Spinal cord injury involves non-reversible damage to the central nervous system that is characterized by limited regenerative capacity and secondary inflammatory damage.The expression of the C-C motif chemokine ligand...Spinal cord injury involves non-reversible damage to the central nervous system that is characterized by limited regenerative capacity and secondary inflammatory damage.The expression of the C-C motif chemokine ligand 2/C-C motif chemokine receptor 2 axis exhibits significant differences before and after injury.Recent studies have revealed that the C-C motif chemokine ligand 2/C-C motif chemokine receptor 2 axis is closely associated with secondary inflammatory responses and the recruitment of immune cells following spinal cord injury,suggesting that this axis is a novel target and regulatory control point for treatment.This review comprehensively examines the therapeutic strategies targeting the C-C motif chemokine ligand 2/C-C motif chemokine receptor 2 axis,along with the regenerative and repair mechanisms linking the axis to spinal cord injury.Additionally,we summarize the upstream and downstream inflammatory signaling pathways associated with spinal cord injury and the C-C motif chemokine ligand 2/C-C motif chemokine receptor 2 axis.This review primarily elaborates on therapeutic strategies that target the C-C motif chemokine ligand 2/C-C motif chemokine receptor 2 axis and the latest progress of research on antagonistic drugs,along with the approaches used to exploit new therapeutic targets within the C-C motif chemokine ligand 2/C-C motif chemokine receptor 2 axis and the development of targeted drugs.Nevertheless,there are presently no clinical studies relating to spinal cord injury that are focusing on the C-C motif chemokine ligand 2/C-C motif chemokine receptor 2 axis.This review aims to provide new ideas and therapeutic strategies for the future treatment of spinal cord injury.展开更多
Objective Hepatocyte nuclear factor 4-alpha(HNF4A)is a critical transcription factor in the liver and pancreas.Dysfunctions of HNF4A lead to maturity onset diabetes of the young 1(MODY1).Notably,MODY1 patients with HN...Objective Hepatocyte nuclear factor 4-alpha(HNF4A)is a critical transcription factor in the liver and pancreas.Dysfunctions of HNF4A lead to maturity onset diabetes of the young 1(MODY1).Notably,MODY1 patients with HNF4A pathogenic mutations exhibit decreased responses to arginine and reduced plasma triglyceride levels,but the mechanisms remain unclear.This study aims to investigate the potential target genes transcriptionally regulated by HNF4A and explore its role in these metabolic pathways.Methods A stable 293T cell line expressing the HNF1A reporter was overexpressed with HNF4A.RNA sequencing(RNA-seq)was performed to analyze transcriptional differences.Transcription factor binding site prediction was then conducted to identify HNF4A binding motifs in the promoter regions of relevant target genes.Results RNA-seq results revealed a significant upregulation of transmembrane 4 L six family member 5(TM4SF5)mRNA in HNF4A-overexpressing cells.Transcription factor binding predictions suggested the presence of five potential HNF4A binding motifs in the TM4SF5 promoter.Finally,we confirmed that the DR1 site in the-57 to-48 region of the TM4SF5 promoter is the key binding motif for HNF4A.Conclusion This study identified TM4SF5 as a target gene of HNF4A and determined the key binding motif involved in its regulation.Given the role of TM4SF5 as an arginine sensor in mTOR signaling activation and triglyceride secretion,which closely aligns with phenotypes observed in MODY1 patients,our findings provide novel insights into the possible mechanisms by which HNF4A regulates triglyceride secretion in the liver and arginine-stimulated insulin secretion in the pancreas.展开更多
Temporal link prediction has attracted increasingattention in various fields of complex networkanalysis, which has important value in the theory andapplication. However, many existing similarity-basedtemporal link pre...Temporal link prediction has attracted increasingattention in various fields of complex networkanalysis, which has important value in the theory andapplication. However, many existing similarity-basedtemporal link prediction methods, only analyze the influenceof the edge or the point, ignoring the influenceof the structures in the network. In this paper, boththe spatial-domain model and the time-domain modelare taken into consideration, and a novel temporal linkprediction method based on the evolution of motif features(TLP-EMF) is proposed. Firstly, a new generalizedsemi-triangle motif is proposed. And the multilevelcontribution of motif point (MP) and motif edge(ME) are described, which is based on the relationshipbetween the full-triangle and the semi-triangle. Secondly,the motif point density (MPD) index and themotif edge density (MED) index are also proposed ina similar way. Thirdly, a novel motif character fusionindex (MCF) and a novel motif character density index(MCD) are proposed for the spatial-informationprocessing. Furthermore, a novel forecasting model ofthe adaptive exponential weighted moving (AEWM)method is proposed for the time-domain evolution. Ituses the one-order exponential function to fit the effectof time evolution and uses the global attenuationparameter to adaptively quantify the changes in exponentialparameters. Experiments on three real social network data sets show that the proposed method caneffectively improve the accuracy of temporal link prediction.展开更多
Flammable gas leakage in a semi-enclosed scenario can lead to catastrophic consequences,such as vapor cloud explosions.To reduce casualties and environmental damage,predicting the consequences based on the initial con...Flammable gas leakage in a semi-enclosed scenario can lead to catastrophic consequences,such as vapor cloud explosions.To reduce casualties and environmental damage,predicting the consequences based on the initial concentration time series monitored by sensors is of paramount importance.This paper proposes a consequence prediction model based on deep learning using variable-length concentration time series.Incomplete concentration values are padded and then passed through a masking layer,enabling the network to focus exclusively on valid data.The temporal correlations are extracted using a long short-term memory(LSTM)network,and the final prediction results are obtained by passing these features into a feedforward neural network(FNN).Computational fluid dynamics(CFD)software was used to simulate the leakage of hydrogen-mixed natural gas.Experiments were carried out for nine distinct prediction targets,derived from combinations of the mass and centroid coordinates of vapor clouds formed by various gases.These prediction targets were modeled using both fixed-length and variable-length input sequences.The high accuracy of the experimental results validates the effectiveness of the proposed method.展开更多
BACKGROUND The diagnosis of inflammatory bowel disease(IBD)involves clinical,endoscopic,and radiologic evaluation.Endoscopic procedures,particularly in pediatrics,require general anesthesia and carry potential risks.A...BACKGROUND The diagnosis of inflammatory bowel disease(IBD)involves clinical,endoscopic,and radiologic evaluation.Endoscopic procedures,particularly in pediatrics,require general anesthesia and carry potential risks.AIM To investigate whether serum biomarkers can differentiate between pediatric patients with and without IBD.Secondary objectives included identifying biomarkers that distinguish Crohn’s disease(CD)from ulcerative colitis(UC)and assessing their predictive value for progression to biologic therapy.METHODS Pediatric patients undergoing diagnostic colonoscopy at British Columbia Children’s Hospital between December 2017 and June 2022 were enrolled.Blood samples were collected at colonoscopy,and demographic clinical data,laboratory,and histopathologic evaluation were obtained.An exploratory screen of 50 biomarkers was undertaken in a subset of patients(54 IBD,41 controls)using LegendplexTM flow cytometry kits to identify candidates.A refined panel of 12 serum biomarkers was subsequently selected and a supervised learning model was developed to classify patients.RESULTS The study included 246 pediatric patients,who had a median age of 13.03 years and were 37.4%female(103 CD,52 UC,91 controls).In univariate analyses,C-X-C motif chemokine ligand 9(CXCL9)was the only biomarker significantly elevated in IBD vs controls(P<0.001).A multivariable model achieved an area under the receiver operating characteristic of 0.861 for distinguishing IBD from controls.Interleukin 8(IL-8)emerged as a key biomarker alongside CXCL9 and IL-22 in the model.The random forest model identified CXCL9 with the greatest diagnostic accuracy(area under the curve[AUC]=0.81),followed by IL8 and IL22(AUC=0.737 and 0.68,respectively).CXCL9 and IL-18 showed higher levels in CD(P=0.016),whereas CXCL1 levels predicted progression to biologic therapy within 1 year(P=0.039).However,the model did not effectively predict disease subclassification or progression to biologic therapy.CONCLUSION Serum biomarkers,particularly CXCL9,IL-8,and IL-22,can aid in the diagnosis of pediatric IBD.CXCL9 and IL18 were found to be significant predictors of CD,and CXCL1 differed between patients requiring biologic therapy vs those who did not.展开更多
The integrated systems of unmanned surface vehicles(USVs) and remotely operated vehicles(ROVs) have been extensively applied in marine exploration and seabed coverage. However, the simultaneous navigation of USV-ROV s...The integrated systems of unmanned surface vehicles(USVs) and remotely operated vehicles(ROVs) have been extensively applied in marine exploration and seabed coverage. However, the simultaneous navigation of USV-ROV systems is frequently limited by strong disturbances induced by waves or currents. This paper develops a novel rigidflexible coupling multibody dynamic model that incorporates disturbances of variable-length marine cables with geometrically nonlinear motion. A hybrid Lagrangian-Eulerian absolute nodal coordinate formulation(ANCF) element is developed to accurately model subsea cables which undergo significant overall motion, substantial deformation,and mass flow during the deployment of underwater equipment. Furthermore, the governing equations of the coupled USV-umbilical-ROV system are derived, considering wave-induced forces and current disturbances. A numerical solver based on the Newmark-beta method is proposed, along with an adaptive meshing technique near the release point. After validating three experimental cases, the cable disturbances at both the USV and ROV ends—caused by ocean currents, heave motion, and simultaneous navigation—are comprehensively compared and evaluated. Finally,it is demonstrated that a PD controller with disturbance compensation can enhance the simultaneous navigation performance of USV-ROV systems.展开更多
Discoidin domain receptors(DDRs)are single-pass transmembrane proteins belonging to receptor tyrosine kinases(RTKs)family,which are activated by collagen ligands with unusual slow,sustained kinetics,distinguishing the...Discoidin domain receptors(DDRs)are single-pass transmembrane proteins belonging to receptor tyrosine kinases(RTKs)family,which are activated by collagen ligands with unusual slow,sustained kinetics,distinguishing them from canonical RTKs.While DDRs play critical roles in cell adhesion,differentiation,and cancer progression,their activation mechanisms remain partly understood.Here,we investigated the transmembrane domains(TMDs)of DDR1 and DDR2 to elucidate their interaction dynamics in membrane.Using bacterial adenylate cyclase two-hybrid(BACTH)assays,we demonstrated robust homotypic interactions and even stronger heterotypic associations between DDRTMDs.NMR spectroscopy of DDR1TMD and DDR2TMD reconstituted in lipid bilayer-mimetic bicelles showed obvious chemical shift alterations,further validating the stability of their heterocomplex formation.Systematic mutagenesis identified leucine zipper motifs rather than GXXXA motifs mediated both homo-and hetero-associations of DDR1TMD and DDR2TMD.These findings demonstrated the TMD as a critical mediator of DDRs oligomerization and revealed their interaction patterns within membrane.Our study advances the understanding of DDR signaling regulation and highlights transmembrane domain interactions as potential targets for modulating DDR-related pathologies.展开更多
文摘随着智能交通系统(Intelligent Transportation Systems, ITS)的发展,城市交通车辆轨迹预测技术在交通管理和智能导航中具有重要的应用价值。在城市交通中,车辆出行轨迹受路网约束,将路网引入轨迹预测模型中有助于提高预测精度,但目前已有的基于路网的轨迹预测模型尚未充分利用路网中的高阶结构。因此,本文提出了一种基于路网motif图注意力网络的轨迹预测模型(Graph Attention Network for Trajectory Prediction based on Road Network Motifs, GRAM),该模型依靠真实路网中的motif来挖掘路网的高阶结构属性。GRAM基于路网motif构建交通流图,并利用图注意力网络从基于motif的交通流图和局部个体轨迹图中学习特征,同时通过结合不同motif对同一位置的影响训练模型,以获得最优比例。在3个真实轨迹数据集(波尔图、成都、北京)上的实验结果表明,本文的GRAM展示出了更好的性能。
基金supported by the National Natural Science Foundation of China(Key Program),No.11932013the National Natural Science Foundation of China(General Program),No.82272255+2 种基金Armed Police Force High-Level Science and Technology Personnel ProjectThe Armed Police Force Focuses on Supporting Scientific and Technological Innovation TeamsKey Project of Tianjin Science and Technology Plan,No.20JCZDJC00570(all to XC)。
文摘Spinal cord injury involves non-reversible damage to the central nervous system that is characterized by limited regenerative capacity and secondary inflammatory damage.The expression of the C-C motif chemokine ligand 2/C-C motif chemokine receptor 2 axis exhibits significant differences before and after injury.Recent studies have revealed that the C-C motif chemokine ligand 2/C-C motif chemokine receptor 2 axis is closely associated with secondary inflammatory responses and the recruitment of immune cells following spinal cord injury,suggesting that this axis is a novel target and regulatory control point for treatment.This review comprehensively examines the therapeutic strategies targeting the C-C motif chemokine ligand 2/C-C motif chemokine receptor 2 axis,along with the regenerative and repair mechanisms linking the axis to spinal cord injury.Additionally,we summarize the upstream and downstream inflammatory signaling pathways associated with spinal cord injury and the C-C motif chemokine ligand 2/C-C motif chemokine receptor 2 axis.This review primarily elaborates on therapeutic strategies that target the C-C motif chemokine ligand 2/C-C motif chemokine receptor 2 axis and the latest progress of research on antagonistic drugs,along with the approaches used to exploit new therapeutic targets within the C-C motif chemokine ligand 2/C-C motif chemokine receptor 2 axis and the development of targeted drugs.Nevertheless,there are presently no clinical studies relating to spinal cord injury that are focusing on the C-C motif chemokine ligand 2/C-C motif chemokine receptor 2 axis.This review aims to provide new ideas and therapeutic strategies for the future treatment of spinal cord injury.
文摘Objective Hepatocyte nuclear factor 4-alpha(HNF4A)is a critical transcription factor in the liver and pancreas.Dysfunctions of HNF4A lead to maturity onset diabetes of the young 1(MODY1).Notably,MODY1 patients with HNF4A pathogenic mutations exhibit decreased responses to arginine and reduced plasma triglyceride levels,but the mechanisms remain unclear.This study aims to investigate the potential target genes transcriptionally regulated by HNF4A and explore its role in these metabolic pathways.Methods A stable 293T cell line expressing the HNF1A reporter was overexpressed with HNF4A.RNA sequencing(RNA-seq)was performed to analyze transcriptional differences.Transcription factor binding site prediction was then conducted to identify HNF4A binding motifs in the promoter regions of relevant target genes.Results RNA-seq results revealed a significant upregulation of transmembrane 4 L six family member 5(TM4SF5)mRNA in HNF4A-overexpressing cells.Transcription factor binding predictions suggested the presence of five potential HNF4A binding motifs in the TM4SF5 promoter.Finally,we confirmed that the DR1 site in the-57 to-48 region of the TM4SF5 promoter is the key binding motif for HNF4A.Conclusion This study identified TM4SF5 as a target gene of HNF4A and determined the key binding motif involved in its regulation.Given the role of TM4SF5 as an arginine sensor in mTOR signaling activation and triglyceride secretion,which closely aligns with phenotypes observed in MODY1 patients,our findings provide novel insights into the possible mechanisms by which HNF4A regulates triglyceride secretion in the liver and arginine-stimulated insulin secretion in the pancreas.
文摘Temporal link prediction has attracted increasingattention in various fields of complex networkanalysis, which has important value in the theory andapplication. However, many existing similarity-basedtemporal link prediction methods, only analyze the influenceof the edge or the point, ignoring the influenceof the structures in the network. In this paper, boththe spatial-domain model and the time-domain modelare taken into consideration, and a novel temporal linkprediction method based on the evolution of motif features(TLP-EMF) is proposed. Firstly, a new generalizedsemi-triangle motif is proposed. And the multilevelcontribution of motif point (MP) and motif edge(ME) are described, which is based on the relationshipbetween the full-triangle and the semi-triangle. Secondly,the motif point density (MPD) index and themotif edge density (MED) index are also proposed ina similar way. Thirdly, a novel motif character fusionindex (MCF) and a novel motif character density index(MCD) are proposed for the spatial-informationprocessing. Furthermore, a novel forecasting model ofthe adaptive exponential weighted moving (AEWM)method is proposed for the time-domain evolution. Ituses the one-order exponential function to fit the effectof time evolution and uses the global attenuationparameter to adaptively quantify the changes in exponentialparameters. Experiments on three real social network data sets show that the proposed method caneffectively improve the accuracy of temporal link prediction.
基金supported by the National Key Research and Development Program of China(2022YFB3305900)National Natural Science Foundation of China(62373153,62173147)+1 种基金the Programme of Introducing Talents of Discipline to Universities(the 111 Project)under Grant B17017Fundamental Research Funds for the Central Universities(222202517006)。
文摘Flammable gas leakage in a semi-enclosed scenario can lead to catastrophic consequences,such as vapor cloud explosions.To reduce casualties and environmental damage,predicting the consequences based on the initial concentration time series monitored by sensors is of paramount importance.This paper proposes a consequence prediction model based on deep learning using variable-length concentration time series.Incomplete concentration values are padded and then passed through a masking layer,enabling the network to focus exclusively on valid data.The temporal correlations are extracted using a long short-term memory(LSTM)network,and the final prediction results are obtained by passing these features into a feedforward neural network(FNN).Computational fluid dynamics(CFD)software was used to simulate the leakage of hydrogen-mixed natural gas.Experiments were carried out for nine distinct prediction targets,derived from combinations of the mass and centroid coordinates of vapor clouds formed by various gases.These prediction targets were modeled using both fixed-length and variable-length input sequences.The high accuracy of the experimental results validates the effectiveness of the proposed method.
基金Supported by the Lutsky Family Foundation and AdMare Bioinnovations(previously known as the Genome BC CDRD Development Fund).
文摘BACKGROUND The diagnosis of inflammatory bowel disease(IBD)involves clinical,endoscopic,and radiologic evaluation.Endoscopic procedures,particularly in pediatrics,require general anesthesia and carry potential risks.AIM To investigate whether serum biomarkers can differentiate between pediatric patients with and without IBD.Secondary objectives included identifying biomarkers that distinguish Crohn’s disease(CD)from ulcerative colitis(UC)and assessing their predictive value for progression to biologic therapy.METHODS Pediatric patients undergoing diagnostic colonoscopy at British Columbia Children’s Hospital between December 2017 and June 2022 were enrolled.Blood samples were collected at colonoscopy,and demographic clinical data,laboratory,and histopathologic evaluation were obtained.An exploratory screen of 50 biomarkers was undertaken in a subset of patients(54 IBD,41 controls)using LegendplexTM flow cytometry kits to identify candidates.A refined panel of 12 serum biomarkers was subsequently selected and a supervised learning model was developed to classify patients.RESULTS The study included 246 pediatric patients,who had a median age of 13.03 years and were 37.4%female(103 CD,52 UC,91 controls).In univariate analyses,C-X-C motif chemokine ligand 9(CXCL9)was the only biomarker significantly elevated in IBD vs controls(P<0.001).A multivariable model achieved an area under the receiver operating characteristic of 0.861 for distinguishing IBD from controls.Interleukin 8(IL-8)emerged as a key biomarker alongside CXCL9 and IL-22 in the model.The random forest model identified CXCL9 with the greatest diagnostic accuracy(area under the curve[AUC]=0.81),followed by IL8 and IL22(AUC=0.737 and 0.68,respectively).CXCL9 and IL-18 showed higher levels in CD(P=0.016),whereas CXCL1 levels predicted progression to biologic therapy within 1 year(P=0.039).However,the model did not effectively predict disease subclassification or progression to biologic therapy.CONCLUSION Serum biomarkers,particularly CXCL9,IL-8,and IL-22,can aid in the diagnosis of pediatric IBD.CXCL9 and IL18 were found to be significant predictors of CD,and CXCL1 differed between patients requiring biologic therapy vs those who did not.
基金financially supported in part by the General Program of the National Natural Science Foundation of China (Grant No.12272221)the State Key Laboratory of Ocean Engineering (Shanghai Jiao Tong University)(Grant No. GKZD010087)。
文摘The integrated systems of unmanned surface vehicles(USVs) and remotely operated vehicles(ROVs) have been extensively applied in marine exploration and seabed coverage. However, the simultaneous navigation of USV-ROV systems is frequently limited by strong disturbances induced by waves or currents. This paper develops a novel rigidflexible coupling multibody dynamic model that incorporates disturbances of variable-length marine cables with geometrically nonlinear motion. A hybrid Lagrangian-Eulerian absolute nodal coordinate formulation(ANCF) element is developed to accurately model subsea cables which undergo significant overall motion, substantial deformation,and mass flow during the deployment of underwater equipment. Furthermore, the governing equations of the coupled USV-umbilical-ROV system are derived, considering wave-induced forces and current disturbances. A numerical solver based on the Newmark-beta method is proposed, along with an adaptive meshing technique near the release point. After validating three experimental cases, the cable disturbances at both the USV and ROV ends—caused by ocean currents, heave motion, and simultaneous navigation—are comprehensively compared and evaluated. Finally,it is demonstrated that a PD controller with disturbance compensation can enhance the simultaneous navigation performance of USV-ROV systems.
基金supported by the National Natural Science Foundation of China(32471354 to T.C.and 82260400 to J.L)Natural Science Foundation of Hainan Province(No.822RC703 to J.L)。
文摘Discoidin domain receptors(DDRs)are single-pass transmembrane proteins belonging to receptor tyrosine kinases(RTKs)family,which are activated by collagen ligands with unusual slow,sustained kinetics,distinguishing them from canonical RTKs.While DDRs play critical roles in cell adhesion,differentiation,and cancer progression,their activation mechanisms remain partly understood.Here,we investigated the transmembrane domains(TMDs)of DDR1 and DDR2 to elucidate their interaction dynamics in membrane.Using bacterial adenylate cyclase two-hybrid(BACTH)assays,we demonstrated robust homotypic interactions and even stronger heterotypic associations between DDRTMDs.NMR spectroscopy of DDR1TMD and DDR2TMD reconstituted in lipid bilayer-mimetic bicelles showed obvious chemical shift alterations,further validating the stability of their heterocomplex formation.Systematic mutagenesis identified leucine zipper motifs rather than GXXXA motifs mediated both homo-and hetero-associations of DDR1TMD and DDR2TMD.These findings demonstrated the TMD as a critical mediator of DDRs oligomerization and revealed their interaction patterns within membrane.Our study advances the understanding of DDR signaling regulation and highlights transmembrane domain interactions as potential targets for modulating DDR-related pathologies.
