Investigating the performance of medical students in anatomy examinations 2002-07

Medical students are examined four times in anatomy over two years. There is a progress test in January each year (formative) and a final summative examination in June. The purpose of this study was to examine the performance of undergraduate medical students of the University of Malta in anatomy over 4 semesters. We were specifically interested in the ways in which students’ results in the final anatomy exam could be predicted by their performance in the previous anatomy exams. We also investigated whether the strength of this correlation and the students’ actual performance were affected by their gender or nationality.peer-reviewe

Neural Networks for Modeling and Control of Particle Accelerators

We describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.Comment: 21 p

Eco-Driving Strategy Implementation for Ultra-Efficient Lightweight Electric Vehicles in Realistic Driving Scenarios

This paper aims to provide a quantitative assessment of the effect of driver action and road traffic conditions in the real implementation of eco-driving strategies. The study specifically refers to an ultra-efficient battery-powered electric vehicle designed for energy-efficiency competitions. The method is based on the definition of digital twins of vehicle and driving scenario. The models are used in a driving simulator to accurately evaluate the power demand. The vehicle digital twin is built in a co-simulation environment between VI-CarRealTime and Simulink. A digital twin of the Brooklands Circuit (UK) is created leveraging the software RoadRunner. After validation with actual telemetry acquisitions, the model is employed offline to find the optimal driving strategy, namely, the optimal input throttle profile, which minimizes the energy consumption over an entire lap. The obtained reference driving strategy is used during real-time driving sessions at the dynamic driving simulator installed at Politecnico di Milano (DriSMi) to include the effects of human driver and road traffic conditions. Results assess that, in a realistic driving scenario, the energy demand could increase more than 20% with respect to the theoretical value. Such a reduction in performance can be mitigated by adopting eco-driving assistance systems

Stabilized Weighted Reduced Basis Methods for Parametrized Advection Dominated Problems with Random Inputs

In this work, we propose viable and efficient strategies for stabilized parametrized advection dominated problems, with random inputs. In particular, we investigate the combination of wRB (weighted reduced basis) method for stochastic parametrized problems with stabilized reduced basis method, which is the integration of classical stabilization methods (SUPG, in our case) in the Offline--Online structure of the RB method. Moreover, we introduce a reduction method that selectively enables online stabilization; this leads to a sensible reduction of computational costs, while keeping a very good accuracy with respect to high fidelity solutions. We present numerical test cases to assess the performance of the proposed methods in steady and unsteady problems related to heat transfer phenomena

Fertility in a i(Xq) Klinefelter patient: importance of XIST expression level determined by qRT-PCR in ruling out Klinefelter cryptic mosaicism as cause of oligozoospermia

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Combining the Multitargeted Tyrosine Kinase Inhibitor Vandetanib with the Antiestrogen Fulvestrant Enhances Its Antitumor Effect in Non-small Cell Lung Cancer

IntroductionEstrogen is known to promote proliferation and to activate the epidermal growth factor receptor (EGFR) in non-small cell lung cancer (NSCLC). Vascular endothelial growth factor (VEGF) is a known estrogen responsive gene in breast cancer. We sought to determine whether the VEGF pathway is also regulated by estrogen in lung cancer cells, and whether combining an inhibitor of the ER pathway with a dual vascular endothelial growth factor receptor (VEGFR)/EGFR inhibitor would show enhanced antitumor effects.MethodsWe examined activation of EGFR and expression of VEGF in response to β-estradiol, and the antitumor activity of the multitargeted VEGFR/EGFR/RET inhibitor, vandetanib, when combined with the antiestrogen fulvestrant both in vitro and in vivo.ResultsNSCLC cells expressed VEGFR-3 and EGFR. Vandetanib treatment of NSCLC cells resulted in inhibition of EGFR and VEGFR-3 and inhibition of β-estradiol-induced P-MAPK activation, demonstrating that vandetanib blocks β-estradiol-induced EGFR signaling. Treatment with β-estradiol stimulated VEGFA mRNA and protein (p < 0.0001 over baseline), suggesting estrogenic signaling causes heightened VEGFA pathway activation. This estrogenic induction of VEGFA mRNA seems largely dependent on cross-talk with EGFR. Long-term vandetanib treatment also significantly increased ERβ protein expression. The combination of vandetanib with fulvestrant maximally inhibited cell growth compared with single agents (p < 0.0001) and decreased tumor xenograft volume by 64%, compared with 51% for vandetanib (p < 0.05) and 23% for fulvestrant (p < 0.005). Antitumor effects of combination therapy were accompanied by a significant increase in apoptotic cells compared with single agents.ConclusionsFulvestrant may enhance effects of vandetanib in NSCLC by blocking estrogen-driven activation of the EGFR pathway