The amount of work the heart can perform during ejection is governed by the inherent contractile properties of individual myocytes. One way to alter contractile properties is to alter contractile proteins such as myosin heavy chain (MyHC), which is known to demonstrate isoform plasticity in response to disease states. The purpose of this study was to examine myocyte functionality over the complete range of MyHC expression in heart, from 100% alpha-MyHC to 100% beta-MyHC, using euthyroid and hypothyroid rats. Peak power output in skinned cardiac myocytes decreased as a nearly linear function of beta-MyHC expression during maximal (r2 = 0.85, n = 44 myocyte preparations) and submaximal (r2 = 0.82, n = 31 myocyte preparations) Ca2+ activation. To determine whether single myocyte function translated to the level of the whole heart, power output was measured in working heart preparations expressing varied ratios of MyHC. Left ventricular power output of isolated working heart preparations also decreased as a linear function of increasing beta-MyHC expression (r2 = 0.82, n = 34 myocyte preparations). These results demonstrate that power output is highly dependent on MyHC expression in single myocytes, and this translates to the performance of working left ventricles.
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Sci Rep
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Department of Electrical and Electronics, Faculty of Engineering, Alberoni University, Kapisa, Afghanistan.
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Shandong Key Laboratory of Biophysics, Institute of Biophysics, Institute of Rural Revitalization, School of Pharmacy, Dezhou University, 253023, Dezhou, China. Electronic address:
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School of Materials Science and Engineering, Henan Key Laboratory of Advanced Nylon Materials and Application, Zhengzhou University, Zhengzhou 450001, China.
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Background: Both listening to music during warm-up and consuming caffeine before exercise have been independently shown to enhance athletic performance. However, the potential synergistic effects of combining these strategies remain largely unexplored. To date, only two studies have reported additional benefits to combining music during warm-up with a caffeine dose of 3 mg/kg on taekwondo-specific performance tasks.
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School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi 214122, China.
With the rapid development of AI algorithms and computational power, object recognition based on deep learning frameworks has become a major research direction in computer vision. UAVs equipped with object detection systems are increasingly used in fields like smart transportation, disaster warning, and emergency rescue. However, due to factors such as the environment, lighting, altitude, and angle, UAV images face challenges like small object sizes, high object density, and significant background interference, making object detection tasks difficult.
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