通过病毒感染和疫苗接种中细胞与免疫相互作用的动态建模探索免疫反应

IF 1.7 4区 工程技术 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Complexity Pub Date : 2024-09-02 DOI:10.1155/2024/3357763
Kwang Su Kim, Il Hyo Jung, Jong Hyuk Byun
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引用次数: 0

摘要

传染病对全球健康构成重大威胁,因此有必要制定有效的疫苗接种策略。本研究探讨了病毒感染和免疫反应的动态变化,尤其关注疫苗接种诱导的抗体和 CD8+ T 细胞的作用。通过数学模型,我们探索了宿主细胞和病毒之间错综复杂的相互作用,以评估疫苗接种对病毒复制的影响。我们的研究结果与实验结果一致,证明接种疫苗能大大增强免疫反应并减少病毒复制。抗体和 CD8+ T 细胞反应对实现最佳疫苗效果至关重要。该模型的预测结果与实验观察结果进行了验证,强调了在疫苗设计中纳入诱导强大免疫反应机制的必要性。这项研究强调了数学建模在理解免疫动态和完善疫苗接种策略以开发更有效的病毒感染治疗方法方面的关键作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Exploring Immune Responses through Dynamic Modeling of Cell-Immune Interactions in Viral Infection and Vaccination

Exploring Immune Responses through Dynamic Modeling of Cell-Immune Interactions in Viral Infection and Vaccination

Infectious diseases pose a significant threat to global health, necessitating the development of effective vaccination strategies. This study examines the dynamics of viral infections and immune responses, with a particular focus on the roles of antibodies and CD8+ T cells induced by vaccination. Through a mathematical model, we explore the intricate interactions between host cells and viruses to assess the impact of vaccination on viral replication. Our findings align with experimental results, demonstrating that vaccination substantially enhances immune responses and reduces viral replication. The contributions of both antibody and CD8+ T cell responses are shown to be vital for achieving optimal vaccine efficacy. The model’s predictions, validated against experimental observations, emphasize the need to incorporate mechanisms that induce robust immune responses in vaccine design. This study underscores the critical role of mathematical modeling in understanding immune dynamics and in refining vaccination strategies to develop more effective treatments against viral infections.

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来源期刊
Complexity
Complexity 综合性期刊-数学跨学科应用
CiteScore
5.80
自引率
4.30%
发文量
595
审稿时长
>12 weeks
期刊介绍: Complexity is a cross-disciplinary journal focusing on the rapidly expanding science of complex adaptive systems. The purpose of the journal is to advance the science of complexity. Articles may deal with such methodological themes as chaos, genetic algorithms, cellular automata, neural networks, and evolutionary game theory. Papers treating applications in any area of natural science or human endeavor are welcome, and especially encouraged are papers integrating conceptual themes and applications that cross traditional disciplinary boundaries. Complexity is not meant to serve as a forum for speculation and vague analogies between words like “chaos,” “self-organization,” and “emergence” that are often used in completely different ways in science and in daily life.
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