Enhancing cycling durability of Li-ion batteries with hierarchical structured silicon–graphene hybrid anodes

Hybrid anode materials consisting of micro-sized silicon (Si) particles interconnected with few-layer graphene (FLG) nanoplatelets and sodium-neutralized poly(acrylic acid) as a binder were evaluated for Li-ion batteries. The hybrid film has demonstrated a reversible discharge capacity of ∼1800 mA h g−1 with a capacity retention of 97% after 200 cycles. The superior electrochemical properties of the hybrid anodes are attributed to a durable, hierarchical conductive network formed between Si particles and the multi-scale carbon additives, with enhanced cohesion by the functional polymer binder. Furthermore, improved solid electrolyte interphase (SEI) stability is achieved from the electrolyte additives, due to the formation of a kinetically stable film on the surface of the Si

Imaging striatal dopamine release using a nongenetically encoded near infrared fluorescent catecholamine nanosensor.

Neuromodulation plays a critical role in brain function in both health and disease, and new tools that capture neuromodulation with high spatial and temporal resolution are needed. Here, we introduce a synthetic catecholamine nanosensor with fluorescent emission in the near infrared range (1000-1300 nm), near infrared catecholamine nanosensor (nIRCat). We demonstrate that nIRCats can be used to measure electrically and optogenetically evoked dopamine release in brain tissue, revealing hotspots with a median size of 2 µm. We also demonstrated that nIRCats are compatible with dopamine pharmacology and show D2 autoreceptor modulation of evoked dopamine release, which varied as a function of initial release magnitude at different hotspots. Together, our data demonstrate that nIRCats and other nanosensors of this class can serve as versatile synthetic optical tools to monitor neuromodulatory neurotransmitter release with high spatial resolution

Surface structure and solidification morphology of aluminum nanoclusters

Classical molecular dynamics simulation with embedded atom method potential had been performed to investigate the surface structure and solidification morphology of aluminum nanoclusters Aln (n = 256, 604, 1220 and 2048). It is found that Al cluster surfaces are comprised of (111) and (001) crystal planes. (110) crystal plane is not found on Al cluster surfaces in our simulation. On the surfaces of smaller Al clusters (n = 256 and 604), (111) crystal planes are dominant. On larger Al clusters (n = 1220 and 2048), (111) planes are still dominant but (001) planes can not be neglected. Atomic density on cluster (111)/(001) surface is smaller/larger than the corresponding value on bulk surface. Computational analysis on total surface area and surface energies indicates that the total surface energy of an ideal Al nanocluster has the minimum value when (001) planes occupy 25% of the total surface area. We predict that a melted Al cluster will be a truncated octahedron after equilibrium solidification.Comment: 22 pages, 6 figures, 34 reference

Temperature and nitrogen supply interact to determine protein distribution gradients in the wheat grain endosperm

Gradients exist in the distribution of storage proteins in the wheat (Triticum aestivum L.) endosperm and determine the milling properties and protein recovery rate of the grain. A novel image analysis technique was developed to quantify both the gradients in protein concentration, and the size distribution of protein bodies within the endosperm of wheat plants grown under two different (20 °C or 28 °C) post-anthesis temperatures, and supplied with a nutrient solution with either high or low nitrogen content. Under all treatment combinations protein concentration was greater in the endosperm cells closest to the aleurone layer, and decreased towards the centre of the two lobes of the grain, i.e. a negative gradient. This was accompanied by a decrease in size of protein bodies from the outer to the inner endosperm layers in all but one of the treatments. Elevated post-anthesis temperature had the effect of increasing the magnitude of the negative gradients in both protein concentration and protein body size, whilst limiting nitrogen supply decreased the gradients

Deep learning predicts function of live retinal pigment epithelium from quantitative microscopy.

Increases in the number of cell therapies in the preclinical and clinical phases have prompted the need for reliable and non-invasive assays to validate transplant function in clinical biomanufacturing. We developed a robust characterization methodology composed of quantitative bright-field absorbance microscopy (QBAM) and deep neural networks (DNNs) to non-invasively predict tissue function and cellular donor identity. The methodology was validated using clinical-grade induced pluripotent stem cell derived retinal pigment epithelial cells (iPSC-RPE). QBAM images of iPSC-RPE were used to train DNNs that predicted iPSC-RPE monolayer transepithelial resistance, predicted polarized vascular endothelial growth factor (VEGF) secretion, and matched iPSC-RPE monolayers to the stem cell donors. DNN predictions were supplemented with traditional machine learning algorithms that identified shape and texture features of single cells that were used to predict tissue function and iPSC donor identity. These results demonstrate non-invasive cell therapy characterization can be achieved with QBAM and machine learning

Percutaneous Cell Delivery Into the Heart Using Hydrogels Polymerizing In Situ

Heart disease is the leading cause of death in the US. Following an acute myocardial infarction, a fibrous, noncontractile scar develops, and results in congestive heart failure in more than 500,000 patients in the US each year. Muscle regeneration and the induction of new vascular growth to treat ischemic disorders of the heart can have significant therapeutic implications. Early studies in patients with chronic ischemic systolic left ventricular dysfunction (SLVD) using skeletal myoblasts or bone marrow-derived cells report improvement in left ventricular ejection function (LVEF) and clinical status, without notable safety issues. Nonetheless, the efficacy of cell transfer for cardiovascular disease is not established, in part due to a lack of control over cell retention, survival, and function following delivery. We studied the use of biocompatible hydrogels polymerizable in situ as a cell delivery vehicle, to improve cell retention, survival, and function following delivery into the ischemic myocardium. The study was conducted using human bone marrow-derived mesenchymal stem cells and fibrin glue, but the methods are applicable to any human stem cells (adult or embryonic) and a wide range of hydrogels. We first evaluated the utility of several commercially available percutaneous catheters for delivery of viscous cell/hydrogel suspensions. Next we characterized the polymerization kinetics of fibrin glue solutions to define the ranges of concentrations compatible with catheter delivery. We then demonstrate the in vivo effectiveness of this preparation and its ability to increase cell retention and survival in a nude rat model of myocardial infarction

An Alternative Approach to Nucleic Acid Memory

DNA is a compelling alternative to non-volatile information storage technologies due to its information density, stability, and energy efficiency. Previous studies have used artificially synthesized DNA to store data and automated next-generation sequencing to read it back. Here, we report digital Nucleic Acid Memory (dNAM) for applications that require a limited amount of data to have high information density, redundancy, and copy number. In dNAM, data is encoded by selecting combinations of single-stranded DNA with (1) or without (0) docking-site domains. When self-assembled with scaffold DNA, staple strands form DNA origami breadboards. Information encoded into the breadboards is read by monitoring the binding of fluorescent imager probes using DNA-PAINT super-resolution microscopy. To enhance data retention, a multi-layer error correction scheme that combines fountain and bi-level parity codes is used. As a prototype, fifteen origami encoded with ‘Data is in our DNA!\n’ are analyzed. Each origami encodes unique data-droplet, index, orientation, and error-correction information. The error-correction algorithms fully recover the message when individual docking sites, or entire origami, are missing. Unlike other approaches to DNA-based data storage, reading dNAM does not require sequencing. As such, it offers an additional path to explore the advantages and disadvantages of DNA as an emerging memory material

Assessing the impact of comparative genomic sequence data on the functional annotation of the Drosophila genome

BACKGROUND: It is widely accepted that comparative sequence data can aid the functional annotation of genome sequences; however, the most informative species and features of genome evolution for comparison remain to be determined. RESULTS: We analyzed conservation in eight genomic regions (apterous, even-skipped, fushi tarazu, twist, and Rhodopsins 1, 2, 3 and 4) from four Drosophila species (D. erecta, D. pseudoobscura, D. willistoni, and D. littoralis) covering more than 500 kb of the D. melanogaster genome. All D. melanogaster genes (and 78-82% of coding exons) identified in divergent species such as D. pseudoobscura show evidence of functional constraint. Addition of a third species can reveal functional constraint in otherwise non-significant pairwise exon comparisons. Microsynteny is largely conserved, with rearrangement breakpoints, novel transposable element insertions, and gene transpositions occurring in similar numbers. Rates of amino-acid substitution are higher in uncharacterized genes relative to genes that have previously been studied. Conserved non-coding sequences (CNCSs) tend to be spatially clustered with conserved spacing between CNCSs, and clusters of CNCSs can be used to predict enhancer sequences. CONCLUSIONS: Our results provide the basis for choosing species whose genome sequences would be most useful in aiding the functional annotation of coding and cis-regulatory sequences in Drosophila. Furthermore, this work shows how decoding the spatial organization of conserved sequences, such as the clustering of CNCSs, can complement efforts to annotate eukaryotic genomes on the basis of sequence conservation alone