Red Nacional de reconocedores de suelos.

Los relevamientos sistemáticos de suelos en Argentina comenzaron en la década de 1960, en el marco del Plan Mapa de Suelos. Dicho plan, desarrollado y liderado por el INTA, dio impulso a la formación de especialistas y a la producción de cartografía de suelos a diferentes escalas. Sin embargo, a partir del año 2000 las actividades se redujeron notablemente y gran parte de los equipos provinciales formados hasta ese momento se desarticularon. Desde entonces los relevamientos continuaron de manera aislada sólo en aquellas provincias donde se mantuvieron los grupos de trabajo. Este hecho condujo a que actualmente diferentes regiones del país no cuenten con información acerca de las propiedades y distribución de suelos a una escala adecuada para la toma de decisiones. En este contexto, en el 2018 se crea la Red Nacional de Reconocedores de Suelos (RNRS) que organiza las capacidades técnicas y operativas a nivel nacional para dar pronta respuesta a la creciente demanda de cartografía. Se trata de un equipo interinstitucional e interdisciplinario de especialistas distribuidos por todo el país, que realiza tareas de relevamiento, produce y difunde cartografía básica y utilitaria de suelos, ofrece capacitación y genera espacios de discusión y actualización metodológica. A la fecha, la RNRS ha relevado aproximadamente 760.000 ha en el sur de Córdoba, estimando completar durante el presente año el relevamiento del departamento Río Cuarto. Esta estrategia organizacional permitirá avanzar en el mapeo semidetallado de suelos en nuestro país, estableciendo vinculaciones sinérgicas entre profesionales de diferentes instituciones a fin de fortalecer y potenciar los equipos de trabajo en cada región. El motivo de esta contribución es presentar la RNRS, sus objetivos, avances a la fecha y desafíos a futuro, haciendo una breve revisión del estado actual de los relevamientos a escala semidetallada en nuestro país.Fil: Moretti, Lucas M. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Cerro Azul; ArgentinaFil: Rodriguez, Darío M. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; ArgentinaFil: Schulz, Guillermo A. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; ArgentinaFil: Kurtz, Ditmar Bernardo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Corrientes; ArgentinaFil: Altamirano D. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi; ArgentinaFil: Amin, S. Universidad Nacional de Río Cuarto; ArgentinaFil: Angelini, Marcos Esteban. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; Argentina. Wageningen University. Soil Geography and Landscape group; Holanda. International Soil Reference and Information Centre. World Soil Information; HolandaFil: Babelis, German Claudio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria San Juan; ArgentinaFil: Becerra, Alejandra Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Bedendo, Dante Julian. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná; ArgentinaFil: Boldrini, C. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez. Agencia de Extensión Rural Río Cuarto; AgentinaFil: Bongiovanni, C. Universidad Nacional de Río Cuarto; ArgentinaFil: Bozzer, S. Universidad Nacional de Río Cuarto; ArgentinaFil: Cabrera, A. Universidad Nacional de Río Cuarto; ArgentinaFil: Canale, A. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez. Agencia de Extensión Rural Río Cuarto; AgentinaFil: Chilano, Y. Universidad Nacional de Río Cuarto; ArgentinaFil: Cholaky, Carmen. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria; ArgentinaFil: Cisneros; José Manuel. Universidad Nacional de Río Cuarto. Cátedra de Uso y Manejo de Suelos; ArgentinaFil: Colazo, Juan Cruz. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria San Luis; ArgentinaFil: Corigliano, J. Universidad Nacional de Río Cuarto; ArgentinaFil: Degioanni, Américo José. Universidad Nacional Río Cuarto. Facultad de Agronomía y Veterinaria. Departamento de Ecología Agraria; ArgentinaFil: de la Fuente, Juan Carlos Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; ArgentinaFil: Escobar, Dardo. Ministerio de Agricultura, Ganadería y Pesca; ArgentinaFil: Faule, L. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi. Córdoba. ArgentinaFil: Galarza, Carlos Martin. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez; ArgentinaFil: González, J. Universidad Nacional de Río Cuarto; ArgentinaFil: Holzmann, R. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Alto Valle; ArgentinaFil: Irigoin, Julieta. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; Argentina. Universidad Nacional de Luján. Departamento Tecnología; ArgentinaFil: Lanfranco, M. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi; ArgentinaFil: León Giacosa, C. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Rafaela; ArgentinaFil: Matteio, J.P. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; ArgentinaFil: Márquez, C. Gobierno de Córdoba. Ministerio de Agricultura y Ganadería; ArgentinaFil: Marzari, R. Universidad Nacional de Río Cuarto; ArgentinaFil: Mattalia, M.L. Universidad Nacional de Río Cuarto; ArgentinaFil: Morales Poclava, P.C. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Salta; ArgentinaFil: Muñoz, S. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez; ArgentinaFil: Paladino, Ileana Ruth. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; Argentina. Universidad Nacional de Lomas de Zamora. Facultad de Ciencias Agrarias; ArgentinaFil: Parra, B. Universidad Nacional de Río Cuarto; ArgentinaFil: Pérez, M. Gobierno de Córdoba. Ministerio de Agricultura y Ganadería; ArgentinaFil: Pezzola, A. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Hilario Ascasubi; ArgentinaFil: Perucca, S. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez. Agencia de Extensión Rural Río Cuarto; ArgentinaFil: Porcel de Peralta, R. Gobierno de Córdoba. Ministerio de Agricultura y Ganadería; ArgentinaFil: Renaudeau, S. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Corrientes; ArgentinaFil: Salustio, M. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez. Agencia de Extensión Rural Río Cuarto; ArgentinaFil: Sapino, V. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Rafaela; ArgentinaFil: Tenti Vuegen, L.M. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos. ArgentinaFil: Tosolini, R. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Rafaela; ArgentinaFil: Vicondo, M.E. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi; Argentina. Universidad Nacional de Córdoba. ArgentinaFil: Vizgarra, L.A. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Quimili; ArgentinaFil: Ybarra, D.D. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Corrientes; ArgentinaFil: Winschel, C. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Hilario Ascasubi; ArgentinaFil: Zamora, E. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Corrientes; Argentin

Effects of Kifunensine on Production and N-Glycosylation Modification of Butyrylcholinesterase in a Transgenic Rice Cell Culture Bioreactor.

The production and N-glycosylation of recombinant human butyrylcholinesterase (BChE), a model highly glycosylated therapeutic protein, in a transgenic rice cell suspension culture treated with kifunensine, a strong α-mannosidase I inhibitor, was studied in a 5 L bioreactor. A media exchange was performed at day 7 of cultivation by removing spent sugar-rich medium (NB+S) and adding fresh sugar-free (NB-S) medium to induce the rice α-amylase 3D (RAmy3D) promoter to produce rice recombinant human BChE (rrBChE). Using a 1.25X-concentrated sugar-free medium together with an 80% reduced working volume during the media exchange led to a total active rrBChE production level of 79 ± 2 µg (g FW)-1 or 7.5 ± 0.4 mg L-1 in the presence of kifunensine, which was 1.5-times higher than our previous bioreactor runs using normal sugar-free (NB-S) media with no kifunensine treatment. Importantly, the amount of secreted active rrBChE in culture medium was enhanced in the presence of kifunensine, comprising 44% of the total active rrBChE at day 5 following induction. Coomassie-stained SDS-PAGE gel and Western blot analyses revealed different electrophoretic migration of purified rrBChE bands with and without kifunensine treatment, which was attributed to different N-glycoforms. N-Glycosylation analysis showed substantially increased oligomannose glycans (Man5/6/7/8) in rrBChE treated with kifunensine compared to controls. However, the mass-transfer limitation of kifunensine was likely the major reason for incomplete inhibition of α-mannosidase I in this bioreactor study

Effects of Kifunensine on Production and N-Glycosylation Modification of Butyrylcholinesterase in a Transgenic Rice Cell Culture Bioreactor.

The production and N-glycosylation of recombinant human butyrylcholinesterase (BChE), a model highly glycosylated therapeutic protein, in a transgenic rice cell suspension culture treated with kifunensine, a strong α-mannosidase I inhibitor, was studied in a 5 L bioreactor. A media exchange was performed at day 7 of cultivation by removing spent sugar-rich medium (NB+S) and adding fresh sugar-free (NB-S) medium to induce the rice α-amylase 3D (RAmy3D) promoter to produce rice recombinant human BChE (rrBChE). Using a 1.25X-concentrated sugar-free medium together with an 80% reduced working volume during the media exchange led to a total active rrBChE production level of 79 ± 2 µg (g FW)-1 or 7.5 ± 0.4 mg L-1 in the presence of kifunensine, which was 1.5-times higher than our previous bioreactor runs using normal sugar-free (NB-S) media with no kifunensine treatment. Importantly, the amount of secreted active rrBChE in culture medium was enhanced in the presence of kifunensine, comprising 44% of the total active rrBChE at day 5 following induction. Coomassie-stained SDS-PAGE gel and Western blot analyses revealed different electrophoretic migration of purified rrBChE bands with and without kifunensine treatment, which was attributed to different N-glycoforms. N-Glycosylation analysis showed substantially increased oligomannose glycans (Man5/6/7/8) in rrBChE treated with kifunensine compared to controls. However, the mass-transfer limitation of kifunensine was likely the major reason for incomplete inhibition of α-mannosidase I in this bioreactor study

Global variation in postoperative mortality and complications after cancer surgery: a multicentre, prospective cohort study in 82 countries

© 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 licenseBackground: 80% of individuals with cancer will require a surgical procedure, yet little comparative data exist on early outcomes in low-income and middle-income countries (LMICs). We compared postoperative outcomes in breast, colorectal, and gastric cancer surgery in hospitals worldwide, focusing on the effect of disease stage and complications on postoperative mortality. Methods: This was a multicentre, international prospective cohort study of consecutive adult patients undergoing surgery for primary breast, colorectal, or gastric cancer requiring a skin incision done under general or neuraxial anaesthesia. The primary outcome was death or major complication within 30 days of surgery. Multilevel logistic regression determined relationships within three-level nested models of patients within hospitals and countries. Hospital-level infrastructure effects were explored with three-way mediation analyses. This study was registered with ClinicalTrials.gov, NCT03471494. Findings: Between April 1, 2018, and Jan 31, 2019, we enrolled 15 958 patients from 428 hospitals in 82 countries (high income 9106 patients, 31 countries; upper-middle income 2721 patients, 23 countries; or lower-middle income 4131 patients, 28 countries). Patients in LMICs presented with more advanced disease compared with patients in high-income countries. 30-day mortality was higher for gastric cancer in low-income or lower-middle-income countries (adjusted odds ratio 3·72, 95% CI 1·70–8·16) and for colorectal cancer in low-income or lower-middle-income countries (4·59, 2·39–8·80) and upper-middle-income countries (2·06, 1·11–3·83). No difference in 30-day mortality was seen in breast cancer. The proportion of patients who died after a major complication was greatest in low-income or lower-middle-income countries (6·15, 3·26–11·59) and upper-middle-income countries (3·89, 2·08–7·29). Postoperative death after complications was partly explained by patient factors (60%) and partly by hospital or country (40%). The absence of consistently available postoperative care facilities was associated with seven to 10 more deaths per 100 major complications in LMICs. Cancer stage alone explained little of the early variation in mortality or postoperative complications. Interpretation: Higher levels of mortality after cancer surgery in LMICs was not fully explained by later presentation of disease. The capacity to rescue patients from surgical complications is a tangible opportunity for meaningful intervention. Early death after cancer surgery might be reduced by policies focusing on strengthening perioperative care systems to detect and intervene in common complications. Funding: National Institute for Health Research Global Health Research Unit

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

© 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licenseBackground: Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide. Methods: A multimethods analysis was performed as part of the GlobalSurg 3 study—a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital. Findings: Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3·85 [95% CI 2·58–5·75]; p<0·0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63·0% vs 82·7%; OR 0·35 [0·23–0·53]; p<0·0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer. Interpretation: Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised. Funding: National Institute for Health and Care Research