Evidence map›Paper›PMID 35593221›Full record

ArticleCytometry. Part A : the journal of the International Society for Analytical Cytology2022

Full spectrum flow cytometry and mass cytometry: A 32-marker panel comparison.

Maria C Jaimes, Michael Leipold, Geoffrey Kraker, El-Ad Amir, Holden Maecker, Joanne Lannigan

Open access · hybridAbstract read
In one paragraph

Article in Cytometry. Part A : the journal of the International Society for Analytical Cytology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
3.3field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 39 citations in OpenAlex.

  1. Review
  2. Decreased PD-1Scandinavian journal of immunology · 2026
    Article
  3. Review
  4. Article
  5. Immunological biomarkers of aging.Journal of immunology (Baltimore, Md. : 1950) · 2025
    Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Targeting T regulatory (TCancer drug resistance (Alhambra, Calif.) · 2024
    Review
  13. Article
  14. Recent Developments in Blood Biomarkers in Neuro-oncology.Current neurology and neuroscience reports · 2023
    Review
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 5 institutions in 1 country.

Maria C JaimesApplications, Cytek Biosciences, Inc, Fremont, California, USA.
Michael LeipoldDepartment of Microbiology/Immunology, Stanford University, Stanford, California, USA.ORCID 0000-0001-5389-0906
Geoffrey KrakerTechnical Applications Support, Cytek Biosciences Inc., Fremont, California, USA.
El-Ad AmirAstrolabe Diagnostics, Fort Lee, New Jersey, USA.
Holden MaeckerDepartment of Microbiology/Immunology, Stanford University, Stanford, California, USA.
Joanne LanniganFlow Cytometry Support Services, LLC, Alexandria, Virginia, USA.ORCID 0000-0002-3981-8681
Stanford University · USApplications Research (United States) · USFlometrics (United States) · USJewish Community Center of Fort Lee · USSystem Science Applications (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High-dimensional single-cell data has become an important tool in unraveling the complexity of the immune system and its involvement in homeostasis and a large array of pathologies. As technological tools are developed, researchers are adopting them to answer increasingly complex biological questions. Up until recently, mass cytometry (MC) has been the main technology employed in cytometric assays requiring more than 29 markers. Recently, however, with the introduction of full spectrum flow cytometry (FSFC), it has become possible to break the fluorescence barrier and go beyond 29 fluorescent parameters. In this study, in collaboration with the Stanford Human Immune Monitoring Center (HIMC), we compared five patient samples using an established immune panel developed by the HIMC using their MC platform. Using split samples and the same antibody panel, we were able to demonstrate highly comparable results between the two technologies using multiple data analysis approaches. We report here a direct comparison of two technology platforms (MC and FSFC) using a 32-marker flow cytometric immune monitoring panel that can identify all the previously described and anticipated immune subpopulations defined by this panel.

Indexed as

Data AnalysisBiomarkersFlow CytometryHumansImmunophenotypingBiomarkersAuroraCyTOFfull spectrum flow cytometryhigh-dimensional immunophenotypingmass cytometry

Identifiers

PMID35593221
PMCPMC9790709
OpenAlexW4280647382

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.