41 research outputs found

    Evaluation of AIH-associated autoantigens.

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    <p>(A) The heatmap summarizes the recognition frequencies among different sample groups (AIH, HD and the VH) for the new four autoantigens out of the 31 candidates selected with the proposed bioinformatic strategy after DELFIA screening. Colour intensity denotes the degree of recognition frequency within the sample group. (B) Recognition frequency for two of the four autoantigens, that were statistical significant. (C) Signals distribution detected for each of the new two proteins are displayed. Statistical differences in recognition frequency (ChiSquare test) and in signal intensity (t test) are denoted as single (p<0,05), double (p<0,001) or triple stars (p <0,0001). (D), ROC curve of the biomarker candidates exhibited AUCs of 0.899 (SE = 87.5% and SP = 77.7%), 0.782 (SE = 65.0% and SP = 81.5%) for UNQ9419 and CHAD, respectively. The arrows denote best cut-off points. Combo curve represents the combination, UNQ9419+CHAD, which exhibited AUC of 0.915 (SE = 95.0% and SP = 76.2%).</p

    Selection strategy of serum autoantigens.

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    <p>The Venn diagram shows the autoantigen selection obtained according to (i) VIP scores >1.0 and (ii) a delta difference recognition frequency of 25%. 70 autoantigens overlap between the two filter criteria. Then, final selection of autoantigens was based on relative frequency of autoantigens from all generated datasets. There were 31 variables that were present in all datasets.</p

    Evaluation of feature stability.

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    <p>Robustness of the R-SVM and PLS-DA rankers across the different 50 datasets is plotted as heat maps. Columns and rows represent the independent 50 subsets and each square indicates the Tanimoto index between two subsets. The colour code of the heat map ranges from blue to red where a blue colour reflects a low similarity index suggesting few proteins in common between the subsets while a red colour denotes an high similarity index. For each considered selection method a similarity heat map is obtained. (A), The average similarity over all pair wise comparison is 69% for PLS-DA; (B), and 31% for R-SVM; thus PLS-DA outperforms the R-SVM.</p

    AIH sera recognize UNQ9419 and CHAD.

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    <p>(A), SDS-PAGE (left panel) and western blot against anti-His antibody analysis (right panel) of the purified UNQ9419 and CHAD recombinant proteins. (B), western blot analysis of the purified UNQ9419 and CHAD recombinant proteins against sera from AIH patients (left panel) and no AIH subjects (right panel), respectively.</p

    Identification of human miRNAs associated with serum HBsAg.

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    <p>(a) The circulating HBsAg-miRNA signature: average RQs were obtained from the comparative DDC<sub>T</sub> analysis. Values are reported in a bar plot as a logarithmic scale base 10 along with SD. (b) Differentially detected miRNAs between HBsAg positive immunoprecipitates (HBs-IP+) samples (left-most, n = 11; right-most, n = 4) and the group of control HBsAg negative immunoprecipiates (ctrl-IPs) (n = 4) were selected by Mann-Whitney test on –DCt values (left-most, p<0.1; right-most, p<0.05), and an unsupervised hierarchical cluster analysis was finally performed. Venn diagrams indicate the comparison among the pool of HBsAg-associated miRNAs obtained from the comparative DDC<sub>T</sub> analysis of panel a (blu circle) and the HBsAg-associated miRNAs obtained from the Mann-Whitney tests (red circle).</p

    Overview of the PLS-DA analysis for the comparison between AIH and HD group.

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    <p>The normalized Mean Fluorescence Intensity (MFI) from microarray data was analyzed using PCA and PLS-DA models. (A) PCA shows that AIH (red circle) and HD (green triangle) have distinctive profiles with little overlap between the two groups of samples; the exception was the sample HD0088 (blue arrow) so this sample was omitted from the subsequently explorative analysis. (B) Plot of R<sup>2</sup>Y (explained variation) and Q<sup>2</sup>Y (predicted variation) shows how the considered parameters change as a function of increasing model complexity. Three components were calculated through cross-validation, R<sup>2</sup>Y and Q<sup>2</sup>Y were 74.28% and 62.18% and resulted significant in order to explain the relationship between the descriptor matrix and the class response. (C) PLS-DA 3D score plot reveals that each sample is found close to the samples belonging to the same subgroup. Samples are coloured according to the disease status (AIH- red circle, HD green triangle—the axes of the plot indicate PLS-DA component 1–3). (D) Density plot of the Q<sup>2</sup>Y values in the analysis of 1000 permutation tests, solid red line shows the real Q<sup>2</sup>Y value. Such reference distribution can be seen as sign of the degrees of overfit and overprediction of the model. The permutation test showed that the real PLS-DA model was not over-fitted and not over-predicted.</p

    Differences in Western Blotting and human miRNA analyses between immunoprecipitated HBsAg particles and control immunoprecipitations.

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    <p>Left-most: Western blotting analysis of protein lysates from HBsAg positive immunoprecipitates (HBs-IP+) and control HBsAg negative immunoprecipitates (ctrl-IPs) for detection of Ago2 protein. IP+ lanes contain pooled protein lysates from samples # 1–13 and single lysates from samples # 1 and 9 respectively. Ctrl-IPs lanes contain protein lysates from immunoprecipitates obtained from HBsAg positive sera with mouse monoclonal anti-human c-myc antibody (unrelated-IP+) and HBsAg negative sera using anti-HBs monoclonal antibody (HBs-IP−). HEK is the protein lysate from HEK cells used as positive control for Ago2 protein. The figure is representative of 3 independent experiments. Right-most: HCL is unsupervised hierarchical cluster analysis of detected miRNAs (DC<sub>T</sub> values) in both HBs-immunoprecipitated fractions from HBsAg positive immunoprecipitates (HBs-IP+) and control HBsAg negative immunoprecipitates (ctrl-IPs). GDM is supervised gene distance matrix correlating DCt values of HBs-IP+ vs ctrl-IP samples.</p

    Demographic and Virologic Characteristics of Individuals and Sera.

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    <p>Abbreviations: VP = viral particles, virion; SVP = subviral HBsAg particles; IU = International Units; ng = nanograms; ALT = serum alanine amino trasferase.</p><p>Quantitative values for VP and SVP were obtained as previously reported <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031952#pone.0031952-Gerlich1" target="_blank">[14]</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031952#pone.0031952-Desire1" target="_blank">[15]</a>: 1 IU of HBsAg corresponds to 1,1E+06 IU HBV DNA and1 ng of HBsAg corresponds to 2,08E+08 SVP or 5,0E+07 VP.</p><p>HBV infection and disease phases were characterized as previuosly reported <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031952#pone.0031952-Brunetto1" target="_blank">[8]</a>: IC = Inactive HBsAg Carriers with serum HBV-DNA persistently below 2000 IU and without liver disease; AC1 = Active HBsAg Carriers with serum HBV-DNA fluctuating below 20.000 IU with normal liver histology; AC2 = Active HBsAg carriers with serum HBV-DNA fluctuating above 20.000 IU with chronic active hepatitis at histology, patients with chronic hepatitis B (CHB).</p

    HBs-immunoprecipitation led to a significant change of detection of some human miRNAs in examined sera.

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    <p>Heatmap of differentially detected miRNAs in whole HBsAg sera (S+) and HBsAg positive flowthroughs after immunoprecipitation (HBs-F+) was obtained by Mann-Whitney test (p<0.05) followed by hierarchical clustering (-DC<sub>T</sub> are represented). Venn diagram: the 157 differentially abundant serum miRNAs between whole HBsAg positive sera (S+) and HBsAg positive flowthroughs (HBs-F+) were compared to miRNAs of clusters 1-to-5 in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031952#pone-0031952-g003" target="_blank">Figure 3b</a> (right panel).</p

    Overview of sensitivity and specificity in a validation step.

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    <p><sup><b>a</b></sup> Sensitivity is defined as the true positive rate in %.</p><p><sup><b>b</b></sup> Specificity is defined as the true negative rate in Healthy Donor (HD)subject in %.</p><p><sup><b>c</b></sup> Specificity is defined as the true negative rate in Viral Hepatitis (VH)patients in %.</p><p>Overview of sensitivity and specificity in a validation step.</p
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