Delay-Distribution-Dependent Consensus for Second-Order Leader-Follower Nonlinear Multiagent Systems via Pinning Control

This paper investigates the consensus problem for second-order leader-follower nonlinear multiagent systems with general network topologies. A pinning control algorithm is proposed, where it includes time-varying delay information. By using the information of delay-partition and delay-distribution and constructing an appropriate Lyapunov-Krasovskii functional, the consensus criteria are derived to achieve leader-follower consensus for multiagent systems, which are in the form of linear inequalities that can be solved by employing the semidefinite programme method. Moreover, this paper addresses what kind of agents and how many agents should be pinned. Two numerical examples are presented to further demonstrate the effectiveness of the proposed approach

Effects of a novel pH-sensitive liposome with cleavable esterase-catalyzed and pH-responsive double smart mPEG lipid derivative on ABC phenomenon

Daquan Chen1,2, Wanhui Liu1,2, Yan Shen3, Hongjie Mu1,2, Yanchun Zhang4 , Rongcai Liang1,2, Aiping Wang1,2, Kaoxiang Sun1,2, Fenghua Fu1,2 1School of Pharmacy, Yantai University, Yantai, People’s Republic of China; 2State Key Laboratory of Long-acting and Targeting Drug Delivery System, Yantai, People’s Republic of China; 3College of Pharmacy, China Pharmaceutical University, Nanjing, People’s Republic of China; 4College of Pharmacy, Anhui University of Traditional Chinese Medicine, Hefei, People’s Republic of China Background: The ABC phenomenon is described as a syndrome of accelerated clearance of polyethylene glycol (PEG)-modified liposomes from the bloodstream when repeatedly injected, with their increased accumulation in the liver and spleen. Methods: To clarify this immune response phenomenon, we evaluated a novel modified pH-sensitive liposome with a cleavable double smart PEG-lipid derivative (mPEG-Hz-CHEMS). Results: The ABC phenomenon in mice was brought about by repeated injection of conventional PEG-PE liposomes and was accompanied by a greatly increased uptake in the liver. However, a slight ABC phenomenon was brought about by repeated injection of mPEG-CHEMS liposomes and was accompanied by only a slightly increased uptake in the liver, and repeated injection of mPEG-Hz-CHEMS liposomes did not induce the ABC phenomenon and there was no increase in liver accumulation. This finding indicates that the cleavable mPEG-Hz-CHEMS derivative could lessen or eliminate the ABC phenomenon induced by repeated injection of PEGylated liposomes. Conclusion: This research has shed some light on a solution to the ABC phenomenon using a cleavable PEG-Hz-CHEMS derivative encapsulated in nanoparticles. Keywords: accelerated blood clearance, double smart, cleavable, mPEG-lipid derivates, pH-sensitive liposom

A Game-Theoretic Response Strategy for Coordinator Attack in Wireless Sensor Networks

The coordinator is a specific node that controls the whole network and has a significant impact on the performance in cooperative multihop ZigBee wireless sensor networks (ZWSNs). However, the malicious node attacks coordinator nodes in an effort to waste the resources and disrupt the operation of the network. Attacking leads to a failure of one round of communication between the source nodes and destination nodes. Coordinator selection is a technique that can considerably defend against attack and reduce the data delivery delay, and increase network performance of cooperative communications. In this paper, we propose an adaptive coordinator selection algorithm using game and fuzzy logic aiming at both minimizing the average number of hops and maximizing network lifetime. The proposed game model consists of two interrelated formulations: a stochastic game for dynamic defense and a best response policy using evolutionary game formulation for coordinator selection. The stable equilibrium best policy to response defense is obtained from this game model. It is shown that the proposed scheme can improve reliability and save energy during the network lifetime with respect to security

Efficacy of adjunctive azithromycin versus single-dose cephalosporin prophylaxis for caesarean scar defect : Study protocol for a randomised controlled trial

Peer reviewedPublisher PD

Significant Upregulation of Alzheimer's β-Amyloid Levels in a Living System Induced by Extracellular Elastin Polypeptides

Alzheimer's disease (AD) is a neurodegenerative disorder and the primary cause of age-related dementia. The etiology of AD is complex and has not been completely elucidated. Herein, we report that treatment with elastin-like polypeptides (ELPs), a component of the brain extracellular matrix (ECM), significantly increased the levels of AD-related amyloid-β peptides (Aβ) both in vitro and in vivo. Regarding the molecular mechanism(s), the upregulation of Aβ levels was related to increased proteolytic processing of the amyloid precursor protein. Furthermore, nesting tests demonstrated that the ELP-treated animals showed significant neurobehavioral deficits with cognitive impairment. These results suggest that the elastin is associated with AD-related pathological and behavioral changes. This finding presents a new aspect for Alzheimer's amyloidosis event and provides a great promise in developing ELP-based model systems to better understand the pathogenesis of AD. © 201

Identification of membrane protein types via deep residual hypergraph neural network

A membrane protein's functions are significantly associated with its type, so it is crucial to identify the types of membrane proteins. Conventional computational methods for identifying the species of membrane proteins tend to ignore two issues: High-order correlation among membrane proteins and the scenarios of multi-modal representations of membrane proteins, which leads to information loss. To tackle those two issues, we proposed a deep residual hypergraph neural network (DRHGNN), which enhances the hypergraph neural network (HGNN) with initial residual and identity mapping in this paper. We carried out extensive experiments on four benchmark datasets of membrane proteins. In the meantime, we compared the DRHGNN with recently developed advanced methods. Experimental results showed the better performance of DRHGNN on the membrane protein classification task on four datasets. Experiments also showed that DRHGNN can handle the over-smoothing issue with the increase of the number of model layers compared with HGNN. The code is available at https://github.com/yunfighting/Identification-of-Membrane-Protein-Types-via-deep-residual-hypergraph-neural-network

METTL14 regulates chromatin bivalent domains in mouse embryonic stem cells

METTL14 (methyltransferase-like 14) is an RNA-binding protein that partners with METTL3 to mediate N6-methyladenosine (m6A) methylation. Recent studies identified a function for METTL3 in heterochromatin in mouse embryonic stem cells (mESCs), but the molecular function of METTL14 on chromatin in mESCs remains unclear. Here, we show that METTL14 specifically binds and regulates bivalent domains, which are marked by trimethylation of histone H3 lysine 27 (H3K27me3) and lysine 4 (H3K4me3). Knockout of Mettl14 results in decreased H3K27me3 but increased H3K4me3 levels, leading to increased transcription. We find that bivalent domain regulation by METTL14 is independent of METTL3 or m6A modification. METTL14 enhances H3K27me3 and reduces H3K4me3 by interacting with and probably recruiting the H3K27 methyltransferase polycomb repressive complex 2 (PRC2) and H3K4 demethylase KDM5B to chromatin. Our findings identify an METTL3-independent role of METTL14 in maintaining the integrity of bivalent domains in mESCs, thus indicating a mechanism of bivalent domain regulation in mammals