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In this paper, we investigate a stochastic human immunodeficiency virus (HIV) model with logistic growth and Ornstein-Uhlenbeck process, which is used to describe the pathogenesis and transmission dynamics of HIV in the population. We first validate that the stochastic system has a unique global solution with any initial value. Then we use a novel Lyapunov function method to establish sufficient conditions for the existence of a stationary distribution of the system, which shows the coexistence of all CD4+ T cells and free viruses. Especially, under some mild conditions which are used to ensure the local asymptotic stability of the quasi-chronic infection equilibrium of the stochastic system, we obtain the specific expression of covariance matrix in the probability density around the quasi-chronic infection equilibrium of the stochastic system. In addition, for completeness, we also obtain sufficient criteria for elimination of all infected CD4+ T cells and free virus particles. Finally, several examples together with comprehensive numerical simulations are conducted to support our analytic results. [ABSTRACT FROM AUTHOR]

In this paper, we establish and analyze a stochastic human immunodeficiency virus model with both virus-to-cell and cell-to-cell transmissions and Ornstein–Uhlenbeck process, in which we suppose that the virus-to-cell infection rate and the cell-to-cell infection rate satisfy the Ornstein–Uhlenbeck process. First, we validate that there exists a unique global solution to the stochastic model with any initial value. Then, we adopt a stochastic Lyapunov function technique to develop sufficient criteria for the existence of a stationary distribution of positive solutions to the stochastic system, which reflects the strong persistence of all CD4+ T cells and free viruses. In particular, under the same conditions as the existence of a stationary distribution, we obtain the specific form of the probability density around the quasi-chronic infection equilibrium of the stochastic system. Finally, numerical simulations are conducted to validate these analytical results. Our results suggest that the methods used in this paper can be applied to study other viral infection models in which the infected CD4+ T cells are divided into latently infected and actively infected subgroups. [ABSTRACT FROM AUTHOR]

The human immunodeficiency virus (HIV) interacts with the immune cells within the human body, where the environment is uncertain and noisy. Stochastic models can successfully encapsulate the effect of such a noisy environment compared to their deterministic counterparts. The human immune system is complex but well-coordinated with various immune cells like C D 4 + T cells, dendritic cells, and cytotoxic T-lymphocyte (CTL) cells, among many others. The CTL can kill the antigenic cells after its recognition. However, the efficacy of CTL in removing the infected C D 4 + T cells is progressively compromised in HIV-infected individuals. This paper considers a noise-induced HIV-immune cell interaction model with immune impairment. A multiplicative white noise is introduced in the infection rate parameter to represent the fluctuations around the average value of the rate parameter as a causative effect of the noise. We analyzed the deterministic and stochastic models and prescribed sufficient conditions for infection eradication and persistence. It is determined under what parametric restrictions the asymptotic solutions of the noise-induced system will be a limiting case of the deterministic solutions. Simulation results revealed that the solutions of the deterministic system either converge to a CTL-dominated interior equilibrium or a CTL-free immunodeficient equilibrium, depending on the initial values of the system. Stochastic analysis divulged that higher noise might be helpful in the infection removal process. The extinction time of infected C D 4 + T cells for some fixed immune impairment gradually decreases with increasing noise intensity and follows the power law. [ABSTRACT FROM AUTHOR]

The signal transduction of human programmed death ligand 1 (PD-L1), as an important checkpoint gene in the immune system, plays a key role in the internal function and survival of cancer cells. In this paper, PD-L1-siRNA and immunostimulatory IL-2 encoding plasmid DNA loaded by polyethylenimine (PEI) lipid nanoparticles (PEI-LNPs) were constructed. Its therapeutic effect on lung cancer was evaluated, and its physical parameters such as particle size and potential were measured. The binding capacity, cytotoxicity, apoptosis, and cell uptake capacity of PD-L1-siRNA/IL-2 DNA-PEI-LNPs were tested by in vitro experiments. The down-regulation effect of PD-L1 in A549 cancer cells and the cytokine level of co-cultured T cells were also examined. The study indicated that the PD-L1-siRNA/IL-2-PEI-LNP complexes can provide effective treatment for lung cancer cells; the significant increase in IFN-γ and TNF-α levels and the decrease in the IL-10 level confirmed the change in secreted cytokines. The lipid NPs combined with the tumor-targeting therapeutic gene siRNA/pDNA constructed in this study had the ability to target cells in vitro and down-regulate the expression of PD-L1, which realized the tumor-specific expression of immunostimulatory cytokines, and were considered to be highly effective and safe nanocarriers for targeted therapy. [ABSTRACT FROM AUTHOR]

T lymphocytes (T cells) play an important role in orchestrating an adaptive immune response in complex organisms. Recent experiments have shown that when T cells recognize antigen presenting cells, a complex and large-scale reorganization of intercellular membrane proteins and cell shape occurs. The resulting motif is implicated in information transfer between T cells and antigen presenting cells, and has been labeled the immunological synapse. Numerical solutions of a mathematical model that incorporates binding kinetics, protein mobility, and down regulation, and membrane mechanics has proven successful in describing some of these observations. In this paper, we analyze the equations that describe this model, and this sheds light on the origins of pattern formation in the immunological synapse. In particular, the thermodynamic considerations and dynamic instabilities that lead to pattern formation in and out of equilibrium are elucidated. [ABSTRACT FROM AUTHOR]

1, PD-L1-SiRNA should be wrapped by PEI-LNP, so PD-L1-SiRNA in the flow chart should be placed in DOPC and other raw materials, and the binding method of PD-L1 antibody and PEI-LNP was incorrectly suggested in the article. The Editor and the Publisher of AIP Advances (ADV) have retracted the referenced paper due to the following data errors and omissions. [Extracted from the article]

This paper presents the design, fabrication, and testing of a magnetophoretic bioseparation chip for the rapid isolation and concentration of CD4 + T cells from the peripheral blood. In a departure from conventional magnetic separation techniques, this microfluidic-based bioseperation device has several unique features, including locally engineered magnetic field gradients and a continuous flow with a buffer switching scheme to improve the performance of the separation process. Additionally, the chip is capable of processing significantly smaller sample volumes than conventional methods and sample losses are eliminated due to decreased handling. Furthermore, the possibility of sample-to-sample contamination is reduced with the disposable format. The overall dimensions of the device were 22 mm by 60 mm by 1 mm, approximately the size of a standard microscope slide. The results indicate a cell purity of greater than 95% at a sample flow rate of 50 ml/h and a cell recovery of 81% at a sample flow rate of 10 ml/h. The cell purity was found to increase with increasing the sample flow rate. However, the cell recovery decreases with an increase in the flow rate. A parametric study was also performed to investigate the effects of channel height, substrate thickness, magnetic bead size, and number of beads per cell on the cell separation performance. [ABSTRACT FROM AUTHOR]