PDF(Pubmed)
Abstract：
The preBötzinger complex (preBötC), located in the medulla, is the essential rhythm-generating neural network for breathing. The actions of opioids on this network impair its ability to generate robust, rhythmic output, contributing to life-threatening opioid-induced respiratory depression (OIRD). The occurrence of OIRD varies across individuals and internal and external states, increasing the risk of opioid use, yet the mechanisms of this variability are largely unknown. In this study, we utilize a computational model of the preBötC to perform several in silico experiments exploring how differences in network topology and the intrinsic properties of preBötC neurons influence the sensitivity of the network rhythm to opioids. We find that rhythms produced by preBötC networks in silico exhibit variable responses to simulated opioids, similar to the preBötC network in vitro. This variability is primarily due to random differences in network topology and can be manipulated by imposed changes in network connectivity and intrinsic neuronal properties. Our results identify features of the preBötC network that may regulate its susceptibility to opioids.
摘要：
pre-Botzinger复合物（preBotC），位于髓质，是呼吸的基本节律生成神经网络。阿片类药物在这个网络上的作用削弱了它产生强大的能力，有节奏的输出，导致危及生命的阿片类药物引起的呼吸抑制（OIRD）。OIRD的发生因个人和内部和外部状态而异，增加使用阿片类药物的风险，然而，这种变异性的机制在很大程度上是未知的。在这项研究中,我们利用preBotC的计算模型进行了一些计算机模拟实验，探索网络拓扑和preBotC神经元的固有特性的差异如何影响网络节奏对阿片类药物的敏感性。我们发现，preBotC网络在计算机上产生的节律对模拟阿片类药物表现出可变的反应，与体外preBotC网络相似。这种可变性主要是由于网络拓扑的随机差异，并且可以通过网络连接和固有神经元属性的强加变化来操纵。我们的结果确定了preBootC网络的特征，这些特征可能会调节其对阿片类药物的敏感性。意义陈述脑干中产生呼吸节律的神经网络被阿片类药物破坏。然而,这种反应出奇的不可预测。通过构建这个节奏生成网络的计算模型，我们说明了个体网络中生物物理特性和连接模式分布的随机差异如何预测它们对阿片类药物的反应，我们展示了这些网络特征的调节如何使呼吸更容易受到阿片类药物的影响或抵抗。
