Results: The proliferation rate was significantly higher in the livers at one week of age compared to controls (22% vs 17%, respectively; P=0.01). Studies on these livers using Sox9 and Ki67 have excluded the Sox9 progenitor

compartment as the source of proliferation. Rather proliferation rates for both Sox9 progenitors and hepato-cytes were lower in the mutants compared to controls (10% vs 19% and 33% vs 46%, respectively). However, we identified a significant increase in single Z-VAD-FMK datasheet Sox9+ progenitor numbers in the one-week old Jag1+/−Rfng+/− livers when comparing them to age-matched controls (Ave =145 vs 37; P=0.0001). Co-localization studies have identified a significant increase in Hnf4α+/Sox9+ as well (Ave =65 vs 26; P=0.05), but a significant reduction in the number of CK+/Sox9+ population (Avg =178 vs 359; P=0.0004). Conclusions:

We identified a proliferation rate increase in the one-week old Jag1+/−Rfng+/−mutants and determined that neither the Sox9 progenitor compartment nor the hepatocytes were proliferating. However, due to their significant increases in overall numbers, we concluded that these compartments are aberrantly differentiating toward both cholangiocytes and hepatocytes. The reduced number of CK+/Sox9+ cells at the same time point also supports a delay in maturation of biliary cells as CK19 is a marker of the mature cholangiocyte. This work further substantiates recent findings whereby Sox9 progenitors differentiate along both see more the cholangiocyte and hepatocyte lineages. Disclosures: The following people have nothing to disclose: 上海皓元 Lara A. Underkoffler, Emily K. McComb, John Dutton, Anthony Nelson, Kathleen M. Loomes, Matthew J. Ryan

Objective: Pediatric Acute Liver Failure (PALF) is a rapidly evolving clinical condition. Tools to reliably predict spontaneous survival (S) and non-survival (NS), to assess biomarkers of disease severity and trajectory, and to inform liver transplantation (LTx) decisions are not available. We hypothesized that key inflammatory interactions as well as subgroup-specific dynamic patterns using data-driven computational modeling of protein-level expression of inflammatory mediators in serum may serve as tools for predicting outcomes. Methods: During the 7 days following enrollment in the PALF study, serum samples from 140 children were collected and assayed for 27 inflammatory mediators. Outcomes (S [n=80], NS [n=18], and LTx [n=42]) were assessed within 21 days. Data were analyzed using Two-Way ANOVA, time-interval Principal Component Analysis (PCA), and Dynamic Network Analysis (DyNA). Results: Two-Way ANOVA revealed multiple inflammatory mediators that changed significantly and separated patient groups: MCP-1 and most interleukins differentiated S and LTx from NS; Eotaxin, MIG and IL-17 segregated LTx from S and NS; and sIL-2Rβ and IP-10 differentiated S from LTx.