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Huishan HAN,정재경,한상배,남상윤,오기완,홍진태 한국식품영양과학회 2011 Journal of medicinal food Vol.14 No.7
This study investigated the anxiolytic-like effects of 4-O-methylhonokiol, a neolignan compound of Magnolia officinalis, by using the experimental paradigms of anxiety and compared the results with those of a known anxiolytic, diazepam. A single treatment with 4-O-methylhonokiol (0.1, 0.2, and 0.5 mg/kg, p.o.) or treatment for 7 days (0.5 mg/kg in drinking water) increased the percentage of time spent in the open arms and the number of open arms entries in the elevated plus-maze test. However, the 4-O-methylhonokiol-increased percentage of time spent in the open arm was abolished by treatment with flumazenil, a benzodiazepine receptor antagonist (10 mg/kg). 4-O-Methylhonokiol also increased the number of head dips in the hole-board test, but decreased locomotor activity. Molecular experiments revealed that the α1-subunit of γ-aminobutyric acid (GABA) type A receptors was overexpressed in the cortex of brains of mice after treatment with 4-O-methylhonokiol for 7 days. In addition, 4-O-methylhonokiol also increased chloride influx in cultured cortical cells. It is concluded that 4-O-methylhonokiol may have anxiolytic-like effects and that these effects may be mediated by GABAergic transmission with the increase of Cl– channel opening.
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Research on Computer Network Virus Defense Technology in Cloud Technology Environmen
Zhao Sheng,Han HuiShan,Shi XueKui 보안공학연구지원센터 2016 International Journal of Security and Its Applicat Vol.10 No.3
With the rapid development of the Internet, the antivirus software of the network is always emerging and constantly changing. Traditional detection methods can’t effectively kill the new viruses and malicious software, the complexity of which also makes itself easy to be attacked by malicious software. The emergence of cloud computing has changed the status quo. Therefore, the architecture model of virus malware detection based on cloud computing is proposed in this paper. Based on the combination of the method for detecting malicious software virus based on cloud computing and the algorithm analysis theory in machine learning, a new type of distributed CFO algorithm is proposed, and the closed environment of cloud computing virtual machine nodes is used to realize dynamic behavior monitoring to the virus malware, then the distributed fluctuations PIF algorithm is used to describe the process of dynamic analysis and analysis reporting, besides, the wave algorithm is carried out corresponding improvement based on the analysis of the environment. Experimental results show that the model can detect the conditional trigger behavior of virus malware, so as to find the conditions for triggering malicious behavior and the input data that satisfy these conditions and the performance of this monitoring system is greatly improved compared with the common single machine system.
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Research on Data Intrusion Detection Technology based on Fuzzy Algorithm
Sheng Zhao,Huishan Han,Xuekui Shi 보안공학연구지원센터 2016 International Journal of Security and Its Applicat Vol.10 No.8
The computer system is becoming more complex and massive network data, which brings great difficulties to the traditional intrusion detection system. Intrusion detection system is an important part of the network and information security architecture, which is mainly used to distinguish the normal activities of the system and the suspicious and intrusion patterns. But the challenge is how to effectively detect network intrusion behavior in order to reduce the false alarm rate and false negative rate. Based on the shortcomings of existing intrusion detection methods, the fuzzy C- means clustering method is proposed to analyze the intrusion detection data, so as to find out the abnormal network behavior patterns. By testing the CUP99 data set, the results show that the IFCA is not only feasible but also accurate and efficient. The improved fuzzy clustering algorithm proposed in this paper can improve the detection rate of intrusion detection and reduce the false detection rate, and can be widely used in intrusion detection system.
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Ma, Yuan,Han, Huishan,Eun, Jae Soon,Kim, Hyung-Chun,Hong, Jin-Tae,Oh, Ki-Wan Pharmaceutical Society of Japan 2007 Biological & pharmaceutical bulletin Vol.30 No.9
<P>Zizyphi Spinosi Semen (ZSS) has been widely used for the treatment of insomnia in oriental countries. This experiment was performed to investigate whether sanjoinine A, one of major alkaloid compounds of ZSS, has hypnotic effects and/or enhances pentobarbital-induced sleeping behaviors through the γ-aminobutyric acid (GABA)-ergic systems. Sanjoinine A itself did not induce sleeping at the higher dose used in this experiment. However, sanjoinine A prolonged sleeping time and reduced the sleeping latency induced by pentobarbital in a dose-dependent manner similar to muscimol, a GABA<SUB>A</SUB> receptor agonist. Sanjoinine A also increased sleeping rate and sleeping time when administered combined with pentobarbital at a sub-hypnotic dosage and showed synergistic effects with muscimol in potentiating sleeping onset and enhancing sleeping time induced by pentobarbital. In addition, both sanjoinine A and pentobarbital increased chloride influx in primary cultured cerebellar granule cells. Sanjoinine A also showed similar effects with muscimol in potentiating chloride influx inducing effects of low dose pentobarbital. Sanjoinine A decreased GABA<SUB>A</SUB> receptor α-subunit expression and increased γ-subunit expression, and had no effects on the abundance of β-subunits in primary cultured cerebellar granule cells, showing different subunit expression from pentobarbital. In addition, we found that sanjoinine A also enhanced expression of glutamic acid decarboxylase (GAD), but pentobarbital did not. In conclusion, sanjoinine A itself does not induce sleeping, but it augments pentobarbital-induced sleeping behaviors through the modification of GABA-ergic systems.</P>
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