Modification of conductive polymer for polymeric anodes of flexible organic light-emitting diodes

Author name used in this publication: Guang-Feng WangAuthor name used in this publication: Xiao-Ming TaoAuthor name used in this publication: John H. Xin2008-2009 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Synthesis and characterization of folate-poly(ethylene glycol) chitosan graft-polyethylenimine as a non-viral carrier for tumor-targeted gene delivery

The use of chitosan and chitosan derivatives for gene delivery is limited due to the low transfection efficiency and difficulty in transfecting into a variety of cell types, including some cancer cells overexpressing folate receptor (FRs). In order to solve this problem, folate (FA) and poly(ethylene glycol) (PEG) was conjugated to chitosan-graft-polyethylenimine (CHI-g-PEI) to enhance water-solubility and the transfection efficiency. In the present study, a cell specific targeting molecule FA was linked on PEG and then grafted the FA-PEG onto CHI-g-PEI. The FA-PEG-grafted CHI-g-PEI (FA-PEG-CHI-g-PEI) effectively condensed the plasmid DNA (pDNA) into nanoparticles with positive surface charge under the suitable nitrogen/phosphorus (N/P) ratio. In vitro, transfection efficiency of the FA-PEG-CHI-g-PEI /pDNA complex in 293T cells and LoVo cells (FRs over-expressing cell lines) increased with increasing N/P ratio under N/P = 15 and was more than 50%, but no significant difference in human lung carcinoma cells (A549) cells (FRs deficient cell lines). Importantly, in vivo luciferase expression showed that the efficiency of FA-PEG-CHI-g-PEI -mediated transfection (50 μg luciferase plasmid (pLuc), N/P ratio = 15) was comparable to that of adenovirus-mediated luciferase transduction (1 × 109 pfu) in melanomabearing mice. It was concluded that FA-PEG-CHI-g-PEI, which has improved transfection efficiency and FRs specificity in vitro and in vivo, may be useful in gene therapy.Key words: Folate poly(ethylene glycol)-chitosan-grafted-polyethylenimine (FA-PEG-CHI-g-PEI), gene transfection, non-virus vector, in vitro, in viv

Synthetic and Real Inputs for Tool Segmentation in Robotic Surgery

Semantic tool segmentation in surgical videos is important for surgical scene understanding and computer-assisted interventions as well as for the development of robotic automation. The problem is challenging because different illumination conditions, bleeding, smoke and occlusions can reduce algorithm robustness. At present labelled data for training deep learning models is still lacking for semantic surgical instrument segmentation and in this paper we show that it may be possible to use robot kinematic data coupled with laparoscopic images to alleviate the labelling problem. We propose a new deep learning based model for parallel processing of both laparoscopic and simulation images for robust segmentation of surgical tools. Due to the lack of laparoscopic frames annotated with both segmentation ground truth and kinematic information a new custom dataset was generated using the da Vinci Research Kit (dVRK) and is made available

A False Start in the Race Against Doping in Sport: Concerns With Cycling’s Biological Passport

Professional cycling has suffered from a number of doping scandals. The sport’s governing bodies have responded by implementing an aggressive new antidoping program known as the biological passport. Cycling’s biological passport marks a departure from traditional antidoping efforts, which have focused on directly detecting prohibited substances in a cyclist’s system. Instead, the biological passport tracks biological variables in a cyclist’s blood and urine over time, monitoring for fluctuations that are thought to indirectly reveal the effects of doping. Although this method of indirect detection is promising, it also raises serious legal and scientific concerns. Since its introduction, the cycling community has debated the reliability of indirect biological-passport evidence and the clarity, consistency, and transparency of its use in proving doping violations. Such uncertainty undermines the legitimacy of finding cyclists guilty of doping based on this indirect evidence alone. Antidoping authorities should address these important concerns before continuing to pursue doping sanctions against cyclists solely on the basis of their biological passports

Colored Resonant Signals at the LHC: Largest Rate and Simplest Topology

We study the colored resonance production at the LHC in a most general approach. We classify the possible colored resonances based on group theory decomposition, and construct their effective interactions with light partons. The production cross section from annihilation of valence quarks or gluons may be on the order of 400 - 1000 pb at LHC energies for a mass of 1 TeV with nominal couplings, leading to the largest production rates for new physics at the TeV scale, and simplest event topology with dijet final states. We apply the new dijet data from the LHC experiments to put bounds on various possible colored resonant states. The current bounds range from 0.9 to 2.7 TeV. The formulation is readily applicable for future searches including other decay modes.Comment: 29 pages, 9 figures. References updated and additional K-factors include

Using metrics and sustainability considerations to evaluate the use of bio-based and non-renewable Brønsted acidic ionic liquids to catalyse Fischer esterification reactions

Background Ionic liquids have found uses in many applications, one of which is the joint solvation and catalysis of chemical transformations. Suitable Brønsted acidic ionic liquids can be formed by combining lactams with sulphonic acids. This work weighs up the relative benefits and disadvantages of applying these Brønsted acidic ionic liquid catalysts in esterifications through a series of comparisons using green chemistry metrics. Results A new bio-based ionic liquid was synthesised from N-methyl pyrrolidinone and p-cymenesulphonic acid, and tested as a catalyst in three Fischer esterifications under different conditions. An evaluation of the performance of this Brønsted acidic ionic liquid was made through the comparison to other ionic liquid catalysts as well as conventional homogeneous Brønsted acids. Conclusion Extending the argument to feedstock security as well as mass utilisation, ultimately in most instances traditional mineral acids appear to be the most sensible option for Brønsted acid esterification catalysts. Ester yields obtained from Brønsted acidic ionic liquid catalysed procedures were modest. This calls into question the diversity of research exploring esterification catalysis and the role of ionic liquids in esterifications

Determining the neurotransmitter concentration profile at active synapses

Establishing the temporal and concentration profiles of neurotransmitters during synaptic release is an essential step towards understanding the basic properties of inter-neuronal communication in the central nervous system. A variety of ingenious attempts has been made to gain insights into this process, but the general inaccessibility of central synapses, intrinsic limitations of the techniques used, and natural variety of different synaptic environments have hindered a comprehensive description of this fundamental phenomenon. Here, we describe a number of experimental and theoretical findings that has been instrumental for advancing our knowledge of various features of neurotransmitter release, as well as newly developed tools that could overcome some limits of traditional pharmacological approaches and bring new impetus to the description of the complex mechanisms of synaptic transmission

Comparison of hospital charge prediction models for gastric cancer patients: neural network vs. decision tree models

<p>Abstract</p> <p>Background</p> <p>In recent years, artificial neural network is advocated in modeling complex multivariable relationships due to its ability of fault tolerance; while decision tree of data mining technique was recommended because of its richness of classification arithmetic rules and appeal of visibility. The aim of our research was to compare the performance of ANN and decision tree models in predicting hospital charges on gastric cancer patients.</p> <p>Methods</p> <p>Data about hospital charges on 1008 gastric cancer patients and related demographic information were collected from the First Affiliated Hospital of Anhui Medical University from 2005 to 2007 and preprocessed firstly to select pertinent input variables. Then artificial neural network (ANN) and decision tree models, using same hospital charge output variable and same input variables, were applied to compare the predictive abilities in terms of mean absolute errors and linear correlation coefficients for the training and test datasets. The transfer function in ANN model was sigmoid with 1 hidden layer and three hidden nodes.</p> <p>Results</p> <p>After preprocess of the data, 12 variables were selected and used as input variables in two types of models. For both the training dataset and the test dataset, mean absolute errors of ANN model were lower than those of decision tree model (1819.197 vs. 2782.423, 1162.279 vs. 3424.608) and linear correlation coefficients of the former model were higher than those of the latter (0.955 vs. 0.866, 0.987 vs. 0.806). The predictive ability and adaptive capacity of ANN model were better than those of decision tree model.</p> <p>Conclusion</p> <p>ANN model performed better in predicting hospital charges of gastric cancer patients of China than did decision tree model.</p

Contribution of genetic effects to genetic variance components with epistasis and linkage disequilibrium

<p>Abstract</p> <p>Background</p> <p>Cockerham genetic models are commonly used in quantitative trait loci (QTL) analysis with a special feature of partitioning genotypic variances into various genetic variance components, while the F_∞genetic models are widely used in genetic association studies. Over years, there have been some confusion about the relationship between these two type of models. A link between the additive, dominance and epistatic effects in an F_∞model and the additive, dominance and epistatic variance components in a Cockerham model has not been well established, especially when there are multiple QTL in presence of epistasis and linkage disequilibrium (LD).</p> <p>Results</p> <p>In this paper, we further explore the differences and links between the F_∞and Cockerham models. First, we show that the Cockerham type models are allelic based models with a special modification to correct a confounding problem. Several important moment functions, which are useful for partition of variance components in Cockerham models, are also derived. Next, we discuss properties of the F_∞models in partition of genotypic variances. Its difference from that of the Cockerham models is addressed. Finally, for a two-locus biallelic QTL model with epistasis and LD between the loci, we present detailed formulas for calculation of the genetic variance components in terms of the additive, dominant and epistatic effects in an F_∞model. A new way of linking the Cockerham and F_∞model parameters through their coding variables of genotypes is also proposed, which is especially useful when reduced F_∞models are applied.</p> <p>Conclusion</p> <p>The Cockerham type models are allele-based models with a focus on partition of genotypic variances into various genetic variance components, which are contributed by allelic effects and their interactions. By contrast, the F_∞regression models are genotype-based models focusing on modeling and testing of within-locus genotypic effects and locus-by-locus genotypic interactions. When there is no need to distinguish the paternal and maternal allelic effects, these two types of models are transferable. Transformation between an F_∞model's parameters and its corresponding Cockerham model's parameters can be established through a relationship between their coding variables of genotypes. Genetic variance components in terms of the additive, dominance and epistatic genetic effects in an F_∞model can then be calculated by translating formulas derived for the Cockerham models.</p

Pulse energy packing effects on material transport during laser processing of &lt; 1

The effects of energy pulse packing on material transport during single-pulse laser processing of silicon is studied using temporarily shaped pulses with durations from 50 to 150 ns. Six regimes of material transport were identified and disambiguated through energy packing considerations over a range of pulse durations. Energy packing has been shown to shift the interaction to energetically costlier regimes without appreciable benefit in either depth, material removal or crater morphology and quality.The authors would like to thank the UK Technology Strategy Board under project TP14/HVM/6/I/BD5665. The authors acknowledge the EPSRC Centre for Doctoral Training in Photonic Systems Development for their generous support