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Objective: To investigate the effect of memantine on Parkinson’s disease cell models. Methods: Parkinson’s disease cell models were established using PC12 cells incubated with 6-hydroxydopamine (6-OHDA). Flow cytometry and microscopy were used to investigate the apoptotic process and the percentage of different apoptotic stages. PC12 cells were infected with lentiviral vectors to knockdown Nur77. Western blotting was used to detect the expression of Nur77 and caspase -3, -8, -9, -12 in PC12 cells withdifferent concentrations of 6-OHDA or 6-OHDA+memantine. Results: 6-OHDA led to apoptosis PC12 cells, and increased the expression of Nur77 and caspases. Memantine significantly inhibited 6-OHDA-induced apoptosis of PC12 cells. Meanwhile, memantine could mitigate apoptosis of PC12 cells by regulating the Nur77 and caspase pathway. Conclusions: Memantine has a protective effect on the PC12 cell model via regulating the Nur77 and caspases pathway.

In order to overcome the problems of traditional power information system and improve the work efficiency of power information system, a novel construction method of log fusion technology of power information system based on fuzzy reasoning is proposed in this paper. The construction method aims at the characteristics of the data in the traditional power information system, which are multi-source, heterogeneity and magnanimity, and the requirements of the current society for the power information system. Based on this, the construction method integrates a variety of high and new technologies, such as massive multi-source heterogeneous log data fusion processing technology, data analysis technology, big data evaluation technology and so on. The research results show that the construction method can optimize the current power information system from many aspects, such as the process of collection and transmission of multi-source heterogeneous data, the process of identifying and filtering massive data, and then fundamentally improve the work efficiency of the power information system.

In view of the current situation that the power information system is becoming larger and larger and the operation and maintenance is more and more complex, this paper proposes an objective evaluation method of power information system index based on DEA-CCR. Apriori association rule algorithm is used to mine the association relationship between log information, and then select the important association rules that can express the health of power information system. Combined with the extracted association rules, using DEA-CCR evaluation model to get the comprehensive efficiency quantitative index of each decision-making unit, and then according to the extracted index, to evaluate the health of the system. Finall•y, an example is analyzed based on the log data of the host computer of the marketing system of a power company. The results show that the method in this paper is effective and objective, and has strong application value.