461 research outputs found

    Understanding the distribution of marine megafauna in the English channel region: identifying key habitats for conservation within the busiest seaway on earth.

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    Published onlineJournal ArticleResearch Support, Non-U.S. Gov'tThis is the final version of the article. Available from Public Library of Science via the DOI in this record.The temperate waters of the North-Eastern Atlantic have a long history of maritime resource richness and, as a result, the European Union is endeavouring to maintain regional productivity and biodiversity. At the intersection of these aims lies potential conflict, signalling the need for integrated, cross-border management approaches. This paper focuses on the marine megafauna of the region. This guild of consumers was formerly abundant, but is now depleted and protected under various national and international legislative structures. We present a meta-analysis of available megafauna datasets using presence-only distribution models to characterise suitable habitat and identify spatially-important regions within the English Channel and southern bight of the North Sea. The integration of studies from dedicated and opportunistic observer programmes in the United Kingdom and France provide a valuable perspective on the spatial and seasonal distribution of various taxonomic groups, including large pelagic fishes and sharks, marine mammals, seabirds and marine turtles. The Western English Channel emerged as a hotspot of biodiversity for megafauna, while species richness was low in the Eastern English Channel. Spatial conservation planning is complicated by the highly mobile nature of marine megafauna, however they are important components of the marine environment and understanding their distribution is a first crucial step toward their inclusion into marine ecosystem management.The INTERREG IV A France (Channel) – England cross-border European cooperation programme, co-financed by the European Regional Development Fund as part of the CHannel integrated Approach for marine Resource Management (CHARM) Phase III project provided funding for the meta-analysis presented in this manuscript through EU postdoctoral fellowships to C. McClellan and S. Patrick. R. Deaville provided the UK cetacean strandings data, which together with the marine turtle data was co-funded by the UK Department for Environment, Food and Rural Affairs (Defra) and by the devolved governments in Scotland and Wales. G. Bradbury and J. Darke provided data from the UK's Wildfowl and Wetlands Trust, which was funded by the Department of Energy and Climate Change. T. Dunn provided the Joint Cetacean Database and the European Seabirds at Sea data. P.S. Hammond provided the SCANS and SCANS-II data funded by EU LIFE Nature projects LIFE 92-2/UK/027 and LIFE04NAT/GB/000245, respectively. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

    Proposals for evaluating the regularity of a scientist'sresearch output

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    Evaluating the career of individual scientists according to their scientific output is a common bibliometric problem. Two aspects are classically taken into account: overall productivity and overall diffusion/impact, which can be measured by a plethora of indicators that consider publications and/or citations separately or synthesise these two quantities into a single number (e.g. h-index). A secondary aspect, which is sometimes mentioned in the rules of competitive examinations for research position/promotion, is time regularity of one researcher's scientific output. Despite the fact that it is sometimes invoked, a clear definition of regularity is still lacking. We define it as the ability of generating an active and stable research output over time, in terms of both publications/ quantity and citations/diffusion. The goal of this paper is introducing three analysis tools to perform qualitative/quantitative evaluations on the regularity of one scientist's output in a simple and organic way. These tools are respectively (1) the PY/CY diagram, (2) the publication/citation Ferrers diagram and (3) a simplified procedure for comparing the research output of several scientists according to their publication and citation temporal distributions (Borda's ranking). Description of these tools is supported by several examples

    Life v2.0 - Quo vadis Homo sapiens?

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    Comparison of hospital charge prediction models for gastric cancer patients: neural network vs. decision tree models

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    <p>Abstract</p> <p>Background</p> <p>In recent years, artificial neural network is advocated in modeling complex multivariable relationships due to its ability of fault tolerance; while decision tree of data mining technique was recommended because of its richness of classification arithmetic rules and appeal of visibility. The aim of our research was to compare the performance of ANN and decision tree models in predicting hospital charges on gastric cancer patients.</p> <p>Methods</p> <p>Data about hospital charges on 1008 gastric cancer patients and related demographic information were collected from the First Affiliated Hospital of Anhui Medical University from 2005 to 2007 and preprocessed firstly to select pertinent input variables. Then artificial neural network (ANN) and decision tree models, using same hospital charge output variable and same input variables, were applied to compare the predictive abilities in terms of mean absolute errors and linear correlation coefficients for the training and test datasets. The transfer function in ANN model was sigmoid with 1 hidden layer and three hidden nodes.</p> <p>Results</p> <p>After preprocess of the data, 12 variables were selected and used as input variables in two types of models. For both the training dataset and the test dataset, mean absolute errors of ANN model were lower than those of decision tree model (1819.197 vs. 2782.423, 1162.279 vs. 3424.608) and linear correlation coefficients of the former model were higher than those of the latter (0.955 vs. 0.866, 0.987 vs. 0.806). The predictive ability and adaptive capacity of ANN model were better than those of decision tree model.</p> <p>Conclusion</p> <p>ANN model performed better in predicting hospital charges of gastric cancer patients of China than did decision tree model.</p

    K201 improves aspects of the contractile performance of human failing myocardium via reduction in Ca2+ leak from the sarcoplasmic reticulum

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    In heart failure, intracellular Ca2+ leak from cardiac ryanodine receptors (RyR2s) leads to a loss of Ca2+ from the sarcoplasmic reticulum (SR) potentially contributing to decreased function. Experimental data suggest that the 1,4-benzothiazepine K201 (JTV-519) may stabilise RyR2s and thereby reduce detrimental intracellular Ca2+ leak. Whether K201 exerts beneficial effects in human failing myocardium is unknown. Therefore, we have studied the effects of K201 on muscle preparations from failing human hearts. K201 (0.3 μM; extracellular [Ca2+]e 1.25 mM) showed no effects on contractile function and micromolar concentrations resulted in negative inotropic effects (K201 1 μM; developed tension −9.8 ± 2.5% compared to control group; P < 0.05). Interestingly, K201 (0.3 μM) increased the post-rest potentiation (PRP) of failing myocardium after 120 s, indicating an increased SR Ca2+ load. At high [Ca2+]e concentrations (5 mmol/L), K201 increased PRP already at shorter rest intervals (30 s). Strikingly, treatment with K201 (0.3 μM) prevented diastolic dysfunction (diastolic tension at 5 mmol/L [Ca2+]e normalised to 1 mmol/L [Ca2+]e: control 1.26 ± 0.06, K201 1.01 ± 0.03, P < 0.01). In addition at high [Ca2+]e, K201 (0.3 μM) treatment significantly improved systolic function [developed tension +27 ± 8% (K201 vs. control); P < 0.05]. The beneficial effects on diastolic and systolic functions occurred throughout the physiological frequency range of the human heart rate from 1 to 3 Hz. Upon elevated intracellular Ca2+ concentration, systolic and diastolic contractile functions of terminally failing human myocardium are improved by K201

    Phase Shifting Capacity of the Circadian Pacemaker Determined by the SCN Neuronal Network Organization

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    In mammals, a major circadian pacemaker that drives daily rhythms is located in the suprachiasmatic nuclei (SCN), at the base of the hypothalamus. The SCN receive direct light input via the retino-hypothalamic tract. Light during the early night induces phase delays of circadian rhythms while during the late night it leads to phase advances. The effects of light on the circadian system are strongly dependent on the photoperiod to which animals are exposed. An explanation for this phenomenon is currently lacking.We recorded running wheel activity in C57 mice and observed large amplitude phase shifts in short photoperiods and small shifts in long photoperiods. We investigated whether these different light responses under short and long days are expressed within the SCN by electrophysiological recordings of electrical impulse frequency in SCN slices. Application of N-methyl-D-aspartate (NMDA) induced sustained increments in electrical activity that were not significantly different in the slices from long and short photoperiods. These responses led to large phase shifts in slices from short days and small phase shifts in slices from long days. An analysis of neuronal subpopulation activity revealed that in short days the amplitude of the rhythm was larger than in long days.The data indicate that the photoperiodic dependent phase responses are intrinsic to the SCN. In contrast to earlier predictions from limit cycle theory, we observed large phase shifting responses in high amplitude rhythms in slices from short days, and small shifts in low amplitude rhythms in slices from long days. We conclude that the photoperiodic dependent phase responses are determined by the SCN and propose that synchronization among SCN neurons enhances the phase shifting capacity of the circadian system

    Graz Endocrine Causes of Hypertension (GECOH) study: a diagnostic accuracy study of aldosterone to active renin ratio in screening for primary aldosteronism

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    <p>Abstract</p> <p>Background</p> <p>Primary aldosteronism (PA) affects approximately 5 to 10% of all patients with arterial hypertension and is associated with an excess rate of cardiovascular complications that can be significantly reduced by a targeted treatment. There exists a general consensus that the aldosterone to renin ratio should be used as a screening tool but valid data about the accuracy of the aldosterone to renin ratio in screening for PA are sparse. In the Graz endocrine causes of hypertension (GECOH) study we aim to prospectively evaluate diagnostic procedures for PA.</p> <p>Methods and design</p> <p>In this single center, diagnostic accuracy study we will enrol 400 patients that are routinely referred to our tertiary care center for screening for endocrine hypertension. We will determine the aldosterone to active renin ratio (AARR) as a screening test. In addition, all study participants will have a second determination of the AARR and will undergo a saline infusion test (SIT) as a confirmatory test. PA will be diagnosed in patients with at least one AARR of ≥ 5.7 ng/dL/ng/L (including an aldosterone concentration of ≥ 9 ng/dL) who have an aldosterone level of ≥ 10 ng/dL after the saline infusion test. As a primary outcome we will calculate the receiver operating characteristic curve of the AARR in diagnosing PA. Secondary outcomes include the test characteristics of the saline infusion test involving a comparison with 24 hours urine aldosterone levels and the accuracy of the aldosterone to renin activity ratio in diagnosing PA. In addition we will evaluate whether the use of beta-blockers significantly alters the accuracy of the AARR and we will validate our laboratory methods for aldosterone and renin.</p> <p>Conclusion</p> <p>Screening for PA with subsequent targeted treatment is of great potential benefit for hypertensive patients. In the GECOH study we will evaluate a standardised procedure for screening and diagnosing of this disease.</p

    Abnormal Placental Development and Early Embryonic Lethality in EpCAM-Null Mice

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    BACKGROUND: EpCAM (CD326) is encoded by the tacstd1 gene and expressed by a variety of normal and malignant epithelial cells and some leukocytes. Results of previous in vitro experiments suggested that EpCAM is an intercellular adhesion molecule. EpCAM has been extensively studied as a potential tumor marker and immunotherapy target, and more recent studies suggest that EpCAM expression may be characteristic of cancer stem cells. METHODOLOGY/PRINCIPAL FINDINGS: To gain insights into EpCAM function in vivo, we generated EpCAM -/- mice utilizing an embryonic stem cell line with a tacstd1 allele that had been disrupted. Gene trapping resulted in a protein comprised of the N-terminus of EpCAM encoded by 2 exons of the tacstd1 gene fused in frame to betageo. EpCAM +/- mice were viable and fertile and exhibited no obvious abnormalities. Examination of EpCAM +/- embryos revealed that betageo was expressed in several epithelial structures including developing ears (otocysts), eyes, branchial arches, gut, apical ectodermal ridges, lungs, pancreas, hair follicles and others. All EpCAM -/- mice died in utero by E12.5, and were small, developmentally delayed, and displayed prominent placental abnormalities. In developing placentas, EpCAM was expressed throughout the labyrinthine layer and by spongiotrophoblasts as well. Placentas of EpCAM -/- embryos were compact, with thin labyrinthine layers lacking prominent vascularity. Parietal trophoblast giant cells were also dramatically reduced in EpCAM -/- placentas. CONCLUSION: EpCAM was required for differentiation or survival of parietal trophoblast giant cells, normal development of the placental labyrinth and establishment of a competent maternal-fetal circulation. The findings in EpCAM-reporter mice suggest involvement of this molecule in development of vital organs including the gut, kidneys, pancreas, lungs, eyes, and limbs

    TrakEM2 Software for Neural Circuit Reconstruction

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    A key challenge in neuroscience is the expeditious reconstruction of neuronal circuits. For model systems such as Drosophila and C. elegans, the limiting step is no longer the acquisition of imagery but the extraction of the circuit from images. For this purpose, we designed a software application, TrakEM2, that addresses the systematic reconstruction of neuronal circuits from large electron microscopical and optical image volumes. We address the challenges of image volume composition from individual, deformed images; of the reconstruction of neuronal arbors and annotation of synapses with fast manual and semi-automatic methods; and the management of large collections of both images and annotations. The output is a neural circuit of 3d arbors and synapses, encoded in NeuroML and other formats, ready for analysis
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