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Epidemiological Features, Clinical Symptoms, and Environmental Risk Factors for Notifiable Japanese Encephalitis in Taiwan From 2008 to 2020: Retrospective Study.
JMIR Public Health Surveill
January 2025
School of Public Health, National Defense Medical Center, Taipei City, Taiwan.
Background: Japanese encephalitis (JE) is a zoonotic parasitic disease caused by the Japanese encephalitis virus (JEV), and may cause fever, nausea, headache, or meningitis. It is currently unclear whether the epidemiological characteristics of the JEV have been affected by the extreme climatic conditions that have been observed in recent years.
Objective: This study aimed to examine the epidemiological characteristics, trends, and potential risk factors of JE in Taiwan from 2008 to 2020.
Institutional, neighborhood, and life stressors on loneliness among older adults.
BMC Public Health
January 2025
Faculty of Social Work, University of Toronto, 246 Bloor St W, Toronto, ON, M5S 1V4, Canada.
Background: Loneliness is a public health epidemic in the United States (US), with older adults being vulnerable to experiencing loneliness. Predictors of loneliness are less understood among racial/ethnic groups of US older adults, and few studies have included perceived institutional discrimination (PID), stressful life events (SLE), and perceived neighborhood characteristics (PNC) as antecedent stressors of loneliness in diverse older adult samples. Our study assessed the relationship between these stressors and loneliness among specific racial/ethnic groups of older adults.
View Article and Find Full Text PDFDeterminants of rural practice among a cohort of dental professionals in Australia.
BMC Med Educ
January 2025
La Trobe Rural Health School, La Trobe University, Bendigo, VIC, 3550, Australia.
Background: Most research on tracking practice locations of health students has focused on medical students, particularly the factors influencing their choice to work in rural and remote areas. However, there is limited research on how rural origin and training in regional or rural settings affect the employment destinations of dental and oral health graduates. This paper explores the practice locations of dentistry and oral health therapy (OHT) graduates from rural backgrounds compared to those from metropolitan areas in Australia.
View Article and Find Full Text PDFComparative study of degree, neighborhood and reverse degree based indices for drugs used in lung cancer treatment through QSPR analysis.
Sci Rep
January 2025
Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, 11461, Riyadh, Saudi Arabia.
Quantitative structure-property relationship (QSPR) modeling has emerged as a pivotal tool in the field of medicinal chemistry and drug design, offering a predictive framework for understanding the correlation between chemical structure and physicochemical properties. Topological indices are mathematical descriptors derived from the molecular graphs that capture structural features and connectivity, playing a crucial role in QSPR analysis by quantitatively relating chemical structures to their physicochemical properties and biological activities. Lung cancer is characterized by its aggressive nature and late-stage diagnosis, often limiting treatment options and significantly impacting patient survival rates.
View Article and Find Full Text PDFA hybrid deep learning air pollution prediction approach based on neighborhood selection and spatio-temporal attention.
Sci Rep
January 2025
School of Architecture and Urban Planning, Beijing University of Civil Engineering and Architecture, Beijing, 100055, China.
Air pollution is a critical global environmental issue, further exacerbated by rapid industrialization and urbanization. Accurate prediction of air pollutant concentrations is essential for effective pollution prevention and control measures. The complex nature of pollutant data is influenced by fluctuating meteorological conditions, diverse pollution sources, and propagation processes, underscores the crucial importance of the spatial and temporal feature extraction for accurately predicting air pollutant concentrations.
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