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

OPTIma:simplifying calorimetry for proton computed tomography in high proton flux environments

Objective. Proton computed tomography (pCT) offers a potential route to reducing range uncertainties for proton therapy treatment planning, however the current trend towards high current spot scanning treatment systems leads to high proton fluxes which are challenging for existing systems. Here we demonstrate a novel approach to energy reconstruction, referred to as ‘de-averaging’, which allows individual proton energies to be recovered using only a measurement of their integrated energy without the need for spatial information from the calorimeter. Approach. The method is evaluated in the context of the Optimising Proton Therapy through Imaging (OPTIma) system which uses a simple, relatively inexpensive, scintillator-based calorimeter that reports only the integrated energy deposited by all protons within a cyclotron period, alongside a silicon strip based tracking system capable of reconstructing individual protons in a high flux environment. GEANT4 simulations have been performed to examine the performance of such a system at a modern commercial cyclotron facility using a σ ≈ 10 mm beam for currents in the range 10–50 pA at the nozzle. Main results. Apart from low-density lung tissue, a discrepancy of less than 1% on the Relative Stopping Power is found for all other considered tissues when embedded within a 150 mm spherical Perspex phantom in the 10–30 pA current range, and for some tissues even up to 50 pA. Significance. By removing the need for the calorimeter system to provide spatial information, it is hoped that the de-averaging approach can facilitate clinically relevant, cost effective and less complex calorimeter systems for performing high current pCTs

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

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 /

Optimal Configuration of Proton-Therapy Accelerators for Relative-Stopping-Power Resolution in Proton Computed Tomography

The determination of relative stopping power (RSP) via proton computed tomography (pCT) of a patient is dependent in part on the knowledge of the incoming proton kinetic energies; the uncertainty in these energies is in turn determined by the proton source—typically a cyclotron. Here, we show that reducing the incident proton beam energy spread may significantly improve RSP determination in pCT. We demonstrate that the reduction of beam energy spread from the typical 1.0% (at 70 MeV) down to 0.2% can be achieved at the proton currents needed for imaging at the Paul Scherrer Institut 250-MeV cyclotron. Through a simulated pCT imaging system, we find that this effect results in RSP resolutions as low as 0.2% for materials such as cortical bone, up to 1% for lung tissue. Several materials offer further improvement when the beam (residual) energy is also chosen such that the detection mechanisms used provide the optimal RSP resolution

Limiting Pseudomonas aeruginosa Biofilm Formation Using Cold Atmospheric Pressure Plasma

We investigate the ability to disrupt and limit growth biofilms of Pseudomonas aeruginosa using application of cold atmospheric pressure (CAP) plasma. The effect of the bio-film's exposure to a helium (CAP) jet was assessed at varying time points during biofilm maturation. Results showed that the amount of time during biofilm growth that CAP pressure was applied has a crucial role on the ability of biofilms to mature and recover after CAP exposure. Intervention during the early stages of biofilm formation (0-8 h) results in a 4-5-log reduction in viable bacterial cells (measured at 24 h of incubation) relative to untreated biofilms. However, CAP treatment of biofilm at 12 h and above only results in a 2-log reduction in viable cells. This has potentially important implications for future clinical application of CAP to treat infected wounds

Performance of a novel wafer scale CMOS active pixel sensor for bio-medical imaging

Recently CMOS Active Pixels Sensors (APSs) have become a valuable alternative to amorphous Silicon and Selenium Flat Panel Imagers (FPIs) in bio-medical imaging applications. CMOS APSs can now be scaled up to the standard 20 cm diameter wafer size by means of a reticle stitching block process. However despite wafer scale CMOS APS being monolithic, sources of non-uniformity of response and regional variations can persist representing a significant challenge for wafer scale sensor response. Non-uniformity of stitched sensors can arise from a number of factors related to the manufacturing process, including variation of amplification, variation between readout components, wafer defects and process variations across the wafer due to manufacturing processes. This paper reports on an investigation into the spatial non-uniformity and regional variations of a wafer scale stitched CMOS APS. For the first time a per-pixel analysis of the electro-optical performance of a wafer CMOS APS is presented, to address inhomogeneity issues arising from the stitching techniques used to manufacture wafer scale sensors. A complete model of the signal generation in the pixel array has been provided and proved capable of accounting for noise and gain variations across the pixel array. This novel analysis leads to readout noise and conversion gain being evaluated at pixel level, stitching block level and in regions of interest, resulting in a coefficient of variation ≤ 1.9%. The uniformity of the image quality performance has been further investigated in a typical X-ray application, i.e. mammography, showing a uniformity in terms of CNR among the highest when compared with mammography detectors commonly used in clinical practise. Finally, in order to compare the detection capability of this novel APS with the currently used technology (i.e. FPIs), theoretical evaluation of the Detection Quantum Efficiency (DQE) at zero-frequency has been performed, resulting in a higher DQE for this detector compared to FPIs. Optical characterization, X-ray contrast measurements and theoretical DQE evaluation suggest that a trade off can be found between the need of a large imaging area and the requirement of a uniform imaging performance, making the DynAMITe large area CMOS APS suitable for a range of bio-medical applications