Sustainable Urbanization as a Key to Advancing International Climate Agreements

Introduction Cities have always played a role in the United Nations Framework Convention on Climate Change’s (UNFCCC) process and meetings. A key actor in facilitating their input and engagement is ICLEI – Local Governments for Sustainability, a city network that acts as the official focal point of the Local Governments and Municipal Authorities (LGMA) observer group to the UNFCCC. This text will shed light on the history of this engagement and will outline the prospects for the topic of sust..

Middle Eastern Cities in a Time of Climate Crisis

The climate crisis is hitting around the world, including in the Middle East and its cities. Urban regions are exposed to increasingly frequent heat waves and floods that leave decision makers without immediate answers. In the context of this global crisis, this book addresses the need for a better understanding of the current model of urban expansion. Cities are major sources of greenhouse gas (GHG) emissions but they are also celebrated for their contribution to economic growth. The current moment is one of a large paradigm shift as climate change is now recognized as a legitimate public problem. This is especially true for city dwellers, who are increasingly exposed to climate change, the loss of biodiversity and heavy pollution while natural breathing spaces continue to shrink around them. The sixteen chapters of this book do not offer any off-the-rack or technical solutions, but they analyze the urban conundrum and the contribution of cities to the climate crisis. Some chapters focus on individual car ownership, land privatization, waste management and land use changes under the guise of development. Others explore local and contextual answers to urban governance issues. With the support of CEDEJ and the Friedrich-Ebert-Stiftung, researchers, experts and civil society actors explore the ongoing transformations of Middle Eastern urban environments and mobilities and question them in relation to the climate crisis. The contributions are based on empirical knowledge gathered in the Nile Delta, the Greater Cairo Region, Riyadh and Beirut. Without concessions to mainstream thinking, this book contributes to a better understanding of urban challenges, climate threats and policy responses in contexts marked by growing environmental inequalities

Quantification of urban mitigation potentials - coping with data heterogeneity

Cities are at the forefront of European and international climate action. However, in many cities, the ever-growing urban population is putting pressure on settlement and infrastructure development, increasing attention to urban planning, infrastructure and buildings. This paper introduces a set of quantification approaches, capturing impacts of urban planning measures in three fields of action: sustainable building, transport and redensification. The quantification approaches have been developed to account for different levels of data availability, thus providing users with quantification approaches that are applicable across cities. The mitigation potentials of various measures such as a modal shift, the substitution of building materials with wood, and different redensification scenarios were calculated. The substitution of conventional building materials with wood was analyzed as having a high mitigation potential. Building construction, in combination with urban planning and design, are key drivers for mitigating climate change in cities. Given the data heterogeneity among cities, mixed quantification approaches could be defined and the measures and policy areas with the greatest climate mitigation potential identified

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

Evolution over Time of Ventilatory Management and Outcome of Patients with Neurologic Disease∗

OBJECTIVES: To describe the changes in ventilator management over time in patients with neurologic disease at ICU admission and to estimate factors associated with 28-day hospital mortality. DESIGN: Secondary analysis of three prospective, observational, multicenter studies. SETTING: Cohort studies conducted in 2004, 2010, and 2016. PATIENTS: Adult patients who received mechanical ventilation for more than 12 hours. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Among the 20,929 patients enrolled, we included 4,152 (20%) mechanically ventilated patients due to different neurologic diseases. Hemorrhagic stroke and brain trauma were the most common pathologies associated with the need for mechanical ventilation. Although volume-cycled ventilation remained the preferred ventilation mode, there was a significant (p &lt; 0.001) increment in the use of pressure support ventilation. The proportion of patients receiving a protective lung ventilation strategy was increased over time: 47% in 2004, 63% in 2010, and 65% in 2016 (p &lt; 0.001), as well as the duration of protective ventilation strategies: 406 days per 1,000 mechanical ventilation days in 2004, 523 days per 1,000 mechanical ventilation days in 2010, and 585 days per 1,000 mechanical ventilation days in 2016 (p &lt; 0.001). There were no differences in the length of stay in the ICU, mortality in the ICU, and mortality in hospital from 2004 to 2016. Independent risk factors for 28-day mortality were age greater than 75 years, Simplified Acute Physiology Score II greater than 50, the occurrence of organ dysfunction within first 48 hours after brain injury, and specific neurologic diseases such as hemorrhagic stroke, ischemic stroke, and brain trauma. CONCLUSIONS: More lung-protective ventilatory strategies have been implemented over years in neurologic patients with no effect on pulmonary complications or on survival. We found several prognostic factors on mortality such as advanced age, the severity of the disease, organ dysfunctions, and the etiology of neurologic disease

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)