Evidence map›Paper›PMID 31794384›Full record

ArticleIEEE transactions on bio-medical engineering2020

Assay and Isolation of Single Proliferating CD4+ Lymphocytes Using an Automated Microraft Array Platform.

Cody A LaBelle, Raymond J Zhang, Paul M Armistead, Nancy L Allbritton

Open access · greenAbstract read
In one paragraph

Article in IEEE transactions on bio-medical engineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.5field-weighted citation impact, top 30% 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

7 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Deep Learning-Assisted Label-Free Parallel Cell Sorting with Digital Microfluidics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  3. Article
  4. Microraft arrays for serial-killer CD19 chimeric antigen receptor T cells and single cell isolation.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2023
    Article
  5. Article
  6. Review
  7. Image-Based Live Cell Sorting.Trends in biotechnology · 2021
    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

4 authors at 1 institution in 1 country.

Cody A LaBelle
Raymond J Zhang
Paul M Armistead
Nancy L Allbritton
University of North Carolina at Chapel Hill · US

Funding

Generation of a Gene-Targeted Human iPS Cell Library for Macular DegenerationR01EY024556 · NEI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ALLBRITTON, NANCY L. · 2014 to 2018
$2.9M
PROFILING SIGNALING ACTIVITY AND GENE EXPRESSION IN SINGLE, PANCREATIC ADENOCARCINOMA CELLS USING CE-RNA-SEQR01CA224763 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ALLBRITTON, NANCY L., LAWRENCE, DAVID S. · 2018 to 2022
$2.9M
CellRaft Array for Screening and Isolation of Highly Effective Cytotoxic T CellsR42AI126905 · NIAID · CELL MICROSYSTEMS, INC. · PI ALLBRITTON, NANCY L., ARMISTEAD, PAUL MICHAEL · 2017 to 2018
$1.6M
NCI NIH HHS R01 CA224763NEI NIH HHS R01 EY024556NIAID NIH HHS R42 AI126905
6 · The paper itself

Abstract

objectiveWhile T lymphocytes have been employed as a cancer immunotherapy, the development of effective and specific T-cell-based therapeutics remains challenging. A key obstacle is the difficulty in identifying T cells reactive to cancer-associated antigens. The objective of this research was to develop a versatile platform for single cell analysis and isolation that can be applied in immunology research and clinical therapy development.

methodsAn automated microscopy and cell sorting system was developed to track the proliferative behavior of single-cell human primary CD4+ lymphocytes in response to stimulation using allogeneic lymphoblastoid feeder cells.

resultsThe system identified single human T lymphocytes with a sensitivity of 98% and specificity of 99% and possessed a cell collection efficiency of 86%. Time-lapse imaging simultaneously tracked 4,534 alloreactive T cells on a single array; 19% of the arrayed cells formed colonies of ≥2 cells. From the array, 130 clonal colonies were isolated and 7 grew to colony sizes of >10,000 cells, consistent with the known proliferative capacity of T cells in vitro and their tendency to become exhausted with prolonged stimulation. The isolated colonies underwent ELISA assay to detect interferon-γ secretion and Sanger sequencing to determine T cell receptor β sequences with a 100% success rate.

conclusionThe platform is capable of both identification and isolation of proliferative T cells in an automated manner. SIGNIFICANCE: This novel technology enables the identification of TCR sequences based on T cell proliferation which is expected to speed the development of future cancer immunotherapies.

Indexed as

CD4-Positive T-LymphocytesLymphocyte ActivationCells, CulturedCell SeparationHumans

Identifiers

PMID31794384
PMCPMC7247929
OpenAlexW2991054871

What OpenQuestion holds

Textmetadata
LicenceTDM
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.