Reducible disulfide-based non-viral gene delivery systems

The design and synthesis of safe efficient non-viral vectors for gene delivery has attracted significant attention in recent years due primarily to the severe side-effect profile reported with the use of their viral counterparts. Previous experiments have revealed that the strong interaction between the carriers and nucleic acid may well hinder the release of the gene from the complex in the cytosol adversely affecting transfection efficiency. However, incorporating reducible disulfide bonds within the delivery systems themselves which are then cleaved in the glutathione-rich intracellular environment may help in solving this puzzle. This review focuses on recent development of these reducible carriers. The biological rationale and approaches to the synthesis of reducible vectors are discussed in detail. The in vitro and in vivo evaluations of reducible carriers are also summarized and it is evident that they offer a promising approach in non-viral gene delivery system design.

Enhanced dispersibility and deposition of spray-dried powders for pulmonary gene therapy

Spray-drying represents a viable alternative to freeze-drying for preparing dry powder dispersions for delivering macromolecules to the lung. The dispersibility of spray-dried powders is limited however, and needs to be enhanced to improve lung deposition and subsequent biological activity. In this study, we investigate the utility of leucine as a dry powder dispersibility enhancer when added prior to spray-drying a model non-viral gene therapy formulation (lipid:polycation:pDNA, LPD). Freeze-dried lactose-LPD, spray-dried lactose-LPD and spray-dried leucine-lactose-LPD powders were prepared. Scanning electron microscopy showed that leucine, increased the surface roughness of spray-dried lactose particles. Particle size analysis revealed that leucine-containing spray-dried powders were unimodally dispersed with a mean particle diameter of 3.12 μm. Both gel electrophoresis and in vitro cell (A549) transfection showed that leucine may compromise the integrity and biological functionality of the gene therapy vector. The deposition of the leucine containing powder was however significantly enhanced as evidenced by an increase in gene expression mediated by dry powder collected at lower stages of a multistage liquid impinger (MSLI). Further studies are required to determine the potential of leucine as a ubiquitous dispersibility enhancer for a variety of pulmonary formulations. © 2003 Taylor & Francis Ltd.

Drug delivery strategies for the treatment of Helicobacter pylori infections

Helicobacter pylori is one of the most common pathogenic bacterial infections, colonising an estimated half of all humans. It is associated with the development of serious gastroduodenal disease - including peptic ulcers, gastric lymphoma and acute chronic gastritis. Current recommended regimes are not wholly effective and patient compliance, side-effects and bacterial resistance can be problematic. Drug delivery to the site of residence in the gastric mucosa may improve efficacy of the current and emerging treatments. Gastric retentive delivery systems potentially allow increased penetration of the mucus layer and therefore increased drug concentration at the site of action. Proposed gastric retentive systems for the enhancement of local drug delivery include floating systems, expandable or swellable systems and bioadhesive systems. Generally, problems with these formulations are lack of specificity, limited to mucus turnover or failure to persist in the stomach. Gastric mucoadhesive systems are hailed as a promising technology to address this issue, penetrating the mucus layer and prolonging activity at the mucus-epithelial interface. This review appraises gastroretentive delivery strategies specifically with regard to their application as a delivery system to target Helicobacter. As drug-resistant strains emerge, the development of a vaccine to eradicate and prevent reinfection is an attractive proposition. Proposed prophylactic and therapeutic vaccines have been delivered using a number of mucosal routes using viral and non-viral vectors. The delivery form, inclusion of adjuvants, and delivery regime will influence the immune response generated. © 2005 Bentham Science Publishers Ltd.

Flexibility of short-strand RNA in aqueous solution as revealed by molecular dynamics simulation:are A′-RNA and A-RNA distinct conformational structures?

We use molecular dynamics simulations to compare the conformational structure and dynamics of a 21-base pair RNA sequence initially constructed according to the canonical A-RNA and A'-RNA forms in the presence of counterions and explicit water. Our study aims to add a dynamical perspective to the solid-state structural information that has been derived from X-ray data for these two characteristic forms of RNA. Analysis of the three main structural descriptors commonly used to differentiate between the two forms of RNA namely major groove width, inclination and the number of base pairs in a helical twist over a 30 ns simulation period reveals a flexible structure in aqueous solution with fluctuations in the values of these structural parameters encompassing the range between the two crystal forms and more. This provides evidence to suggest that the identification of distinct A-RNA and A'-RNA structures, while relevant in the crystalline form, may not be generally relevant in the context of RNA in the aqueous phase. The apparent structural flexibility observed in our simulations is likely to bear ramifications for the interactions of RNA with biological molecules (e.g. proteins) and non-biological molecules (e.g. non-viral gene delivery vectors). © CSIRO 2009.

The effect of pH on PAMAM dendrimer-siRNA complexation:endosomal considerations as determined by molecular dynamics simulation

Intracellular degradation of genes, most notably within the endo-lysosomal compartment is considered a significant barrier to (non-viral) gene delivery in vivo. Previous reports based on in vitro studies claim that carriers possessing a mixture of primary, secondary and tertiary amines are able to buffer the acidic environment within the endosome, allowing for timely release of their contents, leading to higher transfection rates. In this report, we adopt an atomistic molecular dynamics (MD) simulation approach, comparing the complexation of 21-bp siRNA with low-generation polyamidoamine (PAMAM) dendrimers (G0 and G1) at both neutral and acidic pHs, the latter of which mimics the degradative environment within maturing 'late-endosomes'. Our simulations reveal that the time taken for the dendrimer-gene complex (dendriplex) to reach equilibrium is appreciably longer at low pH and this is accompanied by more compact packaging of the dendriplex, as compared to simulations performed at neutral pH. We also note larger absolute values of calculated binding free energies of the dendriplex at low pH, indicating a higher dendrimer-nucleic acid affinity in comparison with neutral pH. These novel simulations provide a more detailed understanding of low molecular-weight polymer-siRNA behavior, mimicking the endosomal environment and provide input of direct relevance to the "proton sponge theory", thereby advancing the rational design of non-viral gene delivery systems.

The use of amino acids to enhance the aerosolisation of spray-dried powders for pulmonary gene therapy

Background Pulmonary delivery of gene therapy offers the potential for the treatment of a range of lung conditions, including cystic fibrosis, asthma and lung cancer. Spray-drying may be used to prepare dry powders for inhalation; however, aerosolisation of such powders is limited, resulting in poor lung deposition and biological functionality. In this study, we examine the use of amino acids (arginine, aspartic acid, threonine, phenylalanine) to enhance the aerosolisation of spray-dried powders containing model non-viral gene vectors. Methods Lipid/polycation/pDNA (LPD) vectors, in the presence or absence of amino acids, were dispersed in lactose solutions, and spray-dried to produce appropriately sized dry powders. Scanning electron microscopy and laser diffraction were used to determine particle morphology and diameter, respectively. Gel electrophoresis was used to examine the influence of amino acids on the structural integrity of the LPD complex. In vitro cell (A.549) transfection was used to determine the biological functionality of the dry powders, and the in vitro aerosolisation performance was assessed using a multistage liquid impinger (MSLI). Results Both gel electrophoresis and in vitro cell transfection indicated that certain amino acids (aspartic acid, threonine) can adversely affect the integrity and biological functionality of the LPD complex. All amino acids significantly increased the aerosolisation of the powder, with the arginine and phenylalanine powders showing optimal deposition in the lower stages of the MSLI. Conclusions Amino acids can be used to enhance the aerosolisation of spray-dried powders for respiratory gene delivery, allowing the development of stable and viable formulations for pulmonary gene therapy.

The use of absorption enhancers to enhance the despersibility of spray-dried powders for pulmonary gene therapy

Background: Pulmonary gene therapy requires aerosolisation of the gene vectors to the target region of the lower respiratory tract. Pulmonary absorption enhancers have been shown to improve the penetration of pharmaceutically active ingredients in the airway. In this study, we investigate whether certain absorption enhancers may also enhance the aerosolisation properties of spray-dried powders containing non-viral gene vectors. Methods: Spray-drying was used to prepare potentially respirable trehalose-based dry powders containing lipid-polycation-pDNA (LPD) vectors and absorption enhancers. Powder morphology and particle size were characterised using scanning electron microscopy and laser diffraction, respectively, with gel electrophoresis used to assess the structural integrity of the pDNA. The biological functionality of the powders was quantified using in vitro cell (A549) transfection. Aerosolisation from a Spinhaler® dry powder inhaler into a multistage liquid impinger (MSLI) was used to assess the in vitro dispersibility and deposition of the powders. Results: Spray-dried powder containing dimethyl-β-cyclodextrin (DMC) demonstrated substantially altered particle morphology and an optimal particle size distribution for pulmonary delivery. The inclusion of DMC did not adversely affect the structural integrity of the LPD complex and the powder displayed significantly greater transfection efficiency as compared to unmodified powder. All absorption enhancers proffered enhanced powder deposition characteristics, with the DMC-modified powder facilitating high deposition in the lower stages of the MSLI. Conclusions: Incorporation of absorption enhancers into non-viral gene therapy formulations prior to spray-drying can significantly enhance the aerosolisation properties of the resultant powder and increase biological functionality at the site of deposition in an in vitro model. Copyright © 2005 John Wiley & Sons, Ltd.

Gene therapy strategies for the treatment of spinal cord injury

Spinal cord injury is a complex pathology often resulting in functional impairment and paralysis. Gene therapy has emerged as a possible solution to the problems of limited neural tissue regeneration through the administration of factors promoting axonal growth, while also offering long-term local delivery of therapeutic molecules at the injury site. Of note, gene therapy is our response to the requirements of neural and glial cells following spinal cord injury, providing, in a time-dependent manner, growth substances for axonal regeneration and eliminating axonal growth inhibitors. Herein, we explore different gene therapy strategies, including targeting gene expression to modulate the presence of neurotrophic growth or survival factors and increase neural tissue plasticity. Special attention is given to describing advances in viral and non-viral gene delivery systems, as well as the available routes of gene delivery. Finally, we discuss the future of combinatorial gene therapies and give consideration to the implementation of gene therapy in humans. © 2014 Future Science Ltd.

Discriminating antigen and non-antigen using proteome dissimilarity II:viral and fungal antigens

Immunogenicity arises via many synergistic mechanisms, yet the overall dissimilarity of pathogenic proteins versus the host proteome has been proposed as a key arbiter. We have previously explored this concept in relation to Bacterial antigens; here we extend our analysis to antigens of viral and fungal origin. Sets of known viral and fungal antigenic and non-antigenic protein sequences were compared to human and mouse proteomes. Both antigenic and non-antigenic sequences lacked human or mouse homologues. Observed distributions were compared using the non-parametric Mann-Whitney test. The statistical null hypothesis was accepted, indicating that antigen and non-antigens did not differ significantly. Likewise, we could not determine a threshold able meaningfully to separate non-antigen from antigen. We conclude that viral and fungal antigens cannot be predicted from pathogen genomes based solely on their dissimilarity to mammalian genomes.

Non-zero mean Gaussian process prior wind field models

This report outlines the derivation and application of a non-zero mean, polynomial-exponential covariance function based Gaussian process which forms the prior wind field model used in 'autonomous' disambiguation. It is principally used since the non-zero mean permits the computation of realistic local wind vector prior probabilities which are required when applying the scaled-likelihood trick, as the marginals of the full wind field prior. As the full prior is multi-variate normal, these marginals are very simple to compute.

Model specification and forecasting foreign exchange rates with vector autoregressions

This study examines the forecasting accuracy of alternative vector autoregressive models each in a seven-variable system that comprises in turn of daily, weekly and monthly foreign exchange (FX) spot rates. The vector autoregressions (VARs) are in non-stationary, stationary and error-correction forms and are estimated using OLS. The imposition of Bayesian priors in the OLS estimations also allowed us to obtain another set of results. We find that there is some tendency for the Bayesian estimation method to generate superior forecast measures relatively to the OLS method. This result holds whether or not the data sets contain outliers. Also, the best forecasts under the non-stationary specification outperformed those of the stationary and error-correction specifications, particularly at long forecast horizons, while the best forecasts under the stationary and error-correction specifications are generally similar. The findings for the OLS forecasts are consistent with recent simulation results. The predictive ability of the VARs is very weak.

Discriminating antigen and non-antigen using proteome dissimilarity III:tumour and parasite antigens

Computational genome analysis enables systematic identification of potential immunogenic proteins within a pathogen. Immunogenicity is a system property that arises through the interaction of host and pathogen as mediated through the medium of a immunogenic protein. The overt dissimilarity of pathogenic proteins when compared to the host proteome is conjectured by some to be the determining principal of immunogenicity. Previously, we explored this idea in the context of Bacterial, Viral, and Fungal antigen. In this paper, we broaden and extend our analysis to include complex antigens of eukaryotic origin, arising from tumours and from parasite pathogens. For both types of antigen, known antigenic and non-antigenic protein sequences were compared to human and mouse proteomes. In contrast to our previous results, both visual inspection and statistical evaluation indicate a much wider range of homologues and a significant level of discrimination; but, as before, we could not determine a viable threshold capable of properly separating non-antigen from antigen. In concert with our previous work, we conclude that global proteome dissimilarity is not a useful metric for immunogenicity for presently available antigens arising from Bacteria, viruses, fungi, parasites, and tumours. While we see some signal for certain antigen types, using dissimilarity is not a useful approach to identifying antigenic molecules within pathogen genomes.

Ontology-based protein-protein interactions extraction from literature using the hidden vector state model

This paper proposes a novel framework of incorporating protein-protein interactions (PPI) ontology knowledge into PPI extraction from biomedical literature in order to address the emerging challenges of deep natural language understanding. It is built upon the existing work on relation extraction using the Hidden Vector State (HVS) model. The HVS model belongs to the category of statistical learning methods. It can be trained directly from un-annotated data in a constrained way whilst at the same time being able to capture the underlying named entity relationships. However, it is difficult to incorporate background knowledge or non-local information into the HVS model. This paper proposes to represent the HVS model as a conditionally trained undirected graphical model in which non-local features derived from PPI ontology through inference would be easily incorporated. The seamless fusion of ontology inference with statistical learning produces a new paradigm to information extraction.

Quantitative prediction of mouse class I MHC peptide binding affinity using support vector machine regression (SVR) models

Background - The binding between peptide epitopes and major histocompatibility complex proteins (MHCs) is an important event in the cellular immune response. Accurate prediction of the binding between short peptides and the MHC molecules has long been a principal challenge for immunoinformatics. Recently, the modeling of MHC-peptide binding has come to emphasize quantitative predictions: instead of categorizing peptides as "binders" or "non-binders" or as "strong binders" and "weak binders", recent methods seek to make predictions about precise binding affinities. Results - We developed a quantitative support vector machine regression (SVR) approach, called SVRMHC, to model peptide-MHC binding affinities. As a non-linear method, SVRMHC was able to generate models that out-performed existing linear models, such as the "additive method". By adopting a new "11-factor encoding" scheme, SVRMHC takes into account similarities in the physicochemical properties of the amino acids constituting the input peptides. When applied to MHC-peptide binding data for three mouse class I MHC alleles, the SVRMHC models produced more accurate predictions than those produced previously. Furthermore, comparisons based on Receiver Operating Characteristic (ROC) analysis indicated that SVRMHC was able to out-perform several prominent methods in identifying strongly binding peptides. Conclusion - As a method with demonstrated performance in the quantitative modeling of MHC-peptide binding and in identifying strong binders, SVRMHC is a promising immunoinformatics tool with not inconsiderable future potential.

Rotation invariant iris feature extraction using Gaussian Markov random fields with non-separable wavelet

Rotation invariance is important for an iris recognition system since changes of head orientation and binocular vergence may cause eye rotation. The conventional methods of iris recognition cannot achieve true rotation invariance. They only achieve approximate rotation invariance by rotating the feature vector before matching or unwrapping the iris ring at different initial angles. In these methods, the complexity of the method is increased, and when the rotation scale is beyond the certain scope, the error rates of these methods may substantially increase. In order to solve this problem, a new rotation invariant approach for iris feature extraction based on the non-separable wavelet is proposed in this paper. Firstly, a bank of non-separable orthogonal wavelet filters is used to capture characteristics of the iris. Secondly, a method of Markov random fields is used to capture rotation invariant iris feature. Finally, two-class kernel Fisher classifiers are adopted for classification. Experimental results on public iris databases show that the proposed approach has a low error rate and achieves true rotation invariance. © 2010.