Radiotherapy is commonly used to treat advanced pancreatic cancers and can improve survival by2 months in combination with gemcitabine.However,prognosis and survival improvement remain unsatisfactory,and effective the...Radiotherapy is commonly used to treat advanced pancreatic cancers and can improve survival by2 months in combination with gemcitabine.However,prognosis and survival improvement remain unsatisfactory,and effective therapies are urgently needed.Piperlongumine has been demonstrated to have therapeutic potentials against various cancers.In this study,we synthesized a series of piperlongumine derivatives and provided evidence that piperlongumine derivatives could be used as effective radiosensitizers in pancreatic cancer.Two compounds enhanced the radiosensitivity of Panc-1 and SW1990 cells.In a pancreatic bi-flank xenograft tumor model,they significantly inhibited tumor growth.Piperlongumine derivatives could induce reactive oxygen species(ROS)expression and regulate the Keapl-Nrf2 protective pathway with enhancement of radiation-induced DNA damage,G2/M-phase cell cycle arrest,and apoptosis.Collectively,our data offer a proof of concept for the use of piperlongumine derivatives as a novel class of radiosensitizers for the treatment of pancreatic cancer.展开更多
This paper develops an adaptive neural network(NN)observer for proton-exchange membrane fuel cells(PEMFCs).Indeed,information on the oxygen excess ratio(OER)value is crucial to ensure optimal management of the durabil...This paper develops an adaptive neural network(NN)observer for proton-exchange membrane fuel cells(PEMFCs).Indeed,information on the oxygen excess ratio(OER)value is crucial to ensure optimal management of the durability and reliability of the PEMFC.The OER indicator is computed from the mass of oxygen and nitrogen inside the PEMFC cathode.Unfortunately,the measurement process of both these masses is difficult and costly.To solve this problem,the design of a PEMFC state observer is attractive.However,the behaviour of the fuel cell system is highly non-linear and its modelling is complex.Due to this constraint,a multilayer perceptron neural network(MLPNN)-based observer is proposed in this paper to estimate the oxygen and nitrogen masses.One notable advantage of the suggested MLPNN observer is that it does not require a database to train the NN.Indeed,the weights of the NN are updated in real time using the output error.In addition,the observer parameters,namely the learning rate and the damping factor,are online adapted using the optimization tools of extremum seeking.Moreover,the proposed observer stability analysis is performed using the Lyapunov theory.The observer performances are validated by simulation under MATLAB®/Simulink®.The supremacy of the proposed adaptive MLPNN observer is highlighted by comparison with a fixed-parameter MLPNN observer and a classical high-gain observer(HGO).The mean rela-tive error value of the excess oxygen rate is considered the performance index,which is equal to 1.01%for an adaptive MLPNN and 3.95%and 9.95%for a fixed MLPNN and HGO,respectively.Finally,a robustness test of the proposed observer with respect to measurement noise is performed.展开更多
基金supported by grants from the Shanghai Municipal Commission of Health and Family Planning(No.2017YQ052)the Young Elite Scientists Sponsorship Program by the China Association for Science and Technology(No.2017QNRC061)+3 种基金the National Natural Science Foundation of China(Nos.81673352,81872453)the Bio-Pharmaceutical Project of Science and Technology of Shanghai(No.15431901700)the Natural Science Foundation of Shanghai(No.18ZR1438700)the Key Research and Development Program of Ningxia(Nos.2018BFH02001 and 2019BFG02017)。
文摘Radiotherapy is commonly used to treat advanced pancreatic cancers and can improve survival by2 months in combination with gemcitabine.However,prognosis and survival improvement remain unsatisfactory,and effective therapies are urgently needed.Piperlongumine has been demonstrated to have therapeutic potentials against various cancers.In this study,we synthesized a series of piperlongumine derivatives and provided evidence that piperlongumine derivatives could be used as effective radiosensitizers in pancreatic cancer.Two compounds enhanced the radiosensitivity of Panc-1 and SW1990 cells.In a pancreatic bi-flank xenograft tumor model,they significantly inhibited tumor growth.Piperlongumine derivatives could induce reactive oxygen species(ROS)expression and regulate the Keapl-Nrf2 protective pathway with enhancement of radiation-induced DNA damage,G2/M-phase cell cycle arrest,and apoptosis.Collectively,our data offer a proof of concept for the use of piperlongumine derivatives as a novel class of radiosensitizers for the treatment of pancreatic cancer.
基金supported by the Ministry of Higher Education,Scientific Research and Innovation,the Digital Development Agency and the CNRST of Morocco(Alkhawarizmi/2020/39).
文摘This paper develops an adaptive neural network(NN)observer for proton-exchange membrane fuel cells(PEMFCs).Indeed,information on the oxygen excess ratio(OER)value is crucial to ensure optimal management of the durability and reliability of the PEMFC.The OER indicator is computed from the mass of oxygen and nitrogen inside the PEMFC cathode.Unfortunately,the measurement process of both these masses is difficult and costly.To solve this problem,the design of a PEMFC state observer is attractive.However,the behaviour of the fuel cell system is highly non-linear and its modelling is complex.Due to this constraint,a multilayer perceptron neural network(MLPNN)-based observer is proposed in this paper to estimate the oxygen and nitrogen masses.One notable advantage of the suggested MLPNN observer is that it does not require a database to train the NN.Indeed,the weights of the NN are updated in real time using the output error.In addition,the observer parameters,namely the learning rate and the damping factor,are online adapted using the optimization tools of extremum seeking.Moreover,the proposed observer stability analysis is performed using the Lyapunov theory.The observer performances are validated by simulation under MATLAB®/Simulink®.The supremacy of the proposed adaptive MLPNN observer is highlighted by comparison with a fixed-parameter MLPNN observer and a classical high-gain observer(HGO).The mean rela-tive error value of the excess oxygen rate is considered the performance index,which is equal to 1.01%for an adaptive MLPNN and 3.95%and 9.95%for a fixed MLPNN and HGO,respectively.Finally,a robustness test of the proposed observer with respect to measurement noise is performed.
