Local activity is regarded as the origin of complexity. In this study, a locally active memristor with coexisting two stable pinched hysteresis loops and two local activity regions is proposed. Its ...nonvolatile memory, as well as locally active characteristics, is validated by the power-off plot and DC
V
–
I
plot. Based on two-dimensional Hindmarsh–Rose and two-dimensional Fitzhugh–Nagumo neurons, a simple neural network is constructed by connecting the two neurons with the locally active memristor. Coexisting multiple firing patterns under different initial conditions are investigated by considering the coupling strength as a unique controlled parameter. The results suggest that the system exhibits coexisting periodic and chaotic bursting firing patterns as well as coexisting two periodic firing patterns with different topologies. Furthermore, state switching without parameters is also explored. In particular, phase synchronization of the memristor synapse-coupled neurons is discussed, which implies that two nonidentical neurons gradually become phase synchronized with the increase in the coupling strength. In order to confirm the effectiveness of numerical simulations, circuit simulations are included.
The continuous memristor is a popular topic of research in recent years, however, there is rare discussion about the discrete memristor model, especially the locally active discrete memristor model. ...This paper proposes a locally active discrete memristor model for the first time and proves the three fingerprints characteristics of this model according to the definition of generalized memristor. A novel hyperchaotic map is constructed by coupling the discrete memristor with a two-dimensional generalized square map. The dynamical behaviors are analyzed with attractor phase diagram, bifurcation diagram, Lyapunov exponent spectrum, and dynamic behavior distribution diagram. Numerical simulation analysis shows that there is significant improvement in the hyperchaotic area, the quasi periodic area and the chaotic complexity of the two-dimensional map when applying the locally active discrete memristor. In addition, antimonotonicity and transient chaos behaviors of system are reported. In particular, the coexisting attractors can be observed in this discrete memristive system, resulting from the different initial values of the memristor. Results of theoretical analysis are well verified with hardware experimental measurements. This paper lays a great foundation for future analysis and engineering application of the discrete memristor and relevant the study of other hyperchaotic maps.
Inadequate oxygenation is a major challenge in cell encapsulation, a therapy which holds potential to treat many diseases including type I diabetes. In such systems, cellular oxygen (O
) delivery is ...limited to slow passive diffusion from transplantation sites through the poorly O
-soluble encapsulating matrix, usually a hydrogel. This constrains the maximum permitted distance between the encapsulated cells and host site to within a few hundred micrometers to ensure cellular function. Inspired by the natural gas-phase tracheal O
delivery system of insects, we present herein the design of a biomimetic scaffold featuring internal continuous air channels endowed with 10,000-fold higher O
diffusivity than hydrogels. We incorporate the scaffold into a bulk hydrogel containing cells, which facilitates rapid O
transport through the whole system to cells several millimeters away from the device-host boundary. A computational model, validated by in vitro analysis, predicts that cells and islets maintain high viability even in a thick (6.6 mm) device. Finally, the therapeutic potential of the device is demonstrated through the correction of diabetes in immunocompetent mice using rat islets for over 6 months.
Host recognition and immune-mediated foreign body response to biomaterials can compromise the performance of implanted medical devices. To identify key cell and cytokine targets, here we perform ...in-depth systems analysis of innate and adaptive immune system responses to implanted biomaterials in rodents and non-human primates. While macrophages are indispensable to the fibrotic cascade, surprisingly neutrophils and complement are not. Macrophages, via CXCL13, lead to downstream B cell recruitment, which further potentiated fibrosis, as confirmed by B cell knockout and CXCL13 neutralization. Interestingly, colony stimulating factor-1 receptor (CSF1R) is significantly increased following implantation of multiple biomaterial classes: ceramic, polymer and hydrogel. Its inhibition, like macrophage depletion, leads to complete loss of fibrosis, but spares other macrophage functions such as wound healing, reactive oxygen species production and phagocytosis. Our results indicate that targeting CSF1R may allow for a more selective method of fibrosis inhibition, and improve biomaterial biocompatibility without the need for broad immunosuppression.
Abstract
Metabolic reprogramming of the tumor microenvironment (TME) and poor immunogenicity are two of the challenges that cancer immunotherapies have to overcome for improved clinical benefits. ...Among various immunosuppressive metabolites that keep anti-tumor immunity in check, the tryptophan catabolite kynurenine (Kyn) is an attractive target for blockade given its role in mediating immunosuppression through multiple pathways. Here, we present a local chemo-immunometabolic therapy through injection of a supramolecular hydrogel concurrently releasing doxorubicin that induces immunogenic tumor cell death and kynureninase that disrupts Kyn-mediated immunosuppressive pathways in TME. The combination synergically enhances tumor immunogenicity and unleashes anti-tumor immunity. In mouse models of triple negative breast cancer and melanoma, a single low dose peritumoral injection of the therapeutic hydrogel promotes TME transformation toward more immunostimulatory, which leads to enhanced tumor suppression and extended mouse survival. In addition, the systemic anti-tumor surveillance induced by the local treatment exhibits an abscopal effect and prevents tumor relapse post-resection. This versatile approach for local chemo-immunometabolic therapy may serve as a general strategy for enhancing anti-tumor immunity and boosting the efficacy of cancer immunotherapies.
This paper introduces a three-stable locally active memristor whose internal state equation is composed of sign functions related to internal state and voltage. The memristor has three asymptotically ...stable equilibrium points and a locally active region. The non-volatility and local activity of the memristor are verified by the POP (power-off plot) and the DC
V
-
I
plot, respectively. Furthermore, the proposed memristor has a petal-like continuous DC
V
-
I
curve, and thus it also is a new type of 4-lobe Chua corsage memristor. Biasing the memristor at its locally active region and connecting it in series with an inductor, a second-order oscillator is developed in this paper. The required inductance and the oscillation frequency are determined by analyzing the admittance function
Y
(
iw,V
) of memristor’s small-signal equivalent circuit. Based on Hopf bifurcation theory and the pole-zero diagram of the composite admittance function
Y
c
(
s
,
Q
)
, the dynamics of the resultant oscillator circuit are analyzed in detail. In addition, a third-order chaotic oscillation circuit is obtained by adding a capacitor to the second-order oscillation circuit. Its dynamical characteristics are analyzed through Lyapunov exponent spectrum, bifurcation diagram and dynamic diagram. Finally, simulation results based on Multisim are given to verify the correctness of the numerical simulation.
Continuous memristors have been widely studied in recent years; however, there are few studies on discrete memristors in the field of neural networks. In this paper, a four-stable locally active ...discrete memristor (LADM) is proposed as a synapse, which is used to connect a two-dimensional Chialvo neuron and a three-dimensional KTZ neuron, and construct a simple heterogeneous discrete neural network (HDNN). Through a bifurcation diagram and Lyapunov exponents diagram, the period and chaotic regions of the discrete neural network model are shown. Through numerical analysis, it was found that the chaotic region and periodic region of the neural network based on DLAM are significantly improved. In addition, coexisting chaos and chaos attractors, coexisting periodic and chaotic attractors, and coexisting periodic and periodic attractors will appear when the initial value of the LADM is changed. Coupled by a LADM synapse, two heterogeneous discrete neurons are gradually synchronized by changing the coupling strength. This paper lays a good foundation for the future analysis of LADMs and the related research of discrete neural networks coupled by LADMs.
Delayed bifurcation behavior is ubiquitous in multi-time scale systems and has a great important effect on bursting oscillations. In this paper, a parametrically driven Shimizu-Morioka system is ...proposed and distinct delay behavior is observed when the slow-varying parameter passes through the transcritical bifurcation point periodically. Periodic and chaotic bursting oscillations induced by such delay behavior are investigated by using the fast-slow analysis method with different excitation amplitudes. More interesting, the fast subsystem has a zero equilibrium point branch and two asymmetrically distributed equilibrium point branches with respect to the slow-varying parameter. Thus, there exist two possible routes for the trajectory to choose when the delayed transcritical bifurcation takes place. This leads to that the bursting patterns corresponding to different excitation periods may be different. As a result, two possible mixed bursting patterns, named as “delayed transcritical/transcritical” bursting of point-point type mixed with “delayed transcritical/supHopf/fold” bursting of point-cycle type and “delayed transcritical/subHopf/subHopf/fold” bursting of point-cycle type mixed with “delayed transcritical/supHopf/fold” bursting of point-cycle, are revealed. Furthermore, the effect of the excitation frequency on the delay behavior is also considered. We find the delay behavior may terminate at different parameter areas when the excitation amplitude is fixed and the excitation frequency varies and thus leads to different bursting patterns. Numerical simulations are provided to verify the validity of the study.
A versatile method to produce superhydrophobic fabrics by combining electrospinning and initiated chemical vapor deposition (iCVD) is reported. In this study, poly(caprolactone) (PCL) was first ...electrospun and then coated with a thin layer of hydrophobic polymerized perfluoroalkyl ethyl methacrylate (PPFEMA) by iCVD. The hierarchical surface roughness inherent in the PCL electrospun mats and the extremely low surface free energy of the coating layer obtained by iCVD yields stable superhydrophobicity with a contact angle of 175° and a threshold sliding angle less than 2.5° for a 20 mg droplet. This PPFEMA-coated PCL mat was also shown to exhibit at least “grade 8” oleophobicity. Hydrophobicity was demonstrated to increase monotonically with a reduction in diameter among bead-free fibers and with the introduction of a high density of relatively small diameter beads. The systematic effect of fiber morphology on superhydrophobicity was also investigated theoretically and experimentally using both beaded and bead-free fibers with diameters ranging from 600 to 2200 nm.
In order to enrich the dynamic behaviors of discrete neuron models and more effectively mimic biological neural networks, this paper proposes a bistable locally active discrete memristor (LADM) model ...to mimic synapses. We explored the dynamic behaviors of neural networks by introducing the LADM into two identical Rulkov neurons. Based on numerical simulation, the neural network manifested multistability and new firing behaviors under different system parameters and initial values. In addition, the phase synchronization between the neurons was explored. Additionally, it is worth mentioning that the Rulkov neurons showed synchronization transition behavior; that is, anti-phase synchronization changed to in-phase synchronization with the change in the coupling strength. In particular, the anti-phase synchronization of different firing patterns in the neural network was investigated. This can characterize the different firing behaviors of coupled homogeneous neurons in the different functional areas of the brain, which is helpful to understand the formation of functional areas. This paper has a potential research value and lays the foundation for biological neuron experiments and neuron-based engineering applications.
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