Central mechanisms of respiratory adaptation to mechanical ventilation

 描述(由申请人提供)：重症监护病房(ICU)患者机械通气过程中的一个主要挑战是如何平稳有效地使呼吸机与患者的呼吸努力同步。不同步可能会导致患者不适，对镇静的需求增加，住院时间更长，生存概率更低。目前用于ICU的机械呼吸机设计没有考虑到患者对迷走量相关反馈的深刻的呼吸适应，并且容易出现患者-呼吸机不同步。了解呼吸控制和机械通气之间的双向关系，并将这些新概念带到床边，越来越被认为是重症监护医学中尚未满足的主要优先事项。基于夹带的机械通气是一种新型的机械通气方法，通过将呼吸神经生物学的概念融入到机械呼吸机的设计中，可能会给这一领域带来革命性的变化，并改变临床实践。这一创新的机械通气技术是由最近的证据所推动的，该证据表明，桥脑充气中枢的神经回路通过学习和记忆Hering-Breuer反射，在促进机械通气的呼吸夹带方面发挥着重要作用。患者-呼吸机夹带是一种基本的生理现象，它植根于耦合振子之间相互夹带的经典物理理论。在基于夹带的呼吸机中，患者的自发呼吸节律和呼吸机节律在相同的节奏下彼此相锁，就像两个人一起跳舞。这种新一代通风模式最近获得了FDA批准的用于临床试验的研究设备豁免。为了促进TE基础技术从台面到床边的转换，R01的这一应用提出了一系列临床前研究，目的是更好地了解患者-呼吸机相互作用的神经生理学决定因素。由于患者-呼吸机夹带是一种复杂的现象，因此将实验测试和多尺度建模相结合的系统生物学方法对于定量数据分析和新结果的预测是必不可少的。为此，将在系统(目标1)和细胞(目标2)两个层面阐明呼吸适应机械通风的核心机制，并开发患者-呼吸机相互作用的多尺度神经网络模型，以便模拟实验结果并定量预测开环和闭环呼吸-呼吸机的携带频率和相反应关系(目标3)。一个需要检验的主要假说是，机械通气的呼吸夹带是由桥脑趋气中心的一个独特的神经元群介导的，其特点是严重依赖Nmda受体的活性和对抑制的敏感性。 神经肽生长抑素。

 DESCRIPTION (provided by applicant): A major challenge during mechanical ventilation of patients in the intensive care unit (ICU) is how to synchronize the ventilator with the patient's breathing effort smoothly and effectively. Dyssynchrony could lead to patient discomfort and increased need for sedation, longer hospital stay and lower probability of survival. Current mechanical ventilator designs for use in the ICU do not take into consideration the patient's profound respiratory adaptation to vagal volume-related feedback, and are prone to patient-ventilator asynchrony. Understanding the bidirectional relationship between control of breathing and mechanical ventilation and bringing such new concepts to the bedside is increasingly recognized as a major unmet priority in critical care medicine. Entrainment-based mechanical ventilation is a novel ventilation approach that may potentially revolutionize the field and shift clinical practice by incorporating respiratory neurobiology concepts into mechanical ventilator designs. This innovative mechanical ventilation technique is motivated by recent evidence indicating that neural circuits in the pontine pneumotaxic center plays an important role in promoting respiratory entrainment to mechanical ventilation through learning and memory of the Hering-Breuer reflex. Patient-ventilator entrainment is a fundamental physiologic phenomenon that is grounded in the classical physics theory of mutual entrainment between coupled oscillators. In entrainment-based ventilation, the patient's spontaneous respiratory rhythm and the ventilator rhythm are phase-locked to one another on the same tempo, just like two individuals dancing together. This new-generation ventilation mode has recently gained FDA approval of investigational device exemption for clinical trial. To facilitate the translation of te base technology from the benchtop to the bedside, this R01 application proposes a series of preclinical studies with an objective to gain better understanding of the neurophysiologic determinants of patient-ventilator interaction. Because patient-ventilator entrainment is a complex phenomenon, a systems biology approach combining experimental testing and multiscale modeling for quantitative data analysis and prediction of novel outcomes is essential. This will be achieved by elucidating the central mechanisms underlying respiratory adaptation to mechanical ventilation at both the systems (Aim 1) and cellular levels (Aim 2), and developing a multiscale neural network model of patient-ventilator interaction in order to simulate the experimental results and predict the open-loop and closed-loop respiratory-ventilator entrainment frequency and phase response relationships in a quantitative manner (Aim 3). A major hypothesis to be tested is that respiratory entrainment to mechanical ventilation is mediated by a distinct neuronal population in the pontine pneumotaxic center which is distinguished by its critical dependence on NMDA receptor activity and sensitivity to inhibition by the neuropeptide somatostatin.