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data processing hyperion mass imaging system  (fluidigm)


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    fluidigm data processing hyperion mass imaging system
    Data Processing Hyperion Mass Imaging System, supplied by fluidigm, used in various techniques. Bioz Stars score: 93/100, based on 1523 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/mass+cytometry+data/Hyperion+Imaging+Mass+Cytometry+System/pm41672987-268-13-19
    Average 93 stars, based on 1523 article reviews
    data processing hyperion mass imaging system - by Bioz Stars, 2026-10
    93/100 stars

    Images

    Related Articles

    Mass Cytometry:

    Article Title: Uncovering the connection between Ly6ChiCD103+ myeloid cells and radiation-induced cardiac fibrosis by CyTOF
    Article Snippet: After washing with FACS buffer, the cells were counted and re-suspended in distilled water filtered through capFACS tubes (corning). .. Mass cytometry data were obtained using a Helios system (Helios, Fluidigm). .. The acquired raw data were uploaded to a Cytobank web server (Cytobank Inc., Santa Clara, CA, USA) for further data processing and to gate dead cells and normalization beads.

    Article Title: Photosensitive Hydrogel with Temperature-Controlled Reversible Nano-Apertures for Single-Cell Protein Analysis.
    Article Snippet: Metal-labeled antibodies were labeled in-house using the MaxPar X8 labeling kit according to the manufacturer’s instructions (Fluidigm). .. Mass cytometry data were obtained using Helios (Fluidigm) as previously reported. .. Briefly, stained cells were suspended in deionized H2O, and added 4-element normalization beads (Fluidigm) immediately before applying the samples to the instrument.

    Article Title: Anti-IL-6R antibody treatment changes microglial phenotype in AQP4 peptide-immunized mice, leading to suppression of myelitis severity.
    Article Snippet: After washing, cells were resuspended in Maxper Cell Acquisition Solution Plus (201248, Standard BioTools). .. Mass cytometry data were acquired on a Helios mass cytometry system (Standard BioTools) and analyzed using the Cytobank platform (Beckman Coulter Inc., Brea, CA, USA). ..

    Article Title: Phase II Study of Eribulin plus Pembrolizumab in Metastatic Soft-tissue Sarcomas: Clinical Outcomes and Biological Correlates
    Article Snippet: .. Mass cytometry data were collected using a CyToF XT Mass Cytometer (Standard Biotools). ..

    Article Title: Photosensitive Hydrogel with Temperature‐Controlled Reversible Nano‐Apertures for Single‐Cell Protein Analysis
    Article Snippet: Metal‐labeled antibodies were labeled in‐house using the MaxPar X8 labeling kit according to the manufacturer's instructions (Fluidigm). .. Mass cytometry data were obtained using Helios (Fluidigm) as previously reported. .. Briefly, stained cells were suspended in deionized H 2 O, and added 4‐element normalization beads (Fluidigm) immediately before applying the samples to the instrument.

    Article Title: Identification of senescent, TREM2-expressing microglia in aging and Alzheimer's disease model mouse brain.
    Article Snippet: Alzheimer’s disease (AD) and dementia in general are age-related diseases with multiple contributing factors, including brain inflammation.. Microglia, and specifically those expressing the AD risk gene TREM2, are considered important players in AD, but their exact contribution to pathology remains unclear.. In this study, using high-throughput mass cytometry in the 5×FAD mouse model of amyloidosis, we identified senescent microglia that express high levels of TREM2 but also exhibit a distinct signature from TREM2-dependent disease-associated microglia (DAM).

    Article Title: NK cell-macrophage interactions in granulomas correlate with limited tuberculosis pathology
    Article Snippet: .. All mass cytometry data was acquired on the Hyperion mass cytometry imaging system (Standard Biotools, San Fransisco, CA, USA) at the Flow cytometry Core Facility at the LUMC. .. A tuning protocol and 3-element tuning slide were used to autotune the system, as per the Hyperion imaging system user guide (Standard Biotools).

    Article Title: NK cell-macrophage interactions in granulomas correlate with limited tuberculosis pathology
    Article Snippet: .. All mass cytometry data was acquired on the Hyperion mass cytometry imaging system (Standard Biotools, San Fransisco, CA, USA) at the Flow cytometry Core Facility at the LUMC. .. A tuning protocol and 3-element tuning slide were used to autotune the system, as per the Hyperion imaging system user guide (Standard Biotools).

    Cytometry:

    Article Title: Phase II Study of Eribulin plus Pembrolizumab in Metastatic Soft-tissue Sarcomas: Clinical Outcomes and Biological Correlates
    Article Snippet: .. Mass cytometry data were collected using a CyToF XT Mass Cytometer (Standard Biotools). ..

    Imaging:

    Article Title: NK cell-macrophage interactions in granulomas correlate with limited tuberculosis pathology
    Article Snippet: .. All mass cytometry data was acquired on the Hyperion mass cytometry imaging system (Standard Biotools, San Fransisco, CA, USA) at the Flow cytometry Core Facility at the LUMC. .. A tuning protocol and 3-element tuning slide were used to autotune the system, as per the Hyperion imaging system user guide (Standard Biotools).

    Article Title: NK cell-macrophage interactions in granulomas correlate with limited tuberculosis pathology
    Article Snippet: .. All mass cytometry data was acquired on the Hyperion mass cytometry imaging system (Standard Biotools, San Fransisco, CA, USA) at the Flow cytometry Core Facility at the LUMC. .. A tuning protocol and 3-element tuning slide were used to autotune the system, as per the Hyperion imaging system user guide (Standard Biotools).

    Flow Cytometry:

    Article Title: NK cell-macrophage interactions in granulomas correlate with limited tuberculosis pathology
    Article Snippet: .. All mass cytometry data was acquired on the Hyperion mass cytometry imaging system (Standard Biotools, San Fransisco, CA, USA) at the Flow cytometry Core Facility at the LUMC. .. A tuning protocol and 3-element tuning slide were used to autotune the system, as per the Hyperion imaging system user guide (Standard Biotools).

    Article Title: NK cell-macrophage interactions in granulomas correlate with limited tuberculosis pathology
    Article Snippet: .. All mass cytometry data was acquired on the Hyperion mass cytometry imaging system (Standard Biotools, San Fransisco, CA, USA) at the Flow cytometry Core Facility at the LUMC. .. A tuning protocol and 3-element tuning slide were used to autotune the system, as per the Hyperion imaging system user guide (Standard Biotools).



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    data processing hyperion mass imaging system  (fluidigm)
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    a ) Differentially abundant CyTOF features in the peripheral blood (by two-sided Wilcoxon rank-sum test with Benjamini-Hochberg adjustment for multiple comparisons), and b ) differentially expressed genes in total peripheral blood mononuclear cells (PBMCs) between the viremic post-intervention controllers (n = 6) and non-controllers (n = 3) at baseline (on ART, prior to interventions). Differential expression analysis was performed using lmfit through limma using the empirical Bayes method to calculate a t-statistic. Significance cut-offs were set at a fold change > 1.5 and nominal P value < 0.05. c ) CyTOF landmark and sub-landmark gating scheme. Populations labelled in blue represent landmark populations and populations labelled in red represent sub-landmark populations. CyTOF, <t>cytometry</t> time of flight. PICs, post-intervention controllers. NCs, non-controllers.
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    mass cytometry data  (fluidigm)
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    (A) Imaging mass <t>cytometry</t> images overlaid with cellular identities determined in and , showing one granuloma of each lung pathology score category (low, intermediate, high). (B) Interaction analysis for the granuloma of each lung pathology category with the colour of the square representing the frequency of the interaction between the phenotype of interest and the phenotype of neighborhood cells as a percentage of the total interactions for the phenotype of interest (blue to green gradient). The statistical analysis of the significant occurrence of an interaction is represented as a dot on the interaction square, showing only positive correlations (grey to black gradient). (C) Localization and frequency of NK cell-macrophage interactions in the three granuloma shown in Fig A. (D) Frequency of cell interactions as frequency of total macrophage interactions. (E) Frequency of macrophage-NK cell (interactions in each granuloma as percentage of total interactions in the granuloma, shown across the lung pathology score categories. (F) Interaction glyphs showing an abstract representation of the four most abundant neighborhoods found in the macrophage-NK cell interactions and a table showing the proportion this neighborhood makes up of the macrophage-NK cell interactions, with the associated Z-score in brackets.
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    (A) Imaging mass <t>cytometry</t> images overlaid with cellular identities determined in and , showing one granuloma of each lung pathology score category (low, intermediate, high). (B) Interaction analysis for the granuloma of each lung pathology category with the colour of the square representing the frequency of the interaction between the phenotype of interest and the phenotype of neighborhood cells as a percentage of the total interactions for the phenotype of interest (blue to green gradient). The statistical analysis of the significant occurrence of an interaction is represented as a dot on the interaction square, showing only positive correlations (grey to black gradient). (C) Localization and frequency of NK cell-macrophage interactions in the three granuloma shown in Fig A. (D) Frequency of cell interactions as frequency of total macrophage interactions. (E) Frequency of macrophage-NK cell (interactions in each granuloma as percentage of total interactions in the granuloma, shown across the lung pathology score categories. (F) Interaction glyphs showing an abstract representation of the four most abundant neighborhoods found in the macrophage-NK cell interactions and a table showing the proportion this neighborhood makes up of the macrophage-NK cell interactions, with the associated Z-score in brackets.
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    (A) Imaging mass <t>cytometry</t> images overlaid with cellular identities determined in and , showing one granuloma of each lung pathology score category (low, intermediate, high). (B) Interaction analysis for the granuloma of each lung pathology category with the colour of the square representing the frequency of the interaction between the phenotype of interest and the phenotype of neighborhood cells as a percentage of the total interactions for the phenotype of interest (blue to green gradient). The statistical analysis of the significant occurrence of an interaction is represented as a dot on the interaction square, showing only positive correlations (grey to black gradient). (C) Localization and frequency of NK cell-macrophage interactions in the three granuloma shown in Fig A. (D) Frequency of cell interactions as frequency of total macrophage interactions. (E) Frequency of macrophage-NK cell (interactions in each granuloma as percentage of total interactions in the granuloma, shown across the lung pathology score categories. (F) Interaction glyphs showing an abstract representation of the four most abundant neighborhoods found in the macrophage-NK cell interactions and a table showing the proportion this neighborhood makes up of the macrophage-NK cell interactions, with the associated Z-score in brackets.
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    (A) Imaging mass <t>cytometry</t> images overlaid with cellular identities determined in and , showing one granuloma of each lung pathology score category (low, intermediate, high). (B) Interaction analysis for the granuloma of each lung pathology category with the colour of the square representing the frequency of the interaction between the phenotype of interest and the phenotype of neighborhood cells as a percentage of the total interactions for the phenotype of interest (blue to green gradient). The statistical analysis of the significant occurrence of an interaction is represented as a dot on the interaction square, showing only positive correlations (grey to black gradient). (C) Localization and frequency of NK cell-macrophage interactions in the three granuloma shown in Fig A. (D) Frequency of cell interactions as frequency of total macrophage interactions. (E) Frequency of macrophage-NK cell (interactions in each granuloma as percentage of total interactions in the granuloma, shown across the lung pathology score categories. (F) Interaction glyphs showing an abstract representation of the four most abundant neighborhoods found in the macrophage-NK cell interactions and a table showing the proportion this neighborhood makes up of the macrophage-NK cell interactions, with the associated Z-score in brackets.
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    Image Search Results


    a ) Differentially abundant CyTOF features in the peripheral blood (by two-sided Wilcoxon rank-sum test with Benjamini-Hochberg adjustment for multiple comparisons), and b ) differentially expressed genes in total peripheral blood mononuclear cells (PBMCs) between the viremic post-intervention controllers (n = 6) and non-controllers (n = 3) at baseline (on ART, prior to interventions). Differential expression analysis was performed using lmfit through limma using the empirical Bayes method to calculate a t-statistic. Significance cut-offs were set at a fold change > 1.5 and nominal P value < 0.05. c ) CyTOF landmark and sub-landmark gating scheme. Populations labelled in blue represent landmark populations and populations labelled in red represent sub-landmark populations. CyTOF, cytometry time of flight. PICs, post-intervention controllers. NCs, non-controllers.

    Journal: Nature

    Article Title: Correlates of HIV-1 control after combination immunotherapy

    doi: 10.1038/s41586-025-09929-5

    Figure Lengend Snippet: a ) Differentially abundant CyTOF features in the peripheral blood (by two-sided Wilcoxon rank-sum test with Benjamini-Hochberg adjustment for multiple comparisons), and b ) differentially expressed genes in total peripheral blood mononuclear cells (PBMCs) between the viremic post-intervention controllers (n = 6) and non-controllers (n = 3) at baseline (on ART, prior to interventions). Differential expression analysis was performed using lmfit through limma using the empirical Bayes method to calculate a t-statistic. Significance cut-offs were set at a fold change > 1.5 and nominal P value < 0.05. c ) CyTOF landmark and sub-landmark gating scheme. Populations labelled in blue represent landmark populations and populations labelled in red represent sub-landmark populations. CyTOF, cytometry time of flight. PICs, post-intervention controllers. NCs, non-controllers.

    Article Snippet: De-identified raw .fcs files with mass cytometry data were deposited at Mendeley (10.17632/3wfkd6rrht.1).

    Techniques: Quantitative Proteomics, Cytometry

    (A) Imaging mass cytometry images overlaid with cellular identities determined in and , showing one granuloma of each lung pathology score category (low, intermediate, high). (B) Interaction analysis for the granuloma of each lung pathology category with the colour of the square representing the frequency of the interaction between the phenotype of interest and the phenotype of neighborhood cells as a percentage of the total interactions for the phenotype of interest (blue to green gradient). The statistical analysis of the significant occurrence of an interaction is represented as a dot on the interaction square, showing only positive correlations (grey to black gradient). (C) Localization and frequency of NK cell-macrophage interactions in the three granuloma shown in Fig A. (D) Frequency of cell interactions as frequency of total macrophage interactions. (E) Frequency of macrophage-NK cell (interactions in each granuloma as percentage of total interactions in the granuloma, shown across the lung pathology score categories. (F) Interaction glyphs showing an abstract representation of the four most abundant neighborhoods found in the macrophage-NK cell interactions and a table showing the proportion this neighborhood makes up of the macrophage-NK cell interactions, with the associated Z-score in brackets.

    Journal: PLOS Pathogens

    Article Title: NK cell-macrophage interactions in granulomas correlate with limited tuberculosis pathology

    doi: 10.1371/journal.ppat.1012980

    Figure Lengend Snippet: (A) Imaging mass cytometry images overlaid with cellular identities determined in and , showing one granuloma of each lung pathology score category (low, intermediate, high). (B) Interaction analysis for the granuloma of each lung pathology category with the colour of the square representing the frequency of the interaction between the phenotype of interest and the phenotype of neighborhood cells as a percentage of the total interactions for the phenotype of interest (blue to green gradient). The statistical analysis of the significant occurrence of an interaction is represented as a dot on the interaction square, showing only positive correlations (grey to black gradient). (C) Localization and frequency of NK cell-macrophage interactions in the three granuloma shown in Fig A. (D) Frequency of cell interactions as frequency of total macrophage interactions. (E) Frequency of macrophage-NK cell (interactions in each granuloma as percentage of total interactions in the granuloma, shown across the lung pathology score categories. (F) Interaction glyphs showing an abstract representation of the four most abundant neighborhoods found in the macrophage-NK cell interactions and a table showing the proportion this neighborhood makes up of the macrophage-NK cell interactions, with the associated Z-score in brackets.

    Article Snippet: All mass cytometry data was acquired on the Hyperion mass cytometry imaging system (Standard Biotools, San Fransisco, CA, USA) at the Flow cytometry Core Facility at the LUMC.

    Techniques: Imaging, Mass Cytometry