SYNJ2BP Improves the Production of Lentiviral Envelope Protein by Facilitating the Formation of Mitochondrion-Associated Endoplasmic Reticulum Membrane.

Equine infectious anemia virus (EIAV) and HIV are both members of the Lentivirus genus and are similar in major virological characters. EIAV endangers the horse industry. In addition, EIAV can also be used as a model for HIV research. The maturation of the lentiviral Env protein, which is necessary for viral entry, requires Env to be folded in the endoplasmic reticulum (ER). It is currently unclear how this process is regulated. Mitochondrion-associated endoplasmic reticulum membrane (MAM) is a specialized part of the close connection between the ER and mitochondria, and one of the main functions of MAM is to promote oxidative protein production in the ER. SYNJ2BP is one of the key proteins that make up the MAM, and we found that SYNJ2BP is essential for EIAV replication. We therefore constructed a SYNJ2BP knockout HEK293T cell line in which the number of MAMs is significantly reduced. Moreover, overexpression of SYNJ2BP could increase the number of MAMs. Our study demonstrates that SYNJ2BP can improve the infectivity of the EIAV virus with elevated production of the viral Env protein through increased MAM formation. Interestingly, SYNJ2BP was able to improve the production of not only EIAV Env but also HIV. Further investigation showed that MAMs can provide more ATP and calcium ions, which are essential factors for Env production, to the ER and can also reduce ER stress induced by HIV or EIAV Envs to increase the Env production level in cells. These results may help us to understand the key production mechanisms of lentiviral Env. IMPORTANCE Lentiviral Env proteins, which are rich in disulfide bonds, need to be fully folded in the ER; otherwise, misfolded Env proteins will induce ER stress and be degraded by ER-associated protein degradation (ERAD). To date, it is still unclear about Env production mechanism in the ER. MAM is the structure of closely connection between the ER and mitochondria. MAMs play important roles in the calcium steady state and oxidative stress, especially in the production of oxidative protein. For the first time, we found that SYNJ2BP can promote the production of lentiviral Env proteins by providing the ATP and calcium ions required for oxidative protein production in the ER and by reducing ER stress through facilitating formation of MAMs. These studies shed light on how MAMs improve lentiviral Env production, which will lay the foundation for the study of replication mechanisms in other lentiviruses from the perspective of the cellular organelle microenvironment.

Discrete Memristor and Discrete Memristive Systems.

In this paper, we investigate the mathematical models of discrete memristors based on Caputo fractional difference and G-L fractional difference. Specifically, the integer-order discrete memristor is a special model of those two cases. The "∞"-type hysteresis loop curves are observed when input is the bipolar periodic signal. Meanwhile, numerical analysis results show that the area of hysteresis decreases with the increase of frequency of input signal and the decrease of derivative order. Moreover, the memory effect, characteristics and physical realization of the discrete memristors are discussed, and a discrete memristor with short memory effects is designed. Furthermore, discrete memristive systems are designed by introducing the fractional-order discrete memristor and integer-order discrete memristor to the Sine map. Chaos is found in the systems, and complexity of the systems is controlled by the parameter of the memristor. Finally, FPGA digital circuit implementation is carried out for the integer-order and fractional-order discrete memristor and discrete memristive systems, which shows the potential application value of the discrete memristor in the engineering application field.

A hyperchaotic cycloid map with attractor topology sensitive to system parameters.

We propose herein a novel discrete hyperchaotic map based on the mathematical model of a cycloid, which produces multistability and infinite equilibrium points. Numerical analysis is carried out by means of attractors, bifurcation diagrams, Lyapunov exponents, and spectral entropy complexity. Experimental results show that this cycloid map has rich dynamical characteristics including hyperchaos, various bifurcation types, and high complexity. Furthermore, the attractor topology of this map is extremely sensitive to the parameters of the map. The x--y plane of the attractor produces diverse shapes with the variation of parameters, and both the x--z and y--z planes produce a full map with good ergodicity. Moreover, the cycloid map has good resistance to parameter estimation, and digital signal processing implementation confirms its feasibility in digital circuits, indicating that the cycloid map may be used in potential applications.

A Modified Multivariable Complexity Measure Algorithm and Its Application for Identifying Mental Arithmetic Task.

Properly measuring the complexity of time series is an important issue. The permutation entropy (PE) is a widely used as an effective complexity measurement algorithm, but it is not suitable for the complexity description of multi-dimensional data. In this paper, in order to better measure the complexity of multi-dimensional time series, we proposed a modified multivariable PE (MMPE) algorithm with principal component analysis (PCA) dimensionality reduction, which is a new multi-dimensional time series complexity measurement algorithm. The analysis results of different chaotic systems verify that MMPE is effective. Moreover, we applied it to the comlexity analysis of EEG data. It shows that the person during mental arithmetic task has higher complexity comparing with the state before mental arithmetic task. In addition, we also discussed the necessity of the PCA dimensionality reduction.

SEIR modeling of the COVID-19 and its dynamics.

In this paper, a SEIR epidemic model for the COVID-19 is built according to some general control strategies, such as hospital, quarantine and external input. Based on the data of Hubei province, the particle swarm optimization (PSO) algorithm is applied to estimate the parameters of the system. We found that the parameters of the proposed SEIR model are different for different scenarios. Then, the model is employed to show the evolution of the epidemic in Hubei province, which shows that it can be used to forecast COVID-19 epidemic situation. Moreover, by introducing the seasonality and stochastic infection the parameters, nonlinear dynamics including chaos are found in the system. Finally, we discussed the control strategies of the COVID-19 based on the structure and parameters of the proposed model.

Parameter Identification of Fractional-Order Discrete Chaotic Systems.

Research on fractional-order discrete chaotic systems has grown in recent years, and chaos synchronization of such systems is a new topic. To address the deficiencies of the extant chaos synchronization methods for fractional-order discrete chaotic systems, we proposed an improved particle swarm optimization algorithm for the parameter identification. Numerical simulations are carried out for the Hénon map, the Cat map, and their fractional-order form, as well as the fractional-order standard iterated map with hidden attractors. The problem of choosing the most appropriate sample size is discussed, and the parameter identification with noise interference is also considered. The experimental results demonstrate that the proposed algorithm has the best performance among the six existing algorithms and that it is effective even with random noise interference. In addition, using two samples offers the most efficient performance for the fractional-order discrete chaotic system, while the integer-order discrete chaotic system only needs one sample.

Improved Cryptanalysis and Enhancements of an Image Encryption Scheme Using Combined 1D Chaotic Maps.

This paper presents an improved cryptanalysis of a chaos-based image encryption scheme, which integrated permutation, diffusion, and linear transformation process. It was found that the equivalent key streams and all the unknown parameters of the cryptosystem can be recovered by our chosen-plaintext attack algorithm. Both a theoretical analysis and an experimental validation are given in detail. Based on the analysis of the defects in the original cryptosystem, an improved color image encryption scheme was further developed. By using an image content-related approach in generating diffusion arrays and the process of interweaving diffusion and confusion, the security of the cryptosystem was enhanced. The experimental results and security analysis demonstrate the security superiority of the improved cryptosystem.

Multivariate Multiscale Complexity Analysis of Self-Reproducing Chaotic Systems.

Designing a chaotic system with infinitely many attractors is a hot topic. In this paper, multiscale multivariate permutation entropy (MMPE) and multiscale multivariate Lempel-Ziv complexity (MMLZC) are employed to analyze the complexity of those self-reproducing chaotic systems with one-directional and two-directional infinitely many chaotic attractors. The analysis results show that complexity of this class of chaotic systems is determined by the initial conditions. Meanwhile, the values of MMPE are independent of the scale factor, which is different from the algorithm of MMLZC. The analysis proposed here is helpful as a reference for the application of the self-reproducing systems.

Controllable quantum scars induced by spin-orbit couplings in quantum dots.

Spin-orbit couplings (SOCs), originating from the relativistic corrections in the Dirac equation, offer nonlinearity in the classical limit and are capable of driving chaotic dynamics. In a nanoscale quantum dot confined by a two-dimensional parabolic potential with SOCs, various quantum scar states emerge quasi-periodically in the eigenstates of the system, when the ratio of confinement energies in the two directions is nearly commensurable. The scars, displaying both quantum interference and classical trajectory features on the electron density, due to relativistic effects, serve as a bridge between the classical and quantum behaviors of the system. When the strengths of Rashba and Dresselhaus SOCs are identical, the chaos in the classical limit is eliminated as the classical Hamilton's equations become linear, leading to the disappearance of all quantum scar states. Importantly, the quantum scars induced by SOCs are robust against small perturbations of system parameters. With precise control achievable through external gating, the quantum scar induced by Rashba SOC is fully controllable and detectable.

Dynamical behaviors, circuit design, and synchronization of a novel symmetric chaotic system with coexisting attractors.

In this paper, we introduce a novel three-dimension chaotic system with strange characteristic by applying construction of a 3D chaotic circuit method. Multiple equilibria and abundant coexisting attractors exist in this system. A mathematical model is developed and detailed stability analyses for equilibrium points are executed with obtaining significant results of the period-doubling bifurcation patterns confirmed by phase plane plots and Lyapunov exponent spectra. By varying the initial value and unique controlled parameter, the double-scroll chaotic attractor is broken up into a pair of symmetric singular attractors. Then, the local basins of attraction are investigated concerning the initial condition. Next, the circuit synthesis results generated by Multisim simulation tool validate the self-excitation characteristics of this system. Finally, the feedback control technique is used to study difference synchronization of this system. Main conclusions prove the validity and reliability of difference synchronization.

Cartilage-bioinspired, tough and lubricated hydrogel based on nanocomposite enhancement effect.

The maintenance of high load-bearing tissues and joint lubrication is essential for suppressing osteoarthritis. The lubrication of natural joints is mainly attributed to the hydration lubrication mechanism of articular cartilage. Phospholipids on the cartilage surface attract water molecules to form a tough hydrated layer to reduce friction. In this work, inspired by the phosphatidylcholine lipids, we synthesized lubricated nanospheres by grafting hydrophilic polymer brushes and further synthesized a nanocomposite hydrogel. The addition of the lubricated nanospheres enhanced both the mechanical and lubricated properties of the hydrogel. The nanocomposite-lubricated hydrogel exhibited a friction coefficient 81.7% lower than the blank hydrogel because of grafting the polymer brushes. Also, the nanocomposite enhancement helped the hydrogel achieve high mechanical properties with a compressive strength of 6.63 MPa (50%). The nanocomposite hydrogel developed here could be a promising candidate material in bionic articular cartilage substitute materials.

A Novel Fabrication of Single Electron Transistor from Patterned Gold Nanoparticle Array Template-Prepared by Polystyrene Nanospheres.

In this paper, polystyrene microspheres were firstly prepared by seeded emulsion polymerization, and the uniform monolayer of polystyrene microspheres was prepared on the substrate by the dipping method. Then, polystyrene monolayer film was used as a mask and a low dimensional array structure of gold was prepared by bottom-up self-assembly process. After that, the method of solution etching and annealing was used, and the gold nanoparticle array was post-processed. As a result, gold nanoparticles were recrystallized, with an average diameter of about 50 nm. Subsequently, the semiconductor process was adopted, with focused ion beams induced deposition and electron beam evaporation, and single electron transistors were fabricated, based on self-assembled gold nanoparticles. Finally, the devices were fixed in a liquid helium cryostat and Coulomb blockade was observed at 320 mK. It is a novel fabrication of a single electron transistor based on gold nanoparticle array template and prepared with polystyrene nanospheres.

Assessment of angiotensin-converting enzyme inhibitor/angiotensin receptor blocker on the split renal function in the patients with primary hypertension.

ABSTRACT: Bilateral kidney damage in hypertensive patients is not parallel. Angiotensin-converting enzyme inhibitor/angiotensin receptor blocker (ACEI/ARB), as a commonly used antihypertensive drug, could protect kidney function and delay its deterioration. Most studies focused on overall renal function, but the researches on split renal function (SRF) are rare. We investigated the effects of ACEI/ARB on the SRF in patients with primary hypertension.Patients with primary hypertension (n = 429; male: 213; female: 216) admitted to our department between January 2014 and December 2016 were included in this study. The glomerular filtration rate (GFR) of split and total renal function were determined using diethylenetriaminepentaacetic acid tagged with 99mTc renal dynamic imaging method. For the same patient, the side with high GFR was considered as higher GFR kidney, whereas that with a low GFR was considered as lower GFR kidney. The split function score (Q value) was utilized to evaluate the differences of bilateral renal function. The patients were divided into 3 groups based on the Q values (Group 1, Q value <5%; Group 2, Q value of 5%-10%; Group 3, Q value ≥10%). All the patients received antihypertensive therapy based on ACEI/ARB. The renal dynamic imaging was performed in the 1-year follow-up to investigate the changes of the SRF.Compared with the baseline level, significant decline was noticed in the serum creatinine (Scr) in Group 2 and Group 3 (P < .05). The cystatin C in Group 3 showed significant decline (P < .05). Compared with the baseline, there was significant decline in the Q value in Group 2, whereas the GFR of lower GFR kidney showed significant increase (P < .05). No statistical differences were noticed in the Q value and split GFR in Group 1 and Group 3 (P > .05).In primary hypertension patients, ACEI/ARB therapy could improve the SRF of lower GFR kidney in the presence of certain differences between the SRF. As a result, the SRF difference was reduced. In case of Q value in a range of 5% to 10%, ACEI/ARB could improve the renal function effectively. It may be significant for the design of antihypertensive drugs.

Stochastic resonance in a single-well potential and its application in rolling bearing fault diagnosis.

In this paper, a single-well model based on the piecewise function and classical bistable stochastic resonance (CBSR) is proposed. The steady state probability density of particles and mean first passage time in the model are calculated. The output characteristics and performance of the proposed model are analyzed through numerical simulation. On the basis of CBSR and the proposed model, an adaptive system is established (ACSSR) to generate the highest gain of signal-to-noise ratio (SNRg). Finally, the effectiveness of ACSSR in weak signal detection is verified with both simulated and experimental input signals. The results indicate that the ACSSR could detect the defect signal correctly and improve the SNRg.

Multiscale permutation Rényi entropy and its application for EEG signals.

There is considerable interest in analyzing the complexity of electroencephalography (EEG) signals. However, some traditional complexity measure algorithms only quantify the complexities of signals, but cannot discriminate different signals very well. To analyze the complexity of epileptic EEG signals better, a new multiscale permutation Rényi entropy (MPEr) algorithm is proposed. In this algorithm, the coarse-grained procedure is introduced by using weighting-averaging method, and the weighted factors are determined by analyzing nonlinear signals. We apply the new algorithm to analyze epileptic EEG signals. The experimental results show that MPEr algorithm has good performance for discriminating different EEG signals. Compared with permutation Rényi entropy (PEr) and multiscale permutation entropy (MPE), MPEr distinguishes different EEG signals successfully. The proposed MPEr algorithm is effective and has good applications prospects in EEG signals analysis.