Nucleolar proteome dynamics

The nucleolus is a key organelle that coordinates the synthesis and assembly of ribosomal subunits and forms in the nucleus around the repeated ribosomal gene clusters. Because the production of ribosomes is a major metabolic activity, the function of the nucleolus is tightly linked to cell growth and proliferation, and recent data suggest that the nucleolus also plays an important role in cell-cycle regulation, senescence and stress responses. Here, using mass-spectrometry-based organellar proteomics and stable isotope labelling, we perform a quantitative analysis of the proteome of human nucleoli. In vivo fluorescent imaging techniques are directly compared to endogenous protein changes measured by proteomics. We characterize the flux of 489 endogenous nucleolar proteins in response to three different metabolic inhibitors that each affect nucleolar morphology. Proteins that are stably associated, such as RNA polymerase I subunits and small nuclear ribonucleoprotein particle complexes, exit from or accumulate in the nucleolus with similar kinetics, whereas protein components of the large and small ribosomal subunits leave the nucleolus with markedly different kinetics. The data establish a quantitative proteomic approach for the temporal characterization of protein flux through cellular organelles and demonstrate that the nucleolar proteome changes significantly over time in response to changes in cellular growth conditions.     

Chromosome-wide and promoter-specific analyses identify sites of differential DNA methylation in normal and transformed human cells

Cytosine methylation is required for mammalian development and is often perturbed in human cancer. To determine how this epigenetic modification is distributed in the genomes of primary and transformed cells, we used an immunocapturing approach followed by DNA microarray analysis to generate methylation profiles of all human chromosomes at 80-kb resolution and for a large set of CpG islands. In primary cells we identified broad genomic regions of differential methylation with higher levels in gene-rich neighborhoods. Female and male cells had indistinguishable profiles for autosomes but differences on the X chromosome. The inactive X chromosome (Xi) was hypermethylated at only a subset of gene-rich regions and, unexpectedly, overall hypomethylated relative to its active counterpart. The chromosomal methylation profile of transformed cells was similar to that of primary cells. Nevertheless, we detected large genomic segments with hypomethylation in the transformed cell residing in gene-poor areas. Furthermore, analysis of 6,000 CpG islands showed that only a small set of promoters was methylated differentially, suggesting that aberrant methylation of CpG island promoters in malignancy might be less frequent than previously hypothesized.     

基于时域局部线性预测的视频镜头变换检测

提出了通过时域局部线性预测，在统一框架中准确、高效地检测视频镜头的切变和叠化等镜头变换的新方法．通过理论分析和基于视频数据的线性回归，分别得到叠化预测模式和平稳镜头预测模式．通过同时比较分析两个线性预测模式的误差，在统一框架中检测切变和叠化变换．由于直接在视频流压缩域中进行分析，因此节省了视频解码的时间．采用新方法检测时仅需要对整数进行加、减、比较和移位操作，计算复杂度很低，适合在低功耗、嵌入式设备上运行．采用MPEG-7标准测试视频的实验结果显示：切变检测查全率为95．5％，查准率为93．9%；叠化变换检测查全率为82．2%，查准率为76．0％．检测一段38min的视频耗时仅3．5s．     

Sequence and analysis of chromosome 1 of the plant Arabidopsis thaliana

The genome of the flowering plant Arabidopsis thaliana has five chromosomes. Here we report the sequence of the largest, chromosome 1, in two contigs of around 14.2 and 14.6 megabases. The contigs extend from the telomeres to the centromeric borders, regions rich in transposons, retrotransposons and repetitive elements such as the 180-base-pair repeat. The chromosome represents 25% of the genome and contains about 6,850 open reading frames, 236 transfer RNAs (tRNAs) and 12 small nuclear RNAs. There are two clusters of tRNA genes at different places on the chromosome. One consists of 27 tRNA(Pro) genes and the other contains 27 tandem repeats of tRNA(Tyr)-tRNA(Tyr)-tRNA(Ser) genes. Chromosome 1 contains about 300 gene families with clustered duplications. There are also many repeat elements, representing 8% of the sequence.     

A Nonlinear Programming Approach to Metric Unidimensional Scaling

Classical unidimensional scaling provides a difficult combinatorial task. A procedure formulated as a nonlinear programming (NLP) model is proposed to solve this problem. The new method can be implemented with standard mathematical programming software. Unlike the traditional procedures that minimize either the sum of squared error (L ₂ norm) or the sum pf absolute error (L ₁ norm), the proposed method can minimize the error based on any L _p norm for 1 ≤p < ∞. Extensions of the NLP formulation to address a multidimensional scaling problem under the city-block model are also discussed.     

Perfluorooctane sulfonate （PFOS） and related fluorochemicals in chicken egg in China

The ubiquitous occurrence of perfluorinated compounds （PFCs） in environmental samples has drawn much attention. Recent human exposure studies found relatively high perfluorooctane sulfonate （PFOS） concentrations in blood samples from several cities in China when compared with other countries. The objectives of the present study were： （1） to measure PFC concentrations and compositions in chicken egg samples from local markets in China; and （2） to conduct a preliminary human health risk assessment of egg consumption. Eight pooled egg samples from eight locations were analyzed for 11 PFCs. The results showed that close to 100% of the PFOS in the egg was distributed in egg yolk and PFOS was not detected in egg white （〈0.08 ng/g wet weight, w/w）. Of the perfluoroalkylsulfonates, only PFOS was detected in all egg samples, while of the perfluoroalkylcarboxylates, perfluoroundecanoic acid （PFUnDA） was detected in all samples, followed by perfluorooctanoate （PFOA） （75% occurrence） and perfluorodecanoic acid （PFDA） （50% occurrence）. PFOS concentrations in egg ranged from 45.0 to 86.9 ng/g w/w. The results suggested that current concentrations of PFOS in domestic chicken eggs are unlikely to cause immediate harm to Chinese populations.     

Emerging knowledge of regulatory roles of <Emphasis Type="SmallCaps">d-</Emphasis>amino acids in bacteria

The d-enantiomers of amino acids have been thought to have relatively minor functions in biological processes. While l-amino acids clearly predominate in nature, d-amino acids are sometimes found in proteins that are not synthesized by ribosomes, and d-Ala and d-Glu are routinely found in the peptidoglycan cell wall of bacteria. Here, we review recent findings showing that d-amino acids have previously unappreciated regulatory roles in the bacterial kingdom. Many diverse bacterial phyla synthesize and release d-amino acids, including d-Met and d-Leu, which were not previously known to be made. These noncanonical d-amino acids regulate cell wall remodeling in stationary phase and cause biofilm dispersal in aging bacterial communities. Elucidating the mechanisms by which d-amino acids govern cell wall remodeling and biofilm disassembly will undoubtedly reveal new paradigms for understanding how extracytoplasmic processes are regulated as well as lead to development of novel therapeutics.     

Weighted Empirical Likelihood Estimator for Vector Multiplicative Error Model

The vector multiplicative error model (vector MEM) is capable of analyzing and forecasting multidimensional non‐negative valued processes. Usually its parameters are estimated by generalized method of moments (GMM) and maximum likelihood (ML) methods. However, the estimations could be heavily affected by outliers. To overcome this problem, in this paper an alternative approach, the weighted empirical likelihood (WEL) method, is proposed. This method uses moment conditions as constraints and the outliers are detected automatically by performing a k‐means clustering on Oja depth values of innovations. The performance of WEL is evaluated against those of GMM and ML methods through extensive simulations, in which three different kinds of additive outliers are considered. Moreover, the robustness of WEL is demonstrated by comparing the volatility forecasts of the three methods on 10‐minute returns of the S&P 500 index. The results from both the simulations and the S&P 500 volatility forecasts have shown preferences in using the WEL method. Copyright © 2012 John Wiley & Sons, Ltd.     

Duplication of Atxn1l suppresses SCA1 neuropathology by decreasing incorporation of polyglutamine-expanded ataxin-1 into native complexes

Spinocerebellar ataxia type 1 (SCA1) is a dominantly inherited neurodegenerative disease caused by expansion of a glutamine tract in ataxin-1 (ATXN1). SCA1 pathogenesis studies support a model in which the expanded glutamine tract causes toxicity by modulating the normal activities of ATXN1. To explore native interactions that modify the toxicity of ATXN1, we generated a targeted duplication of the mouse ataxin-1-like (Atxn1l, also known as Boat) locus, a highly conserved paralog of SCA1, and tested the role of this protein in SCA1 pathology. Using a knock-in mouse model of SCA1 that recapitulates the selective neurodegeneration seen in affected individuals, we found that elevated Atxn1l levels suppress neuropathology by displacing mutant Atxn1 from its native complex with Capicua (CIC). Our results provide genetic evidence that the selective neuropathology of SCA1 arises from modulation of a core functional activity of ATXN1, and they underscore the importance of studying the paralogs of genes mutated in neurodegenerative diseases to gain insight into mechanisms of pathogenesis.