Data Fusion Algorithm for Myocardial Proteomics and Its Research in Sports

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Abstract

Sport is a type of comprehensive activity that the human body consciously engages in to improve physical fitness. Proteomics is a comprehensive technology dedicated to the study of all protein profiles expressed by a species, individual organ, tissue, or cell under specific conditions and specific times. Proteomics is a science that studies the protein composition of cells, tissues, or organisms and their changing laws with proteomics as the research object. Related technologies are now widely used in sports and other fields. The purpose of this article is to study myocardial proteomic technology and its application in sports. During the research process, the main methods used in this study are literature survey and controlled experiment. The results achieved and the problems in this field, followed by selecting 30 SD rats into 3 groups for control experiments. The results of the study showed that among the three groups of rats, the left ventricular ejection fraction of the sham operation group was the highest, which was 7.7% and 4.6% higher than that of the operation group and the model group, respectively. The operation group had the highest left ventricular short axis shortening rate, and the left ventricle diastolic inner diameter is the longest. It can be seen that myocardial proteomics can accurately reflect the heart condition of rats. In addition, the length, diastolic velocity, and diastolic time of cardiomyocytes of the three groups of rats were different. Among them, the cardiomyocytes of the operation group had the longest time and the longest diastolic time, which were 37.1% and 8.5% higher than those of the sham operation group and the model group.

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Song, D., & Hu, X. (2022). Data Fusion Algorithm for Myocardial Proteomics and Its Research in Sports. Computational and Mathematical Methods in Medicine, 2022. https://doi.org/10.1155/2022/4049169

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