Environmental toxicants and pollutants are causes of adverse health consequences, including well-established associations between environmental exposures and cardiovascular diseases. Environmental degradation is widely prevalent and has a long latency period between exposure and health outcome, potentially placing a large number of individuals at risk of these health consequences. Emerging evidence suggests that environmental exposures in early life may be key risk factors for cardiovascular conditions across the life span. Children are a particularly sensitive population for the detrimental effects of environmental toxicants and pollutants given the long-term cumulative effects of early-life exposures on health outcomes, including congenital heart disease, acquired cardiac diseases, and accumulation of cardiovascular disease risk factors. This scientific statement highlights representative examples for each of these cardiovascular disease subtypes and their determinants, focusing specifically on the associations between climate change and congenital heart disease, airborne particulate matter and Kawasaki disease, blood lead levels and blood pressure, and endocrine-disrupting chemicals with cardiometabolic risk factors. Because children are particularly dependent on their caregivers to address their health concerns, this scientific statement highlights the need for clinicians, research scientists, and policymakers to focus more on the linkages of environmental exposures with cardiovascular conditions in children and adolescents.
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http://dx.doi.org/10.1161/CIR.0000000000001234 | DOI Listing |
Sci Rep
December 2024
Department of Ecology, Faculty of Sciences, Institute of Biology, University of Pécs, Ifjúság útja 6, Pécs, 7624, Hungary.
The European pond turtle (Emys orbicularis) is a wide-ranging, long-living freshwater species with low reproductive success, mainly due to high predation pressure. We studied how habitat variables and predator communities in near-natural marshes affect the survival of turtle eggs and hatchlings. We followed the survival of artificial turtle nests placed in marshes along Lake Balaton (Hungary) in May and June as well as hatchlings (dummies) exposed in September.
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December 2024
Division of Pulmonary and Critical Care, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095-1690, USA.
Electronic cigarettes (e-cigs) fundamentally differ from tobacco cigarettes in their generation of liquid-based aerosols. Investigating how e-cig aerosols behave when inhaled into the dynamic environment of the lung is important for understanding vaping-related exposure and toxicity. A ventilated artificial lung model was developed to replicate the ventilatory and environmental features of the human lung and study their impact on the characteristics of inhaled e-cig aerosols from simulated vaping scenarios.
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December 2024
Department of Applied Mathematics, Faculty of Mathematical Science, Ferdowsi University of Mashhad, Mashhad, Iran.
This study presents a web application for predicting cardiovascular disease (CVD) and hypertension (HTN) among mine workers using machine learning (ML) techniques. The dataset, collected from 699 participants at the Gol-Gohar mine in Iran between 2016 and 2020, includes demographic, occupational, lifestyle, and medical information. After preprocessing and feature engineering, the Random Forest algorithm was identified as the best-performing model, achieving 99% accuracy for HTN prediction and 97% for CVD, outperforming other algorithms such as Logistic Regression and Support Vector Machines.
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December 2024
British Antarctic Survey, High Cross, Madingley Road, Cambridge, UK.
Marine microplastic is pervasive, polluting the remotest ecosystems including the Southern Ocean. Since this region is already undergoing climatic changes, the additional stress of microplastic pollution on the ecosystem should not be considered in isolation. We identify potential hotspot areas of ecological impact from a spatial overlap analysis of multiple data sets to understand where marine biota are likely to interact with local microplastic emissions (from ship traffic and human populations associated with scientific research and tourism).
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December 2024
Department of Electrical Engineering, College of Engineering, Taif University, P.O. BOX 11099, 21944, Taif, Saudi Arabia.
Weather recognition is crucial due to its significant impact on various aspects of daily life, such as weather prediction, environmental monitoring, tourism, and energy production. Several studies have already conducted research on image-based weather recognition. However, previous studies have addressed few types of weather phenomena recognition from images with insufficient accuracy.
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