转录靶向性KDR启动子调控双自杀基因治疗肺癌的实验研究

从人肺癌细胞株中克隆KDR基因的启动子(kinasedomainreceptorpromotor,KDRp),构建KDR基因启动子调控的双自杀基因(CDglyTK)真核表达质粒pcDNA3-KDRp-CdglyTK,将其导入ECV304、L9981和NL9980细胞,建立相应的转基因细胞系,并应用不同的前药处理。体内、外实验结果显示:KDR启动子调控的双自杀基因在KDR高表达人肺癌细胞和人脐静脉内皮细胞靶向表达,而在KDR不表达的正常细胞或正常血管内皮细胞中未检测到双自杀基因表达;联合应用5-FC和GCV处理,对转双自杀基因细胞的杀伤作用显著高于单独应用5-FC或GCV,且二者显示了良好的药物协同作用。     

Revisiting Targeted Factors

This paper proposes new methods for ‘targeting’ factors estimated from a big dataset. We suggest that forecasts of economic variables can be improved by tuning factor estimates: (i) so that they are both more relevant for a specific target variable; and (ii) so that variables with considerable idiosyncratic noise are down‐weighted prior to factor estimation. Existing targeted factor methodologies are limited to estimating the factors with only one of these two objectives in mind. We therefore combine these ideas by providing new weighted principal components analysis (PCA) procedures and a targeted generalized PCA (TGPCA) procedure. These methods offer a flexible combination of both types of targeting that is new to the literature. We illustrate this empirically by forecasting a range of US macroeconomic variables, finding that our combined approach yields important improvements over competing methods, consistently surviving elimination in the model confidence set procedure. Copyright © 2016 John Wiley & Sons, Ltd.     

Prediction from the One‐Way Error Components Model with AR(1) Disturbances

In this paper we extend the works of Baillie and Baltagi (1999, in Analysis of Panels and Limited Dependent Variables Models, Hsiao C et al. (eds). Cambridge University Press: Cambridge, UK; 255–267) and generalize certain results from the Baltagi and Li (1992, Journal of Forecasting 11 : 561–567) paper accounting for AR(1) errors in the disturbance term. In particular, we derive six predictors for the one‐way error components model, as well as their associated asymptotic mean squared error of multi‐step prediction in the presence of AR(1) errors in the disturbance term. In addition, we also provide both theoretical and simulation evidence as to the relative efficiency of our alternative predictors. The adequacy of the prediction AMSE formula is also investigated by the use of Monte Carlo methods and indicates that the ordinary optimal predictor performs well for various accuracy criteria. Copyright © 2011 John Wiley & Sons, Ltd.     

通过区分读者类型与提供优质服务充分彰显图书馆职能

服务读者是图书馆工作的根本,搞好服务工作、提高服务质量是图书馆赖以生存和发展的基础,是彰显图书馆职能、提升图书馆地位的精髓。从区分读者类型出发,提出了一些针对不同类型读者提供各具特色服务的设想。     

自制靶向超声造影剂兔肾炎症组织显像实验研究

为探讨自制靶向超声造影剂对兔肾炎症组织显像的增强效果,建立兔缺血再灌注损伤肾模型,用自制靶向超声造影剂行声学造影,谐波显像观察造影前后6只兔缺血再灌注损伤肾和6只对照兔正常肾实质回声强度变化.结果表明:造影后两组兔肾实质回声均增强,造影前后缺血再灌注损伤肾和对照组正常肾实质灰阶值(GS)差值分别为25.88±4.04和9.98±1.96(p<0.001).自制靶向超声造影剂可显著增强兔肾炎症组织显像.     

平台企业的进入、竞争与规制

基于经典的Salop模型,研究了定向广告情况下平台企业的进入、竞争与规制问题。研究发现：当广告定向精度较小（大）时,均衡广告量与平台的广告定向精度成反（正）比;与社会最优状态相比,当广告 定向精度较小（大）时,均衡的广告量过多（少）,而均衡平台数量是否过多既取决于平台的差异化程度,又取 决于平台的广告定向精度;如果政府只管控平台数量,那么,相对于社会最优而言,当广告定向精度较小（大） 时,平台的数量过多（少）;如果政瘠只管控广告量,广告量既可能大于也可能小于社会最优的广告量,最终結 果取决于平台的差异化程度及其广告定向精度。     

一种新型的速度和加速度估计器

将扩张状态观测器和递归线性平滑牛顿预测器相结合,形成了一种新型的速度和加速度估计器,它在跟踪位移和估计速度的同时能一并估计出加速度.虽然扩张状态观测器本身对量测噪声已经具有较好的滤波特性,但为了减小时间延迟,不能使滤波参数过大,这样会使估计出的加速度噪声稍高,需再用递归线性平滑牛顿预测器对加速度进行二次滤波.仿真结果表明,由扩张状态观测器和递归线性平滑牛顿预测器构成的滤波估计器在仅有位置量测信号且在噪声较大的情况下能有效地估计出速度和加速度,最终得到的速度和加速度估计信噪比高且时间延迟小.该估计器主要用于运动控制和机动目标跟踪中.     

环境因子对滇西北地区植物多样性分布格局的影响

利用一元回归分析和偏回归分析,探讨了滇西北地区温、热带植物的分布格局及其控制因素.结果表明,温带植物多样性的高值主要出现在研究区域北部,而热带植物多样性则未呈现明显的纬度趋势.热带植物比重高值主要出现在研究区域南部,而温带植物比重高值主要出现在北部.生境异质性对温带植物多样性的解释率明显高于对热带植物多样性的解释率.这意味着,生境异质性对多样性格局的影响力可能在一定程度上取决于植物的生物地理分布区性质.气候因子对温、热带植物比重的解释率明显高于对温、热植物多样性的解释率.相比气候因子与温、热带植物多样性的关系,气候因子与温、热带植物比重之间关系可能更能反映滇西北地区温、热带植物的生态位保守性.     

定向广告中消费者隐私态度对行为意愿的影响机制

基于消费者隐私视角，检验消费者隐私态度、定向广告认知和行为意愿之间的关系。通过对258份消费者随机抽样数据进行实证研究，分析个体特征变量在隐私态度，隐私控制度、隐私敏感度上的差异，并通过结构方程路径分析验证假设。研究结果表明：消费者隐私态度直接显著正向影响其定向广告认知水平和行为意愿；消费者定向广告认知水平直接显著负向影响其行为意愿；定向广告认知在消费者隐私态度和行为意愿之间存在显著的部分中介作用。因此，企业应重视消费者隐私关注，在投放过程中关注用户感知以优化定向广告。从而实现定向广告精准投放与消费者个人隐私关注的平衡。     

The Predictive Performance Evaluation of Biased Regression Predictors With Correlated Errors

When the interdependence of disturbances is present in a regression model, the pattern of sample residuals contains information which is useful in the prediction of post‐sample drawings and when multicollinearity among regressors is also present, it is useful to use biased regression estimators. This information is exploited in the biased predictors derived here. Also, the predictive performance of various biased predictors with correlated errors is discussed and all pair‐wise comparisons are made among these predictors. The theoretical results are illustrated by a numerical example. Copyright © 2015 John Wiley & Sons, Ltd.