Embedding generic employability skills in an accounting degree: development and impediments

This paper explores and analyses the views of, and effects on, students of a project that integrated the development of employability skills within the small group classes of two compulsory courses in the first year of an accounting degree at a UK university. The project aimed to build, deliver and evaluate course materials designed to encourage the development of a broad range of employability skills: skills needed for life-long learning and a successful business career. By analysing students' opinions gathered from a series of focus groups spread throughout the year, three prominent skill areas of interest were identified: time management, modelling, and learning to learn. Further analysis highlighted the complex nature of skills development, and brought to light a range of impediments and barriers to both students' development of employability skills and their subject learning. The analysis suggests the need for accounting educators to see skills development as being an essential element of the path to providing a successful accounting education experience

Gorenstein homological algebra and universal coefficient theorems

We study criteria for a ring—or more generally, for a small category—to be Gorenstein and for a module over it to be of finite projective dimension. The goal is to unify the universal coefficient theorems found in the literature and to develop machinery for proving new ones. Among the universal coefficient theorems covered by our methods we find, besides all the classic examples, several exotic examples arising from the KK-theory of C*-algebras and also Neeman’s Brown–Adams representability theorem for compactly generated categories

Characterization of BRD4 during mammalian post-meiotic sperm development

During spermiogenesis, the post-meiotic phase of mammalian spermatogenesis, transcription is progressively repressed as nuclei of haploid spermatids are compacted through a dramatic chromatin reorganization involving hyper-acetylation and replacement of most histones with protamines. Although BRDT functions in transcription and histone removal in spermatids, it is unknown whether other BET family proteins play a role. Immunofluorescence of spermatogenic cells revealed BRD4 in a ring around the nuclei of spermatids containing hyper-acetylated histones. The ring lies directly adjacent to the acroplaxome, the cytoskeletal base of the acrosome, previously linked to chromatin reorganization. The BRD4 ring does not form in acrosomal mutant mice. ChIP sequencing in spermatids revealed enrichment of BRD4 and acetylated histones at the promoters of active genes. BRD4 and BRDT show distinct and synergistic binding patterns, with a pronounced enrichment of BRD4 at spermatogenesis-specific genes. Direct association of BRD4 with acetylated H4 decreases in late spermatids as acetylated histones are removed from the condensing nucleus in a wave following the progressing acrosome. These data provide evidence for a prominent transcriptional role of BRD4 and suggest a possible removal mechanism for chromatin components from the genome via the progressing acrosome as transcription is repressed in response to chromatin condensation during spermiogenesis

White Matter Deterioration May Foreshadow Impairment of Emotional Valence Determination in Early-Stage Dementia of the Alzheimer Type

In Alzheimer Disease (AD), non-verbal skills often remain intact for far longer than verbally mediated processes. Four (1 female, 3 males) participants with early-stage Clinically Diagnosed Dementia of the Alzheimer Type (CDDAT) and eight neurotypicals (NTs; 4 females, 4 males) completed the emotional valence determination test (EVDT) while undergoing BOLD functional magnetic resonance imaging (fMRI). We expected CDDAT participants to perform just as well as NTs on the EVDT, and to display increased activity within the bilateral amygdala and right anterior cingulate cortex (r-ACC). We hypothesized that such activity would reflect an increased reliance on these structures to compensate for on-going neuronal loss in frontoparietal regions due to the disease. We used diffusion tensor imaging (DTI) to determine if white matter (WM) damage had occurred in frontoparietal regions as well. CDDAT participants had similar behavioral performance and no differences were observed in brain activity or connectivity patterns within the amygdalae or r-ACC. Decreased fractional anisotropy (FA) values were noted, however, for the bilateral superior longitudinal fasciculi and posterior cingulate cortex (PCC). We interpret these findings to suggest that emotional valence determination and non-verbal skill sets are largely intact at this stage of the disease, but signs foreshadowing future decline were revealed by possible WM deterioration. Understanding how non-verbal skill sets are altered, while remaining largely intact, offers new insights into how non-verbal communication may be more successfully implemented in the care of AD patients and highlights the potential role of DTI as a presymptomatic biomarker

Analysis of high-depth sequence data for studying viral diversity: a comparison of next generation sequencing platforms using Segminator II

Background: Next generation sequencing provides detailed insight into the variation present within viral populations, introducing the possibility of treatment strategies that are both reactive and predictive. Current software tools, however, need to be scaled up to accommodate for high-depth viral data sets, which are often temporally or spatially linked. In addition, due to the development of novel sequencing platforms and chemistries, each with implicit strengths and weaknesses, it will be helpful for researchers to be able to routinely compare and combine data sets from different platforms/chemistries. In particular, error associated with a specific sequencing process must be quantified so that true biological variation may be identified. Results: Segminator II was developed to allow for the efficient comparison of data sets derived from different sources. We demonstrate its usage by comparing large data sets from 12 influenza H1N1 samples sequenced on both the 454 Life Sciences and Illumina platforms, permitting quantification of platform error. For mismatches median error rates at 0.10 and 0.12%, respectively, suggested that both platforms performed similarly. For insertions and deletions median error rates within the 454 data (at 0.3 and 0.2%, respectively) were significantly higher than those within the Illumina data (0.004 and 0.006%, respectively). In agreement with previous observations these higher rates were strongly associated with homopolymeric stretches on the 454 platform. Outside of such regions both platforms had similar indel error profiles. Additionally, we apply our software to the identification of low frequency variants. Conclusion: We have demonstrated, using Segminator II, that it is possible to distinguish platform specific error from biological variation using data derived from two different platforms. We have used this approach to quantify the amount of error present within the 454 and Illumina platforms in relation to genomic location as well as location on the read. Given that next generation data is increasingly important in the analysis of drug-resistance and vaccine trials, this software will be useful to the pathogen research community. A zip file containing the source code and jar file is freely available for download from http://www.bioinf.manchester.ac.uk/segminator/

The Effect of the Earned Income Tax Credit in the District of Columbia on Poverty and Income Dynamics

Using unique longitudinal administrative tax panel data for the District of Columbia (DC), we assess the combined effect of the DC supplemental earned income tax credit (EITC) and the federal EITC on poverty and income dynamics within Washington, DC, from 2001 to 2011. The EITC in DC merits investigation, as the DC supplement to the federal credit is the largest in the nation. The supplemental DC EITC was enacted in 2000, and has been expanded from 10 percent of the federal credit in 2001 to 40 percent as of 2009. To implement the study, we estimate least squares models with 0/1 dependent variables to estimate the likelihood of net-EITC income above poverty and near-poverty thresholds. We also estimate the likelihood of earnings growth and income stabilization from the EITC. To identify the effect of the EITC, we exploit variation in the EITC subsidy rate from 2008 to 2009, when an additional EITC bracket of 45 percent was added for workers with three or more dependent children, up from 40 percent in the previous year for workers with two or more children. We also estimate a model examining the impact of city-level changes to the EITC. The structure and richness of our data enable us to control for tax filer fixed effects, an important innovation from many previous EITC studies. Overall, we find that the combined EITC raises the likelihood of net-EITC income above poverty and near poverty by as much as 9 percent, with the largest consistent effects accruing to single-parent families

High-Resolution Mapping of Expression-QTLs Yields Insight into Human Gene Regulation

Recent studies of the HapMap lymphoblastoid cell lines have identified large numbers of quantitative trait loci for gene expression (eQTLs). Reanalyzing these data using a novel Bayesian hierarchical model, we were able to create a surprisingly high-resolution map of the typical locations of sites that affect mRNA levels in cis. Strikingly, we found a strong enrichment of eQTLs in the 250 bp just upstream of the transcription end site (TES), in addition to an enrichment around the transcription start site (TSS). Most eQTLs lie either within genes or close to genes; for example, we estimate that only 5% of eQTLs lie more than 20 kb upstream of the TSS. After controlling for position effects, SNPs in exons are ∼2-fold more likely than SNPs in introns to be eQTLs. Our results suggest an important role for mRNA stability in determining steady-state mRNA levels, and highlight the potential of eQTL mapping as a high-resolution tool for studying the determinants of gene regulation

In Vitro and In Vivo Antagonism of a G Protein-Coupled Receptor (S1P3) with a Novel Blocking Monoclonal Antibody

Background: S1P 3 is a lipid-activated G protein-couple receptor (GPCR) that has been implicated in the pathological processes of a number of diseases, including sepsis and cancer. Currently, there are no available high-affinity, subtypeselective drug compounds that can block activation of S1P3. We have developed a monoclonal antibody (7H9) that specifically recognizes S1P3 and acts as a functional antagonist. Methodology/Principal Findings: Specific binding of 7H9 was demonstrated by immunocytochemistry using cells that over-express individual members of the S1P receptor family. We show, in vitro, that 7H9 can inhibit the activation of S1P3mediated cellular processes, including arrestin translocation, receptor internalization, adenylate cyclase inhibiton, and calcium mobilization. We also demonstrate that 7H9 blocks activation of S1P3 in vivo, 1) by preventing lethality due to systemic inflammation, and 2) by altering the progression of breast tumor xenografts. Conclusions/Significance: We have developed the first-reported monoclonal antibody that selectively recognizes a lipidactivated GPCR and blocks functional activity. In addition to serving as a lead drug compound for the treatment of sepsi