Alcohol Activates the Hedgehog Pathway and Induces Related Procarcinogenic Processes in the Alcohol-Preferring Rat Model of Hepatocarcinogenesis

Alcohol consumption promotes hepatocellular carcinoma (HCC). The responsible mechanisms are not well understood. Hepatocarcinogenesis increases with age and is enhanced by factors that impose a demand for liver regeneration. Because alcohol is hepatotoxic, habitual alcohol ingestion evokes a recurrent demand for hepatic regeneration. The alcohol-preferring (P) rat model mimics the level of alcohol consumption by humans who habitually abuse alcohol. Previously, we showed that habitual heavy alcohol ingestion amplified age-related hepatocarcinogenesis in P-rats, with over 80% of alcohol-consuming P rats developing HCCs after 18 months of alcohol exposure, compared to only 5% of water-drinking controls

Baseline Levels and Temporal Stability of 27 Multiplexed Serum Cytokine Concentrations in Healthy Subjects

<div><p>Background</p><p>Cytokines are humoral molecules that elicit regulatory function in immunologic pathways. The level and type of cytokine production has become critical in distinguishing physiologic from pathologic immune conditions. Cytokine profiling has become an important biomarker discovery tool in monitoring of the immune system. However, the variations in cytokine levels in individual subjects over time in healthy individuals have not been extensively studied. In this study, we use multiplex bead arrays to evaluate 27 analytes in paired serum samples taken seven days apart from 144 healthy individuals in order to assess variations over a short time period.</p> <p>Methods</p><p>Fluorescent bead-based immunoassay (Luminex) was used to measure 27 analytes in serum samples. Measurements were performed on matched samples from 144 healthy donors. To assess inter-plate variability, one arbitrarily selected serum sample was analyzed on each of the first ten plates as bridge sample. </p> <p>Results</p><p>Using the bridge sample, we showed minimal inter-plate variations in the measurement of most analytes. In measurement of cytokines from the 144 patients at two time points, we found that three cytokines (IL-2, IL-15 and GM-CSF) were undetectable and five analytes (RANTES, MCP-1, VEGF, MIP-1β and PDGF-BB) showed significant difference in concentrations at Day 0 compared to Day 7. </p> <p>Conclusions</p><p>The current study demonstrated higher variations in cytokine levels among individuals than were observed for samples obtained one week apart from identical donors. These data suggest that a serum sample from each subject for use as a baseline measurement is a better control for clinical trials rather than sera from a paired cohort.</p> </div

Correction: Baseline Levels and Temporal Stability of 27 Multiplexed Serum Cytokine Concentrations in Healthy Subjects

<p>Correction: Baseline Levels and Temporal Stability of 27 Multiplexed Serum Cytokine Concentrations in Healthy Subjects</p

Mean concentrations for cytokines in serum samples at Day 0 and Day 7.

<p>Serum cytokine concentrations were measured on matched samples at Day 0 and Day 7. Paired T-tests were performed to measure the significance of the difference of the mean between Day 0 and Day 7. Cytokines for which %CV is higher than 20% are shown with “*”.</p

Concentrations for three cytokines in serum specimens measured at Day 0 and Day 7 for all 144 healthy volunteers.

<p>Serum cytokine concentrations were measured on samples at day 0 and day 7. Each data point corresponds to a matched measurement at Day 0 (black circle) and Day 7 (black square). These plots demonstrate 3 of the 27 analytes and display RANTES (A), IL-7 (B), IL-9 (C) concentrations.</p

Correlation between cytokine concentration and age.

<p>Correlations of serum cytokine concentrations versus age were measured on samples at Day 0 and Day 7.</p

Cytokine concentrations in bridge sample.

<p>Results show mean concentrations of analytes for the bridge sample assayed in 10 plates with the bars representing the standard errors of the mean.</p