Hindsinght of Habsburgs Empire by historians from the United Kingdom

V tématu své práce bych se chtěla věnovat srovnání přístupu k nazírání na dějiny Habsurské monarchie. Budu porovnávat přístup českých a anglických historiků a jejich pohledy na naše dějiny či dějiny Habsburské monarchie. Bude mezi jejich a naším pohledem rozdíl? Vzhledem k tomu, že nepředpokládám velký zápal Britů o znalost dějin habsburské monarchie, budu své téma rozšiřovat i někdy o starší a nové děj iny Českých zemí. Jelikož se s děj inami setkáváme ve vyučovacích hodinách, tak v didaktické části práce budu porovnávat přístup k vyučování dějepisu u nás a ve Velké Británi. Vyberu si určitou věkovou skupinu žáků a porovnáme učebnice používané k výuce u nich s našimi. Stejně jako jejich vzdělávací systém. Později svému zkoumání podrobím všeobecné historické publikace vydané ve Velké Británii. Otázkou výzkumu bude, zda vůbec se v dějepisných encyklopediích či odborných publikacích objevují události z našich dějin či nikoliv? A pokud ano, které události z naší minulosti to jsou? Výstupem z porovnávání publikací bude pro mne orientace v tématech, které znají či neznají britští autoři. Kam budou sahat jejich znalosti? Která témata jsou vykládána rozdílně oproti jejich pojetí u nás? To jsou mé hlavní otázky, jenž Sl kladu. Aplikovat budu nakonec svůj poznatek zcela konkrétně. Vyberu Sl jedno z problematických..

MAD classifier.

<p>Radviz plots showing how the 20 genes selected by MTGDR procedure separate the lesional (LS) and non-lesional (NL) samples apart in each study. Perfect separation between LS and NL samples can be seen in every study. S-F+: Suarez-Farinas 2012, hgu33plus2 chips; G: Gudhjonsson’2009; S-F: Suarez-Farinas’2010; R: Reischl’2007; Y: Yao’2008. Center insert shows biological relevance of these genes. Top 25 psoriasis genes in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044274#pone-0044274-t001" target="_blank">Table 1</a> are underline. 6 of these 20 genes have been identified as top methylation genes discriminating between psoriasis (LS) and healthy skin. 4/20 were identified as part of the Residual Disease Genomic Profile (RGDP) or “Molecular Scar”.</p

Meta-Analysis Derived (MAD) Transcriptome of Psoriasis Defines the “Core” Pathogenesis of Disease

<div><p>The cause of psoriasis, a common chronic inflammatory skin disease, is not fully understood. Microarray experiments have been widely used in recent years to identify genes associated with psoriasis pathology, by comparing expression levels of lesional (LS) with adjacent non-lesional (NL) skin. It is commonly observed that the differentially expressed genes (DEGs) differ greatly across experiments, due to variations introduced in the microarray experiment pipeline. Therefore, a statistically based meta-analytic approach, which combines the results of individual studies, is warranted. In this study, a meta-analysis was conducted on 5 microarray data sets, including 193 LS and NL pairs. We termed this the Meta-Analysis Derived (MAD) transcriptome. In “MAD-5” transcriptome, 677 genes were up-regulated and 443 were down-regulated in LS skin compared to NL skin. This represents a much larger set than the intersection of DEGs of these 5 studies, which consisted of 100 DEGs. We also analyzed 3 of the studies conducted on the Affymetrix hgu133plus2 chips and found a greater number of DEGs (1084 up- and 748 down-regulated). Top canonical pathways over-represented in the MAD transcriptome include <em>Atherosclerosis Signaling</em> and <em>Fatty Acid Metabolism</em>, while several “new” genes identified are involved in Cardiovascular Development and Lipid Metabolism. These findings highlight the relationship between psoriasis and systemic manifestations such as the metabolic syndrome and cardiovascular disease. Then, the Meta Threshold Gradient Descent Regularization (MTGDR) algorithm was used to select potential markers distinguishing LS and NL skin. The resulting set (20 genes) contained many genes that were part of the residual disease genomic profile (RDGP) or “molecular scar” after successful treatment, and also genes subject to differential methylation in LS tissues. To conclude, this MAD transcriptome yielded a reference list of reliable psoriasis DEGs, and represents a robust pool of candidates for further discovery of pathogenesis and treatment evaluation.</p> </div

Overview of the MAD-5 and MAD-3 transcriptomes.

<p>A. Venn diagram showing that when comparing the MAD-5 transcriptome with the intersection of DEGs identified by individual studies, the meta-analysis always identified a much larger set. B. Venn diagram showing the same comparison as A but for MAD-3 transcriptome. C. 3D Barplots showing the overlap of MAD-5 genes (blue bars) by the number of individual studies (x-axis). For example: among the MAD-5 transcriptome, 347 genes were identified by 4 studies and 100 by all 5 studies. For comparison the numbers for the set of genes that were identified by any of the individual studies (Union) is also represented (red bars). Most DEGs from the meta-analysis appeared in at least two of these studies. Integration Discovery Genes (IDD) represents the set of genes only identified by the meta-analysis. D. 3D Barplots showing the same comparison as C for MAD-3. E. Color-coded graphs showing the comparison of MADs transcriptomes and individual studies. Each row represents a gene and the color indicates whether the gene is up-regulated (red), down-regulated (green) or not differentially expressed (gray) in each (columns) and the meta-analysis. Meta: meta-analysis; S-F+: Suarez-Farinas 2012, hgu33plus2 chips; G: Gudjonsson’2009; S-F: Suarez-Farinas’2010; R: Reischl’2007; Y: Yao’2008.</p

PRIMA diagram and study schema.

<p>A. PRIMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) diagram. B. Schema describing the steps taken during the meta-analysis. N and P represent the number of samples (N) and patients (P) respectively in each study.</p

Integration-Driven Discovery (IDD) genes in the MAD-3 transcriptome.

1<p>Detected by LCM in the Dermis (no idd gene was detected in the Epidermis)</p>2<p>Gene-sets (defined by our group) with known role in psoriasis including keratinocytes’ response to IFNγ <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044274#pone.0044274-Zaba1" target="_blank">[9]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044274#pone.0044274-Nograles1" target="_blank">[18]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044274#pone.0044274-Mee1" target="_blank">[31]</a>, TNF <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044274#pone.0044274-Zaba1" target="_blank">[9]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044274#pone.0044274-Nograles1" target="_blank">[18]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044274#pone.0044274-Mee1" target="_blank">[31]</a> and IL-1 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044274#pone.0044274-Zaba1" target="_blank">[9]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044274#pone.0044274-Nograles1" target="_blank">[18]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044274#pone.0044274-Mee1" target="_blank">[31]</a>, psoriasis inflammatory <u>DC</u> transcriptome <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044274#pone.0044274-Zaba2" target="_blank">[32]</a> and <u>AD</u> transcriptome <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044274#pone.0044274-SuarezFarinas2" target="_blank">[33]</a></p>3<p>IPA Networks DD = <u>D</u>ermatological <u>D</u>isease and Conditions, CD = <u>C</u>ardiovascular System <u>D</u>evelopment and Function, IR = cell-mediated <u>I</u>mmune <u>R</u>esponse, LM = <u>L</u>ipid <u>M</u>etabolism</p

Additional file 1: of Integrative genomic deconvolution of rheumatoid arthritis GWAS loci into gene and cell type associations

Contains the cis-eQTLs with FDR <5 %. (TXT 104041 kb

Heat map representing the expression profiles of the top 50 differentially expressed genes (DEG) of normal acral versus normal non-acral skin.

<p>Gene expression patterns from normal acral and non-acral skin are strikingly different. For DEG (FDR<0.05, FCH>2), the top 25 up and 25 down-regulated genes in terms of the fold change are presented according to an unsupervised cluster analysis. Yellow-red scale: red represents low gene expression and yellow high gene expression.</p

Additional file 7: Figure S3. of Integrative genomic deconvolution of rheumatoid arthritis GWAS loci into gene and cell type associations

Genes associated with RA GWAS in T cell specific epigenomic datasets. Heatmap of genes associated with RA GWAS SNPs overlapping enhancers in the shown T cell datasets. PB, peripheral blood. Two T cell epigenomes uniquely identify genes that might be explained by unique aspects of the selection markers and (when carried out) in vitro differentiation protocols: (1) “Primary T cells from PB” was the only T cell sample to use CD3+ as a selection marker; and (2) “Primary T helper cells PMA-I stimulated” was the only sample that used Magnetic-activated cell sorting (MACS) [5]. The differences between the two “Primary T helper memory cells from PB” samples might be explained by their different differentiation protocols (number 1 uniquely used CD25M and CD45RO as selection markers) or by the differing donors of origin [5]. (PDF 7665 kb

Additional file 6: of Integrative genomic deconvolution of rheumatoid arthritis GWAS loci into gene and cell type associations

Contains the full results of the integration with enhancers described by H3K27ac or H3K4me marks. (XLSX 276 kb