Emigration in Paraguay: effects of remittances

Neste trabalho analisou-se o impacto das remessas financeiras sobre os patrimônios dos ativos nos domicílios, no país de origem. Utilizamos dados da Encuesta Permanente de Hogares de 2008, os quais foram fornecidos pelo órgão Dirección General de Estadística, Encuestas y Censos do Paraguai. Com estes dados realizamos uma comparação entre os domicílios com e sem remessas, independente de terem ou não emigrantes. A metodologia utilizada para realizar a comparação foi o Propensity Score Matching (PSM) com dois algoritmos, Vizinhos Próximos e Kernel. Os patrimônios dos ativos são carros, aluguéis e combinados. Os resultados em todos os casos foram estatisticamente significativos, porém, negativos. Com amesma metodologia e os mesmos dados, comparamos apenas os domicílios com emigrantes, e os resultados continuaram negativos, porém, com nível de significância menor.In this study we analyzed the impact of remittances on financial assets in the wealth of households in the country of origin. We use data from the Encuesta Permanente Hogares 2008, which were provided by the agency Dirección General de Estadística, Encuestas y Censos of Paraguay. With these data we performed a comparison between households with and without remittances, regardless of whether or not immigrants. The methodology for conducting the comparison was the Propensity Score Matching (PSM) with two algorithms, Kernel and Nearest Neighbors. The stockholders\' assets are cars, rentals and combined. The results in all cases were statistically significant, but negative. With the same methodology and same data, comparing only households with migrants, the results remained negative, but with lower significance level

Educación ambiental y jóvenes: Influencia de las creencias y actitudes en comportamientos pro-ambientales en estudiantes de noveno grado, del departamento Central - Paraguay

The objective of this study was to analyze the influence of belief and attitudes the ninth grade students toward pro-environmental behaviors. The data were collected from non-probabilistic sample from public school of the Central Department from Paraguay. We apply a Likert questionnaire to 200 students from ninth grade, sort out items such as beliefs, attitudes and behaviors. The methodology applied was the chi-square test where we want to relate the beliefs to attitudes and sustainable behaviors. The results suggest that general beliefs about the importance of environment they do not have implicance in attitudes and behaviors environmental, however, when the beliefs are specific, and clearly wrong, the consequences in the actions are not in lines with the sustainability of the environment are clear. Hence, is very important to rethink about Paraguay environmental education and arise actions strategy that implies the involvement and coordination with different sectors of society.El objetivo del presente trabajo fue analizar la influencia que ejercen las creencias y actitudes de los estudiantes de noveno grado hacia comportamientos pro-ambientales. Para ello se realizó una muestra no probabilística de colegios de gestión oficial del departamento Central de Paraguay, se aplicó un cuestionario con escala tipo Likert a 200 estudiantes de noveno grado, con ítems clasificados en creencias, actitudes y comportamientos. A partir de las respuestas se aplicó el análisis estadístico de chi-X2, donde se buscaba relacionar las creencias con actitudes y comportamientos sostenibles. Resultó que cuando se trata de creencias generales sobre la importancia del medio ambiente, no tienen implicancia en las actitudes y comportamientos ambientales responsables, sin embargo, cuando estas creencias son sobre cuestiones específicas, y claramente erradas, las consecuencias en acciones no acordes con la sostenibilidad del medio son claras. Por lo tanto, es importante repensar sobre la educación ambiental en Paraguay y plantearse estrategias de acción que implique el involucramiento y coordinación con los diferentes sectores de la sociedad

Educación ambiental y jóvenes: Influencia de las creencias y actitudes en comportamientos pro-ambientales en estudiantes de noveno grado, del departamento Central - Paraguay

El objetivo del presente trabajo fue analizar la influencia que ejercen las creencias y actitudes de los estudiantes de noveno grado hacia comportamientos pro-ambientales. Para ello se realizó una muestra no probabilística de colegios de gestión oficial del departamento Central de Paraguay, se aplicó un cuestionario con escala tipo Likert, a 200 estudiantes de noveno grado, con ítems clasificados en creencias, actitudes y comportamientos. A partir de las respuestas se aplicó el análisis estadístico de chi-X2, donde se buscaba relacionar las creencias con actitudes y comportamientos sostenibles. Resultó que cuando se trata de creencias generales sobre la importancia del medio ambiente, no tienen implicancia en las actitudes y comportamientos ambientales responsables, sin embargo, cuando estas creencias son sobre cuestiones específicas, y claramente erradas, las consecuencias en acciones no acordes con la sostenibilidad del medio son claras

GWAS and meta-analysis identifies 49 genetic variants underlying critical COVID-19

Data availability: Downloadable summary data are available through the GenOMICC data site (https://genomicc.org/data). Summary statistics are available, but without the 23andMe summary statistics, except for the 10,000 most significant hits, for which full summary statistics are available. The full GWAS summary statistics for the 23andMe discovery dataset will be made available through 23andMe to qualified researchers under an agreement with 23andMe that protects the privacy of the 23andMe participants. For further information and to apply for access to the data, see the 23andMe website (https://research.23andMe.com/dataset-access/). All individual-level genotype and whole-genome sequencing data (for both academic and commercial uses) can be accessed through the UKRI/HDR UK Outbreak Data Analysis Platform (https://odap.ac.uk). A restricted dataset for a subset of GenOMICC participants is also available through the Genomics England data service. Monocyte RNA-seq data are available under the title ‘Monocyte gene expression data’ within the Oxford University Research Archives (https://doi.org/10.5287/ora-ko7q2nq66). Sequencing data will be made freely available to organizations and researchers to conduct research in accordance with the UK Policy Framework for Health and Social Care Research through a data access agreement. Sequencing data have been deposited at the European Genome–Phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGAS00001007111.Extended data figures and tables are available online at https://www.nature.com/articles/s41586-023-06034-3#Sec21 .Supplementary information is available online at https://www.nature.com/articles/s41586-023-06034-3#Sec22 .Code availability: Code to calculate the imputation of P values on the basis of SNPs in linkage disequilibrium is available at GitHub (https://github.com/baillielab/GenOMICC_GWAS).Acknowledgements: We thank the members of the Banco Nacional de ADN and the GRA@CE cohort group; and the research participants and employees of 23andMe for making this work possible. A full list of contributors who have provided data that were collated in the HGI project, including previous iterations, is available online (https://www.covid19hg.org/acknowledgements).Change history: 11 July 2023: A Correction to this paper has been published at: https://doi.org/10.1038/s41586-023-06383-z. -- In the version of this article initially published, the name of Ana Margarita Baldión-Elorza, of the SCOURGE Consortium, appeared incorrectly (as Ana María Baldion) and has now been amended in the HTML and PDF versions of the article.Copyright © The Author(s) 2023, Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte–macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).GenOMICC was funded by Sepsis Research (the Fiona Elizabeth Agnew Trust), the Intensive Care Society, a Wellcome Trust Senior Research Fellowship (to J.K.B., 223164/Z/21/Z), the Department of Health and Social Care (DHSC), Illumina, LifeArc, the Medical Research Council, UKRI, a BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070 and BBS/E/D/30002275) and UKRI grants MC_PC_20004, MC_PC_19025, MC_PC_1905 and MRNO2995X/1. A.D.B. acknowledges funding from the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z), the Edinburgh Clinical Academic Track (ECAT) programme. This research is supported in part by the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant MC_PC_20029). Laboratory work was funded by a Wellcome Intermediate Clinical Fellowship to B.F. (201488/Z/16/Z). We acknowledge the staff at NHS Digital, Public Health England and the Intensive Care National Audit and Research Centre who provided clinical data on the participants; and the National Institute for Healthcare Research Clinical Research Network (NIHR CRN) and the Chief Scientist’s Office (Scotland), who facilitate recruitment into research studies in NHS hospitals, and to the global ISARIC and InFACT consortia. GenOMICC genotype controls were obtained using UK Biobank Resource under project 788 funded by Roslin Institute Strategic Programme Grants from the BBSRC (BBS/E/D/10002070 and BBS/E/D/30002275) and Health Data Research UK (HDR-9004 and HDR-9003). UK Biobank data were used in the GSMR analyses presented here under project 66982. The UK Biobank was established by the Wellcome Trust medical charity, Medical Research Council, Department of Health, Scottish Government and the Northwest Regional Development Agency. It has also had funding from the Welsh Assembly Government, British Heart Foundation and Diabetes UK. The work of L.K. was supported by an RCUK Innovation Fellowship from the National Productivity Investment Fund (MR/R026408/1). J.Y. is supported by the Westlake Education Foundation. SCOURGE is funded by the Instituto de Salud Carlos III (COV20_00622 to A.C., PI20/00876 to C.F.), European Union (ERDF) ‘A way of making Europe’, Fundación Amancio Ortega, Banco de Santander (to A.C.), Cabildo Insular de Tenerife (CGIEU0000219140 ‘Apuestas científicas del ITER para colaborar en la lucha contra la COVID-19’ to C.F.) and Fundación Canaria Instituto de Investigación Sanitaria de Canarias (PIFIISC20/57 to C.F.). We also acknowledge the contribution of the Centro National de Genotipado (CEGEN) and Centro de Supercomputación de Galicia (CESGA) for funding this project by providing supercomputing infrastructures. A.D.L. is a recipient of fellowships from the National Council for Scientific and Technological Development (CNPq)-Brazil (309173/2019-1 and 201527/2020-0)