Flexible Distance-Based TCR Analysis in Python with tcrdist3.

Paired- and single-chain T cell receptor (TCR) sequencing are now commonly used techniques for interrogating adaptive immune responses. TCRs targeting the same epitope frequently share motifs consisting of critical contact residues. Here we illustrate the key features of tcrdist3, a new Python package for distance-based TCR analysis through a series of three interactive examples. In the first example, we illustrate how tcrdist3 can integrate sequence similarity networks, gene-usage plots, and background-adjusted CDR3 logos to identify TCR sequence features conferring antigen specificity among sets of peptide-MHC-multimer sorted receptors. In the second example, we show how the TCRjoin feature in tcrdist3 can be used to flexibly query receptor sequences of interest against bulk repertoires or libraries of previously annotated TCRs based on matching of similar sequences. In the third example, we show how the TCRdist metric can be leveraged to identify candidate polyclonal receptors under antigenic selection in bulk repertoires based on sequence neighbor enrichment testing, a statistical approach similar to TCRNET and ALICE algorithms, but with added flexibility in how the neighborhood can be defined.

Virtual auscultation course via video chat in times of COVID-19 improves cardiac auscultation skills compared to literature self-study in third-year medical students: a prospective randomized controlled cross-over study.

Background: Cardiac auscultation is a core clinical skill taught in medical school. Due to contact restrictions during the SARS-CoV-2 pandemic, interaction with patients was very limited. Therefore, a peer-to-peer virtual case-based auscultation course via video conference was established. Methods: A randomized controlled cross-over study was conducted to evaluate whether participation in a virtual auscultation course could improve heart auscultation skills in 3rd-year medical students. A total of sixty medical students were randomly assigned to either the experimental or control group after informed consent was obtained. Due to no-shows, 55 students participated. Depending on allocation, students attended three ninety-minute courses in intervals of one week in a different order: a virtual case-based auscultation course held via video chat, literature self-study, and an on-site course using a high-fidelity auscultation simulator (SAM II). The study's primary endpoint was the performance of the two groups at the simulator after participating in the virtual auscultation course or literature self-study. To evaluate their auscultation skills, students participated in five assessments using the same six pathologies: stenosis and regurgitation of the aortic and mitral valve, ventricular septal defect, and patent ductus arteriosus. Moreover, participants rated their satisfaction with each course and provided a self-assessment of competence. Results: Compared to literature self-study, participation in the virtual auscultation course led to a significantly improved description of heart murmurs at the auscultation simulator with regard to the presence in systole and diastole, low- and high-pitched sounds, and volume dynamics. There was no significant difference between the groups in diagnostic accuracy and identification of the point of maximal intensity. After the virtual course, students showed higher satisfaction rates and a higher increase in self-assessed competence compared to participants who engaged in literature self-study. Conclusions: For the first time, this study demonstrates that a case-based virtual auscultation course can improve aspects of cardiac auscultation skills on a simulator. This may facilitate the further acquisition of an essential clinical skill, even when contact restrictions will be lifted.