Ensuring the statistical soundness of competitive gene set approaches: gene filtering and genome-scale coverage are essential

In this article, we focus on the analysis of competitive gene set methods for detecting the statistical significance of pathways from gene expression data. Our main result is to demonstrate that some of the most frequently used gene set methods, GSEA, GSEArot and GAGE, are severely influenced by the filtering of the data in a way that such an analysis is no longer reconcilable with the principles of statistical inference, rendering the obtained results in the worst case inexpressive. A possible consequence of this is that these methods can increase their power by the addition of unrelated data and noise. Our results are obtained within a bootstrapping framework that allows a rigorous assessment of the robustness of results and enables power estimates. Our results indicate that when using competitive gene set methods, it is imperative to apply a stringent gene filtering criterion. However, even when genes are filtered appropriately, for gene expression data from chips that do not provide a genome-scale coverage of the expression values of all mRNAs, this is not enough for GSEA, GSEArot and GAGE to ensure the statistical soundness of the applied procedure. For this reason, for biomedical and clinical studies, we strongly advice not to use GSEA, GSEArot and GAGE for such data sets.

Dielectronic recombination of W 35 +

Accurate data for dielectronic recombination (DR) of the ions of tungsten are of significant interest in the modelling of tungsten impurity transport and radiative power loss in current tokamaks and in ITER. However, the complexity of the atomic structure for many of these ions makes level-resolved DR calculations untenable on currently available computers, especially for open d- and f-subshell ions. The majority of DR data presently available for ITER modelling are based on an average-atom approximation. To improve upon these baseline calculations, we investigate the use of the configuration-average distorted-wave (CADW) method to calculate DR rate coefficients for complex open d-shell systems. The aim is to produce rate coefficients that are sufficiently accurate in terms of modelling, yet greatly reduced in term of computational complexity compared to level-resolved calculations. In this paper, we consider the DR of W 35 + . Initially, we carry out several large-scale level-resolved calculations for the DR associated with the 4d → 4f and 4p → 4d excitations in this ion, using both the level-resolved distorted-wave and Dirac R -matrix methods. These calculations allow us to test the validity of the CADW approach on these same excitations by comparing cross sections and rate coefficients. These comparisons demonstrate that the CADW method is relatively accurate in relation to these level-resolved methods for the temperature range for which W 35 + should exist in a collisionally ionized plasma. We then present results for CADW rate coefficients for both Δ n = 0 and Δ n = 1 excitations for this ion. This study indicates that it is now feasible to generate a much improved comprehensive set of DR data for the entire tungsten isonuclear sequence.

Reduced vision in older adults with age related macular degeneration interferes with ability to care for self and impairs role as carer

Aim: To study the relation between visual impairment and ability to care for oneself or a dependant in older people with age related macular degeneration (AMD). Method: Cross sectional study of older people with visual impairment due to AMD in a specialised retinal service clinic. 199 subjects who underwent visual function assessment (fully corrected distance and near acuity and contrast sensitivity in both eyes), followed by completion of a package of questionnaires dealing with general health status (SF36), visual functioning (Daily Living Tasks Dependent on Vision, DLTV) and ability to care for self or provide care to others. The outcome measure was self reported ability to care for self and others. Three levels of self reported ability to care were identified—inability to care for self (level 1), ability to care for self but not others (level 2), and ability to care for self and others (level 3). Results: People who reported good general health status and visual functioning (that is, had high scores on SF36 and DLTV) were more likely to state that they were able to care for self and others. Similarly people with good vision in the better seeing eye were more likely to report ability to care for self and others. People with a distance visual acuity (DVA) worse than 0.4 logMAR (Snellen 6/15) had less than 50% probability of assigning themselves to care level 3 and those with DVA worse than 1.0 logMAR (Snellen 6/60) had a probability of greater than 50% or for assigning themselves to care level 1. Regression analyses with level of care as the dependent variable and demographic factors, DLTV subscales, and SF36 dimensions as the explanatory variables confirmed that the DLTV subscale 1 was the most important variable in the transition from care level 3 to care level 2. The regression analyses also confirmed that the DLTV subscale 2 was the most important in the transition from care level 3 to care level 1. Conclusions: Ability to care for self and dependants has a strong relation with self reported visual functioning and quality of life and is adversely influenced by visual impairment. The acuity at which the balance of probability shifts in the direction of diminished ability to care for self or others is lower than the level set by social care agencies for provision of support. These findings have implications for those involved with visual rehabilitation and for studies of the cost effectiveness of interventions in AMD.

PATHOLOGY AND RESIDUES IN VEAL CALVES TREATED EXPERIMENTALLY WITH CLENBUTEROL

Six veal calves were medicated with clenbuterol at 20 mu g kg bodyweightl day(-1) for 42 days before they were slaughtered, to evaluate the lesions and residues in target organs. Compared with six unmedicated calves the most noticeable changes were tracheal dilatation, decreased uterine weight, slight mucous hypersecretion in the uterus and vagina and depletion of liver glycogen. The highest concentrations of clenbuterol (62 to 128 ng/g(-1)) were recorded in the choroid/retina, and the aqueous humour had the lowest concentration (0.5 to 2.4 ng ml(-1)). The residue concentrations were higher than the maximum residue level set for clenbuterol (0.5 ng g(-1))

Double-detonation sub-Chandrasekhar supernovae: Can minimum helium shell masses detonate the core?

The explosion of sub-Chandrasekhar mass white dwarfs via the double detonation scenario is a potential explanation for type Ia supernovae. In this scenario, a surface detonation in a helium layer initiates a detonation in the underlying carbon/oxygen core leading to an explosion. For a given core mass, a lower bound has been determined on the mass of the helium shell required for dynamical burning during a helium flash, which is a necessary prerequisite for detonation. For a range of core and corresponding minimum helium shell masses, we investigate whether an assumed surface helium detonation is capable of triggering a subsequent detonation in the core even for this limiting case. We carried out hydrodynamic simulations on a co-expanding Eulerian grid in two dimensions assuming rotational symmetry. The detonations are propagated using the level-set approach and a simplified scheme for nuclear reactions that has been calibrated with a large nuclear network. The same network is used to determine detailed nucleosynthetic abundances in a post-processing step. Based on approximate detonation initiation criteria in the literature, we find that secondary core detonations are triggered for all of the simulated models, ranging in core mass from 0.810 up to 1.385 M? with corresponding shell masses from 0.126 down to 0.0035 M?. This implies that, as soon as a detonation triggers in a helium shell covering a carbon/oxygen white dwarf, a subsequent core detonation is virtually inevitable.

Development of sampling methods for Raman analysis of solid dosage forms of therapeutic and illicit drugs

The results of a study aimed at determining the most important experimental parameters for automated, quantitative analysis of solid dosage form pharmaceuticals (seized and model 'ecstasy' tablets) are reported. Data obtained with a macro-Raman spectrometer were complemented by micro-Raman measurements, which gave information on particle size and provided excellent data for developing statistical models of the sampling errors associated with collecting data as a series of grid points on the tablets' surface. Spectra recorded at single points on the surface of seized MDMA-caffeine-lactose tablets with a Raman microscope (lambda(ex) = 785 nm, 3 mum diameter spot) were typically dominated by one or other of the three components, consistent with Raman mapping data which showed the drug and caffeine microcrystals were ca 40 mum in diameter. Spectra collected with a microscope from eight points on a 200 mum grid were combined and in the resultant spectra the average value of the Raman band intensity ratio used to quantify the MDMA: caffeine ratio, mu(r), was 1.19 with an unacceptably high standard deviation, sigma(r), of 1.20. In contrast, with a conventional macro-Raman system (150 mum spot diameter), combined eight grid point data gave mu(r) = 1.47 with sigma(r) = 0.16. A simple statistical model which could be used to predict sigma(r) under the various conditions used was developed. The model showed that the decrease in sigma(r) on moving to a 150 mum spot was too large to be due entirely to the increased spot diameter but was consistent with the increased sampling volume that arose from a combination of the larger spot size and depth of focus in the macroscopic system. With the macro-Raman system, combining 64 grid points (0.5 mm spacing and 1-2 s accumulation per point) to give a single averaged spectrum for a tablet was found to be a practical balance between minimizing sampling errors and keeping overhead times at an acceptable level. The effectiveness of this sampling strategy was also tested by quantitative analysis of a set of model ecstasy tablets prepared from MDEA-sorbitol (0-30% by mass MDEA). A simple univariate calibration model of averaged 64 point data had R-2 = 0.998 and an r.m.s. standard error of prediction of 1.1% whereas data obtained by sampling just four points on the same tablet showed deviations from the calibration of up to 5%.

Revealing differences in gene network inference algorithms on the network level by ensemble methods

Motivation: The inference of regulatory networks from large-scale expression data holds great promise because of the potentially causal interpretation of these networks. However, due to the difficulty to establish reliable methods based on observational data there is so far only incomplete knowledge about possibilities and limitations of such inference methods in this context.

Results: In this article, we conduct a statistical analysis investigating differences and similarities of four network inference algorithms, ARACNE, CLR, MRNET and RN, with respect to local network-based measures. We employ ensemble methods allowing to assess the inferability down to the level of individual edges. Our analysis reveals the bias of these inference methods with respect to the inference of various network components and, hence, provides guidance in the interpretation of inferred regulatory networks from expression data. Further, as application we predict the total number of regulatory interactions in human B cells and hypothesize about the role of Myc and its targets regarding molecular information processing.

Decompressive hemicraniectomy following malignant middle cerebral artery infarctions:a mixed methods exploration of carer experience and level of burden

Purpose: This study explores the experiences and sense of burden of family carers of survivors of malignant middle cerebral artery infarctions who had undergone decompressive hemicraniectomy. To date, there have been no studies examining carer outcomes among this unique population. This study, taken alongside an already published study of survivor outcomes, provides a more holistic picture with regard to sequelae within the sample. Method: Six family carers completed the Sense of Competence Questionnaire and the Hospital Anxiety and Depression Scale. These results were compared with existing normative data. Carers also consented to a semi-structured interview. Interview data were examined using thematic content analysis. Consistent with the mixed methods design, quantitative and qualitative findings were integrated for further analysis. Results: While carers experienced many losses, their overall sense of burden was not outside 'Average' limits, nor did they experience clinically significant symptoms of depression. All carers identified methods of coping with the demands of caregiving. These included intrapersonal, interpersonal and practical strategies. All carers apart from one were able to identify areas of post-traumatic growth. Conclusion: Carers will benefit from information, support and care. In addition, problem solving skills are essential in managing the myriad difficulties that arise in the aftermath of stroke. [Box: see text].

Analysing partial ranks by using smoothed paired comparison methods:An investigation of value orientation in Europe

This paper introduces the paired comparison model as a suitable approach for the analysis of partially ranked data. For example, the Inglehart index, collected in international social surveys to examine shifts in post-materialistic values, generates such data on a set of attitude items. However, current analysis methods have failed to account for the complex shifts in individual item values, or to incorporate subject covariates. The paired comparison model is thus developed to allow for covariate subject effects at the individual level, and a reparameterization allows the inclusion of smooth non-linear effects of continuous covariates. The Inglehart index collected in the 1993 International Social Science Programme survey is analysed, and complex non-linear changes of item values with age, level of education and religion are identified. The model proposed provides a powerful tool for social scientists.

Harnessing the complexity of gene expression data from cancer: from single gene to structural pathway methods

High-dimensional gene expression data provide a rich source of information because they capture the expression level of genes in dynamic states that reflect the biological functioning of a cell. For this reason, such data are suitable to reveal systems related properties inside a cell, e.g., in order to elucidate molecular mechanisms of complex diseases like breast or prostate cancer. However, this is not only strongly dependent on the sample size and the correlation structure of a data set, but also on the statistical hypotheses tested. Many different approaches have been developed over the years to analyze gene expression data to (I) identify changes in single genes, (II) identify changes in gene sets or pathways, and (III) identify changes in the correlation structure in pathways. In this paper, we review statistical methods for all three types of approaches, including subtypes, in the context of cancer data and provide links to software implementations and tools and address also the general problem of multiple hypotheses testing. Further, we provide recommendations for the selection of such analysis methods.

Earthmoving trucks condition level prediction using neural networks

Purpose: The purpose of this paper is to present an artificial neural network (ANN) model that predicts earthmoving trucks condition level using simple predictors; the model’s performance is compared to the respective predictive accuracy of the statistical method of discriminant analysis (DA).

Design/methodology/approach: An ANN-based predictive model is developed. The condition level predictors selected are the capacity, age, kilometers travelled and maintenance level. The relevant data set was provided by two Greek construction companies and includes the characteristics of 126 earthmoving trucks.

Findings: Data processing identifies a particularly strong connection of kilometers travelled and maintenance level with the earthmoving trucks condition level. Moreover, the validation process reveals that the predictive efficiency of the proposed ANN model is very high. Similar findings emerge from the application of DA to the same data set using the same predictors.

Originality/value: Earthmoving trucks’ sound condition level prediction reduces downtime and its adverse impact on earthmoving duration and cost, while also enhancing the maintenance and replacement policies effectiveness. This research proves that a sound condition level prediction for earthmoving trucks is achievable through the utilization of easy to collect data and provides a comparative evaluation of the results of two widely applied predictive methods.

UK consensus project on quality in palliative day services: developing a quality indicator set using the RAND/UCLA appropriateness method

Introduction
Evaluating quality of palliative day services is essential for assessing care across diverse settings, and for monitoring quality improvement approaches.

Aim
To develop a set of quality indicators for assessment of all aspects (structure, process and outcome) of care in palliative day services.

Methods
Using a modified version of the RAND/UCLA appropriateness method (Fitch et al., 2001), a multidisciplinary panel of 16 experts independently completed a survey rating the appropriateness of 182 potential quality indicators previously identified during a systematic evidence review. Panel members then attended a one day, face-to-face meeting where indicators were discussed and subsequently re-rated. Panel members were also asked to rate the feasibility and necessity of measuring each indicator.

Results
71 indicators classified as inappropriate during the survey were removed based on median appropriateness ratings and level of agreement. Following the panel discussions, a further 60 were removed based on appropriateness and feasibility ratings, level of agreement and assessment of necessity. Themes identified during the panel discussion and findings of the evidence review were used to translate the remaining 51 indicators into a final set of 27.

Conclusion
The final indicator set included information on rationale and supporting evidence, methods of assessment, risk adjustment, and recommended performance levels. Further implementation work will test the suitability of this ‘toolkit’ for measurement and benchmarking. The final indicator set provides the basis for standardised assessment of quality across services, including care delivered in community and primary care settings.

Reference

• Fitch K, Bernstein SJ, Aguilar MD, et al. The RAND/UCLA Appropriateness Method User’s Manual. Santa Monica, CA: RAND Corporation; 2001. http://www.rand.org/pubs/monograph_reports/MR1269