Clear vision: a step towards unravelling student recruitment in English universities?

Purpose The recruitment of undergraduate students within English universities is of vital importance to both the academic success and the financial stability of the organisation. Despite the primacy of the task, there has been a dearth of research looking at related performance and how to ensure that the process is optimised. The purpose of this study was to investigate the degree of variation both within a university and between different universities. The reliance that individual programmes and/or universities place on the Clearing process is key; given its uncertainty, resource demands and timing shortly before students take up their places. Design/methodology/approach The Nomogramma di Gandy diagrammatical approach utilises readily available data to analyse universities’ performance in recruiting students to different programmes, and the degree to which they each rely of the Clearing process. Inter-university performance was investigated on a whole-student intake basis for a sample of English universities, representative of type and region. Findings The study found that there were disparate patterns for the many programmes within the pilot university and also disparate patterns between different types of universities across England. Accordingly, universities should internally benchmark their programmes to inform both strategic and tactical decision-making. Similarly, Universities and Colleges Admissions Service benchmarking inter-university patterns could inform the overall sector. Originality/value The approach and findings provide lessons for analysing student recruitment which could be critical to universities’ academic and financial health, in an increasingly competitive environment

Should tumor depth be included in prognostication of soft tissue sarcoma?

BACKGROUND: Most staging systems for soft tissue sarcoma are based on histologic malignancy-grade, tumor size and tumor depth. These factors are generally dichotomized, size at 5 cm. We believe it is unlikely that tumor depth per se should influence a tumor's metastatic capability. Therefore we hypothesized that the unfavourable prognostic importance of depth could be explained by the close association between size and depth, deep-seated tumors on average being larger than the superficial ones. When tumor size is dichotomized, this effect should be most pronounced in the large size (>5 cm) group in which the size span is larger. METHODS: We analyzed the associations between tumor size and depth and the prognostic importance of grade, size and depth in a population-based series of 490 adult patients with soft tissue sarcoma of the extremity or trunk wall with complete, 4.5 years minimum, follow-up. RESULTS: Multivariate analysis showed no major prognostic effect of tumor depth when grade and size were taken into account. The mean size of small tumors was the same whether superficial or deep but the mean size of large and deep-seated tumors were one third larger than that of large but superficial tumors. Tumor depth influenced the prognosis in the subset of high-grade and large tumors. In this subset deep-seated tumors had poorer survival rate than superficial tumors, which could be explained by the larger mean size of the deep-seated tumors. CONCLUSION: Most of the prognostic value of tumor depth in soft tissue sarcomas of the extremity or trunk wall can be explained by the association between tumor size and depth

Tyrosine kinase signalling in breast cancer: Modulation of tyrosine kinase signalling in human breast cancer through altered expression of signalling intermediates

The past decade has seen the definition of key signalling pathways downstream of receptor tyrosine kinases (RTKs) in terms of their components and the protein-protein interactions that facilitate signal transduction. Given the strong evidence that links signalling by certain families of RTKs to the progression of breast cancer, it is not surprising that the expression profile of key downstream signalling intermediates in this disease has also come under scrutiny, particularly because some exhibit transforming potential or amplify mitogenic signalling pathways when they are overexpressed. Reflecting the diverse cellular processes regulated by RTKs, it is now clear that altered expression of such signalling proteins in breast cancer may influence not only cellular proliferation (eg Grb2) but also the invasive properties of the cancer cells (eg EMS1/cortactin)

SMEs' Confidentiality Concerns for Security Information Sharing

Small and medium-sized enterprises are considered an essential part of the EU economy, however, highly vulnerable to cyberattacks. SMEs have specific characteristics which separate them from large companies and influence their adoption of good cybersecurity practices. To mitigate the SMEs' cybersecurity adoption issues and raise their awareness of cyber threats, we have designed a self-paced security assessment and capability improvement method, CYSEC. CYSEC is a security awareness and training method that utilises self-reporting questionnaires to collect companies' information about cybersecurity awareness, practices, and vulnerabilities to generate automated recommendations for counselling. However, confidentiality concerns about cybersecurity information have an impact on companies' willingness to share their information. Security information sharing decreases the risk of incidents and increases users' self-efficacy in security awareness programs. This paper presents the results of semi-structured interviews with seven chief information security officers of SMEs to evaluate the impact of online consent communication on motivation for information sharing. The results were analysed in respect of the Self Determination Theory. The findings demonstrate that online consent with multiple options for indicating a suitable level of agreement improved motivation for information sharing. This allows many SMEs to participate in security information sharing activities and supports security experts to have a better overview of common vulnerabilities. The final publication is available at Springer via https://doi.org/10.1007/978-3-030-57404-8_22Comment: 10 pages, 2 figures, 14th International Symposium on Human Aspects of Information Security & Assurance (HAISA 2020

Understanding animal fears: a comparison of the cognitive vulnerability and harm-looming models

Background: The Cognitive Vulnerability Model holds that both clinical and sub-clinical manifestations of animal fears are a result of how an animal is perceived, and can be used to explain both individual differences in fear acquisition and the uneven distribution of fears in the population. This study looked at the association between fear of a number of animals and perceptions of the animals as uncontrollable, unpredictable, dangerous and disgusting. Also assessed were the perceived loomingness, prior familiarity, and negative evaluation of the animals as well as possible conditioning experiences. Methods: 162 first-year University students rated their fear and perceptions of four high-fear and four low-fear animals. Results: Perceptions of the animals as dangerous, disgusting and uncontrollable were significantly associated with fear of both high- and low-fear animals while perceptions of unpredictability were significantly associated with fear of high-fear animals. Conditioning experiences were unrelated to fear of any animals. In multiple regression analyses, loomingness did not account for a significant amount of the variance in fear beyond that accounted for by the cognitive vulnerability variables. However, the vulnerability variables accounted for between 20% and 51% of the variance in all animals fears beyond that accounted for by perceptions of the animals as looming. Perceptions of dangerousness, uncontrollability and unpredictability were highly predictive of the uneven distribution of animal fears. Conclusion: This study provides support for the Cognitive Vulnerability Model of the etiology of specific fears and phobias and brings into question the utility of the harm-looming model in explaining animal fearJason M Armfiel

A Unique Radiation Scheme for the Treatment of High-Grade Non-Metastatic Soft Tissue Sarcoma: The Detroit Medical Center Experience

Purpose:This is the initial report on the utilization of combined photon irradiation followed by a neutron boost irradiation for the initial management of patients with high-grade non-metastatic soft tissue sarcoma (STS). We present data on local control, complications, disease-free survival and overall survival in patients at high risk for local relapse

Impact of Tumor Grade on Prognosis in Pancreatic Cancer: Should We Include Grade in AJCC Staging?

AJCC staging of pancreatic cancer (PAC) is used to determine prognosis, yet survival within each stage shows wide variation and remains unpredictable. We hypothesized that tumor grade might be responsible for some of this variation and that the addition of grade to current AJCC staging would provide improved prognostication. The Surveillance, Epidemiology, and End Results (SEER) database (1991–2005) was used to identify 8082 patients with resected PAC. The impact of grade on overall and stage-specific survival was assessed using Cox regression analysis. Variables in the model were age, sex, tumor size, lymph node status, and tumor grade. For each AJCC stage, survival was significantly worse for high-grade versus low-grade tumors. On multivariate analysis, high tumor grade was an independent predictor of survival for the entire cohort (hazard ratio [HR] 1.40, 95% confidence interval [95% CI] 1.31–1.48) as well as for stage I (HR 1.28, 95% CI 1.07–1.54), stage IIA (HR 1.43, 95% CI 1.26–1.61), stage IIB (HR 1.38, 95% CI 1.27–1.50), stage III (HR 1.28, 95% CI 1.02–1.59), and stage IV (HR 1.58, 95% CI 1.21–2.05) patients. The addition of grade to staging results in a statistically significant survival discrimination between all stages. Tumor grade is an important prognostic variable of survival in PAC. We propose a novel staging system incorporating grade into current AJCC staging for pancreas cancer. The improved prognostication is more reflective of tumor biology and may impact therapy decisions and stratification of future clinical trials

Interaction between O-GlcNAc Modification and Tyrosine Phosphorylation of Prohibitin: Implication for a Novel Binary Switch

Prohibitin (PHB or PHB1) is an evolutionarily conserved, multifunctional protein which is present in various cellular compartments including the plasma membrane. However, mechanisms involved in various functions of PHB are not fully explored yet. Here we report for the first time that PHB interacts with O-linked β-N-acetylglucosamine transferase (O-GlcNAc transferase, OGT) and is O-GlcNAc modified; and also undergoes tyrosine phosphorylation in response to insulin. Tyrosine 114 (Tyr114) and tyrosine 259 (Tyr259) in PHB are in the close proximity of potential O-GlcNAc sites serine 121 (Ser121) and threonine 258 (Thr258) respectively. Substitution of Tyr114 and Tyr259 residues in PHB with phenylalanine by site-directed mutagenesis results in reduced tyrosine phosphorylation as well as reduced O-GlcNAc modification of PHB. Surprisingly, this also resulted in enhanced tyrosine phosphorylation and activity of OGT. This is attributed to the presence of similar tyrosine motifs in PHB and OGT. Substitution of Ser121 and Thr258 with alanine and isoleucine respectively resulted in attenuation of O-GlcNAc modification and increased tyrosine phosphorylation of PHB suggesting an association between these two dynamic modifications. Sequence analysis of O-GlcNAc modified proteins having known O-GlcNAc modification site(s) or known tyrosine phosphorylation site(s) revealed a strong potential association between these two posttranslational modifications in various proteins. We speculate that O-GlcNAc modification and tyrosine phosphorylation of PHB play an important role in tyrosine kinase signaling pathways including insulin, growth factors and immune receptors signaling. In addition, we propose that O-GlcNAc modification and tyrosine phosphorylation is a novel previously unidentified binary switch which may provide new mechanistic insights into cell signaling pathways and is open for direct experimental examination

MICE: The muon ionization cooling experiment. Step I: First measurement of emittance with particle physics detectors

Copyright @ 2011 APSThe Muon Ionization Cooling Experiment (MICE) is a strategic R&D project intended to demonstrate the only practical solution to providing high brilliance beams necessary for a neutrino factory or muon collider. MICE is under development at the Rutherford Appleton Laboratory (RAL) in the United Kingdom. It comprises a dedicated beamline to generate a range of input muon emittances and momenta, with time-of-flight and Cherenkov detectors to ensure a pure muon beam. The emittance of the incoming beam will be measured in the upstream magnetic spectrometer with a scintillating fiber tracker. A cooling cell will then follow, alternating energy loss in Liquid Hydrogen (LH2) absorbers to RF cavity acceleration. A second spectrometer, identical to the first, and a second muon identification system will measure the outgoing emittance. In the 2010 run at RAL the muon beamline and most detectors were fully commissioned and a first measurement of the emittance of the muon beam with particle physics (time-of-flight) detectors was performed. The analysis of these data was recently completed and is discussed in this paper. Future steps for MICE, where beam emittance and emittance reduction (cooling) are to be measured with greater accuracy, are also presented.This work was supported by NSF grant PHY-0842798

Harvest: an open-source tool for the validation and improvement of peptide identification metrics and fragmentation exploration

<p>Abstract</p> <p>Background</p> <p>Protein identification using mass spectrometry is an important tool in many areas of the life sciences, and in proteomics research in particular. Increasing the number of proteins correctly identified is dependent on the ability to include new knowledge about the mass spectrometry fragmentation process, into computational algorithms designed to separate true matches of peptides to unidentified mass spectra from spurious matches. This discrimination is achieved by computing a function of the various features of the potential match between the observed and theoretical spectra to give a numerical approximation of their similarity. It is these underlying "metrics" that determine the ability of a protein identification package to maximise correct identifications while limiting false discovery rates. There is currently no software available specifically for the simple implementation and analysis of arbitrary novel metrics for peptide matching and for the exploration of fragmentation patterns for a given dataset.</p> <p>Results</p> <p>We present Harvest: an open source software tool for analysing fragmentation patterns and assessing the power of a new piece of information about the MS/MS fragmentation process to more clearly differentiate between correct and random peptide assignments. We demonstrate this functionality using data metrics derived from the properties of individual datasets in a peptide identification context. Using Harvest, we demonstrate how the development of such metrics may improve correct peptide assignment confidence in the context of a high-throughput proteomics experiment and characterise properties of peptide fragmentation.</p> <p>Conclusions</p> <p>Harvest provides a simple framework in C++ for analysing and prototyping metrics for peptide matching, the core of the protein identification problem. It is not a protein identification package and answers a different research question to packages such as Sequest, Mascot, X!Tandem, and other protein identification packages. It does not aim to maximise the number of assigned peptides from a set of unknown spectra, but instead provides a method by which researchers can explore fragmentation properties and assess the power of novel metrics for peptide matching in the context of a given experiment. Metrics developed using Harvest may then become candidates for later integration into protein identification packages.</p