Understanding the Mechanism of Protection Following Challenge and Immunization

疫苗的目标是模仿自然感染，诱导有效的免疫反应，最重要的是建立免疫记忆。这种经验方法未能诱导针对某些病原体的保护，因为疫苗有效性可能受到多种因素的组合的阻碍，包括病原体遗传多样性、复杂的发病机制和/或病原体逃避免疫系统的能力。数学模型与数据分析相结合可以帮助促进对相关因素和保护机制的理解。该研究项目提供了一个跨学科的方法来研究感染，持久性和保护等机制。它结合了数学技术的发展和生物学数据的使用，用于研究抗体在清除病毒感染中的作用，诱导免疫引发和外部挑战后记忆的动态机制，以及疫苗接种和加强后复杂的免疫细胞相互作用。该项目旨在帮助确定参与挑战和疫苗接种后免疫记忆形成的关键机制，旨在指导疾病预防和控制策略。 在这个项目中，将开发、分析数学模型，并与时间数据进行比较，目的是（1）评估病毒攻击后抗体的数量、质量和动态之间的关系;（2）研究使先天免疫细胞倾向于炎症或耐受表型的分子机制;（3）确定免疫记忆与通过疫苗接种诱导的细胞和分子标志物的大小和动态之间的关系。该项目对生物开关的复杂非线性动力学系统的研究旨在导致渐近的严格理论标准，全局行为，以及出现非线性解决方案所需的模型特征。针对数据的模型验证将深入了解保护和抗体产生之间的关系，并将促进对免疫因素和疫苗接种结果之间关系的理解。最重要的是，它将在细胞和分子水平上预测参与挑战后免疫记忆形成的关键机制。这些知识对于合理的疫苗设计至关重要。该项目将促进数学和生物学知识的进步，为数学和医学界的研究人员提供跨学科合作的机会，并将涉及对本科生和研究生的培训。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。

The goal of vaccines is to mimic natural infections, induce potent immune responses and, most importantly, establish immunological memory. This empirical approach has failed to induce protection against some pathogens, as vaccine effectiveness can be hindered by a combination of factors including pathogen genetic diversity, complex pathogenesis, and/or ability of pathogens to evade the immune system. Mathematical models in combination with data analysis can help advance the understanding of correlates and mechanisms of protection. This research project provides an interdisciplinary approach into the study of such mechanisms of infection, persistence, and protection. It combines development of mathematical techniques and the use of biological data for the investigation of the role of antibody in the clearance of viral infections, the dynamic mechanisms that induce immunological priming and memory following external challenge, and the complex immune cell interactions following vaccination and boosting. The project aims to help identify key mechanisms involved in the formation of immunological memory after challenge and vaccination with the aim of guiding strategies for disease prevention and control. In this project, mathematical models will be developed, analyzed, and compared with temporal data with the aim of (1) evaluating the relationship between protection and the quantity, quality, and dynamics of antibodies following virus challenge; (2) investigating the molecular mechanisms that tilt innate immune cells into inflammatory or tolerant phenotypes; (3) determining the relationship between immunological memory and the size and dynamics of cellular and molecular markers induced through vaccination. The project's investigation of complex non-linear dynamical systems of biological switches is intended to lead to rigorous theoretical criteria on asymptotic, global behavior, as well as model features needed for the emergence of bistable solutions. Model validation against data will provide insight into the relationship between protection and antibody development, and will advance understanding of the relationship between immune factors and vaccination outcomes. Most importantly, it will predict key mechanisms, at cellular and molecular level, involved in the formation of immunological memory following challenge. Such knowledge is essential for rational vaccine design. The project will promote the advancement of mathematical and biological knowledge, will provide an opportunity for interdisciplinary collaboration with researchers in the mathematical and medical communities, and will involve training of undergraduate and graduate students.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.