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cd19 pecy7  (Alomone Labs)


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    Structured Review

    Alomone Labs cd19 pecy7
    Cd19 Pecy7, supplied by Alomone Labs, used in various techniques. Bioz Stars score: 93/100, based on 14 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Thermo Fisher cd19 antibody 1d3 pecy7
    EBF1 interacts with the regulatory elements of broadly expressed genes (A) Heatmap with the z -scores of normalized gene expression of Ebf1-bound elements in early lymphoid progenitors from the Immgen dataset (GEO: GSE100738 ). Percentage of genes in each cluster is presented. (B) Gene ontology (GO) analysis of enriched biologic processes in genes bound by EBF1 at promoters or distal regions. Gene sets are categorized based on differential expression between Wt and Ebf1 −/− FL pro-B cells [Up-/Down-regulated: padj 0.05 & |log2FC| >1, common: log2FC < log2(1.5)]. (C) Diagram displaying the relative number of generated <t>CD19</t> + cells after 11 days of in vitro incubation of KIT + cells on OP9 stroma cells compared to R26 control. The red to blue color scale represents log2FC Wt vs. Ebf1 −/− from RNA-seq. Data are based on at least 3 separate experiments, and samples (n = 3–12) with a single guide or pool of individual guides are aggregated per gene. Statistical analysis is based on Student’s t test using the R26 control guide as reference: ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001. (D) Promoter and distal elements associated to the gene sets from 2B are identified by ICE-A interaction-based annotation with H3K4me3 PLAC-seq data from FL Wt pro-B cells. Fraction of elements with a significant change (padj <0.05 & abs(log2FC) > 1) in accessibility between Wt and Ebf1 −/− FL pro-B cells are visualized in a stacked barplot, split into categories based on gene category and EBF1 occupancy. (E) The Myc locus is shown as an example of a gene that shows EBF1-addicted activation, visualized in the WashU genome Epigenome Browser. Selected EBF1-bound elements located in a distal enhancer region ∼1.6 Mb from the Myc TSS are highlighted in gray. The epigenome browser tracks include EBF1 ChIP-seq (GEO: GSE159957 ), ATAC-seq data from Wt/Ebf1 −/− FL pro-B cells and H3K4me3 PLAC-seq interactions from Wt FL pro-B cells. (F) Venn diagram displaying the overlap between common genes (defined as in B) and genes with differential expression at EBF1 degradation (|log2FC| > log2(1.5)), from ( GSE201141 ). Genes that show the strongest EBF1-addicted activation or repressive expression are listed.
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    Thermo Fisher anti-cd19-pecy7
    EBF1 interacts with the regulatory elements of broadly expressed genes (A) Heatmap with the z -scores of normalized gene expression of Ebf1-bound elements in early lymphoid progenitors from the Immgen dataset (GEO: GSE100738 ). Percentage of genes in each cluster is presented. (B) Gene ontology (GO) analysis of enriched biologic processes in genes bound by EBF1 at promoters or distal regions. Gene sets are categorized based on differential expression between Wt and Ebf1 −/− FL pro-B cells [Up-/Down-regulated: padj 0.05 & |log2FC| >1, common: log2FC < log2(1.5)]. (C) Diagram displaying the relative number of generated <t>CD19</t> + cells after 11 days of in vitro incubation of KIT + cells on OP9 stroma cells compared to R26 control. The red to blue color scale represents log2FC Wt vs. Ebf1 −/− from RNA-seq. Data are based on at least 3 separate experiments, and samples (n = 3–12) with a single guide or pool of individual guides are aggregated per gene. Statistical analysis is based on Student’s t test using the R26 control guide as reference: ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001. (D) Promoter and distal elements associated to the gene sets from 2B are identified by ICE-A interaction-based annotation with H3K4me3 PLAC-seq data from FL Wt pro-B cells. Fraction of elements with a significant change (padj <0.05 & abs(log2FC) > 1) in accessibility between Wt and Ebf1 −/− FL pro-B cells are visualized in a stacked barplot, split into categories based on gene category and EBF1 occupancy. (E) The Myc locus is shown as an example of a gene that shows EBF1-addicted activation, visualized in the WashU genome Epigenome Browser. Selected EBF1-bound elements located in a distal enhancer region ∼1.6 Mb from the Myc TSS are highlighted in gray. The epigenome browser tracks include EBF1 ChIP-seq (GEO: GSE159957 ), ATAC-seq data from Wt/Ebf1 −/− FL pro-B cells and H3K4me3 PLAC-seq interactions from Wt FL pro-B cells. (F) Venn diagram displaying the overlap between common genes (defined as in B) and genes with differential expression at EBF1 degradation (|log2FC| > log2(1.5)), from ( GSE201141 ). Genes that show the strongest EBF1-addicted activation or repressive expression are listed.
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    Cytek Biosciences cd19 1d3 buv395 bd 563557 multiple panels cd69 h1 2 f3 pecy7 invitrogen 25 0691 82 cd11b m1 70 buv737 bd 612801 ghost live
    EBF1 interacts with the regulatory elements of broadly expressed genes (A) Heatmap with the z -scores of normalized gene expression of Ebf1-bound elements in early lymphoid progenitors from the Immgen dataset (GEO: GSE100738 ). Percentage of genes in each cluster is presented. (B) Gene ontology (GO) analysis of enriched biologic processes in genes bound by EBF1 at promoters or distal regions. Gene sets are categorized based on differential expression between Wt and Ebf1 −/− FL pro-B cells [Up-/Down-regulated: padj 0.05 & |log2FC| >1, common: log2FC < log2(1.5)]. (C) Diagram displaying the relative number of generated <t>CD19</t> + cells after 11 days of in vitro incubation of KIT + cells on OP9 stroma cells compared to R26 control. The red to blue color scale represents log2FC Wt vs. Ebf1 −/− from RNA-seq. Data are based on at least 3 separate experiments, and samples (n = 3–12) with a single guide or pool of individual guides are aggregated per gene. Statistical analysis is based on Student’s t test using the R26 control guide as reference: ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001. (D) Promoter and distal elements associated to the gene sets from 2B are identified by ICE-A interaction-based annotation with H3K4me3 PLAC-seq data from FL Wt pro-B cells. Fraction of elements with a significant change (padj <0.05 & abs(log2FC) > 1) in accessibility between Wt and Ebf1 −/− FL pro-B cells are visualized in a stacked barplot, split into categories based on gene category and EBF1 occupancy. (E) The Myc locus is shown as an example of a gene that shows EBF1-addicted activation, visualized in the WashU genome Epigenome Browser. Selected EBF1-bound elements located in a distal enhancer region ∼1.6 Mb from the Myc TSS are highlighted in gray. The epigenome browser tracks include EBF1 ChIP-seq (GEO: GSE159957 ), ATAC-seq data from Wt/Ebf1 −/− FL pro-B cells and H3K4me3 PLAC-seq interactions from Wt FL pro-B cells. (F) Venn diagram displaying the overlap between common genes (defined as in B) and genes with differential expression at EBF1 degradation (|log2FC| > log2(1.5)), from ( GSE201141 ). Genes that show the strongest EBF1-addicted activation or repressive expression are listed.
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    Thermo Fisher cd19 pecy7 (hib19
    The expression of TIM-3 and CD83 in CD45 + immune cells was assessed using flow cytometry. ( A ) CD14/TIM-3 of viable CD45 + cells. ( B ) CD14/CD83 of viable CD45 + immune cells. ( C ) CD14 of viable CD45 + cells. ( D ) <t>CD4</t> of viable CD45 + cells. ( E ) CD14/CD4 of viable CD45 + cells. ( F ) CD83/TIM-3 of CD14 + CD4 + cells. Representative data for 2 patients with WHO grade 1 meningioma from 2 experiments.
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    Becton Dickinson pecy7-cd19 antibody
    The expression of TIM-3 and CD83 in CD45 + immune cells was assessed using flow cytometry. ( A ) CD14/TIM-3 of viable CD45 + cells. ( B ) CD14/CD83 of viable CD45 + immune cells. ( C ) CD14 of viable CD45 + cells. ( D ) <t>CD4</t> of viable CD45 + cells. ( E ) CD14/CD4 of viable CD45 + cells. ( F ) CD83/TIM-3 of CD14 + CD4 + cells. Representative data for 2 patients with WHO grade 1 meningioma from 2 experiments.
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    Thermo Fisher anti-cd19 pecy7
    The expression of TIM-3 and CD83 in CD45 + immune cells was assessed using flow cytometry. ( A ) CD14/TIM-3 of viable CD45 + cells. ( B ) CD14/CD83 of viable CD45 + immune cells. ( C ) CD14 of viable CD45 + cells. ( D ) <t>CD4</t> of viable CD45 + cells. ( E ) CD14/CD4 of viable CD45 + cells. ( F ) CD83/TIM-3 of CD14 + CD4 + cells. Representative data for 2 patients with WHO grade 1 meningioma from 2 experiments.
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    Image Search Results


    EBF1 interacts with the regulatory elements of broadly expressed genes (A) Heatmap with the z -scores of normalized gene expression of Ebf1-bound elements in early lymphoid progenitors from the Immgen dataset (GEO: GSE100738 ). Percentage of genes in each cluster is presented. (B) Gene ontology (GO) analysis of enriched biologic processes in genes bound by EBF1 at promoters or distal regions. Gene sets are categorized based on differential expression between Wt and Ebf1 −/− FL pro-B cells [Up-/Down-regulated: padj 0.05 & |log2FC| >1, common: log2FC < log2(1.5)]. (C) Diagram displaying the relative number of generated CD19 + cells after 11 days of in vitro incubation of KIT + cells on OP9 stroma cells compared to R26 control. The red to blue color scale represents log2FC Wt vs. Ebf1 −/− from RNA-seq. Data are based on at least 3 separate experiments, and samples (n = 3–12) with a single guide or pool of individual guides are aggregated per gene. Statistical analysis is based on Student’s t test using the R26 control guide as reference: ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001. (D) Promoter and distal elements associated to the gene sets from 2B are identified by ICE-A interaction-based annotation with H3K4me3 PLAC-seq data from FL Wt pro-B cells. Fraction of elements with a significant change (padj <0.05 & abs(log2FC) > 1) in accessibility between Wt and Ebf1 −/− FL pro-B cells are visualized in a stacked barplot, split into categories based on gene category and EBF1 occupancy. (E) The Myc locus is shown as an example of a gene that shows EBF1-addicted activation, visualized in the WashU genome Epigenome Browser. Selected EBF1-bound elements located in a distal enhancer region ∼1.6 Mb from the Myc TSS are highlighted in gray. The epigenome browser tracks include EBF1 ChIP-seq (GEO: GSE159957 ), ATAC-seq data from Wt/Ebf1 −/− FL pro-B cells and H3K4me3 PLAC-seq interactions from Wt FL pro-B cells. (F) Venn diagram displaying the overlap between common genes (defined as in B) and genes with differential expression at EBF1 degradation (|log2FC| > log2(1.5)), from ( GSE201141 ). Genes that show the strongest EBF1-addicted activation or repressive expression are listed.

    Journal: iScience

    Article Title: Chromatin interaction-based annotation of regulatory elements reveals dynamic promoter-enhancer interactions in lymphocyte development

    doi: 10.1016/j.isci.2025.112855

    Figure Lengend Snippet: EBF1 interacts with the regulatory elements of broadly expressed genes (A) Heatmap with the z -scores of normalized gene expression of Ebf1-bound elements in early lymphoid progenitors from the Immgen dataset (GEO: GSE100738 ). Percentage of genes in each cluster is presented. (B) Gene ontology (GO) analysis of enriched biologic processes in genes bound by EBF1 at promoters or distal regions. Gene sets are categorized based on differential expression between Wt and Ebf1 −/− FL pro-B cells [Up-/Down-regulated: padj 0.05 & |log2FC| >1, common: log2FC < log2(1.5)]. (C) Diagram displaying the relative number of generated CD19 + cells after 11 days of in vitro incubation of KIT + cells on OP9 stroma cells compared to R26 control. The red to blue color scale represents log2FC Wt vs. Ebf1 −/− from RNA-seq. Data are based on at least 3 separate experiments, and samples (n = 3–12) with a single guide or pool of individual guides are aggregated per gene. Statistical analysis is based on Student’s t test using the R26 control guide as reference: ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001. (D) Promoter and distal elements associated to the gene sets from 2B are identified by ICE-A interaction-based annotation with H3K4me3 PLAC-seq data from FL Wt pro-B cells. Fraction of elements with a significant change (padj <0.05 & abs(log2FC) > 1) in accessibility between Wt and Ebf1 −/− FL pro-B cells are visualized in a stacked barplot, split into categories based on gene category and EBF1 occupancy. (E) The Myc locus is shown as an example of a gene that shows EBF1-addicted activation, visualized in the WashU genome Epigenome Browser. Selected EBF1-bound elements located in a distal enhancer region ∼1.6 Mb from the Myc TSS are highlighted in gray. The epigenome browser tracks include EBF1 ChIP-seq (GEO: GSE159957 ), ATAC-seq data from Wt/Ebf1 −/− FL pro-B cells and H3K4me3 PLAC-seq interactions from Wt FL pro-B cells. (F) Venn diagram displaying the overlap between common genes (defined as in B) and genes with differential expression at EBF1 degradation (|log2FC| > log2(1.5)), from ( GSE201141 ). Genes that show the strongest EBF1-addicted activation or repressive expression are listed.

    Article Snippet: At day 11, the cells were stained with an antibody cocktail containing CD45 (30-F11, AF700, BioLegend, 103128), CD19 (1D3, PECy7, eBioscience, 15360900), Thy1.2 (53-2.1, Pacific Blue, BioLegend, 140306), Gr1 (RB6-8C5, APCCy7, BioLegend, 108424), CD11b (M1/70, APCCy7, BioLegend, 101226), NK1.1 (PK136, PE, BioLegned, 108708) and CD11c (N418, APC, BioLegned, 117310).

    Techniques: Gene Expression, Quantitative Proteomics, Generated, In Vitro, Incubation, Control, RNA Sequencing, Activation Assay, ChIP-sequencing, Expressing

    The expression of TIM-3 and CD83 in CD45 + immune cells was assessed using flow cytometry. ( A ) CD14/TIM-3 of viable CD45 + cells. ( B ) CD14/CD83 of viable CD45 + immune cells. ( C ) CD14 of viable CD45 + cells. ( D ) CD4 of viable CD45 + cells. ( E ) CD14/CD4 of viable CD45 + cells. ( F ) CD83/TIM-3 of CD14 + CD4 + cells. Representative data for 2 patients with WHO grade 1 meningioma from 2 experiments.

    Journal: Cancers

    Article Title: Flow Cytometry Analyses of Meningioma Immune Cell Composition Using a Short, Optimized Digestion Protocol

    doi: 10.3390/cancers16233942

    Figure Lengend Snippet: The expression of TIM-3 and CD83 in CD45 + immune cells was assessed using flow cytometry. ( A ) CD14/TIM-3 of viable CD45 + cells. ( B ) CD14/CD83 of viable CD45 + immune cells. ( C ) CD14 of viable CD45 + cells. ( D ) CD4 of viable CD45 + cells. ( E ) CD14/CD4 of viable CD45 + cells. ( F ) CD83/TIM-3 of CD14 + CD4 + cells. Representative data for 2 patients with WHO grade 1 meningioma from 2 experiments.

    Article Snippet: The following antibodies were used for the labeling of cells: CD3 PerCPCy5.5 (UCHT1), CD3 PECy7 (UCHT1), CD4 BUV395 (SK3), CD4 APCCy7 (RPA-T4), CD11c PECy7 (BLY6), CD11c BV510 (B-ly6), CD19 Alexa Fluor-488 (HIB19), CD45 BV605 (HI30), CD45 BV510 (HI30), CD45RO APC-H7 (UCHL1), CD64 PerCPCy5.5 (10.1), HLA-DR APC (G46-6), TIM-3 BV711 (7D3) (BD Biosciences), CD8 BV510 (SK1), CD8 PECy7 (SK1), CD45 PECy7 (HI30), CD56 BV421 (HCD56), CD56 APC (5.1H11), CD83 APCCy7 (HB15e), TCRa/b BV421 (IP26) (BioLegend), CD4 APC (RPA-TA), CD19 PECy7 (HIB19) (Invitrogen), CD3 BV421 (REA613), CD3 APC (BW264/56), CD8 BV421 (REA734), CD11c BV421 (REA618), CD11c APC-Vio770 (REA618), CD14 APC-Vio770 (TÜK4), CD14 PE (TÜK), CD45 APC-Vio770 (REA747), HLA-DR PE (REA805) (Miltenyi Biotec), and CD45RA PerCPCy5.5 (HI100) (ProSci Incorporated, Poway, CA, USA).

    Techniques: Expressing, Flow Cytometry

    Overview of the lymphoid compartment. ( A ) The gating strategy for the flow cytometric analyses. ( B ) T cell proportion of CD45 + immune cells. ( C ) The proportion of CD4 + helper T cells and CD8 + cytotoxic T cells. ( D ) The proportion of CD19 + B cells. ( E ) The proportion of CD56 + NK cells. Data is presented as mean with SEM (( B ) with n = 5 from 4 experiments, ( C ) with n = 3 from 3 experiments, ( D ) with n = 22 from 14 experiments, and ( E ) with n = 12 from 7 experiments). A t -test was used for statistical comparison. Statistical significances are presented as ** = p < 0.01.

    Journal: Cancers

    Article Title: Flow Cytometry Analyses of Meningioma Immune Cell Composition Using a Short, Optimized Digestion Protocol

    doi: 10.3390/cancers16233942

    Figure Lengend Snippet: Overview of the lymphoid compartment. ( A ) The gating strategy for the flow cytometric analyses. ( B ) T cell proportion of CD45 + immune cells. ( C ) The proportion of CD4 + helper T cells and CD8 + cytotoxic T cells. ( D ) The proportion of CD19 + B cells. ( E ) The proportion of CD56 + NK cells. Data is presented as mean with SEM (( B ) with n = 5 from 4 experiments, ( C ) with n = 3 from 3 experiments, ( D ) with n = 22 from 14 experiments, and ( E ) with n = 12 from 7 experiments). A t -test was used for statistical comparison. Statistical significances are presented as ** = p < 0.01.

    Article Snippet: The following antibodies were used for the labeling of cells: CD3 PerCPCy5.5 (UCHT1), CD3 PECy7 (UCHT1), CD4 BUV395 (SK3), CD4 APCCy7 (RPA-T4), CD11c PECy7 (BLY6), CD11c BV510 (B-ly6), CD19 Alexa Fluor-488 (HIB19), CD45 BV605 (HI30), CD45 BV510 (HI30), CD45RO APC-H7 (UCHL1), CD64 PerCPCy5.5 (10.1), HLA-DR APC (G46-6), TIM-3 BV711 (7D3) (BD Biosciences), CD8 BV510 (SK1), CD8 PECy7 (SK1), CD45 PECy7 (HI30), CD56 BV421 (HCD56), CD56 APC (5.1H11), CD83 APCCy7 (HB15e), TCRa/b BV421 (IP26) (BioLegend), CD4 APC (RPA-TA), CD19 PECy7 (HIB19) (Invitrogen), CD3 BV421 (REA613), CD3 APC (BW264/56), CD8 BV421 (REA734), CD11c BV421 (REA618), CD11c APC-Vio770 (REA618), CD14 APC-Vio770 (TÜK4), CD14 PE (TÜK), CD45 APC-Vio770 (REA747), HLA-DR PE (REA805) (Miltenyi Biotec), and CD45RA PerCPCy5.5 (HI100) (ProSci Incorporated, Poway, CA, USA).

    Techniques: Comparison

    Assessment of CD45RA and CD45RO expression on immune cells within meningioma. ( A ) The gating strategy for the flow cytometry analyses. The proportion of CD45RA and CD45RO of the following populations: ( B ) CD45 + cells, ( C ) CD4 + cells, ( D ) CD8 + cells, and ( E ) CD4 − CD8 − cells. Data is presented as mean with SEM (( B – E ) with n = 15 from 13 experiments), and a t -test was used for statistical comparisons. Statistical significances are presented as * = p < 0.05 and **** = p < 0.0001.

    Journal: Cancers

    Article Title: Flow Cytometry Analyses of Meningioma Immune Cell Composition Using a Short, Optimized Digestion Protocol

    doi: 10.3390/cancers16233942

    Figure Lengend Snippet: Assessment of CD45RA and CD45RO expression on immune cells within meningioma. ( A ) The gating strategy for the flow cytometry analyses. The proportion of CD45RA and CD45RO of the following populations: ( B ) CD45 + cells, ( C ) CD4 + cells, ( D ) CD8 + cells, and ( E ) CD4 − CD8 − cells. Data is presented as mean with SEM (( B – E ) with n = 15 from 13 experiments), and a t -test was used for statistical comparisons. Statistical significances are presented as * = p < 0.05 and **** = p < 0.0001.

    Article Snippet: The following antibodies were used for the labeling of cells: CD3 PerCPCy5.5 (UCHT1), CD3 PECy7 (UCHT1), CD4 BUV395 (SK3), CD4 APCCy7 (RPA-T4), CD11c PECy7 (BLY6), CD11c BV510 (B-ly6), CD19 Alexa Fluor-488 (HIB19), CD45 BV605 (HI30), CD45 BV510 (HI30), CD45RO APC-H7 (UCHL1), CD64 PerCPCy5.5 (10.1), HLA-DR APC (G46-6), TIM-3 BV711 (7D3) (BD Biosciences), CD8 BV510 (SK1), CD8 PECy7 (SK1), CD45 PECy7 (HI30), CD56 BV421 (HCD56), CD56 APC (5.1H11), CD83 APCCy7 (HB15e), TCRa/b BV421 (IP26) (BioLegend), CD4 APC (RPA-TA), CD19 PECy7 (HIB19) (Invitrogen), CD3 BV421 (REA613), CD3 APC (BW264/56), CD8 BV421 (REA734), CD11c BV421 (REA618), CD11c APC-Vio770 (REA618), CD14 APC-Vio770 (TÜK4), CD14 PE (TÜK), CD45 APC-Vio770 (REA747), HLA-DR PE (REA805) (Miltenyi Biotec), and CD45RA PerCPCy5.5 (HI100) (ProSci Incorporated, Poway, CA, USA).

    Techniques: Expressing, Flow Cytometry