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• A reaction-diffusion fractional-order model for M1 oncolytic virotherapy with CTL immune response is presented. • Threshold parameters and equilibria are determined. • Stability analysis are rigorously established. • Numerical simulations are given to illustrate the analytical results. Despite many years of research, cancer continues to be a major worldwide concern. Several researchers proposed their mathematical models to understand and describe the dynamics of tumor cells under some cancer treatments. In this paper, we present a fractional partial differential equation system to describe the dynamics in space and time of the concentration of normal cells, tumor cells, nutrient, M1 virus, and cytotoxic T lymphocytes (CTL) cells, as well as the interaction between them. We study and analyze the equilibrium points of the presented system. The global stability of these equilibrium points is proved by constructing adequate Lyapunov functional for each equilibrium point. Furthermore, we give some numerical simulations to illustrate our results. [ABSTRACT FROM AUTHOR]

Type 1 diabetes (T1D), previously known as juvenile diabetes or insulin-dependent diabetes, is an autoimmune disease characterized by the insufficient (or lack of) production of insulin by the pancreas. Insulin is crucial to maintain blood sugar at healthy levels. High blood sugar damages the body and causes a variety of symptoms, ranging from severe thirst, fatigue, to urinary infections. The cells responsible for the production of insulin are the β -cells. In T1D, these are killed by an abnormal response of the immune system. Specific clones of cytotoxic T-cells invade the pancreatic islets of Langerhans, and eliminate them. T1D diabetes may develop in human immunodeficiency virus (HIV)-infected patients, though in rare situations. In this paper, we propose a cell model for the development of T1D in these patients, after immune restoration, during highly active antiretroviral therapy (HAART). The study includes the derivation of the qualitative properties of the model, and its comprehensive investigation via path-following methods, using the continuation platform COCO. In this way, the main theoretical predictions are verified in detail. Furthermore, this numerical part establishes accurate parameter thresholds to ensure an effective disease treatment in HIV-infected persons to prevent the development of T1D. [ABSTRACT FROM AUTHOR]

This paper proposes and analyzes an adaptive immunity HIV infection model. The model describes the interaction between healthy CD 4 + T cells, silent (latent) infected cells, active infected cells, free HIV particles, Cytotoxic T lymphocytes (CTLs) and antibodies. The healthy CD 4 + T cells can be infected when they are contacted by one of the following: (i) free HIV particles, and this is known as virus-to-cell (VTC) transmission (ii) silent infected cells, and we call this mode of infection as silent HIV-infected cell-to-cell (CTC) transmission, and (iii) active infected cells, and we call this mechanism active HIV-infected CTC transmission. The incidence rates of the healthy CD 4 + T cells with free HIV particles, silent infected cells, and active infected cells are given by general functions. Moreover, the production/proliferation and removal/death rates of all compartments are represented by general functions. The model is an improvement of the existing HIV infection models which have neglected the incidence between the silent infected cells and healthy CD 4 + T cells. We first show that the model is well-posed. Then, we show that the model has five equilibria and their existence are governed by five threshold parameters. Under a set of conditions on the general functions and the threshold parameters, we have proven the global asymptotic stability of all equilibria by using Lyapunov's method. We have illustrated the theoretical results via numerical simulations. We have studied the effect of CTC transmission on the dynamical behavior of the system. We have shown that inclusion of CTC transmission decreases the concentration of the healthy CD4 + T cells and increases the concentrations of the infected cells and free HIV particles. [ABSTRACT FROM AUTHOR]