Multiculturalism and integration of Japanese children into Czech nursery schools

The theoretical part has two main aims. The first one is to clarify terms related to multiculturalism using professional literature. The second very important aim is to introduce the Japanese culture, the evolution of Japanese family and the status of a child in society. Also there is the outlook on Japanese preschool education institutions. These information comes basically from the interview with the Japanese national, nevertheless some additional information comes from literature. The aim of the practical part is analysed the stay of seven Japanese children in the kindergarten in one class during approximately three years. Then it introduce integration program of Japanese children to typical Czech kindergarten which is based on practical experiences. Also the practical part describes the preschool attendance of the foreign children in one kindergarten during 10 years. The research has proved the attendance of the foreign children to other kindergarten in Prague parts Břevnov, Dejvice and Hanspaulka. As well the research presents teacher's experiences with multiculturalism and multicultural education

Main findings of the LIHC report.

<p>A) Principal Components Analysis (PCA) (based on correlation matrix) of miRNA samples. B) Volcano plot showing the miRNAs according to its logratio between cancer and control. C) Heatmap of the top 50 most deregulated miRNAs according to its FDR. D) Density plot of the Pearson Correlation Coefficients of all possible miRNA-mRNA interactions. Lines show different cutoff: p-value < 0.05, p-value < 0.01, FDR < 0.05 and FDR < 0.01. E) Correlation of miR-139-5p and CCNB1 as an example. F) Venn diagram showing the total number of sigifnicant correlations (FDR < 0.05), the total number of predicted interactions in at least one database (TargetScan or microcosm), and the intersection of both. G) Network of selected interactions. Each miRNA-mRNA interaction is negatively correlated (FDR < 10–33) and predicted at least in one database (Targetscan or MicroCosm). Circles represent miRNAs and squares mRNAs; red fill means upregulated miRNA/mRNA, while green fill means downregulated miRNA/mRNA; lines indicate the miRNA-mRNA pairs; red line means positive score and green line means negative score; arrow width is proportional to the number of appearances on the databases (TargetScan or MicroCosm). H) Pie chart showing the number of mRNAs regulated by 0, 1, 2, 3, 4, 5, and >5 miRNAs. I) Barplot showing the number of targets per miRNA and the percentage of mRNAs that are cumulatively regulated by the miRNAs. J) Circos plot of the top 45 miRNA-mRNA interactions sorted by FDR, a line means a miRNA-mRNA pair. Blue lines are the position of the miRNAs and orange lines are the position of the mRNAs.</p

Specificity of MiRNA-mRNA interactions in LIHC.

<p>Number of total miRNA targets in LIHC versus number of miRNA targets present only in LIHC but not in COAD, ESCA, READ or STAD. Size of the points is proportional to the mean miRNA expression on the LIHC samples included.</p

Summary of the main miRComb computations of the five digestive cancer data sets analysed.

<p>Summary of the main miRComb computations of the five digestive cancer data sets analysed.</p

Top 10 miRNAs sorted by number of specific targets in STAD.

<p>Target mRNAs are sorted according to its negative correlation value (top 20 are dislplayed).</p

Flow diagram showing the main steps of an analysis using the <i>miRComb</i> package.

<p>Flow diagram showing the main steps of an analysis using the <i>miRComb</i> package.</p

Percentage of false positive miRNA-mRNA predicted interactions in LIHC.

<p>Plot showing the ratios of negatively correlated predicted targets respect to all predicted targets according to the databases for each miRNA. The intensity of the grey color dot is related to the percentage of false postive miRNA-mRNA predicted interactions. In brackets, the exact percentages of false positivesfrom selected miRNAs (miR-122; miR-122*; miR-378c).</p

Venn diagram for miRComb miRNA-mRNA interactions between 5 digestive cancers.

<p>Venn diagram showing miRComb miRNA-mRNA interactions (FDR < 0.05 and predicted in at least one database) that are present in at least one cancer. 1570 miRNA-mRNA interactions appear in the 5 studied digestive cancers.</p

Clustering and Principal Components Analysis of the five digestive cancers.

<p>Computations are based on the correlation coefficients of the 106.426 miRNA-mRNA pairs that are expressed across all five cancer data sets. A) Heatmap showing the centers of the different clusters. Values represent the mean of the Pearson correlation coefficient of the miRNA-mRNA pairs that fall into the cluster. B) Principal Components Analysis (based on correlation matrix) of the Pearson correlation coefficient of the miRNA-mRNA pairs from the five digestive cancer data sets.</p

Additional file 1: of Mutational Signatures in Cancer (MuSiCa): a web application to implement mutational signatures analysis in cancer samples

Figure S1. Somatic mutational prevalence in MuSiCa web app. Figure S2. Mutational profile representation in MuSiCa web app. Figure S3. Reconstruction of mutational profile in MuSiCa web app. Figure S4. Comparison with cancer signatures in MuSiCa web app. Figure S5. Principal component analysis in MuSiCa web app. (PDF 3039 kb