Specific nuclear envelope transmembrane proteins can promote the location of chromosomes to and from the nuclear periphery

BACKGROUND: Different cell types have distinctive patterns of chromosome positioning in the nucleus. Although ectopic affinity-tethering of specific loci can be used to relocate chromosomes to the nuclear periphery, endogenous nuclear envelope proteins that control such a mechanism in mammalian cells have yet to be widely identified. RESULTS: To search for such proteins twenty three nuclear envelope transmembrane proteins were screened for their ability to promote peripheral localization of human chromosomes in HT1080 fibroblasts. Five of these proteins had strong effects on chromosome 5, but individual proteins affected different subsets of chromosomes. The repositioning effects were reversible and the proteins with effects all exhibited highly tissue-restricted patterns of expression. Depletion of two nuclear envelope transmembrane proteins that were preferentially expressed in liver each reduced the normal peripheral positioning of chromosome 5 in liver cells. CONCLUSIONS: The discovery of nuclear envelope transmembrane proteins that can modulate chromosome position and have restricted patterns of expression may enable dissection of the functional relevance of tissue-specific patterns of radial chromosome positioning.Publisher PDFPeer reviewe

Synthesis and characterization of nanocrystalline U1−x_{1-x}Pux_{x}O2(+y)_{2(+y)} mixed oxides

We report here the first synthesis of mixed oxide U$_{1-x}$Pu$_{x}$O$_{2(+y)}$ nanoparticles. The obtained nanopowders were characterized by X-ray diffraction, thermal ionization mass spectrometry, transmission electron microscopy, Raman spectroscopy, and U M$_{4}$ edge high-energy-resolution X-ray absorption near edge structure (HR-XANES). The HR-XANES spectra give evidence for the partial oxidation of U$^{IV}$ to U$^{V}$. This novel route toward the formation of actinide–actinide solid solution opens research opportunities that are not accessible using bulk materials. We give details on the X-ray diffraction study on plutonium oxalate hexahydrate, as a reagent for the synthesis of such nanoparticles

Alternating runtime and size complexity analysis of integer programs

We present a modular approach to automatic complexity analysis. Based on a novel alternation between finding symbolic time bounds for program parts and using these to infer size bounds on program variables, we can restrict each analysis step to a small part of the program while maintaining a high level of precision. Extensive experiments with the implementation of our method demonstrate its performance and power in comparison with other tools

Tight polynomial bounds for Loop programs in polynomial space

We consider the following problem: given a program, find tight asymptotic bounds on the values of some variables at the end of the computation (or at any given program point) in terms of its input values. We focus on the case of polynomially-bounded variables, and on a weak programming language for which we have recently shown that tight bounds for polynomially-bounded variables are computable. These bounds are sets of multivariate polynomials. While their computability has been settled, the complexity of this program-analysis problem remained open. In this paper, we show the problem to be PSPACE-complete. The main contribution is a new, space-efficient analysis algorithm. This algorithm is obtained in a few steps. First, we develop an algorithm for univariate bounds, a sub-problem which is already PSPACE-hard. Then, a decision procedure for multivariate bounds is achieved by reducing this problem to the univariate case; this reduction is orthogonal to the solution of the univariate problem and uses observations on the geometry of a set of vectors that represent multivariate bounds. Finally, we transform the univariate-bound algorithm to produce multivariate bounds

Peak Cost Analysis of Distributed Systems (Author's version)

We present a novel static analysis to infer the peak cost of distributed systems. The different locations of a distributed system communicate and coordinate their actions by posting tasks among them. Thus, the amount of work that each location has to perform can greatly vary along the execution depending on: (1) the amount of tasks posted to its queue, (2) their respective costs, and (3) the fact that they may be posted in parallel and thus be pending to execute simultaneously. The peak cost of a distributed location refers to the maximum cost that it needs to carry out along its execution. Inferring the peak cost is challenging because it increases and decreases along the execution, unlike the standard notion of total cost which is cumulative. Our key contribution is the novel notion of quantified queue configuration which captures the worst-case cost of the tasks that may be simultaneously pending to execute at each location along the execution. A prototype implementation demonstrates the accuracy and feasibility of the proposed peak cost analysis

Parallel Cost Analysis of Distributed Systems

We present a novel static analysis to infer the parallel cost of distributed systems. Parallel cost differs from the standard notion of serial cost by exploiting the truly concurrent execution model of distributed processing to capture the cost of synchronized tasks executing in parallel. It is challenging to analyze parallel cost because one needs to soundly infer the parallelism between tasks while accounting for waiting and idle processor times at the different locations. Our analysis works in three phases: (1) It first performs a block-level analysis to estimate the serial costs of the blocks between synchronization points in the program; (2) Next, it constructs a distributed ow graph (DFG) to capture the parallelism, the waiting and idle times at the locations of the distributed system; Finally, (3) the parallel cost can be obtained as the path of maximal cost in the DFG. A prototype implementation demonstrates the accuracy and feasibility of the proposed analysis