How Naive T-Cell Clone Counts Are Shaped By Heterogeneous Thymic Output and Homeostatic Proliferation

Advances in research on immunocyte iron metabolism, ferroptosis, and their regulatory roles in autoimmune and autoinflammatory diseases

Autoimmune diseases commonly affect various systems, but their etiology and pathogenesis remain unclear. Currently, increasing research has highlighted the role of ferroptosis in immune regulation, with immune cells being a crucial component of the body's immune system. This review provides an overview and discusses the relationship between ferroptosis, programmed cell death in immune cells, and autoimmune diseases. Additionally, it summarizes the role of various key targets of ferroptosis, such as GPX4 and TFR, in immune cell immune responses. Furthermore, the release of multiple molecules, including damage-associated molecular patterns (DAMPs), following cell death by ferroptosis, is examined, as these molecules further influence the differentiation and function of immune cells, thereby affecting the occurrence and progression of autoimmune diseases. Moreover, immune cells secrete immune factors or their metabolites, which also impact the occurrence of ferroptosis in target organs and tissues involved in autoimmune diseases. Iron chelators, chloroquine and its derivatives, antioxidants, chloroquine derivatives, and calreticulin have been demonstrated to be effective in animal studies for certain autoimmune diseases, exerting anti-inflammatory and immunomodulatory effects. Finally, a brief summary and future perspectives on the research of autoimmune diseases are provided, aiming to guide disease treatment strategies.

Surrogate modeling and control of medical digital twins

The vision of personalized medicine is to identify interventions that maintain or restore a person's health based on their individual biology. Medical digital twins, computational models that integrate a wide range of health-related data about a person and can be dynamically updated, are a key technology that can help guide medical decisions. Such medical digital twin models can be high-dimensional, multi-scale, and stochastic. To be practical for healthcare applications, they often need to be simplified into low-dimensional surrogate models that can be used for optimal design of interventions. This paper introduces surrogate modeling algorithms for the purpose of optimal control applications. As a use case, we focus on agent-based models (ABMs), a common model type in biomedicine for which there are no readily available optimal control algorithms. By deriving surrogate models that are based on systems of ordinary differential equations, we show how optimal control methods can be employed to compute effective interventions, which can then be lifted back to a given ABM. The relevance of the methods introduced here extends beyond medical digital twins to other complex dynamical systems.

Mild HIV-specific selective forces overlaying natural CD4+ T cell dynamics explain the clonality and decay dynamics of HIV reservoir cells

The latent reservoir of HIV persists for decades in people living with HIV (PWH) on antiretroviral therapy (ART). To determine if persistence arises from the natural dynamics of memory CD4+ T cells harboring HIV, we compared the clonal dynamics of HIV proviruses to that of memory CD4+ T cell receptors (TCRβ) from the same PWH and from HIV-seronegative people. We show that clonal dominance of HIV proviruses and antigen-specific CD4+ T cells are similar but that the field's understanding of the persistence of the less clonally dominant reservoir is significantly limited by undersampling. We demonstrate that increasing reservoir clonality over time and differential decay of intact and defective proviruses cannot be explained by mCD4+ T cell kinetics alone. Finally, we develop a stochastic model of TCRβ and proviruses that recapitulates experimental observations and suggests that HIV-specific negative selection mediates approximately 6% of intact and 2% of defective proviral clearance. Thus, HIV persistence is mostly, but not entirely, driven by natural mCD4+ T cell kinetics.

Algorithms for the Uniqueness of the Longest Common Subsequence

Given several number sequences, determining the longest common subsequence is a classical problem in computer science. This problem has applications in bioinformatics, especially determining transposable genes. Nevertheless, related works only consider how to find one longest common subsequence. In this paper, we consider how to determine the uniqueness of the longest common subsequence. If there are multiple longest common subsequences, we also determine which number appears in all/some/none of the longest common subsequences. We focus on four scenarios: (1) linear sequences without duplicated numbers; (2) circular sequences without duplicated numbers; (3) linear sequences with duplicated numbers; (4) circular sequences with duplicated numbers. We develop corresponding algorithms and apply them to gene sequencing data.

Mathematical Characterization of Private and Public Immune Receptor Sequences

Diverse T and B cell repertoires play an important role in mounting effective immune responses against a wide range of pathogens and malignant cells. The number of unique T and B cell clones is characterized by T and B cell receptors (TCRs and BCRs), respectively. Although receptor sequences are generated probabilistically by recombination processes, clinical studies found a high degree of sharing of TCRs and BCRs among different individuals. In this work, we use a general probabilistic model for T/B cell receptor clone abundances to define "publicness" or "privateness" and information-theoretic measures for comparing the frequency of sampled sequences observed across different individuals. We derive mathematical formulae to quantify the mean and the variances of clone richness and overlap. Our results can be used to evaluate the effect of different sampling protocols on abundances of clones within an individual as well as the commonality of clones across individuals. Using synthetic and empirical TCR amino acid sequence data, we perform simulations to study expected clonal commonalities across multiple individuals. Based on our formulae, we compare these simulated results with the analytically predicted mean and variances of the repertoire overlap. Complementing the results on simulated repertoires, we derive explicit expressions for the richness and its uncertainty for specific, single-parameter truncated power-law probability distributions. Finally, the information loss associated with grouping together certain receptor sequences, as is done in spectratyping, is also evaluated. Our approach can be, in principle, applied under more general and mechanistically realistic clone generation models.

T-Cell Immunity in COVID-19-Recovered Individuals and Individuals Vaccinated with the Combined Vector Vaccine Gam-COVID-Vac

The COVID-19 pandemic has required extensive research on the new coronavirus SARS-CoV-2 and the creation of new highly effective vaccines. The presence of T-cells in the body that respond to virus antigens suggests adequate antiviral immunity. We investigated T-cell immunity in individuals who recovered from mild and moderate COVID-19 and in individuals vaccinated with the Gam-COVID-Vac combined vector vaccine. The ELISPOT method was used to determine the number of T-cells responding with IFN-γ synthesis to stimulation by peptides containing epitopes of the S-protein or N-, M-, ORF3, and ORF7 proteins, using peripheral blood mononuclear cells (PBMCs). At the same time, the multiplex method was used to determine the accumulation of IFN-γ and other cytokines in the culture medium. According to the data obtained, the proportion of positive conclusions about the T-cell immune response to SARS-CoV-2 antigens in control, recovered, and vaccinated individuals was 12%, 70%, and 52%, respectively. At the same time, more than half of the vaccinated individuals with a T-cell response were sensitized to the antigens of N-, M-, ORF3, and ORF7 proteins not produced by Gam-COVID-Vac, indicating a high likelihood of asymptomatic SARS-CoV-2 infection. Increased IFN-γ release by single sensitized T-cells in response to specific stimulation in recovered and vaccinated individuals did not result in the accumulation of this and other cytokines in the culture medium. These findings suggest a balance between cytokine production and utilization by immunocompetent cells as a prerequisite for providing a controlled cytokine signal and avoiding a "cytokine storm".