Additionally, while fluorescent microscopy systems are vital tool for muscle biology research, they require significant manual optimization and continuous human supervision. Moreover, image acquisition and reconstitution of different multiple subsets of the whole muscle may expose the overall results to bias. In addition, the shape of the cells in normal muscle is characterized by polygonal and angular myofibers with keeping their contact with each other, while in regenerating myofibers they are round-shaped, highly variable in size, and smallest ones do not regularly contact surrounding fibers. While, these strategies induce prominent regenerating capability, there are questions about their physiological relevance due to invasive nature and the potential to damage the skeletal muscle 9. Most of current available softwares were developed to measure myofiber CSA in normal muscle or under conditions targeting muscle regeneration including synergist ablation or cardiotoxin injection 4, 8. This is why some laboratories have developed their own automated programs to limit the experimenter bias and save time 4, 5, 6, 7, 8. Image quantification is highly time-consuming and labor intensive part of this process and may susceptible to both inter-individual and inter-laboratory variabilities. Currently, CSA quantification is commonly performed method to delineate individual myofibers using immunohistochemical approaches targeting laminin or dystrophin in the basal lamina or inside of the sarcolemma, respectively 4, 5. Among different cellular, molecular and structural components, CSA quantification of myofibers in microscopic images is widely used since it reflects the regenerative capability of the muscle as a final results of activating, proliferating, differentiating and fusing of muscle stem cells 1. Moreover, during physical inactivity, aging and some metabolic disorders, skeletal muscle losses in mass due to atrophy of individual myofibers 3. Exercise training is a unique physiologicall-hypertrophy stimulus with the capability to induce muscle regeneration machinery throw increasing myofiber CSA to overcome corresponding skeletal muscle demands. Skeletal muscle is an exceptionally regenerative tissue with the ability to undergoes extensive adaptation by changing its fiber type composition and cross-sectional area (CSA) upon external stimuli 1, 2. We present MyoView as a new tool to quantify CSA, myonuclei and satellite cells in skeletal muscle from any experimental condition including exercise-induced regenerating myofibers. Furthermore, we demonstrated that to obtain an accurate CSA quantification of exercise-induced regenerating myofibers, whole muscle cross-section analysis is an essential part, especially for the measurement of different fiber-types. We also showed that MyoView is more accurate and efficient to measure CSA in post-exercise regenerating myofibers as compared with Open-CSAM, MuscleJ, SMASH and MyoVision. We showed that MyoView is comparable with manual quantification. MyoView provides relatively efficient, accurate, and reliable measurements for CSA quantification and detecting different myofibers, myonuclei and satellite cells in response to the post-exercise regenerating process. Here, we have developed a novel fully-automated image segmentation method based on neutrosophic set algorithms to analyse whole skeletal muscle cross sections in exercise-induced regenerating myofibers, referred as MyoView, designed to obtain accurate fiber size and distribution measurements. Although several excellent programs are available to automate analysis of muscle histology, they fail to efficiently and accurately measure CSA in regenerating myofibers in response to exercise training. Cross-sectional area (CSA) quantification, as a main parameter to assess muscle regeneration capability, is highly tedious and time-consuming, necessitating an accurate and automated approach to analysis. Skeletal muscle is an adaptive tissue with the ability to regenerate in response to exercise training.
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