The modular synthesis of 7 libraries containing 51 self-assembling amphiphilic Janus dendrimers with the monosaccharides D-mannose and D-galactose and the disaccharide D-lactose in their hydrophilic part is reported. These unprecedented sugar-containing dendrimers are named amphiphilic Janus glycodendrimers. Their self-assembly by simple injection of THF or ethanol solution into water or buffer and by hydration was analyzed by a combination of methods including dynamic light scattering, confocal microscopy, cryogenic transmission electron microscopy, Fourier transform analysis, and micropipet-aspiration experiments to assess mechanical properties. These libraries revealed a diversity of hard and soft assemblies, including unilamellar spherical, polygonal, and tubular vesicles denoted glycodendrimersomes, aggregates of Janus glycodendrimers and rodlike micelles named glycodendrimer aggregates and glycodendrimermicelles, cubosomes denoted glycodendrimercubosomes, and solid lamellae. These assemblies are stable over time in water and in buffer, exhibit narrow molecular-weight distribution, and display dimensions that are programmable by the concentration of the solution from which they are injected. This study elaborated the molecular principles leading to single-type soft glycodendrimersomes assembled from amphiphilic Janus glycodendrimers. The multivalency of glycodendrimersomes with different sizes and their ligand bioactivity were demonstrated by selective agglutination with a diversity of sugar-binding protein receptors such as the plant lectins concanavalin A and the highly toxic mistletoe Viscum album L. agglutinin, the bacterial lectin PA-IL from Pseudomonas aeruginosa, and, of special biomedical relevance, human adhesion/growth-regulatory galectin-3 and galectin-4. These results demonstrated the candidacy of glycodendrimersomes as new mimics of biological membranes with programmable glycan ligand presentations, as supramolecular lectin blockers, vaccines, and targeted delivery devices.

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Rationale: Prone positioning reduces mortality in patients with severe acute respiratory distress syndrome (ARDS), a feature of severe COVID-19. Despite this, most patients with ARDS do not receive this life-saving therapy. Objectives: To identify determinants of prone positioning utilization, to develop specific implementation strategies, and to incorporate strategies into an overarching response to the COVID-19 crisis. Methods: We used an implementation mapping approach guided by implementation science frameworks. We conducted semi-structured interviews with 30 ICU clinicians who staffed 12 ICUs within the Penn Medicine health system and the University of Michigan Medical Center. We performed thematic analysis utilizing the Consolidated Framework for Implementation Research (CFIR). We then conducted three focus groups with a task force of ICU leaders to develop an implementation menu, using the Expert Recommendations for Implementing Change (ERIC) framework. The implementation strategies were adapted as part of the Penn Medicine COVID-19 pandemic response. Results: We identified five broad themes of determinants of prone positioning: knowledge, resources, alternative therapies, team culture, and patient factors, which collectively spanned all five CFIR domains. The task force developed five specific implementation strategies: educational outreach, learning collaborative, clinical protocol, prone positioning team, and automated alerting, elements of which were rapidly implemented at Penn Medicine.

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Citizen science projects have the potential to address hypotheses requiring extremely large datasets that cannot be collected with the financial and labour constraints of most scientific projects. Data collection by the general public could expand the scope of scientific enquiry if these data accurately capture the system under study. However, data collection inconsistencies by the untrained public may result in biased datasets that do not accurately represent the natural world. In this paper, we harness the availability of scientific and public datasets of the Lyme disease tick vector to identify and account for biases in citizen science tick collections. Estimates of tick abundance from the citizen science dataset correspond moderately with estimates from direct surveillance but exhibit consistent biases. These biases can be mitigated by including factors that may impact collector participation or effort in statistical models, which, in turn, result in more accurate estimates of tick population sizes. Accounting for collection biases within large-scale, public participation datasets could update species abundance maps and facilitate using the wealth of citizen science data to answer scientific questions at scales that are not feasible with traditional datasets.