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

Artificial Neural Network Symbol Estimator With Enhanced Robustness to Nonlinear Phase Noise

This letter reports a novel approach for nonlinear phase noise mitigation, based on artificial neural networks (ANNs) tailored to classification applications and a pre-processing stage of feature engineering. Starting with a set of proof-of-concept simulations, we verify that the proposed system can achieve optimal performance for the additive white Gaussian noise (AWGN) channel. Then, considering a dispersion-less channel with strong nonlinear phase noise (NLPN) distortion, we demonstrate a Q-factor increase of 0.4dB, comparing with standard carrier-phase estimation (CPE) followed by minimum distance detection. Finally, simulating the propagation of 64Gbaud PM-16QAM over standard single mode fiber (SSMF), we verify that the ANN-based solution is effective on wavelength-division multiplexing (WDM) transmission conditions, enabling to increase the maximum signal reach by approximately 1 fiber span over the legacy CPE-enabled NLPN compensation

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

Management of ibrutinib treatment in patients with B-cell malignancies: clinical practice in Portugal and multidisciplinary recommendations

Objectives: Ibrutinib, a potent inhibitor of the Bruton tyrosine kinase, has revolutionized the treatment of many B-cell malignancies. Ibrutinib has an established favorable toxicity profile with up to 8 years of experience in clinical trials; however, despite ibrutinib’s favorable toxicity profile, dose reductions and treatment discontinuations are becoming more evident in clinical practice, particularly in the setting of specific clinical contexts and patient characteristics. This manuscript is set to provide practical recommendations on the management of patients treated with this agent in daily practice. Methods: A group of multidisciplinary experts from Portugal met to discuss and highlight practical recommendations, supported on both literature and clinical insights, for the management of the treatment with ibrutinib. Results/discussion: Handling of both toxicities and drug–drug interactions during ibrutinib treatment poses several challenges to healthcare providers and can benefit from a multidisciplinary approach. The involvement of specialties, such as cardiology, infectiology and pharmacology, can bring an added value to patient care, not only in anticipating/managing safety issues and dose adjustments but also in enhancing adherence to treatment, ultimately improving the risk/benefit balance. Conclusion: By involving a multidisciplinary group of experts, this work provides a set of key recommendations to optimize care and outcomes for ibrutinib-treated patients. Despite not being a fully comprehensive review on the topic, it is intended as a framework to hematologists and other healthcare professionals who manage these patients in their daily clinical practice.The project received financial support from Janssen for logistics of expert meetings and editorial support. The sponsor had no influence on the opinions expressed here, which are those of the authors

Agregação familiar da cefaleia em salvas

Several studies suggest a strong familial aggregation for cluster headache (CH), but so far none of them have included subjects with probable cluster headache (PCH) in accordance with the International Classification of Headache Disorders. OBJECTIVE: To identify cases of probable cluster headache and to assess the familial aggregation of cluster headache by including these subjects. METHOD: Thirty-six patients attending a headache consultation and diagnosed with trigeminal autonomic headaches were subjected to a questionnaire-based interview. A telephone interview was also applied to all the relatives who were pointed out as possibly affected as well as to some of the remaining relatives. RESULTS: Twenty-four probands fulfilled the criteria for CH or PCH; they had 142 first-degree relatives, of whom five were found to have CH or PCH, including one case of CH sine headache. The risk for first-degree relatives was observed to be increased by 35- to 46-fold. CONCLUSION: Our results suggest a familial aggregation of cluster headache in the Portuguese population