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Aim: Transcatheter mitral valve-in-valve (TMViV) replacement for degenerated surgically implanted bioprosthetic valves has been described by both transseptal and transapical approaches. The balloon-expandable Myval transcatheter valve (Meril Life Sciences, Vapi, India) is commonly used for transcatheter valve-in-valve procedures in India. This study aimed to report in-hospital, 30-day, and 1-year outcomes of Myval patients who underwent TMViV in a single tertiary care centre in India., Methods: Symptomatic patients with surgical bioprosthetic mitral valve failure with New York Heart Association (NYHA) class III-IV symptoms, despite optimal medical therapy and high or very high risk for redo surgery, were assigned to TMViV following heart team discussions. Data were retrospectively collected and outcomes assessed., Results: Twenty patients were treated, with mean age 64.4 years, 60% were female, and mean Society of Thoracic Surgeons (STS) predicted risk of operative mortality score was 8.1. The failure mechanism was combined stenosis and regurgitation in 60% of patients. Technical success was achieved in 100% of patients. The mean postprocedure and 30-day gradients were 4.6±2.7 and 6.3±2.1, respectively. None of them had significant valvular or paravalvular leaks or left ventricular outflow tract obstruction. All-cause mortality at 1 year was 10%, and all survivors were in New York Heart Association (NYHA) class I or II., Conclusion: TMViV replacement with a Meril Myval can be safely performed with high technical success, and low 30-day and 1-year mortality., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

The projective synchronization work presented in this article is focused on a class of nonlinear discontinuous coupled inertial neural networks with mixed time-varying delays and a cluster topological structure. The synchronization problem for discontinuous coupled inertial neural networks with clustering topology is examined in consideration with the mismatched parameters and the mutual influence among various clusters. To determine the required conditions for network convergence under the influence of an extensive range of impulses, the matrix measure technique and the average impulsive intervals are employed. To illustrate the effectiveness of the theoretical findings, graphical representation of varied impulsive ranges for multiple cases are provided using numerical simulations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 ISA. Published by Elsevier Ltd. All rights reserved.)

Herein, we discuss an optimal control problem (OC-P) of a stochastic delay differential model to describe the dynamics of tumor-immune interactions under stochastic white noises and external treatments. The required criteria for the existence of an ergodic stationary distribution and possible extinction of tumors are obtained through Lyapunov functional theory. A stochastic optimality system is developed to reduce tumor cells using some control variables. The study found that combining white noises and time delays greatly affected the dynamics of the tumor-immune interaction model. Based on numerical results, it can be shown which variables are optimal for controlling tumor growth and which controls are effective for reducing tumor growth. With some conditions, white noise reduces tumor cell growth in the optimality problem. Some numerical simulations are conducted to validate the main results.

The dynamical study of continuous-/discontinuous-time fractional-order neural networks (FONNs) has been thoroughly explored, and several publications have been made available. This study is designed to give an exhaustive review of the dynamical studies of multidimensional FONNs in continuous/discontinuous time, including Hopfield NNs (HNNs), Cohen-Grossberg NNs, and bidirectional associative memory NNs, and similar models are considered in real ( [Formula: see text]), complex ( [Formula: see text]), quaternion ( [Formula: see text]), and octonion ( [Formula: see text]) fields. Since, in practice, delays are unavoidable, theoretical findings from multidimensional FONNs with various types of delays are thoroughly evaluated. Some required and adequate stability and synchronization requirements are also mentioned for fractional-order NNs without delays.

In this article, we discuss bipartite fixed-time synchronization for fractional-order signed neural networks with discontinuous activation patterns. The Filippov multi-map is used to convert the fixed-time stability of the fractional-order general solution into the zero solution of the fractional-order differential inclusions. On the Caputo fractional-order derivative, Lyapunov-Krasovskii functional is proved to possess the indefinite fractional derivatives for fixed-time stability of fragmentary discontinuous systems. Furthermore, the fixed-time stability of the fractional-order discontinuous system is achieved as well as an estimate of the new settling time.. The discontinuous controller is designed for the delayed fractional-order discontinuous signed neural networks with antagonistic interactions and new conditions for permanent fixed-time synchronization of these networks with antagonistic interactions are also provided, as well as the settling time for permanent fixed-time synchronization. Two numerical simulation results are presented to demonstrate the effectiveness of the main results., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Ltd. All rights reserved.)