American journal of respiratory and critical care medicine
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Am. J. Respir. Crit. Care Med. · Sep 2014
Genome-wide Interrogation of Longitudinal FEV1 in Children with Asthma.
Most genomic studies of lung function have used phenotypic data derived from a single time-point (e.g., presence/absence of disease) without considering the dynamic progression of a chronic disease. ⋯ This study offers a strategy to explore the genetic determinants of longitudinal phenotypes, provide a comprehensive picture of disease pathophysiology, and suggest potential treatment targets.
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It is often difficult to accurately predict when, why, and which patients develop shock, because signs of shock often occur late, once organ injury is already present. Three levels of aggregation of information can be used to aid the bedside clinician in this task: analysis of derived parameters of existing measured physiologic variables using simple bedside calculations (functional hemodynamic monitoring); prior physiologic data of similar subjects during periods of stability and disease to define quantitative metrics of level of severity; and libraries of responses across large and comprehensive collections of records of diverse subjects whose diagnosis, therapies, and course is already known to predict not only disease severity, but also the subsequent behavior of the subject if left untreated or treated with one of the many therapeutic options. ⋯ To address these issues, multivariable models using machine learning data-driven classification techniques can be used to parsimoniously predict cardiorespiratory insufficiency. We briefly describe how these machine learning approaches are presently applied to address earlier identification of cardiorespiratory insufficiency and direct focused, patient-specific management.
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Am. J. Respir. Crit. Care Med. · Sep 2014
Squalene Synthase Induces TNFR1 Enrichment in Lipid Rafts to Promote Lung Cancer Metastasis.
Metabolic alterations contribute to cancer development and progression. However, the molecular mechanisms relating metabolism to cancer metastasis remain largely unknown. ⋯ Up-regulation of SQS promotes metastasis of lung cancer by enhancing tumor necrosis factor-α receptor 1 and nuclear factor-κB activation and matrix metallopeptidase 1 expression. Targeting SQS may have considerable potential as a novel therapeutic strategy to treat metastatic lung cancer.