@article{pittir20418,
          volume = {8},
          number = {12},
           month = {December},
           title = {Central role for MCP-1/CCL2 in injury-induced inflammation revealed by in vitro, in silico, and clinical studies},
          author = {C Ziraldo and Y Vodovotz and RA Namas and K Almahmoud and V Tapias and Q Mi and D Barclay and BS Jefferson and G Chen and TR Billiar and R Zamora},
            year = {2013},
         journal = {PLoS ONE},
             url = {http://d-scholarship-dev.library.pitt.edu/20418/},
        abstract = {The translation of in vitro findings to clinical outcomes is often elusive. Trauma/hemorrhagic shock (T/HS) results in hepatic hypoxia that drives inflammation. We hypothesize that in silico methods would help bridge in vitro hepatocyte data and clinical T/HS, in which the liver is a primary site of inflammation. Primary mouse hepatocytes were cultured under hypoxia (1\% O 2) or normoxia (21\% O2) for 1-72 h, and both the cell supernatants and protein lysates were assayed for 18 inflammatory mediators by Luminex? technology. Statistical analysis and data-driven modeling were employed to characterize the main components of the cellular response. Statistical analyses, hierarchical and k-means clustering, Principal Component Analysis, and Dynamic Network Analysis suggested MCP-1/CCL2 and IL-1{\ensuremath{\alpha}} as central coordinators of hepatocyte-mediated inflammation in C57BL/6 mouse hepatocytes. Hepatocytes from MCP-1-null mice had altered dynamic inflammatory networks. Circulating MCP-1 levels segregated human T/HS survivors from non-survivors. Furthermore, T/HS survivors with elevated early levels of plasma MCP-1 post-injury had longer total lengths of stay, longer intensive care unit lengths of stay, and prolonged requirement for mechanical ventilation vs. those with low plasma MCP-1. This study identifies MCP-1 as a main driver of the response of hepatocytes in vitro and as a biomarker for clinical outcomes in T/HS, and suggests an experimental and computational framework for discovery of novel clinical biomarkers in inflammatory diseases. {\copyright} 2013 Ziraldo et al.}
}