Background. Intestinal sensitivity to mechanical stimuli has been studied intensively in visceral pain studies. The ability to sense different stimuli in the gut and translate these to physiological outcomes relies on the mechanosensory and transductive capacity of intrinsic intestinal nerves. However, the nature of the mechanosensitive channels and principal mechanical stimulus for mechanosensitive receptors are unknown. To be able to characterize intestinal mechanoelectrical transduction, that is, the molecular basis of mechanosensation, comprehensive mathematical models to predict responses of the sensory neurons to controlled mechanical stimuli are needed. This study aims to develop a biophysically based mathematical model of the myenteric neuron with the parameters constrained by learning from existing experimental data. Findings. The conductance-based single-compartment model was selected. The parameters in the model were optimized by using a combination of hand tuning and automated estimation. Using the optimized parameters, the model successfully predicted the electrophysiological features of the myenteric neurons with and without mechanical stimulation. Conclusions. The model provides a method to predict features and levels of detail of the underlying physiological system in generating myenteric neuron responses. The model could be used as building blocks in future large-scale network simulations of intrinsic primary afferent neurons and their network.

中文翻译：

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肌间神经元动力学响应机械拉伸的模拟

背景. 肠道对机械刺激的敏感性已经在内脏疼痛研究中进行了深入研究。感知肠道中不同刺激并将其转化为生理结果的能力依赖于内在肠道神经的机械感觉和传导能力。然而，机械敏感通道的性质和机械敏感受体的主要机械刺激是未知的。为了能够表征肠道机械电转导，即机械感觉的分子基础，需要综合数学模型来预测感觉神经元对受控机械刺激的反应。本研究旨在开发一种基于生物物理的肌间神经元数学模型，其参数受现有实验数据的学习限制。调查结果。选择了基于电导的单室模型。模型中的参数通过手动调整和自动估计相结合进行了优化。使用优化的参数，该模型成功地预测了有和没有机械刺激的肌间神经元的电生理特征。结论。该模型提供了一种方法来预测产生肌间神经元反应的潜在生理系统的特征和细节水平。该模型可用作内部初级传入神经元及其网络的未来大规模网络模拟的构建块。