Incorporating Diversity, Equity, and Inclusion Content Into Bioengineering Curricula: A Program-Level Approach.

Diversity, equity, and inclusion (DEI) are interconnected with bioengineering, yet have historically been absent from accreditation standards and curricula. Toward educating DEI-competent bioengineers and meeting evolving accreditation requirements, we took a program-level approach to incorporate, catalog, and assess DEI content through the bioengineering undergraduate program. To support instructors in adding DEI content and inclusive pedagogy, our team developed a DEI planning worksheet and surveyed instructors pre- and post-course. Over the academic year, 74% of instructors provided a pre-term and/or post-term response. Of responding instructors, 91% described at least one DEI curricular content improvement, and 88% incorporated at least one new inclusive pedagogical approach. Based on the curricular adjustments reported by instructors, we grouped the bioengineering-related DEI content into five DEI competency categories: bioethics, inclusive design, inclusive scholarship, inclusive professionalism, and systemic inequality. To assess the DEI content incorporation, we employed direct assessment via course assignments, end-of-module student surveys, end-of-term course evaluations, and an end-of-year program review. When asked how much their experience in the program helped them develop specific DEI competencies, students reported a relatively high average of 3.79 (scale of 1 = "not at all" to 5 = "very much"). Additionally, based on student performance in course assignments and other student feedback, we found that instructors were able to effectively incorporate DEI content into a wide variety of courses. We offer this framework and lessons learned to be adopted by programs similarly motivated to train DEI-competent engineering professionals and provide an equitable, inclusive engineering education for all students.

Innovations in Remote Teaching of Engineering Design Teams.

The University of Washington's Engineering Innovation in Health program is a yearlong engineering design course sequence where senior undergraduate and graduate engineering students across different disciplines work in teams with health professionals to address their unmet needs. With the onset of the COVID-19 pandemic, these team- and project-based courses shifted from an in-person to remote course environment. Here, we share innovative teaching strategies for a team-based, remote course environment. We show how this shift affected productivity by comparing survey results from before (in person) and during (remote) the pandemic. Preliminary results show that overall project outcomes and productivity were as high or, in some cases, higher during the pandemic than prior to the pandemic. These findings suggest that the innovative remote teaching strategies implemented by the teaching team provided effective options in the absence of certain hands-on experiences that are considered critical to engineering capstone design courses. A discussion on these teaching strategies in the context beyond the pandemic are considered in the discussion.

The use of positron emission tomography and [18F]fluorodeoxyglucose for functional imaging of muscular activity during exercise with a stride assistance system.

The aim of this study was to investigate the use of [18F]fluorodeoxyglucose and positron emission tomography (FDG PET) for quantitative evaluation of glucose metabolism in skeletal muscle during walking. Ten young males underwent FDG PET twice during walks, which were done with or without an automated stride assistance system (SAS). Walk ratios were significantly increased by the SAS in seven subjects. Regional glucose metabolism in muscles between the crista iliaca and the planta was clearly visualized in all ten subjects. Glucose utilization increased significantly in the tibialis posterior and medial gastrocnemius muscles of the seven subjects in whom walk ratios were increased by the SAS. FDG PET is useful for analysis of muscle activity during exercise and rehabilitation.

Pre-mRNA secondary structure prediction aids splice site prediction.

Accurate splice site prediction is a critical component of any computational approach to gene prediction in higher organisms. Existing approaches generally use sequence-based models that capture local dependencies among nucleotides in a small window around the splice site. We present evidence that computationally predicted secondary structure of moderate length pre-mRNA subsequencies contains information that can be exploited to improve acceptor splice site prediction beyond that possible with conventional sequence-based approaches. Both decision tree and support vector machine classifiers, using folding energy and structure metrics characterizing helix formation near the splice site, achieve a 5-10% reduction in error rate with a human data set. Based on our data, we hypothesize that acceptors preferentially exhibit short helices at the splice site.