A Scanning Transmission X-ray Microscopy Study of Cubic and Orthorhombic C₃A and Their Hydration Products in the Presence of Gypsum.

This paper shows the microstructural differences and phase characterization of pure phases and hydrated products of the cubic and orthorhombic (Na-doped) polymorphs of tricalcium aluminate (C₃A), which are commonly found in traditional Portland cements. Pure, anhydrous samples were characterized using scanning transmission X-ray microscopy (STXM), X-ray photoelectron spectroscopy (XPS) and X-ray diffraction (XRD) and demonstrated differences in the chemical and mineralogical composition as well as the morphology on a micro/nano-scale. C₃A/gypsum blends with mass ratios of 0.2 and 1.9 were hydrated using a water/C₃A ratio of 1.2, and the products obtained after three days were assessed using STXM. The hydration process and subsequent formation of calcium sulfate in the C₃A/gypsum systems were identified through the changes in the LIII edge fine structure for Calcium. The results also show greater Ca LII binding energies between hydrated samples with different gypsum contents. Conversely, the hydrated samples from the cubic and orthorhombic C₃A at the same amount of gypsum exhibited strong morphological differences but similar chemical environments

Artificially sweetened beverages and the response to the global obesity crisis

In March 2015, the World Health Organization (WHO) published revised guidelines on sugar intake that call on national governments to institute policies to reduce sugar intake and increase the scope for regulation of sugar-sweetened beverages (SSBs). • In face of the growing threat of regulatory action on SSBs, transnational beverage companies are responding in multiple ways, including investing in the formulation and sales of artificially sweetened beverages (ASBs), promoted as healthier alternatives to SSBs. • The absence of consistent evidence to support the role of ASBs in preventing weight gain and the lack of studies on other long-term effects on health strengthen the position that ASBs should not be promoted as part of a healthy diet. • The promotion of ASBs must be discussed in a broader context of the additional potential impacts on health and the environment. In addition, a more robust evidence base, free of conflicts of interest, is needed

Predictive Modelling using Neuroimaging Data in the Presence of Confounds

When training predictive models from neuroimaging data, we typically have available non-imaging variables such as age and gender that affect the imaging data but which we may be uninterested in from a clinical perspective. Such variables are commonly referred to as 'confounds'. In this work, we firstly give a working definition for confound in the context of training predictive models from samples of neuroimaging data. We define a confound as a variable which affects the imaging data and has an association with the target variable in the sample that differs from that in the population-of-interest, i.e., the population over which we intend to apply the estimated predictive model. The focus of this paper is the scenario in which the confound and target variable are independent in the population-of-interest, but the training sample is biased due to a sample association between the target and confound. We then discuss standard approaches for dealing with confounds in predictive modelling such as image adjustment and including the confound as a predictor, before deriving and motivating an Instance Weighting scheme that attempts to account for confounds by focusing model training so that it is optimal for the population-of-interest. We evaluate the standard approaches and Instance Weighting in two regression problems with neuroimaging data in which we train models in the presence of confounding, and predict samples that are representative of the population-of-interest. For comparison, these models are also evaluated when there is no confounding present. In the first experiment we predict the MMSE score using structural MRI from the ADNI database with gender as the confound, while in the second we predict age using structural MRI from the IXI database with acquisition site as the confound. Considered over both datasets we find that none of the methods for dealing with confounding gives more accurate predictions than a baseline model which ignores confounding, although including the confound as a predictor gives models that are less accurate than the baseline model. We do find, however, that different methods appear to focus their predictions on specific subsets of the population-of-interest, and that predictive accuracy is greater when there is no confounding present. We conclude with a discussion comparing the advantages and disadvantages of each approach, and the implications of our evaluation for building predictive models that can be used in clinical practice

A multimodal multiple kernel learning approach to Alzheimer's disease detection

In neuroimaging-based diagnostic problems, the combination of different sources of information as MR images and clinical data is a challenging task. Their simple combination usually does not provides an improvement if compared with using the best source alone. In this paper, we deal with the well known Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset tackling the AD versus Control task. We use a recently proposed multiple kernel learning approach, called EasyMKL, to combine a huge amount of basic kernels in synergy with a feature selection methodology, pursuing an optimal and sparse solution to facilitate interpretability. Our new approach, called EasyMKLFS, outperforms baselines (e.g. SVM) and state-of-the-art methods as recursive feature elimination and SimpleMKL

Astrocyte Activation via Stat3 Signaling Determines the Balance of Oligodendrocyte versus Schwann Cell Remyelination.

Remyelination within the central nervous system (CNS) most often is the result of oligodendrocyte progenitor cells differentiating into myelin-forming oligodendrocytes. In some cases, however, Schwann cells, the peripheral nervous system myelinating glia, are found remyelinating demyelinated regions of the CNS. The reason for this peripheral type of remyelination in the CNS and what governs it is unknown. Here, we used a conditional astrocytic phosphorylated signal transducer and activator of transcription 3 knockout mouse model to investigate the effect of abrogating astrocyte activation on remyelination after lysolecithin-induced demyelination of spinal cord white matter. We show that oligodendrocyte-mediated remyelination decreases and Schwann cell remyelination increases in lesioned knockout mice in comparison with lesioned controls. Our study shows that astrocyte activation plays a crucial role in the balance between Schwann cell and oligodendrocyte remyelination in the CNS, and provides further insight into remyelination of CNS axons by Schwann cells.The work was funded by grants from the UK Multiple Sclerosis Society. GMdC received financial support from CNPq 200993/2010-0; Ciência Sem Fronteiras CNPq 201797/2011-9.This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.ajpath.2015.05.01

Pathotypic diversity of Hyaloperonospora brassicae collected from Brassica oleracea

Downy mildew caused by Hyaloperonospora brassicae is an economically destructive disease of brassica crops in many growing regions throughout the world. Specialised pathogenicity of downy mildews from different Brassica species and closely related ornamental or wild relatives has been described from host range studies. Pathotypic variation amongst Hyaloperonospora brassicae isolates from Brassica oleracea has also been described; however, a standard set of B. oleracea lines that could enable reproducible classification of H. brassicae pathotypes was poorly developed. For this purpose, we examined the use of eight genetically refined host lines derived from our previous collaborative work on downy mildew resistance as a differential set to characterise pathotypes in the European population of H. brassicae. Interaction phenotypes for each combination of isolate and host line were assessed following drop inoculation of cotyledons and a spectrum of seven phenotypes was observed based on the level of sporulation on cotyledons and visible host responses. Two host lines were resistant or moderately resistant to the entire collection of isolates, and another was universally susceptible. Five lines showed differential responses to the H. brassicae isolates. A minimum of six pathotypes and five major effect resistance genes are proposed to explain all of the observed interaction phenotypes. The B. oleracea lines from this study can be useful for monitoring pathotype frequencies in H. brassicae populations in the same or other vegetable growing regions, and to assess the potential durability of disease control from different combinations of the predicted downy mildew resistance genes

The diseases we cause: Iatrogenic illness in a department of internal medicine

BACKGROUND: The aim of this study was to estimate the incidence, main causes, and risk factors of iatrogenic disease occurring in a department of internal medicine. METHODS: Over a 1-year period, physicians systematically filled out a 2-page questionnaire for all patients admitted to the ward. A database was created and the data were statistically analyzed. Patients undergoing immunosuppressive, chemo-, or radiation therapy were excluded. Missing data were completed by reviewing the patients' charts. The patients were then divided into two groups: those with and those without iatrogenic disease. The groups were compared using several parameters including gender, age, social features, days of hospitalization, associated illness, functional status, medical impression, prognosis, associated renal or liver function impairment, drugs taken daily, and outcome. In the group with iatrogenic disease, the type, severity, and predictability were also analyzed. RESULTS: Of the 879 patients admitted to the ward, 445 completed questionnaires and were included in the study. A total of 102 patients (22.9%) developed 121 iatrogenic events. Forty-four patients (43.1%) were admitted for iatrogenic illness, 10 (9.8%) developed life-threatening events, and in 3 (6.8%) it was the cause of death. Fifty-eight patients (56.8%) registered 77 episodes of iatrogenic disease during their hospital stay, 20 (19.6%) developed life-threatening events, and 9 (11.7%) died, 4 (5.2%) of an iatrogenic cause (nosocomial infections). Significant differences were found in 20 out of 26 parameters studied (p<0.005 for all cases; 95% confidence interval). Eighteen percent of all iatrogenic disease was severe, 61.9% predictable, 54.5% avoidable, and 59% drug-related, 80% of which was due to side effects or adverse reactions. Infection and metabolic and electrolyte disorders were the most frequent effects. CONCLUSIONS: It is possible to identify risk factors for iatrogenic events. Chronically ill elderly inpatients are the main target of iatrogenic events