Evidence map›Paper›PMID 31130961›Full record

ArticleFrontiers in immunology2019

Mass Cytometry Identifies Distinct Subsets of Regulatory T Cells and Natural Killer Cells Associated With High Risk for Type 1 Diabetes.

Hugo Barcenilla, Linda Åkerman, Mikael Pihl, Johnny Ludvigsson, Rosaura Casas

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
4.3field-weighted citation impact, top 6% 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

25 citing papers in PubMed, 40 citations in OpenAlex.

  1. Review
  2. Review
  3. [Research progress and optimization strategies for early screening of type 1 diabetes].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2025
    Review
  4. Article
  5. Review
  6. Article
  7. Review
  8. Single-cell profiling identifies a CD8Nature communications · 2024
    Article
  9. Article
  10. Review
  11. Article
  12. Review
  13. Review
  14. Article
  15. Review
  16. Observational
  17. Review
  18. Profiling of the Human Natural Killer Cell Receptor-Ligand Repertoire.Journal of visualized experiments : JoVE · 2020
    Article
  19. Article
  20. Review
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

5 authors at 1 institution in 1 country.

Hugo BarcenillaDivision of Pediatrics, Department of Clinical and Experimental Medicine, Faculty of Medicine and Health Sciences, Linköping University, Linköping, Sweden.
Linda ÅkermanDivision of Pediatrics, Department of Clinical and Experimental Medicine, Faculty of Medicine and Health Sciences, Linköping University, Linköping, Sweden.
Mikael PihlCore Facility, Flow Cytometry Unit, Linköping University, Linköping, Sweden.
Johnny LudvigssonDivision of Pediatrics, Department of Clinical and Experimental Medicine, Faculty of Medicine and Health Sciences, Linköping University, Linköping, Sweden.
Rosaura CasasDivision of Pediatrics, Department of Clinical and Experimental Medicine, Faculty of Medicine and Health Sciences, Linköping University, Linköping, Sweden.
Linköping University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Type 1 diabetes (T1D) is characterized by autoimmune destruction of insulin producing β-cells. The time from onset of islet autoimmunity to manifest clinical disease can vary widely in length, and it is fairly uncharacterized both clinically and immunologically. In the current study, peripheral blood mononuclear cells from autoantibody-positive children with high risk for T1D, and from age-matched healthy individuals, were analyzed by mass cytometry using a panel of 32 antibodies. Surface markers were chosen to identify multiple cell types including T, B, NK, monocytes, and DC, and antibodies specific for identification of differentiation, activation and functional markers were also included in the panel. By applying dimensional reduction and computational unsupervised clustering approaches, we delineated in an unbiased fashion 132 phenotypically distinct subsets within the major immune cell populations. We were able to identify an effector memory Treg subset expressing HLA-DR, CCR4, CCR6, CXCR3, and GATA3 that was increased in the high-risk group. In addition, two subsets of NK cells defined by CD16

Indexed as

AdolescentChildCytological TechniquesDiabetes Mellitus, Type 1FemaleHumansKiller Cells, NaturalMaleRisk FactorsT-Lymphocytes, RegulatoryT-Lymphocyte Subsetsautoantibody-positive childrenhigh-risk for T1Dmass cytometry (CyTOF)NK cellsregulatory T cellstype 1 diabetes (T1D)

Identifiers

PMID31130961
PMCPMC6509181
OpenAlexW2942708362

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.