This article develops a novel spatial quantile function-on-scalar regression model, which studies the conditional spatial distribution of a high-dimensional functional response given scalar predictors. With the strength of both quantile regression and copula modeling, we are able to explicitly characterize the conditional distribution of the functional or image response on the whole spatial domain. Our method provides a comprehensive understanding of the effect of scalar covariates on functional responses across different quantile levels and also gives a practical way to generate new images for given covariate values. Theoretically, we establish the minimax rates of convergence for estimating coefficient functions under both fixed and random designs. We further develop an efficient primal-dual algorithm to handle high-dimensional image data. Simulations and real data analysis are conducted to examine the finite-sample performance.
This work is about strong and weak convergence of schemes for multiscale stochastic dynamical systems driven by $\alpha$-stable processes. Firstly, we analyze a class of projective integration methods, which are used to estimate the effect that the fast components have on slow ones. Secondly, we obtain the $p$th moment error bounds between the results of the method and the slow components of the original system with $p \in (1, \min(\alpha_1, \alpha_2))$. Finally, a numerical experiment is constructed to illustrate this scheme.
Mouse vimentin intermediate filaments (IFs) reconstituted in vitro were analyzed for their capacity to select certain DNA sequences from a mixture of about 500-bp-long fragments of total mouse genomic DNA. The fragments preferentially bound by the IFs and enriched by several cycles of affinity binding and polymerase chain reaction (PCR) amplification were cloned and sequenced. In general, they were G-rich and highly repetitive in that they often contained Gn, (GT)n, and (GA)n repeat elements. Other, more complex repeat sequences were identified as well. Apart from the capacity to adopt a Z-DNA and triple helix configuration under superhelical tension, many fragments were potentially able to form cruciform structures and contained consensus binding sites for various transcription factors. All of these sequence elements are known to occur in introns and 5'/3'-flanking regions of genes and to play roles in DNA transcription, recombination and replication. A FASTA search of the EMBL data bank indeed revealed that sequences homologous to the mouse repetitive DNA fragments are commonly associated with gene-regulatory elements. Unexpectedly, vimentin IFs also bound a large number of apparently overlapping, AT-rich DNA fragments that could be aligned into a composite sequence highly homologous to the 234-bp consensus centromere repeat sequence of gamma-satellite DNA. Previous experiments have shown a high affinity of vimentin for G-rich, repetitive telomere DNA sequences, superhelical DNA, and core histones. Taken together, these data support the hypothesis that, after penetration of the double nuclear membrane via an as yet unidentified mechanism, vimentin IFs cooperatively fix repetitive DNA sequence elements in a differentiation-specific manner in the nuclear periphery subjacent to the nuclear lamina and thus participate in the organization of chromatin and in the control of transcription, replication, and recombination processes. This includes aspects of global regulation of gene expression such as the position effects associated with translocation of genes to heterochromatic centromere and telomere regions of the chromosomes.
In this article, approximations and inequalities for the distribution of a two dimensional scan statistic are derived for independently and identically distributed observations from a continuous distribution. The accuracy of these approximations and inequalities is investigated for a normal model. The cases of mean and variance being known and unknown are discussed. Based on approximations for the distributions of one and two dimensional fixed window scan statistics, variable window scan statistics are introduced. We investigate the performance of these variable window scan statistics as test statistics for detection of a local change in the mean of a normal distribution. By utilizing R algorithms for the multivariate normal and distributions established by Genz and Bretz (2009 Genz, A., Bretz, F. (2009). Computation of Multivariate Normal and T Probabilities. New York: Springer.[Crossref] , [Google Scholar]), numerical results are presented to evaluate the efficiency of implementing the variable window scan statistics and compare their performance, via power calculations, with fixed window scan statistics. It is evident from the numerical results that if the dimension of the window where a change has occurred is unknown, the variable window scan statistics outperform the fixed window scan statistics.
Self-assembly is a powerful means to fabricate multifunctional smart nanotheranostics. However, the complicated preparation, toxicity of responsive carriers, and low loading efficiency of drug cargo hinder the outcome. Herein, we developed a responsive carrier-free noncovalent self-assembly strategy of a metallized Au(III) tetra-(4-pyridyl) porphine (AuTPyP) anticancer drug for the preparation of a heat/acid dual-stimulated nanodrug, and it generated a better photothermal effect than monomers under irradiation. The photothermal effect promoted the protonation of the hydrophobic pyridyl group and the following release into tumorous acidic microenvironments. With cRGD modification, the released drug induced the aggravation of intracellular reactive oxygen species (ROS) via the activity inhibition of thioredoxin reductase (TrxR) for synergistic chemo-photothermal therapy of tumors.
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