Natural product bufotenine(5)which could be isolated from Venenum Bufonis,has been widely used as a tool in central nervous system(CNS)studies.We present here its quaternary ammonium salt(6)which was synthesized with ...Natural product bufotenine(5)which could be isolated from Venenum Bufonis,has been widely used as a tool in central nervous system(CNS)studies.We present here its quaternary ammonium salt(6)which was synthesized with high yields using 5-benzyloxyindole as raw materials,and we firstly discover its analgesic effects in vivo.The analgesic evaluation showed that compounds 5 and 6 had stronger effects on the behavior of formalin induced pain in mice.Moreover,the combination of compound 6 and morphine has a synergistic effect.We intended to explain the molecular mechanism of this effect.Therefore,36 analgesic-related targets(including 15 G protein-coupled receptors,6 enzymes,13 ion channels,and 2 others)were systemically evaluated using reverse docking.The results indicate that bufotenine and its derivatives are closely related to acetyl cholinesterase(AChE)orα_(4)β_(2) nicotinic acetylcholine receptor(nAChR).This study provides practitioners a new insight of analgesic effects.展开更多
Previous studies indicate that ENSO predictions are particularly sensitive to the initial conditions in some key areas（socalled ＂sensitive areas＂）. And yet, few studies have quantified improvements in prediction s...Previous studies indicate that ENSO predictions are particularly sensitive to the initial conditions in some key areas（socalled ＂sensitive areas＂）. And yet, few studies have quantified improvements in prediction skill in the context of an optimal observing system. In this study, the impact on prediction skill is explored using an intermediate coupled model in which errors in initial conditions formed to make ENSO predictions are removed in certain areas. Based on ideal observing system simulation experiments, the importance of various observational networks on improvement of El Ni n？o prediction skill is examined. The results indicate that the initial states in the central and eastern equatorial Pacific are important to improve El Ni n？o prediction skill effectively. When removing the initial condition errors in the central equatorial Pacific, ENSO prediction errors can be reduced by 25%. Furthermore, combinations of various subregions are considered to demonstrate the efficiency on ENSO prediction skill. Particularly, seasonally varying observational networks are suggested to improve the prediction skill more effectively. For example, in addition to observing in the central equatorial Pacific and its north throughout the year,increasing observations in the eastern equatorial Pacific during April to October is crucially important, which can improve the prediction accuracy by 62%. These results also demonstrate the effectiveness of the conditional nonlinear optimal perturbation approach on detecting sensitive areas for target observations.展开更多
Colorectal cancer(CRC)is one of the most common human malignant diseases and the second leading cause of cancer-related deaths worldwide.The treatment of advanced CRC has improved significantly in recent years.With th...Colorectal cancer(CRC)is one of the most common human malignant diseases and the second leading cause of cancer-related deaths worldwide.The treatment of advanced CRC has improved significantly in recent years.With the emergence of two targeted antibodies,cetuximab(Erbitux),an anti-epidermal growth factor receptor monoclonal antibody and bevacizumab(Avastin),a vascular endothelial growth factor monoclonal antibody,the treatment of metastatic CRC has entered the era of personalized therapy.Predictive and prognostic biomarkers have,and will continue to,facilitate the selection of suitable patients and the personalization of treatment for metastatic CRC(mCRC).In this review,we will focus primarily on the important progresses made in the personalized treatment of mCRC and discuss the potentially novel predictive and prognostic biomarkers for improved selection of patients for anti-cancer treatment in the future.展开更多
According to the characteristic of maneuvering targets tracking system, adaptive track predicting control is proposed from the point of predicting the motion track of the maneuvering target. For this method, least mea...According to the characteristic of maneuvering targets tracking system, adaptive track predicting control is proposed from the point of predicting the motion track of the maneuvering target. For this method, least mean square（LMS） adaptive filter is applied to estimate the future track of the target. The structure of this filter is simple and the calculation amount is small. It is therefore suitable to being used in real-time control system. Testing results have proved that the control method can improve the tracking precision for maneuvering targets obviously.展开更多
Objective:To study the drug activity and therapeutic targets of Niga-ichigoside F1 predicted based on network pharmacology and molecular docking.Methods:Download the 2D and 3D structures of Niga-ichigoside F1 from the...Objective:To study the drug activity and therapeutic targets of Niga-ichigoside F1 predicted based on network pharmacology and molecular docking.Methods:Download the 2D and 3D structures of Niga-ichigoside F1 from the PubChem database for target prediction and molecular docking,respectively.Target information was predicted by PharmMapper and swiss ADME databases,target gene names were extracted and rechecked by Uniprot database,and disease information corresponding to target was queried by TTD database.The enrichment analysis of GO and KEGG signal pathway was conducted by Metascape database.AutoDuck Vina was used for molecular docking of Niga-ichigoside F1 3D structure with key proteins of related diseases and common pathways.Finally,the conformation of molecular docking was visualized by PyMOL.Results:A total of 34 targets and 69 related disease information were obtained from the database screening.The targets with high degree of acquisition of the association network between target and disease were AR,F2,VDR,PDE10A,mTOR,and NR3C2,etc..Diseases with a high degree of relief were solid tumour,breast cancer, acute myeloid leukemia, hypertension, and thrombocytopenia,etc..The items with significance in GO analysis included positive regulation of transferase activity,protein autophosphorylation,negative regulation of cGMP-mediated signaling,intracellular receptor signaling pathway,regulation of cellular response to stress,blood vessel development,reactive oxygen species metabolic process,negative regulation of immune response,regulation of transcription from RNA polymerase Ⅱ promoter in response to stress,and nucleobase-containing small molecule metabolic process,etc..The items with significance in KEGG enrichment analysis(P<0.01) included Pathways in cancer,Purine metabolism,Focal adhesion,MAPK signaling pathway,GnRH signaling pathway,AGE-RAGE signaling pathway in diabetic complications,Ras signaling pathway,Leukocyte transendothelial migration and Platelet activation,etc..Molecular docking suggested that the target of Niga-ichigoside F1 had good binding ability with related diseases and key proteins of common pathways.Conclusion:According to the results of network pharmacology and molecular docking,Niga-ichigoside F1 has rich drug activity and may act on a variety of diseases.After comprehensive analysis, we proposed for the first time the high correlation between Niga-ichigoside F1 and cancer,as well as the possible association with acute myeloid leukemia and hypertension.It has the characteristics of multi-target and multi-pathway,which is worthy of further research,development and utilization.展开更多
Remote tracking for mobile targets is one of the most important applications in wireless sensor networks （WSNs）. A target tracking protoco–exponential distributed predictive tracking （EDPT） is proposed. To reduce...Remote tracking for mobile targets is one of the most important applications in wireless sensor networks （WSNs）. A target tracking protoco–exponential distributed predictive tracking （EDPT） is proposed. To reduce energy waste and response time, an improved predictive algorithm–exponential smoothing predictive algorithm （ESPA） is presented. With the aid of an additive proportion and differential （PD） controller, ESPA decreases the system predictive delay effectively. As a recovery mechanism, an optimal searching radius （OSR） algorithm is applied to calculate the optimal radius of the recovery zone. The simulation results validate that the proposed EDPT protocol performes better in terms of track failed ratio, energy waste ratio and enlarged sensing nodes ratio, respectively.展开更多
Grey modeling can be used to predict the behavioral development of a system and find out the lead control values of the system. By using fuzzy inference, PID parameters can be adjusted on line by the fuzzy controller ...Grey modeling can be used to predict the behavioral development of a system and find out the lead control values of the system. By using fuzzy inference, PID parameters can be adjusted on line by the fuzzy controller with PID parameters self-tuning. According to the characteristics of target tracking system in a robot weapon, grey prediction theory and fuzzy PID control ideas are combined. A grey prediction mathematical model is constructed and a fuzzy PID controller with grey prediction was developed. Simulation result shows fuzzy PID control algorithm with grey prediction is an efficient method that can improve the control equality and robustness of traditional PID control and fuzzy PID control, and has much better performance for target tracking.展开更多
This paper presents a nonlinear multidimensional scaling model, called kernelized fourth quantifica- tion theory, which is an integration of kernel techniques and the fourth quantification theory. The model can deal w...This paper presents a nonlinear multidimensional scaling model, called kernelized fourth quantifica- tion theory, which is an integration of kernel techniques and the fourth quantification theory. The model can deal with the problem of mineral prediction without defining a training area. In mineral target prediction, the pre-defined statistical cells, such as grid cells, can be implicitly transformed using kernel techniques from input space to a high-dimensional feature space, where the nonlinearly separable clusters in the input space are ex- pected to be linearly separable. Then, the transformed cells in the feature space are mapped by the fourth quan- tifieation theory onto a low-dimensional scaling space, where the sealed cells can be visually clustered according to their spatial locations. At the same time, those cells, which are far away from the cluster center of the majority of the sealed cells, are recognized as anomaly cells. Finally, whether the anomaly cells can serve as mineral potential target cells can be tested by spatially superimposing the known mineral occurrences onto the anomaly ceils. A case study shows that nearly all the known mineral occurrences spatially coincide with the anomaly cells with nearly the smallest scaled coordinates in one-dimensional sealing space. In the case study, the mineral target cells delineated by the new model are similar to those predicted by the well-known WofE model.展开更多
Systems with large operating regions and non-zero state target tracking have limited the industrial application of robust model predictive control (RMPC) with synthetic action. To overcome the problem, this paper pres...Systems with large operating regions and non-zero state target tracking have limited the industrial application of robust model predictive control (RMPC) with synthetic action. To overcome the problem, this paper presents a novel formulation of synthesizing scheduled RMPC for linear time varying (LTV) systems. Off-line, we compute the matrix that transforms target output into steady state first. Then a set of stabilizing state feedback laws which are corresponding to a set of estimated regions of stability covering the desired operating region are provided. On-line, these control laws are implemented as a single scheduled state feedback model predictive control (MPC) which switches between the set of local controllers and achieve the desired target at last. Finally, the algorithm is illustrated with an example.展开更多
两歧双歧杆菌作为重要益生菌,其工业化培养过程中存在氮源利用率低、生长密度低等问题。前期研究发现,两歧双歧杆菌可利用含脯氨酸的肽。该研究旨在根据两歧双歧杆菌的氮源利用特征靶向制备脯氨酸肽,以提升氮源利用效率和生长水平。研...两歧双歧杆菌作为重要益生菌,其工业化培养过程中存在氮源利用率低、生长密度低等问题。前期研究发现,两歧双歧杆菌可利用含脯氨酸的肽。该研究旨在根据两歧双歧杆菌的氮源利用特征靶向制备脯氨酸肽,以提升氮源利用效率和生长水平。研究优选5种富脯氨酸蛋白和5种蛋白酶制备短肽,结合菌株培养从中筛选出了2种高含脯氨酸且对生长有益的底物蛋白(酪蛋白、谷蛋白)。结合菌株氮源利用特性与肽酶特征制定多步酶解策略,利用计算机工具预测了酶解肽,并使用分子对接模拟肽段与肽转运的关键蛋白寡肽结合蛋白OppA(oligopeptide binding protein A,OppA)的结合,发现77.5%以上的肽都能与OppA有效结合。经酶解制备得到了6种脯氨酸肽,分子质量为180~2000 Da的肽占到72.49%以上(180~500 Da的短肽>50%),且脯氨酸大多以肽的形式存在(极少量游离)。将制备的脯氨酸肽与1种乳清蛋白肽都用作培养,发现乳清蛋白肽WA(whey protein peptides hydrolyzed by alkaline protease,WA)与酪蛋白肽CAF(casein peptides hydrolyzed by alkaline protease and flavourzyme,CAF)按质量比2∶1复配,添加量8 g/L时活菌数达到(2.04±0.1)×10^(9)CFU/mL,单位氮源产生(1.38±0.18)×10^(12)CFU的活菌,相较于传统MRS培养基分别提升35%和198.5%。该研究为两歧双歧杆菌的高效培养及工业化应用提供了创新策略。展开更多
基金supported by National Natural Science Foundation of China(No.81973171)Postgraduate Research&Practice Innovation Program of Jiangsu Province(Nos.KYCX20J561,SJCX200533).
文摘Natural product bufotenine(5)which could be isolated from Venenum Bufonis,has been widely used as a tool in central nervous system(CNS)studies.We present here its quaternary ammonium salt(6)which was synthesized with high yields using 5-benzyloxyindole as raw materials,and we firstly discover its analgesic effects in vivo.The analgesic evaluation showed that compounds 5 and 6 had stronger effects on the behavior of formalin induced pain in mice.Moreover,the combination of compound 6 and morphine has a synergistic effect.We intended to explain the molecular mechanism of this effect.Therefore,36 analgesic-related targets(including 15 G protein-coupled receptors,6 enzymes,13 ion channels,and 2 others)were systemically evaluated using reverse docking.The results indicate that bufotenine and its derivatives are closely related to acetyl cholinesterase(AChE)orα_(4)β_(2) nicotinic acetylcholine receptor(nAChR).This study provides practitioners a new insight of analgesic effects.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA19060102)the National Natural Science Foundation of China (Grant Nos. 41475101, 41690122, 41690120 and 41421005)the National Programme on Global Change and Air–Sea Interaction Interaction (Grant Nos. GASI-IPOVAI-06 and GASI-IPOVAI-01-01)
文摘Previous studies indicate that ENSO predictions are particularly sensitive to the initial conditions in some key areas（socalled ＂sensitive areas＂）. And yet, few studies have quantified improvements in prediction skill in the context of an optimal observing system. In this study, the impact on prediction skill is explored using an intermediate coupled model in which errors in initial conditions formed to make ENSO predictions are removed in certain areas. Based on ideal observing system simulation experiments, the importance of various observational networks on improvement of El Ni n？o prediction skill is examined. The results indicate that the initial states in the central and eastern equatorial Pacific are important to improve El Ni n？o prediction skill effectively. When removing the initial condition errors in the central equatorial Pacific, ENSO prediction errors can be reduced by 25%. Furthermore, combinations of various subregions are considered to demonstrate the efficiency on ENSO prediction skill. Particularly, seasonally varying observational networks are suggested to improve the prediction skill more effectively. For example, in addition to observing in the central equatorial Pacific and its north throughout the year,increasing observations in the eastern equatorial Pacific during April to October is crucially important, which can improve the prediction accuracy by 62%. These results also demonstrate the effectiveness of the conditional nonlinear optimal perturbation approach on detecting sensitive areas for target observations.
基金Supported by National High-Tech R and D Program of China,863 Program,No.2012AA02A506The Science and Technology Department of Guangdong Province,China,No.2012B031800088
文摘Colorectal cancer(CRC)is one of the most common human malignant diseases and the second leading cause of cancer-related deaths worldwide.The treatment of advanced CRC has improved significantly in recent years.With the emergence of two targeted antibodies,cetuximab(Erbitux),an anti-epidermal growth factor receptor monoclonal antibody and bevacizumab(Avastin),a vascular endothelial growth factor monoclonal antibody,the treatment of metastatic CRC has entered the era of personalized therapy.Predictive and prognostic biomarkers have,and will continue to,facilitate the selection of suitable patients and the personalization of treatment for metastatic CRC(mCRC).In this review,we will focus primarily on the important progresses made in the personalized treatment of mCRC and discuss the potentially novel predictive and prognostic biomarkers for improved selection of patients for anti-cancer treatment in the future.
文摘According to the characteristic of maneuvering targets tracking system, adaptive track predicting control is proposed from the point of predicting the motion track of the maneuvering target. For this method, least mean square（LMS） adaptive filter is applied to estimate the future track of the target. The structure of this filter is simple and the calculation amount is small. It is therefore suitable to being used in real-time control system. Testing results have proved that the control method can improve the tracking precision for maneuvering targets obviously.
基金National Natural Science Foundation of China(No.82060855)。
文摘Objective:To study the drug activity and therapeutic targets of Niga-ichigoside F1 predicted based on network pharmacology and molecular docking.Methods:Download the 2D and 3D structures of Niga-ichigoside F1 from the PubChem database for target prediction and molecular docking,respectively.Target information was predicted by PharmMapper and swiss ADME databases,target gene names were extracted and rechecked by Uniprot database,and disease information corresponding to target was queried by TTD database.The enrichment analysis of GO and KEGG signal pathway was conducted by Metascape database.AutoDuck Vina was used for molecular docking of Niga-ichigoside F1 3D structure with key proteins of related diseases and common pathways.Finally,the conformation of molecular docking was visualized by PyMOL.Results:A total of 34 targets and 69 related disease information were obtained from the database screening.The targets with high degree of acquisition of the association network between target and disease were AR,F2,VDR,PDE10A,mTOR,and NR3C2,etc..Diseases with a high degree of relief were solid tumour,breast cancer, acute myeloid leukemia, hypertension, and thrombocytopenia,etc..The items with significance in GO analysis included positive regulation of transferase activity,protein autophosphorylation,negative regulation of cGMP-mediated signaling,intracellular receptor signaling pathway,regulation of cellular response to stress,blood vessel development,reactive oxygen species metabolic process,negative regulation of immune response,regulation of transcription from RNA polymerase Ⅱ promoter in response to stress,and nucleobase-containing small molecule metabolic process,etc..The items with significance in KEGG enrichment analysis(P<0.01) included Pathways in cancer,Purine metabolism,Focal adhesion,MAPK signaling pathway,GnRH signaling pathway,AGE-RAGE signaling pathway in diabetic complications,Ras signaling pathway,Leukocyte transendothelial migration and Platelet activation,etc..Molecular docking suggested that the target of Niga-ichigoside F1 had good binding ability with related diseases and key proteins of common pathways.Conclusion:According to the results of network pharmacology and molecular docking,Niga-ichigoside F1 has rich drug activity and may act on a variety of diseases.After comprehensive analysis, we proposed for the first time the high correlation between Niga-ichigoside F1 and cancer,as well as the possible association with acute myeloid leukemia and hypertension.It has the characteristics of multi-target and multi-pathway,which is worthy of further research,development and utilization.
基金supported by the National Basic Research Program of China (973 Program) (2010CB731800)the National Natural Science Foundation of China (60934003+2 种基金 60974123 60804010)the Hebei Provincial Educational Foundation of China (2008147)
文摘Remote tracking for mobile targets is one of the most important applications in wireless sensor networks （WSNs）. A target tracking protoco–exponential distributed predictive tracking （EDPT） is proposed. To reduce energy waste and response time, an improved predictive algorithm–exponential smoothing predictive algorithm （ESPA） is presented. With the aid of an additive proportion and differential （PD） controller, ESPA decreases the system predictive delay effectively. As a recovery mechanism, an optimal searching radius （OSR） algorithm is applied to calculate the optimal radius of the recovery zone. The simulation results validate that the proposed EDPT protocol performes better in terms of track failed ratio, energy waste ratio and enlarged sensing nodes ratio, respectively.
基金the Ministerial Level Advanced Research Foundation (061103)
文摘Grey modeling can be used to predict the behavioral development of a system and find out the lead control values of the system. By using fuzzy inference, PID parameters can be adjusted on line by the fuzzy controller with PID parameters self-tuning. According to the characteristics of target tracking system in a robot weapon, grey prediction theory and fuzzy PID control ideas are combined. A grey prediction mathematical model is constructed and a fuzzy PID controller with grey prediction was developed. Simulation result shows fuzzy PID control algorithm with grey prediction is an efficient method that can improve the control equality and robustness of traditional PID control and fuzzy PID control, and has much better performance for target tracking.
基金supported by National Natural Science Foundation of China (No.40872193)
文摘This paper presents a nonlinear multidimensional scaling model, called kernelized fourth quantifica- tion theory, which is an integration of kernel techniques and the fourth quantification theory. The model can deal with the problem of mineral prediction without defining a training area. In mineral target prediction, the pre-defined statistical cells, such as grid cells, can be implicitly transformed using kernel techniques from input space to a high-dimensional feature space, where the nonlinearly separable clusters in the input space are ex- pected to be linearly separable. Then, the transformed cells in the feature space are mapped by the fourth quan- tifieation theory onto a low-dimensional scaling space, where the sealed cells can be visually clustered according to their spatial locations. At the same time, those cells, which are far away from the cluster center of the majority of the sealed cells, are recognized as anomaly cells. Finally, whether the anomaly cells can serve as mineral potential target cells can be tested by spatially superimposing the known mineral occurrences onto the anomaly ceils. A case study shows that nearly all the known mineral occurrences spatially coincide with the anomaly cells with nearly the smallest scaled coordinates in one-dimensional sealing space. In the case study, the mineral target cells delineated by the new model are similar to those predicted by the well-known WofE model.
文摘Systems with large operating regions and non-zero state target tracking have limited the industrial application of robust model predictive control (RMPC) with synthetic action. To overcome the problem, this paper presents a novel formulation of synthesizing scheduled RMPC for linear time varying (LTV) systems. Off-line, we compute the matrix that transforms target output into steady state first. Then a set of stabilizing state feedback laws which are corresponding to a set of estimated regions of stability covering the desired operating region are provided. On-line, these control laws are implemented as a single scheduled state feedback model predictive control (MPC) which switches between the set of local controllers and achieve the desired target at last. Finally, the algorithm is illustrated with an example.
文摘两歧双歧杆菌作为重要益生菌,其工业化培养过程中存在氮源利用率低、生长密度低等问题。前期研究发现,两歧双歧杆菌可利用含脯氨酸的肽。该研究旨在根据两歧双歧杆菌的氮源利用特征靶向制备脯氨酸肽,以提升氮源利用效率和生长水平。研究优选5种富脯氨酸蛋白和5种蛋白酶制备短肽,结合菌株培养从中筛选出了2种高含脯氨酸且对生长有益的底物蛋白(酪蛋白、谷蛋白)。结合菌株氮源利用特性与肽酶特征制定多步酶解策略,利用计算机工具预测了酶解肽,并使用分子对接模拟肽段与肽转运的关键蛋白寡肽结合蛋白OppA(oligopeptide binding protein A,OppA)的结合,发现77.5%以上的肽都能与OppA有效结合。经酶解制备得到了6种脯氨酸肽,分子质量为180~2000 Da的肽占到72.49%以上(180~500 Da的短肽>50%),且脯氨酸大多以肽的形式存在(极少量游离)。将制备的脯氨酸肽与1种乳清蛋白肽都用作培养,发现乳清蛋白肽WA(whey protein peptides hydrolyzed by alkaline protease,WA)与酪蛋白肽CAF(casein peptides hydrolyzed by alkaline protease and flavourzyme,CAF)按质量比2∶1复配,添加量8 g/L时活菌数达到(2.04±0.1)×10^(9)CFU/mL,单位氮源产生(1.38±0.18)×10^(12)CFU的活菌,相较于传统MRS培养基分别提升35%和198.5%。该研究为两歧双歧杆菌的高效培养及工业化应用提供了创新策略。
