Luminescence Nanothermometry Selecting green fluorescent protein and Ag2S nanocrystals as illustrative multiparametric thermographic phosphors, in article number 2100301, Luís D. Carlos and co-workers demonstrate that the synergy between multiparametric readouts and multiple linear regression makes possible a 10-fold improvement in the performance of luminescent thermometers reaching a world record in the relative thermal sensitivity (Sr = 50 %·K−1) and an impressive temperature uncertainty of 0.05 K.
The vast differences in material properties accessible via crosslinking of sidechain-functionalized polymers are driven by topology. For example, vulcanized rubbery networks feature intermolecular connections and loop topologies of various orders while single-chain nanoparticles (SCNPs) are comprised, in principle, entirely of primary loops. Despite this fact, precise quantification of loops in sidechain crosslinked polymers has not been accomplished. Here, it is demonstrated that by introducing cleavable linkers and mass labels onto the pendant functional groups of reactive polymers, the number of primary loops in sidechain crosslinked materials ranging from rubbery networks (gels) to soluble SCNPs can be precisely quantified. This study sheds new light on the topology of sidechain-crosslinked networks, providing design principles for augmenting the properties of this industrially and academically important class of materials through topological control.
This article provides a brief overview of 18 projects funded in Track D—Data and Model Sharing to Enable AI Innovation—of the 2020 Cohort of the National Science Foundation's (NSF) Convergence Accelerator (CA) program. The NSF CA is focused on transitioning research to practice for societal impact. The projects described here were funded for one year in phase I of the program, beginning September 2020. Their focus is on delivering tools, technologies, and techniques to assist in sharing data as well as data-driven models to enable AI innovation. A broad range of domain areas is covered by the funded efforts, spanning across healthcare and medicine, to climate change and disaster, and civil/built infrastructure. The projects are addressing sharing of open as well as sensitive/private data. In September 2021, six of the eighteen projects described here were selected for phase II of the program, as noted in this article.
Abstract This article provides a brief overview of 18 projects funded in Track D—Data and Model Sharing to Enable AI Innovation—of the 2020 Cohort of the National Science Foundation's (NSF) Convergence Accelerator (CA) program. The NSF CA is focused on transitioning research to practice for societal impact. The projects described here were funded for one year in phase I of the program, beginning September 2020. Their focus is on delivering tools, technologies, and techniques to assist in sharing data as well as data‐driven models to enable AI innovation. A broad range of domain areas is covered by the funded efforts, spanning across healthcare and medicine, to climate change and disaster, and civil/built infrastructure. The projects are addressing sharing of open as well as sensitive/private data. In September 2021, six of the eighteen projects described here were selected for phase II of the program, as noted in this article.
Intravenous nanoparticle hemostats offer a potentially attractive approach to promote hemostasis, in particular for inaccessible wounds such as noncompressible torso hemorrhage (NCTH). In this work, particle size was tuned over a range of <100-500 nm, and its effect on nanoparticle-platelet interactions was systematically assessed using in vitro and in vivo experiments. Smaller particles bound a larger percentage of platelets per mass of particle delivered, while larger particles resulted in higher particle accumulation on a surface of platelets and collagen. Intermediate particles led to the greatest platelet content in platelet-nanoparticle aggregates, indicating that they may be able to recruit more platelets to the wound. In biodistribution studies, smaller and intermediate nanoparticles exhibited longer circulation lifetimes, while larger nanoparticles resulted in higher pulmonary accumulation. The particles were then challenged in a 2 h lethal inferior vena cava (IVC) puncture model, where intermediate nanoparticles significantly increased both survival and injury-specific targeting relative to saline and unfunctionalized particle controls. An increase in survival in the second hour was likewise observed in the smaller nanoparticles relative to saline controls, though no significant increase in survival was observed in the larger nanoparticle size. In conjunction with prior in vitro and in vivo experiments, these results suggest that platelet content in aggregates and extended nanoparticle circulation lifetimes are instrumental to enhancing hemostasis. Ultimately, this study elucidates the role of particle size in platelet-particle interactions, which can be a useful tool for engineering the performance of particulate hemostats and improving the design of these materials.
