Emisiones de gases de efecto invernadero: simulación de un sistema ganadero de carne típico de la región central Argentina

La demanda global de alimentos estimula el aumento de la producción agro-ganadera para garantizar la disponibilidad alimentaria pero, a la vez, plantea desafíos en cuanto al aumento en las emisiones de gases de efecto invernadero. Existen claras evidencias que la ganadería bovina contribuye de forma importante, directa e indirectamente, a estas emisiones. Sin embargo, no es claro el aporte relativo de los diferentes subsistemas de producción ganaderos, como la cría, la recría y la terminación o engorde. En este trabajo, estimamos las emisiones de metano (CH4 ) y óxido nitroso (N2 O) que producen los subsistemas de cría, recría y terminación en un sistema ganadero típico de la región central Argentina, en la provincia de San Luis. Para estas estimaciones, se utilizó el nivel 2 de la metodología recomendada por el Grupo Intergubernamental de Expertos sobre el Cambio Climático (IPCC, 2006). Las emisiones promedio para todo el sistema fueron de 1.500 kg eq-CO2 por animal al año. De este total, el 76% corresponden a las emisiones de CH4 y el 24% a las emisiones de N2 O. En los subsistemas de cría y recría, la mayor emisión de gases también corresponde a CH4 , pero en la etapa de terminación es mayor la emisión de N2 O. En la cría, la categoría vaca en lactancia fue la que tuvo mayor cantidad de emisiones de CH4 (2.407 eq-CO2 /animal), seguida de la categoría toros (2.306 eqCO2 /animal); en la recría, los novillos fueron las categorías que mayor emisión de CH4 (1.100 eq-CO2 /animal) y N2 O (324 eq-CO2 /animal) produjeron. En terminación, emitieron mayor cantidad de N2 O la vaca cut (vaca criando último ternero) (728 eq-CO2 /animal) seguida de la categoría toro (549 eq-CO2 /animal). Con el análisis de regresión de mínimos cuadrados parciales (PLS) se observó una estrecha relación entre las variables predictoras (consumo del animal y peso), como así también las variables respuestas (CH4 y N2 O). A su vez, el CH4 es la variable que más se asocia a las variables de clasificación (subsistemas ganaderos) observándose mayor relación con la cría. Estas emisiones de gases de efecto invernadero producidas por el ganado bovino podrían reducirse aplicando distintas estrategias tecnológicas: i) vinculadas a la alimentación manejando la dieta de los rumiantes; ii) relativas a la composición del rodeo realizando una exhaustiva selección de categorías evitando animales improductivos; iii) observando la salud del animal y iv) procurando ajustar la genética del animal al ambiente y al producto que se quiera obtener.The global food demand stimulates livestock production to ensure food availability, but it may also represent a problem in terms of increasing emissions of greenhouse gases. There are clear evidences that the cattle industry directly and indirectly contributes, in an important way, to these gases emissions. However, it is unclear the relative contribution of the each subsystems of livestock production, such as breeding, calf rearing and fattening. Here we estimate the emissions of methane (CH4 ) and nitrous oxide (N2 O) produced by the three subsystems in a typical beef livestock system in San Luis province at central Argentina. For these estimates we used the level 2 of the methodology recommended by the Intergovernmental Panel on Climate Change (IPCC 2006). The average emissions for the entire system were 1.500 kg eq-CO2 , per animal and year. From this total, 76% are CH4 and 24% are N2 O emissions. In the breeding and rearing subsystems, the major emission also corresponds to CH4 , but in the fattening stage, N2 O emissions are higher. In breeding, lactating cow was the animal class that had the most amounts of CH4 emissions (2.407 kg eq-CO2 /animal), followed by bulls class (2.306 kg eq-CO2 /animal); in rearing, steers were the class that increased emission of CH4 (1.100 kg eq-CO2 /animal) and N2 O (324 kg eq-CO2 /animal), produced. In fattening, culled cows (cow breeding last calf) (728 kg eq-CO2 / animal) emitted larger amount of N2 O followed by the bull class (549 kg eq-CO2 /animal). With the analysis of partial least squares regression (PLS) a close relationship between the predictor variables (consumption and animal weight) as well as variable responses (CH4 and N2 O) was observed. In turn, the CH4 is the variable that is associated with the classification variables (livestock subsystems) observed greater relationship with farming. These emissions of greenhouse gases produced by cattle could be reduced by applying different technological strategies: i) related to food handling ruminant diet ii) concerning the composition of the rodeo conducting a comprehensive selection of animal classes avoiding unproductive animals; iii) to monitor animal health and iv) seeking for adequate animal genetics to the environment and the animal products to be obtained.EEA San LuisFil: Nieto, Maria Isabel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria San Luis; ArgentinaFil: Guzman, M.L. Universidad Nacional de San Luis. Facultad de Ingeniería y Ciencias Económicas Sociales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Stenaiker, D. University of Regina. Department of Biology; Canad

PhiGO 2020 stakeholder workshop : information dissemination and data portal design

This report presents the summarised responses from participants at two stakeholder workshops, held in Iloilo and Pampanga, between 28th January and 5th of February 2020. The workshop focus centred on how stakeholders access hydrological information relevant to their jobs, and the required format that this data needs to take. Participants were asked about their current access routes to information, and their ideal access platform/web portal for hydrological data. This was so that the outputs of the PhiGO project could be tailored to meet as many stakeholder requirements as possible. Stakeholders clearly identified several common points for data access and formats across a number of sectors, and both in their professional and personal environments. Stakeholders required that data is predominantly visual, with a strong focus on maps, figures, and graphs, but backed up by information that can be interrogated, whether that be tabular data or summarised reports. Stakeholders desired a web portal that needed to be clean and easy to use, with guidance for navigation and explanation of complex terms. Detailed information must also be readily available, and the data should be available for offline downloading. The feedback from these stakeholders will feed directly into the final design of the PhiGO data portal

Cranberry A-type proanthocyanidins selectively target acute myeloid leukemia cells

Most elderly patients affected with acute myeloid leukemia (AML) will relapse and die of their disease even after achieving complete remission, thus emphasizing the urgent need for new therapeutic approaches with minimum toxicity to normal hematopoietic cells. Cranberry (Vaccinium spp.) extracts have exhibited anticancer and chemopreventive properties that have been mostly attributed to A-type proanthocyanidin (A-PAC) compounds. A-PACs, isolated from a commercially available cranberry extract, were evaluated for their effects on leukemia cell lines, primary AML samples, and normal CD34+ cord blood specimens. Our results indicated potent and specific antileukemia activity in vitro. In addition, the antileukemia activity of A-PACs extended to malignant progenitor and stem cell populations, sparing their normal counterparts. The antileukemia effects of A-PACs were also observed in vivo using patient derived xenografts. Surprisingly, we found that the mechanism of cell death was driven by activation of NF-κB. Overall, our data suggest that A-PACs could be used to improve treatments for AML by targeting leukemia stem cells through a potentially novel pathway

Updates on radiotherapy-immunotherapy combinations: Proceedings of 6th annual ImmunoRad conference.

Focal radiation therapy (RT) has attracted considerable attention as a combinatorial partner for immunotherapy (IT), largely reflecting a well-defined, predictable safety profile and at least some potential for immunostimulation. However, only a few RT-IT combinations have been tested successfully in patients with cancer, highlighting the urgent need for an improved understanding of the interaction between RT and IT in both preclinical and clinical scenarios. Every year since 2016, ImmunoRad gathers experts working at the interface between RT and IT to provide a forum for education and discussion, with the ultimate goal of fostering progress in the field at both preclinical and clinical levels. Here, we summarize the key concepts and findings presented at the Sixth Annual ImmunoRad conference

The comparative responsiveness of Hospital Universitario Princesa Index and other composite indices for assessing rheumatoid arthritis activity

Objective To evaluate the responsiveness in terms of correlation of the Hospital Universitario La Princesa Index (HUPI) comparatively to the traditional composite indices used to assess disease activity in rheumatoid arthritis (RA), and to compare the performance of HUPI-based response criteria with that of the EULAR response criteria. Methods Secondary data analysis from the following studies: ACT-RAY (clinical trial), PROAR (early RA cohort) and EMECAR (pre-biologic era long term RA cohort). Responsiveness was evaluated by: 1) comparing change from baseline (Delta) of HUPI with Delta in other scores by calculating correlation coefficients; 2) calculating standardised effect sizes. The accuracy of response by HUPI and by EULAR criteria was analyzed using linear regressions in which the dependent variable was change in global assessment by physician (Delta GDA-Phy). Results Delta HUPI correlation with change in all other indices ranged from 0.387 to 0.791); HUPI's standardized effect size was larger than those from the other indices in each database used. In ACT-RAY, depending on visit, between 65 and 80% of patients were equally classified by HUPI and EULAR response criteria. However, HUPI criteria were slightly more stringent, with higher percentage of patients classified as non-responder, especially at early visits. HUPI response criteria showed a slightly higher accuracy than EULAR response criteria when using Delta GDA-Phy as gold standard. Conclusion HUPI shows good responsiveness in terms of correlation in each studied scenario (clinical trial, early RA cohort, and established RA cohort). Response criteria by HUPI seem more stringent than EULAR''s

Genome-wide association study identifies 30 Loci Associated with Bipolar Disorder

This paper is dedicated to the memory of Psychiatric Genomics Consortium (PGC) founding member and Bipolar disorder working group co-chair Pamela Sklar. We thank the participants who donated their time, experiences and DNA to this research, and to the clinical and scientific teams that worked with them. We are deeply indebted to the investigators who comprise the PGC. The views expressed are those of the authors and not necessarily those of any funding or regulatory body. Analyses were carried out on the NL Genetic Cluster Computer (http://www.geneticcluster.org ) hosted by SURFsara, and the Mount Sinai high performance computing cluster (http://hpc.mssm.edu).Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P<1x10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (GWS, p < 5x10-8) in the discovery GWAS were not GWS in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis 30 loci were GWS including 20 novel loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene-sets including regulation of insulin secretion and endocannabinoid signaling. BDI is strongly genetically correlated with schizophrenia, driven by psychosis, whereas BDII is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential new biological mechanisms for BD.This work was funded in part by the Brain and Behavior Research Foundation, Stanley Medical Research Institute, University of Michigan, Pritzker Neuropsychiatric Disorders Research Fund L.L.C., Marriot Foundation and the Mayo Clinic Center for Individualized Medicine, the NIMH Intramural Research Program; Canadian Institutes of Health Research; the UK Maudsley NHS Foundation Trust, NIHR, NRS, MRC, Wellcome Trust; European Research Council; German Ministry for Education and Research, German Research Foundation IZKF of Münster, Deutsche Forschungsgemeinschaft, ImmunoSensation, the Dr. Lisa-Oehler Foundation, University of Bonn; the Swiss National Science Foundation; French Foundation FondaMental and ANR; Spanish Ministerio de Economía, CIBERSAM, Industria y Competitividad, European Regional Development Fund (ERDF), Generalitat de Catalunya, EU Horizon 2020 Research and Innovation Programme; BBMRI-NL; South-East Norway Regional Health Authority and Mrs. Throne-Holst; Swedish Research Council, Stockholm County Council, Söderström Foundation; Lundbeck Foundation, Aarhus University; Australia NHMRC, NSW Ministry of Health, Janette M O'Neil and Betty C Lynch

Description of Atmospheric Conditions at the Pierre Auger Observatory using the Global Data Assimilation System (GDAS)

Atmospheric conditions at the site of a cosmic ray observatory must be known for reconstructing observed extensive air showers. The Global Data Assimilation System (GDAS) is a global atmospheric model predicated on meteorological measurements and numerical weather predictions. GDAS provides altitude-dependent profiles of the main state variables of the atmosphere like temperature, pressure, and humidity. The original data and their application to the air shower reconstruction of the Pierre Auger Observatory are described. By comparisons with radiosonde and weather station measurements obtained on-site in Malarg\"ue and averaged monthly models, the utility of the GDAS data is shown

Mapping geographical inequalities in childhood diarrhoeal morbidity and mortality in low-income and middle-income countries, 2000–17 : analysis for the Global Burden of Disease Study 2017

Background Across low-income and middle-income countries (LMICs), one in ten deaths in children younger than 5 years is attributable to diarrhoea. The substantial between-country variation in both diarrhoea incidence and mortality is attributable to interventions that protect children, prevent infection, and treat disease. Identifying subnational regions with the highest burden and mapping associated risk factors can aid in reducing preventable childhood diarrhoea. Methods We used Bayesian model-based geostatistics and a geolocated dataset comprising 15 072 746 children younger than 5 years from 466 surveys in 94 LMICs, in combination with findings of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017, to estimate posterior distributions of diarrhoea prevalence, incidence, and mortality from 2000 to 2017. From these data, we estimated the burden of diarrhoea at varying subnational levels (termed units) by spatially aggregating draws, and we investigated the drivers of subnational patterns by creating aggregated risk factor estimates. Findings The greatest declines in diarrhoeal mortality were seen in south and southeast Asia and South America, where 54·0% (95% uncertainty interval [UI] 38·1–65·8), 17·4% (7·7–28·4), and 59·5% (34·2–86·9) of units, respectively, recorded decreases in deaths from diarrhoea greater than 10%. Although children in much of Africa remain at high risk of death due to diarrhoea, regions with the most deaths were outside Africa, with the highest mortality units located in Pakistan. Indonesia showed the greatest within-country geographical inequality; some regions had mortality rates nearly four times the average country rate. Reductions in mortality were correlated to improvements in water, sanitation, and hygiene (WASH) or reductions in child growth failure (CGF). Similarly, most high-risk areas had poor WASH, high CGF, or low oral rehydration therapy coverage. Interpretation By co-analysing geospatial trends in diarrhoeal burden and its key risk factors, we could assess candidate drivers of subnational death reduction. Further, by doing a counterfactual analysis of the remaining disease burden using key risk factors, we identified potential intervention strategies for vulnerable populations. In view of the demands for limited resources in LMICs, accurately quantifying the burden of diarrhoea and its drivers is important for precision public health

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: A systematic analysis for the Global Burden of Disease Study 2015

Background: The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods: We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings: Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation: Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding: Bill & Melinda Gates Foundation