The burden of injury in Central, Eastern, and Western European sub‑region: a systematic analysis from the Global Burden of Disease 2019 Study

Abstract Background: Injury remains a major concern to public health in the European region. Previous iterations of the Global Burden of Disease (GBD) study showed wide variation in injury death and disability adjusted life year (DALY) rates across Europe, indicating injury inequality gaps between sub-regions and countries. The objectives of this study were to: 1) compare GBD 2019 estimates on injury mortality and DALYs across European sub-regions and countries by cause-of-injury category and sex; 2) examine changes in injury DALY rates over a 20 year-period by cause-of-injury category, sub-region and country; and 3) assess inequalities in injury mortality and DALY rates across the countries. Methods: We performed a secondary database descriptive study using the GBD 2019 results on injuries in 44 European countries from 2000 to 2019. Inequality in DALY rates between these countries was assessed by calculating the DALY rate ratio between the highest-ranking country and lowest-ranking country in each year. Results: In 2019, in Eastern Europe 80 [95% uncertainty interval (UI): 71 to 89] people per 100,000 died from injuries; twice as high compared to Central Europe (38 injury deaths per 100,000; 95% UI 34 to 42) and three times as high compared to Western Europe (27 injury deaths per 100,000; 95%UI 25 to 28). The injury DALY rates showed less pronounced differences between Eastern (5129 DALYs per 100,000; 95% UI: 4547 to 5864), Central (2940 DALYs per 100,000; 95% UI: 2452 to 3546) and Western Europe (1782 DALYs per 100,000; 95% UI: 1523 to 2115). Injury DALY rate was lowest in Italy (1489 DALYs per 100,000) and highest in Ukraine (5553 DALYs per 100,000). The difference in injury DALY rates by country was larger for males compared to females. The DALY rate ratio was highest in 2005, with DALY rate in the lowest-ranking country (Russian Federation) 6.0 times higher compared to the highest-ranking country (Malta). After 2005, the DALY rate ratio between the lowest- and the highest-ranking country gradually decreased to 3.7 in 2019. Conclusions: Injury mortality and DALY rates were highest in Eastern Europe and lowest in Western Europe, although differences in injury DALY rates declined rapidly, particularly in the past decade. The injury DALY rate ratio of highest- and lowest-ranking country declined from 2005 onwards, indicating declining inequalities in injuries between European countries

Rapid inference of antibiotic resistance and susceptibility by genomic neighbour typing

Genomic neighbour typing can be used to infer the antimicrobial susceptibility and resistance of a bacterial sample based on the genomes of closest relatives. Combined with MinION sequencing, it can rapidly determine microbial resistance for clinical samples within 4 h. Surveillance of drug-resistant bacteria is essential for healthcare providers to deliver effective empirical antibiotic therapy. However, traditional molecular epidemiology does not typically occur on a timescale that could affect patient treatment and outcomes. Here, we present a method called 'genomic neighbour typing' for inferring the phenotype of a bacterial sample by identifying its closest relatives in a database of genomes with metadata. We show that this technique can infer antibiotic susceptibility and resistance for both Streptococcus pneumoniae and Neisseria gonorrhoeae. We implemented this with rapid k-mer matching, which, when used on Oxford Nanopore MinION data, can run in real time. This resulted in the determination of resistance within 10 min (91% sensitivity and 100% specificity for S. pneumoniae and 81% sensitivity and 100% specificity for N. gonorrhoeae from isolates with a representative database) of starting sequencing, and within 4 h of sample collection (75% sensitivity and 100% specificity for S. pneumoniae) for clinical metagenomic sputum samples. This flexible approach has wide application for pathogen surveillance and may be used to greatly accelerate appropriate empirical antibiotic treatment

HGCA2.0: An RNA-Seq Based Webtool for Gene Coexpression Analysis in Homo sapiens

Genes with similar expression patterns in a set of diverse samples may be considered coexpressed. Human Gene Coexpression Analysis 2.0 (HGCA2.0) is a webtool which studies the global coexpression landscape of human genes. The website is based on the hierarchical clustering of 55,431 Homo sapiens genes based on a large-scale coexpression analysis of 3500 GTEx bulk RNA-Seq samples of healthy individuals, which were selected as the best representative samples of each tissue type. HGCA2.0 presents subclades of coexpressed genes to a gene of interest, and performs various built-in gene term enrichment analyses on the coexpressed genes, including gene ontologies, biological pathways, protein families, and diseases, while also being unique in revealing enriched transcription factors driving coexpression. HGCA2.0 has been successful in identifying not only genes with ubiquitous expression patterns, but also tissue-specific genes. Benchmarking showed that HGCA2.0 belongs to the top performing coexpression webtools, as shown by STRING analysis. HGCA2.0 creates working hypotheses for the discovery of gene partners or common biological processes that can be experimentally validated. It offers a simple and intuitive website design and user interface, as well as an API endpoint

Measuring sub-mm structural displacements using QDaedalus: a digital clip-on measuring system developed for total stations

The monitoring of rigid structures of modal frequencies greater than 5 Hz and sub-mm displacement is mainly based so far on relative quantities from accelerometers, strain gauges etc. Additionally geodetic techniques such as GPS and Robotic Total Stations (RTS) are constrained by their low accuracy (few mm) and their low sampling rates. In this study the application of QDaedalus is presented, which constitutes a measuring system developed at the Geodesy and Geodynamics Lab, ETH Zurich and consists of a small CCD camera and Total Station, for the monitoring of the oscillations of a rigid structure. In collaboration with the Institute of Structural Engineering of ETH Zurich and EMPA, the QDaedalus system was used for monitoring of the sub-mm displacement of a rigid prototype beam and the estimation of its modal frequencies up to 30 Hz. The results of the QDaedalus data analysis were compared to those of accelerometers and proved to hold sufficient accuracy and suitably supplementing the existing monitoring techniques

Graph Neural Networks for Human-aware Social Navigation

Autonomous navigation is a key skill for assistive and service robots. To be successful, robots have to comply with social rules, such as avoiding the personal spaces of the people surrounding them, or not getting in the way of human-to-human and human-to-object interactions. This paper suggests using Graph Neural Networks to model how inconvenient the presence of a robot would be in a particular scenario according to learned human conventions so that it can be used by path planning algorithms. To do so, we propose two automated scenario-to-graph transformations and benchmark them with different Graph Neural Networks using the SocNav1 dataset. We achieve close-to-human performance in the dataset and argue that, in addition to its promising results, the main advantage of the approach is its scalability in terms of the number of social factors that can be considered and easily embedded in code in comparison with model-based approaches. The code used to train and test the resulting graph neural network is available in a public repository

Navigating paediatric virology through the COVID‑19 era (Review).

The present review article presents the key messages of the 8th Workshop on Paediatric Virology organised virtually by the Institute of Paediatric Virology based on the island of Euboea in Greece. The major topics covered during the workshop were the following: i) New advances in antiviral agents and vaccines against cytomegalovirus; ii) hantavirus nephropathy in children; iii) human rhinovirus infections in children requiring paediatric intensive care; iv) complications and management of human adenovirus infections; v) challenges of post‑coronavirus disease 2019 (COVID‑19) syndrome in children and adolescents; and vi) foetal magnetic resonance imaging in viral infections involving the central nervous system. The COVID‑19 era requires a more intensive, strategic, global scientific effort in the clinic and in the laboratory, focusing on the diagnosis, management and prevention of viral infections in neonates and children

Automated office blood pressure measurements in primary care are misleading in more than one third of treated hypertensives: The VALENTINE-Greece Home Blood Pressure Monitoring study

Abstract Background This study assessed the diagnostic reliability of automated office blood pressure (OBP) measurements in treated hypertensive patients in primary care by evaluating the prevalence of white coat hypertension (WCH) and masked uncontrolled hypertension (MUCH) phenomena. Methods Primary care physicians, nationwide in Greece, assessed consecutive hypertensive patients on stable treatment using OBP (1 visit, triplicate measurements) and home blood pressure (HBP) measurements (7 days, duplicate morning and evening measurements). All measurements were performed using validated automated devices with bluetooth capacity (Omron M7 Intelli-IT). Uncontrolled OBP was defined as ≥140/90 mmHg, and uncontrolled HBP was defined as ≥135/85 mmHg. Results A total of 790 patients recruited by 135 doctors were analyzed (age: 64.5 ± 14.4 years, diabetics: 21.4%, smokers: 20.6%, and average number of antihypertensive drugs: 1.6 ± 0.8). OBP (137.5 ± 9.4/84.3 ± 7.7 mmHg, systolic/diastolic) was higher than HBP (130.6 ± 11.2/79.9 ± 8 mmHg; difference 6.9 ± 11.6/4.4 ± 7.6 mmHg, p Conclusions In primary care, automated OBP measurements are misleading in approximately 40% of treated hypertensive patients. HBP monitoring is mandatory to avoid overtreatment of subjects with WCH phenomenon and prevent undertreatment and subsequent excess cardiovascular disease in MUCH

Global, regional, and national burden of low back pain, 1990–2020, its attributable risk factors, and projections to 2050: a systematic analysis of the Global Burden of Disease Study 2021

Background: Low back pain is highly prevalent and the main cause of years lived with disability (YLDs). We present the most up-to-date global, regional, and national data on prevalence and YLDs for low back pain from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021. Methods: Population-based studies from 1980 to 2019 identified in a systematic review, international surveys, US medical claims data, and dataset contributions by collaborators were used to estimate the prevalence and YLDs for low back pain from 1990 to 2020, for 204 countries and territories. Low back pain was defined as pain between the 12th ribs and the gluteal folds that lasted a day or more; input data using alternative definitions were adjusted in a network meta-regression analysis. Nested Bayesian meta-regression models were used to estimate prevalence and YLDs by age, sex, year, and location. Prevalence was projected to 2050 by running a regression on prevalence rates using Socio-demographic Index as a predictor, then multiplying them by projected population estimates. Findings: In 2020, low back pain affected 619 million (95% uncertainty interval 554–694) people globally, with a projection of 843 million (759–933) prevalent cases by 2050. In 2020, the global age-standardised rate of YLDs was 832 per 100 000 (578–1070). Between 1990 and 2020, age-standardised rates of prevalence and YLDs decreased by 10·4% (10·9–10·0) and 10·5% (11·1–10·0), respectively. A total of 38·8% (28·7–47·0) of YLDs were attributed to occupational factors, smoking, and high BMI. Interpretation: Low back pain remains the leading cause of YLDs globally, and in 2020, there were more than half a billion prevalent cases of low back pain worldwide. While age-standardised rates have decreased modestly over the past three decades, it is projected that globally in 2050, more than 800 million people will have low back pain. Challenges persist in obtaining primary country-level data on low back pain, and there is an urgent need for more high-quality, primary, country-level data on both prevalence and severity distributions to improve accuracy and monitor change. Funding: Bill and Melinda Gates Foundation

Learning environment, attitudes and anxiety across the transition from primary to secondary school mathematics

Past research has revealed that, relative to primary-school students, high-school students have less-positive attitudes to mathematics and perceive their classroom environments and teacher–student relationships less favourably. This study involved the transition experience of 541 students in 47 classes in 15 primary (year 7) and secondary (year 8) government and Catholic schools in metropolitan and regional South Australia. Scales were adapted from three established instruments, namely, the What Is Happening In this Class?, Test of Mathematics Related Attitudes and Revised Mathematics Anxiety Ratings Scale, to identify changes across the transition from primary to secondary school in terms of the classroom learning environment and students’ attitude/anxiety towards mathematics. Relative to year 7 students, year 8 students reported less Involvement, less positive Attitude to Mathematical Inquiry, less Enjoyment of Mathematics and greater Mathematics Anxiety. Differences between students in Years 7 and 8 were very similar for male and female students, although the magnitude of sex differences in attitudes was slightly different in Years 7 and 8