一种仅基于离子扩散系数预测可兴奋细胞膜电流的原始模型
A Primitive Model for Predicting Membrane Currents in Excitable Cells Based Only on Ion Diffusion Coefficients
AI总结：
本研究提出一种仅基于离子扩散系数的可兴奋细胞膜电流预测原始模型，通过耦合电扩散过程实现钠通道自然启闭，无需经验电压门控参数即可匹配巨乌贼轴突实验数据。
摘要：
最初由Hodgkin和Huxley提出的、用于预测轴突等可兴奋细胞中电流流动的经典模型，依赖于经验性电压门控参数，这些参数量化了钠离子和钾离子通道的离子转运。我们提出了一种完全基于已确立的离子扩散系数来预测这些电流的原始模型。中央钠通道开放导致的可兴奋细胞内部变化被限制在一个不断扩大的半球内，其半径由钠离子扩散系数决定。在整个计算过程中保持开放的钠通道，会因耦合的电扩散过程而自然激活和失活。皮安量级的电流脉冲的特征时间，会随着通道密度从每平方微米10000个降至1个，而从10⁻⁵秒增加到10⁻¹秒。我们将模型预测结果与从巨乌贼轴突获得的数据进行了比较，过程中未引入任何门控参数。
英文摘要：
Classical models for predicting current flow in excitable cells such as axons, originally proposed by Hodgkin and Huxley, rely on empirical voltage-gating parameters that quantify ion transport across sodium and potassium ion channels. We propose a primitive model for predicting these currents based entirely on well-established ion diffusion coefficients. Changes inside the excitable cell due to the opening of a central sodium channel are confined to a growing hemisphere with a radius that is governed by the sodium ion diffusion coefficient. The sodium channel, which is open throughout the calculation, activates and deactivates naturally due to coupled electrodiffusion processes. The characteristic time of current pulses, which are in the picoampere range, increases from 10$^{-5}$ to 10$^{-1}$ s as channel density is decreased from 10,000 to 1 channel per micrometer squared. Model predictions are compared with data obtained from giant squid axons without invoking any gating parameters.
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