Efficacy of a children's procedural preparation and distraction device on healing in acute burn wound care procedures : study protocol for a randomized controlled trial

BACKGROUND: The intense pain and anxiety triggered by burns and their associated wound care procedures are well established in the literature. Non-pharmacological intervention is a critical component of total pain management protocols and is used as an adjunct to pharmacological analgesia. An example is virtual reality, which has been used effectively to dampen pain intensity and unpleasantness. Possible links or causal relationships between pain/anxiety/stress and burn wound healing have previously not been investigated. The purpose of this study is to investigate these relationships, specifically by determining if a newly developed multi-modal procedural preparation and distraction device (Ditto) used during acute burn wound care procedures will reduce the pain and anxiety of a child and increase the rate of re-epithelialization. METHODS/DESIGN: Children (4 to 12 years) with acute burn injuries presenting for their first dressing change will be randomly assigned to either the (1) Control group (standard distraction) or (2) Ditto intervention group (receiving Ditto, procedural preparation and Ditto distraction). It is intended that a minimum of 29 participants will be recruited for each treatment group. Repeated measures of pain intensity, anxiety, stress and healing will be taken at every dressing change until complete wound re-epithelialization. Further data collection will aid in determining patient satisfaction and cost effectiveness of the Ditto intervention, as well as its effect on speed of wound re-epithelialization. DISCUSSION: Results of this study will provide data on whether the disease process can be altered by reducing stress, pain and anxiety in the context of acute burn wounds. TRIAL REGISTRATION: ACTRN12611000913976.

An Artificial Neutral Network (ANN) model for predicting biodiesel kinetic viscosity as a function of temperature and chemical compositions

An Artificial Neural Network (ANN) is a computational modeling tool which has found extensive acceptance in many disciplines for modeling complex real world problems. An ANN can model problems through learning by example, rather than by fully understanding the detailed characteristics and physics of the system. In the present study, the accuracy and predictive power of an ANN was evaluated in predicting kinetic viscosity of biodiesels over a wide range of temperatures typically encountered in diesel engine operation. In this model, temperature and chemical composition of biodiesel were used as input variables. In order to obtain the necessary data for model development, the chemical composition and temperature dependent fuel properties of ten different types of biodiesels were measured experimentally using laboratory standard testing equipments following internationally recognized testing procedures. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture was optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the absolute fraction of variance (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found that ANN is highly accurate in predicting the viscosity of biodiesel and demonstrates the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties at different temperature levels. Therefore the model developed in this study can be a useful tool in accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

Strain engineering of selective chemical adsorption on monolayer MoS2

Nanomaterials are prone to influence by chemical adsorption because of their large surface to volume ratios. This enables sensitive detection of adsorbed chemical species which, in turn, can tune the property of the host material. Recent studies discovered that single and multi-layer molybdenum disulfide (MoS2) films are ultra-sensitive to several important environmental molecules. Here we report new findings from ab inito calculations that reveal substantially enhanced adsorption of NO and NH3 on strained monolayer MoS2 with significant impact on the properties of the adsorbates and the MoS2 layer. The magnetic moment of adsorbed NO can be tuned between 0 and 1 μB; strain also induces an electronic phase transition between half-metal and metal. Adsorption of NH3 weakens the MoS2 layer considerably, which explains the large discrepancy between the experimentally measured strength and breaking strain of MoS2 films and previous theoretical predictions. On the other hand, adsorption of NO2, CO, and CO2 is insensitive to the strain condition in the MoS2 layer. This contrasting behavior allows sensitive strain engineering of selective chemical adsorption on MoS2 with effective tuning of mechanical, electronic, and magnetic properties. These results suggest new design strategies for constructing MoS2-based ultrahigh-sensitivity nanoscale sensors and electromechanical devices.

Toxic state–corporate crimes, Neo-liberalism and green criminology : the hazards and legacies of the oil, chemical and mineral industries

This paper uses examples from the history and practices of multi-national and large companies in the oil, chemical and asbestos industries to examine their legal and illegal despoiling and destruction of the environment and impact on human and non-human life. The discussion draws on the literature on green criminology and state-corporate crime and considers measures and arrangements that might mitigate or prevent such damaging acts. This paper is part of ongoing work on green criminology and crimes of the economy. It places these actions and crimes in the context of a global neo-liberal economic system and considers and critiques the distorting impact of the GDP model of ‘economic health’ and its consequences for the environment.

Estimation of biodiesel properties from chemical composition – An artificial neural network (ANN) approach

Biodiesel, produced from renewable feedstock represents a more sustainable source of energy and will therefore play a significant role in providing the energy requirements for transportation in the near future. Chemically, all biodiesels are fatty acid methyl esters (FAME), produced from raw vegetable oil and animal fat. However, clear differences in chemical structure are apparent from one feedstock to the next in terms of chain length, degree of unsaturation, number of double bonds and double bond configuration-which all determine the fuel properties of biodiesel. In this study, prediction models were developed to estimate kinematic viscosity of biodiesel using an Artificial Neural Network (ANN) modelling technique. While developing the model, 27 parameters based on chemical composition commonly found in biodiesel were used as the input variables and kinematic viscosity of biodiesel was used as output variable. Necessary data to develop and simulate the network were collected from more than 120 published peer reviewed papers. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture and learning algorithm were optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the coefficient of determination (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found high predictive accuracy of the ANN in predicting fuel properties of biodiesel and has demonstrated the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties. Therefore the model developed in this study can be a useful tool to accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

Paint spray mass spectrometry for the detection of additives from polymers on conducting surfaces

Paint Spray is developed as a direct sampling ionisation method for mass spectrometric analysis of additives in polymer-based surface coatings. The technique simply involves applying an external high voltage (5 kV) to the wetted sample placed in front of the mass spectrometer inlet and represents a much simpler ionisation technique compared to those currently available. The capabilities of Paint Spray are demonstrated herein with the detection of four commercially available hindered amine light stabilisers; TINUVIN® 770, TINUVIN® 292, TINUVIN® 123 and TINUVIN® 152 directly from thermoset polyester-based coil coatings. Paint Spray requires no sample preparation or pre-treatment and combined with its simplicity - requiring no specialised equipment - makes it ideal for use by non-specialists. The application of Paint Spray for industrial use has significant potential as sample collection from a coil coating production line and Paint Spray ionisation could enable fast quality control screening at high sensitivity.

Preparation of mesoporous bioglass coated zirconia scaffold for bone tissue engineering

Porous yttria-stabilized zirconia (YSZ) has been regarded as a potential candidate for bone substitute due to its high mechanical strength. However, porous YSZ is biologically inert to bone tissue. It is therefore necessary to introduce bioactive coatings onto the walls of the porous structures to enhance its bioactivity. In this study, porous YSZ scaffolds were prepared using a replication technique and then coated with mesoporous bioglass due to its excellent bioactivity. The microstructures were examined using scanning electron microscopy and the mechanical strength was evaluated via compression test. The biocompatibility and bioactivity were also evaluated using bone marrow stromal cell (BMSC) proliferation test and simulated body fluid test.

The fragmentation pathways of protonated Amiton in the gas phase : towards the structural characterisation of organophosphorus chemical warfare agents by electrospray ionisation tandem mass spectrometry

Amiton (O,O-diethyl-S-[2-(diethylamino)ethyl]phosphorothiolate), otherwise known as VG, is listed in schedule 2 of the Chemical Weapons Convention (CWC) and has a structure closely related to VX (O-ethyl-S-(2-diisopropylamino)ethylmethylphosphonothiolate). Fragmentation of protonated VG in the gas phase was performed using electrospray ionisation ion trap mass spectrometry (ESI-ITMS) and revealed several characteristic product ions. Quantum chemical calculations provide the most probable structures for these ions as well as the likely unimolecular mechanisms by which they are formed. The decomposition pathways predicted by computation are consistent with deuterium-labeling studies. The combination of experimental and theoretical data suggests that the fragmentation pathways of VG and analogous organophosphorus nerve agents, such as VX and Russian VX, are predictable and thus ESI tandem mass spectrometry is a powerful tool for the verification of unknown compounds listed in the CWC. Copyright (c) 2006 Commonwealth of Australia. Published by John Wiley & Sons, Ltd.

Stepwise engineering of a Pichia pastoris D-amino acid oxidase whole cell catalyst

Trigonopsis variabilis D-amino acid oxidase (TvDAO) is a well characterized enzyme used for cephalosporin C conversion on industrial scale. However, the demands on the enzyme with respect to activity, operational stability and costs also vary with the field of application. Processes that use the soluble enzyme suffer from fast inactivation of TvDAO while immobilized oxidase preparations raise issues related to expensive carriers and catalyst efficiency. Therefore, oxidase preparations that are more robust and active than those currently available would enable a much broader range of economically viable applications of this enzyme in fine chemical syntheses. A multi-step engineering approach was chosen here to develop a robust and highly active Pichia pastoris TvDAO whole-cell biocatalyst. As compared to the native T. variabilis host, a more than seven-fold enhancement of the intracellular level of oxidase activity was achieved in P. pastoris through expression optimization by codon redesign as well as efficient subcellular targeting of the enzyme to peroxisomes. Multi copy integration further doubled expression and the specific activity of the whole cell catalyst. From a multicopy production strain, about 1.3 x 103 U/g wet cell weight (wcw) were derived by standard induction conditions feeding pure methanol. A fed-batch cultivation protocol using a mixture of methanol and glycerol in the induction phase attenuated the apparent toxicity of the recombinant oxidase to yield final biomass concentrations in the bioreactor of >or= 200 g/L compared to only 117 g/L using the standard methanol feed. Permeabilization of P. pastoris using 10% isopropanol yielded a whole-cell enzyme preparation that showed 49% of the total available intracellular oxidase activity and was notably stabilized (by three times compared to a widely used TvDAO expressing Escherichia coli strain) under conditions of D-methionine conversion using vigorous aeration. Stepwise optimization using a multi-level engineering approach has delivered a new P. pastoris whole cell TvDAO biocatalyst showing substantially enhanced specific activity and stability under operational conditions as compared to previously reported preparations of the enzyme. The production of the oxidase through fed-batch bioreactor culture and subsequent cell permeabilization is high-yielding and efficient. Therefore this P. pastoris catalyst has been evaluated for industrial purposes.

A rapid transcriptional activation is induced by the dormancy-breaking chemical hydrogen cyanamide in kiwifruit (Actinidia deliciosa) buds

Budbreak in kiwifruit (Actinidia deliciosa) can be poor in locations that have warm winters with insufficient winter chilling. Kiwifruit vines are often treated with the dormancy-breaking chemical hydrogen cyanamide (HC) to increase and synchronize budbreak. This treatment also offers a tool to understand the processes involved in budbreak. A genomics approach is presented here to increase our understanding of budbreak in kiwifruit. Most genes identified following HC application appear to be associated with responses to stress, but a number of genes appear to be associated with the reactivation of growth. Three patterns of gene expression were identified: Profile 1, an HC-induced transient activation; Profile 2, an HC-induced transient activation followed by a growth-related activation; and Profile 3, HC- and growth-repressed. One group of genes that was rapidly up-regulated in response to HC was the glutathione S-transferase (GST) class of genes, which have been associated with stress and signalling. Previous budbreak studies, in three other species, also report up-regulated GST expression. Phylogenetic analysis of these GSTs showed that they clustered into two sub-clades, suggesting a strong correlation between their expression and budbreak across species.

Preparation and in vitro evaluation of a polymer based controlled release dry powder inhaler formulation for pulmonary delivery

This thesis described the synthesis of an L-leucine conjugate of the biodegradable polymer, chitosan and its potential application for the development of controlled release nanoparticulate dry powder inhaler (DPI) formulations. The study demonstrated that the physicochemical properties of conjugated chitosan nanoparticles had favourable effects on the dispersibility and controlled release profile of a model drug. The toxicity profile of the nanoparticulate formulation revealed promising outcome for its use in pulmonary delivery. The chitosan conjugate produced in this project would be useful for the application of polymer nanoparticulate systems for efficient lung delivery of drugs.

Impact of a change in tillage and crop residue management practice on soil chemical and microbiological properties in a cereal-producing red duplex soil in NSW, Australia

The effect of a change of tillage and crop residue management practice on the chemical and micro-biological properties of a cereal-producing red duplex soil was investigated by superimposing each of three management practices (CC: conventional cultivation, stubble burnt, crop conventionally sown; DD: direct-drilling, stubble retained, no cultivation, crop direct-drilled; SI: stubble incorporated with a single cultivation, crop conventionally sown), for a 3-year period on plots previously managed with each of the same three practices for 14 years. A change from DD to CC or SI practice resulted in a significant decline, in the top 0-5 cm of soil, in organic C, total N, electrical conductivity, NH4-N, NO3-N, soil moisture holding capacity, microbial biomass and CO2 respiration as well as a decline in the microbial quotient (the ratio of microbial biomass C to organic C; P <0.05). In contrast, a change from SI to DD or CC practice or a change from CC to DD or SI practice had only negligible impact on soil chemical properties (P >0.05). However, there was a significant increase in microbial biomass and the microbial quotient in the top 0-5 cm of soil following the change from CC to DD or SI practice and with the change from SI to DD practice (P <0.05). Analysis of ester-linked fatty acid methyl esters (EL-FAMEs) extracted from the 0- to 5-cm and 5- to 10-cm layers of the soils of the various treatments detected changes in the FAME profiles following a change in tillage practice. A change from DD practice to SI or CC practice was associated with a significant decline in the ratio of fungal to bacterial fatty acids in the 0- to 5-cm soil (P <0.05). The results show that a change in tillage practice, particularly the cultivation of a previously minimum-tilled (direct-drilled) soil, will result in significant changes in soil chemical and microbiological properties within a 3-year period. They also show that soil microbiological properties are sensitive indicators of a change in tillage practice.

Formation and electron field emission of graphene films grown by hot filament chemical vapor deposition

Graphene films with different structures were catalytically grown on the silicon substrate pre-deposited with a gold film by hot filament chemical vapor deposition under different conditions, where methane, hydrogen and nitrogen were used as the reactive gases. The morphological and compositional properties of graphene films were studied using advanced instruments including field emission scanning electron microscopy, micro-Raman spectroscopy and X-ray photoelectron spectroscopy. The results indicate that the structure and composition of graphene films are changed with the variation of the growth conditions. According to the theory related to thermodynamics, the formation of graphene films was theoretically analyzed and the results indicate that the formation of graphene films is related to the fast incorporation and precipitation of carbon. The electron field emission (EFE) properties of graphene films were studied in a high vacuum system of ∼10-6 Pa and the EFE results show that the turn-on field is in a range of 5.2-5.64 V μm-1 and the maximum current density is about 63 μ A cm-2 at the field of 7.7 V μm-1. These results are important to control the structure of graphene films and have the potential applications of graphene in various nanodevices.

Microplasma-chemical synthesis and tunable real-time plasmonic responses of alloyed Aux Ag1−x nanoparticles

Tunable synthesis of bimetallic AuxAg1-x alloyed nanoparticles and in situ monitoring of their plasmonic responses is presented. This is a new conceptual approach based on green and energy efficient, reactive, and highly-non-equilibrium microplasma chemistry.

Nanoherding : plasma-chemical synthesis and electric-charge-driven self organization of SiO2 nanodots

We report on the chemical synthesis of the arrays of silicon oxide nanodots and their self-organization on the surface via physical processes triggered by surface charges. The method based on chemically active oxygen plasma leads to the rearrangement of nanostructures and eventually to the formation of groups of nanodots. This behavior is explained in terms of the effect of electric field on the kinetics of surface processes. The direct measurements of the electric charges on the surface demonstrate that the charge correlates with the density and arrangement of nanodots within the array. Extensive numerical simulations support the proposed mechanism and prove a critical role of the electric charges in the self-organization. This simple and environment-friendly self-guided process could be used in the chemical synthesis of large arrays of nanodots on semiconducting surfaces for a variety of applications in catalysis, energy conversion and storage, photochemistry, environmental and biosensing, and several others.