Dennishelbo2343

© 2020 The Population Council, Inc.PURPOSE Leukemia is a lethal disease that is harmful to bone marrow and overall blood health. selleckchem The classification of white blood cell images is crucial for leukemia diagnosis. The purpose of this study is to classify white blood cells by extracting discriminative information from cell segmentation and combining it with the fine-grained features. We propose a hybrid adversarial residual network with support vector machine (SVM), which utilizes the extracted features to improve the classification accuracy for human peripheral white cells. METHODS Firstly, we segment the cell and nucleus by utilizing an adversarial residual network, which contains a segmentation network and a discriminator network. To extract features that can handle the inter-class consistency problem effectively, we introduce the adversarial residual network. Then, we utilize convolutional neural network (CNN) features and histogram of oriented gradient (HOG) features, which can extract discriminative features from images of segmented cell nucllty and time pressure of doctors' work, and economizes the valuable time of doctors in daily clinical diagnosis. This article is protected by copyright. All rights reserved.Liquid biopsy, screening cancer non-invasively and frequently by detecting and quantifying molecular markers in physiological fluids, would significantly improve cancer survival rate but it remains a distant goal. The key obstacles presented by the highly heterogeneous samples are rapid/high-yield purification and precise/selective marker capture by their antibody and oligo probes. As irregular expressions of these molecular biomarkers are the key signals, quantifying only those from the cancer cells would greatly enhance the performance of the screening tests. The recent discovery that the biomarkers are carried by nanocarriers, such as exosomes, with cell-specific membrane proteins suggests that such selection may be possible, although a new suite of fractionation and quantification technologies would need to be developed. Although under-appreciated, membrane microfluidics has made considerable contributions to resolving these issues. We review the progress made so far, based on ion-selective, track-etched and gel membranes and advanced electrophoretic and nano-filtration designs, in this perspective and suggest future directions. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.AIM This project has two aims 1) What do relatives to brought in dead describe as helpful and supportive care when they arrive at the emergency department to see and say goodbye to a deceased? 2) What do nurses describe as good nursing practice for brought in dead persons and their relatives and what may hinder or facilitate this practice in an emergency setting?. DESIGN A qualitative study within the methodology Interpretive Description. METHODS Data will be collected through three data sources Individual interviews with relatives to brought in dead persons, participant observations of relatives to brought in dead persons during their presence in the emergency department and focus group interviews with emergency nurses. DISCUSSION Brought in dead persons and their relatives are received and cared for in emergency departments by emergency nurses. Knowledge of how to render care for the relatives to brought in dead persons in an acute setting including what skills and competences this require of the nurses is warranted. We need to explore, describe and comprehend the experiences of both the relatives and the nurses in order to point out potential areas of improvement. IMPACT This paper is a protocol of an Interpretive Description study offering insight into considerations and reflections in designing the study. This article is protected by copyright. All rights reserved.There is increased interest in the development of cognitive training targeting working memory (WM) to alleviate anxiety symptoms, but the effectiveness of such an approach is unclear. Improved understanding of the effect of cognitive training on anxiety may facilitate the development of more effective cognitive training treatment for anxiety disorders. This study uses an experimental approach to examine the interplay of WM and anxiety following WM training. Previous studies show that increased demand on WM reduces concurrent anxiety evoked by threat of shock (induced anxiety). However, improving WM pharmacologically or via exercise prevents this anxiolytic effect. Conceivably, improving WM frees up cognitive resources to process threat information, thereby increasing anxiety. The present study tested the hypothesis that practicing a high load WM (i.e., increased demand) task would improve WM, and thus, free cognitive resources to process threat of shock, resulting in more anxiety (i.e., greater startle) during a subsequent WM task. Participants were randomly assigned to two training groups. The active-training group (N = 20) was trained on a 1- (low load) & 3-back (high load) WM task, whereas the control-training group (N = 20) performed a 0-back WM task. The experimental phase, similar in both groups, consisted of a 1- & 3-back WM task performed during both threat of shock and safety. As predicted, active training improved WM accuracy and increased anxiety during the experimental 3-back WM task. Therefore, improving WM efficiency can increase anxiety, possibly by freeing WM resources to process threat information. Published 2020. This article is a U.S. Government work and is in the public domain in the USA.We present a solar-centric approach to estimating the probability of extreme coronal mass ejections (CME) using the Solar and Heliospheric Observatory (SOHO)/Large Angle and Spectrometric Coronagraph Experiment (LASCO) CME Catalog observations updated through May 2018 and an updated list of near-Earth interplanetary coronal mass ejections (ICME). We examine robust statistical approaches to the estimation of extreme events. We then assume a variety of time-independent distributions fitting, and then comparing, the different probability distributions to the relevant regions of the cumulative distributions of the observed CME speeds. Using these results, we then obtain the probability that the velocity of a CME exceeds a particular threshold by extrapolation. We conclude that about 1.72% of the CMEs recorded with SOHO LASCO arrive at the Earth over the time both data sets overlap (November 1996 to September 2017). Then, assuming that 1.72% of all CMEs pass the Earth, we can obtain a first-order estimate of the probability of an extreme space weather event on Earth.