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In this paper, we consider a high-dimensional stochastic HIV/AIDS model that incorporates both multiple stages treatment and higher order perturbation. Firstly, we establish sufficient criteria for the existence of a unique ergodic stationary distribution by making use of stochastic Lyapunov analysis method. Stationary distribution shows that the disease will be persistent in the long term. Then, conditions for extinction of the disease are obtained. Theoretical analysis indicates that large noise intensity can suppress the prevalence of HIV/AIDS epidemic. Finally, we provide some numerical simulations to illustrate the analytical results. [ABSTRACT FROM AUTHOR]

This paper considers a stochastic chemostat model with degenerate diffusion. Firstly, the Markov semigroup theory is used to establish sufficient criteria for the existence of a unique stable stationary distribution. The authors show that the densities of the distributions of the solutions can converge in L1 to an invariant density. Then, conditions are obtained to guarantee the washout of the microorganism. Furthermore, through solving the corresponding Fokker-Planck equation, the authors give the exact expression of density function around the positive equilibrium of deterministic system. Finally, numerical simulations are performed to illustrate the theoretical results. [ABSTRACT FROM AUTHOR]

Drug discovery focused on target proteins has been a successful strategy, but many diseases and biological processes lack obvious targets to enable such approaches. Here, to overcome this challenge, we describe a deep learning–based efficacy prediction system (DLEPS) that identifies drug candidates using a change in the gene expression profile in the diseased state as input. DLEPS was trained using chemically induced changes in transcriptional profiles from the L1000 project. We found that the changes in transcriptional profiles for previously unexamined molecules were predicted with a Pearson correlation coefficient of 0.74. We examined three disorders and experimentally tested the top drug candidates in mouse disease models. Validation showed that perillen, chikusetsusaponin IV and trametinib confer disease-relevant impacts against obesity, hyperuricemia and nonalcoholic steatohepatitis, respectively. DLEPS can generate insights into pathogenic mechanisms, and we demonstrate that the MEK–ERK signaling pathway is a target for developing agents against nonalcoholic steatohepatitis. Our findings suggest that DLEPS is an effective tool for drug repurposing and discovery. Drug discovery based on transcriptional profiling does not require knowledge of protein targets. [ABSTRACT FROM AUTHOR]

This study explored effects of dietary OCP intake from plant-origin foods (cereals, fruits, and vegetables) consumption on lipid metabolism and inflammation of women using a multiple follow-up study. The results showed that dietary intake of p,p′-dichlorodiphenyltrichloroethane (DDT) [β = − 10.11, 95% confidence interval (95%CI): − 17.32, − 2.905] and o,p′-dichlorodiphenyldichloroethylene (DDE) (β = − 6.077, 95%CI: − 9.954, − 2.200) were overall negatively associated with serum high-density lipoprotein cholesterol (HDL), whereas other OCPs were not. Serum interleukin (IL)-8 was positively associated with intake of dieldrin (β = 0.390, 95%CI: 0.105, 0.674), endosulfan-β (β = 0.361, 95%CI: 0.198, 0.523), total endosulfan (β = 0.136, 95%CI: 0.037, 0.234), and total OCPs (β = 0.084, 95%CI: 0.016, 0.153), and negatively correlated with intake of p,p′-DDE (β = − 2.692, 95%CI: − 5.185, − 0.198). We concluded that dietary intake of some individual DDT-, DDE- dieldrin-, and endosulfan-class chemicals from plant-origin foods may interfere with lipid metabolism and inflammation responses. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive fixed time parameter estimation and synchronization control scheme is proposed for multiple robotic manipulators with unknown parameters and lumped disturbances. A mean coupling synchronization error is defined by averaging all the tracking errors of multiple robotic manipulators, and an adaptive fixed time synchronization control scheme is proposed to guarantee that both the tracking error and the synchronization error can simultaneously converge to zero within a fixed time, which means that the upper bound of the settling time is independent of the initial conditions. Moreover, an adaptive parameter estimation law is developed through constructing auxiliary filtered variables to achieve the accurate estimation of the unknown system parameters. Comparative simulations are provided to validate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper investigates a renewal risk model with stochastic return and Brownian perturbation, where the price process of the investment portfolio is described as a geometric Lévy process. When the claim sizes have a subexponential distribution, we derive the asymptotics for the finite-time ruin probability of the above risk model. The obtained result confirms that the asymptotics for the finite-time ruin probability of the risk model with heavy-tailed claim sizes are insensitive to the Brownian perturbation. [ABSTRACT FROM AUTHOR]

Let $X_{i}, i\geq1$ be a sequence of random variables with different distributions $F_{i}, i\geq1$ . The partial sums are denoted by $S_{n}=\sum_{i=1}^{n} X_{i}$ , $n\geq1$ . This paper mainly investigates the precise large deviations of $S_{n}, n\geq1$ , for the widely orthant dependent random variables $X_{i}, i\geq1$ . Under some mild conditions, the lower and upper bounds of the precise large deviations of the partial sums $S_{n}$ , $n\geq1$ , are presented. [ABSTRACT FROM AUTHOR]

We consider a discrete-time risk model with insurance and financial risks. Within period i ≥ 1, the real-valued net insurance loss caused by claims is the insurance risk, denoted by Xi, and the positive stochastic discount factor over the same time period is the financial risk, denoted by Yi. Assume that {(X, Y), (Xi, Yi), i ≥ 1} form a sequence of independent identically distributed random vectors. In this paper, we investigate a discrete-time risk model allowing a dependence structure between the two risks. When (X, Y ) follows a bivariate Sarmanov distribution and the distribution of the insurance risk belongs to the class ℒ(γ) for some γ > 0, we derive the asymptotics for the finite-time ruin probability of this discrete-time risk model. [ABSTRACT FROM AUTHOR]

We consider a discrete-time risk model with insurance and financial risks. Within period i ≥ 1, the real-valued net insurance loss caused by claims is the insurance risk, denoted by Xi, and the positive stochastic discount factor over the same time period is the financial risk, denoted by Yi. Assume that {(X, Y), (Xi, Yi), i ≥ 1} form a sequence of independent identically distributed random vectors. In this paper, we investigate a discrete-time risk model allowing a dependence structure between the two risks. When (X, Y ) follows a bivariate Sarmanov distribution and the distribution of the insurance risk belongs to the class ℒ(γ) for some γ > 0, we derive the asymptotics for the finite-time ruin probability of this discrete-time risk model. [ABSTRACT FROM AUTHOR]

Liquid chromatography with electrochemical detection (LC-ED), coupled with in vivo microdialysis sampling, has been used for analysis of thiols. An acetylene black–dihexadecyl hydrogen phosphate (AB–DHP) composite film-modified electrode was used as working electrode. The AB–DHP-modified electrode enabled efficient electrocatalytic oxidation of l-cysteine ( l-Cys) and glutathione (GSH) with relatively high sensitivity, stability, and longevity. The peak currents of l-Cys and GSH were linear in the concentrations ranges 2.0 × 10–2.0 × 10 and 3.0 × 10–5.0 × 10 mol L, respectively, with calculated detection limits (S/N = 3) of 1.0 × 10 and 2.0 × 10 mol L, respectively. The method has been successfully used to measure the amounts of l-Cys and GSH in striatal microdialysate of freely moving rats. [ABSTRACT FROM AUTHOR]