magnetic particles easysep human cd8 positive selection kit ii Search Results


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a , Percentages of human myeloid cells (hCD33 + ) among human hematopoietic cells (hCD45 + ) in the blood of the indicated recipient mice, engrafted as newborns by intra-hepatic injection of fetal liver CD34 + cells after X-ray preconditioning. Each symbol represents an individual mouse and the red bars indicate mean values (n=20-113; statistical analysis is shown in ). b , Composition of human white blood cells in the same mice as in a (n=20-113 mice/group; n=8 human donors; error bars indicate SEM). c , Immunohistological staining of human myeloid cells (hCD68 + ) in non-lymphoid tissues of the indicated recipient mice. The black bar represents 20 μm, and the images shown are representative of at least three mice analyzed per group. d-e , Representative flow cytometry analysis ( d ) and frequencies ( e ) of human monocyte subsets, identified by expression of CD14 and CD16 among hCD45 + <t>CD33</t> + cells in the blood of recipient mice (n=8-12 mice/group; error bars indicate SEM). Dot plots in d are gated on CD33 hi SSC lo cells to show the subset distribution among monocytic cells. f , Human monocytes in the blood of MISTRG recipients and human monocytes from a human donor were stained with the indicated antibodies. Staining with isotype control antibodies is shown in red and specific antibodies in blue.
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a , Percentages of human myeloid cells (hCD33 + ) among human hematopoietic cells (hCD45 + ) in the blood of the indicated recipient mice, engrafted as newborns by intra-hepatic injection of fetal liver CD34 + cells after X-ray preconditioning. Each symbol represents an individual mouse and the red bars indicate mean values (n=20-113; statistical analysis is shown in ). b , Composition of human white blood cells in the same mice as in a (n=20-113 mice/group; n=8 human donors; error bars indicate SEM). c , Immunohistological staining of human myeloid cells (hCD68 + ) in non-lymphoid tissues of the indicated recipient mice. The black bar represents 20 μm, and the images shown are representative of at least three mice analyzed per group. d-e , Representative flow cytometry analysis ( d ) and frequencies ( e ) of human monocyte subsets, identified by expression of CD14 and CD16 among hCD45 + <t>CD33</t> + cells in the blood of recipient mice (n=8-12 mice/group; error bars indicate SEM). Dot plots in d are gated on CD33 hi SSC lo cells to show the subset distribution among monocytic cells. f , Human monocytes in the blood of MISTRG recipients and human monocytes from a human donor were stained with the indicated antibodies. Staining with isotype control antibodies is shown in red and specific antibodies in blue.
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a , Percentages of human myeloid cells (hCD33 + ) among human hematopoietic cells (hCD45 + ) in the blood of the indicated recipient mice, engrafted as newborns by intra-hepatic injection of fetal liver CD34 + cells after X-ray preconditioning. Each symbol represents an individual mouse and the red bars indicate mean values (n=20-113; statistical analysis is shown in ). b , Composition of human white blood cells in the same mice as in a (n=20-113 mice/group; n=8 human donors; error bars indicate SEM). c , Immunohistological staining of human myeloid cells (hCD68 + ) in non-lymphoid tissues of the indicated recipient mice. The black bar represents 20 μm, and the images shown are representative of at least three mice analyzed per group. d-e , Representative flow cytometry analysis ( d ) and frequencies ( e ) of human monocyte subsets, identified by expression of CD14 and CD16 among hCD45 + <t>CD33</t> + cells in the blood of recipient mice (n=8-12 mice/group; error bars indicate SEM). Dot plots in d are gated on CD33 hi SSC lo cells to show the subset distribution among monocytic cells. f , Human monocytes in the blood of MISTRG recipients and human monocytes from a human donor were stained with the indicated antibodies. Staining with isotype control antibodies is shown in red and specific antibodies in blue.
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( a,b ) Cell clustering and identification by UMAP. ( c,d ) The heatmap and box plot of expression of SLC2A3 in identified subpopulations. ( e ) Purified <t>CD8</t> + T cells from HNSC tissue were assayed by flow cytometric analysis. ( f ) Differential analysis of mRNA and protein expression between purified CD8 + T cells and other cell types in HNSC tissues.
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The intestinal microenvironment of Crohn’s disease patients promotes an inflammatory transcriptome in blood monocytes. [A–C] Differentially expressed transcriptomic pathways in blood <t>CD14</t> + monocytes from healthy donors treated for 5 h with [A] TREM-1 agonist antibody [5 µg/mL], [B] LP-CM from three controls or [C] LP-CM from three Crohn’s disease patients. Quantification of gene expression was done with the NanoString nCounter Human Myeloid Innate Immunity V2 Panel. Pathway signature scores condense each sample’s gene expression profile into a small set of pathway scores. An experiment can then be explored through the lens of pathway signature scores instead of in the much higher-dimension lens of gene expression values. Pathway signature scores are fit using the first principal component of each gene set’s data. They are orientated such that an increasing score corresponds to mostly increasing expression [specifically, each pathway score has positive weights for at least half its genes]. Covariates plots compare pathway signature scores to covariates. Red triangles and green triangles help to show the relative increase and decrease in pathways, respectively, compared to the control condition. [D] The 38 molecules that increased by a minimum two-fold in LP-CM from the three Crohn’s disease patients compared to LP-CM from the three controls. The fold change is based on the mean of the three values per group. [E] LP-CM inflammation score for each sample. This score is the mean of the linear NPX values [see Section 2.6] of the 38 proteins shown in D as a way to get a relative quantification of the inflammation status of the individuals analysed. [F] Correlations between the LP-CM inflammation scores and the top ten increased genes in human blood CD14 + monocytes treated with the Crohn’s disease LP-CM compared to cells treated with the control LP-CM [see ]. [G] Correlations between the LP-CM inflammation scores and the frequency of cells in the same individual determined by flow cytometry [gated as in ]. [F, G] Correlations were assessed by Spearman’s test. Abbreviations: Ctr, controls; LP-CM, lamina propria conditioned media; Mfs, macrophages.
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The intestinal microenvironment of Crohn’s disease patients promotes an inflammatory transcriptome in blood monocytes. [A–C] Differentially expressed transcriptomic pathways in blood <t>CD14</t> + monocytes from healthy donors treated for 5 h with [A] TREM-1 agonist antibody [5 µg/mL], [B] LP-CM from three controls or [C] LP-CM from three Crohn’s disease patients. Quantification of gene expression was done with the NanoString nCounter Human Myeloid Innate Immunity V2 Panel. Pathway signature scores condense each sample’s gene expression profile into a small set of pathway scores. An experiment can then be explored through the lens of pathway signature scores instead of in the much higher-dimension lens of gene expression values. Pathway signature scores are fit using the first principal component of each gene set’s data. They are orientated such that an increasing score corresponds to mostly increasing expression [specifically, each pathway score has positive weights for at least half its genes]. Covariates plots compare pathway signature scores to covariates. Red triangles and green triangles help to show the relative increase and decrease in pathways, respectively, compared to the control condition. [D] The 38 molecules that increased by a minimum two-fold in LP-CM from the three Crohn’s disease patients compared to LP-CM from the three controls. The fold change is based on the mean of the three values per group. [E] LP-CM inflammation score for each sample. This score is the mean of the linear NPX values [see Section 2.6] of the 38 proteins shown in D as a way to get a relative quantification of the inflammation status of the individuals analysed. [F] Correlations between the LP-CM inflammation scores and the top ten increased genes in human blood CD14 + monocytes treated with the Crohn’s disease LP-CM compared to cells treated with the control LP-CM [see ]. [G] Correlations between the LP-CM inflammation scores and the frequency of cells in the same individual determined by flow cytometry [gated as in ]. [F, G] Correlations were assessed by Spearman’s test. Abbreviations: Ctr, controls; LP-CM, lamina propria conditioned media; Mfs, macrophages.
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The intestinal microenvironment of Crohn’s disease patients promotes an inflammatory transcriptome in blood monocytes. [A–C] Differentially expressed transcriptomic pathways in blood <t>CD14</t> + monocytes from healthy donors treated for 5 h with [A] TREM-1 agonist antibody [5 µg/mL], [B] LP-CM from three controls or [C] LP-CM from three Crohn’s disease patients. Quantification of gene expression was done with the NanoString nCounter Human Myeloid Innate Immunity V2 Panel. Pathway signature scores condense each sample’s gene expression profile into a small set of pathway scores. An experiment can then be explored through the lens of pathway signature scores instead of in the much higher-dimension lens of gene expression values. Pathway signature scores are fit using the first principal component of each gene set’s data. They are orientated such that an increasing score corresponds to mostly increasing expression [specifically, each pathway score has positive weights for at least half its genes]. Covariates plots compare pathway signature scores to covariates. Red triangles and green triangles help to show the relative increase and decrease in pathways, respectively, compared to the control condition. [D] The 38 molecules that increased by a minimum two-fold in LP-CM from the three Crohn’s disease patients compared to LP-CM from the three controls. The fold change is based on the mean of the three values per group. [E] LP-CM inflammation score for each sample. This score is the mean of the linear NPX values [see Section 2.6] of the 38 proteins shown in D as a way to get a relative quantification of the inflammation status of the individuals analysed. [F] Correlations between the LP-CM inflammation scores and the top ten increased genes in human blood CD14 + monocytes treated with the Crohn’s disease LP-CM compared to cells treated with the control LP-CM [see ]. [G] Correlations between the LP-CM inflammation scores and the frequency of cells in the same individual determined by flow cytometry [gated as in ]. [F, G] Correlations were assessed by Spearman’s test. Abbreviations: Ctr, controls; LP-CM, lamina propria conditioned media; Mfs, macrophages.
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The intestinal microenvironment of Crohn’s disease patients promotes an inflammatory transcriptome in blood monocytes. [A–C] Differentially expressed transcriptomic pathways in blood <t>CD14</t> + monocytes from healthy donors treated for 5 h with [A] TREM-1 agonist antibody [5 µg/mL], [B] LP-CM from three controls or [C] LP-CM from three Crohn’s disease patients. Quantification of gene expression was done with the NanoString nCounter Human Myeloid Innate Immunity V2 Panel. Pathway signature scores condense each sample’s gene expression profile into a small set of pathway scores. An experiment can then be explored through the lens of pathway signature scores instead of in the much higher-dimension lens of gene expression values. Pathway signature scores are fit using the first principal component of each gene set’s data. They are orientated such that an increasing score corresponds to mostly increasing expression [specifically, each pathway score has positive weights for at least half its genes]. Covariates plots compare pathway signature scores to covariates. Red triangles and green triangles help to show the relative increase and decrease in pathways, respectively, compared to the control condition. [D] The 38 molecules that increased by a minimum two-fold in LP-CM from the three Crohn’s disease patients compared to LP-CM from the three controls. The fold change is based on the mean of the three values per group. [E] LP-CM inflammation score for each sample. This score is the mean of the linear NPX values [see Section 2.6] of the 38 proteins shown in D as a way to get a relative quantification of the inflammation status of the individuals analysed. [F] Correlations between the LP-CM inflammation scores and the top ten increased genes in human blood CD14 + monocytes treated with the Crohn’s disease LP-CM compared to cells treated with the control LP-CM [see ]. [G] Correlations between the LP-CM inflammation scores and the frequency of cells in the same individual determined by flow cytometry [gated as in ]. [F, G] Correlations were assessed by Spearman’s test. Abbreviations: Ctr, controls; LP-CM, lamina propria conditioned media; Mfs, macrophages.
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The intestinal microenvironment of Crohn’s disease patients promotes an inflammatory transcriptome in blood monocytes. [A–C] Differentially expressed transcriptomic pathways in blood <t>CD14</t> + monocytes from healthy donors treated for 5 h with [A] TREM-1 agonist antibody [5 µg/mL], [B] LP-CM from three controls or [C] LP-CM from three Crohn’s disease patients. Quantification of gene expression was done with the NanoString nCounter Human Myeloid Innate Immunity V2 Panel. Pathway signature scores condense each sample’s gene expression profile into a small set of pathway scores. An experiment can then be explored through the lens of pathway signature scores instead of in the much higher-dimension lens of gene expression values. Pathway signature scores are fit using the first principal component of each gene set’s data. They are orientated such that an increasing score corresponds to mostly increasing expression [specifically, each pathway score has positive weights for at least half its genes]. Covariates plots compare pathway signature scores to covariates. Red triangles and green triangles help to show the relative increase and decrease in pathways, respectively, compared to the control condition. [D] The 38 molecules that increased by a minimum two-fold in LP-CM from the three Crohn’s disease patients compared to LP-CM from the three controls. The fold change is based on the mean of the three values per group. [E] LP-CM inflammation score for each sample. This score is the mean of the linear NPX values [see Section 2.6] of the 38 proteins shown in D as a way to get a relative quantification of the inflammation status of the individuals analysed. [F] Correlations between the LP-CM inflammation scores and the top ten increased genes in human blood CD14 + monocytes treated with the Crohn’s disease LP-CM compared to cells treated with the control LP-CM [see ]. [G] Correlations between the LP-CM inflammation scores and the frequency of cells in the same individual determined by flow cytometry [gated as in ]. [F, G] Correlations were assessed by Spearman’s test. Abbreviations: Ctr, controls; LP-CM, lamina propria conditioned media; Mfs, macrophages.
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The intestinal microenvironment of Crohn’s disease patients promotes an inflammatory transcriptome in blood monocytes. [A–C] Differentially expressed transcriptomic pathways in blood <t>CD14</t> + monocytes from healthy donors treated for 5 h with [A] TREM-1 agonist antibody [5 µg/mL], [B] LP-CM from three controls or [C] LP-CM from three Crohn’s disease patients. Quantification of gene expression was done with the NanoString nCounter Human Myeloid Innate Immunity V2 Panel. Pathway signature scores condense each sample’s gene expression profile into a small set of pathway scores. An experiment can then be explored through the lens of pathway signature scores instead of in the much higher-dimension lens of gene expression values. Pathway signature scores are fit using the first principal component of each gene set’s data. They are orientated such that an increasing score corresponds to mostly increasing expression [specifically, each pathway score has positive weights for at least half its genes]. Covariates plots compare pathway signature scores to covariates. Red triangles and green triangles help to show the relative increase and decrease in pathways, respectively, compared to the control condition. [D] The 38 molecules that increased by a minimum two-fold in LP-CM from the three Crohn’s disease patients compared to LP-CM from the three controls. The fold change is based on the mean of the three values per group. [E] LP-CM inflammation score for each sample. This score is the mean of the linear NPX values [see Section 2.6] of the 38 proteins shown in D as a way to get a relative quantification of the inflammation status of the individuals analysed. [F] Correlations between the LP-CM inflammation scores and the top ten increased genes in human blood CD14 + monocytes treated with the Crohn’s disease LP-CM compared to cells treated with the control LP-CM [see ]. [G] Correlations between the LP-CM inflammation scores and the frequency of cells in the same individual determined by flow cytometry [gated as in ]. [F, G] Correlations were assessed by Spearman’s test. Abbreviations: Ctr, controls; LP-CM, lamina propria conditioned media; Mfs, macrophages.
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The intestinal microenvironment of Crohn’s disease patients promotes an inflammatory transcriptome in blood monocytes. [A–C] Differentially expressed transcriptomic pathways in blood <t>CD14</t> + monocytes from healthy donors treated for 5 h with [A] TREM-1 agonist antibody [5 µg/mL], [B] LP-CM from three controls or [C] LP-CM from three Crohn’s disease patients. Quantification of gene expression was done with the NanoString nCounter Human Myeloid Innate Immunity V2 Panel. Pathway signature scores condense each sample’s gene expression profile into a small set of pathway scores. An experiment can then be explored through the lens of pathway signature scores instead of in the much higher-dimension lens of gene expression values. Pathway signature scores are fit using the first principal component of each gene set’s data. They are orientated such that an increasing score corresponds to mostly increasing expression [specifically, each pathway score has positive weights for at least half its genes]. Covariates plots compare pathway signature scores to covariates. Red triangles and green triangles help to show the relative increase and decrease in pathways, respectively, compared to the control condition. [D] The 38 molecules that increased by a minimum two-fold in LP-CM from the three Crohn’s disease patients compared to LP-CM from the three controls. The fold change is based on the mean of the three values per group. [E] LP-CM inflammation score for each sample. This score is the mean of the linear NPX values [see Section 2.6] of the 38 proteins shown in D as a way to get a relative quantification of the inflammation status of the individuals analysed. [F] Correlations between the LP-CM inflammation scores and the top ten increased genes in human blood CD14 + monocytes treated with the Crohn’s disease LP-CM compared to cells treated with the control LP-CM [see ]. [G] Correlations between the LP-CM inflammation scores and the frequency of cells in the same individual determined by flow cytometry [gated as in ]. [F, G] Correlations were assessed by Spearman’s test. Abbreviations: Ctr, controls; LP-CM, lamina propria conditioned media; Mfs, macrophages.
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The intestinal microenvironment of Crohn’s disease patients promotes an inflammatory transcriptome in blood monocytes. [A–C] Differentially expressed transcriptomic pathways in blood <t>CD14</t> + monocytes from healthy donors treated for 5 h with [A] TREM-1 agonist antibody [5 µg/mL], [B] LP-CM from three controls or [C] LP-CM from three Crohn’s disease patients. Quantification of gene expression was done with the NanoString nCounter Human Myeloid Innate Immunity V2 Panel. Pathway signature scores condense each sample’s gene expression profile into a small set of pathway scores. An experiment can then be explored through the lens of pathway signature scores instead of in the much higher-dimension lens of gene expression values. Pathway signature scores are fit using the first principal component of each gene set’s data. They are orientated such that an increasing score corresponds to mostly increasing expression [specifically, each pathway score has positive weights for at least half its genes]. Covariates plots compare pathway signature scores to covariates. Red triangles and green triangles help to show the relative increase and decrease in pathways, respectively, compared to the control condition. [D] The 38 molecules that increased by a minimum two-fold in LP-CM from the three Crohn’s disease patients compared to LP-CM from the three controls. The fold change is based on the mean of the three values per group. [E] LP-CM inflammation score for each sample. This score is the mean of the linear NPX values [see Section 2.6] of the 38 proteins shown in D as a way to get a relative quantification of the inflammation status of the individuals analysed. [F] Correlations between the LP-CM inflammation scores and the top ten increased genes in human blood CD14 + monocytes treated with the Crohn’s disease LP-CM compared to cells treated with the control LP-CM [see ]. [G] Correlations between the LP-CM inflammation scores and the frequency of cells in the same individual determined by flow cytometry [gated as in ]. [F, G] Correlations were assessed by Spearman’s test. Abbreviations: Ctr, controls; LP-CM, lamina propria conditioned media; Mfs, macrophages.
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Image Search Results


a , Percentages of human myeloid cells (hCD33 + ) among human hematopoietic cells (hCD45 + ) in the blood of the indicated recipient mice, engrafted as newborns by intra-hepatic injection of fetal liver CD34 + cells after X-ray preconditioning. Each symbol represents an individual mouse and the red bars indicate mean values (n=20-113; statistical analysis is shown in ). b , Composition of human white blood cells in the same mice as in a (n=20-113 mice/group; n=8 human donors; error bars indicate SEM). c , Immunohistological staining of human myeloid cells (hCD68 + ) in non-lymphoid tissues of the indicated recipient mice. The black bar represents 20 μm, and the images shown are representative of at least three mice analyzed per group. d-e , Representative flow cytometry analysis ( d ) and frequencies ( e ) of human monocyte subsets, identified by expression of CD14 and CD16 among hCD45 + CD33 + cells in the blood of recipient mice (n=8-12 mice/group; error bars indicate SEM). Dot plots in d are gated on CD33 hi SSC lo cells to show the subset distribution among monocytic cells. f , Human monocytes in the blood of MISTRG recipients and human monocytes from a human donor were stained with the indicated antibodies. Staining with isotype control antibodies is shown in red and specific antibodies in blue.

Journal: Nature biotechnology

Article Title: Development and function of human innate immune cells in a humanized mouse model

doi: 10.1038/nbt.2858

Figure Lengend Snippet: a , Percentages of human myeloid cells (hCD33 + ) among human hematopoietic cells (hCD45 + ) in the blood of the indicated recipient mice, engrafted as newborns by intra-hepatic injection of fetal liver CD34 + cells after X-ray preconditioning. Each symbol represents an individual mouse and the red bars indicate mean values (n=20-113; statistical analysis is shown in ). b , Composition of human white blood cells in the same mice as in a (n=20-113 mice/group; n=8 human donors; error bars indicate SEM). c , Immunohistological staining of human myeloid cells (hCD68 + ) in non-lymphoid tissues of the indicated recipient mice. The black bar represents 20 μm, and the images shown are representative of at least three mice analyzed per group. d-e , Representative flow cytometry analysis ( d ) and frequencies ( e ) of human monocyte subsets, identified by expression of CD14 and CD16 among hCD45 + CD33 + cells in the blood of recipient mice (n=8-12 mice/group; error bars indicate SEM). Dot plots in d are gated on CD33 hi SSC lo cells to show the subset distribution among monocytic cells. f , Human monocytes in the blood of MISTRG recipients and human monocytes from a human donor were stained with the indicated antibodies. Staining with isotype control antibodies is shown in red and specific antibodies in blue.

Article Snippet: Human CD33 + cells were enriched by magnetic isolation (EasySep CD33 selection kit, StemCell Technologies).

Techniques: Injection, Staining, Flow Cytometry, Expressing, Control

( a,b ) Cell clustering and identification by UMAP. ( c,d ) The heatmap and box plot of expression of SLC2A3 in identified subpopulations. ( e ) Purified CD8 + T cells from HNSC tissue were assayed by flow cytometric analysis. ( f ) Differential analysis of mRNA and protein expression between purified CD8 + T cells and other cell types in HNSC tissues.

Journal: Scientific Reports

Article Title: SLC2A3 promotes head and neck squamous cancer developing through negatively regulating CD8 + T cell in tumor microenvironment

doi: 10.1038/s41598-024-79417-9

Figure Lengend Snippet: ( a,b ) Cell clustering and identification by UMAP. ( c,d ) The heatmap and box plot of expression of SLC2A3 in identified subpopulations. ( e ) Purified CD8 + T cells from HNSC tissue were assayed by flow cytometric analysis. ( f ) Differential analysis of mRNA and protein expression between purified CD8 + T cells and other cell types in HNSC tissues.

Article Snippet: CD8 + T-cells were negatively isolated from PBMCs or clinical HNSC tumor tissues by magnetic separation using the EasySep Human CD8 + T-Cell Enrichment Kit (Stemcell Technologies, USA).

Techniques: Expressing, Purification

( a ) CD8 + T cells purified and activated from PBMCs were identified by flow cytometry(single/live/CD8 + /PD-1 - /Lag-3 - /Tim-3 − /Granzyme b + ). ( b ) Activated CD8 + T cells knockdown on SLC2A3 were assay by PCR and Western blot. ( c ) Knockdown of SLC2A3 and negative control of CD8 + T cell in CCK8 proliferation assessment. ( d ) The proliferation curve of CCK8 in a co-culture system. Two pairs were compared at the same time point. (TU686 vs TU686+ CD8 + T cell(si-NC), TU686+ CD8 + T cell(si-NC) vs TU686+ CD8 + T cell(si-SLC2A3)). ( e ) GSEA and Western blot were used to analyze ferroptosis in CD8 + T cells.

Journal: Scientific Reports

Article Title: SLC2A3 promotes head and neck squamous cancer developing through negatively regulating CD8 + T cell in tumor microenvironment

doi: 10.1038/s41598-024-79417-9

Figure Lengend Snippet: ( a ) CD8 + T cells purified and activated from PBMCs were identified by flow cytometry(single/live/CD8 + /PD-1 - /Lag-3 - /Tim-3 − /Granzyme b + ). ( b ) Activated CD8 + T cells knockdown on SLC2A3 were assay by PCR and Western blot. ( c ) Knockdown of SLC2A3 and negative control of CD8 + T cell in CCK8 proliferation assessment. ( d ) The proliferation curve of CCK8 in a co-culture system. Two pairs were compared at the same time point. (TU686 vs TU686+ CD8 + T cell(si-NC), TU686+ CD8 + T cell(si-NC) vs TU686+ CD8 + T cell(si-SLC2A3)). ( e ) GSEA and Western blot were used to analyze ferroptosis in CD8 + T cells.

Article Snippet: CD8 + T-cells were negatively isolated from PBMCs or clinical HNSC tumor tissues by magnetic separation using the EasySep Human CD8 + T-Cell Enrichment Kit (Stemcell Technologies, USA).

Techniques: Purification, Flow Cytometry, Knockdown, Western Blot, Negative Control, Co-Culture Assay

The intestinal microenvironment of Crohn’s disease patients promotes an inflammatory transcriptome in blood monocytes. [A–C] Differentially expressed transcriptomic pathways in blood CD14 + monocytes from healthy donors treated for 5 h with [A] TREM-1 agonist antibody [5 µg/mL], [B] LP-CM from three controls or [C] LP-CM from three Crohn’s disease patients. Quantification of gene expression was done with the NanoString nCounter Human Myeloid Innate Immunity V2 Panel. Pathway signature scores condense each sample’s gene expression profile into a small set of pathway scores. An experiment can then be explored through the lens of pathway signature scores instead of in the much higher-dimension lens of gene expression values. Pathway signature scores are fit using the first principal component of each gene set’s data. They are orientated such that an increasing score corresponds to mostly increasing expression [specifically, each pathway score has positive weights for at least half its genes]. Covariates plots compare pathway signature scores to covariates. Red triangles and green triangles help to show the relative increase and decrease in pathways, respectively, compared to the control condition. [D] The 38 molecules that increased by a minimum two-fold in LP-CM from the three Crohn’s disease patients compared to LP-CM from the three controls. The fold change is based on the mean of the three values per group. [E] LP-CM inflammation score for each sample. This score is the mean of the linear NPX values [see Section 2.6] of the 38 proteins shown in D as a way to get a relative quantification of the inflammation status of the individuals analysed. [F] Correlations between the LP-CM inflammation scores and the top ten increased genes in human blood CD14 + monocytes treated with the Crohn’s disease LP-CM compared to cells treated with the control LP-CM [see ]. [G] Correlations between the LP-CM inflammation scores and the frequency of cells in the same individual determined by flow cytometry [gated as in ]. [F, G] Correlations were assessed by Spearman’s test. Abbreviations: Ctr, controls; LP-CM, lamina propria conditioned media; Mfs, macrophages.

Journal: Journal of Crohn's & Colitis

Article Title: TREM-1 + Macrophages Define a Pathogenic Cell Subset in the Intestine of Crohn’s Disease Patients

doi: 10.1093/ecco-jcc/jjab022

Figure Lengend Snippet: The intestinal microenvironment of Crohn’s disease patients promotes an inflammatory transcriptome in blood monocytes. [A–C] Differentially expressed transcriptomic pathways in blood CD14 + monocytes from healthy donors treated for 5 h with [A] TREM-1 agonist antibody [5 µg/mL], [B] LP-CM from three controls or [C] LP-CM from three Crohn’s disease patients. Quantification of gene expression was done with the NanoString nCounter Human Myeloid Innate Immunity V2 Panel. Pathway signature scores condense each sample’s gene expression profile into a small set of pathway scores. An experiment can then be explored through the lens of pathway signature scores instead of in the much higher-dimension lens of gene expression values. Pathway signature scores are fit using the first principal component of each gene set’s data. They are orientated such that an increasing score corresponds to mostly increasing expression [specifically, each pathway score has positive weights for at least half its genes]. Covariates plots compare pathway signature scores to covariates. Red triangles and green triangles help to show the relative increase and decrease in pathways, respectively, compared to the control condition. [D] The 38 molecules that increased by a minimum two-fold in LP-CM from the three Crohn’s disease patients compared to LP-CM from the three controls. The fold change is based on the mean of the three values per group. [E] LP-CM inflammation score for each sample. This score is the mean of the linear NPX values [see Section 2.6] of the 38 proteins shown in D as a way to get a relative quantification of the inflammation status of the individuals analysed. [F] Correlations between the LP-CM inflammation scores and the top ten increased genes in human blood CD14 + monocytes treated with the Crohn’s disease LP-CM compared to cells treated with the control LP-CM [see ]. [G] Correlations between the LP-CM inflammation scores and the frequency of cells in the same individual determined by flow cytometry [gated as in ]. [F, G] Correlations were assessed by Spearman’s test. Abbreviations: Ctr, controls; LP-CM, lamina propria conditioned media; Mfs, macrophages.

Article Snippet: After washing in PBS and removal of erythrocytes as described above, CD14 + monocytes were isolated using CD14 + magnetic beads (EasySep Human CD14 Positive Selection Kit II [Stemcell Technologies, Canada]).

Techniques: Gene Expression, Expressing, Control, Quantitative Proteomics, Flow Cytometry

The intestinal microenvironment of Crohn’s disease patients promotes an inflammatory transcriptome in blood monocytes, which is partly reduced by TREM-1 blockade.

Journal: Journal of Crohn's & Colitis

Article Title: TREM-1 + Macrophages Define a Pathogenic Cell Subset in the Intestine of Crohn’s Disease Patients

doi: 10.1093/ecco-jcc/jjab022

Figure Lengend Snippet: The intestinal microenvironment of Crohn’s disease patients promotes an inflammatory transcriptome in blood monocytes, which is partly reduced by TREM-1 blockade.

Article Snippet: After washing in PBS and removal of erythrocytes as described above, CD14 + monocytes were isolated using CD14 + magnetic beads (EasySep Human CD14 Positive Selection Kit II [Stemcell Technologies, Canada]).

Techniques:

IL-6 induced in blood monocytes by Crohn’s disease LP-CM is partially reduced by TREM-1/TNF double blockade. Differentially expressed [A] transcriptomic pathways or [B] CCL3 , CCL4 and IL-6 expression in blood CD14 + monocytes from a healthy donor treated for 5 h with LP-CM from three Crohn’s disease patients plus TREM-1 antagonist antibody [1 µg/mL]. Quantification of gene expression was done with the NanoString nCounter Human Myeloid Innate Immunity V2 Panel. Explanation of pathway signature scores is described in the legend to . [C–E] CCL3 , CCL4 and IL-6 expression, determined by RT-PCR, in human blood CD14 + monocytes treated for 5 h with LP-CM from six additional Crohn’s disease patients plus TREM-1 antagonist antibody alone [1 µg/mL], TNF adalimumab antibody alone [1 µg/mL], or both antibodies together. These blocking experiments were done with the appropriate isotype controls, IgG1 and IgG4, as described in sheet 1. [B–E] Each colour indicates a different individual. [B–E] Data are shown as median values. The difference between paired samples was assessed by a Wilcoxon test; * p vs adalimumab alone. Abbreviations: LP-CM, lamina propria conditioned media.

Journal: Journal of Crohn's & Colitis

Article Title: TREM-1 + Macrophages Define a Pathogenic Cell Subset in the Intestine of Crohn’s Disease Patients

doi: 10.1093/ecco-jcc/jjab022

Figure Lengend Snippet: IL-6 induced in blood monocytes by Crohn’s disease LP-CM is partially reduced by TREM-1/TNF double blockade. Differentially expressed [A] transcriptomic pathways or [B] CCL3 , CCL4 and IL-6 expression in blood CD14 + monocytes from a healthy donor treated for 5 h with LP-CM from three Crohn’s disease patients plus TREM-1 antagonist antibody [1 µg/mL]. Quantification of gene expression was done with the NanoString nCounter Human Myeloid Innate Immunity V2 Panel. Explanation of pathway signature scores is described in the legend to . [C–E] CCL3 , CCL4 and IL-6 expression, determined by RT-PCR, in human blood CD14 + monocytes treated for 5 h with LP-CM from six additional Crohn’s disease patients plus TREM-1 antagonist antibody alone [1 µg/mL], TNF adalimumab antibody alone [1 µg/mL], or both antibodies together. These blocking experiments were done with the appropriate isotype controls, IgG1 and IgG4, as described in sheet 1. [B–E] Each colour indicates a different individual. [B–E] Data are shown as median values. The difference between paired samples was assessed by a Wilcoxon test; * p vs adalimumab alone. Abbreviations: LP-CM, lamina propria conditioned media.

Article Snippet: After washing in PBS and removal of erythrocytes as described above, CD14 + monocytes were isolated using CD14 + magnetic beads (EasySep Human CD14 Positive Selection Kit II [Stemcell Technologies, Canada]).

Techniques: Expressing, Gene Expression, Reverse Transcription Polymerase Chain Reaction, Blocking Assay