Suppr超能文献

精准疫苗研发:从天然免疫中获得启示。

Precision Vaccine Development: Cues From Natural Immunity.

机构信息

Precision Vaccines Program, Division of Infectious Diseases, Boston Children's Hospital, Boston, MA, United States.

Department of Pediatrics, Harvard Medical School, Boston, MA, United States.

出版信息

Front Immunol. 2022 Feb 10;12:662218. doi: 10.3389/fimmu.2021.662218. eCollection 2021.

Abstract

Traditional vaccine development against infectious diseases has been guided by the overarching aim to generate efficacious vaccines normally indicated by an antibody and/or cellular response that correlates with protection. However, this approach has been shown to be only a partially effective measure, since vaccine- and pathogen-specific immunity may not perfectly overlap. Thus, some vaccine development strategies, normally focused on targeted generation of both antigen specific antibody and T cell responses, resulting in a long-lived heterogenous and stable pool of memory lymphocytes, may benefit from better mimicking the immune response of a natural infection. However, challenges to achieving this goal remain unattended, due to gaps in our understanding of human immunity and full elucidation of infectious pathogenesis. In this review, we describe recent advances in the development of effective vaccines, focusing on how understanding the differences in the immunizing and non-immunizing immune responses to natural infections and corresponding shifts in immune ontogeny are crucial to inform the next generation of infectious disease vaccines.

摘要

传统的传染病疫苗开发是以产生有效的疫苗为指导目标,通常通过抗体和/或细胞反应来表示,这些反应与保护作用相关。然而,这种方法已被证明只是一种部分有效的措施,因为疫苗和病原体特异性免疫可能不完全重叠。因此,一些疫苗开发策略通常侧重于有针对性地产生针对抗原的抗体和 T 细胞反应,从而产生长期存在的异质且稳定的记忆淋巴细胞池,可能会从更好地模拟自然感染的免疫反应中受益。然而,由于我们对人类免疫的理解存在差距,以及对传染病发病机制的全面阐明,实现这一目标的挑战仍然存在。在这篇综述中,我们描述了有效疫苗开发的最新进展,重点介绍了了解自然感染中免疫和非免疫反应的差异以及免疫个体发生的相应变化,对于为下一代传染病疫苗提供信息至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/755b/8866702/3c1a4627f673/fimmu-12-662218-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验