The challenges of widening access to the medical profession: how to facilitate medical careers for those at a genuine disadvantage

Widening Participation (WP) for medical school entry has been politically encouraged to ensure access and participation for underrepresented groups rarely able to gain access to this high demand profession. Those who reside in the 20-40% most deprived postcodes in Scotland (SIMD20) are much less likely to apply for medical school entrance, and even less likely to succeed. The National Reach programme in Scotland aims to rectify the existing situation by encouraging and supporting students from working class backgrounds to apply to high demand courses, including medicine, and has achieved great success in helping pupils from target secondary schools to gain a place in Glasgow Medical School. However, some of the Reach students have similar demographics to the rest of the medical school class and arguably do not genuinely belong in the target group. To address this, a second flag based on SIMD20 residence was employed. However, applying more than one WP flag - while substantially improving the targeting of this programme and helping those who truly are multiply deprived - reduces the Reach-eligible applicant pool to the point of undermining the high WP targets imposed on Universities. But using only a single criterion of MD20 residence or school progression rate would unfairly advantage some pupils that are actually not disadvantaged. Ideally, individualised indicators such as eligibility for Free School Meals, possession of an Educational Maintenance Allowance or receipt of a UKCAT bursary, would complement residential data and school progression rates. This paper reflects on the evolution of the admissions practices in our medical school designed to comply with the targets, but also create a medical workforce reflecting the population it serves

Predictive power of UKCAT and other pre-admission measures for performance in a medical school in Glasgow: a cohort study

<b>Background</b><p></p> The UK Clinical Aptitude Test (UKCAT) and its four subtests are currently used by 26 Medical and Dental Schools in the UK for admissions. This longitudinal study examines the predictive validity of UKCAT for final performance in the undergraduate medical degree programme at one Medical School and compares this with the predictive validity of the selection measures available pre-UKCAT.<p></p> <b>Methods</b><p></p> This was a retrospective observational study of one cohort of students, admitted to Glasgow Medical School in 2007. We examined the associations which UKCAT scores, school science grades and pre-admissions interview scores had with performance indicators, particularly final composite scores that determine students' postgraduate training opportunities and overall ranking (Educational Performance Measure - EPM, and Honours and Commendation - H&C). Analyses were conducted both with and without adjustment for potential socio-demographic confounders (gender, age, ethnicity and area deprivation).<p></p> <b>Results</b><p></p> Despite its predictive value declining as students progress through the course, UKCAT was strongly associated with the final composite scores. In mutually adjusted analyses (also adjusted for socio-demographic confounders), only UKCAT total showed independent relationships with both EPM (p = 0.005) and H&C (p = 0.004). School science achievements predicted EPM (p = 0.009); pre-admissions interview score predicted neither. UKCAT showed less socio-demographic variation than did TSS.<p></p> <b>Conclusion</b><p></p> UKCAT has a modest predictive power for overall course performance at the University of Glasgow Medical School over and above that of school science achievements or pre-admission interview score and we conclude that UKCAT is the most useful predictor of final ranking

Increasing collaborative discussion in case-based learning improves student engagement and knowledge acquisition

Background: In the transition from academic to clinical learning, the development of clinical reasoning skills and teamwork is essential, but not easily achieved by didactic teaching only. Case-based learning (CBL) was designed to stimulate discussions of genuine clinical cases and diagnoses but in our initial format (CBL’10) remained predominantly tutor-driven rather than student-directed. However, interactive teaching methods stimulate deep learning and consolidate taught material, and we therefore introduced a more collaborative CBL (cCBL), featuring a structured format with discussions in small breakout groups. This aimed to increase student participation and improve learning outcomes. Method: A survey with open and closed questions was distributed among 149 students and 36 tutors that had participated in sessions of both CBL formats. A statistical analysis compared exam scores of topics taught via CBL’10 and cCBL. Results: Students and tutors both evaluated the switch to cCBL positively, reporting that it increased student participation and enhanced consolidation and integration of the wider subject area. They also reported that the cCBL sessions increased constructive discussion and stimulated deep learning. Moreover, tutors found the more structured cCBL sessions easier to facilitate. Analysis of exam results showed that summative assessment scores of subjects switched to cCBL significantly increased compared to previous years, whereas scores of subjects that remained taught as CBL’10 did not change. Conclusions: Compared to our initial, tutor-led CBL format, cCBL resulted in improved educational outcomes, leading to increased participation, confidence, discussion and higher exam scores

Internalization Dissociates β2-Adrenergic Receptors

G protein-coupled receptors (GPCRs) self-associate as dimers or higher-order oligomers in living cells. The stability of associated GPCRs has not been extensively studied, but it is generally thought that these receptors move between the plasma membrane and intracellular compartments as intact dimers or oligomers. Here we show that β2-adrenergic receptors (β2ARs) that self-associate at the plasma membrane can dissociate during agonist-induced internalization. We use bioluminescence-resonance energy transfer (BRET) to monitor movement of β2ARs between subcellular compartments. BRET between β2ARs and plasma membrane markers decreases in response to agonist activation, while at the same time BRET between β2ARs and endosome markers increases. Energy transfer between β2ARs is decreased in a similar manner if either the donor- or acceptor-labeled receptor is mutated to impair agonist binding and internalization. These changes take place over the course of 30 minutes, persist after agonist is removed, and are sensitive to several inhibitors of arrestin- and clathrin-mediated endocytosis. The magnitude of the decrease in BRET between donor- and acceptor-labeled β2ARs suggests that at least half of the receptors that contribute to the BRET signal are physically segregated by internalization. These results are consistent with the possibility that β2ARs associate transiently with each other in the plasma membrane, or that β2AR dimers or oligomers are actively disrupted during internalization

In Silico Veritas: The Pitfalls and Challenges of Predicting

Recently the first community-wide assessments of the prediction of the structures of complexes between proteins and small molecule ligands have been reported in the so-called GPCR Dock 2008 and 2010 assessments. In the current review we discuss the different steps along the protein-ligand modeling workflow by critically analyzing the modeling strategies we used to predict the structures of protein-ligand complexes we submitted to the recent GPCR Dock 2010 challenge. These representative test cases, focusing on the pharmaceutically relevant G Protein-Coupled Receptors, are used to demonstrate the strengths and challenges of the different modeling methods. Our analysis indicates that the proper performance of the sequence alignment, introduction of structural adjustments guided by experimental data, and the usage of experimental data to identify protein-ligand interactions are critical steps in the protein-ligand modeling protocol. © 2011 by the authors; licensee MDPI, Basel, Switzerland