An optimised assay for quantitative, high-throughput analysis of polysialyltransferase activity

Analyst, 2016, Accepted Manuscript
DOI: 10.1039/C6AN01073C, Paper

Sara Elkashef, Mark Sutherland, L H Patterson, Paul Loadman, Robert Andrew Falconer
The polysialyltransferases are biologically important glycosyltransferase enzymes responsible for the biosynthesis of polysialic acid, a carbohydrate polymer that plays a critical role in the progression of several diseases, notably cancer....
The content of this RSS Feed (c) The Royal Society of Chemistry

http://ift.tt/2az9SKP

Fluorescence detection of single-nucleotide differences using aptamer-forming binary DNA probes

Analyst, 2016, Accepted Manuscript
DOI: 10.1039/C6AN00912C, Paper

Saori Kamoto, Masumi Hyuga, Teru Kato
We report a simple method for fluorescence detection of single-nucleotide alterations in a long target DNA, which is based on the formation of a three-way-junction-structured cholic-acid-binding DNA aptamer by the...
The content of this RSS Feed (c) The Royal Society of Chemistry

http://ift.tt/2az9yf0

Remote Sensing, Vol. 8, Pages 646: Maximizing the Diversity of Ensemble Random Forests for Tree Genera Classification Using High Density LiDAR Data

Recent research into improving the effectiveness of forest inventory management using airborne LiDAR data has focused on developing advanced theories in data analytics. Furthermore, supervised learning as a predictive model for classifying tree genera (and species, where possible) has been gaining popularity in order to minimize this labor-intensive task. However, bottlenecks remain that hinder the immediate adoption of supervised learning methods. With supervised classification, training samples are required for learning the parameters that govern the performance of a classifier, yet the selection of training data is often subjective and the quality of such samples is critically important. For LiDAR scanning in forest environments, the quantification of data quality is somewhat abstract, normally referring to some metric related to the completeness of individual tree crowns; however, this is not an issue that has received much attention in the literature. Intuitively the choice of training samples having varying quality will affect classification accuracy. In this paper a Diversity Index (DI) is proposed that characterizes the diversity of data quality (Qi) among selected training samples required for constructing a classification model of tree genera. The training sample is diversified in terms of data quality as opposed to the number of samples per class. The diversified training sample allows the classifier to better learn the positive and negative instances and; therefore; has a higher classification accuracy in discriminating the "unknown" class samples from the "known" samples. Our algorithm is implemented within the Random Forests base classifiers with six derived geometric features from LiDAR data. The training sample contains three tree genera (pine; poplar; and maple) and the validation samples contains four labels (pine; poplar; maple; and "unknown"). Classification accuracy improved from 72.8%; when training samples were selected randomly (with stratified sample size); to 93.8%; when samples were selected with additional criteria; and from 88.4% to 93.8% when an ensemble method was used.

http://ift.tt/2aEZdhi

Biosensors, Vol. 6, Pages 43: Effects of Surface Epitope Coverage on the Sensitivity of Displacement Assays that Employ Modified Nanoparticles: Using Bisphenol A as a Model Analyte

With the ever-increasing use of nanoparticles in immunosensors, a fundamental study on the effect of epitope density is presented herein, with a small molecule epitope, on the performance of the displacement assay format in an enzyme-linked immunosorbent assay (ELISA). Thiolated bisphenol A (BPA) functionalized gold nanoparticles (cysBPAv-AuNPs) and specific anti-BPA antibodies are employed for this purpose. It is shown that the displacement of cysBPAv-AuNPs bound to the immobilized antibodies was influenced by both the avidity of bound cysBPAv-AuNPs and the concentration of free BPA to displace it. The importance of surface epitope density was that it changed the number of epitopes in close proximity to the antibody-binding site. This then influenced the avidity of cysBPAv-AuNPs bound to the immobilized antibody. Furthermore, the molar epitope concentration in an assay appears to affect the degree of antibody binding site saturation. Controlling surface epitope density of the functionalized nanoparticles and molar epitope concentration in an assay leads to a decrease of the concentration of free BPA required to displace the bound cysBPAv-AuNP, and hence better assay performance with regards to the D50 value and dynamic range in the displacement assay.

http://ift.tt/2aGauRE

Molecules, Vol. 21, Pages 1031: New Sesquiterpenenoids from Ainsliaea yunnanensis

Investigation of the ethanol extract of the whole plant of Ainsliaea yunnanensis led to the isolation of four new dimeric sesquiterpene lactones, ainsliadimer F–I (1–4), together with seven known dimeric sesquiterpene lactones (5–11) and ten sesquiterpenes (12–21). Their structures were elucidated by spectroscopic methods. The relative stereochemistry of ainsliadimer F was further confirmed by single crystal X-ray diffraction analysis. Compounds 1–21 were tested for the inhibition of nuclear factor kappa B (NF-κB) in the 293-NF-κB-luciferase reporter cell line induced by lipopolysaccharide (LPS), and Compounds 5, 18, 20 and 21 were further tested for the production of TNF-α, IL-1β, IL-6 and IL-10 in RAW 264.7 macrophages induced by LPS. Compounds 5, 18, 20 and 21 exhibited significant activity in anti-inflammatory activity assays.

http://ift.tt/2aF03L0

Polymers, Vol. 8, Pages 289: Key Role of Reinforcing Structures in the Flame Retardant Performance of Self-Reinforced Polypropylene Composites

The flame retardant synergism between highly stretched polymer fibres and intumescent flame retardant systems was investigated in self-reinforced polypropylene composites. It was found that the structure of reinforcement, such as degree of molecular orientation, fibre alignment and weave type, has a particular effect on the fire performance of the intumescent system. As little as 7.2 wt % additive content, one third of the amount needed in non-reinforced polypropylene matrix, was sufficient to reach a UL-94 V-0 rating. The best result was found in self-reinforced polypropylene composites reinforced with unidirectional fibres. In addition to the fire retardant performance, the mechanical properties were also evaluated. The maximum was found at optimal consolidation temperature, while the flame retardant additive in the matrix did not influence the mechanical performance up to the investigated 13 wt % concentration.

http://ift.tt/2az29wp

IJERPH, Vol. 13, Pages 802: Effects of Long-Term Exposure to 60 GHz Millimeter-Wavelength Radiation on the Genotoxicity and Heat Shock Protein (Hsp) Expression of Cells Derived from Human Eye

Human corneal epithelial (HCE-T) and human lens epithelial (SRA01/04) cells derived from the human eye were exposed to 60 gigahertz (GHz) millimeter-wavelength radiation for 24 h. There was no statistically significant increase in the micronucleus (MN) frequency in cells exposed to 60 GHz millimeter-wavelength radiation at 1 mW/cm2 compared with sham-exposed controls and incubator controls. The MN frequency of cells treated with bleomycin for 1 h provided positive controls. The comet assay, used to detect DNA strand breaks, and heat shock protein (Hsp) expression also showed no statistically significant effects of exposure. These results indicate that exposure to millimeter-wavelength radiation has no effect on genotoxicity in human eye cells.

http://ift.tt/2aua2aO