Search

In this paper, a dynamic HIV model with cell-to-cell transmission, two immune responses, and induced apoptosis is proposed and studied. First, the non-negativity and boundedness of the solutions of the model are given, and then the exact expression of the basic reproduction number R0 is obtained by using the next generation matrix method. Second, criteria are obtained for the local stability of the disease-free equilibrium, immune response-free equilibrium, and the infected equilibrium with both humoral and cellular immune responses. Furthermore, the threshold conditions are also derived for the global asymptotic stability of the disease-free equilibrium, immune responsefree equilibrium, and the infected equilibrium with both humoral and cellular immune responses by constructing the suitable Lyapunov function. Finally, some numerical simulations are conducted to verify the theoretical results; the numerical simulation results show that the increase of apoptosis rate had a positive role in the control of viral infection. [ABSTRACT FROM AUTHOR]

In this paper, a fractional order HIV/HTLV co-infection model with HIV-specific antibody immune response is established. Two cases are considered: constant control and optimal control. For the constant control system, the existence and uniqueness of the positive solutions are proved, and then the sufficient conditions for the existence and stability of five equilibriums are obtained. For the second case, the Pontryagin's Maximum Principle is used to analyze the optimal control, and the formula of the optimal solution are derived. After that, some numerical simulations are performed to validate the theoretical prediction. Numerical simulations indicate that in the case of HIV/HTLV co-infection, the concentration of CD4+T cells is no longer suitable as an effective reference data for understanding the development process of the disease. On the contrary, the number of HIV virus particles should be used as an important indicator for reference. [ABSTRACT FROM AUTHOR]

The gut microbiota (GM), as a forgotten organ, refers to the microbial community that resides in the gastrointestinal tract and plays a critical role in a variety of physiological activities in different body organs. The GM affects its targets through neurological, metabolic, immune, and endocrine pathways. The GM is a dynamic system for which exogenous and endogenous factors have negative or positive effects on its density and composition. Since the mid-twentieth century, laboratory animals are known as the major tools for preclinical research; however, each model has its own limitations. So far, two main models have been used to explore the effects of the GM under normal and abnormal conditions: the isolated germ-free and antibiotic-treated models. Both methods have strengths and weaknesses. In many fields of host-microbe interactions, research on these animal models are known as appropriate experimental subjects that enable investigators to directly assess the role of the microbiota on all features of physiology. These animal models present biological model systems to either study outcomes of the absence of microbes, or to verify the effects of colonization with specific and known microbial species. This paper reviews these current approaches and gives advantages and disadvantages of both models. [ABSTRACT FROM AUTHOR]

In this paper, a mathematical model for HIV-1 infection and immune response is considered, involving two discrete time delays in the intracellular as well as in activation of immune response. Using a recently developed geometric method for studying a class of transcendental equation with two time delays and delay dependent coefficients, we obtain the stability and bifurcation results at the non-trivial equilibrium. In particular, the crossing curves on the two-delays parameter plane can be completely characterized, on which Hopf and double-Hopf bifurcation will take place. In the case of Hopf bifurcation, there exist stability switches, and the direction and stability of delay induced Hopf-bifurcation can be determined using normal form theory and center manifold theorem. These results imply the model will exhibit complex temporal dynamics, such as period oscillations, quasi-periodic solutions, etc. Numerical examples are also carried out to verify these results. [ABSTRACT FROM AUTHOR]

New cancer therapies, methods and protocols are needed to treat affected patients. Oncolytic viral therapy is a good suggestion for such treatment. This paper proposes a diffusive cancer model with virotherapy and an immune response. This work aims to study the aforementioned model while theoretically including positivity, boundedness and stability, as well as to find the analytical solutions. The analytical solutions are found by using the tanh-expansion method. As a result, we realized that the relative immune cell killing rate can be controlled by the viral burst size. The viral burst size is the number of viruses released from each infected cell during cell lysis. The increasing diffusion of the activated immune system leads to an increase in the uninfected cells. The presented model can be used to study the combination of immunotherapy and virotherapy. [ABSTRACT FROM AUTHOR]

This paper is devoted to proposing a mathematical model in order to explore the dynamics of HTLV-Ⅰ (human T-cell leukemia virus type-Ⅰ) infection, in which the closely related target cell-virus-immune system interaction and the time-delay cytotoxic T lymphocyte (CTL) immune response are taken into consideration. Firstly, we give the relevant lemma for the existence of feasible equilibrium points of the model, and then further certify the global asymptotic stabilities of the infection-free equilibrium (IFFE) $ E_1 $ and the immune-free equilibrium (IMFE) $ E_2 $. Furthermore, we research the existence of Hopf bifurcation (HB) occurring at the immune equilibrium (IE) $ E^* $ due to the influence of the delay bifurcation parameter. Also, the numerical simulations confirm this fact. In addition, we obtain the explicit expressions which determine the direction and stability of HB. Finally, a succinct discussion shows that the delay in CTL response can destabilize $ E^* $ and generate HB, but not affect stabilities of $ E_1 $ and $ E_2 $. [ABSTRACT FROM AUTHOR]

Phase is the most fundamental physical quantity when we study an oscillatory time series. There have been many tools aiming to estimate phase, and most of them are developed based on the analytic function model. Unfortunately, these analytic function model based tools might be limited in handling modern signals with intrinsic nonstartionary structure, for example, biomedical signals composed of multiple oscillatory components, each with time-varying frequency, amplitude, and non-sinusoidal oscillation. There are several consequences of such limitation, and we specifically focus on the one that phases estimated from signals simultaneously recorded from different sensors for the same physiological system from the same subject might be different. This fact might challenge reproducibility, communication, and scientific interpretation. Thus, we need a standardized approach with theoretical support over a unified model. In this paper, after summarizing existing models for phase and discussing the main challenge caused by the above-mentioned intrinsic nonstartionary structure, we introduce the adaptive non-harmonic model (ANHM), provide a definition of phase called fundamental phase, which is a vector-valued function describing the dynamics of all oscillatory components in the signal, and suggest a time-varying bandpass filter (tvBPF) scheme based on time-frequency analysis tools to estimate the fundamental phase. The proposed approach is validated with a simulated database and a real-world database with experts' labels, and it is applied to two real-world databases, each of which has biomedical signals recorded from different sensors, to show how to standardize the definition of phase in the real-world experimental environment. We report that the phase describing a physiological system, if properly modeled and extracted, is immune to the selected sensor for that system, while other approaches might fail. In conclusion, the proposed approach resolves the above-mentioned scientific challenge. We expect its scientific impact on a broad range of applications. [ABSTRACT FROM AUTHOR]

Food allergies are of great public health concern due to their rising prevalence. Our understanding of how the immune system reacts to food remains incomplete. Allergic responses vary between individuals with food allergies. This variability could be caused by genetic, environmental, hormonal, or metabolic factors that impact immune responses mounted against allergens found in foods. Peanut (PN) allergy is one of the most severe and persistent of food allergies, warranting examination into how sensitization occurs to drive IgE-mediated allergic reactions. In recent years, much has been learned about the mechanisms behind the initiation of IgE-mediated food allergies, but additional questions remain. One unresolved issue is whether sex hormones impact the development of food allergies. Sex differences are known to exist in other allergic diseases, so this poses the question about whether the same phenomenon is occurring in food allergies. Studies show that females exhibit a higher prevalence of atopic conditions, such as allergic asthma and eczema, relative to males. Discovering such sex differences in allergic diseases provide a basis for investigating the mechanisms of how hormones influence the development of IgE-mediated reactions to foods. Analysis of existing food allergy demographics found that they occur more frequently in male children and adult females, which is comparable to allergic asthma. This paper reviews existing allergic mechanisms, sensitization routes, as well as how sex hormones may play a role in how the immune system reacts to common food allergens such as PN. [ABSTRACT FROM AUTHOR]

In this paper, a biophysical fractional diffusive cancer model with virotherapy is thoroughly analyzed and analytically simulated. The goal of this biophysical model is to represent both the dynamics of cancer development and the results of virotherapy, which uses viruses to target and destroy cancer cells. The Caputo sense is applied to the fractional derivatives. We look at the governing model's existence and uniqueness. For analytical solutions, the Laplace residual power series approach is used. The study investigates the model's dynamic behavior, shedding light on the development of cancer and the effects of virotherapy. The research advances our knowledge of cancer modeling and treatment options. Numerical simulations show the agreement between the analytical results and the related numerical solutions, proving the usefulness of the analytical solution. [ABSTRACT FROM AUTHOR]

In this paper, we study two-dimensional, three-dimensional monotonic and nonmonotonic immune responses in viral infection systems. Our results show that the viral infection systems with monotonic immune response has no bistability appear. However, the systems with nonmonotonic immune response has bistability appear under some conditions. For immune intensity, we got two important thresholds, post-treatment control threshold and elite control threshold. When immune intensity is less than post-treatment control threshold, the virus will be rebound. The virus will be under control when immune intensity is larger than elite control threshold. While between the two thresholds is a bistable interval. When immune intensity is in the bistable interval, the system can have bistability appear. Select the rate of immune cells stimulated by the viruses as a bifurcation parameter for nonmonotonic immune responses, we prove that the system exhibits saddle-node bifurcation and transcritical bifurcation. [ABSTRACT FROM AUTHOR]

In this paper, we investigate an in-host model for the viral dynamics of HIV-1 infection and its interaction with the CTL immune response. The model is sufficiently general to allow nonlinear forms for both viral infection and CTL response. Threshold parameters are identified that completely determine the global dynamics and outcomes of the virus-target cell-CTL interactions. Impacts of key parameter values for CTL functions and viral budding rate on the HIV-1 viral load and CD4 count are investigated using numerical simulations. Results support clinical evidence for important differences between HIV-1 nonprogressors and progressors. [ABSTRACT FROM AUTHOR]

Tuberculosis infection is still a major threat to humans and it may progress slowly or rapidly to clearance, latent infection, or active disease. In this paper, considering T cells can perform acceleration effect on their own recruitment, an in-host model of Mycobacterium tuberculosis is studied. Focus type and elliptic type of nilpotent singularities of codimension 3 are analyzed in this four dimensional model. Complex dynamical behaviors such as homoclinic loop, saddle-node bifurcation of limit cycle and co-existence of two limit cycles are revealed by bifurcation analysis. Especially, the slow-fast periodic solution with large-amplitude or small-amplitude is observed in numerical simulations, which provides a perfect explanation for the reactivation of latent infection. [ABSTRACT FROM AUTHOR]

This paper aims to show the global behaviour of a viral kinetic model with two time delays and general incidence rate. For the basic reproduction number Ro < 1, the disease-free equilibrium is shown to be globally asymptotically stable by constructing Lyapunov functional and using LaSalle invariance principle. For the basic reproduction number Ro > 1, the interior equilibrium of model exists and is also globally asymptotically stable. Our work show more general conclusion than other known papers on delayed viral models. [ABSTRACT FROM AUTHOR]

In this paper, the dynamical behaviors of a viral infection model with cytotoxic T-lymphocyte (CTL) immune response, immune response delay and production delay are investigated. The threshold values for virus infection and immune response are established. By means of Lyapunov functionals methods and LaSalle's invariance principle, sufiicient conditions for the global stability of the infection-free and CTL-absent equilibria are established. Global stability of the CTL-present infection equilibrium is also studied when there is no immune delay in the model. Furthermore, to deal with the local stability of the CTL-present infection equilibrium in a general case with two delays being positive, we extend an existing geometric method to treat the associated characteristic equation. When the two delays are positive, we show some conditions for Hopf bifurcation at the CTL-present infection equilibrium by using the immune delay as a bifurcation parameter. Numerical simulations are performed in order to illustrate the dynamical behaviors of the model. [ABSTRACT FROM AUTHOR]

This paper presents a mathematical model for immune response against cancer aimed at reproducing emerging phenomena arising from the interactions between tumor and immune cells. The model is stated in terms of integro-differential equations and describes the dynamics of tumor cells, characterized by heterogeneous antigenic expressions, antigen-presenting cells and T-cells. Asymptotic analysis and simulations, developed with an exploratory aim, are addressed to verify the consistency of the model outputs as well as to provide biological insights into the mechanisms that rule tumor-immune interactions. In particular, the present model seems able to mimic the recognition, learning and memory aspects of immune response and highlights how the immune system might act as an additional selective pressure leading, eventually, to the selection for the most resistant cancer clones. [ABSTRACT FROM AUTHOR]

Let HIV infection be modeled by a dynamical system with a Michaelis-Mente-type immune response. A functional cure refers to driving the system from a stable high-viral-load state to a stable low-viral-load state. This may occur only when at least two stable equilibrium states coexist in the system. This paper analyzes how the number of biologically meaningful equilibrium states varies with system parameters. Meanwhile, it investigates how patients' profiles of immune responses determine their clinical outcomes, with focus on functional curability. The analysis provides a criterion that a functional cure is possible only if the capability of immune stimulation starts to attenuate when the density of infected cells is below a threshold. From treatment viewpoints, such a criterion is crucial because it identifies which patients cannot use a low-viral-load state as a treatment endpoint. The deriving process also provides a method to study functional curability problems with a wider class of immune response functions and functional curability problems of similar virus infections such as chronic hepatitis B virus infection. [ABSTRACT FROM AUTHOR]

Oncolytic virotherapy is a viable chemotherapeutic agent that identifies and kills tumor cells using replication-competent pathogens. Oncolytic alphavirus M1 is a naturally existing disease that has been shown to have rising specificity and potency in cancer progression. The objective of this research is to introduce and analyze an oncolytic M1 virotherapy framework with spatial variability and anti-tumor immune function via piecewise fractional differential operator techniques. To begin, we potentially demonstrate that the stochastic system's solution is non-negative and global by formulating innovative stochastic Lyapunov candidates. Then, we derive the existence-uniqueness of an ergodic stationary distribution of the stochastic framework and we establish a sufficient assumption ... extermination of tumor cells and oncolytic M1 virus. Using meticulous interpretation, this model allows us to analyze and anticipate the procedure from the start to the end of the tumor because it allows us to examine a variety of behaviours ranging from crossover to random mechanisms. Furthermore, the piecewise differential operators, which can be assembled with operators including classical, Caputo, Caputo-Fabrizio, Atangana-Baleanu, and stochastic derivative, have decided to open up innovative avenues for readers in various domains, allowing them to encapsulate distinct characteristics in multiple time intervals. Consequently, by applying these operators to serious challenges, scientists can accomplish better outcomes in documenting facts. [ABSTRACT FROM AUTHOR]

A mathematical model was built using delay differential equations to investigate the effect of active and passive immunotherapies in delaying the progression of Parkinson's Disease. The model described the dynamics between healthy and infected neurons and alpha-synuclein with innate and adaptive immune responses. The model was examined qualitatively and numerically. The qualitative analysis produced two equilibrium points. The local stability of the free and endemic equilibrium points was established depending on the basic reproduction number, R0. Numerical simulations were executed to show the agreement with the qualitative results. Moreover, a sensitivity analysis on R0 was conducted to examine the critical parameters in controlling R0. We found that if treatment is administered in the early stages of the disease with short time delays, alpha-synuclein is combated, inhibiting activated microglia and T cells and preserving healthy neurons. It can be concluded that administering time of immunotherapies plays a significant role in hindering the advancement of Parkinson's disease. [ABSTRACT FROM AUTHOR]

Human T-cell Lymphotropic virus type 1(HTLV-I) causes HAM/T SP and other illnesses. HTLV-I mainly infects CD4 + T cells and activates HTLV-I-specific immune response. In this paper, we formulate a mathematical model of HTLV-I to investigate the role of selective mitotic transmission, Tax expression, and CTL response in vivo. We define two parameters (R0 and R1) to study the model dynamics. The unique infection-free equilibrium P0 is globally asymptomatic stable if R0 < 1. There exists the chronic-infection equilibrium P1 if R1 < 1 < R0. There exists a unique chronic-infection equilibrium P2 if R1 > 1. There is a backward bifurcation of chronic-infection equilibria with CTL response if R1 < 1 < R0. The numerical simulations shown that the existence of backward bifurcation may lead to the existence of periodic solutions. [ABSTRACT FROM AUTHOR]

In this paper, a delayed viral infection model with nonlinear immune response and general incidence rate is discussed. We prove the existence and uniqueness of the equilibria. We study the effect of three kinds of time delays on the dynamics of the model. By using the Lyapunov functional and LaSalle invariance principle, we obtain the conditions of global stabilities of the infection-free equilibrium, the immune-exhausted equilibrium and the endemic equilibrium. It is shown that an increase of the viral-infection delay and the virus-production delay may stabilize the infection-free equilibrium, but the immune response delay can destabilize the equilibrium, leading to Hopf bifurcations. Numerical simulations are given to verify the analytical results. This can provide a possible interpretation for the viral oscillation observed in chronic hepatitis B virus (HBV) and human immunodeficiency virus (HIV) infected patients. [ABSTRACT FROM AUTHOR]

In this study, we develop a diffusive HIV-1 infection model with intracellular invasion, production and latent infection distributed delays, nonlinear incidence rate and nonlinear CTL immune response. The well-posedness, local and global stability for the model proposed are carefully investigated in spite of its strong nonlinearity and high dimension. It is revealed that its threshold dynamics are fully determined by the viral infection reproduction number [Math Processing Error] R 0 and the reproduction number of CTL immune response [Math Processing Error] R 1. We also observe that the viral load at steady state (SS) fails to decrease even if [Math Processing Error] R 1 increases through unit to lead to a stability switch from immune-inactivated infected SS to immune-activated infected SS. Finally, some simulations are performed to verify the analytical conclusions and we explore the significant impact of delays and CTL immune response on the spatiotemporal dynamics of HIV-1 infection. [ABSTRACT FROM AUTHOR]

Clinical pharmacology is a multidisciplinary function playing a critical role in the monoclonal antibody development. Besides the requirements of understanding pharmacology, pharmacokinetics, model simulation, biostatistics and immunogenicity, wisely implementation of tactics and strategies to fulfill the agencies' requirements per guidance documents are critical. In this review, clinical pharmacology studies categorized as required, target dependent, development strategy dependent, and not usually needed are discussed. The review ends with the outlook of recent initiations in the clinical pharmacology such as the application of QSP with the integration of AI and machine learning technologies. [ABSTRACT FROM AUTHOR]

This paper develops and analyzes an age-structured model of HIV infection with various compartments, including target cells, infected cells, viral loads and immune effector cells, to provide a better understanding of the interaction between HIV and the immune system. We show that the proposed model has one uninfected steady state and several infected steady states. We conduct a local stability analysis of these steady states by using a generalized Jacobian matrix method in conjunction with the Laplace transform. In addition, we consider various techniques and ideas from optimal control theory to derive optimal therapy protocols by using two types of dynamic treatment methods representing reverse transcriptase inhibitors and protease inhibitors. We derive the necessary conditions (an optimality system) for optimal control functions by considering the first variations of the Lagrangian. Further, we obtain optimal therapy protocols by solving a large optimality system of equations through the use of a difference scheme based on the Runge-Kutta method. The results of numerical simulations indicate that the optimal therapy protocols can facilitate long-term control of HIV through a strong immune response after the discontinuation of the therapy. [ABSTRACT FROM AUTHOR]

Body‟s defence mechanism has ability to combat tumour cells but tumour cells can circumvent immune system in order to flourish. Therefore, current research focuses on reinvigorating immune system to combat against extensive range of human malignancies through immunotherapy. Recently, immuno-therapy has demonstrated beneficial outcomes in cancers treatment but the main drawbacks are primary and acquired resistance to the therapeutic agents and immune-related toxicities. Therefore, novel immune therapies are direly required. Co-stimulatory molecules such as TNF Receptor Superfamily Member 4 (OX40, CD134) and its ligand TNF Superfamily Member 4 (CD252, OX40L) are expressed on different immune cells. The mutual interaction between OX40 and its ligand (OX40/OX40L) decreases the functional capacity of immunosuppression offered by regulatory T cells (Tregs) and induces the proliferation of T cells against specific antigen enhancing the immune response. Many clinical trials are focusing on OX40/OX40L therapeutic agents to find out whether they have therapeutic effect on cancer treatment. The initial phase trials result of OX40 and its ligands focusing therapeutic agents are encouraging but still not sufficient. This review will concentrate on the cellular and molecular pathways of OX40-mediated T-cell co-stimulation, the expression of OX40 and OX40L in tumours, the implications of their interactions and their under-or over-expression patterns, with particular focus on the function of OX40 in tumours of different origins. Finally, we discuss results of clinical trials of OX40 and OX40L directed pharmacotherapy and the lacunae that need to be filled. [ABSTRACT FROM AUTHOR]

To study the emergence and evolution of drug resistance during treatment of HIV infection, we study a mathematical model with two strains, one drug-sensitive and the other drug-resistant, by incorporating cytotoxic T lymphocyte (CTL) immune response. The reproductive numbers for each strain with and without the CTL immune response are obtained and shown to determine the stability of the steady states. By sensitivity analysis, we evaluate how the changes of parameters influence the reproductive numbers. The model shows that CTL immune response can suppress the development of drug resistance. There is a dynamic relationship between antiretroviral drug administration, the prevalence of drug resistance, the total level of viral production, and the strength of immune responses. We further investigate the scenario under which the drug-resistant strain can outcompete the wild-type strain. If drug efficacy is at an intermediate level, the drug-resistant virus is likely to arise. The slower the immune response wanes, the slower the drug-resistant strain grows. The results suggest that immunotherapy that aims to enhance immune responses, combined with antiretroviral drug treatment, may result in a functional control of HIV infection. [ABSTRACT FROM AUTHOR]

We propose a model of tumor-immune interaction with time delay in immune reaction and noise in tumor cell reproduction. Immune response is modeled as a non-monotonic function of tumor burden, for which the tumor is immunogenic at nascent stage but starts inhibiting immune system as it grows large. Without time delay and noise, this system demonstrates bistability. The effects of response time of the immune system and uncertainty in the tumor innate proliferation rate are studied by including delay and noise in the appropriate model terms. Stability, persistence and extinction of the tumor are analyzed. We find that delay and noise can both induce the transition from low tumor burden equilibrium to high tumor equilibrium. Moreover, our result suggests that the elimination of cancer depends on the basal level of the immune system rather than on its response speed to tumor growth. [ABSTRACT FROM AUTHOR]

It is well known that CTL (cytotoxic T lymphocyte) immune response could be broadly classified into lytic and nonlytic components, nonlinear functions can better reproduce saturated effects in the interaction processes between cell and viral populations, and distributed intracellular delay can realistically reflect the stochastic element in the delay effects. For these reasons, we develop an HTLV-I (Human T-cell leukemia virus type I) infection model with nonlinear lytic and nonlytic CTL immune responses, nonlinear incidence rate, distributed intracellular delay and immune impairment. Through conducting complete analysis, it is revealed that all these factors influence the concentration level of infected T-cells at the chronic-infection equilibrium, whereas intracellular distributed delay and nonlinear incidence rate may change the expression of the basic reproduction number R0 in the context where the model proposed still preserves the threshold dynamics. Our analysis results obtained may improve several existing works by comparison. We also perform global sensitivity analysis for R0 in order to explore the effective strategies of lowering the concentration level of infected T-cells. [ABSTRACT FROM AUTHOR]

During the primary CD8 T cell immune response, CD8 T cells undergo proliferation and continuous differentiation, acquiring cytotoxic abilities to address the infection and generate an immune memory. At the end of the response, the remaining CD8 T cells are antigen-specific memory cells that will respond stronger and faster in case they are presented this very same antigen again. We propose a nonlinear multiscale mathematical model of the CD8 T cell immune response describing dynamics of two inter-connected physical scales. At the intracellular scale, the level of expression of key proteins involved in proliferation, death, and differentiation of CD8 T cells is modeled by a delay differential system whose dynamics define maturation velocities of CD8 T cells. At the population scale, the amount of CD8 T cells is represented by a discrete density and cell fate depends on their intracellular content. We introduce the model, then show essential mathematical properties (existence, uniqueness, positivity) of solutions and analyse their asymptotic behavior based on the behavior of the intracellular regulatory network. We numerically illustrate the model's ability to qualitatively reproduce both primary and secondary responses, providing a preliminary tool for investigating the generation of long-lived CD8 memory T cells and vaccine design. [ABSTRACT FROM AUTHOR]

Tuberculosis (TB) is a leading cause of death from infectious disease. TB is caused mainly by a bacterium called Mycobacterium tuberculosis which often initiates in the respiratory tract. The interaction of macrophages and T cells plays an important role in the immune response during TB infection. Recent experimental results support that active TB infection may be induced by the dysfunction of Treg cell regulation that provides a balance between anti-TB T cell responses and pathology. To better understand the dynamics of TB infection and Treg cell regulation, we build a mathematical model using a system of differential equations that qualitatively and quantitatively characterizes the dynamics of macrophages, Th1 and Treg cells during TB infection. For sufficiently analyzing the interaction between immune response and bacterial infection, we separate our model into several simple subsystems for further steady state and stability studies. Using this system, we explore the conditions of parameters for three situations, recovery, latent disease and active disease, during TB infection. Our numerical simulations support that Th1 cells and Treg cells play critical roles in TB infection: Th1 cells inhibit the number of infected macrophages to reduce the chance of active disease; Treg cell regulation reduces the immune response to stabilize the dynamics of the system. [ABSTRACT FROM AUTHOR]

The inflammatory response is the first line of defense against infectious agents or tissue damage. Innate immune cells are the crucial effectors regulating the different phase of inflammation. Their ability to timely develop an immune response is tightly controlled by the interplay of transcriptional and epigenetic mechanisms. The immunological imprinting elicited by exposure to different concentrations and types of infectious agents determine the functional fate of immune cells, forming the basis of innate immune memory. In this review we highlight the best-characterized examples of gene reprogramming occurring during different phases of inflammation with particular emphasis on the epigenetic marks that determine the specificity of the immune response. We further review the potential of cutting edge experimental techniques that have recently helped to reveal the deep complexity of epigenetic regulation during the inflammatory response. [ABSTRACT FROM AUTHOR]

Melatonin is the main secretory product synthesized and secreted by the pineal gland during the night. Melatonin is a pleitropic molecule with a wide distribution within phylogenetically distant organisms and has a great functional versatility, including the regulation of circadian and seasonal rhythms and antioxidant and anti-inflammatory properties. It also possesses the capacity to modulate immune responses by regulation of the TH1/TH2 balance and cytokine production. Immune system eradicates infecting organisms without serious injury to host tissues, but sometimes these responses are inadequately controlled, giving rise to called hypersensitivity diseases, or inappropriately targeted to host tissues, causing the autoimmune diseases. In clinical medicine, the hypersensitivity diseases include the allergic or atopic diseases and the hallmarks of these diseases are the activation of TH2 cells and the production of IgE antibody. Regarding autoimmunity, at the present time we know that the key events in the development of autoimmunity are a failure or breakdown of the mechanisms normally responsible for maintaining self-tolerance in B lymphocytes, T lymphocytes, or both, the recognition of self-antigens by autoreactive lymphocytes, the activation of these cells to proliferate and differentiate into effector cells, and the tissue injury caused by the effector cells and their products. Melatonin treatment has been investigated in atopic diseases, in several animal models of autoimmune diseases, and has been also evaluated in clinical autoimmune diseases. This review summarizes the role of melatonin in atopic diseases (atopic dermatitis and asthma) and in several autoimmune diseases, such as arthritis rheumatoid, multiple sclerosis, systemic lupus erythematosus, type 1 diabetes mellitus, and inflammatory bowel diseases. [ABSTRACT FROM AUTHOR]

An almost periodic epidemic model with age structure in a patchy environment is considered. The existence of the almost periodic disease-free solution and the definition of the basic reproduction ratio R0 are given. Based on those, it is shown that a disease dies out if the basic reproduction number R0 is less than unity and persists in the population if it is greater than unity. [ABSTRACT FROM AUTHOR]

To study the effect of immune response in viral infections, a new mathematical model is proposed and analyzed. It describes the interactions between susceptible host cells, infected host cells, free virus, lytic and nonlytic immune response. Using the LaSalle's invariance principle, we establish conditions for the global stability of equilibria. Uniform persistence is obtained when there is a unique endemic equilibrium. Mathematical analysis and numerical simulations indicate that the basic reproduction number of the virus and immune response reproductive number are sharp threshold parameters to determine outcomes of infection. Lytic and nonlytic antiviral activities play a significant role in the amount of susceptible host cells and immune cells in the endemic steady state. We also present potential applications of the model in clinical practice by introducing antiviral effects of antiviral drugs. [ABSTRACT FROM AUTHOR]

B cell chronic lymphocytic leukemia (B-CLL) is known to have substantial clinical heterogeneity. There is no cure, but treatments allow for disease management. However, the wide range of clinical courses experienced by B-CLL patients makes prognosis and hence treatment a significant challenge. In an attempt to study disease progression across different patients via a unified yet exible approach, we present a mathematical model of B-CLL with immune response, that can capture both rapid and slow disease progression. This model includes four different cell populations in the peripheral blood of humans: B-CLL cells, NK cells, cytotoxic T cells and helper T cells. We analyze existing data in the medical literature, determine ranges of values for parameters of the model, and compare our model outcomes to clinical patient data. The goal of this work is to provide a tool that may shed light on factors affecting the course of disease progression in patients. This modeling tool can serve as a foundation upon which future treatments can be based. [ABSTRACT FROM AUTHOR]

We present a mathematical model to study the effects of the regulatory T cells (Treg) on Renal Cell Carcinoma (RCC) treatment with sunitinib. The drug sunitinib inhibits the natural self-regulation of the immune system, allowing the effector components of the immune system to function for longer periods of time. This mathematical model builds upon our non-linear ODE model by de Pillis et al. (2009) [13] to incorporate sunitinib treatment, regulatory T cell dynamics, and RCC-specific parameters. The model also elucidates the roles of certain RCC-specific parameters in determining key differences between in silico patients whose immune profiles allowed them to respond well to sunitinib treatment, and those whose profiles did not. Simulations from our model are able to produce results that reflect clinical outcomes to sunitinib treatment such as: (1) sunitinib treatments following standard protocols led to improved tumor control (over no treatment) in about 40% of patients; (2) sunitinib treatments at double the standard dose led to a greater response rate in about 15% the patient population; (3) simulations of patient response indicated improved responses to sunitinib treatment when the patient's immune strength scaling and the immune system strength coefficients parameters were low, allowing for a slightly stronger natural immune response. [ABSTRACT FROM AUTHOR]