Rapamycin repairs damaged nerve cells and neurological function in rats with spinal cord injury through ERK signaling pathway

High-Intensity Injury Recognition Pattern of Sports Athletes Based on the Deep Neural Network

In order to solve the problem of low efficiency and accuracy of injury image recognition for sports athletes in high-intensity injury treatment, this paper proposes an injury recognition mode based on the deep neural network. In this paper, the image of sports injury is converted to gray level, and the contour of the injury part in the image is extracted according to the combination of adaptive thresholding and mathematical morphology. In this model, the seed points are selected, the active contour is used to approximate the initial contour, and the curve fitting method is used to fit the obtained discrete points to obtain the final damaged contour. The digital matrix is constructed by using the extracted number of pixels at the damaged position and relevant information. The images are arranged into feature vectors with a length of 64 according to the mode of column concatenation. The overall mean vector of the image is calculated. The calculation results, training samples, and image samples to be recognized are substituted into the Euclidean distance to obtain the preliminary recognition results of the damaged position of the image of sports injury. Then, the image segmentation is realized by clustering. The clustering segmentation results are used to color describe the pixel categories of the original image, calculate the relative damage proportion area in the sports injury image, and identify the damage parts of the high-intensity sports injury image. The experimental results show that the recognition rate of the neural network is 80%-100%, and the recognition time of this method is 0-0.6/s. The above method can improve the accuracy of the recognition of the damaged part of the sports injury image and shorten the recognition time and has certain feasibility in determining the sports injury part.

Role of the Extracellular Traps in Central Nervous System

It has been reported that several immune cells can release chromatin and granular proteins into extracellular space in response to the stimulation, forming extracellular traps (ETs). The cells involved in the extracellular trap formation are recognized including neutropils, macrophages, basophils, eosinophils, and mast cells. With the development of research related to central nervous system, the role of ETs has been valued in neuroinflammation, blood–brain barrier, and other fields. Meanwhile, it has been found that microglial cells as the resident immune cells of the central nervous system can also release ETs, updating the original understanding. This review aims to clarify the role of the ETs in the central nervous system, especially in neuroinflammation and blood–brain barrier.