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
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
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
MicroRNAs （miRNAs） are a class of newly identified, small, non-coding RNAs that play vital roles in regulation. Based on miRNAs unique features of expression pattern, evolutionary conservation, secondary structure a...MicroRNAs （miRNAs） are a class of newly identified, small, non-coding RNAs that play vital roles in regulation. Based on miRNAs unique features of expression pattern, evolutionary conservation, secondary structure and genetic requirements for biogenesis, computational predication strategy is adopted to predicate the novel miRNAs. In this research, potential miRNAs and their targets in grapevine （Vitis vinifera） were predicted. We used previously known plant miRNAs against grapevine genome sequence databases to search for potential miRNAs. A total of 81 potential miRNAs were detected following a range of strict filtering criteria. Using these potential miRNA sequences, we could further blast the mRNA database to find the potential targets in this species. Comparative analysis of miRNAs in grapevine and other species reveals that miRNAs exhibit an evolutional conservation, the number and function of miRNAs must have significantly expanded during the evolution of land plants. Furthermore divergence made versatile functions of miRNAs feasible. Cluster of miRNAs likely represents an ancient expression mechanism. Predicted target genes include not only transcription factors but also genes implicated in floral development, signal transduction, diseases and stress response. Till now, little is known about experimental or computational identification of miRNA in grapevine species. Increased knowledge of the biological mechanisms of the grapevine will allow targeted approaches to increase the quality of fruit and reduce the impact of parasites together with stress, which could enable a sustainable, environmentally-sound, farming policv.展开更多
Edible plant derived exosome-like nanoparticles(ELNs)have been shown to have multiple nutraceutical functions.However,the diversity of plant materials makes the plant derived ELN study challenging.More efforts are sti...Edible plant derived exosome-like nanoparticles(ELNs)have been shown to have multiple nutraceutical functions.However,the diversity of plant materials makes the plant derived ELN study challenging.More efforts are still needed to explore the feasible isolation methods of edible plant derived ELNs and the possible roles of food-derived ELNs in improving human health.In this study,a size exclusion chromatography based method was compared with the traditional ultracentrifugation method to isolate blueberry derived ELNs(B-ELNs),and the miRNA profile of B-ELNs was analyzed by high-throughput sequencing.A total of 36 miRNAs were found to be enriched in B-ELNs compared with berry tissue,and their potential cross-kingdom human gene targets were further predicted.Results showed that size exclusion chromatography was effective for B-ELN isolation.The most abundant miRNAs in B-ELNs mainly belonged to the miR166 family and miR396 family.Target gene prediction indicated that B-ELNs could potentially regulate pathways related to the human digestive system,immune system and infectious diseases.展开更多
Objective The aim of the study was to summarize the diagnostic value of miR-21 as a biomarker in oral squamous cell carcinoma(OSCC)using a review of the literature and data from the cancer genome atlas(TCGA)database.M...Objective The aim of the study was to summarize the diagnostic value of miR-21 as a biomarker in oral squamous cell carcinoma(OSCC)using a review of the literature and data from the cancer genome atlas(TCGA)database.Methods Data from TCGA database was sorted and analyzed by bioinformatics to determine the expression level of miR-21 in OSCC.Further,we searched for relevant articles in Embase,PubMed/Medline,Scopus,and Web of Science published before March 2021,extracted the data,and conducted quality assessment.The bivariate meta-analysis model with Stata 16.0 was used to analyze the diagnostic value of miR-21 for OSCC.Results A total of 304 related articles were identified,and seven were selected for meta-analysis.The diagnostic results after analysis were as follows:sensitivity 0.76[95%confidence interval(CI),0.57-0.88];specificity 0.77(95%CI,0.58-0.89);positive likelihood ratio 3.34(95%CI,1.58-7.08);negative likelihood ratio 0.31(95%CI,0.15-0.63);diagnostic odds ratio 10.75(95%CI,2.85-40.51);and area under the curve 0.83(95%CI,0.80-0.86).The Deeks’funnel chart showed that there was no potential bias(P=0.54).Prediction analysis of the potential target genes of miR-21 was performed via the biological website,and DAVID was used to cross target genes for gene ontology(GO)annotation function analysis.Conclusion The results showed that miR-21-3p and miR-21-5p were significantly more highly expressed in OSCC tissues than in normal tissues(P<0.05),and the results of the meta-analysis indicated that they could be used as potential biomarkers in the diagnosis of OSCC.In addition,58 potential target genes of miR-21 were significantly enriched in 28 GO annotation functional pathways,which provided a biological basis for further clinical diagnostic value research.展开更多
Target tracking is one typical application of visual servoing technology. It is still a difficult task to track high speed target with current visual servo system. The improvement of visual servoing scheme is strongly...Target tracking is one typical application of visual servoing technology. It is still a difficult task to track high speed target with current visual servo system. The improvement of visual servoing scheme is strongly required. A position-based visual servo parallel system is presented for tracking target with high speed. A local Frenet frame is assigned to the sampling point of spatial trajectory. Position estimation is formed by the differential features of intrinsic geometry, and orientation estimation is formed by homogenous transformation. The time spent for searching and processing can be greatly reduced by shifting the window according to features location prediction. The simulation results have demonstrated the ability of the system to track spatial moving object.展开更多
Objective:To analyze the potential targets and mechanism of Xingxiao Pill for the treatment of lung cancer based on network pharmacology and molecular docking,providing reference for the research and clinical developm...Objective:To analyze the potential targets and mechanism of Xingxiao Pill for the treatment of lung cancer based on network pharmacology and molecular docking,providing reference for the research and clinical development of Xingxiao Pill.Method:The main chemical constituents and their targets of Xingxiao Pill was obtained through BATMAN-TCM database.Effective compounds were screened based on SwissADME and their targets were predicted by SwissTargetPrediction.Main lung cancer targets were obtained and integrated through GeneCards,OMIM(OMIM-Gene-Map-Retrieval),TTD and DRUGBANK databases.The intersection targets of Xingxiao Pill for lung cancer were obtained by Venn.The String platform was used to obtain the intersection targets.The core targets of Xingxiao Pill for lung cancer were screened by BisoGenet3.0.The Metasacpe database was used to analyze the biological processes and pathways involved in intersection targets.Cytoscape3.7.2 software was used to construct the"active ingredients of Xingxiao Pill-targets-pathways"network.Finally,Autodock was used for molecular docking verification.Results:The core active components of Xingxiao Pill for the treatment of lung cancer were morin,testosterone,17-Beta-Estradiol,alphaEstradiol,muscone,commiferin,commisterone,octyl acetate,etc.The primary pathways mainly included PI3K/Akt,MTOR,MAPK signaling pathway and MicroRNAs in cancer,etc.It has been proved that the combination of testosterone and estradiol with AKT1,SIRT7 and MDM2 was stable and could be used as reference.Conclusion:This study preliminarily revealed the mechanism of Xingxiao Pill on treating lung cancer with multiple components,targets and pathways,providing some ideas and references for clinical application and basic research in the future.展开更多
This paper studies the problem of using multiple unmanned air vehicles (UAVs) to search for moving targets with sensing capabilities. When multiple UAVs (multi-UAV) search for a number of moving targets in the mission...This paper studies the problem of using multiple unmanned air vehicles (UAVs) to search for moving targets with sensing capabilities. When multiple UAVs (multi-UAV) search for a number of moving targets in the mission area, the targets can intermittently obtain the position information of the UAVs from sensing devices, and take appropriate actions to increase the distance between themselves and the UAVs. Aiming at this problem, an environment model is established using the search map, and the updating method of the search map is extended by considering the sensing capabilities of the moving targets. A multi-UAV search path planning optimization model based on the model predictive control (MPC) method is constructed, and a hybrid particle swarm optimization algorithm with a crossover operator is designed to solve the model. Simulation results show that the proposed method can effectively improve the cooperative search efficiency and can find more targets per unit time compared with the coverage search method and the random search method.展开更多
By analyzing the outputs of the pre-industrial control runs of four models within phase 5 of the Coupled Model Intercomparison Project, the effects of initial sea temperature errors on the predictability of Indian Oce...By analyzing the outputs of the pre-industrial control runs of four models within phase 5 of the Coupled Model Intercomparison Project, the effects of initial sea temperature errors on the predictability of Indian Ocean Dipole events were identified. The initial errors cause a significant winter predictability barrier(WPB) or summer predictability barrier(SPB).The WPB is closely related with the initial errors in the tropical Indian Ocean, where two types of WPB-related initial errors display opposite patterns and a west–east dipole. In contrast, the occurrence of the SPB is mainly caused by initial errors in the tropical Pacific Ocean, where two types of SPB-related initial errors exhibit opposite patterns, with one pole in the subsurface western Pacific Ocean and the other in the upper eastern Pacific Ocean. Both of the WPB-related initial errors grow the fastest in winter, because the coupled system is at its weakest, and finally cause a significant WPB. The SPB-related initial errors develop into a La Ni ?na–like mode in the Pacific Ocean. The negative SST errors in the Pacific Ocean induce westerly wind anomalies in the Indian Ocean by modulating the Walker circulation in the tropical oceans. The westerly wind anomalies first cool the sea surface water in the eastern Indian Ocean. When the climatological wind direction reverses in summer, the wind anomalies in turn warm the sea surface water, finally causing a significant SPB. Therefore, in addition to the spatial patterns of the initial errors, the climatological conditions also play an important role in causing a significant predictability barrier.展开更多
Objective： To select the antisense oligonucleotides （asONs） which hybridize with the mRNA of vascular endothelial growth factor receptor2 （VEGFR2, also named as kinase insert domain-containing receptor：KDR） in a...Objective： To select the antisense oligonucleotides （asONs） which hybridize with the mRNA of vascular endothelial growth factor receptor2 （VEGFR2, also named as kinase insert domain-containing receptor：KDR） in an effective and specific way, and to investigate their antitumor activity in MCF-7 cells. Methods： The effective antisense oligonucleotides were chosen by computer prediction combined with oligonucleotide microarrays. The inhibition effect on MCF-7 cells proliferation was measured by MTT; and VEGFR2 expression was surveyed by Western-blotting and RT- PCR. Results： Using predicting secondary structure of VEGFR2 mRNA with RNA folding program, computer prediction designed 30 antisense oligonucleotide probes that were directed to local loose regions of RNA structure. In 30 probes, 4（4/30, 13.33%） antisense oligonucleotides showed strong hybridization intensities in oligonucleotide microarrays test and were selected. All these antisense oligonucleotides targeting 4 different sites of VEGFR2 mRNA lowered the level of VEGFR2 mRNA and protein present in MCF-7 cells. Proliferation of MCF-7 cells was reduced by 4 antisense oligonucleotides, respectively, in which asON1 was the most effective, with the inhibitory rates being 53.06% at 0.8 I.tmol/L. Conclusion： Combination of computer prediction with oligonucleotide microarrays is an effective way in selecting optimal antisense oligonucleotides. The antisense oligonucleotides showed good correlation between their antitumor activity and the hybridization intensities. The antisense oligonucleotides targeting VEGFR2 mRNA demonstrated prominent antitumor role in vitro.展开更多
A method for maneuvering target tracking based on in- ductive factor of posture information is proposed. A distinguished charactedstic of video frequency tracking is that it can capture the target posture changes from...A method for maneuvering target tracking based on in- ductive factor of posture information is proposed. A distinguished charactedstic of video frequency tracking is that it can capture the target posture changes from its picture easily, and the posture change means the motive model of the target will change. This information is very important to predict the trace of maneuvering target. Based on this idea, the quantified values of the target pos- ture change are obtained using Hough algorithm, this key values are defined as inductive factor of posture information, and then, the multiple grey trace predict models are established and the degrees of fuzzy subordinate values for every model are calculated with the inductive factor, the maneuvering extent values are determined by a new analysis method of stochastic differential equations for each model used to modify the degree of fuzzy subordinate values, these constitute the weighted values for every grey predict collec- tion. Finally, the synthesis predicting weighted result is obtained. The experimental results show that the new method is superior to the conventional algorithm.展开更多
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.
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.
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MicroRNAs （miRNAs） are a class of newly identified, small, non-coding RNAs that play vital roles in regulation. Based on miRNAs unique features of expression pattern, evolutionary conservation, secondary structure and genetic requirements for biogenesis, computational predication strategy is adopted to predicate the novel miRNAs. In this research, potential miRNAs and their targets in grapevine （Vitis vinifera） were predicted. We used previously known plant miRNAs against grapevine genome sequence databases to search for potential miRNAs. A total of 81 potential miRNAs were detected following a range of strict filtering criteria. Using these potential miRNA sequences, we could further blast the mRNA database to find the potential targets in this species. Comparative analysis of miRNAs in grapevine and other species reveals that miRNAs exhibit an evolutional conservation, the number and function of miRNAs must have significantly expanded during the evolution of land plants. Furthermore divergence made versatile functions of miRNAs feasible. Cluster of miRNAs likely represents an ancient expression mechanism. Predicted target genes include not only transcription factors but also genes implicated in floral development, signal transduction, diseases and stress response. Till now, little is known about experimental or computational identification of miRNA in grapevine species. Increased knowledge of the biological mechanisms of the grapevine will allow targeted approaches to increase the quality of fruit and reduce the impact of parasites together with stress, which could enable a sustainable, environmentally-sound, farming policv.
基金supported by the National Natural Science Foundation of China(31701561)。
文摘Edible plant derived exosome-like nanoparticles(ELNs)have been shown to have multiple nutraceutical functions.However,the diversity of plant materials makes the plant derived ELN study challenging.More efforts are still needed to explore the feasible isolation methods of edible plant derived ELNs and the possible roles of food-derived ELNs in improving human health.In this study,a size exclusion chromatography based method was compared with the traditional ultracentrifugation method to isolate blueberry derived ELNs(B-ELNs),and the miRNA profile of B-ELNs was analyzed by high-throughput sequencing.A total of 36 miRNAs were found to be enriched in B-ELNs compared with berry tissue,and their potential cross-kingdom human gene targets were further predicted.Results showed that size exclusion chromatography was effective for B-ELN isolation.The most abundant miRNAs in B-ELNs mainly belonged to the miR166 family and miR396 family.Target gene prediction indicated that B-ELNs could potentially regulate pathways related to the human digestive system,immune system and infectious diseases.
基金Supported by a grant from the National Natural Science Foundation of China(No.81402298).
文摘Objective The aim of the study was to summarize the diagnostic value of miR-21 as a biomarker in oral squamous cell carcinoma(OSCC)using a review of the literature and data from the cancer genome atlas(TCGA)database.Methods Data from TCGA database was sorted and analyzed by bioinformatics to determine the expression level of miR-21 in OSCC.Further,we searched for relevant articles in Embase,PubMed/Medline,Scopus,and Web of Science published before March 2021,extracted the data,and conducted quality assessment.The bivariate meta-analysis model with Stata 16.0 was used to analyze the diagnostic value of miR-21 for OSCC.Results A total of 304 related articles were identified,and seven were selected for meta-analysis.The diagnostic results after analysis were as follows:sensitivity 0.76[95%confidence interval(CI),0.57-0.88];specificity 0.77(95%CI,0.58-0.89);positive likelihood ratio 3.34(95%CI,1.58-7.08);negative likelihood ratio 0.31(95%CI,0.15-0.63);diagnostic odds ratio 10.75(95%CI,2.85-40.51);and area under the curve 0.83(95%CI,0.80-0.86).The Deeks’funnel chart showed that there was no potential bias(P=0.54).Prediction analysis of the potential target genes of miR-21 was performed via the biological website,and DAVID was used to cross target genes for gene ontology(GO)annotation function analysis.Conclusion The results showed that miR-21-3p and miR-21-5p were significantly more highly expressed in OSCC tissues than in normal tissues(P<0.05),and the results of the meta-analysis indicated that they could be used as potential biomarkers in the diagnosis of OSCC.In addition,58 potential target genes of miR-21 were significantly enriched in 28 GO annotation functional pathways,which provided a biological basis for further clinical diagnostic value research.
基金This project is supported by National Electric Power Corporation Foundation of China(No.SPKJ010-27).
文摘Target tracking is one typical application of visual servoing technology. It is still a difficult task to track high speed target with current visual servo system. The improvement of visual servoing scheme is strongly required. A position-based visual servo parallel system is presented for tracking target with high speed. A local Frenet frame is assigned to the sampling point of spatial trajectory. Position estimation is formed by the differential features of intrinsic geometry, and orientation estimation is formed by homogenous transformation. The time spent for searching and processing can be greatly reduced by shifting the window according to features location prediction. The simulation results have demonstrated the ability of the system to track spatial moving object.
基金Tongrentang Xingxiao Pill Horizontal Project of Zhou Tian(No.040101003063)National Key R&D Program of China(No.2018YFC1705102)Capital Health Development Scientific Research Special Project(No.2018-1-4201)。
文摘Objective:To analyze the potential targets and mechanism of Xingxiao Pill for the treatment of lung cancer based on network pharmacology and molecular docking,providing reference for the research and clinical development of Xingxiao Pill.Method:The main chemical constituents and their targets of Xingxiao Pill was obtained through BATMAN-TCM database.Effective compounds were screened based on SwissADME and their targets were predicted by SwissTargetPrediction.Main lung cancer targets were obtained and integrated through GeneCards,OMIM(OMIM-Gene-Map-Retrieval),TTD and DRUGBANK databases.The intersection targets of Xingxiao Pill for lung cancer were obtained by Venn.The String platform was used to obtain the intersection targets.The core targets of Xingxiao Pill for lung cancer were screened by BisoGenet3.0.The Metasacpe database was used to analyze the biological processes and pathways involved in intersection targets.Cytoscape3.7.2 software was used to construct the"active ingredients of Xingxiao Pill-targets-pathways"network.Finally,Autodock was used for molecular docking verification.Results:The core active components of Xingxiao Pill for the treatment of lung cancer were morin,testosterone,17-Beta-Estradiol,alphaEstradiol,muscone,commiferin,commisterone,octyl acetate,etc.The primary pathways mainly included PI3K/Akt,MTOR,MAPK signaling pathway and MicroRNAs in cancer,etc.It has been proved that the combination of testosterone and estradiol with AKT1,SIRT7 and MDM2 was stable and could be used as reference.Conclusion:This study preliminarily revealed the mechanism of Xingxiao Pill on treating lung cancer with multiple components,targets and pathways,providing some ideas and references for clinical application and basic research in the future.
基金supported by the National Natural Science Foundation of China(7140104871671059)the National Natural Science Funds of China for Innovative Research Groups(71521001)
文摘This paper studies the problem of using multiple unmanned air vehicles (UAVs) to search for moving targets with sensing capabilities. When multiple UAVs (multi-UAV) search for a number of moving targets in the mission area, the targets can intermittently obtain the position information of the UAVs from sensing devices, and take appropriate actions to increase the distance between themselves and the UAVs. Aiming at this problem, an environment model is established using the search map, and the updating method of the search map is extended by considering the sensing capabilities of the moving targets. A multi-UAV search path planning optimization model based on the model predictive control (MPC) method is constructed, and a hybrid particle swarm optimization algorithm with a crossover operator is designed to solve the model. Simulation results show that the proposed method can effectively improve the cooperative search efficiency and can find more targets per unit time compared with the coverage search method and the random search method.
基金jointly sponsored by the National Natural Science Foundation of China (Grant Nos. 41506032 and 41530961)the National Programme on Global Change and Air–Sea Interaction (Grant No. GASI-IPOVAI-06)
文摘By analyzing the outputs of the pre-industrial control runs of four models within phase 5 of the Coupled Model Intercomparison Project, the effects of initial sea temperature errors on the predictability of Indian Ocean Dipole events were identified. The initial errors cause a significant winter predictability barrier(WPB) or summer predictability barrier(SPB).The WPB is closely related with the initial errors in the tropical Indian Ocean, where two types of WPB-related initial errors display opposite patterns and a west–east dipole. In contrast, the occurrence of the SPB is mainly caused by initial errors in the tropical Pacific Ocean, where two types of SPB-related initial errors exhibit opposite patterns, with one pole in the subsurface western Pacific Ocean and the other in the upper eastern Pacific Ocean. Both of the WPB-related initial errors grow the fastest in winter, because the coupled system is at its weakest, and finally cause a significant WPB. The SPB-related initial errors develop into a La Ni ?na–like mode in the Pacific Ocean. The negative SST errors in the Pacific Ocean induce westerly wind anomalies in the Indian Ocean by modulating the Walker circulation in the tropical oceans. The westerly wind anomalies first cool the sea surface water in the eastern Indian Ocean. When the climatological wind direction reverses in summer, the wind anomalies in turn warm the sea surface water, finally causing a significant SPB. Therefore, in addition to the spatial patterns of the initial errors, the climatological conditions also play an important role in causing a significant predictability barrier.
基金This work was supported by the National Natural Sciences Foundation of China (No. 3017111) and National Project "863" (No. 2001AA234041)
文摘Objective： To select the antisense oligonucleotides （asONs） which hybridize with the mRNA of vascular endothelial growth factor receptor2 （VEGFR2, also named as kinase insert domain-containing receptor：KDR） in an effective and specific way, and to investigate their antitumor activity in MCF-7 cells. Methods： The effective antisense oligonucleotides were chosen by computer prediction combined with oligonucleotide microarrays. The inhibition effect on MCF-7 cells proliferation was measured by MTT; and VEGFR2 expression was surveyed by Western-blotting and RT- PCR. Results： Using predicting secondary structure of VEGFR2 mRNA with RNA folding program, computer prediction designed 30 antisense oligonucleotide probes that were directed to local loose regions of RNA structure. In 30 probes, 4（4/30, 13.33%） antisense oligonucleotides showed strong hybridization intensities in oligonucleotide microarrays test and were selected. All these antisense oligonucleotides targeting 4 different sites of VEGFR2 mRNA lowered the level of VEGFR2 mRNA and protein present in MCF-7 cells. Proliferation of MCF-7 cells was reduced by 4 antisense oligonucleotides, respectively, in which asON1 was the most effective, with the inhibitory rates being 53.06% at 0.8 I.tmol/L. Conclusion： Combination of computer prediction with oligonucleotide microarrays is an effective way in selecting optimal antisense oligonucleotides. The antisense oligonucleotides showed good correlation between their antitumor activity and the hybridization intensities. The antisense oligonucleotides targeting VEGFR2 mRNA demonstrated prominent antitumor role in vitro.
基金supported by the National Basic Research program of China(973 program)(613610303)
文摘A method for maneuvering target tracking based on in- ductive factor of posture information is proposed. A distinguished charactedstic of video frequency tracking is that it can capture the target posture changes from its picture easily, and the posture change means the motive model of the target will change. This information is very important to predict the trace of maneuvering target. Based on this idea, the quantified values of the target pos- ture change are obtained using Hough algorithm, this key values are defined as inductive factor of posture information, and then, the multiple grey trace predict models are established and the degrees of fuzzy subordinate values for every model are calculated with the inductive factor, the maneuvering extent values are determined by a new analysis method of stochastic differential equations for each model used to modify the degree of fuzzy subordinate values, these constitute the weighted values for every grey predict collec- tion. Finally, the synthesis predicting weighted result is obtained. The experimental results show that the new method is superior to the conventional algorithm.
