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http://dx.doi.org/10.1002/ijc.23854 | DOI Listing |
J Sports Med Phys Fitness
January 2025
Department of Human Movement Studies, University of Ostrava, Ostrava, Czech Republic.
Background: Although runners are healthier than most of the population, they can incur a risk of injury. Literature shows a strong evidence of risk factors for running-related injuries (RRIs) based on characteristics of running. This study aimed to assess differences in psychosocial factors between injured and uninjured recreational runners.
View Article and Find Full Text PDFR Soc Open Sci
January 2025
Department of Anatomy, Kanazawa Medical University, Uchinada, Ishikawa 9200293, Japan.
Acute myeloid leukaemia (AML) is a haematologic malignancy with high relapse rates in both adults and children. Leukaemic stem cells (LSCs) are central to leukaemopoiesis, treatment response and relapse and frequently associated with measurable residual disease (MRD). However, the dynamics of LSCs within the AML microenvironment is not fully understood.
View Article and Find Full Text PDFPostgrad Med J
January 2025
Faculty of Law, University of Abuja, PMB 117, Gwagwalada, Abuja 902101, Nigeria.
Engaging in research during medical training is crucial for fostering critical thinking, enhancing clinical skills, and deepening understanding of medical science. Despite its importance, the shortage of physician-scientists lingers with many trainees and junior doctors encountering challenges navigating the research process. Drawing on current literature, this article provides a comprehensive roadmap, categorising 12 actionable strategies into five themes, to help medical trainees overcome common obstacles and optimise their research experience.
View Article and Find Full Text PDFALTEX
January 2025
National Institutes of Health, National Institute for Environmental Health Sciences, DTT/NICEATM, Durham, NC, USA.
The integration of artificial intelligence (AI) into new approach methods (NAMs) for toxicology rep-resents a paradigm shift in chemical safety assessment. Harnessing AI appropriately has enormous potential to streamline validation efforts. This review explores the challenges, opportunities, and future directions for validating AI-based NAMs, highlighting their transformative potential while acknowledging the complexities involved in their implementation and acceptance.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Rehabilitation Medicine, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200336, China.
Accurately extracting organs from medical images provides radiologist with more comprehensive evidences to clinical diagnose, which offers up a higher accuracy and efficiency. However, the key to achieving accurate segmentation lies in abundant clues for contour distinction, which has a high demand for the network architecture design and its practical training status. To this end, we design auxiliary and refined constraints to optimize the energy function by supplying additional guidance in training procedure, thus promoting model's ability to capture information.
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