Topological Susceptibility under Gradient Flow

We study the impact of the Gradient Flow on the topology in various models of lattice field theory. The topological susceptibility $\chi_{\rm t}$ is measured directly, and by the slab method, which is based on the topological content of sub-volumes ("slabs") and estimates $\chi_{\rm t}$ even when the system remains trapped in a fixed topological sector. The results obtained by both methods are essentially consistent, but the impact of the Gradient Flow on the characteristic quantity of the slab method seems to be different in 2-flavour QCD and in the 2d O(3) model. In the latter model, we further address the question whether or not the Gradient Flow leads to a finite continuum limit of the topological susceptibility (rescaled by the correlation length squared, $\xi^{2}$). This ongoing study is based on direct measurements of $\chi_{\rm t}$ in $L \times L$ lattices, at $L/\xi \simeq 6$.Comment: 8 pages, LaTex, 5 figures, talk presented at the 35th International Symposium on Lattice Field Theory, June 18-24, 2017, Granada, Spai

Additional file 1 of Deconvolution at the single-cell level reveals ovarian cell-type-specific transcriptomic changes in PCOS

Supplementary Material

GSEA of the THP1r2<i>Mtb</i>-induced signature using transcriptome data from human patients with acute infections.

1<p><i>Strep</i>: <i>Streptococcus pneumonia</i> infection, <i>Staph</i>: <i>Staphylococcus aureus</i> infection.</p>2,3<p>The same as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0038367#pone-0038367-t001" target="_blank">Table 1</a>.</p

Experimental design for detecting host transcriptional responses to different <i>Mtb</i> W-Beijing strains.

<p>Genetic diversity of W-Beijing family strains, as revealed by SNPs-based genotyping (see our recent work <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0038367#pone.0038367-Mestre1" target="_blank">[16]</a> for details). In brief, 48 SNPs were characterized by sequencing 22 genes (being involved in DNA repair, replication, and recombination) in 58 W-Beijing isolates plus one non-W-Beijing isolate (Myc2). Each node represents one genotype (the same SNPs profile), with the node area proportional to the population size (the number of W-Beijing isolates in it was indicated on the left). Strains from the corresponding node used for the THP-1 infection in this study (e.g., R1.4 from Bmyc10) were indicated on the right. Lab strain H37Rv, which was also recruited for the THP-1 infection, was not shown here.</p

GSEA of the THP1r2<i>Mtb</i>-induced signature using transcriptome data from human tuberculosis patients.

1<p>Traning set: all the donors, which were defined as PTB, LTB or healthy, were recruited from London, UK. Test set: all the donors were from London UK. Validation set: all the donors were from Cape Town, South Africa. Test set_seperated: purified neutrophils, monocytes, CD4⁺ T cells, and CD8⁺ T cells from both PTB and healthy controls. Longitudinal study: PTB patients before drug treatment, 2 months after drug treatment, and 12 months after drug treatment.</p>2<p>Group-group contrasted and ranked by LIMMA-based method.</p>3<p>(+) NES for positive correlation, (−) NES for negative correlation.</p>4<p>Significance of correlation, an FDR of 0.05 or lower was accepted as statistically significant for NES (“Positive” or “Negative”), otherwise “Null”. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0038367#pone.0038367.s007" target="_blank">Figures S7</a>,S8,S9 for plot graph of each group comparison. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0038367#pone.0038367.s010" target="_blank">Figure S10</a> for CPP-SOM graph of expression data of each donor.</p

Transcriptome classification of THP-1 cells to W-Beijing strains as well as the lab strain H37Rv.

<p>(<b>A</b>) Sample classification of THP-1 transcriptome responses to <i>Mtb</i> W-Beijing and H37Rv strains.W-Beijing strains from the same node (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0038367#pone-0038367-g001" target="_blank">Figure 1</a>) were highlighted by the same color. For example, two CHN50 strains (CHN50.1 and CHN50.2) from node Bmyc26 were colored in black. (<b>B</b>) Component plane presentation integrated self-organizing map (CPP-SOM) of host transcriptomic responses to 11 different W-Beijing family strains as well as duplicated H37Rv (columns) at 3 time points (rows). Each presentation illustrates a sample- and time-specific transcriptome map, in which all the up-regulated (represented by neurons in red), down-regulated (represented by neurons in blue) and moderately regulated (represented by neurons in yellow and green) genes were well delineated. Linking these presentations allows visual-easy comparisons of transcriptome changes across time points and strains.</p

GSEA of the THP1r2<i>Mtb</i>-induced signature using transcriptomes from patients with other inflammatory or pathological conditions.

1<p><i>Staph</i>: <i>Staphylococcus aureus</i> infection, Liver-transplant: liver-transplant undergoing immunosuppressive therapy, Melanoma: metastatic melanoma, SLE: systemic lupus erythematosus, JIA: systemic juvenile idiopathic arthritis.</p>2,3<p>The same as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0038367#pone-0038367-t001" target="_blank">Table 1</a>.</p

Peripheral arterial occlusive disease: Global gene expression analyses suggest a major role for immune and inflammatory responses-2

a Venn diagram. B, C. Heatmap representation of commonly up-regulated genes (B) and commonly down-regulated genes (C) in overlapping genes, respectively. Samples are displayed in columns and genes in rows. Gene expression is represented as a color, normalized across each row, with brighter red for higher values and brighter green for lower values. Gene symbols are listed to the right. N (Normal control group), Int (intermediate lesions group), Ad (advanced lesions group).<p><b>Copyright information:</b></p><p>Taken from "Peripheral arterial occlusive disease: Global gene expression analyses suggest a major role for immune and inflammatory responses"</p><p>http://www.biomedcentral.com/1471-2164/9/369</p><p>BMC Genomics 2008;9():369-369.</p><p>Published online 1 Aug 2008</p><p>PMCID:PMC2529314.</p><p></p

A common host transcriptome response signature and its biological characteristics.

<p>(<b>A</b>) Illustration of expression patterns of differentially expressed genes (THP1r2<i>Mtb</i>) between 4 h to 18 h after <i>Mtb</i> infection. Those genes induced are most prominent, thus representing a common host transcriptome response signature spectrum. Genes whose promoter regions (2,000 bp upstream to 200 bp downstream of transcription start site) harbouring the putative TFBSs obtained from Expander <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0038367#pone.0038367-Shamir1" target="_blank">[53]</a> were indicated by bars in blue. (<b>B</b>, <b>C</b>, and <b>D</b>) Significant functional and regulatory features in the THP1r2<i>Mtb</i>-induced signature, including GO for functional enrichments, KEGG for pathway enrichments and positional weighted matrix (PWM) for regulatory enrichments. Also listed underneath in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0038367#pone-0038367-g003" target="_blank">Figure 3C</a> are genes involved in the cytokine-cytokine receptor interaction, wherein those independently validated by qRT-PCR were highlighted in bold (see also <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0038367#pone.0038367.s005" target="_blank">Figure S5</a>).</p

Transcriptional importance of STATs, IRF-1, and IRF-7 as supported by cross-signature and cross-module comparisons.

<p>(<b>A</b>) qRT-PCR validation of <i>IFNB1</i> induction. Data were from samples as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0038367#pone-0038367-g004" target="_blank">Figure 4</a>. ** for P-value<0.01. (<b>B</b>) Gene overlap of the THP1r2<i>Mtb</i>-induced signature and an active pulmonary TB (PTB) signature <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0038367#pone.0038367-Berry1" target="_blank">[13]</a>. (<b>C</b>) Regulatory/TFBS enrichment analysis in promoter regions of the active PTB signature in the form of PWM. (<b>D</b>) Gene overlap analysis of predefined modules and the THP1r2<i>Mtb</i>-induced signature. Only those modules with more than 10% of genes (represented by the proportion of black area in the pie) presented in the THP1r2<i>Mtb</i>-induced signature were displayed. Functional interpretations of modules through literature profiling <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0038367#pone.0038367-Chaussabel1" target="_blank">[15]</a> were indicated at lower panel. (<b>E</b>) Regulatory/TFBS enrichment analysis of module M3.1.</p