In vivo Kinetic Biodistribution of Nano‐Sized Outer Membrane Vesicles Derived from Bacteria

Evaluation of kinetic distribution and behaviors of nanoparticles in vivo provides crucial clues into their roles in living organisms. Extracellular vesicles are evolutionary conserved nanoparticles, known to play important biological functions in intercellular, inter‐species, and inter‐kingdom communication. In this study, the first kinetic analysis of the biodistribution of outer membrane vesicles (OMVs)—bacterial extracellular vesicles—with immune‐modulatory functions is performed. OMVs, injected intraperitoneally, spread to the whole mouse body and accumulate in the liver, lung, spleen, and kidney within 3 h of administration. As an early systemic inflammation response, increased levels of TNF‐α and IL‐6 are observed in serum and bronchoalveolar lavage fluid. In addition, the number of leukocytes and platelets in the blood is decreased. OMVs and cytokine concentrations, as well as body temperature are gradually decreased 6 h after OMV injection, in concomitance with the formation of eye exudates, and of an increase in ICAM‐1 levels in the lung. Following OMV elimination, most of the inflammatory signs are reverted, 12 h post‐injection. However, leukocytes in bronchoalveolar lavage fluid are increased as a late reaction. Taken together, these results suggest that OMVs are effective mediators of long distance communication in vivo.     

Evolution of Local Structural Ordering and Chemical Distribution upon Delithiation of a Rock Salt–Structured Li1.3Ta0.3Mn0.4O2 Cathode

Lithium‐rich disordered rock‐salt oxides have attracted great interest owing to their promising performance as Li‐ion battery cathodes. While experimental and theoretical efforts are critical in advancing this class of materials, a fundamental understanding of key property changes upon Li extraction is largely missing. In the present study, single‐crystal synthesis of a new disordered rock‐salt cathode material, Li_1.3Ta_0.3Mn_0.4O₂ (LTMO), and its use as a model compound to investigate Li concentration–driven evolution of local cationic ordering, charge compensation, and chemical distribution are reported. Through the combined use of 2D and 3D X‐ray nanotomography, it is shown that Li removal accompanied by oxygen oxidation is correlated with the development of morphological defects such as particle cracking. Chemical heterogeneity, quantified by subparticle level distribution of Mn valence state, is minimal during Mn redox, which drastically increases upon the formation of cracks during oxygen redox. Density functional theory and bond valence sum mismatch calculations reveal the presence of local short‐range ordering in the pristine oxide, which gradually disappears along with the extraction of Li. The study suggests that with cycling the transformation into true cation–disordered state can be expected, which likely impacts the voltage profile and obtainable energy density of the oxide cathodes.     

Properties and applications of β‐glycosidase from Bacteroides thetaiotaomicron that specifically hydrolyses isoflavone glycosides

To modify the glycan part of glycosides, the gene encoding β‐glycosidase was cloned from Bacteroides thetaiotaomicron VPI‐5482. The cloned gene, bt_1780, was expressed in Escherichia coli MC1061 and the expressed enzyme was purified using Ni‐NTA affinity chromatography. The purified enzyme, BTBG, showed optimal activity at 50 °C and pH 5.5. Interestingly, this enzyme did not have any hydrolysing activity on ordinary β‐linkage–containing substrates such as xylobiose, lactose and cello‐oligosaccharide, but specifically hydrolysed isoflavone glycosides such as daidzin, genistin and glycitin. Compared to a commercial beta glucosidase, BTBG selectively hydrolysed isoflavone glycosides in soybean extract mixture solution. These results suggest that BTBG may be a specialized enzyme for the hydrolysis of glycosides and that the substrate specificity of BTBG is applicable for the bioconversion of isoflavone glycosides in the food industry.     

Visualizing for the Non‐Visual: Enabling the Visually Impaired to Use Visualization

The majority of visualizations on the web are still stored as raster images, making them inaccessible to visually impaired users. We propose a deep‐neural‐network‐based approach that automatically recognizes key elements in a visualization, including a visualization type, graphical elements, labels, legends, and most importantly, the original data conveyed in the visualization. We leverage such extracted information to provide visually impaired people with the reading of the extracted information. Based on interviews with visually impaired users, we built a Google Chrome extension designed to work with screen reader software to automatically decode charts on a webpage using our pipeline. We compared the performance of the back‐end algorithm with existing methods and evaluated the utility using qualitative feedback from visually impaired users.     

Adaptive viewpoints for co-browsing on heterogeneous devices

Co-browsing is an activity in which a group of users navigate their way through of a set of Web pages together for a shared purpose. Effective co-browsing among users with different device capabilities requires a shared understanding of those Web pages. This paper demonstrates the concept of shared viewpoints (SVPs), and personal viewpoints (PVPs), for co-browsing, before detailing a framework for implementing these concepts. Finally, the effectiveness of the framework is presented through a perceptual experiment.