A Partnership Approach to Higher Educational Accreditation of the UK’s National Direct Entry Superintendents Programme

The evolution of the UK’s high profile and first ever Direct-Entry (DE) Superintendents programme followed the recommendations for policing identified by Winsor (2012) and the UK Government’s vision of enabling “fresh thinking and fresh blood [to be] brought in from outside the profession” (Green, 2013). The eighteen�month DE programme aims to attract highly talented and proven leaders from alternative sectors directly into executive policing roles. The College of Policing’s (2015) own review identifies the importance for executive leaders to demonstrate on-going personal development. As a result a joint College of Policing and Teesside University team worked together to develop the Post Graduate Certificate in Strategic Police Leadership which was mapped onto the new DE education and training programme, resulting in the provision of an educational award which meets the needs of the contemporary police service. The programme has been designed primarily to be both academically and vocationally challenging, recognising the education and training previously completed by direct entry superintendents, who may not have any previous policing experience, who are joining the police service in senior executive roles. The aim being that on successful completion of the eighteen-month mandatory higher educational programme, learners will be able to operate independently across a wide range of strategic leadership deployments as competent uniformed superintendents, bringing with them a range of new skills and ideas to the service

A comparison of massively parallel nucleotide sequencing with oligonucleotide microarrays for global transcription profiling

<p>Abstract</p> <p>Background</p> <p>RNA-Seq exploits the rapid generation of gigabases of sequence data by Massively Parallel Nucleotide Sequencing, allowing for the mapping and digital quantification of whole transcriptomes. Whilst previous comparisons between RNA-Seq and microarrays have been performed at the level of gene expression, in this study we adopt a more fine-grained approach. Using RNA samples from a normal human breast epithelial cell line (MCF-10a) and a breast cancer cell line (MCF-7), we present a comprehensive comparison between RNA-Seq data generated on the Applied Biosystems SOLiD platform and data from Affymetrix Exon 1.0ST arrays. The use of Exon arrays makes it possible to assess the performance of RNA-Seq in two key areas: detection of expression at the granularity of individual exons, and discovery of transcription outside annotated loci.</p> <p>Results</p> <p>We found a high degree of correspondence between the two platforms in terms of exon-level fold changes and detection. For example, over 80% of exons detected as expressed in RNA-Seq were also detected on the Exon array, and 91% of exons flagged as changing from Absent to Present on at least one platform had fold-changes in the same direction. The greatest detection correspondence was seen when the read count threshold at which to flag exons Absent in the SOLiD data was set to <it>t</it><1 suggesting that the background error rate is extremely low in RNA-Seq. We also found RNA-Seq more sensitive to detecting differentially expressed exons than the Exon array, reflecting the wider dynamic range achievable on the SOLiD platform. In addition, we find significant evidence of novel protein coding regions outside known exons, 93% of which map to Exon array probesets, and are able to infer the presence of thousands of novel transcripts through the detection of previously unreported exon-exon junctions.</p> <p>Conclusions</p> <p>By focusing on exon-level expression, we present the most fine-grained comparison between RNA-Seq and microarrays to date. Overall, our study demonstrates that data from a SOLiD RNA-Seq experiment are sufficient to generate results comparable to those produced from Affymetrix Exon arrays, even using only a single replicate from each platform, and when presented with a large genome.</p

The utility of MAS5 expression summary and detection call algorithms

<p>Abstract</p> <p>Background</p> <p>Used alone, the MAS5.0 algorithm for generating expression summaries has been criticized for high False Positive rates resulting from exaggerated variance at low intensities.</p> <p>Results</p> <p>Here we show, with replicated cell line data, that, when used alongside detection calls, MAS5 can be both selective and sensitive. A set of differentially expressed transcripts were identified that were found to be changing by MAS5, but unchanging by RMA and GCRMA. Subsequent analysis by real time PCR confirmed these changes. In addition, with the Latin square datasets often used to assess expression summary algorithms, filtered MAS5.0 was found to have performance approaching that of its peers.</p> <p>Conclusion</p> <p>When used alongside detection calls, MAS5 is a sensitive and selective algorithm for identifying differentially expressed genes.</p

Left ventricular remodeling and hypertrophy in patients with aortic stenosis:insights from cardiovascular magnetic resonance

<p>Abstract</p> <p>Background</p> <p>Cardiovascular magnetic resonance (CMR) is the gold standard non-invasive method for determining left ventricular (LV) mass and volume but has not been used previously to characterise the LV remodeling response in aortic stenosis. We sought to investigate the degree and patterns of hypertrophy in aortic stenosis using CMR.</p> <p>Methods</p> <p>Patients with moderate or severe aortic stenosis, normal coronary arteries and no other significant valve lesions or cardiomyopathy were scanned by CMR with valve severity assessed by planimetry and velocity mapping. The extent and patterns of hypertrophy were investigated using measurements of the LV mass index, indexed LV volumes and the LV mass/volume ratio. Asymmetric forms of remodeling and hypertrophy were defined by a regional wall thickening <b>≥</b>13 mm and >1.5-fold the thickness of the opposing myocardial segment.</p> <p>Results</p> <p>Ninety-one patients (61±21 years; 57 male) with aortic stenosis (aortic valve area 0.93±0.32cm2) were recruited. The severity of aortic stenosis was unrelated to the degree (r²=0.012, P=0.43) and pattern (P=0.22) of hypertrophy. By univariate analysis, only male sex demonstrated an association with LV mass index (P=0.02). Six patterns of LV adaption were observed: normal ventricular geometry (n=11), concentric remodeling (n=11), asymmetric remodeling (n=11), concentric hypertrophy (n=34), asymmetric hypertrophy (n=14) and LV decompensation (n=10). Asymmetric patterns displayed considerable overlap in appearances (wall thickness 17±2mm) with hypertrophic cardiomyopathy.</p> <p>Conclusions</p> <p>We have demonstrated that in patients with moderate and severe aortic stenosis, the pattern of LV adaption and degree of hypertrophy do not closely correlate with the severity of valve narrowing and that asymmetric patterns of wall thickening are common.</p> <p>Trial registration</p> <p>ClinicalTrials.gov Reference Number: NCT00930735</p

The removal of multiplicative, systematic bias allows integration of breast cancer gene expression datasets – improving meta-analysis and prediction of prognosis

BACKGROUND: The number of gene expression studies in the public domain is rapidly increasing, representing a highly valuable resource. However, dataset-specific bias precludes meta-analysis at the raw transcript level, even when the RNA is from comparable sources and has been processed on the same microarray platform using similar protocols. Here, we demonstrate, using Affymetrix data, that much of this bias can be removed, allowing multiple datasets to be legitimately combined for meaningful meta-analyses. RESULTS: A series of validation datasets comparing breast cancer and normal breast cell lines (MCF7 and MCF10A) were generated to examine the variability between datasets generated using different amounts of starting RNA, alternative protocols, different generations of Affymetrix GeneChip or scanning hardware. We demonstrate that systematic, multiplicative biases are introduced at the RNA, hybridization and image-capture stages of a microarray experiment. Simple batch mean-centering was found to significantly reduce the level of inter-experimental variation, allowing raw transcript levels to be compared across datasets with confidence. By accounting for dataset-specific bias, we were able to assemble the largest gene expression dataset of primary breast tumours to-date (1107), from six previously published studies. Using this meta-dataset, we demonstrate that combining greater numbers of datasets or tumours leads to a greater overlap in differentially expressed genes and more accurate prognostic predictions. However, this is highly dependent upon the composition of the datasets and patient characteristics. CONCLUSION: Multiplicative, systematic biases are introduced at many stages of microarray experiments. When these are reconciled, raw data can be directly integrated from different gene expression datasets leading to new biological findings with increased statistical power

Midwall Fibrosis Is an Independent Predictor of Mortality in Patients With Aortic Stenosis

ObjectivesThe goal of this study was to assess the prognostic significance of midwall and infarct patterns of late gadolinium enhancement (LGE) in aortic stenosis.BackgroundMyocardial fibrosis occurs in aortic stenosis as part of the hypertrophic response. It can be detected by LGE, which is associated with an adverse prognosis in a range of other cardiac conditions.MethodsBetween January 2003 and October 2008, consecutive patients with moderate or severe aortic stenosis undergoing cardiovascular magnetic resonance with administration of gadolinium contrast were enrolled into a registry. Patients were categorized into absent, midwall, or infarct patterns of LGE by blinded independent observers. Patient follow-up was completed using patient questionnaires, source record data, and the National Strategic Tracing Service.ResultsA total of 143 patients (age 68 ± 14 years; 97 male) were followed up for 2.0 ± 1.4 years. Seventy-two underwent aortic valve replacement, and 27 died (24 cardiac, 3 sudden cardiac deaths). Compared with those with no LGE (n = 49), univariate analysis revealed that patients with midwall fibrosis (n = 54) had an 8-fold increase in all-cause mortality despite similar aortic stenosis severity and coronary artery disease burden. Patients with an infarct pattern (n = 40) had a 6-fold increase. Midwall fibrosis (hazard ratio: 5.35; 95% confidence interval: 1.16 to 24.56; p = 0.03) and ejection fraction (hazard ratio: 0.96; 95% confidence interval: 0.94 to 0.99; p = 0.01) were independent predictors of all-cause mortality by multivariate analysis.ConclusionsMidwall fibrosis was an independent predictor of mortality in patients with moderate and severe aortic stenosis. It has incremental prognostic value to ejection fraction and may provide a useful method of risk stratification. (The Prognostic Significance of Fibrosis Detection in Cardiomyopathy; NCT00930735

Climate emergency summit III:nature-based solutions report

An RSGS &amp; SNH report from the Climate Summit held in April 2020"The Climate Emergency is the result of burning fossils fuels and changes in the way we use the land that short-circuit global carbon and nitrogen cycles. To remain within safe climate limits (1.5-2°C), the remaining carbon budget for all people, and for all time, is now so small that stopping fossil fuel use, while essential, will not by itself address the problem. Changing the way we use the land and sea is now essential. Nature-based solutions are vital to creating a safe operating space for humanity. "Extract from the foreword by Dr Clive Mitchell, Outcome Manager: People and Nature, Scottish Natural Heritage. The report has 45 contributors for a variety of institutions

Holier than thou? Identity buffers and adoption of controversial practices in the Islamic banking category

Existing scholarship on categories frequently highlights how some category members may violate codes that others diligently abide by. In this paper, we take into account the differences in identity across category members, and ask how these relative differences determine their response to a code-violating change. Taking a case where category members are clearly identified as ‘insiders’ and ‘outsiders’, we argue that insiders’ reaction to a code violation depends upon the extent to which they believe their identity to be distinct from the code violator’s, who might be an insider or an outsider. Specifically, we suggest that it is the presence or absence of an ‘identity buffer’ – i.e., a relative identity advantage – which determines insiders’ reaction. We hypothesize that when a code violation is introduced by a fellow category insider, the focal insider will be more likely to refrain from the practice. When it is an outsider who introduces the code violation, insiders will be more likely to adopt the code violation as long as they can retain an identity buffer. We further posit that when outsiders adopt code-preserving behavior, thus narrowing the identity buffer between insiders and outsiders, it will mitigate insiders’ likelihood of code violation adoption. We test and find support for our hypotheses using data on Islamic banking industry in 12 countries (2003-2014)