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This study explores undergraduate engineering and education students’ perspectives on their interdisciplinary teams throughout the rapid transition to online learning and instruction from a face-to-face to a virtual format. In this qualitative study, students’ reflections and focus groups from three interdisciplinary collaborations were analyzed using the lens of Social Cognitive Theory. COVID-19 created a dramatic change in the environment such that the most immediate and direct impact on students’ experiences was on the environmental aspects of Bandura’s triadic reciprocal determinism model, which then triggered behavioral and personal responses to adapt to the new environment. Subsequent evidence of reciprocal effects between environmental, behavioral, and personal factors took place as students continued to adapt. Results suggest that the modifications made to transition the project fully online were meaningful experiences for students’ learning and teaching of engineering through teams. This interdisciplinary partnership provided both pre-service teachers and undergraduate engineering students with the opportunity to learn and practice content and professional skills that will be essential for success in future work environments.more » « less
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Abstract Atopic dermatitis (AD) is a common skin disease in childhood whose diagnosis requires expertise in dermatology. Recent studies have indicated that host genes–microbial interactions in the gut contribute to human diseases including AD. We sought to develop an accurate and automated pipeline for AD diagnosis based on transcriptome and microbiota data. Using these data of 161 subjects including AD patients and healthy controls, we trained a machine learning classifier to predict the risk of AD. We found that the classifier could accurately differentiate subjects with AD and healthy individuals based on the omics data with an average F1-score of 0.84. With this classifier, we also identified a set of 35 genes and 50 microbiota features that are predictive for AD. Among the selected features, we discovered at least three genes and three microorganisms directly or indirectly associated with AD. Although further replications in other cohorts are needed, our findings suggest that these genes and microbiota features may provide novel biological insights and may be developed into useful biomarkers of AD prediction.
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Abstract Background Entinostat is an oral small molecule inhibitor of class I histone deacetylases (HDAC), which has not previously been evaluated in pediatrics. We conducted a phase I trial to determine the maximum tolerated dose/recommended phase 2 dose (MTD/RP2D), toxicity profile, pharmacokinetics (PK), and pharmacodynamics (PD) of entinostat in children with relapsed or refractory solid tumors including central nervous system (CNS) malignancies.
Methods A rolling six dose escalation design evaluated two dose levels. Entinostat oral tablet formulation was administered once per week, four doses per 28‐day cycle. PK and PD studies were performed.
Results Twenty‐one eligible patients’ median (range) age was 14 years (6‐20). Six subjects were treated at 3 mg/m2dose level and 15 were treated in 4 mg/m2dose level. The study included patients with CNS tumors (n = 12), sarcomas (n = 6), or other solid tumors (n = 3). Eight patients were not fully evaluable for toxicity due to progression of disease prior to receiving the required percentage of protocol therapy. No cycle one dose‐limiting toxicity (DLT) was observed at either dose level. A three‐fold higher area under the curve (AUC) was achieved in our cohort compared to adults using a similar dosing schedule. The PD studies showed increase in acetylated lysine in peripheral blood leukocytes at both doses.
Conclusions Entinostat was well tolerated with no DLT observed. All patients experienced progression within the first two cycles, except one patient with ependymoma with stable disease. Based on PK and PD, the R2PD in pediatric patients with solid tumors is 4 mg/m2orally administered once weekly.
