Measurement of the Photon Structure Function F2gamma with the L3 Detector at LEP

The e+e- -> e+e- hadrons reaction, where one of the two electrons is detected in a low polar-angle calorimeter, is analysed in order to measure the hadronic photon structure function F2gamma . The full high-energy and high-luminosity data set, collected with the L3 detector at centre-of-mass energies 189-209GeV, corresponding to an integrated luminosity of 608/pb is used. The Q^2 range 11-34GeV^2 and the x range 0.006-0.556 are considered. The data are compared with recent parton density functions

Geographical and temporal distribution of SARS-CoV-2 clades in the WHO European Region, January to June 2020

We show the distribution of SARS-CoV-2 genetic clades over time and between countries and outline potential genomic surveillance objectives. We applied three available genomic nomenclature systems for SARS-CoV-2 to all sequence data from the WHO European Region available during the COVID-19 pandemic until 10 July 2020. We highlight the importance of real-time sequencing and data dissemination in a pandemic situation. We provide a comparison of the nomenclatures and lay a foundation for future European genomic surveillance of SARS-CoV-2.Peer reviewe

Measuring progress and projecting attainment on the basis of past trends of the health-related Sustainable Development Goals in 188 countries: an analysis from the Global Burden of Disease Study 2016

The UN’s Sustainable Development Goals (SDGs) are grounded in the global ambition of “leaving no one behind”. Understanding today’s gains and gaps for the health-related SDGs is essential for decision makers as they aim to improve the health of populations. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016), we measured 37 of the 50 health-related SDG indicators over the period 1990–2016 for 188 countries, and then on the basis of these past trends, we projected indicators to 2030

Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

As mortality rates decline, life expectancy increases, and populations age, non-fatal outcomes of diseases and injuries are becoming a larger component of the global burden of disease. The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of prevalence, incidence, and years lived with disability (YLDs) for 328 causes in 195 countries and territories from 1990 to 2016

Erratum: Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017

Interpretation: By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Accuracy and interrater reliability for the diagnosis of Barrett’s neoplasia among users of a novel, portable high-resolution microendoscope

The high-resolution microendoscope (HRME) is a novel imaging modality that may be useful in the surveillance of Barrett’s esophagus in low-resource or community-based settings. In order to assess accuracy and interrater reliability of microendoscopists in identifying Barrett’s-associated neoplasia using HRME images, we recruited 20 gastroenterologists with no microendoscopic experience and three expert microendoscopists in a large academic hospital in New York City to interpret HRME images. They prospectively reviewed 40 HRME images from 28 consecutive patients undergoing surveillance for metaplasia and low-grade dysplasia and/or evaluation for high-grade dysplasia or cancer. Images were reviewed in a blinded fashion, after a 4-minute training with 11 representative images. All imaged sites were biopsied and interpreted by an expert pathologist. Sensitivity of all endoscopists for identification of high-grade dysplasia or cancer was 0.90 (95% confidence interval [CI]: 0.88-0.92) and specificity was 0.82 (95% CI: 0.79-0.85). Positive and negative predictive values were 0.72 (95% CI: 0.68-0.77) and 0.94 (95% CI: 0.92-0.96), respectively. No significant differences in accuracy were observed between experts and novices (0.90 vs. 0.84). The kappa statistic for all raters was 0.56 (95% CI: 0.54-0.58), and the difference between groups was not significant (0.64 vs. 0.55). These data suggest that gastroenterologists can diagnose Barrett’s-related neoplasia on HRME images with high sensitivity and specificity, without the aid of prior microendoscopy experience