No abstract

The liver and spleen are major biological barriers to translating nanomedicines because they sequester the majority of administered nanomaterials and prevent delivery to diseased tissue. Here we examined the blood clearance mechanism of administered hard nanomaterials in relation to blood flow dynamics, organ microarchitecture, and cellular phenotype. We found that nanomaterial velocity reduces 1000-fold as they enter and traverse the liver, leading to 7.5 times more nanomaterial interaction with hepatic cells relative to peripheral cells. In the liver, Kupffer cells (84.8%±6.4%), hepatic B cells (81.5±9.3%), and liver sinusoidal endothelial cells (64.6±13.7%) interacted with administered PEGylated quantum dots but splenic macrophages took up less (25.4±10.1%) due to differences in phenotype. The uptake patterns were similar for two other nanomaterial types and five different surface chemistries. Potential new strategies to overcome off-target nanomaterial accumulation may involve manipulating intra-organ flow dynamics and modulating cellular phenotype to alter hepatic cell interaction.

Despite evidence that the intestinal microbiota (IM) is involved in the pathogenesis of obesity, the IM composition of patients with nonalcoholic fatty liver disease (NAFLD) has not been well characterized. This prospective, cross-sectional study was aimed at identifying differences in IM between adults with biopsy-proven NAFLD (simple steatosis [SS] or nonalcoholic steatohepatitis [NASH]) and living liver donors as healthy controls (HC). Fifty subjects were included: 11 SS, 22 NASH, and 17 HC. One stool sample was collected from each participant. Quantitative real-time polymerase chain reaction was used to measure total bacterial counts, Bacteroides/Prevotella (herein referred to as Bacteroidetes), Clostridium leptum, C. coccoides, bifidobacteria, Escherichia coli and Archaea in stool. Clinical and laboratory data, food records, and activity logs were collected. Patients with NASH had a lower percentage of Bacteroidetes (Bacteroidetes to total bacteria counts) compared to both SS and HC (P 5 0.006) and higher fecal C. coccoides compared to those with SS (P 5 0.04). There were no differences in the remaining microorganisms. As body mass index (BMI) and dietary fat intake differed between the groups (P < 0.05), we performed linear regression adjusting for these variables. The difference in C. coccoides was no longer significant after adjusting for BMI and fat intake. However, there continued to be a significant association between the presence of NASH and lower percentage Bacteroidetes even after adjusting for these variables (P 5 0.002; 95% confidence interval 5 20.06 to 20.02). Conclusion: There is an inverse and diet-/BMI-independent association between the presence of NASH and percentage Bacteroidetes in the stool, suggesting that the IM may play a role in the development of NAFLD. (HEPATOLOGY 2013;58:120-127)