Medical Students' Perspectives on the Factors Affecting Empathy Development During Their Undergraduate Training.

INTRODUCTION: This study investigated the perspectives of medical students on the factors influencing empathy development during their undergraduate training. METHODOLOGY: A descriptive phenomenological approach was used to generate illustrations of empathy development and decline that had educational significance and applicability. Individual online semi-structured interviews were conducted to elicit experiential details from twelve final-year medical students. The interview recordings were transcribed verbatim, and data were analysed employing Braun and Clarke's thematic analysis method. RESULTS: The self-reported empathic behavior of medical students seemed to have improved with time in medical school. Students attributed their empathy development to real patient encounters, positive role-modelling by teachers, and attainment of confidence and personal maturity. They identified exams, academic overload, time constraints, personal stresses, negative role models, unconducive learning environments, and lack of formal empathy training as barriers to empathy development. CONCLUSION: Medical institutes should identify and address the barriers to empathy development and encourage the holistic development of medical students. Furthermore, medical educators should model their behavior accurately for their increasing roles and responsibilities and support the students in their empathic expressions with patients.

How to Improve the Efficacy of Student Feedback.

CONTEXT: Feedback processes are intricate, generally misunderstood, hard to execute efficiently, and often fail in their goals to influence students learning. Research highlights that students usually do not value the benefits of feedback. This paper reviews the literature on the definition, purpose, and models of feedback; and on exploring why some students do not value feedback, what factors are influencing the effectiveness of feedback, and how to improve the efficacy of feedback. EVIDENCE ACQUISITION: The relevant articles were searched through 'Google Scholar,' 'CINAHIL' and 'PubMed' using the key terms- "Student feedback," "Frameworks of feedback," "Barriers to effective feedback," and "Students' perspectives on feedback." The search criteria included: review and original research articles in the English language published in high-impact journals in the past ten years. RESULTS: The results of different studies have illuminated diverse factors demanding the attention of educators to the effectiveness of feedback. Personal, relational, procedural, and environmental factors seem to affect the utility of feedback. To be effective, feedback should be actionable, non-judgmental, descriptive and specific, based on observable behavior, and should be given at a mutually agreeable time and place. CONCLUSION: The efficacy of feedback can be enhanced by creating students' feedback literacy, addressing students' perceptions and expectations, encouraging productive educational alliances, improving procedural elements of feedback, and environmental conditions.

RNAPosers: Machine Learning Classifiers for Ribonucleic Acid-Ligand Poses.

Determining the three-dimensional (3D) structures of ribonucleic acid (RNA)-small molecule ligand complexes is critical to understanding molecular recognition in RNA. Computer docking can, in principle, be used to predict the 3D structure of RNA-small molecule complexes. Unfortunately, retrospective analysis has shown that the scoring functions that are typically used for pose prediction tend to misclassify non-native poses as native and vice versa. Here, we use machine learning to train a set of pose classifiers that estimate the relative "nativeness" of a set of RNA-ligand poses. At the heart of our approach is the use of a pose "fingerprint" (FP) that is a composite of a set of atomic FPs, which individually encode the local "RNA environment" around ligand atoms. We found that by ranking poses based on classification scores from our machine learning classifiers, we were able to recover native-like poses better than when we ranked poses based on their docking scores. With a leave-one-out training and testing approach, we found that one of our classifiers could recover poses that were within 2.5 Šof the native poses in ∼80% of the 80 cases we examined, and, on two separate validation sets, we could recover such poses in ∼60% of the cases. Our set of classifiers, which we refer to as RNAPosers, should find utility as a tool to aid in RNA-ligand pose prediction, and so we make RNAPosers open to the academic community via https://github.com/atfrank/RNAPosers.

Computational Protocol for Assessing the Optimal Pixel Size to Improve the Accuracy of Single-particle Cryo-electron Microscopy Maps.

Cryo-electron microscopy (cryo-EM) single-particle analysis has come a long way in achieving atomic-level resolution when imaging biomolecules. To obtain the best possible three-dimensional (3D) structure in cryo-EM, many parameters have to be carefully considered. Here we address the often-overlooked parameter of the pixel size, which describes the magnification of the image produced by the experiment. While efforts are made to refine and validate this parameter in the analysis of cryo-EM experimental data, there is no systematic protocol in place. Since the pixel size parameter can have an impact on the resolution and accuracy of a cryo-EM map, and the atomic resolution 3D structure models derived from it, we propose a computational protocol to estimate the appropriate pixel size parameter. In our protocol, we fit and refine atomic structures against cryo-EM maps at multiple pixel sizes. The resulting fitted and refined structures are evaluated using the GOAP (generalized orientation-dependent, all-atom statistical potential) score, which we found to perform better than other commonly used functions, such as Molprobity and the correlation coefficient from refinement. Finally, we describe the efficacy of this protocol in retrieving appropriate pixel sizes for several examples; simulated data based on yeast elongation factor 2 and experimental data from Gro-EL chaperone, beta-galactosidase, and the TRPV1 ion channel.

Team-based Learning Strategy in Biochemistry: Perceptions and Attitudes of Faculty and 1st-Year Medical Students.

BACKGROUND: Team-based learning (TBL) strategy has been widely adapted by medical schools all over the world, but the reports regarding the perceptions and the attitudes of faculty and undergraduate medical students towards TBL approach have been conflicting. AIM: The study aimed to introduce TBL strategy in curriculum of Biochemistry after evaluating its effectiveness through perceptions and attitudes of faculty and 1st-year medical students. MATERIALS AND METHODS: One hundred and fifty students of first professional M.B.B.S and five faculty members participated in the study. Their responses regarding perceptions and attitudes towards TBL strategy were collected using structured questionnaires, focus group discussions, and in-depth interviews. Data were analyzed using Wilcoxon signed-rank test, paired sample t-test, and Mann-Whitney U-test. RESULTS: Majority of the students expressed satisfaction with team approach and reported improvement in the academic scores, learning styles, and development of problem-solving, interpersonal, and professional skills. The faculty, however, recommended a modified TBL approach to benefit all sections of the students for the overall success of this intervention. CONCLUSION: TBL is an effective technique to enable the students to master the core concepts and develop professional and critical thinking skills; however, for the 1st-year medical students, a modified TBL approach might be more appropriate for the effective outcomes.

Rapid transformation of chronic lymphocytic leukemia to acute lymphoblastic leukemia: A rare case report.

Chronic lymphocytic leukemia (CLL) is characterized by the accumulation of mature-appearing lymphocytes in blood, bone marrow, lymph nodes, and spleen with a median lymphocyte count of 20-30 × 10(9)/L at the time of diagnosis. In half of the patients, the lymphocyte count doubles over a period of 1-year and cyclic rise up to 50 × 10(9)/L can occur in untreated patients while in others the count may remain stable for years. Based on the cytogenetic and molecular studies, it has been demonstrated that multiple clones may occur in CLL and clonal evolution is a frequent occurrence. The transformation of CLL to a high-grade non-Hodgkin's lymphoma such as diffuse large B cell lymphoma, Hodgkin lymphoma, and prolymphocytic leukemia is well documented. Whereas the transformation of CLL to acute leukemia occurs in <1% cases and this contrasts the almost invariable progression in patients with chronic myeloid leukemia. Here, we report a rare case of a 55-year-old lady, a diagnosed case of CLL transforming into B-cell acute lymphocytic leukemia over a very short interval of 1 week period.