Evidence map›Paper›PMID 42814321›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2027

Immunophenotyping of Human Regulatory T-Cells from Peripheral Blood Mononuclear Cells.

Maria Lopez-Ocasio, Wan-Chi Lin, Steven C Hockman, Keyvan Keyvanfar, Pradeep K Dagur

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Article in Methods in molecular biology (Clifton, N.J.), 2027. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Maria Lopez-OcasioFlow Cytometry Core, NHLBI, NIH, Bethesda, MD, USA. maria.ocasio@nih.gov.
Wan-Chi LinFlow Cytometry Core, NHLBI, NIH, Bethesda, MD, USA.
Steven C HockmanFlow Cytometry Core, NHLBI, NIH, Bethesda, MD, USA.
Keyvan KeyvanfarFlow Cytometry Core, NHLBI, NIH, Bethesda, MD, USA.
Pradeep K DagurFlow Cytometry Core, NHLBI, NIH, Bethesda, MD, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Regulatory T cells, or Tregs, are a unique type of CD4⁺ T cell that act as the immune system's brakes-they stop it from turning against the body's own tissues. For about twenty years now, researchers have been digging into what sets Tregs apart from other T cells, both in their composition and function (1). Markers like CD25 (IL-2Rα), Foxp3, and CTLA-4 usually show up when Tregs are active, but these markers aren't always reliable-they can shift depending on where the cells are and what they are doing. Foxp3 is a transcription factor that Tregs need to develop and function. Mutations on Foxp3 gene lead to serious autoimmune diseases like immune dysregulation, polyendocrinopathy, enteropathy, and X-linked (IPEX) syndrome. Lately, studies have uncovered even more variety within Tregs by finding subsets with markers like Helios, TIGIT, CD127 (which is usually low in Tregs), and neuropilin-1. Identifying and measuring Tregs accurately is important not only in research but also in the clinic. Identifying Tregs on patient samples provides a clear picture of what is going on with their immune system-whether it is an autoimmune disease, a transplant, or cancer treatment. Flow cytometry has become a go-to tool for identifying, typing, and subclassifying subsets. It helps  showing how Tregs work, how stable they are, and how well they keep other immune cells in check. By profiling Tregs, doctors can group patients more accurately and find biomarkers that tell you if a treatment's working or if a disease is getting worse. Better protocols to test Treg mean more personalized immune therapies. Tregs are serious power players when it comes to immune suppression, and being able to profile them precisely-whether in animals or people-is important for both science and medical care.

Indexed as

ImmunophenotypingLeukocytes, MononuclearT-Lymphocytes, RegulatoryBiomarkersFlow CytometryForkhead Transcription FactorsHumansBiomarkersForkhead Transcription FactorsFOXP3 protein, humanCD25CD4CTLA-4Flow cytometryFoxp3ImmunophenotypingSuppressionTregs

Identifiers

What OpenQuestion holds

Textmetadata
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.