A complex systems approach to bronchoconstriction in Asthma
A complex systems approach to bronchoconstriction in Asthma
批准号:
7462755
负责人:
Tilo Winkler
金额:
$45.87万
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-07-01 至 2011-06-30
关键词:
AffectAnimal ExperimentsAnimalsAsthmaBackBehaviorBreathingBronchial TreeBronchoconstrictionCaliberChronic DiseaseComplexComputer SimulationDataDevelopmentDiagnosisDiseaseEconomic BurdenEffectivenessElementsEnvironmental air flowExposure toFunctional disorderHeterogeneityImageIncidenceIndividualInterventionKnowledgeLeadLifeLungMeasurementMeasuresMechanicsMethodsModelingMolecularOrganPatternPeripheralPhasePhysicsPhysiologicalPropertyProtocols documentationRecording of previous eventsRecoveryRefractoryReportingResearchSeveritiesSmooth MuscleSourceStretchingStructureSystemSystems AnalysisTestingTherapeuticTherapeutic InterventionTidal VolumeTimeTreesUnited StatesWorkairway obstructionanalytical toolasthmatic airwaybaseconstrictiondesignimprovedinnovationlung imagingnetwork modelsnovelpreventpublic health relevancerespiratoryrespiratory smooth muscleresponsesystems researchtheoriestool
中文摘要
描述(申请人提供):哮喘是一种发病率迅速上升的疾病,仅在美国就有1700多万人受到影响。了解异质通气和气道阻塞的原因是非常重要的,这是导致哮喘患者肺功能障碍的主要特征。然而,尽管对单个呼吸道的行为以及哮喘的细胞和分子机制有详细的了解,但人们对哮喘呼吸道树为什么异质性收缩知之甚少。我们的工作假设是,在哮喘中观察到的通风和呼吸道阻塞的异质性,是一个复杂网络的紧急行为的表现,放大了单个呼吸道结构或功能的空间异质性的影响。在这个项目中,我们建议应用复杂系统研究的分析工具来分析肺的综合网络模型在稳定和非稳定条件下的行为。该项目涉及结合使用计算建模和使用PET-CT的成像研究,重点关注两个主要的具体目标,每个目标都涉及理论和实验方面:SA 1:确定导致肺部从均匀状态到异质状态的关键转变的条件,并根据现有和新的实验数据校准理论预测。SA 2:阐明肺的动态行为及其病史是否会使系统陷入不正常的异质状态,以及是否可以使用某些干预措施将系统重新设置到正常的均匀状态。该项目挑战了哮喘研究中的现有范式,并提出了一种新的综合生理系统方法来解决这一问题。我们认为,这种方法是朝着改善对该病的了解迈出的重要一步,这是开发诊断和治疗该病的创新方法所必需的。这些研究的一个更广泛的目标是提供理论和实验证据,以支持J.H.T.Bates(17)最近提出的关于复杂疾病的新理论,根据该理论,反复暴露于侮辱可能会使系统陷入异常状态,一旦去除侮辱来源,系统可能不会自发恢复正常。这项研究具有很高的杠杆作用,因为它将导致开发用于治疗系统的通用复杂系统工具,这些系统的特点是具有双稳元件的分级网络。公共卫生相关性:
哮喘是一种多种原因的疾病,正变得越来越常见,影响着全球超过3亿人,估计每年总经济负担为60亿美元。预测哮喘发作的时间和严重程度对于避免危及生命的情况很重要。这项研究旨在了解哮喘发作期间肺部的复杂行为,这是开发和测试预防或逆转哮喘发作的治疗干预措施所需的关键步骤。
英文摘要
DESCRIPTION (provided by applicant): Asthma is a disease of rapidly increasing incidence that affects more than 17 million people in the United States alone. It is of major importance to understand the causes of heterogeneous ventilation and airway obstruction, cardinal features responsible for lung dysfunction in asthma. Yet, despite detailed knowledge of the behavior of individual airways, and of cellular and molecular mechanism of asthma, not much is known about why the asthmatic airway tree constricts heterogeneously. Our working hypothesis is that heterogeneity of ventilation and airway obstruction observed in asthma, is an expression of emergent behavior of a complex network that magnifies the effects of spatial heterogeneity in structure or function of individual airways. In this project we propose to apply analytical tools from complex systems research to analyze the behavior of an integrative network model of the lung under both steady and unsteady conditions. The project involves the combined use of computational modeling and imaging studies using PET-CT focused on two major specific aims, each involving theoretical and experimental aspects: SA 1: Identify the conditions leading to a critical transition in the lungs from a uniform to a heterogeneous state, and calibrate theoretical predictions against existing and new experimental data. SA 2: Elucidate whether the dynamic behavior of the lung and its history can trap the system in abnormal heterogeneous states, and whether certain interventions can be used to reset the system back to a normal uniform state. This project challenges existing paradigms in asthma research and proposes a novel integrated physiological systems approach to the problem. This approach, we feel, is a vital step towards improved understanding of the disease that is needed for development of innovative methods to its diagnosis and therapy. A broader objective of these studies is to provide theoretical and experimental evidence in support of a novel theory on complex diseases recently formulated by J. H. T. Bates (17) whereby repeated exposure to insults could trap the system in abnormal states from which return to normality may not spontaneously occur once the insult source is removed. The research is highly leveraged, as it will lead to development of general complex systems tools for treating systems that, like the lung, are characterized by hierarchical networks with bistable elements. PUBLIC HEALTH RELEVANCE:
Asthma is a disease of multiple origins that is becoming increasingly common and affects more than 300 million people worldwide with an estimated total economic burden of $6 billion annually. Predicting the timing and severity of an asthma attack is important to avoid life-threatening situations. This research is aimed at understanding the complex behavior of the lungs during an asthma attack, a key step needed for developing and testing therapeutic interventions to prevent or reverse asthma attacks.
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依托单位:
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