A comparative study on antioxidant, anti-inflammatory, antimicrobial activities and chemical composition of Pyrus ussuriensis cultivars from northeastern China

Xiaoqian Wang,Chunyan Liu,Qiang Wang,Chang Liu,Huili Sun,Maojun Zhang,Deguo Lyu,Guodong Du 한국원예학회 2021 Horticulture, Environment, and Biotechnology Vol.62 No.3

Pyrus ussuriensis is the most important cultivated pear in the northeastern, cold areas of China. However, studies on thebiological activity of Pyrus ussuriensis fruit are rare in the public domain. The present study compared antioxidant, antiinflammatory, and antimicrobial activities and chemical composition in tissues from the peel and fl esh of nine Pyrus ussuriensiscultivars. The chemical composition diff ered among cultivars and tissue sources. Phenolics were predominant in peelsamples, whereas sugars were predominant in fl esh samples. Twenty-one phenolic compounds were identifi ed and quantifi ed,including hydroxycinnamic acids, hydroquinones, fl avanols, fl avonols, fl avones, and anthocyanins (only in peel samples). The total phenolic content ranged between 363.0 and 1734.0 mg kg − 1 FW in the peel and from 28.5 to 182.3 mg kg − 1 FWin the fl esh. In addition, cultivars with high total phenolic and fl avonoid contents had signifi cantly higher antioxidant activities. The in vitro anti-infl ammatory study, performed using an egg albumin denaturation assay, demonstrated that both peeland fl esh samples had strong activity, which was comparable with that of the standard anti-infl ammatory drug diclofenacsodium. The antimicrobial results showed that ‘Jianba’ and ‘Balixiang’ cultivars exhibited strong activity against bacteriastrains in the peel and fl esh, respectively. The present study provided information for selecting promising Pyrus ussuriensiscultivars with improved health benefi ts.

Dietary Saponins of Sea Cucumber Ameliorate Obesity, Hepatic Steatosis, and Glucose Intolerance in High-Fat Diet–Fed Mice

Xiaoqian Hu,Zhaojie Li,Yong Xue,Jingfeng Wang,Yuming Wang 한국식품영양과학회 2012 Journal of medicinal food Vol.15 No.10

Much attention has been focused on food components that may be beneficial in preventing lifestyle-related diseases. In this study, we investigated the effects of saponins of sea cucumber (SSC) on high-fat diet–induced obesity, insulin resistance, and fatty liver in mice. C57/BL6 mice were fed a high-fat diet, containing 0.03% SSC, or 0.1% SSC for 8 weeks. Both doses of SSC exhibited a weight-loss effect and significantly decreased adipose tissue weight, in both visceral and subcutaneous depots. Furthermore, 0.1% SSC treatment dramatically decreased the hepatic triglyceride and total cholesterol accumulation. Mice administrated with 0.1% SSC had significantly decreased serum glucose and insulin levels, lower homeostatic model assessment for insulin resistance index, and area under the blood glucose curve, suggesting that insulin sensitivity is enhanced by dietary SSC. Dietary SSC also prevented adipokine imbalance, by increasing adiponectin production and decreasing tumor necrosis factor alpha level caused by high-fat diet. Overall, these data demonstrate that SSC could improve certain metabolic parameters associated with obesity.

Purification and Identification of a Natural Antioxidant Protein from Fertilized Eggs

Shaohua Yang,Lulu Wang,Ying Wang,Xiaoqian Ou,Zhaoyuan Shi,Chongchong Lu,Wei Wang,Guoqing Liu 한국축산식품학회 2017 한국축산식품학회지 Vol.37 No.5

Fertilized hen eggs are rich in a variety of bioactive ingredients. In this study, we aimed to obtain an antioxidant protein from fertilized eggs and the radical scavenging abilities on 1, 1- diphenyl-2-picrylhydrazyl (DPPH), hydroxyl radical (•OH), superoxide anion (O2-•) were used to evaluate the antioxidant activity of the purified protein. During 20 d of incubation, the radical scavenging ability of protein extracted from fertilized eggs exhibited significantly differences and the protein on day 16 showed higher antioxidant capacity. Based on this, the antioxidant protein of the samples on day 16 were isolated for the follow-up study. With a molecular weight 43.22 kDa, the antioxidant protein was purified by Diethylaminoethyl cellulose -52 (DEAE-52) column and Sephadex G-100. The LC-MS analysis showed that the purified protein molecular weight was 43.22 kDa, named D2-S. The sequence of amino acids was highly similar to ovalbumin and the coverage reached to 84%. The purified protein showed a radical scavenging rate of 52.34±3.27% on DPPH and 63.49±0.25% on •OH, respectively. Furthermore, the C-terminal amino acid sequence was NAVLFFGRCVSP, which was consistent with the sequence of ovabumin. These results here indicated that purified protein may be a potential resource as a natural antioxidant.

Verification of SARAX code system in the reactor core transient calculation based on the simplifi ed EBRII benchmark

Xiaoqian Jia,Youqi Zheng,Xianna Du,Yongping Wang,Jianda Chen 한국원자력학회 2022 Nuclear Engineering and Technology Vol.54 No.5

This paper shows the verification work of SARAX code system in the reactor core transient calculationbased on the simplified EBR-II Benchmark. The SARAX code system is an analysis package developed byXi'an Jiaotong University and aims at the advanced reactor R&D. In this work, a neutron-photon coupledpower calculation model and a spatial-dependent reactivity feedback model were introduced. To verifythe models used in SARAX, the EBR-II SHRT-45R test was simplified to an ULOF transient with an inputflowrate change curve by fitting from reference. With the neutron-photon coupled power calculationmodel, SARAX gave close results in both power fraction and peak power prediction to the referenceresults. The location of the hottest assembly from SARAX and reference are the same and the relativepower deviation of the hottest assembly is 2.6%. As for transient analysis, compared with experimentalresults and other calculated results, SARAX presents coincident results both in trend and absolute value. The minimum value of core net reactivity during the transient agreed well with the reported results,which ranged from 0.3$ to 0.35$. The results verify the models in SARAX, which are correct and ableto simulate the in-core transient with reliable accuracy.

HEALER: homomorphic computation of ExAct Logistic rEgRession for secure rare disease variants analysis in GWAS

Wang, Shuang,Zhang, Yuchen,Dai, Wenrui,Lauter, Kristin,Kim, Miran,Tang, Yuzhe,Xiong, Hongkai,Jiang, Xiaoqian Oxford University Press 2016 Bioinformatics Vol.32 No.2

<P>Motivation: Genome-wide association studies (GWAS) have been widely used in discovering the association between genotypes and phenotypes. Human genome data contain valuable but highly sensitive information. Unprotected disclosure of such information might put individual's privacy at risk. It is important to protect human genome data. Exact logistic regression is a bias-reduction method based on a penalized likelihood to discover rare variants that are associated with disease susceptibility. We propose the HEALER framework to facilitate secure rare variants analysis with a small sample size. Results: We target at the algorithm design aiming at reducing the computational and storage costs to learn a homomorphic exact logistic regression model (i.e. evaluate P-values of coefficients), where the circuit depth is proportional to the logarithmic scale of data size. We evaluate the algorithm performance using rare Kawasaki Disease datasets.</P>

Solution to Mixed H2/H∞ Control for Discrete-time Systems with (x,u,v)-dependent Noise

Xiaoqian Li,Wei Wang,Juanjuan Xu,Huanshui Zhang 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.2

In this paper, the stochastic H2=H∞ control problem for linear discrete-time systems with (x;u;v)-dependent noise is studied. By applying the leader-follower stochastic game approach, the disturbance is treatedas the follower and the control input is treated as the leader, respectively. Necessary and sufficient conditions forthe mixed control problem are presented which guarantee the existence and uniqueness of the optimal solution. Byapplying the stochastic maximum principle, the follower first solves a stochastic linear quadratic optimal controlproblem which is given in the form of H∞-norm with the aid of stochastic Riccati equations. Then the leader solves astochastic linear quadratic problem with the aid of forward and backward equations. The main technique is to introducetwo new co-states to capture the future information, the encountered difficulty is to establish a homogeneousrelationship between the new co-states.

Adaptive Attention Annotation Model: Optimizing the Prediction Path through Dependency Fusion

( Fangxin Wang ),( Jie Liu ),( Shuwu Zhang ),( Guixuan Zhang ),( Yang Zheng ),( Xiaoqian Li ),( Wei Liang ),( Yuejun Li ) 한국인터넷정보학회 2019 KSII Transactions on Internet and Information Syst Vol.13 No.9

Previous methods build image annotation model by leveraging three basic dependencies: relations between image and label (image/label), between images (image/image) and between labels (label/label). Even though plenty of researches show that multiple dependencies can work jointly to improve annotation performance, different dependencies actually do not "work jointly" in their diagram, whose performance is largely depending on the result predicted by image/label section. To address this problem, we propose the adaptive attention annotation model (AAAM) to associate these dependencies with the prediction path, which is composed of a series of labels (tags) in the order they are detected. In particular, we optimize the prediction path by detecting the relevant labels from the easy-to-detect to the hard-to-detect, which are found using Binary Cross-Entropy (BCE) and Triplet Margin (TM) losses, respectively. Besides, in order to capture the inforamtion of each label, instead of explicitly extracting regional featutres, we propose the self-attention machanism to implicitly enhance the relevant region and restrain those irrelevant. To validate the effective of the model, we conduct experiments on three well-known public datasets, COCO 2014, IAPR TC-12 and NUSWIDE, and achieve better performance than the state-of-the-art methods.

State-Space Model Predictive Control Method for Core Power Control in Pressurized Water Reactor Nuclear Power Stations

Guoxu Wang,Jie Wu,Bifan Zeng,Zhibin Xu,Wanqiang Wu,Xiaoqian Ma 한국원자력학회 2017 Nuclear Engineering and Technology Vol.49 No.1

A well-performed core power control to track load changes is crucial in pressurized waterreactor (PWR) nuclear power stations. It is challenging to keep the core power stable at thedesired value within acceptable error bands for the safety demands of the PWR due to thesensitivity of nuclear reactors. In this paper, a state-space model predictive control (MPC)method was applied to the control of the core power. The model for core power control wasbased on mathematical models of the reactor core, the MPC model, and quadratic programming(QP). The mathematical models of the reactor core were based on neutron dynamicmodels, thermal hydraulic models, and reactivity models. The MPC model waspresented in state-space model form, and QP was introduced for optimization solutionunder system constraints. Simulations of the proposed state-space MPC control system inPWR were designed for control performance analysis, and the simulation results manifestthe effectiveness and the good performance of the proposed control method for core powercontrol.

Hepatocellular carcinoma prediction model performance decreases with long-term antiviral therapy in chronic hepatitis B patients

Xiaoning Wu,Xiaoqian Xu,Jialing Zhou,Yameng Sun,Huiguo Ding,Wen Xie,Guofeng Chen,Anlin Ma,Hongxin Piao,Bingqiong Wang,Shuyan Chen,Tongtong Meng,Xiaojuan Ou,Hwai-I Yang,Jidong Jia,Yuanyuan Kong,Hong Yo 대한간학회 2023 Clinical and Molecular Hepatology(대한간학회지) Vol.29 No.3

Background/Aims: Existing hepatocellular carcinoma (HCC) prediction models are derived mainly from pretreatment or early on-treatment parameters. We reassessed the dynamic changes in the performance of 17 HCC models in patients with chronic hepatitis B (CHB) during long-term antiviral therapy (AVT). Methods: Among 987 CHB patients administered long-term entecavir therapy, 660 patients had 8 years of follow-up data. Model scores were calculated using on-treatment values at 2.5, 3, 3.5, 4, 4.5, and 5 years of AVT to predict threeyear HCC occurrence. Model performance was assessed with the area under the receiver operating curve (AUROC). The original model cutoffs to distinguish different levels of HCC risk were evaluated by the log-rank test. Results: The AUROCs of the 17 HCC models varied from 0.51 to 0.78 when using on-treatment scores from years 2.5 to 5. Models with a cirrhosis variable showed numerically higher AUROCs (pooled at 0.65–0.73 for treated, untreated, or mixed treatment models) than models without (treated or mixed models: 0.61–0.68; untreated models: 0.51–0.59). Stratification into low, intermediate, and high-risk levels using the original cutoff values could no longer reflect the true HCC incidence using scores after 3.5 years of AVT for models without cirrhosis and after 4 years of AVT for models with cirrhosis. Conclusions: The performance of existing HCC prediction models, especially models without the cirrhosis variable, decreased in CHB patients on long-term AVT. The optimization of existing models or the development of novel models for better HCC prediction during long-term AVT is warranted.

Improved Four-channel PBTDPA Control Strategy Using Force Feedback Bilateral Teleoperation System

Xin Gong,Lixiao Wang,Yuanyuan Mou,Haili Wang,Xiaoqian Wei,Wenfeng Zheng,Lirong Yin 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.3

Bilateral teleoperation robots with force feedback enable humans to accomplish these tasks without exposing them to these hazardous environments. Its stability and transparency describe the performance of bilateral teleoperation systems with force feedback. Bilateral teleoperation with force feedback enables humans to combine tactics with optesthesia. However, the force feedback may lead to bilateral teleoperation instability if the communication channels’ time delay exists. The instability of bilateral teleoperation with force feedback, which is brought in by the time delay, has become one of the complicated problems researchers need to solve. Transparency is one of the leading design objectives of the teleoperation system. There are two evaluation criteria for transparency: the accuracy of the position followed by the master mechanical arm and the accuracy of the feedback received by the slave arm from the master arm. The main content of this paper is as follows: 1) This paper researches and summarizes the control structures and control algorithms of several well-developed force-feedback bilateral teleoperation systems and decides to improve the PBTDPA algorithm, which aligns with practical application requirements. 2) The fourchannel structure makes the transparency of force-feedback bilateral teleoperation systems perfect in theory. This paper uses the four-channel structure combined with the PBTDPA algorithm to improve the transparency of the approach. 3) Moreover, the delay predictor is used to improve the four-channel power-based time domain passivity approach (PBTDPA) control strategy. The delay differential predictor is added to the communication channel. The delay change rate differential predictor can estimate the communication channel’s delay change rate instead of the maximum delay change rate to improve transparency. The simulation experiment of the improved control strategy was carried out. The results show the excellent performance of our design.