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:
7846879
负责人:
Emilia Bagiella
金额:
$27.09万
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 2012-05-31
关键词:
Autonomic nervous systemBehaviorBehavioralBehavioral MedicineCardiacCardiologyCell physiologyCellsCharacteristicsClinicalComplexDataData AnalysesData SetDisciplineDiseaseExerciseFrequenciesFundingGoalsHostilityImmunologyInflammationInflammatoryInterdisciplinary StudyLinkLow Birth Weight InfantMeasuresMediatingMental DepressionMethodologyMethodsMyocardial InfarctionOrthostasisOutcomePatientsPhysiologicalPhysiologyPlayPregnancy OutcomePrincipal Component AnalysisProcessPsychophysiologyRaceRegulationResearchResearch PersonnelResearch Project GrantsResourcesRheumatoid ArthritisRoleSeveritiesSocietiesSocioeconomic StatusStatistical MethodsStructureSystemTraininganalytical methodbasebehavioral/social sciencecomputerized data processingexperienceindexinginflammatory markermortalitynovelpsychologicresponseskillssocialstatisticstechnological innovationtrait
中文摘要
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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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