Spatial characterization of climatic variables for Arica-Parinacota and Tarapacá, Chile using topoclimatic analysis

In the present study, models were developed to determine the monthly and annual spatio-temporal variation of temperature, precipitation, and solar radiation based on topoclimatic analysis of Arica-Parinacota and Tarapacá in northern Chile. To construct the equations of the topoclimatic model, the data from meteorological stations and physiographic factors (latitude, longitude, altitude, and distance to bodies of water) obtained from a digital terrain model with a resolution of 90 m were compiled in a database. The equations of the topoclimatic model were generated by a stepwise regression with a backward selection technique. The equations for average monthly temperature, precipitation, and solar radiation were determined by linear combinations. The results were statistically significant with coefficients of determination greater than 90%, in addition to being greater than the existing climate databases for this area

The Science Performance of JWST as Characterized in Commissioning

This paper characterizes the actual science performance of the James Webb Space Telescope (JWST), as determined from the six month commissioning period. We summarize the performance of the spacecraft, telescope, science instruments, and ground system, with an emphasis on differences from pre-launch expectations. Commissioning has made clear that JWST is fully capable of achieving the discoveries for which it was built. Moreover, almost across the board, the science performance of JWST is better than expected; in most cases, JWST will go deeper faster than expected. The telescope and instrument suite have demonstrated the sensitivity, stability, image quality, and spectral range that are necessary to transform our understanding of the cosmos through observations spanning from near-earth asteroids to the most distant galaxies.Comment: 5th version as accepted to PASP; 31 pages, 18 figures; https://iopscience.iop.org/article/10.1088/1538-3873/acb29

The James Webb Space Telescope Mission

Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least $4m$. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the $6.5m$ James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 years, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit.Comment: Accepted by PASP for the special issue on The James Webb Space Telescope Overview, 29 pages, 4 figure

Monthly calibration of Hargreaves – Samani equation using remote sensing and topoclimatology in central southern Chile

Reference evapotranspiration (ETo) has a key role in irrigation scheduling. In this sense, the Hargreaves-Samani equation (HS) is a reliable and widely used method to estimate ETo. The HS equation just requires temperature and solar radiation data, making it a suitable method for places that lack of wind speed and relative humidity information. However, literature shows that a local calibration of its empiric parameter is needed for its complete application. This work shows a calibration for the Maule region in central-southern Chile. For this purpose, the Penman-Monteith equation from FAO-56 (PM) was considered as a reference, using a network of 400 meteorological stations between the 32 degrees and 39 degrees of south latitude for the 1973-2011 period. The calibration was based on the computation of the ratio of ETo calculated by HS and PM and the spatial behaviour of input variables and parameters. The spatial distribution was done by geographical weighted regression and ordinary Kriging with a linear variogram, assisted by a digital elevation model from the Shuttle Radar Topography Mission and surface reflectances from Moderate Resolution Imaging Spectroradiometer. The process of calibration was validated with daily data through all months, with comparative errors of 5% against PM.Universidad de Talca FONDECYT 1130139 1020202 116180

Odanacatib for the treatment of postmenopausal osteoporosis : Results of the LOFT multicentre, randomised, double-blind, placebo-controlled trial and LOFT Extension study

Background Odanacatib, a cathepsin K inhibitor, reduces bone resorption while maintaining bone formation. Previous work has shown that odanacatib increases bone mineral density in postmenopausal women with low bone mass. We aimed to investigate the efficacy and safety of odanacatib to reduce fracture risk in postmenopausal women with osteoporosis. Methods The Long-term Odanacatib Fracture Trial (LOFT) was a multicentre, randomised, double-blind, placebo-controlled, event-driven study at 388 outpatient clinics in 40 countries. Eligible participants were women aged at least 65 years who were postmenopausal for 5 years or more, with a femoral neck or total hip bone mineral density T-score between −2·5 and −4·0 if no previous radiographic vertebral fracture, or between −1·5 and −4·0 with a previous vertebral fracture. Women with a previous hip fracture, more than one vertebral fracture, or a T-score of less than −4·0 at the total hip or femoral neck were not eligible unless they were unable or unwilling to use approved osteoporosis treatment. Participants were randomly assigned (1:1) to either oral odanacatib (50 mg once per week) or matching placebo. Randomisation was done using an interactive voice recognition system after stratification for previous radiographic vertebral fracture, and treatment was masked to study participants, investigators and their staff, and sponsor personnel. If the study completed before 5 years of double-blind treatment, consenting participants could enrol in a double-blind extension study (LOFT Extension), continuing their original treatment assignment for up to 5 years from randomisation. Primary endpoints were incidence of vertebral fractures as assessed using radiographs collected at baseline, 6 and 12 months, yearly, and at final study visit in participants for whom evaluable radiograph images were available at baseline and at least one other timepoint, and hip and non-vertebral fractures adjudicated as being a result of osteoporosis as assessed by clinical history and radiograph. Safety was assessed in participants who received at least one dose of study drug. The adjudicated cardiovascular safety endpoints were a composite of cardiovascular death, myocardial infarction, or stroke, and new-onset atrial fibrillation or flutter. Individual cardiovascular endpoints and death were also assessed. LOFT and LOFT Extension are registered with ClinicalTrials.gov (number NCT00529373) and the European Clinical Trials Database (EudraCT number 2007-002693-66). Findings Between Sept 14, 2007, and Nov 17, 2009, we randomly assigned 16 071 evaluable patients to treatment: 8043 to odanacatib and 8028 to placebo. After a median follow-up of 36·5 months (IQR 34·43–40·15) 4297 women assigned to odanacatib and 3960 assigned to placebo enrolled in LOFT Extension (total median follow-up 47·6 months, IQR 35·45–60·06). In LOFT, cumulative incidence of primary outcomes for odanacatib versus placebo were: radiographic vertebral fractures 3·7% (251/6770) versus 7·8% (542/6910), hazard ratio (HR) 0·46, 95% CI 0·40–0·53; hip fractures 0·8% (65/8043) versus 1·6% (125/8028), 0·53, 0·39–0·71; non-vertebral fractures 5·1% (412/8043) versus 6·7% (541/8028), 0·77, 0·68–0·87; all p<0·0001. Combined results from LOFT plus LOFT Extension for cumulative incidence of primary outcomes for odanacatib versus placebo were: radiographic vertebral fractures 4·9% (341/6909) versus 9·6% (675/7011), HR 0·48, 95% CI 0·42–0·55; hip fractures 1·1% (86/8043) versus 2·0% (162/8028), 0·52, 0·40–0·67; non-vertebral fractures 6·4% (512/8043) versus 8·4% (675/8028), 0·74, 0·66–0·83; all p<0·0001. In LOFT, the composite cardiovascular endpoint of cardiovascular death, myocardial infarction, or stroke occurred in 273 (3·4%) of 8043 patients in the odanacatib group versus 245 (3·1%) of 8028 in the placebo group (HR 1·12, 95% CI 0·95–1·34; p=0·18). New-onset atrial fibrillation or flutter occurred in 112 (1·4%) of 8043 patients in the odanacatib group versus 96 (1·2%) of 8028 in the placebo group (HR 1·18, 0·90–1·55; p=0·24). Odanacatib was associated with an increased risk of stroke (1·7% [136/8043] vs 1·3% [104/8028], HR 1·32, 1·02–1·70; p=0·034), but not myocardial infarction (0·7% [60/8043] vs 0·9% [74/8028], HR 0·82, 0·58–1·15; p=0·26). The HR for all-cause mortality was 1·13 (5·0% [401/8043] vs 4·4% [356/8028], 0·98–1·30; p=0·10). When data from LOFT Extension were included, the composite of cardiovascular death, myocardial infarction, or stroke occurred in significantly more patients in the odanacatib group than in the placebo group (401 [5·0%] of 8043 vs 343 [4·3%] of 8028, HR 1·17, 1·02–1·36; p=0·029, as did stroke (2·3% [187/8043] vs 1·7% [137/8028], HR 1·37, 1·10–1·71; p=0·0051). Interpretation Odanacatib reduced the risk of fracture, but was associated with an increased risk of cardiovascular events, specifically stroke, in postmenopausal women with osteoporosis. Based on the overall balance between benefit and risk, the study's sponsor decided that they would no longer pursue development of odanacatib for treatment of osteoporosis

The Science Performance of JWST as Characterized in Commissioning

This paper characterizes the actual science performance of the James Webb Space Telescope (JWST), as determined from the six month commissioning period. We summarize the performance of the spacecraft, telescope, science instruments, and ground system, with an emphasis on differences from pre-launch expectations. Commissioning has made clear that JWST is fully capable of achieving the discoveries for which it was built. Moreover, almost across the board, the science performance of JWST is better than expected; in most cases, JWST will go deeper faster than expected. The telescope and instrument suite have demonstrated the sensitivity, stability, image quality, and spectral range that are necessary to transform our understanding of the cosmos through observations spanning from near-earth asteroids to the most distant galaxies

The James Webb Space Telescope Mission

Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least 4 m. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the 6.5 m James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 yr, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit

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)