A geospatial framework to support integrated biogeochemical modelling in the United Kingdom

Anthropogenic impacts on the aquatic environment, especially in the context of nutrients, provide a major challenge for water resource management. The heterogeneous nature of policy relevant management units (e.g. catchments), in terms of environmental controls on nutrient source and transport, leads to the need for holistic management. However, current strategies are limited by current understanding and knowledge that is transferable between spatial scales and landscape typologies. This study presents a spatially-explicit framework to support the modelling of nutrients from land to water, encompassing environmental and spatial complexities. The framework recognises nine homogeneous landscape units, distinct in terms of sensitivity of nutrient losses to waterbodies. The functionality of the framework is demonstrated by supporting an exemplar nutrient model, applied within the Environmental Virtual Observatory pilot (EVOp) cloud cyber-infrastructure. We demonstrate scope for the use of the framework as a management decision support tool and for further development of integrated biogeochemical modelling

Effectiveness of moving on: an Australian designed generic self-management program for people with a chronic illness

Background: This paper presents the evaluation of “Moving On”, a generic self-management program for people with a chronic illness developed by Arthritis NSW. The program aims to help participants identify their need for behavior change and acquire the knowledge and skills to implement changes that promote their health and quality of life. Method: A prospective pragmatic randomised controlled trial involving two group programs in community settings: the intervention program (Moving On) and a control program (light physical activity). Participants were recruited by primary health care providers across the north-west region of metropolitan Sydney, Australia between June 2009 and October 2010. Patient outcomes were self-reported via pre- and post-program surveys completed at the time of enrolment and sixteen weeks after program commencement. Primary outcomes were change in self-efficacy (Self-efficacy for Managing Chronic Disease 6-Item Scale), self-management knowledge and behaviour and perceived health status (Self-Rated Health Scale and the Health Distress Scale). Results: A total of 388 patient referrals were received, of whom 250 (64.4%) enrolled in the study. Three patients withdrew prior to allocation. 25 block randomisations were performed by a statistician external to the research team: 123 patients were allocated to the intervention program and 124 were allocated to the control program. 97 (78.9%) of the intervention participants commenced their program. The overall attrition rate of 40.5% included withdrawals from the study and both programs. 24.4% of participants withdrew from the intervention program but not the study and 22.6% withdrew from the control program but not the study. A total of 62 patients completed the intervention program and follow-up evaluation survey and 77 patients completed the control program and follow- up evaluation survey. At 16 weeks follow-up there was no significant difference between intervention and control groups in self-efficacy; however, there was an increase in self-efficacy from baseline to follow-up for the intervention participants (t=−1.948, p=0.028). There were no significant differences in self-rated health or health distress scores between groups at follow-up, with both groups reporting a significant decrease in health distress scores. There was no significant difference between or within groups in self-management knowledge and stage of change of behaviours at follow-up. Intervention group attenders had significantly higher physical activity (t=−4.053, p=0.000) and nutrition scores (t=2.315, p= 0.01) at follow-up; however, these did not remain significant after adjustment for covariates. At follow-up, significantly more participants in the control group (20.8%) indicated that they did not have a self-management plan compared to those in the intervention group (8.8%) (X2=4.671, p=0.031). There were no significant changes in other self-management knowledge areas and behaviours after adjusting for covariates at follow-up. Conclusions: The study produced mixed findings. Differences between groups as allocated were diluted by the high proportion of patients not completing the program. Further monitoring and evaluation are needed of the impact and cost effectiveness of the program. Trial registration: Australian New Zealand Clinical Trials Registry: ACTRN1260900029821

AII amacrine cells discriminate between heterocellular and homocellular locations when assembling connexin36-containing gap junctions

Electrical synapses (gap junctions) rapidly transmit signals between neurons and are composed of connexins. In neurons, connexin36 (C×36) is the most abundant isoform; however, the mechanisms underlying formation of C×36-containing electrical synapses are unknown. We focus on homocellular and heterocellular gap junctions formed by an AII amacrine cell, a key interneuron found in all mammalian retinas. In mice lacking native C×36 but expressing a variant tagged with enhanced green fluorescent protein at the C-terminus (KO-C×36-EGFP), heterocellular gap junctions formed between AII cells and ON cone bipolar cells are fully functional, whereas homocellular gap junctions between two AII cells are not formed. A tracer injected into an AII amacrine cell spreads into ON cone bipolar cells but is excluded from other AII cells. Reconstruction of C×36-EGFP clusters on an AII cell in the KO-C×36-EGFP genotype confirmed that the number, but not average size, of the clusters is reduced - as expected for AII cells lacking a subset of electrical synapses. Our studies indicate that some neurons exhibit at least two discriminatory mechanisms for assembling C×36. We suggest that employing different gapjunction- forming mechanisms could provide the means for a cell to regulate its gap junctions in a target-cell-specific manner, even if these junctions contain the same connexin

Why honey is effective as a medicine. 1. Its use in modern medicine

Honey has been used as a medicine for thousands of years and its curative properties are well documented. However, modern medicine turned its back on honey and it is only now, with the advent of multi-resistant bacteria, that the antibiotic properties of honey are being rediscovered

Quantitative PET image reconstruction employing nested expectation-maximization deconvolution for motion compensation

Bulk body motion may randomly occur during PET acquisitions introducing blurring, attenuation-emission mismatches and, in dynamic PET, discontinuities in the measured time activity curves between consecutive frames. Meanwhile, dynamic PET scans are longer, thus increasing the probability of bulk motion. In this study, we propose a streamlined 3D PET motion-compensated image reconstruction (3D-MCIR) framework, capable of robustly deconvolving intra-frame motion from a static or dynamic 3D sinogram. The presented 3D-MCIR methods need not partition the data into multiple gates, such as 4D MCIR algorithms, or access list-mode (LM) data, such as LM MCIR methods, both associated with increased computation or memory resources. The proposed algorithms can support compensation for any periodic and non-periodic motion, such as cardio-respiratory or bulk motion, the latter including rolling, twisting or drifting. Inspired from the widely adopted point-spread function (PSF) deconvolution 3D PET reconstruction techniques, here we introduce an image-based 3D generalized motion deconvolution method within the standard 3D maximum-likelihood expectation-maximization (ML-EM) reconstruction framework. In particular, we initially integrate a motion blurring kernel, accounting for every tracked motion within a frame, as an additional MLEM modeling component in the image space (integrated 3D-MCIR). Subsequently, we replaced the integrated model component with a nested iterative Richardson-Lucy (RL) image-based deconvolution method to accelerate the MLEM algorithm convergence rate (RL-3D-MCIR). The final method was evaluated with realistic simulations of whole-body dynamic PET data employing the XCAT phantom and real human bulk motion profiles, the latter estimated from volunteer dynamic MRI scans. In addition, metabolic uptake rate Ki parametric images were generated with the standard Patlak method. Our results demonstrate significant improvement in contrast-to-noise ratio (CNR) and noise-bias performance in both dynamic and parametric images. The proposed nested RL-3D-MCIR method is implemented on the Software for Tomographic Image Reconstruction (STIR) open-source platform and is scheduled for public release

Helical coherence of DNA in crystals and solution

The twist, rise, slide, shift, tilt and roll between adjoining base pairs in DNA depend on the identity of the bases. The resulting dependence of the double helix conformation on the nucleotide sequence is important for DNA recognition by proteins, packaging and maintenance of genetic material, and other interactions involving DNA. This dependence, however, is obscured by poorly understood variations in the stacking geometry of the same adjoining base pairs within different sequence contexts. In this article, we approach the problem of sequence-dependent DNA conformation by statistical analysis of X-ray and NMR structures of DNA oligomers. We evaluate the corresponding helical coherence length—a cumulative parameter quantifying sequence-dependent deviations from the ideal double helix geometry. We find, e.g. that the solution structure of synthetic oligomers is characterized by 100–200 Å coherence length, which is similar to ∼150 Å coherence length of natural, salmon-sperm DNA. Packing of oligomers in crystals dramatically alters their helical coherence. The coherence length increases to 800–1200 Å, consistent with its theoretically predicted role in interactions between DNA at close separations

Major 20th century changes of water-soluble humic-like substances (HULISWS) aerosol over Europe inferred from Alpine ice cores

Using a newly developed method dedicated to measurements of water-soluble humic-like substances (HULISWS) in atmospheric aerosol samples, the carbon mass quantification of HULISWS in an Alpine ice core is achieved for the first time. The method is based on the extraction of HULISWS with a weak anion-exchanger resin and the subsequent quantification of the extracted carbon fraction with a total organic carbon (TOC) analyzer. Measurements were performed along a Col du Dôme (4250m above sea level, French Alps) ice core covering the 1920-2004 time period. The HULISWS concentrations exhibit a well-marked seasonal cycle with winter minima close to 7 ppbC and summer maxima ranging between 10 and 50 ppbC. Whereas the winter HULISWS concentrations remained unchanged over the twentieth century, the summer concentrations increased from 20 ppbC prior to the Second World War to 35 ppbC in the 1970-1990s. These different trends reflect the different types of HULISWS sources in winter and summer. HULISWS are mainly primarily emitted by domestic wood burning in winter and secondary in summer being produced from biogenic precursors. For unknown reason, the HULISWS signal is found to be unusual in ice samples corresponding to World War II

DNA from Plant leaf Extracts: A Review for Emerging and Promising Novel Green Corrosion Inhibitors.

With growing global awareness and concern for environmental protection through the use of less hazardous and environmentally-friendly extracts of plant origin, there has been a plethora of green corrosion inhibitors research with far reaching contributions to the science of corrosion prevention and control. Attention has increasingly turned towards green corrosion inhibitors, compounds of natural origin with anti-oxidant activity towards metals and their alloys. Green inhibitors have been investigated for their corrosion and adsorption properties with good results. The findings from these research works provide evidence of the adsorption behavior of green inhibitors which was confirmed by the adsorption isotherms that were proposed. Adsorption is the first step of any surface reaction and since corrosion is a surface phenomenon the effectiveness of green corrosion inhibitors is related to their ability to adsorb on metal surfaces. This review proposes the potential of plant dna as an emerging and promising novel inhibitor for mild steel. It begins with a list of plants that have been used in studies to determine corrosion inhibition properties and moves on to establish the adsorption behavior of bio macromolecules; protein, polysaccharides (chitosan) and dna. It reviews studies and investigation of dna interaction and adsorption on inorganic surfaces before focusing on the use of salmon (fish) sperm dna and calf thymus gland dna as green corrosion inhibitors for mild steel. It concludes that plant dna is a promising candidate for green corrosion inhibitor given the similarity between the plant and animal dna structure and function, and the fact that the use of plant is more environmentally sustainable than animal-based produc

An Introduction to EEG Source Analysis with an illustration of a study on Error-Related Potentials

International audienceOver the last twenty years blind source separation (BSS) has become a fundamental signal processing tool in the study of human electroencephalography (EEG), other biological data, as well as in many other signal processing domains such as speech, images, geophysics and wireless communication (Comon and Jutten, 2010). Without relying on head modeling BSS aims at estimating both the waveform and the scalp spatial pattern of the intracranial dipolar current responsible of the observed EEG, increasing the sensitivity and specificity of the signal received from the electrodes on the scalp. This chapter begins with a short review of brain volume conduction theory, demonstrating that BSS modeling is grounded on current physiological knowledge. We then illustrate a general BSS scheme requiring the estimation of second-order statistics (SOS) only. A simple and efficient implementation based on the approximate joint diagonalization of covariance matrices (AJDC) is described. The method operates in the same way in the time or frequency domain (or both at the same time) and is capable of modeling explicitly physiological and experimental source of variations with remarkable flexibility. Finally, we provide a specific example illustrating the analysis of a new experimental study on error-related potentials