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| 1 | Erianin,a novel dibenzyl compound in Dendrobium extract,inhibits lung cancer cell growth and migration via calcium/calmodulin-dependent ferroptosis显示文摘Ferroptosis,a novel form of programmed cell death,is characterized by iron-dependent lipid peroxidation and has been shown to be involved in multiple diseases,including cancer.Stimulating ferroptosis in cancer cells may be a potential strategy for cancer therapy.Therefore,ferroptosis-inducing drugs are attracting more attention for cancer treatment.Here,we showed that erianin,a natural product isolated from Dendrobium chrysotoxum Lindl,exerted its anticancer activity by inducing cell death and inhibiting cell migration in lung cancer cells.Subsequently,we demonstrated for the first time that erianin induced ferroptotic cell death in lung cancer cells,which was accompanied by ROS accumulation,lipid peroxidation,and GSH depletion.The ferroptosis inhibitors Fer-1 and Lip-1 but not Z-VAD-FMK,CQ,or necrostatin-1 rescued erianin-induced cell death,indicating that ferroptosis contributed to erianin-induced cell death.Furthermore,we demonstrated that Ca^(2+)/CaM signaling was a critical mediator of erianin-induced ferroptosis and that blockade of this signaling significantly rescued cell death induced by erianin treatment by suppressing ferroptosis.Taken together,our data suggest that the natural product erianin exerts its anticancer effects by inducing Ca^(2+)/CaMdependent ferroptosis and inhibiting cell migration,and erianin will hopefully serve as a prospective compound for lung cancer treatment. | Peng Chen Qibiao Wu Jiao Feng Lili Yan Yitian Sun Shuiping Liu Yu Xiang Mingming Zhang Ting Pan Xiaying Chen Ting Duan Lijuan Zhai Bingtao Zhai Wengang Wang Ruonan Zhang Bi Chen Xuemeng Han Yicong Li Liuxi Chen Ying Liu Xingxing Huang Ting Jin Wenzheng Zhang Hong Luo Xiaohui Chen Yongqiang Li Qiujie Li Guohua Li Qin Zhang Lvjia Zhuo Zuyi Yang Huifen Tang Tian Xie Xiaoping Ouyang Xinbing Sui | 2020 | Signal Transduction and Targeted Therapy2020，5，1： | 42 |
| 2 | Multivariate adaptive regression splines and neural network models for prediction of pile drivability显示文摘Piles are long, slender structural elements used to transfer the loads from the superstructure through weak strata onto stiffer soils or rocks. For driven piles, the impact of the piling hammer induces compression and tension stresses in the piles. Hence, an important design consideration is to check that the strength of the pile is sufficient to resist the stresses caused by the impact of the pile hammer. Due to its complexity, pile drivability lacks a precise analytical solution with regard to the phenomena involved.In situations where measured data or numerical hypothetical results are available, neural networks stand out in mapping the nonlinear interactions and relationships between the system's predictors and dependent responses. In addition, unlike most computational tools, no mathematical relationship assumption between the dependent and independent variables has to be made. Nevertheless, neural networks have been criticized for their long trial-and-error training process since the optimal configuration is not known a priori. This paper investigates the use of a fairly simple nonparametric regression algorithm known as multivariate adaptive regression splines(MARS), as an alternative to neural networks, to approximate the relationship between the inputs and dependent response, and to mathematically interpret the relationship between the various parameters. In this paper, the Back propagation neural network(BPNN) and MARS models are developed for assessing pile drivability in relation to the prediction of the Maximum compressive stresses(MCS), Maximum tensile stresses(MTS), and Blow per foot(BPF). A database of more than four thousand piles is utilized for model development and comparative performance between BPNN and MARS predictions. | Wengang Zhang Anthony T.C.Goh | 2016 | Geoscience Frontiers2016，7，1： | 34 |
| 3 | State-of-the-art review of soft computing applications in underground excavations显示文摘Soft computing techniques are becoming even more popular and particularly amenable to model the complex behaviors of most geotechnical engineering systems since they have demonstrated superior predictive capacity,compared to the traditional methods.This paper presents an overview of some soft computing techniques as well as their applications in underground excavations.A case study is adopted to compare the predictive performances of soft computing techniques including eXtreme Gradient Boosting(XGBoost),Multivariate Adaptive Regression Splines(MARS),Artificial Neural Networks(ANN),and Support Vector Machine(SVM) in estimating the maximum lateral wall deflection induced by braced excavation.This study also discusses the merits and the limitations of some soft computing techniques,compared with the conventional approaches available. | Wengang Zhang Runhong Zhang Chongzhi Wu Anthony Teck Chee Goh Suzanne Lacasse Zhongqiang Liu Hanlong Liu | 2020 | Geoscience Frontiers2020，11，4： | 33 |
| 4 | Prediction of undrained shear strength using extreme gradient boosting and random forest based on Bayesian optimization显示文摘Accurate assessment of undrained shear strength(USS)for soft sensitive clays is a great concern in geotechnical engineering practice.This study applies novel data-driven extreme gradient boosting(XGBoost)and random forest(RF)ensemble learning methods for capturing the relationships between the USS and various basic soil parameters.Based on the soil data sets from TC304 database,a general approach is developed to predict the USS of soft clays using the two machine learning methods above,where five feature variables including the preconsolidation stress(PS),vertical effective stress(VES),liquid limit(LL),plastic limit(PL)and natural water content(W)are adopted.To reduce the dependence on the rule of thumb and inefficient brute-force search,the Bayesian optimization method is applied to determine the appropriate model hyper-parameters of both XGBoost and RF.The developed models are comprehensively compared with three comparison machine learning methods and two transformation models with respect to predictive accuracy and robustness under 5-fold cross-validation(CV).It is shown that XGBoost-based and RF-based methods outperform these approaches.Besides,the XGBoostbased model provides feature importance ranks,which makes it a promising tool in the prediction of geotechnical parameters and enhances the interpretability of model. | Wengang Zhang Chongzhi Wu Haiyi Zhong Yongqin Li Lin Wang | 2021 | Geoscience Frontiers2021，12，1： | 33 |
| 5 | Baicalin induces ferroptosis in bladder cancer cells by downregulating FTH1显示文摘Ferroptosis is a non-apoptotic regulated cell death caused by iron accumulation and subsequent lipid peroxidation.Currently,the therapeutic role of ferroptosis on cancer is gaining increasing interest.Baicalin an active component in Scutellaria baicalensis Georgi with anticancer potential various cancer types;however,the effects of baicalein on bladder cancer and the underlying molecular mechanisms remain largely unknown.In the study,we investigated the effect of baicalin on bladder cancer cells5637 and KU-19-19.As a result,we show baicalin exerted its anticancer activity by inducing apoptosis and cell death in bladder cancer cells.Subsequently,we for the first time demonstrate baicalin-induced ferroptotic cell death in vitro and in vivo,accompanied by reactive oxygen species(ROS) accumulation and intracellular chelate iron enrichment.The ferroptosis inhibitor deferoxamine but not necrostatin-1,chloroquine(CQ),N-acetyl-L-cysteine,L-glutathione reduced,or carbobenzoxy-valyl-alanyl-aspartyl-[O-methyl]-fluoromethylketone(Z-VAD-FMK) rescued baicalin-induced cell death,indicating ferroptosis contributed to baicalin-induced cell death.Mechanistically,we show that ferritin heavy chain1(FTH1) was a key determinant for baicalin-induced ferroptosis.Overexpression of FTH1 abrogated the anticancer effects of baicalin in both 5637 and KU19-19 cells.Taken together,our data for the first time suggest that the natural product baicalin exerts its anticancer activity by inducing FTH1-dependent ferroptosis,which will hopefully provide a prospective compound for bladder cancer treatment. | Na Kong Xiaying Chen Jiao Feng Ting Duan Shuiping Liu Xueni Sun Peng Chen Ting Pan Lili Yan Ting Jin Yu Xiang Quan Gao Chengyong Wen Weirui Ma Wencheng Liu Mingming Zhang Zuyi Yang Wengang Wang Ruonan Zhang Bi Chen Tian Xie Xinbing Sui Wei Tao | 2021 | Acta Pharmaceutica Sinica B2021，11，12： | 23 |
| 6 | Probabilistic stability analyses of undrained slopes by 3D random fields and finite element methods显示文摘A long slope consisting of spatially random soils is a common geographical feature. This paper examined the necessity of three-dimensional(3 D) analysis when dealing with slope with full randomness in soil properties. Although 3 D random finite element analysis can well reflect the spatial variability of soil properties, it is often time-consuming for probabilistic stability analysis. For this reason, we also examined the least advantageous(or most pessimistic) cross-section of the studied slope. The concept of'most pessimistic' refers to the minimal cross-sectional average of undrained shear strength. The selection of the most pessimistic section is achievable by simulating the undrained shear strength as a 3 D random field. Random finite element analysis results suggest that two-dimensional(2 D) plane strain analysis based the most pessimistic cross-section generally provides a more conservative result than the corresponding full 3 D analysis. The level of conservativeness is around 15% on average. This result may have engineering implications for slope design where computationally tractable 2 D analyses based on the procedure proposed in this study could ensure conservative results. | Yong Liu Wengang Zhang Lei Zhang Zhiren Zhu Jun Hu Hong Wei | 2018 | Geoscience Frontiers2018，9，6： | 17 |
| 7 | Equilibrium scour depth at offshore monopile foundation in combined waves and current显示文摘Unlike the pier scour in bridge waterways,the local scour at offshore monopile foundations should take into account the effect of wave-current combination.Under the condition of wave-current coexistence,the water-soil interfacial scouring is usually coupled with the pore-pressure dynamics inside of the seabed.The aforementioned wave/current-pile-soil coupling process was physically modeled with a specially designed flow-structure-soil interaction flume.Experimental results indicate that superimposing a current onto the waves obviously changes the pore-pressure and the flow velocity at the bed around the pile.The concomitance of horseshoe vortex and local scour hole around a monopile proves that the horseshoe vortex is one of the main controlling mechanisms for scouring development under the combined waves and current.Based on similarity analyses,an average-velocity based Froude number(Fra)is proposed to correlate with the equilibrium scour depth(S/D)at offshore monopile foundation in the combined waves and current.An empirical expression for the correlation between S/D and Fra is given for predicting equilibrium scour depth,which may provide a guide for offshore engineering practice. | QI WenGang GAO FuPing | 2014 | Science China(Technological Sciences)2014，57，5： | 16 |
| 8 | Single-atom catalyst: a rising star for green synthesis of fine chemicals显示文摘The green synthesis of fine chemicals calls for a new generation of efficient and robust catalysts. Single-atom catalysts(SACs), in which all metal species are atomically dispersed on a solid support, and which often consist of well-defined mononuclear active sites, are expected to bridge homogeneous and heterogeneous catalysts for liquid-phase organic transformations. This review summarizes major advances in the SAC-catalysed green synthesis of fine chemicals in the past several years, with a focus on the catalytic activity, selectivity and reusability of SACs in various organic reactions. The relationship between catalytic performance and the active site structure is discussed in terms of the valence state, coordination environment and anchoring chemistry of single atoms to the support, in an effort to guide the rational design of SACs in this special area, which has traditionally been dominated by homogeneous catalysis.Finally, the challenges remaining in this research area are discussed and possible future research directions are proposed. | Leilei Zhang Yujing Ren Wengang Liu Aiqin Wang Tao Zhang | 2018 | National Science Review2018，5，5： | 15 |
| 9 | Apelin-13 induces ERK1/2 but not p38 MAPK activation through coupling of the human apelin receptor to the Gi2 pathway显示文摘 | Bo Bai Jiyou Tang Haiqing Liu Jing Chen Yalin Li Wengang Song | 2008 | Acta Biochimica et Biophysica Sinica2008，40，4： | 14 |
| 10 | Landslide susceptibility mapping using hybrid random forest with GeoDetector and RFE for factor optimization显示文摘The present study aims to develop two hybrid models to optimize the factors and enhance the predictive ability of the landslide susceptibility models.For this,a landslide inventory map was created with 406 historical landslides and 2030 non-landslide points,which was randomly divided into two datasets for model training(70%)and model testing(30%).22 factors were initially selected to establish a landslide factor database.We applied the GeoDetector and recursive feature elimination method(RFE)to address factor optimization to reduce information redundancy and collinearity in the data.Thereafter,the frequency ratio method,multicollinearity test,and interactive detector were used to analyze and evaluate the optimized factors.Subsequently,the random forest(RF)model was used to create a landslide susceptibility map with original and optimized factors.The resultant hybrid models GeoDetector-RF and RFE-RF were evaluated and compared by the area under the receiver operating characteristic curve(AUC)and accuracy.The accuracy of the two hybrid models(0.868 for GeoDetector-RF and 0.869 for RFE-RF)were higher than that of the RF model(0.860),indicating that the hybrid models with factor optimization have high reliability and predictability.Both RFE-RF GeoDetector-RF had higher AUC values,respectively 0.863 and 0.860,than RF(0.853).These results confirm the ability of factor optimization methods to improve the performance of landslide susceptibility models. | Xinzhi Zhou Haijia Wen Yalan Zhang Jiahui Xu Wengang Zhang | 2021 | Geoscience Frontiers2021，12，5： | 12 |
| 11 | Optimization of clay material mixture ratio and filling process in gypsum mine goaf显示文摘Because there is neither waste rock nor mill tailings in the gypsum mine, and the buildings on the goaf of gypsum mine are needed to be protected, the research proposed the scheme of the clay filling technology. Gypsum, cement, lime and water glass were used as adhesive, and the strength of different material ratios were investigated in this study. The influence factors of clay strength were obtained in the order of cement, gypsum, water glass and lime. The results show that the cement content is the determinant influence factor, and gypsum has positive effects, while the water glass can enhance both clay strength and the fluidity of the filing slurry. Furthermore, combining chaotic optimization method with neural network, the optimal ratio of composite cementing agent was obtained. The results show that the optimal ratio of water glass, cement, lime and clay (in quality) is 1.17:6.74:4.17:87.92 in the process of bottom self-flow filling, while the optimal ratio is 1.78:9.58:4.71:83.93 for roof-contacted filling. A novel filling process to fill in gypsum mine goaf with clay is established. The engineering practice shows that the filling cost is low, thus, notable economic benefit is achieved. | Liu Zhixiang Dang Wengang Liu Qingling Chen Guanghui Peng Kang | 2013 | International Journal of Mining Science and Technology2013，23，3： | 11 |
| 12 | Temperature field distribution of burnt surrounding rock in UCG stope显示文摘In order to study temperature field distribution in burnt surrounding rock and to determine ranges of burnt surrounding rock, coal-wall coking cycle and heat influence in the underground coal gasification(UCG) stope, based on the Laplace transform and inversion formula, we studied the temperature analytical solution of one-dimensional unsteady heat conduction for multi-layer overlying strata under the first and the forth kinds of boundary conditions, and we also carried out a numerical simulation of twodimensional unsteady heat conduction by the COMSOL multiphysics. The results show that when the boundary temperature of surrounding rock has a linear decrease because of a directional movement of heat source in the UCG flame working face, the temperature in surrounding rock increases first and then decreases with time, the peak of temperature curve decreases gradually and its position moves inside surrounding rock from the boundary. In the surrounding rock of UCG stope, there is an envelope curve of temperature curve clusters. We analyzed the influence of thermophysical parameters on envelope curves and put forward to take envelope curve as the calculation basis for ranges of burnt surrounding rock, coal-wall coking cycle and heat influence. Finally, the concrete numerical values are given by determining those judgement standards and temperature thresholds, which basically tally with the field geophysical prospecting results. | Xin Lin Wang Zuotang Huang Wengang Kang Guojun Lu Xuefeng Zhang Peng Wang Jianhua | 2014 | International Journal of Mining Science and Technology2014，24，4： | 10 |
| 13 | Predicting TBM penetration rate in hard rock condition:A comparative study among six XGB-based metaheuristic techniques显示文摘A reliable and accurate prediction of the tunnel boring machine(TBM)performance can assist in minimizing the relevant risks of high capital costs and in scheduling tunneling projects.This research aims to develop six hybrid models of extreme gradient boosting(XGB)which are optimized by gray wolf optimization(GWO),particle swarm optimization(PSO),social spider optimization(SSO),sine cosine algorithm(SCA),multi verse optimization(MVO)and moth flame optimization(MFO),for estimation of the TBM penetration rate(PR).To do this,a comprehensive database with 1286 data samples was established where seven parameters including the rock quality designation,the rock mass rating,Brazilian tensile strength(BTS),rock mass weathering,the uniaxial compressive strength(UCS),revolution per minute and trust force per cutter(TFC),were set as inputs and TBM PR was selected as model output.Together with the mentioned six hybrid models,four single models i.e.,artificial neural network,random forest regression,XGB and support vector regression were also built to estimate TBM PR for comparison purposes.These models were designed conducting several parametric studies on their most important parameters and then,their performance capacities were assessed through the use of root mean square error,coefficient of determination,mean absolute percentage error,and a10-index.Results of this study confirmed that the best predictive model of PR goes to the PSO-XGB technique with system error of(0.1453,and 0.1325),R^(2) of(0.951,and 0.951),mean absolute percentage error(4.0689,and 3.8115),and a10-index of(0.9348,and 0.9496)in training and testing phases,respectively.The developed hybrid PSO-XGB can be introduced as an accurate,powerful and applicable technique in the field of TBM performance prediction.By conducting sensitivity analysis,it was found that UCS,BTS and TFC have the deepest impacts on the TBM PR. | Jian Zhou Yingui Qiu Danial Jahed Armaghani Wengang Zhang Chuanqi Li Shuangli Zhu Reza Tarinejad | 2021 | Geoscience Frontiers2021，12，3： | 10 |
| 14 | Estimation of diaphragm wall deflections for deep braced excavation in anisotropic clays using ensemble learning显示文摘This paper adopts the NGI-ADP soil model to carry out finite element analysis,based on which the effects of soft clay anisotropy on the diaphragm wall deflections in the braced excavation were evaluated.More than one thousand finite element cases were numerically analyzed,followed by extensive parametric studies.Surrogate models were developed via ensemble learning methods(ELMs),including the e Xtreme Gradient Boosting(XGBoost),and Random Forest Regression(RFR)to predict the maximum lateral wall deformation(δhmax).Then the results of ELMs were compared with conventional soft computing methods such as Decision Tree Regression(DTR),Multilayer Perceptron Regression(MLPR),and Multivariate Adaptive Regression Splines(MARS).This study presents a cutting-edge application of ensemble learning in geotechnical engineering and a reasonable methodology that allows engineers to determine the wall deflection in a fast,alternative way. | Runhong Zhang Chongzhi Wu Anthony T.C.Goh Thomas Bohlke Wengang Zhang | 2021 | Geoscience Frontiers2021，12，1： | 9 |
| 15 | Programmed Death Ligand-1 on Microglia Regulates Th1 Differentiation via Nitric Oxide in Experimental Autoimmune Encephalomyelitis显示文摘Microglia are considered to be potential antigen-presenting cells and have the ability to present antigen under pathological conditions. Nevertheless, whether and how microglia are involved in immune regulation are largely unknown. Here, we investigated the suppressive activity of microglia during experimental autoimmune encephalomyelitis(EAE) induced by myelin oligodendrocyte glycoprotein, with the goal of understanding their role in regulating the T cell reaction. Using flow cytometric analysis, we found that microglia were characterized by increased cell number and up-regulated programmed death ligand-1(PD-L1) at the peak phase of EAE. Meanwhile,both the CD^(4+)T cells and microglia that infiltrated the central nervous system expressed higher levels of PD1, the receptor for PD-L1, accompanied by a decline of Th1 cells.In an ex vivo co-culture system, microglia from EAE mice inhibited the proliferation of antigen-specific CD^(4+)T cells and the differentiation of Th1 cells, and this was significantly inhibited by PD-L1 blockade. Further,microglia suppressed Th1 cells via nitric oxide(NO), the production of which was dependent on PD-L1. Thus, these data suggest a scenario in which microglia are involved in the regulation of EAE by suppressing Th1-cell differentiation via the PD-L1-NO pathway. | Jingxia Hu Hao He Zhengang Yang Guangming Zhu Li Kang Xiuli Jing Hai Lu Wengang Song Bo Bai Hua Tang | 2016 | Neuroscience Bulletin2016，32，1： | 9 |
| 16 | Big data and machine learning in geoscience and geoengineering:Introduction显示文摘In recent years,we have entered the so-called Fourth Paradigm with the regular production of huge amount of observational data.Big data is often characterized by the three‘V's:Volume of data,Variety and Velocity.The concept of big data can potentially address some existing issues in areas of geoscience and geoengineering.Large-scale,comprehensive,multidirectional and multifield geotechnical monitoring is becoming a reality in the very near future. | Wengang Zhang Jianye Ching Anthony T.C.Goh Andy Y.F.Leung | 2021 | Geoscience Frontiers2021，12，1： | 8 |
| 17 | A new strawberry harvesting robot for elevated-trough culture显示文摘In order to improve robotic harvesting and reduce production cost,a harvesting robot system for strawberry on the elevated-trough culture was designed.It was supposed to serve for sightseeing agriculture and technological education.Based on the sonar-camera sensor,an autonomous navigation system of the harvesting robot was built to move along the trough lines independently.The mature fruits were recognized according to the H(Hue)and S(Saturation)color feature and the picking-point were located by the binocular-vision unit.A nondestructive end-effector,used to suck the fruit,hold and cut the fruit-stem,was designed to prevent pericarp damage and disease infection.A joint-type industrial manipulator with six degrees-of-freedom(DOF)was utilized to carry the end-effector.The key points and time steps for the collision-free and rapid motion of manipulator were planned.Experimental results showed that all the 100 mature strawberry targets were recognized automatically in the harvesting test.The success harvesting rate was 86%,and the success harvesting operation cost 31.3 seconds on average,including a single harvest operation of 10 seconds.The average error for fruit location was less than 4.6 mm. | Feng Qingchun Wang Xiu Zheng Wengang Qiu Quan Jiang Kai | 2012 | International Journal of Agricultural and Biological Engineering2012，5，2： | 8 |
| 18 | Active Contours Based on Image Laplacian Fitting Energy显示文摘 | ZHANG Kaihua XU Shoushi ZHOU Wengang LIU Bo | 2009 | Chinese Journal of Electronics2009，18，2： | 7 |
| 19 | Effect of butanol on flotation separation of quartz from hematite with N-dodecyl ethylenediamine显示文摘In order to investigate the effect of butanol on quartz flotation when N-dodecyl ethylenediamine(ND)was used as collector, single mineral flotation and artificial mixed mineral(hematite and quartz were mixed at a mass ratio of 3:2) separation were conducted in the laboratory. Experimental results indicated that addition of butanol could improve the collecting performance of ND on quartz and enhance the floatability of quartz. Best flotation recovery of quartz was obtained when butanol was mixed with ND at a mass ratio of 1:1. Moreover, the molecular structure of alcohols had a significant effect on mineral recovery. Best separation efficiency could be obtained when tert-butanol was added as it had the largest cross-sectional area. Zeta potential measurements indicated that alcohols could strengthen electrostatic adsorption between quartz and collector. Molecular dynamic simulations revealed that co-adsorption of alcohols along with ND had taken place on the quartz surface, and ND/tert-butyl combinations were more easily absorbed on the quartz surface. | Liu Wengang Liu Wenbao Wang Xinyang Wei Dezhou Zhang Hao Liu Wei | 2016 | International Journal of Mining Science and Technology2016，26，6： | 7 |
| 20 | Preparation, characterization, pharmacokinetics and anticancer effects of PEGylated β-elemene liposomes显示文摘Objective:This study aimed to develop a new polyethylene glycol(PEG)ylatedβ-elemene liposome(PEG-Lipo-β-E)and evaluate its characterization,pharmacokinetics,antitumor effects and safety in vitro and in vivo.Methods:The liposomes were prepared by ethanol injection and high-pressure micro-jet homogenization.Characterization of the liposomes was conducted,and drug content,entrapment efficiency(EE),in vitro release and stability were studied by ultra-fast liquid chromatography(UFLC)and a liquid surface method.Blood was drawn from rats to establish the pharmacokinetic parameters.The anticancer effect was evaluated in a KU-19-19 bladder cancer xenograft model.Histological analyses were performed to evaluate safety.Results:The PEG-Lipo-β-E showed good stability and was characterized as 83.31±0.181 nm in size,0.279±0.004 in polydispersity index(PDI),-21.4±1.06 mV in zeta potential,6.65±0.02 in pH,5.024±0.107 mg/mL inβ-elemene(β-E)content,and 95.53±1.712%in average EE.The Fourier transform infrared spectroscopy(FTIR)and differential scanning calorimetry(DSC)indicated the formation of PEG-Lipo-β-E.Compared to elemene injection,PEG-Lipo-β-E demonstrated a 1.75-fold decrease in clearance,a 1.62-fold increase in half-life,and a 1.76-fold increase in area under the concentration-time curves(AUCs)from 0 hour to 1.5 hours(P<0.05).PEG-Lipo-β-E also showed an enhanced anticancer effect in vivo.Histological analyses showed that there was no evidence of toxicity to the heart,kidney,liver,lung or spleen.Conclusions:The present study demonstrates PEG-Lipo-β-E as a new formulation with ease of preparation,high EE,good stability,improved bioavailability and antitumor effects. | Bingtao Zhai Qibiao Wu Wengang Wang Mingming Zhang Xuemeng Han Qiujie Li Peng Chen Xiaying Chen Xingxing Huang Guohua Li Qin Zhang Ruonan Zhang Yu Xiang Shuiping Liu Ting Duan Jianshu Lou Tian Xie Xinbing Sui | 2020 | Cancer Biology & Medicine2020，17，1： | 6 |
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