正交试验优选盐炙续断炮制工艺

目的:研究盐炙工艺对川续断皂苷Ⅵ含量的影响,优选盐炙续断炮制工艺.方法:以HPLC测定川续断皂苷Ⅵ含量为评价指标,采用正交试验法筛选盐炙续断炮制工艺参数.结果:优选的盐炙续断炮制工艺为每500 g续断药材用10 g盐浸润45 min,150℃炒制8 min.结论:优选的盐炙续断炮制工艺可明显提高续断有效成分的溶出率,且工艺稳定、质量可控,为续断炮制规范的研究提供参考.     

Additive survival least‐squares support vector machines

This work studies a new survival modeling technique based on least‐squares support vector machines. We propose the use of a least‐squares support vector machine combining ranking and regression. The advantage of this kernel‐based model is threefold: (i) the problem formulation is convex and can be solved conveniently by a linear system; (ii) non‐linearity is introduced by using kernels, componentwise kernels in particular are useful to obtain interpretable results; and (iii) introduction of ranking constraints makes it possible to handle censored data. In an experimental setup, the model is used as a preprocessing step for the standard Cox proportional hazard regression by estimating the functional forms of the covariates. The proposed model was compared with different survival models from the literature on the clinical German Breast Cancer Study Group data and on the high‐dimensional Norway/Stanford Breast Cancer Data set. Copyright © 2009 John Wiley & Sons, Ltd.     

澳洲坚果果仁营养成分分析

<正>澳洲坚果(Macadamia integrifolia),属山龙眼科(Proteaceae),澳洲坚果属(Macadamia)常绿乔木果树,又称夏威夷果、澳洲核桃、昆士兰坚果。原产于澳大利亚昆士兰州东南部和新南     

Coconut kernel-derived proteins enhance hypolipidemic and antioxidant activity in alloxan-induced diabetic rats

Impaired lipid levels and oxidative stress are indicative of malfunction of endogenous antioxidant capacity. The aim of this study was to determine the effect of coconut kernel protein (CKP) on the lipid peroxides and antioxidant enzyme activities in diabetic rats. Diabetes was induced prior to feeding by injecting a single dose of alloxan (150 mg/kg body weight) intraperitoneally. CKP (8% w/w) was administered to these rats along with a semi-synthetic diet for 45 days. After the experimental period, peroxide products and antioxidant enzyme activities were determined. Results show that CKP maintained the antioxidant enzyme activities and levels of peroxides to the normal levels in treated group compared to diabetic rats. This study clearly show that CKP has potential effect in lowering oxidative stress associated with diabetes. This beneficial effect of CKP may be due to the high amount of biologically potent arginine present in it.     

A general semiparametric hazards regression model: efficient estimation and structure selection

We consider a general semiparametric hazards regression model that encompasses the Cox proportional hazards model and the accelerated failure time model for survival analysis. To overcome the nonexistence of the maximum likelihood, we derive a kernel‐smoothed profile likelihood function and prove that the resulting estimates of the regression parameters are consistent and achieve semiparametric efficiency. In addition, we develop penalized structure selection techniques to determine which covariates constitute the accelerated failure time model and which covariates constitute the proportional hazards model. The proposed method is able to estimate the model structure consistently and model parameters efficiently. Furthermore, variance estimation is straightforward. The proposed estimation performs well in simulation studies and is applied to the analysis of a real data set. Copyright © 2013 John Wiley & Sons, Ltd.     

Estimating treatment effects in a two‐arm parallel trial of a continuous outcome

For a continuous outcome in a two‐arm trial that satisfies normal distribution assumptions, we can transform the standardized mean difference with the use of the cumulative distribution function to be the effect size measure P(X < Y ). This measure is already established within engineering as the reliability parameter in stress–strength models, where Y represents the strength of a component and X represents the stress the component undergoes. If X is greater than Y, then the component will fail. In this paper, we consider the closely related effect size measure, This measure is also known as Somer's d, which was introduced by Somers in 1962 as an ordinal measure of association. In this paper, we explore this measure as a treatment effect size for a continuous outcome. Although the point estimates for λ are easily calculated, the interval is not so readily obtained. We compare kernel density estimation and use of bootstrap and jackknife methods to estimate confidence intervals against two further methods for estimating P(X < Y ) and their respective intervals, one of which makes no assumption about the underlying distribution and the other assumes a normal distribution. Simulations show that the choice of the best estimator depends on the value of λ, the variability within the data, and the underlying distribution of the data. Copyright © 2012 John Wiley & Sons, Ltd.     

Kernel Machine SNP‐Set Testing Under Multiple Candidate Kernels

Joint testing for the cumulative effect of multiple single‐nucleotide polymorphisms grouped on the basis of prior biological knowledge has become a popular and powerful strategy for the analysis of large‐scale genetic association studies. The kernel machine (KM)‐testing framework is a useful approach that has been proposed for testing associations between multiple genetic variants and many different types of complex traits by comparing pairwise similarity in phenotype between subjects to pairwise similarity in genotype, with similarity in genotype defined via a kernel function. An advantage of the KM framework is its flexibility: choosing different kernel functions allows for different assumptions concerning the underlying model and can allow for improved power. In practice, it is difficult to know which kernel to use a priori because this depends on the unknown underlying trait architecture and selecting the kernel which gives the lowest P‐value can lead to inflated type I error. Therefore, we propose practical strategies for KM testing when multiple candidate kernels are present based on constructing composite kernels and based on efficient perturbation procedures. We demonstrate through simulations and real data applications that the procedures protect the type I error rate and can lead to substantially improved power over poor choices of kernels and only modest differences in power vs. using the best candidate kernel.     

GEE‐Based SNP Set Association Test for Continuous and Discrete Traits in Family‐Based Association Studies

Family‐based genetic association studies of related individuals provide opportunities to detect genetic variants that complement studies of unrelated individuals. Most statistical methods for family association studies for common variants are single marker based, which test one SNP a time. In this paper, we consider testing the effect of an SNP set, e.g., SNPs in a gene, in family studies, for both continuous and discrete traits. Specifically, we propose a generalized estimating equations (GEEs) based kernel association test, a variance component based testing method, to test for the association between a phenotype and multiple variants in an SNP set jointly using family samples. The proposed approach allows for both continuous and discrete traits, where the correlation among family members is taken into account through the use of an empirical covariance estimator. We derive the theoretical distribution of the proposed statistic under the null and develop analytical methods to calculate the P‐values. We also propose an efficient resampling method for correcting for small sample size bias in family studies. The proposed method allows for easily incorporating covariates and SNP‐SNP interactions. Simulation studies show that the proposed method properly controls for type I error rates under both random and ascertained sampling schemes in family studies. We demonstrate through simulation studies that our approach has superior performance for association mapping compared to the single marker based minimum P‐value GEE test for an SNP‐set effect over a range of scenarios. We illustrate the application of the proposed method using data from the Cleveland Family GWAS Study.     

仙鹤草、金樱子等药物对心脏影响的初步观察

选用了一些药物对离体蟾蜍心脏进行灌流,观察对离体心脏的影响,能否用在临床上,尚待作更多生理和药理方面的研究。     

芒果核仁乙酸乙酯部位化学成分

目的:研究芒果核仁的化学成分.方法:采用硅胶柱色谱、凝胶柱色谱、薄层制备色谱、重结晶等方法进行分离纯化,通过理化性质和多种波谱数据鉴定化合物.结果:从芒果核的乙酸乙酯部位分离得到9个化合物,分别鉴定为香豆素(1)、β-谷甾醇(2)、香兰素(3)、表儿茶素(4)、没食子酸(5)、咖啡酸(6)、阿魏酸(7)、熊果苷(8)和鞣花酸(9).结论:化合物1～4,6～9为首次从该植物中分离得到.