ArticlePloS one2018
Accurately tracking single-cell movement trajectories in microfluidic cell sorting devices.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- DEP-track: a motion-aware framework for large-scale cell tracking and crossover frequency estimation in dielectrophoresis.Frontiers in bioinformatics · 2026Article
- Tutorial on compressed ultrafast photography.Journal of biomedical optics · 2024Review
- iCLOTS: open-source, artificial intelligence-enabled software for analyses of blood cells in microfluidic and microscopy-based assays.Nature communications · 2023Article
- Article
- FastTrack: An open-source software for tracking varying numbers of deformable objects.PLoS computational biology · 2021Article
- A graph-based cell tracking algorithm with few manually tunable parameters and automated segmentation error correction.PloS one · 2021Article
- Label-free microfluidic enrichment of photoreceptor cells.Experimental eye research · 2020Article
- FluoroCellTrack: An algorithm for automated analysis of high-throughput droplet microfluidic data.PloS one · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Microfluidics are routinely used to study cellular properties, including the efficient quantification of single-cell biomechanics and label-free cell sorting based on the biomechanical properties, such as elasticity, viscosity, stiffness, and adhesion. Both quantification and sorting applications require optimal design of the microfluidic devices and mathematical modeling of the interactions between cells, fluid, and the channel of the device. As a first step toward building such a mathematical model, we collected video recordings of cells moving through a ridged microfluidic channel designed to compress and redirect cells according to cell biomechanics. We developed an efficient algorithm that automatically and accurately tracked the cell trajectories in the recordings. We tested the algorithm on recordings of cells with different stiffness, and showed the correlation between cell stiffness and the tracked trajectories. Moreover, the tracking algorithm successfully picked up subtle differences of cell motion when passing through consecutive ridges. The algorithm for accurately tracking cell trajectories paves the way for future efforts of modeling the flow, forces, and dynamics of cell properties in microfluidics applications.
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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.