Student at Risk Identification and Remedial Action System for Improving Retention on Computer Science Programmes

Retention has been a serious problem for computing programmes in the Computer Science and Creative Technology Department (CSCT) at the University of the West of England (UWE): for example in 2013-14 the BSc (Hons) Computer Science programme lost 18% of its year-one intake. Addressing this, CSCT developed a three-pronged strategy comprising retention research, the monitoring of module performance and the development of a student-at-risk-identification-and-remedial-action-system (SRIRAS). The last initiative was prioritised in 2015-16. An intern team was recruited to run a system to monitor student attendance and academic performance across seven CSCT programmes, identify those students most at risk and then, with the collaboration of programme leaders and year-tutors, help them. Help included phone calls, email warnings, and face-to-face meetings. The latter led to problem identification, advice on non-academic problems, encouragement to attend more lectures, tutorials and peer assisted learning (PAL) sessions, encouragement to engage with module staff, setting up special PAL sessions, and advice to attend catch-up programming sessions. Results indicated that many of those most at risk are struggling with non-academic concerns such as starting the programme late due to a visa problem, or not being able to attend due to a grant not arriving. Results also indicate that some students seem to be being “saved” while others do not. But overall, they indicate that the introduction of the retention system was mixed

Κυβερνοθετική

Γραμμένη μέσω των τεχνικών της μίξης και του μοντάζ, συγχωνεύοντας την αισθητική της επιστημονικής φαντασίας με τη φιλοσοφία των Ντελέζ και Γκουαταρί, η Κυβερνοθετική χαρτογραφεί ένα μέλλον που ίσως και να είναι ήδη εδώ. Με σημείο εκκίνησης τη «θετική ανάδραση» του Γουίνερ, το κείμενο συγκεράζει τις δυνάμεις τις αγοράς με τα συστήματα ασφάλειας και τα βιοπληροφοριακά μέσα για να καταδείξει το πως δημιουργούνται συνθήκες κρίσης στις κοινωνίες και αποσταθεροποιούνται οι κρατικές δομές διακυβέρνησης και ελέγχου

Inhibition of prenyltransferase activity by statins in both liver and muscle cell lines is not causative of cytotoxicity

As inhibitors of 3-hydroxy-3-methylglutaryl-CoA reductase, statins are an important first-line treatment for hypercholesterolemia. However, a recognized side-effect of statin therapy is myopathy, which in severe cases can present as potentially fatal rhabdomyolysis. This represents an important impediment to successful statin therapy, and despite decades of research the molecular mechanisms underlying this side-effect remain unclear. Current evidence supports a role for reduced levels of mevalonate pathway intermediates, with the most accepted hypothesis being a reduction in isoprenoids formation, leading to faulty post-translational modifications of membrane-associated proteins. We have undertaken a comprehensive analysis of the impact of nine statins on two human cell lines; Huh7 hepatoma and RD rhabdomyosarcoma. In both cell lines, concentration-dependent inhibition of prenylation was observed for cerivastatin and simvastatin, which could be rescued with the pathway intermediate mevalonate; in general, muscle cells were more sensitive to this effect, as measured by the levels of unprenylated Rap1A, a marker for prenylation by geranylgeranyl transferase I. Concentration-dependent toxicity was observed in both cell lines, with muscle cells again being more sensitive. Importantly, there was no correlation between inhibition of prenylation and cell toxicity, suggesting they are not causally linked. The lack of a causal relationship was confirmed by the absence of cytotoxicity in all cell lines following exposure to specific inhibitors of geranylgeranyl transferases I and II, and farnesyl transferase. As such, we provide strong evidence against the commonly accepted hypothesis linking inhibition of prenylation and statin-mediated toxicity, with the two processes likely to be simultaneous but independent

Design principles of nuclear receptor signaling: how complex networking improves signal transduction

Nuclear receptors often function in the cytoplasm.A triple conveyor belt pumps ligand (signal) into the nucleus and onto the DNA.The active export of importins enhances signaling to the nucleus.Sharing a single nuclear pore may reduce rather than increase crosstalk

Can a systems approach produce a better understanding of mood disorders?

Background: One in twenty-five people suffer from a mood disorder. Current treatments are sub-optimal with poor patient response and uncertain modes-of-action. There is thus a need to better understand underlying mechanisms that determine mood, and how these go wrong in affective disorders. Systems biology approaches have yielded important biological discoveries for other complex diseases such as cancer, and their potential in affective disorders will be reviewed. Scope of review: This review will provide a general background to affective disorders, plus an outline of experimental and computational systems biology. The current application of these approaches in understanding affective disorders will be considered, and future recommendations made. Major conclusions: Experimental systems biology has been applied to the study of affective disorders, especially at the genome and transcriptomic levels. However, data generation has been slowed by a lack of human tissue or suitable animal models. At present, computational systems biology has only be applied to understanding affective disorders on a few occasions. These studies provide sufficient novel biological insight to motivate further use of computational biology in this field. General significance: In common with many complex diseases much time and money has been spent on the generation of large-scale experimental datasets. The next step is to use the emerging computational approaches, predominantly developed in the field of oncology, to leverage the most biological insight from these datasets. This will lead to the critical breakthroughs required for more effective diagnosis, stratification and treatment of affective disorders