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( A ) The imaging mass cytometry <t>(IMC)</t> <t>data</t> collection and analysis workflow outlines the steps involved in gaining comprehensive insights into the spatial distribution of immune cells and relevant cell types within undecidualized (UnD) and decidualized (DD) EM-like lesions of WT, CNR1 k/o, and CNR2 k/o mice. ( B, C ) Representative images showing the single-cell segmentation performed following the acquisition of two regions of interest (ROI) per section (three biological samples per genotype) and segmentation quality of the data after segmentation analysis was conducted, respectively. ( D ) Non-linear dimensionality reduction after batch effect correction showed distinct expression patterns of immune cells and cell state markers between UnD and DD lesions. DD lesions from the CNR1 k/o and CNR2 k/o mice showed expression pattern that was significantly different from the DD lesions of WT mice, as well as compared to UnD lesions among different genotypes. ( E ) Uniform manifold approximation and projection (UMAP) dimensionality reduction highlighted key cell types and differences in composition between UnD and DD lesions. DD lesions exhibited increased stroma and fibroblasts, decreased epithelial cells, and heightened macrophage infiltration compared to UnD lesions.
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( A ) The imaging mass cytometry <t>(IMC)</t> <t>data</t> collection and analysis workflow outlines the steps involved in gaining comprehensive insights into the spatial distribution of immune cells and relevant cell types within undecidualized (UnD) and decidualized (DD) EM-like lesions of WT, CNR1 k/o, and CNR2 k/o mice. ( B, C ) Representative images showing the single-cell segmentation performed following the acquisition of two regions of interest (ROI) per section (three biological samples per genotype) and segmentation quality of the data after segmentation analysis was conducted, respectively. ( D ) Non-linear dimensionality reduction after batch effect correction showed distinct expression patterns of immune cells and cell state markers between UnD and DD lesions. DD lesions from the CNR1 k/o and CNR2 k/o mice showed expression pattern that was significantly different from the DD lesions of WT mice, as well as compared to UnD lesions among different genotypes. ( E ) Uniform manifold approximation and projection (UMAP) dimensionality reduction highlighted key cell types and differences in composition between UnD and DD lesions. DD lesions exhibited increased stroma and fibroblasts, decreased epithelial cells, and heightened macrophage infiltration compared to UnD lesions.
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( A ) The imaging mass cytometry <t>(IMC)</t> <t>data</t> collection and analysis workflow outlines the steps involved in gaining comprehensive insights into the spatial distribution of immune cells and relevant cell types within undecidualized (UnD) and decidualized (DD) EM-like lesions of WT, CNR1 k/o, and CNR2 k/o mice. ( B, C ) Representative images showing the single-cell segmentation performed following the acquisition of two regions of interest (ROI) per section (three biological samples per genotype) and segmentation quality of the data after segmentation analysis was conducted, respectively. ( D ) Non-linear dimensionality reduction after batch effect correction showed distinct expression patterns of immune cells and cell state markers between UnD and DD lesions. DD lesions from the CNR1 k/o and CNR2 k/o mice showed expression pattern that was significantly different from the DD lesions of WT mice, as well as compared to UnD lesions among different genotypes. ( E ) Uniform manifold approximation and projection (UMAP) dimensionality reduction highlighted key cell types and differences in composition between UnD and DD lesions. DD lesions exhibited increased stroma and fibroblasts, decreased epithelial cells, and heightened macrophage infiltration compared to UnD lesions.
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( A ) The imaging mass cytometry (IMC) data collection and analysis workflow outlines the steps involved in gaining comprehensive insights into the spatial distribution of immune cells and relevant cell types within undecidualized (UnD) and decidualized (DD) EM-like lesions of WT, CNR1 k/o, and CNR2 k/o mice. ( B, C ) Representative images showing the single-cell segmentation performed following the acquisition of two regions of interest (ROI) per section (three biological samples per genotype) and segmentation quality of the data after segmentation analysis was conducted, respectively. ( D ) Non-linear dimensionality reduction after batch effect correction showed distinct expression patterns of immune cells and cell state markers between UnD and DD lesions. DD lesions from the CNR1 k/o and CNR2 k/o mice showed expression pattern that was significantly different from the DD lesions of WT mice, as well as compared to UnD lesions among different genotypes. ( E ) Uniform manifold approximation and projection (UMAP) dimensionality reduction highlighted key cell types and differences in composition between UnD and DD lesions. DD lesions exhibited increased stroma and fibroblasts, decreased epithelial cells, and heightened macrophage infiltration compared to UnD lesions.

Journal: eLife

Article Title: Endocannabinoids and their receptors modulate endometriosis pathogenesis and immune response

doi: 10.7554/eLife.96523

Figure Lengend Snippet: ( A ) The imaging mass cytometry (IMC) data collection and analysis workflow outlines the steps involved in gaining comprehensive insights into the spatial distribution of immune cells and relevant cell types within undecidualized (UnD) and decidualized (DD) EM-like lesions of WT, CNR1 k/o, and CNR2 k/o mice. ( B, C ) Representative images showing the single-cell segmentation performed following the acquisition of two regions of interest (ROI) per section (three biological samples per genotype) and segmentation quality of the data after segmentation analysis was conducted, respectively. ( D ) Non-linear dimensionality reduction after batch effect correction showed distinct expression patterns of immune cells and cell state markers between UnD and DD lesions. DD lesions from the CNR1 k/o and CNR2 k/o mice showed expression pattern that was significantly different from the DD lesions of WT mice, as well as compared to UnD lesions among different genotypes. ( E ) Uniform manifold approximation and projection (UMAP) dimensionality reduction highlighted key cell types and differences in composition between UnD and DD lesions. DD lesions exhibited increased stroma and fibroblasts, decreased epithelial cells, and heightened macrophage infiltration compared to UnD lesions.

Article Snippet: Bulk mRNA sequencing data is provided in the supplementary files (Supplementary Data 4) and IMC data generated in this study has been deposited in Mendeley Data ( https://doi.org/10.17632/2ptns5yhzh.2 ).

Techniques: Imaging, Mass Cytometry, Expressing