Annals of medicine
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Over the past two decades, the use of Metaverse-enhanced simulations in medical education has witnessed significant advancement. These simulations offer immersive environments and technologies, such as augmented reality, virtual reality, and artificial intelligence that have the potential to revolutionize medical training by providing realistic, hands-on experiences in diagnosing and treating patients, practicing surgical procedures, and enhancing clinical decision-making skills. This scoping review aimed to examine the evolution of simulation technology and the emergence of metaverse applications in medical professionals' training, guided by Friedman's three dimensions in medical education: physical space, time, and content, along with an additional dimension of assessment. ⋯ Our study provides an updated perspective on the achievements and limitations of using simulation to transform medical education, offering insights that can inform development priorities and research directions for human-centered, ethical metaverse applications that enhance healthcare professional training.
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Review
Epidemiology, pathogenesis, clinical characteristics, and treatment of mucormycosis: a review.
This review aims to summarize the epidemiology, etiology, pathogenesis, clinical manifestations, and current diagnostic and therapeutic approaches for mucormycosis. The goal is to improve understanding of mucormycosis and promote early diagnosis and treatment to reduce mortality. ⋯ An enhanced understanding of the epidemiology, pathogenesis, and clinical presentation of mucormycosis, along with the adoption of improved diagnostic and therapeutic approaches, is essential for reducing mortality rates associated with this opportunistic fungal infection. Early diagnosis and prompt treatment are critical to improving patient outcomes.
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The findings of the last decade suggest a complex link between inflammatory cells, coagulation, and the activation of platelets and their synergistic interaction to promote venous thrombosis. Inflammation is present throughout the process of venous thrombosis, and various metabolic pathways of erythrocytes, endothelial cells, and immune cells involved in venous thrombosis, including glucose metabolism, lipid metabolism, homocysteine metabolism, and oxidative stress, are associated with inflammation. ⋯ We also explore the great potential of anti-inflammatory strategies targeting venous thrombosis and the complex link between anti-inflammation and metabolism. Furthermore, we suggest how we can use our existing knowledge to reduce the risk of venous thrombosis.
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Many studies have explored the value of the systemic inflammation response index (SIRI) in predicting the prognosis of patients with breast cancer (BC); however, their findings remain controversial. Consequently, we performed the present meta-analysis to accurately identify the role of SIRI in predicting BC prognosis. ⋯ According to our results, a high SIRI significantly predicted poor OS in patients with BC. Furthermore, elevated SIRI was also remarkably related to increased tumor size and later BC tumor stage. The SIRI can serve as a novel prognostic biomarker for patients with BC.
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Infectious diseases are a major threat for human and animal health worldwide. Artificial Intelligence (AI) combined algorithms including Machine Learning and Big Data analytics have emerged as a potential solution to analyse diverse datasets and face challenges posed by infectious diseases. In this commentary we explore the potential applications and limitations of ML to management of infectious disease. ⋯ We propose potential solutions to mitigate these hurdles and applications of ML to identify biomolecules for effective treatment and prevention of infectious diseases. In addition to use of ML for management of infectious diseases, potential applications are based on catastrophic evolution events for the identification of biomolecular targets to reduce risks for infectious diseases and vaccinomics for discovery and characterization of vaccine protective antigens using intelligent Big Data analytics techniques. These considerations set a foundation for developing effective strategies for managing infectious diseases in the future.