Comparing families of dynamic causal models

Mathematical models of scientific data can be formally compared using Bayesian model evidence. Previous applications in the biological sciences have mainly focussed on model selection in which one first selects the model with the highest evidence and then makes inferences based on the parameters of that model. This “best model” approach is very useful but can become brittle if there are a large number of models to compare, and if different subjects use different models. To overcome this shortcoming we propose the combination of two further approaches: (i) family level inference and (ii) Bayesian model averaging within families. Family level inference removes uncertainty about aspects of model structure other than the characteristic of interest. For example: What are the inputs to the system? Is processing serial or parallel? Is it linear or nonlinear? Is it mediated by a single, crucial connection? We apply Bayesian model averaging within families to provide inferences about parameters that are independent of further assumptions about model structure. We illustrate the methods using Dynamic Causal Models of brain imaging data

Accounting students' IT applicaton skills over a 10-year period

This paper reports on the changing nature of a range of information technology (IT) application skills that students declare on entering an accounting degree over the period from 1996 to 2006. Accounting educators need to be aware of the IT skills students bring with them to university because of the implications this has for learning and teaching within the discipline and the importance of both general and specific IT skills within the practice and craft of accounting. Additionally, IT skills constitute a significant element within the portfolio of employability skills that are increasingly demanded by employers and emphasized within the overall Higher Education (HE) agenda. The analysis of students' reported IT application skills on entry to university, across a range of the most relevant areas of IT use in accounting, suggest that their skills have continued to improve over time. However, there are significant differential patterns of change through the years and within cohorts. The paper addresses the generalizability of these findings and discusses the implications of these factors for accounting educators, including the importance of recognising the differences that are potentially masked by the general increase in skills; the need for further research into the changing nature, and implications, of the gender gap in entrants' IT application skills; and the low levels of entrants' spreadsheet and database skills that are a cause for concern

Pope Leo IX: A reforming pope?

No abstract available

A fresh look at the evolution and diversification of photochemical reaction centers

In this review, I reexamine the origin and diversification of photochemical reaction centers based on the known phylogenetic relations of the core subunits, and with the aid of sequence and structural alignments. I show, for example, that the protein folds at the C-terminus of the D1 and D2 subunits of Photosystem II, which are essential for the coordination of the water-oxidizing complex, were already in place in the most ancestral Type II reaction center subunit. I then evaluate the evolution of reaction centers in the context of the rise and expansion of the different groups of bacteria based on recent large-scale phylogenetic analyses. I find that the Heliobacteriaceae family of Firmicutes appears to be the earliest branching of the known groups of phototrophic bacteria; however, the origin of photochemical reaction centers and chlorophyll synthesis cannot be placed in this group. Moreover, it becomes evident that the Acidobacteria and the Proteobacteria shared a more recent common phototrophic ancestor, and this is also likely for the Chloroflexi and the Cyanobacteria. Finally, I argue that the discrepancies among the phylogenies of the reaction center proteins, chlorophyll synthesis enzymes, and the species tree of bacteria are best explained if both types of photochemical reaction centers evolved before the diversification of the known phyla of phototrophic bacteria. The primordial phototrophic ancestor must have had both Type I and Type II reaction centers

Transverse spin dependence of pp total cross‐sections

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87331/2/72_1.pd

Transverse-spin dependence of the p-p total cross section ΔσT from 0.8 to 2.5 GeV/c

The difference ΔσT=σ(↓↑)-σ(↑↑) between the proton-proton total cross sections for protons in pure transverse-spin states, was measured at incident momenta 0.8 to 2.5 GeV/c in experiments performed at the Los Alamos Clinton P. Anderson Meson Physics Facility and the Argonne Zero Gradient Synchrotron. In agreement with other data, peaks were observed at center-of-mass energies of 2.14 and 2.43 GeV/c2, where 1D2 and 1G4 dibaryon resonances have been proposed

Bayesian Mode Regression

This article has been made available through the Brunel Open Access Publishing Fund.Like mean, quantile and variance, mode is also an important measure of central tendency of a distribution. Many practical questions, particularly in the analysis of big data, such as \Which element (gene or le or signal) is the most typical one among all elements in a network?" are directly related to mode. Mode regression, which provides a convenient summary of how the regressors a ect the conditional mode, is totally di erent from other models based on conditional mean or conditional quantile or conditional variance. Some inference methods for mode regression exist but none of them is from the Bayesian perspective. This paper introduces Bayesian mode regression by exploring three different approaches, including their theoretic properties. The proposed approacher are illustrated using simulated datasets and a real data set

Co-expression of CD147 (EMMPRIN), CD44v3-10, MDR1 and monocarboxylate transporters is associated with prostate cancer drug resistance and progression

Background: The aim of this study is to seek an association between markers of metastatic potential, drug resistance-related protein and monocarboxylate transporters in prostate cancer (CaP). Methods: We evaluated the expression of invasive markers (CD147, CD44v3-10), drug-resistance protein (MDR1) and monocarboxylate transporters (MCT1 and MCT4) in CaP metastatic cell lines and CaP tissue microarrays (n=140) by immunostaining. The co-expression of CD147 and CD44v3-10 with that of MDR1, MCT1 and MCT4 in CaP cell lines was evaluated using confocal microscopy. The relationship between the expression of CD147 and CD44v3-10 and the sensitivity (IC50) to docetaxel in CaP cell lines was assessed using MTT assay. The relationship between expression of CD44v3-10, MDR1 and MCT4 and various clinicopathological CaP progression parameters was examined. Results: CD147 and CD44v3-10 were co-expressed with MDR1, MCT1 and MCT4 in primary and metastatic CaP cells. Both CD147 and CD44v3-10 expression levels were inversely related to docetaxel sensitivity (IC50) in metastatic CaP cell lines. Overexpression of CD44v3-10, MDR1 and MCT4 was found in most primary CaP tissues, and was significantly associated with CaP progression. Conclusions: Our results suggest that the overexpression of CD147, CD44v3-10, MDR1 and MCT4 is associated with CaP progression. Expression of both CD147 and CD44v3-10 is correlated with drug resistance during CaP metastasis and could be a useful potential therapeutic target in advanced disease