Ginkgetin aglycone exerts anti-osteoporotic effect via regulation of NOX4/Akt/PI3K pathway

Purpose: To investigate the protective effect of Ginkgetin aglycone (GA) on ovariectomy-induced osteoporosis in rats, as well as the mechanism of action involved. Methods: Adult female Wistar rats (n = 40) were separated into four group: normal control, ovariectomy (OVR), 100 mg GA/kg dose, and 200 mg GA/kg dose. The rats were ovariectomized using standard procedures, except for those in normal control group. Rats in the two treatment groups received 100 or 200 mg GA/kg orally for a period of 12 weeks. Biochemical assays were performed on the urine and blood. Markers of bone formation and mediators of inflammation were assessed. Bone microarchitectural changes were examined using micro-CT scanner, while Western blotting was used to determine the expressions of NOX4, NF-κB p65, PI3K, Akt and JNK proteins in rat femurs. Results: Phosphorus and calcium levels in the serum varied among different groups. Levels of calcium, phosphorus and creatinine decreased (p < 0.01) significantly to a greater extent in the urine of GA group than in that of OVR group (p < 0.05). Interleukin-1β (IL-1β), tumor necrosis factor α (TNF-α) and osteocalcin (OC) levels and the activity of alkaline phosphatase (ALP) decreased more in GA group than in OVR group. In GA-treated group, bone mineral density (BMD) was enhanced in a dose dependent manner than OVR group (p < 0.05). Treatment with GA ameliorated altered bone microarchitecture in OVR rats. Treatment of osteoporotic rats with GA led to significant and dosedependent decrease in the expressions of JNK, NOX4, NF-κB p65 and PI3K, and (p < 0.05) increase in the expression of Akt in femur tissue. Conclusion: In conclusion, result of study proves the anti-osteoporotic activity of GA is exerted via regulation of NOX4/PI3K/Akt pathway

Single-nanowire spectrometers.

Spectrometers with ever-smaller footprints are sought after for a wide range of applications in which minimized size and weight are paramount, including emerging in situ characterization techniques. We report on an ultracompact microspectrometer design based on a single compositionally engineered nanowire. This platform is independent of the complex optical components or cavities that tend to constrain further miniaturization of current systems. We show that incident spectra can be computationally reconstructed from the different spectral response functions and measured photocurrents along the length of the nanowire. Our devices are capable of accurate, visible-range monochromatic and broadband light reconstruction, as well as spectral imaging from centimeter-scale focal planes down to lensless, single-cell-scale in situ mapping.EPSRC (EP/M013812/1, EP/L016087/1), the Royal Commission for the Exhibition of 1851, CRUK Pioneer Award (C55962/A24669), , Business Finland (A-Photonics), Academy of Finland, ERC (834742), EU Horizon 2020 (820423), the Cambridge Trust, the Royal Society

Antibody binding loop insertions as diversity elements

In the use of non-antibody proteins as affinity reagents, diversity has generally been derived from oligonucleotide-encoded random amino acids. Although specific binders of high-affinity have been selected from such libraries, random oligonucleotides often encode stop codons and amino acid combinations that affect protein folding. Recently it has been shown that specific antibody binding loops grafted into heterologous proteins can confer the specific antibody binding activity to the created chimeric protein. In this paper, we examine the use of such antibody binding loops as diversity elements. We first show that we are able to graft a lysozyme-binding antibody loop into green fluorescent protein (GFP), creating a fluorescent protein with lysozyme-binding activity. Subsequently we have developed a PCR method to harvest random binding loops from antibodies and insert them at predefined sites in any protein, using GFP as an example. The majority of such GFP chimeras remain fluorescent, indicating that binding loops do not disrupt folding. This method can be adapted to the creation of other nucleic acid libraries where diversity is flanked by regions of relative sequence conservation, and its availability sets the stage for the use of antibody loop libraries as diversity elements for selection experiments

Synthesis and catalysis of chemically reduced metal–metalloid amorphous alloys

This is the published version. Copyright 2012 Royal Society of ChemistryAmorphous alloys structurally deviate from crystalline materials in that they possess unique short-range ordered and long-range disordered atomic arrangement. They are important catalytic materials due to their unique chemical and structural properties including broadly adjustable composition, structural homogeneity, and high concentration of coordinatively unsaturated sites. As chemically reduced metal–metalloid amorphous alloys exhibit excellent catalytic performance in applications such as efficient chemical production, energy conversion, and environmental remediation, there is an intense surge in interest in using them as catalytic materials. This critical review summarizes the progress in the study of the metal–metalloid amorphous alloy catalysts, mainly in recent decades, with special focus on their synthetic strategies and catalytic applications in petrochemical, fine chemical, energy, and environmental relevant reactions. The review is intended to be a valuable resource to researchers interested in these exciting catalytic materials. We concluded the review with some perspectives on the challenges and opportunities about the future developments of metal–metalloid amorphous alloy catalysts

Genome Shuffling Improves Degradation of the Anthropogenic Pesticide Pentachlorophenol by Sphingobium chlorophenolicum ATCC 39723

Pentachlorophenol (PCP), a highly toxic anthropogenic pesticide, can be mineralized by Sphingobium chlorophenolicum, a gram-negative bacterium isolated from PCP-contaminated soil. However, degradation of PCP is slow and S. chlorophenolicum cannot tolerate high levels of PCP. We have used genome shuffling to improve the degradation of PCP by S. chlorophenolicum. We have obtained several strains that degrade PCP faster and tolerate higher levels of PCP than the wild-type strain. Several strains obtained after the third round of shuffling can grow on one-quarter-strength tryptic soy broth plates containing 6 to 8 mM PCP, while the original strain cannot grow in the presence of PCP at concentrations higher than 0.6 mM. Some of the mutants are able to completely degrade 3 mM PCP in one-quarter-strength tryptic soy broth, whereas no degradation can be achieved by the wild-type strain. Analysis of several improved strains suggests that the improved phenotypes are due to various combinations of mutations leading to an enhanced growth rate, constitutive expression of the PCP degradation genes, and enhanced resistance to the toxicity of PCP and its metabolites

Systemic Congestion Propagation in the Airspace Network

To be different from the traditional concept of congestion, congestion propagation based on the correlation between aircraft is given. And the main resource shared and competed for in airspace is the air route network, especially the intersection linking the multiroute. The system composed of congestion propagation units operates in airspace network, which is limited by the network geometry and the correlation between aircraft. This paper presents models based on the congestion and propagation characteristics in complex network, predicting the trend of congestion propagation and the peak of congestion size. By analyzing the relationships between system parameters and congestion propagation and accounting for the effects of propagation across networks, this paper enhances the current dynamics models of congestion propagation in airspace. Firstly, a heterogeneous network model is introduced to reveal the propagation process of aircraft with different degrees of correlation. This is followed by the specification of two simplified models for short-term prediction, just taking the sector capacity, propagation rate, and dissipation rate into account. And the propagation rate and dissipation rate depend on the sector geometry and aircraft distribution. Using them (sector capacity, propagation rate, and dissipation rate), the prediction models are accurate in predicting the evolution of congestion peak and propagation trend in comparison with the sample data of intersections in the sector. Of them, the model with capacity limitation is more accurate on busy hour. And on non-busy hour, capacity is insensitive in predicting congestion clusters. Furthermore, the computing method of propagation rate and dissipation rate is given in our paper. Finally, a numerical analysis is performed, in which it is demonstrated that system capacity, propagation rate, and dissipation rate have different effects on congestion propagation in airspace. The results show that low propagation and high dissipation rates not only are nonlinear but also decrease the level of congestion in the propagation of congestion. In particular, of the three parameters, system capacity affects the rate of convergence, with a low-capacity system reaching a stable state quickly and therefore providing a basis for sector partitioning. The method proposed in this paper should enable air traffic controllers to better understand the characteristics of congestion and its propagation for the benefits of both congestion management and improvement of efficiency. Significantly, airspace designers can take congestion propagation into consideration for optimizing the airspace structure in the future

Modeling Congestion Propagation in Multistage Schedule within an Airport Network

In order to alleviate flight delay it is important to understand how air traffic congestion evolves or propagates. In this context, this paper focusses on the aggravation of airport congestion by the accumulation of delayed departure flights. We start by applying a heterogeneous network model that takes congestion connection/degree into consideration to predict departure congestion clusters. This is on the basis of the fact that, from a micro perspective, the connection between congestion and discrete clusters can be embodied in models. However, the results show prediction to be of high accuracy and time consuming due to the complexities in capturing the connection in congested flights. The problem of being highly time consuming is resolved in this paper by improving the models by stages. Stage partitioning based on the variation of delay clusters is similar to the typical infectious cycle. For heterogeneous networks the model can describe the congestion propagation and its causes at the different stages of operation. If the connection between flights is homogeneous, the model can describe a more indicative process or trend of congestion propagation. In particular, for single source congestion, the simplified multistage models enable short-term prediction to be fast. Furthermore, for the controllers, the accuracy of prediction using simplified models can be acceptable and the speed on the prediction is significantly increased. The simplified models can help controllers to understand congestion propagation characteristics at different stages of operation, make a fast and short-term prediction of congestion clusters, and facilitate the formulation of traffic control strategies