Disruption of ion channel function is increasingly associated with neurodevelopmental disorders (NDDs) such as autism spectrum disorder (ASD). ASD has complex etiology and symptoms, but recent studies suggest that individuals with ASD have disrupted mesostriatal network activity associated with social interaction deficits. Although mutated ion channels play a key role in NDDs, the degree to which they disrupt mesostriatal network activity is not well understood. The Kv7 family of voltage-gated potassium channels encoded by KCNQ1-5 genes are increasingly linked to NDDs including ASD. These channels are broadly expressed, including within the ventral tegmental area (VTA), a nucleus of the mesostriatal pathway that plays an important role in social behavior. Here we assessed the impact of the ASD-associated variant KCNQ3(R2C) on VTA dopamine neuron excitability and social behavior in mice. We used a viral-based strategy to conditionally inactivate endogenous Kv7.3 with CRISPR/SaCas9 and re-express human wildtype (hKv7.3/WT) or mutant (hKv7.3/R2C) KCNQ3. Whole-cell patch clamp electrophysiology in brain slices revealed that hKv7.3/R2C significantly decreased excitability of dopamine neurons. I also observed a loss of social novelty preference using the three-chamber social interaction task in mice expressing hKv7.3/R2C but not in controls expressing hKv7.3/WT. These results suggest that hKv7.3/R2C and other similar Kv7 mutant variants may disrupt mesostriatal network activity and social interaction by decreasing dopamine neuron excitability.

The Xpert Xpress SARS-CoV-2 assay is a rapid RT-PCR test developed by Cepheid during the early stages of the COVID-19 pandemic. However, with the emergence of novel variants, concerns have been raised about possible diminished sensitivity of RT-PCR assays that were developed using earlier strains of SARS-CoV-2. We sought to address these concerns by testing known positive Alpha, Beta, Delta, Gamma, and Omicron SARS-CoV-2 samples which, at the time of testing, were classified by the CDC as variants of concern (VOCs). Since these samples were stored in TE buffer, a medium not formally evaluated for use in the Cepheid Xpert Xpress SARS-CoV-2 assay, we also tested positive controls using both TE buffer and the standard viral transport medium (VTM). All samples were run using the Xpert Xpress SARS-CoV-2 assay per Cepheid's provided instructions. Testing of known VOC positives revealed no substantial reduction of PCR sensitivity when compared to a clinically certified RT-qPCR assay. Comparison of TE and VTM samples also revealed no reduction in performance when using TE buffer, validating the use of TE buffer to store SARS-CoV-2 samples. Our findings show that the mutations present in the current circulating VOCs do not lead to false negative patient results, indicating the Xpert Xpress assay may still be used for diagnostic testing.

This work proposes a novel generative design tool for passive grippers—robot end effectors that have no additional actuation and instead leverage the existing degrees of freedom in a robotic arm to perform grasping tasks. Passive grippers offer interesting trade-offs between cost and capabilities. However, existing designs are limited in the types of shapes that can be grasped. This work proposes to use rapid-manufacturing and design optimization to expand the space of shapes that can be passively grasped. Our novel generative design algorithm takes in an object and its orientation with respect to a robotic arm and generates a 3D printable passive gripper that can stably pick the object up. To achieve this, we address the key challenge by jointly optimizing the gripper shape and the insert trajectory to enlarge the set of objects that can be pasively grasped. We evaluate our method on a testing suite of 23 objects, all of which were evaluated with physical experiments to bridge the virtual-to-real gap. Inspired by the true cost of repurposing infrastructures in assembly lines following the recent changes in demand early in the COVID-19 crisis, our work allows a cost effective solution to rapidly generate, fabricate, and deploy custom passive grippers on the existing robot arms for the new products in demand.

The NIH 3D Print Exchange is a public and open source repository for primarily 3D printable medical device designs with contributions from expert-amateur makers, engineers from industry and academia, and clinicians. In response to the COVID-19 pandemic, a collection was formed to foster creative submissions of low-cost, locally manufacturable personal protective equipment (PPE). To understand trends from this extraordinary occurrence of medical making, we performed a mixed-methods analysis of this collection. We used a combination of qualitative data from a thematic analysis and quantitative data from web scraped details of over 600 submissions. From this analysis, we found a disconnect between the NIH’s intention for the platform and how it was used. Instead of generating a diverse array of designs, the submission requirements and rating designations led to a rapid convergence of the design space. In this presentation, I present our findings for what we believe resulted in this disconnect and provide suggestions for how to improve upon the repository’s design. This work contributes valuable insights into the outcomes of distributed, community-based medical making and how platforms can support regulated maker activities in high-risk domains such as healthcare. Furthermore, many of our recommendations could be applied to non-health focused maker repositories such as Thingiverse and Instructables.

This research project seeks to understand resource management policy and its effectiveness in practice, especially as climate change exacerbates pre-existing scarcities. As a case study, this project examines two policies that attempt to manage water use in California– the Sustainable Groundwater Management Act (2014) and the Central Valley Water Project Improvement Act (1992). The former was chosen because it focuses on the regulation of groundwater, a resource that had yet to be overseen in California, and the latter was selected as it is one of the most recent pieces of notable legislation that sought to improve the sustainable management of surface water. By considering how effective the policies have been in regulating two important sources, it can provide insight into the current and prospective water situation in California. This project measures the effectiveness of these acts through the agricultural sector, given that the industry uses approximately 80% of the state’s water supply in a given year. Therefore, by measuring the growth of water intensive crops in the years following the passage of said legislation, we can better understand whether these acts were successful in curbing exorbitant water use. To measure growth, I record the acres harvested of almonds, walnuts, avocados, and wheat (as a control); I then translate this data into growth rate for each year and record the unit price for further understanding. After conducting the aforementioned methodology, this project finds that the Central Valley Water Project Improvement Act is significantly more effective in limiting the growth of thirsty crops, whereas the Sustainable Groundwater Management Act was found to have little impact.

Since late 2020, vaccination rates against SARS-CoV-2 have increased with 64% of the U.S. population fully vaccinated as of February 2022 [CDC, 2021]. Although vaccines are an effective method of protection, breakthrough cases have been occurring especially with variants of concern (VOC). Vaccination has remained protective against severe disease for multiple VOCs, including Delta and more recently Omicron. It is important to understand how different levels of vaccination, such as the number of doses received, impact symptom severity as additional VOCs continue to emerge. I utilized data collected from the Husky Coronavirus Testing research program, which provides testing to students, faculty, and staff at the University of Washington, to evaluate the relationship between severity of COVID-19 symptoms and number of doses received and type of vaccine received. Self-reported symptom severity data was collected from individuals who completed a follow-up questionnaire 7 days after testing positive for COVID-19. This analysis can help us to learn more about vaccination status and its impact on illness severity in those infected with the omicron variant. From this research I anticipate vaccinated individuals to report mild COVID-19 symptoms and those who are unvaccinated, or only slightly vaccinated to report more moderate or severe symptoms.