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Exergames have been recommended as alternative ways to increase the health benefits of physical exercise. However, energy system contributions (phosphagen, glycolytic, and oxidative) of exergames in specific age groups remain unclear. The purpose of this study was to investigate the contributions of three energy systems and metabolic profiles in specific age groups during exergames. Seventy-four healthy males and females participated in this study (older adults, = 26: Age of 75.4 ± 4.4 years, body mass of 59.4 ± 8.7 kg, height of 157.2 ± 8.6 cm; adults, = 24: Age of 27.8 ± 3.3 years, body mass of 73.4 ± 17.8 kg, height of 170.9 ± 11.9 cm; and adolescents, = 24: Age of 14 ± 0.8 years, body mass of 71.3 ± 11.5 kg, height of 173.3 ± 5.2 cm). To evaluate the demands of different energy systems, all participants engaged in exergames named Action-Racing. Exergames protocol comprised whole-body exercises such as standing, sitting, stopping, jumping, and arm swinging. During exergames, mean heart rate (HR), peak heart rate (HR), mean oxygen uptake (VO), peak oxygen uptake (VO), peak lactate (Peak La), difference in lactate (ΔLa), phosphagen (W), glycolytic (W), oxidative (W), and total energy demands (W) were analyzed. The contribution of the oxidative energy system was higher than that of the phosphagen or glycolytic energy system (65.9 ± 12% vs. 29.5 ± 11.1% or 4.6 ± 3.3%, both < 0.001). The contributions of the total energy demands and oxidative system in older adults were significantly lower than those in adults and adolescents (72.1 ± 28 kJ, = 0.028; 70.3 ± 24.1 kJ, = 0.024, respectively). The oxidative energy system was predominantly used for exergames applied in the current study. In addition, total metabolic work in older adults was lower than that in adolescents and adults. This was due to a decrease in the oxidative energy system. For future studies, quantification of intensity and volume is needed to optimize exergames. Such an approach plays a crucial role in encouraging physical activity in limited spaces.
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http://dx.doi.org/10.3390/ijerph17134905 | DOI Listing |
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Department of Clinical Molecular Biology, University of Oslo and Akershus University Hospital, Lørenskog, Norway.
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Cellular and Molecular Physiology Department, Yale School of Medicine, New Haven, CT, USA.
The essential cofactor coenzyme A (CoASH) and its thioester derivatives (acyl-CoAs) have pivotal roles in cellular metabolism. However, the mechanism by which different acyl-CoAs are accurately partitioned into different subcellular compartments to support site-specific reactions, and the physiological impact of such compartmentalization, remain poorly understood. Here, we report an optimized liquid chromatography-mass spectrometry-based pan-chain acyl-CoA extraction and profiling method that enables a robust detection of 33 cellular and 23 mitochondrial acyl-CoAs from cultured human cells.
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State Key Laboratory of Flexible Electronics, Institute of Advanced Materials (IAM), Nanjing University of Posts & Telecommunications (NUPT), Nanjing, 210023, China.
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September 2025
Fukushima Renewable Energy Institute, Koriyama, Japan.
Ultra-fast charging stations (UFCS) present a significant challenge due to their high power demand and reliance on grid electricity. This paper proposes an optimization framework that integrates deep learning-based solar forecasting with a Genetic Algorithm (GA) for optimal sizing of photovoltaic (PV) and battery energy storage systems (BESS). A Gated Recurrent Unit (GRU) model is employed to forecast PV output, while the GA maximizes the Net Present Value (NPV) by selecting optimal PV and BESS sizes tailored to weekday and weekend demand profiles.
View Article and Find Full Text PDFACS Appl Mater Interfaces
September 2025
Affiliated Hospital of Shandong Second Medical University, Shandong Second Medical University, Weifang, Shandong 261053, P.R. China.
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