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| 1 | Zinc finger transcription factor Sp7/Osterix acts on bone formation and regulates col10a1a expression in zebrafish显示文摘Sp7/Osterix as a zinc finger transcription factor is expressed specifically in osteoblasts.Embryonic lethality of Sp7 knockout mice,however,has prevented from examining the functions of Sp7 in osteoblast and bone formation in live animals.Here we used TALEN,a versatile genome-editing tool,to generate one zebrafish sp7 mutant line.Homozygous sp7-/- mutant zebrafish are able to survive to adulthood.Alizarin Red staining and Micro-CT analysis showed that sp7-/- larvae and adult fish fail to develop normal opercula,and display curved tail fins and severe craniofacial malformation,while Alcian Blue staining showed no obvious cartilage defects in sp7-/- fish.Quantitative RT-PCR showed that a number of osteoblast markers including spp1,phex,col1 ala,and col1a1 b are significantly down-regulated in sp7-/- fish.Furthermore,col10a1 a,whose ortholog is the cartilage marker in mice,was shown to be a novel downstream gene of Sp7 as an osteoblast marker in zebrafish.Together,these results suggest that Sp7 is required for zebrafish bone development and zebrafish sp7 mutants provide animal models for investigating novel aspects of bone development. | Pengfei Niu Zhaomin Zhong Mingyong Wang Guodong Huang Shuhao Xu Yi HOU Yilin Yan Han Wang | 2017 | Science Bulletin2017，62，3： | 4 |
| 2 | The improved artificial bee colony algorithm for mixed additive and multiplicative random error model and the bootstrap method for its precision estimation显示文摘To solve the complex weight matrix derivative problem when using the weighted least squares method to estimate the parameters of the mixed additive and multiplicative random error model(MAM error model),we use an improved artificial bee colony algorithm without derivative and the bootstrap method to estimate the parameters and evaluate the accuracy of MAM error model.The improved artificial bee colony algorithm can update individuals in multiple dimensions and improve the cooperation ability between individuals by constructing a new search equation based on the idea of quasi-affine transformation.The experimental results show that based on the weighted least squares criterion,the algorithm can get the results consistent with the weighted least squares method without multiple formula derivation.The parameter estimation and accuracy evaluation method based on the bootstrap method can get better parameter estimation and more reasonable accuracy information than existing methods,which provides a new idea for the theory of parameter estimation and accuracy evaluation of the MAM error model. | Leyang Wang Shuhao Han | 2023 | Geodesy and Geodynamics2023，14，3： | 3 |
| 3 | Improved cat swarm optimization for parameter estimation of mixed additive and multiplicative random error model显示文摘To estimate the parameters of the mixed additive and multiplicative(MAM)random error model using the weighted least squares iterative algorithm that requires derivation of the complex weight array,we introduce a derivative-free cat swarm optimization for parameter estimation.We embed the Powell method,which uses conjugate direction acceleration and does not need to derive the objective function,into the original cat swarm optimization to accelerate its convergence speed and search accuracy.We use the ordinary least squares,weighted least squares,original cat swarm optimization,particle swarm algorithm and improved cat swarm optimization to estimate the parameters of the straight-line fitting MAM model with lower nonlinearity and the DEM MAM model with higher nonlinearity,respectively.The experimental results show that the improved cat swarm optimization has faster convergence speed,higher search accuracy,and better stability than the original cat swarm optimization and the particle swarm algorithm.At the same time,the improved cat swarm optimization can obtain results consistent with the weighted least squares method based on the objective function only while avoiding multiple complex weight array derivations.The method in this paper provides a new idea for theoretical research on parameter estimation of MAM error models. | Leyang Wang Shuhao Han | 2023 | Geodesy and Geodynamics2023，14，4： | 2 |
| 4 | Copper-tetracyanoquinodimethane-derived copper electrocatalysts for highly selective carbon dioxide reduction to ethylene显示文摘As one of the most promising CO_(2)utilization techniques,electrochemical CO_(2)reduction has recently received considerable attention.Cu is a unique electrocatalyst that can convert CO_(2)to value-added multi-carbon chemicals.Nevertheless,Cu catalysts are always limited by the poor selectivity and stability.Here,we report that using copper-tetracyanoquinodimethane(CuTCNQ)derived Cu nanoparticles as efficient electrocatalysts for conversion of CO_(2)to ethylene characteristic with high selectivity and stability,showing 56%Faradaic efficiency(FE)to C2H4 at−1.3 V vs.reversible hydrogen electrode(RHE).Upon the electrochemical CO_(2)reduction,CuTCNQ slowly reconstructs to Cu nanoparticles with abundant grain boundaries and residual Cu+on the surface.Theoretical calculation and operando characterization disclose that both as-formed Cu nanoparticle grain boundaries and residual Cu+endow the catalyst with high selectivity toward ethylene.Furthermore,during the reconstruction of CuTCNQ to Cu nanoparticles,the grain boundaries Cu surface is slowly refreshed by continual addition of Cu atoms,thus inhibiting the surface passivation and guaranteeing the electrocatalytic stability. | Xuewei Huang Dawei Wang Shuhao Yan Pengfei An Jianyu Han Zhiyu Guo Xinwei Li Zhongjun Chen Lin Chang Siyu Lu Zhiyong Tang | 2022 | Nano Research2022，15，9： | 0 |
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