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Abstract Background Cerebral infarction ranks as the second leading cause of disability and death globally, and inflammatory response of glial cells is the main cause of brain damage during cerebral infarction. Methods Studies have shown that mesenchymal stem cells (MSCs) can secrete exosomes and contribute to cerebral disease. Here, we would explore the function of MSC-derived exosome in cerebral infarction. Results Microarray indicated a decrease of miR-542-3p and an increase of Toll-Like Receptor 4 (TLR4) in middle cerebral artery occlusion (MCAO) mice comparing with sham mice. And luciferase and RIP analysis indicated a binding of miR-542-3p and TLR4. Then, we injected AAV9-miR-542-3p into paracele of sham or MCAO mice. Functional analysis showed that AAV9-miR-542-3p inhibited infarction area and the number of degenerating neurons and suppressed inflammatory factors’ expression and inflammatory cell infiltration. As well, transfection of miR-542-3p mimics into HA1800 cells underwent oxygen and glucose deprivation (OGD). Similarly, overexpression of miR-542-3p alleviated OGD induced cell apoptosis, ROS, and activation of inflammation response. Moreover, miR-542-3p could be packaged into MSCs and secreted into HA1800 cells. The extractive exosome-miR-21-3p treatment relieved MCAO- or OGD-induced cerebral injury and inflammation through targeting TLR4. Conclusion These results confirmed that MSC-derived exosome miR-542-3p prevented ischemia-induced glial cell inflammatory response via inhibiting TLR4. These results suggest possible therapeutic strategies for using exosome delivery of miR-542-3p to cure cerebral ischemic injury.

Because the traditional maximum power point tracking (MPPT) of photovoltaic (PV) array is easy to fail in complex environment, and the existing intelligent optimization algorithms have shortcomings such as slow convergence speed, low convergence precision and poor stability. Therefore, this paper proposes a new intelligent optimization algorithm MPPT tracking method. Based on mayfly intelligent optimization algorithm, this method can track the maximum power point (MPP) of PV system by two populations, which can quickly and accurately track MPP of PV system under complex environmental conditions. By using Matlab/Simulink simulation platform, the method was studied under uniform illumination and non-uniform illumination respectively, and its effectiveness was verified. Compared with the particle swarm optimization algorithm (PSO), its superiority is verified.