An EM-based Semi-Parametric Mixture Model Approach to the Regression Analysis of Competing-Risks Data

We consider a mixture model approach to the regression analysis of competing-risks data. Attention is focused on inference concerning the effects of factors on both the probability of occurrence and the hazard rate conditional on each of the failure types. These two quantities are specified in the mixture model using the logistic model and the proportional hazards model, respectively. We propose a semi-parametric mixture method to estimate the logistic and regression coefficients jointly, whereby the component-baseline hazard functions are completely unspecified. Estimation is based on maximum likelihood on the basis of the full likelihood, implemented via an expectation-conditional maximization (ECM) algorithm. Simulation studies are performed to compare the performance of the proposed semi-parametric method with a fully parametric mixture approach. The results show that when the component-baseline hazard is monotonic increasing, the semi-parametric and fully parametric mixture approaches are comparable for mildly and moderately censored samples. When the component-baseline hazard is not monotonic increasing, the semi-parametric method consistently provides less biased estimates than a fully parametric approach and is comparable in efficiency in the estimation of the parameters for all levels of censoring. The methods are illustrated using a real data set of prostate cancer patients treated with different dosages of the drug diethylstilbestrol. Copyright (C) 2003 John Wiley Sons, Ltd.

Effect of changing data collection parameters on statistical motor unit number estimates

The effect of number of samples and selection of data for analysis on the calculation of surface motor unit potential (SMUP) size in the statistical method of motor unit number estimates (MUNE) was determined in 10 normal subjects and 10 with amyotrophic lateral sclerosis (ALS). We recorded 500 sequential compound muscle action potentials (CMAPs) at three different stable stimulus intensities (10–50% of maximal CMAP). Estimated mean SMUP sizes were calculated using Poisson statistical assumptions from the variance of 500 sequential CMAP obtained at each stimulus intensity. The results with the 500 data points were compared with smaller subsets from the same data set. The results using a range of 50–80% of the 500 data points were compared with the full 500. The effect of restricting analysis to data between 5–20% of the CMAP and to standard deviation limits was also assessed. No differences in mean SMUP size were found with stimulus intensity or use of different ranges of data. Consistency was improved with a greater sample number. Data within 5% of CMAP size gave both increased consistency and reduced mean SMUP size in many subjects, but excluded valid responses present at that stimulus intensity. These changes were more prominent in ALS patients in whom the presence of isolated SMUP responses was a striking difference from normal subjects. Noise, spurious data, and large SMUP limited the Poisson assumptions. When these factors are considered, consistent statistical MUNE can be calculated from a continuous sequence of data points. A 2 to 2.5 SD or 10% window are reasonable methods of limiting data for analysis. Muscle Nerve 27: 320–331, 2003

Model-based clustering in gene expression microarrays: An application to breast cancer data

In microarray studies, the application of clustering techniques is often used to derive meaningful insights into the data. In the past, hierarchical methods have been the primary clustering tool employed to perform this task. The hierarchical algorithms have been mainly applied heuristically to these cluster analysis problems. Further, a major limitation of these methods is their inability to determine the number of clusters. Thus there is a need for a model-based approach to these. clustering problems. To this end, McLachlan et al. [7] developed a mixture model-based algorithm (EMMIX-GENE) for the clustering of tissue samples. To further investigate the EMMIX-GENE procedure as a model-based -approach, we present a case study involving the application of EMMIX-GENE to the breast cancer data as studied recently in van 't Veer et al. [10]. Our analysis considers the problem of clustering the tissue samples on the basis of the genes which is a non-standard problem because the number of genes greatly exceed the number of tissue samples. We demonstrate how EMMIX-GENE can be useful in reducing the initial set of genes down to a more computationally manageable size. The results from this analysis also emphasise the difficulty associated with the task of separating two tissue groups on the basis of a particular subset of genes. These results also shed light on why supervised methods have such a high misallocation error rate for the breast cancer data.

America's nuclear deterrence in the age of terrorism

The September 11, 2001 terrorist attacks in the US and the leakage of the Nuclear Posture Report (NPR) spur a complete review of the nuclear doctrine under Pres George W. Bush's administration. Kampmark discusses the contrariness of NPR in relation to America's deterrence of nuclear weapons and the possible proliferation of tactical offensive weapons as compared to strategic nuclear weapons.

The Wilms' Tumour Suppressor Protein, WT1, Undergoes CRM1-independent Nucleocytoplasmic Shuttling

The Wilms' tumour suppressor gene (WT1) encodes a zinc finger-containing nuclear protein essential for kidney and urogenital development. Initially considered a transcription factor, there is mounting evidence that WT1 has a role in post-transcriptional processing. Using the interspecies heterokaryon assay, we have demonstrated that WT1 can undergo nucleocytoplasmic shuttling. We have also mapped the region responsible for nuclear export to residues 182-324. Our data add further complexity to the role of WT1 in trancriptional and post-transcriptional regulation. (C) 2003 Published by Elsevier B.V. on behalf of the Federation of European Biochemical Societies.

Zygosity Diagnosis in the Absence of Genotypic Data: An Approach Using Latent Class Analysis

For zygosity diagnosis in the absence of genotypic data, or in the recruitment phase of a twin study where only single twins from same-sex pairs are being screened, or to provide a test for sample duplication leading to the false identification of a dizygotic pair as monozygotic, the appropriate analysis of respondents' answers to questions about zygosity is critical. Using data from a young adult Australian twin cohort (N = 2094 complete pairs and 519 singleton twins from same-sex pairs with complete responses to all zygosity items), we show that application of latent class analysis (LCA), fitting a 2-class model, yields results that show good concordance with traditional methods of zygosity diagnosis, but with certain important advantages. These include the ability, in many cases, to assign zygosity with specified probability on the basis of responses of a single informant (advantageous when one zygosity type is being oversampled); and the ability to quantify the probability of misassignment of zygosity, allowing prioritization of cases for genotyping as well as identification of cases of probable laboratory error. Out of 242 twins (from 121 like-sex pairs) where genotypic data were available for zygosity confirmation, only a single case was identified of incorrect zygosity assignment by the latent class algorithm. Zygosity assignment for that single case was identified by the LCA as uncertain (probability of being a monozygotic twin only 76%), and the co-twin's responses clearly identified the pair as dizygotic (probability of being dizygotic 100%). In the absence of genotypic data, or as a safeguard against sample duplication, application of LCA for zygosity assignment or confirmation is strongly recommended.

The validity of publication and citation counts for Sociology and other selected disciplines

The use of bibliometric data is a means of comparing. research productivity and scholarly. impact for individuals, work groups, institutions and nations within and between disciplines. Central to this debate is the notion that disciplines differ in the ways in which,they exchange ideas and disseminate information and therefore have diverse publishing and citation patterns. In this article we use two different approaches to compiling bibliometric data to compare publishing patterns of five different disciplines that encompass Molecular Biology; Administration/Political Science, Psychology,. Philosophy and Sociology/Anthropology. We find that the social sciences differ from each other as well as from the physical sciences in their publication and citation patterns. Further, while the different ways of organizing the data produce somewhat different results, the substantive findings for the general patterning of publications and citations of disciplines are consistent for both data sets. Sociology/Anthropology, when compared with the other disciplines, shows substantial differences across universities.

Systematic characterization of mutations in yeast acetohydroxyacid synthase: Interpretation of herbicide-resistance data

Acetohydroxyacid synthase (AHAS, EC 4.1.3.18) catalyses the first step in branched-chain amino acid biosynthesis and is the target for sulfonylurea and imidazolinone herbicides, which act as potent and specific inhibitors. Mutants of the enzyme have been identified that are resistant to particular herbicides. However, the selectivity of these mutants towards various sulfonylureas and imidazolinones has not been determined systematically. Now that the structure of the yeast enzyme is known, both in the absence and presence of a bound herbicide, a detailed understanding of the molecular interactions between the enzyme and its inhibitors becomes possible. Here we construct 10 active mutants of yeast AHAS, purify the enzymes and determine their sensitivity to six sulfonylureas and three imidazolinones. An additional three active mutants were constructed with a view to increasing imidazolinone sensitivity. These three variants were purified and tested for their sensitivity to the imidazolinones only. Substantial differences are observed in the sensitivity of the 13 mutants to the various inhibitors and these differences are interpreted in terms of the structure of the herbicide-binding site on the enzyme.

The new nuclear danger by Helen Caldicott

No Abstract

Mechanisms of exercise training in patients with heart failure

Background The reduction of exercise capacity because of fatigue and dyspnea in patients with heart failure can be improved with exercise training. We sought to examine the mechanisms of exercise training, as an adjunctive treatment strategy for patients with heart failure. Methods a reviewed the published data on the possible mechanisms of effect of exercise training in heart failure. Results Symptoms of heart failure may be explained on the basis of abnormal skeletal muscle perfusion and structure and endothelial function. Exercise training has been shown to engender changes in muscle structure and biochemistry and vascular function, although effects on cardiac function have not been detected uniformly and may require longer training periods. Conclusions A suitable, long-term program of exercise training may reverse unfavorable interactions among the heart, vessels, and skeletal muscles. These improvements may be preserved with an ongoing maintenance program.

The AF-1 Domain of the Orphan Nuclear Receptor NOR-1 Mediates Trans-activation, Coactivator Recruitment, and Activation by the Purine Anti-metabolite 6-Mercaptopurine

NOR-1/NR4A3 is an orphan member of the nuclear hormone receptor superfamily. NOR-1 and its close relatives Nurr1 and Nur77 are members of the NR4A subgroup of nuclear receptors. Members of the NR4A subgroup are induced through multiple signal transduction pathways. They have been implicated in cell proliferation, differentiation, T-cell apoptosis, chondrosarcomas, neurological disorders, inflammation, and atherogenesis. However, the mechanism of transcriptional activation, coactivator recruitment, and agonist-mediated activation remain obscure. Hence, we examined the molecular basis of NOR-1-mediated activation. We observed that NOR-1 trans-activates gene expression in a cell- and target-specific manner; moreover, it operates in an activation function (AF)-1-dependent manner. The N-terminal AF-1 domain delimited to between amino acids 1 and 112, preferentially recruits the steroid receptor coactivator (SRC). Furthermore, SRC-2 modulates the activity of the AF-1 domain but not the C-terminal ligand binding domain (LBD). Homology modeling indicated that the NOR-1 LBD was substantially different from that of hRORbeta, a closely related AF-2-dependent receptor. In particular, the hydrophobic cleft characteristic of nuclear receptors was replaced with a very hydrophilic surface with a distinct topology. This observation may account for the inability of this nuclear receptor LBD to efficiently mediate cofactor recruitment and transcriptional activation. In contrast, the N-terminal AF-1 is necessary for cofactor recruitment and can independently conscript coactivators. Finally, we demonstrate that the purine anti-metabolite 6-mercaptopurine, a widely used antineoplastic and anti-inflammatory drug, activates NOR-1 in an AF-1-dependent manner. Additional 6-mercaptopurine analogs all efficiently activated NOR-1, suggesting that the signaling pathways that modulate proliferation via inhibition of de novo purine and/or nucleic acid biosynthesis are involved in the regulation NR4A activity. We hypothesize that the NR4A subgroup mediates the genotoxic stress response and suggest that this subgroup may function as sensors that respond to genotoxicity.

Low-temperature single-crystal Raman and neutron-diffraction study of the hydrogenous ammonium copper(II) tutton salt and the deuterated analogue in the metastable state

Low-temperature (15 K) single-crystal neutron-diffraction structures and Raman spectra of the salts (NX4)(2)[CU(OX2)(6)](SO4)(2), where X = H or D, are reported. This study is concerned with the origin of the structural phase change that is known to occur upon deuteration. Data for the deuterated salt were measured in the metastable state, achieved by application of 500 bar of hydrostatic pressure at similar to303 K followed by cooling to 281 K and the subsequent release of pressure. This allows for the direct comparison between the hydrogenous and deuterated salts, in the same modification, at ambient pressure and low temperature. The Raman spectra provide no intimation of any significant change in the intermolecular bonding. Furthermore, structural differences are few, the largest being for the long Cu-O bond, which is 2.2834(5) and 2.2802(4) Angstrom for the hydrogenous and the deuterated salts, respectively. Calorimetric data for the deuterated salt are also presented, providing an estimate of 0.17(2) kJ/mol for the enthalpy difference between the two structural forms at 295.8(5) K. The structural data suggest that substitution of hydrogen for deuterium gives rise to changes in the hydrogen-bonding interactions that result in a slightly reduced force field about the copper(II) center. The small structural differences suggest different relative stabilities for the hydrogenous and deuterated salts, which may be sufficient to stabilize the hydrogenous salt in the anomalous structural form.