Bilayer matrix composed of polycation/DNA complex and sodium alginate gel as a tumor cell catcher

A bilayer matrix consisting of TABP-SS/DNA complexes and sodium alginate gel is formed via electrostatic interaction. In vitro cell adhesion, proliferation and transfection of the bilayer matrix are investigated in HepG2, HeLa and COS7 cells. Results show that this matrix can only promote tumor cell attachment and growth. Compared with normal cells, the bilayer matrix exhibits significantly higher transfection efficacy in tumor cells. Cell co-culture competitive transfection assay shows that the cell uptake of TABP-SS/DNA complexes is significantly enhanced in tumor cells rather than normal cells under the co-culture competitive condition, which confirms that TABP-SS/DNA complexes have strong tumor cell selectivity and tumor targeting transfection ability.     

Dual disjoint hypercyclic operators

Let E be a separable Fréchet space. The operators T₁,…,Tm are disjoint hypercyclic if there exists x∈E such that the orbit of (x,…,x) under (T₁,…,Tm) is dense in E×?×E. We show that every separable Banach space E admits an m-tuple of bounded linear operators which are disjoint hypercyclic. If, in addition, its dual E^∗ is separable, then they can be constructed such that are also disjoint hypercyclic.     

介导GAD基因的人泡沫病毒载体的构建及其应用

构建了两种新的重组人泡沫病毒载体pGPSNI—hGAD67和pGPSNI—hGAD65，分别携带人符氨酸脱羧酶（GAD）的两种同工酶GAD65和GAD67基因，并研究其在帕金森病（PD）模刭鼠丘脑底核中的表达及对帕金森病的治疗作用．RT—PCR结果表明，人泡沫病毒载体成功地介导了GAD65基因和GAD67基因在PD模型鼠丘脑底核中有效表达．动物行为检测表明，GAD65基因导入组PD模型鼠行为与对照组相比得到明显的改善（n=12，由〈0．01）．     

Collineations of the curvature tensor in general relativity

Curvature collineations for the curvature tensor, constructed from a fundamental Bianchi Type-V metric, are studied. We are concerned with a symmetry property of space-time which is called curvature collineation, and we briefly discuss the physical and kinematical properties of the models.     

Construction of multivariate compactly supported orthonormal wavelets

We propose a constructive method to find compactly supported orthonormal wavelets for any given compactly supported scaling function φ in the multivariate setting. For simplicity, we start with a standard dilation matrix 2I_2×2 in the bivariate setting and show how to construct compactly supported functions ψ₁,. . .,ψ_n with n>3 such that {2^kψ_j(2^kx−ℓ,2^ky−m), k,ℓ,m∈Z, j=1,. . .,n} is an orthonormal basis for L₂(ℝ²). Here, n is dependent on the size of the support of φ. With parallel processes in modern computer, it is possible to use these orthonormal wavelets for applications. Furthermore, the constructive method can be extended to construct compactly supported multi-wavelets for any given compactly supported orthonormal multi-scaling vector. Finally, we mention that the constructions can be generalized to the multivariate setting. Dedicated to Professor Charles A. Micchelli on the occasion of his 60th birthday Mathematics subject classifications (2000) 42C15, 42C30.     

二阶完全对称张量空间中可分元素的坐标间的齐次关系

本文给出了二阶完全对称张量间Ｖ^（２）中可分元素的坐标间齐次关系，特别地，这种齐次关系可以由行列式表示出来。并由此得到了Ｖ^（２）中可分元素的一个等价条件。     

关于Witt向量之序列

对出现于公式Π_ｎ≥１１/(１＋ｄ_ｎｔ^ｎ／ｎ！)＝（１－ｔ）ｅ^ｔ中的整数ｄ_ｎ给出了精确估计     

Semi-parametric multivariate modelling when the marginals are the same

A model is developed for multivariate distributions which have nearly the same marginals, up to shift and scale. This model, based on “interpolation” of characteristic functions, gives a new notion of “correlation”. It allows straightforward nonparametric estimation of the common marginal distribution, which avoids the “curse of dimensionality” present when nonparametically estimating the full multivariate distribution. The method is illustrated with environmental monitoring network data, where multivariate modelling with common marginals is often appropriate.     

Infinite-variate wide-sense Markov processes and functional analysis for bounded operator-forming vectors

Let p, q be arbitrary parameter sets, and let $\text{H}$ be a Hilbert space. We say that x = (xⁱ)_i?q, xⁱ ? $\text{H}$, is a bounded operator-forming vector (?$\text{H}$_F^q) if the Gram matrix 〈x, x〉 = [(xⁱ, x^j)]_i?q,j?q is the matrix of a bounded (necessarily ≥ 0) operator on $\text{l}{}_{\mathrm{q}}{}^2$, the Hilbert space of square-summable complex-valued functions on q. Let A be p × q, i.e., let A be a linear operator from $\text{l}{}_{\mathrm{q}}{}^2$ to $\text{l}{}_{\mathrm{p}}{}^2$. Then exists a linear operator ǎ from (the Banach space) $\text{H}$_F^q to $\text{H}$_F^p on $\text{D}$(A) = {x:x ? $\text{H}$_F^q, $\text{A〈x, x〉}{}^{\mathrm{<mtext>1</mtext><mtext>2</mtext>}}$ is p × q bounded on $\text{l}{}_{\mathrm{q}}{}^2$} such that y = ǎx satisfies y^j?σ(x) = {space spanned by the xⁱ}, 〈y, x〉 = A〈x, x〉 and $\text{〈y, y〉 = A〈x, x〉}{}^{\mathrm{<mtext>1</mtext><mtext>2</mtext>}}\text{(A〈x, x〉}{}^{\mathrm{<mtext>1</mtext><mtext>2</mtext>}}\text{)}{}^1$. This is a generalization of our earlier [J. Multivariate Anal.4 (1974), 166–209; 6 (1976), 538–571] results for the case of a spectral measure concentrated on one point. We apply these tools to investigate q-variate wide-sense Markov processes.