Antimicrobial efficacy of tobramycin polymeric nanoparticles for Pseudomonas aeruginosa infections in cystic fibrosis: formulation, characterisation and functionalisation with dornase alfa (DNase).

Inhaled antibiotics, such as tobramycin, for the treatment of Pseudomonas aeruginosa pulmonary infections are associated with the increase in life expectancy seen in cystic fibrosis (CF) patients over recent years. However, the effectiveness of this aminoglycoside is still limited by its inability to penetrate the thick DNA-rich mucus in the lungs of these patients, leading to low antibiotic exposure to resident bacteria. In this study, we created novel polymeric nanoparticle (NP) delivery vehicles for tobramycin. Using isothermal titration calorimetry, we showed that tobramycin binds with alginate polymer and, by exploiting this interaction, optimised the production of tobramycin alginate/chitosan NPs. It was established that NP antimicrobial activity against P. aeruginosa PA01 was equivalent to unencapsulated tobramycin (minimum inhibitory concentration 0.625 mg/L). Galleria mellonella was employed as an in vivo model for P. aeruginosa infection. Survival rates of 90% were observed following injection of NPs, inferring low NP toxicity. After infection with P. aeruginosa, we showed that a lethal inoculum was effectively cleared by tobramycin NPs in a dose dependent manner. Crucially, a treatment with NPs prior to infection provided a longer window of antibiotic protection, doubling survival rates from 40% with free tobramycin to 80% with NP treatment. Tobramycin NPs were then functionalised with dornase alfa (recombinant human deoxyribonuclease I, DNase), demonstrating DNA degradation and improved NP penetration of CF sputum. Following incubation with CF sputum, tobramycin NPs both with and without DNase functionalisation, exhibited anti-pseudomonal effects. Overall, this work demonstrates the production of effective antimicrobial NPs, which may have clinical utility as mucus-penetrating tobramycin delivery vehicles, combining two widely used CF therapeutics into a single NP formulation. This nano-antibiotic represents a strategy to overcome the mucus barrier, increase local drug concentrations, avoid systemic adverse effects and improve outcomes for pulmonary infections in CF.

Design and physicochemical characterisation of novel dissolving polymeric microneedle arrays for transdermal delivery of high dose, low molecular weight drugs

We describe formulation and evaluation of novel dissolving polymeric microneedle (MN) arrays for the facilitated delivery of low molecular weight, high dose drugs. Ibuprofen sodium was used as the model here and was successfully formulated at approximately 50% w/w in the dry state using the copolymer poly(methylvinylether/maleic acid). These MNs were robust and effectively penetrated skin in vitro, dissolving rapidly to deliver the incorporated drug. The delivery of 1.5mg ibuprofen sodium, the theoretical mass of ibuprofen sodium contained within the dry MN alone, was vastly exceeded, indicating extensive delivery of the drug loaded into the baseplates. Indeed in in vitro transdermal delivery studies, approximately 33mg (90%) of the drug initially loaded into the arrays was delivered over 24h. Iontophoresis produced no meaningful increase in delivery. Biocompatibility studies and in vivo rat skin tolerance experiments raised no concerns. The blood plasma ibuprofen sodium concentrations achieved in rats (263μgml(-1) at the 24h time point) were approximately 20 times greater than the human therapeutic plasma level. By simplistic extrapolation of average weights from rats to humans, a MN patch design of no greater than 10cm(2) could cautiously be estimated to deliver therapeutically-relevant concentrations of ibuprofen sodium in humans. This work, therefore, represents a significant progression in exploitation of MN for successful transdermal delivery of a much wider range of drugs.

High Strength Thermoplastic Bonding for Multi-channel, Multi-layer Lab-on-Chip Devices for Ocean and Environmental applications

A solvent-vapour thermoplastic bonding process is reported which provides high strength bonding of PMMA over a large area for multi-channel and multi-layer microfluidic devices with shallow high resolution channel features. The bond process utilises a low temperature vacuum thermal fusion step with prior exposure of the substrate to chloroform (CHCl3) vapour to reduce bond temperature to below the PMMA glass transition temperature. Peak tensile and shear bond strengths greater than 3 MPa were achieved for a typical channel depth reduction of 25 µm. The device-equivalent bond performance was evaluated for multiple layers and high resolution channel features using double-side and single-side exposure of the bonding pieces. A single-sided exposure process was achieved which is suited to multi-layer bonding with channel alignment at the expense of greater depth loss and a reduction in peak bond strength. However, leak and burst tests demonstrate bond integrity up to at least 10 bar channel pressure over the full substrate area of 100 mm x 100 mm. The inclusion of metal tracks within the bond resulted in no loss of performance. The vertical wall integrity between channels was found to be compromised by solvent permeation for wall thicknesses of 100 µm which has implications for high resolution serpentine structures. Bond strength is reduced considerably for multi-layer patterned substrates where features on each layer are not aligned, despite the presence of an intermediate blank substrate. Overall a high performance bond process has been developed that has the potential to meet the stringent specifications for lab-on-chip deployment in harsh environmental conditions for applications such as deep ocean profiling.

Material Identification of Loose Particles in Sealed Electronic Devices Using PCA and SVM

The existence of loose particles left inside the sealed electronic devices is one of the main factors affecting the reliability of the whole system. It is important to identify the particle material for analyzing their source. The conventional material identification algorithms mainly rely on time, frequency and wavelet domain features. However, these features are usually overlapped and redundant, resulting in unsatisfactory material identification accuracy. The main objective of this paper is to improve the accuracy of material identification. First, the principal component analysis (PCA) is employed to reselect the nine features extracted from time and frequency domains, leading to six less correlated principal components. And then the reselected principal components are used for material identification using a support vector machine (SVM). Finally, the experimental results show that this new method can effectively distinguish the type of materials including wire, aluminum and tin particles.

An Investigation into the Role of Polymeric Carriers on Crystal Growth within Amorphous Solid Dispersion Systems

Using phase diagrams derived from Flory–Huggins theory, we defined the thermodynamic state of amorphous felodipine within three different polymeric carriers. Variation in the solubility and miscibility of felodipine within different polymeric materials (using F–H theory) has been identified and used to select the most suitable polymeric carriers for the production of amorphous drug–polymer solid dispersions. With this information, amorphous felodipine solid dispersions were manufactured using three different polymeric materials (HPMCAS-HF, Soluplus, and PVPK15) at predefined drug loadings, and the crystal growth rates of felodipine from these solid dispersions were investigated. Crystallization of amorphous felodipine was studied using Raman spectral imaging and polarized light microscopy. Using this data, we examined the correlation among several characteristics of solid dispersions to the crystal growth rate of felodipine. An exponential relationship was found to exist between drug loading and crystal growth rate. Moreover, crystal growth within all selected amorphous drug–polymer solid dispersion systems were viscosity dependent (η–ξ). The exponent, ξ, was estimated to be 1.36 at a temperature of 80 °C. Values of ξ exceeding 1 may indicate strong viscosity dependent crystal growth in the amorphous drug–polymer solid dispersion systems. We argue that the elevated exponent value (ξ > 1) is a result of drug–polymer mixing which leads to a less fragile amorphous drug–polymer solid dispersion system. All systems investigated displayed an upper critical solution temperature, and the solid–liquid boundary was always higher than the spinodal decomposition curve. Furthermore, for PVP–FD amorphous dispersions at drug loadings exceeding 0.6 volume ratio, the mechanism of phase separation within the metastable zone was found to be driven by nucleation and growth rather than liquid–liquid separation.

Long-Term Economic Model for Allocation of FACTS Devices in Restructured Power System Integrated Wind Generation

This study proposes an approach to optimally allocate multiple types of flexible AC transmission system (FACTS) devices in market-based power systems with wind generation. The main objective is to maximise profit by minimising device investment cost, and the system's operating cost considering both normal conditions and possible contingencies. The proposed method accurately evaluates the long-term costs and benefits gained by FACTS devices (FDs) installation to solve a large-scale optimisation problem. The objective implies maximising social welfare as well as minimising compensations paid for generation re-scheduling and load shedding. Many technical operation constraints and uncertainties are included in problem formulation. The overall problem is solved using both particle swarm optimisations for attaining optimal FDs allocation as main problem and optimal power flow as sub-optimisation problem. The effectiveness of the proposed approach is demonstrated on modified IEEE 14-bus test system and IEEE 118-bus test system.

Validity of model devices used to assess canine temperament in behavioral tests

Temperament tests are widely accepted as instruments for profiling behavioral variability in dogs, and they are applied in numerous areas of investigation (e.g. suitability for adoption or for breeding). During testing, to elicit a dog's reaction toward novel stimuli and predict its behavior in everyday life, model devices such as a child-like doll, or a fake dog, are often employed. However, the reliability of these devices to accurately stimulate dogs' reactions to children or dogs, is unknown and perhaps overestimated. This may be a particular concern in the case of aggressive behavior toward humans, a significant public health issue. The aim of this study was to: (1) evaluate the correlation between dogs' reactions to these devices, and owners' reports of their dog's aggression history (using the C-BARQ ??); (2) compare reactions toward the devices of dogs with and without histories of aggression. Subjects were selected among those visiting for behavioral consultation at the Veterinary Hospital of the University of Pennsylvania, and previously categorized as aggressive toward unfamiliar children, conspecifics, or as non-aggressive dogs (control). The test consisted of different components: an unfamiliar female tester approaching the dog; the presentation of a child-like doll, an ambiguous object, and a fake plastic dog. All tests were videotaped and durations of behaviors were later analyzed on the basis of a specified ethogram. Dogs' reactions were compared to C-BARQ scores, and interesting correlations emerged for 'dog-directed aggression/fear' (R = 0.48, P = 0.004), and 'stranger-directed aggression' (R = 0.58, P <0.001) factors. Dogs differed in their reactions toward the devices: the child-like doll and the fake dog elicited more social behaviors than the ambiguous object used as a control stimulus. Issues concerning the reliability of these tools to assess canine temperament are discussed. ?? 2012 Elsevier B.V. All rights reserved.

Heterogeneous error-resilient scheme for spectral analysis in ultra-low power wearable electrocardiogram devices

Wearable devices performing advanced bio-signal analysis algorithms are aimed to foster a revolution in healthcare provision of chronic cardiac diseases. In this context, energy efficiency is of paramount importance, as long-term monitoring must be ensured while relying on a tiny power source. Operating at a scaled supply voltage, just above the threshold voltage, effectively helps in saving substantial energy, but it makes circuits, and especially memories, more prone to errors, threatening the correct execution of algorithms. The use of error detection and correction codes may help to protect the entire memory content, however it incurs in large area and energy overheads which may not be compatible with the tight energy budgets of wearable systems. To cope with this challenge, in this paper we propose to limit the overhead of traditional schemes by selectively detecting and correcting errors only in data highly impacting the end-to-end quality of service of ultra-low power wearable electrocardiogram (ECG) devices. This partition adopts the protection of either significant words or significant bits of each data element, according to the application characteristics (statistical properties of the data in the application buffers), and its impact in determining the output. The proposed heterogeneous error protection scheme in real ECG signals allows substantial energy savings (11% in wearable devices) compared to state-of-the-art approaches, like ECC, in which the whole memory is protected against errors. At the same time, it also results in negligible output quality degradation in the evaluated power spectrum analysis application of ECG signals.