The structure of human thioredoxin reductase 1 provides insights into C-terminal rearrangements during catalysis

Human thioredoxin reductase (hTrxR) is a homodimeric flavoprotein crucially involved in the regulation of cellular redox reactions, growth and differentiation. The enzyme contains a selenocysteine residue at its C-terminal active site that is essential for catalysis. This redox center is located on a flexible arm, solvent-exposed and reactive towards electrophilic inhibitors, thus representing a target for antitumor drug development. During catalysis reducing equivalents are transferred from the cofactor NADPH to FAD, then to the N-terminal active site cysteine residues and from there to the flexible C-terminal part of the other subunit to be finally delivered to a variety of second substrates at the molecule's surface. Here we report the first crystal structure of hTrxR1 (Sec-->Cys) in complex with FAD and NADP(+) at a resolution of 2.8 A. From the crystals three different conformations of the carboxy-terminal arm could be deduced. The predicted movement of the arm is facilitated by the concerted action of the three side-chain residues of N418, N419 and W407, which act as a guiding bar for the C-terminal sliding process. As supported by previous kinetic data, the three visualized conformations might reflect different stages in enzymatic catalysis. Comparison with other disulfide reductases including human glutathione reductase revealed specific inhibitor binding sites in the intersubunit cavity of hTrxR that can be exploited for structure-based inhibitor development.     

基于小波变换的心电信号去噪算法

目的:去除在心电信号采集过程中混入的肌电干扰、工频干扰、基线漂移等噪声信号,避免噪声对心电信号特征点的识别和提取造成误判和漏判。方法:首先利用coif4小波对心电信号按Mallat算法进行分解,然后采用软、硬阈值折衷与小波重构的算法进行去噪。结果:采用MIT/BIH Arrhythmia Database中的心电信号进行仿真、验证,有效去除了三种常见的噪声信号。结论:本方法实时性好,为临床分析与诊断奠定了基础。     

Inhibition of hepatic glucose 6-phosphatase system by the green tea flavanol epigallocatechin gallate

Effect of 5-100 microM epigallocatechin gallate (EGCG) on hepatic glucose 6-phosphatase (G6Pase) system was investigated. EGCG inhibited G6Pase in intact but not in permeabilized rat liver microsomes, suggesting the interference with the transport. However, EGCG did not hinder microsomal glucose 6-phosphate (G6P) uptake. Instead, it increased the accumulation of radioactivity after the addition of [(14)C]G6P, presumably due to a slower release of [(14)C]glucose, the product of luminal hydrolysis. Indeed, EGCG was found to inhibit microsomal glucose efflux. Since G6Pase activity is depressed by glucose in a concentration-dependent manner, we concluded that EGCG inhibits G6Pase through an elevated luminal glucose level.     

Static magnetic field influence on rat brain function detected by heart rate monitoring

The aim of the present study was to identify the effects of a static magnetic field (SMF) on rat brain structures that control autonomic functions, specifically heart rate and heart rhythmicity. The experiments were carried out on 44 male Wistar rats under ketamine-xylazine anesthesia. SMF was induced using samarium-cobalt fused magnets (20 x 20 x 10 mm in size) placed bitemporally. Magnetic induction intensity was 100 mT on the surface of the head. Duration of magnetic field application was 15 min. An electrocardiogram was recorded from limb lead II, and both heart rate (average duration of cardiac cycles) and heart rhythmicity were analyzed before and after SMF application. SMF evoked changes in both heart rate and rhythm in 80% of the animals; the predominant effects were bradycardia and disappearance of respiratory sinus arrhythmia. However, the effectiveness of SMF in large measure depends on both functional peculiarities and functional activities of brain autonomic centers.     

心电图ST段不同改变与急性心肌梗死患者冠脉造影病变特点及生活质量的相关性研究

目的:探讨心电图ST段不同改变与急性心肌梗死患者冠脉造影病变特点及生活质量的相关性。方法:选取选取2015年6月到2017年6月在本院接受治疗的急性心肌梗死患者208例,根据心电图ST段的改变情况将患者分为ST段抬高组(124例)、ST段压低组(64例)、ST段无偏移组(20例),所有患者进行冠脉造影检查和常规治疗,比较治疗前三组患者的冠脉造影情况和冠脉狭窄程度,比较治疗1个月后三组患者的生活质量评分。结果:在ST段抬高组中,共检测出单支血管闭塞病变99例,占79.84%,两支或两支以上血管病变25例,占20.16%,其中侧支循环开放19例,开放率为15.32%。在ST段压低组中,共检测出单支血管非闭塞病变6例,占9.38%,两支或两支以上血管非闭塞病变56例,占87.50%,单支血管闭塞病变2例,占3.13%,其中侧支循环开放34例,开放率为53.13%。在ST段无偏移组中,单支血管闭塞病变15例,占75.00%,单支或多支血管非闭塞病变5例,占25.00%,其中侧支循环开放7例,开放率为35.00%。ST段抬高组、ST段无偏移组患者的冠脉狭窄程度以重度狭窄为主,ST段压低组患者的冠脉狭窄程度以中度狭窄为主,三组患者的轻度狭窄、中度狭窄、重度狭窄整体比较存在统计学差异(P0.05)。三组患者的疼痛评分、躯体受限评分、精神及活动评分整体比较具有统计学差异(P0.05),ST段压低组的上述评分均显著高于ST段抬高组和ST段无偏移组(P0.05)。结论:心电图ST段不同改变与急性心肌梗死患者冠脉造影病变密切相关,且ST段压低患者的预后通常较好。     

基于小波变换的ECG压缩

小波变换现已成为信号压缩的有力工具,小波压缩称法所基于的“嵌入零树小波”（ＥＥＷ）编码已发展为心电信号进行综压缩。     

Co-Designed Exposure Protocol in the Study of Idiopathic Environmental Intolerance Attributed to Electromagnetic Fields

The hypothesis of an electromagnetic origin of idiopathic environmental intolerance (IEI) attributed to electromagnetic fields (EMF) has been widely investigated by provocation studies, which consist of deliberately exposing people with IEI-EMF in laboratory settings to particular EMF to observe volunteers’ reactions. In the majority of these studies, reactions have been found to be independent of exposure. However, most of these studies suffer from design and methodological limitations that might bias their findings or reduce their precision. As provocation studies are best suited for isolating the effects of EMF, innovative protocols should be applied. In the ExpoComm project (PNREST Anses, EST/2017/2 RF/19), several innovations have been introduced: the involvement of people with IEI-EMF in the development of the protocol, the attenuation of the anxiogenic nature of the tests, the individualization of the protocol, the validation of the neutral or normal reactivity state before the test, and the use of a cocktail of real, rather than artificially generated, sources. The objective of involving people with IEI-EMF was to increase the relevance and acceptability of the protocol, while respecting technical constraints and scientific quality requirements. This paper describes the protocol resulting from the collaborative process. Bioelectromagnetics. 2020;41:425–437. © 2020 Bioelectromagnetics Society.     

Classification of electrocardiogram signals with support vector machines and genetic algorithms using power spectral features

This paper proposes a new power spectral-based hybrid genetic algorithm-support vector machines (SVMGA) technique to classify five types of electrocardiogram (ECG) beats, namely normal beats and four manifestations of heart arrhythmia. This method employs three modules: a feature extraction module, a classification module and an optimization module. Feature extraction module extracts electrocardiogram's spectral and three timing interval features. Non-parametric power spectral density (PSD) estimation methods are used to extract spectral features. Support vector machine (SVM) is employed as a classifier to recognize the ECG beats. We investigate and compare two such classification approaches. First they are specified experimentally by the trial and error method. In the second technique the approach optimizes the relevant parameters through an intelligent algorithm. These parameters are: Gaussian radial basis function (GRBF) kernel parameter σ and C penalty parameter of SVM classifier. Then their performances in classification of ECG signals are evaluated for eight files obtained from the MIT–BIH arrhythmia database. Classification accuracy of the SVMGA approach proves superior to that of the SVM which has constant and manually extracted parameter.     

Chaotic based reconstructed phase space features for detecting ventricular fibrillation

Among the variety of cardiac arrhythmias, ventricular fibrillation (VF) and ventricular tachycardia (VT) are life-threatening; thus, accurate classification of these arrhythmias is a crucial task for cardiologists. Nevertheless, VT and VF signals are very similar in the time domain and accurate distinguishing these signals with naked eyes in some cases is impossible. In this paper, a novel self-similarity image-based scheme is introduced to classify the underlying information of VT, VF and normal electrocardiogram (ECG) signals. In this study, VT, VF and normal ECG signals are selected from CCU of the Royal Infirmary of Edinburgh and MIT-BIH datasets. According to the time delay method, signal samples can be assigned to state variables and a trajectory can be achieved. To extract the proposed self-similarity feature, first, two different trajectories from each signal trial are drawn according to two different delay time values. The two-dimensional state space of each trial trajectory is considered as an image. Therefore, two trajectory images are produced for each signal. Number of visited pixels in the first image is determined and is subtracted from that of the second image as the self-similarity feature of that signal. Moreover, another scheme is proposed to have a better estimation of self-similarity in which the logical AND operator is applied to both images (matrices) of each ECG trial. The third proposed criterion is similar to box counting method by this difference that each pixel is assigned a weight according to the trajectory density at that point and finally visited weighted pixels are counted. To classify VF from VT and normal ECG, a threshold is determined through the cross validation phase under the Receiver Operating Characteristic (ROC) criterion. To assess the proposed methods, the mentioned signals are classified using the-state-of-art chaotic features such as correlation dimension, the largest Lyapunov exponent and Approximate Entropy (ApEn). Experimental results indicate superiority of the proposed method in classifying the VT, VF and normal ECG signals compared to present traditional schemes. In addition, computational complexity of the introduced methods is very low and can be implemented in real-time applications.     

基于Flexible ICA的睡眠EEG及EOG中心电伪差的消除

提出了一种采用自适应非线性函数的ICA学习算法,Flexible ICA算法,并将其应用于睡眠EEG自动分期的前期预处理中,用于消除采集到的各通道信号中的心电伪差.实验结果证明,Flexible ICA算法能够快速有效的消除各通道的心电伪差,为后期的睡眠EEG自动分期打下了良好的基础.