Cardiac arrhythmogenesis: a tale of two clocks?

Around 3.7 million individuals worldwide die each year from cardiac arrhythmias; this exceeds the total numbers of deaths from all cancers in the Western world. Despite major progress in interventional including device therapy, antiarrhythmic medication remains central to their management. In the late 1960s, Miles Vaughan Williams classified the existing drugs then used to treat cardiac arrhythmias. This was widely adopted worldwide in both clinical management and as guidance for the development of new drugs that have saved countless lives

Cardiomyocyte electrophysiology and its modulation: current views and future prospects

Normal and abnormal cardiac rhythms are of key physiological and clinical interest. This introductory article begins from Sylvio Weidmann's key historic 1950s microelectrode measurements of cardiac electrophysiological activity and Singh & Vaughan Williams's classification of cardiotropic targets. It then proceeds to introduce the insights into cardiomyocyte function and its regulation that subsequently emerged and their therapeutic implications. We recapitulate the resulting view that surface membrane electrophysiological events underlying cardiac excitation and its initiation, conduction and recovery constitute the final common path for the cellular mechanisms that impinge upon this normal or abnormal cardiac electrophysiological activity. We then consider progress in the more recently characterized successive regulatory hierarchies involving Ca2+ homeostasis, excitation–contraction coupling and autonomic G-protein signalling and their often reciprocal interactions with the surface membrane events, and their circadian rhythms. Then follow accounts of longer-term upstream modulation processes involving altered channel expression, cardiomyocyte energetics and hypertrophic and fibrotic cardiac remodelling. Consideration of these developments introduces each of the articles in this Phil. Trans. B theme issue. The findings contained in these articles translate naturally into recent classifications of cardiac electrophysiological targets and drug actions, thereby encouraging future iterations of experimental cardiac electrophysiological discovery, and testing directed towards clinical management

TNFRSF11B computational development network construction and analysis between frontal cortex of HIV encephalitis (HIVE) and HIVE-control patients

<p>Abstract</p> <p>Background</p> <p><it>TNFRSF11B </it>computational development network construction and analysis of frontal cortex of HIV encephalitis (HIVE) is very useful to identify novel markers and potential targets for prognosis and therapy.</p> <p>Methods</p> <p>By integration of gene regulatory network infer (GRNInfer) and the database for annotation, visualization and integrated discovery (DAVID) we identified and constructed significant molecule <it>TNFRSF11B </it>development network from 12 frontal cortex of HIVE-control patients and 16 HIVE in the same GEO Dataset GDS1726.</p> <p>Results</p> <p>Our result verified <it>TNFRSF11B </it>developmental process only in the downstream of frontal cortex of HIVE-control patients (<it>BST2, DGKG, GAS1, PDCD4, TGFBR3, VEZF1 </it>inhibition), whereas in the upstream of frontal cortex of HIVE (<it>DGKG, PDCD4 </it>activation) and downstream (<it>CFDP1, DGKG, GAS1, PAX6 </it>activation; <it>BST2, PDCD4, TGFBR3, VEZF1 </it>inhibition). Importantly, we datamined that <it>TNFRSF11B </it>development cluster of HIVE is involved in T-cell mediated immunity, cell projection organization and cell motion (only in HIVE terms) without apoptosis, plasma membrane and kinase activity (only in HIVE-control patients terms), the condition is vital to inflammation, brain morphology and cognition impairment of HIVE. Our result demonstrated that common terms in both HIVE-control patients and HIVE include developmental process, signal transduction, negative regulation of cell proliferation, RNA-binding, zinc-finger, cell development, positive regulation of biological process and cell differentiation.</p> <p>Conclusions</p> <p>We deduced the stronger <it>TNFRSF11B </it>development network in HIVE consistent with our number computation. It would be necessary of the stronger <it>TNFRSF11B </it>development function to inflammation, brain morphology and cognition of HIVE.</p

Possible Way to Synthesize Superheavy Element Z=117

Within the framework of the dinuclear system model, the production of superheavy element Z=117 in possible projectile-target combinations is analyzed systematically. The calculated results show that the production cross sections are strongly dependent on the reaction systems. Optimal combinations, corresponding excitation energies and evaporation channels are proposed in this letter, such as the isotopes ^{248,249}Bk in ^{48}Ca induced reactions in 3n evaporation channels and the reactions ^{45}Sc+^{246,248}Cm in 3n and 4n channels, and the system ^{51}V+^{244}Pu in 3n channel.Comment: 10 pages, 4 figures, 1 tabl

Applying the ARPSO Algorithm to Shafting Alignment Optimization Design

Trial-and-error method for shafting alignment at the initial design stage in the shipbuilding industry is mostly carried out by shipyard designers. However, adjusting of a highly sensitive shaft line within a short period in order to obtain a reasonable positive design value for each bearing reaction force (load) and bearing pressure for the entire propulsion shafting system is very difficult. Any minor changes in the bearing location and/or off-set design values may cause different analytical results with a large design deviation, such that the fi nal design result may not comply with the classifi cation society requirements and manufacturers’ design criteria. The innovative ARPSO-SHAALIN design program successfully combines and integrates the Three Moment Equation Method (TMEM) for a continuous beam with the Attractive and Repulsive Particle Swarm Optimization (ARPSO) algorithm. The ARPSO algorithm searches for the values of global optimal design parameter for each bearing off-set and location of the propulsion shafting in the initial design stage in order to create a brand new optimal shafting arrangement. Design results are verifi ed and presented

Applying the ARPSO Algorithm to Shafting Alignment Optimization Design

Trial-and-error method for shafting alignment at the initial design stage in the shipbuilding industry is mostly carried out by shipyard designers. However, adjusting of a highly sensitive shaft line within a short period in order to obtain a reasonable positive design value for each bearing reaction force (load) and bearing pressure for the entire propulsion shafting system is very difficult. Any minor changes in the bearing location and/or off-set design values may cause different analytical results with a large design deviation, such that the fi nal design result may not comply with the classifi cation society requirements and manufacturers’ design criteria. The innovative ARPSO-SHAALIN design program successfully combines and integrates the Three Moment Equation Method (TMEM) for a continuous beam with the Attractive and Repulsive Particle Swarm Optimization (ARPSO) algorithm. The ARPSO algorithm searches for the values of global optimal design parameter for each bearing off-set and location of the propulsion shafting in the initial design stage in order to create a brand new optimal shafting arrangement. Design results are verifi ed and presented

Update on antiarrhythmic drug pharmacology.

Cardiac arrhythmias constitute a major public health problem. Pharmacological intervention remains mainstay to their clinical management. This, in turn, depends upon systematic drug classification schemes relating their molecular, cellular, and systems effects to clinical indications and therapeutic actions. This approach was first pioneered in the 1960s Vaughan-Williams classification. Subsequent progress in cardiac electrophysiological understanding led to a lag between the fundamental science and its clinical translation, partly addressed by The working group of the European Society of Cardiology (1991), which, however, did not emerge with formal classifications. We here utilize the recent Revised Oxford Classification Scheme to review antiarrhythmic drug pharmacology. We survey drugs and therapeutic targets offered by the more recently characterized ion channels, transporters, receptors, intracellular Ca2+ handling, and cell signaling molecules. These are organized into their strategic roles in cardiac electrophysiological function. Following analysis of the arrhythmic process itself, we consider (a) pharmacological agents directly targeting membrane function, particularly the Na+ and K+ ion channels underlying depolarizing and repolarizing events in the cardiac action potential. (b) We also consider agents that modify autonomic activity that, in turn, affects both the membrane and (c) the Ca2+ homeostatic and excitation-contraction coupling processes linking membrane excitation to contractile activation. Finally, we consider (d) drugs acting on more upstream energetic and structural remodeling processes currently the subject of clinical trials. Such systematic correlations of drug actions and arrhythmic mechanisms at different molecular to systems levels of cardiac function will facilitate current and future antiarrhythmic therapy

Constructing Robust Emotional State-based Feature with a Novel Voting Scheme for Multi-modal Deception Detection in Videos

Deception detection is an important task that has been a hot research topic due to its potential applications. It can be applied in many areas, from national security (e.g., airport security, jurisprudence, and law enforcement) to real-life applications (e.g., business and computer vision). However, some critical problems still exist and are worth more investigation. One of the significant challenges in the deception detection tasks is the data scarcity problem. Until now, only one multi-modal benchmark open dataset for human deception detection has been released, which contains 121 video clips for deception detection (i.e., 61 for deceptive class and 60 for truthful class). Such an amount of data is hard to drive deep neural network-based methods. Hence, those existing models often suffer from overfitting problems and low generalization ability. Moreover, the ground truth data contains some unusable frames for many factors. However, most of the literature did not pay attention to these problems. Therefore, in this paper, we design a series of data preprocessing methods to deal with the aforementioned problem first. Then, we propose a multi-modal deception detection framework to construct our novel emotional state-based feature and use the open toolkit openSMILE to extract the features from the audio modality. We also design a voting scheme to combine the emotional states information obtained from visual and audio modalities. Finally, we can determine the novel emotion state transformation feature with our self-designed algorithms. In the experiment, we conduct the critical analysis and comparison of the proposed methods with the state-of-the-art multi-modal deception detection methods. The experimental results show that the overall performance of multi-modal deception detection has a significant improvement in the accuracy from 87.77% to 92.78% and the ROC-AUC from 0.9221 to 0.9265.Comment: 8 pages, for AAAI23 publicatio