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1. Peri-interventional outcome study in the elderly in Europe : A 30-day prospective cohort study

Author

Kowark, Ana, Rossaint, Rolf, Rückbeil, Marcia V., Hilgers, Ralf-Dieter, Bilotta, Federico, Bollheimer, Leo C., Buhre, Wolfgang, Guenther, Ulf, Hoeft, Andreas, Lee, Peter, Matot, Idit, Rex, Steffen, Steinmetz, Jacob, Tournoy, Jos, Alanoglu, Zekeriyya, Berger, Marc M., Falières, Xavier, Goettel, Nicolai, Kartalov, Andrijan, Katsanoulas, Konstantinos, Kenig, Jakub, Khoronenko, Victoria, Lundstrøm, Lars H., Macharadze, Tamar, Milenovic, Miodrag, Molliex, Serge, Órfão, Rosário, Soro, Marina, Stefan, Mihai, Sungur, Zerrin, Szakmany, Tamas, Baños, Victoria, Rodriguez, Mireia, Martinez, Selene, Saller, Thomas, Schäfer, Simon T., Clermond, Edouard, Martin, Charlotte, Le Moal, Charlene, Staikowsky, Frederik, Delannoy, Bertand, Desebbe, Olivier, Missant, Carlo, Desmet, Matthias, Gillmann, Hans-Joerg, Stueber, Thomas, Dalsø, Sille M., Vester-Andersen, Morten, Ranft, Andreas, Schneider, Gerhard, Huygens, Christel, Meeusen, Roselien, Cruz, Patricia, Fernández, Carmen, Otto, Mareike, Giltaire, Agathe, Hofmann, Pascal, Gurlit, Simone, Fernández, Alejandro Romero, Castelli, Federica, Ntouba, Alexandre, Lanoiselée, Julien, Schulz, Regina, Opperer, Mathias, Van Waesberghe, Julia, Ziemann, Sebastian, Refaeli-Awin, Einat, Bengisun, Zuleyha Kazak, Buchman, Immanuel, Yahav-Shafir, Dana, Dimakopoulou, Antonia, Le Guen, Morgan, Rodríguez-Pérez, Aurelio, Beran, Maud, Bonnal, Aurelien, Garot, Matthias, Maupain, Olivier, Michel, Denis, Fernandes, Sofia, Sanabra, Maria, Mangoubi, Eitan, Boselli, Emmanuel, Switzer, Timothy, García-Sánchez, Jose I., Boisson, Matthieu, Stamoulis, Konstantinos, García, María Merino, Wulf, Hinnerk, Gouraud, David, Lebrun, Christophe, Lasocki, Sigismond, Steiner, Luzius A., Bergmann, Lars, Baenziger, Bertram, Karpetas, Georgios, Meco, Basak C., Hızal, Ayşe, Hernández, Rosa Méndez, Smit-Fun, Valerie, Charco, Pedro, Nickel, Frank, Grau Torradeflot, Laura, Coburn, Mark, Berger, Marc, Farcher, Helmut, Adriaensens, Ine, Saldien, Vera, Berghmans, Johan, Van Hove, Sofie, Eerdekens, Gert-Jan, Mesotten, Dieter, Timmers, Maxim, Vandermeulen, Elly, De Bruyne, Ann, De Hert, Stefan, De Ruyter, Hendrik, Van Belleghem, Vincent, Boscart, Isabelle, De Corte, Wouter, Carlier, Stefaan, Castelain, Charlotte, Demeyer, Caroline, Vandenbossche, Carl, Detienne, Hans, Devroe, Sarah, Dewinter, Geertrui, Hoogma, Danny, Van de Velde, Marc, Poels, Stéphanie, Soetens, Filiep, Fenger-Eriksen, Christian, Draegert, Christina, Santos, Sofia Gaspar, Soelling, Christine, Andersen, Gertrud, Haderslev, Pernille, Rasmussen, Vibe M., Sommer, Tine G., Kirkegaard, Johan, Olesen, Christian M., Paramanathan, Sansu, Jensen, Lisbet Tokkesdal, Knudsen, Halfdan H., Schmidt, Jens C., Stehen, Nick P., Dupont, Hervé, Herbinet, Clément, Lorne, Emmanuel, Mahjoub, Yazine, Fritsch, Marine, Garcia, Manuela, Petit Phan, Jonathan, Lieutaud, Thomas, Bonneric, Laura, Gaillet, Maxime, des Déserts, Marc Danguy, Montelescaut, Etienne, Lamblin, Antoine, Muller, Violaine, Lagrange, Celine, Robert, Alain, Lebas, Benoit, Lebuffe, Gilles, Beuvelot, Johanne, Dejour, David, Deligne, Emmanuel, Gignoux, Benoit, Guillaud, Olivier, Nloga, Joseph, Prunier-Bossion, Florence, Sibellas, Franck, Abraham, Paul, Bidon, Cyril, Rimmele, Thomas, Bruge-Ansel, Marie-Hélène, Friggeri, Arnaud, Lukaszewicz, Anne-Claire, Dziadzko, Mikhail, Leone, Marc, Meresse, Zoe, Pastene, Bruno, Odin, Isabelle, Bouic, Nicolas, Trinh Duc, Pierre, Pillant, Thomas, Riboulet, Fabien, Degoul, Samuel, Saumier, Nicolas, Wasilewski, Marion, Asehnoune, Karim, Roquilly, Antoine, Glasman, Pauline, Puybasset, Louis, Garnier, Fanny, Verdonk, Franck, Samama, Charles M., Towa, Line, Blet, Alice, Barrau, Stéphanie, Debaene, Bertrand, Frasca, Denis, Imzi, Nadia, Delvaux, Bernard, Huynh, Davy, Mercadal, Luc, Zanoun, Nabil, de Baene, Armelle, Boulay-Maninovsky, Catherine, Fernandes, Olivier, Gomis, Philippe, Malinovsky, Jean-Marc, Romain, François-Xavier, Calmelet, Astrid, Dupont, Ségolène, Millet, Sophie, Simonneau, Frédéric, Charret, Francoise, Couturier, Charlène, Lornage, Estelle, Mallard, Jeremy, Milati, Ryan, Passot, Sylvie, Vallier, Sylvain, Agavriloaia, Mihaela L., Badoux, Quentin, Lewandowski, Mehdi, Mermet, Yanis, Kiskira, Olga, Adjavon, Sherifa, Dumans, Virginie, Josserand, Julien, Ma, Sabrina, Castanera, Jeremy, Massiera, Benjamin, Petua, Philippe, Bounes-Vardon, Fanny, Bosc, Gaëlle, Bosch, Laëtitia, Ferre, Fabrice, Labaste, François, Menut, Rémi, Minville, Vincent, Srairi, Mohamed, Tarasi, Maria, Varin, Florent, Grüßer, Linda, Nowak, Hartmuth, Oprea, Günther, Rump, Katharina, Unterberg, Matthias, Vogelsang, Heike, Klutzny, Mitja, Neumann, Claudia, Soehle, Martin, Wittmann, Maria, Scharffenberg, Martin, Wittenstein, Jakob, Hinterberg, Jonas, Kienbaum, Peter, Lurati-Buse, Giovanna, Schäfer, Maximilian, Lindau, Simone, Meybohm, Patrick, Piekarski, Florian, Kaufhold, Theresa A., Koppert, Wolfgang, Leffler, Andreas, Reiffen, Hans-Peter, Rudolph, Diana, Starke, Henning, Bischoff, Petra, Haberecht, Heinz, Plehn, Heiko, Bauer, Michael, Kortgen, Andreas, Sponholz, Christoph, Krüger, Uwe, Müller-Esch, Sabine, Rempf, Christian, Schmidt, Christian, Schumacher, Dunja, Blazek, Juliane, Büttner, Christin, Leibeling, Andrea, Rüsch, Dirk, Burow, Karsten, El-Hilali, Eugen A., Greke, Christian, Großmann, Paul, Kluth, Mario, Dridi, Sofiane, Popovska, Ivana, Brenes, Andrés, Feddersen, Pia, Gerstmeyer, Dominik, Fthenakis, Philippe, Miketta, Dirk, von Dossow, Vera, Groene, Philipp, Höchter, Dominik, Hofmann-Kiefer, Klaus, Kammerer, Tobias, Kamrath, Malte, Schaefer, Simon T., Tomasi, Roland, Wiedemann, Tobias, Zeuzem-Lampert, Catharina, Zwissler, Bernhard, Braune, Stephan, Brune, Mona, Hemping-Bovenkerk, André, Möllmann, Michael, Santamaria, Mario, Schirwitz, Leonie M., Meersch, Melanie, Zarbock, Alexander, Decker, Stefanie, Drexler, Berthold, Hipp, Silvia, Müller, Markus, Roth, Judith, Seiß, Miriam, Adam, Christian, Schwartges, Ingo, Kranke, Peter, Chloropoulou, Pelagia, Andreeva, Antonia, Douma, Amalia, Gregoriadou, Iphigeneia, Koutsouli, Evelina, Mendrinou, Konstantina, Mavrommati, Eirini, Stathopoulos, Anastasios, Batistaki, Chrysanthi, Matsota, Paraskevi, Kalopita, Konstantina, Skandalou, Vasiliki, Balanika, Marina, Papathanakos, Georgios, Tzimas, Petros, Ketikidou, Evgenia, Vachlioti, Anastasia, Kiamiloglou, Bioulent, Nikouli, Evangelia, Arnaoutoglou, Eleni, Kolonia, Konstantina, Laou, Eleni, Vlachakis, Epaminondas, Lianou, Ioanna, Spyraki, Maria, Tatani, Irini, Panagiotou, Eleni, Samara, Evangelia, Kolesnikova, Anna, Sifaki, Freideriki, Zarzava, Eirini, Bampzelis, Athanasios, Georgopoulou, Eleni, Christidou, Eleni, Tsaousi, Georgia, Nastou, Maria, Ioannidis, Orestis, Dolzenko, Eugene, Geleve, Georgia, Logotheti, Eleni, Yfantidis, Fotios, Rajamanickam, Senbagam, Ramaswamy, Shanmuga, Das Punshi, Gurmukh, Srinivasan, Karthikeyan, Gilmartin, Michael, Morris, Osmond, Gozal, Yaacov, Merissat, Amar, Peled, Reut, Willner, Dafna, Chariski, Hila A., Eidelman, Leonid A., Livne, Michal Y., Berkenstadt, Haim, Orlcin, Dina, Aharonov, Rita, Cattan, Anat, Felman, Lior, Steinberg, Yohai, Zabeeda, Wisam, Kuzmanovska, Biljana, Naumovski, Filip, Toleska, Marija, Sivevski, Atanas, Andriessen, Anouk, Kortekaas, Minke, Van Gorp, Roos, de Korte-de Boer, Dianne, Theunissen, Maurice, Droger, Mirjam, van den Enden, Toine, Koopman, Seppe, Marsman, Marije, van Schaik, Eva, Azenha, Marta, Lanzaro, Camile, Borrego, Andreia, Branquinho, Pedro, Laires, Miguel, de Noronha, Denise, Ferraz, Inês, Pires, Ana, Silva, Joana, Corneci, Dan, Oprea, Oana, Zahiu, Stefan-Vladimir, Tomescu, Dana R., Grintescu, Ioana M., Filipescu, Daniela, Stefanescu, Elena, Vazenin, Andrey, Baskakov, Danil, Tipisev, Dmitry, Kozlova, Ksenia, Marinkovic, Olivera, Sekulic, Ana, Rajkovic, Marija, Djukanovic, Marija, Nikolic, Jovanka, Sreckovic, Svetlana, Stojanovic, Marina, Ladjevic, Nebojsa, Jovicic, Jelena, Unic-Stojanovic, Dragana, Stosic, Biljana, Bulasevic, Aleksandra, Espinosa-Moreno, Alma M., Martín-Vaquerizo, Beatriz, Morandeira-Rivas, Clara, Zamudio, Diana, Guadalupe, Nerea, Herranz, Gracia, Baute, Javier, Madrona, Vanesa, de Jose, Roser, Miralles, Jordi, Merten, Alfred, Muñoz, Rolando, Delgado, Anabel, Moral, Victoria, Blesa, Aleix Carmona, Espejo, Sara, Grau Torredeflot, Laura, Pujol, Pere Serra, Alvira Uribe, Maria J., Perez, Astrid Alvarez, Brunetto, Espedito, Aguirre, Jorge Gonzalez, Villar, Adriana Herivas, Rojas, Guido Munoz, Montero, Natalia, González, Víctor Baladrón, Becerra-Bolaños, Ángel, Santana-Ortega, Luis, Suárez-Romero, Vanessa, Torres-Machí, María L., Ferrero de Paz, Javier, Marcos-Vidal, Jose M., Garcia, Ana Martín, Diaz, Consuelo Rego, Santiago, Ana Crespo, Laso, Lourdes Ferreira, Solores, Felix Lobato, Burgos, Alba, Calvo, Alberto, Fernández, Ignacio, Garutti, Ignacio, Higuero, Fernando, Martinez, David, Piñeiro, Patricia, Carazo, Sonia Expósito, Rodríguez, Mar Orts, Rueda, Fernando Ramasco, Abad-Motos, Ane, Ripollés-Melchor, Javier, López, Carmen Pastor, Perez-Palao, Sara, Sancho-Iñigo, Laura, Segura, Nasara, Utrera, Esther, Albinarrate, Ania, Fondarella, Ana M., Gallego-Ligorit, Lucia, Torrijos, Luisa Lacosta, Bandschapp, Oliver, Blum, Andrea A., Seeberger, Esther, Thomann, Alessandra E., Frei, Seraina, Hoehn, Susan, Capaldo, Giuliana, Christ, Daniel, Doerig, Ramon, Hodel, Daniel, Weiss, Andreas, Witt, Lukas, Schumacher, Philippe, Siebing, Dirk A., Akbuz, Seyma Orcan, Kazbek, Baturay K., Koksoy, Ulku C., Terzi, Engin Z., Yilmaz, Hakan, Alkis, Neslihan, Turhan, Sanem Cakar, Hajiyeva, Konul, Guclu, Cigdem Yildirim, Ergil, Jülide, Ceran, Emine Unal, Ozcelik, Menekse, Bülent, Atik, Gökhan, Kilinc, Saracoglu, Kemal T., Kir, Bunyamin, Koltka, Kemalettin, Sivrikoz, Nükhet, Dincer, Pelin Corman, Canbolat, Nur, Kudsioglu, Turkan, Aydin, Gaye, Mucuoglu, Ceren Aygün, Inal, Duriye G., Kucukguclu, Semih, Egilmez, Ayse I., Kozanhan, Betul, Yildiz, Munise, Pinar, Hüseyin U., Erdivanlı, Başar, Karagöz, Emre, Kazdal, Hızır, Özdemir, Abdullah, Tas Tuna, Ayca, Gulgun, Gamze, and Oleg, Dolya

Abstract

European journal of anaesthesiology : EJA 39(3), 198-209 (2022). doi:10.1097/EJA.0000000000001639, Published by Lippincott Williams & Wilkins, Philadelphia, Pa.

Published
2022
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3. High Efficacy of Therapeutic Equine Hyperimmune Antibodies Against SARS-CoV-2 Variants of Concern

Author

Moreira Soto, Andrés, Gutiérrez, José María, Alape Girón, Alberto, Drexler, Jan Felix, Arguedas Gómez, Mauricio, Brenes Porras, Hebleen, Buján Boza, Willem Aart, Corrales Aguilar, Eugenia, Díaz Oreiro, Cecilia, Echeverri McCandless, Ann, Flores Díaz, Marietta, Macaya Hayes, Román, Kühne, Arne, Molina Mora, José Arturo, Mora Rodríguez, Javier Francisco, Sanabria Castro, Alfredo, Sánchez Brenes, Andrés, Sánchez Céspedes, Laura Vanessa, Segura Ruiz, Álvaro, Segura Agüero, Eduardo, Solano Centeno, Daniela, Soto Garita, Claudio, Stynoski, Jennifer Lynn, Vargas Arroyo, Mariángela, Villalta Arrieta, Mauren, Reusken, Chantal B. E. M., and Drosten, Christian

Subjects
Variant of concern, PRNT titers 50, SARS-CoV-2, VIROLOGÍA, COVID-19, Neutralization test, Therapy, Equine antibodies
Abstract

SARS-CoV-2 variants of concern show reduced neutralization by vaccine-induced and therapeutic monoclonal antibodies; therefore, treatment alternatives are needed. We tested therapeutic equine polyclonal antibodies (pAbs) that are being assessed in clinical trials in Costa Rica against five globally circulating variants of concern: alpha, beta, epsilon, gamma and delta, using plaque reduction neutralization assays. We show that equine pAbs efficiently neutralize the variants of concern, with inhibitory concentrations in the range of 0.146–1.078µg/mL, which correspond to extremely low concentrations when compared to pAbs doses used in clinical trials. Equine pAbs are an effective, broad coverage, low-cost and a scalable COVID-19 treatment. German academic exchange services/[57592642]/DAAD/Alemania Universidad de Costa Rica/[741-C0-198]/UCR/Costa Rica Banco Centroamericano de Integración Económica/[]/BCIE/Costa Rica UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias de la Salud::Centro de Investigación en Enfermedades Tropicales (CIET) UCR::Vicerrectoría de Docencia::Salud::Facultad de Microbiología UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias de la Salud::Instituto Clodomiro Picado (ICP) UCR::Vicerrectoría de Docencia::Salud::Facultad de Medicina::Escuela de Medicina

Published
2021
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5. Evaluación proteómica y toxinológica del veneno de Hemachatus haemachatus y su comparación con venenos de cobras del genero Naja sp. en términos de inmunoreactividad y neutralización cruzada para la preparación de un antiveneno poliespecífico para África

Author

Sánchez Brenes, Andrés and Vargas Arroyo, Mariángela

Subjects
Veneno de serpiente
Abstract

Las cobras representan el grupo de serpientes clínicamente más relevantes de la familia Elapidae en África, dentro de los cuales los géneros Naja y Hemachatus incluyen serpientes con venenos neurotóxicos y citotóxicos. Debido a que la composición proteica del veneno de Hemachatus haemachatus (Ringhals) no había sido descrita completamente, y que posee características análogas a venenos citotóxicos y neurotóxicos, se realizó una caracterización de este veneno a nivel proteómico y toxinológico para determinar su similitud antigénica con otras cobras. Adicionalmente, se desarrolló un antiveneno monoespecífico experimental anti-H. haemachatus, para evaluar la reactividad cruzada contra venenos del género Naja del África sub-Sahariana, mediante análisis preclínicos y antivenómica de tercera generación. La composición proteica del veneno de la cobra escupidora H. haemachatus se caracterizó mediante la metodología proteómica “bottom-up”. El veneno se compone de abundante presencia de toxinas de tres dedos (3FTx; 63,3%), seguido de fosfolipasas A2 (PLA2; 22,8%), metaloproteinasas (SVMPs; 7,1%), proteínas secretoras ricas en cisteína (CRISPs; 4,1%) y proteínas inhibidoras tipo kunitz (KTPIs; 1,5%). El veneno de H. haemachatus comparte una composición similar en cuanto a la presencia de familias de toxinas con los venenos de N. annulifera, N. mossambica y N. nigricollis; sin embargo, presenta variaciones en las proporciones de toxinas de 3FTx, PLA2, SVMPs y CRISPs. El antiveneno anti-Hemachatus neutralizó la actividad letal de los tres venenos de cobras escupidoras: H. haemachatus (veneno homólogo neuro/citotóxico), N. mossambica y N. nigricollis (venenos heterólogos cito/cardiotóxicos). No obstante, no neutralizó la actividad letal y actividades tóxicas del veneno neurotóxico de la cobra no escupidora N. annulifera. La capacidad del antiveneno anti-Hemachatus para neutralizar la actividad dermonecrótica, anticoagulante y fosfolipasa de los venenos de cobras escupidoras, así como su perfil de inmunoreactividad obtenido mediante antivenómica de tercera generación, sugieren mayor similitud antigénica y una relación filogenética más cercana entre H. haemachatus y el género Naja subgénero Afrocobra (cobras escupidoras), en comparación al género Naja subgénero Uraeus (cobras neurotóxicas). Este estudio aporta evidencia para la producción de antivenenos de amplio espectro contra envenenamientos de especies de cobra. A partir de los resultados obtenidos, se propone que para la preparación de antivenenos, si la mezcla de inmunización incluye venenos de N. mossambica y N. nigricollis, no es estrictamente necesario incluir en el esquema de inmunización el veneno de H. haemachatus. UCR::Vicerrectoría de Investigación::Sistema de Estudios de Posgrado::Salud::Maestría Académica en Microbiología

Published
2020

6. Aplicación de Cadenas de Markov en un proceso de producción de plantas in vitro

Author

Sánchez-Brenes, Andrés, Alvarado-Ulloa, Carlos, Solís-Blanco, Ricardo, Chacón-Cerdas, Randall, and Villalta-Solano, Humberto

Subjects
Markov Chain Method, in vitro plants, estochastic methods, Cadenas Markov, plantas in vitro, métodos estocásticos
Abstract

The application of Biotechnology includes a number of industrial processes involving living organisms or parts of them. The interaction of genotype with other industrial manipulation factors, characterized by predictable actions and random elements, makes the system to be stochastic. Commercial production of in vitro plants is one example of the biotechnology industry, where the production process consists of the propagation of plants in sterile growth media under controlled physical conditions. During this process, contamination or death of in vitro plants is considered as scrap (waste); however, if plants present oxidation or deformation they have to be reworked, in order to recover or reincorporate to the previous stage. Plant material requirement to accomplish a client demand was studied using the in vitro production process of Solanum tuberosum from the company VitroPlant S.A., to establish a model using Markov Chain Method, in which scrap and rework are included. Thus, the Markov method is a viable option in biological production processes that could be applied to other plant species and even other systems using different living organisms, such as fungi, bacteria, insects and algae, common in the industry. La aplicación de la biotecnología incluye una serie de procesos industriales que involucran organismos vivos o partes de ellos. La interacción del genotipo con los demás factores de manipulación industrial, aunque controlables, provoca que el sistema sea estocástico o no determinista, caracterizado por acciones predecibles y con elementos aleatorios. La producción masiva de plantas in vitro es un ejemplo de este tipo de industrias biotecnológicas, en el que se cultivan plantas seleccionadas bajo condiciones controladas de incubación y en medios nutritivos. Durante el proceso se producen pérdidas por contaminación o muerte del material y reprocesos, cuando las plantas se oxidan o deforman, pero una parte de ellas se puede rescatar y reintegrar a la etapa anterior. Tomando como modelo el proceso de producción de vitroplantas de papa (Solanum tuberosum) en la empresa VitroPlant S.A., se aplicó el método de Cadenas de Markov para determinar los requerimientos de material vegetal para cumplir con una demanda determinada de acuerdo con la etapa del proceso de la que se inicia, incluyendo en ese cálculo las pérdidas y reprocesos. Así, el método de Markov es una opción viable en los procesos biológicos productivos que podría aplicarse a otras especies vegetales e incluso a otros sistemas que utilicen diferentes organismos vivos, tales como hongos, bacterias, insectos y microalgas, todos comunes en la industria.

Published
2016

7. Aplicación de Cadenas de Markov en un proceso de producción de plantas in vitro

Author

Sánchez Brenes, Andrés, Alvarado Ulloa, Carlos, Solís Blanco, Ricardo, Chacón Cerda, Randall, Villalta Solano, Humberto, Sánchez Brenes, Andrés, Alvarado Ulloa, Carlos, Solís Blanco, Ricardo, Chacón Cerda, Randall, and Villalta Solano, Humberto

Abstract

The application of Biotechnology includes a number of industrial processes involving living organisms or parts of them. The interaction of genotype with other industrial manipulation factors, characterized by predictable actions and random elements, makes the system to be stochastic. Commercial production of in vitro plants is one example of the biotechnology industry, where the production process consists of the propagation of plants in sterile growth media under controlled physical conditions. During this process, contamination or death of in vitro plants is considered as scrap (waste); however, if plants present oxidation or deformation they have to be reworked, in order to recover or reincorporate to the previous stage. Plant material requirement to accomplish a client demand was studied using the in vitro production process of Solanum tuberosum from the company VitroPlant S.A., to establish a model using Markov Chain Method, in which scrap and rework are included. Thus, the Markov method is a viable option in biological production processes that could be applied to other plant species and even other systems using different living organisms, such as fungi, bacteria, insects and algae, common in the industry., La aplicación de la biotecnología incluye una serie de procesos industriales que involucran organismos vivos o partes de ellos. La interacción del genotipo con los demás factores de manipulación industrial, aunque controlables, provoca que el sistema sea estocástico o no determinista, caracterizado por acciones predecibles y con elementos aleatorios. La producción masiva de plantas in vitro es un ejemplo de este tipo de industrias biotecnológicas, en el que se cultivan plantas seleccionadas bajo condiciones controladas de incubación y en medios nutritivos. Durante el proceso se producen pérdidas por contaminación o muerte del material y reprocesos, cuando las plantas se oxidan o deforman, pero una parte de ellas se puede rescatar y reintegrar a la etapa anterior. Tomando como modelo el proceso de producción de vitroplantas de papa (Solanum tuberosum) en la empresa VitroPlant S.A., se aplicó el método de Cadenas de Markov para determinar los requerimientos de material vegetal para cumplir con una demanda determinada de acuerdo con la etapa del proceso de la que se inicia, incluyendo en ese cálculo las pérdidas y reprocesos. Así, el método de Markov es una opción viable en los procesos biológicos productivos que podría aplicarse a otras especies vegetales e incluso a otros sistemas que utilicen diferentes organismos vivos, tales como hongos, bacterias, insectos y microalgas, todos comunes en la industria.

Published
2016

10. Soluciones energéticas para la vida cotidiana

Author

Brenes, Andrés

Subjects
Instituto Costarricense de Electricidad, Energía eléctrica, Energía hidroeléctrica, Abastecimiento de energía, Recursos energéticos
Abstract

Informe de Investigación--Universidad de Costa Rica, Vicerrectoría de Acción Social, Trabajo Comunal Universitario. 2002. Para mayor información puede escribir a accion.social@ucr.ac.cr Resumen de la ubicación y descripción general de las diferentes plantas que el Instituto Costarricense de Electricidad (ICE) ha construido o adquirido desde su creación, en 1949, y que permanecen funcionando en la actualidad. También se presenta una reseña histórica del ICE, en las áreas de electricidad y telecomunicaciones. Esta es la segunda versión de una investigación anterior. Universidad de Costa Rica UCR::Vicerrectoría de Acción Social::Trabajo Comunal Universitario (TCU)

Published
2002

11. Peri-interventional outcome study in the elderly in Europe A 30-day prospective cohort study

Author

Ana Sekulic, Selene Martinez Perez, Danny Feike Hoogma, GÖKHAN KILINÇ, Marc Danguy des Déserts, Evangelia Samara, AYSE HIZAL, Nicolai Goettel, Martin Scharffenberg, Sofia Fernandes, Jose Ignacio García-Sánchez, Tobias Kammerer, Marc Moritz Berger, Florian Piekarski, CEREN AYGÜN MUÇUOĞLU, PATRICIA PIÑEIRO OTERO, Angel Becerra, Aurelio Rodriguez-Perez, Ülkü Ceren Köksoy, Jakob Wittenstein, Lars Lundstrøm, Diana Zamudio Penko, Hans-Joerg Gillmann, Dianne De Korte-de Boer, Jose miguel Marcos-vidal, Sebastian Ziemann, Tournoy, Jos, Kowark, Ana, Rossaint, Rolf, Matot, Idit, Nickel, Frank, Grau Torradeflot, Laura, Coburn, Mark, Berger, Marc, Farcher, Helmut, Opperer, Mathias, Adriaensens, Ine, Saldien, Vera, Berghmans, Johan, Van Hove, Sofie, Rex, Steffen, Beran, Maud, Eerdekens, Gert-Jan, Mesotten, Dieter, Timmers, Maxim, Vandermeulen, Elly, De Bruyne, Ann, De Hert, Stefan, De Ruyter, Hendrik, Van Belleghem, Vincent, Boscart, Isabelle, Steinmetz, Jacob, De Corte, Wouter, Desmet, Matthias, Missant, Carlo, Carlier, Stefaan, Castelain, Charlotte, Demeyer, Caroline, Vandenbossche, Carl, Detienne, Hans, Devroe, Sarah, Dewinter, Geertrui, Hoogma, Danny, Huygens, Christel, Meeusen, Roselien, Van de Velde, Marc, Lebrun, Christophe, Poels, Stéphanie, Soetens, Filiep, Fenger-Eriksen, Christian, Alanoglu, Zekeriyya, Draegert, Christina, Santos, Sofia Gaspar, Soelling, Christine, Andersen, Gertrud, Dalsø, Sille M., Haderslev, Pernille, Rasmussen, Vibe M., Vester-Andersen, Morten, Sommer, Tine G., Berger, Marc M., Kirkegaard, Johan, Lundstrøm, Lars H., Olesen, Christian M., Paramanathan, Sansu, Jensen, Lisbet Tokkesdal, Knudsen, Halfdan H., Schmidt, Jens C., Stehen, Nick P., Dupont, Hervé, Herbinet, Clément, Falières, Xavier, Lorne, Emmanuel, Mahjoub, Yazine, Ntouba, Alexandre, Fritsch, Marine, Garcia, Manuela, Lasocki, Sigismond, Petit Phan, Jonathan, Lieutaud, Thomas, Bonneric, Laura, Boselli, Emmanuel, Goettel, Nicolai, Gaillet, Maxime, des Déserts, Marc Danguy, Montelescaut, Etienne, Lamblin, Antoine, Muller, Violaine, Lagrange, Celine, Le Moal, Charlene, Robert, Alain, Staikowsky, Frederik, Lebas, Benoit, Kartalov, Andrijan, Lebuffe, Gilles, Garot, Matthias, Beuvelot, Johanne, Dejour, David, Deligne, Emmanuel, Desebbe, Olivier, Delannoy, Bertand, Gignoux, Benoit, Guillaud, Olivier, Nloga, Joseph, Katsanoulas, Konstantinos, Prunier-Bossion, Florence, Sibellas, Franck, Abraham, Paul, Bidon, Cyril, Rimmele, Thomas, Bruge-Ansel, Marie-Hélène, Friggeri, Arnaud, Lukaszewicz, Anne-Claire, Dziadzko, Mikhail, Leone, Marc, Rückbeil, Marcia V., Kenig, Jakub, Meresse, Zoe, Pastene, Bruno, Odin, Isabelle, Bonnal, Aurelien, Bouic, Nicolas, Trinh Duc, Pierre, Pillant, Thomas, Riboulet, Fabien, Degoul, Samuel, Saumier, Nicolas, Khoronenko, Victoria, Wasilewski, Marion, Asehnoune, Karim, Roquilly, Antoine, Glasman, Pauline, Puybasset, Louis, Garnier, Fanny, Verdonk, Franck, Samama, Charles M., Towa, Line, Blet, Alice, Barrau, Stéphanie, Boisson, Matthieu, Debaene, Bertrand, Frasca, Denis, Imzi, Nadia, Delvaux, Bernard, Huynh, Davy, Maupain, Olivier, Mercadal, Luc, Zanoun, Nabil, Macharadze, Tamar, de Baene, Armelle, Boulay-Maninovsky, Catherine, Fernandes, Olivier, Giltaire, Agathe, Gomis, Philippe, Malinovsky, Jean-Marc, Romain, François-Xavier, Calmelet, Astrid, Dupont, Ségolène, Gouraud, David, Milenovic, Miodrag, Millet, Sophie, Simonneau, Frédéric, Charret, Francoise, Couturier, Charlène, Lanoiselée, Julien, Lornage, Estelle, Mallard, Jeremy, Milati, Ryan, Passot, Sylvie, Vallier, Sylvain, Molliex, Serge, Agavriloaia, Mihaela L., Badoux, Quentin, Lewandowski, Mehdi, Mermet, Yanis, Michel, Denis, Kiskira, Olga, Adjavon, Sherifa, Dumans, Virginie, Le Guen, Morgan, Josserand, Julien, Órfão, Rosário, Ma, Sabrina, Castanera, Jeremy, Massiera, Benjamin, Petua, Philippe, Bounes-Vardon, Fanny, Bosc, Gaëlle, Bosch, Laëtitia, Clermond, Edouard, Ferre, Fabrice, Labaste, François, Soro, Marina, Martin, Charlotte, Menut, Rémi, Minville, Vincent, Srairi, Mohamed, Tarasi, Maria, Varin, Florent, Grüßer, Linda, Stefan, Mihai, Van Waesberghe, Julia, Ziemann, Sebastian, Bergmann, Lars, Nowak, Hartmuth, Oprea, Günther, Rump, Katharina, Unterberg, Matthias, Vogelsang, Heike, Klutzny, Mitja, Neumann, Claudia, Sungur, Zerrin, Soehle, Martin, Wittmann, Maria, Scharffenberg, Martin, Wittenstein, Jakob, Hinterberg, Jonas, Kienbaum, Peter, Lurati-Buse, Giovanna, Schäfer, Maximilian, Lindau, Simone, Hilgers, Ralf-Dieter, Szakmany, Tamas, Meybohm, Patrick, Gillmann, Hans-Joerg, Piekarski, Florian, Kaufhold, Theresa A., Koppert, Wolfgang, Leffler, Andreas, Reiffen, Hans-Peter, Rudolph, Diana, Starke, Henning, Stueber, Thomas, Baños, Victoria, Bischoff, Petra, Haberecht, Heinz, Plehn, Heiko, Bauer, Michael, Kortgen, Andreas, Sponholz, Christoph, Krüger, Uwe, Müller-Esch, Sabine, Otto, Mareike, Rempf, Christian, Rodriguez, Mireia, Schmidt, Christian, Schumacher, Dunja, Blazek, Juliane, Büttner, Christin, Leibeling, Andrea, Rüsch, Dirk, Wulf, Hinnerk, Burow, Karsten, El-Hilali, Eugen A., Greke, Christian, Martinez, Selene, Großmann, Paul, Kluth, Mario, Schulz, Regina, Dridi, Sofiane, Popovska, Ivana, Brenes, Andrés, Ranft, Andreas, Feddersen, Pia, Gerstmeyer, Dominik, Fthenakis, Philippe, Saller, Thomas, Schneider, Gerhard, Miketta, Dirk, von Dossow, Vera, Groene, Philipp, Höchter, Dominik, Hofmann-Kiefer, Klaus, Kammerer, Tobias, Kamrath, Malte, Schaefer, Simon T., Schäfer, Simon T., Tomasi, Roland, Wiedemann, Tobias, Zeuzem-Lampert, Catharina, Zwissler, Bernhard, Braune, Stephan, Brune, Mona, Gurlit, Simone, Hemping-Bovenkerk, André, Möllmann, Michael, Santamaria, Mario, Schirwitz, Leonie M., Meersch, Melanie, Zarbock, Alexander, Guenther, Ulf, Decker, Stefanie, Drexler, Berthold, Hipp, Silvia, Hofmann, Pascal, Müller, Markus, Roth, Judith, Seiß, Miriam, Adam, Christian, Schwartges, Ingo, Kranke, Peter, Chloropoulou, Pelagia, Andreeva, Antonia, Dimakopoulou, Antonia, Douma, Amalia, Gregoriadou, Iphigeneia, Koutsouli, Evelina, Mendrinou, Konstantina, Mavrommati, Eirini, Stathopoulos, Anastasios, Batistaki, Chrysanthi, Matsota, Paraskevi, Kalopita, Konstantina, Skandalou, Vasiliki, Balanika, Marina, Papathanakos, Georgios, Tzimas, Petros, Ketikidou, Evgenia, Vachlioti, Anastasia, Kiamiloglou, Bioulent, Nikouli, Evangelia, Arnaoutoglou, Eleni, Kolonia, Konstantina, Laou, Eleni, Stamoulis, Konstantinos, Vlachakis, Epaminondas, Bilotta, Federico, Karpetas, Georgios, Lianou, Ioanna, Spyraki, Maria, Tatani, Irini, Panagiotou, Eleni, Samara, Evangelia, Kolesnikova, Anna, Sifaki, Freideriki, Zarzava, Eirini, Bampzelis, Athanasios, Georgopoulou, Eleni, Christidou, Eleni, Tsaousi, Georgia, Nastou, Maria, Ioannidis, Orestis, Dolzenko, Eugene, Geleve, Georgia, Logotheti, Eleni, Yfantidis, Fotios, Lee, Peter, Rajamanickam, Senbagam, Ramaswamy, Shanmuga, Switzer, Timothy, Das Punshi, Gurmukh, Srinivasan, Karthikeyan, Gilmartin, Michael, Morris, Osmond, Buchman, Immanuel, Gozal, Yaacov, Merissat, Amar, Peled, Reut, Willner, Dafna, Chariski, Hila A., Eidelman, Leonid A., Livne, Michal Y., Mangoubi, Eitan, Berkenstadt, Haim, Orlcin, Dina, Yahav-Shafir, Dana, Aharonov, Rita, Cattan, Anat, Felman, Lior, Refaeli-Awin, Einat, Steinberg, Yohai, Zabeeda, Wisam, Kuzmanovska, Biljana, Naumovski, Filip, Toleska, Marija, Sivevski, Atanas, Andriessen, Anouk, Kortekaas, Minke, Buhre, Wolfgang, Van Gorp, Roos, de Korte-de Boer, Dianne, Smit-Fun, Valerie, Theunissen, Maurice, Droger, Mirjam, van den Enden, Toine, Koopman, Seppe, Marsman, Marije, van Schaik, Eva, Azenha, Marta, Lanzaro, Camile, Borrego, Andreia, Branquinho, Pedro, Fernandes, Sofia, Laires, Miguel, de Noronha, Denise, Ferraz, Inês, Pires, Ana, Silva, Joana, Corneci, Dan, Oprea, Oana, Zahiu, Stefan-Vladimir, Tomescu, Dana R., Grintescu, Ioana M., Filipescu, Daniela, Stefanescu, Elena, Vazenin, Andrey, Baskakov, Danil, Tipisev, Dmitry, Kozlova, Ksenia, Marinkovic, Olivera, Sekulic, Ana, Rajkovic, Marija, Djukanovic, Marija, Nikolic, Jovanka, Sreckovic, Svetlana, Stojanovic, Marina, Ladjevic, Nebojsa, Jovicic, Jelena, Unic-Stojanovic, Dragana, Bollheimer, Leo C., Stosic, Biljana, Bulasevic, Aleksandra, Espinosa-Moreno, Alma M., García-Sánchez, Jose I., Martín-Vaquerizo, Beatriz, Morandeira-Rivas, Clara, Zamudio, Diana, Guadalupe, Nerea, Herranz, Gracia, Baute, Javier, Madrona, Vanesa, de Jose, Roser, Miralles, Jordi, Merten, Alfred, Muñoz, Rolando, Delgado, Anabel, Cruz, Patricia, Moral, Victoria, Blesa, Aleix Carmona, Espejo, Sara, Grau Torredeflot, Laura, Fernández, Alejandro Romero, Sanabra, Maria, Pujol, Pere Serra, Alvira Uribe, Maria J., Perez, Astrid Alvarez, Brunetto, Espedito, Fernández, Carmen, Castelli, Federica, Aguirre, Jorge Gonzalez, Villar, Adriana Herivas, Rojas, Guido Munoz, Montero, Natalia, González, Víctor Baladrón, Becerra-Bolaños, Ángel, Rodríguez-Pérez, Aurelio, Santana-Ortega, Luis, Suárez-Romero, Vanessa, Torres-Machí, María L., Ferrero de Paz, Javier, Marcos-Vidal, Jose M., Garcia, Ana Martín, García, María Merino, Diaz, Consuelo Rego, Santiago, Ana Crespo, Laso, Lourdes Ferreira, Solores, Felix Lobato, Burgos, Alba, Calvo, Alberto, Fernández, Ignacio, Garutti, Ignacio, Higuero, Fernando, Martinez, David, Piñeiro, Patricia, Carazo, Sonia Expósito, Hernández, Rosa Méndez, Rodríguez, Mar Orts, Rueda, Fernando Ramasco, Abad-Motos, Ane, Ripollés-Melchor, Javier, López, Carmen Pastor, Charco, Pedro, Perez-Palao, Sara, Sancho-Iñigo, Laura, Segura, Nasara, Utrera, Esther, Albinarrate, Ania, Fondarella, Ana M., Gallego-Ligorit, Lucia, Torrijos, Luisa Lacosta, Bandschapp, Oliver, Blum, Andrea A., Seeberger, Esther, Steiner, Luzius A., Thomann, Alessandra E., Frei, Seraina, Hoehn, Susan, Baenziger, Bertram, Capaldo, Giuliana, Christ, Daniel, Doerig, Ramon, Hodel, Daniel, Weiss, Andreas, Witt, Lukas, Schumacher, Philippe, Siebing, Dirk A., Akbuz, Seyma Orcan, Bengisun, Zuleyha Kazak, Kazbek, Baturay K., Koksoy, Ulku C., Terzi, Engin Z., Yilmaz, Hakan, Alkis, Neslihan, Turhan, Sanem Cakar, Meco, Basak C., Hajiyeva, Konul, Guclu, Cigdem Yildirim, Ergil, Jülide, Ceran, Emine Unal, Ozcelik, Menekse, Bülent, Atik, Gökhan, Kilinc, Saracoglu, Kemal T., Kir, Bunyamin, Koltka, Kemalettin, Sivrikoz, Nükhet, Dincer, Pelin Corman, Canbolat, Nur, Kudsioglu, Turkan, Aydin, Gaye, Mucuoglu, Ceren Aygün, Inal, Duriye G., Kucukguclu, Semih, Egilmez, Ayse I., Kozanhan, Betul, Yildiz, Munise, Pinar, Hüseyin U., Erdivanlı, Başar, Hızal, Ayşe, Karagöz, Emre, Kazdal, Hızır, Özdemir, Abdullah, Tas Tuna, Ayca, Gulgun, Gamze, Oleg, Dolya, Hoeft, Andreas, MUMC+: MA Anesthesiologie (3), RS: MHeNs - R3 - Neuroscience, and MUMC+: MA Anesthesiologie (9)

Subjects
Aged, 80 and over, Male, Patient, Frailty, Preoperative assessment, Surgical outcomes, Europe, Hospitalization, Older, Anesthesiology and Pain Medicine, Outcome Assessment, Health Care, Humans, Female, Surgery, Prospective Studies, Derivation, Mortality, Aged
Abstract

OBJECTIVES The aim of this study was to describe the 30-day mortality rate of patients aged 80 years and older undergoing surgical and nonsurgical procedures under anaesthesia in Europe and to identify risk factors associated with mortality. DESIGN A prospective cohort study. SETTING European multicentre study, performed from October 2017 to December 2018. Centres committed to a 30-day recruitment period within the study period. PATIENTS Nine thousand four hundred and ninety-seven consecutively recruited patients aged 80 years and older undergoing any kind of surgical or nonsurgical procedures under anaesthesia. MAIN OUTCOME MEASURES The primary outcome was all-cause mortality within 30 days after procedure described by Kaplan–Meier curves with 95% CI. Risk factors for 30-day mortality were analysed using a Cox regression model with 14 fixed effects and a random centre effect. RESULTS Data for 9497 patients (median age, 83.0 years; 52.8% women) from 177 academic and nonacademic hospitals in 20 countries were analysed. Patients presented with multimorbidity (77%), frailty (14%) and at least partial functional dependence (38%). The estimated 30-day mortality rate was 4.2% (95% CI 3.8 to 4.7). Among others, independent risk factors for 30-day mortality were multimorbidity, hazard ratio 1.87 (95% CI 1.26 to 2.78), frailty, hazard ratio 2.63 (95% CI 2.10 to 3.30), and limited mobility, hazard ratio 2.19 (95% CI 1.24 to 3.86). The majority of deaths (76%) occurred in hospital. Mortality risk for unplanned ICU admission was higher, hazard ratio 3.57 (95% CI 2.38 to 5.26) than for planned ICU admission, hazard ratio 1.92 (95% CI 1.47 to 2.50). Compared with other studies, the in-hospital complication rates of 17.4 and 3.9% after discharge were low. Admission to a unit with geriatric care within 30 days after the intervention was associated with a better survival within the first 10 days. CONCLUSIONS The estimated 30-day mortality rate of 4.2% was lower than expected in this vulnerable population. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT03152734, https://clinicaltrials.gov. ispartof: European Journal Of Anaesthesiology vol:39 issue:3 pages:198-209 ispartof: location:England status: published

Published
2022
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