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Lu, Beibei,Ding, Ruxian,Zhang, Lei,Yu, Xiaojing,Huang, Beibei,Chen, Wansheng Korean Society for Biochemistry and Molecular Biol 2006 Journal of biochemistry and molecular biology Vol.39 No.5
A novel calcium-dependent protein kinase gene (designated as IiCPK2) was cloned from tetraploid Isatis indigotica. The full-length cDNA of IiCPK2 was 2585 bp long with an open reading frame (ORF) of 1878 bp encoding a polypeptide of 625 amino acid residues. The predicted IiCPK2 polypeptide included three domains: a kinase domain, a junction domain (or autoinhibitory region), and a C-terminal calmodulin-like domain (or calcium-binding domain), which presented a typical structure of plant CDPKs. Further analysis of IiCPK2 genomic DNA revealed that it contained 7 exons, 6 introns and the length of most exons was highly conserved. Semi-quantitative RT-PCR revealed that the expression of IiCPK2 in root, stem and leaf were much higher in tetraploid sample than that in diploid progenitor. Further expression analysis revealed that gibberellin ($GA_3$), NaCl and cold treatments could up-regulate the IiCPK2 transcription. All our findings suggest that IiCPK2 might participate in the cold, high salinity and GA3 responsive pathways.
Ruilian Xiu,Jie Jia,Qing Zhang,Fengjiao Liu,Yaxin Jia,Yuanyuan Zhang,Beibei Song,Xiaodan Liu,Jingwei Chen,Dongyang Huang,Fan Zhang,Juanjuan Ma,Honglin Li,Xuan Zhang,Yunyun Geng 대한약리학회 2023 The Korean Journal of Physiology & Pharmacology Vol.27 No.6
Transmembrane protein TMEM16A, which encodes calcium-activated chloride channel has been implicated in tumorigenesis. Overexpression of TMEM16A is associated with poor prognosis and low overall survival in multiple cancers including lung adenocarcinoma, making it a promising biomarker and therapeutic target. In this study, three structure-related sesquiterpene lactones (mecheliolide, costunolide and dehydrocostus lactone) were extracted from the traditional Chinese medicine Aucklandiae Radix and identified as novel TMEM16A inhibitors with comparable inhibitory effects. Their effects on the proliferation and migration of lung adenocarcinoma cells were examined. Whole-cell patch clamp experiments showed that these sesquiterpene lactones potently inhibited recombinant TMEM16A currents in a concentration- dependent manner. The half-maximal concentration (IC50) values for three tested sesquiterpene lactones were 29.9 ± 1.1 μM, 19.7 ± 0.4 μM, and 24.5 ± 2.1 μM, while the maximal effect (Emax) values were 100.0% ± 2.8%, 85.8% ± 0.9%, and 88.3% ± 4.6%, respectively. These sesquiterpene lactones also significantly inhibited the endogenous TMEM16A currents and proliferation, and migration of LA795 lung cancer cells. These results demonstrate that mecheliolide, costunolide and dehydrocostus lactone are novel TMEM16A inhibitors and potential candidates for lung adenocarcinoma therapy.
Medical Monitoring Model of Internet of Things Based on the Adaptive Threshold Difference Algorithm
Beibei Dong,Jingjing Yang,Yanli Ma,Xiao Zhang 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.5
There are still problems such as low detection accuracy and poor noise immunity in the application of the standard threshold difference algorithm in the signal detection of electrocardiosignal (ECG), in this paper, a medical monitoring model based on the adaptive threshold difference is proposed. First we use a nonlinear filter to filter the P wave and T wave which are low frequency in ECG signal. Then complex wave QRS will be tested. Then the algorithm will be more accuracy through the detection of the R-R interval length and the adjustment of threshold. Finally, the ECG signal will be test with quadratic spline wavelet twice, and the error judgment will be known through adaptive threshold difference. In the simulation experiments, after judging error by wavelet transformation and making the standard threshold difference algorithm optimize adaptively, algorithm showed excellent detection accuracy with and without noise.
Cluster Head Selection Optimization of IOT Medical Data Transmission Ant Colony Algorithm
Beibei Dong,Benzhen Guo,Yanli Ma,Xiao Zhang 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.12
According to the standard ant colony algorithm in Internet of things (IOT) medical data transmission path selection, there are the problems of searching time is not long, easy to fall into partial optimization. This paper puts forward a kind of IOT medical data transmission model based on quantum pheromone updating and cluster heads choose optimization ant colony algorithm. First of all, using quantum bit probability amplitude encodes information of each path element, using quantum revolving doors and the route of the ants to update pheromone, then the ant search behavior is concentrated near the optimal solution, and the way of searching and restriction mechanism of avoiding precocious pheromone are combined, and finally optimizing the cluster heads of IOT medical data transmission model with the improved algorithm. The simulation experiments show that, through the pheromone update optimization of standard ant colony algorithm, and after the cluster heads optimization of IOT medical data transmission model, improved ant colony algorithm is more robust compared with the standard algorithm.
Generalization Threshold Optimization of Fuzzy Rough Set algorithm in Healthcare Data Classification
Beibei Dong,Yu Liu,Benzhen Guo,Xiao Zhang 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.3
There is ineffective classification problem in application of K-means clustering algorithm in massive data cluster analysis. This paper presents a K-means algorithm based on generalization threshold rough set optimization weight. Firstly, utilize attribute order described method, using the average distance calculation with Laplace method to optimize the generalization threshold of fuzzy rough set , then the Euclidean distance metric is used in the calculation of the similarity of K-means algorithm, introducing the variation coefficient into the cluster analysis, clustering the Euclidean distance weighted K-means algorithm totally based on data, finally, combine the rough set algorithm based on the generalization threshold optimization and K-means clustering algorithm, applied to medical and health data classification. The K-means algorithm based on generalization threshold rough set optimization weight presented by this paper has a better effect on medical and health data classification.
Research on Home Healthcare Management System Based on the Improved Internet of Things Architecture
Benzhen Guo,Beibei Dong,Xiao Zhang,Jingjing Yang,Zhihui Wang 보안공학연구지원센터 2015 International Journal of Smart Home Vol.9 No.9
This paper designs an improved internet of things architecture to redefine the internet of things architecture into the node domain, the network domain and the application domain so as to design and implement a home healthcare management system based on this improved internet of things architecture. In this way, all of the equipments characterized with Zigbee communication function in the blood pressure measuring node, the blood oxygen measuring node and the ECG measuring node can be connected to the internet through the Zigbee-Wifi gateway. Meanwhile data uploaded by the users can be stored and analyzed on the backend server of the internet of things so that the users can review their health data and control the node devices through the intelligent terminals such as cell phone etc. Taking the blood pressure measurement as an instance, the experiment has proved the feasibility and reliability of this system.
Direct Power Control without Current Sensors for Nine-Switch Inverters
Pan, Lei,Zhang, Junru,Wang, Kai,Wang, Beibei,Pang, Yi,Zhu, Lin The Korean Institute of Power Electronics 2018 JOURNAL OF POWER ELECTRONICS Vol.18 No.1
Recently, the nine-switch inverter has been proposed as a dual output inverter. To date, studies on the control strategies for NSIs have been mostly combined with their application. However, in this paper, a mathematical model and control strategy for nine-switch inverters has been proposed in view of the topology. A switching function model and equivalent circuit model of a nine-switch inverter have been built in ${\alpha}{\beta}$ coordinates. Then, a novel current observer with an improved integrator is proposed based on the switching function model, and a direct power control strategy is proposed. No current sensors are used in the proposed strategy, and only two voltage sensors are employed. The performance of the proposed control method is verified by simulation and experimental results.
Yuan Ke,Beibei Ding,Yang Fu,Miaomiao Zhang,Shensheng Xiao,Wenping Ding,Heng Yang,Qingyun Lv,Zhuo Zheng,Xuedong Wang 한국식품과학회 2021 Food Science and Biotechnology Vol.30 No.7
Effects of chitosan oligosaccharide (COS) andhyriopsis cumingii polysaccharide (HCP) on the quality ofwheat flour and corresponding extruded flour productswere investigated in this work. The results showed thatboth COS and HCP are conducive to the improvement ofdough quality. Moreover, compared to control groupsamples, the moisture content, expansion ratio and oilabsorption rate of the samples were increased and thehardness were decreased with the addition of COS. Thesephenomena indicate the quality of extruded flour productsbecame better in the presence of COS as well. However,HCP has little or no effect on the quality of extruded flourproducts may be due to its degradation under high temperatureand pressure extrusion. COS with higher stabilityexhibited better improvement effects on the quality ofextruded flour products and showed a promising prospectfor application in extruded food industry.
A Motivation Filter Scheme for Behavior Sequence Learning in Virtual Environment
Wei Song,Beibei Zhang,Kyungeun Cho,Kyhyun Um 한국멀티미디어학회 2009 한국멀티미디어학회 국제학술대회 Vol.2009 No.-
This paper proposes a motivation filter scheme for behavior sequence learning system which does not require predefined probability of the states' transition. When interacting with unknown environments, a virtual agent needs to learn how to generate a behavior sequence to achieve a goal and determine the transition probability based on the current state and the action taken. In a sequence learning process, the sensed states are grouped by a set of proposed motivation filters in order to reduce the learning computation of the large state space. The proposed motivation filters work motivated by the change in the agent's internal variables. We simulate a virtual environment to elucidate the process of the system.