Dynamic balance of pro- and anti-inflammatory signals controls disease and limits pathology.
Dynamic balance of pro- and anti-inflammatory signals controls disease and limits pathology.
复制标题
DOI：
10.1111/imr.12671
复制
发表时间：
2018-09
影响因子：
8.7
通讯作者：
Kirschner DE
中科院分区：
文献类型：
--
作者：
Cicchese JM;Evans S;Hult C;Joslyn LR;Wessler T;Millar JA;Marino S;Cilfone NA;Mattila JT;Linderman JJ;Kirschner DE
对病原体的免疫反应是复杂的，在许多疾病中还不清楚，对于持久性病原体的感染尤其如此。允许长期控制感染同时还防止过度热情的炎症反应引起广泛的组织损伤的一种机制是免疫系统平衡促炎细胞和抗炎细胞和信号。这种平衡是动态的，免疫系统对来自宿主和病原体的线索做出反应，通过持续的反馈在多个尺度上保持稳定状态。识别信号，细胞，细胞因子和其他免疫反应因子，随着时间的推移，调解这种平衡一直很难使用传统的研究策略。基于传统系统数据的计算建模研究可以确定这种平衡如何有助于免疫力。在这里，我们提供的证据，从实验和数学/计算研究，以支持一个动态平衡的概念，在持续和其他感染的情况下运行。我们主要关注结核病，这是目前世界上因传染病导致死亡的主要原因，同时也为其他感染提供证据。更好地了解动态平衡的免疫反应可以帮助制定利用药物和宿主导向疗法的治疗策略。
Immune responses to pathogens are complex and not well understood in many diseases, and this is especially true for infections by persistent pathogens. One mechanism that allows for long-term control of infection while also preventing an over-zealous inflammatory response from causing extensive tissue damage is for the immune system to balance pro- and anti-inflammatory cells and signals. This balance is dynamic and the immune system responds to cues from both host and pathogen, maintaining a steady state across multiple scales through continuous feedback. Identifying the signals, cells, cytokines, and other immune response factors that mediate this balance over time has been difficult using traditional research strategies. Computational modeling studies based on data from traditional systems can identify how this balance contributes to immunity. Here we provide evidence from both experimental and mathematical/computational studies to support the concept of a dynamic balance operating during persistent and other infection scenarios. We focus mainly on tuberculosis, currently the leading cause of death due to infectious disease in the world, and also provide evidence for other infections. A better understanding of the dynamically balanced immune response can help shape treatment strategies that utilize both drugs and host-directed therapies.
登录
查看更多内容
影响因子：
4.3
作者：
Albergante L;Timmis J;Beattie L;Kaye PM
通讯作者：
Kaye PM
DOI：
10.1084/jem.20070663
发表时间：
2007-08-06
期刊：
The Journal of experimental medicine
影响因子：
--
作者：
Annunziato F;Cosmi L;Santarlasci V;Maggi L;Liotta F;Mazzinghi B;Parente E;Filì L;Ferri S;Frosali F;Giudici F;Romagnani P;Parronchi P;Tonelli F;Maggi E;Romagnani S
通讯作者：
Romagnani S
DOI：
10.1038/nri.2017.69
发表时间：
2017-11
期刊：
Nature reviews. Immunology
影响因子：
--
作者：
Cadena AM;Fortune SM;Flynn JL
通讯作者：
Flynn JL
影响因子：
5.4
作者：
Beveridge, Natalie E. R.;Price, David A.;McShane, Helen
通讯作者：
McShane, Helen
影响因子：
3.8
作者：
Aoun, Jessica;Habib, Robert;Khalifeh, Ibrahim
通讯作者：
Khalifeh, Ibrahim