Intermetallic Nanoarchitectures for Efficient Electrocatalysis

Intermetallic structures whose regular atomic arrays of constituent elements present unique catalytic properties have attracted considerable attention as efficient electrocatalysts for energy conversion reactions. Further performance enhancement in intermetallic catalysts hinges on constructing catalytic surfaces possessing high activity, durability, and selectivity. In this Perspective, we introduce recent endeavors to boost the performance of intermetallic catalysts by generating nanoarchitectures, which have well-defined size, shape, and dimension. We discuss the beneficial effects of nanoarchitectures compared with simple nanoparticles in catalysis. We highlight that the nanoarchitectures have high intrinsic activity owing to their inherent structural factors, including controlled facets, surface defects, strained surfaces, nanoscale confinement effects, and a high density of active sites. We next present notable examples of intermetallic nanoarchitectures, namely, facet-controlled intermetallic nanocrystals and multidimensional nanomaterials. Finally, we suggest the future research directions of intermetallic nanoarchitectures

Skeletal Nanostructures Promoting Electrocatalytic Reactions with Three-Dimensional Frameworks

Hollow skeletal nanomaterials, such as nanoframes and nanocages, represent a class of advanced electrocatalysts and exhibit excellent performance in various electrochemical energy conversion reactions. Their three-dimensional (3D) framework, which allows a high surface-area-to-volume ratio, efficient molecular accessibility, and nanoscale confinement effect, leads to higher catalytic activity compared to solid nanoparticle (NP)-based catalysts without requiring the use of a significant amount of precious metal. In this Perspective, we present notable exemplars of skeletal nanostructures that have demonstrated superior activity over solid NP-based catalysts. In particular, we highlight that the 3D framework in skeletal nanostructures consists of inherently reactive catalytic surfaces and discuss a multitude of factors affecting the excellent performance of skeletal nanocatalysts. We next introduce the design strategies that promote the catalytic activity and durability of skeletal nanostructures, including the strengthening of framework structures and the reorganization of the atomic array in a skeletal nanostructure. Finally, we provide future research directions in this emerging class of catalysts

Estimation of Occupancy Using IoT Sensors and a Carbon Dioxide-Based Machine Learning Model with Ventilation System and Differential Pressure Data

Infectious diseases such as the COVID-19 pandemic have necessitated preventive measures against the spread of indoor infections. There has been increasing interest in indoor air quality (IAQ) management. Air quality can be managed simply by alleviating the source of infection or pollution, but the person within a space can be the source of infection or pollution, thus necessitating an estimation of the exact number of people occupying the space. Generally, management plans for mitigating the spread of infections and maintaining the IAQ, such as ventilation, are based on the number of people occupying the space. In this study, carbon dioxide (CO2)-based machine learning was used to estimate the number of people occupying a space. For machine learning, the CO2 concentration, ventilation system operation status, and indoor–outdoor and indoor–corridor differential pressure data were used. In the random forest (RF) and artificial neural network (ANN) models, where the CO2 concentration and ventilation system operation modes were input, the accuracy was highest at 0.9102 and 0.9180, respectively. When the CO2 concentration and differential pressure data were included, the accuracy was lowest at 0.8916 and 0.8936, respectively. Future differential pressure data will be associated with the change in the CO2 concentration to increase the accuracy of occupancy estimation

Electrophysiological Rotor Ablation in In-Silico Modeling of Atrial Fibrillation: Comparisons with Dominant Frequency, Shannon Entropy, and Phase Singularity.

Although rotors have been considered among the drivers of atrial fibrillation (AF), the rotor definition is inconsistent. We evaluated the nature of rotors in 2D and 3D in- silico models of persistent AF (PeAF) by analyzing phase singularity (PS), dominant frequency (DF), Shannon entropy (ShEn), and complex fractionated atrial electrogram cycle length (CFAE-CL) and their ablation.Mother rotor was spatiotemporally defined as stationary reentries with a meandering tip remaining within half the wavelength and lasting longer than 5 s. We generated 2D- and 3D-maps of the PS, DF, ShEn, and CFAE-CL during AF. The spatial correlations and ablation outcomes targeting each parameter were analyzed.1. In the 2D PeAF model, we observed a mother rotor that matched relatively well with DF (>9 Hz, 71.0%, p5.5 Hz, 39.7%, p<0.001), ShEn (upper 8.5%, 15.1%, p <0.001), and CFAE (lower 8.5%, 8.0%, p = 0.002). 3. In both the 2D and 3D models, virtual ablation targeting the upper 5% of the DF terminated AF within 20 s, but not the ablations based on long-lasting PS, high ShEn area, or lower CFAE-CL area.Mother rotors were observed in both 2D and 3D human AF models. Rotor locations were well represented by DF, and their virtual ablation altered wave dynamics and terminated AF

Multiple factors influence the morphology of the bipolar electrogram: An in silico modeling study.

Although bipolar electrograms (Bi-egms) are commonly used for catheter mapping and ablation of cardiac arrhythmias, the accuracy and reproducibility of Bi-egms have not been evaluated. We aimed to clarify the influence of the catheter orientation (CO), catheter contact angle (CA), local conduction velocity (CV), scar size, and catheter type on the Bi-egm morphology using an in silico 3-dimensional realistic model of atrial fibrillation. We constructed a 3-dimensional, realistic, in silico left atrial model with activation wave propagation including bipolar catheter models. Bi-egms were obtained by computing the extracellular potentials from the distal and proximal electrodes. The amplitude and width were measured on virtual Bi-egms obtained under different conditions created by changing the CO according to the wave direction, catheter-atrial wall CA, local CV, size of the non-conductive area, and catheter type. Bipolar voltages were also compared between virtual and clinically acquired Bi-egms. Bi-egm amplitudes were lower for a perpendicular than parallel CO relative to the wave direction (p<0.001), lower for a 90° than 0° CA (p<0.001), and lower for a CV of 0.13m/s than 0.48m/s (p<0.001). Larger sized non-conductive areas were associated with a decreased bipolar amplitude (p<0.001) and increased bipolar width (p<0.001). Among three commercially available catheters (Orion, Pentaray, and Thermocool), those with more narrowly spaced and smaller electrodes produced higher voltages on the virtual Bi-egms (p<0.001). Multiple factors including the CO, CA, CV, and catheter design significantly influence the Bi-egm morphology. Universal voltage cut-off values may not be appropriate for bipolar voltage-guided substrate mapping

The Contribution of Ionic Currents to Rate-Dependent Action Potential Duration and Pattern of Reentry in a Mathematical Model of Human Atrial Fibrillation.

Persistent atrial fibrillation (PeAF) in humans is characterized by shortening of action potential duration (APD) and attenuation of APD rate-adaptation. However, the quantitative influences of particular ionic current alterations on rate-dependent APD changes, and effects on patterns of reentry in atrial tissue, have not been systematically investigated. Using mathematical models of human atrial cells and tissue and performing parameter sensitivity analysis, we evaluated the quantitative contributions to action potential (AP) shortening and APD rate-adaptation of ionic current remodeling seen with PeAF. Ionic remodeling in PeAF was simulated by reducing L-type Ca2+ channel current (ICaL), increasing inward rectifier K+ current (IK1) and modulating five other ionic currents. Parameter sensitivity analysis, which quantified how each ionic current influenced APD in control and PeAF conditions, identified interesting results, including a negative effect of Na+/Ca2+ exchange on APD only in the PeAF condition. At high pacing rate (2 Hz), electrical remodeling in IK1 alone accounts for the APD reduction of PeAF, but at slow pacing rate (0.5 Hz) both electrical remodeling in ICaL alone (-70%) and IK1 alone (+100%) contribute equally to the APD reduction. Furthermore, AP rate-adaptation was affected by IKur in control and by INaCa in the PeAF condition. In a 2D tissue model, a large reduction (-70%) of ICaL becomes a dominant factor leading to a stable spiral wave in PeAF. Our study provides a quantitative and unifying understanding of the roles of ionic current remodeling in determining rate-dependent APD changes at the cellular level and spatial reentry patterns in tissue

Effects of Anti-Cancer Drug Sensitivity-Related Genetic Differences on Therapeutic Approaches in Refractory Papillary Thyroid Cancer

Thyroid cancer (TC) includes tumors of follicular cells; it ranges from well differentiated TC (WDTC) with generally favorable prognosis to clinically aggressive poorly differentiated TC (PDTC) and undifferentiated TC (UTC). Papillary thyroid cancer (PTC) is a WDTC and the most common type of thyroid cancer that comprises almost 70&ndash;80% of all TC. PTC can present as a solid, cystic, or uneven mass that originates from normal thyroid tissue. Prognosis of PTC is excellent, with an overall 10-year survival rate &gt;90%. However, more than 30% of patients with PTC advance to recurrence or metastasis despite anti-cancer therapy; consequently, systemic therapy is limited, which necessitates expansion of improved clinical approaches. We strived to elucidate genetic distinctions due to patient-derived anti-cancer drug-sensitive or -resistant PTC, which can support in progress novel therapies. Patients with histologically proven PTC were evaluated. PTC cells were gained from drug-sensitive and -resistant patients and were compared using mRNA-Seq. We aimed to assess the in vitro and in vivo synergistic anti-cancer effects of a novel combination therapy in patient-derived refractory PTC. This combination therapy acts synergistically to promote tumor suppression compared with either agent alone. Therefore, genetically altered combination therapy might be a novel therapeutic approach for refractory PTC

A New Efficient Method for Detecting Phase Singularity in Cardiac Fibrillation

<div><p>Background</p><p>The point of phase singularity (PS) is considered to represent a spiral wave core or a rotor in cardiac fibrillation. Computational efficiency is important for detection of PS in clinical electrophysiology. We developed a novel algorithm for highly efficient and robust detection of PS.</p><p>Methods</p><p>In contrast to the conventional method, which calculates PS based on the line integral of the phase around a PS point equal to ±2π (the Iyer-Gray method), the proposed algorithm (the location-centric method) looks for the phase discontinuity point at which PS actually occurs. We tested the efficiency and robustness of these two methods in a two-dimensional mathematical model of atrial fibrillation (AF), with and without remodeling of ionic currents.</p><p>Results</p><p>1. There was a significant association, in terms of the Hausdorff distance (3.30 ± 0.0 mm), between the PS points measured using the Iyer-Gray and location-centric methods, with almost identical PS trajectories generated by the two methods. 2. For the condition of electrical remodeling of AF (0.3 × I_CaL), the PS points calculated by the two methods were satisfactorily co-localized (with the Hausdorff distance of 1.64 ± 0.09 mm). 3. The proposed location-centric method was substantially more efficient than the Iyer-Gray method, with a 28.6-fold and 28.2-fold shorter run times for the control and remodeling scenarios, respectively.</p><p>Conclusion</p><p>We propose a new location-centric method for calculating PS, which is robust and more efficient compared with the conventionally used method.</p></div