61 research outputs found
Main metabolic pathways for the production of microbial metabolites.
<p>VOC are shown in bold <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0052387#pone.0052387-Welberg1" target="_blank">[52]</a>.</p
Summary of the parameters of colonic metabolism and toxicity.
<p>All values are expressed as median (IQR) (n = 20). Parameters with different letters (a, b, c) in superscript were significantly different between the dietary interventions. Friedman and Wilcoxon tests were used to evaluate the results, except for urinary <sup>15</sup>N and p-cresol, and fecal <sup>15</sup>N. Due to missing values an unstructured linear mixed model was applied using treatment as fixed effect. P-values refer to Friedman tests.</p
Scatter plot of the comparison between urinary p-cresol excretion (mg/24 h) and absolute protein intake (g/24 h).
<p>Urinary p-cresol excretion correlated positively with absolute protein intake (Spearman’s r = 0.371, p = 0.007).</p
Scatter plot in which cytotoxicity (IC50) is plotted against urinary p-cresol excretion (mg/24 h).
<p>The plot shows a negative correlation between both parameters (Spearman’s r = −0.435, p = 0.001).</p
Bland-Altman plot comparing energy intake measured using indirect calorimetry (kcal/d) and energy intake calculated from the dietary records (kcal/d).
<p>Mean energy intake measured by calorimetry and dietary record are plotted against the difference between energy intake measured by calorimetry and by dietary record.</p
Score plots showing clustering of the metabolite profiles analyzed using PLS-DA according to genotoxicity (A) and cytotoxicity (B).
<p>(A) High genotoxicity samples are located on the right side of the score plot, while low genotoxicity samples are present on the left side, indicating a difference in VOC profile between high and low genotoxicity samples. (B) High cytotoxicity samples are present on the upper right side of the score plot and low cytotoxicity samples on the lower left side, indicating a difference in VOC profile between high and low cytotoxicity samples.</p
Summary of dietary records and validating measures in urine.
<p>All values are expressed as medians (IQR) (n = 20). Parameters with different letters (a, b, c) in superscript are significantly different between the dietary interventions, test. Friedman and Wilcoxon tests were used to evaluate the results, except for urinary N and urea. Due to missing, values an unstructured linear mixed model was applied using treatment as fixed effect. P-values refer to Friedman tests.</p
Gene Expression Profiling of Early Hepatic Stellate Cell Activation Reveals a Role for Igfbp3 in Cell Migration
<div><p>Background</p><p>Scarring of the liver is the result of prolonged exposure to exogenous or endogenous stimuli. At the onset of fibrosis, quiescent hepatic stellate cells (HSCs) activate and transdifferentiate into matrix producing, myofibroblast-like cells. </p> <p>Aim and methods</p><p>To identify key players during early HSC activation, gene expression profiling was performed on primary mouse HSCs cultured for 4, 16 and 64 hours. Since valproic acid (VPA) can partly inhibit HSC activation, we included VPA-treated cells in the profiling experiments to facilitate this search. </p> <p>Results</p><p>Gene expression profiling confirmed early changes for known genes related to HSC activation such as <i>alpha</i><i>smooth</i><i>muscle</i><i>actin</i> (<i>Acta2</i>)<i>, lysyl</i><i>oxidase</i> (<i>Lox</i>) and <i>collagen</i>, type <i>I</i>, alpha <i>1</i> (<i>Col1a1</i>). In addition we noticed that, although genes which are related to fibrosis change between 4 and 16 hours in culture, most gene expression changes occur between 16 and 64 hours. <i>Insulin-like</i><i>growth</i><i>factor</i><i>binding</i> protein <i>3</i> (<i>Igfbp3</i>) was identified as a gene strongly affected by VPA treatment. During normal HSC activation <i>Igfbp3</i> is up regulated and this can thus be prevented by VPA treatment <i>in</i><i>vitro</i> and <i>in</i><i>vivo</i>. siRNA-mediated silencing of <i>Igfbp3</i> in primary mouse HSCs induced matrix metalloproteinase (Mmp) <i>9</i> mRNA expression and strongly reduced cell migration. The reduced cell migration after <i>Igfbp3</i> knock-down could be overcome by tissue inhibitor of metalloproteinase (TIMP) 1 treatment. </p> <p>Conclusion</p><p>Igfbp3 is a marker for culture-activated HSCs and plays a role in HSC migration. VPA treatment prevents <i>Igfbp3</i> transcription during activation of HSCs <i>in</i><i>vitro</i> and <i>in</i><i>vivo</i>.</p> </div
Validation of VPA-dependent genes during HSC activation <i>in</i><i>vitro</i> and <i>in</i><i>vivo</i>.
<p>(<b>A</b>, <b>B</b>) mRNA levels of <i>Uchl1</i>, <i>Aplp1</i>, <i>Prtpn, Plat</i> and <i>Igfbp3</i> in <i>in </i><i>vitro</i> activating HSCs cultured for 4 or 64 hours with or without VPA supplementation determined by qPCR. n=3 (<b>C</b>) mRNA expression of HSC activation markers <i>Acta2</i> and Lox in HSCs isolated from CCl<sub>4</sub> treated mice , (<b>D</b>) <i>Uchl1</i>, <i>Aplp1</i> and <i>Igfbp3</i> mRNA levels in <i>in </i><i>vivo</i> activated hepatic stellate cells (HSCs). The cells were isolated from Balb/C jicco CBY mice that were treated for 2 weeks with CCl<sub>4</sub> with or without VPA supplementation to the drinking water. (<b>E</b>) Different liver cell types were isolated from healthy mouse livers; hepatocytes were obtained with Percoll gradients, HSCs with Nycodenz gradients and KC and LSECs were isolated using respectively FACS based F4/80- and CD146-FITC-positivity. QPCR analysis was performed for <i>Igfbp3</i> mRNA in the different liver cell types. Experiments were repeated at least 2 times. In the graphs, the results are displayed as means ± SEM. ns = not significant p ≥ 0.05, * p < 0.05, ** p < 0.01.</p
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