汉坦病毒在原代人胚肾与人胚肺细胞中增殖及其特性的研究

近年来研究发现,汉坦病毒能在多种细胞株及人体细胞中增殖、适应.国内学者用人胚肺二倍体细胞(2BS)体外适应该病毒成功,但有关原代人胚肺、肾细胞的报道尚少.作者选用两株病毒及两种原代人胚细胞用于体外感染、观察,应用免疫荧光间接法及胶体金包埋前染色电镜技术对宿主细胞中增殖的病毒进行了动态观察及特异性定位研究,现报告如下.1 材料和方法1.1 细胞的分离和培养1.1.1 人胚细胞:取正常孕妇5—7个月水囊引产胚肾及肺组织,按常规方法分散细胞,5—7天后长满单层.1.1.2 非洲绿猴肾上皮细胞(VeroE6):由安徽省医学科学研究所倪大石惠赠.1.2     

Efficient weighting methods for genomic best linear-unbiased prediction (BLUP) adapted to the genetic architectures of quantitative traits

Genomic best linear-unbiased prediction (GBLUP) assumes equal variance for all marker effects, which is suitable for traits that conform to the infinitesimal model. For traits controlled by major genes, Bayesian methods with shrinkage priors or genome-wide association study (GWAS) methods can be used to identify causal variants effectively. The information from Bayesian/GWAS methods can be used to construct the weighted genomic relationship matrix (G). However, it remains unclear which methods perform best for traits varying in genetic architecture. Therefore, we developed several methods to optimize the performance of weighted GBLUP and compare them with other available methods using simulated and real data sets. First, two types of methods (marker effects with local shrinkage or normal prior) were used to obtain test statistics and estimates for each marker effect. Second, three weighted G matrices were constructed based on the marker information from the first step: (1) the genomic-feature-weighted G, (2) the estimated marker-variance-weighted G, and (3) the absolute value of the estimated marker-effect-weighted G. Following the above process, six different weighted GBLUP methods (local shrinkage/normal-prior GF/EV/AEWGBLUP) were proposed for genomic prediction. Analyses with both simulated and real data demonstrated that these options offer flexibility for optimizing the weighted GBLUP for traits with a broad spectrum of genetic architectures. The advantage of weighting methods over GBLUP in terms of accuracy was trait dependant, ranging from 14.8% to marginal for simulated traits and from 44% to marginal for real traits. Local-shrinkage prior EVWGBLUP is superior for traits mainly controlled by loci of a large effect. Normal-prior AEWGBLUP performs well for traits mainly controlled by loci of moderate effect. For traits controlled by some loci with large effects (explain 25–50% genetic variance) and a range of loci with small effects, GFWGBLUP has advantages. In conclusion, the optimal weighted GBLUP method for genomic selection should take both the genetic architecture and number of QTLs of traits into consideration carefully.Subject terms: Quantitative trait, Genome-wide association studies, Animal breeding, Quantitative trait, Genome-wide association studies     

Tuberculosis models with fast and slow dynamics: the role of close and casual contacts

Models that incorporate local and individual interactions are introduced in the context of the transmission dynamics of tuberculosis (TB). The multi-level contact structure implicitly assumes that individuals are at risk of infection from close contacts in generalized household (clusters) as well as from casual (random) contacts in the general population. Epidemiological time scales are used to reduce the dimensionality of the model and singular perturbation methods are used to corroborate the results of time-scale approximations. The concept and impact of optimal average cluster or generalized household size on TB dynamics is discussed. We also discuss the potential impact of our results on the spread of TB.     

The threshold of survival for systems in a fluctuating environment

Thresholds for survival and extinction are important for assessing the risk of mortality in systems exposed to exogeneous stress. For generic, rudimentary population models and the classical resource-consumer models of Leslie and Gallopin, we demonstrate the existence of a survival threshold for situations where demographic parameters are fluctuating, generally, in a nonperiodic manner. The fluctuations are assumed, to be generated by exogenous, anthropogenic stresses such as toxic chemical exposures. In general, the survival threshold is determined by a relationship between mean stress measure in organisms to the ratio of the population intrinsic growth rate and stress response rate. Research supported by the fund of Chinese Natural Science. Research supported in part by the U.S. Enviromental Protection Agency under cooperative agreement CR-813353-01-0.