44 research outputs found

    Artificial intelligence for the detection of sacroiliitis on magnetic resonance imaging in patients with axial spondyloarthritis

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    BackgroundMagnetic resonance imaging (MRI) is important for the early detection of axial spondyloarthritis (axSpA). We developed an artificial intelligence (AI) model for detecting sacroiliitis in patients with axSpA using MRI.MethodsThis study included MRI examinations of patients who underwent semi-coronal MRI scans of the sacroiliac joints owing to chronic back pain with short tau inversion recovery (STIR) sequences between January 2010 and December 2021. Sacroiliitis was defined as a positive MRI finding according to the ASAS classification criteria for axSpA. We developed a two-stage framework. First, the Faster R-CNN network extracted regions of interest (ROIs) to localize the sacroiliac joints. Maximum intensity projection (MIP) of three consecutive slices was used to mimic the reading of two adjacent slices. Second, the VGG-19 network determined the presence of sacroiliitis in localized ROIs. We augmented the positive dataset six-fold. The sacroiliitis classification performance was measured using the sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC). The prediction models were evaluated using three-round three-fold cross-validation.ResultsA total of 296 participants with 4,746 MRI slices were included in the study. Sacroiliitis was identified in 864 MRI slices of 119 participants. The mean sensitivity, specificity, and AUROC for the detection of sacroiliitis were 0.725 (95% CI, 0.705–0.745), 0.936 (95% CI, 0.924–0.947), and 0.830 (95%CI, 0.792–0.868), respectively, at the image level and 0.947 (95% CI, 0.912–0.982), 0.691 (95% CI, 0.603–0.779), and 0.816 (95% CI, 0.776–0.856), respectively, at the patient level. In the original model, without using MIP and dataset augmentation, the mean sensitivity, specificity, and AUROC were 0.517 (95% CI, 0.493–0.780), 0.944 (95% CI, 0.933–0.955), and 0.731 (95% CI, 0.681–0.780), respectively, at the image level and 0.806 (95% CI, 0.729–0.883), 0.617 (95% CI, 0.523–0.711), and 0.711 (95% CI, 0.660–0.763), respectively, at the patient level. The performance was improved by MIP techniques and data augmentation.ConclusionAn AI model was developed for the detection of sacroiliitis using MRI, compatible with the ASAS criteria for axSpA, with the potential to aid MRI application in a wider clinical setting

    Effect modification of greenness on the association between heat and mortality: A multi-city multi-country study

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    Background: Identifying how greenspace impacts the temperature-mortality relationship in urban environments is crucial, especially given climate change and rapid urbanization. However, the effect modification of greenspace on heat-related mortality has been typically focused on a localized area or single country. This study examined the heat-mortality relationship among different greenspace levels in a global setting. Methods: We collected daily ambient temperature and mortality data for 452 locations in 24 countries and used Enhanced Vegetation Index (EVI) as the greenspace measurement. We used distributed lag non-linear model to estimate the heat-mortality relationship in each city and the estimates were pooled adjusting for city-specific average temperature, city-specific temperature range, city-specific population density, and gross domestic product (GDP). The effect modification of greenspace was evaluated by comparing the heat-related mortality risk for different greenspace groups (low, medium, and high), which were divided into terciles among 452 locations. Findings: Cities with high greenspace value had the lowest heat-mortality relative risk of 1·19 (95% CI: 1·13, 1·25), while the heat-related relative risk was 1·46 (95% CI: 1·31, 1·62) for cities with low greenspace when comparing the 99th temperature and the minimum mortality temperature. A 20% increase of greenspace is associated with a 9·02% (95% CI: 8·88, 9·16) decrease in the heat-related attributable fraction, and if this association is causal (which is not within the scope of this study to assess), such a reduction could save approximately 933 excess deaths per year in 24 countries. Interpretation: Our findings can inform communities on the potential health benefits of greenspaces in the urban environment and mitigation measures regarding the impacts of climate change.Research in context - I-Evidence before this study: Urbanization and climate change have resulted in changes to the urban environment, including the urban heat island effect and contributions to other extreme weather events. Recently, as metropolitan areas have become denser due to rapid urbanization, environmental problems such as high temperatures are also worsening. Many studies showed that high temperatures increase health risks, including mortality. Therefore, identifying factors that could mitigate the high-temperature conditions in urban environments are a crucial part of climate change mitigation strategies. Many studies found that urban green spaces may play an important role in mitigating heat. Specifically, large green spaces have shown a significant and positive cooling effect. Vegetation can promote air convection through shading and evapotranspiration, which indicates that dense vegetation can lower air temperature. Therefore, more greenspace could result in lower temperatures during the warm season, which would lower exposure to high temperatures that impact human health. Importantly, while greenspace can lower exposure to heat, this study examined how greenspace modifies the heat-health relationship. Some studies have investigated this issue. For example, studies found that heat-related mortality and ambulance calls are negatively correlated with the amount of greenspace coverage. However, most previous work on how greenspace modifies the heat-health relationship was based on one country or region. Research is needed on a global scale to understand how greenspace in urban areas among different countries, with different populations, levels of urbanization, and types of greenspace, can modify the relationship between extreme temperatures and health. As climate change is anticipated to increase temperatures and the associated health consequences worldwide, greenspace may be a plausible mitigation strategy for cities in order to address heat-related health impacts at present and in the future. II-Added value of this study: In this study, we explored the effect modification of greenspace on the heat-mortality relationship on a global scale. With a dataset of 452 locations from 24 countries located in various climate zones and continents, this study incorporated variability in greenspace, temperature, and population characteristics. We found that, based on 452 locations, the heat-mortality risks differed with greenspace category and the cities with higher greenspace values had lower heat-mortality risk than those with lower greenspace values. III-Implications of all the available evidence: Our findings provide evidence that higher greenspace reduces the heat-related mortality, which is similar to other previous smaller studies, and our study results were consistent in different countries around various climate zones. These findings indicate that disparate greenspace levels, temperature, and environment settings should be considered when developing policies and strategies in climate change mitigation and public health adaptation. This study adds to the existing literature that greenspace can reduce the urban heat island effect, by providing evidence for the theory that greenspace can also lower the heat-mortality association, and documents such impacts on a global scale.This publication was developed under Assistance Agreement No. RD83587101 awarded by the U.S. Environmental Protection Agency to Yale University. Research reported in this publication was also supported by the National Institute on Minority Health and Health Disparities of the National Institutes of Health under Award Number R01MD012769. Also, this work has been supported by the National Research Foundation of Korea (2021R1A6A3A03038675), Medical Research Council-UK (MR/V034162/1 and MR/R013349/1), Natural Environment Research Council UK (Grant ID: NE/R009384/1), Academy of Finland (Grant ID: 310372), European Union's Horizon 2020 Project Exhaustion (Grant ID: 820655 and 874990), Czech Science Foundation (22-24920S), Emory University's NIEHS-funded HERCULES Center (Grant ID: P30ES019776), and Grant CEX2018-000794-S funded by MCIN/AEI/ 10.13039/501100011033.info:eu-repo/semantics/publishedVersio

    A study on the Korean government's supporting measures for private firms' science, technology, and innovation promotion

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    노트 : Government Publications Registration Number 11-1051000-000458-0

    Suicide and Associations with Air Pollution and Ambient Temperature: A Systematic Review and Meta-Analysis

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    Given health threats of climate change, a comprehensive review of the impacts of ambient temperature and ar pollution on suicide is needed. We performed systematic literature review and meta-analysis of suicide risks associated with short-term exposure to ambient temperature and air pollution. Pubmed, Scopus, and Web of Science were searched for English-language publications using relevant keywords. Observational studies assessing risks of daily suicide and suicide attempts associated with temperature, particulate matter with aerodynamic diameter ≤10 μm (PM10) and ≤2.5 mm (PM2.5), ozone (O3), sulfur dioxide (SO2), nitrogen dioxide (NO2), and carbon monoxide (CO) were included. Data extraction was independently performed in duplicate. Random-effect meta-analysis was applied to pool risk ratios (RRs) for increases in daily suicide per interquartile range (IQR) increase in exposure. Meta-regression analysis was applied to examine effect modification by income level based on gross national income (GNI) per capita, national suicide rates, and average level of exposure factors. In total 2274 articles were screened, with 18 studies meeting inclusion criteria for air pollution and 32 studies for temperature. RRs of suicide per 7.1 °C temperature was 1.09 (95% CI: 1.06, 1.13). RRs of suicide per IQR increase in PM2.5, PM10, and NO2 were 1.02 (95% CI: 1.00, 1.05), 1.01 (95% CI: 1.00, 1.03), and 1.03 (95% CI: 1.00, 1.07). O3, SO2, and CO were not associated with suicide. RR of suicide was significantly higher in higher-income than lower-income countries (1.09, 95% CI: 1.07, 1.11 and 1.20, 95% CI: 1.14, 1.26 per 7.1 °C increased temperature, respectively). Suicide risks associated with air pollution did not significantly differ by income level, national suicide rates, or average exposure levels. Research gaps were found for interactions between air pollution and temperature on suicide risks

    2013 경제발전경험모듈화사업 : 경제성장 기반구축을 위한 기업의 자생적 연구환경 조성

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    Summary Chapter 1 Preface 1. Overview of the Technique Innovation Support System 2. Background of the Private Companies Technology Innovation Promotion Policy Chapter 2 The Establishment and Revision of the Technology Development Promotion Law 1. Enactment and Changes of the Technology Development Promotion Law 2. Technique Innovation Support Systems between 1972~1980 3. Technique Innovation Support Systems between 1981~1995 Chapter 3 Technology Innovation Support System’s Contents by Sector 1. Evolution of Tax Incentives 2. Evolution of the Financial Support System Chapter 4 Performance of the Technique Innovation Support System 1. Overview 2. Size of Support from Technology Innovation Framework Private Companies 3. Expansion of Private Sector’s Research Organizations and R&D Investment 4. Science & Technology and Economic Achievements Chapter 5 Conclusio

    Predictive long-range allele-specific mapping of regulatory variants and target transcripts - Fig 2

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    <p>(A) Comparison of sensitivity between allelic mapping versus eQTL mapping. The number of GWAS SNPs with ChIP-seq imbalance versus that of GWAS SNPs that are histone QTLs (middle row), and the number of the imbalanced GWAS SNPs with paired allele-specific expression versus that of the histone QTLs that are eQTLs for paired genes (top row). For both allelic mapping and eQTL mapping, an unadjusted P < 0.05 was used as a threshold. (B) Allelic mapping for ITGA4. Three SNPs (blue) showed allele imbalance in ChIP-seq reads (blue bar graphs) with bias towards the disease risk allele. These SNPs were connected to ITGA4 as indicated by three different chromatin interactome datasets (black lines). The RNA-seq variants (red) showed allele-specific expression (red bar graphs) in the same direction as the ChIP-seq variants. eQTL mapping failed to detect association (boxplots).</p

    A nationwide time-series analysis for short-term effects of ambient temperature on violent crime in South Korea

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    Abstract Psychological theories on heat-aggression relationship have existed for decades and recent models suggest climate change will increase violence through varying pathways. Although observational studies have examined the impact of temperature on violent crime, the evidence for associations is primarily limited to coarse temporal resolution of weather and crime (e.g., yearly/monthly) and results from a few Western communities, warranting studies based on higher temporal resolution data of modern systemic crime statistics for various regions. This observational study examined short-term temperature impacts on violent crime using national crime data for the warm months (Jun.–Sep.) across South Korea (2016–2020). Distributed lag non-linear models assessed relative risks (RRs) of daily violent crime counts at the 70th, 90th, and 99th summer temperature percentiles compared to the reference temperature (10th percentile), with adjustments for long-term trends, seasonality, weather, and air pollution. Results indicate potentially non-linear relationships between daily summer temperature (lag0–lag10) and violent crime counts. Violent crimes consistently increased from the lowest temperature and showed the highest risk at the 70th temperature (~ 28.0 °C). The RR at the 70th and 90th percentiles of daily mean temperature (lag0–lag10), compared to the reference, was 1.11 (95% CI 1.09, 1.15) and 1.04 (95% CI 1.01, 1.07), indicating significant associations. Stratified analysis showed significant increases in assault and domestic violence for increases in temperature. The lagged effects, the influences of heat on subsequent crime incidence, did not persist 21 days after the exposure, possibly due to the displacement phenomenon. We found curvilinear exposure–response relationships, which provide empirical evidence to support the psychological theories for heat and violence. Lower public safety through increased violent crime may be an additional public health harm of climate change
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