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The concept of resilience is surging in popularity, but relevant discussions are often disconnected from one field to another. To prompt integration of disparate conversations on resilience, we examine the concept’s origins etymologically, genealogically, and by analyzing the interdependencies of drinking water and public health systems in six academic disciplines and practice-oriented fields. These disciplines are engineering, social work, urban studies, political science, communication, and public health. While the disciplinary resilience literatures are relatively stove-piped from one another’s contexts, they all theorize resilience at multiple levels of analysis. They also engage a range of understandings of how to build resilience in complex systems. This paper brings several conversations together, addressing gaps and resonances in disciplinary conceptualizations of resilience with nine propositions to cultivate interdisciplinary and transdisciplinary discussions and debates. We ground this creative inquiry in real-world examples of water system crises to highlight subthemes among the propositions and stimulate more diverse discussions moving forward. We examine dynamics of interfaces and interactions within and between systems through the Elk River Water chemical contamination in Charleston, West Virginia in 2014. We investigate tensions that arise in knowledge and practice through lead poisoning of public water systems in Washington, D.C. and Flint, MI. Finally, we consider how change and persistence shape learning through water infrastructure in Southern California. All together, these propositions offer a starting point and a provocation to strengthen theorizing around resilience for critical infrastructure systems. 

Abstract Hearing loss is the leading sensory deficit, affecting ~ 5% of the population. It exhibits remarkable heterogeneity across 223 genes with 6328 pathogenic missense variants, making deafness-specific expertise a prerequisite for ascribing phenotypic consequences to genetic variants. Deafness-implicated variants are curated in the Deafness Variation Database (DVD) after classification by a genetic hearing loss expert panel and thorough informatics pipeline. However, seventy percent of the 128,167 missense variants in the DVD are “variants of uncertain significance” (VUS) due to insufficient evidence for classification. Here, we use the deep learning protein prediction algorithm, AlphaFold2, to curate structures for all DVD genes. We refine these structures with global optimization and the AMOEBA force field and use DDGun3D to predict folding free energy differences (∆∆G_Fold) for all DVD missense variants. We find that 5772 VUSs have a large, destabilizing ∆∆G_Foldthat is consistent with pathogenic variants. When also filtered for CADD scores (> 25.7), we determine 3456 VUSs are likely pathogenic at a probability of 99.0%. Of the 224 genes in the DVD, 166 genes (74%) exhibit one or more missense variants predicted to cause a pathogenic change in protein folding stability. The VUSs prioritized here affect 119 patients (~ 3% of cases) sequenced by the OtoSCOPE targeted panel. Approximately half of these patients previously received an inconclusive report, and reclassification of these VUSs as pathogenic provides a new genetic diagnosis for six patients.