An Adaptive Control Scheme for Interleukin-2 Therapy.

An Adaptive Control Scheme for Interleukin-2 Therapy.
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白介素-2治疗的自适应控制方案。

DOI:
10.1016/j.isci.2020.101663
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发表时间:
2020-11-20
期刊:
影响因子:
5.8
通讯作者:
Meyer-Hermann M
Meyer-Hermann M
中科院分区:
综合性期刊2区
文献类型:
--
作者:
Khailaie S;Montaseri G;Meyer-Hermann M

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调节性T细胞(Treg)是一种抑制细胞,控制自身反应性和过度的效应性常规T辅助细胞(Tconv)反应。T细胞和T细胞之间平衡的破坏是自身免疫性和炎症性疾病的标志。白介素2(IL-2)是两种人群的生长因子,也是IL-2治疗中恢复健康免疫平衡的微妙杠杆。通过使用机械数学模型,我们引入了一种自适应控制策略来设计增加和稳定Treg群体并限制炎症反应所需的最小治疗性IL-2剂量。这种自适应方案允许根据患者免疫动力学的反馈进行剂量调整。我们的模拟结果表明,需要最小的Treg群体来限制IL-2注射对效应器Tconv反应的瞬时副作用。硅胶研究结果表明,IL-2和过继Treg转移疗法的结合可以限制这种副作用。介绍了一种用于IL-2治疗的自适应剂量策略,并对其进行了分析。IL-2注射可以调整以增加和稳定调节性T细胞数量免疫抑制IL-2疗法可能暂时加剧效应性T细胞反应联合IL-2和过继调节性T细胞疗法可以安全地限制炎症
Regulatory T cells (Treg) are suppressor cells that control self-reactive and excessive effector conventional T helper cell (Tconv) responses. Breakdown of the balance between Tregs and Tconvs is a hallmark of autoimmune and inflammatory diseases. Interleukin-2 (IL-2) is a growth factor for both populations and subtle leverage to restore the healthy immune balance in IL-2 therapy. By using a mechanistic mathematical model, we introduced an adaptive control strategy to design the minimal therapeutic IL-2 dosage required to increase and stabilize Treg population and restrict inflammatory response. This adaptive protocol allows for dose adjustments based on the feedback of the immune kinetics of the patient. Our simulation results showed that a minimal Treg population was required to restrict the transient side effect of IL-2 injections on the effector Tconv response. In silico results suggested that a combination of IL-2 and adoptive Treg transfer therapies can limit this side effect. An adaptive dosing strategy for IL-2 therapy is introduced and analyzed in silico IL-2 injections can be tuned to increase and stabilize regulatory T-cell numbers Immunosuppressive IL-2 therapy may transiently exacerbate effector T-cell responses Combined IL-2 and adoptive regulatory T-cell therapy can safely limit inflammation Biological Sciences; Immunology; Mathematical Bioscience
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