Lifecycle CO2 emissions from US bioethanol production with CCS

There is growing consensus that carbon dioxide removal (CDR) technologies – also referred to as “negative emissions” technologies (NETs) – will be part of the portfolio of strategies and technologies needed to hold the increase in the global average temperature to “well below 2 °C” (1), as agreed by parties to the Paris Agreement. The production of bioenergy with carbon capture and sequestration (BECCS) is one class of CDR technology (2), involving the capture and geologic storage of CO2 (CCS) that would otherwise be emitted to the atmosphere from use of biomass as a fuel for electricity generation or feedstock for production of liquid fuels. Use of CCS typically imposes two energy penalties that can diminish its benefits: energy is needed to separate CO2 from dilute CO2-containing mixtures (e.g. flue gas), and to liquefy CO2 so that it can be transported and injected into geologic formations. The predominant biofuel production pathway in the United States (U.S.) today is conversion of corn starch to ethanol, which generates relatively high-concentration CO2 from fermentation and dilute-CO2 from fuel combustion for process heat. In 2015, the U.S. produced approximately 53 billion liters of bioethanol from nearly 200 facilities (3) releasing approximately 40 MtCO2 of CO2 from fermentation and a further 20 MtCO2 from process heat (4). The climate benefit of applying CCS to biofuel production – and BECCS more generally – can only be accurately assessed in the context of emissions over the entire fuel production pathway, including the biomass supply chain. Few prior studies have quantified the carbon intensity of biofuels, such as ethanol, produced from processes including CCS (5–8). While previous studies consider a range of feedstocks (i.e., sugar cane, beets, and corn), none consider the emissions from direct and indirect land-use change associated with feedstock production and some use dated assumptions for key parameters, such as corn and ethanol yields (7,8). However, all conclude that, with the addition of CCS, GHG intensity of produced fuels decreases and can become negative (even without credit for displacement). In this paper, we quantify the life-cycle emissions of several corn-ethanol production pathways coupled with CCS at different process steps. Specifically, we assess the lifecycle emissions for dry-mill ethanol production with and without CCS for fermentation process emissions and for onsite boiler or cogeneration emissions. We run these scenarios for representative U.S. corn ethanol plants, and include recent estimates of indirect land use change. Finally, we do a detailed parametric sensitivity analysis of our results. 1. Sanderson BM, O’Neill BC, Tebaldi C. What would it take to achieve the Paris temperature targets? Geophys Res Lett. 2016 Jul 16;43(13):7133–42. 2. The Royal Society. Geoengineering the climate: science, governance and uncertainty [Internet]. London, UK: The Royal Society; 2009. Available from: https://royalsociety.org/topics- policy/publications/2009/geoengineering-climate/ 3. U.S. DOE. Renewable & Alternative Fuels - Data [Internet]. U.S. Energy Information Administration (EIA). [cited 2017 Jan 14]. Available from: http://www.eia.gov/renewable/data.cfm#alternative 4. U.S. EPA. EPA Facility Level GHG Emissions Data [Internet]. [cited 2017 Jan 14]. Available from: https://ghgdata.epa.gov/ghgp/main.do 5. Lindfeldt EG, Westermark MO. System study of carbon dioxide (CO2) capture in bio-based motor fuel production. 19th Int Conf Effic Cost Optim Simul Environ Impactof Energy Syst 2006. 2008 Feb;33(2):352–61. 6. Laude A, Ricci O, Bureau G, Royer-Adnot J, Fabbri A. CO2 capture and storage from a bioethanol plant: Carbon and energy footprint and economic assessment. Int J Greenh Gas Control. 2011;5(5):1220–31. 7. Möllersten K, Yan J, R. Moreira J. Potential market niches for biomass energy with CO2 capture and storage--Opportunities for energy supply with negative CO2 emissions. Biomass Bioenergy. 2003;25(3):273–85. 8. Kheshgi HS, Prince RC. Sequestration of fermentation CO2 from ethanol production. Energy. 2005 Jul;30(10):1865–71

Erica: Prevalence Of Metabolic Syndrome In Brazilian Adolescents

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)To determine the prevalence of metabolic syndrome and its components in Brazilian adolescents. METHODS: We evaluated 37,504 adolescents who were participants in the Study of Cardiovascular Risks in Adolescents (ERICA), a cross-sectional, school-based, national study. The adolescents, aged from 12 to 17 years, lived in cities with populations greater than 100,000 inhabitants. The sample was stratified and clustered into schools and classes. The criteria set out by the International Diabetes Federation were used to define metabolic syndrome. Prevalences of metabolic syndrome were estimated according to sex, age group, school type and nutritional status. RESULTS: Of the 37,504 adolescents who were evaluated: 50.2% were female; 54.3% were aged from 15 to 17 years, and 73.3% were from public schools. The prevalence of metabolic syndrome was 2.6% (95% CI 2.3-2.9), slightly higher in males and in those aged from 15 to 17 years in most macro-regions. The prevalence was the highest in residents from the South macro-region, in the younger female adolescents and in the older male adolescents. The prevalence was higher in public schools (2.8% [95% CI 2.4-3.2]), when compared with private schools (1.9% [95% CI 1.4-2.4]) and higher in obese adolescents when compared with nonobese ones. The most common combinations of components, referring to 3/4 of combinations, were: enlarged waist circumference (WC), low HDL-cholesterol (HDL-c) and high blood pressure; followed by enlarged WC, low HDL-c and high triglycerides; and enlarged WC, low HDL-c, high triglycerides and blood pressure. Low HDL was the second most frequent component, but the highest prevalence of metabolic syndrome (26.8%) was observed in the presence of high triglycerides. CONCLUSIONS: ERICA is the first Brazilian nation-wide study to present the prevalence of metabolic syndrome and describe the role of its components. Despite the prevalence of Metabolic Syndrome being low, the high prevalences of some components and participation of others in the syndrome composition shows the importance of early diagnosis of this changes, even if not grouped within the metabolic syndrome.501Department of Science and Technology of the Secretariat of Science, Technology and Strategic Inputs of the Ministry of Health (Decit/SCTIE/MS)Health Sectorial Fund (Fundo Setorial de Saude - CT-Saude) of the Ministry of Science, Technology and Innovation (MCTI)FINEP [01090421]CNPq [2010/565037-2]Research Incentive Fund of the Hospital de Clinicas de Porto Alegre - (Fundo de Incentivo a Pesquisa do Hospital de Clinicas de Porto Alegre - FIPE-HCPA) [405.009/2012-7]Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq

Intestinal Microbiota Composition of Interleukin-10 Deficient C57BL/6J Mice and Susceptibility to Helicobacter hepaticus-Induced Colitis

The mouse pathobiont Helicobacter hepaticus can induce typhlocolitis in interleukin-10-deficient mice, and H. hepaticus infection of immunodeficient mice is widely used as a model to study the role of pathogens and commensal bacteria in the pathogenesis of inflammatory bowel disease. C57BL/6J Il10[superscript −/−] mice kept under specific pathogen-free conditions in two different facilities (MHH and MIT), displayed strong differences with respect to their susceptibilities to H. hepaticus-induced intestinal pathology. Mice at MIT developed robust typhlocolitis after infection with H. hepaticus, while mice at MHH developed no significant pathology after infection with the same H. hepaticus strain. We hypothesized that the intestinal microbiota might be responsible for these differences and therefore performed high resolution analysis of the intestinal microbiota composition in uninfected mice from the two facilities by deep sequencing of partial 16S rRNA amplicons. The microbiota composition differed markedly between mice from both facilities. Significant differences were also detected between two groups of MHH mice born in different years. Of the 119 operational taxonomic units (OTUs) that occurred in at least half the cecum or colon samples of at least one mouse group, 24 were only found in MIT mice, and another 13 OTUs could only be found in MHH samples. While most of the MHH-specific OTUs could only be identified to class or family level, the MIT-specific set contained OTUs identified to genus or species level, including the opportunistic pathogen, Bilophila wadsworthia. The susceptibility to H. hepaticus-induced colitis differed considerably between Il10[superscript −/−] mice originating from the two institutions. This was associated with significant differences in microbiota composition, highlighting the importance of characterizing the intestinal microbiome when studying murine models of IBD.National Institutes of Health (U.S.) (Grant NIH P01-CA26731)National Institutes of Health (U.S.) (Grant NIH P30ES0026731)National Institutes of Health (U.S.) (Grant NIH R01-OD011141

Quality control of B-lines analysis in stress Echo 2020

Background The effectiveness trial “Stress echo (SE) 2020” evaluates novel applications of SE in and beyond coronary artery disease. The core protocol also includes 4-site simplified scan of B-lines by lung ultrasound, useful to assess pulmonary congestion. Purpose To provide web-based upstream quality control and harmonization of B-lines reading criteria. Methods 60 readers (all previously accredited for regional wall motion, 53 B-lines naive) from 52 centers of 16 countries of SE 2020 network read a set of 20 lung ultrasound video-clips selected by the Pisa lab serving as reference standard, after taking an obligatory web-based learning 2-h module ( http://se2020.altervista.org ). Each test clip was scored for B-lines from 0 (black lung, A-lines, no B-lines) to 10 (white lung, coalescing B-lines). The diagnostic gold standard was the concordant assessment of two experienced readers of the Pisa lab. The answer of the reader was considered correct if concordant with reference standard reading ±1 (for instance, reference standard reading of 5 B-lines; correct answer 4, 5, or 6). The a priori determined pass threshold was 18/20 (≥ 90%) with R value (intra-class correlation coefficient) between reference standard and recruiting center) > 0.90. Inter-observer agreement was assessed with intra-class correlation coefficient statistics. Results All 60 readers were successfully accredited: 26 (43%) on first, 24 (40%) on second, and 10 (17%) on third attempt. The average diagnostic accuracy of the 60 accredited readers was 95%, with R value of 0.95 compared to reference standard reading. The 53 B-lines naive scored similarly to the 7 B-lines expert on first attempt (90 versus 95%, p = NS). Compared to the step-1 of quality control for regional wall motion abnormalities, the mean reading time per attempt was shorter (17 ± 3 vs 29 ± 12 min, p < .01), the first attempt success rate was higher (43 vs 28%, p < 0.01), and the drop-out of readers smaller (0 vs 28%, p < .01). Conclusions Web-based learning is highly effective for teaching and harmonizing B-lines reading. Echocardiographers without previous experience with B-lines learn quickly.info:eu-repo/semantics/publishedVersio

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

Rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART): Study protocol for a randomized controlled trial

Background: Acute respiratory distress syndrome (ARDS) is associated with high in-hospital mortality. Alveolar recruitment followed by ventilation at optimal titrated PEEP may reduce ventilator-induced lung injury and improve oxygenation in patients with ARDS, but the effects on mortality and other clinical outcomes remain unknown. This article reports the rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART). Methods/Design: ART is a pragmatic, multicenter, randomized (concealed), controlled trial, which aims to determine if maximum stepwise alveolar recruitment associated with PEEP titration is able to increase 28-day survival in patients with ARDS compared to conventional treatment (ARDSNet strategy). We will enroll adult patients with ARDS of less than 72 h duration. The intervention group will receive an alveolar recruitment maneuver, with stepwise increases of PEEP achieving 45 cmH(2)O and peak pressure of 60 cmH2O, followed by ventilation with optimal PEEP titrated according to the static compliance of the respiratory system. In the control group, mechanical ventilation will follow a conventional protocol (ARDSNet). In both groups, we will use controlled volume mode with low tidal volumes (4 to 6 mL/kg of predicted body weight) and targeting plateau pressure &lt;= 30 cmH2O. The primary outcome is 28-day survival, and the secondary outcomes are: length of ICU stay; length of hospital stay; pneumothorax requiring chest tube during first 7 days; barotrauma during first 7 days; mechanical ventilation-free days from days 1 to 28; ICU, in-hospital, and 6-month survival. ART is an event-guided trial planned to last until 520 events (deaths within 28 days) are observed. These events allow detection of a hazard ratio of 0.75, with 90% power and two-tailed type I error of 5%. All analysis will follow the intention-to-treat principle. Discussion: If the ART strategy with maximum recruitment and PEEP titration improves 28-day survival, this will represent a notable advance to the care of ARDS patients. Conversely, if the ART strategy is similar or inferior to the current evidence-based strategy (ARDSNet), this should also change current practice as many institutions routinely employ recruitment maneuvers and set PEEP levels according to some titration method.Hospital do Coracao (HCor) as part of the Program 'Hospitais de Excelencia a Servico do SUS (PROADI-SUS)'Brazilian Ministry of Healt

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

Induced seismicity hazard and risk by enhanced geothermal systems: an expert elicitation approach

Induced seismicity is a concern for multiple geoenergy applications, including low-carbon Enhanced Geothermal Systems (EGS). We present results of an international expert elicitation (N=14) on EGS induced seismicity hazard and risk. Using a hypothetical scenario of an EGS plant and its geological context, we show that expert best-guess estimates of annualized exceedance probabilities of a M≥3 event range from 0.2% to 95% during reservoir stimulation and 0.2% to 100% during operation. Best-guess annualized exceedance probabilities of M≥5 event span from 0.002% to 2% during stimulation and 0.003% to 3% during operation. Assuming that tectonic M7 events could occur, some experts do not exclude induced (triggered) events of up to M7 too. If induced M=3 event happens at 5 km depth beneath a town with 10 thousand inhabitants, most experts estimate 50% probability that the loss is contained within 0.5 million USD without any injuries or fatalities. In case of induced M=5 event, there is 50% chance that the loss is below 50 million USD with the most-likely outcome of 50 injuries and 1 or no fatality. As we observe vast diversity in quantitative expert judgements and underlying mental models, we conclude with implications for induced seismicity risk governance. That is, we suggest to document individual expert judgements in induced seismicity elicitations before proceeding to consensual judgements, to convene larger expert panels in order not to cherry-pick experts, and to aim for multi-organization multi-model assessments of EGS induced seismicity hazard and risk

Effects of government incentives on wind innovation in the United States

<p>In the United States, as elsewhere, state and federal governments have considered or implemented a range of policies to create more sustainable energy generation systems in response to concerns over climate change, security of fuel supply, and environmental impacts. These policies include both regulatory instruments such as renewable portfolio standards (RPSs) and market incentives such as tax credits. While these policies are primarily geared towards increasing renewable generation capacity, they can indirectly affect innovation in associated technologies through a 'demand-pull' dynamic. Other policies, such as public research and development (R&D) funding, directly incentivize innovation through 'technology-push' means. In this letter, we examine these effects on innovation in the United States wind energy industry. We estimate a set of econometric models relating a set of US federal and state policies to patenting activity in wind technologies over the period 1974–2009. We find that RPS policies have had significant positive effects on wind innovation, whereas tax-based incentives have not been particularly effective. We also find evidence that the effects of RPS incentives differ between states. Finally, we find that public R&D funding can be a significant driver of wind innovation, though its effect in the US has been modest.</p