Cultured cardiomyocytes can be used to study cardiomyocyte biology using techniques that are complementary to in vivo systems. For example, the purity and accessibility of in vitro culture enables fine control over biochemical analyses, live imaging, and electrophysiology. Long-term culture of cardiomyocytes offers access to additional experimental approaches that cannot be completed in short term cultures. For example, the in vitro investigation of dedifferentiation, cell cycle re-entry, and cell division has thus far largely been restricted to rat cardiomyocytes, which appear to be more robust in long-term culture. However, the availability of a rich toolset of transgenic mouse lines and well-developed disease models make mouse systems attractive for cardiac research. Although several reports exist of adult mouse cardiomyocyte isolation, few studies demonstrate their long-term culture. Presented here, is a step-by-step method for the isolation and long-term culture of adult mouse cardiomyocytes. First, retrograde Langendorff perfusion is used to efficiently digest the heart with proteases, followed by gravity sedimentation purification. After a period of dedifferentiation following isolation, the cells gradually attach to the culture and can be cultured for weeks. Adenovirus cell lysate is used to efficiently transduce the isolated cardiomyocytes. These methods provide a simple, yet powerful model system to study cardiac biology. Video LinkThe video component of this article can be found at http://www.jove.com/video/54012/ IntroductionCultured cardiomyocytes are frequently used to monitor cell behavior in a well-controlled environment in vitro. For example, morphological, electrical, biochemical, or mechanical cell properties can be studied on engineered substrates, 1,2 in defined media, and in response to small molecule drugs, peptides, gene regulation, 3 or electrical stimulation. 4 The cellular content can also be controlled using defined co-cultures. 5These in vitro experiments are useful in large drug or genetic screens and complement in vivo methods for various types of investigations involving cardiomyocyte biology.Long-term culture enables experimental avenues that require extended periods of time to achieve phenotypic change. A timely example is that of adult mammalian cardiomyocyte proliferation, where dedifferentiation, cell cycle re-entry, and cell division is typically studied over several days to weeks. 6,7 Here, the extended culture time facilitates genetic manipulation, 7,8 functional dedifferentiation (e.g., sarcomeric disassembly) 9 and potentially transcriptional dedifferentiation.6 Subsequent cell cycle re-entry and cell division requires even longer culture periods to observe, especially if multiple rounds of division are the experimental goal. The importance of the cardiomyocyte cell-cycle is central to several recent key scientific works in heart regeneration, where the dedifferentiation and proliferation of pre-existing cardiomyocytes has been shown responsible for heart regeneration in ...
Considering the limitation of tracking range on sports video target tracking in basketball games, there are some problems, such as poor tracking effect, low accuracy, low anti-interference ability, and being time-consuming. Therefore, this study proposes a target tracking algorithm of basketball video based on improved grey neural network. According to the pixel grey difference of the target image in basketball video, this study applies the adaptive threshold algorithm in order to segment the target image of basketball video and obtain the target area of basketball video. This algorithm can normalize the grey level of the target area, build the generating sequence of the target area, and collect the target data of the basketball video. It obtains the feature output matrix of basketball video target based on the geometric dispersion of the target image and extracts the key feature points of basketball video target by single frame visual difference analysis. In addition, it makes use of the improved grey neural network to track and locate the feature points of basketball video target and reconstruct the basketball video target image with superresolution to realize basketball video target tracking. The experimental results show that the proposed algorithm has good target tracking effect of basketball video, can effectively improve the target tracking accuracy and anti-interference ability, and can shorten the target tracking time.
Football is one of the favorite sports of people nowadays. Shooting is the ultimate goal of all offensive tactics in football matches. This is the most basic way to score a goal and the only way to score a goal. The choice and use of shooting technical indicators can have a great impact on the final result of the game. Therefore, how to improve the shooting technique of football players and how to adjust the shooting posture of football players are important issues faced by coaches and athletes. In recent years, deep learning has been widely used in various fields such as image classification and recognition and language processing. How to apply deep learning optimization to shooting gesture recognition is a very promising research direction. This article aims to study the football player’s shooting posture specification based on deep learning in sports event videos. Based on the analysis of target motion detection algorithm, target motion tracking algorithm, target motion recognition algorithm, and football shooting posture classification, KTH and Weizmann data sets are used. As the experimental verification data set of this article, the shooting posture of football players in the sports event video is recognized, and the accuracy of the action recognition is finally calculated to standardize the football shooting posture. The experimental results show that the Weizmann data set has a higher accuracy rate than the KTH data set and is more suitable for shooting attitude specifications.
Introduction: It is necessary to adjust the physical training of swimmers according to their physical conditions, being the progressive stages method the most indicated nowadays. However, this is not the most observed technique in teaching swimming to college students. Objective: Study a protocol for applying progressive physical training in teaching swimming to college students. Methods: In one semester of teaching swimming sports, two volunteer students (n=40) classes were selected for the experiment. Equally divided into experimental and control group, the experimental group trained according to the phased physical training, while the control trained according to the usual semester physical training program. Before and after the experiment, the relevant indices were measured. Results: Compared with constant general physical training, progressive physical training can provide better guidance of necessary training according to the actual situation of students, and the efficiency of optimization on body composition is more evident during the semester. Conclusion: Selecting progressive physical training and adjusting training items and intensity according to students’ actual situation can amplify the effect of swimming instruction on college students, its promotion is suggested. Level of evidence II; Therapeutic studies - investigation of treatment outcomes.
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