Screening for potential effects of endocrine-disrupting chemicals in peri-urban creeks and rivers in Melbourne, Australia using mosquitofish and recombinant receptor-reporter gene assays

Sexually mature male mosquitofish (Gambusia holbrooki) were collected from various sites around Melbourne in 2009 to evaluate the performance of gonopodial indices as a biomarker for endocrine disruption in Melbourne's waterways. The mosquitofish indices assessed were body length (BL), gonopodial length (GL)/BL ratio, ray 4:6 ratio and the absence or presence of hooks and serrae, and these varied between sites. The study was complemented by measurements of estrogenic, retinoid, thyroid and aryl hydrocarbon (AhR) receptor activities of the water. Male mosquitofish were 16.3-21.5 mm in length, and although there was a statistically significant positive relationship showing that bigger fish had longer gonopodia than small fish (r2 = 0.52, p < 0.001), there were few significant differences in GL/BL ratio of fish between sites. Measured estrogenic activity was mostly in the range 0.1-1.7 ng/L EEQ, with one site having much higher levels (similar to 12 ng/L EEQ). Aryl hydrocarbon (AhR) receptor activity was observed in all water samples (7-180 ng/L beta NF EQ), although there was no consistent pattern in the level of AhR activity observed, i.e., 'clean' sites were as likely to return a high AhR activity response as urban or wastewater treatment plant (WWTP)-impacted sites. There was no correlation between measurements of receptor actvity and gonopodial length (GL):BL ratio and BL. We conclude that the mosquitofish gonopodia only fulfills part of the criteria for biomarker selection for screening. The mosquitofish indices assessed were cheap and easy-to-perform procedures; however, there is no baseline data from the selected sites to evaluate whether differences in the morpholical indices observed at a site were a result of natural selection in the population or due to estrogenic exposure

Effect of increasing salinity on the acute toxicity of a commercial endosulfan formulation to the bdelloid rotifer Philodina acuticornis odiosa

Pesticides, such as endosulfan, can enter surface waters such as lakes and rivers, potentially posing an ecological risk. Rotifers are a dominant zooplankton species in many inland freshwater lakes in Australia; such lakes can also experience increased salinities. Acute toxicity tests (24 h) were conducted to determine the toxicity of a commercial formaulation of endosulfan to the freshwater rotifer Philodina sp. and to investigate the influence of increasing salinity on endosulfan toxicity. Rotifers were found to be relatively tolerant to endosulfan with an EC50 of 1.75 mgL-1 (a.i.), with results also suggesting that there are no interactive effects of salinity on endosulfan toxicity

Utilization of a new bdelloid rotifer (Philodina acuticornis odiosa) assay to evaluate the effect of salinity on the toxicity of chlorothalonil

Acute (24 h) toxicity tests were conducted to determine the toxicity of the fungicide chlorothalonil towards the freshwater bdelloid rotifer (Philodina acuticornis odiosa). Since rotifers are the dominant zooplankton species in many inland freshwater lakes in Australia, the influence of salinity on chlorothalonil toxicty was also assessed. The rotifers used in this study appeared to be reasonably tolerant to changes in salinity, with little mortality observed at 3760 &micro;S cm-1, increasing thereafter at higher salinity. The bdelloid rotifers were, however, found to be highly sensitive to chlorothalonil (24 h LC50, 3.2 &micro;g L-1) with results also suggesting that as salinity increases, so does toxicity (e.g., 24 h LC50 at 5000 &micro;S cm-1, 0.5 &micro;g L-1). <br /

Modelling solute transport in structured soils: performance evaluation of the ADR and TRM models

The movement of chemicals through the soil to the groundwater or discharged to surface waters represents a degradation of these resources. In many cases, serious human and stock health implications are associated with this form of pollution. The chemicals of interest include nutrients, pesticides, salts, and industrial wastes. Recent studies have shown that current models and methods do not adequately describe the leaching of nutrients through soil, often underestimating the risk of groundwater contamination by surface-applied chemicals and overestimating the concentration of resident solutes. This inaccuracy results primarily from ignoring soil structure and nonequilibrium between soil constituents, water, and solutes. A multiple sample percolation system (MSPS), consisting of 25 individual collection wells, was constructed to study the effects of localized soil heterogeneities on the transport of nutrients (NO&minus;3, Cl&minus;, PO3&minus;4) in the vadose zone of an agricultural soil predominantly dominated by clay. Very significant variations in drainage patterns across a small spatial scale were observed (one-way ANOVA, p &lt; 0.001 indicating considerable heterogeneity in water flow patterns and nutrient leaching. Using data collected from the multiple sample percolation experiments, this paper compares the performance of two mathematical models for predicting solute transport, the advective-dispersion model with a reaction term (ADR), and a two-region preferential flow model (TRM) suitable for modelling nonequilibrium transport. These results have implications for modelling solute transport and predicting nutrient loading on a larger scale.<br /

Supervised learning based multimodal MRI brain tumour segmentation using texture features from supervoxels

BACKGROUND: Accurate segmentation of brain tumour in magnetic resonance images (MRI) is a difficult task due to various tumour types. Using information and features from multimodal MRI including structural MRI and isotropic (p) and anisotropic (q) components derived from the diffusion tensor imaging (DTI) may result in a more accurate analysis of brain images. METHODS: We propose a novel 3D supervoxel based learning method for segmentation of tumour in multimodal MRI brain images (conventional MRI and DTI). Supervoxels are generated using the information across the multimodal MRI dataset. For each supervoxel, a variety of features including histograms of texton descriptor, calculated using a set of Gabor filters with different sizes and orientations, and first order intensity statistical features are extracted. Those features are fed into a random forests (RF) classifier to classify each supervoxel into tumour core, oedema or healthy brain tissue. RESULTS: The method is evaluated on two datasets: 1) Our clinical dataset: 11 multimodal images of patients and 2) BRATS 2013 clinical dataset: 30 multimodal images. For our clinical dataset, the average detection sensitivity of tumour (including tumour core and oedema) using multimodal MRI is 86% with balanced error rate (BER) 7%; while the Dice score for automatic tumour segmentation against ground truth is 0.84. The corresponding results of the BRATS 2013 dataset are 96%, 2% and 0.89, respectively. CONCLUSION: The method demonstrates promising results in the segmentation of brain tumour. Adding features from multimodal MRI images can largely increase the segmentation accuracy. The method provides a close match to expert delineation across all tumour grades, leading to a faster and more reproducible method of brain tumour detection and delineation to aid patient management

Observations on metal concentrations in commercial landings of two species of tilapia (Oreochromis mossambicus and Oreochromis niloticus) from reservoirs in six river basins in Sri Lanka

Samples of the muscle of two species of tilapia (Oreochromis mossambicus and O. niloticus; 17-20 cm length) were obtained from at least one reservoir in each of the six river basins (Aruvi Aru, Kala Oya, Kirindi Oya, Ma Oya, Mahaweli, and Walawe Ganga catchments) in Sri Lanka. The metals Ca, Cu, Fe, K, Mg, Mn, Na, and Zn were consistently detected in the muscle tissue. Overall, there were few differences in the concentration of metals between the two species of fish, although there were also some statistically significant differences (p &lt; 0.05) in the concentrations of some metals in fish obtained from some of the reservoirs. Aruvi Aru stands out as a river basin in which the two fish species have significantly lower concentration of metals when compared to other river basins. The concentration of the metals studied were below WHO and FSANZ guideline values for fish, suggesting that the consumption of the metals found in tilapia from these reservoirs poses little risk to human health. <br /

Sociology of Enterprise. Department for Business Innovation & Skills Research Rport

There are more than five million small businesses in the UK. These businesses employ 12.1 million people and account for 33% of the total private sector turnover (BIS, 2014). Although a buoyant small business sector is vital to the success of the UK economy, it is well established that most small businesses never grow or, at best, achieve only modest growth. Accordingly, understanding the factors that drive and shape small business performance is a key concern for both academics and policymakers. By increasing our understanding of these factors, this innovative project can make a major contribution to entrepreneurship research and to the evidence base underpinning enterprise policy