Microparticle-mediated gene delivery for the enhanced expression of a 19-KDa fragment of merozoite surface protein 1 of Plasmodium falciparum

The 19 kDa carboxyl-terminal fragment of merozoite surface protein 1 (MSP119) is a major component of the invasion-inhibitory response in individual immunity to malaria. A novel ultrasonic atomization approach for the formulation of biodegradable poly(lactic-co-glycolic acid) (PLGA) microparticles of malaria DNA vaccines encoding MSP119 is presented here. After condensing the plasmid DNA (pDNA) molecules with a cationic polymer polyethylenimine (PEI), a 40 kHz ultrasonic atomization frequency was used to formulate PLGA microparticles at a flow rate of 18 mL h1. High levels of gene expression and moderate cytotoxicity in COS-7 cells were achieved with the condensed pDNA at a nitrogen to phosphate (N/P) ratio of 20, thus demonstrating enhanced cellular uptake and expression of the transgene. The ability of the microparticles to convey pDNA was examined by characterizing the formulated microparticles. The microparticles displayed Z-average hydrodynamic diameters of 1.50-2.10 lm and zeta potentials of 17.8-23.2 mV. The encapsulation efficiencies were between 78 and 83%, and 76 and 85% of the embedded malaria pDNA molecules were released under physiological conditions in vitro. These results indicate that PLGA-mediated microparticles can be employed as potential gene delivery systems to antigen-presenting cells in the prevention of malaria.

The pragmatic approach : the myriad gene patents before the Australian courts

The Full Court of the Federal Court of Australia in D'Arcy v Myriad Genetics [2014] FCAFC 115 recently upheld the validity of Myriad Genetics' Australian BRCA1 gene patent over isolated DNA sequences.

Learning the learning rate for prediction with expert advice

Most standard algorithms for prediction with expert advice depend on a parameter called the learning rate. This learning rate needs to be large enough to fit the data well, but small enough to prevent overfitting. For the exponential weights algorithm, a sequence of prior work has established theoretical guarantees for higher and higher data-dependent tunings of the learning rate, which allow for increasingly aggressive learning. But in practice such theoretical tunings often still perform worse (as measured by their regret) than ad hoc tuning with an even higher learning rate. To close the gap between theory and practice we introduce an approach to learn the learning rate. Up to a factor that is at most (poly)logarithmic in the number of experts and the inverse of the learning rate, our method performs as well as if we would know the empirically best learning rate from a large range that includes both conservative small values and values that are much higher than those for which formal guarantees were previously available. Our method employs a grid of learning rates, yet runs in linear time regardless of the size of the grid.

Superpixel-based appearance change prediction for long-term navigation across seasons

Changing environments pose a serious problem to current robotic systems aiming at long term operation under varying seasons or local weather conditions. This paper is built on our previous work where we propose to learn to predict the changes in an environment. Our key insight is that the occurring scene changes are in part systematic, repeatable and therefore predictable. The goal of our work is to support existing approaches to place recognition by learning how the visual appearance of an environment changes over time and by using this learned knowledge to predict its appearance under different environmental conditions. We describe the general idea of appearance change prediction (ACP) and investigate properties of our novel implementation based on vocabularies of superpixels (SP-ACP). Our previous work showed that the proposed approach significantly improves the performance of SeqSLAM and BRIEF-Gist for place recognition on a subset of the Nordland dataset under extremely different environmental conditions in summer and winter. This paper deepens the understanding of the proposed SP-ACP system and evaluates the influence of its parameters. We present the results of a large-scale experiment on the complete 10 h Nordland dataset and appearance change predictions between different combinations of seasons.

Edge-weighting of gene expression graphs

In recent years, considerable research efforts have been directed to micro-array technologies and their role in providing simultaneous information on expression profiles for thousands of genes. These data, when subjected to clustering and classification procedures, can assist in identifying patterns and providing insight on biological processes. To understand the properties of complex gene expression datasets, graphical representations can be used. Intuitively, the data can be represented in terms of a bipartite graph, with weighted edges corresponding to gene-sample node couples in the dataset. Biologically meaningful subgraphs can be sought, but performance can be influenced both by the search algorithm, and, by the graph-weighting scheme and both merit rigorous investigation. In this paper, we focus on edge-weighting schemes for bipartite graphical representation of gene expression. Two novel methods are presented: the first is based on empirical evidence; the second on a geometric distribution. The schemes are compared for several real datasets, assessing efficiency of performance based on four essential properties: robustness to noise and missing values, discrimination, parameter influence on scheme efficiency and reusability. Recommendations and limitations are briefly discussed. Keywords: Edge-weighting; weighted graphs; gene expression; bi-clustering

Prediction of GMA welding characteristic parameter by artificial neural network system

Nowadays, demand for automated Gas metal arc welding (GMAW) is growing and consequently need for intelligent systems is increased to ensure the accuracy of the procedure. To date, welding pool geometry has been the most used factor in quality assessment of intelligent welding systems. But, it has recently been found that Mahalanobis Distance (MD) not only can be used for this purpose but also is more efficient. In the present paper, Artificial Neural Networks (ANN) has been used for prediction of MD parameter. However, advantages and disadvantages of other methods have been discussed. The Levenberg–Marquardt algorithm was found to be the most effective algorithm for GMAW process. It is known that the number of neurons plays an important role in optimal network design. In this work, using trial and error method, it has been found that 30 is the optimal number of neurons. The model has been investigated with different number of layers in Multilayer Perceptron (MLP) architecture and has been shown that for the aim of this work the optimal result is obtained when using MLP with one layer. Robustness of the system has been evaluated by adding noise into the input data and studying the effect of the noise in prediction capability of the network. The experiments for this study were conducted in an automated GMAW setup that was integrated with data acquisition system and prepared in a laboratory for welding of steel plate with 12 mm in thickness. The accuracy of the network was evaluated by Root Mean Squared (RMS) error between the measured and the estimated values. The low error value (about 0.008) reflects the good accuracy of the model. Also the comparison of the predicted results by ANN and the test data set showed very good agreement that reveals the predictive power of the model. Therefore, the ANN model offered in here for GMA welding process can be used effectively for prediction goals.

The O-specific polysaccharide structure and biosynthetic gene cluster of Yersinia pseudotuberculosis serotype O:11

In the Yersinia pseudotuberculosis serotyping scheme, 21 serotypes are present originating from about 30 different O-factors distributed within the species. With regard to the chemical structures of lipopolysaccharides (LPSs) and the genetic basis of their biosynthesis, a number, but not all, of Y. pseudotuberculosis strains representing different serotypes have been investigated. In order to present an overall picture of the relationship between genetics and structures, we have been working on the genetics and structures of various Y. pseudotuberculosis O-specific polysaccharides (OPSs). Here, we present a structural and genetic analysis of the Y. pseudotuberculosis serotype O:11 OPS. Our results showed that this OPS structure has the same backbone as that of Y. pseudotuberculosis O:1b, but with a 6d-l-Altf side-branch instead of Parf. The 3′ end of the gene cluster is the same as that for O:1b and has the genes for synthesis of the backbone and for processing the completed repeat unit. The 5′ end has genes for synthesis of 6d-l-Altf and its transfer to the repeating unit backbone. The pathway for the synthesis of the 6d-l-Altf appears to be different from that for 6d-l-Altp in Y. enterocolitica O:3. The chemical structure of the O:11 repeating unit is [Figure]

The O-specific polysaccharide structure and gene cluster of serotype O:12 of the Yersinia pseudotuberculosis complex, and the identification of a novel L-quinovose biosynthesis gene

A major virulence factor for Yersinia pseudotuberculosis is lipopolysaccharide, including O-polysaccharide (OPS). Currently, the OPS based serotyping scheme for Y. pseudotuberculosis includes 21 known O-serotypes, with genetic and structural data available for 17 of them. The completion of the OPS structures and genetics of this species will enable the visualization of relationships between O-serotypes and allow for analysis of the evolutionary processes within the species that give rise to new serotypes. Here we present the OPS structure and gene cluster of serotype O:12, thus adding one more to the set of completed serotypes, and show that this serotype is present in both Y. pseudotuberculosis and the newly identified Y. similis species. The O:12 structure is shown to include two rare sugars: 4-C[(R)-1-hydroxyethyl]-3,6-dideoxy-d-xylo-hexose (d-yersiniose) and 6-deoxy-l-glucopyranose (l-quinovose). We have identified a novel putative guanine diphosphate (GDP)-l-fucose 4-epimerase gene and propose a pathway for the synthesis of GDP-l-quinovose, which extends the known GDP-l-fucose pathway.

Structure of the K2 capsule associated with the KL2 gene cluster of Acinetobacter baumannii

The repeat unit structure of the K2 capsule from an extensively antibiotic-resistant Acinetobacter baumannii global clone 2 (GC2) strain was determined. The oligosaccharide contains three simple sugars, d-glucopyranose, d-galatopyranose and N-acetyl-d-galactosamine, and the complex sugar, 5,7-diacetamido-3,5,7,9-tetradeoxy-l-glycero-l-manno-non-2-ulosonic acid (Pse5Ac7Ac or pseudaminic acid), which has not previously been reported in any A. baumannii capsule. The strain was found to carry all the genes required for the synthesis of the sugars and construction of the K2 structure. The linkages catalyzed by the initiating transferase, three glycosyltransferases and the Wzy polymerase were also predicted. Examination of publicly available A. baumannii genome sequences revealed that the same gene cluster, KL2, often occurs in extensively antibiotic-resistant GC2 isolates and in further strain types. The gene module responsible for the synthesis of pseudaminic acid was also detected in four other K loci. A related module including genes for an acylated relative of pseudaminic acid was also found in two new KL types. A polymerase chain reaction scheme was developed to detect all modules containing genes for sugars based on pseudaminic acid and to specifically detect KL2.

A conjugative plasmid carrying the carbapenem resistance gene blaOXA-23 in AbaR4 in an extensively resistant GC1 Acinetobacter baumannii isolate

OBJECTIVES: To locate the acquired bla(OXA-23) carbapenem resistance gene in an Australian A. baumannii global clone 1 (GC1) isolate. METHODS: The genome of the extensively antibiotic-resistant GC1 isolate A85 harbouring bla(OXA-23) in Tn2006 was sequenced using Illumina HiSeq, and the reads were used to generate a de novo assembly. PCR was used to assemble relevant contigs. Sequences were compared with ones in GenBank. Conjugation experiments were conducted. RESULTS: The sporadic GC1 isolate A85, recovered in 2003, was extensively resistant, exhibiting resistance to imipenem, meropenem and ticarcillin/clavulanate, to cephalosporins and fluoroquinolones and to the older antibiotics gentamicin, kanamycin and neomycin, sulfamethoxazole, trimethoprim and tetracycline. Genes for resistance to older antibiotics are in the chromosome, in an AbaR3 resistance island. A second copy of the ampC gene in Tn6168 confers cephalosporin resistance and the gyrA and parC genes have mutations leading to fluoroquinolone resistance. An 86 335 bp repAci6 plasmid, pA85-3, carrying bla(OXA-23) in Tn2006 in AbaR4, was shown to transfer imipenem, meropenem and ticarcillin/clavulanate resistance into a susceptible recipient. A85 also contains two small cryptic plasmids of 2.7 and 8.7 kb. A85 is sequence type ST126 (Oxford scheme) and carries a novel KL15 capsule locus and the OCL3 outer core locus. CONCLUSIONS: A85 represents a new GC1 lineage identified by the novel capsule locus but retains AbaR3 carrying genes for resistance to older antibiotics. Resistance to imipenem, meropenem and ticarcillin/clavulanate has been introduced into A85 by pA85-3, a repAci6 conjugative plasmid carrying Tn2006 in AbaR4.

Molecular analysis of asymptomatic bacteriuria escherichia coli strain VR50 reveals adaptation to the urinary tract by gene acquisition

Urinary tract infections (UTIs) are among the most common infectious diseases of humans, with Escherichia coli responsible for >80% of all cases. One extreme of UTI is asymptomatic bacteriuria (ABU), which occurs as an asymptomatic carrier state that resembles commensalism. To understand the evolution and molecular mechanisms that underpin ABU, the genome of the ABU E. coli strain VR50 was sequenced. Analysis of the complete genome indicated that it most resembles E. coli K-12, with the addition of a 94-kb genomic island (GI-VR50-pheV), eight prophages, and multiple plasmids. GI-VR50-pheV has a mosaic structure and contains genes encoding a number of UTI-associated virulence factors, namely, Afa (afimbrial adhesin), two autotransporter proteins (Ag43 and Sat), and aerobactin. We demonstrated that the presence of this island in VR50 confers its ability to colonize the murine bladder, as a VR50 mutant with GI-VR50-pheV deleted was attenuated in a mouse model of UTI in vivo. We established that Afa is the island-encoded factor responsible for this phenotype using two independent deletion (Afa operon and AfaE adhesin) mutants. E. coli VR50afa and VR50afaE displayed significantly decreased ability to adhere to human bladder epithelial cells. In the mouse model of UTI, VR50afa and VR50afaE displayed reduced bladder colonization compared to wild-type VR50, similar to the colonization level of the GI-VR50-pheV mutant. Our study suggests that E. coli VR50 is a commensal-like strain that has acquired fitness factors that facilitate colonization of the human bladder.

Remaining useful life prediction of rotating equipment using covariate-based hazard models : industry applications

The ability to estimate the expected Remaining Useful Life (RUL) is critical to reduce maintenance costs, operational downtime and safety hazards. In most industries, reliability analysis is based on the Reliability Centred Maintenance (RCM) and lifetime distribution models. In these models, the lifetime of an asset is estimated using failure time data; however, statistically sufficient failure time data are often difficult to attain in practice due to the fixed time-based replacement and the small population of identical assets. When condition indicator data are available in addition to failure time data, one of the alternate approaches to the traditional reliability models is the Condition-Based Maintenance (CBM). The covariate-based hazard modelling is one of CBM approaches. There are a number of covariate-based hazard models; however, little study has been conducted to evaluate the performance of these models in asset life prediction using various condition indicators and data availability. This paper reviews two covariate-based hazard models, Proportional Hazard Model (PHM) and Proportional Covariate Model (PCM). To assess these models’ performance, the expected RUL is compared to the actual RUL. Outcomes demonstrate that both models achieve convincingly good results in RUL prediction; however, PCM has smaller absolute prediction error. In addition, PHM shows over-smoothing tendency compared to PCM in sudden changes of condition data. Moreover, the case studies show PCM is not being biased in the case of small sample size.

The effect of BCMO1 gene variants on macular pigment optical density in young healthy Caucasians

Background Serum lutein (L) and zeaxanthin (Z) positively correlate with macular pigment optical density (MPOD), hence the latter is a valuable indirect tool for measuring L and Z content in the macula. L and Z have been attributed antioxidant capacity and protection from certain retinal diseases but their uptake within the eye is thought to depend on genetic, age and environmental factors. In particular gene variants within beta-carotene monooxygenase (BCMO1) are thought to modulate MPOD in the macula. Objectives: To determine the effect of BCMO1 single nucleotide polymorphisms (SNPs) rs11645428, rs6420424 and rs6464851 on macular pigment optical density (MPOD) in a cohort of young healthy participants of Caucasian origin with normal ocular health. Design In this cohort study, MPOD was assessed in 46 healthy participants (22 male and 24 female) with a mean age of 24 ± 4.0 years (range 19-33). The three SNPs, rs11645428, rs6420424, rs6564851 that have established associations with MPOD were determined using MassEXTEND (hME) Sequenom assay. One-way analysis of variance (ANOVA) was performed on groups segregated into homozygous and heterozygous BCMO1 genotypes. Correlations between body mass index (BMI), iris colour, gender, central retinal thickness (CRT), diet and MPOD were investigated. Results MPOD did not significantly vary with BCMO1 rs11645428 (F2,41 = 0.700, p = 0.503), rs6420424 (F2,41 = 0.210, p = 0.801) nor rs6464851 homozygous or heterozygous genotypes (F2,41 = 0,13, p = 0.88), in this young healthy cohort. The combination of these three SNPs into triple genotypes based on plasma conversion efficiency did not affect MPOD (F2,41 = 0.07, p = 0.9). There was a significant negative correlation with MPOD and central retinal thickness (r = - 0.39, p = 0.01) but no significant correlation between BMI, iris colour, gender and MPOD. Conclusion Our results indicate that macular pigment deposition within the central retina is not dependent on BCMO1 gene variants in young healthy people. We propose that MPOD is saturated in younger persons and/or other gene variant combinations determine its deposition.