From Cell to Society: A New Method to Characterize Cardiac Autonomic Control
From Cell to Society: A New Method to Characterize Cardiac Autonomic Control
批准号:
7503516
负责人:
Emilia Bagiella
金额:
$27.64万
依托单位国家:
美国
项目类别:
财政年份:
2007
资助国家:
美国
项目状态:
已结题
起止时间:
2007-09-28 至 2011-05-31
关键词:
Autonomic nervous systemBehaviorBehavioralBehavioral MedicineCardiacCardiologyCell physiologyCellsCharacteristicsClinicalComplexConditionDataData AnalysesData SetDisciplineDiseaseExerciseFrequenciesFundingGoalsHandHostilityImmunologyInflammationInflammatoryInterdisciplinary StudyLinkLow Birth Weight InfantMeasuresMediatingMental DepressionMethodologyMethodsMyocardial InfarctionNumbersOrthostasisOutcomePatientsPhysiologicalPhysiologyPlayPregnancy OutcomePrincipal Component AnalysisProcessPsychophysiologyRaceRangeRegulationResearchResearch PersonnelResearch Project GrantsResourcesRheumatoid ArthritisRoleSeveritiesSocietiesStatistical MethodsStructureSystemTraininganalytical methodbasebehavioral/social sciencecomputerized data processingexperienceindexingmortalitynovelpsychologicresponseskillssocialsocioeconomicsstatisticstechnological innovationtrait
中文摘要
描述(由申请人提供):这份来自经验丰富的跨学科研究团队的申请书描述了我们整合各种研究领域的方法,以回应RFA:RM-07-004,题为“通过行为和社会科学的方法学和技术创新促进跨学科研究(R21)”。自主神经系统(ANS)在社会、心理和行为与各种生理系统和病理生理状态的整合中起着至关重要的作用。一些研究表明,ANS与宏观领域之间的联系,从社会领域到心理领域,再到行为领域。其他研究已经证明了ANS在疾病的微观领域中的作用,从生理到细胞。这项应用的总体目标是使用一种新的统计学方法--功能数据分析,来分析RR间期变异性(RRV),这是ANS活动的一个指标,将社会、行为和心理特征与临床、生理和炎症标记物联系起来。本申请的具体目的集中于调查是否将功能数据分析的统计方法扩展到RRV功能形式的分析)增强和/或阐明心脏自主神经控制、炎症过程、临床心脏病学结果以及行为和社会因素之间的复杂关系,以及b)解释这些关系的多维方面。这一应用的方法论、临床和跨学科的相关性在于,这里讨论的新方法可能使研究人员能够更清楚地解释和更有效地分析RRV数据,并确定和理解ANS在连接多个学科中的作用,将社会力量、心理特征和行为等不同现象与任何数量的临床条件、基本生理和细胞活动联系起来。自主神经系统(ANS)在社会、心理和行为与各种生理系统和病理生理状态的整合中起着至关重要的作用。我们介绍了一种新的统计方法,功能数据分析,用于分析RR间期变异性(RRV),这是ANS活动的一个指标。我们希望能够更好地确定和理解ANS在连接多个学科方面的作用。
英文摘要
DESCRIPTION (provided by applicant): This application from a highly experienced and interdisciplinary team of investigators describes our approach to integrate a variety of research fields in response to the RFA: RM-07-004 entitled "Facilitating Interdisciplinary Research via Methodological and Technological Innovation in the Behavioral and Social Sciences (R21)". The autonomic nervous system (ANS) plays a critical role in integrating the social, psychological, and behavioral with various physiological systems and pathophysiological states. Several studies have shown links between the ANS and macro domains ranging from the social to the psychological to the behavioral. Other studies have demonstrated the role of the ANS in the micro domains of disease, from physiology to the cellular. The overall aim of this application is to use a novel statistical approach, functional data analysis, for the analysis of RR interval variability (RRV), an index of ANS activity, to relate social, behavioral, and psychological traits to clinical, physiological and inflammatory markers. The specific aims of this application focus on investigating whether extending statistical methods of functional data analysis to the analysis of the functional form of RRV a) enhances and/or elucidates the complex relationships between cardiac autonomic control, inflammatory processes, clinical cardiology outcomes, and behavioral and social factors, and b) explains the multi-dimensional aspect of these relationships. The methodological, clinical and interdisciplinary relevance of this application is that the new methodology discussed here might enable researchers to interpret more clearly and to analyze more efficiently RRV data, and to determine and understand the role of the ANS in connecting multiple disciplines, linking such diverse phenomena as social forces, psychological characteristics, and behaviors to any number of clinical conditions, basic physiology, and cellular activity. The autonomic nervous system (ANS) plays a critical role in integrating the social, psychological, and behavioral with various physiological systems and pathophysiological states. We introduce a novel statistical approach, functional data analysis, for the analysis of RR interval variability (RRV), an index of ANS activity. We hope to be able to better determine and understand the role of the ANS in connecting multiple disciplines.
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