Cytotoxicity of topical antimicrobial agents used in burn wounds in Australasia

Background: Burn sepsis is a leading cause of mortality and morbidity in patients with major burns. The use of topical antimicrobial agents has helped improve the survival of these patients. Silvazine (Sigma Pharmaceuticals, Melbourne, Australia) (1% silver sulphadiazine and 0.2% chlorhexidine digluconate) is used exclusively in Australasia, and there is no published study on its cytotoxicity. This study compared the relative cytotoxicity of Silvazine with 1% silver sulphadiazine (Flamazine (Smith & Nephew Healthcare. Hull. UK)) and a silver-based dressing (Acticoat (Smith & Nephew Healthcare, Hull, UK)). Methods: Dressings were applied to the centre of culture plates that were then seeded with keratinocytes at an estimated 25% confluence. The plates were incubated for 72 h and culture medium and dressings then removed. Toluidine blue was added to stain the remaining keratinocytes. Following removal of the dye, the plates were photographed under standard conditions and these digital images were analysed using image analysis software. Data was analysed using Student's t-test. Results: In the present study, Silvazine is the most cytotoxic agent. Seventy-two hour exposure to Silvazine in the present study results in almost no keratinocyte survival at all and a highly statistically significant reduction in cell survival relative to control, Acticoat and Flamazine (P

The oil shock of 2005

During the course of 2005, the price of crude oil reached unprecedented high levels, at least in nominal terms. Australian motorists have become used to paying more than a dollar a litre for petrol. Given the past volatility in oil prices, often described in terms of a series of oil ‘shocks’ (the large price increases in 1973, 1979 and 1999), several questions arise. First, will current high prices persist, or will prices decline substantially as occurred after previous oil shocks? Second, is the current shortage of oil a temporary phenomenon, caused by inadequate investment in oil exploration, drilling and refining capacity, or is it a signal that the supply of oil available to the world has peaked? Third, will high oil prices lead to broader economic disruption, as is commonly supposed to have happened after previous shocks? Fourth, how painful will an adjustment to lower use of oil be? Finally, how does all this relate to our efforts to deal with the problem of climate change? This article is an effort to answer some of these questions in the light of the knowledge available to us.

Automatic building detection using the Dempster-Shafer algorithm

An approach and strategy for automatic detection of buildings from aerial images using combined image analysis and interpretation techniques is described in this paper. It is undertaken in several steps. A dense DSM is obtained by stereo image matching and then the results of multi-band classification, the DSM, and Normalized Difference Vegetation Index (NDVI) are used to reveal preliminary building interest areas. From these areas, a shape modeling algorithm has been used to precisely delineate their boundaries. The Dempster-Shafer data fusion technique is then applied to detect buildings from the combination of three data sources by a statistically-based classification. A number of test areas, which include buildings of different sizes, shape, and roof color have been investigated. The tests are encouraging and demonstrate that all processes in this system are important for effective building detection.

Bacterial community structure associated with white band disease in the elkhorn coral Acropora palmata determined using culture-independent 16S rRNA techniques

Culture-independent molecular (16S ribosomal RNA) techniques showed distinct differences in bacterial communities associated with white band disease (WBD) Type I and healthy elkhorn coral Acropora palmata. Differences were apparent at all levels, with a greater diversity present in tissues of diseased colonies. The bacterial community associated with remote, non-diseased coral was distinct from the apparently healthy tissues of infected corals several cm from the disease lesion. This demonstrates a whole-organism effect from what appears to be a localised disease lesion, an effect that has also been recently demonstrated in white plague-like disease in star coral Montastraea annularis. The pattern of bacterial community structure changes was similar to that recently demonstrated for white plague-like disease and black band disease. Some of the changes are likely to be explained by the colonisation of dead and degrading tissues by a micro-heterotroph community adapted to the decomposition of coral tissues. However, specific ribosomal types that are absent from healthy tissues appear consistently in all samples of each of the diseases. These ribotypes are closely related members of a group of alpha-proteobacteria that cause disease, notably juvenile oyster disease, in other marine organisms. It is clearly important that members of this group are isolated for challenge experiments to determine their role in the diseases.

Population differences in finger-length ratios: Ethnicity or latitude?

The relative length of the second and fourth fingers (the 2D:4D ratio) has been taken to be an indicator of prenatal exposure to testosterone, and hence possibly relevant to sexual orientation and other sex-differentiated behaviors. Studies have reported a difference in this ratio between Caucasian males in Britain and in the U.S.: higher average 2D:4D ratios were obtained in Britain. This raises the question of whether differences among different Caucasian gene pools were responsible or whether some environmental variable associated with latitude might be involved (e.g., exposure to sunlight or different day-length patterns). This question was explored by examining 2D:4D ratios for an Australian adolescent sample. The Australians were predominantly of British ancestry, but lived at distances from the equator more like those of the U.S. studies. The Australian 2D:4D ratios resembled those in Britain rather than those in the U.S., tending to exclude hypotheses related to latitude and making differences in gene pools a plausible explanation.

Prismatic dentine in the Australian lungfish, Neoceratodus forsteri (Osteichthyes : Dipnoi)

The Australian lungfish, Neoceratodus forsteri, has a dentition consisting of enamel, mantle dentine and bone, enclosing circumdenteonal, core and interdenteonal dentines. Branching processes from cells that produce interdenteonal dentine leave the cell surface at different angles, with collagen fibrils aligned parallel to the long axis of each process. In the interdenteonal dentine, crystals of calcium hydroxyapatite, form within fibrils of collagen, and grow within a matrix of non-collagenous protein. Crystals are aligned parallel to the cell process, as are the original collagen fibrils. Because the processes are angled to the cell surface, the crystals within the core or interdenteonal dentine are arranged in bundles set at angles to each other. Apatite crystals in circumdenteonal dentine are finer and denser than those of the interdenteonal dentine, and form outside the fibrils of collagen. In mature circumdenteonal dentine the crystals of circumdenteonal dentine form a dense tangled mass, linked to interdenteonal dentine by isolated crystals. The functional lungfish tooth plate contains prisms of large apatite crystals in the interdenteonal dentine and masses of fine tangled crystals around each denteon. This confers mechanical strength on a structure with little enamel that is subjected to heavy wear. (c) 2006 Elsevier Ltd. All rights reserved.

An upper bound on the Bayesian error bars for generalized linear regression

In the Bayesian framework, predictions for a regression problem are expressed in terms of a distribution of output values. The mode of this distribution corresponds to the most probable output, while the uncertainty associated with the predictions can conveniently be expressed in terms of error bars. In this paper we consider the evaluation of error bars in the context of the class of generalized linear regression models. We provide insights into the dependence of the error bars on the location of the data points and we derive an upper bound on the true error bars in terms of the contributions from individual data points which are themselves easily evaluated.

Regression with Gaussian processes

The Bayesian analysis of neural networks is difficult because the prior over functions has a complex form, leading to implementations that either make approximations or use Monte Carlo integration techniques. In this paper I investigate the use of Gaussian process priors over functions, which permit the predictive Bayesian analysis to be carried out exactly using matrix operations. The method has been tested on two challenging problems and has produced excellent results.

Capacity of the upstart algorithm

The storage capacity of multilayer networks with overlapping receptive fields is investigated for a constructive algorithm within a one-step replica symmetry breaking (RSB) treatment. We find that the storage capacity increases logarithmically with the number of hidden units class='mathrm'>K without saturating the Mitchison-Durbin bound. The slope of the logarithmic increase decays exponentionally with the stability with which the patterns have been stored.

Identification of candidate genes for dyslexia susceptibility on chromosome 18

Six independent studies have identified linkage to chromosome 18 for developmental dyslexia or general reading ability. Until now, no candidate genes have been identified to explain this linkage. Here, we set out to identify the gene(s) conferring susceptibility by a two stage strategy of linkage and association analysis. Methodology/Principal Findings: Linkage analysis: 264 UK families and 155 US families each containing at least one child diagnosed with dyslexia were genotyped with a dense set of microsatellite markers on chromosome 18. Association analysis: Using a discovery sample of 187 UK families, nearly 3000 SNPs were genotyped across the chromosome 18 dyslexia susceptibility candidate region. Following association analysis, the top ranking SNPs were then genotyped in the remaining samples. The linkage analysis revealed a broad signal that spans approximately 40 Mb from 18p11.2 to 18q12.2. Following the association analysis and subsequent replication attempts, we observed consistent association with the same SNPs in three genes; melanocortin 5 receptor (MC5R), dymeclin (DYM) and neural precursor cell expressed, developmentally down-regulated 4-like (NEDD4L). Conclusions: Along with already published biological evidence, MC5R, DYM and NEDD4L make attractive candidates for dyslexia susceptibility genes. However, further replication and functional studies are still required.

Minimum description length, regularisation and multi-modal data

Conventional feed forward Neural Networks have used the sum-of-squares cost function for training. A new cost function is presented here with a description length interpretation based on Rissanen's Minimum Description Length principle. It is a heuristic that has a rough interpretation as the number of data points fit by the model. Not concerned with finding optimal descriptions, the cost function prefers to form minimum descriptions in a naive way for computational convenience. The cost function is called the Naive Description Length cost function. Finding minimum description models will be shown to be closely related to the identification of clusters in the data. As a consequence the minimum of this cost function approximates the most probable mode of the data rather than the sum-of-squares cost function that approximates the mean. The new cost function is shown to provide information about the structure of the data. This is done by inspecting the dependence of the error to the amount of regularisation. This structure provides a method of selecting regularisation parameters as an alternative or supplement to Bayesian methods. The new cost function is tested on a number of multi-valued problems such as a simple inverse kinematics problem. It is also tested on a number of classification and regression problems. The mode-seeking property of this cost function is shown to improve prediction in time series problems. Description length principles are used in a similar fashion to derive a regulariser to control network complexity.