Semiparametric Multivariate Accelerated Failure Time Model with Generalized Estimating Equations

The semiparametric accelerated failure time model is not as widely used as the Cox relative risk model mainly due to computational difficulties. Recent developments in least squares estimation and induced smoothing estimating equations provide promising tools to make the accelerate failure time models more attractive in practice. For semiparametric multivariate accelerated failure time models, we propose a generalized estimating equation approach to account for the multivariate dependence through working correlation structures. The marginal error distributions can be either identical as in sequential event settings or different as in parallel event settings. Some regression coefficients can be shared across margins as needed. The initial estimator is a rank-based estimator with Gehan's weight, but obtained from an induced smoothing approach with computation ease. The resulting estimator is consistent and asymptotically normal, with a variance estimated through a multiplier resampling method. In a simulation study, our estimator was up to three times as efficient as the initial estimator, especially with stronger multivariate dependence and heavier censoring percentage. Two real examples demonstrate the utility of the proposed method

Effect of Silicon Content on Carbide Precipitation and Low-Temperature Toughness of Pressure Vessel Steels

Cr – Mn – Mo – Ni pressure vessel steels containing 0.54 and 1.55% Si are studied. Metallographic and fractographic analyses of the steels after tempering at 650 and 700°C are performed. The impact toughness at – 30°C and the hardness of the steels are determined. The mass fraction of the carbide phase in the steels is computed with the help of the J-MatPro 4.0 software

Mitochondrial DNA Copy Number Is Associated with Breast Cancer Risk

Mitochondrial DNA (mtDNA) copy number in peripheral blood is associated with increased risk of several cancers. However, data from prospective studies on mtDNA copy number and breast cancer risk are lacking. We evaluated the association between mtDNA copy number in peripheral blood and breast cancer risk in a nested case-control study of 183 breast cancer cases with pre-diagnostic blood samples and 529 individually matched controls among participants of the Singapore Chinese Health Study. The mtDNA copy number was measured using real time PCR. Conditional logistic regression analyses showed that there was an overall positive association between mtDNA copy number and breast cancer risk (Ptrend = 0.01). The elevated risk for higher mtDNA copy numbers was primarily seen for women with <3 years between blood draw and cancer diagnosis; ORs (95% CIs) for 2nd, 3rd, 4th, and 5th quintile of mtDNA copy number were 1.52 (0.61, 3.82), 2.52 (1.03, 6.12), 3.12 (1.31, 7.43), and 3.06 (1.25, 7.47), respectively, compared with the 1st quintile (Ptrend = 0.004). There was no association between mtDNA copy number and breast cancer risk among women who donated a blood sample ≥3 years before breast cancer diagnosis (Ptrend = 0.41). This study supports a prospective association between increased mtDNA copy number and breast cancer risk that is dependent on the time interval between blood collection and breast cancer diagnosis. Future studies are warranted to confirm these findings and to elucidate the biological role of mtDNA copy number in breast cancer risk. © 2013 Thyagarajan et al

Reliability analysis of the Ahringer Caenorhabditis elegans RNAi feeding library: a guide for genome-wide screens

<p>Abstract</p> <p>Background</p> <p>The Ahringer <it>C. elegans </it>RNAi feeding library prepared by cloning genomic DNA fragments has been widely used in genome-wide analysis of gene function. However, the library has not been thoroughly validated by direct sequencing, and there are potential errors, including: 1) mis-annotation (the clone with the retired gene name should be remapped to the actual target gene); 2) nonspecific PCR amplification; 3) cross-RNAi; 4) mis-operation such as sample loading error, <it>etc</it>.</p> <p>Results</p> <p>Here we performed a reliability analysis on the Ahringer <it>C. elegans </it>RNAi feeding library, which contains 16,256 bacterial strains, using a bioinformatics approach. Results demonstrated that most (98.3%) of the bacterial strains in the library are reliable. However, we also found that 2,851 (17.54%) bacterial strains need to be re-annotated even they are reliable. Most of these bacterial strains are the clones having the retired gene names. Besides, 28 strains are grouped into unreliable category and 226 strains are marginal because of probably expressing unrelated double-stranded RNAs (dsRNAs). The accuracy of the prediction was further confirmed by direct sequencing analysis of 496 bacterial strains. Finally, a freely accessible database named CelRNAi (<url>http://biocompute.bmi.ac.cn/CelRNAi/</url>) was developed as a valuable complement resource for the feeding RNAi library by providing the predicted information on all bacterial strains. Moreover, submission of the direct sequencing result or any other annotations for the bacterial strains to the database are allowed and will be integrated into the CelRNAi database to improve the accuracy of the library. In addition, we provide five candidate primer sets for each of the unreliable and marginal bacterial strains for users to construct an alternative vector for their own RNAi studies.</p> <p>Conclusions</p> <p>Because of the potential unreliability of the Ahringer <it>C. elegans </it>RNAi feeding library, we strongly suggest the user examine the reliability information of the bacterial strains in the CelRNAi database before performing RNAi experiments, as well as the post-RNAi experiment analysis.</p

Assessing Performance of Orthology Detection Strategies Applied to Eukaryotic Genomes

Orthology detection is critically important for accurate functional annotation, and has been widely used to facilitate studies on comparative and evolutionary genomics. Although various methods are now available, there has been no comprehensive analysis of performance, due to the lack of a genomic-scale ‘gold standard’ orthology dataset. Even in the absence of such datasets, the comparison of results from alternative methodologies contains useful information, as agreement enhances confidence and disagreement indicates possible errors. Latent Class Analysis (LCA) is a statistical technique that can exploit this information to reasonably infer sensitivities and specificities, and is applied here to evaluate the performance of various orthology detection methods on a eukaryotic dataset. Overall, we observe a trade-off between sensitivity and specificity in orthology detection, with BLAST-based methods characterized by high sensitivity, and tree-based methods by high specificity. Two algorithms exhibit the best overall balance, with both sensitivity and specificity>80%: INPARANOID identifies orthologs across two species while OrthoMCL clusters orthologs from multiple species. Among methods that permit clustering of ortholog groups spanning multiple genomes, the (automated) OrthoMCL algorithm exhibits better within-group consistency with respect to protein function and domain architecture than the (manually curated) KOG database, and the homolog clustering algorithm TribeMCL as well. By way of using LCA, we are also able to comprehensively assess similarities and statistical dependence between various strategies, and evaluate the effects of parameter settings on performance. In summary, we present a comprehensive evaluation of orthology detection on a divergent set of eukaryotic genomes, thus providing insights and guides for method selection, tuning and development for different applications. Many biological questions have been addressed by multiple tests yielding binary (yes/no) outcomes but no clear definition of truth, making LCA an attractive approach for computational biology

Design of Experiments for Screening

The aim of this paper is to review methods of designing screening experiments, ranging from designs originally developed for physical experiments to those especially tailored to experiments on numerical models. The strengths and weaknesses of the various designs for screening variables in numerical models are discussed. First, classes of factorial designs for experiments to estimate main effects and interactions through a linear statistical model are described, specifically regular and nonregular fractional factorial designs, supersaturated designs and systematic fractional replicate designs. Generic issues of aliasing, bias and cancellation of factorial effects are discussed. Second, group screening experiments are considered including factorial group screening and sequential bifurcation. Third, random sampling plans are discussed including Latin hypercube sampling and sampling plans to estimate elementary effects. Fourth, a variety of modelling methods commonly employed with screening designs are briefly described. Finally, a novel study demonstrates six screening methods on two frequently-used exemplars, and their performances are compared

Regulation of Neuronal Cell Death by c-Abl-Hippo/MST2 Signaling Pathway

BACKGROUND: Mammalian Ste20-like kinases (MSTs) are the mammalian homologue of Drosophila hippo and play critical roles in regulation of cell death, organ size control, proliferation and tumorigenesis. MSTs exert pro-apoptotic function through cleavage, autophosphorylation and in turn phosphorylation of downstream targets, such as Histone H2B and FOXO (Forkhead box O). Previously we reported that protein kinase c-Abl mediates oxidative stress-induced neuronal cell death through phosphorylating MST1 at Y433, which is not conserved among mammalian MST2, Drosophila Hippo and C.elegans cst-1/2. METHODOLOGY/PRINCIPAL FINDINGS: Using immunoblotting, in vitro kinase and cell death assay, we demonstrate that c-Abl kinase phosphorylates MST2 at an evolutionarily conserved site, Y81, within the kinase domain. We further show that the phosphorylation of MST2 by c-Abl leads to the disruption of the interaction with Raf-1 proteins and the enhancement of homodimerization of MST2 proteins. It thereby enhances the MST2 activation and induces neuronal cell death. CONCLUSIONS/SIGNIFICANCE: The identification of the c-Abl tyrosine kinase as a novel upstream activator of MST2 suggests that the conserved c-Abl-MST signaling cascade plays an important role in oxidative stress-induced neuronal cell death

Analysis of the functional conservation of ethylene receptors between maize and Arabidopsis

Ethylene, a regulator of plant growth and development, is perceived by specific receptors that act as negative regulators of the ethylene response. Five ethylene receptors, i.e., ETR1, ERS1, EIN4, ETR2, and ERS2, are present in Arabidopsis and dominant negative mutants of each that confer ethylene insensitivity have been reported. In contrast, maize contains just two types of ethylene receptors: ZmERS1, encoded by ZmERS1a and ZmERS1b, and ZmETR2, encoded by ZmETR2a and ZmETR2b. In this study, we introduced a Cys to Tyr mutation in the transmembrane domain of ZmERS1b and ZmETR2b that is present in the etr1-1 dominant negative mutant and expressed each protein in Arabidopsis. Mutant Zmers1b and Zmetr2b receptors conferred ethylene insensitivity and Arabidopsis expressing Zmers1b or Zmetr2b were larger and exhibited a delay in leaf senescence characteristic of ethylene insensitive Arabidopsis mutants. Zmers1b and Zmetr2b were dominant and functioned equally well in a hemizygous or homozygous state. Expression of the Zmers1b N-terminal transmembrane domain was sufficient to exert dominance over endogenous Arabidopsis ethylene receptors whereas the Zmetr2b N-terminal domain failed to do so. Neither Zmers1b nor Zmetr2b functioned in the absence of subfamily 1 ethylene receptors, i.e., ETR1 and ERS1. These results suggest that Cys65 in maize ZmERS1b and ZmETR2b plays the same role that it does in Arabidopsis receptors. Moreover, the results demonstrate that the mutant maize ethylene receptors are functionally dependent on subfamily 1 ethylene receptors in Arabidopsis, indicating substantial functional conservation between maize and Arabidopsis ethylene receptors despite their sequence divergence

Solitary waves in the Nonlinear Dirac Equation

In the present work, we consider the existence, stability, and dynamics of solitary waves in the nonlinear Dirac equation. We start by introducing the Soler model of self-interacting spinors, and discuss its localized waveforms in one, two, and three spatial dimensions and the equations they satisfy. We present the associated explicit solutions in one dimension and numerically obtain their analogues in higher dimensions. The stability is subsequently discussed from a theoretical perspective and then complemented with numerical computations. Finally, the dynamics of the solutions is explored and compared to its non-relativistic analogue, which is the nonlinear Schr{\"o}dinger equation. A few special topics are also explored, including the discrete variant of the nonlinear Dirac equation and its solitary wave properties, as well as the PT-symmetric variant of the model

Naturally Occurring Osmolyte, Trehalose Induces Functional Conformation in an Intrinsically Disordered Activation Domain of Glucocorticoid Receptor

Intrinsically disordered (ID) regions are frequently found in the activation domains of many transcription factors including nuclear hormone receptors. It is believed that these ID regions promote molecular recognition by creating large surfaces suitable for interactions with their specific protein binding partners, which is a critical component of gene regulation by transcription factors. It has been hypothesized that conditional folding of these activation domains may be a prerequisite for their efficient interaction with specific coregulatory proteins, and subsequent transcriptional activity leading to the regulation of target gene(s). In this study, we tested whether a naturally occurring osmolyte, trehalose can promote functionally ordered conformation in glucocorticoid receptor's major activation function domain, AF1, which is found to exist as an ID protein, and requires an efficient interaction with coregulatory proteins for optimal activity. Our data show that trehalose induces an ordered conformation in AF1 such that its interaction with steroid receptor coactivator-1 (SRC-1), a critical coregulator of glucocorticoid receptor's activity, is greatly enhanced