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We focused on the quasi-projective synchronization (QPS) and finite-time synchronization (FNTS) for a class of fractional-order memristive complex-valued delay neural networks (FOMCVDNNs). Rather than decomposing the complex-valued system into its real and imaginary components, we adopted a more streamlined approach by introducing a lemma associated with the complex-valued sign function. This innovative technique enabled us to design a simpler discontinuous controller. Then, based on the finite-time Lemma, measurable selection theorem, Lyapunov function theory, properties of the Mittag-Leffler function, and the fractional-order Razumikhin theorem, various substantial results were derived using a novel hybrid control scheme. In conclusion, we presented numerical simulations to illustrate the practical effectiveness of our theoretical findings.

Abstract Background Major depressive disorder (MDD) is a common mental illness that affects millions of people worldwide and imposes a heavy burden on individuals, families and society. Previous studies on MDD predominantly focused on neurons and employed bulk homogenates of brain tissues. This paper aims to decipher the relationship between oligodendrocyte lineage (OL) development and MDD at the single-cell resolution level. Methods Here, we present the use of a guided regularized random forest (GRRF) algorithm to explore single-nucleus RNA sequencing profiles (GSE144136) of the OL at four developmental stages, which contains dorsolateral prefrontal cortex of 17 healthy controls (HC) and 17 MDD cases, generated by Nagy C et al. We prioritized and ordered differentially expressed genes (DEGs) based on Nagy et al., which could predominantly discriminate cells in the four developmental stages and two adjacent developmental stages of the OL. We further screened top-ranked genes that distinguished between HC and MDD in four developmental stages. Moreover, we estimated the performance of the GRRF model via the area under the curve value. Additionally, we validated the pivotal candidate gene Malat1 in animal models. Results We found that, among the four developmental stages, the onset development of OL (OPC2) possesses the best predictive power for distinguishing HC and MDD, and long noncoding RNA MALAT1 has top-ranked importance value in candidate genes of four developmental stages. In addition, results of fluorescence in situ hybridization assay showed that Malat1 plays a critical role in the occurrence of depression. Conclusions Our work elucidates the mechanism of MDD from the perspective of OL development at the single-cell resolution level and provides novel insight into the occurrence of depression.

Based on direct quaternion method, this paper explores the finite-time adaptive synchronization (FAS) of fractional-order delayed quaternion-valued fuzzy neural networks (FODQVFNNs). Firstly, a useful fractional differential inequality is created, which offers an effective way to investigate FAS. Then two novel quaternion-valued adaptive control strategies are designed. By means of our newly proposed inequality, the basic knowledge about fractional calculus, reduction to absurdity as well as several inequality techniques of quaternion and fuzzy logic, several sufficient FAS criteria are derived for FODQVFNNs. Moreover, the settling time of FAS is estimated, which is in connection with the order and initial values of considered systems as well as the controller parameters. Ultimately, the validity of obtained FAS criteria is corroborated by numerical simulations.

This paper addresses the synchronization problem of delayed stochastic neural networks with discontinuous activation functions (DSNNsDF), specifically focusing on fixed/preassigned-time synchronization. The objective is to develop a class of simplified controllers capable of effectively addressing the challenges posed by time delays, discontinuous activation functions, and stochastic perturbations during the synchronization process. In this regard, we propose several controllers with simpler structures to achieve the desired preassigned-time synchronization (PTS) result. To enhance the accuracy of time estimation, stochastic fixed-time control theory is employed. Rigorous numerical simulations are conducted to validate the effectiveness of our approach. The utilization of our proposed results significantly improves the performance of the synchronization controller for DSNNsDF, thereby enabling advancements and diverse applications in the field.

This paper addresses the stability problem of genetic regulatory networks by involving the spatial diffusion of concentration, discrete and infinite distributed delays. By using the theories of partial differential equation and Lyapunov stability, the global exponential stability criteria in algebraic form are derived for reaction diffusion genetic regulatory networks (RDGRNs) with discrete and distributed delays. The derived stability conditions are simple and can be directly calculated by using the parameters of the networks. Moreover, the theoretical results are universal and can be applied to deal with the stability problem of RDGRNs with or without distributed delays. Eventually, the validity and feasibility of the results are illustrated by numerical simulations.

In this paper, the diffusion effect, distributed delays and stochastic disturbance are involved in constructing the model of neural networks. Then, the global exponential synchronization problem is investigated for a class of reaction diffusion neural networks (RDNNs) with infinite distributed delays and stochastic disturbance. By employing the stochastic analysis method and Lyapunov functional theory, an adaptive controller is designed to guarantee the exponential synchronization of the drive and response RDNNs. The derived synchronization conditions are simple and the theoretical results can be directly extended to other RDNNs with or without distributed delays and stochastic disturbance. Finally, one example is provided to verify the effectiveness of the theoretical results and adaptive control approach.

In this paper, the delay-dependent stability of haptic systems is studied by developing a new stability criterion. Firstly, the haptic system inevitably introduces time delays by using communication networks to transmit information between the controller and the haptic device. When discussing the stability of the haptic system near its operating point, the original nonlinear system is modeled as a linear system with the time delay mentioned above. In addition, a suitable augmented Lyapunov–Krasovskii functional (LKF) with more integral forms is constructed and an auxiliary function-based integral inequality is applied to estimate the derivative of the proposed LKF. Then, a less conservative delay-dependent criterion in terms of the linear matrix inequality (LMI) is derived to calculate the delay margin for the haptic system. Finally, case studies are carried out based on a one degree of freedom haptic system. The results show that, compared with criteria in existing works, the proposed criterion can obtain more accurate results and require less calculation complexity, and, with the increase in virtual damping in a certain range, the stable upper bound of the haptic system increases at first and then decreases.

Background/Aims: Acute myocardial infarction (AMI) is a devastating cardiovascular disease with a high rate of morbidity and mortality, partly due to enhanced arrhythmogenicity. MicroRNAs (miRNAs) have been shown to participate in the regulation of cardiac ion channels and the associated arrhythmias. The purpose of this study was to test our hypothesis that miR-223-3p contributes to the electrical disorders in AMI via modulating KCND2, the gene encoding voltage-gated channel Kv4.2 that carries transient outward K+ current Ito. Methods: AMI model was established in male Sprague-Dawley (SD) rats by left anterior descending artery (LAD) ligation. Evans blue and TTC staining was used to measure infarct area. Ito was recorded in isolated ventricular cardiomyocytes or cultured neonatal rat ventricular cells (NRVCs) by whole-cell patch-clamp techniques. Western blot analysis was employed to detect the protein level of Kv4.2 and real-time RT-PCR to determine the transcript level of miR-223-3p. Luciferase assay was used to examine the interaction between miR-223-3p and KCND2 in cultured NRVCs. Results: Expression of miR-223-3p was remarkably upregulated in AMI relative to sham control rats. On the contrary, the protein level of Kv4.2 and Ito density were significantly decreased in AMI. Consistently, transfection of miR-223-3p mimic markedly reduced Kv4.2 protein level and Ito current in cultured NRVCs. Co-transfection of AMO-223-3p (an antisense inhibitor of miR-223-3p) reversed the repressive effect of miR-223-3p. Luciferase assay showed that miR-223-3p, but not the negative control, substantially suppressed the luciferase activity, confirming the direct binding of miR-223-3p to the seed site within the KCND2 sequence. Finally, direct intramuscular injection of AMO-223-3p into the ischemic myocardium to knockdown endogenous miR-223-3p decreased the propensity of ischemic arrhythmias. Conclusions: Upregulation of miR-223-3p in AMI repressed the expression of KCND2/Kv4.2 resulting in reduction of Ito density that can cause APD prolongation and promote arrhythmias in AMI, and therefore knockdown of endogenous miR-223-3p might be considered a new approach for antiarrhythmic therapy of ischemic arrhythmias.

Background: Several studies have confirmed the role of microRNAs in regulating ischemia/reperfusion-induced cardiac injury (I/R-I). MiR-17-5p has been regarded as an oncomiR in the development of cancer. However, its potential role in cardiomyocytes has not been exploited. The aim of this study is to investigate the role of miR-17-5p in I/R-I and the underlying mechanism through targeting Stat3, a key surviving factor in cardiomyocytes. Methods: MTT (3-[4, 5-dimethylthiazol-2-yl]-2, 5 diphenyl tetrazolium bromide) assay was used to detect the cell viability. ELISA and TUNEL were performed to measure apoptosis of neonatal rat ventricular cardiomyocytes (NRVCs). Infarct area was estimated by TTC (triphenyltetrazolium chloride) and Evans blue staining. Western blot analysis was employed to detect the Stat3 and p-Stat3 levels and real-time RT-PCR was used to quantify miR-17-5p level. Results: The miR-17-5p level was significantly up-regulated in I/R-I mice and in NRVCs under oxidative stress. Overexpression of miR-17-5p aggravated cardiomyocyte injury with reduced cell viability and enhanced apoptotic cell death induced by H2O2, whereas inhibition of miR-17-5p by its antisense AMO-17-5p abrogated the deleterious changes. Moreover, the locked nucleic acid-modified antisense (LNA-anti-miR-17-5p) markedly decreased the infarct area and apoptosis induced by I/R-I in mice. Furthermore, overexpression of miR-17-5p diminished the p-Stat3 level in response to H2O2. The results from Western blot analysis and luciferase reporter gene assay confirmed Stat3 as a target gene for miR-17-5p. Conclusion: Upregulation of miR-17-5p promotes apoptosis induced by oxidative stress via targeting Stat3, accounting partially for I/R-I.

Aims: microRNA-101 (miR-101) is down-regulated in several cancers. In this study, we explored the effects of dysregulated miR-101 on breast cancer cells and the underlying mechanisms. Methods: miR-101 level was quantified by real-time RT-PCR. Cell viability was analyzed by MTT assay. Apoptosis was detected by flow cytometry and TUNEL assay. Moreover, the level of protein expression was determined by Western blot. Results: miR-101 level was markedly reduced in both the human breast cancer samples and cultured breast cancer cell lines (MCF-7, MDA-MB-231). Overexpression of miR-101 inhibited the proliferation and promoted the apoptosis in cultured MCF-7 and MDA-MB-231 cells, which were reversed by co-transfection of AMO-101, the inhibitor of miR-101. We validated Janus kinase 2 (Jak2) as a direct target of miR-101. Knockdown of Jak2 induced apoptosis in cultured breast cancer cells. Moreover, the level of miR-101 is negatively correlated with Jak2 in breast cancer tissues and cell lines. Conclusions: miR-101 suppressed proliferation and promoted apoptosis in breast cancer cells by targeting Jak2. These findings indicate that manipulation of miR-101 expression may represent a novel therapeutic strategy in the treatment of breast cancer.