基于希尔伯特黄变换和深度卷积神经网络的房颤检测

房颤是一种常见的心律失常,其发病率会随着年龄增长而升高.因此,从心电(ECG)信号中尽早识别出房颤,有助于降低中风风险和心源性死亡率.为有效提高其检测准确率,该文提出一种基于希尔伯特黄变换(HHT)和深度卷积神经网络的房颤检测方法.1维的时域心电信号通过希尔伯特黄变换,转换为时频域信号,旨在通过时频分析,丰富原始信号的...     

Dual‐Drug Delivery Using Dextran‐Functionalized Nanoparticles Targeting Cardiac Fibroblasts for Cellular Reprogramming

The inability of the heart to recover from an ischemic insult leads to the formation of fibrotic scar tissue and heart failure. From the therapeutic strategies under investigation, cardiac regeneration holds the promise of restoring the full functionality of a damaged heart. Taking into consideration the presence of vast numbers of fibroblasts and myofibroblasts in the injured heart, direct fibroblast reprogramming into cardiomyocytes using small drug molecules is an attractive therapeutic option to replenish the lost cardiomyocytes. Here, a spermine‐acetalated dextran‐based functional nanoparticle is developed for pH‐triggered drug delivery of two poorly water soluble small molecules, CHIR99021 and SB431542, both capable of increasing the efficiency of direct reprogramming of fibroblast into cardiomyocytes. Upon functionalization with polyethylene glycol and atrial natriuretic peptide, the biocompatibility of the nanosystem is improved, and the cellular interactions with the cardiac nonmyocytes are specifically augmented. The dual delivery of the compounds is verified in vitro, and the compounds exerted concomitantly anticipate biological effects by stabilizing β‐catenin (CHIR99021) and by preventing translocation of Smad3 to the nucleus of (myo)fibroblasts (SB431542). These observations highlight the potential of this nanoparticle‐based system toward improved drug delivery and efficient direct reprogramming of fibroblasts into cardiomyocyte‐like cells, and thus, potential cardiac regeneration therapy.     

A Quantitative Model for the Ventricular Response During Atrial Fibrillation

We review the principal statistical properties of the RR interval sequence during atrial fibrillation. A simple quantitative electrophysiologic model is presented which successfully accounts for these statistical features. In this model the atrioventricular junction (AVJ) is treated as a single cell equivalent characterized by a refractory period and spontaneous rate of phase 4 depolarization. The atria are presumed to bombard the AVJ with impulses that arrive randomly in time; each impulse induces a partial depolarization of the AVJ equivalent cell. We show that other models for the ventricular response during atrial fibrillation (e. g., concealed conduction models) do not adequately account for the salient statistical features of the RR interval sequence. The present model may be utilized to characterize a sequence of RR intervals recorded from a given individual in terms of the numerical magnitudes of the model's four parameters: the mean rate at which atrial impulses bombard the AVJ, the relative amplitude of the impulses, the relative rate of spontaneous phase 4 depolarization of the AVJ equivalent cell, and the refractory period of the AVJ equivalent cell. Such a characterization may be useful in studying mechanisms of drug action and interaction, as well as potentially offering a quantitative means for optimizing pharmacologic manangement of chronic atrial fibrillation.     

A multiscale graph theoretical approach to gene regulation networks: a case study in atrial fibrillation

The changes in between gene expression correlation structure induced in heart tissue by atrial fibrillation are studied by means of a graph theoretical approach. As expected by general statistical mechanics principles, the disease increases the general connectivity of the gene regulation network; the multiscale character of the analysis allows us to get both a general appreciation of regulation network connectivity and the sketching of a biological interpretation of the studied disease. The presence of a still largely unknown, scale invariant, global correlation field encompassing the entire genome is demonstrated as well.     

Proteinous amino acids in muscle cytosol of rats' heart, after their treatment with propranolol, pentylenetetrazol or reserpine

Tissue levels of nineteen amino acids and total free amino acids, were assayed by gas-liquid chromatography in cytosols of rat atrial and ventricular muscle cardiomyocytes. The tissues were assayed after the rats had been administered IP with the three cardioactive drugs, exerting a significant effect on their heart action: propranolol, pentylenetetrazol and reserpine. It was demonstrated that while in the atrial and ventricular cardiac muscle cytosols of control rats, arginine, glutamine and cysteine were detected in high levels (35.1% and 17.6%; 14.8% and 51.6%; 9.9% and 0.25% of the total free amino acids, respectively), all three drugs significantly reduced the total amounts of cytosolic free amino acids in both atrial and ventricular heart muscles. All three drugs (with reserpine in particular) modified the levels of arginine, cysteine, phenylalanine, tryptophan, isoleucine and tyrosine. The role of these amino acids in the heart muscle cytosol, and their involvement in the mechanism of action of these three cardioactive drugs, is discussed.     

Proteinous amino acids in hearts' muscle cytosol of rats pretreated with digoxin, caffeine or isoproterenol

Levels of the 19 proteinous amino acids and total free amino acids were assayed by gas-liquid chromatography in cytosols of rat atrial and ventricular muscle cardiomyocytes. The tissues were assayed after the rats had been exposed to the cardioactive drugs digoxin, caffeine, and isoproterenol, each having different mechanisms of action. We demonstrated that, in the atrial and ventricular cardiac muscle cytosol of control (untreated) rats, arginine, glutamine, and cysteine existed in their highest levels: 35.1% and 17.6%; 14.8% and 51.6%; 9.9% and 0.25% of the total free amino acids, respectively. The levels of the other amino acids in the atrial and ventricular cardiac muscle cytosols ranged between 0.1% and 10.0% of the total free amino acids. Digoxin, caffeine, and isoproterenol significantly reduced the total amount of cytosolic free amino acids in the atrial heart muscle cytosol to 7.6%, 9.0%, and 9.2% of the control value (100%), and in the ventricular heart muscle cytosol to 31.1%, 43.2%, and 28.3% of the control. The three drugs tested changed the cytosols' levels of arginine, cysteine, tryptophane, asparagine, and tyrosine in atrial and ventricular heart muscle cytosol, as compared to the control groups (calculated as a percent of the total free amino acids in the experimental groups). The role of proteinous amino acids in the function of the heart muscle and in the mechanism of action of these drugs on the mammalian heart is discussed.     

Classification of electrocardiographic P-wave morphology

The atrial activity of the human heart is normally visible in the electrocardiogram as a P-wave. In patients with intermittent atrial fibrillation, a different P-wave morphology can sometimes be seen, indicating atrial conduction defects. The purpose of this study was to develop a method to discriminate between such P-waves and normal ones. 20 recordings of each type were used in a classification which, based on impulse response analysis of the P-wave and linear discrimination between various parameters, produced a correct classification in 37 of the 40 recordings (sensitivity 95%, specificity 90%).     

A High-Precision,Low-Voltage Pulsed Field Ablation Device with Capability of Minimally Invasive Surgery

Pulsed field ablation is a novel approach to treating 33.5 million patients with atrial fibrillation and offers a tissue-specific advantage over conventional radiofrequency ablation and cryoablation. However, for complex structural targets in the heart, current electrodes often damage non-target areas due to inaccurate ablation and have to employ electrical pulses with amplitudes of several kilovolts. Herein, materials and designs of a catheter-integrated microelectrode and sensors that can be used for high-precision and low-voltage pulsed field ablation through minimally invasive operation on a large animal model, is reported. The device with a new electrode configuration supports point-by-point ablation with a width of 3.8 mm (≈1/10 that of a typical ablation electrode) for individual lesions at the voltage of 300 V (an order of magnitude reduction compared to the current state-of-the-art). More impressively, the integrated catheter allows for pulsed field ablation on the large animal heart through minimally invasive surgery and blocks the electrical conduction pathway on the heart, which is the key to treating atrial fibrillation. This catheter-integrated device will enhance the efficiency and safety of pulsed field ablation, especially for complex cardiac structures, thus facilitating its move to the clinic.     

Comparison of atrial signal extraction algorithms in 12-lead ECGs with atrial fibrillation

Analysis of atrial rhythm is important in the treatment and management of patients with atrial fibrillation. Several algorithms exist for extracting the atrial signal from the electrocardiogram (ECG) in atrial fibrillation, but there are few reports on how well these techniques are able to recover the atrial signal. We assessed and compared three algorithms for extracting the atrial signal from the 12-lead ECG. The 12-lead ECGs of 30 patients in atrial fibrillation were analyzed. Atrial activity was extracted by three algorithms, Spatiotemporal QRST cancellation (STC), principal component analysis (PCA), and independent component analysis (ICA). The amplitude and frequency characteristics of the extracted atrial signals were compared between algorithms and against reference data. Mean (standard deviation) amplitude of QRST segments of V1 was 0.99 (0.54) mV, compared to 0.18 (0.11) mV (STC), 0.19 (0.13) mV (PCA), and 0.29 (0.22) mV (ICA). Hence, for all algorithms there were significant reductions in the amplitude of the ventricular activity compared with that in V1. Reference atrial signal amplitude in V1 was 0.18 (0.11) mV, compared to 0.17 (0.10) mV (STC), 0.12 (0.09) mV (PCA), and 0.18 (0.13) mV (ICA) in the extracted atrial signals. PCA tended to attenuate the atrial signal in these segments. There were no significant differences for any of the algorithms when comparing the amplitude of the reference atrial signal with that of the extracted atrial signals in segments in which ventricular activity had been removed. There were no significant differences between algorithms in the frequency characteristics of the extracted atrial signals. There were discrepancies in amplitude and frequency characteristics of the atrial signal in only a few cases resulting from notable residual ventricular activity for PCA and ICA algorithms. In conclusion, the extracted atrial signals from these algorithms exhibit very similar amplitude and frequency characteristics. Users of these algorithms should be observant of residual ventricular activities which can affect the analysis of the fibrillatory waveform in clinical practice.     

Computer modeling of ventricular rhythm during atrial fibrillation and ventricular pacing

We propose a unified atrial fibrillation (AF)-ventricular pacing (VP) (AF-VP) model to demonstrate the effects of VP on the ventricular rhythm during atrial fibrillation AF. In this model, the AV junction (AVJ) is treated as a lumped structure characterized by refractoriness and automaticity. Bombarded by random AF impulses, the AVJ can also be invaded by the VP-induced retrograde wave. The model includes bidirectional conduction delays in the AVJ and ventricle. Both refractory period and conduction delay of the AVJ are dependent upon its recovery time. The electrotonic modulation by blocked impulses is also considered in the model. Our simulations show that, with proper parameter settings, the present model can account for most principal statistical properties of the RR intervals during AF. We further demonstrate that the AV conduction property and the ventricular rate in AF depend on both AF rate and the degree of electrotonic modulation in the AVJ. Finally, we show that multilevel interactions between AF and VP can generate various patterns of ventricular rhythm that are consistent with previous experimental observations.     

Effective Codelivery of lncRNA and pDNA by Pullulan‐Based Nanovectors for Promising Therapy of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most common cancers. Maternally expressed gene 3 (MEG3, one kind of long noncoding RNA [lncRNA]) can act as a tumor suppressor and regulate P53 target gene expression. However, lncRNA MEG3 demonstrates relatively low or no expression in human HCC. This study provides a promising concept to codeliver lncRNA and pDNA for cancer therapy. As proof‐of‐concept, the pcDNA‐MEG3 and pcDNA‐P53 plasmids‐condensed nanocomplexes with the liver‐targeting polycation gene vector, pullulan‐based ethanolamine‐modified poly(glycidyl methacrylate) (denoted as PuPGEA), are proposed to codeliver lncRNA and pDNA to treat HCC. Pullulan‐containing nanovectors are shown to be able to effectively mediate gene delivery in liver cells. To assess gene delivery performances of PuPGEA, a series of assays such as in vitro gene transfection, HCC cell proliferation, colony formation, migration, matrigel transwell assays, and in vivo xenograft animal models are carried out. The codelivery system with PuPGEA/(MEG3+P53) nanocomplexes demonstrates additive effects in suppressing HCC compared to PuPGEA/MEG3 or PuPGEA/P53 nanocomplexes alone. These results suggest that codelivery of lncRNA and pDNA by polycation nanovectors is a promising method to treat cancers.     

A new method for analysis of atrial activation during chronicatrial fibrillation in man

To further clarify the mechanisms maintaining chronic atrial fibrillation (CAF), a method identifying preferable activation patterns of the atria during fibrillation, by time averaging of multiple discrete excitation vectors, was developed. Repeated recordings, each of 56 atrial bipolar electrograms simultaneously acquired during 8 s, were made at multiple sites in the right atrial free wall and the left atrial appendage in 16 patients with CAF using a 2.17×3.54 cm electrode array. The local activation times (LAT's) in each recording were estimated as the median activation time at the respective measurement point. By calculating the time difference between the LAT's at adjacent measurement points in two spatial dimensions, a direction vector was created for each activation wave passing each set of measurement points, a total of 42 sets. By time averaging of the individual direction vectors (typically n=55) at each set of measurement points, preferable activation patterns were determined. Three types of activation patterns were found: 1) inconsistent activation (n=5), 2) consistent activation with preferential propagation directions (n=7) and 3) consistent activation with impulses originating from a localizable site within the recording area (n=4). All activation patterns were reproducible and the two latter patterns were proven significant using statistical tests. It is concluded that this new method is useful in further clarification of the mechanisms involved in the maintenance of atrial fibrillation     

绿激光穴照PCI术后冠心病患者的疗效分析

本研究通过对PCI术后冠心病患者应用绿激光内关穴照射治疗和单纯西药干预两组临床疗效观察,对血脂、心功能EF（%）、Hs-CRP等相关指标变化进行分析,研究绿激光对PCI术后冠心病患者的治疗作用。结果提示PCI术后冠心病患者应用绿激光内关穴照射治疗,能更有效控制心绞痛症状,提高冠心病患者生活质量。     

Prediction of Drug-Drug Interactions Based on Multi-layer Feature Selection and Data Balance

Drug-drug interactions (DDIs) occur when two drugs react with each other, which may cause unex-pected side effects and even death of the patient. Methods that use adverse event reports to predict unexpected DDIs are limited by two critical yet challenging issues. One is the diffi culty of selecting discriminative features from numer-ous redundant and irrelevant adverse events for modeling. The other is the data imbalance, i.e., the drug pairs causing adverse effects are far less than those not causing adverse effects, which leads to poor accuracy of DDIs detection. We propose a multi-layer feature selection method to select discriminative adverse events and apply an over-sampling technique to make the data balanced. The experimental re-sults show that the validation accuracy of positive DDIs on the Canada Vigilance Adverse Reaction Online Database increases to two times, and 110 DDIs are identified on the drug interactions checker of Drugs.com in USA.     

A wide-range programmable frequency synthesizer based on a finite state machine filter

In this article, an FPGA-based design and implementation of a fully digital wide-range programmable frequency synthesizer based on a finite state machine filter is presented. The advantages of the proposed architecture are that, it simultaneously generates a high frequency signal from a low frequency reference signal (i.e. synthesising), and synchronising the two signals (signals have the same phase, or a constant difference) without jitter accumulation issue. The architecture is portable and can be easily implemented for various platforms, such as FPGAs and integrated circuits. The frequency synthesizer circuit can be used as a part of SERDES devices in intra/inter chip communication in system-on-chip (SoC). The proposed circuit is designed using Verilog language and synthesized for the Altera DE2-70 development board, with the Cyclone II (EP2C35F672C6) device on board. Simulation and experimental results are included; they prove the synthesizing and tracking features of the proposed architecture. The generated clock signal frequency of a range from 19.8?MHz to 440?MHz is synchronized to the input reference clock with a frequency step of 0.12?MHz.     

An automatic system for the analysis and classification of human atrial fibrillation patterns from intracardiac electrograms

This paper presents an automatic system for the analysis and classification of atrial fibrillation (AF) patterns from bipolar intracardiac signals. The system is made up of: 1) a feature-extraction module that defines and extracts a set of measures potentially useful for characterizing AF types on the basis of their degree of organization; 2) a feature-selection module (based on the Jeffries-Matusita distance and a branch and bound search algorithm) identifying the best subset of features for discriminating different AF types; and 3) a support vector machine technique-based classification module that automatically discriminates the AF types according to the Wells' criteria. The automatic system was applied on 100 intracardiac AF signal strips and on a selection of 11 representative features, demonstrating: a) the possibility to properly identify the most significant features for the discrimination of AF types; b) higher accuracy (97.7% using the seven most informative features) than the traditional maximum likelihood classifier; and c) effectiveness in AF classification also with few training samples (accuracy = 88.3% with only five training signals). Finally, the system identifies a combination of indices characterizing changes of morphology of atrial activation waves and perturbation of the isoelectric line as the most effective in separating the AF types.     

Waveform Characterization of Atrial Fibrillation Using Phase Information

A novel method for characterization of f-wave morphology in atrial fibrillation (AF) is presented. The method decomposes atrial activity into fundamental and harmonic components, dividing each component into short blocks for which the amplitudes, frequencies, and phases are estimated. The phase delays between the fundamental and each of the harmonics, here referred to as harmonic phase relationships, are used as features of f-wave morphology. The estimated waves are clustered into typical morphologic patterns. The performance of the method is illustrated by simulated signals, ECG signals recorded from 36 patients with organized AF, and an ECG signal recorded during drug loading with flecainide. The results show that the method can distinguish a wide variety of f-wave morphologies, and that typical morphologies can be established for further analysis of AF.      

Clinical evaluation of respiratory motion compensation for anatomical roadmap guided cardiac electrophysiology procedures

X-ray fluoroscopically guided cardiac electrophysiological procedures are routinely carried out for diagnosis and treatment of cardiac arrhythmias. X-ray images have poor soft tissue contrast and, for this reason, overlay of static 3-D roadmaps derived from preprocedural volumetric data can be used to add anatomical information. However, the registration between the 3-D roadmap and the 2-D X-ray image can be compromised by patient respiratory motion. Three methods were designed and evaluated to correct for respiratory motion using features in the 2-D X-ray images. The first method is based on tracking either the diaphragm or the heart border using the image intensity in a region of interest. The second method detects the tracheal bifurcation using the generalized Hough transform and a 3-D model derived from 3-D preoperative volumetric data. The third method is based on tracking the coronary sinus (CS) catheter. This method uses blob detection to find all possible catheter electrodes in the X-ray image. A cost function is applied to select one CS catheter from all catheter-like objects. All three methods were applied to X-ray images from 18 patients undergoing radiofrequency ablation for the treatment of atrial fibrillation. The 2-D target registration errors (TRE) at the pulmonary veins were calculated to validate the methods. A TRE of 1.6 mm ± 0.8 mm was achieved for the diaphragm tracking; 1.7 mm ± 0.9 mm for heart border tracking, 1.9 mm ± 1.0 mm for trachea tracking, and 1.8 mm ± 0.9 mm for CS catheter tracking. We present a comprehensive comparison between the techniques in terms of robustness, as computed by tracking errors, and accuracy, as computed by TRE using two independent approaches.