A note on leapfrogging vortex rings

In this paper we provide examples, by numerical simulation using the Navier-Stokes equations for axisymmetric laminar flow, of the 'leapfrogging' motion of two, initially identical, vortex rings which share a common axis of symmetry. We show that the number of clear passes that each ring makes through the other increases with Reynolds number, and that as long as the configuration remains stable the two rings ultimately merge to form a single vortex ring

Ultrasound Liver Fibrosis Diagnosis using Multi-indicator guided Deep Neural Networks

Accurate analysis of the fibrosis stage plays very important roles in follow-up of patients with chronic hepatitis B infection. In this paper, a deep learning framework is presented for automatically liver fibrosis prediction. On contrary of previous works, our approach can take use of the information provided by multiple ultrasound images. An indicator-guided learning mechanism is further proposed to ease the training of the proposed model. This follows the workflow of clinical diagnosis and make the prediction procedure interpretable. To support the training, a dataset is well-collected which contains the ultrasound videos/images, indicators and labels of 229 patients. As demonstrated in the experimental results, our proposed model shows its effectiveness by achieving the state-of-the-art performance, specifically, the accuracy is 65.6%(20% higher than previous best).Comment: Jiali Liu and Wenxuan Wang are equal contributio

The global burden of non-typhoidal salmonella invasive disease: a systematic analysis for the Global Burden of Disease Study 2017

Background Non-typhoidal salmonella invasive disease is a major cause of global morbidity and mortality. Malnourished children, those with recent malaria or sickle-cell anaemia, and adults with HIV infection are at particularly high risk of disease. We sought to estimate the burden of disease attributable to non-typhoidal salmonella invasive disease for the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017. Methods We did a systematic review of scientific databases and grey literature, and estimated non-typhoidal salmonella invasive disease incidence and mortality for the years 1990 to 2017, by age, sex, and geographical location using DisMod-MR, a Bayesian meta-regression tool. We estimated case fatality by age, HIV status, and sociodemographic development. We also calculated the HIV-attributable fraction and estimated health gap metrics, including disability-adjusted life-years (DALYs). Findings We estimated that 535 000 (95% uncertainty interval 409 000-705 000) cases of non-typhoidal salmonella invasive disease occurred in 2017, with the highest incidence in sub-Saharan Africa (34.5 [26.6-45.0] cases per 100 000 person-years) and in children younger than 5 years (34.3 [23.2-54.7] cases per 100 000 person-years). 77 500 (46 400-123 000) deaths were estimated in 2017, of which 18 400 (12 000-27 700) were attributable to HIV. The remaining 59 100 (33 300-98 100) deaths not attributable to HIV accounted for 4.26 million (2.38-7.38) DALYs in 2017. Mean all-age case fatality was 14.5% (9.2-21.1), with higher estimates among children younger than 5 years (13.5% [8.4-19.8]) and elderly people (51.2% [30.2-72.9] among those aged >= 70 years), people with HIV infection (41.8% [30.0-54.0]), and in areas of low sociodemographic development (eg, 15.8% [10.0-22.9] in sub-Saharan Africa). Interpretation We present the first global estimates of non-typhoidal salmonella invasive disease that have been produced as part of GBD 2017. Given the high disease burden, particularly in children, elderly people, and people with HIV infection, investigating the sources and transmission pathways of non-typhoidal salmonella invasive disease is crucial to implement effective preventive and control measures. Funding Bill & Melinda Gates Foundation. Copyright (c) 2019 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Keywords: 195 COUNTRIES; CLINICAL PRESENTATION; TERRITORIES; RESISTANCE; EPIDEMIOLOGY; INFECTIONS; DISABILITY; INJURIES; OUTCOME

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

Background The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk–outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk–outcome pairs, and new data on risk exposure levels and risk–outcome associations. Methods We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk–outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017. Findings In 2017, 34·1 million (95% uncertainty interval [UI] 33·3–35·0) deaths and 1·21 billion (1·14–1·28) DALYs were attributable to GBD risk factors. Globally, 61·0% (59·6–62·4) of deaths and 48·3% (46·3–50·2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10·4 million (9·39–11·5) deaths and 218 million (198–237) DALYs, followed by smoking (7·10 million [6·83–7·37] deaths and 182 million [173–193] DALYs), high fasting plasma glucose (6·53 million [5·23–8·23] deaths and 171 million [144–201] DALYs), high body-mass index (BMI; 4·72 million [2·99–6·70] deaths and 148 million [98·6–202] DALYs), and short gestation for birthweight (1·43 million [1·36–1·51] deaths and 139 million [131–147] DALYs). In total, risk-attributable DALYs declined by 4·9% (3·3–6·5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23·5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18·6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low. 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 plannin

Population and fertility by age and sex for 195 countries and territories, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017

Background The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk–outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk–outcome pairs, and new data on risk exposure levels and risk–outcome associations. Methods We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk–outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017. Findings In 2017, 34·1 million (95% uncertainty interval [UI] 33·3–35·0) deaths and 1·21 billion (1·14–1·28) DALYs were attributable to GBD risk factors. Globally, 61·0% (59·6–62·4) of deaths and 48·3% (46·3–50·2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10·4 million (9·39–11·5) deaths and 218 million (198–237) DALYs, followed by smoking (7·10 million [6·83–7·37] deaths and 182 million [173–193] DALYs), high fasting plasma glucose (6·53 million [5·23–8·23] deaths and 171 million [144–201] DALYs), high body-mass index (BMI; 4·72 million [2·99–6·70] deaths and 148 million [98·6–202] DALYs), and short gestation for birthweight (1·43 million [1·36–1·51] deaths and 139 million [131–147] DALYs). In total, risk-attributable DALYs declined by 4·9% (3·3–6·5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23·5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18·6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low. 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 plannin

Association of Trauma Molecular Endotypes With Differential Response to Transfusion Resuscitation Strategies

IMPORTANCE: It is not clear which severely injured patients with hemorrhagic shock may benefit most from a 1:1:1 vs 1:1:2 (plasma:platelets:red blood cells) resuscitation strategy. Identification of trauma molecular endotypes may reveal subgroups of patients with differential treatment response to various resuscitation strategies. OBJECTIVE: To derive trauma endotypes (TEs) from molecular data and determine whether these endotypes are associated with mortality and differential treatment response to 1:1:1 vs 1:1:2 resuscitation strategies. DESIGN, SETTING, AND PARTICIPANTS: This was a secondary analysis of the Pragmatic, Randomized Optimal Platelet and Plasma Ratios (PROPPR) randomized clinical trial. The study cohort included individuals with severe injury from 12 North American trauma centers. The cohort was taken from the participants in the PROPPR trial who had complete plasma biomarker data available. Study data were analyzed on August 2, 2021, to October 25, 2022. EXPOSURES: TEs identified by K-means clustering of plasma biomarkers collected at hospital arrival. MAIN OUTCOMES AND MEASURES: An association between TEs and 30-day mortality was tested using multivariable relative risk (RR) regression adjusting for age, sex, trauma center, mechanism of injury, and injury severity score (ISS). Differential treatment response to transfusion strategy was assessed using an RR regression model for 30-day mortality by incorporating an interaction term for the product of endotype and treatment group adjusting for age, sex, trauma center, mechanism of injury, and ISS. RESULTS: A total of 478 participants (median [IQR] age, 34.5 [25-51] years; 384 male [80%]) of the 680 participants in the PROPPR trial were included in this study analysis. A 2-class model that had optimal performance in K-means clustering was found. TE-1 (n = 270) was characterized by higher plasma concentrations of inflammatory biomarkers (eg, interleukin 8 and tumor necrosis factor α) and significantly higher 30-day mortality compared with TE-2 (n = 208). There was a significant interaction between treatment arm and TE for 30-day mortality. Mortality in TE-1 was 28.6% with 1:1:2 treatment vs 32.6% with 1:1:1 treatment, whereas mortality in TE-2 was 24.5% with 1:1:2 treatment vs 7.3% with 1:1:1 treatment (P for interaction = .001). CONCLUSIONS AND RELEVANCE: Results of this secondary analysis suggest that endotypes derived from plasma biomarkers in trauma patients at hospital arrival were associated with a differential response to 1:1:1 vs 1:1:2 resuscitation strategies in trauma patients with severe injury. These findings support the concept of molecular heterogeneity in critically ill trauma populations and have implications for tailoring therapy for patients at high risk for adverse outcomes

Genome-wide association study identifies loci associated with liability to alcohol and drug dependence that is associated with variability in reward-related ventral striatum activity in African- and European-Americans.

Genetic influences on alcohol and drug dependence partially overlap, however, specific loci underlying this overlap remain unclear. We conducted a genome-wide association study (GWAS) of a phenotype representing alcohol or illicit drug dependence (ANYDEP) among 7291 European-Americans (EA; 2927 cases) and 3132 African-Americans (AA: 1315 cases) participating in the family-based Collaborative Study on the Genetics of Alcoholism. ANYDEP was heritable (h 2 in EA = 0.60, AA = 0.37). The AA GWAS identified three regions with genome-wide significant (GWS; P < 5E-08) single nucleotide polymorphisms (SNPs) on chromosomes 3 (rs34066662, rs58801820) and 13 (rs75168521, rs78886294), and an insertion-deletion on chromosome 5 (chr5:141988181). No polymorphisms reached GWS in the EA. One GWS region (chromosome 1: rs1890881) emerged from a trans-ancestral meta-analysis (EA + AA) of ANYDEP, and was attributable to alcohol dependence in both samples. Four genes (AA: CRKL, DZIP3, SBK3; EA: P2RX6) and four sets of genes were significantly enriched within biological pathways for hemostasis and signal transduction. GWS signals did not replicate in two independent samples but there was weak evidence for association between rs1890881 and alcohol intake in the UK Biobank. Among 118 AA and 481 EA individuals from the Duke Neurogenetics Study, rs75168521 and rs1890881 genotypes were associated with variability in reward-related ventral striatum activation. This study identified novel loci for substance dependence and provides preliminary evidence that these variants are also associated with individual differences in neural reward reactivity. Gene discovery efforts in non-European samples with distinct patterns of substance use may lead to the identification of novel ancestry-specific genetic markers of risk