3,984 research outputs found

    Multiple Imputation Ensembles (MIE) for dealing with missing data

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    Missing data is a significant issue in many real-world datasets, yet there are no robust methods for dealing with it appropriately. In this paper, we propose a robust approach to dealing with missing data in classification problems: Multiple Imputation Ensembles (MIE). Our method integrates two approaches: multiple imputation and ensemble methods and compares two types of ensembles: bagging and stacking. We also propose a robust experimental set-up using 20 benchmark datasets from the UCI machine learning repository. For each dataset, we introduce increasing amounts of data Missing Completely at Random. Firstly, we use a number of single/multiple imputation methods to recover the missing values and then ensemble a number of different classifiers built on the imputed data. We assess the quality of the imputation by using dissimilarity measures. We also evaluate the MIE performance by comparing classification accuracy on the complete and imputed data. Furthermore, we use the accuracy of simple imputation as a benchmark for comparison. We find that our proposed approach combining multiple imputation with ensemble techniques outperform others, particularly as missing data increases

    Iron Status and Analysis of Efficacy and Safety of Ferric Carboxymaltose Treatment in Patients with Inflammatory Bowel Disease

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    Background and Aims:We analyzed iron deficiency and the therapeutic response following intravenous ferric carboxymaltose in a large single-center inflammatory bowel disease (IBD) cohort. Methods: 250 IBD patients were retrospectively analyzed for iron deficiency and iron deficiency anemia. A subgroup was analyzed regarding efficacy and side effects of iron supplementation with ferric carboxymaltose. Results: In the cohort (n = 250), 54.4% of the patients had serum iron levels 60 mu g/dl, 61.6% had ferritin >100 ng/ml, and 90.7% reached Hb >12/13 g/dl at follow-up (p < 0.0001 for all parameters vs. pretreatment values). The most frequent adverse event was a transient increase of liver enzymes with male gender as risk factor (p = 0.008, OR 8.62, 95% CI 1.74-41.66). Conclusions: Iron deficiency and anemia are frequent in IBD patients. Treatment with ferric carboxymaltose is efficious, safe and well tolerated in iron-deficient IBD patients. Copyright (C) 2011 S. Karger AG, Base

    Soluble human Suppression of Tumorigenicity 2 is associated with endoscopic activity in patients with moderate-to-severe ulcerative colitis treated with golimumab

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    Suppressor of Tumorigenicity 2 (ST2) is an IL33 receptor detected in the mucosa and serum of ulcerative colitis (UC) patients. We evaluated soluble ST2 (sST2) as a surrogate biomarker of disease outcome and therapeutic response, in moderate-to-severe UC patients treated with golimumab.Agência financiadora Merck Sharp and Dohme, Lda, Portugal MK8259-22info:eu-repo/semantics/publishedVersio

    The dusty SF history of high-z galaxies, modelling tools and future prospects

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    We summarize recent advances in the determination of the cosmic history of star formation and other properties of high-z galaxies, and the relevance of this information in our understanding of the formation of structures. We emphasize the importance of dust reprocessing in the high--z universe, as demonstrated in particular by IR and sub-mm data. This demand a panchromatic approach to observations and suitable modelling tools. We spend also some words on expectations from future instruments

    Altered Neurocircuitry in the Dopamine Transporter Knockout Mouse Brain

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    The plasma membrane transporters for the monoamine neurotransmitters dopamine, serotonin, and norepinephrine modulate the dynamics of these monoamine neurotransmitters. Thus, activity of these transporters has significant consequences for monoamine activity throughout the brain and for a number of neurological and psychiatric disorders. Gene knockout (KO) mice that reduce or eliminate expression of each of these monoamine transporters have provided a wealth of new information about the function of these proteins at molecular, physiological and behavioral levels. In the present work we use the unique properties of magnetic resonance imaging (MRI) to probe the effects of altered dopaminergic dynamics on meso-scale neuronal circuitry and overall brain morphology, since changes at these levels of organization might help to account for some of the extensive pharmacological and behavioral differences observed in dopamine transporter (DAT) KO mice. Despite the smaller size of these animals, voxel-wise statistical comparison of high resolution structural MR images indicated little morphological change as a consequence of DAT KO. Likewise, proton magnetic resonance spectra recorded in the striatum indicated no significant changes in detectable metabolite concentrations between DAT KO and wild-type (WT) mice. In contrast, alterations in the circuitry from the prefrontal cortex to the mesocortical limbic system, an important brain component intimately tied to function of mesolimbic/mesocortical dopamine reward pathways, were revealed by manganese-enhanced MRI (MEMRI). Analysis of co-registered MEMRI images taken over the 26 hours after introduction of Mn^(2+) into the prefrontal cortex indicated that DAT KO mice have a truncated Mn^(2+) distribution within this circuitry with little accumulation beyond the thalamus or contralateral to the injection site. By contrast, WT littermates exhibit Mn^(2+) transport into more posterior midbrain nuclei and contralateral mesolimbic structures at 26 hr post-injection. Thus, DAT KO mice appear, at this level of anatomic resolution, to have preserved cortico-striatal-thalamic connectivity but diminished robustness of reward-modulating circuitry distal to the thalamus. This is in contradistinction to the state of this circuitry in serotonin transporter KO mice where we observed more robust connectivity in more posterior brain regions using methods identical to those employed here

    Tissue Localization and Extracellular Matrix Degradation by PI, PII and PIII Snake Venom Metalloproteinases: Clues on the Mechanisms of Venom-Induced Hemorrhage

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    20 páginas, 4 figuras, 3 tablas y 7 tablas en material suplementario.Snake venom hemorrhagic metalloproteinases (SVMPs) of the PI, PII and PIII classes were compared in terms of tissue localization and their ability to hydrolyze basement membrane components in vivo, as well as by a proteomics analysis of exudates collected in tissue injected with these enzymes. Immunohistochemical analyses of co-localization of these SVMPs with type IV collagen revealed that PII and PIII enzymes co-localized with type IV collagen in capillaries, arterioles and post-capillary venules to a higher extent than PI SVMP, which showed a more widespread distribution in the tissue. The patterns of hydrolysis by these three SVMPs of laminin, type VI collagen and nidogen in vivo greatly differ, whereas the three enzymes showed a similar pattern of degradation of type IV collagen, supporting the concept that hydrolysis of this component is critical for the destabilization of microvessel structure leading to hemorrhage. Proteomic analysis of wound exudate revealed similarities and differences between the action of the three SVMPs. Higher extent of proteolysis was observed for the PI enzyme regarding several extracellular matrix components and fibrinogen, whereas exudates from mice injected with PII and PIII SVMPs had higher amounts of some intracellular proteins. Our results provide novel clues for understanding the mechanisms by which SVMPs induce damage to the microvasculature and generate hemorrhage.This work was performed in partial fulfillment of the requirements for the PhD degree for Cristina Herrera at Universidad de Costa Rica.Peer reviewe

    The novel Fh8 and H fusion partners for soluble protein expression in Escherichia coli : a comparison with the traditional gene fusion technology

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    The Escherichia coli host system is an advantageous choice for simple and inexpensive recombinant protein production but it still presents bottlenecks at expressing soluble proteins from other organisms. Several efforts have been taken to overcome E. coli limitations, including the use of fusion partners that improve protein expression and solubility. New fusion technologies are emerging to complement the traditional solutions. This work evaluates two novel fusion partners, the Fh8 tag (8 kDa) and the H tag (1 kDa), as solubility enhancing tags in E. coli and their comparison to commonly used fusion partners. A broad range comparison was conducted in a small-scale screening and subsequently scaled-up. Six difficult-to-express target proteins (RVS167, SPO14, YPK1, YPK2, Frutalin and CP12) were fused to eight fusion tags (His, Trx, GST, MBP, NusA, SUMO, H and Fh8). The resulting protein expression and solubility levels were evaluated by sodium dodecyl sulfate polyacrylamide gel electrophoresis before and after protein purification and after tag removal. The Fh8 partner improved protein expression and solubility as the well-known Trx, NusA or MBP fusion partners. The H partner did not function as a solubility tag. Cleaved proteins from Fh8 fusions were soluble and obtained in similar or higher amounts than proteins from the cleavage of other partners as Trx, NusA or MBP. The Fh8 fusion tag therefore acts as an effective solubility enhancer, and its low molecular weight potentially gives it an advantage over larger solubility tags by offering a more reliable assessment of the target protein solubility when expressed as a fusion protein.The financial support of the EMBL Heidelberg, Germany and Fundacao para a Ciencia e Tecnologia (FCT), Portugal, is acknowledged: the fellowship SFRH/BD/46482/2008 to Sofia J. Costa and the project PTDC/CVT/103081/2008. The authors wish to acknowledge Anne-Claude Gavin for providing four of the constructs for this study (RVS167, SPO14, YPK1, and YPK2) and Emmanuel Poilpre for the experimental help (both from the EMBL Heidelberg, Germany)

    TRY plant trait database - enhanced coverage and open access

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    Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives
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