Case-Based Collaborative Learning in Undergraduate Radiology Teaching-Are Essential Conditions for Group Discussions Met?

BACKGROUND: Delivering case-based collaborative learning (cCBL) at scale using technology that both presents the clinical problem authentically and seeks to foster quality group discussion is a challenge, especially argumentation which is critical for effective learning. The aim of this study was to investigate the presence of essential conditions to capitalize on a technology-enhanced cCBL scenario for teaching radiology and facilitating quality group discussion. METHODS: A questionnaire was administered to 114 fourth-year medical students who completed a technology-enhanced cCBL scenario for teaching neuroradiology. It consisted of individual online pre-class work and face-to-face in-class work, where group discussion followed individual work at a workstation. Items from the "Heedful Interrelating in Collaborative Educational Settings" scale and "positive emotional engagement" questionnaire assessed the quality of social-cognitive processes and emotional engagement during the group discussions. Structured interviews were used to explore the teachers' awareness of and engagement with the technology. RESULTS: The mean scores of most "heedfulness" items were below 3.5 (7-point scale), suggesting that participants did not enter the debriefing with a mindset conducive for argumentation. However, for the affective states "interest" and "enjoyment" the mean scores were above 5. Free text comments suggested participants enjoyed the superficial interactions, but did not necessarily engage in argumentation. Structured interviews revealed teachers were aware of the possibilities of the learning dashboard and used it as a common frame of reference, but did not really succeed to use it as a springboard for discussion. CONCLUSION: A technology-enhanced cCBL scenario is useful for teaching radiology in undergraduate medical education, but the added value of acquiring in-depth knowledge will only be achieved when students are aware of the importance of an "heedful" mind-set

Genetic Structure and Expansion of Golden Jackals (Canis aureus) in Europe and the Caucasus

We analyzed 65 samples of golden jackals (Canis aureus) collected in south-eastern and central Europe, the Caucasus, and from Estonia (north-eastern Europe). Microsatellite markers and partial sequences of the mitochondrial control region were used to characterize the genetic structure of jackals in the sampled regions. The main aim of the study was to identify possible source populations of the golden jackals in north-eastern Europe

Brown bear attacks on humans : a worldwide perspective

The increasing trend of large carnivore attacks on humans not only raises human safety concerns but may also undermine large carnivore conservation efforts. Although rare, attacks by brown bears Ursus arctos are also on the rise and, although several studies have addressed this issue at local scales, information is lacking on a worldwide scale. Here, we investigated brown bear attacks (n = 664) on humans between 2000 and 2015 across most of the range inhabited by the species: North America (n = 183), Europe (n = 291), and East (n = 190). When the attacks occurred, half of the people were engaged in leisure activities and the main scenario was an encounter with a female with cubs. Attacks have increased significantly over time and were more frequent at high bear and low human population densities. There was no significant difference in the number of attacks between continents or between countries with different hunting practices. Understanding global patterns of bear attacks can help reduce dangerous encounters and, consequently, is crucial for informing wildlife managers and the public about appropriate measures to reduce this kind of conflicts in bear country.Peer reviewe

Prognostic value of texture analysis from cardiac magnetic resonance imaging in patients with Takotsubo syndrome: a machine learning based proof-of-principle approach

Cardiac magnetic resonance (CMR) imaging has become an important technique for non-invasive diagnosis of takotsubo syndrome (TTS). The long-term prognostic value of CMR imaging in TTS has not been fully elucidated yet. This study sought to evaluate the prognostic value of texture analysis (TA) based on CMR images in patients with TTS using machine learning. In this multicenter study (InterTAK Registry), we investigated CMR imaging data of 58 patients (56 women, mean age 68 ± 12 years) with TTS. CMR imaging was performed in the acute to subacute phase (median time after symptom onset 4 days) of TTS. TA of the left ventricle was performed using free-hand regions-of-interest in short axis late gadolinium-enhanced and on T2-weighted (T2w) images. A total of 608 TA features adding the parameters age, gender, and body mass index were included. Dimension reduction was performed removing TA features with poor intra-class correlation coefficients (ICC ≤ 0.6) and those being redundant (correlation matrix with Pearson correlation coefficient r > 0.8). Five common machine-learning classifiers (artificial neural network Multilayer Perceptron, decision tree J48, NaïveBayes, RandomForest, and Sequential Minimal Optimization) with tenfold cross-validation were applied to assess 5-year outcome including major adverse cardiac and cerebrovascular events (MACCE). Dimension reduction yielded 10 TA features carrying prognostic information, which were all based on T2w images. The NaïveBayes machine learning classifier showed overall best performance with a sensitivity of 82.9% (confidence interval (CI) 80–86.2), specificity of 83.7% (CI 75.7–92), and an area-under-the receiver operating characteristics curve of 0.88 (CI 0.83–0.92). This proof-of-principle study is the first to identify unique T2w-derived TA features that predict long-term outcome in patients with TTS. These features might serve as imaging prognostic biomarkers in TTS patients.ISSN:2045-232