Functional categorization.

<p><b>Bold</b> = highest gene expression, Standard = medium gene expression, <i>Italic</i> = lowest gene expression among the three monocyte subsets</p><p>The data indicate relative Log2 transformed gene expression levels.</p

Genes of interest investigated in the three monocyte subsets.

<p>Protein function adapted from <a href="http://GeneCards.org" target="_blank">GeneCards.org</a></p><p>Genes of interest investigated in the three monocyte subsets.</p

Multimodal expression in the three monocyte subsets.

<p><b>Bold</b> = Multimodal expression <i>P</i> <0.05, <i>Italic</i> = Unimodal expression</p><p>Multimodal expression in the three monocyte subsets.</p

Expression level of genes deviating in identified subgroups.

<p>Subgroups of cells were identified based on the PCA of single-cell PCR gene expression analysis data. One subgroup among the classical monocytes, intermediate monocytes and non-classical monocytes, and co-expression of genes within the subgroups were assessed using a student T test (<i>P <</i> 0.05). A) Bar graph demonstrating the differentially expressed genes by the subgroup within the classical monocyte subset identified on the PCA score plot. The subgroup is marked by filled red circles in the PCA score plot. B) Bar graph demonstrating the differentially expressed genes by the subgroup within the intermediate monocyte subset identified on the PCA score plot. The subgroup is marked by filled green triangles in the PCA score plot. C) Bar graph demonstrating the differentially expressed genes by the subgroup within the non-classical monocyte subset identified on the PCA score plot. The subgroup is marked by filled blue pluses in the PCA score plot.</p

Relative Log2 transformed gene expression levels of the three subsets and statistical significance the subsets in between.

<p>C = Classical, I = Intermediate, NC = Non-Classical</p><p>Relative Log2 transformed gene expression levels of the three subsets and statistical significance the subsets in between.</p

Single-cell gene expression analysis on human monocytes.

<p>Human monocytes were single-cell sorted according to the expression of the cell surface markers CD14 and CD16 and gene expression on single cells was assessed. A) Representative plot of flow cytometry analysis demonstrating the monocyte subset gating strategy, used to single-cell sort monocytes from the three classified monocyte subsets (<i>n =</i> 1). Classical (CD14⁺⁺CD16^-) monocytes, intermediate (CD14⁺⁺CD16⁺) monocytes and non-classical (CD14⁺⁺CD16⁺) monocytes are depicted in the upper left quadrant, upper right quadrant and lower right quadrant, respectively. B) Principal component analyses (PCA) of single-cell PCR gene expression analysis data showing genetic clustering of the three monocyte subsets. The PCA plot confirmed the classification of the three human monocyte subsets done by flow cytometry, visualized by gene families. Each dot represents a single cell. C) Heatmap of gene expression values for PCA showing hierarchical clustering of single-cell PCR gene expression data from the three human monocyte sub-populations. The analysis revealed cellular heterogeneity by distinct gene signatures. Red circles = classical monocytes (<i>n</i> = 94 cells), green triangles = intermediate monocytes (<i>n</i> = 92 cells), and blue pluses = non-classical monocytes (<i>n</i> = 80 cells).</p

Multimodal variation in expression levels across the three monocyte subsets.

<p>Violin plot demonstrating multimodal variation in gene expression levels of the 85 genes examined in the monocyte subsets. The classical monocytes, intermediate monocytes and non-classical monocytes are indicated in the figure by red, green and blue, respectively. The data depict the multimodal expression levels of the genes listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0144351#pone.0144351.t004" target="_blank">Table 4</a> calculated by using the Hartigans dip test (<i>P <</i> 0.05).</p

Supplementary_Tables – Supplemental material for Switching from originator infliximab to the biosimilar CT-P13 in 313 patients with inflammatory bowel disease

Supplemental material, Supplementary_Tables for Switching from originator infliximab to the biosimilar CT-P13 in 313 patients with inflammatory bowel disease by Viktoria Bergqvist, Mohammad Kadivar, Daniel Molin, Leif Angelison, Per Hammarlund, Marie Olin, Jörgen Torp, Olof Grip, Stefan Nilson, Erik Hertervig, Jan Lillienau and Jan Marsal in Therapeutic Advances in Gastroenterology</p

sj-docx-3-tag-10.1177_17562848231174953 – Supplemental material for Long-term outcomes of vedolizumab in inflammatory bowel disease: the Swedish prospective multicentre SVEAH extension study

Supplemental material, sj-docx-3-tag-10.1177_17562848231174953 for Long-term outcomes of vedolizumab in inflammatory bowel disease: the Swedish prospective multicentre SVEAH extension study by Isabella Visuri, Carl Eriksson, Sara Karlqvist, Byron Lykiardopoulos, Per Karlén, Olof Grip, Charlotte Söderman, Sven Almer, Erik Hertervig, Jan Marsal, Carolina Malmgren, Jenny Delin, Hans Strid, Mats Sjöberg, Daniel Bergemalm, Henrik Hjortswang and Jonas Halfvarson in Therapeutic Advances in Gastroenterology</p

sj-docx-2-tag-10.1177_17562848231174953 – Supplemental material for Long-term outcomes of vedolizumab in inflammatory bowel disease: the Swedish prospective multicentre SVEAH extension study

Supplemental material, sj-docx-2-tag-10.1177_17562848231174953 for Long-term outcomes of vedolizumab in inflammatory bowel disease: the Swedish prospective multicentre SVEAH extension study by Isabella Visuri, Carl Eriksson, Sara Karlqvist, Byron Lykiardopoulos, Per Karlén, Olof Grip, Charlotte Söderman, Sven Almer, Erik Hertervig, Jan Marsal, Carolina Malmgren, Jenny Delin, Hans Strid, Mats Sjöberg, Daniel Bergemalm, Henrik Hjortswang and Jonas Halfvarson in Therapeutic Advances in Gastroenterology</p