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anti mouse cd8 apc vio770 antibody (Miltenyi Biotec)

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Miltenyi Biotec anti mouse cd8 apc vio770 antibody

a Heatmap showing Pearson’s correlation between hypoxic signature genes expression and immune-related genes expression in basal TNBC samples ( n = 98) in TCGA dataset. b Scatter plots (upper panel) and Pearson’s correlation coefficients (lower panel) showing the expression of hypoxic gene signatures and immune-related genes in breast cancers in TCGA dataset (Basal, n = 98; HER2, n = 58; Luminal A, n = 231; Luminal B, n = 129). Regression lines with a 95% confidence interval (gray fill) are shown in the scatter plots. c Images of fluorescent staining of human TNBC samples. Scale bar, 50 µm. Data were representative of 30 independent experiments. d Quantification of infiltrating IFNγ + <t>CD8</t> + T cell number in HIF1α − and HIF1α + regions of human TNBC sample ( n = 30). P values were determined with paired two-tailed t -test. e Correlation between infiltrating IFNγ + CD8 + T cell count and HIF1α fluorescent intensity in human TNBC samples ( n = 30). The simple linear regression R 2 and P values (two-tailed) are calculated. Dot plot is shown with regression line and 95% confidence interval. f Representative images of fluorescent staining of mouse 4T1 tumor samples. Scale bar, 50 µm. Data represents three independent experiments. g Flow cytometry (left panel) demonstrating the gating strategy of activated-PIM high (H) and activated-PIM low (L) populations in living cells dissociated from 4T1 tumors. The CD8 + T cell percentage and IFNγ expression in CD8 + T cells was quantified (right panel, n = 6). Data were presented as box and whiskers, with median value and whiskers of minimum and maximum values. P values were determined with an unpaired two-tailed t -test. h Kaplan–Meier overall survival (OS) and distant metastasis-free survival (DMFS) analysis of the indicated gene signatures in TNBC patients. The publicly available data used in Fig. 1a, b are available in the TCGA database under accession code BRCA.exp.547.med.txt [ https://gdc.cancer.gov/about-data/publications/brca_2012 ]. The publicly available data used in h are available in the KM-Plotter-Breast Cancer [ https://kmplot.com/analysis/index.php?p=service&cancer=breast ]. For the remaining data, source data are provided in Source Data file.

Anti Mouse Cd8 Apc Vio770 Antibody, supplied by Miltenyi Biotec, used in various techniques. Bioz Stars score: 94/100, based on 106 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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anti mouse cd8 apc vio770 antibody - by Bioz Stars, 2026-08

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1) Product Images from "Hypoxia induces HIF1α-dependent epigenetic vulnerability in triple negative breast cancer to confer immune effector dysfunction and resistance to anti-PD-1 immunotherapy"

Article Title: Hypoxia induces HIF1α-dependent epigenetic vulnerability in triple negative breast cancer to confer immune effector dysfunction and resistance to anti-PD-1 immunotherapy

Journal: Nature Communications

doi: 10.1038/s41467-022-31764-9

Figure Legend Snippet: a Heatmap showing Pearson’s correlation between hypoxic signature genes expression and immune-related genes expression in basal TNBC samples ( n = 98) in TCGA dataset. b Scatter plots (upper panel) and Pearson’s correlation coefficients (lower panel) showing the expression of hypoxic gene signatures and immune-related genes in breast cancers in TCGA dataset (Basal, n = 98; HER2, n = 58; Luminal A, n = 231; Luminal B, n = 129). Regression lines with a 95% confidence interval (gray fill) are shown in the scatter plots. c Images of fluorescent staining of human TNBC samples. Scale bar, 50 µm. Data were representative of 30 independent experiments. d Quantification of infiltrating IFNγ + CD8 + T cell number in HIF1α − and HIF1α + regions of human TNBC sample ( n = 30). P values were determined with paired two-tailed t -test. e Correlation between infiltrating IFNγ + CD8 + T cell count and HIF1α fluorescent intensity in human TNBC samples ( n = 30). The simple linear regression R 2 and P values (two-tailed) are calculated. Dot plot is shown with regression line and 95% confidence interval. f Representative images of fluorescent staining of mouse 4T1 tumor samples. Scale bar, 50 µm. Data represents three independent experiments. g Flow cytometry (left panel) demonstrating the gating strategy of activated-PIM high (H) and activated-PIM low (L) populations in living cells dissociated from 4T1 tumors. The CD8 + T cell percentage and IFNγ expression in CD8 + T cells was quantified (right panel, n = 6). Data were presented as box and whiskers, with median value and whiskers of minimum and maximum values. P values were determined with an unpaired two-tailed t -test. h Kaplan–Meier overall survival (OS) and distant metastasis-free survival (DMFS) analysis of the indicated gene signatures in TNBC patients. The publicly available data used in Fig. 1a, b are available in the TCGA database under accession code BRCA.exp.547.med.txt [ https://gdc.cancer.gov/about-data/publications/brca_2012 ]. The publicly available data used in h are available in the KM-Plotter-Breast Cancer [ https://kmplot.com/analysis/index.php?p=service&cancer=breast ]. For the remaining data, source data are provided in Source Data file.

Techniques Used: Expressing, Staining, Two Tailed Test, Cell Counting, Flow Cytometry

a Schematic graph demonstrating the coculture model. b Representative flow cytograms (upper panel) gated from human pan-T cell culture and quantification (lower panel, n = 3) of differentiated CD8 + T cell subtypes: Tn (naïve T cells), Tcm (central memory T cells), Tem (effector memory T cells), Teff (effector T cells). c Schematic graph demonstrating the normoxia (20% O 2 ) and hypoxia (1% O 2 ) culture condition of T cells coculturing with human TNBC cell line. d Heatmap of the differentially expressed genes (DEGs) in hypoxic cultured human T cells compared to normoxia group. DEGs were identified in edgeR (|logFC| > 1, adjusted P < 0.01). P values were adjusted using Benjamini–Hochberg method in edgeR. DEGs identified in the indicated GO gene clusters are marked in the heatmap. e GSEA analysis of human T cells in hypoxic versus normoxic conditions. Analysis was based on ranked logFC from edgeR. FDR and adjusted p value are shown in the graph. P values were adjusted using Benjamini–Hochberg method in GSEA analysis. f Flow cytometry quantifications of immune effector molecules and exhaustion markers in CD8 + T cells gated from human pan-T cells cultured under the indicated conditions ( n = 4). g Representative flow cytograms of PD-1 and TIM-3 expression in CD8 + T cells gated from human pan-T cells culture. h Flow cytometric quantification of terminally exhausted T cells (PD-1 + TIM-3 + ) in CD8 + T cells gated from human pan-T cells culture ( n = 3). i Flow cytometric quant i fication of proliferating cells (Ki76 + ) in CD8 + and CD4 + T cells gated from human T cells cocultured with TNBC ( n = 3). All flow cytometry data ( b , f , h , and i ) are presented as the mean ± SD of samples from three to four donors. For all flow cytometry data, P values were determined by one-way ANOVA ( f , h ) or two-way ANOVA ( b ) with Turkey’s test, or paired two-tailed t -test ( i ). Raw RNA-seq data i s available in the GEO database with accession number GSE179885 . For the remaining data, source data are provided in Source Data file.

Figure Legend Snippet: a Schematic graph demonstrating the coculture model. b Representative flow cytograms (upper panel) gated from human pan-T cell culture and quantification (lower panel, n = 3) of differentiated CD8 + T cell subtypes: Tn (naïve T cells), Tcm (central memory T cells), Tem (effector memory T cells), Teff (effector T cells). c Schematic graph demonstrating the normoxia (20% O 2 ) and hypoxia (1% O 2 ) culture condition of T cells coculturing with human TNBC cell line. d Heatmap of the differentially expressed genes (DEGs) in hypoxic cultured human T cells compared to normoxia group. DEGs were identified in edgeR (|logFC| > 1, adjusted P < 0.01). P values were adjusted using Benjamini–Hochberg method in edgeR. DEGs identified in the indicated GO gene clusters are marked in the heatmap. e GSEA analysis of human T cells in hypoxic versus normoxic conditions. Analysis was based on ranked logFC from edgeR. FDR and adjusted p value are shown in the graph. P values were adjusted using Benjamini–Hochberg method in GSEA analysis. f Flow cytometry quantifications of immune effector molecules and exhaustion markers in CD8 + T cells gated from human pan-T cells cultured under the indicated conditions ( n = 4). g Representative flow cytograms of PD-1 and TIM-3 expression in CD8 + T cells gated from human pan-T cells culture. h Flow cytometric quantification of terminally exhausted T cells (PD-1 + TIM-3 + ) in CD8 + T cells gated from human pan-T cells culture ( n = 3). i Flow cytometric quant i fication of proliferating cells (Ki76 + ) in CD8 + and CD4 + T cells gated from human T cells cocultured with TNBC ( n = 3). All flow cytometry data ( b , f , h , and i ) are presented as the mean ± SD of samples from three to four donors. For all flow cytometry data, P values were determined by one-way ANOVA ( f , h ) or two-way ANOVA ( b ) with Turkey’s test, or paired two-tailed t -test ( i ). Raw RNA-seq data i s available in the GEO database with accession number GSE179885 . For the remaining data, source data are provided in Source Data file.

Techniques Used: Cell Culture, Flow Cytometry, Expressing, Two Tailed Test, RNA Sequencing

a RT-qPCR analysis assessing IFNG expression in T/NK cells in an epigenetic-drug screening. Both T cells and NK cells were cultured under 1% O 2 with indicated treatments. Data were presented as the log2 fold change of IFNG mRNA level normalized to vehicle control, mean ± SD of technical triplicates, representative of two independent experiments ( n = 2). b , c Representative histograms (left panel) and flow cytometric quantifications (right panel) of IFNγ expression in human CD8 + T cells ( b n = 4) and NK cells ( c n = 3) with indicated treatments. Quantification data were presented as the mean ± SD of samples from three to four donors. P values were determined by two-way ANOVA with Turkey’s test. d ChIP-qPCR analysis of HDAC1, HDAC2, HDAC3, EZH2, and SUZ12 occupancy on IFNG promoter of human T cells. Four primers were designed to span the promoters of IFNG , with P1 at −1448 to −1354b, P2 at −707 to −628b, P3 at −257 to −171b, P4 at +350 to +461b, relative to TSS. For ChIP analysis of EZH2 and SUZ12 occupancy, RPL30 serves as the negative control and CCND2 as the positive control. e , f ChIP-qPCR analysis of H3K27ac and H3K27me3 enrichment on IFNG promoter of human T cells under indicated conditions. All ChIP-qPCR data ( d – f ) are presented as fold enrichment relative to IgG and expressed as mean ± SD of technical triplicates, representative of two independent experiments ( n = 2). For ChIP-qPCR data of d , e , statistics were performed to analyze bindings of indicated markers across different sites in IFNG promoter ( RPL30 and CCND2 excluded) between hypoxia and normoxia. P values were determined by two-way ANOVA analysis. g RT-qPCR analysis of human T cell with indicated gene knockdown. Data were presented as the fold change of mRNA level normalized to the control group under normoxia (1% O2), mean ± SD of technical triplicates, representative of two independent experiments ( n = 2). Source data are provided as a source data file.

Figure Legend Snippet: a RT-qPCR analysis assessing IFNG expression in T/NK cells in an epigenetic-drug screening. Both T cells and NK cells were cultured under 1% O 2 with indicated treatments. Data were presented as the log2 fold change of IFNG mRNA level normalized to vehicle control, mean ± SD of technical triplicates, representative of two independent experiments ( n = 2). b , c Representative histograms (left panel) and flow cytometric quantifications (right panel) of IFNγ expression in human CD8 + T cells ( b n = 4) and NK cells ( c n = 3) with indicated treatments. Quantification data were presented as the mean ± SD of samples from three to four donors. P values were determined by two-way ANOVA with Turkey’s test. d ChIP-qPCR analysis of HDAC1, HDAC2, HDAC3, EZH2, and SUZ12 occupancy on IFNG promoter of human T cells. Four primers were designed to span the promoters of IFNG , with P1 at −1448 to −1354b, P2 at −707 to −628b, P3 at −257 to −171b, P4 at +350 to +461b, relative to TSS. For ChIP analysis of EZH2 and SUZ12 occupancy, RPL30 serves as the negative control and CCND2 as the positive control. e , f ChIP-qPCR analysis of H3K27ac and H3K27me3 enrichment on IFNG promoter of human T cells under indicated conditions. All ChIP-qPCR data ( d – f ) are presented as fold enrichment relative to IgG and expressed as mean ± SD of technical triplicates, representative of two independent experiments ( n = 2). For ChIP-qPCR data of d , e , statistics were performed to analyze bindings of indicated markers across different sites in IFNG promoter ( RPL30 and CCND2 excluded) between hypoxia and normoxia. P values were determined by two-way ANOVA analysis. g RT-qPCR analysis of human T cell with indicated gene knockdown. Data were presented as the fold change of mRNA level normalized to the control group under normoxia (1% O2), mean ± SD of technical triplicates, representative of two independent experiments ( n = 2). Source data are provided as a source data file.

Techniques Used: Quantitative RT-PCR, Expressing, Drug discovery, Cell Culture, Control, ChIP-qPCR, Negative Control, Positive Control, Knockdown

a ChIP-qPCR analysis of HIF1α and HIF2α occupancy on IFNG promoter in human T cells. VEGFA served as a positive control. b Co-immunoprecipitation shows the physical interaction between HDAC1 and HIF1α, and the interaction between HDAC1 and SUZ12 in human T cells. Data is representative of two independent experiments ( n = 2). c Representative western blot images ( n = 2) to demonstrate knockdown of HIF1α in human T cells. d ChIP-qPCR analysis of HDAC1 occupancy on IFNG promoter in human T cells. e ChIP-qPCR analysis of H3K27ac and H3K27me3 enrichment on IFNG promoter in human T cells with indicated treatments. All ChIP-qPCR data ( a , d , e ) are presented as fold enrichment relative to IgG and expressed as mean ± SD of technical triplicates, representative of two independent experiments ( n = 2). For ChIP-qPCR data of a , statistics were performed to analyze bindings of indicated markers across different sites in IFNG promoter ( VEGFA excluded) between hypoxia and normoxia. P values were determined by two-way ANOVA analysis. f Flow cytometric quantifications of IFNγ in CD8 + T cells gated from human pan-T cells cultured under the indicated conditions. Data were presented as the mean ± SD of three independent experiments ( n = 3). P values were determined by one-way ANOVA with Turkey’s test. g Representative western blot images ( n = 2) to demonstrate the inhibition of HIF1α level by indicated compounds in human T cells. h Representative histograms (left panel) and flow cytometric quantifications (right panel) of IFNγ expression in human CD8 + T cells with indicated treatments. Quantification data were presented as the mean ± SD of samples from four donors ( n = 4). P values were determined by two-way ANOVA with Turkey’s test. Source data are provided as a source data file.

Figure Legend Snippet: a ChIP-qPCR analysis of HIF1α and HIF2α occupancy on IFNG promoter in human T cells. VEGFA served as a positive control. b Co-immunoprecipitation shows the physical interaction between HDAC1 and HIF1α, and the interaction between HDAC1 and SUZ12 in human T cells. Data is representative of two independent experiments ( n = 2). c Representative western blot images ( n = 2) to demonstrate knockdown of HIF1α in human T cells. d ChIP-qPCR analysis of HDAC1 occupancy on IFNG promoter in human T cells. e ChIP-qPCR analysis of H3K27ac and H3K27me3 enrichment on IFNG promoter in human T cells with indicated treatments. All ChIP-qPCR data ( a , d , e ) are presented as fold enrichment relative to IgG and expressed as mean ± SD of technical triplicates, representative of two independent experiments ( n = 2). For ChIP-qPCR data of a , statistics were performed to analyze bindings of indicated markers across different sites in IFNG promoter ( VEGFA excluded) between hypoxia and normoxia. P values were determined by two-way ANOVA analysis. f Flow cytometric quantifications of IFNγ in CD8 + T cells gated from human pan-T cells cultured under the indicated conditions. Data were presented as the mean ± SD of three independent experiments ( n = 3). P values were determined by one-way ANOVA with Turkey’s test. g Representative western blot images ( n = 2) to demonstrate the inhibition of HIF1α level by indicated compounds in human T cells. h Representative histograms (left panel) and flow cytometric quantifications (right panel) of IFNγ expression in human CD8 + T cells with indicated treatments. Quantification data were presented as the mean ± SD of samples from four donors ( n = 4). P values were determined by two-way ANOVA with Turkey’s test. Source data are provided as a source data file.

Techniques Used: ChIP-qPCR, Positive Control, Immunoprecipitation, Western Blot, Knockdown, Cell Culture, Inhibition, Expressing

a Cell lysis of TNBC cells cocultured with human T cells from two different healthy donors. Human T cells were stimulated with TNBC cell lysate-primed DC cells. Data were presented as mean ± SD of three independent experiments ( n = 3). P values were determined by two-way ANOVA. b Western blot analysis of IFNγ–regulated proteins in TNBC cells cocultured with human T cells. Data were representative of two independent experiments ( n = 2). c Cell lysis of TNBC cells cocultured with human T cells. Human T cells were stimulated with TNBC cell lysate-primed DC cells and pretreated with indicated compounds. Data presented as mean ± SD of three independent experiments ( n = 3). P values were determined by one-way ANOVA with Dunnett’s test. d Western blot analysis of IFNγ–regulated proteins in TNBC cells cocultured with human T cells. Human T cells were stimulated with TNBC cell lysate-primed DC cells and pretreated with indicated compounds. Data were representative of two independent experiments ( n = 2). e Cell lysis of TNBC cells cocultured with human T cells. Data were presented as mean ± SD of three independent experiments ( n = 3). P values were determined by two-way ANOVA with Dunnett’s test. f Flow cytometric quantifications of immune effector molecules in human CD8 + T cells cultured under the indicated conditions. Data were presented as the mean ± SD of samples from three donors ( n = 3). P values were determined by two-way ANOVA with Turkey’s test. Source data are provided as a source data file.

Figure Legend Snippet: a Cell lysis of TNBC cells cocultured with human T cells from two different healthy donors. Human T cells were stimulated with TNBC cell lysate-primed DC cells. Data were presented as mean ± SD of three independent experiments ( n = 3). P values were determined by two-way ANOVA. b Western blot analysis of IFNγ–regulated proteins in TNBC cells cocultured with human T cells. Data were representative of two independent experiments ( n = 2). c Cell lysis of TNBC cells cocultured with human T cells. Human T cells were stimulated with TNBC cell lysate-primed DC cells and pretreated with indicated compounds. Data presented as mean ± SD of three independent experiments ( n = 3). P values were determined by one-way ANOVA with Dunnett’s test. d Western blot analysis of IFNγ–regulated proteins in TNBC cells cocultured with human T cells. Human T cells were stimulated with TNBC cell lysate-primed DC cells and pretreated with indicated compounds. Data were representative of two independent experiments ( n = 2). e Cell lysis of TNBC cells cocultured with human T cells. Data were presented as mean ± SD of three independent experiments ( n = 3). P values were determined by two-way ANOVA with Dunnett’s test. f Flow cytometric quantifications of immune effector molecules in human CD8 + T cells cultured under the indicated conditions. Data were presented as the mean ± SD of samples from three donors ( n = 3). P values were determined by two-way ANOVA with Turkey’s test. Source data are provided as a source data file.

Techniques Used: Lysis, Western Blot, Cell Culture

a Schematic diagram showing the establishment of humanized mice (humice) with human immune system reconstituted in NIKO mice. The presence of human CD45 + cells, NK cells, CD4 + and CD8 + T cells in the mice’s peripheral system was validated by flow cytometry. b Primary LM2 tumor size in humice (control, n = 14; Keytruda, n = 14; ENT, n = 12; PX478, n = 14; ENT + Keytruda, n = 16; PX478 + Keytruda, n = 16) and NIKO mice (control, n = 10; ENT + Keytruda, n = 10; PX478 + Keytruda, n = 10), at Day 21 of treatments. c Lung metastasis of humice (control, n = 6; Keytruda, n = 6; ENT, n = 6; PX478, n = 6; ENT + Keytruda, n = 7; PX478 + Keytruda, n = 7) and NIKO mice (control, n = 5; ENT + Keytruda, n = 5; PX478 + Keytruda, n = 5) bearing LM2 tumors at Day 35 assessed by bioluminescence (BLI) measurement. d Representative bioluminescence (BLI) images showing the lung metastasis of humice and NIKO mice. e Flow cytometric analysis of LM2 tumors harvested from humanized mice. IFNγ, TNFα, and granzyme B expression was examined in tumor-infiltrating human CD8 + T cells and NK cells. N = 5 for each group. f Flow cytometry analysis of LM2 tumors harvested from humanized mice. Expressions of human PD-L1 and PD-L2 were examined in total living cells dissociated from LM2 tumors. N = 5 for each group. Quantification data of flow cytometry ( e , f ) are presented as a box and whiskers, with median values and whiskers of minimum and maximum values. Data for b and c were presented as mean ± SD . P values were determined by one-way ( e , f ) or two-way ( b , c ) ANOVA with Turkey’s test. Source data are provided as a source data file.

Figure Legend Snippet: a Schematic diagram showing the establishment of humanized mice (humice) with human immune system reconstituted in NIKO mice. The presence of human CD45 + cells, NK cells, CD4 + and CD8 + T cells in the mice’s peripheral system was validated by flow cytometry. b Primary LM2 tumor size in humice (control, n = 14; Keytruda, n = 14; ENT, n = 12; PX478, n = 14; ENT + Keytruda, n = 16; PX478 + Keytruda, n = 16) and NIKO mice (control, n = 10; ENT + Keytruda, n = 10; PX478 + Keytruda, n = 10), at Day 21 of treatments. c Lung metastasis of humice (control, n = 6; Keytruda, n = 6; ENT, n = 6; PX478, n = 6; ENT + Keytruda, n = 7; PX478 + Keytruda, n = 7) and NIKO mice (control, n = 5; ENT + Keytruda, n = 5; PX478 + Keytruda, n = 5) bearing LM2 tumors at Day 35 assessed by bioluminescence (BLI) measurement. d Representative bioluminescence (BLI) images showing the lung metastasis of humice and NIKO mice. e Flow cytometric analysis of LM2 tumors harvested from humanized mice. IFNγ, TNFα, and granzyme B expression was examined in tumor-infiltrating human CD8 + T cells and NK cells. N = 5 for each group. f Flow cytometry analysis of LM2 tumors harvested from humanized mice. Expressions of human PD-L1 and PD-L2 were examined in total living cells dissociated from LM2 tumors. N = 5 for each group. Quantification data of flow cytometry ( e , f ) are presented as a box and whiskers, with median values and whiskers of minimum and maximum values. Data for b and c were presented as mean ± SD . P values were determined by one-way ( e , f ) or two-way ( b , c ) ANOVA with Turkey’s test. Source data are provided as a source data file.

Techniques Used: Flow Cytometry, Control, Expressing

Image Search Results

CD8 + T cytotoxic cells are the predominant subset within the T and NK cell compartment in the colon of chronically infected mice (A) Uniform manifold approximation and projection (UMAP) plot showing nine T and NK cell subclusters. Each point represents a single cell. (B) Bar graph depicts the relative percentages of each cell subtype in naive and infected mice. (C) Representative flow cytometry plots of CD8 + T cells in naive (left) and infected mice (right). Cells were gated on live, singlets, CD3 + cells. (D) Violin plot shows the percentage of CD8 + T cells in naive and infected mice. (E) Representative flow cytometry plots of T follicular helper cells in naive (left) and infected mice (right). Cells were gated on live, singlets, CD3 + CD4 + cells. (F) Violin plot shows the percentage of PD-1 + CXCR4 + T follicular helper cells in naive and chronically infected mice. Data are representative of two independent experiments with a total of 6 (in D) or 4 (in F) mice per group. In (D and F), violin plots show the distribution of values for each group. Individual points represent biological replicates. Large dashed horizontal lines indicate the median. Statistical significance was determined by an unpaired t test. ∗∗∗: p < 0.001; ns: not significant.

Journal: iScience

Article Title: CCL signaling drives T Cell–Macrophage crosstalk in the mouse colon during chronic Trypanosoma cruzi infection

doi: 10.1016/j.isci.2026.116611

Figure Lengend Snippet: CD8 + T cytotoxic cells are the predominant subset within the T and NK cell compartment in the colon of chronically infected mice (A) Uniform manifold approximation and projection (UMAP) plot showing nine T and NK cell subclusters. Each point represents a single cell. (B) Bar graph depicts the relative percentages of each cell subtype in naive and infected mice. (C) Representative flow cytometry plots of CD8 + T cells in naive (left) and infected mice (right). Cells were gated on live, singlets, CD3 + cells. (D) Violin plot shows the percentage of CD8 + T cells in naive and infected mice. (E) Representative flow cytometry plots of T follicular helper cells in naive (left) and infected mice (right). Cells were gated on live, singlets, CD3 + CD4 + cells. (F) Violin plot shows the percentage of PD-1 + CXCR4 + T follicular helper cells in naive and chronically infected mice. Data are representative of two independent experiments with a total of 6 (in D) or 4 (in F) mice per group. In (D and F), violin plots show the distribution of values for each group. Individual points represent biological replicates. Large dashed horizontal lines indicate the median. Statistical significance was determined by an unpaired t test. ∗∗∗: p < 0.001; ns: not significant.

Article Snippet: CD8a (Ly-2) Microbeads , Miltenyi Biotec , Cat-130-117-044.

Techniques: Infection, Single Cell, Flow Cytometry

CD8 + cytotoxic T cells contribute as central mediators within the CCL signaling network (A) Violin plots show the distribution and density of CCL5 (left) and CCR5 (right) expression across T and NK cell subsets, as well as macrophages, in the colon of naive and chronically infected mice. Wider sections of the violin indicate a higher proportion of cells expressing CCL5 or CCR5 at that level. Data were generated from CellChat-guided analysis of scRNA-seq profiles. (B) Representative flow cytometry plots show CD8 + CCR5 + T cells in the colon of naive (upper panel) and chronically infected mice (bottom panel). Cells were gated on live, singlets, and CD3 + cells. (C) Representative flow cytometry plots show F4/80 + CCR5 + T cells in naive (upper panel) and chronically infected mice (bottom panel). Cells were gated on live, singlets, and CD45 + cells. (D) Violin plot shows the frequency of CD8 + CCR5 + T cells in naive and chronically infected mice. Data are representative of two independent experiments ( n = 4 mice per group). (E) mRNA quantification of Ccl5 and Ccr5 by qRT-PCR in naive and chronically infected mice. The plot shows log 2 fold changes (FC) in gene expression determined by the ΔC t method with normalization to GAPDH. The horizontal line indicates the median value for each group, with individual data points plotted. CD8 + T cells were purified from the lamina propria of naive and chronically infected mice using magnetic bead–based separation prior to RNA extraction. Data are from three independent experiments. (F) Violin plot shows the frequency of F4/80 + CCR5 + T cells in the colon of naive and chronically infected mice. Data are representative of two independent experiments ( n = 3 mice per group). In (D and F), violin plots show the distribution of values for each group. Individual points represent biological replicates. Large dashed horizontal lines indicate the median. Statistical significance was determined by an unpaired t test. ∗∗: p < 0.01; ns: not significant.

Journal: iScience

Article Title: CCL signaling drives T Cell–Macrophage crosstalk in the mouse colon during chronic Trypanosoma cruzi infection

doi: 10.1016/j.isci.2026.116611

Figure Lengend Snippet: CD8 + cytotoxic T cells contribute as central mediators within the CCL signaling network (A) Violin plots show the distribution and density of CCL5 (left) and CCR5 (right) expression across T and NK cell subsets, as well as macrophages, in the colon of naive and chronically infected mice. Wider sections of the violin indicate a higher proportion of cells expressing CCL5 or CCR5 at that level. Data were generated from CellChat-guided analysis of scRNA-seq profiles. (B) Representative flow cytometry plots show CD8 + CCR5 + T cells in the colon of naive (upper panel) and chronically infected mice (bottom panel). Cells were gated on live, singlets, and CD3 + cells. (C) Representative flow cytometry plots show F4/80 + CCR5 + T cells in naive (upper panel) and chronically infected mice (bottom panel). Cells were gated on live, singlets, and CD45 + cells. (D) Violin plot shows the frequency of CD8 + CCR5 + T cells in naive and chronically infected mice. Data are representative of two independent experiments ( n = 4 mice per group). (E) mRNA quantification of Ccl5 and Ccr5 by qRT-PCR in naive and chronically infected mice. The plot shows log 2 fold changes (FC) in gene expression determined by the ΔC t method with normalization to GAPDH. The horizontal line indicates the median value for each group, with individual data points plotted. CD8 + T cells were purified from the lamina propria of naive and chronically infected mice using magnetic bead–based separation prior to RNA extraction. Data are from three independent experiments. (F) Violin plot shows the frequency of F4/80 + CCR5 + T cells in the colon of naive and chronically infected mice. Data are representative of two independent experiments ( n = 3 mice per group). In (D and F), violin plots show the distribution of values for each group. Individual points represent biological replicates. Large dashed horizontal lines indicate the median. Statistical significance was determined by an unpaired t test. ∗∗: p < 0.01; ns: not significant.

Article Snippet: CD8a (Ly-2) Microbeads , Miltenyi Biotec , Cat-130-117-044.

Techniques: Expressing, Infection, Generated, Flow Cytometry, Quantitative RT-PCR, Gene Expression, Purification, RNA Extraction

CD8 + cytotoxic T cell–macrophage interactions likely shape colonic immune homeostasis during chronic T. cruzi infection (A) Volcano plot showing differentially expressed genes (DEGs) in lamina propria CD8 + cytotoxic T cells from infected mice compared with naive controls. Red dots depict upregulated genes, blue dots indicate downregulated genes, and gray dots represent genes with a non-significant change in expression. Genes with log 2 fold change ≥1.5, and p < 0.05 were considered significant. (B) Top five differentially regulated canonical pathways in lamina propria CD8 + cytotoxic T cells from infected mice, as predicted by ingenuity pathway analysis (IPA). Bars represent −log ( p value); red indicates pathway activation and blue indicates pathway inhibition. (C) Top 10 upregulated genes associated with the IL-4/IL-13 signaling pathway (left) and the pathogen-induced cytokine storm (PICS) pathway (right) in CD8 + cytotoxic T cells. (D) Volcano plot of DEGs in lamina propria macrophages from infected mice compared with naive controls, displayed as in (A). (E) Top five differentially regulated canonical pathways in lamina propria macrophages from infected mice, as predicted by IPA, displayed as in (B). (F) Top 10 upregulated genes associated with the S100 protein family signaling pathway (left) and the neutrophil degranulation pathway (right) in macrophages. In (C and F), bars indicate log 2 fold change between infected and naive mice.

Journal: iScience

Article Title: CCL signaling drives T Cell–Macrophage crosstalk in the mouse colon during chronic Trypanosoma cruzi infection

doi: 10.1016/j.isci.2026.116611

Figure Lengend Snippet: CD8 + cytotoxic T cell–macrophage interactions likely shape colonic immune homeostasis during chronic T. cruzi infection (A) Volcano plot showing differentially expressed genes (DEGs) in lamina propria CD8 + cytotoxic T cells from infected mice compared with naive controls. Red dots depict upregulated genes, blue dots indicate downregulated genes, and gray dots represent genes with a non-significant change in expression. Genes with log 2 fold change ≥1.5, and p < 0.05 were considered significant. (B) Top five differentially regulated canonical pathways in lamina propria CD8 + cytotoxic T cells from infected mice, as predicted by ingenuity pathway analysis (IPA). Bars represent −log ( p value); red indicates pathway activation and blue indicates pathway inhibition. (C) Top 10 upregulated genes associated with the IL-4/IL-13 signaling pathway (left) and the pathogen-induced cytokine storm (PICS) pathway (right) in CD8 + cytotoxic T cells. (D) Volcano plot of DEGs in lamina propria macrophages from infected mice compared with naive controls, displayed as in (A). (E) Top five differentially regulated canonical pathways in lamina propria macrophages from infected mice, as predicted by IPA, displayed as in (B). (F) Top 10 upregulated genes associated with the S100 protein family signaling pathway (left) and the neutrophil degranulation pathway (right) in macrophages. In (C and F), bars indicate log 2 fold change between infected and naive mice.

Article Snippet: CD8a (Ly-2) Microbeads , Miltenyi Biotec , Cat-130-117-044.

Techniques: Infection, Expressing, Activation Assay, Inhibition

Proposed model of the immune response mechanisms to Trypanosoma cruzi in the mouse colon, integrating our findings with prior studies ① Infected smooth muscle cells release trypomastigotes into the surrounding colonic tissue. ② Trypomastigotes are phagocytosed by macrophages. ③ After 18–24 hs post-internalization, amastigotes are released into the cytoplasm, where they replicate and synthesize proteins that are presented on the macrophage surface. ④ CD8 + and CD4 + T cells recognize T. cruzi peptides presented by MHC complexes. ⑤ Upon activation, CD8 + T cells secrete granzyme A and multiple cytokines. ⑥ Granzyme A -containing granules may enter parasite-infected smooth muscle cells through pores formed by perforin-1 (PRF1; secreted by NK cells), contributing to cell death. ⑦ Tumor necrosis factor (TNF) may promote macrophage polarization to an M1 phenotype by inducing the expression of inducible nitric oxide synthase (NOS2). This enzyme subsequently oxidizes arginine to produce nitric oxide, which may contribute to parasite killing. ⑧ Activated CD4 + T cells can differentiate into Th and Tfh cells that produce Interleukin-4 (IL-4) and Interleukin-13 (IL-13) [⑨], which in turn induce M2 macrophage polarization. ⑩ C-C Motif Ligand 5 (CCL5) could further support M2 macrophage polarization via arginase I (ARG1) upregulation, promoting polyamines associated with parasite multiplication and persistence. ⑪ Amastigotes differentiate into trypomastigotes, completing the cycle by infecting naive smooth muscle cells.

Journal: iScience

Article Title: CCL signaling drives T Cell–Macrophage crosstalk in the mouse colon during chronic Trypanosoma cruzi infection

doi: 10.1016/j.isci.2026.116611

Figure Lengend Snippet: Proposed model of the immune response mechanisms to Trypanosoma cruzi in the mouse colon, integrating our findings with prior studies ① Infected smooth muscle cells release trypomastigotes into the surrounding colonic tissue. ② Trypomastigotes are phagocytosed by macrophages. ③ After 18–24 hs post-internalization, amastigotes are released into the cytoplasm, where they replicate and synthesize proteins that are presented on the macrophage surface. ④ CD8 + and CD4 + T cells recognize T. cruzi peptides presented by MHC complexes. ⑤ Upon activation, CD8 + T cells secrete granzyme A and multiple cytokines. ⑥ Granzyme A -containing granules may enter parasite-infected smooth muscle cells through pores formed by perforin-1 (PRF1; secreted by NK cells), contributing to cell death. ⑦ Tumor necrosis factor (TNF) may promote macrophage polarization to an M1 phenotype by inducing the expression of inducible nitric oxide synthase (NOS2). This enzyme subsequently oxidizes arginine to produce nitric oxide, which may contribute to parasite killing. ⑧ Activated CD4 + T cells can differentiate into Th and Tfh cells that produce Interleukin-4 (IL-4) and Interleukin-13 (IL-13) [⑨], which in turn induce M2 macrophage polarization. ⑩ C-C Motif Ligand 5 (CCL5) could further support M2 macrophage polarization via arginase I (ARG1) upregulation, promoting polyamines associated with parasite multiplication and persistence. ⑪ Amastigotes differentiate into trypomastigotes, completing the cycle by infecting naive smooth muscle cells.

Article Snippet: CD8a (Ly-2) Microbeads , Miltenyi Biotec , Cat-130-117-044.

Techniques: Infection, Activation Assay, Expressing

GPCR68 as a pH-Sensing regulator in T Cells and generation of GPCR68 fl/fl CD4 Cre mice. (A) Schematic diagram of the effect of pH on T cell GPCR68 as well as tumor. (B) Naïve CD4 + T cells were isolated and activated using anti-CD3 and anti-CD28 using the culture media with varying pH. RT-qPCR was performed to determine the expression of GPCR68 at various pH. (C) Naïve CD4 + T cells were activated with anti-CD3 and anti-CD28 under different pH conditions, and GPCR68 protein expression was assessed by Western blot analysis. (D) To generate conditional knockout (CKO) of GPCR68 in T cells, GPCR68 fl/fl mice were crossed with CD4 Cre mice and generated GPCR68 fl/fl CD4 Cre (CKO). (E) Flow cytometry was used to determine the population of CD4 and CD8 cells in the lymph nodes (LN), thymus (THY), and spleen (SP) at the basal level in CD4 Cre or GPCR68 fl/fl CD4 Cre mice. (F) Flow cytometry was used to determine the population of Foxp3+ Treg cells in the lymph nodes, thymus, and spleen at the basal level in the CD4 Cre or GPCR68 fl/fl CD4 Cre mice. (G-H) The population of F4/80+, CD11c+ (G), and B220+ (H) cells was determined in the lymph nodes and spleen at the basal level in the CD4 Cre or GPCR68 fl/fl CD4 Cre mice. (I-J) Flow cytometry was used to evaluate the CD4 + or CD8 + T cells for the determination of intracellular cytokines IFN-γ+ (I), or TNF-α+ (J) from the spleen and lymph nodes at basal level in the CD4 Cre or GPCR68 fl/fl CD4 Cre mice. Student t-test was performed for comparison between the two groups. Data are mean ± SEM (n = 5), ∗ p < 0.05.

Journal: Bioactive Materials

Article Title: pH-neutralization strategy to suppress GPCR68 spatiotemporally activates T cells and enhances anti-tumor immunity

doi: 10.1016/j.bioactmat.2026.02.039

Figure Lengend Snippet: GPCR68 as a pH-Sensing regulator in T Cells and generation of GPCR68 fl/fl CD4 Cre mice. (A) Schematic diagram of the effect of pH on T cell GPCR68 as well as tumor. (B) Naïve CD4 + T cells were isolated and activated using anti-CD3 and anti-CD28 using the culture media with varying pH. RT-qPCR was performed to determine the expression of GPCR68 at various pH. (C) Naïve CD4 + T cells were activated with anti-CD3 and anti-CD28 under different pH conditions, and GPCR68 protein expression was assessed by Western blot analysis. (D) To generate conditional knockout (CKO) of GPCR68 in T cells, GPCR68 fl/fl mice were crossed with CD4 Cre mice and generated GPCR68 fl/fl CD4 Cre (CKO). (E) Flow cytometry was used to determine the population of CD4 and CD8 cells in the lymph nodes (LN), thymus (THY), and spleen (SP) at the basal level in CD4 Cre or GPCR68 fl/fl CD4 Cre mice. (F) Flow cytometry was used to determine the population of Foxp3+ Treg cells in the lymph nodes, thymus, and spleen at the basal level in the CD4 Cre or GPCR68 fl/fl CD4 Cre mice. (G-H) The population of F4/80+, CD11c+ (G), and B220+ (H) cells was determined in the lymph nodes and spleen at the basal level in the CD4 Cre or GPCR68 fl/fl CD4 Cre mice. (I-J) Flow cytometry was used to evaluate the CD4 + or CD8 + T cells for the determination of intracellular cytokines IFN-γ+ (I), or TNF-α+ (J) from the spleen and lymph nodes at basal level in the CD4 Cre or GPCR68 fl/fl CD4 Cre mice. Student t-test was performed for comparison between the two groups. Data are mean ± SEM (n = 5), ∗ p < 0.05.

Article Snippet: Naïve T cells were purified from lymph nodes as well as spleens of C57/BL6, CD4 Cre , GPCR68 fl/fl CD4 Cre (CKO) mice by using the mouse naïve CD4 + T Cell Isolation Kit (#130-104-453; Miltenyi Biotec) or naïve CD8 + T Cell Isolation Kit (#130-096-543; Miltenyi Biotec) for negative selection.

Techniques: Isolation, Quantitative RT-PCR, Expressing, Western Blot, Knock-Out, Generated, Flow Cytometry, Comparison

GPCR68 fl/fl CD4 Cre mice exhibit improved anti-tumor mmune responses. (A-C) Naïve CD4 + T cells were isolated from CD4 Cre or GPCR68 fl/fl CD4 Cre mice and activated using anti-CD3 and anti-CD28 using the culture media under physiologic neutral pH (7.4) or varying pH 6.0, 6.5, or 7.8. Flow cytometry plots showing the expression of IFN-γ and IL-2 in CD4 + T cells from CD4 Cre and GPCR68 fl/fl CD4 Cre mice. Each panel represents the frequency of IFN-γ + and IL-2 + cells. (B) Bar graph summarizing the percentage of IFN-γ + CD4 + T cells at each pH level for CD4 Cre and GPCR68 fl/fl CD4 Cre mice. (C) Bar graph showing the percentage of IL-2 + CD4 + T cells at each pH for CD4 Cre and GPCR68 fl/fl CD4 Cre mice. (D) Experimental timeline depicting tumor induction and treatment protocol in CD4 Cre and GPCR68 fl/fl CD4 Cre mice. (E) Tumor growth curves in CD4 Cre and GPCR68 fl/fl CD4 Cre mice. (F) Tumor weight in CD4 Cre versus GPCR68 fl/fl CD4 Cre mice at the time of harvesting on day 21. (G) Representative images of excised tumors at day 21. (H) Flow cytometric analysis of IFN-γ production by tumor-infiltrating CD4 + and CD8 + T cells. (I) Flow cytometric analysis of TNF-α production by tumor-infiltrating CD4 + and CD8 + T cells. Student t-test was performed for comparison between the two groups. Two-way ANOVA was used for multiple comparisons. Data are mean ± SEM (n = 5). ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ns = not significant.

Journal: Bioactive Materials

Article Title: pH-neutralization strategy to suppress GPCR68 spatiotemporally activates T cells and enhances anti-tumor immunity

doi: 10.1016/j.bioactmat.2026.02.039

Figure Lengend Snippet: GPCR68 fl/fl CD4 Cre mice exhibit improved anti-tumor mmune responses. (A-C) Naïve CD4 + T cells were isolated from CD4 Cre or GPCR68 fl/fl CD4 Cre mice and activated using anti-CD3 and anti-CD28 using the culture media under physiologic neutral pH (7.4) or varying pH 6.0, 6.5, or 7.8. Flow cytometry plots showing the expression of IFN-γ and IL-2 in CD4 + T cells from CD4 Cre and GPCR68 fl/fl CD4 Cre mice. Each panel represents the frequency of IFN-γ + and IL-2 + cells. (B) Bar graph summarizing the percentage of IFN-γ + CD4 + T cells at each pH level for CD4 Cre and GPCR68 fl/fl CD4 Cre mice. (C) Bar graph showing the percentage of IL-2 + CD4 + T cells at each pH for CD4 Cre and GPCR68 fl/fl CD4 Cre mice. (D) Experimental timeline depicting tumor induction and treatment protocol in CD4 Cre and GPCR68 fl/fl CD4 Cre mice. (E) Tumor growth curves in CD4 Cre and GPCR68 fl/fl CD4 Cre mice. (F) Tumor weight in CD4 Cre versus GPCR68 fl/fl CD4 Cre mice at the time of harvesting on day 21. (G) Representative images of excised tumors at day 21. (H) Flow cytometric analysis of IFN-γ production by tumor-infiltrating CD4 + and CD8 + T cells. (I) Flow cytometric analysis of TNF-α production by tumor-infiltrating CD4 + and CD8 + T cells. Student t-test was performed for comparison between the two groups. Two-way ANOVA was used for multiple comparisons. Data are mean ± SEM (n = 5). ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ns = not significant.

Techniques: Isolation, Flow Cytometry, Expressing, Comparison

Anti-tumor effects of borate bioactive glass (BOLT) in B16 tumor. (A) Schematic illustration depicting the induction of B16 melanoma tumors, followed by treatment with BOLT at various time points, and tumor harvesting for subsequent analysis. (B) Tumor growth curves showing tumor volume in Control and BOLT-treated B16 melanoma tumors in mice. (C) Tumor weight at the time of harvesting in the BOLT-treated group compared to the Control. (D) Representative images of excised tumors from Control and BOLT-treated mice. (E) In vivo imaging of tumor-bearing mice in both the Control and BOLT-treated groups. (F) Flow cytometry analysis showing IFN-γ production in CD4 + and CD8 + T cells following BOLT treatment compared to Control. (G) Flow cytometry analysis demonstrated TNF-α production in CD4 + and CD8 + T cells in the BOLT-treated group, with a significant increase observed in CD8 + T cells. Student t-test was performed for comparison between the two groups. Two-way ANOVA was used for multiple comparisons. Data represent the mean ± SEM (n = 5). ∗ p < 0.05, ∗∗ p < 0.01.

Journal: Bioactive Materials

Article Title: pH-neutralization strategy to suppress GPCR68 spatiotemporally activates T cells and enhances anti-tumor immunity

doi: 10.1016/j.bioactmat.2026.02.039

Figure Lengend Snippet: Anti-tumor effects of borate bioactive glass (BOLT) in B16 tumor. (A) Schematic illustration depicting the induction of B16 melanoma tumors, followed by treatment with BOLT at various time points, and tumor harvesting for subsequent analysis. (B) Tumor growth curves showing tumor volume in Control and BOLT-treated B16 melanoma tumors in mice. (C) Tumor weight at the time of harvesting in the BOLT-treated group compared to the Control. (D) Representative images of excised tumors from Control and BOLT-treated mice. (E) In vivo imaging of tumor-bearing mice in both the Control and BOLT-treated groups. (F) Flow cytometry analysis showing IFN-γ production in CD4 + and CD8 + T cells following BOLT treatment compared to Control. (G) Flow cytometry analysis demonstrated TNF-α production in CD4 + and CD8 + T cells in the BOLT-treated group, with a significant increase observed in CD8 + T cells. Student t-test was performed for comparison between the two groups. Two-way ANOVA was used for multiple comparisons. Data represent the mean ± SEM (n = 5). ∗ p < 0.05, ∗∗ p < 0.01.

Techniques: Control, In Vivo Imaging, Flow Cytometry, Comparison

Combinational treatment of BOLT and anti-CTLA-4 blockade enhances anti-tumor immune response in B16 melanoma. (A) C57BL/6 mice were subcutaneously injected with 1 × 10 5 B16 melanoma cells on day 0 to induce tumors. On day 7, mice were randomly divided into groups and treated with either BOLT alone (intratumoral injection administered on alternate days starting from day 7), anti-CTLA-4 (intraperitoneal injection administered on days 9, 11, 13, and 15), or a combination of both treatments. PBS was used as a vehicle Control, while IgG was used as anti-CTLA-4 Control. Tumor growth was monitored throughout the treatment period, and tumors were harvested for analysis on day 21. (B-C) Tumor growth curves and area under the curve (AUC) analysis for WT mice treated with BOLT, with or without anti-CTLA-4 antibody, following subcutaneous injection of B16 melanoma cells. Tumor growth was monitored, and analysis was conducted on day 21. (D) Representative images of excised tumors at day 21, showed reduced tumor size in combination-treated mice. (E, F) Flow cytometry analysis of IFN-γ production by tumor-infiltrating CD4 + and CD8 + T cells. (G, H) Flow cytometry analysis of TNF-α production by tumor-infiltrating CD4 + and CD8 + T cells. Two-way ANOVA was used for multiple comparisons. Data are mean ± SEM (n = 5), ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, and ∗∗∗∗ p < 0.0001.

Journal: Bioactive Materials

Article Title: pH-neutralization strategy to suppress GPCR68 spatiotemporally activates T cells and enhances anti-tumor immunity

doi: 10.1016/j.bioactmat.2026.02.039

Figure Lengend Snippet: Combinational treatment of BOLT and anti-CTLA-4 blockade enhances anti-tumor immune response in B16 melanoma. (A) C57BL/6 mice were subcutaneously injected with 1 × 10 5 B16 melanoma cells on day 0 to induce tumors. On day 7, mice were randomly divided into groups and treated with either BOLT alone (intratumoral injection administered on alternate days starting from day 7), anti-CTLA-4 (intraperitoneal injection administered on days 9, 11, 13, and 15), or a combination of both treatments. PBS was used as a vehicle Control, while IgG was used as anti-CTLA-4 Control. Tumor growth was monitored throughout the treatment period, and tumors were harvested for analysis on day 21. (B-C) Tumor growth curves and area under the curve (AUC) analysis for WT mice treated with BOLT, with or without anti-CTLA-4 antibody, following subcutaneous injection of B16 melanoma cells. Tumor growth was monitored, and analysis was conducted on day 21. (D) Representative images of excised tumors at day 21, showed reduced tumor size in combination-treated mice. (E, F) Flow cytometry analysis of IFN-γ production by tumor-infiltrating CD4 + and CD8 + T cells. (G, H) Flow cytometry analysis of TNF-α production by tumor-infiltrating CD4 + and CD8 + T cells. Two-way ANOVA was used for multiple comparisons. Data are mean ± SEM (n = 5), ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, and ∗∗∗∗ p < 0.0001.

Techniques: Injection, Control, Flow Cytometry

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