466 research outputs found

    Simultaneous feature selection and parameter optimisation using an artificial ant colony: case study of melting point prediction.

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    BACKGROUND: We present a novel feature selection algorithm, Winnowing Artificial Ant Colony (WAAC), that performs simultaneous feature selection and model parameter optimisation for the development of predictive quantitative structure-property relationship (QSPR) models. The WAAC algorithm is an extension of the modified ant colony algorithm of Shen et al. (J Chem Inf Model 2005, 45: 1024-1029). We test the ability of the algorithm to develop a predictive partial least squares model for the Karthikeyan dataset (J Chem Inf Model 2005, 45: 581-590) of melting point values. We also test its ability to perform feature selection on a support vector machine model for the same dataset. RESULTS: Starting from an initial set of 203 descriptors, the WAAC algorithm selected a PLS model with 68 descriptors which has an RMSE on an external test set of 46.6 degrees C and R2 of 0.51. The number of components chosen for the model was 49, which was close to optimal for this feature selection. The selected SVM model has 28 descriptors (cost of 5, epsilon of 0.21) and an RMSE of 45.1 degrees C and R2 of 0.54. This model outperforms a kNN model (RMSE of 48.3 degrees C, R2 of 0.47) for the same data and has similar performance to a Random Forest model (RMSE of 44.5 degrees C, R2 of 0.55). However it is much less prone to bias at the extremes of the range of melting points as shown by the slope of the line through the residuals: -0.43 for WAAC/SVM, -0.53 for Random Forest. CONCLUSION: With a careful choice of objective function, the WAAC algorithm can be used to optimise machine learning and regression models that suffer from overfitting. Where model parameters also need to be tuned, as is the case with support vector machine and partial least squares models, it can optimise these simultaneously. The moving probabilities used by the algorithm are easily interpreted in terms of the best and current models of the ants, and the winnowing procedure promotes the removal of irrelevant descriptors

    Harmful phytoplankton events caused by variability in the Irish Coastal Current along the west of Ireland

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    Frequent sampling in summer along the western and northwestern coasts of Ireland showed the rapid onshore development of blooms of potentially harmful phytoplankton species. In both 1998 and 1999, concentrations of Gyrodinium cf. aureolum rose by four orders of magnitude to over one million cells per litre in Donegal Bay(northwestern Ireland) in less than 10days. The rapid development of these populations was linked to advection resulting from unfavourable wind-forcing of the Irish Coastal Current (ICG) which runs northwards along the western Irish coast. Current measurements showed that after a particular sequence of changes in wind direction phytoplankton populations could be rapidly advected from areas of slack circulation on the shelf via the ICC into aquaculturally sensitive coastal zones such as Donegal Bay. The model presented is similar to one already demonstrated for the occurrence of toxic events in the bays of southwestern Ireland. Other historical harmful events along the west and northwest coasts relating to substantial losses in both finfish and shellfish culture could also be explained using the model. These include the G. aureolum bloom of 1992, the Prorocentrum balticum bloom in 1997

    Pilot Water Quality Monitoring Station in Dublin Bay North Bank Monitoring Station (NBMS): MATSIS Project Part I

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    The lack of short-term temporal resolution associated with traditional spot sampling for monitoring water quality of dynamic coastal and estuarine waters has meant that many organisations are interesting in autonomous monitoring technologies to provide near real-time semi-continuous data. Such approaches enable capturing short term episodic events (which may be missed or alternatively skew datasets when using spot samples) and provide early warning of water quality problems. New policy drivers such as the Water Framework Directive (WFD) provide added impetus to develop this field. Therefore, as part of the interreg IIIa funded MATSIS project the Marine Institute undertook to develop and pilot an autonomous monitoring station in Dublin Bay (North Bank Monitoring Station NBMS). This report presents the outcome for this pilot study.Funder: Marine Institut

    CCL2 nitration is a negative regulator of chemokine-mediated inflammation.

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    Chemokines promote leukocyte recruitment during inflammation. The oxidative burst is an important effector mechanism, this leads to the generation of reactive nitrogen species (RNS), including peroxynitrite (ONOO). The current study was performed to determine the potential for nitration to alter the chemical and biological properties of the prototypical CC chemokine, CCL2. Immunofluorescence was performed to assess the presence of RNS in kidney biopsies. Co-localisation was observed between RNS-modified tyrosine residues and the chemokine CCL2 in diseased kidneys. Nitration reduced the potential of CCL2 to stimulate monocyte migration in diffusion gradient chemotaxis assays (p < 0.05). This was consistent with a trend towards reduced affinity of the nitrated chemokine for its cognate receptor CCR2b. The nitrated chemokine was unable to induce transendothelial monocyte migration in vitro and failed to promote leukocyte recruitment when added to murine air pouches (p < 0.05). This could potentially be attributed to reduced glycosaminoglycan binding ability, as surface plasmon resonance spectroscopy showed that nitration reduced heparan sulphate binding by CCL2. Importantly, intravenous administration of nitrated CCL2 also inhibited the normal recruitment of leukocytes to murine air pouches filled with unmodified CCL2. Together these data suggest that nitration of CCL2 during inflammation provides a mechanism to limit and resolve acute inflammation

    Investigating the influence of the sulfur oxidation state on solid state conformation

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    Design, synthesis and structural characterization of a series of diphenylacetylene derivatives bearing organosulfur, amide and amine moieties has been achieved in which the molecular conformation is controlled through variation of the hydrogen bond properties on alteration of the oxidisation level of sulfur

    How Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) progresses. The natural history of ME/CFS

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    We propose a framework for understanding and interpreting the pathophysiology of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) that considers wider determinants of health and long-term temporal variation in pathophysiological features and disease phenotype throughout the natural history of the disease. As in other chronic diseases, ME/CFS evolves through different stages, from asymptomatic predisposition, progressing to a prodromal stage, and then to symptomatic disease. Disease incidence depends on genetic makeup and environment factors, the exposure to singular or repeated insults, and the nature of the host response. In people who develop ME/CFS, normal homeostatic processes in response to adverse insults may be replaced by aberrant responses leading to dysfunctional states. Thus, the predominantly neuro-immune manifestations, underlined by a hyper-metabolic state, that characterize early disease, may be followed by various processes leading to multi-systemic abnormalities and related symptoms. This abnormal state and the effects of a range of mediators such as products of oxidative and nitrosamine stress, may lead to progressive cell and metabolic dysfunction culminating in a hypometabolic state with low energy production. These processes do not seem to happen uniformly; although a spiraling of progressive inter-related and self-sustaining abnormalities may ensue, reversion to states of milder abnormalities is possible if the host is able to restate responses to improve homeostatic equilibrium. With time variation in disease presentation, no single ME/CFS case description, set of diagnostic criteria, or molecular feature is currently representative of all patients at different disease stages. While acknowledging its limitations due to the incomplete research evidence, we suggest the proposed framework may support future research design and health care interventions for people with ME/CFS

    Confab - Systematic generation of diverse low-energy conformers

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    <p>Abstract</p> <p>Background</p> <p>Many computational chemistry analyses require the generation of conformers, either on-the-fly, or in advance. We present Confab, an open source command-line application for the systematic generation of low-energy conformers according to a diversity criterion.</p> <p>Results</p> <p>Confab generates conformations using the 'torsion driving approach' which involves iterating systematically through a set of allowed torsion angles for each rotatable bond. Energy is assessed using the MMFF94 forcefield. Diversity is measured using the heavy-atom root-mean-square deviation (RMSD) relative to conformers already stored. We investigated the recovery of crystal structures for a dataset of 1000 ligands from the Protein Data Bank with fewer than 1 million conformations. Confab can recover 97% of the molecules to within 1.5 Å at a diversity level of 1.5 Å and an energy cutoff of 50 kcal/mol.</p> <p>Conclusions</p> <p>Confab is available from <url>http://confab.googlecode.com</url>.</p

    Stroke Induces Prolonged Changes in Lipid Metabolism, the Liver and Body Composition in Mice

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    Acknowledgements We would like to thank the Biological Services Facility at the University of Manchester for expert animal husbandry and Karen Davies who helped with the MRI. The Histology Facility equipment that was used in this study was purchased by the University of Manchester Strategic Fund. Special thanks goes to Peter Walker for their help with the histology. Funding information This work was supported by the Kohn Foundation, an Edward Bonham Carter Doctoral Scholarship, an EPSRC/MRC Centre for Doctoral Training in Regenerative Medicine studentship grant (EP/L014904/1), and the Medical Research Council (MR/K501311/1).Peer reviewedPublisher PD
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