3,422 research outputs found

    Does psychosocial stress impact cognitive reappraisal? Behavioral and neural evidence

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    Cognitive reappraisal (CR) is regarded as an effective emotion regulation strategy. Acute stress, however, is believed to impair the functioning of prefrontal-based neural systems, which could result in lessened effectiveness of CR under stress. This study tested the behavioral and neurobiological impact of acute stress on CR. While undergoing fMRI, adult participants (n = 54) passively viewed or used CR to regulate their response to negative and neutral pictures and provided ratings of their negative affect in response to each picture. Half of the participants experienced an fMRI-adapted acute psychosocial stress manipulation similar to the Trier Social Stress Test, and a contr ol group received parallel manipulations without the stressful components. Relative to the control group, the stress group exhibited heightened stress as indexed by self-report, heart rate, and salivary cortisol throughout the scan. Contrary to our hypothesis, we found that reappraisal success was equivalent in the control and stress groups, as was electrodermal response to the pictures. Heart rate deceleration, a physiological response typically evoked by aversive pictures, was blunted in response to negative pictures and heightened in response to neutral pictures in the stress group. In the brain, we found weak evidence of stress-induced increases of reappraisalrelated activity in parts of the PFC and left amygdala, but these relationships were statistically fragile. Together, these findings suggest that both the self-reported and neural effects of CR may be robust to at least moderate levels of stress, informing theoretical models of stress effects on cognition and emotion

    Islet autoimmunity identifies a unique pattern of impaired pancreatic beta-cell function, markedly reduced pancreatic beta cell mass and insulin resistance in clinically diagnosed type 2 diabetes

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    There is a paucity of literature describing metabolic and histological data in adult-onset autoimmune diabetes. This subgroup of diabetes mellitus affects at least 5% of clinically diagnosed type 2 diabetic patients (T2DM) and it is termed Latent Autoimmune Diabetes in Adults (LADA). We evaluated indexes of insulin secretion, metabolic assessment, and pancreatic pathology in clinically diagnosed T2DM patients with and without the presence of humoral islet autoimmunity (Ab). A total of 18 patients with at least 5-year duration of clinically diagnosed T2DM were evaluated in this study. In those subjects we assessed acute insulin responses to arginine, a glucose clamp study, whole-body fat mass and fat-free mass. We have also analyzed the pancreatic pathology of 15 T2DM and 43 control cadaveric donors, using pancreatic tissue obtained from all the T2DM organ donors available from the nPOD network through December 31, 2013. The presence of islet Ab correlated with severely impaired β-cell function as demonstrated by remarkably low acute insulin response to arginine (AIR) when compared to that of the Ab negative group. Glucose clamp studies indicated that both Ab positive and Ab negative patients exhibited peripheral insulin resistance in a similar fashion. Pathology data from T2DM donors with Ab or the autoimmune diabetes associated DR3/DR4 allelic class II combination showed reduction in beta cell mass as well as presence of autoimmune-associated pattern A pathology in subjects with either islet autoantibodies or the DR3/DR4 genotype. In conclusion, we provide compelling evidence indicating that islet Ab positive long-term T2DM patients exhibit profound impairment of insulin secretion as well as reduced beta cell mass seemingly determined by an immune-mediated injury of pancreatic β-cells. Deciphering the mechanisms underlying beta cell destruction in this subset of diabetic patients may lead to the development of novel immunologic therapies aimed at halting the disease progression in its early stage

    Computer-aided diagnosis for (123I)FP-CIT imaging: impact on clinical reporting

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    BACKGROUND: For (123I)FP-CIT imaging, a number of algorithms have shown high performance in distinguishing normal patient images from those with disease, but none have yet been tested as part of reporting workflows. This study aims to evaluate the impact on reporters' performance of a computer-aided diagnosis (CADx) tool developed from established machine learning technology. Three experienced (123I)FP-CIT reporters (two radiologists and one clinical scientist) were asked to visually score 155 reconstructed clinical and research images on a 5-point diagnostic confidence scale (read 1). Once completed, the process was then repeated (read 2). Immediately after submitting each image score for a second time, the CADx system output was displayed to reporters alongside the image data. With this information available, the reporters submitted a score for the third time (read 3). Comparisons between reads 1 and 2 provided evidence of intra-operator reliability, and differences between reads 2 and 3 showed the impact of the CADx. RESULTS: The performance of all reporters demonstrated a degree of variability when analysing images through visual analysis alone. However, inclusion of CADx improved consistency between reporters, for both clinical and research data. The introduction of CADx increased the accuracy of the radiologists when reporting (unfamiliar) research images but had less impact on the clinical scientist and caused no significant change in accuracy for the clinical data. CONCLUSIONS: The outcomes for this study indicate the value of CADx as a diagnostic aid in the clinic and encourage future development for more refined incorporation into clinical practice

    Developmental changes in the role of different metalinguistic awareness skills in Chinese reading acquisition from preschool to third grade

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    Copyright @ 2014 Wei et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.The present study investigated the relationship between Chinese reading skills and metalinguistic awareness skills such as phonological, morphological, and orthographic awareness for 101 Preschool, 94 Grade-1, 98 Grade-2, and 98 Grade-3 children from two primary schools in Mainland China. The aim of the study was to examine how each of these metalinguistic awareness skills would exert their influence on the success of reading in Chinese with age. The results showed that all three metalinguistic awareness skills significantly predicted reading success. It further revealed that orthographic awareness played a dominant role in the early stages of reading acquisition, and its influence decreased with age, while the opposite was true for the contribution of morphological awareness. The results were in stark contrast with studies in English, where phonological awareness is typically shown as the single most potent metalinguistic awareness factor in literacy acquisition. In order to account for the current data, a three-stage model of reading acquisition in Chinese is discussed.National Natural Science Foundation of China and Knowledge Innovation Program of the Chinese Academy of Sciences

    Prediction-Coherent LSTM-based Recurrent Neural Network for Safer Glucose Predictions in Diabetic People

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    In the context of time-series forecasting, we propose a LSTM-based recurrent neural network architecture and loss function that enhance the stability of the predictions. In particular, the loss function penalizes the model, not only on the prediction error (mean-squared error), but also on the predicted variation error. We apply this idea to the prediction of future glucose values in diabetes, which is a delicate task as unstable predictions can leave the patient in doubt and make him/her take the wrong action, threatening his/her life. The study is conducted on type 1 and type 2 diabetic people, with a focus on predictions made 30-minutes ahead of time. First, we confirm the superiority, in the context of glucose prediction, of the LSTM model by comparing it to other state-of-the-art models (Extreme Learning Machine, Gaussian Process regressor, Support Vector Regressor). Then, we show the importance of making stable predictions by smoothing the predictions made by the models, resulting in an overall improvement of the clinical acceptability of the models at the cost in a slight loss in prediction accuracy. Finally, we show that the proposed approach, outperforms all baseline results. More precisely, it trades a loss of 4.3\% in the prediction accuracy for an improvement of the clinical acceptability of 27.1\%. When compared to the moving average post-processing method, we show that the trade-off is more efficient with our approach

    A Cross-Sectional Study on Patient Satisfaction with Universiti Kebangsaan Malaysia Medical Centre (UKMMC) Primary Care Clinic

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    ABSTRAK .867 for type of occupation, and p=0.623 for family income). In conclusion, many patients perceived that clinic facilities were substandard but they still had a high level of general satisfaction. Nevertheless, strategies in improving the facilities are still required as it will contribute to the quality of care and patient satisfaction

    Quantum mechanical polar surface area

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    A correlation has been established between the absorbed fraction of training-set molecules after oral administration in humans and the Quantum Mechanical Polar Surface Area (QMPSA). This correlation holds for the QMPSA calculated with structures where carboxyl groups are deprotonated. The correlation of the absorbed fraction and the QMPSA calculated on the neutral gas phase optimized structures is much less pronounced. This suggests that the absorption process is mainly determined by polar interactions of the drug molecules in water solution. Rules are given to derive the optimal polar/apolar ranges of the electrostatic potential

    Some Thoughts About Appealing Directions for the Future of Fuzzy Theory and Technologies Along the Path Traced by Lotfi Zadeh

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    The quoted text is an interesting instance of a fuzzy object: it is currently known in slightly diversified forms, each rather different from the quoted one, which corresponds to the first known appearance in English of this adage
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