ArticleLab on a chip2012
Prediction and control of number of cells in microdroplets by stochastic modeling.
Article in Lab on a chip, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- The progressive trend of modeling and drug screening systems of breast cancer bone metastasis.Journal of biological engineering · 2024Review
- Microfluidics-based fabrication of cell-laden microgels.Biomicrofluidics · 2020Review
- High-throughput Characterization of HIV-1 Reservoir Reactivation Using a Single-Cell-in-Droplet PCR Assay.EBioMedicine · 2017Article
- Engineering cancer microenvironments forMaterials today (Kidlington, England) · 2015Article
- Bio-inspired cryo-ink preserves red blood cell phenotype and function during nanoliter vitrification.Advanced materials (Deerfield Beach, Fla.) · 2014Article
- Engineering anisotropic biomimetic fibrocartilage microenvironment by bioprinting mesenchymal stem cells in nanoliter gel droplets.Molecular pharmaceutics · 2014Article
- Preserving human cells for regenerative, reproductive, and transfusion medicine.Biotechnology journal · 2014Review
- Manipulating biological agents and cells in micro-scale volumes for applications in medicine.Chemical Society reviews · 2013Review
- Simple precision creation of digitally specified, spatially heterogeneous, engineered tissue architectures.Advanced materials (Deerfield Beach, Fla.) · 2013Article
- Bioprinting for stem cell research.Trends in biotechnology · 2013Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Manipulation and encapsulation of cells in microdroplets has found many applications in various fields such as clinical diagnostics, pharmaceutical research, and regenerative medicine. The control over the number of cells in individual droplets is important especially for microfluidic and bioprinting applications. There is a growing need for modeling approaches that enable control over a number of cells within individual droplets. In this study, we developed statistical models based on negative binomial regression to determine the dependence of number of cells per droplet on three main factors: cell concentration in the ejection fluid, droplet size, and cell size. These models were based on experimental data obtained by using a microdroplet generator, where the presented statistical models estimated the number of cells encapsulated in droplets. We also propose a stochastic model for the total volume of cells per droplet. The statistical and stochastic models introduced in this study are adaptable to various cell types and cell encapsulation technologies such as microfluidic and acoustic methods that require reliable control over number of cells per droplet provided that settings and interaction of the variables is similar.
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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.