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TRANSLATIONAL PHYSIOLOGY
Departments of 1Anesthesiology and Critical Care Medicine, 2Pulmonary and Critical Care Medicine, and 3Pathology, The Johns Hopkins University, Baltimore, Maryland
Submitted 2 November 2005 ; accepted in final form 9 June 2006
Human acute lung injury is characterized by heterogeneous tissue involvement, leading to the potential for extremes of mechanical stress and tissue injury when mechanical ventilation, required to support critically ill patients, is employed. Our goal was to establish whether regional cellular responses to these disparate local mechanical conditions could be determined as a novel approach toward understanding the mechanism of development of ventilator-associated lung injury. We utilized cross-species genomic microarrays in a unilateral model of ventilator-associated lung injury in anesthetized dogs to assess regional cellular responses to local mechanical conditions that potentially contribute pathogenic mechanisms of injury. Highly significant regional differences in gene expression were observed between lung apex/base regions as well as between gravitationally dependent/nondependent regions of the base, with 367 and 1,544 genes differentially regulated between these regions, respectively. Major functional groupings of differentially regulated genes included inflammation and immune responses, cell proliferation, adhesion, signaling, and apoptosis. Expression of genes encoding both acute lung injury-associated inflammatory cytokines and protective acute response genes were markedly different in the nondependent compared with the dependent regions of the lung base. We conclude that there are significant differences in the local responses to stress within the lung, and consequently, insights into the cellular responses that contribute to ventilator-associated lung injury development must be sought in the context of the mechanical heterogeneity that characterizes this syndrome.
adult respiratory distress syndrome; mechanical ventilation; canine; computed tomography; cross-species microarray
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