Endogenous metabolites play key functions in many important physiological and biochemical processes.The comprehensive in situ detection and direct imaging of metabolites in bio-tissues by matrix-assisted laser desorpt...Endogenous metabolites play key functions in many important physiological and biochemical processes.The comprehensive in situ detection and direct imaging of metabolites in bio-tissues by matrix-assisted laser desorption/ionization mass spectrometry imaging(MALDI-MSI)is very important for understanding complex and diverse biological processes and has become an essential aspect of spatial omics.In this work,4-aminoazobenzene(AAB)was successfully screened and optimized as a new negative ion(-)MALDI matrix to enhance the in situ detection and imaging of metabolites in tissues using MALDIMSI.Obviously,AAB exhibited superior properties in terms of ultraviolet absorption,background ion interference,matrix morphology,and metabolite ionization efficiency.AAB was used for in situ detection and imaging of metabolites in rat brain and germinating Chinese yew seed tissue sections,where 264and 339 metabolite ion signals were successfully detected and imaged using(-)MALDI-MS,respectively.In addition,high-resolution imaging of mouse eyeball section using MALDI-tims TOF MSI with spatial resolution of up to 10μm was successfully carried out,showing that AAB is an efficient(-)MALDI matrix for capturing high-resolution images of metabolites in biological tissue sections.展开更多
Collective motion is one of the most fascinating phenomena and mainly caused by the interactions between individuals. Physical-barriers, as the particular facilities which divide the crowd into different lanes, greatl...Collective motion is one of the most fascinating phenomena and mainly caused by the interactions between individuals. Physical-barriers, as the particular facilities which divide the crowd into different lanes, greatly affect the measurement of such interactions. In this paper we propose the physical-barrier detection based collective motion analysis (PDCMA) approach. The main idea is that the interaction between spatially adjacent pedestrians actually does not exist if they are separated by the physical-barrier. Firstly, the physical-barriers are extracted by two-stage clustering. The scene is automatically divided into several motion regions. Secondly, local region collectiveness is calculated to represent the interactions between pedestrians in each region. Finally, extensive evaluations use the three typical methods, i.e., the PDCMA, the Collectiveness, and the average normalized Velocity, to show the efficiency and efficacy of our approach in the scenes with and without physical barriers. Moreover, several escalator scenes are selected as the typical physical-barrier test scenes to demonstrate the performance of our approach. Compared with the current collective motion analysis methods, our approach better adapts to the scenes with physical barriers.展开更多
基金supported by the National Natural Science Foundation of China(Nos.31770384 and 21605164)the Youth Academic Team Project of MUC(No.10301-02200301)+1 种基金the Huayi Technology Innovation Center for Research Resources(No.HTIC P01RR2017001A)the Key Laboratory Construction Funds of State Ethnic Affairs Commission of China(No.10301-02200303)。
文摘Endogenous metabolites play key functions in many important physiological and biochemical processes.The comprehensive in situ detection and direct imaging of metabolites in bio-tissues by matrix-assisted laser desorption/ionization mass spectrometry imaging(MALDI-MSI)is very important for understanding complex and diverse biological processes and has become an essential aspect of spatial omics.In this work,4-aminoazobenzene(AAB)was successfully screened and optimized as a new negative ion(-)MALDI matrix to enhance the in situ detection and imaging of metabolites in tissues using MALDIMSI.Obviously,AAB exhibited superior properties in terms of ultraviolet absorption,background ion interference,matrix morphology,and metabolite ionization efficiency.AAB was used for in situ detection and imaging of metabolites in rat brain and germinating Chinese yew seed tissue sections,where 264and 339 metabolite ion signals were successfully detected and imaged using(-)MALDI-MS,respectively.In addition,high-resolution imaging of mouse eyeball section using MALDI-tims TOF MSI with spatial resolution of up to 10μm was successfully carried out,showing that AAB is an efficient(-)MALDI matrix for capturing high-resolution images of metabolites in biological tissue sections.
基金the National Key Research and Development Program of China (2016YFA0502300)the National Natural Science Foundation of China (Grant No. 61602175)+3 种基金Shanghai Municipal Commission of Economy and Informatization (150809)the Open Research Funding Program of KLGIS (KLGIS2015A05) and BUAA (BUAAVR- 15KF-03)the Fundamental Research Funds for the Central Universities (222201514331)Green Manufacturing System Integration Project of Ministry of Industry and Technology of China (9908000006).
文摘Collective motion is one of the most fascinating phenomena and mainly caused by the interactions between individuals. Physical-barriers, as the particular facilities which divide the crowd into different lanes, greatly affect the measurement of such interactions. In this paper we propose the physical-barrier detection based collective motion analysis (PDCMA) approach. The main idea is that the interaction between spatially adjacent pedestrians actually does not exist if they are separated by the physical-barrier. Firstly, the physical-barriers are extracted by two-stage clustering. The scene is automatically divided into several motion regions. Secondly, local region collectiveness is calculated to represent the interactions between pedestrians in each region. Finally, extensive evaluations use the three typical methods, i.e., the PDCMA, the Collectiveness, and the average normalized Velocity, to show the efficiency and efficacy of our approach in the scenes with and without physical barriers. Moreover, several escalator scenes are selected as the typical physical-barrier test scenes to demonstrate the performance of our approach. Compared with the current collective motion analysis methods, our approach better adapts to the scenes with physical barriers.
