A branching stochastic evolutionary model of the B-cell repertoire.

We propose a stochastic framework to describe the evolution of the B-cell repertoire during germinal center (GC) reactions. Our model is formulated as a multitype age-dependent branching process with time-varying immigration. The immigration process captures the mechanism by which founder B cells initiate clones by gradually seeding GC over time, while the branching process describes the temporal evolution of the composition of these clones. The model assigns a type to each cell to represent attributes of interest. Examples of attributes include the binding affinity class of the B cells, their clonal family, or the nucleotide sequence of the heavy and light chains of their receptors. The process is generally non-Markovian. We present its properties, including as t → ∞ when the process is supercritical, the most relevant case to study expansion of GC B cells. We introduce temporal alpha and beta diversity indices for multitype branching processes. We focus on the dynamics of clonal dominance, highlighting its non-stationarity, and the accumulation of somatic hypermutations in the context of sequential immunization. We evaluate the impact of the ongoing seeding of GC by founder B cells on the dynamics of the B-cell repertoire, and quantify the effect of precursor frequency and antigen availability on the timing of GC entry. An application of the model illustrates how it may help with interpretation of BCR sequencing data.

Lyapunov functionals for a general time-delayed virus dynamic model with different CTL responses.

A time-delayed virus dynamic model is proposed with general monotonic incidence, different nonlinear CTL (cytotoxic T lymphocyte) responses [CTL elimination function pyg1(z) and CTL stimulation function cyg2(z)], and immune impairment. Indeed, the different CTL responses pose challenges in obtaining the dissipativeness of the model. By constructing appropriate Lyapunov functionals with some detailed analysis techniques, the global stability results of all equilibria of the model are obtained. By the way, we point out that the partial derivative fv(x,0) is increasing (but not necessarily strictly) in x>0 for the general monotonic incidence f(x,v). However, some papers defaulted that the partial derivative was strictly increasing. Our main results show that if the basic reproduction number R0≤1, the infection-free equilibrium E0 is globally asymptotically stable (GAS); if CTL stimulation function cyg2(z)=0 for z=0 and the CTL threshold parameter R1≤1

A mathematical model for HIV dynamics with multiple infections: implications for immune escape.

Multiple infections enable the recombination of different strains, which may contribute to viral diversity. How multiple infections affect the competition dynamics between the two types of strains, the wild and the immune escape mutant, remains poorly understood. This study develops a novel mathematical model that includes the two strains, two modes of viral infection, and multiple infections. For the representative double-infection case, the reproductive numbers are derived and global stabilities of equilibria are obtained via the Lyapunov direct method and theory of limiting systems. Numerical simulations indicate similar viral dynamics regardless of multiplicities of infections though the competition between the two strains would be the fiercest in the case of quadruple infections. Through sensitivity analysis, we evaluate the effect of parameters on the set-point viral loads in the presence and absence of multiple infections. The model with multiple infections predict that there exists a threshold for cytotoxic T lymphocytes (CTLs) to minimize the overall viral load. Weak or strong CTLs immune response can result in high overall viral load. If the strength of CTLs maintains at an intermediate level, the fitness cost of the mutant is likely to have a significant impact on the evolutionary dynamics of mutant viruses. We further investigate how multiple infections alter the viral dynamics during the combination antiretroviral therapy (cART). The results show that viral loads may be underestimated during cART if multiple-infection is not taken into account.

Construction and validation of a novel immunological model to predict prognosis in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer, with limited treatment options. In this study, we investigated the role of immune cell infiltration in PDAC progression and constructed an immune-related predictive model for patients with PDAC based on the International Cancer Genome Consortium (ICGC) cohort. Related algorithms have been used to assess the immune microenvironment. Least Absolute Shrinkage and Selection Operator (LASSO) Cox analysis was used to construct the model, and receiver operating characteristic and decision curve analysis analyses were conducted to evaluate its diagnostic and prognostic efficacy. The results demonstrated a correlation between high immune infiltration and better prognosis in PDAC. The immune-related prognostic model (IPM) identified four genes through LASSO Cox analysis, with the high IPM group being associated with a worse prognosis. Cox regression analysis confirmed that IPM is an independent risk factor for PDAC. Validation through analysis of The Cancer Genome Atlas cohort and our own individual tumor samples revealed a similar trend to that observed in the ICGC cohort. Finally, a nomogram incorporating age and IPM demonstrated efficacy in the prognostic evaluation of patients with PDAC. In conclusion, we developed a novel immune-related prognosis prediction model for PDAC that offers new possibilities for the measurement of immunotherapy and prognostic assessment of patients.

An immuno-epidemiological model with waning immunity after infection or vaccination.

In epidemics, waning immunity is common after infection or vaccination of individuals. Immunity levels are highly heterogeneous and dynamic. This work presents an immuno-epidemiological model that captures the fundamental dynamic features of immunity acquisition and wane after infection or vaccination and analyzes mathematically its dynamical properties. The model consists of a system of first order partial differential equations, involving nonlinear integral terms and different transfer velocities. Structurally, the equation may be interpreted as a Fokker-Planck equation for a piecewise deterministic process. However, unlike the usual models, our equation involves nonlocal effects, representing the infectivity of the whole environment. This, together with the presence of different transfer velocities, makes the proved existence of a solution novel and nontrivial. In addition, the asymptotic behavior of the model is analyzed based on the obtained qualitative properties of the solution. An optimal control problem with objective function including the total number of deaths and costs of vaccination is explored. Numerical results describe the dynamic relationship between contact rates and optimal solutions. The approach can contribute to the understanding of the dynamics of immune responses at population level and may guide public health policies.

Modelling the Impact of NETosis During the Initial Stage of Systemic Lupus Erythematosus.

The development of autoimmune diseases often takes years before clinical symptoms become detectable. We propose a mathematical model for the immune response during the initial stage of Systemic Lupus Erythematosus which models the process of aberrant apoptosis and activation of macrophages and neutrophils. NETosis is a type of cell death characterised by the release of neutrophil extracellular traps, or NETs, containing material from the neutrophil's nucleus, in response to a pathogenic stimulus. This process is hypothesised to contribute to the development of autoimmunogenicity in SLE. The aim of this work is to study how NETosis contributes to the establishment of persistent autoantigen production by analysing the steady states and the asymptotic dynamics of the model by numerical experiment.

Dynamical analysis of a general delayed HBV infection model with capsids and adaptive immune response in presence of exposed infected hepatocytes.

The aim of this paper is to develop and investigate a novel mathematical model of the dynamical behaviors of chronic hepatitis B virus infection. The model includes exposed infected hepatocytes, intracellular HBV DNA-containing capsids, uses a general incidence function for viral infection covering a variety of special cases available in the literature, and describes the interaction of cytotoxic T lymphocytes that kill the infected hepatocytes and the magnitude of B-cells that send antibody immune defense to neutralize free virions. Further, one time delay is incorporated to account for actual capsids production. The other time delays are used to account for maturation of capsids and free viruses. We start with the analysis of the proposed model by establishing the local and global existence, uniqueness, non-negativity and boundedness of solutions. After defined the threshold parameters, we discuss the stability properties of all possible steady state constants by using the crafty Lyapunov functionals, the LaSalle's invariance principle and linearization methods. The impacts of the three time delays on the HBV infection transmission are discussed through local and global sensitivity analysis of the basic reproduction number and of the classes of infected states. Finally, an application is provided and numerical simulations are performed to illustrate and interpret the theoretical results obtained. It is suggested that, a good strategy to eradicate or to control HBV infection within a host should concentrate on any drugs that may prolong the values of the three delays.

Stability of a diffusive-delayed HCV infection model with general cell-to-cell incidence function incorporating immune response and cell proliferation.

In this work, we analyse the dynamics of a five-dimensional hepatitis C virus infection mathematical model including the spatial mobility of hepatitis C virus particles, the transmission of hepatitis C virus infection by mitosis process of infected hepatocytes with logistic growth, time delays, antibody response and cytotoxic T lymphocyte (CTL) immune response with general incidence functions for both modes of infection transmission, namely virus-to-cell as well as cell-to-cell. Firstly, we prove rigorously the existence, the uniqueness, the positivity and the boundedness of the solution of the initial value and boundary problem associated with the new constructed model. Secondly, we found that the basic reproductive number is the sum of the basic reproduction number determined by cell-free virus infection, determined by cell-to-cell infection and determined by proliferation of infected cells. It is proved the existence of five spatially homogeneous equilibria known as infection-free, immune-free, antibody response, CTL response and antibody and CTL responses. By using the linearization methods, the local stability of the latter is established under some rigorous conditions. Finally, we proved the existence of periodic solutions by highlighting the occurrence of a Hopf bifurcation for a certain threshold value of one delay.

Decoding systems immunological model of sphingolipids with IL-6/IL-17/IL-23 axes in L. major infection.

IL-6, IL-17, IL-23 and IL-1ß are the crucial cytokines controlling inflammatory and immune response during L. major infection. During cutaneous leishmaniasis, an important T helper cell type CD4+ Th17 subset plays a deterministic role in lesion formation through channelling infected macrophages and production of IL-1ß, IL-6, IL-23 and IFN-γ. Ceramide derived sphingosine precursors may assist in pro-inflammatory cytokine response. However, the role of these metabolites in inflammation with pleiotropic pro-inflammatory cytokines in L. major infection is unknown. The present study indicates IL-6/IL-17/IL-23 and SPHK1-S1P-S1PRs signaling axes with the overexpression of SATB1 aiding in disease progression. Targeting SATB1 might modulate the secretion of pro-inflammatory cytokines and abnormal immune functioning, thereby killing the intracellular parasite. Systems immunological methods assisted in a step towards identifying the key to the mystery of crucial components and serving as an approach for therapeutic intervention in L. major infection.

CircRNA-Based Cervical Cancer Prognosis Model, Immunological Validation and Drug Prediction.

BACKGROUND: Cervical cancer (CC) is a common cancer in female, which is associated with problems like poor prognosis. Circular RNA (circRNA) is a kind of competing endogenous RNA (ceRNA) that has an important role in regulating microRNA (miRNA) in many cancers. The regulatory mechanisms of CC immune microenvironment and the transcriptome level remain to be fully explored. METHODS: In this study, we constructed the ceRNA network through the interaction data and expression matrix of circRNA, miRNA and mRNA. Meanwhile, based on the gene expression matrix, CIBERSORT algorithm was used to reveal contents of tumor-infiltrating immune cells (TIICs). Then, we screened prognostic markers based on ceRNA network and immune infiltration and constructed two nomograms. In order to find immunological differences between the high- and low-risk CC samples, we examined multiple immune checkpoints and predicted the effect of PD-L1 ICI immunotherapy. In addition, the sensitive therapeutics for high-risk patients were screened, and the potential agents with anti-CC activity were predicted by Connective Map (CMap). RESULTS: We mapped a ceRNA network including 5 circRNAs, 17 miRNAs and 129 mRNAs. From the mRNA nodes of the network six genes and two kind of cells were identified as prognostic makers for CC. Among them, there was a significant positive correlation between CD8+ T cells and SNX10 gene. The results of TIDE and single sample GSEA (ssGSEA) showed that T cells CD8 do play a key role in inhibiting tumor progression. Further, our study screened 24 drugs that were more sensitive to high-risk CC patients and several potential therapeutic agents for reference. CONCLUSIONS: Our study identified several circRNA-miRNA-mRNA regulatory axes and six prognostic genes based on the ceRNA network. In addition, through TIIC, survival analysis and a series of immunological analyses, T cells were proved to be good prognostic markers, besides play an important role in the immune process. Finally, we screened 24 potentially more effective drugs and multiple potential drug compounds for high- and low-risk patients.

The adaptation model of immunity: Is the goal of central tolerance to eliminate defective T cells or self-reactive T cells?

The self-non-self model and the danger model are designed to understand how an immune response is induced. These models are not meant to predict if an immune response may succeed or fail in destroying/controlling its target. However, these immunological models rely on either self-antigens or self-dendritic cells for understanding of central tolerance, which have been discussed by Fuchs and Matzinger in response to Al-Yassin. In an attempt to address some questions that these models are facing when it comes to understanding central tolerance, I propose that the goal of negative selection in the thymus is to eliminate defective T cells but not self-reactive T cells. Therefore, any escape from negative selection could increase lymphopenia because of the depletion of defective naïve T cells outside the thymus, as seen in the elderly.

Universal antigen encoding of T cell activation from high-dimensional cytokine dynamics.

Systems immunology lacks a framework with which to derive theoretical understanding from high-dimensional datasets. We combined a robotic platform with machine learning to experimentally measure and theoretically model CD8+ T cell activation. High-dimensional cytokine dynamics could be compressed onto a low-dimensional latent space in an antigen-specific manner (so-called "antigen encoding"). We used antigen encoding to model and reconstruct patterns of T cell immune activation. The model delineated six classes of antigens eliciting distinct T cell responses. We generalized antigen encoding to multiple immune settings, including drug perturbations and activation of chimeric antigen receptor T cells. Such universal antigen encoding for T cell activation may enable further modeling of immune responses and their rational manipulation to optimize immunotherapies.

Malnutrition and Dietary Habits Alter the Immune System Which May Consequently Influence SARS-CoV-2 Virulence: A Review.

COVID-19, resulting from the SARS-CoV-2 virus, is a major pandemic that the world is fighting. SARS-CoV-2 primarily causes lung infection by attaching to the ACE2 receptor on the alveolar epithelial cells. However, the ACE2 receptor is also present in intestinal epithelial cells, suggesting a link between nutrition, virulence and clinical outcomes of COVID-19. Respiratory viral infections perturb the gut microbiota. The gut microbiota is shaped by our diet; therefore, a healthy gut is important for optimal metabolism, immunology and protection of the host. Malnutrition causes diverse changes in the immune system by repressing immune responses and enhancing viral vulnerability. Thus, improving gut health with a high-quality, nutrient-filled diet will improve immunity against infections and diseases. This review emphasizes the significance of dietary choices and its subsequent effects on the immune system, which may potentially impact SARS-CoV-2 vulnerability.

Type I interferon-mediated tumor immunity and its role in immunotherapy.

Immune checkpoint blockade (ICB) therapies have achieved remarkable clinical responses in patients with many different types of cancer; however, most patients who receive ICB monotherapy fail to achieve long-term responses, and some tumors become immunotherapy-resistant and even hyperprogressive. Type I interferons (IFNs) have been demonstrated to inhibit tumor growth directly and indirectly by acting upon tumor and immune cells, respectively. Furthermore, accumulating evidence indicates that endo- and exogenously enhancing type I IFNs have a synergistic effect on anti-tumor immunity. Therefore, clinical trials studying new treatment strategies that combine type I IFN inducers with ICB are currently in progress. Here, we review the cellular sources of type I IFNs and their roles in the immune regulation of the tumor microenvironment. In addition, we highlight immunotherapies based on type I IFNs and combination therapy between type I IFN inducers and ICBs.

Quantifying Neutralizing Antibodies in Patients with COVID-19 by a Two-Variable Generalized Additive Model.

Considering the urgent demand for faster methods to quantify neutralizing antibody titers in patients with coronavirus (CoV) disease 2019 (COVID-19), developing an analytical model or method to replace the conventional virus neutralization test (NT) is essential. Moreover, a "COVID-19 immunity passport" is currently being proposed as a certification for people who travel internationally. Therefore, an enzyme-linked immunosorbent assay (ELISA) was designed to detect severe acute respiratory syndrome CoV 2 (SARS-CoV-2)-neutralizing antibodies in serum, which is based on the binding affinity of SARS-CoV-2 viral spike protein 1 (S1) and the viral spike protein receptor-binding domain (RBD) to antibodies. The RBD is considered the major binding region of neutralizing antibodies. Furthermore, S1 covers the RBD and several other regions, which are also important for neutralizing antibody binding. In this study, we assessed 144 clinical specimens, including those from patients with PCR-confirmed SARS-CoV-2 infections and healthy donors, using both the NT and ELISA. The ELISA results analyzed by spline regression and the two-variable generalized additive model precisely reflected the NT value, and the correlation between predicted and actual NT values was as high as 0.917. Therefore, our method serves as a surrogate to quantify neutralizing antibody titer. The analytic method and platform used in this study present a new perspective for serological testing of SARS-CoV-2 infection and have clinical potential to assess vaccine efficacy. IMPORTANCE Herein, we present a new approach for serological testing for SARS-CoV-2 antibodies using innovative laboratory methods that demonstrate a combination of biology and mathematics. The traditional virus neutralization test is the gold standard method; however, it is time-consuming and poses a risk to medical personnel. Thus, there is a demand for methods that rapidly quantify neutralizing antibody titers in patients with COVID-19 or examine vaccine efficacy at a biosafety level 2 containment facility. Therefore, we used a two-variable generalized additive model to analyze the results of the enzyme-linked immunosorbent assay and found the method to serve as a surrogate to quantify neutralizing antibody titers. This methodology has potential for clinical use in assessing vaccine efficacy.

Staphylococcus aureus and Neutrophil Extracellular Traps: The Master Manipulator Meets Its Match in Immunothrombosis.

Over the past 10 years, neutrophil extracellular traps (NETs) have become widely accepted as an integral player in immunothrombosis, due to their complex interplay with both pathogens and components of the coagulation system. While the release of NETs is an attempt by neutrophils to trap pathogens and constrain infections, NETs can have bystander effects on the host by inducing uncontrolled thrombosis, inflammation, and tissue damage. From an evolutionary perspective, pathogens have adapted to bypass the host innate immune response. Staphylococcus aureus (S. aureus), in particular, proficiently overcomes NET formation using several virulence factors. Here we review mechanisms of NET formation and how these are intertwined with platelet activation, the release of endothelial von Willebrand factor, and the activation of the coagulation system. We discuss the unique ability of S. aureus to modulate NET formation and alter released NETs, which helps S. aureus to escape from the host's defense mechanisms. We then discuss how platelets and the coagulation system could play a role in NET formation in S. aureus-induced infective endocarditis, and we explain how targeting these complex cellular interactions could reveal novel therapies to treat this disease and other immunothrombotic disorders.

The gut-meningeal immune axis: Priming brain defense against the most likely invaders.

The gastrointestinal tract contains trillions of microorganisms that exist symbiotically with the host due to a tolerant, regulatory cell-rich intestinal immune system. However, this intimate relationship with the microbiome inevitably comes with risks, with intestinal organisms being the most common cause of bacteremia. The vasculature of the brain-lining meninges contains fenestrated endothelium, conferring vulnerability to invasion by circulating microbes. We propose that this has evolutionarily led to close links between gut and meningeal immunity, to prime the central nervous system defense against the most likely invaders. This paradigm is exemplified by the dural venous sinus IgA defense system, where the antibody repertoire mirrors that of the gut.