ArticleeLife2020
Deep-learning-based three-dimensional label-free tracking and analysis of immunological synapses of CAR-T cells.
Article in eLife, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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.
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.
Who cites it
36 citing papers in PubMed, 77 citations in OpenAlex.
- Celldetective, an AI-enhanced image analysis tool for unraveling dynamic cell interactions.eLife · 2026Article
- Review
- Light sheet microscopy imaging dataset of CAR-T-cell-mediated cytotoxicity.Scientific data · 2026Article
- isMap - immunological synapse map analysis program.Frontiers in immunology · 2026Article
- Single-Molecule and Super-Resolution Techniques for Investigating Protein Organizations and Biological Functions of Immune Cells.Advances in experimental medicine and biology · 2026Review
- AI-based hardware and software tools in microscopy to boost research in immunology and virology.Frontiers in immunology · 2025Review
- Measuring Molecular Mass Densities at Subcellular Resolution Using Optical Diffraction Tomography.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Smart CAR-T Nanosymbionts: archetypes and proto-models.Frontiers in immunology · 2025Review
- Imaging-Based Efficacy Evaluation of Cancer Immunotherapy in Engineered Tumor Platforms and Tumor Organoids.Advanced healthcare materials · 2024Review
- 3D live imaging and phenotyping of CAR-T cell mediated-cytotoxicity using high-throughput Bessel oblique plane microscopy.Nature communications · 2024Article
- High-resolution assessment of multidimensional cellular mechanics using label-free refractive-index traction force microscopy.Communications biology · 2024Article
- Newer generations of multi-target CAR and STAb-T immunotherapeutics: NEXT CART Consortium as a cooperative effort to overcome current limitations.Frontiers in immunology · 2024Review
- Enhanced functionalities of immune cells separated by a microfluidic lattice: assessment based on holotomography.Biomedical optics express · 2023Article
- Artificial intelligence-enabled quantitative phase imaging methods for life sciences.Nature methods · 2023Review
- Automated detection of apoptotic bodies and cells in label-free time-lapse high-throughput video microscopy using deep convolutional neural networks.Bioinformatics (Oxford, England) · 2023Article
- Volumetric segmentation of biological cells and subcellular structures for optical diffraction tomography images.Biomedical optics express · 2023Article
- Hybrid machine-learning framework for volumetric segmentation and quantification of vacuoles in individual yeast cells using holotomography.Biomedical optics express · 2023Article
- Deep learning-based label-free hematology analysis framework using optical diffraction tomography.Heliyon · 2023Article
- Targeted Enzyme Activity Imaging with Quantitative Phase Microscopy.Nano letters · 2023Article
- Optical trapping with holographically structured light for single-cell studies.Biophysics reviews · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
The immunological synapse (IS) is a cell-cell junction between a T cell and a professional antigen-presenting cell. Since the IS formation is a critical step for the initiation of an antigen-specific immune response, various live-cell imaging techniques, most of which rely on fluorescence microscopy, have been used to study the dynamics of IS. However, the inherent limitations associated with the fluorescence-based imaging, such as photo-bleaching and photo-toxicity, prevent the long-term assessment of dynamic changes of IS with high frequency. Here, we propose and experimentally validate a label-free, volumetric, and automated assessment method for IS dynamics using a combinational approach of optical diffraction tomography and deep learning-based segmentation. The proposed method enables an automatic and quantitative spatiotemporal analysis of IS kinetics of morphological and biochemical parameters associated with IS dynamics, providing a new option for immunological research.
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Identifiers
What OpenQuestion holds
Registered trials
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.