from the R console, or embedded in Shiny applications or R Markdown ...

Abstract	Motivation: Genome browsers are an essential tool in genome analysis. Modern genome browsers enable complex and interactive visualization of a wide variety of genomic data modalities. While such browsers are very powerful, they can be challenging to configure and program for bioinformaticians lacking expertise in web development. Results: We have developed an R package that provides an interface to the JBrowse 2 genome browser. The package can be used to configure and customize the browser entirely with R code. The browser can be deployed from the R console, or embedded in Shiny applications or R Markdown documents. Availability and implementation: JBrowseR is available for download from CRAN, and the source code is openly available from the Github repository at https://github.com/GMOD/JBrowseR/.
MeSH term(s)	Genome ; Genomics ; Software
Language	English
Publishing date	2021-07-07
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	1422668-6
ISSN	1367-4811 ; 1367-4803
ISSN (online)	1367-4811
ISSN	1367-4803
DOI	10.1093/bioinformatics/btab459
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