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http://dx.doi.org/10.1016/j.tmaid.2023.102669 | DOI Listing |
Sensors (Basel)
December 2024
Institute of Atmospheric Pollution Research-National Research Council (IIA-CNR), Research Area of Rome 1, Strada Provinciale 35d, Montelibretti, 9-00010 Roma, Italy.
Ecosystems and environments are impacted by atmospheric pollution, which has significant effects on human health and climate. For these reasons, devices for developing portable and low-cost monitoring systems are required to assess human exposure during daily life. In the last decade, the advancements of 3D printing technology have pushed researchers to exploit, in different fields of applications, the advantages offered, such as rapid prototyping and low-cost replication of complex sample treatment devices.
View Article and Find Full Text PDFTravel Med Infect Dis
January 2025
Second Department of Infectious Disease, Kunming Children's Hospital, Kunming, Yunnan, China; Yunnan Key Specialty of Pediatric Infection (Training and Education Program)/Kunming Key Specialty of Pediatric Infection, China; Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, Yunnan, China. Electronic address:
Aims: The aim of this study was to explore differences in operative autonomy by trainee gender during orthopaedic training in Ireland and the UK, and to explore differences in operative autonomy by trainee gender with regard to training year, case complexity, index procedures, and speciality area.
Methods: This retrospective cohort study examined all operations recorded by orthopaedic trainees in Ireland and the UK between July 2012 and July 2022. The primary outcome was operative autonomy, which was defined as the trainee performing the case without the supervising trainer scrubbed.
New Microbes New Infect
December 2024
National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, 102206, Changping District, Beijing City, China.
Cureus
November 2024
Pharmacology, All India Institute of Medical Sciences, Kalyani, IND.
Introduction Leptospirosis is a zoonotic infection caused by bacteria, which is reemerging in various regions and often poses a diagnostic challenge due to its nonspecific symptoms. While most infections are mild, severe cases occur in 5-10% of patients and are associated with high mortality, especially in areas with poor sanitation and urbanization. This study aims to investigate the association of specific parameters with leptospirosis diagnosis using a machine learning model and geographic mapping tools to identify spatial patterns and high-risk areas for the disease.
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