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Melatonin (Mel) and its receptors (MT1 and MT2) have a well-documented efficacy in treating different pain conditions. However, the anti-nociceptive effects of Mel and Mel receptors in neuropathic pain (NP) are poorly understood. To elucidate this process, pain behaviors were measured in a dorsal root ganglia (DRG)-friendly sciatic nerve cuffing model. We detected up-regulation of MT2 expression in the DRGs of cuff-implanted mice and its activation by the agonist 8-M-PDOT (8MP). Also, Mel attenuated the mechanical and thermal allodynia induced by cuff implantation. Immunohistochemical analysis demonstrated the expression of MT2 in the DRG neurons, while MT1 was expressed in the satellite cells. In cultured primary neurons, microarray analysis and gene knockdown experiments demonstrated that MT2 activation by 8MP or Mel suppressed calcium signaling pathways via MAPK1, which were blocked by RAR-related orphan receptor alpha (RORα) activation with a high dose of Mel. Furthermore, expression of nitric oxide synthase 1 (NOS1) was down-regulated upon Mel treatment regardless of MT2 or RORα. Application of Mel or 8MP in cuff-implanted models inhibited the activation of peptidergic neurons and neuro-inflammation in the DRGs by down-regulating c-fos, calcitonin gene-related peptide [CGRP], and tumor necrosis factor-1α [TNF-1α] and interleukin-1β [IL-1β]. Addition of the MT2 antagonist luzindole blocked the effects of 8MP but not those of Mel. In conclusion, only MT2 was expressed in the DRG neurons and up-regulated upon cuff implantation. The analgesic effects of Mel in cuff-implanted mice were closely associated with both MT2-dependent (MAPK-calcium channels) and MT2-independent (NOS1) pathways in the DRG.

Aiming at the problem of slow speed in image matching,anti-interference difference and relatively poor ability to resist deformation,proposed a fast image matching method based on artificial fish swarm algorithm (AFSA). In the same test environment,Compared with the image matching method based on particle swarm optimization (PSO) algorithm and found,the method is superior to image matching method based on particle swarm optimization,in matching speed and noise resistance ability and deformation resistance ability has a marked improvement.

The optimal design approach of the PID controller was proposed in this paper, based on Artificial Fish Swarm Algorithm (AFSA) for the matter of the optimization of the brushless DC motor controller. In the experiment, through the analysis of the basic principles of artificial fish swarm algorithm, appropriate performance index was selected as fitness function, specific design procedures were given to optimize parameters of PID controller, The experimental results indicate that: Artificial Fish Swarm Algorithm optimized PID controller enables the brushless DC motor speed control system response faster, small overshoot, effectively improve the dynamic performance of a brushless DC motor control system.