ArticleIEEE transactions on bio-medical engineering2020
Assay and Isolation of Single Proliferating CD4+ Lymphocytes Using an Automated Microraft Array Platform.
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.
What it found
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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.
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.
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Who cites it
7 citing papers in PubMed, 10 citations in OpenAlex.
- Development of large-scale gastruloid array to identify aberrant developmental phenotypes.APL bioengineering · 2025Article
- Deep Learning-Assisted Label-Free Parallel Cell Sorting with Digital Microfluidics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Automated microarray platform for single-cell sorting and collection of lymphocytes following HIV reactivation.Bioengineering & translational medicine · 2023Article
- 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 · 2023Article
- Scalable Additive Construction of Arrayed Microstructures with Encoded Properties for Bioimaging.Micromachines · 2022Article
- A technology of a different sort: microraft arrays.Lab on a chip · 2021Review
- Image-Based Live Cell Sorting.Trends in biotechnology · 2021Review
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
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.
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Registered trials
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