LI-F type peptides are a family of cyclic lipodepsipeptide antibiotics isolated from Paenibacillus polymyxa and display potent activities against positive bacteria including methicillin-resistant S. aureus (MRSA). In this study, we investigated the mechanism of action of LI-F type peptide AMP-jsa9 against a MRSA (S. aureus CICC10790), which is resistant to ciprofloxacin, gentamicin, kanamycin, chloramphenicol, methicillin, and tetracycline. It was found that AMP-jsa9 mainly targets the cell membrane of MRSA and is able to inhibit biofilm formation through killing planktonic bacteria cells. Moreover, AMP-jsa9 can bind to DNA in vitro, which represents another pathway for the action on MRSA. Furthermore, in vivo treatment of scalded mice with AMP-jsa9 resulted in inhibiting MRSA infections and healing of the scalded wound. In addition, it was demonstrated that AMP-jsa9 can effectively inhibit MRSA infections in scalded murine epidermis and that inflammatory cytokines including IL-8, IL-6, tumor necrosis factor alpha (TNF-α), and monocyte chemotactic factor-1 (MCP-1) were reduced; moreover, both protein and gene expression levels of vascular endothelial growth factor (VEGF) and endothelial nitric oxide synthase (e-NOS) were enhanced, which promote neovascularization and proliferation of new granulation tissue.
EEG-based human identification has gained a wide range of attention due to the further increase in demand for security. How to improve the accuracy of the human identification system is an issue worthy of attention. Using more features in the human identification system is a potential solution. However, too many features may cause overfitting, resulting in the decline of system accuracy. In this work, the graph convolutional neural network (GCN) was adopted for classification. Multiple features were combined and utilized as the structure matrix of the GCN. Because of the constant signal matrix, the training parameters would not increase as the structure matrix grows. We evaluated the classification accuracy on a classic public dataset. The results showed that utilizing multiple features of functional connectivity (FC) can improve the accuracy of the identity authentication system, the best results of which are at 98.56%. In addition, our methods showed less sensitivity to channel reduction. The method proposed in this paper combines different FCs and reaches high classification accuracy for unpreprocessed data, which inspires reducing the system cost in the actual human identification system.
Deep rock mass tends to be broken into blocks when mining for materials deep below the surface. The rock layer of the roof of the mine can be regarded as a system of blocks of fractured rock mass. When subjected to high ground stress and mining-induced disturbance, the effect of the ultra-low friction of the block system easily becomes apparent, and can induce rock burst and other accidents. By taking the block of rock mass as research object, this study developed a test system for ultra-low friction to experimentally examine its effects on the broken blocks under stress wave-induced disturbance. We used the horizontal displacement of the working block as the characteristic parameter reflecting the effect of ultra-low friction, and examine its characteristic laws of horizontal displacement, acceleration, and energy when subjected to the effects of ultra-low friction by changing the frequency and amplitude of the stress wave-induced disturbance. The results show that the frequency of stress wave-induced disturbance is related to the generation of ultra-low friction in the broken block. The frequency of disturbance of the stress wave is within 1–3 Hz, and significantly increases the maximum acceleration and horizontal displacement of the broken blocks. The greater the intensity of the stress wave-induced disturbance is, the higher is the degree of block fragmentation, and the more likely are effects of ultra-low friction to occur between the blocks. The greater the intensity of the horizontal impact load is, the higher is the degree of fragmentation of the rock mass, and the easier it is for the effects of ultra-low friction to occur. Stress wave-induced disturbance and horizontal impact are the main causes of sliding instability of the broken blocks. When the dominant frequency of the kinetic energy of the broken block is within 20 Hz, the effects of ultra-low friction are more likely.
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