Ginsenoside Rb1 and compound K improve insulin signaling and inhibit ER stress-associated NLRP3 inflammasome activation in adipose tissue

Chen, Weijie,Wang, Junlian,Luo, Yong,Wang, Tao,Li, Xiaochun,Li, Aiyun,Li, Jia,Liu, Kang,Liu, Baolin The Korean Society of Ginseng 2016 Journal of Ginseng Research Vol.40 No.4

Background: This study was designed to investigate whether ginsenoside Rb1 (Rb1) and compound K (CK) ameliorated insulin resistance by suppressing endoplasmic reticulum (ER) stress-induced inflammation in adipose tissue. Methods: To induce ER stress, epididymal adipose tissue from mice or differentiated 3T3 adipocytes were exposed to high glucose. The effects of Rb1 and CK on reactive oxygen species production, ER stress, TXNIP/NLRP3 inflammasome activation, inflammation, insulin signaling activation, and glucose uptake were detected by western blot, emzyme-linked immunosorbent assay, or fluorometry. Results: Rb1 and CK suppressed ER stress by dephosphorylation of $IRE1{\alpha}$ and PERK, thereby reducing TXNIP-associated NLRP3 inflammasome activation in adipose tissue. As a result, Rb1 and CK inhibited IL-$1{\beta}$ maturation and downstream inflammatory factor IL-6 secretion. Inflammatory molecules induced insulin resistance by upregulating phosphorylation of insulin receptor substrate-1 at serine residues and impairing insulin PI3K/Akt signaling, leading to decreased glucose uptake by adipocytes. Rb1 and CK reversed these changes by inhibiting ER stress-induced inflammation and ameliorating insulin resistance, thereby improving the insulin IRS-1/PI3K/Akt-signaling pathway in adipose tissue. Conclusion: Rb1 and CK inhibited inflammation and improved insulin signaling in adipose tissue by suppressing ER stress-associated NLRP3 inflammation activation. These findings offered novel insight into the mechanism by which Rb1 and CK ameliorate insulin resistance in adipose tissue.

Cutting performance and wear mechanisms of TiAlN PVD-coated cemented carbide tool in high speed turning of Ti-5Al-2Sn-2Zr-4Mo-4Cr alloy

Baolin Wang,Anhai Li,Gaihua Liu 대한기계학회 2020 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.34 No.7

The high-speed finish turning tests of Ti-17 titanium alloy (Ti-5Al-2Sn-2Zr-4Mo-4Cr) were carried out by using PVD cemented carbide tools with TiAlN coating. The machinability behaviors in terms of cutting forces, cutting temperatures, surface roughness, and tool service life were measured and evaluated under different machining parameter conditions, and the empirical prediction model of these variables were established depending on the cutting parameters. Incorporating the measured results of scanning electron microscopy (SEM) as well as energy dispersive spectroscopy (EDS), the initial tool wear patterns and the eventual wear patterns when the tool wear states meet the failure criteria were comparably investigated and analyzed. It was found that during the initial wear stage, the sticking wear zone and the sliding wear zone can be distinguished on the tool wear interface. The main wear patterns of are peeling off of coating material, crater wear of rake face, edge breakage and edge wear of tool tip after reaching the tool failure rejection criterion. The cutting tool wear mechanisms were systematically studied, and the results show that the wear mechanisms of a TiAlN PVD-coated carbide cutting tool in turning Ti-17 titanium alloy were dominated by the interaction wear effect among the adhesion, oxidation and diffusion between cemented carbide substrate and workpiece material.

ZnFe2O4/Graphite Composite with High Performance as Anode Material for Lithium-Ion Batteries

Baolin Yao,Ziyue Wang,Chenxi Ding,Min Feng,Zhen Li,Yanqiu Huang 대한금속·재료학회 2023 ELECTRONIC MATERIALS LETTERS Vol.19 No.1

ZnFe 2 O 4 /graphite composite was synthesized by a thermal decomposition method using expanded graphite as matrix. TheZnFe 2 O 4 nanoparticles with the size of 20–30 nm were embedded into the interlayers of graphite. The porous structureformed by the graphite sheets can not only alleviate the adverse eff ects caused by the volume change of the ZnFe 2 O 4 duringcycling, but also improve the lithium storage performance. The specifi c capacity of 1450 mAh g − 1 is achieved after150 charge/discharge cycles at 0.1 A g − 1 . Moreover, the composite still delivers the specifi c capacity of 229 mAh g − 1 atthe ultrahigh current density of 10 A g − 1 after 1800 cycles, showing outstanding electrochemical performance and excellentcycling stability. The composite has great potential for use in the high-power lithium-ion batteries.

A QoS Multicast Routing Optimization Algorithm Based on Genetic Algorithm

Sun Baolin,Li Layuan The Korea Institute of Information and Commucation 2006 Journal of communications and networks Vol.8 No.1

Most of the multimedia applications require strict quality of service (QoS) guarantee during the communication between a single source and multiple destinations. This gives rise to the need for an efficient QoS multicast routing strategy. Determination of such QoS-based optimal multicast routes basically leads to a multi-objective optimization problem, which is computationally intractable in polynomial time due to the uncertainty of resources in Internet. This paper describes a network model for researching the routing problem and proposes a new multicast tree selection algorithm based on genetic algorithms to simultaneously optimize multiple QoS parameters. The paper mainly presents a QoS multicast routing algorithm based on genetic algorithm (QMRGA). The QMRGA can also optimize the network resources such as bandwidth and delay, and can converge to the optimal or near-optimal solution within few iterations, even for the networks environment with uncertain parameters. The incremental rate of computational cost can close to polynomial and is less than exponential rate. The performance measures of the QMRGA are evaluated using simulations. The simulation results show that this approach has fast convergence speed and high reliability. It can meet the real-time requirement in multimedia communication networks.

A Novel SINS/CNS Integrated Navigation Algorithm used in a Ballistic Missile

Lihua Yang,Baolin Li,Lei Ge 보안공학연구지원센터 2015 International Journal of Security and Its Applicat Vol.9 No.9

The position and velocity errors are divergent of traditional navigation algorithms used in ballistic missile for it cannot estimate the bias of accelerometer precisely. To solve this problem, a novel SINS/CNS integrated navigation algorithm is proposed in this paper, which adds high angle error, azimuth angle error and height error on the basis of the traditional navigation method. As these three values are related to the position of missile, the proposed method can constrain the divergence of navigation errors. Meanwhile, a system model for ballistic missile is deduced. To verify the navigation precision of the proposed algorithm, the observable analysis and simulation experiments are performed. And the results show that the system state of proposed method is observable completely, and the divergence of navigation error can be restrained thoroughly.

The Combination Forecasting Model of Auto Sales Based on Seasonal Index and RBF Neural Network

Lihua Yang,Baolin Li 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.1

To effectively predict auto sales and improve the competitiveness of automotive enterprise, the characteristics of actual auto sales were analyzed, owing to the seasonal fluctuations and the nonlinearity of monthly sales, the combination forecasting model based on seasonal Index and RBF neural network was proposed. The weights of the two single models were computed using mean absolute percentage error and the sum of square error respectively, the result shows that mean absolute percentage error is more effective. Finally, the prediction accuracy of different models was compared based on the criteria of MAPE and RMSE, and the effectiveness of the method was proved, the proposed model can take advantage of the strengths of the two single models, the results indicate that the combination forecasting model suitable for auto sales has high prediction accuracy, which can provide a certain reference to auto sales forecasting.

Phage transcription activator RinA regulates Staphylococcus aureus virulence by governing sarA expression

Jiang Ming,Li Yilin,Sun Baolin,Xu Shiwen,Pan Ting,Li Yujie 한국유전학회 2023 Genes & Genomics Vol.45 No.2

Background Staphylococcus aureus is a major human pathogen, that can lead to various community- and hospital-acquired infections. RinA is a transcription activator of S. aureus phage φ 11 involved in phage packaging and virulence gene transfer. However, little is known about the molecular mechanism of RinA in the regulation of virulence. Objective We aimed to explore a novel contribution of RinA in the regulation of virulence and provide a new drug target in the treatment of S. aureus infections. Methods The specific functions of RinA in S. aureus were analyzed by the methods of growth curve, real-time quantitative PCR (RT-qPCR), subcellular localization, electrophoretic mobility shift assay (EMSA), infection model of Galleria mellonella larvae and the mouse subcutaneous abscess model. Results In this study, we demonstrated that RinA is a protein evenly distributed in the cytoplasm of S. aureus, and its deletion could cause the growth defects. RT-qPCR and EMSA determined that rinA could negatively regulate the expression of sarA by directly binding to its promoter, and vice versa. The Galleria mellonella larvae infection and mouse subcutaneous abscess models revealed that the rinA mutant strain exhibited obvious virulence defects. When sarA is knocked out, the virulence of S.aureus had no significantly changes whether rinA is knocked out or not. Conclusion Our fndings demonstrated that phage transcription activator RinA regulates S. aureus virulence by governing sarA expression.

A Novel Combination Forecasting Algorithm Based on Time Series

Lihua Yang,Baolin Li,Xuetao Li,Lvjiang Yin 보안공학연구지원센터 2015 International Journal of Database Theory and Appli Vol.8 No.2

To effectively predict cigarette sales and improve the competitiveness of tobacco business enterprises, the characteristics of actual cigarette sales were detailed analyzed. Due to the long-term growth trends, seasonal fluctuations and the nonlinearity of monthly sales, we established three single forecasting models, which are Exponential Smoothing (ES), Seasonal Decomposition (SD) and Radial Basis Function (RBF) neural network. After obtaining the predicted value of three single models, the combination forecasting model was proposed. The weights of the three single models were computed using Mean Absolute Error and the mean relative error respectively, the result shows that relative error is more effective. A dynamic weight combination forecasting method based on RBF is proposed and compared with fixed weight method. Finally, the prediction accuracy of different models was compared based on the criteria of MAPE and RMSE, and the effectiveness of the combination method was proved, the proposed model can take advantage of the strengths of the three single models, the results indicate that the combination forecasting model suitable for cigarette sales has higher prediction accuracy. In some cases, the prediction accuracy of the fixed weight combination model is better than the dynamic weight combination model. The results can provide a certain reference to cigarette sales forecasting.

A Multi-Criteria Decision-Making Method Using Power Aggregation Operators for Single-valued Neutrosophic Sets

Lihua Yang,Baolin Li 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.2

As a generalization of intuitionistic fuzzy sets, neutrosophic sets (NSs) can be better handle the incomplete, indeterminate and inconsistent information, which have attracted the widespread concerns for researchers. In this paper, some new aggregation operators are proposed under single-valued neutrosophic environment. Firstly, the definition and operational laws of single-valued neutrosophic numbers (SVNNs) are introduced. Then, the single-valued neutrosophic power average (SVNPA) operator and the single- valued neutrosophic power weighted average (SVNPWA) operator are developed, and some properties of SVNPWA operator are also analyzed. Furthermore, a method for solving multi-criteria decision-making (MCDM) problems is explored based on the power aggregation operators and cosine similarity measures. Finally, an illustrative example is shown to verify the effectiveness and practicality of the proposed method.

Application of advanced spectral-ratio radon background correction in the UAV-borne gamma-ray spectrometry

Xia Jigen,Song Baolin,Gu Yi,Li Zhiqiang,Xu Jie,Ge Liangquan,Zhang Qingxian,Zeng Guoqiang,Liu Qiushi,Yang Xiaofeng 한국원자력학회 2023 Nuclear Engineering and Technology Vol.55 No.8

The influence of the atmospheric radon background on the airborne gamma spectrum can seriously affect researchers’ judgement of ground radiation information. However, due to load and endurance, unmanned aerial vehicle (UAV)-borne gamma-ray spectrometry is difficulty installing upward-looking detectors to monitor atmospheric radon background. In this paper, an advanced spectral-ratio method was used to correct the atmospheric radon background for a UAV-borne gamma-ray spectrometry in Inner Mongolia, China. By correcting atmospheric radon background, the ratio of the average count rate of U window in the anomalous radon zone (S5) to that in other survey zone decreased from 1.91 to 1.03, and the average uranium content in S5 decreased from 4.65 mg/kg to 3.37 mg/kg. The results show that the advanced spectral-ratio method efficiently eliminated the influence of the atmospheric radon background on the UAV-borne gamma-ray spectrometry to accurately obtain ground radiation information in uranium exploration. It can also be used for uranium tailings monitoring, and environmental radiation background surveys