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反向工程模型揭示自主神经和皮肤无髓纤维的膜特性差异。

Reverse-engineered models reveal differential membrane properties of autonomic and cutaneous unmyelinated fibers.

机构信息

Department of Biomedical Engineering Duke University Durham, North Carolina, United States of America.

Duke University, Department of Electrical and Computer Engineering, Durham, North Carolina, United States of America.

出版信息

PLoS Comput Biol. 2024 Oct 7;20(10):e1012475. doi: 10.1371/journal.pcbi.1012475. eCollection 2024 Oct.

DOI:10.1371/journal.pcbi.1012475
PMID:39374306
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11486378/
Abstract

Unmyelinated C-fibers constitute the vast majority of axons in peripheral nerves and play key roles in homeostasis and signaling pain. However, little is known about their ion channel expression, which controls their firing properties. Also, because of their small diameters (~ 1 μm), it has not been possible to characterize their membrane properties using voltage clamp. We developed a novel library of isoform-specific ion channel models to serve as the basis functions of our C-fiber models. We then developed a particle swarm optimization (PSO) framework that used the isoform-specific ion channel models to reverse engineer C-fiber membrane properties from measured autonomic and cutaneous C-fiber conduction responses. Our C-fiber models reproduced experimental conduction velocity, chronaxie, action potential duration, intracellular threshold, and paired pulse recovery cycle. The models also matched experimental activity-dependent slowing, a property not included in model optimization. We found that simple conduction responses, characterizing the action potential, were controlled by similar membrane properties in both the autonomic and cutaneous C-fiber models, but complicated conduction response, characterizing the afterpotenials, were controlled by differential membrane properties. The unmyelinated C-fiber models constitute important tools to study autonomic signaling, assess the mechanisms of pain, and design bioelectronic devices. Additionally, the novel reverse engineering approach can be applied to generate models of other neurons where voltage clamp data are not available.

摘要

无髓 C 纤维构成周围神经中绝大多数轴突,并在体内平衡和信号疼痛中发挥关键作用。然而,人们对其离子通道表达知之甚少,而离子通道表达控制着它们的放电特性。此外,由于其直径较小(约 1μm),因此使用电压钳无法对其膜特性进行特征描述。我们开发了一种新型的同工型特异性离子通道模型库,作为我们 C 纤维模型的基础函数。然后,我们开发了一种粒子群优化(PSO)框架,该框架使用同工型特异性离子通道模型从测量的自主和皮肤 C 纤维传导响应中反向工程 C 纤维的膜特性。我们的 C 纤维模型再现了实验传导速度、chronaxie、动作电位持续时间、细胞内阈值和双脉冲恢复周期。模型还匹配了实验的活动依赖性减速,这是模型优化中未包含的特性。我们发现,简单的传导反应,描述动作电位,在自主和皮肤 C 纤维模型中受到相似的膜特性控制,但复杂的传导反应,描述后电位,受到不同的膜特性控制。无髓 C 纤维模型是研究自主信号、评估疼痛机制和设计生物电子设备的重要工具。此外,新的反向工程方法可用于生成电压钳数据不可用的其他神经元的模型。

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