A novel formulation system of phytosomes loaded with mitomycin C-soybean phosphatidylcholine (MMC-SPC) complex (MMC-loaded phytosomes) was prepared by a solvent evaporation method combined with a nanoprecipitation technique for the purpose of development of an MMC drug delivery system. The MMC-loaded phytosomes were evaluated by average particle size, zeta-potential, and residual drug-loading content as well as an in vitro drug release profile. Furthermore, in vitro stability tests and in vitro/vivo biological evaluations of the MMC-loaded phytosomes were performed. DSC, FTIR, and XRD demonstrated that MMC interacted physically with SPC within the phytosomes. DLS and ELS described a dispersion with an average particle size of 210.87 nm, a narrow size distribution (PDI 0.251), and a zeta-potential of -33.38 mV. SEM, TEM, and AFM images showed that the MMC-loaded phytosomes were spherical and intact vesicles. In vitro stability tests demonstrated that the average particle size and residual drug-loading content of the MMC-loaded phytosomes had no evident change at different storage conditions. In vitro drug release profiles indicated biphasic behavior with an initial burst release, followed by a subsequent prolonged sustained release. In vitro cytotoxicity assays with H(22) cells showed that the MMC-loaded phytosomes had remarkable cytotoxicity. In vivo antitumor effect of the MMC-loaded phytosomes also revealed a dose-dependent and superior curative inhibitory effect on tumor growth without loss of body weight compared to free MMC. Histopathological analysis of specimens taken from tumor tissues indicated that MMC-loaded phytosomes had lethal effect to hepatoma cell. These findings suggested that the MMC-loaded phytosomes can serve as a promising and effective formulation for drug delivery and cancer therapy.

Recent studies show that biomaterials are capable of regulating immune responses to induce a favorable osteogenic microenvironment and promote osteogenesis and angiogenesis. In this study, we investigated the effects of zinc silicate/nanohydroxyapatite/collagen (ZS/HA/Col) scaffolds on bone regeneration and angiogenesis and explored the related mechanism. We demonstrate that 10ZS/HA/Col scaffolds significantly enhanced bone regeneration and angiogenesis in vivo compared with HA/Col scaffolds. ZS/HA/Col scaffolds increased tartrate-resistant acid phosphatase (TRAP)-positive cells, nestin-positive bone marrow stromal cells (BMSCs) and CD31-positive neovessels, and expression of osteogenesis (Bmp-2 and Osterix) and angiogenesis-related (Vegf-α and Cd31) genes increased in nascent bone. ZS/HA/Col scaffolds with 10 wt % ZS activated the p38 signaling pathway in monocytes. The monocytes subsequently differentiated into TRAP+ cells and expressed higher levels of the cytokines SDF-1, TGF-β1, VEGF-α, and PDGF-BB, which recruited BMSCs and endothelial cells (ECs) to the defect areas. Blocking the p38 pathway in monocytes reduced TRAP+ differentiation and cytokine secretion and resulted in a decrease in BMSC and EC homing and angiogenesis. Overall, these findings demonstrate that 10ZS/HA/Col scaffolds modulate monocytes and, thereby, create a favorable osteogenic microenvironment that promotes BMSC migration and differentiation and vessel formation by activating the p38 signaling pathway.

Self-assembly of viral coating proteins encapsulating functional nanoparticles provides a new class of biomaterials with robust chemical and physical properties for potential applications in functional imaging, and therapeutic or diagnostic agent delivery. Herein, a straightforward method is demonstrated for efficient encapsidation of magnetic nanoparticles into the engineered virus-like particle (VLP) through the affinity of histidine tags for the nickel- nitrilotriacetic acid (NTA) chelate. Monodispersed, uniformly sized, magnetic core-containing VLPs are obtained at high efficiency (>85%) and used as the cellular T2 contrast agents for MR imaging applications thanks to their biocompatibility, higher cellular uptake, as well as higher r2 values.

In the development of catalytic materials, a set of standard conditions is needed where the kinetic performance of many samples can be compared. This can be challenging when a sample set covers a broad range of activity. Precise kinetic characterization requires uniformity in the gas and catalyst bed composition. This limits the range of convecting devices to low conversion (generally <20%). While steady-state kinetics offer a snapshot of conversion, yield and apparent rates of the slow reaction steps, transient techniques offer much greater detail of rate processes and hence more information as to why certain catalyst compositions offer better performance. In this work, transient experiments in two transport regimes are compared: an advecting differential plug flow reactor (PFR) and a pure-diffusion temporal analysis of products (TAP) reactor. The decomposition of ammonia was used as a model reaction to test three simple materials: polycrystalline iron, cobalt and a bimetallic preparation of the two. These materials presented a wide range of activity and it was not possible to capture transient information in the advecting device for all samples at the same conditions while ensuring uniformity. We push the boundary for the theoretical estimates of uniformity in the TAP device and find reliable kinetic measurement up to 90% conversion. However, what is more advantageous from this technique is the ability to observe the time-dependence of the reaction rate rather than just singular points of conversion and yield. For example, on the iron sample we observed reversible adsorption of ammonia and on cobalt materials we identify two routes for hydrogen production. From the time-dependence of reactants and product, the dynamic accumulation was calculated. This was used to understand the atomic distribution of H and N species regulated by the surface of different materials. When ammonia was pulsed at 550 °C, the surface hydrogen/nitrogen, (H/N), ratios that evolved for Fe, CoFe and Co were 2.4, 0.25 and 0.3 respectively. This indicates that iron will store a mixture of hydrogenated species while materials with cobalt will predominantly store NH and N. While much is already known about iron, cobalt and ammonia decomposition, the goal of this work was to demonstrate new tools for comparing materials over a wider window of conversion and with much greater kinetic detail. As such, this provides an approach for detailed kinetic discrimination of more complex industrial samples beyond conversion and yield.

Classification algorithms for automatically detecting sea surface oil spills from spaceborne Synthetic Aperture Radars (SARs) can usually be regarded as part of a three-step processing framework, which briefly includes image segmentation, feature extraction, and target classification. A Deep Convolutional Neural Network (DCNN), named the Oil Spill Convolutional Network (OSCNet), is proposed in this paper for SAR oil spill detection, which can do the latter two steps of the three-step processing framework. Based on VGG-16, the OSCNet is obtained by designing the architecture and adjusting hyperparameters with the data set of SAR dark patches. With the help of the big data set containing more than 20,000 SAR dark patches and data augmentation, the OSCNet can have as many as 12 weight layers. It is a relatively deep Deep Learning (DL) network for SAR oil spill detection. It is shown by the experiments based on the same data set that the classification performance of OSCNet has been significantly improved compared to that of traditional machine learning (ML). The accuracy, recall, and precision are improved from 92.50%, 81.40%, and 80.95% to 94.01%, 83.51%, and 85.70%, respectively. An important reason for this improvement is that the distinguishability of the features learned by OSCNet itself from the data set is significantly higher than that of the hand-crafted features needed by traditional ML algorithms. In addition, experiments show that data augmentation plays an important role in avoiding over-fitting and hence improves the classification performance. OSCNet has also been compared with other DL classifiers for SAR oil spill detection. Due to the huge differences in the data sets, only their similarities and differences are discussed at the principle level.

Both folic acid (FA)- and methoxypoly(ethylene glycol) (mPEG)-conjugated chitosan nanoparticles (NPs) had been designed for targeted and prolong anticancer drug delivery system. The chitosan NPs were prepared with combination of ionic gelation and chemical cross-linking method, followed by conjugation with both FA and mPEG, respectively. FA-mPEG-NPs were compared with either NPs or mPEG-/FA-NPs in terms of their size, targeting cellular efficiency and tumor tissue distribution. The specificity of the mPEG-FA-NPs targeting cancerous cells was demonstrated by comparative intracellular uptake of NPs and mPEG-/FA-NPs by human adenocarcinoma HeLa cells. Mitomycin C (MMC), as a model drug, was loaded to the mPEG-FA-NPs. Results show that the chitosan NPs presented a narrow-size distribution with an average diameter about 200 nm regardless of the type of functional group. In addition, MMC was easily loaded to the mPEG-FA-NPs with drug-loading content of 9.1%, and the drug releases were biphasic with an initial burst release, followed by a subsequent slower release. Laser confocal scanning imaging proved that both mPEG-FA-NPs and FA-NPs could greatly enhance uptake by HeLa cells. In vivo animal experiments, using a nude mice xenograft model, demonstrated that an increased amount of mPEG-FA-NPs or FA-NPs were accumulated in the tumor tissue relative to the mPEG-NPs or NPs alone. These results suggest that both FA- and mPEG-conjugated chitosan NPs are potentially prolonged drug delivery system for tumor cell-selective targeting treatments.

The second King’s College London Symposium on Ageing and Long-term Care in China was convened from 4 to 5th July 2019 at King’s College London in London. The aim of the Symposium was to have a better understanding of health and social challenges for aging and long-term care in China. This symposium draws research insights from a wide range of disciplines, including economics, public policy, demography, gerontology, public health and sociology. A total of 20 participants from eight countries, seek to identify the key issues and research priorities in the area of aging and long-term care in China. The results published here are a synthesis of the top four research areas that represent the perspectives from some of the leading researchers in the field.

Surface impurities involving parasitic reactions and gas evolution contribute to the degradation of high Ni content LiNi x Mn y Co z O2 (NMC) cathode materials. The transient kinetic technique of temporal analysis of products (TAP), density functional theory, and infrared spectroscopy have been used to study the formation of surface impurities on varying nickel content NMC materials (NMC811, NMC622, NMC532, NMC433, NMC111) in the presence of CO2 and H2O. CO2 reactivity on a clean surface as characterized by CO2 conversion rate in the TAP reactor follows the order: NMC811 > NMC622 > NMC532 > NMC433 > NMC111. The capacity of CO2 uptake follows a different order: NMC532 > NMC433 > NMC622 > NMC811 > NMC111. Moisture pretreatment slows down the direct CO2 adsorption process and creates additional active sites for CO2 adsorption. Electronic structure calculations predict that the (012) surface is more reactive than the (104) surface for CO2 and H2O adsorption. CO2 adsorption leading to carbonate formation is exothermic with formation of ion pairs. The average CO2 binding energies on the different materials follow the CO2 reactivity order. Water hydroxylates the (012) surface and surface OH groups favor bicarbonate formation. Water creates more active sites for CO2 adsorption on the (104) surface due to hydrogen bonding. The composition of surface impurities formed in ambient air exposure is dependent on water concentration and the percentage of different crystal planes. Different surface reactivities suggest that battery performance degradation due to surface impurities can be mitigated by precise control of the dominant surfaces in NMC materials.