flow cytometry data  (Tree Star Inc)

Journal: bioRxiv

Article Title: Type I interferon signaling promotes mucosal inflammation in murine models of colitis

doi: 10.64898/2026.03.02.709022

Figure Lengend Snippet: (A) Feature plots of IFN receptors, including IFN-I receptor ( IFNAR1/IFNAR2 ), IFN-II receptor ( IFNGR1/IFNGR2 ), IFN-III receptor ( IFNLR1/IL10RB ), in epithelial cells and CD14 + myeloid cells, from the scRNA-seq analysis of human colonic biopsies in . (B) Feature plots of IFN receptors, from the scRNA-seq analysis of DSS-induced colitis in . (C) Flow cytometry analysis of IFNAR1 + cells in mouse colon with or without DSS exposure, gated by immune cell marker CD45 and epithelial cell marker EpCAM. (D) Proportions of IFNAR1 + cells classified as immune cells (CD45 + /EpCAM - ) or epithelial cells (CD45 - /EpCAM + ) in mouse colon with or without DSS exposure. n=5 per group. (E-F) Flow cytometry analysis and quantification of median fluorescence intensity (MFI) of IFNAR1 expression in immune cells (CD45 + /EpCAM - ) and epithelial cells (CD45 - /EpCAM + ) from DSS-treated mouse colon.

Article Snippet: Flow cytometry data were acquired on an Aurora flow cytometer (Cytek Biosciences) using SpectroFlo software (version 3.3.0) after calibration with Submicron Bead Calibration Kit (Bangs Laboratories).

Techniques: Flow Cytometry, Marker, Fluorescence, Expressing

Journal: bioRxiv

Article Title: Type I interferon signaling promotes mucosal inflammation in murine models of colitis

doi: 10.64898/2026.03.02.709022

Figure Lengend Snippet: (A) Schematic illustrating how the serine-to-alanine substitution at position 535 of murine IFNAR1 protein affects phosphorylation and ubiquitination-dependent degradation. (B) qRT-PCR analysis of selected IFN-I signature genes in spleen and colon from WT and SA mice at baseline. Data were normalized to the mean of WT mice (set as 1). n=5-10 per group. (C) qRT-PCR analysis of selected IFN-I signature genes in bone marrow-derived macrophages (BMDMs) from WT and SA mice, at baseline (untreated) and after stimulation by interferon-β (IFNβ, 200 IU/mL x 8 hours) or lipopolysaccharides (LPS, 1 µg/mL x 8 hours). Data were normalized to the mean of WT BMDMs at baseline (set as 1). n=5-10 per group. (D-E) Mass cytometry (CyTOF) analysis of colon from WT (n=4) and SA (n=6) mice at baseline. (D) UMAP plots with cells colored by identity. (E) Proportions of immune cells (CD45 + /EpCAM - ), epithelial cells (CD45 - /EpCAM + ), and stromal cells (CD45 - /EpCAM - ). ns: not significant. (F) Heatmap showing the mean expression of target proteins in the antibody panel (Supplemental Table 4), with those having p <0.05 by SAM (Significance Analysis of Microarrays) for their median expression indicated by red asterisks.

Article Snippet: Flow cytometry data were acquired on an Aurora flow cytometer (Cytek Biosciences) using SpectroFlo software (version 3.3.0) after calibration with Submicron Bead Calibration Kit (Bangs Laboratories).

Techniques: Phospho-proteomics, Ubiquitin Proteomics, Quantitative RT-PCR, Derivative Assay, Mass Cytometry, Expressing

Journal: bioRxiv

Article Title: Type I interferon signaling promotes mucosal inflammation in murine models of colitis

doi: 10.64898/2026.03.02.709022

Figure Lengend Snippet:

Article Snippet: Flow cytometry data were acquired on an Aurora flow cytometer (Cytek Biosciences) using SpectroFlo software (version 3.3.0) after calibration with Submicron Bead Calibration Kit (Bangs Laboratories).

Techniques: Cytometry

Journal: Proceedings of the National Academy of Sciences of the United States of America

Article Title: Functionally heterogeneous intratumoral CD4 + CD8 + double-positive T cells can give rise to single-positive T cells

doi: 10.1073/pnas.2506168123

Figure Lengend Snippet: Frequency of DP T cells within human kidney cancer patients. ( A ) Multiplex immunofluorescent staining of DAPI (blue), CD4+ (red), CD8+ (green), and overlay without DAPI (left–right) in malignant and nonmalignant kidney regions from a RCC patient (representative of 3 patients) and from healthy donor thymus tissue and a corresponding tumor field with negative control staining of primary antibodies and nonmammalian RNA probes (bottom rows). T cells that co-express CD4 and CD8 are indicated in the white circles. (Scale bar, 10 μm.) ( B ) PBMCs and dissociated single cells from kidney tumors (Tumor) or nonmalignant kidney tissue (Normal) (N = 11 patients) were assessed by flow cytometry and single cell sequencing for the composition of T cells in each compartment. ( C ) Distribution of T cell subtypes CD4+FoxP3+ Treg (CD4Treg), CD4+FoxP3− Conventional (CD4Eff), CD8+ and CD4+CD8+ DP out of CD3+ cells in tumor, nonmalignant kidney tissue, patient PBMC, and healthy PBMC donors (Mean ± SEM). ( D ) Uniform manifold approximation and projection (UMAP) plots of 105,553 single sorted CD3+CD8+, CD3+CD4+, and CD3+CD4+CD8+ T cells obtained from kidney tumors, adjacent nonmalignant renal tissue (Normal), and peripheral blood (PBMC) from kidney cancer patients and healthy donors (N = 3 patients, N = 4 donors). ( E ) UMAP plots showing distribution of T cell states by sorted cell type and density plots showing distribution of tissue samples. Statistical analyses were calculated using a one -way ANOVA with Tukey’s multiple comparisons test. * P ≤ 0.05, ** P ≤ 0.01, *** P ≤ 0.001, and **** P ≤ 0.0001.

Article Snippet: All flow cytometry data were analyzed by FlowJo 10.7 (Tree-Star).

Techniques: Multiplex Assay, Staining, Negative Control, Flow Cytometry, Sequencing

Journal: bioRxiv

Article Title: Phenotypic dynamics and behaviors of neutrophils during barrier challenge

doi: 10.64898/2026.01.06.697946

Figure Lengend Snippet: A) Schematic representation of S. Aureus biofilm model of skin infection. B) Quantification by flow cytometry of neutrophil numbers per infectious wound over the initial 40 h of infection. N = 4-5 per time point. C) Quantification by flow cytometry of neutrophils and S. aureus+ events in infections over a 10-day time course. N = 5 mice per time point. D) Intravital microscopy of neutrophils (red, Catchup IVM-red) and Ly6G (green) in infectious wounds imaged between 5 and 9 hours post-infection. Scale bar = 100 μm E) Neutrophils (red, Catchup IVM-red) and S. aureus (Green, GFP) imaged in infectious wound at 24h of infection. Scale bar = 55 μm F) Flow cytometry data from Kikume mice representing Kikume-RED+ cells in the infection site 0h (left) and 24h (right) after photoactivation of the wound. G) Intravital microscopy of Kikume-RED (photoconverted) and KIkume-GREEN (non-photoconverted) cells within a 24h infection. Cells were photoactivated at t=0, and images taken at 1h30, 3h, and 10h25 after photoactivation. Scale bars = 100 μm H) UMAP projections of spectral flow cytometry data representing neutrophils from 4, 12, 24, and 48 hour skin infections. N = 4-5 mice per time point, concatenated I) Schematic representation of intravenous (i.v.) cell labeling to distinguish intravascular versus tissue-associated neutrophils in flow cytometry data. J) UMAP representation of intravenous+ cells (colored by density) and tissue-associated cells (gray) in 4h-48h infections. K) Hierarchically clustered heatmap of i.v.+ and i.v.- neutrophil phenotypic markers from 4h-48h infections. L) Histogram representations of flow cytometry data comparing selected marker expression in i.v.+ (pink) and tissue (i.v.-, gray) neutrophils from 4h-48h infections. Error bars = SEM.

Article Snippet: Spectral flow cytometry data was collected on a Cytek Aurora (5-laser) nad spillover/compensation was adjusted in FlowJo before export to omiq.ai for further analysis.

Techniques: Infection, Flow Cytometry, Intravital Microscopy, Labeling, Marker, Expressing

Journal: bioRxiv

Article Title: Phenotypic dynamics and behaviors of neutrophils during barrier challenge

doi: 10.64898/2026.01.06.697946

Figure Lengend Snippet: A) Representative flow cytometry data depicting S. aureus positive neutrophils from a skin infection. B) Intravital microscopy images of Kikume-RED+ and Kikume-GREEN+ neutrophils in the liver focal thermal injury model, taken at 0h and 24h after photoactivation. Scale bar = 50 μm C) Quantification of CD11b+ Ly6G+ events within the dead cell gate as a proportion of total CD11b+ Ly6G+ cells (live + dead) over time. Data are taken from multiple experiments and compare values from 8h, 24h, 48h, 72h, 96h, and 120h after infection. N = 4-19 per time point. D) Histogram representations of neutrophil markers across the 4-48h time course. E) Heatmap representations of relative protein expression (fluorescence signal), normalized per each marker, over time and in the iv.v+ versus i.v.- compartments of infections. Error bars = SEM. Related to figure 1.

Article Snippet: Spectral flow cytometry data was collected on a Cytek Aurora (5-laser) nad spillover/compensation was adjusted in FlowJo before export to omiq.ai for further analysis.

Techniques: Flow Cytometry, Infection, Intravital Microscopy, Expressing, Fluorescence, Marker

Journal: bioRxiv

Article Title: Phenotypic dynamics and behaviors of neutrophils during barrier challenge

doi: 10.64898/2026.01.06.697946

Figure Lengend Snippet: A) Histogram representations of CD101 expression in neutrophils from 4h, 12h, 24h, and 48h infections. B) Histogram representations of CD101 expression in neutrophils from i.v.+ versus i.v.- compartments of h, 12h, 24h, and 48h infections. C) Schematic representation of EdU experimental design. D) Quantification of flow cytometry data depicting EdU positivity as a proportion of various neutrophil subsets. From left to right, CD101-lo bone marrow neutrophils (blue), CD101-hi bone marrow neutrophils (pink), blood neutrophils (purple), and CD101-hi (orange) or CD101-lo (green) skin infection-associated neutrophils. N = 4-5 mice per data point. E) Schematic depiction of adoptive transfer scheme, wherein blood neutrophils of CD45.1 congenic mice were isolated and transferred into infection sites of CD45.2 recipient mice, and analyzed 4h later for phenotypic traits. I) Histogram representations of flow cytometry data depicting CD101 expression in CD45.1 donor neutrophils (top, teal) and CD45.1 neutrophils recovered 4h after adoptive transfer (lower, red), each red histogram representing cells from an individual recipient mouse. J) Quantification of the proportion of endogenous CD45.2 (gray) and donor-derived CD45.1 (red) neutrophils falling into the CD101-lo gate. K) Schematic representation of analysis to compare CD101-hi to CD101-lo i.v.- neutrophils from either bone marrow or skin infections. L-M) Volcano plot representation of phenotypic markers and how they differ between CD101-lo and CD101-hi populations in bone marrow (L) and skin infections (M). Delta gMFI values represent averages over N = 5 mice. N) Venn-diagram representing markers that are decreased (blue) or increased (red) in expression within the CD101-lo gate, compared to the CD101-hi gate, from each tissue. O-P) Pair-wise comparisons of PD-L1 (O) or ICAM-1 (P) expression in CD101-hi versus CD101-lo subpopulations of neutrophils from bone marrow (left) and skin infections (middle), and representative flow cytometry data depicting PD-L1 expression in infection associated neutrophils (right). Error bars = SEM, statistics = t-test for P values shown in volcano plots.

Article Snippet: Spectral flow cytometry data was collected on a Cytek Aurora (5-laser) nad spillover/compensation was adjusted in FlowJo before export to omiq.ai for further analysis.

Techniques: Expressing, Flow Cytometry, Infection, Adoptive Transfer Assay, Isolation, Derivative Assay

Journal: bioRxiv

Article Title: Phenotypic dynamics and behaviors of neutrophils during barrier challenge

doi: 10.64898/2026.01.06.697946

Figure Lengend Snippet: A) tSNE representation of flow cytometry data depicting CD45.1 donor cells before transfer (teal) or 4h after transfer (red) and endogenous cells (gray) from skin infections. N = 3 mice for donor-derived red and gray conditions. Related to figure 2.

Article Snippet: Spectral flow cytometry data was collected on a Cytek Aurora (5-laser) nad spillover/compensation was adjusted in FlowJo before export to omiq.ai for further analysis.

Techniques: Flow Cytometry, Derivative Assay

Journal: bioRxiv

Article Title: Phenotypic dynamics and behaviors of neutrophils during barrier challenge

doi: 10.64898/2026.01.06.697946

Figure Lengend Snippet: A) Schematic depicting artificial subsetting of neutrophils into i.v.+ (pink), i.v.-CD101-hi (green) and i.v.- CD101-lo (blue) subpopulations. B) Flow cytometry data depicting the distribution of each subpopulation, as in A, according to parameters of PD-L1 and ICAM-1 expression. C) Quantification of flow cytometry data as in B. N = 5 mice per group. D-E) Quantification of fluorescent S. Aureus signal within i.v.- CD101-hi and i.v.- CD101-lo subpopulations (D), and PD-L1-hi ICAM-1-hi versus PD-L1-lo ICAM-1-lo subgates (E), within neutrophil from 24h infections. N = 5 mice. F) UMAP representation of neutrophils from 4h-24h infections, colored by fluorescence intensity for CD101 (left) and side scatter (SSC-A, right) parameters. N = 4-5 mice per time point, concatenated. G) CD101 expression plotted against granularity (side scatter, SSC-A) for neutrophils from mice across the 4h-48h time course of infection; each point represents one mouse. H) Histogram representations and quantification of granularity (side scatter, SSC-A) in infection-associated neutrophils from mice treated with NADPH oxidase inhibitor, Rho kinase inhibitor, or Pan-protease inhibitor, or the relevant saline-treated control. Saline controls from NADPH oxidase and Rho Kinase inhibitors are equivalent as these experimental conditions were tested in tandem. N = 5 mice per condition. I) Flow cytometry data depicting the distribution of infection-associated neutrophils in the i.v.- CD101-lo gate per PD-L1 and ICAM-1 expression. J) Quantification of the proportion of CD101-lo i.v.- neutrophils within the PD-L1-hi ICAM-1-hi gate for each condition. N = 5 mice per group. Error bars = SEM, statistics = t-test, P values shown.

Article Snippet: Spectral flow cytometry data was collected on a Cytek Aurora (5-laser) nad spillover/compensation was adjusted in FlowJo before export to omiq.ai for further analysis.

Techniques: Flow Cytometry, Expressing, Fluorescence, Infection, Protease Inhibitor, Saline, Control

Journal: bioRxiv

Article Title: Phenotypic dynamics and behaviors of neutrophils during barrier challenge

doi: 10.64898/2026.01.06.697946

Figure Lengend Snippet: A) Quantification of the proportion of i.v.- neutrophils within the Cd101-lo/negative gate for conditions of NADPH oxidase, Rho kinase, and pan-protease inhibition, compared to saline controls. B) Flow cytometry data depicting the distribution of infection-associated neutrophils in the i.v.- CD101-lo gate per PD-L1 and ICAM-1 expression for pan-protease inhibitor-treated versus experiment-specific saline control. Related to figure 3.

Article Snippet: Spectral flow cytometry data was collected on a Cytek Aurora (5-laser) nad spillover/compensation was adjusted in FlowJo before export to omiq.ai for further analysis.

Techniques: Inhibition, Saline, Flow Cytometry, Infection, Expressing, Protease Inhibitor, Control

Journal: bioRxiv

Article Title: Phenotypic dynamics and behaviors of neutrophils during barrier challenge

doi: 10.64898/2026.01.06.697946

Figure Lengend Snippet: A) Schematic depicting G-CSF treatment regimen for experimental mice. B-C) UMAP representation of spectral flow cytometry data depicting intravascular (B) or tissue-associated (C) neutrophils from 72h skin infections of control mice versus those treated subcutaneously with G-CSF. N = 4-5 mice per group. D) Volcano plot representation of differences neutrophil phenotypic markers between control and G-CSF-treated mice, from intravascular (left) and tissue-associated (right) neutrophil compartments. Data averaged from N = 4-5 mice. E) UMAP representations of spectral flow cytometry data from intravenous (top) and tissue-associated (bottom) neutrophils in control (left) versus G-CSF-treated (right); colored by fluorescence intensity for CD101. F) Quantification of flow cytometry data depicting neutrophil numbers within infection sites (left), infectious wound size (middle), and S. aureus + events per wound (right) from infections of control versus G-CSF-treated mice. For B-F, one outlier in control group was excluded on basis of ROUT outlier identification test (Q = 1%). G) Schematic representation (left) and flow cytometry data quantification (right) for mice treated with i.p. anti-Ly6G antibody versus control mice. Quantification of bone marrow neutrophil numbers (middle left) and their CD101 expression (middle right), as well as blood neutrophil numbers (right) are presented. N = 5 mice per group. H) Intravital microscopy depicting neutrophils (red, Catchup IVM-red) and S. aureus (green) in an infection site from a mouse treated with anti-Ly6G antibody. Scale bar = 50 μm I) Quantification of flow cytometry data depicting neutrophil and S. aureus numbers in 24h infections from mice treated with anti-Ly6G or control mice on days. N = 5-6 mice per group. J) Quantification of flow cytometry data depicting neutrophil and S. aureus numbers in 72h infections (left, right) and wound sizes (middle) from mice treated with anti-Ly6G or control mice. N = 6 mice per group. Error bars = SEM, statistics = t-test for bar charts and volcano plots, P values shown.

Article Snippet: Spectral flow cytometry data was collected on a Cytek Aurora (5-laser) nad spillover/compensation was adjusted in FlowJo before export to omiq.ai for further analysis.

Techniques: Flow Cytometry, Control, Fluorescence, Infection, Expressing, Intravital Microscopy

Journal: bioRxiv

Article Title: Phenotypic dynamics and behaviors of neutrophils during barrier challenge

doi: 10.64898/2026.01.06.697946

Figure Lengend Snippet: A) Quantification of flow cytometry data depicting neutrophil expression of CD101 in intravenous (left) and tissue-associated (right) neutrophils from control mice or those treated with G-CSF. B) Quantification of flow cytometry data depicting neutrophil levels in blood (left), wound size (middle), and the proportion of S. aureus + neutrophils (right) in 24h infections from mice treated with anti-Ly6G or control mice. N = 5-6 mice per group. Error bars = SEM, statistics = t-test, P values shown. Related to figure 4.

Article Snippet: Spectral flow cytometry data was collected on a Cytek Aurora (5-laser) nad spillover/compensation was adjusted in FlowJo before export to omiq.ai for further analysis.

Techniques: Flow Cytometry, Expressing, Control

Journal: bioRxiv

Article Title: Phenotypic dynamics and behaviors of neutrophils during barrier challenge

doi: 10.64898/2026.01.06.697946

Figure Lengend Snippet: A) UMAP projections of spectral flow cytometry data representing neutrophils from 1, 2, 3, and 4 day skin infections. N = 4-5 mice per time point, concatenated B) UMAP representation of intravenous+ cells (colored by density) and tissue-associated cells (gray) in 1-4 day infections. N = 4-5 mice per time point, concatenated. C) Quantification of flow cytometry data depicting the proportion of CD101-lo/ negative versus CD101-hi neutrophils in the i.v.- compartment of skin infections over a 1-4 day time course. N = 4-5 mice per time point. D) Quantification of flow cytometry data depicting neutrophil granularity (side scatter, SSC-A) in i.v.+ and i.v.- compartments of day 1-4 skin infections. N = 4-5 mice per group. E) Histogram representations of flow cytometry data comparing selected marker expression in i.v.+ (pink) and tissue (i.v.-, gray) neutrophils from 1-4 day infections. F) Quantification of flow cytometry data depicting neutrophil numbers (left) and the proportion of CD101-lo PD-L1-hi ICAM-1-hi neutrophils in the i.v.- compartment (right) of day 1-4 skin infections. N = 4-5 mice per time point. G) Hierarchically clustered heatmap of i.v.+ and i.v.- neutrophil phenotypic markers from 1-4 day infections.

Article Snippet: Spectral flow cytometry data was collected on a Cytek Aurora (5-laser) nad spillover/compensation was adjusted in FlowJo before export to omiq.ai for further analysis.

Techniques: Flow Cytometry, Marker, Expressing

Journal: bioRxiv

Article Title: Phenotypic dynamics and behaviors of neutrophils during barrier challenge

doi: 10.64898/2026.01.06.697946

Figure Lengend Snippet: A) Quantification of flow cytometry data depicting numbers of neutrophils in skin infections compared to aseptic excisional wounds. N = 5 mice per condition. B) UMAP projections of spectral flow cytometry data representing neutrophils from 24h infections versus aseptic wounds (left), and clustering representation of spatial regions or the UMAP (right). N = 5 mice per condition. C) Bar plots representing the relative proportion of each cluster ( – ) within the total neutrophils from each condition. D) edgeR analysis of differential cluster representation between infection and aseptic wound conditions. E) Schematic depiction (left) and UMAP projections (right) of intravenous (i.v.+) neutrophils (pink) overlaid on all infection-associated neutrophils (gray) for infection (left UMAP) and aseptic wound (right UMAP) conditions. F) Quantification of flow cytometry data representing fluorescence intensity among selected neutrophil markers in infections versus aseptic wounds. G) Experimental schematic (top) and histogram representations of flow cytometry data (bottom) from contralateral 24h infections versus aseptic wound challenges. H) Pairwise comparisons of CD101 and CXCR2 expression from contralateral 24h infections and aseptic wounds.

Article Snippet: Spectral flow cytometry data was collected on a Cytek Aurora (5-laser) nad spillover/compensation was adjusted in FlowJo before export to omiq.ai for further analysis.

Techniques: Flow Cytometry, Infection, Fluorescence, Expressing

Journal: bioRxiv

Article Title: Phenotypic dynamics and behaviors of neutrophils during barrier challenge

doi: 10.64898/2026.01.06.697946

Figure Lengend Snippet: A) Schematic depicting S. aureus biofilm (top) and planktonic (bottom) infection models. B) Quantification of flow cytometry data depicting neutrophil numbers across various infection MOIs and models. Data pooled from 3 experiments. C) Quantification of flow cytometry data depicting ratios of neutrophils to S. aureus within infections. D) Quantification of flow cytometry data depicting numbers of S. aureus + events in biofilm and planktonic infections at the indicated MOIs. E) Quantification of fluorescence intensity reflecting neutrophil granularity (side scatter, SSC-A) in the intravascular (i.v.+, left) and extravascular (i.v.-, right) compartments of 24h biofilm versus planktonic infections. N = 5 mice per condition. F) UMAP representations of spectral flow cytometry data from mice with either biofilm (left) or 60K CFU MOI planktonic (right) infections, reflecting total tissue neutrophils (top colored, bottom gray) or the i.v.+ compartment (bottom colored) at 24h. N = 3-5 mice per condition. G) UMAPs as in F, colored to reflect fluorescence intensity for side scatter (SSC-A, top) or CD101 expression (bottom). N = 3-5 mice per condition. H-I) Quantification of flow cytometry data depicting CD101 (left) and side scatter (right) fluorescence intensity from mice as in F-G (H), or a separate cohort of biofilm versus planktonic infection-bearing mice (I). J) Intravital microscopy depicting neutrophils (red, Catchup IVM-red) and S. aureus (green) in day 1 biofilm versus planktonic infections. Scale bar = 100 μm. K-L) Intravital microscopy depicting neutrophils (red, Catchup IVM-red) and S. aureus (green) in day 1 biofilm (K) versus planktonic (L) infections. Scale bars = 10 μm. Error bars = SEM, statistics = t-test for bar charts and volcano plots, P values shown.

Article Snippet: Spectral flow cytometry data was collected on a Cytek Aurora (5-laser) nad spillover/compensation was adjusted in FlowJo before export to omiq.ai for further analysis.

Techniques: Infection, Flow Cytometry, Fluorescence, Expressing, Intravital Microscopy

Journal: bioRxiv

Article Title: Phenotypic dynamics and behaviors of neutrophils during barrier challenge

doi: 10.64898/2026.01.06.697946

Figure Lengend Snippet: A) Quantification of flow cytometry data depicting numbers of neutrophils in biofilm (left) and planktonic (right) infections, and indicating biological replicates chosen for phenotypic comparisons between biofilm and planktonic infection-associated neutrophils in Figure 7F-H. B) UMAP representations of neutrophils from biofilm (left) and ∼90K CFU MOI planktonic (right) infections, colored by fluorescence intensity reflecting granularity (side scatter, SSC-A, top) or CD101 expression (bottom). C) Quantification of neutrophil numbers (left) and S. aureus + events (right) in biofilm infections versus 1.8M CFU MOI planktonic infections. Error bars = SEM, statistics = t-test, P values shown. Related to figure 7.

Article Snippet: Spectral flow cytometry data was collected on a Cytek Aurora (5-laser) nad spillover/compensation was adjusted in FlowJo before export to omiq.ai for further analysis.

Techniques: Flow Cytometry, Infection, Fluorescence, Expressing