Central nervous system diseases commonly occur with the destruction of the blood-brain barrier.As a primary cause of morbidity and mortality,stroke remains unpredictable and lacks cellular biomarkers that accurately q...Central nervous system diseases commonly occur with the destruction of the blood-brain barrier.As a primary cause of morbidity and mortality,stroke remains unpredictable and lacks cellular biomarkers that accurately quantify its occurrence and development.Here,we identify NeuN^(+)/CD45^(−)/DAPI^(+)phenotype nonblood cells in the peripheral blood of mice subjected to middle cerebral artery occlusion(MCAO)and stroke patients.Since NeuN is a specific marker of neural cells,we term these newly identified cells as circulating neural cells(CNCs).We find that the enumeration of CNCs in the blood is significantly associated with the severity of brain damage in MCAO mice(p<0:05).Meanwhile,the number of CNCs is significantly higher in stroke patients than in negative subjects(p<0:0001).These findings suggest that the amount of CNCs in circulation may serve as a clinical indicator for the real-time prognosis and progression monitor of the occurrence and development of ischemic stroke and other nervous system disease.展开更多
Visualizing intrinsic structures of high-dimensional data is an essential task in data analysis.Over the past decades,a large number of methods have been proposed.Among all solutions,one promising way for enabling eff...Visualizing intrinsic structures of high-dimensional data is an essential task in data analysis.Over the past decades,a large number of methods have been proposed.Among all solutions,one promising way for enabling effective visual exploration is to construct a k-nearest neighbor(KNN)graph and visualize the graph in a low-dimensional space.Yet,state-of-the-art methods such as the LargeVis still suffer from two main problems when applied to large-scale data:(1)they may produce unappealing visualizations due to the non-convexity of the cost function;(2)visualizing the KNN graph is still time-consuming.In this work,we propose a novel visualization algorithm that leverages a multilevel representation to achieve a high-quality graph layout and employs a cluster-based approximation scheme to accelerate the KNN graph layout.Experiments on various large-scale datasets indicate that our approach achieves a speedup by a factor of five for KNN graph visualization compared to LargeVis and yields aesthetically pleasing visualization results.展开更多
[目的]探究白细胞介素-1β对牙周膜细胞向破骨细胞分化的影响。[方法]选取需要牙齿矫正患者的第一前磨牙和第二前磨牙,取牙周膜组织培养后按照1×10^(8)/mL的密度,对照组向培养基中加入0μg/L白细胞介素-1β或实验组向培养基中加入2...[目的]探究白细胞介素-1β对牙周膜细胞向破骨细胞分化的影响。[方法]选取需要牙齿矫正患者的第一前磨牙和第二前磨牙,取牙周膜组织培养后按照1×10^(8)/mL的密度,对照组向培养基中加入0μg/L白细胞介素-1β或实验组向培养基中加入20μg/L白细胞介素-1β,对比分析两组牙周膜细胞体外增殖能力和TRAP阳性细胞数量;RT-PCR法分别测定牙周膜细胞OPG、RANKL、ODF、OCIF、CTSK、MMP-9和CAⅡmRNA表达水平,Western Blot法测定OPG和RANKL蛋白表达水平。[结果]与培养第1 d相比,培养第4、7、11、14和21 d的各组牙周膜细胞体外增殖能力增加(P<0.05),其中对照组细胞体外增殖能力低于实验组(21 d:0.45±0.03 vs 1.68±0.37)(P<0.05)。与培养第1 d相比,培养第4 d、7 d、11 d、14 d和21 d的各组牙周膜细胞TRAP阳性细胞数量增加(P<0.05),且在第11 d达到最大值(40.36±4.52%),随后出现下降趋势,其中对照组细胞TRAP阳性细胞数量低于实验组(P<0.05)。实验组牙周膜细胞OPG mRNA表达低于对照组(0.42±0.12 vs 1.14±0.19),而RANKL mRNA表达高于对照组(4.65±0.11 vs 2.31±0.27)(P<0.05)。实验组牙周膜细胞OPG蛋白表达低于对照组(0.78±0.17 vs 1.43±0.14),而RANKL蛋白表达高于对照组(2.92±0.17 vs 1.21±0.08)(P<0.05)。实验组牙周膜细胞ODF和OCIF mRNA表达高于对照组(ODF:2.56±0.85 vs 0.71±0.16;OCIF:4.04±0.77 vs 0.99±0.23)(P<0.05)(P<0.05)。实验组牙周膜细胞CTSK、MMP-9、CAⅡmRNA表达高于对照组(CTSK:2.57±0.23 vs 1.05±0.01;MMP-9:2.34±0.18 vs 1.04±0.03;CAII:3.79±0.12 vs 1.06±0.03)(P<0.05)。[结论]白细胞介素-1β可有效诱导牙周膜细胞分化为有骨吸收能力的破骨细胞,其机制是通过上调RANKL表达和下调骨保护素表达来介导。展开更多
基金supported by the National Natural Science Foundation of China(Nos.81871448,81701353,and 82073380)the Science and Technology commission of Shanghai Municipality(2017SHZDZX01)+1 种基金the MedicalEngineering Cross Foundation of Shanghai Jiao Tong University(Nos.19X190020154,YG2016MS60,ZH2018QNA54,ZH2018QNA49,and YG2021QN129)the Shanghai Sailing Program(19YF1446900).
文摘Central nervous system diseases commonly occur with the destruction of the blood-brain barrier.As a primary cause of morbidity and mortality,stroke remains unpredictable and lacks cellular biomarkers that accurately quantify its occurrence and development.Here,we identify NeuN^(+)/CD45^(−)/DAPI^(+)phenotype nonblood cells in the peripheral blood of mice subjected to middle cerebral artery occlusion(MCAO)and stroke patients.Since NeuN is a specific marker of neural cells,we term these newly identified cells as circulating neural cells(CNCs).We find that the enumeration of CNCs in the blood is significantly associated with the severity of brain damage in MCAO mice(p<0:05).Meanwhile,the number of CNCs is significantly higher in stroke patients than in negative subjects(p<0:0001).These findings suggest that the amount of CNCs in circulation may serve as a clinical indicator for the real-time prognosis and progression monitor of the occurrence and development of ischemic stroke and other nervous system disease.
文摘Visualizing intrinsic structures of high-dimensional data is an essential task in data analysis.Over the past decades,a large number of methods have been proposed.Among all solutions,one promising way for enabling effective visual exploration is to construct a k-nearest neighbor(KNN)graph and visualize the graph in a low-dimensional space.Yet,state-of-the-art methods such as the LargeVis still suffer from two main problems when applied to large-scale data:(1)they may produce unappealing visualizations due to the non-convexity of the cost function;(2)visualizing the KNN graph is still time-consuming.In this work,we propose a novel visualization algorithm that leverages a multilevel representation to achieve a high-quality graph layout and employs a cluster-based approximation scheme to accelerate the KNN graph layout.Experiments on various large-scale datasets indicate that our approach achieves a speedup by a factor of five for KNN graph visualization compared to LargeVis and yields aesthetically pleasing visualization results.
文摘[目的]探究白细胞介素-1β对牙周膜细胞向破骨细胞分化的影响。[方法]选取需要牙齿矫正患者的第一前磨牙和第二前磨牙,取牙周膜组织培养后按照1×10^(8)/mL的密度,对照组向培养基中加入0μg/L白细胞介素-1β或实验组向培养基中加入20μg/L白细胞介素-1β,对比分析两组牙周膜细胞体外增殖能力和TRAP阳性细胞数量;RT-PCR法分别测定牙周膜细胞OPG、RANKL、ODF、OCIF、CTSK、MMP-9和CAⅡmRNA表达水平,Western Blot法测定OPG和RANKL蛋白表达水平。[结果]与培养第1 d相比,培养第4、7、11、14和21 d的各组牙周膜细胞体外增殖能力增加(P<0.05),其中对照组细胞体外增殖能力低于实验组(21 d:0.45±0.03 vs 1.68±0.37)(P<0.05)。与培养第1 d相比,培养第4 d、7 d、11 d、14 d和21 d的各组牙周膜细胞TRAP阳性细胞数量增加(P<0.05),且在第11 d达到最大值(40.36±4.52%),随后出现下降趋势,其中对照组细胞TRAP阳性细胞数量低于实验组(P<0.05)。实验组牙周膜细胞OPG mRNA表达低于对照组(0.42±0.12 vs 1.14±0.19),而RANKL mRNA表达高于对照组(4.65±0.11 vs 2.31±0.27)(P<0.05)。实验组牙周膜细胞OPG蛋白表达低于对照组(0.78±0.17 vs 1.43±0.14),而RANKL蛋白表达高于对照组(2.92±0.17 vs 1.21±0.08)(P<0.05)。实验组牙周膜细胞ODF和OCIF mRNA表达高于对照组(ODF:2.56±0.85 vs 0.71±0.16;OCIF:4.04±0.77 vs 0.99±0.23)(P<0.05)(P<0.05)。实验组牙周膜细胞CTSK、MMP-9、CAⅡmRNA表达高于对照组(CTSK:2.57±0.23 vs 1.05±0.01;MMP-9:2.34±0.18 vs 1.04±0.03;CAII:3.79±0.12 vs 1.06±0.03)(P<0.05)。[结论]白细胞介素-1β可有效诱导牙周膜细胞分化为有骨吸收能力的破骨细胞,其机制是通过上调RANKL表达和下调骨保护素表达来介导。
