399 research outputs found

    Children’s agency by design: Design parameters for personalization in story-making apps

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    The importance of children’s agency in the use of technologies is well-established but it continues to be challenged with applications that automatically personalize children’s content. This paper integrates educational theory of personalization with the design principles and empirical work of a story-making app called Our Story, which places a child’s agency at the center of its design. The impact of a series of studies with the OS app is summarized and implications for future design are offered. The Agentic Personalization Framework that consists of a design principle and a set of guiding questions is presented. The design principle is based on two continuous axes: agency/structure and individualism/collectivism, which give rise to four processes: personalization/customization and standardization/individualization. The guiding questions are intended to promote reflection among researchers and designers interested in supporting children’s agency with stories that children can make or interact with on tablets. The Agentic Personalization Framework is rooted in empirical studies, iterative design and theoretical developments and provides a fertile ground for research-design collaborations that place children’s agency at the heart of innovative work

    Integrated plasma proteomic and single-cell immune signaling network signatures demarcate mild, moderate, and severe COVID-19

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    The biological determinants of the wide spectrum of COVID-19 clinical manifestations are not fully understood. Here, over 1400 plasma proteins and 2600 single-cell immune features comprising cell phenotype, basal signaling activity, and signaling responses to inflammatory ligands were assessed in peripheral blood from patients with mild, moderate, and severe COVID-19, at the time of diagnosis. Using an integrated computational approach to analyze the combined plasma and single-cell proteomic data, we identified and independently validated a multivariate model classifying COVID-19 severity (multi-class AUCtraining = 0.799, p-value = 4.2e-6; multi-class AUCvalidation = 0.773, p-value = 7.7e-6). Features of this high-dimensional model recapitulated recent COVID-19 related observations of immune perturbations, and revealed novel biological signatures of severity, including the mobilization of elements of the renin-angiotensin system and primary hemostasis, as well as dysregulation of JAK/STAT, MAPK/mTOR, and NF-ÎşB immune signaling networks. These results provide a set of early determinants of COVID-19 severity that may point to therapeutic targets for the prevention of COVID-19 progression

    Identifying Recent Cholera Infections Using a Multiplex Bead Serological Assay

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    Estimates of incidence based on medically attended cholera can be severely biased. Vibrio cholerae O1 leaves a lasting antibody signal and recent advances showed that these can be used to estimate infection incidence rates from cross-sectional serologic data. Current laboratory methods are resource intensive and challenging to standardize across laboratories. A multiplex bead assay (MBA) could efficiently expand the breadth of measured antibody responses and improve seroincidence accuracy. We tested 305 serum samples from confirmed cholera cases (4 to 1083 d postinfection) and uninfected contacts in Bangladesh using an MBA (IgG/IgA/IgM for 7 Vibrio cholerae O1-specific antigens) as well as traditional vibriocidal and enzyme-linked immunosorbent assays (2 antigens, IgG, and IgA). While postinfection vibriocidal responses were larger than other markers, several MBA-measured antibodies demonstrated robust responses with similar half-lives. Random forest models combining all MBA antibody measures allowed for accurate identification of recent cholera infections (e.g., past 200 days) including a cross-validated area under the curve (cvAUC200) of 92%, with simpler 3 IgG antibody models having similar accuracy. Across infection windows between 45 and 300 days, the accuracy of models trained on MBA measurements was non-inferior to models based on traditional assays. Our results illustrated a scalable cholera serosurveillance tool that can be incorporated into multipathogen serosurveillance platforms. IMPORTANCE Reliable estimates of cholera incidence are challenged by poor clinical surveillance and health-seeking behavior biases. We showed that cross-sectional serologic profiles measured with a high-throughput multiplex bead assay can lead to accurate identification of those infected with pandemic Vibrio cholerae O1, thus allowing for estimates of seroincidence. This provides a new avenue for understanding the epidemiology of cholera, identifying priority areas for cholera prevention/control investments, and tracking progress in the global fight against this ancient disease
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