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Thrombosis occurs in both macrovasculature and microvasculature, causing various cardio-cerebral vascular diseases. The lack of effective and safe antithrombotic drugs leads to a public health crisis. Mounting evidence suggests that protein disulfide isomerase (PDI) plays a critical role in the initial stage of thrombus formation, motivating the research of the feasibility of PDI inhibitors as novel antithrombotics. Rutin, one of the most potent PDI inhibitors, was reported to suppress platelet aggregation and thrombosis in animal models, but further studies and clinical translation were restricted due to its low aqueous solubility and oral bioavailability. In this work, we fabricated rutin-loaded lipidbased nano-formulation (NanoR) and characterized their physical-chemical properties, release profiles, pharmacokinetic process, and pharmacodynamic function against thrombosis in macrovessels and microvessels. NanoR provided increased solubility and dissolution of rutin to achieve earlier Tmax and higher Cmax than the sodium salt of rutin (NaR) after oral gavage. Ex vivo studies demonstrated that NanoR significantly inhibited thrombin generation and clot formation in the plasma of mice. Importantly, such effect was reversed by exogenous recombinant PDI, demonstrating the specificity of the NanoR. In direct current-induced arterial thrombosis model and ferric chloride-induced microvascular thrombosis model, NanoR exhibited greatly enhanced antithrombotic activity compared with NaR. NanoR also showed good safety performance according to tail bleeding assay, global coagulation tests, and histological analysis. Overall, our current results indicated that NanoR offers a promising antithrombotic treatment with potential for clinical translation. [ABSTRACT FROM AUTHOR]

Microbial methylation and demethylation are two competing processes controlling the net production and bioaccumulation of neurotoxic methylmercury (MeHg) in natural ecosystems. Although mercury (Hg) methylation by anaerobic microorganisms and demethylation by aerobic Hg-resistant bacteria have both been extensively studied, little attention has been given to MeHg degradation by anaerobic bacteria, particularly the iron-reducing bacterium Geobacter bemidjiensis Bem. Here we report, for the first time, that the strain G. bemidjiensis Bem can mediate a suite of Hg transformations, including Hg(II) reduction, Hg(0) oxidation, MeHg production and degradation under anoxic conditions. Results suggest that G. bemidjiensis utilizes a reductive demethylation pathway to degrade MeHg, with elemental Hg(0) as the major reaction product, possibly due to the presence of genes encoding homologues of an organomercurial lyase (MerB) and a mercuric reductase (MerA). In addition, the cells can strongly sorb Hg(II) and MeHg, reduce or oxidize Hg, resulting in both time and concentration-dependent Hg species transformations. Moderate concentrations (10-500 μM) of Hg-binding ligands such as cysteine enhance Hg(II) methylation but inhibit MeHg degradation. These findings indicate a cycle of Hg methylation and demethylation among anaerobic bacteria, thereby influencing net MeHg production in anoxic water and sediments. [ABSTRACT FROM AUTHOR]

The guaranteed cost control problem is investigated for a class of nonlinear discrete-time systems with Markovian jumping parameters and mixed time delays. The mixed time delays involved consist of both the mode-dependent discrete delay and the distributed delay with mode-dependent lower bound. The associated cost function is of a quadratic summation form over the infinite horizon. The nonlinear functions are assumed to satisfy sector-bounded conditions. By introducing new Lyapunov- Krasovskii functionals and developing some new analysis techniques, sufficient conditions for the existence of guaranteed cost controllers are derived with respect to the given cost function. Moreover, a convex optimization approach is applied to search for the optimal guaranteed cost controller by minimizing the guaranteed cost of the closed-loop system. Numerical simulation is further carried out to demonstrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

This paper is concernedwith the leader-following consensus probleminmean-square for a class of discrete-timemultiagent systems. The multiagent systems under consideration are the directed and contain arbitrary discrete time-delays. The communication links are assumed to be time-varying and stochastic. It is also assumed that some agents in the network are well informed and act as leaders, and the others are followers. By introducing novel Lyapunov functionals and employing some new analytical techniques, sufficient conditions are derived to guarantee the leader-following consensus inmean-square for the concernedmultiagent systems, so that all the agents are steered to an anticipated state target. A numerical example is presented to illustrate the main results. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a new class of discrete-time neural networks (DNNs) with Markovian jumping parameters as well as mode-dependent mixed time delays (both discrete and distributed time delays). Specifically, the parameters of the DNNs are subject to the switching from one to another at different times according to a Markov chain, and the mixed time delays consist of both discrete and distributed delays that are dependent on the Markovian jumping mode. We first deal with the stability analysis problem of the addressed neural networks. A special inequality is developed to account for the mixed time delays in the discrete-time setting, and a novel Lyapunov-Krasovskii functional is put forward to reflect the mode-dependent time delays. Sufficient conditions are established in terms of linear matrix inequalities (LMIs) that guarantee the stochastic stability. We then turn to the synchronization problem among an array of identical coupled Markovian jumping neural networks with mixed mode-dependent time delays. By utilizing the Lyapunov stability theory and the Kronecker product, it is shown that the addressed synchronization problem is solvable if several LMIs are feasible. Hence, different from the commonly used matrix norm theories (such as the M-matrix method), a unified LMI approach is developed to solve the stability analysis and synchronization problems of the class of neural networks under investigation, where the LMIs can be easily solved by using the available Matlab LMI toolbox. Two numerical examples are presented to illustrate the usefulness and effectiveness of the main results obtained. [ABSTRACT FROM AUTHOR]

In this paper, a synchronization problem is investigated for an array of coupled complex discrete-time networks with the simultaneous presence of both the discrete and distributed time delays. The complex networks addressed which include neural and social networks as special cases are quite general. Rather than the commonly used Lipschitz-type function, a more general sector-like nonlinear function is employed to describe the nonlinearities existing in the network. The distributed infinite time delays in the discrete-time domain are first defined. By utilizing a novel Lyapunov—Krasovskii functional and the Kronecker product, it is shown that the addressed discrete-time complex network with distributed delays is synchronized if certain linear matrix inequalities (LMIs) are feasible. The state estimation problem is then studied for the same complex network, where the purpose is to design a state estimator to estimate the network states through available output measurements such that, for all admissible discrete and distributed delays, the dynamics of the estimation error is guaranteed to be globally asymptotically stable. Again, an LMI approach is developed for the state estimation problem. Two simulation examples are provided to show the usefulness of the proposed global synchronization and state estimation conditions. It is worth pointing out that our main results are valid even if the nominal subsystems within the network are unstable. [ABSTRACT FROM AUTHOR]

In this paper, we consider the long term behavior for the stochastic lattice dynamical systems with some partly dissipative nonlinear term in l2 × l2. The main purpose of this paper is to establish the existence of a compact global random attractor. The uniqueness and existence is first proved for the solution of an infinite dimensional random dynamical system, and a priori estimate is obtained on the solutions. The existence of a random absorbing set is then discussed for the systems, and an estimate on tails of the solutions is derived when the time is large enough, which ensures the asymptotic compactness of solutions. Finally, the global random attractor is proved to exist within the set of tempered random bounded sets rather than all bounded deterministic sets, i.e. the stochastic lattice system has a global random attractor in l2 × l2. [ABSTRACT FROM AUTHOR]

In this letter, the global asymptotic stability analysis problem is considered for a class of stochastic Cohen-Grossberg neural networks with mixed time delays, which consist of both the discrete and distributed time delays. Based on an Lyapunov-Krasovskii functional and the stochastic stability analysis theory, a linear matrix inequality (LMI) approach is developed to derive several sufficient conditions guaranteeing the global asymptotic convergence of the equilibrium point in the mean square. It is shown that the addressed stochastic Cohen-Grossberg neural networks with mixed delays are globally asymptotically stable in the mean square if two LMIs are feasible, where the feasibility of LMIs can be readily checked by the Matlab LMI toolbox. It is also pointed out that the main results comprise some existing results as special cases. A numerical example is given to demonstrate the usefulness of the proposed global stability criteria. [ABSTRACT FROM AUTHOR]

Deforestation poses a global threat to biodiversity and its capacity to deliver ecosystem services. Yet, the impacts of deforestation on soil biodiversity and its associated ecosystem services remain virtually unknown. We generated a global dataset including 696 paired-site observations to investigate how native forest conversion to other land uses affects soil properties, biodiversity, and functions associated with the delivery of multiple ecosystem services. The conversion of native forests to plantations, grasslands, and croplands resulted in higher bacterial diversity and more homogeneous fungal communities dominated by pathogens and with a lower abundance of symbionts. Such conversions also resulted in significant reductions in carbon storage, nutrient cycling, and soil functional rates related to organic matter decomposition. Responses of the microbial community to deforestation, including bacterial and fungal diversity and fungal guilds, were predominantly regulated by changes in soil pH and total phosphorus. Moreover, we found that soil fungal diversity and functioning in warmer and wetter native forests is especially vulnerable to deforestation. Our work highlights that the loss of native forests to managed ecosystems poses a major global threat to the biodiversity and functioning of soils and their capacity to deliver ecosystem services. [ABSTRACT FROM AUTHOR]

This study investigates the sampled-data containment control problem for linear multi-agent systems with multiple leaders under undirected or directed network topology. First, by means of the decomposition method, the containment control problem is transformed into the simultaneous stability analysis issue of certain subsystems. Then, the solution of a class of differential equations, which plays a key role for the addressed problem, is exploited by using the contradiction method. Together with a novel Lyapunov function, sufficient conditions are established to guarantee that all the followers move into the convex hull spanned by the leaders. The proposed results are dependent on the information of the system dynamics, the coupling strength as well as the eigenvalues of topology matrix. Furthermore, the established results are specialised to both the leader--following case and the traditional consensus case. Finally, simulations are given to illustrate the theoretical results derived in this study. [ABSTRACT FROM AUTHOR]

In this paper, global asymptotic stability of impulsive fractional-order complex-valued neural networks with time delay is considered. By employing contraction mapping principle, comparison theorem and inequality scaling skills, several sufficient conditions to ensure the existence, uniqueness and global asymptotic stability of the equilibrium point for the considered neural networks are established. A numerical example illustrates the validity and feasibility of the obtained result. [ABSTRACT FROM AUTHOR]

This essay focuses on the theory, practice, techniques and effects of Liu's Scalp Acupuncture. The technique was invented by Dr. Wei Liu in 2005, and it has since gained wide interest from orthopedic surgeons and researchers. [ABSTRACT FROM AUTHOR]

In this study, the stochastic sampled-data approach is developed to deal with the H∞ control problem for a class of linear multi-agent systems. For each agent, signals should be transmitted to the control input, including not only its own measurements, but also the output information received from the neighbour agents. The relationships of information communications between the whole multi-agents are totally reflected by a weighted directed graph with a fixed topology structure. To the addressed problem, the author's focus is to design an output feedback controller for each agent such that, for the external energy bounded disturbances, the exponential stability in the mean square sense and interference rejection ability under consideration can be guaranteed. By assuming that the sampling period of each agent switches between two values in a probabilistic way, the stochastic sampling phenomenon is well characterised in every sampling tasks. In virtue of Lyapunov theory and semi-definite programming method, sufficient conditions are derived to ensure the exponential stability as well as H∞ performance, and the feedback controllers are also designed by solving some certain matrix inequalities. Finally, a numerical simulation is given to demonstrate the validness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

The impulsive complex-valued neural networks with three kinds of time delays including leakage delay, discrete delay, and distributed delay are considered. Based on the homeomorphism mapping principle of complex domain, a sufficient condition for the existence and uniqueness of the equilibrium point of the addressed complex-valued neural networks is proposed in terms of linear matrix inequality (LMI). By constructing appropriate Lyapunov-Krasovskii functionals, and employing the free weighting matrix method, several delay-dependent criteria for checking the global μ-stability of the complex-valued neural networks are established in LMIs. As direct applications of these results, several criteria on the exponential stability, power-stability, and log-stability are obtained. Two examples with simulations are provided to demonstrate the effectiveness of the proposed criteria. [ABSTRACT FROM AUTHOR]

A class of fractional-order BAM neural networks with delays in the leakage terms is considered. By using inequality technique and analysis method, several delay-dependent sufficient conditions are established to ensure the uniform stability of such networks. Moreover, the sufficient conditions guaranteeing the existence, uniqueness, and stability of the equilibrium point are also obtained. In addition, three simulation examples are given to demonstrate the effectiveness of the obtained results. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editors discuss reports within the issue, including "Second-Order Consensus for Multi-Agent Systems Under Directed and Switching Topologies," "Energy-Aware Topology Evolution Model With Link and Node Deletion in Wireless Sensor Networks," and "Geometric Buildup Algorithms for Sensor Network Localization."

In this paper, the problem of stochastic synchronization analysis is investigated for a new array of coupled discrete-time stochastic complex networks with randomly occurred nonlinearities (RONs) and time delays. The discrete-time complex networks under consideration are subject to: 1) stochastic nonlinearities that occur according to the Bernoulli distributed white noise sequences; 2) stochastic disturbances that enter the coupling term, the delayed coupling term as well as the overall network; and 3) time delays that include both the discrete and distributed ones. Note that the newly introduced RONs and the multiple stochastic disturbances can better reflect the dynamical behaviors of coupled complex networks whose information transmission process is affected by a noisy environment (e.g., internet-based control systems). By constructing a novel Lyapunov-like matrix functional, the idea of delay fractioning is applied to deal with the addressed synchronization analysis problem. By employing a combination of the linear matrix inequality (LMI) techniques, the free-weighting matrix method and stochastic analysis theories, several delay-dependent sufficient conditions are obtained which ensure the asymptotic synchronization in the mean square sense for the discrete-time stochastic complex networks with time delays. The criteria derived are characterized in terms of LMIs whose solution can be solved by utilizing the standard numerical software. A simulation example is presented to show the effectiveness and applicability of the proposed results. [ABSTRACT FROM AUTHOR]

This paper is concerned with the robust synchronization problem for an array of coupled stochastic discrete-time neural networks with time-varying delay. The individual neural network is subject to parameter uncertainty, stochastic disturbance, and time-varying delay, where the norm-bounded parameter uncertainties exist in both the state and weight matrices, the stochastic disturbance is in the form of a scalar Wiener process, and the time delay enters into the activation function. For the array of coupled neural networks, the constant coupling and delayed coupling are simultaneously considered. We aim to establish easy-to-verify conditions under which the addressed neural networks are synchronized. By using the Kronecker product as an effective tool, a linear matrix inequality (LMI) approach is developed to derive several sufficient criteria ensuring the coupled delayed neural networks to be globally, robustly, exponentially synchronized in the mean square. The LMI-based conditions obtained are dependent not only on the lower bound but also on the upper bound of the time-varying delay, and can be solved efficiently via the Matlab LMI Toolbox. Two numerical examples are given to demonstrate the usefulness of the proposed synchronization scheme. [ABSTRACT FROM AUTHOR]

In this paper, the synchronization control problem is considered for two coupled discrete-time complex networks with time delays. The network under investigation is quite general to reflect the reality, where the state delays are allowed to be time varying with given lower and upper bounds, and the stochastic disturbances are assumed to be Brownian motions that affect not only the network coupling but also the overall networks. By utilizing the Lyapunov functional method combined with linear matrix inequality (LMI) techniques, we obtain several sufficient delay-dependent conditions that ensure the coupled networks to be globally exponentially synchronized in the mean square. A control law is designed to synchronize the addressed coupled complex networks in terms of certain LMIs that can be readily solved using the Matlab LMI toolbox. Two numerical examples are presented to show the validity of our theoretical analysis results. [ABSTRACT FROM AUTHOR]

By using finite difference discretization for the sine-Gordon equation, we obtain the sine- Gordon prototypes. For these prototypes, the existence of discrete periodic travelling wave solutions and discrete solitons are proved by the anti-integrable limit method. [ABSTRACT FROM AUTHOR]

Spermatogonial stem cells (SSCs) are unipotent germ cells that are at the foundation of spermatogenesis and male fertility. However, the underlying molecular mechanisms governing SSC stemness and growth properties remain elusive. We have recently identified chromodomain helicase/ATPase DNA binding protein 1-like (Chd1l) as a novel regulator for SSC survival and self-renewal, but how these functions are controlled by Chd1l remains to be resolved. Here, we applied highthroughput small RNA sequencing to uncover the microRNA (miRNA) expression profiles controlled by Chd1l and showed that the expression levels of 124 miRNA transcripts were differentially regulated by Chd1l in SSCs. KEGG pathway analysis shows that the miRNAs that are differentially expressed upon Chd1l repression are significantly enriched in the pathways associated with stem cell pluripotency and proliferation. As a proof of concept, we demonstrate that one of the most highly upregulated miRNAs, miR-486, controls SSC stemness gene expression and growth properties. The matrix metalloproteinase 2 (MMP2) gene has been identified as a novel miR-486 target gene in the context of SSC stemness gene regulation and growth properties. Data from cotransfection experiments showed that Chd1l, miR- 486, and MMP2 work in concert in regulating SSC stemness gene expression and growth properties. Finally, our data also revealed that MMP2 regulates SSC stemness gene expression and growth properties through activating β-catenin signaling by cleaving N-cadherin and increasing β-catenin nuclear translocation. Our data demonstrate that Chd1l-miR-486-MMP2 is a novel regulatory axis governing SSC stemness gene expression and growth properties, offering a novel therapeutic opportunity for treating male infertility. [ABSTRACT FROM AUTHOR]

The complex interactions between cancer cells and their surrounding stromal microenvironment play important roles in tumor initiation and progression and represent viable targets for therapeutic intervention. Here, we propose a concept of common target perturbation (CTP). CTP acts simultaneously on the same target in both the tumor and its stroma that generates a bilateral disruption for potentially improved cancer therapy. To employ this concept, we designed a systems biology strategy by combining experiment and computation to identify potential common target. Through progressive cycles of identification, TGF-β receptor III (TβRIII) is found as an epithelial-mesenchymal common target in oral squamous cell carcinoma. Simultaneous perturbation of TŴRIII in the oral cancerous epithelial cells and their adjacent carcinoma-associated fibroblasts effectively inhibits tumor growth in vivo, and shows superiority to the unilateral perturbation of TβRIII in either cell type alone. This study indicates the strong potential to identify therapeutic targets by considering cancer cells and their adjacent stroma simultaneously. The CTP concept combined with our common target discovery strategy provides a framework for future targeted cancer combinatorial therapies. [ABSTRACT FROM AUTHOR]

This paper deals with the fault detection problem for a class of discrete-time wireless networked control systems described by switching topology with uncertainties and disturbances. System states of each individual node are affected not only by its own measurements, but also by other nodes' measurements according to a certain network topology. As the topology of system can be switched in a stochastic way, we aim to design H∞ fault detection observers for nodes in the dynamic time-delay systems. By using the Lyapunov method and stochastic analysis techniques, sufficient conditions are acquired to guarantee the existence of the filters satisfying the H∞ performance constraint, and observer gains are derived by solving linear matrix inequalities. Finally, an illustrated example is provided to verify the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

Nowadays, the real-world systems are usually subject to various complexities such as parameter uncertainties, time-delays, and nonlinear disturbances. For networked systems, especially large-scale systems such as multiagent systems and systems over sensor networks, the complexities are inevitably enhanced in terms of their degrees or intensities because of the usage of the communication networks. Therefore, it would be interesting to (1) examine how this kind of network-enhanced complexities affects the control or filtering performance; and (2) develop some suitable approaches for controller/filter design problems. In this paper, we aim to survey some recent advances on the performance analysis and synthesis with three sorts of fashionable network-enhanced complexities, namely, fading measurements, event-triggered mechanisms, and attack behaviors of adversaries. First, these three kinds of complexities are introduced in detail according to their engineering backgrounds, dynamical characteristic, and modelling techniques. Then, the developments of the performance analysis and synthesis issues for various networked systems are systematically reviewed. Furthermore, some challenges are illustrated by using a thorough literature review and some possible future research directions are highlighted. [ABSTRACT FROM AUTHOR]

State estimation problem is considered for a kind of wireless network control system with stochastic uncertainty and time delay. A sliding mode observer is designed for the system under the situation that no missing measurement occurs and system uncertainty happens in a stochastic way. The observer designed for the system can guarantee the system states will be driven onto the sliding surface under control law, and the sliding motion of system states on sliding surface will be stable. By constructing proper Lyapunov-Krasovskii functional, sufficient conditions are acquired via linear matrix inequality. Finally, simulation result is employed to show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, we consider the robust H∞ control problem for a class of discrete time-delay stochastic systems with randomly occurring nonlinearities. The parameter uncertainties enter all the system matrices; the stochastic disturbances are both state and control dependent, and the randomly occurring nonlinearities obey the sector boundedness conditions. The purpose of the problem addressed is to design a state feedback controller such that, for all admissible uncertainties, nonlinearities, and time delays, the closed-loop system is robustly asymptotically stable in the mean square, and a prescribed H∞ disturbance rejection attenuation level is also guaranteed. By using the Lyapunov stability theory and stochastic analysis tools, a linear matrix inequality (LMI) approach is developed to derive sufficient conditions ensuring the existence of the desired controllers, where the conditions are dependent on the lower and upper bounds of the time-varying delays. The explicit parameterization of the desired controller gains is also given. Finally, a numerical example is exploited to show the usefulness of the results obtained. [ABSTRACT FROM AUTHOR]

Some recent advances on the filtering and control problems for nonlinear stochastic complex systems with incomplete information are surveyed. The incomplete information under consideration mainly includes missing measurements, randomly varying sensor delays, signal quantization, sensor saturations, and signal sampling. With such incomplete information, the developments on various filtering and control issues are reviewed in great detail. In particular, the addressed nonlinear stochastic complex systems are so comprehensive that they include conventional nonlinear stochastic systems, different kinds of complex networks, and a large class of sensor networks. The corresponding filtering and control technologies for such nonlinear stochastic complex systems are then discussed. Subsequently, some latest results on the filtering and control problems for the complex systems with incomplete information are given. Finally, conclusions are drawn and several possible future research directions are pointed out. [ABSTRACT FROM AUTHOR]

Background aims. Mesenchymal stromal cells (MSC) possess multilineage differentiation potential and characteristics of self-renewal. It has been reported that MSC can acquire characteristics of cells in the periodontal ligament (PDL) in vitro. Moreover, the transplantation of MSC has been shown to be a promising strategy for treating periodontal defects. However, little is known about the fate of MSC in periodontal tissue in vivo. The aim of this study was to trace the paths of MSC after transplantation into periodontal tissues in vivo. Methods. MSC labeled with bromodeoxyuridine (BrdU) were transplanted into periodontal defects of beagle dogs. Six weeks after surgery, the animals were killed and decalcified specimens were prepared. Migration and differentiation of MSC were detected by single/double immunohistochemistry and a combination of immunohistochemistry and in situ hybridization. Results. BrdU-labeled MSC were observed distributing into periodontal tissue that included alveolar bone, PDL, cementum and blood vessels and expressing surface markers typical of osteoblasts and fibroblasts. Conclusions. Cumulatively, our data suggest that MSC migrate throughout periodontal tissue and differentiate into osteoblasts and fibroblasts after transplantation into periodontal defects at 6 weeks in vivo, and have the potential to regenerate periodontal tissue. [ABSTRACT FROM AUTHOR]

Mesenchymal stem cells (MSCs) are well known to have the capability to form bone and cartilage, and chondrogenesis derived from MSCs is reported to be affected by mechanical stimuli. This research was aimed to study the effects of cyclic compressive stress on the chondrogenic differentiation of rat bone marrow-derived MSCs (BMSCs) which were encapsulated in alginate scaffolds and cultured with or without chondrogenic medium, and to investigate the role of p38 MAPK phospho-relay cascade in this process. The results show that the gene expression of chondrocyte-specific markers of Col2α1, aggrecan, Sox9, Runx2, and Ihh was upregulated by dynamic compressive stress introduced at the 8th day of chondrogenic differentiation in vitro. The p38 MAPK was activated by chondrogenic cytokines in a slow and lagged way, but activated by cyclic compressive stimulation in a rapid and transient manner. And inhibition of p38 activity with SB203580 suppressed gene expression of chondrocyte-specific genes stimulated by chondrogenic medium and (or) cyclic compressive stress. These findings suggest that p38 MAPK signal acts as an essential mediator in the mechano-biochemical transduction and subsequent transcriptional regulation in the process of chondrogenesis. J. Cell. Physiol. 221: 609–617, 2009. © 2009 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]