Temporal Association Between Vaping and Risk of Cardiac Events.

OBJECTIVE: To describe our early observations with sudden cardiac arrest (SCA) and sudden death (SD) in patients using vape products. PATIENTS AND METHODS: A retrospective analysis of Mayo Clinic's Windland Smith Rice Genetic Heart Rhythm Clinic and Sudden Death Genomics Laboratory was performed on all SCA survivors and decedents who presented between January 1, 2007, and December 31, 2021, to identify patients/decedents with a history of vaping. Data abstraction included patient demographics, clinical characteristics, and documented use of vape products. RESULTS: Among 144 SCA survivors and 360 SD victims, there were six individuals (1%; 3 females) with unexplained SCA (n=4) or SD (n=2) that was temporally associated with vaping use with a mean age at sentinel event of 23±5 years. The SCA survivors include a 19-year-old male who was resuscitated from documented ventricular fibrillation 40 minutes after vaping and a 19-year-old male who was resuscitated from ventricular fibrillation a few hours post vaping. The first SD victim was a 19-year-old female with exercise-induced asthma who died in her sleep after vaping that evening. Autopsy results showed eosinophilic infiltrates in the lung tissue and death was attributed to bronchial asthma. The second vaping-associated death involved a 26-year-old male whose autopsy attributed the death to acute respiratory distress syndrome. CONCLUSION: We have identified six young individuals with a history of vaping who experienced a near fatal episode or a tragic SD. Although larger cohort studies are needed to quantify the actual risk of SD, it seems prudent to sound an early warning about vaping's potential lethality.

Clinical Utility of Protein Language Models in Resolution of Variants of Uncertain Significance in KCNQ1, KCNH2, and SCN5A Compared With Patch-Clamp Functional Characterization.

BACKGROUND: Genetic testing for cardiac channelopathies is the standard of care. However, many rare genetic variants remain classified as variants of uncertain significance (VUS) due to lack of epidemiological and functional data. Whether deep protein language models may aid in VUS resolution remains unknown. Here, we set out to compare how 2 deep protein language models perform at VUS resolution in the 3 most common long-QT syndrome-causative genes compared with the gold-standard patch clamp. METHODS: A total of 72 rare nonsynonymous VUS (9 KCNQ1, 19 KCNH2, and 50 SCN5A) were engineered by site-directed mutagenesis and expressed in either HEK293 cells or TSA201 cells. Whole-cell patch-clamp technique was used to functionally characterize these variants. The protein language models, evolutionary scale modeling, version 1b and AlphaMissense, were used to predict the variant effect of missense variants and compared with patch clamp. RESULTS: Considering variants in all 3 genes, the evolutionary scale modeling, version 1b model had a receiver operating characteristic curve-area under the curve of 0.75 (P=0.0003). It had a sensitivity of 88% and a specificity of 50%. AlphaMissense performed well compared with patch-clamp with an receiver operating characteristic curve-area under the curve of 0.85 (P<0.0001), sensitivity of 80%, and specificity of 76%. CONCLUSIONS: Deep protein language models aid in VUS resolution with high sensitivity but lower specificity. Thus, these tools cannot fully replace functional characterization but can aid in reducing the number of variants that may require functional analysis.

Multifocal Ectopic Purkinje Premature Contractions due to neutralization of an SCN5A negative charge: structural insights into the gating pore hypothesis.

Background: We identified a novel SCN5A variant, E171Q, in a neonate with very frequent ectopy and reduced ejection fraction which normalized after arrhythmia suppression by flecainide. This clinical picture is consistent with multifocal ectopic Purkinje-related premature contractions (MEPPC). Most previous reports of MEPPC have implicated SCN5A variants such as R222Q that neutralize positive charges in the S4 voltage sensor helix of the channel protein NaV1.5 and generate a gating pore current. Methods and Results: E171 is a highly conserved negatively-charged residue located in the S2 transmembrane helix of NaV1.5 domain I. E171 is a key component of the Gating Charge Transfer Center, a region thought to be critical for normal movement of the S4 voltage sensor helix. We used heterologous expression, CRISPR-edited induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs), and molecular dynamics simulations to demonstrate that E171Q generates a gating pore current, which was suppressed by a low concentration of flecainide (IC50 = 0.71±0.07 µM). R222Q shifts voltage dependence of activation and inactivation in a negative direction but we observed positive shifts with E171Q. E171Q iPSC-CMs demonstrated abnormal spontaneous activity and prolonged action potentials. Molecular dynamics simulations revealed that both R222Q and E171Q proteins generate a water-filled permeation pathway that underlies generation of the gating pore current. Conclusion: Previously identified MEPPC-associated variants that create gating pore currents are located in positively-charged residues in the S4 voltage sensor and generate negative shifts in the voltage dependence of activation and inactivation. We demonstrate that neutralizing a negatively charged S2 helix residue in the Gating Charge Transfer Center generates positive shifts but also create a gating pore pathway. These findings implicate the gating pore pathway as the primary functional and structural determinant of MEPPC and widen the spectrum of variants that are associated with gating pore-related disease in voltage-gated ion channels.

Q-Learning-Based Hyperheuristic Evolutionary Algorithm for Dynamic Task Allocation of Crowdsensing.

Task allocation is a crucial issue of mobile crowdsensing. The existing crowdsensing systems normally select the optimal participants giving no consideration to the sudden departure of mobile users, which significantly affects the sensing quality of tasks with a long sensing period. Furthermore, the ability of a mobile user to collect high-precision data is commonly treated as the same for different types of tasks, causing the unqualified data for some tasks provided by a competitive user. To address the issue, a dynamic task allocation model of crowdsensing is constructed by considering mobile user availability and tasks changing over time. Moreover, a novel indicator for comprehensively evaluating the sensing ability of mobile users collecting high-quality data for different types of tasks at the target area is proposed. A new Q -learning-based hyperheuristic evolutionary algorithm is suggested to deal with the problem in a self-learning way. Specifically, a memory-based initialization strategy is developed to seed a promising population by reusing participants who are capable of completing a particular task with high quality in the historical optima. In addition, taking both sensing ability and cost of a mobile user into account, a novel comprehensive strength-based neighborhood search is introduced as a low-level heuristic (LLH) to select a substitute for a costly participant. Finally, based on a new definition of the state, a Q -learning-based high-level strategy is designed to find a suitable LLH for each state. Empirical results of 30 static and 20 dynamic experiments expose that this hyperheuristic achieves superior performance compared to other state-of-the-art algorithms.

Functional characterization and identification of a therapeutic for a novel SCN5A-F1760C variant causing type 3 long QT syndrome refractory to all guideline-directed therapies.

BACKGROUND: Pathogenic variants in the SCN5A-encoded Nav1.5 sodium channel cause type 3 long QT syndrome (LQT3). We present the case of an infant with severe LQT3 who was refractory to multiple pharmacologic therapies as well as bilateral stellate ganglionectomy. The patient's novel variant, p.F1760C-SCN5A, involves a critical residue of the Nav1.5's local anesthetic binding domain. OBJECTIVE: The purpose of this study was to characterize functionally the p.F1760C-SCN5A variant using TSA-201 and patient-specific induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). METHODS: Whole-cell patch clamp was used to assess p.F1760C-SCN5A associated sodium currents with/without lidocaine (Lido), flecainide, and phenytoin (PHT) in TSA-201 cells. p.F1760C-SCN5A and CRISPR-Cas9 variant-corrected isogenic control (IC) iPSC-CMs were generated. FluoVolt voltage dye was used to measure the action potential duration (APD) with/without mexiletine or PHT. RESULTS: V1/2 of inactivation was right-shifted significantly in F1760C cells (-72.2 ± 0.7 mV) compared to wild-type (WT) cells (-86.3 ± 0.9 mV; P <.0001) resulting in a marked increase in window current. F1760C increased sodium late current 2-fold from 0.18% ± 0.04% of peak in WT to 0.49% ± 0.07% of peak in F1760C (P = .0005). Baseline APD to 90% repolarization (APD90) was increased markedly in F1760C iPSC-CMs (601 ± 4 ms) compared to IC iPSC-CMs (423 ± 15 ms; P <.0001). However, 4-hour treatment with 10 µM mexiletine failed to shorten APD90, and treatment with 5µM PHT significantly decreased APD90 of F1760C iPSC-CMs (453 ± 6 ms; P <.0001). CONCLUSION: PHT rescued electrophysiological phenotype and APD of a novel p.F1760C-SCN5A variant. The antiepileptic drug PHT may be an effective alternative therapeutic for the treatment of LQT3, especially for variants that disrupt the Lido/mexiletine binding site.

Injectable contraceptive Depo-Provera induces erratic beating patterns in patient-specific induced pluripotent stem cell-derived cardiomyocytes with long QT syndrome type 2.

BACKGROUND: Long QT syndrome type 2 (LQT2) is caused by pathogenic variants in KCNH2. LQT2 may manifest as QT prolongation on an electrocardiogram and present with arrhythmic syncope/seizures and sudden cardiac arrest/death. Progestin-based oral contraceptives may increase the risk of LQT2-triggered cardiac events in women. We previously reported on a woman with LQT2 and recurrent cardiac events temporally related and attributed to the progestin-based contraceptive medroxyprogesterone acetate ("Depo-Provera" [Depo] MilliporeSigma, Catalog# 1378001, St. Louis, MO). OBJECTIVE: The purpose of this study was to evaluate the arrhythmic risk of Depo in a patient-specific induced pluripotent stem cell-derived cardiomyocyte (iPSC-CM) model of LQT2. METHODS: An iPSC-CM line was generated from a 40-year-old woman with p.G1006Afs∗49-KCNH2. A CRISPR/Cas9 gene-edited/variant-corrected isogenic control iPSC-CM line was generated. FluoVolt (Invitrogen, F10488, Waltham, MA) was used to measure the action potential duration after treatment with 10 µM Depo. Erratic beating patterns characterized as alternating spike amplitudes, alternans, or early afterdepolarization-like phenomena were assessed using multielectrode array (MEA) after 10 µM Depo, 1 µM isoproterenol (ISO), or combined Depo + ISO treatment. RESULTS: Depo treatment shortened the action potential duration at 90% repolarization of G1006Afs∗49 iPSC-CMs from 394 ± 10 to 303 ± 10 ms (P < .0001). Combined Depo + ISO treatment increased the percentage of electrodes displaying erratic beating in G1006Afs∗49 iPSC-CMs (baseline: 18% ± 5% vs Depo + ISO: 54% ± 5%; P < .0001) but not in isogenic control iPSC-CMs (baseline: 0% ± 0% vs Depo + ISO: 10% ± 3%; P = .9659). CONCLUSION: This cell study provides a potential mechanism for the patient's clinically documented Depo-associated episodes of recurrent ventricular fibrillation. This in vitro data should prompt a large-scale clinical assessment of Depo's potential proarrhythmic effect in women with LQT2.

SGK1 inhibition attenuated the action potential duration in patient- and genotype-specific re-engineered heart cells with congenital long QT syndrome.

Background: Long QT syndrome (LQTS) stems from pathogenic variants in KCNQ1 (LQT1), KCNH2 (LQT2), or SCN5A (LQT3) and is characterized by action potential duration (APD) prolongation. Inhibition of serum and glucocorticoid regulated kinase-1 (SGK1) is proposed as a novel therapeutic for LQTS. Objective: The study sought to test the efficacy of novel, selective SGK1 inhibitors in induced pluripotent stem cell-derived cardiomyocyte (iPSC-CM) models of LQTS. Methods: The mexiletine (MEX)-sensitive SCN5A-P1332L iPSC-CMs were tested initially compared with a CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9 SCN5A-P1332L variant-corrected isogenic control (IC). The SGK1-I1 therapeutic efficacy, compared with MEX, was tested for APD at 90% repolarization (APD90) shortening in SCN5A-P1332L, SCN5A-R1623Q, KCNH2-G604S, and KCNQ1-V254M iPSC-CMs using FluoVolt. Results: The APD90 was prolonged in SCN5A-P1332L iPSC-CMs compared with its IC (646 ± 7 ms vs 482 ± 23 ms; P < .0001). MEX shortened the APD90 to 560 ± 7 ms (52% attenuation, P < .0001). SGK1-I1 shortened the APD90 to 518 ± 5 ms (78% attenuation, P < .0001) but did not shorten the APD90 in the IC. SGK1-I1 shortened the APD90 of the SCN5A-R1623Q iPSC-CMs (753 ± 8 ms to 475 ± 19 ms compared with 558 ± 19 ms with MEX), the KCNH2-G604S iPSC-CMs (666 ± 10 ms to 574 ± 18 ms vs 538 ± 15 ms after MEX), and the KCNQ1-V254M iPSC-CMs (544 ± 10 ms to 475 ± 11ms; P = .0004). Conclusions: Therapeutically inhibiting SGK1 effectively shortens the APD in human iPSC-CM models of the 3 major LQTS genotypes. These preclinical data support development of SGK1 inhibitors as novel, first-in-class therapy for patients with congenital LQTS.

An Immersive Human-Robot Interactive Game Framework Based on Deep Learning for Children's Concentration Training.

In order to alleviate bottlenecks such as the lack of professional teachers, inattention during training processes, and low effectiveness in concentration training, we have proposed an immersive human-robot interactive (HRI) game framework based on deep learning for children's concentration training and demonstrated its use through human-robot interactive games based on gesture recognition. The HRI game framework includes four functional modules: video data acquisition, image recognition modeling, a deep learning algorithm (YOLOv5), and information feedback. First, we built a gesture recognition model containing 10,000 pictures of children's gestures, using the YOLOv5 algorithm. The average accuracy in recognition trainingwas 98.7%. Second, we recruited 120 children with attention deficits (aged from 9 to 12 years) to play the HRI games, including 60 girls and 60 boys. In the HRI game experiment, we obtained 8640 sample data, which were normalized and processed.According to the results, we found that the girls had better visual short-term memory and a shorter response time than boys. The research results showed that HRI games had a high efficacy, convenience, and full freedom, making them appropriate for children's concentration training.

A Fast Hybrid Feature Selection Based on Correlation-Guided Clustering and Particle Swarm Optimization for High-Dimensional Data.

The "curse of dimensionality" and the high computational cost have still limited the application of the evolutionary algorithm in high-dimensional feature selection (FS) problems. This article proposes a new three-phase hybrid FS algorithm based on correlation-guided clustering and particle swarm optimization (PSO) (HFS-C-P) to tackle the above two problems at the same time. To this end, three kinds of FS methods are effectively integrated into the proposed algorithm based on their respective advantages. In the first and second phases, a filter FS method and a feature clustering-based method with low computational cost are designed to reduce the search space used by the third phase. After that, the third phase applies oneself to finding an optimal feature subset by using an evolutionary algorithm with the global searchability. Moreover, a symmetric uncertainty-based feature deletion method, a fast correlation-guided feature clustering strategy, and an improved integer PSO are developed to improve the performance of the three phases, respectively. Finally, the proposed algorithm is validated on 18 publicly available real-world datasets in comparison with nine FS algorithms. Experimental results show that the proposed algorithm can obtain a good feature subset with the lowest computational cost.

Colorectal polyp region extraction using saliency detection network with neutrosophic enhancement.

Colorectal polyp recognition is crucial for early colorectal cancer detection and treatment. Colonoscopy is always employed for colorectal polyp scanning. However, one out of four polyps may be ignored, due to the similarity of polyp and normal tissue. In this paper, we present a novel method called NeutSS-PLP for polyp region extraction in colonoscopy images using a short connected saliency detection network with neutrosophic enhancement. We first utilize the neutrosophic theory to enhance the quality of specular reflections detection in the colonoscopy images. We develop the local and global threshold criteria in the single-valued neutrosophic set (SVNS) domain and define the corresponding T (Truth), I (Indeterminacy), and F (Falsity) functions for each criterion. The well-built neutrosophic images are processed and employed for specular reflection detection and suppressing. Next, we introduce two-level short connections into the saliency detection network, aiming to take advantage of the multi-level and multi-scale features extracted from different stages of the network. Experimental results conducted on two public colorectal polyp datasets achieve 0.877 and 0.9135 mIoU for polyp extraction respectively, and our method performs better compared with several state-of-the-art saliency networks and semantic segmentation networks, which demonstrate the effectiveness of applying the saliency detection mechanism for colorectal polyp region extraction.

Impacts of Human Robot Proxemics on Human Concentration-Training Games with Humanoid Robots.

The use of humanoid robots within a therapeutic role, that is, helping individuals with social disorders, is an emerging field, but it remains unexplored in terms of concentration training. To seamlessly integrate humanoid robots into concentration games, an investigation into the impacts of human robot interactive proxemics on concentration-training games is particularly important. In the case of an epidemic diffusion especially-for example, during the COVID-19 pandemic-HRI games may help in the therapeutic phase, significantly reducing the risk of contagion. In this paper, concentration games were designed by action imitation involving 120 participants to verify the hypothesis. Action-imitation accuracy, the assessment of emotional expression, and a questionnaire were compared with analysis of variance (ANOVA). Experimental results showed that a 2 m distance and left-front orientation for a human and a robot are optimal for human robot interactive concentration training. In addition, females worked better than males did in HRI imitation games. This work supports some valuable suggestions for the development of HRI concentration-training technology, involving the designs of friendlier and more useful robots, and HRI game scenarios.

Performance Analysis of Radial Basis Function Metamodels for Predictive Modelling of Laminated Composites.

High-fidelity structural analysis using numerical techniques, such as finite element method (FEM), has become an essential step in design of laminated composite structures. Despite its high accuracy, the computational intensiveness of FEM is its serious drawback. Once trained properly, the metamodels developed with even a small training set of FEM data can be employed to replace the original FEM model. In this paper, an attempt is put forward to investigate the utility of radial basis function (RBF) metamodels in the predictive modelling of laminated composites. The effectiveness of various RBF basis functions is assessed. The role of problem dimensionality on the RBF metamodels is studied while considering a low-dimensional (2-variable) and a high-dimensional (16-variable) problem. The effect of uniformity of training sample points on the performance of RBF metamodels is also explored while considering three different sampling methods, i.e., random sampling, Latin hypercube sampling and Hammersley sampling. It is observed that relying only on the performance metrics, such as cross-validation error that essentially reuses training samples to assess the performance of the metamodels, may lead to ill-informed decisions. The performance of metamodels should also be assessed based on independent test data. It is further revealed that uniformity in training samples would lead towards better trained metamodels.

Comparison of NSGA-II, MOALO and MODA for Multi-Objective Optimization of Micro-Machining Processes.

The popularity of micro-machining is rapidly increasing due to the growing demands for miniature products. Among different micro-machining approaches, micro-turning and micro-milling are widely used in the manufacturing industry. The various cutting parameters of micro-turning and micro-milling has a significant effect on the machining performance. Thus, it is essential that the cutting parameters are optimized to obtain the most from the machining process. However, it is often seen that many machining objectives have conflicting parameter settings. For example, generally, a high material removal rate (MRR) is accompanied by high surface roughness (SR). In this paper, metaheuristic multi-objective optimization algorithms are utilized to generate Pareto optimal solutions for micro-turning and micro-milling applications. A comparative study is carried out to assess the performance of non-dominated sorting genetic algorithm II (NSGA-II), multi-objective ant lion optimization (MOALO) and multi-objective dragonfly optimization (MODA) in micro-machining applications. The complex proportional assessment (COPRAS) method is used to compare the NSGA-II, MOALO and MODA generated Pareto solutions.

Generalized cure rate model for infectious diseases with possible co-infections.

This research mainly aims to develop a generalized cure rate model, estimate the proportion of cured patients and their survival rate, and identify the risk factors associated with infectious diseases. The generalized cure rate model is based on bounded cumulative hazard function, which is a non-mixture model, and is developed using a two-parameter Weibull distribution as the baseline distribution, to estimate the cure rate using maximum likelihood method and real data with R and STATA software. The results showed that the cure rate of tuberculosis (TB) patients was 26.3%, which was higher than that of TB patients coinfected with human immunodeficiency virus (HIV; 23.1%). The non-parametric median survival time of TB patients was 51 months, while that of TB patients co-infected with HIV was 33 months. Moreover, no risk factors were associated with TB patients co-infected with HIV, while age was a significant risk factor for TB patients among the suspected risk factors considered. Furthermore, the bounded cumulative hazard function was extended to accommodate infectious diseases with co-infections by deriving an appropriate probability density function, determining the distribution, and using real data. Governments and related health authorities are also encouraged to take appropriate actions to combat infectious diseases with possible co-infections.

Negligible-Cost and Weekend-Free Chemically Defined Human iPSC Culture.

Human induced pluripotent stem cell (hiPSC) culture has become routine, yet the cost of pluripotent cell media, frequent medium changes, and the reproducibility of differentiation have remained restrictive. Here, we describe the formulation of a hiPSC culture medium (B8) as a result of the exhaustive optimization of medium constituents and concentrations, establishing the necessity and relative contributions of each component to the pluripotent state and cell proliferation. The reagents in B8 represent only 3% of the costs of commercial media, made possible primarily by the in-lab generation of three E. coli-expressed, codon-optimized recombinant proteins: fibroblast growth factor 2, transforming growth factor ß3, and neuregulin 1. We demonstrate the derivation and culture of 34 hiPSC lines in B8 as well as the maintenance of pluripotency long term (over 100 passages). This formula also allows a weekend-free feeding schedule without sacrificing capacity for differentiation.

Prospective cohort study of the safety of an influenza A(H1N1) vaccine in pregnant Chinese women.

To monitor and evaluate the safety of the influenza A(H1N1) vaccine in pregnant women and its influence on the fetus and neonate, we performed a prospective study in which 122 pregnant Chinese women who received the influenza A(H1N1) vaccine and 104 pregnant women who did not receive any vaccine (serving as controls) were observed. The results indicated that the seroconversion rate in the vaccinated group was 90.4% (95% confidence interval [CI], 82.6% to 95.5%). The rate of adverse events following immunization in the pregnant women who received the influenza A(H1N1) vaccine was 3.3%. The spontaneous abortion rates in the vaccinated group and the unvaccinated group were 0.8% and 1.9%, respectively (exact probability test, P = 0.470), the prolonged-pregnancy rates were 8.2% and 4.8%, respectively (χ(2) = 1.041, P = 0.308), the low-birth-weight rates were 1.6% and 0.95%, respectively (exact probability test, P = 1.000), and the spontaneous-labor rates were 70.5% and 75%, respectively (χ(2) = 0.573, P = 0.449). All newborns who have an Apgar score of ≥7 are considered healthy; Apgar scores of ≥9 were observed in 38.5% and 57.7% of newborns in the vaccinated group and the unvaccinated group, respectively (χ(2) = 8.274, P = 0.004). From these results, we conclude that the influenza A(H1N1) vaccine is safe for pregnant women and has no observed adverse effects on fetal growth. (This study has been registered at ClinicalTrials.gov under registration no. NCT01842997.).