VIRAL PRODUCTION AND TRANSDUCTION FOR GENE-EDITING USING MICROFLUIDICS

Viral production and transduction have seen a considerable increase in use for gene therapies and especially vaccines (e.g., COVID-19) due to their abilities to deliver a significant amount of genetic information and integrate it into the genome. However, challenges associated with viral production/transduction involve steps that are very time consuming, manually intensive, and laborious. In efforts to expedite this process, we have created a microfluidic methodology that will provide a “hands-off” workflow in the genome engineering pipeline. In this work, we developed a platform which can generate lentiviral particles on-demand containing the gene-editing machinery that will be able to modify target breast cancer cell lines. © 2021 MicroTAS 2021 - 25th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.

Virtual Adaptation of Resident I-PASS Training Session During COVID-19.

Introduction: Effective communication during the patient handoff process is critical for ensuring patient safety. At our academic medical center, first-year interns complete hand-off training before starting clinical rotations. The purpose of this study was to evaluate a virtual handoff training for residents as an alternative to in-person sessions due to limitations imposed by COVID-19. Methods: Fifty residents were administered pre/post surveys to gauge the helpfulness of the training for clinical practice, familiarity and confidence in providing a hand-off, and whether they would recommend the virtual format for incoming interns. Additionally, faculty rated the virtual form of the hand-off activity, made comparisons to in-person sessions, and assessed the helpfulness of the session for residents in clinical practice. Results: Forty-four residents (88%) and 11 faculty (85%) completed surveys. After the training session, residents who received instruction and feedback reported significant improvements in familiarity with the hand-off tool and confidence in their hand-off abilities (both p < 0.001). Both residents and faculty were satisfied with the virtual format of hand-off training. Most faculty felt the virtual platform was comparable to in-person sessions and would recommend ongoing use of the virtual platform when in-person sessions were not possible. Conclusions: Teaching hospitals mandate resident training to include strategies for a uniform hand-off method to avoid medical errors. Adaptation to a virtual platform can be a successful instruction strategy, allowing for didactic and interactive sessions with direct faculty observation and feedback.

Hands Off: A Handshake Interaction Detection and Localization Model for COVID-19 Threat Control

The COVID-19 outbreak has affected millions of people across the globe and is continuing to spread at a drastic scale. Out of the numerous steps taken to control the spread of the virus, social distancing has been a crucial and effective practice. However, recent reports of social distancing violations suggest the need for non-intrusive detection techniques to ensure safety in public spaces. In this paper, a real-time detection model is proposed to identify handshake interactions in a range of realistic scenarios with multiple people in the scene and also detect multiple interactions in a single frame. The efficacy of the proposed model was evaluated across two different datasets on more than 3200 frames, thus enabling a robust localization model in different environments. The proposed model is the first dyadic interaction localizer in a multi-person setting, which enables it to be used in public spaces to identify handshake interactions and thereby identify and mitigate COVID-19 transmission. © 2021 IEEE.