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The anti-hyperglycemic and immunomodulatory activities of the ethanol extract from Paecilomyces Hepiali Chen (PHC), a Chinese medicine, were investigated in streptozotocin-induced type 1 diabetic (T1DM) mice. Male Balb/c mice, which were i.p. injected with streptozotocin (STZ, 50 mg/kg, for 5 consecutive days) on Day 7, were orally administered saline (the normal control and diabetic control group), Metformin (60 mg/kg, b.w., positive group), or the extract (100 mg/kg, b.w., PHC prevention group) from Day 1 to Day 28, Mice i.p. injected with streptozotocin (STZ, 50 mg/kg, b.w.) for 5 consecutive days prior to PHC treatment (100 mg/kg, b.w.) were used as the PHC treatment group. The effects of PHC on postprandial blood glucose concentrations, plasmatic insulin levels, morphology of pancreatic β cells and CD4⁺ T cells proliferation after 28-day treatment were monitored. Results showed that PHC administered 6 days before STZ induction of diabetes in mice significantly decreased blood glucose level (p < 0.01). An increase of insulin level was also observed as compared to those in the diabetic control group (p < 0.01). In addition, fewer inflammatory cells infiltrated the pancreatic islet and fewer β cells death by apoptosis within the inflamed islets were observed. More importantly, the CD4⁺ T cell proliferation was remarkably attenuated ex vivo in mice preventively treated with PHC (p < 0.01). In comparison to the PHC prevention group, no significant hypoglycemia, changes of insulin level and β cell protection were observed in mice treated with PHC after STZ administration. Our findings demonstrated that preventive administration of PHC protected β cells from apoptosis in type 1 diabetes induced by STZ, and the underlying mechanism may be involved in suppressing CD4⁺ T cells reaction, reducing inflammatory cells infiltration and protecting beta cell apoptosis in pancreatic islet.

In this paper, we present a dynamical model to study the spread of HIV-1 in vivo. Our goal is to better understand the interaction between HIV-1 and the human immune system. Making use of the Hill function, we describe two kinds of processions occurring in the immune response: the activation interactions or inhibitory interactions occurring between different components in the immune response, and the autocatalytic maintenance of the CD4+ T cells and CD8+ T cells populations. We also consider the impact of the cytokine interleukin-2 (IL-2) and the CD8 antiviral factor (CAF) on HIV-1 infection. Through numerical simulations we get several results. First, we find that the effects of IL-2 and CAF in the treatment for the infected are limiting. Namely, the curative effect will not always increase along with the dose of IL-2 or CAF or both. The increasing trend will stagnate at a certain dose that we used. Second, we find some possible reasons for the collapse of the lymph system in HIV-1 infection — the loss of these restraining functions, and/or the genetic variability of the virus due to immune escape that enhances the virulence, which then bring the collapse of the immune system. In some conditions the system will produce a Hopf bifurcation. We also simulate the theoretical warrant of the feasibility of the combined chemotherapy strategies for the HIV-1 infected patient.

A mathematical model for the effect of Reverse Transcriptase (RT) Inhibitor on the dynamics of HIV is proposed and analyzed. Further, with help of numerical simulations, the relation between efficacy of administered drug, the total number of virus particles emitted from the infected cell and the transition period is also discussed.

A number of lines of evidence suggest that immunotherapy with the cytokine interleukin-2 (IL-2) may boost the immune response to fight HIV infection. CD4⁺ T cells, the cells which orchestrate the immune response, are also the cells that become infected by the HIV virus. These cells use cytokines as signaling mechanisms for immune-response stimulation, growth and differentiation. Since CD4⁺ T cells are hampered due to HIV infection, normal signaling, and the resulting cascade, may not occur. Introduction of IL-2 into the system can restore or enhance these effects. We illustrate, through mathematical modeling, the effects of IL-2 treatment on an HIV-infected patient. With good comparison to existing clinical data, we can better understand what mechanisms of immune-viral dynamics are necessary to produce the typical disease dynamics.

This paper investigates the stochastic HTLV-I infection model with CTL immune response, and the corresponding deterministic model has two basic reproduction numbers. We consider the nonlinear CTL immune response for the interaction between the virus and the CTL immune cells. Firstly, for the theoretical needs of system dynamical behavior, we prove that the stochastic model solution is positive and global. In addition, we obtain the existence of ergodic stationary distribution by stochastic Lyapunov functions. Meanwhile, sufficient condition for the extinction of the stochastic system is acquired. Reasonably, the dynamical behavior of deterministic model is included in our result of stochastic model when the white noise disappears.

The main target of both human immunodeficiency virus type 1 (HIV-1) and human T-lymphotropic virus type I (HTLV-I) is the CD4⁺ T cell which is considered the key player in the immune system. Moreover, HIV-1 has another target that is the macrophages. The present paper aims to formulate and develop a mathematical model to analyze the interaction of two viruses, HIV-1 and HTLV-I with the immune system. We determine a bounded domain for the concentrations of the model’s compartments. We discuss the dynamical behavior of the model and analyze the existence and stability of the system’s steady states. The global asymptotic stability of all steady states is proven by utilizing the Lyapunov method. We also demonstrate the dynamical behavior of the system numerically. The significant impact of macrophages on the HTLV-I/HIV-1 co-infection dynamics is discussed. Our developed model will contribute to the understanding of HTLV-I/HIV-1 co-infection dynamics and help to choose different treatment strategies against HIV-1 and HTLV-I.