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Identification of novel serum lipid metabolism potential markers and metabolic pathways for oral cancer: a population-based study.
BMC Cancer
January 2025
Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, School of Public Health, Fujian Medical University, 1 Xueyuan Road, Fujian, 350108, China.
Objective: This study aims to identify potential lipid biomarkers and metabolic pathways associated with oral cancer (OC). Then to establish and evaluate disease classification models capable of distinguishing OC patients from healthy controls.
Methods: A total of 41 OC patients and 41 controls were recruited from a hospital in Southeast China to examine the serum lipidomics by Ultra-high Performance Liquid Chromatography Q Exactive Mass Spectrometry (UHPLC-QE-MS).
An optimized lightweight real-time detection network model for IoT embedded devices.
Sci Rep
January 2025
School of Computer Science, Guangdong Polytechnic Normal University, Guangzhou, 510665, China.
With the rapid development of Internet of Things (IoT) technology, embedded devices in various computer vision scenarios can realize real-time target detection and recognition tasks, such as intelligent manufacturing, automatic driving, smart home, and so on. YOLOv8, as an advanced deep learning model in the field of target detection, has attracted much attention for its excellent detection speed, high precision, and multi-task processing capability. However, since IoT embedded devices typically own limited computing resources, direct deployment of YOLOv8 is a big challenge, especially for real-time detection tasks.
View Article and Find Full Text PDFExperience using conventional compared to ancestry-based population descriptors in clinical genomics laboratories.
Am J Hum Genet
January 2025
Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
Various scientific and professional groups, including the American Medical Association (AMA), American Society of Human Genetics (ASHG), American College of Medical Genetics (ACMG), and the National Academies of Sciences, Engineering, and Medicine (NASEM), have appropriately clarified that certain population descriptors, such as race and ethnicity, are social and cultural constructs with no basis in genetics. Nevertheless, these conventional population descriptors are routinely collected during the course of clinical genetic testing and may be used to interpret test results. Experts who have examined the use of population descriptors, both conventional and ancestry based, in human genetics and genomics have offered guidance on using these descriptors in research but not in clinical laboratory settings.
View Article and Find Full Text PDFCoevolutionary dynamics in the grass-livestock social-ecological system of China's alpine pastoral areas: A case study of the Qilian Mountains region in China.
PLoS One
January 2025
Department of Geography, University College London, London, England, United Kingdom.
Evaluating the dynamic co-evolution and feedback mechanisms within socio-ecological systems is crucial for determining the resilience and sustainability of environmental governance strategies. The grass-livestock system, as a complex entity encompassing livestock nutrition, foraging behavior, vegetation ecology, pastoralists' economic income, and policy interventions, indicates that any change in a single element may trigger a chain reaction within the system. This paper uses a system dynamics approach to construct a simulation model of the grass-livestock system in alpine pastoral areas, simulating the long-term dynamic co-evolution of the socio-ecological system in the Qilian Mountains region of China.
View Article and Find Full Text PDFApplication of the modified RIAM method in assessing the environmental impact of municipal solid waste management scenarios (A case study).
Heliyon
January 2025
School of Engineering, Mining Engineering Department, Urmia University, Urmia, Iran.
The rapid impact assessment matrix (RIAM) is a widely utilized tool for evaluating environmental impacts in municipal solid waste management. However, the traditional RIAM (T-RIAM) method includes ambiguities in its scoring classification, which can hinder decision-making accuracy. This study introduces a modified RIAM approach, enhancing classification precision by refining impact categories, making it particularly valuable for projects constrained by time and resources.
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