Evidence map›Paper›PMID 42814317›Full record

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

Multiparametric Flow Cytometry Analysis of Naïve, Memory, and Effector T-Cells.

Chih-Hsiung Chen, Pradeep K Dagur, Ankit Saxena

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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
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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

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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

3 authors.

Chih-Hsiung ChenRutgers, Cancer Institute of New Jersey, New Brunswick, NJ, USA.
Pradeep K Dagur, Frederick, MD, USA.
Ankit SaxenaImmune Monitoring Flow Cytometry Shared Resource, Rutgers, Cancer Institute of New Jersey, 195 Little Albany St., Room 5548-04, New Brunswick, NJ, 08901, USA. as4075@cinj.rutgers.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Polychromatic flow cytometry enables the detection and characterization of markers that are helpful in defining the phenotype of various cell subsets. Here, we described a flow cytometry-based method to characterize the phenotype of naïve, memory, and effector T cells. Being able to differentiate these cells is crucial in understanding immune response and immune profiling. Naïve T cells enable the body to fight off new, unrecognized infections and diseases, and Memory T cells are enriched for response to recall antigens. Furthermore, the antigen-experienced T-cell populations can be broadly divided into effector and memory cell compartments, which are needed to sustain a responsive immune system. Simplistically, the effector T cells require active antigenic stimulation to eliminate pathogens. On the other hand, Memory T cells are described as cells that remain present without antigenic stimulation and can expand rapidly upon secondary challenges. Recently, with the identification of central and effector memory T-cell subsets, tremendous effort has been devoted to characterize markers on the surfaces of these cells. Though various markers have been used to identify the subsets, no single marker that segregates one subset from the other has been described. Thus, multiple markers are needed to subset the cells in order to characterize them. Here we report the verification of a nine-color panel (CD3, CD4, CD8, CD45RO, CD28, CD95, CCR7, Live/Dead Aqua, Dump channel-CD19, CD14, CD56, CD16) that can successfully identify six distinct CD4 and CD8 T-cell populations within the naïve and effector cell subsets from human donors.

Indexed as

Flow CytometryImmunologic MemoryImmunophenotypingMemory T CellsT-Lymphocyte SubsetsBiomarkersHumansBiomarkersImmunophenotypingMemory T cellsMulticolor-flow cytometryNaïve T cellsT cellsWhole blood

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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.