Mcknightheath0265

Brugada syndrome (BS) is a genetic pathological condition associated with a high risk for sudden cardiac death (SCD). Ventricular depolarization disorders have been suggested as a potential electrophysiological mechanism associated with high SCD risk on patients with BS. This paper aims to characterize the dynamic changes of ventricular depolarization observed during physical exercise in symptomatic and asymptomatic BS patients. To this end, cardiac ventricular depolarization features were automatically extracted from 12-lead ECG recordings acquired during standardized exercise stress test in 110 BS patients, of whom 25 were symptomatic. Conventional parameters were evaluated, including QRS duration, R and S wave amplitudes ([Formula see text], [Formula see text]), as well as QRS morphological features, such as up-stroke and down-stroke slopes of the R and S waves ([Formula see text], [Formula see text] and [Formula see text]). The effects of physical exercise and recovery on the dynamics of these markers werspecificity = 100% (AUC = 94%). The study highlights the importance of physical exercise test to unmask differentiated behaviors between symptomatic and asymptomatic BS patients through depolarization dynamic analysis. This analysis together with the obtained model may help to identify asymptomatic patients at low or high risk of future cardiac events, but it should be confirmed by further prospective studies.BACKGROUND Uncorrected refractive error (URE) is a major cause of vision impairment among children that impacts negatively on their lives including distresses. We aim to understand the disability-related distress among vision-impaired children due to URE in rural and semi-rural South Africa using qualitative techniques. METHODS Structured focus groups of children (aged 5-12 years old) with normal vision and vision impairment due to URE from four schools in Pinetown, KwaZulu Natal, South Africa, were performed (four mixed-gender group discussions and eight single gender group discussions). We recruited the study participants after the children underwent standardised vision screening. Criterion sampling was used when selecting study participants. The interviews were transcribed to identify meaning units and broken down to condensed meaning units, which were then grouped into megathemes. Themes were then generated. RESULTS Thirteen children with normal vision and 63 children with vision impairment due to URE participated in the twelve focus group discussions with 36 boys (47%) and 40 girls (53%). Twelve themes were generated. The megathemes were Loss of Self Confidence (number of themes (n) = 3), Loss of self-worth (n = 3), Loss of interconnection/ interaction with community (n = 2), Humiliation (n = 2) and Discrimination (n = 2). CONCLUSIONS We found that vision impairment due to URE can cause distress in different domains in children's life and further grouped them into different themes. The themes will be used for the development of a tool to assess disability-related distress among children with vision impairment due to URE. We also recommend that distresses caused by URE should be taken into consideration when designing eye care programmes for children.Though traditional thresholding methods are simple and efficient, they may result in poor segmentation results because only image's brightness information is taken into account in the procedure of threshold selection. Considering the contextual information between pixels can improve segmentation accuracy. To to this, a new thresholding method is proposed in this paper. The proposed method constructs a new two dimensional histogram using brightness of a pixel and local relative entropy of it's neighbor pixels. The local relative entropy (LRE) measures the brightness difference between a pixel and it's neighbor pixels. The two dimensional histogram, consisting of gray level and LRE, can reflect the contextual information between pixels to a certain extent. The optimal thresholding vector is obtained via minimizing cross entropy criteria. Experimental results show that the proposed method can achieve more accurate segmentation results than other thresholding methods.Kratom is a botanical substance that is marketed and promoted in the US for pharmaceutical opioid indications despite having no US Food and Drug Administration approved uses. Kratom contains over forty alkaloids including two partial agonists at the mu opioid receptor, mitragynine and 7-hydroxymitragynine, that have been subjected to the FDA's scientific and medical evaluation. However, pharmacological and toxicological data for the remaining alkaloids are limited. Therefore, we applied the Public Health Assessment via Structural Evaluation (PHASE) protocol to generate in silico binding profiles for 25 kratom alkaloids to facilitate the risk evaluation of kratom. PHASE demonstrates that kratom alkaloids share structural features with controlled opioids, indicates that several alkaloids bind to the opioid, adrenergic, and serotonin receptors, and suggests that mitragynine and 7-hydroxymitragynine are the strongest binders at the mu opioid receptor. Subsequently, the in silico binding profiles of a subset of the alkaloids were experimentally verified at the opioid, adrenergic, and serotonin receptors using radioligand binding assays. The verified binding profiles demonstrate the ability of PHASE to identify potential safety signals and provide a tool for prioritizing experimental evaluation of high-risk compounds.In CT (computerized tomography) imaging reconstruction, the acquired sinograms are usually noisy, so artifacts will appear on the resulting images. Thus, it is necessary to find the adequate filters to combine with reconstruction methods that eliminate the greater amount of noise possible without altering in excess the information that the image contains. The present work is focused on the evaluation of several filtering techniques applied in the elimination of artifacts present in CT sinograms. In particular, we analyze the elimination of Gaussian and Speckle noise. The chosen filtering techniques have been studied using four functions designed to measure the quality of the filtered image and compare it with a reference image. find more In this way, we determine the ideal parameters to carry out the filtering process on the sinograms, prior to the process of reconstruction of the images. Moreover, we study their application on reconstructed noisy images when using noisy sinograms and finally we select the best filter to combine with an iterative reconstruction method in order to test if it improves the quality of the images.