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Huang Jun-Hao,Gao Hui-Wen,Gao Dong-Dong,Yang Wei-Yue,Zhao Meng-Ke,Shen Bing,Hu Min 대한천식알레르기학회 2023 Allergy, Asthma & Immunology Research Vol.15 No.3
Purpose: Increased evidence has shown that aerobic exercise reduces airway hyperresponsiveness in asthmatic individuals. However, the underlying mechanisms of action remain elusive. This study aimed to investigate the effect of exercise on airway smooth muscle (ASM) contractile function in asthmatic rats, and uncover the possible involvement of interleukin 4 (IL-4) and the store-operated Ca2+ entry (SOCE) pathway. Methods: In this study, chicken ovalbumin was used to induce asthma in male Sprague-Dawley rats. The exercise group received moderate-intensity aerobic exercise training for 4 weeks. IL-4 concentrations in bronchoalveolar lavage fluid (BALF) samples were evaluated by enzyme linked immunosorbent assay. The contractile function of the ASM was investigated using tracheal ring tension experiments and intracellular Ca2+ imaging techniques. Western blot analysis was used to evaluate expression levels of calcium-release activated calcium (CRAC) channel protein (Orai) and stromal interaction molecule 1 (STIM1) in ASM. Results: Our data showed that the carbachol-stimulated, SOCE-mediated contraction of rat ASM was significantly increased in asthmatic rats, which could be abolished by exercise. Pharmacological studies revealed that GSK5498A and BTP-2, selective blockers of CRAC channels significantly inhibited SOCE-induced ASM contraction. In addition, exercise inhibited the up-regulation of IL-4 in BALF as well as STIM1 and Orai expression in the ASM of asthmatic rats. In line with these observations, we demonstrated that pretreatment of the ASM with IL-4 up-regulated the expression level of STIM1, Orai1 and Orai2, thereby promoting SOCE-mediated ASM contraction. Conclusions: The data in this study reveal that aerobic exercise may improve the ASM contractile function in asthmatic rats by inhibiting IL-4 secretion and by down-regulating the expression of STIM1, Orai1 and Orai2, thus decreasing excessive SOCE-mediated ASM contraction in asthmatic rats.
Gao Huang,Weimin Zhang,Fei Meng,Zhangguo Yu,Xuechao Chen,Marco Ceccarelli,Qiang Huang 한국정밀공학회 2018 International Journal of Precision Engineering and Vol.19 No.7
In this paper, a master-slave control system is proposed and applied in an intention-actuated exoskeletal robot to assist user locomotion and lower extremity rehabilitation simultaneously. In particular, to increase users’ sense of participation, the motion of the exoskeleton and the wheelchair, which is denoted as slave motion in this study, is actuated by the user’s intention, which is denoted as master motion and thus makes patients feel that they are moving the wheelchair. This master-slave motion control system can help to eliminate patients’ fear of medical apparatus and instruments. The bicycling motion actuated by one motor is implemented to realize the rehabilitation motion exercise. Experimental results validate a position-force control strategy for the exoskeleton motors, and show that the proposed method can help users to move around and to exercise their legs simultaneously and effectively.
Improved Convolutional Neural Network for Laser Welding Defect Prediction
Weiwei Huang,Xiangdong Gao,Yuhui Huang,Yanxi Zhang 한국정밀공학회 2023 International Journal of Precision Engineering and Vol.24 No.1
In order to predict the laser welding defects, a convolutional neural network prediction model is established. The keyhole image and plume image collected by a high-speed camera are processed to obtain visual information such as keyhole area and plume area. The rolling mean and standard deviation methods are used to calculate the fluctuation degree indicators of the visual information and the optical radiation information obtained by the photoelectric sensor. Finally, three improved one-dimensional convolutional neural network prediction models with a learning rate dynamic adjustment mechanism are established to predict welding defects. Experimental results indicate that the improved one-dimensional convolutional neural network prediction model can avoid premature convergence four times to achieve the best performance. The fluctuation degree indicators of sensor features can distinguish the welding state more easily than the sensor features. The reliability test of the new weld is carried out. The prediction accuracy of fusion detection model of sensor features and fluctuation degree indicators is 99.21%. The improved model can accurately predict laser welding defects.
Lu Gao,Xuehua Pu,Yujing Huang,Jing Huang 한국유전학회 2019 Genes & Genomics Vol.41 No.6
Objectives Neuropathic pain (NP) is one of the main challenges towards NP syndrome treatment. miR-340-5p exhibit different expression levels in NP models. Its effects on NP remained unclear. The objective of this study was to explore the potential regulation mechanisms of miR-340-5p in NP. Methods Rat model of chronic constriction injury (CCI) was established to induce NP in vivo. NP levels were assessed using mechanical withdrawal threshold (MWT). The inflammation response in CCI rats were determined by HE staining and ELISA assay. The target genes of miR-340-5p were verified by luciferase report assays. Results In CCI rats, level of miR-340-5p was down-regulated both in spinal cord tissues and isolated microglial cells. Paw withdrawal threshold (PWT) and paw withdrawal latency (PWL) were decreased in CCI rats, which were restored upon miR-340-5p overexpression. miR-340-5p overexpression also decreased inflammation as well as expression levels of COX- 2, IL-1β, TNF-α and IL-6 in CCI rats. Luciferase report assays revealed Rap1A was a target gene of miR-340-5p in the experimental model. Elevated miR-340-5p decreased Rap1A expression level in vitro and in vivo. Overexpression of Rap1A protein restored expression levels of COX-2, IL-1β, TNF-α and IL-6, reduced the PWT and PWL and increased inflammation response in CCI rats. Conclusion miR-340-5p alleviated CCI-induced NP by targeting Rap1A. miR-340-5p and Rap1A may be the potential treatment targets for NP therapeutics.
( Qianhui Huang ),( Xing Han ),( Irum Mukhtar ),( Lingling Gao ),( Rongmei Huang ),( Liping Fu ),( Junjie Yan ),( Yongxin Tao ),( Bingzhi Chen ),( Baogui Xie ) 한국미생물생명공학회(구 한국산업미생물학회) 2018 Journal of microbiology and biotechnology Vol.28 No.4
Expansins are cell wall proteins that mediate cell wall loosening and promote specific tissue and organ morphogenesis in plants and in some microorganisms. Unlike plant expansins, the biological functions of fungal expansin-like proteins have rarely been discussed. In the present study, an expansin-like protein-encoding fvexpl1 gene, was identified from Flammulina velutipes by using local BLAST. It consisted of five exons with a total length of 822 bp. The deduced protein FVEXPL1 contained 274 amino acids with a predicted molecular mass and isoelectric point of 28,589 Da and pH 4.93, respectively. The first 19 amino acids from the N terminal are the signal peptide. Phylogenetic analysis and multiple protein alignment indicated FVEXPL1 was an expansin-like protein. The expression level of fvexpl1 gene in the stipe was significantly higher than that in the mycelia, primordia, and cap. However, the expression level of fvexpl1 gene was significantly higher in the fast elongation region of the stipe as compared with the slow elongation region. Expression analysis indicated that fvexpl1 gene might have an auxiliary role in the stipe morphogenesis of F. velutipes.
Effect of Solution-treated on Electrochemical Properties of AZ91 Magnesium Alloy Anode
Zhiquan, Huang,Yanjie, Pei,Renyao, Huang,Xiangyu, Gao,Jinchao, Zou,Lianyun, Jiang The Korean Electrochemical Society 2022 Journal of electrochemical science and technology Vol.13 No.4
The effect of solution-treated on the self-corrosion performance and discharge performance of AZ91 magnesium alloy as anode material was analyzed by microscopic characterization, immersion tests, electrochemical measurements, and discharge performance tests. The study shows that the β-phase in the AZ91 magnesium alloy gradually dissolved in the matrix with the increase of the solution temperature, and the electrochemical activity of the magnesium alloy anode was significantly improved. Through the comparison of three different solution-treated processes, it is found that the AZ91 magnesium alloy has the most vigorous activity and better discharge performance after solution-treated of 415℃+12 h. In addition, the proportion and distribution of β-phase AZ91 magnesium alloy have a direct impact on its discharge performance as an anode material.
Analysis of the Difference of Spray Angles based on Various Definitions and Calculation Criterions
( Yuan Gao ),( Li Guang Li ),( Ya Gao ),( Wei Di Huang ),( Jun Deng ),( Tao Li Gu ) 한국액체미립화학회 2010 한국액체미립화학회 학술강연회 논문집 Vol.2010 No.-
Spray angle is one of the key spray macro parameters which reflect fuel atomization characteristics and fuel and air entrainment quality directly; it then could affect the combustion efficiency and emission formation in cylinder. As the spray characteristics are widely investigated, there are already some kinds of definition and calculation methods for spray angle. Although all these definitions reflect the spray angle trends correspondingly, the difference between these definitions and calculation results was seldom studied. This paper focuses on the comparison and analysis the spray angle results based on the different calculation criterions, and the trend of these key points versus time at various calculation criterions which determine spray angle.
Gao, Dong,Huang, Miaohua The Korean Institute of Power Electronics 2017 JOURNAL OF POWER ELECTRONICS Vol.17 No.5
The estimation of the remaining useful life (RUL) of lithium-ion (Li-ion) batteries is important for intelligent battery management system (BMS). Data mining technology is becoming increasingly mature, and the RUL estimation of Li-ion batteries based on data-driven prognostics is more accurate with the arrival of the era of big data. However, the support vector machine (SVM), which is applied to predict the RUL of Li-ion batteries, uses the traditional single-radial basis kernel function. This type of classifier has weak generalization ability, and it easily shows the problem of data migration, which results in inaccurate prediction of the RUL of Li-ion batteries. In this study, a novel multi-kernel SVM (MSVM) based on polynomial kernel and radial basis kernel function is proposed. Moreover, the particle swarm optimization algorithm is used to search the kernel parameters, penalty factor, and weight coefficient of the MSVM model. Finally, this paper utilizes the NASA battery dataset to form the observed data sequence for regression prediction. Results show that the improved algorithm not only has better prediction accuracy and stronger generalization ability but also decreases training time and computational complexity.